Moth Flame Optimization for Weight Adjustment on Phased Array Antenna

Abstract

Adaptive beamforming refers to a method to proceed a signal to improve strength and steer the main beam of smart antenna to the desired user against interferer. In a phased array antenna, the weight of each element is adapted with Weight Adjustment Moth Flame Optimization (WAMFO). The algorithm is based on Moth Flame Optimization (MFO) that is inspired by the moth making spiral move to the flame as the objective function. The objective function is to obtain the minimum difference between reference and incoming signal. The weighted sum will generate the highest power to the desired direction, and then the interferer will be set to null. The simulation resulted in a uniform linear array showing that weight adjustment with the algorithm proposed could achieve faster convergence than other metaheuristic schemes. WAMFO had the average SNR values improvement of 26 to 32 dB for 100 iterations in five different scenarios.