Abstract
Today, the design of antenna arrays is very important in providing effective and efficient wireless communication. The purpose of antenna array synthesis is to obtain a radiation pattern with a low side lobe level (SLL) at a desired half power beam width in far-field. The amplitude and position values of the array elements can be optimized to obtain a radiation pattern with suppressed SLLs. In this paper, swarm-based metaheuristic algorithms including particle swarm optimization (PSO), artificial bee colony (ABC), mayfly algorithm (MA) and jellyfish search (JS) are compared to determine the optimal design of linear antenna arrays. Extensive experiments are conducted on designing 10-, 16-, 24- and 32-element linear arrays by determining the amplitude and positions. Experiments are repeated 30 times due to the random nature of swarm-based optimizers, and statistical results show that the performance of the novel algorithms, MA and JS, is better than that of the well-known PSO and ABC methods.
Highlights
With the introduction of Industry 4.0 in daily life, the Internet of Things (IoT) has gained importance and with this, the need for wireless communication has increased in every field
Mayfly algorithm (MA) and Jellyfish Search (JS) are optimization techniques recently presented to the literature and in this study these algorithms have been applied to antenna array synthesis for the first time
The optimum design of linear antenna array (LAA) with a different number of elements is realized by using swarm-based optimization methods known as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), MA and JS
Summary
With the introduction of Industry 4.0 in daily life, the Internet of Things (IoT) has gained importance and with this, the need for wireless communication has increased in every field. Generally three parameters are adjusted by optimization algorithms to obtain the desired SLL and HPBW. The synthesis of sequences with 10, 16, 24 and 32-elements, which are widely used in the literature, is carried out by four different swarm-based optimization methods Two of these meta-heuristic methods are PSO and ABC, which are used in the literature in several studies, while the other two novel optimization methods, Mayfly algorithm (MA) and Jellyfish search algorithm (JS), have been used in antenna array synthesis for the first time. To test the performance of these meta-heuristic methods in LAA synthesis; 10, 16, 24 and 32-elements is examined By using these four algorithms, the amplitude and position values of LAA elements with different numbers of elements have been found optimally.
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