PGA Scheme for MAR Maximization in IRS-Assisted UAV NOMA Communication Systems

In this paper, we propose an optimization algorithm for passive reflecting unit (PRU) group allocation (PGA) aimed at enhancing the minimum average rate (MAR) of the intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV)-enabled non-orthogonal multiple access (NOMA) communication system. First, we propose a novel IRS allocation scheme and the phase control policy,i.e., the PRUs of the IRS are grouped for allocation. Then, the MAR is maximized by jointly designing the PRU group allocation and UAV power allocation. To address the multi-variable non-convex problem, we employ the block coordinate descent (BCD) method to decompose it into two subproblems. Subsequently, the subproblems are transformed into convex problems using the successive convex approximation (SCA) technique. Simulation results demonstrate that the PGA algorithm outperforms other traditional algorithms,conventional IRS allocation (CIA) with OMA, NOMA.