Reconfigurable Intelligent Surface Aided NOMA Networks

Abstract: Reconfigurable intelligent surfaces (RISs) constitute a promising performance enhancement for next-generation (NG) wireless networks in terms of enhancing both their spectrum efficiency (SE) and energy efficiency (EE). We conceive a system for serving paired power-domain non-orthogonal multiple access (NOMA) users by designing the passive beamforming weights at the RISs. In an effort to evaluate the network performance, we first derive the best-case and worst-case of new channel statistics for characterizing the effective channel gains. Then, we derive the best-case and worst-case of our closed-form expressions derived both for the outage probability and for the ergodic rate of the prioritized user. For gleaning further insights, we investigate both the diversity orders of the outage probability and the high-signal-to-noise (SNR) slopes of the ergodic rate. We also derive both the SE and EE of the proposed network. Our analytical results demonstrate that the base station (BS)-user links have almost no impact on the diversity orders attained when the number of RISs is high enough. Numerical results are provided for confirming that: i) the high-SNR slope of the RIS-aided network is one; ii) the proposed RIS-aided NOMA network has superior network performance compared to its orthogonal counterpart.

• The paper derives new channel statistics for RIS-aided networks by analyzing both best- and worst-case channel gain scenarios.
• The paper presents closed-form expressions for outage probability and ergodic rate, revealing enhanced diversity and a unity high-SNR slope.
• The paper computes spectrum and energy efficiency metrics, confirming that RIS integration in NOMA outperforms conventional orthogonal systems.

Reconfigurable Intelligent Surface Aided NOMA Networks: A Formal Analysis

The paper "Reconfigurable Intelligent Surface Aided NOMA Networks" investigates the utilization of Reconfigurable Intelligent Surfaces (RISs) as a mechanism for enhancing next-generation wireless communication networks. The focus is on improving spectrum efficiency (SE) and energy efficiency (EE) through the integration of RIS with Non-Orthogonal Multiple Access (NOMA) techniques. The authors propose a system model that leverages passive beamforming at the RISs to optimize network performance.

Analytical and Numerical Contributions

Channel Statistics and Performance Derivation: The paper initiates its analytical exploration by deriving new channel statistics pertinent to RIS-aided networks. Both best-case and worst-case scenarios for effective channel gains are meticulously computed. These derivations form the basis for subsequent evaluations in terms of outage probability and ergodic rates. Notably, it is demonstrated that the powerful combination of RIS and NOMA can deliver enhanced diversity orders and efficient high Signal-to-Noise Ratio (SNR) slopes.

Outage Probability and Ergodic Rate: A key highlight of the paper is the derivation of closed-form expressions for the outage probability and ergodic rate of users in a prioritized NOMA network. The findings suggest that the impact of Base Station (BS)-user links on diversity is minimal when the number of RIS elements deployed is sufficiently large. Furthermore, it is shown that the high-SNR slope of the RIS-assisted network achieves a unity value, underscoring the robustness of the proposed system configuration.

Spectrum and Energy Efficiency: The paper meticulously calculates the spectrum efficiency and energy efficiency of the proposed network model, confirming that the RIS-aided NOMA network surpasses the performance of its orthogonal counterparts. These results underscore the feasibility and effectiveness of integrating RIS in NOMA frameworks, potentially influencing future deployments in real-world 5G and beyond networks.

Implications and Future Directions

Theoretical and Practical Implications: From a theoretical perspective, this research underscores the potential of RIS to operate synergistically with NOMA, offering insights into co-channel interference mitigation and enhanced user capacity. Practically, it demonstrates a feasible avenue to augment existing communication infrastructures, which could lead to cost-effective deployments and increased spectrum utilization efficiencies.

Future Developments: With the promising outcomes delineated in this investigation, future research could explore the integration of RIS in more complex scenarios such as MIMO-NOMA networks. Furthermore, exploration into dynamic beamforming algorithms that can adapt to rapid changes in user environments would be valuable. Additionally, investigating the latency impacts and computational overheads of large-scale RIS deployment remains an open field of inquiry.

In conclusion, the paper provides a structured methodological approach to effectively harness the potential of RIS in conjunction with NOMA techniques. By leveraging the unique properties of RIS, notably passive beamforming, it is possible to achieve significant gains in both spectrum and energy efficiencies. This work not only advances our understanding of RIS-aided communication networks but also sets a valuable foundation for future exploration and deployment in next-generation wireless systems.