Intelligent reflecting surface assisted transmission optimization strategies in wireless networks

Abstract

Wireless Power Transfer (WPT) technology can provide real-time power for many terminal devices in Internet of Things (IoT) through millimeter Wave (mmWave) to support applications with large capacity and low latency. Although the intelligent reflecting surface (IRS) can be adopted to create effective virtual links to address the mmWave blockage problem, the conventional solutions only adopt IRS in the downlink from the Base Station (BS) to the users to enhance the received signal strength. In practice, the reflection of IRS is also applicable to the uplink to improve the spectral efficiency. It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission. In this paper, we first design a Low-Energy Adaptive Clustering Hierarchy (LEACH) clustering protocol for clustering and data collection. Then, the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices, the uplink and downlink transmission times, the active beamforming at the BS, and the IRS dynamic beamforming. To solve this non-convex optimization problem, we propose an alternating optimization (AO)-based joint solution algorithm. Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system, and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.