# AI Optimization-Based Heterogeneous Approach for Green Next-Generation Communication Systems
## 4 Simulation Results and Discussion
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter’s Name** & **Value** \\ \hline Frequency of the Carrier & 1.9 GHz \\ Bandwidth of the Channel & 11 MHz \\ Number of Licensed Subcarriers & 64 \\ Bandwidth of Each Subcarrier & 78 KHz \\ Capacity of the Traffic Model & Full Buffer \\ Macro BS Power Consumption & 20 W \\ SCBS Power Consumption & 5 W \\ Total Number of MBs & 3 \\ Total Number of SCBSs & 7 \\ Overall Coverage Area & 5 km \(\times\) 5 km \\ Path Loss Model & 3 GPP TR 36.814 \\ Allocation of the Spectrum & Partitioned \\ Transmitter Gain & 1 dB \\ Receiver Sensitivity & \(-97\) dBm \\ Noise Power Level & \(-104\) dBm \\ Antenna Pattern & Omnidirectional \\ Antenna Feeder Loss & 3 dB \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters used in simulation [33; 58; 59]. Figure 3: Hypothetical SDR-based system deployment. communicating power consumption. However, the LAUA and B-SINR approaches tended to assign users to the BSs which belonged to the users' operators and had lower loads or the best SINR, respectively. This happened irrespective of the distance between the user and the BS and resulted in some small-cell BSs becoming overwhelmed rather quickly, and fewer subcarriers per user could be achieved. Hence, our proposed approach performed better in terms of the total achieved data rate. Figure 4b demonstrates a comparison between the total power consumption in our proposed approach and the other two approaches under a different number of users. Based on the results shown in Figure 4b, it is evident that the users consumed less power in our approach compared with the best SINR and LAUA approaches. This is because the other two approaches (best SINR and LAUA) assigned users only to their vendors' BSs and based on the SINR or load on the BSs. Hence, they consumed more power to reach their vendors' BSs and not to the closest BSs, as in our approach. From Figure 4a,b, it is clear that our proposed approach showed a tangible enhancement in terms of power savings and throughput in comparison with the best SINR and LAUA approaches. Furthermore, the SDR technology made the access network more flexible and helped the BSs to adapt to the transmission parameters according to the users' locations and their required data rate. It is worth noting that in some cases, some base stations enter a situation where no users have been allocated to them. In such a situation, the sleeping mode concept can be utilized to reduce the overall network power consumption. In our work, we also investigated the influence of changing the number of SDR-based BSs and the amount of their available unlicensed bands on our proposed approach. Figure 5a presents the influence of changing the number of subcarriers in the unlicensed band on the average power consumption per macro base station. We studied the impact under a different number of small-cell BSs. From Figure 5a, it is clear that increasing the number of subcarriers resulted in a decrease in the macro BS's average power consumption. This happened because when the number of subcarriers at small-cell BSs increased, more subcarriers became available at the SCBSs, and the system tended to offload users from macro base stations to the nearest SCBSs to achieve higher throughputs. This resulted in less traffic at the macro BSs, and consequently, the macro BSs consumed less power. Figure 5b displays the influence of changing the number of small-cell BSs per macro BS on the utilization of the macro BSs' licensed spectrum. From Figure 5b, it is clear that an increase in the number of small-cell BSs decreased the utilization of the macros' licensed spectrum. This reduction occurred because the small-cell BSs supported the LTE-LAA architecture; hence, they utilized the unlicensed bands along with the licensed band to exchange data with nearby users, which alleviated the traffic through the licensed spectrum. Moreover, the proposed algorithm tended to assign users to small-cell BSs which had the highest subcarrier number in the unlicensed band.