# AI Optimization-Based Heterogeneous Approach for Green Next-Generation Communication Systems
## 4 Simulation Results and Discussion
Accordingly, the users left macro BSs  
Figure 4: (**a**) Data rate and (**b**) power consumption comparison between LAUA, best SINR, and SDR-LTE-LAA approaches. which utilized the licensed spectrum only to connect to small-cell BSs which had more carriers in the unlicensed spectrum or band. Subsequently, the percentage of the utilized licensed spectrum reduced. Based on our simulation results, it is evident that our proposed approach can decrease the licensed spectrum utilization per macro base station down to 20%. This reduction can be utilized in reallocating the unutilized bands or channels to other overloaded small-cell BSs to serve even more users or to other macro BSs, depending on the vendors' operating conditions. SDR is an enabler technology for this step. Figure 6 illustrates the influence of changing the small-cell BSs' number per macro BS on the average amount of saved power per the vendors' macro base stations. Based on the results in Figure 6, it is clear that increasing the small-cell BS number maximized the average amount of saved power per macro base station. This is because increasing the small-cell BS number caused an increase in the available number of unlicensed subcarriers, and this can be translated to higher achievable throughputs for the users. Accordingly, the algorithm showed a tendency to offload users toward the small-cell BSs, leaving the macro BSs. This offloading process resulted in a reduction in the traffic load at the macro base stations and, hence, their power consumption. Figure 6 also presents the influence of changing the small-cell BS number on the overall network power consumption. From the results in Figure 6, it is evident that increasing the small-cell BS number decreased the overall power consumption. This is because increasing the small-cell BS number gives more options and opportunities for users, especially users at the edge of the macro cell, to offload the far macro base station and connect to any nearby small-cell BSs. Consequently, the proposed algorithm associates users with nearby small-cell BSs, leading to less power being consumed by the BS and users for communication. Additionally, the macro base stations with no users to serve are switched to sleep mode to save power. These factors are combined together to minimize the total network's power consumption. Figure 7a,b shows comparisons between the results of the integer linear programming (ILP) solution and our heuristic solution. From Figure 7a, it is notable that our proposed heuristic results were marginally lower than those for ILP. Hence, our proposed heuristic can be utilized to obtain near-optimal performance. From Figure 7b, it is evident that our heuristic results were slightly higher than those for ILP. Thus, our proposed heuristic can be utilized to obtain near-optimal performance. Table 2 presents a summary of the findings of this work. Additionally, it compares our proposed approach with other approaches. Figure 5: (**a**) Average power consumption for different SCBSs and number of carriers. (**b**) Average licensed spectrum utilization as a function of the number of small-cell BSs and MBSs. Based on the results in Table 2, it is evident that our proposed SDR-based and LTE-LAA-supported strategy consumed less power in comparison with the other strategies by up to 17%. Regarding the total data rate, and based on the results in Table 2, our proposed strategy provides users with higher data rates and throughputs compared with the other techniques. In our proposed system, the SDR-based BSs can allocate more carriers to users by using LTE-LAA technology, which utilizes the unlicensed spectrum along with the licensed spectrum. During the performance evaluation process of our system, we found that 80% of the BSs utilized the unlicensed spectrum to increase their supported data rates and serve more users. However, the other techniques rely only on the licensed spectrum to interact with their users, which limits the available carriers and constrains the data rates and the number of serviceable users.