ARTIFICIAL INTELLIGENCE ENABLED NOMA TOWARD NEXT GENERATION MULTIPLE ACCESS

doi:10.1109/MWC.003.2200239

ARTIFICIAL INTELLIGENCE ENABLED NOMA TOWARD NEXT GENERATION MULTIPLE ACCESS

2023-02-01

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DOI：10.1109/MWC.003.2200239

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This article focuses on the application of artificial intelligence (AI) in non-orthogonal multiple access (NOMA), which aims to achieve automated, adaptive, and high-efficiency multi-user communications toward next generation multiple access (NGMA). First, the limitations of current scenario-specific multiple-antenna NOMA schemes are discussed, and the importance of AI for NGMA is highlighted. Then, to achieve the vision of NGMA, a novel cluster-free NOMA framework is proposed for providing scenario-adaptive NOMA communications, and several promising machine learning solutions are identified. To elaborate further, novel centralized and distributed machine learning paradigms are conceived for efficiently employing the proposed cluster-free NOMA framework in single-cell and multi-cell networks, where numerical results are provided to demonstrate the effectiveness. Furthermore, the interplays between the proposed cluster-free NOMA and emerging wireless techniques are presented. Finally, several open research issues of AI enabled NGMA are discussed.

Keywords:

Wireless communication

NOMA

Machine learning

Next generation networking

ARTIFICIAL INTELLIGENCE ENABLED NOMA TOWARD NEXT GENERATION MULTIPLE ACCESS

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