Non-orthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks

TL;DR

This paper investigates the application of non-orthogonal multiple access (NOMA) in large-scale underlay cognitive radio networks, deriving new outage probability expressions and analyzing diversity under different power constraints, showing NOMA's potential advantages.

Contribution

The paper provides new closed-form outage probability expressions and diversity analysis for NOMA in large-scale underlay cognitive radio networks with different power scenarios.

Findings

NOMA can outperform orthogonal access with proper design.

Diversity order of m at the m-th user under fixed power.

An asymptotic error floor exists when PT power scales with secondary base station.

Abstract

In this paper, non-orthogonal multiple access (NOMA) is applied to large-scale underlay cognitive radio (CR) networks with randomly deployed users. In order to characterize the performance of the considered network, new closed-form expressions of the outage probability are derived using stochastic-geometry. More importantly, by carrying out the diversity analysis, new insights are obtained under the two scenarios with different power constraints: 1) fixed transmit power of the primary transmitters (PTs), and 2) transmit power of the PTs being proportional to that of the secondary base station. For the first scenario, a diversity order of $m$ is experienced at the $m$-th ordered NOMA user. For the second scenario, there is an asymptotic error floor for the outage probability. Simulation results are provided to verify the accuracy of the derived results. A pivotal conclusion is reached that by carefully designing target data rates and power allocation coefficients of users, NOMA can outperform conventional orthogonal multiple access in underlay CR networks.