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This chapter presents an overview of the fundamental concepts of machine learning (ML), including activation functions and learning mechanisms. It also discusses the application of ML-based techniques to various operations in NOMA-based network systems, such as user clustering, resource allocation, task offloading, successive interference cancellation (SIC), and beamforming design.

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Machine Learning (ML) in NOMA: Toward NGMA Networks

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  • 发表日期：

    2026年

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  • Mohammad Abdul Matin,
  • M. Rezwanul Mahmood

摘要

This chapter presents an overview of the fundamental concepts of machine learning (ML), including activation functions and learning mechanisms. It also discusses the application of ML-based techniques to various operations in NOMA-based network systems, such as user clustering, resource allocation, task offloading, successive interference cancellation (SIC), and beamforming design.