Optimizing beamforming in IoT-WET: A symbiotic-based approach under imperfect channel state information

Abstract

This study delves into the energy optimization problem in low-power Internet of Things (IoT) networks utilizing wireless energy transfer (WET) technology. In such IoT systems, conventional optimization schemes relying on complete knowledge of channel state information (CSI) are often irrelevant for practical implementation due to their high complexity and energy consumption. To address this challenge and enhance the fairness of energy harvesting among IoT devices with imperfect CSI, we propose a novel beamforming design based on the symbiotic organisms search (SOS) algorithm. Through comprehensive numerical analysis, we demonstrate the effectiveness of our proposed scheme in terms of computational complexity, convergence speed, and energy harvested at each IoT device. The results highlight the significant advantages of our approach compared to conventional methods, paving the way for practical and efficient energy optimization in IoT networks.