Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks
This book presents reinforcement learning (RL) based solutions for user-centric online network selection optimization. The main content can be divided into three parts. The first part (chapter 2 and 3) focuses on how to learning the best network when QoE
- PDF / 4,449,154 Bytes
- 142 Pages / 453.544 x 683.151 pts Page_size
- 29 Downloads / 196 Views
r-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks A Reinforcement Learning Perspective
Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks
Zhiyong Du Bin Jiang Qihui Wu Yuhua Xu Kun Xu •
•
•
•
Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks A Reinforcement Learning Perspective
123
Zhiyong Du National University of Defense Technology Changsha, Hunan, China
Bin Jiang National University of Defense Technology Changsha, Hunan, China
Qihui Wu Nanjing University of Aeronautics and Astronautics Nanjing, Jiangsu, China
Yuhua Xu Army Engineering University of PLA Nanjing, China
Kun Xu National University of Defense Technology Changsha, Hunan, China
ISBN 978-981-15-1119-6 ISBN 978-981-15-1120-2 https://doi.org/10.1007/978-981-15-1120-2
(eBook)
© Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Preface
With the fast development of wireless communications, users nowadays are no longer satisfied with just being connected but pursue excellent service experience. Accordingly, how to promote users’ QoE (quality of experience) beyond traditional QoS (quality of service) has received great attention from academia and industry in recent years. To this end, this book provides a systematic study on user-centric optimization idea from the perspective of network selection in 5G heterogeneous networks, where (i) the features of user demand are analyzed and characterized for optimizing QoE, which, in turn, drives us to rethink the optimization process in resource management, and (ii) end users can play a more active role in improvi
Data Loading...
