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Wireless Communications and Machine Learning

Authors

Le Liang
, Southeast University, Nanjing,
Shi Jin
, Southeast University, Nanjing,
Hao Ye
, University of California, Santa Cruz,
Geoffrey Ye Li
, Imperial College of Science, Technology and Medicine, London
Published 2025

Description

This focused textbook demonstrates cutting-edge concepts at the intersection of machine learning (ML) and wireless communications, providing students with a deep and insightful understanding of this emerging field. It introduces students to a broad array of ML tools for effective wireless system design, and supports them in exploring ways in which future wireless networks can be designed to enable more effective deployment of federated and distributed learning techniques to enable AI systems. Requiring no previous knowledge of ML, this accessible…

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Key features

  • Coverage includes deep learning for improved channel modeling and estimation; learning-based methods for key communication receiver functionalities; end-to-end learning-enabled system design, and optimized radio resource allocation
  • Features a discussion of 'wireless for AI' that extends the 'AI for wireless' toolset to give more efficient machine learning training and inference
  • Requires no previous knowledge of machine learning, instead building on existing student understanding of probability, signals and systems, and wireless communications

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