Array (Jul 2021)
Optimal receive beamforming in spatial antenna diversity system using evolutionary genetic algorithm
Abstract
Frequent packet loss and power inadequacy are the major issues in wireless fading networks owing to the deep fading effects and inefficient resource utilization caused by unoriented information forwarding mechanisms. Diversity techniques are potentially employed in wireless communication systems to combat the impact of fading and reinforce the desired service level guarantees for data transmission. In this work, we employ spatial diversity and antenna beamforming methods to significantly improve the signal quality performance of wireless networks and enhance the reliability by decreasing the bit error probability. A constrained optimization problem is formulated for alleviating the net noise power integrated with the adaptive beamforming vector and ameliorated channel state information. For this, the evolutionary genetic algorithm scheme is iteratively implemented for evaluating the optimal solution of the proposed optimization problem. The influence of various selection functions in the application of genetic algorithm is investigated for effective heuristic modeling design and searching through the feasible solution space. Through extensive simulation results, several crucial network parameters characterizing the proficiency of wireless communications including the noise power, signal-to-noise ratio (SNR), bit error rate (BER) are estimated and analyzed for varying number of antennas deployed at the receiver node. Furthermore, the performance of the proposed genetic algorithm based optimization technique is compared with the existing models using the key channel quality metrics of achievable SNR, BER, and model computational complexity.
