Joint User Pairing and Power Allocation With Compressive Sensing in NOMA Systems

In this letter, we propose a novel low-complexity user pairing (UP) and power allocation (PA) technique utilizing the compressive sensing (CS) theory for non-orthogonal multiple access (NOMA) systems. In the proposed scheme, we formulate the joint UP and PA optimization problem in NOMA systems as a relaxed sparse l(1)-norm problem, based on the fact that a limited, i.e., `sparse,' number of users has to be paired among a large number of users over a dedicated resource block (RB). By exploiting this inherent sparsity property, we can obtain a near-optimal solution by relaxing the original NP-hard problem of joint UP and PA. Then, a CS technique is proposed to find a solution for the relaxed problem. Simulation results validate the effectiveness of our proposed idea regarding the sum-rate and the reduced complexity compared to the state-of-the-art schemes.