Optimized Scheduling and Beamforming for Enhanced Efficiency in Wireless Powered IoT Networks

Abstract

Wireless powered communication networks (WPCNs) have emerged as a vital technology for enabling sustainable Internet of Things (IoT) systems, particularly in the context of the forthcoming 6G era. WPCNs offer a promising solution to the challenge of powering a large number of energy-constrained IoT devices by wirelessly transmitting energy while concurrently managing data communications. However, optimizing energy efficiency (EE) in the downlink and information efficiency (IE) in the uplink remains a critical challenge in these networks. In this paper, we propose a novel scheduling framework to optimize energy efficiency (EE) in the downlink and information efficiency (IE) in the uplink of a WPCN with a hybrid access point (H-AP) and multiple IoT devices. Our approach reduces beamforming complexity by grouping devices based on location for wireless energy transfer (WET) and introduces a location-aware scheduling method for wireless information transfer (WIT) that minimizes interference using a hybrid NOMA-TDMA scheme. We also optimize time allocations between WET and WIT to enhance overall system efficiency. Simulation results demonstrate the superior performance of our framework, significantly improving both EE and IE compared to existing methods.