Optimal Power Allocation in Downlink Non-Orthogonal Multiple Access (NOMA)

Abstract

Fifth generation of wireless cellular networks promise to enable better services anytime and anywhere. Nonorthogonal multiple access (NOMA) stands as a suitable multiple accessing scheme due to the ability to allow multiple users to share the same radio resource simultaneously via different domains (power, code, etc.). Through the introduced power domain, users multiplexed at the radio resource within different power levels. This paper studies power allocation in downlink NOMA, an optimization problem formulated that aims to maximize the system's sum rate. To solve the problem, a genetic algorithm based power allocation (GAPA) was proposed that uses genetic algorithm (GA) that employs heuristics to search for suitable solutions. The performance of the proposed power allocation algorithm compared with full search power allocation (FSPA) that gives an optimal performance. Results show that GAPA reaches a performance near to FSPA with lower complexity. In addition, GAPA simulated with various user paring algorithms. Channel state sorting based user pairing with GAPA achieves the best performance comparing to random user pairing algorithm and exhaustive user pairing.

Zipf Distribution Power AllocationAapproach for NOMA Systems

“…The eigenvalue based power allocation performs well compared to other power allocation schemes. The author of [18] proposed a power allocation method based on a genetic algorithm GAPA which is defined as an optimization method based on a powerful heuristic, to maximize the sum rate of the NOMA system. The results are evaluated by comparing the performance with FSPA, and show that the proposed GAPA algorithm outperforms FSPA with a large number of users.…”