Nonorthogonal Multiple Access for 5G and Beyond

By Yuanwei Liu, Zhijin Qin, Maged Elkashlan, Zhiguo Ding, Arumgam Nallanathan, Lajos Hanzo. Proceedings of the IEEE, 2017

1,011 citations recorded by the source corpus.

Driven by the rapid escalation of the wireless capacity requirements imposed by advanced multimedia applications (e.g., ultrahigh-definition video, virtual reality, etc.), as well as the dramatically increasing demand for user access required for the Internet of Things (IoT), the fifth-generation (5G) networks face challenges in terms of supporting large-scale heterogeneous data traffic. Nonorthogonal multiple access (NOMA), which has been recently proposed for the third-generation partnership projects long-term evolution advanced (3GPP-LTE-A), constitutes a promising technology of addressing the aforementioned challenges in 5G networks by accommodating several users within the same orthogonal resource block. By doing so, significant bandwidth efficiency enhancement can be attained over conventional orthogonal multiple-access (OMA) techniques. This motivated numerous researchers to dedicate substantial research contributions to this field. In this context, we provide a comprehensive overview of the state of the art in power-domain multiplexing-aided NOMA, with a focus on the theoretical NOMA principles, multiple-antenna-aided NOMA design, on the interplay between NOMA and cooperative transmission, on the resource control of NOMA, on the coexistence of NOMA with other emerging potential 5G techniques and on the comparison with other NOMA variants. We highlight the main advantages of power-domain multiplexing NOMA compared to other existing NOMA techniques. We summarize the challenges of existing research contributions of NOMA and provide potential solutions. Finally, we offer some design guidelines for NOMA systems and identify promising research opportunities for the future.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/20cf74ef2961d0e4779dd05a1e0011e97c44fa9c

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Citations in the corpus

Massive Access for 5G and Beyond (2020, methodology): “Moreover, as a promising technique for B5G cellular IoT, non-orthogonal multiple access (NOMA) was discussed in detail in [31].”
Machine Learning for 5G/B5G Mobile and Wireless Communications: Potential, Limitations, and Future Directions (2019, background): “These schemes can be combined with open- and closed-loop MIMO schemes [137], [138].”
Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis (2019, neutral): “power-domain Non-Orthogonal Multiple Access - NOMA [16]).”
A Primer on Rate-Splitting Multiple Access: Tutorial, Myths, and Frequently Asked Questions (2022, background): “Hence both 4G and 5G already use a combination of orthogonal (in the time-frequency domains) and non-orthogonal (in the spatial domain) approaches in the form of OFDMA combined with SDMA/MU-MIMO/massive MIMO.”
Federated Learning for 6G: Applications, Challenges, and Opportunities (2021, methodology): “The spectral efficiency and connectivity optimization of NOMA typically leads to nonconvex resource allocation problems, which are optimized using conventional algorithms [65].”
Reconfigurable Intelligent Surface Aided NOMA Networks (2019, background): “NOMA networks are capable of serving multiple users at different quality-of-service (QoS) requirements in the same time/frequency/code resource block [10]–[12].”
Grant-Free Non-Orthogonal Multiple Access for IoT: A Survey (2019, neutral): “Dec-2017 [23] X X X • • X X X X • X X X X X X”
Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing (2022, neutral): “often results in less tractable nonconvex resource allocation problems due to interference [2], [18].”
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks (2019, background): “multiple access (NOMA) schemes [184] relying on sophisticated transceiver designs.”
Reconfigurable Intelligent Surfaces: Principles and Opportunities (2020, background): “ose key idea is to superimpose 48 the signals of two users at different powers for exploiting the spectrum more efﬁciently by opportunistically exploring the users’ different channel conditions [48], [146]. Li et al. [147] considered a MISO-NOMA downlink communication network for minimizing the tota”
A Survey of Rate-Optimal Power Domain NOMA With Enabling Technologies of Future Wireless Networks (2019, methodology): “y solutions to solve the user clustering problem through heuristic algorithms which may lead to unpredictable results. Alternatively, the other approaches for handling the NOMA clustering problem are [16]: The monotonic optimization approach as in [71]; the monotonic nature of the objective functio”
A Tutorial on Fluid Antenna System for 6G Networks: Encompassing Communication Theory, Optimization Methods and Hardware Designs (2024, methodology): “In NOMA, users share the same radio resource unit using superposition coding and successive interference cancellation (SIC) [68], [69].”
Exploiting Intelligent Reflecting Surfaces in NOMA Networks: Joint Beamforming Optimization (2019, methodology): “Non-orthogonal multiple access (NOMA) is one of the key technologies in future wireless communication networks due to its higher SE achievement, user fairness guarantee, and massive connectivity support [7], [8].”
Non-Orthogonal Multiple Access: Common Myths and Critical Questions (2018, background): “In light of recent research, experimental results, and practical developments in various settings, see e.g. [1], [6]–[8], today it is known that SIC is amenable to implementation, and has been employed in commercial systems, such as CDMA and IEEE 802.15.4 [9].”
Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G (2021, background): “Depending on whether each user is allocated orthogonal resources or not, the current multiple access techniques can be loosely classified into two categories, namely orthogonal transmission strategies and non-orthogonal transmission strategies [5], [6].”