Compressive Sensing Based Spectrum Allocation and Power Control for NOMA HetNets

Abstract

In this paper, a novel interference management technique based on compressive sensing (CS) theory is investigated for downlink non-orthogonal multiple access (NOMA) heterogeneous networks (HetNets). We mathematically formulate the interference management problem in terms of power and resource blocks (RBs) allocation to maximize the overall sum rate while considering both co-tier and crosstier interferences and then explain its non-convexity. In this paper, we exploit the sparsity of the allocated RBs to relax the non-convexity of the formulated problem by transforming it into a sparse l1-norm problem for a near-optimum solution. Then, based on the CS theory, an interference management technique with a restricted weighted fast iterative shrinkage-thresholding (R-WFISTA) algorithm is proposed to solve the equivalent sparse l1-norm problem. The simulation results verify that compared with the conventional orthogonal multiple access (OMA) HetNets and conventional NOMA HetNets, the proposed technique improves the system performance in terms of overall sum rate and the outage probability.

Keywords

• Compressive sensing (CS)
• heterogeneous networks (HetNets)
• non-orthogonal multiple access (NOMA)
• power allocation (PA)
• sparsity