A Novel Approach to Enhance the Energy Efficiency of a NOMA Network

Abstract

Spectral efficiency is crucial for implementing 5G cellular networks and beyond. Non-orthogonal multiple access (NOMA) is a promising scheme to enhance efficiency. This paper introduces two improvements that will further enhance the channel capacity using the NOMA algorithm. We first introduce a novel algorithm, the User Sub-Channel Fair Matching Algorithm (USFMA), by applying a new sub-channel sorting and compensations scheme and then benefiting from the well-known Hungarian algorithm to allocate users to each sub-channel in a way that guarantees an optimum overall system performance. Then, for per sub-channel power allocation, we convert the non-convex objective function into a convex sub-problem using the concave–convex procedure (CCP) by converting the objective function into convex sub-problems and using the successive convex approximation to solve the convex sub-problems to find effective sub-optimal solutions. We have built a MATLAB simulation cellular environment to evaluate and compare the system performance with other known schemes. The results are promising and showed significant improvements compared to the other capacity and energy efficiency schemes.

Keywords

• non-orthogonal multiple access
• user allocation algorithm
• Hungarian algorithm
• user fairness
• non-convex problem
• DC programming