Applications of Machine Learning in Wireless Communications

Ruisi He

ISBN 10: 1785616579 / ISBN 13: 9781785616570

Published by Institution Of Engineering & Technology Aug 2019, 2019

About this Item

Neuware - This edited book presents current and future developments and trends in wireless communication technologies based on contributions from machine learning and other fields of artificial intelligence, including channel modeling, signal estimation and detection, energy efficiency, and more.

Seller Inventory # 9781785616570

Bibliographic Details

• Title: Applications of Machine Learning in Wireless Communications
• Publisher: Institution Of Engineering & Technology Aug 2019
• Publication Date: 2019
• Language: English
• ISBN 10: 1785616579
• ISBN 13: 9781785616570
• Binding: Buch
• Condition: Neu
• Dimensions: 240W x 165H x 30D millimeters 240 millimeters width by 165 millimeters height by 30 millimeters depth
• Weight: 957 grams

About this title

Synopsis

Machine learning explores the study and development of algorithms that can learn from and make predictions and decisions based on data. Applications of machine learning in wireless communications have been receiving a lot of attention, especially in the era of big data and IoT, where data mining and data analysis technologies are effective approaches to solving wireless system evaluation and design issues.

This edited book presents current and future developments and trends in wireless communication technologies based on contributions from machine learning and other fields of artificial intelligence, including channel modelling, signal estimation and detection, energy efficiency, cognitive radios, wireless sensor networks, vehicular communications, and wireless multimedia communications. The book is aimed at a readership of researchers, engineers and students working on wireless communications and machine learning, especially those working with big data and artificial intelligence multi-disciplinary fields related to wireless communication technologies.

About the Authors

Ruisi He is a Professor at the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China. His research interests include measurement and modelling of wireless channels, machine learning and clustering analysis in wireless communications, vehicular and high-speed railway communications, 5G massive MIMO and high frequency communication techniques.

Zhiguo Ding is a Professor at the School of Electrical and Electronic Engineering at the University of Manchester, UK. He holds a Ph. D degree in Electrical Engineering from Imperial College London, UK. His research interests are in 5G networks, game theory, cooperative and energy harvesting networks and statistical signal processing.