Low-Complexity Energy Antenna Allocation for Wireless-Powered IoT Systems

To improve the performance of a wireless-powered Internet of Things (IoT) system, a multi-source wireless power transfer technique based on a multi-antenna beamforming architecture has emerged as an attractive solution. However, the distance or phase diversity among power beams from various antennas to a wireless device may degrade the energy transfer efficiency. Thus, this paper considers the energy antenna resource allocation problem in a wireless-powered IoT system with multiple wireless devices and multi-antenna energy transmitters. To maximize the system objective function such as the energy transfer efficiency, spectral efficiency, or energy spectral efficiency, we designed a greedy-based antenna allocation algorithm with polynomial time complexity by taking the distance diversity and phase differences among various energy antennas into account. According to numerous experimental tests, the proposed greedy with fine-tuning algorithm achieves a near-optimal solution while preserving very low computation complexity relative to the backtracking and dynamic programming-based algorithms. Our design makes the real-time energy antenna resource allocation in a wireless-powered IoT system feasible.