Power and Channel Allocation for Non-orthogonal Multiple Access in 5G Systems: Tractability and Computation

TL;DR

This paper investigates the complex problem of jointly optimizing power and channel allocation in NOMA systems for 5G, providing theoretical analysis, polynomial-time solutions for some cases, and a novel algorithmic framework for others, with demonstrated performance gains.

Contribution

It offers a comprehensive theoretical and algorithmic framework for resource allocation in NOMA, including tractability analysis, optimality bounds, and a new near-optimal solution method.

Findings

Proves NP-hardness for certain resource allocation cases.

Provides polynomial-time algorithms for tractable cases.

Demonstrates significant performance improvements over existing schemes.

Abstract

Network capacity calls for significant increase for 5G cellular systems. A promising multi-user access scheme, non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC), is currently under consideration. In NOMA, spectrum efficiency is improved by allowing more than one user to simultaneously access the same frequency-time resource and separating multi-user signals by SIC at the receiver. These render resource allocation and optimization in NOMA different from orthogonal multiple access in 4G. In this paper, we provide theoretical insights and algorithmic solutions to jointly optimize power and channel allocation in NOMA. For utility maximization, we mathematically formulate NOMA resource allocation problems. We characterize and analyze the problems' tractability under a range of constraints and utility functions. For tractable cases, we provide polynomial-time solutions for global optimality. For intractable cases, we prove the NP-hardness and propose an algorithmic framework combining Lagrangian duality and dynamic programming (LDDP) to deliver near-optimal solutions. To gauge the performance of the obtained solutions, we also provide optimality bounds on the global optimum. Numerical results demonstrate that the proposed algorithmic solution can significantly improve the system performance in both throughput and fairness over orthogonal multiple access as well as over a previous NOMA resource allocation scheme.