Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks A Reinforcement Learning Perspective

Language: English

Published by Springer, 2019

9811511195 / 9789811511196

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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 is revealed beyond QoS under the framework of multi-armed bandit (MAB). The second part (chapter 4 and 5) focuses on how to meet dynamic user demand in complex and uncertain heterogeneous wireless networks under the framework of markov decision process (MDP). The third part (chapter 6 and 7) focuses on how to meet heterogeneous user demand for multiple users inlarge-scale networks under the framework of game theory. Efficient RL algorithms with practical constraints and considerations are proposed to optimize QoE for realizing intelligent online network selection for future mobile networks. This book is intended as a reference resource for researchers and designers in resource management of 5G networks and beyond. Sprache: Englisch Gewicht in Gramm: 343.…

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Title
Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks A Reinforcement Learning Perspective
Author
Kun Xu, Yuhua Xu, Bin Jiang, Zhiyong Du, Qihui Wu
Publisher
Springer
Publication year
2019
Condition
Neu
Binding
Gebundene Ausgabe
Language
English
ISBN 10
9811511195
ISBN 13
9789811511196
Item weight
343 grams

Home-set

Mannheim, Germany

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AbeBooks seller since April 13, 2026

Shipping rates from Germany to U.S.A.

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Home-set

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