1.

Record Nr.

UNINA9910484135903321

Autore

Wang Kehao

Titolo

Restless multi-armed bandit in opportunistic scheduling / / Kehao Wang, Lin Chen

Pubbl/distr/stampa

Cham, Switzerland : , : Springer, , [2021]

©2021

ISBN

3-030-69959-5

Edizione

[1st ed. 2021.]

Descrizione fisica

1 online resource (XII, 151 p. 12 illus. in color.)

Disciplina

621.384131

Soggetti

Wireless communication systems - Mathematical models

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Introduction -- RMAB in Opportunistic Scheduling -- Optimality of Myopic Policy with Imperfect Sensing -- Whittle Index Policy with Imperfect Sensing -- Heuristic Policy with Imperfect Sensing -- Optimality of Myopic Policy with Imperfect Observation -- Whittle Index Policy for Multi-State Channel Scheduling -- Conclusion.

Sommario/riassunto

This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.e., wireless communication systems. The book provides a systematic treatment of the theoretical foundation and algorithmic tools necessarily in the design of computation-efficient algorithms and protocols in stochastic scheduling. The problems addressed in the book are of both fundamental and practical importance. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on stochastic scheduling and their applications, both from theoretical and engineering perspective. Introduces Restless Multi-Armed Bandit (RMAB) and presents its relevant tools involved in machine learning and how to adapt them for application; Elaborates on research bringing the conventional decision theory and stochastic optimal technology into wireless communication applications involving machine learning; Delivers a comprehensive treatment on problems ranging from theoretical modeling and analysis, to practical algorithm design and optimization.