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Deep Learning Enhanced NOMA System: A Survey on Future Scope and Challenges

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Abstract

As a key important approach for next generation communication systems, Non-Orthogonal Multiple Access (NOMA) has made high attention in the wireless communication. NOMA allows users to transmit the information at same time and frequency to enhance the spectral efficiency compared to Orthogonal Multiple Access (OMA) techniques. Successive Interference Cancellation (SIC), channel estimation and power allocation are essentials for NOMA aided communication system. In recent times, Deep Learning (DL) has attraction towards solving problems in wireless communication; also it makes the system computationally simpler than the conventional system. In this paper we provide the recent research activities of Deep Learning aided NOMA system. Also we present the applications of Deep Learning in other wireless technologies.

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  1. Department of ECE, SRM Institute of Science and Technology, Vadapalani campus, No.1. Jawaharlal Nehru Road, Vadapalani, Chennai, 600026, India

    Vasuki Andiappan

  2. Department of ECE, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chengalpattu, 603203, India

    Vijayakumar Ponnusamy

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Andiappan, V., Ponnusamy, V. Deep Learning Enhanced NOMA System: A Survey on Future Scope and Challenges. Wireless Pers Commun 123, 839–877 (2022). https://doi.org/10.1007/s11277-021-09160-1

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