Massive Multiple-Input-Multiple-Output 5G Wireless Network using Multiple Objective Self-Organizing Sand Cat Swarm Optimization

The establishment of a fifth-generation (5G) Wireless Network (WN) is a worldwide effective research area. The network of 5G allows significant upgrades with the current system of wireless. While the combination of Massive Multiple-input-Multiple-Output (MIMO) in WN enables one to meet 5G technical network necessities, it can manage various difficulties to enhance performances. In this research, a multiple objective Self-Organizing Sand Cat Swarm Optimization (SOMSCSO) approach is proposed to address multiple objective functions like average user rate, average area rate, the efficiency of energy, and Spectral Efficiency (SE) of 5G WN with Massive MIMO. Then, the fuzzy decision maker is employed for choosing a solution vector to acquire the best compromising outcomes. When compared to the existing approach like Self-organizing Particle Swarm Optimization (SOMPSO), the proposed SOMSCSO approach achieves better performance of 30.451 (Mbps/user), 53.487 (Gbps/km
²
), 12.547 (Mbits/J), 49.567 (bps/Hz), and 25.89 sec in F
1
, F
2
, F
3
, F
4
and computational time respectively.