Hybrid PSO-GA assisted MIMO-OFDM systems: Capacity, BER, and detector comparison using QPSK and 16-QAM under Rayleigh fading channel
Author(s): Ibrahim Beram Jasim
Abstract: Multiple-Input MIMO (multiple-input, multiple-output) technology is very important for improving the capacity and spectral efficiency of modern wireless communication systems. But to achieve the most out of a channel, you need to find the best way to set system parameters like transmit power and antenna weights. This is a very difficult optimization problem. Traditional optimization techniques frequently experience slower convergence and rapid regression at local optima. This paper proposes a hybrid Particle Swarm Optimization-Genetic Algorithm (PSO-GA) approach to maximize MIMO channel capacity and enhance BER (Bit Error rate) in an environment of Rayleigh fading. The suggested hybrid algorithm uses both the fast convergence of PSO and the global search strength of GA to make optimization work better. The simulation results demonstrate that the hybrid PSO-GA algorithm has a higher channel capacity and converges faster than the standalone PSO and GA methods, especially at moderate and high signal-to-noise ratio (SNR) levels. The findings validate that hybrid computational optimization is an effective strategy for enhancing capacity in forthcoming wireless communication systems.
Ibrahim Beram Jasim. Hybrid PSO-GA assisted MIMO-OFDM systems: Capacity, BER, and detector comparison using QPSK and 16-QAM under Rayleigh fading channel. Int J Circuit Comput Networking 2026;7(1):85-91. DOI: 10.33545/27075923.2026.v7.i1b.128
Research Journals