Joint Placement and Beamforming Design for IRS-Enhanced Multiuser MISO Systems

Abstract

The fundamental intelligent reflecting surface (IRS) deployment problem is studied for IRS-aided downlink multi-user communication system, where IRSs are arranged to be deployed in a specific area for enhancing the desired signal and suppressing interference. Specifically, we aim to maximize the minimum achievable rate over all locations in a specific area by jointly optimizing the transmit beamforming at the access point (AP) as well as the placement and reflective beamforming at the IRS. The formulated problem is non-convex and thus difficult to be solved directly. To draw essential insights, we first consider the single-user case and the optimal solution is derived in closed-form. The result shows that the optimal locations are in the connecting line between the AP and user, and the IRSs can be optimally deployed along the connecting line. Besides, a hybrid offline and online design scheme is developed for the multi-user case, where an area discretization strategy and deep neural network (DNN)-based curve fitting technique are proposed for optimizing the IRS locations in the offline manner. Then, an online iterative algorithm is presented to solve the transmit and received beamformig vectors, respectively. Numerical results show that the performance gain is increased by optimizing the IRS locations.