LEADER 04216nam 22005533 450 001 9911020005303321 005 20241216120649.0 010 $a9781394227945 010 $a1394227949 010 $a9781394227938 010 $a1394227930 010 $a9781394227952 010 $a1394227957 035 $a(CKB)36976906000041 035 $a(MiAaPQ)EBC31836407 035 $a(Au-PeEL)EBL31836407 035 $a(OCoLC)1481580740 035 $a(Perlego)4740462 035 $a(EXLCZ)9936976906000041 100 $a20241216d2025 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence for Future Networks 205 $a1st ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2025. 210 4$dİ2025. 215 $a1 online resource (414 pages) 311 08$a9781394227921 311 08$a1394227922 327 $aIntelligent beam prediction and tracking -- Signal detection with machine learning -- AI-aided channel prediction -- Semantic communications -- Federated learning for wireless communications -- Federated learning in mesh networks -- Antenna design using artificial intelligence -- AI-driven approaches for solving electromagnetic inverse problems -- Reflectarray-based RIS-1 design using support vector machine to enhance mm-wave 5G coverage -- AI at the physical layer for wireless network security and privacy. 330 8 $aAn exploration of connected intelligent edge, artificial intelligence, and machine learning for B5G/6G architecture Artificial Intelligence for Future Networks illuminates how artificial intelligence (AI) and machine learning (ML) influence the general architecture and improve the usability of future networks like B5G and 6G through increased system capacity, low latency, high reliability, greater spectrum efficiency, and support of massive internet of things (mIoT). The book reviews network design and management, offering an in-depth treatment of AI oriented future networks infrastructure. Providing up-to-date materials for AI empowered resource management and extensive discussion on energy-efficient communications, this book incorporates a thorough analysis of the recent advancement and potential applications of ML and AI in future networks. Each chapter is written by an expert at the forefront of AI and ML research, highlighting current design and engineering practices and emphasizing challenging issues related to future wireless applications. Some of the topics include: * Signal processing and detection, covering preprocess and level signals, transform signals and extract features, and training and deploying AI models and systems * Channel estimation and prediction, covering channel characteristics, modeling, and classic learning-aided and AI-aided estimation techniques * Resource allocation, covering resource allocation optimization and efficient power consumption for different computing paradigms such as Cloud, Edge, Fog, IoT, and MEC * Antenna design using AI, covering basics of antennas, EM simulator/optimization algorithms, and surrogate modeling Identifying technical roadblocks and sharing cutting-edge research on developing methodologies, Artificial Intelligence for Future Networks is an essential reference on the subject for professionals and researchers involved in the field of wireless communications and networks, along with graduate and PhD students in electrical and computer engineering programs of study. 606 $a5G mobile communication systems$xTechnological innovations 606 $aArtificial intelligence$xIndustrial applications 615 0$a5G mobile communication systems$xTechnological innovations. 615 0$aArtificial intelligence$xIndustrial applications. 676 $a621.384 700 $aMatin$b Mohammad A$01064775 701 $aGoudos$b Sotirios K$01838902 701 $aKaragiannidis$b George K$01838903 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911020005303321 996 $aArtificial Intelligence for Future Networks$94417996 997 $aUNINA