Książka Reinforcement Learning for Reconfigurable Intelligent Surfaces Alice Faisal

Reinforcement Learning for Reconfigurable Intelligent Surfaces

Assisted Wireless Communication Systems

Język: Angielski
Oprawa: Miękka
Wydawca: Springer, Berlin
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
196.01
This book presents the intersection of two dynamic fields: Reinforcement Learning (RL) and RIS- Assi...

Informacje o książce

Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2024
strony
55
EAN
9783031525537
Enbook ID
44610599
Waga
119
Wymiary
155 x 235

Pełny opis

This book presents the intersection of two dynamic fields: Reinforcement Learning (RL) and RIS- Assisted Wireless Communications. With an emphasis on both discrete and continuous problems, it introduces a comprehensive overview of RL techniques and their applications in the evolving world of RIS-assisted wireless communications. Chapter 1 introduces the fundamentals of RL and deep RL (DRL), providing a solid foundation for understanding subsequent chapters. It  also presents the Q-learning, deep Q-learning, and deep deterministic policy gradient algorithms. Chapter 2 provides a holistic overview of RIS-assisted systems and details several use cases in wireless communications. Then, Chapters 3 and 4 present various applications of the discrete and continuous DRL to RIS-assisted wireless communications. From maximizing the sum-rate to minimizing, the system resources and maximizing the energy efficiency. These chapters showcase the versatility of the DRL algorithms in tackling a range of challenges. This book concludes with Chapter 5, which introduces the challenges and future directions in this field. It explores the particulars of hyperparameter tuning, problem design, and complexity analysis, while also highlighting the potential of hybrid DRL, multi-agent DRL, and transfer learning techniques for advancing wireless communication systems. Optimizing RIS-Assisted Wireless Systems requires powerful algorithms to cope with the dynamic propagation environment. DRL is envisioned as one of the key enabling techniques to exploit the full potential of RIS-Assisted Wireless Communication Systems. It empowers these systems to intelligently adapt to dynamic wireless environments, maximize performance metrics, and adjusts their configurations to accommodate diverse use cases efficiently. This book serves as a valuable resource, shedding light on the potential of DRL to optimize RIS-Assisted Wireless Communication, enabling researchers, engineers, advanced level students in computer science and electrical engineering and enthusiasts to grasp the intricacies of this topic. It offers a comprehensive understanding of the principles, applications, and challenges, making it a reference to recognize the full potential of the RIS technology in modern wireless communication systems.

Możesz być zainteresowany

Reinforcement Learning

Richard S. Sutton
456.60
1 299.95
277.65
607.30

Mediated Citizenship

Karin Wahl-Jorgensen
289.32
202.29

Reinforcement Learning

D. Phil Winder Ph.
208.88
137.22
36.72

Good Lie

A. R. Torre
53.98

Right(s) to Water

Pierre Thielbörger
434.14
463.58
49.99

Beginning EJB in Java EE 8

Jonathan Wetherbee
283.24

Way to Grow

Simon Akeroyd
77.14

Klienci, którzy kupili tę książkę, kupili również

LUCIA

MINIER
41.11

China

Henry A. Kissinger
76.84
156.28

The Boxer 02

Karolin Schulze
67.76

Noves tendencies en finances corporatives

Associació Catalana de Comptabilitat i Direcció
117.56
53.49

Techno

Philip Anz
134.83
77.84

Qu'il soit extraordinaire !

Les Editions du 20 Décembre
57.18

Perspective actionnelle

CLE International
148.20
32.72

L'homme-montage

Bernd Stiegler
209.18