IMPROVING CHANNEL ESTIMATION USING BAT OPTIMIZATION TECHNIQUE

Abstract

High-speed communications are becoming more and more popular in real-world settings due to the expanding need for multimedia applications and the expansion of internet-related information. Several broadcast and receive antennas are used to create MIMO channels in order to accomplish these objectives. By the utilization of spatial multiplexing, diversity, and interference reduction among different users, MIMO networks contribute to increased system capacity and dependability. The 5G of mobile communications will use massive MIMO as an essential method to enhance important performance features such faster data costs, improved dependability, reduced latency, and increased channel capacity. To increase device’s ability and mitigate fading even more, MIMO diversity devices are merged with OFDM to form MIMO-OFDM systems. This report presents a novel approach for enhancing wireless communication in MIMO-OFDM systems using bat optimization. MIMO-OFDM is a widely adopted approach in modern wireless communication devices due to its ability to improve data rates, spectral efficiency, and overall system performance. The integration of bat optimization into MIMO-OFDM systems aims to optimize system parameters such as channel estimation, power allocation, and modulation schemes to further enhance communication efficiency and reliability. The bat approach, inspired by the echolocation behavior of bats, is introduced as a met heuristic optimization technique that offers adaptive search capabilities and flexibility in exploring the solution space. By applying the bat approach to MIMO-OFDM systems, this research focuses on maximizing throughput, minimizing interference, and improving signal quality to meet the growing demands of next-generation wireless systems. The outcomes show the effectiveness of the suggested method in obtaining significant performance gains compared to conventional optimization algorithms in MIMO-OFDM communication scenarios.