Joint Beamforming and Phase Shift Design in Downlink UAV Networks with IRS-Assisted NOMA
Shiyu Jiao, Fang Fang, Xiaotian Zhou, Haixia Zhang
Abstract
This paper investigates a simple design of intelligent reflecting surface (IRS) based unmanned aerial vehicles (UAV) assisted multiple-input single-output nonorthogonal multiple access (NOMA) downlink network. The aim of this paper is to maximize the rate of the strong user while guaranteeing the target rate of the weak user given by the optimized UAV horizontal position. We first optimize the location of IRS-UAV. Then we propose an iterative algorithm to optimize the transmit beamforming and phase shift of IRS alternatively. For the beamforming optimization, the closed-form expressions of the optimal beamforming vectors are derived. Then, given by the obtained beamforming, we propose two methods to obtain the optimal phase shifting of IRS. One is the semidefinite relaxation based iteration algorithm which provides high data rate and the other one is based on successive convex approximation technique which has low complexity. Finally, simulation results are provided to show that the performance of the two proposed algorithms are significantly better than using random phase shifting scenario and IRS based UAV-assisted orthogonal frequency-division multiple access scheme.