# Energy and Spectral Efficiency Balancing Algorithm for Energy Saving in LTE Downlinks
## 4 Performance Evaluation of the Proposed SET algorithm
### Impact of Varying Traffic Loads in Non-Congested Network  
In this experiment, a low density network with 100 pieces of UE has been used, where the UEs were uniformly distributed with an inter-eNodeB distance of 500 m. The objective here is to determine the network performance under an increasingly stressful scenario. The results of the SE, average response delay, energy consumption, and the SE-EE trade-off are illustrated in Figures 8-11, respectively. In Figure 8, a comparison between the SET algorithm and the DRX power-saving algorithm has been presented in terms of the SE, by varying the number of users from 10 to 100. The proposed algorithm significantly outperforms the DRX algorithm in all cases because the larger share of resource blocks (RBs) is not lost due to users being under good channel condition before allocating resource blocks.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline System bandwidth & 5 MHz \\ Number of resource blocks & 25 \\ Active sector of concern & eNodeB2-sector1 \\ TTI & 1 ms; 1000 TTI per second \\ UE distribution & Uniform \\ Macroscopic path loss model & TS25814 \\ Simulation period & 100 s \\ Speed of the user & 4.16 m/s \\ Transmission scheme & 2 \(\times\) 2 MIMO, OLSM \\ Cyclic prefix & Normal \\ Transmitter antenna gain & 18 dBi \\ Receiver antenna gain & 0 dBi \\ Maximum transmission power & 20 W \\ Maximum delay & 20 ms \\ Inter-eNodeB distance & 500 m \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters setup.  
Figure 6: Network topology in non-congested scenario.  
Figure 7: Network topology in congested scenario.  
blocks. As the number of users increases, the competition among users' resource blocks also increases.  
In addition, the use of transmission power to allocate resource blocks provides the proposed SET algorithm with a higher SE than that of the DRX power-saving algorithm. Furthermore, the DRX attempts to satisfy users while neglecting their conditions, which decreases its eNodeB performance.  
The average response delay of the proposed SET algorithm compared to the DRX power-saving algorithm has been illustrated in Figure 9. The average response delay of the DRX increases rapidly when the number of users increases because this algorithm does not consider the packet delay in resource block allocation. Furthermore, the proposed SET algorithm has lower average response delay than the DRX due to choosing the larger window before switching to the sleep-mode to accommodate incoming packets, which shows a significant improvement in the average response time in all cases.  
The effect on energy consumption by considering the packet arrival pattern in a non-congested network has been presented in Figure 10. Compared to the DRX power-saving algorithm, the energy consumption of the proposed SET algorithm is lower due to the ap  
Figure 8: Spectral efficiency as the number of users increases.  
Figure 9: Average response delay as the number of users increases.  
propriate adjustment of eNodeB in the initial mode. Such an adjustment is performed by predicting the downlink packet arrival that is used to update the initial state. Consequently, minimizing the number of window sleep intervals reduces energy consumption. The proposed SET algorithm can prolong battery life by 81.92% compared to only 18.08% by the DRX algorithm.  
Indeed, the proposed SET is utilized to obtain the Pareto optimal points between the SET algorithm and the DRX power-saving algorithm. In this manner, the MOP in Equation (6) is transformed to the SOP in Equation (7). As shown in Figure 11, optimal EE increases until the saturation point with an increase in the SE. The proposed algorithm achieves considerable gain compared to the DRX algorithm, with optimal points of 1.9 bit/Hz and 1.75 bit/Hz, respectively.