Research on joint optimization of IRS-assisted UAV network

Abstract

To address the problem of obstacles blocking wireless channels and increase the transmission rate of unmanned aerial vehicle (UAV) communication systems, this paper proposes a method for maximizing the system sum rate in downlink communication networks based on intelligent reflecting surface (IRS)-assisted UAV. First, we lead into non orthogonal multiple access (NOMA) technology. Second, the system sum rate is maximized by jointly optimizing the IRS phase shift, 3D UAV trajectory, user scheduling and power allocation. Since the coupling and non-convexity of optimization variables make this problem difficult to solve directly, the original nonconvex problem is converted into four subproblems through block coordinate descent (BCD). Then, the subproblems are solved alternately using methods, such as semi-definite relaxation technique (SDR), relaxation variable introduction, successive convex approximation (SCA), the Lagrange multiplier method and first-order Taylor expansion. The results show that the algorithm proposed in this paper substantially improves the system sum rate and has favorable convergence.