Employing antenna selection to improve energy efficiency in massive MIMO system based on optimal selection of resources

Abstract

Multiple-Input Multiple-Output (MIMO) techniques require a “large number of Base Stations (BSs) and antennas to efficiently serve a large volume of users.” Antenna selection is important for solving the issues of increased costs of Radio Frequency (RF) chains and significant power consumption. The primary objective of the proposed work is to consider a BS with an “optimal number of antennas” to minimize the power utilization of the MIMO system. Therefore, an improved MIMO system is developed using optimal selection of antennas and resource utilization to maximize Spectral Efficiency (SE) and Energy Efficiency (EE). The SE and EE of the system are increased by optimally selecting the active antennas and resources required for the operation using the Hybrid Secretary Bird with Duck Swarm Algorithm (HSB-DSA). Thus, the proposed MIMO system uses adaptive algorithms to dynamically select the active antennas “based on real-time channel conditions and system” requirements, and this optimal allocation is “used to improve the performance” and efficiency of wireless transmission networks. To ensure the reliability of the improved model, performance analyses are conducted on the improved optimal antenna selection and resource utilization model with different encoding and modulation techniques. The encoding techniques of “Space-Time Block Code (STBC) such as Alamouti,” Golden, and Silver are taken for the experimentation, and the modulation techniques including $2\times 2$ and $4\times 4$ Differential Chaos Shift Keying (DCSK) are taken for the experimentation to ensure the effectiveness of MIMO systems in terms of throughput and data rate under diverse channel conditions.