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This paper proposes a novel framework of resource allocation in multi-cellintelligent reflecting surface (IRS) aided non-orthogonal multiple access(NOMA) networks, where an IRS is deployed to enhance the wireless service. Theproblem of joint user association, subchannel assignment, power allocation,phase shifts design, and decoding order determination is formulated formaximizing the achievable sum rate. The challenging mixed-integer non-linearproblem is decomposed into an optimization subproblem (P1) with continuousvariables and a matching subproblem (P2) with integer variables. In an effortto tackle the non-convex optimization problem (P1), iterative algorithms areproposed for allocating transmission power, designing reflection matrix, anddetermining decoding order by invoking relaxation methods such as convex upperbound substitution, successive convex approximation, and semidefiniterelaxation. In terms of the combinational problem (P2), swap matching-basedalgorithms are developed for achieving a two-sided exchange-stable state amongusers, BSs and subchannels. Numerical results demonstrate that: 1) the sum rateof multi-cell NOMA networks is capable of being increased by 35% with the aidof the IRS; 2) the proposed algorithms for multi-cell IRS-aided NOMA networkscan enjoy 22% higher energy efficiency than conventional NOMA counterparts; 3)the trade-off between spectrum efficiency and coverage area can be tuned byjudiciously selecting the location of the IRS.

Resource Allocation for Multi-Cell IRS-Aided NOMA Networks