IEICE Communications Express, Vol.5, No.8, 260–265

Interference-aware channel
segregation based dynamic
channel assignment in HetNet
Ren Sugai, Abolfazl Mehbodniyaa), and Fumiyuki Adachi
Dept. of Comm. Engineering, Graduate School of Engineering, Tohoku University,
6–6–05 Aza-Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980–8579, Japana) mehbod@mobile.ecei.tohoku.ac.jp

Abstract: In this paper, we aim at solving the co-channel interference(CCI) between cells in heterogeneous networks (HetNets), employing aninterference-aware channel segregation based dynamic channel assignment(IACS-DCA). To improve the energy efﬁciency in HetNet, a distributed
ON/OFF switching algorithm for BSs is proposed in which each BS selects
ON/OFF strategy using game-theory. We combine these two algorithms byusing the beacon signal. The beacon signal contains the trafﬁc load information to be used for user equipment (UE) association when BS ON/OFFalgorithm is employed and it is used for measuring the instantaneous beacon
signal in IACS-DCA. We show by computer simulation that by combining
IACS-DCA and distributed ON/OFF switching algorithms for BSs, hightransmission quality is achieved.
Keywords: channel segregation, dynamic channel assignment, co-channelinterference, heterogeneous network
Classiﬁcation: Terrestrial Wireless Communication/Broadcasting Technologies
References© IEICE 2016
DOI: 10.1587/comex.2016XBL0078
Received April 10, 2016
Accepted April 28, 2016
Publicized May 27, 2016
Copyedited August 1, 2016

[1] R. Matsukawa, T. Obara, and F. Adachi, “A dynamic channel assignment
scheme for distributed antenna networks,” Proc. IEEE 75th Vehicular Technology Conference (VTC2012-Spring), May 2012. DOI:10.1109/VETECS.
2012.6240293[2] Y. Matsumura, K. Temma, S. Ren, T. Obara, T. Yamamoto, and F. Adachi,“Interference-aware channel segregation based dynamic channel assignment for
wireless networks,” IEICE Trans. Commun., vol. E98-B, no. 5, pp. 854–860,
May 2015. DOI:10.1587/transcom.E98.B.854[3] R. Sugai, K. Temma, A. Mehbodniya, and F. Adachi, “Interference-awarechannel segregation for HetNet using time- and frequency-division channels,”IEEE Dynamic Spectrum Access Networks 2015 (DYSPAN2015), Stockholm,Sweden, Sept. 2015. DOI:10.1109/DySPAN.2015.7343921[4] S. Samarakoon, M. Bennis, W. Saad, and M. Latva-aho, “Opportunistic sleep
mode strategies in wireless small cell networks,” Proc. IEEE International
Conference on Communications (ICC), pp. 2707–2712, June 2014. DOI:10.
1109/ICC.2014.6883733

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1© IEICE 2016
DOI: 10.1587/comex.2016XBL0078
Received April 10, 2016
Accepted April 28, 2016
Publicized May 27, 2016
Copyedited August 1, 2016

Introduction

Heterogeneous network (HetNet) is a promising network for the 5th generation
mobile communications. By ofﬂoading trafﬁc from macro base station (MBS) tosmall BSs (SBSs), trafﬁc per BS can be decreased. Therefore, HetNet can improve
the system capacity per area under a given number of available channels. Becauseof scarce spectrum resources, the number of available channels is limited inwireless networks and therefore, the same channel needs to be reused by different
BSs. The same channels can be reused by SBSs even in MBS area by allowing acertain amount of co-channel interference (CCI). CCI is a major problem in HeNet.
The CCI between MBS and SBSs becomes serious when MBS and SBSs share thesame radio resource. By increasing the number of SBSs, the throughput per user
and the capacity per area can be improved. In dense deployment of SBSs, CCI
among SBSs themselves becomes a serious problem as well. To solve CCI problem
in HetNet, dynamic channel assignment (DCA) can be applied. There are two typesof DCA: centralized DCA and distributed DCA. The centralized DCA may not bepractical due to its prohibitively high computational complexity and back haulcommunication. Recently, we proposed an interference-aware channel segregation
based DCA (IACS-DCA) [1, 2, 3], which is categorized into distributed DCA.
IACS-DCA can form a channel reuse pattern with low CCI in a distributed manner[1, 2, 3]. We have shown that IACS-DCA can solve CCI problem in HetNet in a
distributed manner [3].
Dense deployment of small cell can improve throughput per user and thecapacity per area. However, dense deployment of small cell leads to the increase ofpower consumption of BSs in HetNet. Therefore, a BS ON/OFF switching will be
introduced to reduce power consumption of BSs. In [4], a distributed energyefﬁcient algorithm is proposed in which each BS selects ON/OFF strategy based on
the current trafﬁc load and network environment, using a game-theoretic approach.
This algorithm is shown to improve the energy efﬁciency and reduces the overallload in the system comparable to conventional approaches in a distributed manner.
According to the network conditions (e.g., power control, user equipment (UE)location and BSs’ ON/OFF switching pattern), CCI environment varies over timeand channel allocation should cope with this changing environment. Especially, inthe dense HetNet, where CCI varies dynamically, radio resource management for
BSs becomes complex and difﬁcult. Therefore, a distributed channel assignment
method to always minimize the CCI, is required.
In this paper, we study the IACS-DCA using the beacon signal in HetNet,
combined with a learning-based game-theoretic BS ON/OFF switching. In learning-based game-theoretic BS ON/OFF switching algorithm, all BSs transmits thebeacon signal for UE association. We use this beacon signal for instantaneous CCI
measurement in IACS-DCA. As a result, BS doesn’t need to transmit any additional signal for channel segregation. We show by computer simulation that theproposed algorithm achieves high transmission quality. The rest of the paper isorganized as follows. Section 2 describes the IACS-DCA algorithm. Section 3
presents the system model and ON/OFF switching algorithm. Computer simulation
results are brought in Section 4. Finally, Section 5 concludes the paper.

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2IACS-DCA

In this section we explain brieﬂy four stages of the IACS-DCA Algorithm. Each BS
is equipped with a channel-priority table. It periodically (I) measures the instantaneous CCI powers by monitoring the beacon signal on all available channels. The
beacon signal is designed to be periodically transmitted from each BS. At stage (II),each BS computes the average CCI power on all available channels, using past CCI
measurement results and in (III) updates the channel-priority table in order to selectthe best channel with the lowest average CCI power in (IV). After channel
selection, each BS continues to use the selected channel until the next channelpriority table updating time. Each BS periodically repeats the procedure in(I)∼(IV). The channel with the lowest average CCI power is considered not to
be used by neighboring BSs and hence, the impact of causing interference to otherBSs by using this channel is expected to be minimal. Therefore, IACS-DCA formsa channel reuse pattern with low CCI in a distributed manner.
3BS ON/OFF switching algorithm

Each BS chooses its strategy (transmission power level). Transmission power of mth BS, BS(m), is given byPBSðmÞ ðtÞ ¼ aBSðmÞ ðtÞ  PMAXBSðmÞ ;ð1Þ

where aBSðmÞ ðtÞ ¼ f0; 1=3; 2=3; 1g is the transmission power coefﬁcient and PMAXBSðmÞis the maximum transmission power of m-th BS. Please note that MBS can only
select one transmission power coefﬁcient, i.e., aBSðmÞ ðtÞ ¼ 1 whereas SBSs canselect all four available coefﬁcients.
UE association is also decided in this algorithm. If the UE belongs to the set ofrecently slept BSs, or if it belongs to the set of UEs which have dropped due tooverload then it should be assigned to a new BS. In order to connect to a new BS,
UEs receive the load estimate of all BSs through the beacon signal and choose theBS to which they want to connect by evaluating an association function.
4© IEICE 2016
DOI: 10.1587/comex.2016XBL0078
Received April 10, 2016
Accepted April 28, 2016
Publicized May 27, 2016
Copyedited August 1, 2016

Computer simulation

We show by computer simulation that transmission quality is improved by
combining IACS-DCA and BS ON/OFF switching algorithm. An MBS is locatedat the center of macro cell. NSBS SBSs are distributed uniformly within one macro
cell and U static UEs are assumed to be uniformly located within the macro cell.
We assume C available frequency channels. Each BS periodically broadcasts abeacon signal on the selected channel containing the load estimate. In IACS-DCA,
each BS measures this instantaneous beacon signal power on each of available
channels as the instantaneous CCI power for IACS-DCA. The simulation parameters are summarized in Table I. We only consider path loss in propagation channel.
Based on IACS-DCA, BSs select one channel from available C ¼ 6 channels at
each updating time. The initial channel is set to channel c ¼ 1 for all BSs and theinitial transmission power coefﬁcient of SBSs is aBSðmÞ ð0Þ ¼ 1.

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Table I. Computer simulation condition

NetworkTransmit power

Path loss

No. of MBSs

NMBS ¼ 1

No. of SBSs

NSBS ¼ 50

No. of channels

C¼6

No. of UEs

U ¼ 50400

Carrier frequency

2 [GHz]Frequency bandwidth! ¼ 10 [MHz]Noise power spectrum density

N0 ¼ 168 [dBm/Hz]

Mean offered trafﬁc per UE

1.8 Mbps

MBS46 [dBm]

SBS30 [dBm]

MBS-SBS, MBS-UE

15:3 þ 37:6 log10 ðdÞ [dB]

SBS-SBS, SBS-UE

30:6 þ 36:7 log10 ðdÞ [dB]

d: distance between BS and BS or between BS and UE [m]IACS-DCA ¼ 0:99

Filter forgetting factor

4.1 Simulation model
The m-th (m ¼ 1NMBS þ NSBS ) BS and the u-th (u ¼ 1U) UE are represented asBS(m) and UE(u), respectively. The downlink SINR of UE(u) connected to BS(m)at time t is given byPBSðmÞlUEðuÞ,BSðmÞ

10 10  10 10SINRðu; tÞ ¼;
IUEðuÞ ðtÞ þ !UEðuÞ N0ð2ÞPBSðmÞ denotes the transmit power in dB transmitted from BS(m). lBSðmÞ,BSðnÞ
represents the propagation loss in dB between UE(u) and BS(m). N0 is the noisepower and !UEðuÞ is the the set of subcarriers assigned by BS(m) to UE(u). IUEðuÞ ðtÞis the received CCI power experienced at UE(u) connected to BS(m) using c-thchannel at time t and is given byXIUEðuÞ,BSðnÞ ðt; cÞ;ð3ÞIUEðuÞ ðtÞ ¼
n2BSGðcÞ
n≠mwhere BSG represents group of BSs using c-th channel and IUEðuÞBSðnÞ ðt; cÞrepresents the received CCI power of c-th channel which comes from BS(n) atupdating time t and is given asPBSðnÞIUEðuÞ,BSðnÞ ðt; cÞ ¼ 10 10  10lUEðuÞ,BSðnÞ
10:

ð4Þ

4.2 Average CCI power measurement
Each BS periodically broadcasts beacon signal on the selected channel. The
received beacon signal power on BS(m) from BS(n) at updating time t is represented asPBSðnÞ© IEICE 2016
DOI: 10.1587/comex.2016XBL0078
Received April 10, 2016
Accepted April 28, 2016
Publicized May 27, 2016
Copyedited August 1, 2016IBSðmÞ,BSðnÞ ðt; cÞÞ ¼ 10 10  10lBSðmÞ,BSðnÞ
10;

ð5Þ

where PBSðnÞ denotes the transmit power of the beacon signal in dB broadcasted
from BS(n). lBSðmÞ,BSðnÞ represents the propagation loss in dB between BS(m) and263

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BS(n). For the computation of the average CCI power, the ﬁrst order ﬁltering with
forgetting factor β is used. The average CCI power computed on BS(m) at updatingtime t is given asIBSðmÞ ðt; cÞ ¼ ð1  Þ  IBSðmÞ ðt; cÞ þ   IBSðmÞ ðt  1; cÞ;ð6Þ

β is the parameter which controls the convergence time. If a too small β is used, theaverage CCI power tends to follow the instantaneous CCI power and the channel
segregation will not be stable. In this paper,  ¼ 0:99 is used.

Fig. 1.

Ave. energy consumption per SBS.

4.3 Simulation results
Fig. 1 plots average energy consumption per SBS vs no. of UE when IACS-DCAand BS ON/OFF switching algorithm are used. For comparison, we also plot
average energy consumption per SBS with no. of UEs when only IACS-DCA isapplied in HetNet. We observe that average energy consumption per SBS isreduced by BS ON/OFF switching algorithm based on the no. of UE. Even when
U ¼ 500, 50% of average energy consumption per SBS is reduced.

© IEICE 2016
DOI: 10.1587/comex.2016XBL0078
Received April 10, 2016
Accepted April 28, 2016
Publicized May 27, 2016
Copyedited August 1, 2016

Fig. 2.

Ave. throughput per UE.

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Fig. 2 plots the average throughput per UE vs no. of UE when IACS-DCA andBS ON/OFF switching algorithm are used. Black line shows the average throughput per UE with no. of UE as a parameter when only IACS-DCA algorithm isapplied. Green line represents the case where there is no interference between BSs
and when only 1 channel is shared by all BSs. It can be seen from Figs. 7, thatthe average throughput per UE is improved by combining IACS-DCA and BS
ON/OFF switching algorithm. This is because that by ON/OFF switching algorithm the amount of CCI in the network is reduced and IACS-DCA can form achannel reuse pattern with low CCI corresponding to the changes of CCI environment. The result when there is no interference achieves 1.8 Mbps even when U ¼500. However, as you can see in Fig. 8, average throughput decrease when U is
more than 600.
5Conclusion

In this paper, we studied the IACS-DCA combined with a learning-based gametheoretic BS ON/OFF switching in HetNet. In learning-based game-theoretic BS
ON/OFF switching algorithm, all BSs transmits the beacon signal for UE association. We use this beacon signal for instantaneous CCI measurement in IACSDCA. As a result, BS doesn’t need to transmit any additional signal for channel
segregation. We showed by computer simulation that IACS-DCA can form achannel reuse pattern in distributed manner, while following the CCI environmentchanges made by BS ON/OFF switching. Therefore, by combining IACS-DCA
and distributed BS ON/OFF switching, higher transmission quality is achieved.
Acknowledgments
The research results presented in this material have been achieved by JUNO Project#1680301 (2014.3∼2017.3) “Towards Energy-Efﬁcient Hyper-Dense Wireless Networks with Trillions of Devices”, a Commissioned Research of NICT, JAPAN.

© IEICE 2016
DOI: 10.1587/comex.2016XBL0078
Received April 10, 2016
Accepted April 28, 2016
Publicized May 27, 2016
Copyedited August 1, 2016265