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Optimizing sidelobe levels in 5G antenna arrays: a grasshopper optimization algorithm approach for enhanced network performance

Mohammadi, R ; Sharif University of Technology | 2023

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  1. Type of Document: Article
  2. DOI: 10.1109/ICCCNT56998.2023.10306923
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2023
  4. Abstract:
  5. The deployment of 5G networks requires advanced antenna technologies to meet the increasing demands for high-capacity and low-latency communication. Antenna arrays, known for their beamforming capabilities, are vital in achieving these goals. However, sidelobes in the antenna radiation pattern can introduce errors and significantly impact the system's overall performance. This paper proposes a novel beamforming optimization technique for linear antenna arrays (LLA) in 5G networks. Our approach leverages the power of metaheuristic algorithms, precisely the Grasshopper Optimization Algorithm (GOA), to optimize the array configuration and reduce the Sidelobe Levels (SLL). The main objective is to minimize the closest SLL to the main lobe, directly affecting antenna performance and frequency reuse. Simulations and statistical analysis are conducted to evaluate the performance of our proposed method. Comparative studies are carried out against well-known approaches, including Archimedes Optimization Algorithm (AOA), Chimp Optimization Algorithm (ChOA), and Sparrow Search Algorithm (SSA), in terms of sidelobe reduction. The results demonstrate our proposed approach's superior performance and effectiveness in achieving lower SLL, which positively impacts the overall antenna performance and system efficiency. This research advances beamforming strategies in 5G networks by introducing a metaheuristic-based optimization approach for LAA. The findings provide valuable insights and guidance for designing high-performance antenna systems in next-generation wireless communication networks. © 2023 IEEE
  6. Keywords:
  7. 5G ; Antenna arrays ; Beamforming ; Grasshopper Optimization Algorithm (GOA) ; Sidelobe Level (SLL)
  8. Source: 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023 ; 2023 ; 979-835033509-5 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/10306923