## 2. Wireless hybrid broadcast/broadband network optimization

optimal operating point of the hybrid network in terms of achievable rate. Indeed, analyzing Problem P1, we can interpret its utility function as an equilibrium function between two spectral efficiency terms,

$$f(x) = x^2 \log(1 + \delta_0 x^{-\alpha}) + (1 - x^2) \xi_0, \qquad (8.20)$$

with,

$$\delta_0 = \Gamma_0^{(B)}, \quad \xi_0 = \frac{\log 2}{B^{(B)}} \quad \text{and,} \quad x = r_B^2 \qquad (8.21)$$

The left term corresponds to the spectral efficiency term obtained from the broadcast component. The right term turns out to be homogeneous to a spectral efficiency and can be analyzed as the ratio between the average rate achieved by the users of the unicast component with the bandwidth available for the broadcast component. Hence, $\xi_0$ can be interpreted as the spectral efficiency a broadband network would offer if it would exploit the spectral resource of the broadcast network.

A first step has been to show that the utility function $f(x)$ is convex over the set of $x$ values corresponding to practical situations and define a cooperation decision parameter helping us to find the optimal broadcast coverage radius $R_B$. This result has been discussed in [R.3], and is summarized in the following contribution.

### Contribution IV.8 (Analytic Expression)

#### Convexity of the equilibrium function of Problem P1

Given $\delta_0 \ge 0$, $\xi_0 \ge 0$ and $\alpha > 0$, the following function $f(x)$ $x \in [0, 1]$ is convex,

$$f(x) = x^2 \log(1 + \delta_0 x^{-\alpha}) + (1 - x^2) \xi_0, \qquad (8.22)$$

such that $\exists x^* \in [0, 1]$, $f(x) \le f(x^*) \forall x \in [0, 1]$ obeying to the following decision parameter $s$

$$s = \frac{\alpha}{2} - \log \frac{\alpha}{2} + \xi_0 \qquad (8.23)$$

as,

$$x^* = \begin{cases} 1 & s < 1 \\ x^* \leftarrow \frac{df(x)}{dx} = 0 & s \ge 1 \\ 0 & s \to \infty \end{cases} \qquad (8.24)$$

From this result, we conclude that there exists a unique optimal broadcast coverage radius $r_B^* = x^*$ which value goes from $r_b = 0$ (unicast mode only) to $r_b = 1$ (broadcast mode only) depending on the decision parameter $s$. This latter cooperation parameter $s$ is mainly driven by $\xi_0$ which reports the average success rate in the cells of the broadband network. In other words, the optimal broadcast coverage radius directly depends on the load of the unicast cells. In the case when $s \ge 1$, the optimal radius needs still to be derived, which turns out not to be straightforward to obtain. In our study, we considered two solutions to give an analytic expression to the optimal solution : a first one based on a tabulated function, an a second one corresponding to an accurate approximation and relaxing the use of the tabulated function. These two solutions are gathered in the Contrib. IV.9. The way to extract such solutions is explained in [R.3].

The function $v(s)$ defined in Eq. (8.25) to express the optimal coverage radius is illustrated in Fig. 8.10. It is observed that $v(s)$ is monotonically decreasing $\lim_{s \to +\infty} v(s) = 0$. Thus when $s$ becomes high enough (e.g. $s > 3$) the optimal solution can be approximated by omitting the tabulated function $v(s)$ in the optimal expression of $r_B$ yielding the approximated result in (8.25). This observation is further highlighted in Fig. 8.11, which shows the optimal coverage radius as a function of the cooperation decision parameter $s$, with different values of $\Gamma_0^{(B)}$. We conclude that that the approximate solution is close to the exact solution even if for a low value of the cooperation decision parameter $s$ and low SNR $\Gamma_0^{(B)}$, the approximation error increases. Indeed, we have shown in [R.3] that the approximation error can be further reduced by using an iterative approach.
<figure><img src="image_90.png" /><figcaption>FIGURE 8.10– Illustration of the tabulated function $v(s)$ as a function of the cooperation decision parameter $s$.</figcaption></figure>

<figure><img src="image_91.png" /><figcaption>FIGURE 8.11– Optimal broadcast coverage radius as a function of the cooperation decision parameter $s$. Comparison of the exact and approximate solutions.</figcaption></figure>

## Contribution IV.9 (Analytic Expression)

### Optimal broadcast coverage radius

Given the broadcast/broadband hybrid network previously defined, the normalized broadcast tower coverage radius $r_B$ yielding maximal average service capacity is expressed as,

$$r_B^* = \left( \frac{\Gamma_0^{(B)}}{\frac{\alpha_B}{2} \frac{e^s}{1+v_0(s)} - 1} \right)^{\frac{1}{\alpha_B}} \approx \left( \frac{\Gamma_0^{(B)}}{\frac{\alpha_B}{2} e^s - 1} \right)^{\frac{1}{\alpha_B}} \quad (8.25)$$

with $s$ introduced in Contrib. IV.8 and $v(s)$ a decreasing function defined over $[1, \infty)$ as,

$$\log(1 + v(s)) = e^{-s} (1 + v(s)). \quad (8.26)$$

From the last theoretical analysis, we have provided a means to set the coverage radius to maximize the global service capacity of the hybrid network. Nevertheless, the optimal $r_B^*$ given by Contrib. IV.9 may not meet the service success rate constraint of Problem P1. For example, if the total number of users $M$ is very high, the optimal radius based on the overall hybrid network capacity optimization may lead to a success rate lower than the constraint. In such situations, it can be demonstrated that solution of the optimization is directly given by solving the constraint equation [R.3] as,

$$r_B^* = \sqrt{\frac{\eta_{ref} - \mathbb{E}[\eta_i^{(U)}]}{1 - \mathbb{E}[\eta_i^{(U)}]}} \quad (8.27)$$

which is valid only if $\mathbb{E}[\eta_i^{(U)}] \neq 1$. Finally, it can be shown that the solving the constraint Problem P1 yields the solution summarized in the following contribution.
## 2. Wireless hybrid broadcast/broadband network optimization

### Contribution IV.10 (Analytic Expression)

#### Optimal solution to Problem P1

Given the broadcast/broadband hybrid network previously defined, the optimal setting for the broadcast station coverage radius for hybrid network capacity maximization under success rate constraint $\eta_{target}$ is obtained through

$$r_B^* = \begin{cases} \text{from (8.25)} & \text{if } \mathbb{E}[\eta_i^{(U)}] < \frac{\eta_{ref} - r_B^2}{1 - r_B^2} \\ \text{from (8.27)} & \text{otherwise} \end{cases} \qquad (8.28)$$

with $\mathbb{E}[\eta_i^{(U)}]$ computed from Contrib. IV.7.

### ► Simulation results

We give here some simulation results showing not only the accuracy of the proposed analytical solution of the hybrid network setting optimization, but also the performance gain obtained from the cooperation between the two components of the network. The Vienna LTE-A downlink system level simulator has been used to emulate the behavior of the hybrid model with a practical system and to provide the numerical results [TBK+15, MWI+09]. During the PhD of Pape FAM, a part of the work has been dedicated to add several features to the simulator to support the HPHT type of infrastructure. To follow the proposal published during the ANR MCube project in [R.3] and also suggested in [RJ14], we used for the PHY layer a dedicated LTE broadcast system based on eMBMS++ specifications. This advanced feature of the Vienna simulator has been shown during a workshop in 2015 [C.17]. Using such a simulator closely reflects the behavior of a real systems since the SNR of each user is mapped to a channel quality indicator (CQI) relying on PHY layer performance results. Then to determine the throughput of the user, a modulation and coding scheme (MCS) is selected based on the reported CQI and the quality of service (QoS) requirements. We use this approach in our simulations using the SNR-to-CQI mapping function extracted from [MWI+09, 3GP15a].

For the presented simulations here, we consider the delivery of a high definition (HD) service to M users in a squared service area of 30 × 30 km². The capacity requirement for the service is set to $C_{req} = 2M bps$ and the reference SNR $\Gamma_0$ is set to 0 dB for both components. Further system parameter settings are available in [R.3] and [C.14]. Fig. 8.12 shows the evolution of the average service capacity as a function of the coverage radius of the HPHT cell without any specification of the targeted service success rate. The simulation results are presented along with the theoretical ones. As observed in this figure the analytical expressions of the optimal broadcast coverage radius are close to the optimal solution obtained from simulation, even considering the approximated closed-form. The difference observed about the capacity gain is due to the use of the theoretical Shannon capacity formula in the analytical model, whereas a practical SNR to capacity mapping function is used in the simulations. Nevertheless, the optimal broadcast coverage area is not that sensitive to such mismatch.

Complementary to the previous results, Fig. 8.13 shows the evolution of the average service success rate as a function of the broadcast coverage radius. The theoretical results are in agreement with the simulation ones. It is also observed that when the LPLT cells are not overloaded i.e. $M = 500$, the average service success rate is constant and equal to one. Thus all users in the service area can be served. On the other hand, when the LPLT cells become overloaded i.e. $M = 10000$, the average service success rate increases as the broadcast coverage radius increases. In this situation, the optimal broadcast coverage radius has to be computed from the constraint optimization problem solution given by Contrib. IV.10.

Further results given in Fig. 8.14 and 8.15 show how the cooperation between the broadcast and broadband networks can help in improving the service delivery performance depending on the user demand, either from a capacity or a success rate point of view. Such results, based on the previously derived theoretical expressions are important outputs of our work on broadcast/broadband cooperation.
# Chapitre 8. Broadcast / Broadband Convergence Studies

<figure><img src="image_92.png" /><figcaption>**FIGURE 8.12**– Average service capacity vs. broadcast coverage radius. Comparison between analytical and simulation results. M = 500 UEs</figcaption></figure>

<figure><img src="image_93.png" /><figcaption>**FIGURE 8.14**– Average service capacity vs. the number of users in the service area; Comparison of the hybrid network, unicast network and broadcast network average service capacity.</figcaption></figure>

<figure><img src="image_94.png" /><figcaption>**FIGURE 8.13**– Average service success rate vs. broadcast coverage radius; analytical and simulation results; M = 500 and M = 10000 UEs.</figcaption></figure>

<figure><img src="image_95.png" /><figcaption>**FIGURE 8.15**– Average service success rate vs. the number of users in the service area; Comparison of the hybrid network, unicast network and broadcast network average service capacity.</figcaption></figure>

## 2.4 ENERGY CONSUMPTION MINIMIZATION

### ► Problem formulation

In the previous section, we have investigated how to optimize the service capacity based on a joint operation of broadband and broadcast modes in a hybrid network. Using the accurate power consumption model complementary contributions in our work have been to optimize the energy efficiency metric of the hybrid network. Actually, considering the energy saving aspects, the LPLT sites within the coverage area of the broadcast network could be turned off to save more energy since there is no data to transmit. In the light of these observations, the aim is to find the optimal broadcast coverage radius that maximizes the energy efficiency (EE) metric of the hybrid network. The general related energy efficiency maximization problem states

$$ P2: \max_{0 \le r_B \le 1} \frac{\mathrm{IE}[C_s^H]}{P_{in}^H} \qquad (8.29) $$
## 2. Wireless hybrid broadcast/broadband network optimization

with $\mathbb{E}[C_s^H]$ and $P_{in}^H$ given from (8.12) and (8.14), respectively. Stated as it is, this problem turns out however to be mathematically untractable. To circumvent this, we formulated two subproblems, not equivalent to the main one, but following the energy efficiency approach. Indeed, the energy efficiency of the hybrid network is maximized either by increasing the capacity of the hybrid network for a fixed transmit power of the broadcast component or by reducing the power consumption of the broadcast component for a given capacity requirement. This leads to two different optimization problems which resolution become analytically feasible as detailed in the sequel.

### ► Power consumption minimization approach

In this subproblem, the energy efficiency is maximized by minimizing the power consumption of the broadcast component with respect to a target capacity at the edge of the broadcast coverage radius based on the service requirement. More precisely, in this approach the transmission power of the broadcast station is set according to the target capacity $C_{req}$, which leads to a minimum SNR $\Gamma_0^{(B)}$ as already discussed. After some manipulations, the energy efficiency of the hybrid network can be expressed as a function of the normalized broadcast coverage radius $r_B$. The optimization problem can thus be formally stated using the following objective function $f(x)$ with $x = r_b \in [0, 1]$ as,

$$f(x) = MC_{req} \left( \frac{\mathbb{E}[\eta_i^{(U)}]}{\Delta_p^{(B)} P_{max}^{(B)}} \right) \cdot \frac{1 + \Theta_c x^2}{\sigma_{p1} - \sigma_{p2} x^2 + x_B^{\alpha}} \quad (8.31)$$

where $\mathbb{E}[\eta_i^{(U)}]$ is given by Contrib. IV.7, and

$$\Theta_c = \frac{B^{(B)} \log_2(1 + \Gamma_0^{(B)})}{C_{req} \mathbb{E}[\eta_i^{(U)}]} - 1, \quad \sigma_{p1} = \frac{P_{in}^{(U)} + P_0^{(B)} r_U^2}{\Delta_p^{(B)} P_{max}^{(B)} r_U^2} \quad \text{and,} \quad \sigma_{p2} = \frac{P_{in}^{(U)} + P_{sleep}^{(U)}}{\Delta_p^{(B)} P_{max}^{(B)} r_U^2} \quad (8.32)$$

Parameter $\Theta_c$ is a parameter resulting from the difference between the average capacity of the broadcast component and the unicast component of the hybrid network, while parameters $\sigma_{p1}$ and $\sigma_{p2}$ are related to the power and system models introduced in (8.13).

In [C.1], we have shown that the function $f(x)$ is convex $\forall x \in [0, 1]$ and $\alpha \ge 2$. Therefore the optimal broadcast coverage radius is obtained by finding the root of the derivative function. We proved that only an approximated closed-form can be found to the optimal coverage radius, however providing a very accurate solution to the problem. The following contribution gives the proposed closed-form approximation.

### Contribution IV.11 (Analytic Expression)

#### Approximated solution to power efficiency maximization through power minimization approach

Given the broadcast/broadband hybrid network previously defined, the optimal broadcast coverage radius for hybrid network energy efficiency maximization obtained through a power minimization approach is

$$r_B^* \approx \frac{S^{\frac{1}{\alpha_B - 2}}}{\sqrt{\Theta_c \left(\frac{2}{\alpha_B} - 1\right)}} \left( 1 + \sum_{k=0}^{2} \frac{k}{\alpha_B - 2} S^{\frac{2k}{\alpha_B - 2}} \right) \quad (8.33)$$

with $s$ a cooperation decision parameter defined as,

$$s = \frac{2}{\alpha_B} (\Theta_c \sigma_{p2} + \sigma_{p1}) \left[ \Theta_c \left( \frac{2}{\alpha_B} - 1 \right) \right]^{\frac{\alpha_B}{2} - 1} \quad (8.34)$$

### ► Capacity maximization approach

Instead of reducing the transmission power of the broadcast component, the energy efficiency is obtained by increasing the capacity of the broadcast component while the transmission power is kept constant. Given a uniform distribution of the location of the users in the service area, we have shown in [C.1] that the energy
efficiency of the hybrid network can be re-expressed as a function of the normalized broadcast coverage radius. Thus, the objective function to maximize in this case is written as

$$f(x) = M \left( \frac{B^{(B)}}{\Delta_{P}^{(B)} P_{max}^{(B)} \log 2} \right) \cdot \frac{x^2 \log \left( 1 + \Gamma_{0}^{(B)} x^{-\alpha_{B}} \right) + (1 - x^2) v_{c}}{\sigma_{p1} - \sigma_{p2} x^2 + 1} \quad (8.35)$$

where $v_c = \frac{C_{req} \log 2}{B^{(B)}} \mathbb{E}[\eta_i^{(U)}]$. Finding the maximum operating point of such an objective function can not easily be obtained. A practical solution can however be provided by means of a tabulated function, following the same approach as that proposed to solve Problem P1. The obtained solution which proof is detailed in [C.1] is given in the following contribution.

## Contribution IV.12 (Analytic Expression)

### Approximated solution to power efficiency maximization through capacity maximization approach

Given the broadcast/broadband hybrid network previously defined, the optimal broadcast coverage radius for hybrid network energy efficiency maximization obtained through a capacity maximization approach is

$$r_B^* \approx \left( \frac{\Gamma_0^{(B)}}{\frac{\alpha_B}{2S(v_p, v_c)} - 1} \right)^{\frac{1}{\alpha_B}} \quad (8.36)$$

with $v_c \in [0, +\infty]$ defined in (8.35), $v_p = \frac{\sigma_{p2}}{1+\sigma_{p1}} \in [0, 1]$ and $S(v_p, v_c)$ a bivariate monotonously decreasing function defined as,

$$z - \log z + v_p \left( z \Gamma_0^{(B)} \right)^{\frac{2}{\alpha_B}} \left( \frac{\alpha_B}{2} - z \right)^{1 - \frac{2}{\alpha_B}} = \frac{\alpha_B}{2} - \log \frac{\alpha_B}{2} + v_c (1 - v_p) \quad (8.37)$$

with $z = S(v_p, v_c)$.

This last solution relies on a function for which no closed-form expression nor approximation has been found. However, it can be tabulated for predetermined parameters $\alpha_B$ and $\Gamma_0^{(B)}$.

## Simulation Results

Let us present some synthetic simulation results obtained by applying both proposed theoretical solutions. Fig. 8.16 gives the comparative results obtained in terms of energy efficiency carrying out the power minimization and the capacity maximization strategies. A first conclusion is that both approaches yield very close results. With a more detailed analysis, power minimization turns out to be slightly more favourable than capacity maximization unless the number M of users becomes very high. This means that the user factorization gain of the broadcast component is asymptotically more favourable to the capacity increase than to the power consumption decrease. Indeed, this can be also concluded through the analysis of the objective functions established in (8.31) and (8.35).

In Fig. 8.17 we focus on the sensitivity of the optimal broadcast coverage radius to the number of users M in the service area. It can be observed that the optimal broadcast coverage radius obtained using the capacity maximization approach is less sensitive to the variation of the number of users in the service area than the optimal broadcast coverage radius obtained with the power minimization approach. Therefore, from a network planning point of view, the capacity maximization approach may be more appropriate than the power minimization approach to optimize the energy efficiency of a hybrid unicast-broadcast network. From these results, a rule of thumb in terms of energy efficiency is to operate the hybrid network so as to ensure a broadcast coverage of about 40-50% of the whole service area.
## 2. Wireless hybrid broadcast/broadband network optimization

<figure><img src="image_96.png" /><figcaption>**FIGURE 8.16**– Maximum energy efficiency vs number of users M. Comparison between the capa-max and pwr-min approaches.</figcaption></figure>

<figure><img src="image_97.png" /><figcaption>**FIGURE 8.17**– Optimal broadcast coverage radius vs number of users M. Comparison between the capa-max and pwr-min approaches.</figcaption></figure>

## 2.5 CONCLUSION

The work achieved during the PhD of P.A. Fam gives further insight to the overall question of broadcast/broadband hybrid network optimization. This issue has been tackled with the definition of the MBMS operation on demand (MooD) in the 3GPP Release 12 [3GP15b]. MooD allows users to dynamically switch between unicast and broadcast transmission modes, nevertheless current deployments of LTE eMBMS are based on the Release 9 or 10 of LTE standard which does not implement this MooD enhancement.

In particular, authors in [CMGB15] have reviewed the state of the art and current trends in mobile multimedia delivery focusing on the potential opportunities and technical challenges of the convergence between mobile broadband and broadcast industries.

further insights Yet, further theoretical investigations studies were needed to

### Summary (PhD/Dissemination/Projects)

- 1 PhD (P.A. Fam)

- 1 International journal paper [R.3]

- 4 communications in international conferences and workshops [C.1][C.14][C.17]

- 1 IRT-Bcom Project (RS-COM)
<figure><img src="image_98.png" /></figure>
The measure of greatness in a scientific idea
is the extent to which it stimulates thought
and opens up new lines of research.

– Paul A.M. Dirac –

1 **GENERAL CONTEXT**

2 **PROPOSED RESEARCH TRACKS**

2.1 UNIFIED MODEL OF HIGH POWER TRANSMITTERS EFFICIENCY

2.2 SPATIAL FILTERING FOR MMWAVE SYSTEMS

2.3 OPTIMIZED MULTI-MODE COMMUNICATION NETWORKS
[1] ETSI TS 122 146. Digital cellular telecommunications system (phase 2+); universal mobile telecommunications system (umts); Ite; multimedia broadcast/multicast service (mbms); stage 1. Technical report, ETSI, 2013. v11.1.0.

[3GP15a] 3GPP. LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer procedures; TS 136.213, 3rd Generation Partnership Project (3GPP), April 2015.

[3GP15b] 3GPP. Multimedia Broadcast/Multicast Service (MBMS) improvements; MBMS operation on demand. TR 26.849, 3rd Generation Partnership Project (3GPP), June 2015.

[2] ETSI TR 136 942. Ite; evolved universal terrestrial radio access (e-utra); radio frequency (rf) system scenarios. Technical report, ETSI, 2012. v11.0.0.

[AHW07] O. Tirkkonen A. Hottinen and R. Wichman. *Multi-antenna Transceiver Techniques for 3G and Beyond*. WILEY, 2007.

[Ala98] Siavash Alamouti. A simple transmit diversity technique for wireless communications. *Selected Areas in Communications, IEEE Journal on*, 16(8):1451–1458, 1998.

[ATS16] ATSC3.0. Atsc proposed standard: Physical layer protocol, a/322:2016. Technical report, ATSC, sept. 2016.

[BAT+11] M. Brandon, M. Ariaudo, S. Traverso, J. Bouvier, I. Fijalkow, and J.L. Gautier. Linearity improvement thanks to the association of Active Constellation Extension and digital predistortion for OFDM. In *New Circuits and Systems Conference (NEWCAS), 2011 IEEE 9th International*, pages 293–296, June 2011.

[BC04] N.C. Beaulieu and J. Cheng. Precise error-rate analysis of bandwidth-efficient bpsk in nakagami fading and cochannel interference. *Communications, IEEE Transactions on*, 52(1):149–158, Jan 2004.

[BF82] S.A. Billings and S.Y. Fakhouri. Identification of systems containing linear dynamic and static nonlinear elements. *Automatica*, 18(1):15–26, 1982.

[BFH96] R. W. Bauml, R. F. H. Fischer, and J.B. Huber. Reducing the peak-to-average power ratio of multi-carrier modulation by selected mapping. *IEE Electronics Letters*, 32(22):2056–2057, 1996.

[BGP02] H. Bolcskei, D. Gesbert, and A. J. Paulraj. On the capacity of ofdm-based spatial multiplexing systems. *IEEE Transactions on Communications*, 50(2):225–234, Feb 2002.

[BHV09] E. Biglieri, Y. Hong, and E. Viterbo. On fast-decodable space-time block codes. *IEEE Transactions on Information Theory*, 55(2):524–530, Feb 2009.

[BLG02] P. Banelli, G. Leus, and G.B. Giannakis. Bayesian estimation of clipped Gaussian processes with application to OFDM. In *Signal Processing Conference, 2002 11th European*, pages 1–4, Sept 2002.

[BLM+14a] N. Bhushan, J. Li, D. Malladi, R. Gilmore, D. Brenner, A. Damnjanovic, R. T. Sukhavasi, C. Patel, and S. Geirhofer. Network densification: the dominant theme for wireless evolution into 5g. *IEEE Communications Magazine*, 52(2):82–89, February 2014.

[BP08] Kitaek Bae and E. J. Powers. Distribution of envelope power using selected mapping in ofdm systems with nonlinearity. In *2008 IEEE International Conference on Acoustics, Speech and Signal Processing*, pages 3065–3068, March 2008.

[BR14] R. Beutler and D. Ratkaj. Crystal ball, tea leaves or mathematics forecasting data traffic for mobile services. Rev. Q1, European Broadcasting Union (EBU), May 2014.

[Bri08] A. Bria. *Mobile Multimedia Multicasting in Future Wireless Systems: A Hybrid Cellular-Broadcasting System Approach*. PhD thesis, KTH, Communication Systems, CoS, 2008.
[BRV05] J. C. Belfiore, G. Rekaya, and E. Viterbo. The golden code : a 2 times;2 full-rate space-time code with nonvanishing determinants. *IEEE Transactions on Information Theory*, 51(4):1432-1436, April 2005.

[BSHD13a] Emil Björnson, Luca Sanguinetti, Jakob Hoydis, and Mérouane Debbah. Designing multi-user mimo for energy efficiency : When is massive mimo the answer ? *arXiv preprint arXiv:1310.3843*, 2013.

[CHH08a] D. Catrein, J. Huschke, and U. Horn. Analytic evaluation of a hybrid broadcast-unicast tv offering. In *Vehicular Technology Conference, 2008. VTC Spring 2008. IEEE*, pages 2864-2868, 2008.

[Chr00] M. Chryssomallis. Smart antennas. *IEEE Antennas and Propagation Magazine*, 42(3):129-136, June 2000.

[CL14] In Kyeong Choi and Sok Kyu Lee. *Method and apparatus for allocating transmission power in multi input multi output system*. Google Patents, November 2014. US Patent 8,891,643.

[CM04] Lai-U Choi and R. D. Murch. A transmit preprocessing technique for multiuser mimo systems using a decomposition approach. *IEEE Transactions on Wireless Communications*, 3(1):20-24, Jan 2004.

[CMGB15] J. Calabuig, J.F. Monserrat, and D. Gomez-Barquero. 5th generation mobile networks : A new opportunity for the convergence of mobile broadband and broadcast services. *Communications Magazine, IEEE*, 53(2):198-205, Feb 2015.

[CS03] Giuseppe Caire and Shlomo Shamai. On the achievable throughput of a multiantenna gaussian broadcast channel. *Information Theory, IEEE Transactions on*, 49(7):1691-1706, 2003.

[CY09] Li-Chung Chang and Chung-Ho Yang. A combined approach of MBAP/PR PAPR reduction and polynomial predistortion for performance enhancement. In *Information, Communications and Signal Processing, 2009. ICICS 2009. 7th International Conference on*, pages 1-5, Dec 2009.

[D+04] Lei Ding et al. A robust digital baseband predistorter constructed using memory polynomials. *Communications, IEEE Transactions on*, 52(1):159-165, Jan 2004.

[DDG+12] C. Desset, B. Debaillie, V. Giannini, A. Fehske, G. Auer, H. Holtkamp, W. Wajda, D. Sabella, F. Richter, M. J. Gonzalez, H. Klessig, I. Gódor, M. Olsson, M. A. Imran, A. Ambrosy, and O. Blume. Flexible power modeling of Ite base stations. In *2012 IEEE Wireless Communications and Networking Conference (WCNC)*, pages 2858-2862, April 2012.

[Din04] Lei Ding. *Digital Predistortion of Power Amplifiers for Wireless Applications*. PhD thesis, School of Electrical and Computer Engineering, Georgia Institute of Technology, 2004.

[DJ98] Esmael H Dinan and Bijan Jabbari. Spreading codes for direct sequence cdma and wideband cdma cellular networks. *Communications Magazine, IEEE*, 36(9):48-54, 1998.

[DT09] DVB-T2. Frame structure channel coding and modulation for a second generation digital terrestrial television broadcasting system (dvb-t2), en-302755 v1.1.1. Technical report, ETSI, sept. 2009.

[DTF99] A. Derode, A. Tourin, and M. Fink. Ultrasonic pulse compression with one-bit time reversal through multiple scattering. *Journal of Applied Physics*, 85:6343-6352, May 1999.

[EAHAS+12] O. El Ayach, R.W. Heath, S. Abu-Surra, S. Rajagopal, and Zhouyue Pi. The capacity optimality of beam steering in large millimeter wave MIMO systems. In *2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)*, pages 100-104, June 2012.

[EVH+04b] Majid Emami, Mai Vu, Jan Hansen, Arogyaswami J Paulraj, and George Papanicolaou. Matched filtering with rate back-off for low complexity communications in very large delay spread channels. In *Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on*, volume 1, pages 218-222. IEEE, 2004.

[Fin92] M. Fink. Time reversal of ultrasonic fields. i. basic principles. *IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control*, 39(5):555-566, Sept. 1992.

[Fos96] Gerard J Foschini. Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. *Bell labs technical journal*, 1(2):41-59, 1996.
Bibliographie

[Fra13] Mobile Marketing Association France. Deuxième édition du baromètre trimestriel du marketing mobile, Juin 2013.

[Fra16] Marcelo Jorge Franco. *Wideband digital predistortion linearization of radio frequency power amplifiers with memory*. PhD thesis, Drexel University, 2016.

[FSY11] W. Fang, H. Sun, and L. Yang. Power allocation for maximizing sum capacity of multiuser mimo downlink with transmit precoding based on slnr. In *2011 IEEE 73rd Vehicular Technology Conference (VTC Spring)*, pages 1–5, May 2011.

[GEPB06] M. J. Fernandez-Getino Garcia, O. Edfors, and J. M. Paez-Borrallo. Peak power reduction for ofdm systems with orthogonal pilot sequences. *IEEE Transactions on Wireless Communications*, 5(1):47–51, Jan 2006.

[GH03] H. El Gamal and A. R. Hammons. On the design of algebraic space-time codes for mimo block-fading channels. *IEEE Transactions on Information Theory*, 49(1):151–163, Jan 2003.

[GMB05] P. Gilabert, G. Montoro, and E. Bertran. On the wiener and hammerstein models for power amplifier predistortion. In *2005 Asia-Pacific Microwave Conference Proceedings*, volume 2, pages 4 pp. –, Dec 2005.

[Gol67] Robert Gold. Optimal binary sequences for spread multiplexing (corresp.). *Information Theory, IEEE Transactions on*, 13(4):619–621, 1967.

[GOU13] Oussoulare Abel GOUBA. *Approche conjointe de la reduction du facteur de crete et de la linearisation dans le contexte ofdm*. PhD thesis, Ecole Doctorale MATISSE, 2013.

[GRJ+65] Izrail Solomonovich Gradshteyn, Iosif Moiseevich Ryzhik, Alan Jeffrey, Daniel Zwillinger, and Scripta Technica. *Table of integrals, series, and products*, volume 6. Academic press New York, 1965.

[H+13] H. Hemesi et al. Analytical Modeling of MIMO-OFDM System in the Presence of Nonlinear Power Amplifier with Memory. *on IEEE Trans. Commun*, 61(1):155–63, Jan. 2013.

[Hat80] M. Hata. Empirical formula for propagation loss in land mobile radio services. *IEEE Transactions on Vehicular Technology*, 29(3):317 – 325, 1980.

[HB06] Jeremiah Hu and Norman C Beaulieu. Accurate closed-form approximations for the error rate and outage of equal gain combining diversity in nakagami fading channels. In *Communications, 2006. ICC'06. IEEE International Conference on*, volume 11, pages 5145–5152. IEEE, 2006.

[HCPR12b] Hoon Huh, Giuseppe Caire, Haralabos C Papadopoulos, and Sean A Ramprashad. Achieving" massive mimo" spectral efficiency with a not-so-large number of antennas. *Wireless Communications, IEEE Transactions on*, 11(9):3226–3239, 2012.

[HCVG09] O. Hammi, S. Carichner, B. Vassilakis, and F. M. Ghannouchi. Effects of crest factor reduction on the predistortion performance for multi-carrier 3g rf power amplifiers. In *2009 IEEE MTT-S International Microwave Symposium Digest*, pages 1085–1088, June 2009.

[Heu10] C. Heuck. An Analytical Approach for Performance Evaluation of Hybrid (Broadcast/Mobile) Networks. *IEEE Transactions on Broadcasting*, 56(1):9–18, March 2010.

[HH02] B. Hassibi and B. M. Hochwald. High-rate codes that are linear in space and time. *IEEE Transactions on Information Theory*, 48(7):1804–1824, Jul 2002.

[HH03] Babak Hassibi and Bertrand M Hochwald. How much training is needed in multiple-antenna wireless links? *Information Theory, IEEE Transactions on*, 49(4):951–963, 2003.

[HL05] Seung Hee Han and Jae Hong Lee. An overview of peak-to-average power ratio reduction techniques for multicarrier transmission. *IEEE Wireless Communications*, 12(2):56–65, April 2005.

[HLGHB01] Maryline Hélard, Rodolphe Le Gouable, Jean-Francois Hélard, and Jean-Yves Baudais. Multicarrier cdma techniques for future wideband wireless networks. *Annales des télécommunications*, 56(5-6):260–274, 2001.

[HTBD+13a] Jakob Hoydis, Stephan Ten Brink, Mérouane Debbah, et al. Massive mimo in the ul/dl of cellular networks: How many antennas do we need? *IEEE Journal on selected Areas in Communications*, 31(2):160–171, 2013.
[HYW<sup>+12</sup>] Feng Han, Yu-Han Yang, Beibei Wang, Yongle Wu, and K.J.R. Liu. Time-reversal division multiple access over multi-path channels. *Communications, IEEE Transactions on*, 60(7):1953–1965, July 2012.

[IFS13] A. Ismail, J. Fiorina, and H. Sari. A new family of low-complexity stbcs for four transmit antennas. *IEEE Transactions on Wireless Communications*, 12(3):1208–1219, March 2013.

[INM89] N. Imai, T. Nojima, and T. Murase. Novel linearizer using balanced circulators and its application to multilevel digital radio systems. *IEEE Transactions on Microwave Theory and Techniques*, 37(8):1237–1243, Aug 1989.

[lon03] D. M. Ionescu. On space-time code design. *IEEE Transactions on Wireless Communications*, 2(1):20–28, Jan 2003.

[IR13] ITU-R. Future spectrum requirements estimate for terrestrial IMT. Tech. Rep. ITU-R M.2290, International Telecommunications Union (ITU), December 2013.

[Jaf01] H. Jafarkhani. A quasi-orthogonal space-time block code. *IEEE Transactions on Communications*, 49(1):1–4, Jan 2001.

[JAMV11] Jubin Jose, Alexei Ashikhmin, Thomas L Marzetta, and Sriram Vishwanath. Pilot contamination and precoding in multi-cell todd systems. *Wireless Communications, IEEE Transactions on*, 10(8):2640–2651, 2011.

[JBS00] Michel C. Jeruchim, Philip Balaban, and K. Sam Shanmugan, editors. *Simulation of Communication Systems: Modeling, Methodology and Techniques*. Kluwer Academic Publishers, Norwell, MA, USA, 2nd edition, 2000.

[JCS14] Jingon Joung, Yeow Khiang Chia, and Sumei Sun. Energy-efficient, large-scale distributed-antenna system (l-das) for multiple users. *Selected Topics in Signal Processing, IEEE Journal of*, 8(5):954–965, Oct 2014.

[JH05] H. Jafarkhani and N. Hassanpour. Super-quasi-orthogonal space-time trellis codes for four transmit antennas. *IEEE Transactions on Wireless Communications*, 4(1):215–227, Jan 2005.

[JKE08] S. Janaaththanan, C. Kasparis, and B. G. Evans. A gradient based algorithm for papr reduction of ofdm using tone reservation technique. In *VTC Spring 2008 - IEEE Vehicular Technology Conference*, pages 2977–2980, May 2008.

[JLL03] Jiho Jang, Kwang Bok Lee, and Yong-Hwan Lee. Transmit power and bit allocations for ofdm systems in a fading channel. In *Global Telecommunications Conference, 2003. GLOBECOM '03. IEEE*, volume 2, pages 858–862 Vol.2, Dec 2003.

[JMZ<sup>+14</sup>] V. Jungnickel, K. Manolakis, W. Zirwas, B. Panzner, V. Braun, M. Lossow, M. Sternad, R. Apel-frojd, and T. Svensson. The role of small cells, coordinated multipoint, and massive mimo in 5g. *IEEE Communications Magazine*, 52(5):44–51, May 2014.

[JR13] F. Juretzek and U. Reimers. Point-to-multipoint-overlay (p2mp) for lte-advanced using dvb-t2 future extension frames. In *IEEE Broadcast Symposium (BTS)*, pages 1–10, 2013.

[JWB94] A. E. Jones, T. A. Wilkinson, and S. K. Barton. Block coding scheme for reduction of peak to mean envelope power ratio of multicarrier transmission schemes. *Electronics Letters*, 30(25):2098–2099, Dec 1994.

[Kai02] S. Kaiser. Ofdm code-division multiplexing in fading channels. *Communications, IEEE Transactions on*, 50(8):1266–1273, Aug 2002.

[KBP<sup>+12</sup>] B. Koussa, S. Bachir, C. Perrine, C. Duvanaud, and R. Vauzelle. A comparison of several gradient based optimization algorithms for papr reduction in ofdm systems. In *CCCA12*, pages 1–6, Dec 2012.

[KC06] J.S. Kenney and Jau-Horng Chen. Power Amplifier Linearization and Efficiency Improvement Techniques for Commercial and Military Applications. In *Microwaves, Radar Wireless Communications, 2006. MIKON 2006. International Conference on*, pages 3–8, May 2006.

[KHNSL12] I. Kotzer, S. Har-Nevo, S. Sodin, and S. Litsyn. An Analytical Approach to the Calculation of EVM in Clipped Multi-Carrier Signals. *Communications, IEEE Transactions on*, 60(5):1371–1380, May 2012.
Bibliographie

[KJ03] B. S. Krongold and D. L. Jones. Par reduction in ofdm via active constellation extension. *IEEE Transactions on Broadcasting*, 49(3):258–268, Sept 2003.

[KK01] J. Kim and K. Konstantinou. Digital predistortion of wideband signals based on power amplifier model with memory. *Electronics Letters*, 37(23):1417–1418, Nov 2001.

[KPR12] F. Khan, Zhouyue Pi, and S. Rajagopal. Millimeter-wave mobile broadband with large scale spatial processing for 5g mobile communication. In *2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)*, pages 1517–1523, October 2012.

[LAZ07] Jun Luo, J.H. Andrian, and Chi Zhou. Bit error rate analysis of jamming for ofdm systems. In *Wireless Telecommunications Symposium, 2007. WTS 2007*, pages 1–8, April 2007.

[LC98] Xiaodong Li and L. J. Cimini. Effects of clipping and filtering on the performance of ofdm. *IEEE Communications Letters*, 2(5):131–133, May 1998.

[LC08] J. Liu and A. R. Calderbank. The icosian code and the $e_8$ lattice: A new $4, times, 4$ space-time code with nonvanishing determinant. *IEEE Transactions on Information Theory*, 54(8):3782–3789, Aug 2008.

[LdRT+04] G. Lerosey, J. de Rosny, A. Tourin, A. Derode, G. Montaldo, and M. Fink. Time reversal of electromagnetic waves. *Physical Review Letters*, 92:193904, May 2004.

[LdT+06] G. Lerosey, J. de Rosny, A. Tourin, A. Derode, and M. Fink. Time reversal of wideband micro-waves. *Applied Physics Letters*, 88(15), Apr. 2006.

[LdTF07] G. Lerosey, J. de Rosny, A. Tourin, and M. Fink. Focusing Beyond the Diffraction Limit with Far-Field Time Reversal. *Science*, 315:1120–, Feb. 2007.

[LETM13] Erik G Larsson, Ove Edfors, Fredrik Tufvesson, and Thomas L Marzetta. Massive mimo for next generation wireless systems. *arXiv preprint arXiv:1304.6690*, 2013.

[LH03] D.J. Love and R.W. Heath. Equal gain transmission in multiple-input multiple-output wireless systems. *Communications, IEEE Transactions on*, 51(7):1102–1110, July 2003.

[LLWZ14] Y. N. R. Li, J. Li, H. Wu, and W. Zhang. Energy efficient small cell operation under ultra dense cloud radio access networks. In *2014 IEEE Globecom Workshops (GC Wkshps)*, pages 1120–1125, Dec 2014.

[Lo99] Titus KY Lo. Maximum ratio transmission. In *Communications, 1999. ICC'99. 1999 IEEE International Conference on*, volume 2, pages 1310–1314. IEEE, 1999.

[LP08] Yves Louët and Jacques Palicot. A classification of methods for efficient power amplification of signals. *Annals of Telecommunications - annales des télécommunications*, 63(2008-08-07):351–368, August 2008.

[LV07] Y. Li and B. Vucetic. Design of differential space-time trellis codes. *IEEE Transactions on Wireless Communications*, 6(5):1631–1637, May 2007.

[Mar10a] Thomas L Marzetta. Noncooperative cellular wireless with unlimited numbers of base station antennas. *Wireless Communications, IEEE Transactions on*, 9(11):3590–3600, 2010.

[Med98] Jonas Medbo. Radio wave propagation characteristics at 5 ghz with modeling suggestions for hiperlan/2. *ETSI BRAN 3ERI074A*, 1998.

[MGL+15] U. Meabe, X. Gil, C. Li, M. Velez, and P. Angueira. On the Coverage and Cost of HPHT Versus LPLT Networks for Rooftop, Portable, and Mobile Broadcast Services Delivery. *IEEE Transactions on Broadcasting*, 61(2):133–141, June 2015.

[MH97] S. H. Muller and J. B. Huber. Ofdm with reduced peak-to-average power ratio by optimum combination of partial transmit sequences. *Electronics Letters*, 33(5):368–369, Feb 1997.

[MMK+06] D. R. Morgan, Z. Ma, J. Kim, M. G. Zierdt, and J. Pastalan. A generalized memory polynomial model for digital predistortion of rf power amplifiers. *IEEE Transactions on Signal Processing*, 54(10):3852–3860, Oct 2006.

[MNP+10a] M. Mroué, A. Nafkha, J. Palicot, B. Gavalda, and N. Dagorne. Performance and implementation evaluation of tr papr reduction methods for dvb-t2. *International Journal of Digital Multimedia Broadcasting*, 10:1–10, August 2010.
[MNP10b] M. Mroué, A. Nafkha, and J. Palicot. An innovative low complexity papr reduction tr-based technique for dvb-t2 system. In *International Congress on Ultra Modern Telecommunications and Control Systems*, pages 148-153, Oct 2010.

[MPB11] P. Moss, T. Y. Poon, and J. Boyer. "a simple model of the uhfcross-polar terrestrial channel for dvb-ngh", white paper,. Technical report, British Broadcasting Corporation, 2011.

[MWI+09] Christian Mehlführer, Martin Wrulich, Josep Colom Ikuno, Dagmar Bosanska, and Markus Rupp. Simulating the long term evolution physical layer. In *Proc. of the 17th European Signal Processing Conference (EUSIPCO 2009)*, Glasgow, Scotland, volume 27, page 124, 2009.

[NBEZ09] I.H. Naqvi, P. Besnier, and G. El Zein. Effects of time variant channel on a time reversal uwb system. In *IEEE Global Telecommunications Conference*, Dec. 2009.

[NE08] V. K. Nguyen and J. S. Evans. Multiuser transmit beamforming via regularized channel inversion : A large system analysis. In *IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference*, pages 1-4, Nov 2008.

[NG66] K. Narendra and P. Gallman. An iterative method for the identification of nonlinear systems using a hammerstein model. *IEEE Transactions on Automatic Control*, 11(3) :546-550, Jul 1966.

[NKE07] Hung Tuan Nguyen, P. Kyritsi, and P.C.F. Eggers. Time reversal technique for multi-user wireless communication with single tap receiver. In *Mobile and Wireless Communications Summit, 2007. 16th IST*, pages 1-5, July 2007.

[NMDL13] Hien Quoc Ngo, Michail Matthaiou, Trung Q Duong, and Erik G Larsson. Uplink performance analysis of multicell mu-simo systems with zf receivers. *Vehicular Technology, IEEE Transactions on*, 62(9) :4471-4483, 2013.

[NNB+13] T. Nakamura, S. Nagata, A Benjebbour, Y. Kishiyama, Tang Hai, Shen Xiaodong, Yang Ning, and Li Nan. Trends in small cell enhancements in LTE advanced. *IEEE Communications Magazine*, 51(2) :98-105, February 2013.

[NR12] P. Neumann and U. Reimers. Live and time-shifted content delivery for dynamic broadcast : terminal aspects. *IEEE Transactions on Consumer Electronics*, 58(1) :53-59, February 2012.

[NXP10] NXP. AN10945 174 MHz to 230 MHz DVB-T power amplifier with the BLF881. Technical report, NXP Semiconductors, 2010.

[NZZK09] Hieu Nguyen, Zhao Zhao, Feng Zheng, and T. Kaiser. On the msi mitigation for mimo uwb time reversal systems. In *Ultra-Wideband, 2009. ICUWB 2009. IEEE International Conference on*, pages 295-299, Sept. 2009.

[OHE+04] C. Oestges, J. Hansen, S. Emami, A. Kim, G. Papanicolaou, and A. Paulraj. Time reversal techniques for broadband wireless communication systems. *European Microwave Conference (Workshop)*, pages 49-66, Oct. 2004.

[OI02b] H. Ochiai and H. Imai. Performance analysis of deliberately clipped ofdm signals. *IEEE Transactions on Communications*, 50(1) :89-101, Jan 2002.

[OKPP05] C. Oestges, A.D. Kim, G. Papanicolaou, and A.J. Paulraj. Characterization of space-time focusing in time-reversed random fields. *Antennas and Propagation, IEEE Transactions on*, 53(1) :283-293, Jan. 2005.

[PFDB09] D. Panaitopol, J. Fiorina, and M.-G. Di Benedetto. Trade-off between the number of fingers in the prefilter and in the rake receiver in time reversal ir-uwb. In *IEEE International Conference on Ultra-Wideband*, pages 819-823, Sept. 2009.

[PKH+03] Jeongho Park, Changeon Kang, Daesik Hong, et al. Effect of partial band jamming on ofdm-based wan in 802.11 g. In *Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP'03)*. 2003 IEEE International Conference on, volume 4, pages IV-560. IEEE, 2003.

[Pop99] B.M. Popovic. Spreading sequences for multicarrier cdma systems. *Communications, IEEE Transactions on*, 47(6) :918-926, Jun 1999.

[QNR11] J. Qi, P. Neumann, and U. Reimers. Dynamic broadcast. In *2011 14th ITG Conference on Electronic Media Technology*, pages 1-6, March 2011.
# Bibliographie

[QR13] J. Qi and U. Reimers. A flexible signalling structure for content delivery in dynamic broadcast. In *2013 IEEE Third International Conference on Consumer Electronics ¿¿ Berlin (ICCE-Berlin)*, pages 1–5, Sept 2013.

[Rap91] C. Rapp. Effects of HPA-nonlinearity on a 4-DPSK/OFDM-signal for a digital sound broadcasting signal. In P. S. Weltevreden, editor, *ESA Special Publication*, volume 332 of *ESA Special Publication*, October 1991.

[RECEH13a] A.A. Razzac, S.E. Elayoubi, T. Chahed, and B. El-Hassan. Comparison of LTE eMBMS and DVB-NGH mobile TV solutions from an energy consumption perspective. In *2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops)*, pages 16–20, September 2013.

[RECEH13c] A.A. Razzac, S.E. Elayoubi, T. Chahed, and B. El Hassan. Planning of Mobile TV service in standalone and cooperative DVB-NGH and LTE networks. In *2013 11th International Symposium on Modeling Optimization in Mobile, Ad Hoc Wireless Networks (WiOpt)*, pages 609–614, 2013.

[Rep14] ECC Report. Long term vision for the UHF broadcasting band. Technical report, Electronic Communications Comitee (ECC), 2014.

[RHL+04] Heung-Gyoon Ryu, Tran Phuong Hoa, Kang Mi Lee, Sang-Woo Kim, and Jin-Soo Park. Improvement of power efficiency of HPA by the PAPR reduction and predistortion. *Consumer Electronics, IEEE Transactions on*, 50(1):119–124, Feb 2004.

[RIJ14] D. Rother, S. Ilsen, and F. Juretzek. A software defined radio based implementation of the tower overlay over Ite-a+ system. In *2014 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting*, pages 1–6, June 2014.

[RL03] Heung-Gyoon Ryu and Yun-Hee Lee. A new combined method of the block coding and predistortion for the nonlinear distortion compensation. *Consumer Electronics, IEEE Transactions on*, 49(1):27–31, Feb 2003.

[RRE14] S. Rangan, T. S. Rappaport, and E. Erkip. Millimeter-wave cellular wireless networks: Potentials and challenges. *Proceedings of the IEEE*, 102(3):366–385, March 2014.

[SAHC14a] A. L. Swindlehurst, E. Ayanoglu, P. Heydari, and F. Capolino. Millimeter-wave massive mimo: the next wireless revolution? *IEEE Communications Magazine*, 52(9):56–62, September 2014.

[Sal81] A. A. M. Saleh. Frequency-independent and frequency-dependent nonlinear models of twt amplifiers. *IEEE Transactions on Communications*, 29(11):1715–1720, November 1981.

[SC92] S. P. Stapleton and F. C. Costescu. An adaptive predistorter for a power amplifier based on adjacent channel emissions [mobile communications]. *IEEE Transactions on Vehicular Technology*, 41(1):49–56, Feb 1992.

[SEH+04] T. Strohmer, M. Emami, J. Hansen, G. Papanicolaou, and A.J. Paulraj. Application of time-reversal with mmse equalizer to uwb communications. In *IEEE Global Telecommunications Conference*, volume 5, pages 3123–3127, Dec. 2004.

[SPCK04] R. Sperlich, Y. Park, G. Copeland, and J.S. Kenney. Power amplifier linearization with digital pre-distortion and crest factor reduction. In *Microwave Symposium Digest, 2004 IEEE MTT-S International*, volume 2, pages 669–672 Vol.2, June 2004.

[SR09] K. P. Srinath and B. S. Rajan. Low ml-decoding complexity, large coding gain, full-rate, full-diversity stbcs for 2 times 2 and 4 times 2 mimo systems. *IEEE Journal of Selected Topics in Signal Processing*, 3(6):916–927, Dec 2009.

[SR13] K. P. Srinath and B. S. Rajan. Improved perfect space-time block codes. *IEEE Transactions on Information Theory*, 59(12):7927–7935, Dec 2013.

[SSH04] Quentin H Spencer, A Lee Swindlehurst, and Martin Haardt. Zero-forcing methods for downlink spatial multiplexing in multiuser mimo channels. *Signal Processing, IEEE Transactions on*, 52(2):461–471, 2004.

[SSS03] W. B. Sander, S. V. Schell, and B. L. Sander. Polar modulator for multi-mode cell phones. In *Custom Integrated Circuits Conference, 2003. Proceedings of the IEEE 2003*, pages 439–445, Sept 2003.
[TBK<sup>+15</sup>] M. Taranetz, T. Blazek, T. Kropfreiter, M.K. Muller, S. Schwarz, and M. Rupp. Runtime Pre-coding: Enabling Multipoint Transmission in LTE-Advanced System-Level Simulations. Access, IEEE, 3:725-736, June 2015.

[TC98] J. Tellado and J. M. Cioffi. Efficient algorithms for reducing par in multicarrier systems. In *Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252)*, pages 191-, Aug 1998.

[Tel99] Emre Telatar. Capacity of multi-antenna gaussian channels. *European transactions on telecommunications*, 10(6):585-595, 1999.

[TJC99] Vahid Tarokh, Hamid Jafarkhani, and A.R. Calderbank. Space-time block codes from orthogonal designs. *Information Theory, IEEE Transactions on*, 45(5):1456-1467, Jul 1999.

[TMoEE99] J. Tellado-Mourelo and Stanford University. Dept. of Electrical Engineering. *Peak to Average Power Reduction for Multicarrier Modulation*. Stanford University, 1999.

[TSC98] Vahid Tarokh, N. Seshadri, and A.R. Calderbank. Space-time codes for high data rate wireless communication: performance criterion and code construction. *Information Theory, IEEE Transactions on*, 44(2):744-765, Mar 1998.

[TvWA<sup>+16</sup>] M. Tercero, P. von Wrycza, A. Amah, J. Widmer, M. Fresia, V. Frascolla, J. Lorca, T. Svensson, M. H. Hamon, S. D. Roblot, A. Vijay, M. Peter, V. Sgardoni, M. Hunukumbure, J. Luo, and N. Vucic. 5g systems: The mmmagic project perspective on use cases and challenges between 6-100 ghz. In *2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)*, pages 200-205, April 2016.

[TZ06] Wojciech Tadej and Karol Życzkowski. A concise guide to complex hadamard matrices. *Open Systems & Information Dynamics*, 13(02):133-177, 2006.

[UK06] Peter Unger and Thomas Kürner. Radio network planning of dvb-h/umts hybrid mobile communication networks. *European Transactions on Telecommunications*, 17(2):193-201, 2006.

[UK09] Peter Unger and Thomas Kürner. Modeling and performance analyses of hybrid cellular and broadcasting networks. *International Journal of Digital Multimedia Broadcasting*, 2009, Article ID 329073, 9 pages, 2009.

[V1.01] ETSI TR 101 290 V1.2.1. Digital video broadcasting (dvb); measurement guidelines for dvb systems. Technical report, ETSI, 2001.

[v1.12a] ETSI TS 102 831 v1.2.1. Implementation guidelines for a second generation digital terrestrial television broadcasting system (dvb-t2). Technical report, Digital Video Broadcasting, 2012.

[VRM01] J. H. K. Vuolevi, T. Rahkonen, and J. P. A. Manninen. Measurement technique for characterizing memory effects in RF power amplifiers. *IEEE Transactions on Microwave Theory and Techniques*, 49(8):1383-1389, Aug 2001.

[Was04] Hugo Durney Wasaff. *Adaptive Pre-Distortion for Nonlinear High Power Amplifiers in OFDM Systems*. PhD thesis, Universitat Politècnica de Catalunya, 2004.

[WC09a] Y. Wang and J. Coon. Full rate orthogonal space-time block coding in ofdm transmission using time reversal. In *IEEE Wireless Communications and Networking Conference*, Apr. 2009.

[WCDS12a] S. Wagner, R. Couillet, M. Debbah, and D. T. M. Slock. Large system analysis of linear precoding in correlated miso broadcast channels under limited feedback. *IEEE Transactions on Information Theory*, 58(7):4509-4537, July 2012.

[WCL14] Kongtao Wang, Zhiyong Chen, and Hui Liu. Push-based wireless converged networks for massive multimedia content delivery. *Wireless Communications, IEEE Transactions on*, 13(5):2894-2905, May 2014.

[WFGV98] P.W. Wolniansky, G.J. Foschini, G.D. Golden, and R. Valenzuela. V-blast: an architecture for realizing very high data rates over the rich-scattering wireless channel. In *Signals, Systems, and Electronics, 1998. ISSSE 98. 1998 URSI International Symposium on*, pages 295-300, Sep 1998.

[WWGY10] J. Wang, X. Wang, Y. Guo, and X. You. A channel adaptive power allocation scheme based on slnr precoding for multiuser mimo systems. In *2010 IEEE 72nd Vehicular Technology Conference - Fall*, pages 1-4, Sept 2010.
[WWH<sup>+11</sup>] Beibei Wang, Yongle Wu, Feng Han, Yu-Han Yang, and KJ Ray Liu. Green wireless communications: a time-reversal paradigm. *Selected Areas in Communications, IEEE Journal on*, 29(8):1698-1710, 2011.

[WYZD13] Desheng Wang, Yifan Yang, Guangxi Zhu, and Xiaojiang Du. Distributed precoder design for inter-cell interference suppressing in multi-cell mu-mimo systems. In *2013 IEEE Wireless Communications and Networking Conference (WCNC)*, pages 1398-1403, April 2013.

[XMH<sup>+17</sup>] Ming Xiao, Shahid Mumtaz, Yongming Huang, Linglong Dai, Yonghui Li, Michail Matthaiou, George K. Karagiannidis, Emil Björnson, Kai Yang, Chih Lin, and Amitava Ghosh. Millimeter wave communications for future mobile networks. *CoRR*, abs/1705.06072, 2017.

[YM13b] Hong Yang and Thomas L Marzetta. Performance of conjugate and zero-forcing beamforming in large-scale antenna systems. *IEEE Journal on Selected Areas in Communications*, 31(2):172-179, 2013.

[ZDPC13] Wence Zhang, Bo Du, Cunhua Pan, and Ming Chen. Downlink sinr distribution in multiuser large scale antenna systems with conjugate beamforming. In *Global Communications Conference (GLOBECOM), 2013 IEEE*, pages 4163-4168. IEEE, 2013.

[ZG02] Shengli Zhou and Georgios B Giannakis. Optimal transmitter eigen-beamforming and space-time block coding based on channel mean feedback. *Signal Processing, IEEE Transactions on*, 50(10):2599-2613, 2002.

[ZHG08] L. Zhao, J. Huber, and W. Gerstacker. Design and analysis of bit interleaved coded space-time modulation. *IEEE Transactions on Communications*, 56(6):904-914, June 2008.

[ZPLL06] S. Zabre, J. Palicot, Y. Louet, and C. Lereau. Sopc approach for ofdm peak-to-average power ratio reduction in the signal adding context. In *2006 IEEE International Symposium on Signal Processing and Information Technology*, pages 834-839, Aug 2006.

[ZZZ13] Long Zhao, Hui Zhao, and Kan Zheng. Energy efficient power allocation strategy for downlink MU-MIMO with massive antennas. *The Journal of China Universities of Posts and Telecommunications*, 20(3):1-7, June 2013.
<figure><img src="image_99.png" /></figure>
Partie III

<figure><img src="image_100.png" /></figure>

Annexes
<figure><img src="image_101.png" /></figure>
Selected Article

S. Sindian, M. Crussière, J.F. Hélard, A.E. Samhat et A. Khalil, "Admission Control and Resource Allocation Strategies for 802.15.5", EURASIP Journal on Wireless Communications and Networking, Springer, novembre 2014, DOI :10.1186/1687-1499-2014-197.

Abstract

In this paper, a novel two-tier mechanism for the access control and resource allocation of a two-hop high data rate IEEE 802.15.5 network is proposed. One of the main contributions in this proposal is the use of a dynamic superframe size in the IEEE 802.15.5. Additionally, the ideas of using a superframe utilization threshold and a channel time allocation period (CTAP) utilization threshold are incorporated, with the aim of allowing more devices to access the shared superframe. Using these thresholds, two new hop-1 resource allocation algorithms are described; CTAP utilization threshold-based resource allocation algorithm (CTRA) and superframe utilization threshold-based resource allocation algorithm (STRA). These algorithms control the access of the hop-1 Mesh PicoNet Coordinators (MPNCs) and Mesh DEVices (MDEVs) to the channel time resources in the superframe. Furthermore, an algorithm for the distribution of the hop-1 MPNCs' resources among the real-time (RT) and non-real-time (NRT) MDEVs at hop-2 is introduced. In this mechanism, a new flag metric is applied to provide higher priorities to MPNCs over MDEVs in the hop-1 algorithms and to the RT MDEVs over the NRT MDEVs in the hop-2 algorithm. Simulation results show the superiority of the proposed mechanism over others by providing a higher satisfaction factor and higher fairness among the competing devices at both hop-1 and hop-2 of the IEEE 802.15.5.

Keywords: IEEE 802.15.5, High data rate WPAN, Resource allocation, Fairness, Dynamic superframe
# Admission control and resource allocation strategies for IEEE 802.15.5

Samar Sindian¹,<fnref n="2" />*, Matthieu Crussière¹, Jean-François Hélard¹, Abed Ellatif Samhat³ and Ayman Khalil¹,<fnref n="2" />

**Abstract**

In this paper, a novel two-tier mechanism for the access control and resource allocation of a two-hop high data rate IEEE 802.15.5 network is proposed. One of the main contributions in this proposal is the use of a dynamic superframe size in the IEEE 802.15.5. Additionally, the ideas of using a superframe utilization threshold and a channel time allocation period (CTAP) utilization threshold are incorporated, with the aim of allowing more devices to access the shared superframe. Using these thresholds, two new hop-1 resource allocation algorithms are described; CTAP utilization threshold-based resource allocation algorithm (CTRA) and superframe utilization threshold-based resource allocation algorithm (STRA). These algorithms control the access of the hop-1 Mesh PicoNet Coordinators (MPNCs) and Mesh DEVices (MDEVs) to the channel time resources in the superframe. Furthermore, an algorithm for the distribution of the hop-1 MPNCs' resources among the real-time (RT) and non-real-time (NRT) MDEVs at hop-2 is introduced. In this mechanism, a new flag metric is applied to provide higher priorities to MPNCs over MDEVs in the hop-1 algorithms and to the RT MDEVs over the NRT MDEVs in the hop-2 algorithm. Simulation results show the superiority of the proposed mechanism over others by providing a higher satisfaction factor and higher fairness among the competing devices at both hop-1 and hop-2 of the IEEE 802.15.5.

**Keywords:** IEEE 802.15.5; High data rate WPAN; Resource allocation; Fairness; Dynamic superframe

## 1. Introduction

A new high data rate (HR) wireless personal area network (WPAN) standard has been developed by IEEE 802.15.3 task group (TG) [1]. The IEEE 802.15.3 standard is designed to provide low complexity, low cost, low power consumption, and high data rate wireless connectivity among portable consumer electronics and communication devices. HR WPAN is expected to play a crucial role in the formation of home area networks and is targeted to support high-end multimedia applications with high throughput requirements. However, HR WPAN has a limited operating range with a single-hop communication between devices. In order to extend this range and enable multi-hop communications, the mesh networking approach is utilized. A HR WPAN mesh network can be formed by interconnecting simultaneously operating piconets (SOPs). Hence, various problems may arise including inter-piconet interferences, beacon collisions,

throughput limitations, channel resource reservation collisions, etc. Different works [2-6] investigate the resource allocation mechanisms and propose solutions to overcome these limitations while trying to extend the coverage area of an IEEE 802.15.3-based WPAN. A detailed description of these works is presented in [7].

However, drawbacks in terms of system coverage and device connectivity are still evident despite the solutions presented in the works stated above. Consequently, and in order to extend the single-hop range of HR WPANs to multiple hops, the IEEE 802.15.5 standard was developed in 2009 to define the necessary specifications for HR WPANs operation in a mesh configuration [8]. The IEEE 802.15.5 [9] network is dynamically self-organized and self-configured, i.e., the nodes in the network automatically establish and maintain mesh connectivity among themselves. IEEE 802.15.5 provides the architectural framework enabling WPAN devices to promote interoperable, stable, and scalable wireless mesh topologies and, if needed, to provide the amendment text to the current WPAN standards that is required to implement this recommended practice [10].

<figure><img src="image_102.png" /></figure>

<footnote>* Correspondence: sindian_s@hotmail.com
¹INSA de Rennes, IETR, UMR 6164, F-35708 Rennes, France</footnote>

<footnote n="2">²CCE Department, Faculty of Engineering, IUL, 30014 Khaldeh, Lebanon
Full list of author information is available at the end of the article</footnote>
In the case of IEEE 802.15.5, multiple WPAN clusters compete for channel time in a shared superframe. Therefore, it is essential to determine the channel time requirements of each cluster with a certain number of devices and to determine how these clusters can compete to the shared channel time.

The work in [11] presents a distributed resource allocation scheme for meshed WPANs based on a utility function. In this paper, a novel centralized scheme for resource allocation in a two-hop IEEE 802.15.5 based on the centralized approach described in [12] is proposed. One of the main contributions in this proposal is the introduction of the notion of dynamic superframe size to the IEEE 802.15.5. This consequently leads to a much more efficient use of the superframe as it will be shown later by results. Additionally, the channel time requests (CTRqs) of both the hop-1 Mesh DEVices (MDEVs) and Mesh PicoNet Coordinators (MPNCs) are taken into consideration. The latter are assigned higher priority and larger channel time allocations (CTAs) providing them with sufficient channel time resources for serving their clusters. The notion of utilization thresholds, which enables the allocation of variable CTA sizes for prompting fairness, is also introduced. Consequently, more devices are granted access to channel time resources but with smaller sizes. In this context, two types of utilization thresholds are proposed in order to be applied in two different hop-1 algorithms. Additionally, a mechanism for distributing the hop-1 MPNC resources among their hop-2 devices is proposed. Moreover, service differentiation is applied by providing higher priority and larger CTA allocations for RT over NRT traffic requests at hop-2. This proposal shows higher satisfaction and fairness by the introduction of a priority flag metric and by taking the devices' rejected requests into account.

The rest of this paper is organized as follows. Section II briefly describes the works related to resource allocation in IEEE 802.15.5. Section III introduces the IEEE 802.15.5 WPAN architecture. In Section IV, the standard resource allocation mechanism is described. In Section V, the new notions to be incorporated into the proposed mechanism are presented. This is followed by the presentation of the different IEEE 802.15.5 hop-1 and hop-2 resource allocation mechanisms in Section VI. In Section VII, the simulation results of the different mechanisms are presented. Finally, Section VIII concludes the paper.

## 2. Related work

Under the IEEE 802.15.5 umbrella, few research works [11,12] investigating the resource allocation mechanisms for the hop-1 of HR IEEE 802.15.5 have been conducted. But to the readers' knowledge, no work has already studied a resource allocation and admission control

mechanism at the IEEE 802.15.5 hop-2. Additionally, no work has introduced the notion of service differentiation among the real-time (RT) and non-real-time (NRT) devices in IEEE 802.15.5.

In [11], a distributed algorithm which calculates a fair share in the superframe for each requesting MPNC is proposed. It considers a cooperative approach in which the utility for each ref-MPNC is maximized in a way that the other requesting MPNCs benefit as well. However, the algorithm is based on the individual requests for each flow by the MPNC. The distributed allocation, although having some merits, has some drawbacks. In [9] and [11], as the number of devices increases in each cluster and also in the presence of a dense meshed WPAN with a high number of MPNCs, the probability of channel time request conflict increases. Additionally, due to the lack of an appropriate mechanism to determine a fair share for each MPNC, unfairness is likely in the reservations by the MPNCs in the mentioned distributed mechanisms.

The most relevant work for resource allocation in meshed WPANs is given in [12], where the resource allocation is done on a centralized basis for a two-hop neighborhood. In the centralized approach, one MPNC among each neighborhood of MPNCs which share a common beacon period (BP) in the superframe is selected as the reference MPNC (ref-MPNC) for the other MPNCs to synchronize their time slots with. In the centralized approach, the ref-MPNC keeps track of the time reservations in the superframe up to two hops and therefore assuring that there are no conflicts in channel time reservation. Another feature of the approach in [12] is that the channel time is reserved in bulk by the MPNCs rather than a request by request basis to reduce the amount of control overhead. The idea behind bulk reservation is to join a group of channel time requests in one large request, thus reducing the possibility of CTA conflicts in case of higher device density. The approach in [12] studies the satisfaction and fairness among the MPNCs at hop-1 of the IEEE 802.15.5. In spite of the advantages of this centralized approach over the distributed one, it does not take into consideration the channel time requirements of neither the hop-1 MDEVs in the ref-MPNC cluster nor the hop-2 MDEVs in the hop-1 MPNCs clusters. Moreover, it considers the fixed maximum superframe size (65,535 µs) according to the IEEE 802.15.3 [1] which could be inefficiently utilized in case of low-loaded networks. Additionally, each MPNC estimates its channel requirements based on a history of previous flows. Therefore, inefficient superframe utilization can occur because of incorrect channel time estimation for a bulk reservation by each MPNC due to either overestimation or underestimation of the channel time requirement of a cluster.
### 3. Mesh WPAN based on the IEEE 802.15.5 standard

The recommendations for operation in a mesh configuration for WPANs are given in the IEEE 802.15.5 standard [9]. This standard has two parts in which one part defines necessary specifications for low data rate (LR) WPANs [13] and the other part for HR WPANs. The mesh-related functions and services reside over the IEEE 802.15.3 MAC sublayer as shown in Figure 1. Providing multi-hop services necessitates a slight amendment of the underlying MAC sublayer in the reference model.

The LR WPAN provides data rate of about 0.25 Mbps, which is not convenient to support high rate or real-time multimedia traffic. The work in [14] presents a new synchronization approach 'High-Performance Synchronization Algorithm for wireless mesh sensor networks (HIPESYN)', which is adapted to the LR IEEE 802.15.5 standard for synchronous communications. However, because of the low data rate provided by the LR WPAN, our work focuses on the HR WPAN which provides a high data transmission of 55 Mbps that is suitable for supporting RT applications.

#### 3.1 IEEE 802.15.5 architecture

The IEEE 802.15.5 Recommended Practice is a member of the WPAN standard family. It is developed based on IEEE 802.15.3-2003/2005 MAC/PHY layer specifications [10]. The architectural framework of the HR WPAN mesh is to allow multiple MPNCs and MDEVs to participate in communications across multiple piconets. The communication between MDEVs and MPNCs of different piconets is called inter-PAN communication while communication between devices in the same piconet is called intra-PAN communication (Figure 2). Additionally, since all the MPNCs could be connected to each other using the mesh topology, there is no single point of failure in the mesh network. Moreover, IEEE 802.15.5 enables the MAC to handle multiple connections at a given time using different channels.

#### 3.2 IEEE 802.15.5 superframe

A MPNC manages the synchronization and controls the data traffic of the system. In a meshed WPAN, communications between MPNCs and within their piconets take place in a shared superframe. The superframe can

be used for transmission of beacons from MPNCs and data communication. It is composed of three main parts (Figure 3):

* The beacon period: the beacon (Figure 4) is transmitted periodically by a MPNC to provide information about neighbor reservations and provide timing information that aids in synchronization. This helps in avoiding beacon reservation conflicts.

* The channel access period (CAP) is carrier sense multiple access with collision avoidance (CSMA/CA) based and it can be used for sending association requests and other commands. The CAP is shared among the MPNCs.

* The channel time allocation period (CTAP) is time division multiple access (TDMA) based. It is divided into equal length medium access slots (MASs) used to address medium reservations between MPNCs. A MAS is composed of CTAs that are used by devices to exchange data connections. The smallest channel time unit is referred to as time unit (TU). A TU is a unit of time of the CTA with a resolution of 1 µs to make the allocation of time easier for the MPNC.

### 4. IEEE 802.15.5 standard resource allocation mechanism

Before allocating the channel time resources, a device calculates the necessary number of TUs per superframe. The device then indicates the minimum and the desired number of TUs it requires through a CTRq command (Figure 5) to the MPNC. The MPNC after getting the CTRq from the device checks the available capacity of the superframe, and if suitable, it sends a channel time response command (CTRp) (Figure 6). Using the CTRp, a MPNC indicates to the requesting device the available number of TUs and also notifies the neighbor MPNCs of the new reservation.

The IEEE 802.15.5 standard in [9] identifies that the MPNCs which are in a single-hop transmission range of each other need to synchronize their boundaries to a common ref-MPNC to avoid time slot overlaps due to synchronization issues. The procedure given in [9] for time reservation by a MPNC for intra-PAN flows is

<table><caption>Figure 1 IEEE 802.15.5 layers.</caption><thead><tr><th colspan="10">IEEE 802.15.5 - WPAN Mesh</th></tr><tr><th>Mesh Sublayer</th><th colspan="5">Low Rate WPAN</th><th colspan="4">High Rate WPAN</th></tr><tr><th>MAC/PHY layers</th><th>15.4b</th><th>15.4a</th><th>15.4c</th><th>15.4d</th><th>15.4e</th><th>15.4f</th><th>15.4g</th><th>15.3</th><th>15.3b</th><th>15.3c</th></tr></thead><tbody><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<figure><img src="image_103.png" /><figcaption>Figure 2 Two-hop IEEE 802.15.5 mesh configuration.</figcaption></figure>

different from inter-PAN flows. But in both cases, if the MPNC reserves channel time in the superframe, it indicates the time reserved via a CTA status information element (IE) and then via a CTA IE in its beacon frame (Figure 4). The other MPNCs, upon checking these IEs, check if the reserved time conflicts with any of the time slots already reserved by them. In case there is a conflict, the other MPNCs can raise an objection IE in their beacon and the MPNC which reserved the time can shift the reserved time slots to another location on the superframe and then wait for an objection again. If there is no objection raised, the MPNC finalizes the reserved time. Since this mechanism is distributed, thus as the number of devices increases in each piconet of a dense meshed WPAN with a higher number of MPNCs, the probability of channel time request conflict increases. Furthermore, the distributed superframe sharing can cause fairness issues because there is no mechanism to determine the requirement of each MPNC and monitor a fair allocation to each MPNC. These are the main drawbacks of the resource allocation mechanism of the IEEE 802.15.5 standard.

## 5. IEEE 802.15.5 proposed admission control schemes

If a MPNC allocates the channel time to a device based on the available time in the superframe only, then most of the devices might not get a fair share of the superframe. While allocating the channel time, the MPNC should ensure an approach such that the maximum number of devices in the piconet gets a fair share of the superframe time based on their requirements.

With the novel proposed admission control approach, a centralized two-tier mechanism for coordinating the resource allocation algorithms of both the hop-1 (between the ref-MPNC and its member hop-1 MDEVs/ MPNCs) and hop-2 (between the hop-1 MPNCs and their member hop-2 RT/NRT MDEVs) of the IEEE 802.15.5 is carried out. With this scheme, the ref-MPNC is used for allocating the channel time to each requesting device at hop-1. Some of the introduced notions are used by both hop-1 and hop-2 access mechanisms, namely, bulk channel time requests and flag metric notions. Other notions are introduced only to the hop-1 resource allocation mechanism, namely dynamic superframe

<figure><img src="image_104.png" /><figcaption>Figure 3 Superframe sharing in IEEE 802.15.5.</figcaption></figure>
<figure><img src="image_105.png" /><figcaption>Figure 4 Beacon frame.</figcaption></figure>

and utilization threshold notions. Under the utilization thresholds, two different thresholds are proposed to be used in the resource allocation mechanisms at hop-1, the superframe utilization threshold and the CTAP threshold.

## 5.1 Dynamic superframe size

With this proposal, the notion of dynamic superframe size starting with a minimum value as identified in [1] is introduced. The increase in the superframe size is restricted by the maximum size of the superframe. There exist two different policies that could be used to manage CTAs according to devices' needs. The first is to start off with a maximum superframe length and try to manage the growing number of CTRq commands by proper allocation of CTAs. The second method is to have an initial small superframe length and adjust its length any time it is necessary. The superframe duration can be extracted from the 'superframe duration field' in the 'piconet synchronization parameters' (see Figure 4) that are broadcasted in the beacon.

The size of the superframe is managed by the ref-MPNC which, based on the novel proposal, recomputes the new superframe size after each CTA request decision. In case of an accepted CTRq, the new allocated channel time size is added to the superframe size and this new size is broadcasted to the devices in the 'superframe timing' field in the piconet parameter change IE (Figure 4) in the beacon. In such cases, the waiting time to start a new superframe is avoided if the maximum superframe size is not reached. Thus, the QoS requirements for real-time traffic in IEEE 802.15.5 can be much satisfied by minimizing the delay between two consecutive CTAs of the same device. Additionally, the superframe capacity is efficiently utilized especially when the network is not overloaded. Consequently, only a portion of the superframe size is used (instead of using its maximum size), thus avoiding the wastage of the superframe capacity.

## 5.2 Bulk channel time requests model

The notion of bulk CTRq (BCTRq) sent by the MPNCs to the ref-MPNC at hop-1 is also considered. In the proposed mechanism, the BCTRqs sent by a MPNC to the ref-MPNC are based on the aggregate of the received CTRqs from its members' MDEVs at hop-2. As highlighted in Figure 5, the MPNCs send BCTRq for requesting CTAs from the ref-MPNC by identifying the 'minimum number of TUs' and the 'desired number of TUs' fields. After receiving the requests, the ref-MPNC can decide to accept or deny the request according to the proposed algorithms, and it notifies the requesting device by sending a CTRp (see Figure 6). The ref-MPNC decision to allocate channel time is based on prioritizing the MPNCs over the MDEVs by granting the MPNCs more TUs.

## 5.3 Flag metric notion

In addition to the use of utilization thresholds, fairness and different priorities are also induced in the proposed mechanism by the use of a priority flag metric (Flag). The ref-MPNC keeps a global record of flag metrics for its members' MDEVs and MPNCs at hop-1. Each hop-1 MPNC also keeps a record of Flag for its member RT and NRT MDEVs at hop-2. Each device is identified at the ref-MPNC by a device identifier (Dev_id) as defined in [9]. Each raised Flag (i.e., its value is greater than zero) refers to a rejected CTRq or BCTRq. The flag metrics list is kept along all the superframe durations. If a device's request is rejected, its flag metric is incremented by one. Otherwise, this metric is decremented, provided that its value is greater than zero (to avoid having a negative flag metric). The flag metrics list is utilized by the ref-MPNC at the CAP of the next superframe to generate a priority list *P* that includes the flag metrics sorted in a descending order. Then, the ref-MPNC uses *P* to sort the Dev_id list accordingly, i.e., Dev_id of the device having first metric in *P* is set at the head of the new Dev_id list. At the CAP of the next superframe, the

<table><caption>Figure 5 Channel time request block field format.</caption><thead><tr><td>Desired number of TUs</td><td>Minimum number of TUs</td><td>CTRq TU</td><td>CTA rate factor</td><td>CTRq control</td><td>Stream index</td><td>Stream request ID</td><td>DSPS set indes</td><td>Target ID list</td><td>Num targets</td></tr></thead></table>
<table><caption>Figure 6 Channel time response command format.</caption><thead><tr><th>Reason code</th><th>Available number of TUs</th><th>Stream index</th><th>Stream request ID</th><th>length</th><th>Command type</th></tr></thead></table>

devices' requests are served according to this new Dev_id list. Moreover, the initial flag metrics assigned to the hop-1 MPNCs and hop-2 RT MDEVs are higher than that of hop-1 MDEVs and hop-2 NRT MDEVs, respectively.

## 5.4 Utilization thresholds

In order to attract more devices, the network must be able to offer a comparatively satisfactory service to the devices to reduce the loss of devices. However, because of a limited superframe capacity, some devices' requests are rejected in order to satisfy other devices' requirements. Obviously, it is not fair to guarantee the requesting devices' QoS by rejecting more devices. Consequently, a compromise between the devices satisfaction and the requests' rejection rate is applied by the use of utilization thresholds at the hop-1 resource allocation mechanism. These thresholds are the CTAP utilization threshold and the superframe utilization threshold.

### 5.4.1 CTAP utilization threshold

In the proposed mechanism, the CTAP threshold (CTAP_T_L) is introduced to split the CTAP into two sub-CTAPs, MPNC-CTAP, and MDEV-CTAP. The sizes of these two sub-CTAPs are referred to as CTAP_MPCN_size and CTAP_MDEV_size, respectively. These sizes are adjusted according to Φ as:

$$ CTAP\_MPNC\_size = \Phi \times size_{max}, \text{ where } (0 < \Phi < 1) \quad (1) $$

and

$$ CTAP\_MDEV\_size = (1-\Phi) \times size_{max} \quad (2) $$

where size_max is the maximum size of the superframe. For providing higher priority for the MPNCs over the MDEVs, a larger CTAP portion is reserved for the

MPNCs, i.e., CTAP_MPCN_size > CTAP_MDEV_size, by adjusting the value of Φ to be greater than (1 - Φ).

Then, a MPNC threshold (MPNC_T_L) is introduced in the CTAP_MPCN and is used by the ref-MPNC to adjust the size of the channel time resources to be granted for the requesting MPNCs. Similarly, a MDEV threshold (MDEV_T_L) is introduced in the CTAP_MDEV which, in its turn, is used by the ref-MPNC to adjust the size of the channel time resources to be granted for the requesting MDEVs (Figure 7). These thresholds are defined as follows:

$$ MPNC\_T_L = \beta_1 \times CTAP\_MPNC\_size, \text{ where } (0 < \beta_1 < 1) \quad (3) $$

$$ MDEV\_T_L = \beta_2 \times CTAP\_MDEV\_size, \text{ where } (0 < \beta_2 < 1) \quad (4) $$

where the values of these thresholds are adjusted according to β1 and β2, respectively. As long as the total allocated channel time size in the CTAP_MPCN and CTAP_MDEV is below the MPNC_T_L and the MDEV_T_L, respectively; the channel times are granted in a way such that the requesting devices are highly satisfied, i.e., the granted channel times are approximately equal to the requested channel times. Otherwise, the ref-MPNC applies a control procedure that minimizes the size of the granted resources in order to allow more devices to get channel access. This is in condition that the granted resources remain greater than or equal to the minimum requested channel times.

### 5.4.2 Superframe utilization threshold

The proposed mechanism applies a common superframe utilization threshold (T_L) for the hop-1 devices (MPNCs and MDEVs) in another hop-1 resource allocation

<figure><img src="image_106.png" /><figcaption>Figure 7 CTAP utilization thresholds.</figcaption></figure>
algorithm. Then, the prioritization of the MPNCs over MDEVs is applied within this algorithm. The use of $T_L$ is such that whenever the total CTAP allocated channel time size is below $T_L$, the requesting devices are highly satisfied. Then when the total allocated superframe size exceeds this threshold, the ref-MPNC reduces the granted resource size to allow more devices to get channel access. Nevertheless, it is guaranteed that the granted channels are still greater than or equal to the minimum requested resources by a device. The threshold $T_L$ is defined as:

$$T_L = size_{max} - 2 \times \alpha \times TU \times N \quad (5)$$

where TU is the duration of a time unit in microseconds, N is the total number of devices and α is a factor through which different values of $T_L$ can be obtained as illustrated in Figure 8. All the other parameters for calculating $T_L$ are considered to be constant in a certain scenario. The reason of the choice of $(2 \times TU \times N)$ is to ensure that two TUs, as minimum, are available for each of the associated devices to be capable of communicating with the ref-MPNC (one TU for uplink stream and another for downlink stream).

## 6. IEEE 802.15.5 proposed resource allocation mechanisms

The block diagram shown in Figure 9 represents the proposed two-hop IEEE 802.15.5 mechanism which can be decomposed into five stages. It is a two-tier mechanism of hop-1 resource allocation algorithms for the MDEVs and MPNCs and a hop-2 resource allocation algorithm for the RT and NRT MDEVs. For the hop-1, two different algorithms are proposed at stage (3) and the hop-2 algorithm takes place at stage (5). It is important to mention that the implementation of the hop-2 algorithm is related to the validity of the condition that the hop-1 device is a MPNC with granted channel time resources as shown in Figure 9. In the sequel, each block is described in details. These algorithms can be defined as follows:

Hop-1 algorithms: control the admission and resource allocation between the ref-MPNC and its member MDEVs/MPNCs belonging to the parent piconet. Individual CTRqs are sent from MDEVs to ref-MPNC

and BCTRqs are sent from MPNCs to ref-MPNC. For the hop-1 mechanism, two algorithms are proposed: the first one is the CTAP utilization threshold-based resource allocation algorithm (CTRA) and the second one is the superframe utilization threshold-based resource allocation algorithm (STRA). Hop-2 algorithm: controls the admission and resource allocation between the hop-1 MPNCs and their member RT/NRT MDEVs. The concerned MPNC applies the hop-2 algorithm which is a service differentiation-based resource allocation algorithm (SDRA) to distribute the CTAs among the RT and NRT MDEVs.

### 6.1 Hop-1 resource allocation algorithms

According to the novel proposal, we have two hop-1 resource allocation algorithms, CTRA and STRA. Each of these algorithms can be divided into several stages. These stages are common between both of these algorithms except for the 'hop-1 channel time calculations' stage which is particular for each of these two algorithms. These stages, identified in Figure 9, are described as follows and are detailed accordingly in the form of block diagrams from Figures 10, 11, 12, 13, 14, 15, and 16:

**Stage (1) - Initialization and hop-1 Priority list creation:** The flow chart corresponding to this stage is described in Figure 10. At the initial stage, the minimum and maximum superframe sizes ($size_{min}$ and $size_{max}$) are set. The ref-MPNC initializes the devices ID list (Dev_id1) of its hop-1 MPNCs and MDEVs. In each superframe S, the Flag metric list is generated with initial values for each device. Higher flag metrics are assigned to the MPNCs to give them higher priority than MDEVs. Prior to its channel time requests decision, a ref-MPNC creates a priority list (P1) from the Flag metric list sorted in a descending order. The Dev_id1 list is then sorted according to P1. The abbreviations' descriptions of all the flowcharts are presented in Table 1.

**Stage (2) - Receiving channel time requests:** The flowchart of this stage is shown in Figure 11. Whenever the ref-MPNC receives a CTRq/BCTRq, it serves it according to the sorted Dev_id1 list. Since the MPNCs are assigned higher flag metrics at the initialization

<figure><img src="image_107.png" /><figcaption>Figure 8 Superframe utilization threshold for different α.</figcaption></figure>
<figure><img src="image_108.png" /><figcaption>Figure 9 Two-hop proposed mechanism block diagram.</figcaption></figure>

<figure><img src="image_109.png" /><figcaption>Figure 10 Initialization stage flowchart.</figcaption></figure>
<figure><img src="image_110.png" /><figcaption>Figure 11 Receiving channel time requests flowchart.</figcaption></figure>

stage, then they occupy the first positions of the Dev_id1 list. The values of the minimum number of TUs (min_TUᵢ) and the desired number of TUs (des_TUᵢ) of each device *i* are equal to a fraction of its requested channel time resources (rᵢ), i.e., (a.rᵢ) and (b.rᵢ), respectively, where a and b values are less than 1. Stage (3) - Hop-1 channel time calculations: In this stage, the behavior of the two hop-1 algorithms is differentiated as follows:

### 6.1.1 CTAP utilization threshold-based resource allocation algorithm

Firstly, the ref-MPNC checks if the request received is sent by a MPNC or a MDEV (see Figure 12). Consequently, it checks the MPNC_TL or MDEV_TL, and it then grants the channel times accordingly. Additionally, the ref-MPNC has to grant channel times for the MPNCs from the CTAP MPNC portion in the shared superframe according to the MPNC_TL. As long as the total allocated CTAP MPNC channel time ($A_{mpnc}$) does not exceed MPNC_TL, the ref-MPNC grants up to the des_TUᵢ for a BCTRq. Otherwise, it indicates to the

attached devices in the capability IE in the beacon (Figure 4) about the new capacity constraints and it reduces the size of the granted channel times to the average of the min_TUᵢ and des_TUᵢ for the requesting MPNC.

Similarly for the MDEV CTRqs, when the total allocated CTAP MDEV channel time ($A_{mdev}$) is below MDEV_TL, the MDEVs are granted up to the average of the min_TUᵢ and des_TUᵢ. When the total MDEVs' allocated resources exceed MDEV_TL, the ref-MPNC indicates to the attached devices in the capability IE about the new capacity constraints. From now on, the ref-MPNC accepts requests with new constraints by granting up to the min_TUᵢ for the requesting MDEVs. In the proposed algorithms, the calculated channel times are referred to as $rq_b$ then if these resources are granted successfully we refer to them as $g_i$.

### 6.1.2 Superframe utilization threshold-based resource allocation algorithm

The algorithm flowchart of the proposed mechanism is shown in Figure 13. The ref-MPNC grants up to the des_TUᵢ for a BCTRq, while it grants up to the average

<figure><img src="image_111.png" /><figcaption>Figure 12 CTRA resource allocation algorithm.</figcaption></figure>
<figure><img src="image_112.png" /><figcaption>Figure 13 STRA resource allocation algorithm.</figcaption></figure>

of the min_TUᵢ and des_TUᵢ for a CTRq. This is applied as long as the total allocated channel time (A) is below a certain superframe utilization threshold T<sub>L</sub>. When the allocated resources exceed T<sub>L</sub>, the ref-MPNC indicates to the attached devices in the capability IE (in the beacon) about the new capacity constraints the ref-MPNC is capable of handling. Later on, the ref-MPNC accepts requests with new constraints, it grants up to the average of the min_TUᵢ and des_TUᵢ for MPNCs and up to the min_TUᵢ for the MDEVS.

Stage (4) - Admission control decision: the flowchart of this stage is shown in Figure 14. For both hop-1 algorithms, the conditions applied on the size of channel time to be granted (rqᵢ) are applied as long as the summation of (A) and (rqᵢ) does not exceed the superframe maximum capacity (size<sub>max</sub>); otherwise, the requests are rejected. In the case where a BCTRq/CTRq is rejected, the Flag metric of the concerned MPNC/MDEV is incremented and a negative CTRp is sent by the ref-MPNC. Otherwise, a positive CTRp is received by the device with the granted channel time resources (gᵢ) and its Flag metric is decremented by one. In both CTRA

and STRA, a satisfaction factor of each device (sat<sub>fᵢ</sub>) is calculated as defined in Equation 7. The new granted resources amount (gᵢ) is added to the total allocated resources (A) during a superframe. The new superframe size (S<sub>z</sub>) is then calculated by the addition of (A) to size<sub>min</sub> as follows:

$$S_z = size_{\min} + A \quad (6)$$

The satisfaction factor of a device i is defined to be equal to the ratio of granted TUs (gᵢ) divided by the desired TUs (des_TUᵢ) requested by a device i as:

$$sat_{f_i} = \frac{g_i}{des\_TU_i} \quad (7)$$

Stage (5) - Average satisfaction and fairness computation: Before moving to the next superframe (j + 1), the hop-2 resource allocation algorithm is applied to the hop-2 members only if the hop-1 member is a MPNC and it has been granted channel time resources, i.e., gᵢ > 0 (Figure 15). Then the algorithm returns back to the point number (C) identified in Figure 11 to repeat stages (2) and

<figure><img src="image_113.png" /><figcaption>Figure 14 Admission control and satisfaction stage.</figcaption></figure>
<figure><img src="image_114.png" /><figcaption>Figure 15 Average satisfaction and fairness computation stage flowchart.</figcaption></figure>

(3) for all the other hop-1 devices until $i$ reaches $N$. Next, it calculates the average satisfaction factor of all the devices after calculating the device satisfaction factor at stage (3). The average satisfaction factor is defined as:

$$ sat_{f_{av}} = \frac{\sum_{i} sat_{f_i}}{n} \qquad (8) $$

where $n$ represents the number of devices (MPNCs or MDEVs). Using only $sat_{f_{av}}$ value is not enough to determine the fairness of the proposed resource allocation mechanism. It is highly desirable to find a method and, preferably, an index to measure and compare the degree of fairness of a particular allocation policy [15]. Many general purpose fairness indexes (Gini, Jain's Fairness,

min-max) have been frequently used to measure fairness of different resource allocation schemes [16,17]. We apply the Jain's Fairness index on the satisfaction factor which is in function of granted resources and requested resources as defined in Equation 7. The Jain's Fairness index is defined as follows:

$$ f(x) = \frac{\left(\sum_{i} sat_{f_i}\right)^2}{N \sum_{i} sat_{f_i}^2} \quad \forall i = 1, 2, \dots, N \qquad (9) $$

where $f(x = sat_f)$ is the Jain's Fairness index and $N$ is the total number of devices. The fairness index value is a positive number with max value 1 indicating a 100% fair system.

<figure><img src="image_115.png" /><figcaption>Figure 16 SDRA resource allocation algorithm.</figcaption></figure>
<table><caption>Table 1 Flowcharts abbreviations</caption><thead><tr><td>Abbreviation</td><td>Description</td></tr></thead><tbody><tr><td>Dev_id1, Dev_id2</td><td>Array of device ID for the devices at hops 1 and 2, respectively</td></tr><tr><td>P1, P2</td><td>Priority lists at hops 1 and 2, respectively</td></tr><tr><td>A</td><td>Total allocated channel time of the superframe</td></tr><tr><td>A<sub>mpnc</sub>, A<sub>mdev</sub></td><td>Total allocated channel time by hop-1 MPNCs and MDEVs, respectively</td></tr><tr><td>S</td><td>Number of superframes</td></tr><tr><td>S<sub>z</sub>, size<sub>max</sub>, size<sub>min</sub></td><td>Current, maximum and minimum sizes of superframe (µs)</td></tr><tr><td>r<sub>ij</sub>, r<sub>ik</sub></td><td>Requested channel time by a device at hops 1 and 2, respectively</td></tr><tr><td>r<sub>qj</sub>, r<sub>qik</sub></td><td>Size of channel time size to be granted to a device if available at hops 1 and 2, respectively</td></tr><tr><td>g<sub>j</sub></td><td>Granted channel time to device according to different algorithms</td></tr><tr><td>N, Q</td><td>Number of devices at hops 1 and 2, respectively</td></tr><tr><td>MPNC_T<sub>l</sub>, MDEV_T<sub>l</sub></td><td>MPNC and MDEV CTAP utilization threshold, respectively</td></tr><tr><td>N<sub>reqj</sub></td><td>Number of rejected requests in a superframe j</td></tr><tr><td>TU</td><td>Duration of a time unit (µs)</td></tr><tr><td>min_TU<sub>i</sub>, des_TU<sub>i</sub></td><td>Minimum and desired number of TUs requested by a device i</td></tr><tr><td>a, b</td><td>Ratio of min_TU and des_TU, respectively, with respect to request</td></tr><tr><td>sat<sub>fr</sub>, sat<sub>fav</sub></td><td>Calculated satisfaction factor for a device i and average satisfaction for n devices</td></tr><tr><td>f(x)</td><td>Jain's Fairness index</td></tr></tbody></table>

After that, the algorithm proceeds to the next superframe by returning back to point (D) identified in Figure 10.

## 6.2 Hop-2 service differentiation-based resource allocation algorithm

The most relevant work for resource allocation for hop-1 WPANs mesh is given in [12] as previously mentioned. In addition to the already identified drawbacks, the work in [12] does not present a mechanism for distributing the MPNCs' resources among their piconets' member MDEVs. In this scheme, a hop-2 centralized service differentiation-based resource allocation algorithm (SDRA) in IEEE 802.15.5 is proposed using the approaches that are applied by the hop-1 algorithms. Whatever the applied hop-1 algorithm (CTRA or STRA) is, the hop-2 algorithm (SDRA) does not change. This algorithm is proposed for fairly sharing the hop-1 MPNC resources among its hop-2 RT and NRT MDEVs. Additionally, this algorithm prioritizes RT over NRT MDEVs and grants them larger CTA allocations. SDRA, which is started at the point number (A) in Figure 15, can be divided into the same stages

described for the hop-1 algorithms as illustrated in Figure 16 but with the following differences:

1. In SDRA, all the stages described for the hop-1 algorithms are performed by the hop-1 MPNC instead of the ref-MPNC.

2. At the initialization stage, initial higher priority is given to the RT MDEVs over the NRT MDEVs by assigning the former higher *Flag* metrics than the latter.

3. Different rules are applied at the 'channel time calculations' stage where a MPNC *i* has to distribute the channel time among its MDEVs according to their requested resources with service differentiation. The MPNC checks if the CTRq of a device *k* is for RT or NRT MDEV. Accordingly, it then sets the size of resources to be granted for an RT CTRq (*rq*<sub>*ik*</sub>) to des_TU<sub>*ik*</sub>, and to the average of min_TU<sub>*ik*</sub> and des_TU<sub>*ik*</sub> for an NRT CTRq.

4. At the admission control stage, the sum of the total allocated resources is compared with the time granted to a MPNC *i* (*g*<sub>impnc</sub>) instead of the maximum superframe size.

5. After computing the average satisfaction factor and fairness for the hop-2 RT and NRT MDEVs at the 'average satisfaction and fairness computation' stage, the algorithm returns back to the applied hop-1 algorithm at point (B) identified in Figure 15. It is necessary to highlight the point that the QoS requirements (for example delay) for the RT CTRqs are included in the demanded des_TU, thus in the calculated RT satisfaction factor.

In the proposed scenarios, when applying the CTRA as the hop-1 algorithm with SDRA at hop-2, the two-hop mechanism is referred to as CTAP utilization threshold-service differentiation-based mechanism (CTSD). Similarly, when applying the STRA as the hop-1 algorithm with SDRA at hop-2, the two-hop mechanism is referred to as superframe utilization threshold-service differentiation-based mechanism (STSD).

## 7. Simulations and results

The proposed algorithms aim to identify the number of TUs to be allocated to each device as described above. To study the performance of these algorithms and without loss of generality, a two-hop meshed scenario with a ref-MPNC having 20 MDEVs and 10 MPNCs as hop-1 members is considered. Then each MPNC embeds 2 RT and 3 NRT MDEVs as its piconet members as illustrated in Figure 17. Therefore, we have a total of 30 devices at hop-1 and 50 devices at hop-2 distributed among 10 hop-2 piconets. This can be considered as a large number of
<figure><img src="image_116.png" /><figcaption>Figure 17 Two-hop IEEE 802.15.5 simulated scenario.</figcaption></figure>

devices in a two-hop WPAN whose piconets do not exceed a 10-m coverage range.

The requests sent by the hop-2 MDEVs to their MPNCs are considered to follow an exponential distribution with mean equals to (μ2) microseconds. The (μ2) refers to the mean of the individual requests sent by the hop-2 MDEVs to their hop-1 MPNCs. Then, the aggregate of these requests (Σμ2) is sent by the hop-1 MPNCs to the ref-MPNC (Figure 17). Additionally, the hop-1 MDEVs send individual requests to the ref-MPNC, which follow an exponential distribution with mean equals to (μ1) μs. One request per each device is sent during a CAP. Several MATLAB simulations were run by using the parameters' values that are summarized in Table 2, while taking different values of the means (μ1) and (μ2) as specified in the sequel. The satisfaction factor, the average requests' rejection rate, the average superframe utilization and the fairness index variations are studied.

Figure 18 shows a comparison of the superframe utilization for different loads (μ1) when using the dynamic superframe size proposal or fixing the superframe size to its maximum value. It is shown that in case of

the proposed mechanism, the superframe is efficiently utilized (100%) since its size increases regarding the network load. However, in case of the fixed superframe size, where the maximum size is always used, the superframe is inefficiently utilized in cases of low- and medium-loaded networks. This consequently imposes more delay between two CTAs for a certain device in two subsequent superframes especially for real-time application devices.

<table><caption>Table 2 Simulation parameters</caption><thead><tr><td>Parameter</td><td>Value</td></tr></thead><tbody><tr><td>TU duration</td><td>1,000 μs</td></tr><tr><td>min_TU</td><td>0.4r</td></tr><tr><td>des_TU</td><td>0.9r</td></tr><tr><td>Number of MPNCs at hop 1</td><td>10</td></tr><tr><td>Number of MDEVs at hop 1</td><td>20</td></tr><tr><td>Number of RT MDEVs at hop 2 per 1 MPNC</td><td>2</td></tr><tr><td>Number of NRT MDEVs at hop 2 per 1 MPNC</td><td>3</td></tr><tr><td>Φ, β1, β2</td><td>0.6, 0.7, 0.7</td></tr><tr><td>Number of superframes S</td><td>10<sup>5</sup></td></tr></tbody></table>
<figure><img src="image_117.png" /><figcaption>Figure 18 Comparison of average superframe utilization between dynamic and fixed superframe size approaches for different μ1.</figcaption></figure>

Figure 19 and Figure 20 show the average satisfaction factor of MPNCs/MDEVs and RT/NRT MDEVs, respectively, when applying each of the hop-1 algorithms (CTRA and STRA) in combination with SDRA at hop-2, thus leading to the already defined CTSD and STSD approaches. Therefore, the results presented in the sequel show the performance of the whole two-hop simulated scenario for each of the hop-1 and hop-2. The simulation time is equal to $10^5$ superframe durations, and constant values of μ1 and μ2 for both hops are considered. It is shown that the MPNCs satisfaction (Figure 19) and

the RT MDEVs satisfaction (Figure 20) are very high, and reach 0.9 when applying STSD. This refers to the maximum satisfaction since the des_TU is set to (0.9r). Consequently, if the des_TU has been set to r, the satisfaction would have reached 1.

When applying STSD, the CTAP is shared among the MPNCs and the MDEVs with one common threshold $T_L$. Additionally, the MPNCs are assigned higher priorities than the MDEVs, thus the MPNCs dominate the shared CTAP channel times and reserve their required resources at hop-1. Then, the remaining CTAP channel

<figure><img src="image_118.png" /><figcaption>Figure 19 Average MPNCs/MDEVs satisfaction factor at hop-1 for fixed μ1 and μ2.</figcaption></figure>
<figure><img src="image_119.png" /><figcaption>Figure 20 Average RT/NRT MDEVs satisfaction factor at hop-2 for fixed μ1 and μ2.</figcaption></figure>

times are distributed among the MDEVs according to their *Flag* metrics. This explains the much higher MPNCs satisfaction factor compared to the MDEVs satisfaction as illustrated in Figure 19. On the other hand, each of the MPNCs and MDEVs is reserved a CTAP portion when applying CTSD, thus the MPNCs do not grip the MDEVs' channel times. This explains the smaller difference between MPNCs and MDEVs satisfaction in comparison with that using STSD. However, the MPNCs CTAP portion and the MPNCs priorities are higher than those of MDEVs, thus the MPNCs satisfaction is greater than that of MDEVs.

Nevertheless, the same satisfaction factor is achieved by the RT and NRT MDEVs at hop-2 using either STSD or CTSD (see Figure 20) for fixed load. This is because the hop-2 algorithm grants the resources to the hop-2 devices in the same manner regardless of the applied hop-1 algorithm. Moreover, the hop-2 algorithm is applied only in case the hop-1 MPNC is granted its requested resources which are the sum of its hop-2 MDEVs requests; therefore, these MDEVs are granted all their requested resources. Additionally, since RT MDEVs are assigned higher priorities, their satisfaction factor is much greater than that of the NRT MDEVs. Finally, compared to the results obtained by applying CTSD, STSD provides much better results for MPNCs and MDEVs at hop-1 but the RT and NRT satisfaction at hop-2 remains the same regardless of the applied hop-1 algorithm.

In the following simulations, the impact of varying the load of both hops on the satisfaction factor, the rejection rate and the Jain's Fairness index, is studied. We take different hop-1 load values (μ1) ranging from low-, medium-, to high-loaded networks, and three values of load μ2 (200, 1,000, and 2,000 μs) that refer to low-, medium-, and high-loaded hop-2 networks, respectively.

Figure 21 and Figure 22 show the variations of the average satisfaction factor of MPNCs and MDEVs when the load at hop-1 increases. Various curves are given for both STSD and CTSD algorithms and for different loads at hop-2. It can be shown that for both algorithms, the MPNCs satisfaction is always higher than that of MDEVs. It is also shown that applying the STSD provides higher satisfaction for both MPNCs and MDEVs for different loaded hop-1 and hop-2 networks. Figure 21 also shows that the MPNCs satisfaction is maintained at 0.9 when applying STSD, whereas it decreases with the increase of the load at both hops when applying CTSD. This is because the CTAP channel times are shared among the MPNCs and MDEVs when applying STSD. Since higher priority is given to the MPNCs, then they usually get all their requested channel times. While for the MDEVs, their satisfaction decreases as the load on both hops decreases as shown in Figure 22. However, in the case of applying CTSD, the CTAP is divided into two parts, one is reserved for the MPNCs and the other for the MDEVs. So even though the MPNCs are provided with higher priority than the MDEVs, they cannot use the resources reserved for the MDEVs. Thus, as the load increases, the same behavior is shown for both MPNCs and MDEVs where the possibility of rejecting or granting smaller channel times than the requested by MPNCs or MDEVs increases. This explains the decrease in the MPNCs and MDEVs satisfaction and the increase in the rejection rate as the load increases as shown in Figure 23. However, the MPNCs satisfaction is still much higher than that of the MDEVs because the MPNCs reserved CTAP portion is larger than that of MDEVs.

Comparing the RT and NRT results at hop-2, it can be shown in Figure 24 and Figure 25 that the RT satisfaction is higher than that of the NRT. In addition, it is
<figure><img src="image_120.png" /><figcaption>Figure 21 MPNC satisfaction at hop-1 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>

noticed that the RT satisfaction remains the same regardless of the applied hop-1 algorithm and for different loads at both hops. This is because the RT requests are provided with higher priority than the NRT requests, so they get their requested channel times (this is why satisfaction is 0.9) and larger CTA sizes. It is also shown in Figure 25 that applying STSD at hop-1 gives better satisfaction for the NRT than applying the CTSD because the NRT satisfaction depends on the size of available hop-1 MPNC channel resources. Since STSD provides larger CTA allocations for the MPNCs than the CTSD, then the capacity of the hop-1 MPNCs is larger when applying the STSD, which finally translates into better results at hop-2.

In Figure 26, it is shown that the average rejected request rate is negligible at hop-2 when applying any of

the hop-1 algorithms for different loaded networks. This is because the hop-2 algorithm is implemented only if the hop-1 MPNC is granted its requested channel times. This guarantees that the hop-2 devices are approximately granted their desired channel time size. However, a minor request rejection rate is noticed at high-loaded hop-2 networks (μ2 = 2,000 μs) when applying CTSD since the latter achieves the lowest MPNC satisfaction factor (i.e., the granted resource size) for μ2 = 2,000 μs as already shown in Figure 21.

For the Jain's Fairness index shown in Figure 27 and Figure 28, it is obvious that both algorithms provide an approximate of 100% fairness for hop-2 devices for different hop-1 loaded networks and for both algorithms (Figure 28). This is because of the same reason explained in the previous paragraph which states that the hop-2

<figure><img src="image_121.png" /><figcaption>Figure 22 MDEV satisfaction at hop-1 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>
<figure><img src="image_122.png" /><figcaption>Figure 23 Average rejected requests percentage at hop-1 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>

devices are granted their desired channel time size. However, the fairness at hop-1 is very high at low-loaded hop-1 and hop-2 networks and starts to decrease as load at both hops increases (Figure 27). It is also noticed that better fairness is obtained when applying the STSD compared to applying CTSD. This is because higher MPNCs and MDEVs satisfaction rate and lower rejection rate are obtained when applying the STSD which implement the $T_L$ notion. Thus, using $T_L$ makes the system more adaptive inducing a compromise between the satisfaction and the rejection rate of the devices (as explained previously).

Concerning the hop-2 simulation results shown above, it is worthy to mention that studying only the performance of SDRA independently of the hop-1 algorithms cannot be implemented in this work. This is because the implementation of SDRA is dependent on the validity of the condition that the hop-1 MPNC is granted resources by the running hop-1 algorithm as mentioned previously.

After showing in Figure 18 that the superframe dynamicity enhances the superframe utilization and the delay, we try to show the usefulness of the use of the *Flag* metric and the utilization thresholds in this part. Therefore, a comparison of the MPNCs/MDEVs satisfaction and fairness indexes between the proposed mechanism that jointly applies the utilization thresholds and priority list and without applying this mechanism is conducted. Since it is concluded from the previous analyses that STSD (i.e., STRA at hop-1) outperforms CTSD (i.e., CTRA at hop-1), only STRA is applied in the sequel. Therefore, comparing the resultant satisfaction factor and the average Jain's Fairness of the proposed mechanism with and without STRA is directly reflecting and showing the usefulness of applying the *Flag* metric and the superframe utilization threshold which are the basis of STRA.

Figure 29 shows a comparison of the MPNCs and the MDEVs average satisfaction factor for different loads μ1

<figure><img src="image_123.png" /><figcaption>Figure 24 RTDEV average satisfaction at hop-2 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>
<figure><img src="image_124.png" /><figcaption>Figure 25 NRT MDEV average satisfaction at hop-2 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>

with or without applying STRA. It is shown that much higher satisfaction is obtained thanks to the STRA for both MDEVs and MPNCs. Moreover, the variations obtained in the case of the STRA reveal the use of the threshold $T_L$, since the STRA adjusts the size of channel time values according to $T_L$. In contrast to that, the satisfaction factor remains constant when the STRA is not carried out. To better reflect the importance of the proposed mechanism, Figure 30 shows a comparison of the system average Jain's Fairness index for different loads applying or not STRA. It is shown that the overall fairness is much higher when applying STRA and it reaches an approximate of 100% in the case of low-loaded networks. This is due to the various advantages achieved when applying STRA as it has been previously explained.

In the literature, only few works ([11] and [12]) study the resource allocation for the HR mesh WPAN as previously mentioned. While [11] presents a distributed solution for the mesh WPAN, [12] presents a centralized solution which is the most relevant work for the resource allocation in the HR mesh WPAN. Since the work in [12] studies only the hop-1 MPNCs satisfaction, then the hop-1 algorithm (STRA) is solely applied to perform this comparison. Thus, the performance of the proposed mechanism is compared with that of [12] on the level of the MPNCs satisfaction and fairness index.

For this comparison, the same simulation environment of [12] is considered. Thus, we consider scenarios of 8, 10, and 12 MPNCs with a 274,663 superframe duration as studied in [12]. Since the authors in [12] do not study

<figure><img src="image_125.png" /><figcaption>Figure 26 Average rejection rate at hop-2 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>
<figure><img src="image_126.png" /><figcaption>Figure 27 Jain's Fairness index at hop-1 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>

the satisfaction of the hop-1 MDEVs, only the hop-1
MPNCs satisfaction obtained by running STRA is stud-
ied in Figure 31. It is shown that the satisfaction factor
achieved in [12] is less than that achieved by STRA for
different numbers of MPNCs. Additionally, Figure 32

shows a comparison of the average Jain's Fairness index
for the number of MPNCs (8, 9, 10, and 11) studied in
[12]. It is also shown that the overall fairness is much
higher when applying STRA compared to that obtained
in [12].

<figure><img src="image_127.png" /><figcaption>Figure 28 Jain's Fairness index at hop-2 for different μ1 and μ2 = 200, 1,000, 2,000 μs.</figcaption></figure>
<figure><img src="image_128.png" /><figcaption>Figure 29 Comparison of average MPNC/MDEV satisfaction with and without applying $T_L$ and $P$ (STRA).</figcaption></figure>

For summarizing the obtained results, we identify herein the reasons for obtaining better results using the proposed mechanism in comparison with [12]. These reasons can be described as follows:

Firstly, in addition to the bulk reservation mode, we add the dynamic superframe size, whereas [12] considers the fixed superframe size which could be inefficiently utilized in case of low-loaded networks. Additionally, each MPNC estimates its channel requirements based on a history of previous flows in [12]. Therefore, inefficient superframe utilization can occur because of incorrect channel time estimation for a bulk reservation by each MPNC due to either overestimation or underestimation of the channel time requirement of a cluster.

Secondly, the proposed algorithm considers the channel time requirements of both hop-1 (MPNCs and MDEVs)

and hop-2 devices (MDEVs), whereas [12] does not consider the channel time requirements of neither the hop-2 MDEVs in the ref-MPNC cluster nor the hop-2 MDEVs in the hop-1 MPNCs' clusters.

Thirdly, the use of the *Flag* metric and the priority list assigns higher priority for the devices with a higher number of unserved requests to ascertain that their requests are served in the subsequent superframes. This ensures higher satisfaction and consequently higher fairness among the competing devices compared to [12].

Fourthly, the introduction of the utilization thresholds induces a tradeoff between the satisfaction factor and the rejection rate which directly affects the fairness. This plays an important role in obtaining better fairness using our proposed mechanism compared to [12].

<figure><img src="image_129.png" /><figcaption>Figure 30 Comparison of Jain's Fairness index with and without applying $T_L$ and $P$ (STRA).</figcaption></figure>
<figure><img src="image_130.png" /><figcaption>Figure 31 Comparison of average MPNC satisfaction for fixed μ1 between STRA and algorithm in [12].</figcaption></figure>

Finally, the better results achieved by STRA reflect the advantages of the various new notions that are introduced in this mechanism, namely, the utilization threshold $T_L$, the *Flag* metric, and the priority list. These advantages have already been thoroughly revealed and discussed throughout the various simulation result analyses and the algorithm descriptions.

## 8. Conclusions

In this paper, a two-hop IEEE 802.15.5 resource allocation mechanism, adopting the dynamic superframe size, was proposed. In this mechanism, two algorithms for resource allocation of two-hop IEEE 802.15.5 were defined. A CTAP utilization threshold, a superframe utilization threshold, a *Flag* metric, and a priority list were introduced.

The conducted simulations illustrated that the superframe is 100% efficiently utilized when using the proposed mechanism. Additionally, it was demonstrated that this mechanism achieves higher satisfaction and fairness by the use of the utilization thresholds and *Flag* metric. It was also illustrated that this mechanism prioritizes the MPNCs over the MDEVs at hop-1 and the RT over NRT MDEVs at hop-2 for a two-hop IEEE 802.15.5. Moreover, comparing the results obtained by the proposed mechanism with other works showed that the proposed mechanism provides better performance on the level of satisfaction factor and fairness.

Finally, the proposed mechanism is fully compliant with the IEEE 802.15.5 standard and is completely relying on the information elements and frames defined in this standard. Thus, this mechanism could be integrated

<figure><img src="image_131.png" /><figcaption>Figure 32 Comparison of Jain's Fairness index for fixed μ1 between STRA and algorithm in [12].</figcaption></figure>
in practice to improve the HR mesh WPAN performance and efficiency as illustrated by the conducted simulation results.

**Competing interests**

The authors declare that they have no competing interests.

**Author details**

¹INSA de Rennes, IETR, UMR 6164, F-35708 Rennes, France. ²CCE Department, Faculty of Engineering, IUL, 30014 Khaldeh, Lebanon. ³Faculty of Engineering, Lebanese University, Rafic Hariri Campus, Hadath, Lebanon.

Received: 4 April 2014 Accepted: 5 November 2014

Published: 23 November 2014

**References**

1. IEEE Standard 802.15.3-2003, "Part 15.3: wireless medium access control (MAC) and physical layer (PHY) specifications for high rate wireless personal area networks (WPANs), 2003, pp. 1–315

2. SB Jung, S-B Yim, TJ Lee, S-D June, HS Lee, TG Kwon, JW Cho, Multipiconet formation to increase channel utilization in IEEE 802.15.3 high-rate WPAN". Springer-Verlag Lect. Notes Comput. Sci. 3392, 1041–1049 (2006)

3. F Da Costa, "Dynamic Beacon Alignment in Simultaneously Operating Piconets (SOP) Using the Heart Beat Approach," IEEE Standard P802.15.04/135r0, 2004

4. Z Fan, "Multi-hop mesh networking for UWB-based 802.15.3 coverage extension", in *Proceedings of the 20th international Conference on Advanced Information Networking and Applications*, vol. 1, 2006, pp. 920–925

5. S Jung, H Kim, S Yim, T Lee, "Channel Time Allocation and Routing Algorithm for Multi-hop Communications in IEEE 802.15.3 High-Rate WPAN Mesh Networks", in *Proceedings of the 7th international Conference on Computational Science*, 2007, pp. 457–465

6. P Xue, P Gong, D Kim, Enhanced IEEE 802.15.3 MAC protocol for efficient support of multiple simultaneously operating piconets. IEEE Trans. Veh. Technol. 57(4), 2548–2559 (2008)

7. S Sindian, A Khalil, A Samhat, M Crussière, J-F Hélard, Resource allocation in high data rate mesh WPAN: a survey paper. Wirel. Pers. Commun. 74(2), 909–932 (2014)

8. S Khan, H Al-Raweshidy, K Sivarajah, Meshed high data rate personal area networks", IEEE Commun. Surv. Tut. 10(1), 58–69 (2008)

9. IEEE Standard 802.15.5-2009, "Part 15.5: Mesh topology capability in Wireless Personal Area Networks (WPANs), 2009, pp. 1–166

10. M Lee, R Zhang, C Zhu, TR Park, C-S Shin, Y-A Jeon, S-H Lee, S-S Choi, Y Liu, S-W Park, Meshing wireless personal area networks: introducing IEEE 802.15.5". IEEE Commun. Mag. 48(1), 54–61 (2010)

11. MS Park, B Lee, SH Rhee, Distributed multiple access control for the wireless mesh personal area networks. Trans. Inform. Syst. E91(2), 258–263 (2008)

12. S Mahmud, S Khan, HS Al-Raweshidy, A resource allocation strategy for meshed high data rate WPANs. IEEE Commun. Lett. 14(6), 524–526 (2010)

13. IEEE Standard 802.15.4-2006, "Part 15.4: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs)", 2006

14. DR Herráiz, A-J García-Sánchez, F García-Sánchez, J García-Haro, On the synchronization of IEEE 802.15.5 wireless mesh sensor networks: shortcomings and improvements". EURASIP J. Wirel. Commun. Netw. 2012(198), 5958–5995 (2012)

15. M Dianati, X Shen, S Naik, "A New Fairness Index for Radio Resource Allocation in Wireless Networks". 5th IEEE Wireless Communications and Networking Conference vol 2, 2005, pp. 712–717

16. A Kumar, J Kleinberg, "Fairness measures for resource allocation", in *IEEE Symposium on Foundation of Computer Science*, 2000, pp. 568–578

17. R Jain, D Chiu, W Hawe, A quantitative measure of fairness and discrimination for resource allocation in shared computer system. DEC Tech. Rep. 301, (1984)

doi:10.1186/1687-1499-2014-197

**Cite this article as:** Sindian et al.: *Admission control and resource allocation strategies for IEEE 802.15.5, EURASIP Journal on Wireless Communications and Networking 2014* **2014**:197.

Submit your manuscript to a SpringerOpen journal and benefit from:

► Convenient online submission

► Rigorous peer review

► Immediate publication on acceptance

► Open access: articles freely available online

► High visibility within the field

► Retaining the copyright to your article

Submit your next manuscript at ► springeropen.com
<figure><img src="image_132.png" /></figure>
Selected Article

M. Crussière, C. Douillard, C. Gallard, M. Le Bot, A. Bouttier, A. Untersee, "A unified broadcast layer for horizon 2020 delivery of multimedia services", IEEE Transaction on Broadcasting, Vol. 60, Issue 2, pp 193-207, June 2014, DOI: 10.1109/TBC.2014.2315764

Abstract

It is expected that, in the coming years, the video data traffic carried by mobile networks will increase drastically. Among the different ways of facing this “mobile data tsunami”, the cooperation of several complementary access technologies offers promising prospects. In the context of such a cooperative approach, this paper proposes the definition of a unified broadcast layer, close to the 3GPP LTE technology, and therefore liable to be easily integrated in mobile devices and infrastructure equipment. The general technical requirements for the design of such a common physical layer are detailed and a practical example based on the 3GPP LTE/E-MBMS and DVB-T2 standards is described. The verification of the proposed approach is performed through simulation results and validation tests carried out on a hardware platform.

Keywords : Access network cooperation, broadband networks, broadcast networks, common physical layer, hardware demonstrator, satellite channels, terrestrial channels, 3GPP LTE/E-MBMS.
# A Unified Broadcast Layer for Horizon 2020 Delivery of Multimedia Services

Matthieu Crussière, Member, IEEE, Catherine Douillard, Senior Member, IEEE, Christian Gallard, Marie Le Bot, Benjamin Ros, Arnaud Bouttier, and Alain Untersee

**Abstract**—It is expected that, in the coming years, the video data traffic carried by mobile networks will increase drastically. Among the different ways of facing this “mobile data tsunami,” the cooperation of several complementary access technologies offers promising prospects. In the context of such a cooperative approach, this paper proposes the definition of a unified broadcast layer, close to the 3GPP LTE technology, and therefore liable to be easily integrated in mobile devices and infrastructure equipment. The general technical requirements for the design of such a common physical layer are detailed and a practical example based on the 3GPP LTE/E-MBMS and DVB-T2 standards is described. The verification of the proposed approach is performed through simulation results and validation tests carried out on a hardware platform.

**Index Terms**—Access network cooperation, broadband networks, broadcast networks, common physical layer, DVB-T2, hardware demonstrator, satellite channels, terrestrial channels, 3GPP LTE/E-MBMS.

## I. INTRODUCTION

GLOBAL mobile data traffic will increase 13-fold between 2012 and 2017". "Two thirds of the world's mobile data traffic will be video by 2017". These words extracted from [1] and often referred to as the so-called "mobile data tsunami" describe how strong the phenomenon of data traffic growth is expected to be in the coming years. With such figures in mind, one can question how mobile operators will be able to face this challenge.

The evolution in network topologies, from current macrocells to future small cells (picocells, femtocells), will provide more capacity locally. The counterparts of such a network densification are twofold. On the one hand, interference will increase and will have to be managed in a not too complex way; technical solutions are currently being studied in the 3GPP standardization groups. On the other hand, backhauling

issues will also have to be solved: how to connect so many small cells to the core network, in a cost-efficient way, while guaranteeing the desired quality of experience for the end user?

In order to provide higher throughput services, a mobile operator can also acquire more spectrum, as data rates are closely related to the amount of available spectrum. To this end, the digital dividend in the 800 MHz band has already been allocated to mobile operators and the 700 MHz band allocation will be discussed during the World Radio-communication Conference in 2015. Consequently, one can imagine that the spectrum size allocated to mobile operators could be roughly doubled by 2020. Nevertheless, such investments in spectrum have a non-negligible cost for mobile operators. A longer term perspective, in terms of spectral resources, could be the use of millimeter waves where huge bandwidths could be available for small cells, due to the short coverage capability of such high frequencies. For instance, the 60 GHz band has been identified as a promising band: a huge amount of unlicensed spectrum is available and acceptable attenuation levels are observed for these frequencies.

Another alternative is to rely on the cooperation of different access technologies. One current example of such cooperation involves offloading part of the mobile traffic over WiFi access networks: in indoor environments such as homes, offices, or airports, the mobile traffic can be diverted to private or public WiFi access points when available. In order to improve the cooperation, enhancements are about to be carried out in 3GPP LTE (Long Term Evolution), release 12, and WiFi standard: (known as High Efficiency WiFi [2]).

A well-known technology which can be also very helpful in delivering video services is broadcasting. Indeed, broadcasting should not be restricted to live TV delivery. It can also beneficially provide other kinds of multimedia services in the coverage area of the network and can then be considered as an efficient “point-to-area” service distribution technology. In particular, taking advantage of the huge amount of memory available in devices, broadcasting is well suited for predictive datacasting services. Different types of contents, such as e-magazines, “top-10” music video-clips, software and application updates, etc., can be pushed to device cache prior to their consumption by the end user, who can then access the contents, even without any connection, with a perfect quality of service. Besides, such a service based on broadcast access technology and known as NOTTV [3] is already available in Japan since April 2012.

Manuscript received July 15, 2013; revised March 18, 2014; accepted April 1, 2014. Date of publication April 29, 2014; date of current version June 4, 2014. This work was supported by the French National Research Agency, Project Mobile MultiMedia (M³, ANR-2010-VERS-0010).

M. Crussière is with the INSA-IETR Laboratory, Rennes, France.

C. Douillard is with the Telecom Bretagne/Lab-STICC Laboratory, Brest, France.

C. Gallard and M. Le Bot are with Orange Labs, Rennes, France.

A. Bouttier is with Mitsubishi Electric R&D Centre Europe, Rennes, France.

A. Untersee is with TeamCast, Rennes, France.

B. Ros is with CNES, Toulouse, France.

Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TBC.2014.2315764
In the framework of the DVB-NGH (Digital Video Broadcasting-Next Generation Handheld) standardization process, it was proposed in February 2010 to re-use 3GPP E-MBMS (Evolved Multimedia Broadcast Multicast Services), i.e., the 4G broadcast mode, as a basis for NGH specifications. The purpose of this proposal was to avoid market fragmentation between standards, while making it easier the integration of broadcast chipsets in mobile devices (e.g., smartphones and tablets).

However, 3GPP E-MBMS as currently specified in Release 9 [4] is not able to meet all the usual broadcasters' requirements. For instance, terrestrial broadcast networks can usually cover areas within a radius of several tens of kilometres. In contrast, E-MBMS signals transmitted in a shared-carrier mode with LTE unicast data can only reach users at a maximum distance of 5 km from the base station, if no specific processing is performed on the receiver side. Moreover, as latency is not an issue for broadcasting services, deep time interleaving can be applied in such systems, which leads to improved performance in terms of quality of service, particularly in mobile conditions. For the development of the LTE standard, one of the initial requirements was conversely the reduction of latency compared to 3G; so no specific time interleaver has been designed for the LTE broadcast mode.

In November 2010, the DVB Forum decided to knock at 3GPP's door in order to propose a common definition for a unified broadcast standard. After an initial phase of mutual presentations of DVB and 3GPP broadcast state-of-the-art standards, a small group of 3GPP companies decided to propose, in May 2011, the creation of a study item dealing with converged mobile broadcast support for LTE. Unfortunately, due to the lack of support from mobile key players (due to unclear business model, uncertain potential profit for operators, etc.), the study item creation proposal was rejected in the end.

The various past attempts to propose pure broadcast solutions to the mobile ecosystem turned out to be vain. DVB-H, the first generation of DVB broadcast standard to handhelds standardized in 2004 [5], which was promoted by Nokia, has met a rather mixed success. DVB-H chipsets have been integrated into Nokia handsets, some services over DVB-H networks have been launched, e.g., in Finland, Austria, and Italy, but most of these services have now been switched off. On the other side of the Atlantic, Qualcomm promoted a proprietary solution known as MediaFLO [6] and got this technology standardized by the European Telecommunications Standards Institute (ETSI) in 2009 [7]. FLO TV services have been launched in the U.S. starting from 2007. Some devices able to receive such services were introduced by LG and Samsung in 2006. Nevertheless, in 2010 Qualcomm decided not to support the MediaFLO technology any longer and sold the spectrum they owned in the 700MHz band to AT&T. A second trial on the DVB side with DVB-SH (Satellite Services to Handhelds) [8], mainly promoted by Alcatel Lucent, did not meet the expected commercial success either.

A few lessons can then be learnt from these experiences:

1) A mobile broadcast standard would more likely become a market success if supported by a worldwide ecosystem, e.g., by 3GPP actors. Without having mobile vendors in the loop from day one, convincing them to embed a

non-3GPP broadcast chipset in their devices afterwards seems to be difficult.

2) Deploying and managing a broadcast network in action to a mobile network also seems hard to achieve. This is mainly due to cost issues since significant investments have to be made to deploy this second network.

3) Beyond historical broadcast services (live TV and radio), additional multimedia services must be considered in order to assess the actual interest in deploying a broadcast solution.

The original approach described in this paper consists in defining a universal broadcast layer, close to the LTE technology, and therefore liable to be easily integrated in mobile devices and infrastructure equipment, which is an essential enabling factor for a worldwide adoption.

This paper is organized as follows. Section II analyses general requirements for a common physical layer (CPHY and compares the main features of the DVB-T2/NGH standard with the broadcast mode of 3GPP LTE. A set of CPHY specifications based on LTE/E-MBMS is then proposed. Section III. Section IV describes a hardware demonstrator implementing the proposed CPHY and presents the differential validation tests carried out so far through simulations and laboratory tests. Section V concludes the paper.

## II. FOUNDATIONS FOR A COMMON PHYSICAL LAYER

In this section, we introduce the concept of CPHY specifications for a convergent broadband/broadcast network. The technical challenges to obtain such a unified system are detailed from a general point of view according to the specific requirements of point-to-area transmissions. Then, a comparison between the broadcast systems coming from DVB and 3GPP standardization bodies is carried out to better understand the key features that should govern the technical choices of a future common broadcast physical layer.

### A. Common Physical Layer Challenges

The CPHY specifications have to be devised to act as an enabler for the deployment of broadcasting transmission modes over various network infrastructures, whether it be conventional terrestrial broadcast, broadband networks or even satellite ones. Such a unified system should allow a common baseband chip embedded in a handheld receiver to demodulate and decode any service delivered through a broadcast transmission mode whatever the bearer network responds to of the transmission. In other words, baseband operations broadcast reception should become network agnostic. In perspective, many basic features have to be guaranteed to make the CPHY well suited for point-to-area transmissions whatever the network environment, i.e., whatever the point (the trans station) and whatever the area (the radio links).

At first, the CPHY waveform should be sufficiently scalar to be fully compatible with the radio deployment plan of the targeted networks in terms of frequency bands, coverage areas and frequency planning strategies. For instance,
the CPHY has to be able to address at once typical frequency bandwidths for mobile communications and Digital TV (DTV). Moreover, as the cell range of cellular networks is far different from the coverage areas targeted by terrestrial or even satellite DTV networks, the CPHY waveform has to be shaped in order to ensure the coverage of cells whose size ranges from a few hundred meters to several tens of kilometers. This is of particular importance when considering Single Frequency Network (SFN) planning for which the coverage distance is mainly driven by the waveform immunity against inter-cellular interference.

Secondly, CPHY should take advantage of the full downlink feature of broadcast transmissions by defining long frame durations. In a pure broadcast mode, transmission frames can indeed be designed without any delay or latency considerations due to the uplink channel constraints. As far as modulation and coding schemes are concerned, using long frames allows the constellations and coding rates to be optimized for large codeword lengths, making the system perform closer to the Shannon limit. Over time-varying channels typical of mobile reception scenarios, interleaving schemes should also be applied over a large time spread to take advantage of time diversity. The increase of the interleaving depth and codeword length should actually essentially be limited by the maximum memory size that can be embedded in nomadic terminals.

Finally, the CPHY specifications should be based on a framing structure adapted to point-to-area transmissions. Such transmissions ensure a universal coverage, i.e., they are not user specific and they deliver a common content to all the terminals within the coverage area whatever their individual situations. This implies that a given user should be able to access the broadcast contents at every time without engaging complex high-level process such as session control protocols. Besides, the user terminal should be able to easily and rapidly extract the multimedia service of interest among the whole delivered content. This involves designing frames with their own embedded signaling messages, giving all the necessary information about the frame structure and service content. Additionally, the frame structure should allow fast synchronization and sounding procedures.

## B. Comparison of the DVB-T2/NGH and 3GPP LTE Standards

This Section analyses the state-of-the-art terrestrial DVB and 3GPP cellular broadcasting technologies. In Europe, the DVB standardization body proposes specifications for signal transmission over terrestrial, satellite, and cable broadcast networks. More specifically, the DVB-T2 [9] and DVB-NGH [10] systems define a family of frames able to operate broadcasting in various network topologies. On the other hand, the 3GPP working groups in charge of LTE have introduced the E-MBMS broadcast mode for cellular network operation [4]. These two systems can thus be viewed as reference systems for this study and the targeted CPHY has been designed taking their specifications as bases.

The first stage of comparison deals with the framing approach. Figs. 1 and 2 give the overall frame structure

in both systems. DVB-T2 is based on a super-frame time segmentation possibly containing different families of frames whose duration can reach 250 ms. It can be noticed that DVB-T2 framing provides the concept of Future Extensible Frames (FEF) for the transmission of non-DVB-T2 frames. In LTE, Fig. 2 gives the framing structure defined for downlink the Frequency Division Duplex (FDD) mode. In this mode, LTE radio interface supports radioframes of 10 ms subdivided into ten sub-frames of 1ms each. This sub-frame duration is the reference value for the LTE system and is referred to as TTI. Transmit Interval (TTI). As shown in the figure, a subset of downlink sub-frames can be configured to deliver E-MBMS broadcast services/signals and E-MBMS services are multiplexed with classical unicast services within the radioframe. Both systems allow several services to be multiplexed with a frame.

This feature is provided by Physical Layer Pipes (PLP): DVB-T2, each PLP being associated to a given set of physical layer parameters (modulation order, coding rate, interleaver depth) corresponding to a particular quality of service. In LTE service multiplexing is inherent to the broadband nature of the systems. Each LTE service is first allocated to a set of elementary containers called Resource Blocks (RB) which mapped onto the subframes. Last but not least, the two systems are based on very different signaling approaches.

On the DVB side, multiplexes of linearly programmed TV services are self-documented (the Electronic Program Guide gives information on multiplexed services and programmed contents), requiring the receivers to discover the services. On that basis, DVB-T2 frames are provided with dedicated preambles, namely P1 and P2 (see Fig. 1), to all

<figure><img src="image_133.png" /><figcaption>Fig. 1. Schematic view of the DVB-T2 frame structure highlighting P1 P2 preambles, multiple physical layer pipes (PLP) multiplexing, and full extension frame (FEF) insertion.</figcaption></figure>

<figure><img src="image_134.png" /><figcaption>Fig. 2. Schematic view of the LTE radioframe structure (in FDD mode) highlighting the resource block allocation units and showing the unicast E-MBMS services multiplexing approach.</figcaption></figure>
<table><caption>TABLE I
COMPARISON OF DVB-T2 LITE AND 3GPP E-MBMS PHYSICAL LAYERS</caption><thead><tr><th></th><th>3GPP E-MBMS</th><th>DVB-T2 Lite</th></tr></thead><tbody><tr><td><strong>Frequencies</strong></td><td></td><td></td></tr><tr><td>Main Frequency bands<br>in Europe [MHz]</td><td>[791-862]<br>[2,500-2,690]</td><td>[174-446]<br>[470-790]</td></tr><tr><td>Main Channel<br>Bandwidths [MHz]</td><td>5; 10; 15; 20</td><td>5; 6; 7; 8</td></tr><tr><td><strong>OFDM parameters</strong></td><td>Bandwidth 5 MHz</td><td>Bandwidth 8 MHz</td></tr><tr><td>FFT size</td><td>From 128 to 2k</td><td>From 2k to 16k</td></tr><tr><td>Δf [kHz]</td><td>15</td><td>From 4.464 to 0.558</td></tr><tr><td>Symbol duration [μs]</td><td>67</td><td>From 224 to 1792</td></tr><tr><td>Guard Interval [μs]</td><td>16.67</td><td>From 14 to 448</td></tr><tr><td>Cell radius [km]</td><td>5</td><td>From 4 to 133</td></tr><tr><td><strong>Channel coding</strong></td><td></td><td></td></tr><tr><td>Code family</td><td>Binary turbo-code</td><td>LDPC code</td></tr><tr><td>Codeword size [bits]</td><td>Variable K={40... 6144}</td><td>Fixed N = 16200</td></tr><tr><td>Code rate</td><td>From 0.1172 to 0.9258</td><td>From 1/3 to 11/15</td></tr><tr><td>Interleav. Depth [ms]</td><td>1 ms max (TTI length)</td><td>250 ms max</td></tr><tr><td><strong>Channel Sounding</strong></td><td></td><td></td></tr><tr><td>Scattered pilots</td><td>Fixed pattern (see [4])</td><td>8 Pilot patterns</td></tr></tbody></table>

the terminal to be fast synchronized and to easily extract the desired service from the frame payload. On the LTE side, broadband services are intermittently using the transmission resources and then are sustained by session opening/closing procedures implemented through a control channel using the bidirectional wireless connection. Hence, synchronization and signaling information is shared between unicast and broadcast services and is distributed across the whole radioframe.

To go further in the system comparison, Table I gives a summary of the main physical layer characteristics of these two broadcast standards. On the DVB side, DVB-T2 Lite parameters are taken as a reference. They constitute a subset of the DVB-T2 specifications that is well suited for mobile reception. As far as 3GPP is concerned, the LTE E-MBMS downlink parameters have been reported in the table, based on the FDD mode of the LTE standard.

These physical layers have a number of commonalities. Firstly, they use an OFDM modulating waveform, due to the fact that they have both been designed to cope with time and frequency selective channels. Various modulation and coding schemes are available in each standard as well, in order to provide flexible system performance. Such flexibility is exploited at the user level on the LTE side whereas it is viewed on the DVB side as the ability for the operator to select sets of parameters according to the targeted network deployment. Besides, DVB and LTE systems carry out a similar approach for channel sounding, using dedicated pilot symbols spread over the OFDM spectrum according to specific patterns. As a last common feature, both systems define SFN modes. For DVB systems, this is actually a basic feature used for the conventional deployment of a terrestrial network.

Apart from these similarities, both systems differ on various key aspects as highlighted in Table I. First of all, both systems operate in different frequency bands. Terrestrial DVB

systems were assigned the VHF and UHF bands whereas LTE systems address bandwidths in the frequency regions around 2.6 GHz. Note however, that the S band between 2 and 4 GHz is envisaged for the future DVB-NGH satellite link. In action, some countries have recently taken the opportunity to reallocate the upper band of the UHF spectrum to LTE systems, namely between 790 and 862 MHz. Concerning bandwidths, typical values for DTV broadcast are 6, 7 and 8 MHz for the terrestrial link and 5 MHz the satellite link. LTE systems are mainly based on bandwidths defined as multiples of 5 MHz. So, it turns out that the two systems are not natively compatible in terms of spectrum usage, which is a first degree of harmonization to do with (see Section III).

As a second major difference, the analysis of the OFDM parameters shows that they have not been chosen following the same strategy. Concerning the LTE standard, the OFDM wave form is governed by a fixed inter-carrier spacing of 15 kHz, the desired OFDM spectrum width being actually obtained through the activation of an adequate number of subcarriers. The FFT stage. Such a large inter-carrier spacing value allows strong Doppler effects to be handled. LTE has in fact been designed to support high mobility scenarios in frequency bands that can be located at 2.6 GHz. In addition, larger values of the inter-carrier spacing are more convenient to limit uplink synchronization constraints. As a consequence of this choice, the time domain OFDM symbol length remains constant, namely 67 µs, whatever the effective signal bandwidth. Hence, considering a maximum ratio of 1/4, the guard interval duration is restricted to 16.67 µs. On the other hand, the DVB-OFDM parameters result from a trade-off between Doppler effect mitigation and guard interval increase. Actually, DVB offers several FFT sizes for each of the possible bandwidths. This leads to variable inter-carrier spacing values and thus to variable degree of resistance against Doppler effect. Besides, this gives rise to various symbol and guard interval durations. From Table I, we can note for instance that the inter-carrier spacing for an 8 MHz bandwidth ranges from 0.558 kHz to 4.464 kHz, yielding guard interval values between 14 µs and 448 µs. The idea behind the guard interval adjustment is to adapt the OFDM signal to various coverage ranges if the system is operated in SFN mode. In such a network configuration the guard interval is chosen according to the distance between two neighboring transmit towers so that it is able to absorb the echoes of the signals coming from each transmission link. In other words, the guard interval duration can directly translated into maximum coverage distance according to the propagation speed, as reported in Table I. As an example, maximum cell radius of 133 km is given for the DVB system considering an 8 MHz bandwidth, which is far larger than the 5 km obtained for the LTE standard. However, LTE specifies an SFN mode allowing the inter-carrier spacing to be reduced to half of its nominal value, i.e., 7.5 kHz, and lead to cells with an increased 10 km radius. This value still remains 13 times smaller than the maximum radius in terrestrial DVB. From this comparison, we can conclude that LTE systems mainly designed for Doppler effect mitigation, whereas DVB systems are tailored to fit large coverage areas. The search
adequate OFDM parameters for a common broadcast PHY under coverage and mobility constraints is investigated in Section III.

The last significant contrast between DVB and LTE specifications can be analyzed from a Forward Error Correction (FEC) coding and interleaving point of view. At a first level, the two systems exploit different families of error correcting codes: DVB is based on LDPC codes while LTE makes use of turbo codes. However, when properly designed, both code families display comparable performance for similar implementation complexity. Consequently, the FEC code family does not represent a key criterion in our analysis. We rather focus on the FEC block size and time interleaving duration values. On the DVB side, the coded block size is fixed and is equal to 16,200 bits; the information block size thus depends on the coding rate. Then, bit interleaving is carried out at the FEC block level and time interleaving is applied to the constellation symbols within the so-called interleaving frames, which can contain a variable number of FEC blocks. As a result, the overall interleaving depth can reach the maximum frame duration, i.e., 250 ms (see Table I and Fig. 1). It can even be extended to larger values with the inter-frame interleaving option which allows each interleaving frame to be mapped across several T2 frames. In this case, the improvement of the interleaving depth comes at the price of a bit-rate reduction and latency increase and has thus to be decided accordingly.

For the satellite case, which is the most sensitive to time selectivity, an interleaver with a time spread of several seconds could be envisaged [14]. From these considerations, it appears that DVB systems have been designed to benefit from high time/frequency diversity in a full downlink transmission mode. On the 3GPP side, the followed strategy is different. Table I indicates that various information block sizes (before coding) ranging from 40 to 6,144 bits are available. Compared to the DVB specifications, the LTE system thus offers more flexibility with respect to the block size, which can be explained by the need to adapt each link to users' requirements in cellular networks. Consequently, interleaving essentially relies on the interleavers used by the turbo code and on the so-called rate-matching functionalities, thus limiting the interleaving depth to a single code block. Each code block is then allocated to the resource blocks defined as the atomic allocation unit in LTE systems. In E-MBMS with SFN operation, these resource blocks are mapped without any additional interleaving process onto the subframes introduced in Fig. 2. Eventually, the maximum time spread in LTE E-MBMS is limited to the 1ms TTI value, which is far lower than what is carried out on the DVB side. The reason for such a difference comes from the fact that the LTE systems have to manage bidirectional communications governed by delay constraints. Nevertheless, LTE FEC functionalities include retransmission procedures that provide the base station with the possibility to transmit additional redundancy in case of erroneous packet reception at the terminal side, hereby implicitly exploiting channel time diversity. In a pure downlink broadcast transmission, such an approach can obviously not be carried out. Hence, in the perspective of a convergent

E-MBMS/DVB system, interleaving is a fundamental issue to be addressed.

### III. CPHY SPECIFICATIONS PROPOSAL

Mobile broadcasting can be viewed as standing at the crossroads of the DVB and 3GPP worlds. Aiming at defining a unified physical layer for mobile broadcasting scenarios that is highly desirable to take advantage of both system designs, our approach involves starting from the LTE/E-MBMS specifications and making them evolve to integrate broadcast requirements in the perspective of a deployment of the CPHY over traditional broadcasting infrastructures, terrestrial and satellite.

Regarding the comparison analysis made in Section II, the E-MBMS specifications are modified according to the following steps:

1. Define a frame structure compatible with the DVB-T frame framing approach;

2. Modify the OFDM parameters in order to address typical broadcasters' bandwidths;

3. Increase the OFDM guard interval duration for SSB operation at the scale of typical broadcasters' cells;

4. Increase time diversity exploitation with time interleaving;

5. Design appropriate pilot patterns according to the previous modifications.

#### A. Framing

As detailed in Section II-B, E-MBMS services are multiplexed with unicast services within the LTE radioframes. Related synchronization and signaling procedures rely on information available in the unicast part of the frame. Since CPHY signals should be delivered through downlink-only transmissions, it should be rather viewed as a dedicated carrier moving from the 3GPP world. The CPHY system has to embed own synchronization and signaling information. Even if the paper is not intended to give complete solutions about signing and synchronization mechanisms, some basic concepts discussed hereafter. A simple solution is for instance to follow the preamble concept offered by the DVB-T2 specifications previously described and depicted in Fig. 1. A dedicated symbol can be defined to enable quick synchronization and to carry some preliminary signaling. To go further, the CPHY can be considered as a particular FEF and can be multiplexed in time with already existing DVB-T2 frames, the dedicated preamble P1 guaranteeing its proper identification. This is sketched in Fig. 3. To keep the CPHY system as close as possible to the E-MBMS specifications, the new frame can benefit from the resource allocation strategy defined 3GPP. In practice, we propose to build CHPY frames from radioframes of 10 ms made of subframes of fixed duration and relying on the elementary RB containers used by the 3GPP LTE systems. This approach gives a solution to the deployment of CPHY frames either in a TDM fashion with DVB-T2 signals or directly embedded in a LTE radioframe. The practical implementation of a time multiplex with native sampling frequencies of each system (DVB and 3GPP) is discussed in Section IV-B.
<figure><img src="image_135.png" /><figcaption>Fig. 3. CPHY framing structure proposal as a particular DVB-T2 FEF. The resource allocation principles of 3GPP LTE, based on resource block units and sub-frame segmentation, are maintained.</figcaption></figure>

## B. Bandwidth Harmonization

As previously mentioned in Section II-B, three native bandwidths of the DVB-T2 standard, i.e., 6 MHz, 7 MHz and 8 MHz, are not addressed by current E-MBMS specifications. As a universal system, CPHY should be compatible with these bandwidth values. Reminding that 3GPP LTE is somehow bandwidth agnostic, it is actually fairly simple to adapt E-MBMS signals to these three new bandwidth cases. This is achieved through the activation of the adequate number of subcarriers for a fixed inter-carrier spacing and a given FFT size. Following 3GPP terminology, this translates into the allocation of a variable number of RBs per OFDM symbol, one RB corresponding to 180 kHz. As an example, one can easily achieve the 6, 7 or 8 MHz bandwidths starting from the existing 10 MHz E-MBMS case by progressively reducing the number of modulated subcarriers. Following this idea, one can calculate the number of subcarriers, or alternatively the number of RBs, being allocated according to the system bandwidth. Table II reports the parameters obtained under the 15 kHz and 7.5 kHz legacy E-MBMS subcarrier spacing and considering 1024- and 2048-point FFTs respectively. Note that a similar approach can be followed starting from a 5 MHz bandwidth with a 512-point FFT and then increasing the number of RBs. The choice between these two possibilities can actually be related to implementation strategies.

It is worth noting that the above proposal keeps approximately the same bandwidth occupancy as in the legacy E-MBMS standard, in such a way that the ratio of effective bandwidth over the total bandwidth is around 90 %. Hence, this proposal retains the spectrum usage policy in use on the 3GPP side and could be considered as a "3GPP compatible" allocation mode. On the DVB side, an extended bandwidth planning is traditionally adopted to increase the system capacity. With this goal in mind, a second bandwidth allocation mode called "DVB compatible" can be considered with improved bandwidth occupancy, yet respecting DVB spectrum usage. The figures for these two modes are reported in Table III, highlighting an improvement of around 5 % of the spectral occupancy when the extended mode is activated.

<table><caption>TABLE II
CPHY PARAMETERS FOR UHF BANDWIDTHS COMPATIBILITY, START FROM THE LTE-NATIVE 10 MHz BANDWIDTH</caption><thead><tr><th>Radio Bandwidth</th><th>Inter-carrier spacing</th><th>FFT size</th><th>Number of RBs</th><th>Activated subcarriers</th><th>Effective Bandwidth</th></tr></thead><tbody><tr><td rowspan="2">10 MHz</td><td>15 kHz</td><td>1024</td><td rowspan="2">50</td><td>600</td><td rowspan="2">9 MHz</td></tr><tr><td>7.5 kHz</td><td>2048</td><td>1200</td></tr><tr><td rowspan="2">8 MHz</td><td>15 kHz</td><td>1024</td><td rowspan="2">40</td><td>480</td><td rowspan="2">7.2 MHz</td></tr><tr><td>7.5 kHz</td><td>2048</td><td>960</td></tr><tr><td rowspan="2">7 MHz</td><td>15 kHz</td><td>1024</td><td rowspan="2">35</td><td>420</td><td rowspan="2">6.3 MHz</td></tr><tr><td>7.5 kHz</td><td>2048</td><td>840</td></tr><tr><td rowspan="2">6 MHz</td><td>15 kHz</td><td>1024</td><td rowspan="2">30</td><td>360</td><td rowspan="2">5.4 MHz</td></tr><tr><td>7.5 kHz</td><td>2048</td><td>720</td></tr></tbody></table>

<table><caption>TABLE III
CPHY PARAMETERS FOR UHF BANDWIDTHS, CONSIDERING NORM. MODE FOR LTE COMPATIBILITY AND EXTENDED MODE FOR DVB COMPATIBILITY. INTERCARRIER SPACING IS 7.5 kHz, FFT SIZE IS 2048.</caption><thead><tr><th>Mode</th><th>Radio Bandwidth</th><th>Number of RBs</th><th>Effective Bandwidth</th><th>Bandwidth occupancy</th></tr></thead><tbody><tr><td rowspan="3">LTE compatible</td><td>8 MHz</td><td>40</td><td>7.2 MHz</td><td>90 %</td></tr><tr><td>7 MHz</td><td>35</td><td>6.3 MHz</td><td>90 %</td></tr><tr><td>6 MHz</td><td>30</td><td>5.4 MHz</td><td>90 %</td></tr><tr><td rowspan="3">DVB compatible</td><td>8 MHz</td><td>42</td><td>7.56 MHz</td><td>94.5 %</td></tr><tr><td>7 MHz</td><td>37</td><td>6.66 MHz</td><td>95.14 %</td></tr><tr><td>6 MHz</td><td>32</td><td>5.76 MHz</td><td>96 %</td></tr></tbody></table>

## C. Coverage Area Extension

From the analysis of Section II, we pointed out that 3GPP LTE system suffers from a very short coverage area for SFN terrestrial operation compared to DVB-T2/NGH systems. The increase of the coverage is thus a crucial issue to be addressed for the design of the CPHY based on E-MBMS standard in the perspective of a deployment in SFN network. Since, in that context, the coverage size directly proportional to the guard interval duration, set to the of the OFDM symbol size in the current E-MBMS standard, possible solution involves increasing the OFDM symbol size. This is obtained by reducing the subcarrier spacing, however leading to lower immunity to Doppler effect. This has then to be analyzed as a trade-off between Doppler echo resistance. Interestingly, with a CPHY deployment in VHF/UHF bands, the Doppler spread values are expected to be much lower than those encountered in classical LTE bands, thus offering more flexibility for system optimization. Taking the practical assumption widely used in wireless communications stating that the admissible Doppler value may not exceed 10 % of the subcarrier spacing, it is possible to compute Doppler resistance for various guard interval values.

Table IV summarizes the maximum Doppler frequency shifts and echo resistances obtained in the UHF band, at 600 MHz, when dividing the current E-MBMS inter-carrier spacing values, namely 15 kHz (normal mode) and 7.5 kHz (SFN mode), by factors of 2, 3 and 6, respectively. From the results, we first note that the maximum Doppler shifts reported by the original LTE systems when operated at a central frequency of 600 MHz are 1500 Hz and 750 Hz. These values correspond to velocities of 2700 km/h and 1350 km/h respectively, which are way too far beyond a realistic situation. After inter-carrier spacing reduction, it comes that
CRUSSIÈRE et al.: UNIFIED BROADCAST LAYER FOR HORIZON 2020

<table><caption>TABLE IV
CPHY PARAMETERS FOR COVERAGE AREA ENHANCEMENT IN THE UHF BAND (BANDWIDTH: 8 MHz, CENTRAL FREQUENCY: 600 MHz)</caption><thead><tr><th>System</th><th>Inter-carrier spacing</th><th>Possible FFT size</th><th>Guard interval duration</th><th>Coverage radius</th><th>Max. Doppler shift</th><th>#OFDM symbols per subframe</th></tr></thead><tbody><tr><td>LTE</td><td>15 kHz</td><td>1024</td><td>16.67 µs</td><td>5 km</td><td>1500 Hz</td><td>12</td></tr><tr><td>LTE SFN</td><td>7.5 kHz</td><td>2048</td><td>33.33 µs</td><td>10 km</td><td>750 Hz</td><td>6</td></tr><tr><td rowspan="3">CPHY</td><td>3.75 kHz</td><td>2048</td><td>66.67 µs</td><td>20 km</td><td>375 Hz</td><td>3</td></tr><tr><td>2.5 kHz</td><td>3072</td><td>100 µs</td><td>30 km</td><td>250 Hz</td><td>2</td></tr><tr><td>1.25 kHz</td><td>6144</td><td>200 µs</td><td>60 km</td><td>125 Hz</td><td>1</td></tr></tbody></table>

maximum coverage can be increased up to 60 km, leading in counterpart to a sacrifice of the Doppler resistance down to 125 Hz in the worst case. In the UHF band however, this actually corresponds to a maximal supported velocity of 225 km/h, which is fairly acceptable. Note that reducing the inter-carrier spacing has also an impact on resource allocation since the OFDM symbol duration increases. Such an effect is reported in the last column of Table IV indicating the number of OFDM symbols to map to subframes. Eventually, the smallest value of inter-carrier spacing, namely 1.25 kHz, is still compatible with the subframe segmentation and leads to the allocation of a single OFDM symbol per subframe.

## D. Interleaving Depth Increase

As explained in Section II, the time interleaving depth offered by the 3GPP specifications is significantly smaller than those specified in the DVB-T2/T2-Lite standards, due to latency constraints. Two main strategies detailed hereafter are proposed to circumvent this limitation of the physical layer:

1) Intra- and inter-frame interleaving schemes based on enlarged TTI and time slicing concept,

2) Retransmission-based interleaving schemes reusing the Hybrid Automatic Repeat reQuest (HARQ) concept.

Note that both approaches can only be carried out if additional soft buffer resources are made available at the terminal.

1) Inter-Frame and Intra-Frame Interleaving: A simple way to increase the frequency/time diversity of the 3GPP E-MBMS system is to incorporate an interleaving scheme at the Multicast Channel (MCH) level while increasing the TTI value. In current 3GPP systems, an MCH is mapped onto a single TTI of 1 ms based on the resource allocation approach depicted in Fig. 2. Keeping the same mechanism, the TTI value could actually be increased to 2 ms for instance, while adding an intra-frame interleaving applied on the coded blocks mapped onto the RBs. Following this example, data allocation within the frame is simply carried out as described in Fig. 4. This principle can also be extended up to a 5 ms TTI in a 10 ms radioframe, or to even larger values if the LTE nominal radioframe duration is extended. Complementary to this, time slicing mechanisms can easily be carried out at the resource allocation level. This concept, originally proposed in the context of DVB-H [5], allows separating in time several fragments of the interleaved and coded data. These fragments, called slices of length $T_{slic}^u$, are spread over the radioframes according to a delay $T_{slic}^\Delta$ between each slice. Thereby, channel time

<figure><img src="image_136.png" /><figcaption>Fig. 4. Intra-frame interleaving and TTI enlargement of 2 ms.</figcaption></figure>

<figure><img src="image_137.png" /><figcaption>Fig. 5. Intra-frame interleaving combined with time slicing concept. TTI enlarged to 2 ms, slice duration is 1 ms, and delay between slices is 5 n</figcaption></figure>

diversity can be better exploited and the power consumpt of the receiver can be lowered. This approach is depicted in Fig. 5 considering an enlarged TTI of 2 ms, slices of length 1 ms and a delay of 5 ms. Note that time slicing can be used to inter-frame interleaving as soon as the delay exceeds radioframe duration. In that case, the data of a single MCH would be mapped onto several frames.

2) Retransmission-Based Scheme: Another way of taking advantage of time diversity is to exploit HARQ concepts already defined in the LTE unicast transmission model. However, since no acknowledgment feedback signals are available in a broadcast mode, HARQ mechanisms have to be based on automatic retransmissions at the MCH level. A basic approach can consist in simply sending the same coded bits to each retransmission. In that case, a Chase combining procedure can be used at the receiver side. Such a scenario is illustrated in Fig. 6 in order to reach a code rate of 1/3, three transmissions with code rate 1 can be used in three 1 ms subframes located in different frames. The delay between retransmissions corresponds to the interleaving depth equal to 21 ms in that example. Note that this method avoids the enlargement of TTI duration as well as the definition of an additional time interleaver.

A more elaborate technique could be based on an incremental redundancy mechanism: a given CPHY is broadcast during an initial subframe, and additional redundancy bits corresponding to the same information bits can
<figure><img src="image_138.png" /><figcaption>Fig. 6. Time interleaving based on automatic retransmissions.</figcaption></figure>

automatically retransmitted in subsequent subframes, after some predefined delays. Then, through the observation of the initial transmission content and of the additional redundancy, each receiver improves the decoding of the information.

Such an automatic retransmission approach results in a reduced code rate but yields increased diversity exploitation if the channel has sufficiently changed between two transmissions. It could only be implemented for push services, not for live TV or radio services, and in situation of limited data traffic, during the night for instance. A typical example of application would be data carousels, repeatedly delivering data in a continuous cycle during a sufficient period, allowing most of the receivers in the coverage area to retrieve the transmitted data.

### E. Sounding Pattern Design

At this stage of the study, all the physical layer parameters of the proposed CPHY waveform have been identified and selected. Since the inter-carrier spacing values and the guard interval durations have been substantially modified, the Pilot Patterns (PP) specified by the LTE E-MBMS standard are no more suitable. Indeed, scattered PPs can be viewed as a time-frequency sampling grid which granularity has to meet certain constraints to properly measure the time and frequency variations of the channel response. These constraints can be computed according to the Nyquist criterion (see [11], Section 10.3.2.3.2 for more details):

$$T_{Nyquist} = \max \left\{ \frac{N_{FFT}}{F_s} \cdot \frac{X}{Y}, \frac{4}{3} \cdot GI \right\}, \quad (1)$$

$$D_{Nyquist} = \frac{F_s}{2N_{FFT} \cdot (1 + GI) \cdot X}, \quad (2)$$

where X denotes the spacing between 2 pilots in time domain and Y denotes the spacing between 2 pilots in frequency domain. A convenient PP should hence be designed such that $T_{Nyquist}$ and $D_{Nyquist}$ remain greater than the guard interval duration and the maximum Doppler shift, respectively.

From these relations, it is then possible to propose PPs suitable for the different parameters of the CPHY, namely considering the inter-carrier spacing and guard interval values introduced in Table IV. In order to remain as close as possible to the LTE specifications, such PPs could be obtained following the same pattern shape as the one used in the LTE standard. However, since the PPs have to be unchanged from one TTI to another, such a strategy would lead to a dramatic increase of the overhead when the intercarrier spacing

<figure><img src="image_139.png" /><figcaption>Fig. 7. Comparison of PPs defined in the 1.25 kHz inter-carrier spacing configuration. On the left, the PP is restricted to the TTI time spread whereas it is defined over 2 TTIs on the right.</figcaption></figure>

is reduced (see [12] for more details). Relaxing this constraint, i.e., allowing defining a PP over several TTIs, leads to more efficient PPs. As an example, Fig. 7 compares two suitable PPs with respect to the Nyquist criterion for 1.25 kHz inter-carrier spacing configuration. The first PP (the left) strictly fulfils the LTE requirements by constraining the pattern to be entirely defined within a single TTI duration. The second PP (on the right) is built over two consecutive TTIs, thus leading to an overhead reduction by a factor of two. Note that the second approach would be compatible and particularly adequate in the case of an enlarged TTI, as proposed in Section III-D for time interleaving improvement.

### F. Impact on Terminals

The resulting impact of CPHY implementation in receive in terms of complexity and power consumption highly depends on the way the proposed generic CPHY is deployed and used. In the case it is deployed by a mobile or broadcast network operator on a dedicated carrier, a specific chipset is necessary to decode it. Conversely, in the case the CPHY is used in a mixed mode by a broadcast network operator (e.g., embeded CPHY frames in Future Extension Frames of DVB-T2) or a mobile network operator (e.g., a time multiplex of LTE Advanced/5G frames and CPHY frames in a shared-carrier mode), the addition of the new broadcast capabilities requires a multi-mode receiver whose complexity can be higher than the basic receiver. However, in the case of a time multiplexed LTE-Advanced and CPHY in a shared-carrier mode, the corresponding receiver should not differ very much from existing LTE-Advanced receivers with E-MBMS capabilities, due to the numerous commonalities between the proposed CPHY and E-MBMS.

## IV. VERIFICATION AND IMPLEMENTATION OF THE CPHY CONCEPT

Beyond the analysis and the specifications proposed in previous sections, the validity of the CPHY concept has been proved by means of simulations and implementation of a time demonstrator.
<figure><img src="image_140.png" /><figcaption>Fig. 8. Introduction of new interleaving blocks (in red) into the LTE transmission chain (terrestrial link).</figcaption></figure>

<figure><img src="image_141.png" /><figcaption>Fig. 9. Proposed time slicing principle (terrestrial link).</figcaption></figure>

Simulations were mainly carried out to assess the gains obtained when increasing the time interleaving depth according to Section III-D, for both terrestrial and satellite channels. Besides, the demonstrator was built in two phases and was assigned two main objectives:

1) Implementing a stand-alone CPHY transmission in order to assess the CPHY concept in transmissions over real Radio Frequency (RF) channels;

2) Implementing CPHY and DVB-T2 combined together, in order to illustrate the feasibility of converged operation of the proposed CPHY and of a DVB-T2 signal in a single RF channel.

A. Validation of the CPHY Concept

1) Validation of CPHY Time Interleaving Enhancements: Due to strong low-latency requirements, the LTE physical layer does not include any time interleaver. Nevertheless, as explained in Section III-D such an interleaver can profitably be inserted into the CPHY in order to take advantage of the time diversity offered by the fading environment.

Therefore, for terrestrial transmission channels, a time inter-
leaver coupled with a bit interleaver was introduced at the
output of the coding and rate matching modules of the LTE
transmission chain, as illustrated in Fig. 8. The simulated time
interleaver structure is based on random interleaving com-
bined with time slicing as proposed in Section III-D and
illustrated in Fig. 9. In this way, the set of bits interleaved
together are split into two slices of duration $T_{slic}^u$ and sepa-
rated in time by the time slicing shift $T_{slic}^\Delta$. The bit interleaver
depth is then equal to $2T_{slic}^u$ while time diversity spans on
$T_{slic}^\Delta + T_{slic}^u$.

<figure><img src="image_142.png" /><figcaption>Fig. 10. Simulation results for the CPHY scenario of Table IV with
without time interleaving.</figcaption></figure>

The impact of the time slicing algorithm on performance was assessed through simulations for the CPHY with a carrier frequency of 800 MHz and with the intercarrier spacing to 1.25 kHz as proposed in Table IV. QPSK, 16QAM, and 64QAM constellations were considered with coding rates and 2/3. Two different time slicing configurations corresponding to different values of slice duration $T_{slic}^u$ and time slicing shift $T_{slic}^\Delta$ were tested:

1) $T_{slic}^u = 1$ ms and $T_{slic}^\Delta = 10$ ms,

2) $T_{slic}^u = 2$ ms and $T_{slic}^\Delta = 20$ ms.

The channel model is the normalized typical urban mobile channel with 6 paths (TU-6) described in the DVB-T2 implementation guidelines [11]. The mobile velocity is equal to 1 km/h, corresponding to a Doppler shift of 26.67 Hz.

Fig. 10 shows the Block Error Rate (BLER) curves over
Signal to Noise Ratio (SNR) at the receiver side for the 6
ferent simulated modulation and coding parameters, with a
without time slicing. In the area of interest for broadcasti
that is for target BLERs lower than 10<sup>-2</sup>, this very sim
time slicing algorithm brings a significant gain, ranging fr
1 dB to 2 dB, for most examples under study. In the partic
case of 64QAM constellation with coding rate 2/3, an en
floor is observed when no time interleaving is implement
This is due to the imperfect estimation of the Doppler sl
performed by the channel equalizer, this effect being stron
do for high order constellations. In this particular case, the
ple introduction of the time interleaver significantly lowers
error floor so that a huge gain (around 10 dB) can be obser
in the 10<sup>-2</sup> BLER region.

Performance enhancements due to time interleaving can be demonstrated in satellite channels. Actually, satellitevel-icular channels can suffer from fast fading events coupled w-deep or average shadowing events whose correlation va-can reach several meters [13]. Note that the CPHY wa-form parameters in the satellite case can remain very cl-to those of the 3GPP LTE system, because of strong sim-ities in terms of frequency bands (5 MHz bandwidth ar2 GHz) and owing to the fact that the coverage range is-more governed by the guard interval duration. Simulation-have been performed with the LTE native intercarrier spa
<figure><img src="image_143.png" /><figcaption>Fig. 11. Satellite case simulations results, LMS ITS channel.</figcaption></figure>

<figure><img src="image_144.png" /><figcaption>Fig. 12. Overview of the CPHY real-time implementation platform.</figcaption></figure>

i.e., 15 kHz, and a guard interval of 1/14, corresponding to a guard interval duration of 4.69 µs. The carrier frequency is set to 2.2 GHz. To address a very large scale of time interleaving values, simulations were obtained using a simple row-column matrix permutation.

Differently from the terrestrial channels, the BLER measurement is not currently used as a quality criterion for video reception over satellite mobile channels. In DVB-SH implementation guidelines [14], the Errored-Second-Ratio at 5 % (ESR5) criterion is preferred to assess the transmission quality in mobile channels. In Land Mobile Satellite (LMS) channels, an ESR5 90 % fulfillment ratio is sought to ensure good video quality on a mobile device.

A first set of simulations were carried out in LMS with Intermediate Tree Shadowing (ITS) channel, with 40° elevation for the satellite [13], and 60 km/h mobile speed. The corresponding results are given in Fig. 11. One can observe that interleaving depths greater than or equal to 150 ms make the ESR5 90 % fulfillment ratio to be achieved at a minimum C/N around 11 dB. This C/N value is quite achievable with a well-designed satellite payload and a vehicular category 1 terminal [14]. Significant interleaving gains exceeding 3 dB can be observed because of the severity of the considered LMS channel.

2) CPHY Demonstrator: In order to validate the relevance of the CPHY specifications under realistic conditions, the CPHY system has been implemented in hardware using an FPGA platform. Fig. 12 depicts the overall architecture of the so-called Hardware Evaluation Platform (HEP) that is made of three entities, a main computing unit, the HEP Central Unit, and two secondary units, HEP Tx and HEP Rx.

<figure><img src="image_145.png" /><figcaption>Fig. 13. Functional diagram of the CPHY platform.</figcaption></figure>

Both the transmitter and the receiver are implemented with the same equipment, namely the HEP Central Unit, which made of a FPGA PCIe board embedded within a PC with a real-time operating system for control and monitoring. order to allow for transmissions over distant locations, main processing board is connected to the secondary unit HEP Tx and HEP Rx via full-duplex optical links running 5 Gbps. The HEP Tx unit implements the Digital-to-Ana Conversion (DAC) on an Intermediate Frequency (IF) with the HEP Rx unit implements the Analog-to-Digital Conversion (ADC) from IF down to baseband. The HEP Tx and Rx unit can interconnect in analog with RF front-ends or with channel emulators, terrestrial or satellite. The CPHY platform is built from an existing design implementing a simplified version of the 3GPP LTE (Release 8) physical layer in downlink [1]. The reference platform was dedicated to the evaluation of the validation of physical layer technologies. There is thus support of the signaling channels. Table V provides the list of parameters of the reference 3GPP LTE system implemented in the platform.

Fig. 13 depicts the functional diagram of the CPHY transmitter and receiver in baseband. This version of the system does not support any time and frequency synchronization mechanism so far. The subset of CPHY specifications supported by the HEP platform is summarized in Table VI.

The main purpose of this first-generation demonstrator is to prove that the current 3GPP E-MBMS broadcasting component can easily be modified to enable broadcasting over large cells, as argued in Section III-C. In the so-called Multicell Broadcast Single Frequency Network (MBSFN) mode E-MBMS, all the cells are tightly synchronized in time and transmit over the same frequency. MBSFN transmission enables highly efficient MBMS, allowing for over-the-air combining of multi-cell transmissions in the User Equipment (UE). An extended cyclic prefix is used to compensate for difference in propagation delays, thus making the MBSFN transmission appear to the UE as a transmission from a single cell. The advantage of this SFN mode is precisely allowed for data transmission from a small number of very large cells.
<table><caption>TABLE V
GENERAL PARAMETERS OF THE CPHY PLATFORM</caption><thead><tr><th colspan="2">BASIC SYSTEM PARAMETERS</th></tr></thead><tbody><tr><td>Carrier frequency</td><td>Low-IF = 70 MHz</td></tr><tr><td>Symbol duration</td><td>66.66 µs</td></tr><tr><td>Short cyclic prefix duration (symbols 1-6/7)</td><td>4.69 / 5.21 µs</td></tr><tr><td>Total symbol duration</td><td>71.35 µs</td></tr><tr><td>Subcarrier spacing</td><td>15 kHz</td></tr><tr><td>Slot duration</td><td>0.5 ms</td></tr><tr><td>Number of symbols per slot</td><td>7</td></tr><tr><td>Frame duration</td><td>10 ms</td></tr><tr><td>Number of subframes in a frame</td><td>10</td></tr><tr><td>Number of subcarriers in a Resource Block</td><td>12</td></tr><tr><th colspan="2">SYSTEM PARAMETERS FOR 20 MHz CHANNELS</th></tr><tr><td>Channelization bandwidth</td><td>20 MHz</td></tr><tr><td>Sampling frequency</td><td>30.72 MHz</td></tr><tr><td>Number of samples per slot</td><td>15,360</td></tr><tr><td>FFT size</td><td>2,048</td></tr><tr><td>Number of null subcarriers</td><td>848</td></tr><tr><td>Number of modulated subcarriers</td><td>1,200</td></tr><tr><td>Number of available RBs</td><td>100</td></tr></tbody></table>

<table><caption>TABLE VI
CPHY FEATURES IMPLEMENTED IN HARDWARE</caption><thead><tr><th>Parameters</th><th>Supported values</th></tr></thead><tbody><tr><td>Bandwidth</td><td>6, 7, 8 and 10 MHz</td></tr><tr><td>Inter-carrier spacing</td><td>1.25, 2.5, 3.75, 7.5 and 15 kHz</td></tr><tr><td>FFT size</td><td>0.5k, 1k, 2k, 4k, 8k, 12k and 24k</td></tr><tr><td>Pilot patterns</td><td>X=2, 6<br>Y=1, 2, 4 and 6 (see section III.E)</td></tr></tbody></table>

The radius of the cells is actually limited by the duration of the guard interval of the OFDM symbols whose task is to avoid the inter-symbol interference due to long echoes coming from distant transmitters (see Fig. 14).

In order to demonstrate the gain provided by the CPHY system in terms of coverage area, the five different physical modes detailed in Table IV have been implemented for a 10 MHz bandwidth. An essential guideline that directed the design of these physical modes was keeping maximum commonality with the 3GPP LTE system, especially the sampling frequency and the 1 ms duration of the 3GPP LTE TTI. With the normal 3GPP LTE subcarrier spacing mode and the SFN reduced subcarrier spacing modes, the system is able to transmit 12, 6, 3, 2 or 1 OFDM symbols per TTI as illustrated in Fig. 15. The most favorable case provides a guard interval of 200 µs, compatible with a coverage radius of 60 km (see Table IV). Note that the reduction of the subcarrier spacing also reduces the robustness to Doppler and that the selection of the mode to be deployed in practice depends on the operating frequency.

3) *Validation Tests Carried Out With the CPHY Demonstrator:* The five framing modes of the CPHY specifications have been implemented on the HEP platform with the ability to dynamically switch from one mode to

<figure><img src="image_146.png" /><figcaption>Fig. 14. Illustration of the impact of the distance between SFN transmitters on OFDM.</figcaption></figure>

<figure><img src="image_147.png" /><figcaption>Fig. 15. Illustration of the guard interval duration with respect to the CF modes.</figcaption></figure>

<figure><img src="image_148.png" /><figcaption>Fig. 16. Impact of a two-path channel with 160 µs delay on E-MBMS. $\Delta f = 15$ kHz.</figcaption></figure>

another. Fig. 16 and Fig. 17 provide an overview of HEP monitoring interface where the platform transmits E-MBMS signal through a hardware channel emulator. In particular case, the interface shows:

1) **at the transmitter side**, the 3D representation of time and frequency samples in the framing module; the transmitted signal in the time domain;

2) **at the receiver side**, the 3D representation of the channel estimation samples and the constellation points; the output of the equalizer.
<figure><img src="image_149.png" /><figcaption>Fig. 17. Impact of a two-path channel with 160 µs delay on CPHY with $\Delta f = 1.25$ kHz.</figcaption></figure>

To demonstrate the robustness of the CPHY system towards long echoes, a simple channel featuring two paths 160 µs apart has been implemented. Fig. 16 illustrates the impact of this channel on the E-MBMS signal when the subcarrier spacing of 15 kHz sets the guard interval duration to 16.7 ms. The signal is obviously degraded due to inter-symbol interference. Once the platform configured to transmit the CPHY signal with the lowest subcarrier spacing value $\Delta f = 1.25$ kHz, the guard interval of 200 µs is large enough to handle the channel delay and inter-symbol interference is no longer observed at the receiver side, as shown in Fig. 17.

## B. Embedding a CPHY Waveform Into DVB-T2 FEF Frames

The second phase of the demonstrator implementation combines two end-to-end real time transmission chains:

1) The CPHY chain, including transmitter, channel emulator, and receiver, as described in the previous subsection;

2) A DVB-T2 transmission chain also including transmitter, channel emulator, and receiver.

As illustrated in Fig. 18, the digital output of the CPHY modulator feeds the DVB-T2 modulator, which inserts the CPHY frames into reserved slots of the T2 signal, by means of the FEF mechanism offered by the DVB-T2 standard. The resulting signal is a sequence of DVB-T2 and CPHY frames in a classical time division multiplexing scheme. At the receiver side, the DVB-T2 demodulator first provides channel estimation and overall synchronization, then extracts the CPHY frames and forwards them to the CPHY demodulator. On the one hand, the DVB-T2 frames are demodulated by the DVB-T2 demodulator which delivers the data to a standard audio/video (AV) decoder and a wide screen. On the other hand, the CPHY frames are demodulated by the CPHY demodulator which delivers the received data to the upper layers for display. Both demodulators provide indications about the quality of the received signals.

<figure><img src="image_150.png" /><figcaption>Fig. 18. Functional description of the demonstrator combining CPHY DVB-T2 waveforms.</figcaption></figure>

<figure><img src="image_151.png" /><figcaption>Fig. 19. T2 and CPHY frame combination.</figcaption></figure>

The structure of the DVB-T2 super-frame structure adopted for the combination of regular T2 frames and CPHY frames is given in Fig. 19 and the parameters of the T2 and CPHY frames are detailed in Table VII. The super-frame duration has been chosen to contain an integer multiple of both the DVB-T2 and CPHY elementary periods, $T_{SDVB}$ and $T_{SCPHY}$. The configuration of the T2 frame is derived from the regular “U” mode”, i.e., it targets fixed receivers at home, with wide horizontal definition (HD) screens. Moreover, the super-frame structure was defined to have approximately the same duration for both the T2 and CPHY frames.

1) **Validation Tests for a Combined DVB-T2/CPHY Transmission:** Three types of validation tests have been defined and carried out so far in order to show that CPHY frames can actually be transmitted within a T2 signal without disturbing the regular T2 reception:

1) **Transmitter test:** Verify with a spectrum analyzer that an oscilloscope the correct insertion of the CPHY-FEF into the T2 frame. When the CPHY signal is not present, the RF signal contains a null FEF corresponding to the CPHY-FEF duration. When the CPHY signal is present, the transmitter generates a continuous RF signal, shown in Fig. 20 (the power for the CPHY and DVB-T2 signals have intentionally been set to different values to distinguish the FEFs).

2) **End-to-end go/no-go test (video test):** Check the video on the T2 receiver and on the CPHY receiver with a cable transmission and over-the-air transmission via aerials. This scenario actually constitutes the convergence demonstration.
<table><caption>TABLE VII
SUPER-FRAME PARAMETERS OF THE DVB-T2/CPHY PLATFORM</caption><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>Frame format</td><td>1 T2 frame + 1 FEF</td></tr><tr><td>Bandwidth</td><td>8 MHz</td></tr><tr><td colspan="2">T2 FRAME PARAMETERS</td></tr><tr><td>DVB-T2 mode</td><td>Mode A (1PLP) - SISO</td></tr><tr><td>T<sub>SVN</sub></td><td>7/64 µs (109 ns)</td></tr><tr><td># OFDM symbols in T2 frame</td><td>46</td></tr><tr><td>FFT size</td><td>32K extended (27,841)</td></tr><tr><td>Δf (kHz)</td><td>0.279</td></tr><tr><td>Guard interval duration</td><td>1/128 (28 µs)</td></tr><tr><td>Pilot pattern</td><td>PP7</td></tr><tr><td>PAPR reduction</td><td>No</td></tr><tr><td>L1 constellation</td><td>64QAM</td></tr><tr><td>LDPC codeword length</td><td>64K</td></tr><tr><td>Code rate</td><td>2/3</td></tr><tr><td>Constellation</td><td>Rotated 256QAM</td></tr><tr><td>Time interleaver</td><td>intra-frame</td></tr><tr><td>High efficiency mode</td><td>Yes</td></tr><tr><td>T2 bitrate (Mbit/s)</td><td>21.69</td></tr><tr><td colspan="2">CPHY FRAME PARAMETERS</td></tr><tr><td>T<sub>SCBS</sub></td><td>1/30.72 µs (32.5 ns)</td></tr><tr><td># Radio frames in CPHY FEF (10ms)</td><td>14</td></tr><tr><td>FFT size</td><td>12k</td></tr><tr><td>Δf (kHz)</td><td>2.5</td></tr><tr><td>Guard interval</td><td>1/4 (33.33 µs)</td></tr><tr><td># RBs</td><td>40</td></tr><tr><td># Occupied subcarriers</td><td>2880</td></tr><tr><td>Effective BW (MHz)</td><td>7.2</td></tr><tr><td>TTI duration</td><td>1 ms</td></tr><tr><td># OFDM symbols per TTI</td><td>2</td></tr><tr><td># OFDM symbols in CPHY frame</td><td>280</td></tr><tr><td>Pilot pattern</td><td>(a)</td></tr><tr><td>Constellation</td><td>16QAM</td></tr><tr><td>Code rate</td><td>1/2</td></tr><tr><td>CPHY bitrate (Mbit/s)</td><td>~3.5</td></tr></tbody></table>

<figure><img src="image_152.png" /><figcaption>Fig. 20. Observation of a combined T2 and CPHY signal.</figcaption></figure>

3) **Test in Additive White Gaussian Noise (AWGN) channel:** Perform a rough assessment of system performance, in presence of noise, for the transmission of the DVB-T2 and CPHY signals. The validation criterion is a video without error. The minimum carrier-to-noise ratio requested for good reception is then compared to the values obtained by simulation.

The complete assembled “CPHY in T2” demonstrator used to carry on these tests is shown in Fig. 21 and Fig. 22.

2) **Future Work:** The first-generation demonstrators presented in this paper have been used to demonstrate both the CPHY concept and a possible broadband/broadcast convergent scenario with the insertion of CPHY traffic within DVB-T2 FEFs. However, only a limited set of the CPHY system parameters have been implemented and tested so far. The next tasks will involve implementing the missing modes in the CPHY demonstrator in order to achieve performance assessment.

<figure><img src="image_153.png" /><figcaption>Fig. 21. “CPHY in T2” overall platform: (from left to right) the DVB-T2 and CPHY video sources, the DVB-T2 and CPHY transmitters, the DVB-T2 receiver control display, the HD widescreen for DVB-T2 video, the screen for the low-resolution CPHY video.</figcaption></figure>

<figure><img src="image_154.png" /><figcaption>Fig. 22. (a)“CPHY in T2” transmitter: The DVB-T2 modulator (front) the CPHY Tx interface board (rear), the CPHY transmitter control display (b) “CPHY in T2” receiver: The DVB-T2 frame splitter (front), the CPHY Rx interface board (rear), the CPHY receiver control display.</figcaption></figure>

## V. CONCLUSION

This paper argues in favor of a broadband-broadcast convergence through the concept of common physical layer, proving a good basis for coverage cooperation between broadband and mobile networks, while relying on non-dedicated mobile receivers.

General technical requirements for the design of such specifications have been given and a practical example of a common physical layer based on the 3GPP LTE/E-MBMS and DVB-T2 standards has been described. Then, the successive steps of the proof of concept demonstration of proposed unified broadcast layer have been presented: simulation results have proved the advantages of introducing time interleaving into 3GPP E-MBMS; the implementation of a hardware platform and subsequent validation tests have demonstrated the common physical layer feasibility as well as its embedding into a DVB-T2 future extension frame (FEF).

Additional laboratory tests with terrestrial/satellite hardware channel emulators and field trials have still to be carried out in order to complete the overall proof of concept demonstration. Nevertheless, the work already done has proved the technical feasibility and the relevance of such a common physical layer approach. Such a convergent approach appears to be a relevant work item in FoBTV’s work on the next generation terrestrial broadcast systems.

The remaining issues mainly concern upper layers, signaling and, beyond physical layer, the idea of cooperation/convergence at the network architecture level has to be considered. In particular, some kind of synchronization
would be required between both networks and network infras-
tructures should be modified in order to create interconnections
and insert gateways.

ACKNOWLEDGMENT

The authors would like to warmly thank all the Mobile MultiMedia (M³) project partners for the numerous and fruitful discussions that contributed to the maturation of the concepts outlined in this paper.

REFERENCES

[1] CISCO White Paper. (2013, Feb.). “Cisco visual networking index: Global mobile data traffic forecast update, 2013–2018,” [Online]. Available: http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white_paper_c11-520862.html

[2] [Online]. Available: http://www.ieee802.org/11/Reports/hew_update.htm

[3] [Online]. Available: http://www.nttdocomo.co.jp/english/binary/pdf/corporate/technology/rd/technical_journal/bn/vol14_3/vol14_3_051en.pdf

[4] [Online]. Available: http://www.3gpp.org/Release-9

[5] Digital Video Broadcasting (DVB), Transmission System for Handheld Terminals (DVB-H), ETSI Standard EN 302 304, V1.1.1, Nov. 2004.

[6] [Online]. Available: http://en.wikipedia.org/wiki/MediaFLO

[7] Forward Link Only Air Interface; Specification for Terrestrial Mobile; Multimedia Multicast, ETSI Standard TS 102 589, V1.1.1, Feb. 2009.

[8] Digital Video Broadcasting (DVB), Framing Structure, Channel Coding and Modulation for Satellite Services to Handheld Devices (SH) Below 3 GHz. ETSI Standard EN 302 583, V1.1.1, Mar. 2008.

[9] Digital Video Broadcasting (DVB); Frame Structure Channel Coding and Modulation for a Second Generation Digital Terrestrial Television Broadcasting System (DVB-T2), ETSI Standard EN 302 755, V1.3.1, Oct. 2011.

[10] Digital Video Broadcasting (DVB); Next Generation Broadcasting System to Handheld, Physical Layer Specification (DVB-NGH), DVB Bluebook Standard A160, Nov. 2012.

[11] Digital Video Broadcasting (DVB); Implementation Guidelines for a Second Generation Digital Terrestrial Television Broadcasting System (DVB-T2), ETSI Standard TS 102 831, V1.2.1, Feb. 2012.

[12] C. Gallard et al., "Universal DVB-3GPP broadcast layer: An enabler for new business in mobile broadcasting landscape," in *Next Generation Mobile Broadcasting*, D. Gómez-Barquero Ed. Hoboken, NJ, USA: CRC Press, 2013.

[13] F. Pérez-Fontán, M. Vázquez-Castro, C.E. Cabado, J. Pita García, and E. Kubista, "Statistical modelling of the LMS channel," *IEEE Trans. Veh. Tech.*, vol. 50, no.6, pp. 1549-1567, Nov. 2001.

[14] Digital Video Broadcasting (DVB); DVB-SH Implementation Guidelines, ETSI Standard TS 102 584, V1.2.1, Jan. 2011.

[15] 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE); Evolved Universal Terrestrial Radio Access (E-UTRA); Physical Channels and Modulation (3GPP TS 36.211 Release 8), ETSI standard TS 136 211 V8.9.0, Jan. 2010.

<figure><img src="image_155.png" /></figure>

Matthieu Crussière received the M.Sc. and Ph.D. degrees in electrical engineering from the National Institute of Applied Sciences (INSA), Rennes, France, in 2002 and 2005, respectively. Since 2005, he has been an Associate Professor with the Department of Telecommunications and Electrical Engineering at INSA, and currently leads his research activities with the Electronics and Telecommunications Institute of Rennes, Rennes, France. His current research interests include digital communications and signal processing techniques.

His works focus on the optimization of high-bit rate communications, resource
allocation mechanisms, adaptive system design based on multicarrier, and mul-
tiantenna schemes. He is the author or co-author of over 80 technical papers
in international conferences and journals. He has been involved in several
European and French national research projects in the field of powerline,
broadcasting, ultra wideband, and mobile radio communications.

<figure><img src="image_156.png" /></figure>

**Catherine Douillard** received the enginee
degree in telecommunications from the E
Nationale Supérieure des Télécommunications
Bretagne, Plouzané, France, in 1988, the Ph
degree in electrical engineering from the Univer
ity of Western Brittany, Brest, France, in 1992,
the accreditation to supervise research from
University of Southern Brittany, Lorient, Fra
in 2004. She is currently a Professor of
the Electronics Department of Telecom Bret
a Plouzané, France, where she is in charge of

Algorithm-Silicon Interaction Research team. Her current research interests include turbo codes and iterative decoding, iterative detection, the efficient combination of high spectral efficiency modulation and turbo coding schemes for multiband systems, and the use of turbo coding for diversity techniques and turbo processing for multicarrier, multiantenna, multiple access transmission systems. In 2009, she received the SEE/IIoT Glavieux Award for her contribution to standards and related industrial impacts.

<figure><img src="image_157.png" /></figure>

**Christian Gallard** received the engineering degree from the Ecole Supérieure d'Électronique de l'O (ESEO), Angers, France, in 1996. From 1997 to 2000, he worked with Matra Communications in the area of digital communications applications. From 2000 to 2002, he worked on digital communications in a UMTS system, and from 2002 to 2004, he worked on text with Philips Consumer Communications (layer simulations). From 2002 to 2004, he was a sub-contractor with France Telecom, working speech processing, UMTS FDD, and MIMO issues.

He joined France Telecom in 2004. From 2005 to 2006, he worked on WiMAX issues (WiMAX Forum, link layer simulations). From 2006 to 2007, he involved in elaboration of 3GPP LTE standard (RAN1 meetings, system definition, link layer simulations). Since the end of 2007, he has been involved in the definition of broadcasting systems (standardization of DVB-T2, DVB-N21, D2.1, D3.1, D3.2, D3.3, B21C, ENGINES Celtic projects). From 2010 to 2013, he led the French collaborative M3 (Mobile Multi-Media) project. He is currently a Research Project Coordinator inside Orange (studies on enablers in digital communications, propagation channel modelling, antennas design for future networks including 5G).

<figure><img src="image_158.png" /></figure>

**Marie Le Bot** received the engineering degree from the Ecole Centrale de Nantes, Nantes, France, in 1997, and the Ph.D. degree in electronics and communications from the Conservatoire National d'Arts et Métiers, Paris, France, in 2001. Since then, she has been working as a Research Engineer at Orange Labs, Rennes, France, in digital signal processing, dimensioning and resource management, and as a wireless networks (GSM, UMTS, HSPA, LTE), power-line communications. Her current research interests include mobile broadcasting systems

the reduction of energy consumption in home networks.

<figure><img src="image_159.png" /></figure>

**Benjamin Ros** graduated from the University of Rennes 1, Rennes, France, in electro and telecommunications engineering in 2005. has first worked on signal processing algorithm for GNSS receivers. Since 2007, he has been working as an Air Interface Engineer with Telecommunications Department at French SIA Agency on topics such as waveforms optimization over satellite mobile channel, channel sounding, satellite system optimization.
CRUSSIÈRE *et al.*: UNIFIED BROADCAST LAYER FOR HORIZON 2020

<figure><img src="image_160.png" /></figure>

**Arnaud Bouttier** was born in Le Mans, France, in 1969. In 1992, he received the Master of Sciences in signal processing from the University of Rennes 1, Rennes, France. He graduated from the Engineering School Ecole Nationale Supérieure des Télécommunications de Bretagne, Plouzané, France, in 1994. He received the Ph.D. degree from the University of Rennes 1 in 2000. During his Ph.D., his research was focused on blind equalization by means of adaptive trellis filtering. He joined MERCE, formerly ITE-TCL, in 2000, with the task to acquire on knowledge digital implementation of telecommunication systems. He is currently a Project Leader with the development of hardware evaluation platforms in the Wireless Communication Systems team with an emphasis on satellite and terrestrial broadcasting. He was involved in several collaborative projects dealing with broadband and broadcasting technologies (IST 4MORE, ANR APOGEE, CELTIC WINNER+, CELTIC ENGINES, and ANR M3).

<figure><img src="image_161.png" /></figure>

**Alain Untersee** received the engineering degree in electronics from the National Electronics Engineering School, Grenoble, France. After spending several years in large French groups, in 1988, he co-founded the Innovation in Telecommunications, Image, and Sound (ITIS) Company, where he held the position as a Sales Director. He developed the worldwide sales of professional equipment for Terrestrial Digital TV and Digital Radio networks. He joined TeamCast in 2007, where he is taking care of the involvement of TeamCast in collaborative research projects at the French and international levels (preparation of proposals, management of projects).