Intelligent Reflecting Surface-Assisted Over-the-Air Computation for Backscatter Sensor Networks

Abstract

For achieving efficient data aggregation and energy supply in Internet of Things, this paper investigates the optimal design for an intelligent reflecting surface (IRS)-aided backscatter sensor network with over-the-air computation (AirComp). To ensure the accuracy of data aggregation, this paper presents a mean-squared error (MSE) minimization problem via jointly optimizing the normalization factor, power splitting ratios of backscatter devices (BDs), and phase shifts of IRS. Inspired by the block coordinate descent technique, we propose an alternating optimization method to solve the formulated non-convex problem. Specifically, we derive the optimal normalization factor and power splitting ratios in closed-form expressions, and exploit the variable substitution technique and semi-definite relaxation method to address the phase shift optimization subproblem. Simulation results demonstrate the significant MSE reduction achieved by the proposed method, in comparison with other benchmark methods.