Robust Distributed Beamforming for Energy-Efficient Wireless Power Transfer in Wireless Sensor Networks

Wireless energy transfer (WET) has emerged as a promising solution to address energy supply challenges in wireless sensor networks (WSNs), with applications that span the agriculture, industry, and military domains. However, conventional WET approaches often suffer from low energy efficiency and significant power loss, especially in long-distance and static transmission scenarios. To overcome these limitations, this paper presents a robust distributed beamforming (DB)-based WET method tailored for energy-constrained WSNs. An adaptive hybrid optimization algorithm is introduced to dynamically adjust node parameters, effectively enhancing energy transmission efficiency while suppressing the maximum sidelobe level (MSLL) in antenna arrays. Simulation results demonstrate that, compared to conventional methods, IBPSO-IGA significantly improves the efficiency of energy transmission across various antenna array configurations, achieving a 22.3% increase in circular antenna arrays, 5. 1% in linear arrays and 10. 2% in random arrays. Moreover, the proposed scheme maintains strong robustness under noisy conditions, validating its applicability to real-world environments. These results highlight the potential of distributed beamforming as a scalable and energy-efficient WET solution for next-generation sensor networks.