Abstract
Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples of SI algorithms have been selected and thoroughly described, namely the Grey Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA), and the Salp Swarm Algorithm (SSA). Firstly, the selected SI algorithms are reviewed in the literature, specifically for optimization problems in antenna design. Secondly, a comparative study is performed against widely known test functions. Thirdly, such SI algorithms are applied to the synthesis of linear antenna arrays for optimizing the peak sidelobe level (pSLL). Numerical tests show that the WOA outperforms the GWO and the SSA algorithms, as well as the well-known Particle Swarm Optimizer (PSO), in terms of average ranking. Finally, the WOA is exploited for solving a more computational complex problem concerned with the synthesis of an dual-band aperture-coupled E-shaped antenna operating in the 5G frequency bands.
Highlights
Fifth Generation (5G) technology is being deployed worldwide and its arrival brings a technological breakthrough in mobile and cellular communications [1]
The spectrum of 5G is classified into two frequency regions, (a) the Frequency Range 1 (FR1) which includes frequency bands similar to 5G’s predecessor (4G) as well as the sub-6 GHz frequency bands up to 5 GHz and (b) the Frequency Range 2 (FR2) that includes frequency bands in the millimeter-wave range from 24.25 GHz to 40 GHz. 5G technology requires antennas with small size, Multiple Input Multiple Output (MIMO) structures, and wideband operation [4,5], characterized by medium or high complexity since they require a considerable number of parameters to define their geometry
We can deduce that the Grey Wolf Optimizer (GWO) achieves the best 50% percentile of the cost function compared to the rest of the algorithms values
Summary
Fifth Generation (5G) technology is being deployed worldwide and its arrival brings a technological breakthrough in mobile and cellular communications [1]. Microstrip patch antennas have been extensively and widely applied in a plethora of wireless communications systems due to their comparative advantages [6]. Among all, these include low-cost prototyping, low design profiling, versatility, compatibility with integrated circuit technology, and easiness in fabrication [7]. With the advent of 5G communication systems, microstrip patch antennas are considerable and well-promising candidates for providing efficacious solutions in cross-haul network architectures. Within this context, meta-heuristic algorithms can be effectively used by reformulating the synthesis problem of designing an antenna as an optimization one. This is one of many and various problems in electromagnetics that needs efficient and reliable computational tools based on meta-heuristic techniques
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