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Machine Learning and Wireless Communications

Hardback

Main Details

Title Machine Learning and Wireless Communications
Authors and Contributors      Edited by Yonina C. Eldar
Edited by Andrea Goldsmith
Edited by Deniz Gunduz
Edited by H. Vincent Poor
Physical Properties
Format:Hardback
Pages:554
Dimensions(mm): Height 251,Width 177
Category/GenreCommunications engineering and telecommunications
Algorithms and data structures
ISBN/Barcode 9781108832984
ClassificationsDewey:621.382
Audience
Tertiary Education (US: College)
Illustrations Worked examples or Exercises; Worked examples or Exercises

Publishing Details

Publisher Cambridge University Press
Imprint Cambridge University Press
Publication Date 4 August 2022
Publication Country United Kingdom

Description

How can machine learning help the design of future communication networks - and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications - an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.

Author Biography

Yonina C. Eldar is a professor of Electrical Engineering at the Weizmann Institute of Science, where she heads the Center for Biomedical Engineering and Signal Processing. She is also a visiting professor at MIT and at the Broad Institute, and an adjunct professor at Duke University. She is a member of the Israel Academy of Sciences and Humanities, an IEEE fellow, and a EURASIP fellow. Andrea Goldsmith is the Dean of Engineering and Applied Science and the Arthur LeGrand Doty Professor of Electrical Engineering at Princeton University. She is a member of the US National Academy of Engineering and the American Academy of Arts and Sciences. In 2020, she received the Marconi Prize. Deniz Gu ndu z is a professor of Information Processing in the Electrical and Electronic Engineering Department of Imperial College London in the UK, where he serves as the Deputy Head of the Intelligent Systems and Networks Group. He is also a part-time faculty member at the University of Modena and Reggio Emilia in Italy. H. Vincent Poor is the Michael Henry Strater University Professor at Princeton University. He is a member of the US National Academy of Engineering and the US National Academy of Sciences. In 2017, he received the IEEE Alexander Graham Bell Medal.