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

TL;DR

This work surveys the evolution from NOMA to NGMA for 6G, detailing information-theoretic capacity limits, NGMA design requirements, and candidate non-orthogonal schemes. It synthesizes state-of-the-art multi-antenna NOMA techniques, promising NGMA application scenarios (e.g., UAV, MC-MTC, MEC, e-health), and the interplay with RIS, OTFS, and ISaC, while highlighting advanced optimization and ML tools to enable scalable NGMA design. A unified framework is proposed that blends multi-antenna processing with NOMA for both downlink and uplink, addressing SIC challenges and enabling flexible operation across underloaded, critically loaded, and overloaded regimes. The paper also discusses practical implementation challenges—modulation/detection, error propagation, and channel estimation—and outlines future directions to realize NGMA in real-world 6G networks.

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.

Figures (10)

• Figure 1: Illustration of two-user NOMA. (a) The signals of two users are multiplexed in the power domain using the same time/frequency resource. (b) Downlink NOMA transmission. (c) Uplink NOMA transmission. (d) BC capacity/rate region comparison, $0\le p_1+p_2\le 1$W. (e) MAC capacity/rate region comparison, $0\le p_1\le 1$W, $0\le p_2\le 1$W. We set $\frac{{{{\left| {{h_1}} \right|}^2}}}{{{\sigma ^2}}} = 10$ dB and $\frac{{{{\left| {{h_2}} \right|}^2}}}{{{\sigma ^2}}} = 0$ dB, where $h_k$ and $p_k$ denote the channel coefficient and transmit power of user $k \in \left\{ {1,2} \right\}$, respectively, ${\sigma ^2}$ denotes the noise power at both users, and $R_k$ denotes the communication rate achieved by user $k \in \left\{ {1,2} \right\}$.
• Figure 2: Illustration of existing multi-antenna techniques for NOMA. (a) Beamformer-based MIMO-NOMA with 3 users using 3 beamformers. (b) Cluster-based MIMO-NOMA with 4 users in 2 clusters using 2 beamformers 18_WC_Liu.
• Figure 3: Two categories of NOMA-based UAV-aided communications.
• Figure 4: Illustration of the obtained communication rate maps for OMA and NOMA, where the AP and the static user are located at $\left( {0,10,2} \right)$ meter and $\left( {0,0,1.3} \right)$ meter, respectively. The five dark blue regions are covered by obstacles with a height of 1.3 meter. The other parameters adopted can be found in xidong_robot.
• Figure 5: A comparison of GF, GB, and semi-GF transmission schemes.