Abstract
In pursuit of enhancing the signal processing capabilities of antenna arrays for directed signal transmission and reception in spatial contexts, novel methodologies have been developed for advanced antenna systems. Leveraging cutting-edge technologies such as beamforming (BF) and multiple-input and multiple-output (MIMO) within smart antenna systems has emerged as a compelling strategy for elevating the quality of service, capacity, and coverage in mobile information systems. This paper presents a comparison, wherein algorithms inspired by natural processes are applied to amplitude-only controlled beamforming techniques. Subsequently, a comprehensive assessment is undertaken to discern the merits and demerits of the weight control methodologies employed. Specifically, this study delves into the application of bat algorithms, multi-verse optimization, hybrid particle swarm optimization, and gray wolf optimization in various scenarios.
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Van Luyen, T., Van Anh, N.T., Van Cuong, N., Duong, T.H., Trang, L.T. (2024). Nature-Inspired Algorithms-Based Beamforming for Advanced Antenna Systems. In: Thi Dieu Linh, N., Hoang, M.K., Dang, T.H. (eds) Ad Hoc Networks. ADHOCNETS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 558. Springer, Cham. https://doi.org/10.1007/978-3-031-55993-8_8
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