On Optimal Power Allocation for Downlink Non-Orthogonal Multiple Access Systems

TL;DR

This paper analytically derives optimal power allocation strategies for downlink NOMA systems under various performance criteria, explicitly considering power order constraints, and proposes an efficient joint channel and power allocation method.

Contribution

It provides the first comprehensive analytical characterization of optimal power allocation in downlink NOMA with multiple criteria, including order constraints, and introduces a low-complexity joint optimization approach.

Findings

Optimal power allocation formulas derived for multiple criteria.

Order constraints significantly affect SIC performance.

Joint optimization improves system performance over existing schemes.

Abstract

Non-orthogonal multiple access (NOMA) enables power-domain multiplexing via successive interference cancellation (SIC) and has been viewed as a promising technology for 5G communication. The full benefit of NOMA depends on resource allocation, including power allocation and channel assignment, for all users, which, however, leads to mixed integer programs. In the literature, the optimal power allocation has only been found in some special cases, while the joint optimization of power allocation and channel assignment generally requires exhaustive search. In this paper, we investigate resource allocation in downlink NOMA systems. As the main contribution, we analytically characterize the optimal power allocation with given channel assignment over multiple channels under different performance criteria. Specifically, we consider the maximin fairness, weighted sum rate maximization, sum rate maximization with quality of service (QoS) constraints, energy efficiency maximization with weights or QoS constraints in NOMA systems. We also take explicitly into account the order constraints on the powers of the users on each channel, which are often ignored in theexisting works, and show that they have a significant impact on SIC in NOMA systems. Then, we provide the optimal power allocation for the considered criteria in closed or semi-closed form. We also propose a low-complexity efficient method to jointly optimize channel assignment and power allocation in NOMA systems by incorporating the matching algorithm with the optimal power allocation. Simulation results show that the joint resource optimization using our optimal power allocation yields better performance than the existing schemes.