Application of Biological Resource Allocation Techniques to SCMA NOMA Networks

Abstract

Non-orthogonal multiple access (NOMA) is envisaged to be an enabling access method for fifth generation (5G) communications. It has the potential to offer enhanced spectral efficiency, massive connectivity, higher data rates and lower latency. Resource allocation (RA) in NOMA networks is important in improving performance of NOMA systems. In this paper, RA to maximize sum-rate optimization in uplink SCMA NOMA is considered. Alternative RA methods to the common analytical methods are proposed and their performance investigated. The proposed RA methods are based on biological algorithms namely ant colony optimization (ACO) and particle swarm optimization (PSO). From simulations performed it is noted that the PSO outperforms the ACO regarding sum-rate optimization.