Lyapunov Drift-Plus-Penalty Based Resource Allocation in IRS-Assisted Wireless Networks with RF Energy Harvesting

Abstract

We propose a resource allocation policy for intelligent reflective surface (IRS)-assisted wireless powered communication network (WPCN) where the energy harvesting (EH) users (EHUs) have finite energy storage and data buffers, for storing the harvested energy and the input (sensory) data, respectively. The IRS reflecting coefficients for uplink and downlink are chosen to focus the beam towards a specific EHU, but have additional constant phase offsets (different for uplink and downlink) in order to account for the direct link between the base station and the IRS targeted EHU, and the influence to the EH process of other EHUs in downlink. The EHUs acquire data from their sensors, receive energy in downlink and send information in uplink. We maximize the overall average amount of sensor information in the WPCN by optimizing the IRS reflecting coefficients for the downlink transmissions, the amount of acquired sensor information and the duration of the information transmission period for each EHU in each epoch using the Lyapunov drift-plus-penalty optimization technique. The simulation results demonstrate the effectiveness of the proposed solution.