# Binary PSO with Classification Trees Algorithm for Enhancing Power Efficiency in 5G Networks
## 2 Literature Review  
Recently, immense research has been carried out to ameliorate the PE of the mod-em communication networks, such as satellite and terrestrial networks [15; 16], massive MIMO systems [17] and SCs networks [18; 19; 20; 21; 22; 23]. SC on/off switching is an auspicious approach to minimize the power consumption and enhance the PE of the system [18; 19; 20; 21; 22; 23]. The authors in [18; 19] studied the elevated the energy consumption of WLAN. They proposed solving the problem by on/off switching and power adjustment of the access stations. The authors in [20] proposed a load-aware strategy, where SCs in HetNets are switched to sleep mode according to their load level. In [21], every SC independently switches off upon the decrease in the number of user equipments (UEs) and activates using one of three approaches. The first approach is the sleeping SC keeps sensing the interference plus noise levels and switches on when a new UE is sensed in its coverage area. The second approach is that the MC sends a wake-up request to all SCs upon increasing the number of UEs associated with the MC, then switches off the SCs with no UEs later. In the third approach, a time advance indicator is sent to the MC by the UEs and the SCs and is utilized by the MC to determine the nearest SC to the UE to switch on. In [22], pre-sleeping SCs at the same zone create a sleeping cluster. Then, the SCs in the sleeping cluster are randomly selected to be switched off leaving only one active SC to guarantee the coverage. On the other hand, the authors in [23] proposed switching off the SCs and handing over the UEs to the MC. However, the unplanned SC off switching may increase the unnecessary handovers and underutilize the SCs. Thus, novel SC on/off switching techniques are required to enhance the performance of the 5G HetNets and to reduce the power consumption of the system. PSO is a prevalent meta-heuristic algorithm used in solving optimization problems [9]; thus, the authors in [9; 24; 25] utilized the PSO algorithm for SC switching to enhance the performance of the system. The authors in [9] proposed an efficient cell modeling (ECM) algorithm to set up the connection initially between the UEs and the SCs by selecting the strongest received signals. Then, the BPSO algorithm is utilized to turn off the excessive SCs. The authors in [24] proposed first utilization of BPSO algorithm to choose the MCs' optimum locations not only to achieve minimum overlap but also to guarantee a reasonable coverage for the UEs. Then, a multi-stage PSO (MS-PSO) algorithm consisting of two interactive loops are utilized. The outer loop is utilized to switch the SCs (on or off), while the inner loop is utilized to optimize the active power of the SC and to elevate the power of the SC if the data rate rises. On the other hand, a combined optimal frequency and power allocation (COFPA) scheme is proposed in [25]. First, using the BPSO algorithm, the MCs are switched on and off until the lead interferer is abolished with minimum cost function and with a reasonable coverage to the UEs. Then, the MS-PSO algorithm is utilized to control the SC switching to mitigate the interference and minimize the power consumption. However, the convergence of the PSO can be enhanced by adjusting its IW, leading to improve the system performance. IW has a significant role in the process of offering a trade-off among diversification and intensification skills of PSO algorithm. Reducing the IW facilitates exploring the search space (global search), although raising the IW aids exploiting the search space (local search) [26] to find the solution (particle). Numerous approaches are presented to adjust the IW such as the constant IW [9; 27] and the random IW [28]. However, the constant IW approach can fail to balance exploration and exploitation because of the lack of adjustment of IW [29; 30]. On the other hand, the authors in [31] propose a linearly decreasing IW technique where the IW is initialized at a larger value; then it is linearly reduced to a smaller value.