# Energy Efficient IoT Data Collection in Smart Cities Exploiting D2D Communications
## 3 Reference System Model  
The reference scenario in this paper is a small-scale area belonging to a Smart City environment with a single LTE-A cell coverage where several IoT devices are deployed. A User Equipment (UE) in an LTE-A network can either communicate through the serving eNodeB (_i.e._, cellular mode) or it can bypass the eNodeB and use direct communications over D2D links (_i.e._, D2D mode). In this latter case, the eNodeB is in charge of the D2D session setup (e.g., bearer setup) [44], while power control and resource allocation procedures on the D2D links can be executed either in a distributed or in a centralized way [45]. In this paper, we assume a network-assisted D2D communications, where the coordination between radio interfaces is controlled by the LTE-A base station (_i.e._, the eNodeB). In particular, the transmission mode (_i.e._, either cellular- or D2D-mode), interference management and scheduling tasks are all managed by the eNodeB. Uplink cellular resources are allocated to D2D communications, which is a common choice in the literature [46], because it makes frequency reuse less challenging as the introduced interference is significantly lower w.r.t. the use of downlink resources.  
The eNodeB is in charge to manage the spectrum by assigning the adequate number of Resource Block (RB) pairs to each scheduled UE and by selecting the MCS for each RB pair. Scheduling procedures are based on the _Channel Quality Indicator_ (CQI) computed by the eNodeB based on the signal-to-interference-plus-noise ratio (SINR) feedback transmitted by a UE to the eNodeB. The CQI is associated to a maximum supported MCS as specified in [11] (see Table 1). This procedure is required every time a UE is accessing the LTE systems. To handle the variations of the radio channel conditions, the Adaptive Modulation and Coding (AMC) mechanism adjusts the transmission rate by selecting the proper MCS. The MCS parameters can be adapted at every _CQI Feedback Cycle_  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**CQI** & **Modulation** & **Efficiency** & **Min. Rate** & **Efficiency** & **Min. Rate** \\
**Index** & **Scheme** & **D2D** & **D2D** & **Cellular** & **Cellular** \\  & & **(bit/s/Hz)** & **(kbps)** & **(bit/s/Hz)** & **(kbps)** \\ \hline
1 & QPSK & 0.1667 & 28.00 & 0.1523 & 25.59 \\
2 & QPSK & 0.2222 & 37.33 & 0.2344 & 39.38 \\
3 & QPSK & 0.3333 & 56.00 & 0.3770 & 63.34 \\
4 & QPSK & 0.6667 & 112.00 & 0.6016 & 101.07 \\
5 & QPSK & 1.0000 & 168.00 & 0.8770 & 147.34 \\
6 & QPSK & 1.2000 & 201.60 & 1.1758 & 197.53 \\
7 & 16-QAM & 1.3333 & 224.00 & 1.4766 & 248.07 \\
8 & 16-QAM & 2.0000 & 336.00 & 1.9141 & 321.57 \\
9 & 16-QAM & 2.4000 & 403.20 & 2.4063 & 404.26 \\
10 & 64-QAM & 3.0000 & 504.00 & 2.7305 & 458.72 \\
11 & 64-QAM & 3.0000 & 504.00 & 3.3223 & 558.72 \\
12 & 64-QAM & 3.6000 & 604.80 & 3.9023 & 655.59 \\
13 & 64-QAM & 4.5000 & 756.00 & 4.5234 & 759.93 \\
14 & 64-QAM & 5.0000 & 840.00 & 5.1152 & 859.35 \\
15 & 64-QAM & 5.5000 & 924.00 & 5.5547 & 933.19 \\ \hline \hline \end{tabular}
\end{table}
Table 1: CQI-MCS mapping for D2D and cell-mode communication links.  
(CFC), which can last one or several Transmission Time Intervals (TTIs) (_i.e._, 1 ms). Each radio resource includes two logical parts: the Transport Block (TB) carrying the Medium Access Control (MAC) header and the Service Data Unit; and the overhead consisting of redundancy bits generated by physical layer processing such as Cyclic Redundancy Check (CRC) insertion and channel coding. The TB Size (TBS) depends on the selected MCS. It is worth noting that when the largest available modulation scheme (64-QAM) is used, _i.e._, when the channel quality if very good, the largest TBS can convey up to 712 bits of payload [14], which is well beyond the typical data size for most IoT applications, thus leading to low efficiency in the use of radio resources. The spectral efficiency expressed in \(bit/s/Hz\) for each MCS is reported in Table 1.