Near-Field Coverage in IRS-Aided Communications: Joint Beamforming and Deployment Optimization

Intelligent reflecting surface (IRS) is a promising technology to extend the wireless communication coverage. However, in practice, the performance gain is significant only when the IRS is of sufficiently large size, for which the conventional uniform plane wave (UPW)-based far-field model may become invalid. In view of this, this paper investigates near-field communication coverage of an IRS-aided communication system. We aim to maximize the minimum received signal-to-noise ratio in a target area, by jointly optimizing the passive beamforming and deployment for the IRS. To simply the problem, we propose a segmented-far-field channel model to approximate the intractable near-field channel. Then we propose an efficient two-stage algorithm to tackle the simplified problem. Specifically, with the proposed IRS beamforming design, the IRS deployment is in the first stage searched by balancing the approximate array gain and the multiplicative path loss, and then in the second stage, the IRS phase shifts are obtained in closed-form based on the obtained IRS deployment. Simulation results show that the proposed algorithm achieves much better coverage performance than the benchmark schemes.