Sequential Learning and Decision-Making in Wireless Resource Management

This book lays out the theoretical foundation of the so-called multi-armed bandit (MAB) problems and puts it in the context of resource management in wireless networks. Part I of the book presents the formulations, algorithms and performance of three forms of MAB problems, namely, stochastic, Markov...

Full description

Bibliographic Details
Main Authors: Zheng, Rong (Author), Hua, Cunqing (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Series:Wireless Networks,
Subjects:
Online Access:Full Text via HEAL-Link
Description
Summary:This book lays out the theoretical foundation of the so-called multi-armed bandit (MAB) problems and puts it in the context of resource management in wireless networks. Part I of the book presents the formulations, algorithms and performance of three forms of MAB problems, namely, stochastic, Markov and adversarial. Covering all three forms of MAB problems makes this book unique in the field. Part II of the book provides detailed discussions of representative applications of the sequential learning framework in cognitive radio networks, wireless LANs and wireless mesh networks. Both individuals in industry and those in the wireless research community will benefit from this comprehensive and timely treatment of these topics. Advanced-level students studying communications engineering and networks will also find the content valuable and accessible.
Physical Description:XIII, 118 p. 22 illus. online resource.
ISBN:9783319505022
ISSN:2366-1186