An Improved PSO-Based Power Allocation Algorithm for the Optimal EE and SE Tradeoff in Downlink NOMA Systems

Abstract

Non-orthogonal multiple access (NOMA) technique can substantially improve the spectral efficiency (SE) and increase the throughput of system. As NOMA has these advantages, it has been investigated as a candidate radio access technology for the fifth-generation (5G) mobile communication. In this paper, we study the benefit of NOMA in enhancing energy efficiency (EE) for downlink systems by introducing a certain power allocation scheme. The expected goal is to maximize the EE of the systems while ensuring the SE is guaranteed. The most common method for achieving the tradeoff of EE and SE is the convex optimization. Because the EE of NOMA systems is a strictly quasi-concave function, it is difficult to apply the convex optimization directly. We propose to adopt the improved particle swarm optimization (PSO) algorithm. Furthermore, in order to avoid the premature convergence, cycle strategy rotation is used in the algorithm. Numerical results and analysis turn out that the improved PSO algorithm achieves higher EE than the exiting power allocation scheme under the same SE. Moreover, the improved PSO algorithm shows fast convergence and it converges within 9 iterations, which is 35% less than the original PSO algorithm under selected parameters.