Non-Orthogonal Multiple Access in Multi-Cell Networks: Theory, Performance, and Practical Challenges
By W. Shin, Mojtaba Vaezi, Byungju Lee, David J. Love, Jungwoo Lee, H. Vincent Poor. IEEE Communications Magazine, 2016
364 citations recorded by the source corpus.
Non-orthogonal multiple access (NOMA) is a potential enabler for the development of 5G and beyond wireless networks. By allowing multiple users to share the same time and frequency, NOMA can scale up the number of served users, increase spectral efficiency, and improve user-fairness compared to existing orthogonal multiple access (OMA) techniques. While single-cell NOMA has drawn significant attention recently, much less attention has been given to multi-cell NOMA. This article discusses the opportunities and challenges of NOMA in a multi-cell environment. As the density of base stations and devices increases, inter-cell interference becomes a major obstacle in multi-cell networks. As such, identifying techniques that combine interference management approaches with NOMA is of great significance. After discussing the theory behind NOMA, this article provides an overview of the current literature and discusses key implementation and research challenges, with an emphasis on multi-cell NOMA.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/506977c3ea6fcbbb49fef93228e021cd9244b886
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Yuanwei Liu
- H. Vincent Poor
- Zhiguo Ding
- Lajos Hanzo
- Arumgam Nallanathan
- Zhijin Qin
- Maged Elkashlan
- Geoffrey Y. Li
Citations in the corpus
- A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art (2019, neutral): “NOMA has the potential to accommodate more users than the number of available subcarriers, which leads to various potentials, including massive connectivity, lower latency, higher spectral efficiency, and relaxed channel feedback [58].”
- Federated Learning for 6G: Applications, Challenges, and Opportunities (2021, background): “Therefore, there is a need to introduce new distributed learning techniques that can be used to address many resource management challenges, such as distributed power control for multicell NOMA [70], joint user association and beamforming design [67], and dynamic user clustering [82].”
- A Survey of Rate-Optimal Power Domain NOMA With Enabling Technologies of Future Wireless Networks (2019, neutral): “…(cid:108) (cid:108) [32] 2015 (cid:108) [33] 2015 (cid:108) [34] 2017 (cid:108) [35] 2017 (cid:108) [36] 2017 (cid:108) (cid:108) (cid:108) [37] 2017 (cid:108) [38] 2018 (cid:108) [39] 2018 (cid:108) [40] 2018 (cid:108) (cid:108) [41] 2018 (cid:108) [42] 2018 (cid:108) [43] 2018 (cid:108)…”
- Modulation and Multiple Access for 5G Networks (2017, background): “details about multi-cell MIMO-NOMA approaches can be found in [68].”
- Nonorthogonal Multiple Access for 5G and Beyond (2017, methodology): “[43] discussed the research challenges and opportunities in terms of NOMA in multi-cell networks, aiming for identifying techniques to manage the multi-cell interference in NOMA.”