Resource Allocation for Multi-Cell IRS-Aided NOMA Networks

This article proposes a novel framework of resource allocation in multi-cell intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks, where an IRS is deployed to enhance the wireless service. The problem joint user association, subchannel assignment, power allocation, phase shifts design, and decoding order determination formulated for maximizing achievable sum rate. challenging mixed-integer non-linear decomposed into optimization subproblem (P1) with continuous variables matching (P2) integer variables. In effort tackle non-convex (P1), iterative algorithms are proposed allocating transmission power, designing reflection matrix, determining by invoking relaxation methods such as convex upper bound substitution, successive approximation, semidefinite relaxation. terms combinational (P2), swap matching-based developed achieving two-sided exchange-stable state among users, BSs subchannels. Numerical results demonstrate that: i) rate NOMA networks capable being increased 35% aid IRS; ii) IRS-aided can enjoy 22% higher energy efficiency than conventional counterparts; iii) trade-off between spectrum coverage area be tuned judiciously selecting location IRS.