How Long to Read Deep Reinforcement Learning for Wireless Communications and Networking

How Long Does it Take to Read Deep Reinforcement Learning for Wireless Communications and Networking?

It takes the average reader 4 hours and 56 minutes to read Deep Reinforcement Learning for Wireless Communications and Networking by Dinh Thai Hoang

Assuming a reading speed of 250 words per minute. Learn more

Description

Deep Reinforcement Learning for Wireless Communications and Networking 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.

How long is Deep Reinforcement Learning for Wireless Communications and Networking?

Deep Reinforcement Learning for Wireless Communications and Networking by Dinh Thai Hoang is 293 pages long, and a total of 74,129 words.

This makes it 99% the length of the average book. It also has 91% more words than the average book.

How Long Does it Take to Read Deep Reinforcement Learning for Wireless Communications and Networking Aloud?

The average oral reading speed is 183 words per minute. This means it takes 6 hours and 45 minutes to read Deep Reinforcement Learning for Wireless Communications and Networking aloud.

What Reading Level is Deep Reinforcement Learning for Wireless Communications and Networking?

Deep Reinforcement Learning for Wireless Communications and Networking is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Deep Reinforcement Learning for Wireless Communications and Networking?

Deep Reinforcement Learning for Wireless Communications and Networking by Dinh Thai Hoang is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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