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Dinh Thai Hoang Nguye Deep Reinforcement Learning for Wir (Hardback) (UK IMPORT)

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
Book Title
Deep Reinforcement Learning for Wireless Communications and Netwo
Title
Deep Reinforcement Learning for Wireless Communications and Netwo
Subtitle
Theory, Applications and Implementation
EAN
9781119873679
ISBN
9781119873679
Genre
Computing & Internet
Release Date
07/25/2023
Release Year
2023
Country/Region of Manufacture
US
Subject Area
Computers, Technology & Engineering
Publication Name
Deep Reinforcement Learning for Wireless Communications and Networking : Theory, Applications and Implementation
Item Length
9 in
Publisher
Wiley & Sons, Incorporated, John
Subject
Mobile & Wireless Communications, Intelligence (Ai) & Semantics, Security / Networking
Publication Year
2023
Type
Textbook
Format
Hardcover
Language
English
Item Height
0.7 in
Author
Dinh Thai Hoang, Diep N. Nguyen, Nguyen Van Huynh, Ekram Hossain, Dusit Niyato
Item Width
6 in
Item Weight
34.5 Oz
Number of Pages
288 Pages

About this product

Product Information

Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking. Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design. Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as: Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learning Physical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer security Medium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell association Network layer applications, covering traffic routing, network classification, and network slicing With comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1119873673
ISBN-13
9781119873679
eBay Product ID (ePID)
27058364225

Product Key Features

Author
Dinh Thai Hoang, Diep N. Nguyen, Nguyen Van Huynh, Ekram Hossain, Dusit Niyato
Publication Name
Deep Reinforcement Learning for Wireless Communications and Networking : Theory, Applications and Implementation
Format
Hardcover
Language
English
Subject
Mobile & Wireless Communications, Intelligence (Ai) & Semantics, Security / Networking
Publication Year
2023
Type
Textbook
Subject Area
Computers, Technology & Engineering
Number of Pages
288 Pages

Dimensions

Item Length
9 in
Item Height
0.7 in
Item Width
6 in
Item Weight
34.5 Oz

Additional Product Features

LCCN
2023-014416
Intended Audience
Scholarly & Professional
Lc Classification Number
Q325.6.H63 2023
Copyright Date
2023
Dewey Decimal
006.31
Dewey Edition
23

Item description from the seller

Business seller information

Value Added Tax Number:
  • GB 864154811
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