On the optimal synthesis of sparsely thinned planar array antenna with constraints using meta-heuristic optimization

The investigations related to the planar antenna array have attracted much attention due to their vast applications in the areas of advanced wireless communication and electromagnetics. This article presents an effective synthesis method of a sparsely thinned symmetric planar antenna array using three well-known meta-heuristics including symbiotic organism search (SOS) algorithm, moth fly optimization (MFO), and multi-verse optimization (MVO) algorithms. The main aim of this work is to optimize the positions of the switched-on antenna elements on the array aperture in order to reduce the value of side-lobe levels in the radiation field pattern in multiple planes for a desired first null beam width and subsequently to obtain the maximum reduced number of array-elements in the antenna array. Two different cases are performed to optimize the radiation pattern in different azimuth angles with two different examples. The proposed methods can constrain the total number of array elements, inter-element distance, and aperture area of the array. The radiation pattern characteristic and computation time linked with each example and each algorithm are recorded and compared with each other as well as with a fully populated planar symmetric rectangular array antenna of same aperture size for arriving at the conclusion. The simulation-based results demonstrate the effectiveness of the proposed design and the efficiency of the performance using the SOS algorithm.     

Meta-heuristic optimization algorithms for comparative analysis of uniform and non-uniform elliptical array antenna for enhanced gain

In this article, the synthesis of a non-uniform elliptical array antenna (EAA) is presented applying three relatively new, well-performing meta-heuristic optimization algorithms; quantum particle swarm optimization (QPSO), symbiotic organism search (SOS), and moth fly optimization (MFO) algorithms. The design objective allows simultaneous minimization of side lobes and maximization of gain by finding the best optimal combination of angular locuses of the antennas in the array structure. The proposed technique is efficient enough to resolve the underlying multi-objective problems at two principle planes of radiation and adaptable enough to the effective implementation of additional design constraints which make this design suitable for practical high-frequency applications as well as long-distance communication. The iterative accomplishment of the three algorithms is compared depending on the radiation parameters as well as statistical parameters. The outcomes are validated by performing a t test on the obtained data sets.     

Mutual coupling compensation of linear antenna array using evolutionary optimization technique

This paper presents an optimization-based approach to compensate for the mutual coupling effect and to reduce the sidelobe level (SLL) of the normalized radiation pattern by optimizing the current excitation amplitude of the antenna array elements. Due to the mutual coupling effect, the SLL of the radiation pattern is increased, and thereby, the field pattern of the antenna array is severely degraded. This causes interference with other communication systems working at the same frequency. Toward the compensation of the mutual coupling effect and reduction of SLL, the Cat swarm optimization (CSO) algorithm is employed, and the excitation amplitudes of the antenna elements are optimized. In this regard, optimizing the cost function is defined by introducing the impedance factor (IF), calculated by using the self-impedance and mutual impedance of the antenna elements. The proposed method for the synthesis of a mutually coupled linear antenna array is less expensive, simpler to use, and more effective. Array sets of 4, 6, 8, and 10 elements are considered for optimization.