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Non-Orthogonal Multiple Access For Cooperative Communications: Challenges, Opportunities, And Trends
Dehuan Wan, Miaowen Wen, Fei Ji, Hua Yu, Fangjiong Chen
TL;DR
The paper addresses how to organize and optimize NOMA-based cooperative relay networks, where effective relay configuration remains an open issue. It develops a unified architecture, compares relay-assisted NOMA schemes, and proposes hybrid power allocation for composite architectures. The reported outcome is lower computational complexity and signaling overhead with marginal sum rate degradation, alongside a synthesis of challenges and future research directions.
Problem
Effective configuration and optimization of NOMA-based cooperative relay networks remains an open issue.
Method
The paper classifies cooperative relay systems into three architectures, compares their settings and performance, and proposes hybrid power allocation for composite architectures.
Results
Hybrid power allocation provides lower computational complexity and reduced signaling overhead at the expense of marginal sum rate degradation.
Takeaways & Limitations
The paper highlights challenges, opportunities, and future research trends for NOMA-based cooperative relay networks.
Abstract
from arXiv · showhide
Non-orthogonal multiple access (NOMA) is a promising radio access technique for next-generation wireless networks. In this article, we investigate the NOMA-based cooperative relay network. We begin with an introduction of the existing relay-assisted NOMA systems by classifying them into three categories: uplink, downlink, and composite architectures. Then, we discuss their principles and key features, and provide a comprehensive comparison from the perspective of spectral efficiency, energy efficiency, and total transmit power. A novel strategy termed hybrid power allocation is further discussed for the composite architecture, which can reduce the computational complexity and signaling overhead at the expense of marginal sum rate degradation. Finally, major challenges, opportunities, and future research trends for the design of NOMA-based cooperative relay systems with other techniques are also highlighted to provide insights for researchers in this field.
I. INTRODUCTION
The article frames cooperative relay-aided NOMA as a response to growing wireless traffic and develops a unified architecture for analyzing its structures, settings, and optimization. It also introduces hybrid power allocation and surveys performance comparisons, challenges, opportunities, and research trends.
- Growing wireless data traffic motivates studying NOMA for next-generation communications and cooperative relaying.
- NOMA can improve throughput by allocating more power to nodes with poor channel quality under the near-far effect.
- NOMA supports integration with OFDMA, SC-FDMA, massive MIMO, and mmWave techniques.
- NOMA cooperative relay systems include dual-hop architectures using decode-and-forward or amplify-and-forward relaying, while relay selection remains an open issue.
- The article develops a unified power-domain NOMA cooperative relay architecture by combining three basic communication structures.
- System settings, decoding orders, asymmetries, power allocation, performance comparisons, hybrid allocation, and future research directions are discussed.
II. STRUCTURES OF RELAY-AIDED WIRELESS NETWORKS
Cooperative relay networks are organized into uplink, downlink, and composite architectures based on their communication modes. The section also distinguishes the relay setting considered and explains how NOMA enables cell-centre users to assist users with poor connections.
- The basic communication modes include one-to-one, one-to-many, and many-to-one structures; many-to-many can be constructed from these modes.
- The article does not discuss the many-to-many mode.
- Cooperative relay networks comprise sources, relays, and users and are categorized as uplink, downlink, or composite architectures.
- For direct links between source and user nodes, the article focuses on classical three-node relay-aided wireless networks.
- Unlike OMA, NOMA's SIC-based multi-user detection allows a cell-centre user to relay for users with poor connections.
A. Processing Procedures
The processing procedures distinguish uplink and downlink NOMA through their signal superposition, SIC operation, power allocation, and decoding orders. The section also notes that NOMA generally outperforms OMA in the two-user rate region.
- In uplink NOMA, users transmit across the full bandwidth with different powers, and the receiver applies SIC to successively decode and cancel signals.
- Uplink decoding first decodes a stronger user's signal while treating weaker-user signals as noise, then subtracts it before decoding weaker users.
- In downlink NOMA, superposition coding is performed at the transmitter, more power is assigned to weaker users, and SIC is applied at receivers.
- The key distinction is decoding order: downlink strong users cancel weak-user signals first, whereas uplink receivers cancel strong-user signals first.
- NOMA generally outperforms OMA in the rate region for the two-user case.
1) Uplink:
NOMA generally outperforms OMA in uplink and downlink rate performance, while decoding order and power allocation must be coordinated across relay links. Composite architectures can improve sum rate and fairness, but some required ordering schemes are impractical.
- Uplink: OMA is generally worse than NOMA for uplink transmission, except at one capacity-bound point where weak-user fairness can be poor.At that point, the weak user’s rate becomes much lower when channel conditions differ substantially.
- Downlink: The downlink NOMA rate region strictly contains the OMA rate region, with a larger gap under greater channel asymmetry.NOMA can still provide reasonable rates for both strong and weak users under severe asymmetry.
- DF relaying: DF relay networks require identical decoding orders on source-to-relay and relay-to-user transmissions; otherwise, the achievable sum rate decreases dramatically.The degradation is attributed to the min function governing the relayed rate.
- Composite architectures: Composite architectures use different decoding-order directions across the two links, which can increase achievable sum rate and balance throughput fairness.Source-to-relay and relay-to-user channel gains are configured in opposite ascending or descending orders.
- AF relaying: AF relay networks similarly require consistent power-allocation ordering across source-to-relay and relay-to-user transmissions; otherwise, sum rate and outage probability deteriorate significantly.For composite architectures, forcing both links into the same channel-gain order is impractical because it produces poor throughput fairness.
- AF relaying: The AF relay network could be a better choice in the stated comparison.
B. System Asymmetry
System asymmetry determines when NOMA’s rate advantage over OMA is strongest and when it can weaken. Effective power allocation must follow decoding order, but DF networks make this optimization especially complex.
- System asymmetry: The cooperative-relay asymmetry degree A_r is the product of the uplink and downlink asymmetry degrees.
- System asymmetry: Asymmetry generally increases NOMA’s achievable-sum-rate advantage over OMA; for example, NOMA is preferable in practice when A_r > 3.
- Diamond networks: In diamond networks, NOMA’s superiority can weaken or disappear when the OMA-selected source-relay-user channel differs from the channel of the user decoded last in NOMA.OMA can then select a better source-relay-user channel, producing a larger achievable sum rate than NOMA.
- Diamond networks: For diamond networks, NOMA is preferred only when asymmetry is sufficiently large and the OMA-selected channel matches the last-decoded NOMA user’s channel.
- Power allocation: Power allocation should assign more power to earlier-decoded symbols and less to later-decoded symbols, but DF optimization is more complex than AF optimization with global instantaneous CSI.Finding a simple and effective DF power-allocation scheme is therefore described as demanding.
D. Performance Comparisons
The comparisons show that cooperative NOMA improves rate performance and power utilization relative to OMA, but its energy-efficiency advantage is not universal. Relay protocol, fading model, asymmetry, and power allocation materially affect the outcome.
- Uplink architecture: Uplink NOMA faces synchronization and inter-user transmit-power-control challenges because users experience different positions and channel conditions.
- Fading channels: Most existing NOMA schemes emphasize Rayleigh fading, motivating a proposed NOMA scheme for Rician fading channels.
- Relay protocols: DF relaying is preferred over AF relaying because its SINR is always higher in the stated comparison.
- Downlink architectures: DF relaying can significantly improve outage probability and achievable sum rate, especially in the low-SNR region.
- Downlink architectures: Allocating more power to the weak user improves outage behavior but decreases NOMA’s achievable sum rate, creating a tradeoff between outage probability and sum rate.
- Power allocation: A central processor using instantaneous CSI can reduce total system power consumption to less than 2P_t, with saved power available for improving weak-user rate, outage probability, and fairness.
- Performance comparison: Under perfect CSI, NOMA shows significant superiority over OMA in achievable sum rate but performs worse in energy efficiency.
- Performance comparison: NOMA’s real power utilization can be up to 30% higher than OMA’s, while its ratio of achievable sum rate to power consumption remains smaller.
V. HYBRID POWER ALLOCATION STRATEGY
The hybrid power allocation strategy combines statistical and instantaneous CSI in a two-stage design for NOMA cooperative relays. Simulations show near-ICSI sum-rate performance, improved performance over SCSI, and strong energy-efficiency benefits with lower scheduling complexity.
- Strategy design: The strategy uses statistical CSI for S→R power allocation and instantaneous CSI for dynamic R→U allocation in two stages.The first stage maximizes sum rate using statistical CSI; the second fixes S→R coefficients and optimizes R→U allocation with instantaneous CSI.
- Performance evaluation: Hybrid allocation achieves almost the same achievable sum rate as ICSI and outperforms SCSI even when the near-far effect is not severe.
- Performance evaluation: With the highest spectral efficiency and lowest power consumption, hybrid allocation performs best in energy efficiency against FDMA.
- Implications: The strategy is promising because it reduces power-scheduling complexity, mitigates the near-far effect, and maintains superior performance.
VI. CHALLENGES, OPPORTUNITIES, AND TRENDS
The paper identifies feedback and computational burdens, security risks, and implementation assumptions as major challenges for NOMA cooperative relays. It highlights lower-overhead allocation, secure relay selection, and cooperative jamming as research directions.
- Feedback Overhead and Computational Complexity: Dynamic allocation can improve performance but requires global instantaneous CSI, creating large signaling overhead and computational complexity as user numbers grow.
- Feedback Overhead and Computational Complexity: Feedback delay, channel-estimation error, and difficult uplink synchronization make perfect CSI challenging to obtain.
- Feedback Overhead and Computational Complexity: New allocation methods are needed to reduce feedback overhead while accepting marginal performance degradation.
- Communication Security: Secure communication remains open for NOMA cooperative relays with untrusted relays, because relays may decode users’ symbols before retransmission.
- Communication Security: A proposed security direction gathers CSI, selects an appropriate relay, and uses cooperative jamming from other relays during both phases.
C. Hardware Development
NOMA improves cooperative-relaying performance but increases hardware complexity, especially for mobile-user detection and interference cancellation. Future implementations require capable SIC units and must address mmWave blockage and relay placement.
- Hardware Development: Although NOMA outperforms conventional OMA in cooperative relaying, its hardware implementation is more complex.
- Hardware Development: Limited processing capability makes multi-user detection and interference cancellation difficult for mobile users.
- Hardware Development: A high-performance SIC unit is a key enabler because NOMA allows more users to access the network simultaneously.
- mmWave Integration: MmWave NOMA can improve spectrum and energy efficiency, but short wavelengths require LOS conditions that mobility and obstacles disrupt.
- mmWave Integration: Applying cooperative relays to mmWave systems raises challenges involving anti-blockage mode switching and optimal relay placement.
VII. CONCLUSIONS
The paper compares three cooperative-relay structures and reports advantages for NOMA, especially in composite architectures. It proposes hybrid power allocation to reduce complexity and signaling overhead with only marginal sum-rate degradation.
- Conclusions: The paper investigates three typical cooperative-relay structures and compares their principles, key features, construction criteria, and engineering feasibility.
- Conclusions: Simulation results demonstrate advantages of cooperative relaying with NOMA, especially for composite structures.
- Conclusions: Hybrid power allocation reduces computational complexity and signaling overhead at the expense of marginal sum-rate degradation.
- Conclusions: The paper highlights challenges, opportunities, and future research trends for designing NOMA cooperative-relay systems.
BIOGRAPHIES
The supplied material combines author biographies with figure captions and experimental descriptions covering communication modes, cooperative relay architectures, and performance comparisons.
- The biographies record academic appointments and training across South China University of Technology, Peking University, Zhejiang University, Northwestern Polytechnical University, and international visiting positions.
- The authors’ research spans wireless communication systems, networking, signal detection, array signal processing, physical-layer technologies, and non-orthogonal multiple access.
- The figures depict one-to-one, one-to-many, and many-to-one communication modes, alongside cooperative relay architectures for OMA and NOMA.
- The experimental comparisons evaluate achievable sum rate, outage probability, energy efficiency, energy efficiency ratio, and normalized power utilization across NOMA, OMA, AF, DF, TDMA, HCSI, ICSI, SCSI, and FDMA schemes.