Joint Passive Beamforming and User Association Optimization for IRS-assisted mmWave Systems
Dan Zhao, Hancheng Lu, Yazheng Wang, Huan Sun
Abstract
In this paper, we investigate an intelligent reflect surface (IRS) assisted multi-user millimeter wave (mmWave) downlink communication system, exploiting IRS to alleviate the blockage effect and enhance the performance of the mmWave system. Considering the impact of IRS on user association, we formulate a sum rate maximization problem by jointly optimizing the passive beamforming at IRS and user association, which is an intractable non-convex problem. Then an alternating optimization algorithm is proposed to solve the problem efficiently. In the proposed algorithm, passive beamforming at IRS is optimized by utilizing the fractional programming method and user association is solved through the network optimization based auction algorithm. We provide numerical comparisons between the proposed algorithm and different reference algorithms. Simulation results demonstrate that the proposed algorithm can achieve significant gains in the sum rate of all users.