Next-generation antenna beamforming via caterpillar fungus optimization for enhanced wireless communication

作者：Farghaly SI, Gafar M, Shaheen AM, Alwakeel AS, Sarhan S · 发表于：Scientific reports · 年份：2026 · DOI：10.1038/s41598-026-55840-y · 被引用次数：102 · 研究领域：Antenna array synthesis、Beamforming、Caterpillar fungus optimization、MIMO、Side lobe levels、Uniform linear array.

Beamforming has emerged as an essential enabling technique for beyond 5G and future 6G systems because it improves spectral efficiency. However, optimizing antenna weights in beamforming is a highly nonlinear and multidimensional problem that traditional approaches struggle to solve. To address this, we offer a unique beamforming strategy based on the Caterpillar Fungus Optimization (CFO) algorithm, which strikes an optimal balance between exploration and exploitation, making it ideal for large-scale antenna systems. The CFO is inspired by the rare lifecycle of caterpillar fungus considering its soil exploration and parasitic behaviors. Its unique blend of wave-like and spiral search strategies, dual parasitism operators, and hybrid noise-handling makes it stand out among bio-inspired algorithms, enabling high accuracy and robustness in complex engineering optimization problems. The proposed scheme has two goals: first, to reduce the number of active antenna elements, thereby improving energy efficiency and reducing system complexity; and second, to suppress side lobe levels (SLL), which mitigate interference and improve communication performance. To assess its efficacy, the CFO-based method is compared to five established algorithms: Artificial Rabbits Optimizer (ARO), Whale Shark Optimization (WSO), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), and Boomerang Aerodynamic Ellipse (BAE). According to simulation data, CFO maintains beamwidth deviations within 1%...