# Energy Efficient IoT Data Collection in Smart Cities Exploiting D2D Communications
## 5 Performance Evaluation  
A simulative analysis has been conducted by using Matlab(r) to assess the performance of the D2D-based scheme proposed for the IoT data collection and to show its superior performance compared to the standard operation of LTE-A. In particular, we will compare three alternative solutions: (i) \(LTE\)-\(A\) standard solution, where the devices upload their own data through unicast link towards the LTE eNodeB; (ii) \(LTE\)-\(EE\) solution, where the devices implement the energy efficient solution presented in [14] on standard LTE unicast links towards the eNodeB; and (iii) \(D2D\)-\(EE\) solution, which is the proposed solution in this paper based on energy efficient D2D communications within clusters of devices and energy efficient unicast cellular transmissions from the cluster aggregator to the eNodeB. The key performance indicators considered in this analysis are (i) the _Transport Block utilization_; and the (ii) the _energy efficiency_.  
The simulated scenario consists of an LTE eNodeB with a coverage radius equal to 250 m. In particular, the IoT devices are uniformly deployed within the LTE coverage and running the same application (e.g., smart parking, traffic congestion, smart roads, environment monitoring, weather conditions monitoring and so on). For the sake of simplicity, we assume that all the devices have to forward the same sensing data to a remote server (_i.e._, Cloud) through the LTE eNodeB. In addition, different transmission power levels have been considered for the transmission modes used by the devices: (i) a transmitted power of 23 dBm is considered for standard LTE cell-mode uplink transmissions; whereas (ii) a power equal to 10 dBm if the devices use the D2D link [51]. Furthermore, the D2D coverage has been fixed to 50 m [49]. The focus is on a single TTI; for data requiring multiple TTIs, the same solution is applied in consecutive TTIs. Channel conditions for the UEs have been evaluated in terms of SINR experienced over each sub-carrier when path loss and fading phenomena affect the signal reception [52]. The performance analysis has been conducted by following the guidelines for the system model defined in [48] and for a number of available RBs \(R=100\) per cell, a varying data size per device to be uploaded in the [10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45;  
When considering, instead, a varying number of devices with a data size set to 10 bytes, we observe that larger number of devices make the energy efficiency increase only for the D2D-EE solution and has no impact on the LTE-A and LTE-EE solutions, see Figure 5b. At its maximum value, with 500 devices, the D2D-EE is about 6 times more efficient than the LTE-EE and about 11 times more efficient than the LTE-A solution. This very important results derive from the three contributions in the D2D-EE solution: low transmission power on D2D links, optimal energy efficient MCS selection on every D2D link within a cluster, and optimal energy efficient MCS selection in the uplink from the aggregator to the eNodeB.