Resource Allocation for Downlink NOMA Systems: Key Techniques and Open Issues (1801.00121v1)

Abstract: This article presents advances in resource allocation (RA) for downlink non-orthogonal multiple access (NOMA) systems, focusing on user pairing (UP) and power allocation (PA) algorithms. The former pairs the users to obtain the high capacity gain by exploiting the channel gain difference between the users, while the later allocates power to users in each cluster to balance system throughput and user fairness. Additionally, the article introduces the concept of cluster fairness and proposes the divideand- next largest difference-based UP algorithm to distribute the capacity gain among the NOMA clusters in a controlled manner. Furthermore, performance comparison between multiple-input multiple-output NOMA (MIMO-NOMA) and MIMO-OMA is conducted when users have pre-defined quality of service. Simulation results are presented, which validate the advantages of NOMA over OMA. Finally, the article provides avenues for further research on RA for downlink NOMA.

• The paper introduces a novel divide-and-next largest difference-based user pairing (D-NLUPA) algorithm to ensure baseline sum rate gains for each user cluster.
• It evaluates diverse power allocation strategies across SISO, MC, and MIMO contexts to balance throughput and fairness in downlink NOMA systems.
• A comparative analysis shows that MIMO-NOMA outperforms MIMO-OMA in outage probability and sum rate while underscoring several open research challenges.

Resource Allocation for Downlink NOMA Systems

The paper "Resource Allocation for Downlink NOMA Systems: Key Techniques and Open Issues" by Islam et al. explores the intricate mechanisms and challenges encountered in resource allocation (RA) for downlink non-orthogonal multiple access (NOMA) systems. The paper specifically explores two pivotal components of RA in NOMA: user pairing (UP) and power allocation (PA). Both are instrumental in harnessing the potential of NOMA to enhance spectral efficiency and user fairness within the context of the fifth-generation (5G) wireless networks.

Core Contributions and Findings

1. User Pairing Techniques:

- The paper provides a comprehensive survey of UP schemes, detailing their implications on system performance. Methods include simplistic random pairing to more sophisticated algorithms like the next largest difference-based UP algorithm (NLUPA), which pairs users with the most significant channel gain disparities to maximize the sum rate.

- A novel algorithm proposed is the divide-and-next largest difference-based UP algorithm (D-NLUPA), which aims to ensure a baseline sum rate gain for each user cluster, addressing the issue of cluster fairness. Simulation results exhibit the algorithm's capability to control capacity gains across clusters effectively.

1. Power Allocation Strategies:

- Under Single-Input Single-Output (SISO) systems, various PA strategies are scrutinized for their effectiveness in balancing throughput and user fairness. Techniques like fixed PA (F-PA), fractional transmit power control (FTPC), and channel gain-aware CR-inspired PA demonstrate varying capabilities in optimizing NOMA system performance.

- For Multi-Carrier (MC) NOMA and Multiple-Input Multiple-Output (MIMO) NOMA contexts, the paper discusses complex RA problems. These include joint optimization of PA and sub-carrier assignment under constraints such as QoS requirements and total power limits. The article emphasizes that issues related to inter-cluster interference, especially in MIMO deployments, require further exploration.

1. Comparative Analysis of MIMO-NOMA and MIMO-OMA:

- The paper undertakes a comparative analysis of MIMO-NOMA versus traditional MIMO orthogonal multiple access (MIMO-OMA) systems. It highlights the superior outage probability and effective sum rate performance of MIMO-NOMA when employing optimized PA strategies.

1. Challenges and Open Research Questions:

- The paper identifies several open challenges in the RA domain for NOMA, such as scalability, inter-cell interference, integration with carrier aggregation, and RA under limited feedback. There is a particular need for low-complexity RA solutions, robust against security vulnerabilities inherent in NOMA systems.

Implications and Future Directions

The implications of this research extend heavily into the domains of wireless communications and network engineering. As 5G networks proliferate, the demand for efficient multiple access techniques like NOMA increases due to spectrum scarcity and diverse service requirements. NOMA's potential to accommodate massive connectivity in dense deployments makes breakthroughs in RA technologies critical.

In future work, addressing unresolved issues such as joint UP and PA optimization, enhanced security measures, and implementation of RA in novel integrated paradigms (such as FD MC-MIMO-NOMA) will be essential. The exploration of these realms promises advancements, not only propelling NOMA's adoptability but also contributing to the broader 5G and beyond wireless communication landscape.

In conclusion, this paper presents substantial advancements in understanding RA mechanisms for downlink NOMA, paving the way for future research that will address theoretical and practical challenges, enhancing the implementation of NOMA in real-world scenarios.