Discrete Particle Swarm Optimization for User Grouping in 5G NOMA Networks

Abstract

The increasing demand for wireless network connections requires efficient network resource allocation. The non-orthogonal multiple access (NOMA) technology offers users sharing the same radio bandwidth to increase the bandwidth efficiency. However, the increase in the number of users demanding for the radio bandwidth and network connections will increase the required computational load for grouping the users to share the radio resources. This paper studies a heuristic method for grouping the users based on the discrete particle swarm optimization. The throughput, the average square error and the fitness function values obtained by the proposed method and the existing schemes are measured and observed. It has been demonstrated that the proposed scheme based on discrete particle swarm optimization has produced the throughput close to the upper limit. The convergence of the proposed method is mainly less than 10 iterations at different numbers of resource blocks.