Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G (2108.04561v2)

Abstract: Due to the explosive growth in the number of wireless devices and diverse wireless services, such as virtual/augmented reality and Internet-of-Everything, next generation wireless networks face unprecedented challenges caused by heterogeneous data traffic, massive connectivity, and ultra-high bandwidth efficiency and ultra-low latency requirements. To address these challenges, advanced multiple access schemes are expected to be developed, namely next generation multiple access (NGMA), which are capable of supporting massive numbers of users in a more resource- and complexity-efficient manner than existing multiple access schemes. As the research on NGMA is in a very early stage, in this paper, we explore the evolution of NGMA with a particular focus on non-orthogonal multiple access (NOMA), i.e., the transition from NOMA to NGMA. In particular, we first review the fundamental capacity limits of NOMA, elaborate on the new requirements for NGMA, and discuss several possible candidate techniques. Moreover, given the high compatibility and flexibility of NOMA, we provide an overview of current research efforts on multi-antenna techniques for NOMA, promising future application scenarios of NOMA, and the interplay between NOMA and other emerging physical layer techniques. Furthermore, we discuss advanced mathematical tools for facilitating the design of NOMA communication systems, including conventional optimization approaches and new machine learning techniques. Next, we propose a unified framework for NGMA based on multiple antennas and NOMA, where both downlink and uplink transmissions are considered, thus setting the foundation for this emerging research area. Finally, several practical implementation challenges for NGMA are highlighted as motivation for future work.

• The paper surveys the evolution of NOMA as a foundation for Next Generation Multiple Access (NGMA) in 6G networks, highlighting its potential for enhanced spectral and energy efficiency over traditional methods.
• It discusses the technical integration of NOMA with technologies like MIMO, RIS, OTFS, and ISaC, showcasing applications in areas such as UAV communications and massive machine-type communications.
• The work explores advanced optimization techniques and machine learning applications for NOMA systems and proposes a unified NGMA framework synthesizing various transmission strategies for future practical implementations.

Overview of "Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G"

The manuscript, "Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G," presents an extensive survey of the evolution of non-orthogonal multiple access (NOMA) as a foundational component in developing the next generation multiple access (NGMA) landscape for the sixth generation (6G) of wireless networks. As wireless technology advances, meeting the massive connectivity and diverse application requirements of 6G is essential. This paper positions NOMA as a crucial enabler of these advancements due to its resource- and complexity-efficient communication capabilities.

Evaluation of NOMA's Role in 6G

The work opens by setting the context of 6G demands, characterized by a combination of ultra-high data rates, massive connectivity, and minimal latency, prompting the reconsideration of traditional orthogonal multiple access (OMA) strategies. NOMA is highlighted due to its ability to address these challenges by allowing multiple users to share spectrum resources non-orthogonally, thus enhancing spectral and energy efficiency.

A comprehensive review of NOMA’s capacity limits in both single-antenna and multiple-antenna (MIMO) configurations highlights its capacity-achieving potential in certain setups, contrasting it with OMA's inherent limitations under such stringent 6G requirements. The paper explores the technical synergies between NOMA and various MIMO strategies which exploit spatial degrees of freedom to enhance network performance, particularly in overloaded scenarios.

Technical Integration and Future Prospects

The authors outline several promising NOMA applications within future wireless networks: UAV communications, massive and critical machine-type communications (MC-MTC), and beyond. For example, UAV-aided systems leveraging NOMA exhibit enhanced flexibility for resource allocation and connectivity, pivotal for emergency scenarios and remote traffic offloading. The manuscript also identifies that NOMA-assisted cellular-connected UAVs offer significant capacity benefits due to their spectrum sharing characteristics.

Moreover, the article addresses the integration of NOMA with cutting-edge physical-layer technologies such as reconfigurable intelligent surfaces (RIS), orthogonal time frequency space (OTFS) modulation, and integrated sensing and communication (ISaC). These integration efforts are pivotal due to their enhanced channel state information manipulation capabilities, further improving spectral efficiency and potentially reimagining channel estimation strategies for emerging wireless environments.

Advanced Mathematical Tools and ML Implications

A considerable segment of the paper is dedicated to advanced optimization techniques and ML applications in NOMA. The authors argue that conventional mathematical optimization remains useful for tractable problems but highlight emerging non-convex challenges where ML, particularly deep and reinforcement learning, can significantly contribute. ML approaches inline NOMA systems with dynamic resource allocation capabilities, adaptive SIC ordering, and smarter power control.

A Unified Framework for NGMA

The authors propose a unified NGMA framework that synthesizes the advantages of multi-antenna techniques and NOMA for both downlink and uplink scenarios. This holistic framework encapsulates various transmission strategies, including the traditional beamforming-based and cluster-based NOMA, into a more adaptable system architecture. The discussion lends itself to potential practical implementations that devise optimal user grouping, beamformer design, and resource management techniques, setting a stage for future development pathways.

Concluding Thoughts and Future Challenges

The paper concludes by recognizing several implementation challenges that lie ahead for NGMA. These challenges include the development of robust modulation schemes, error propagation mitigation strategies, and advanced channel estimation techniques. The research community is encouraged to explore these open issues, which are critical for the practical realization of NOMA within the 6G paradigm.

In sum, this manuscript provides a foundational reference that not only underscores NOMA's promising capacity and efficiency benefits for 6G networks but also stimulates forward-looking research to address ongoing practical challenges. Future studies can leverage this comprehensive evaluation to further enrich the theoretical and application domains of NGMA in next-generation wireless systems.