Constructive Interference Precoding for IRS-NOMA Networks

Ke Cui, Wei Wang, Chao Dong, Nan Zhao, Qihui Wu, Dusit Niyato

Abstract: Owing to the ability of reconfiguring wireless channels, intelligent reflecting surface (IRS) can help non-orthogonal multiple access (NOMA) to release its tremendous potential. However, the inter-user interference becomes the bottleneck of IRS-NOMA networks. To tackle this challenge, we propose two constructive interference precoding (CIP) based countermeasures in this paper for interference exploitation in IRS-NOMA networks. Specifically, the first scheme makes the residual interference from higher-order users (HUs) be constructive to lower-order users (LUs), so that the interference-free decoding can be achieved. While the second scheme directly utilizes the interference from LUs for the signal reception of HUs to avoid successive interference cancellation (SIC). The transmit power is minimized by jointly optimizing the BS active beamforming and the IRS passive beamforming for the two schemes, subject to the signal-to-interference-plus-noise ratio (SINR) requirement of each user, SIC decoding constraints, constructive condition and IRS unit-modulus constraint. Due to the coupled variables and non-convex constraints, we first decompose each problem into two subproblems, and then apply successive convex approximation (SCA) to convert them into convex ones. Finally, an alternating optimization (AO) based algorithm is proposed to solve the two convex subproblems for each scheme iteratively. Simulation results are presented to show the superiority and applicability of the proposed schemes compared to benchmarks.

External IDs:dblp:journals/twc/CuiWDZWN25