000 02743 a2200265 4500
003 OSt
020 _a9781119873679
040 _cIIT Kanpur
041 _aeng
082 _a621.384
_bD36
245 _aDeep reinforcement learning for wireless communications and networking
_btheory, applications and implementation
_cDinh Thai Hoang ...[et al.]
260 _bJohn Wiley
_c2023
_aHoboken
300 _axxii, 264p
520 _aDeep 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.
650 _aReinforcement learning
650 _aDeep learning
650 _aWireless communication
650 _aComputer networks
700 _aHoang, Dinh Thai
700 _aHuynh, Nguyen Van
700 _aNguyen, Diep N.
700 _aHossain, Ekram
700 _aNiyato, Dusit
942 _cBK
999 _c567175
_d567175