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In the case of antenna arrays, researchers usually neglect the effect of mutual coupling of antennas placed in proximity to each other. The interchange of electromagnetic energy between an antenna and a far-field point depends on not only the transmitting antenna, but also its neighboring antennas. This effect is referred to as mutual coupling between dipole antenna elements and is considered here in the synthesis of phase-only reconfigurable antenna arrays. The main objective of this work is to produce the desired side lobe level and voltage standing wave ratio, in addition to few other radiation pattern parameters. Multi-verse Optimization algorithm is employed for the purpose of generating voltage amplitude and discrete phase distributions in the dipole elements to generate attop beam/pencil beam patterns. These two patterns share common amplitude distributions and differ in phase distributions. Results of simulations proved that this algorithm accomplished its task successfully and was superior to other algorithms like particle swarm optimization, grey wolf optimization, and imperialist competitive optimization algorithms. [ABSTRACT FROM AUTHOR]

This paper describes the synthesis of digitally excited pencil/flat top dual beams simultaneously in a linear antenna array constructed of isotropic elements. The objective is to generate a pencil/flat top beam pair using the excitations generated by the evolutionary algorithms. Both the beams share common variable discrete amplitude excitations and differ in variable discrete phase excitations. This synthesis is treated as a multi-objective optimization problem and is handled by Quantum Particle Swarm Optimization algorithm duly controlling the fitness functions. These functions include many of the radiation pattern parameters like side lobe level, half power beam width and beam width at the side lobe level in both the beams along with the ripple in the flat top band of flat top beam. In addition to it, the dynamic range ratio of the amplitudes excitations is set below a certain level to diminish the mutual coupling effects in the array. Two sets of experiments are conducted and the effectiveness of this algorithm is proved by comparing it with various versions of swarm optimization algorithms. [ABSTRACT FROM AUTHOR]