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

EasyChair Preprint 5906

Abstract

The increasing demand for wireless network connections requires efficient net-work resource allocation. The non-orthogonal multiple access (NOMA) technol-ogy offers users sharing the same radio bandwidth to increase the bandwidth ef-ficiency. 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 average mean square error is also close to the lower limit. The convergence of the pro-posed method is mainly less than 10 iterations at different numbers of resource blocks

Keyphrases: discrete, particle swarm, user grouping

@booklet{EasyChair:5906,
  author    = {Hadhrami Ghani and Farah Najwa Roslim and Eissa Mohammed Mohsen Al-Shari and Muhammad Akmal Remli and Nurul Izrin Md Saleh},
  title     = {Discrete Particle Swarm Optimization for User Grouping in 5G NOMA Networks},
  howpublished = {EasyChair Preprint 5906},
  year      = {EasyChair, 2021}}