Joint Power Allocation and Phase Shift Design for IRS-aided NOMA-URLLC Systems

Abstract

This paper investigates the resource allocation algorithm for intelligent reflecting surface (IRS) aided nonorthogonal multiple access (NOMA) networks, where a base station (BS) serves a set of ultra-reliable low-latency communication (URLLC) users. An IRS is deployed between the BS and users to enhance the reliability of the communication channel by reflecting the signal from the BS to users. A weighted sumrate maximization problem that jointly optimizes transmission power allocation of the BS and reflection coefficients of the IRS is formulated. The optimization problem is non-convex and finding the globally optimal solution entails high computation complexity. A low complexity suboptimal algorithm is proposed by exploiting successive convex approximation (SCA) and semi-definite relaxation (SDR). Numerical results show that the proposed algorithm converges to a suboptimal solution after a few iterations and achieves better performance than other baseline schemes.