Social Emotional Optimization Algorithm for Beamforming of Linear Antenna Arrays

Antenna array optimization in electromagnetics has thrown a growing influence on the communication systems. In this paper, a novel meta-heuristic search method based on social emotional optimization algorithm (SEOA) are applied to determine the best optimal current excitation weights and optimal inter-element spacing of optimized hyper beamforming of linear antenna arrays. Hyper beam is derived from sum and difference beam patterns of the array, each raised to the power of a hyper beam exponent parameter. SEOA is a population-based stochastic optimization algorithm where each individual simulates one natural person. All individuals communicate among them through cooperation and competition to increase the social status. The winner with the highest status is the final solution. As compared to uniformly excited linear antenna array with inter-element spacing of lambda/2, conventional non-optimized hyper beamforming and optimal hyper beamforming of the same obtained by FFA [18], SEOA applied to the hyper beam of the same array can achieve much greater reduction in SLL and same or less first null beam width (FNBW), keeping the same value of hyper beam exponent parameter. The whole experiment has been performed for 10-, 14-, and 20-element linear antenna arrays.