Non-orthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks (1601.03613v1)

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.

• The paper presents novel closed-form outage probability expressions for NOMA-based cognitive radio networks under fixed and proportional power constraints.
• The paper reveals that diversity order scales with the NOMA user index for fixed power while proportional power introduces an asymptotic error floor.
• Rigorous simulations validate that integrating NOMA in underlay networks can significantly enhance spectral efficiency for future 5G applications.

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

The paper by Yuanwei Liu, Zhiguo Ding, Maged Elkashlan, and Jinhong Yuan addresses the integration of non-orthogonal multiple access (NOMA) within large-scale underlay cognitive radio (CR) networks. It leverages stochastic geometry to model and analyze the network. The innovative application of NOMA in this context is aimed at enhancing the spectral efficiency, an essential requirement for future 5G networks.

Key Contributions

1. Outage Probability Analysis: The paper presents new closed-form expressions for computing the outage probability in NOMA-based CR networks, considering the network's stochastic nature. It defines the system performance based on two distinct power constraints: a fixed transmit power at primary transmitters (PTs) and a proportional power constraint relative to secondary base station (BS).
2. Diversity Order Insights: The paper provides a thorough diversity order analysis. For fixed transmit power, the diversity order equals the user index $m$ for the $m$-th ordered NOMA user. Contrastingly, in the proportional power scenario, the authors identify an asymptotic error floor in the outage probability, highlighting the impact of PT power scaling on system performance.
3. Simulation Verification: Rigorous simulations support the theoretical findings, validating the accuracy and applicability of the derived expressions. These simulations help confirm that with careful design, NOMA can outperform conventional orthogonal multiple access in underlay CR networks.

Implications

The implications of this research are multifaceted. Practically, the results suggest that NOMA can be effectively implemented in large-scale CR networks, potentially leading to more efficient use of spectrum resources. This lays concrete groundwork for deploying NOMA in real-world 5G systems, offering enhanced throughput and reliability compared to conventional methods.

Theoretically, the research advances the understanding of outage performance in CR networks with a NOMA scheme. It brings new perspectives on diversity order and error floor phenomena under different power constraint scenarios, which can guide future design methodologies for wireless systems incorporating NOMA.

Future Directions

Future research could focus on further optimizing power allocation coefficients and exploring the trade-offs between different network parameters to maximize the performance gain of NOMA over traditional multiple access techniques in cognitive radio settings. Moreover, extending the paper to more complex system models incorporating additional technologies such as MIMO in conjunction with NOMA could further unveil opportunities for performance enhancement.

Ultimately, this paper significantly contributes to the practical and theoretical aspects of wireless communications, especially regarding the implementation of advanced multiple access techniques in future network paradigms.