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Autor(en): 
  • Weihua Zhuang
  • Conghao Zhou
  • Shisheng Hu
  • Edge Intelligence-Empowered Integrated Sensing and Communications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (Oktober 2026)  
    Genre:  EDV / Informatik 
     
    AI Model Lifecycle Management / Collaborative Inference / Communications Engineering, Networks / Computer Communication Networks / Continual Learning / Digital Twin / Drahtlostechnologie / Edge Intelligence
    ISBN:  9783032342812 
    EAN-Code: 
    9783032342812 
    Verlag:  Springer International Publishing 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Seiten:  102 
    Illustration:  X, 102 p. 31 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    This book investigates edge intelligence-empowered integrated sensing and communications (ISAC) systems from the perspectives of artificial intelligence (AI) model management and resource management. It first introduces the evolution, core principles, and representative use cases of the ISAC paradigm, and then presents a virtualization-centric framework based on network slicing, digital twins, and model-based and data-driven optimization. Under this framework, this book presents task offloading and edge continual learning approaches for intelligent sensing data processing, as well as proactive and real-time resource management methods to support efficient resource utilization and service satisfaction.

    Sensing and communications are essential functions in modern autonomous systems and mobile applications. Future wireless networks are expected to integrate these functions by orchestrating network resources, giving rise to the ISAC paradigm. While this integration improves resource utilization efficiency and delivers mutual performance gains, ISAC systems face challenges in sensing signal processing and network resource management due to richer environmental awareness requirements and dynamic service demand.

    By examining the interplay between AI model management and resource management, this book provides customized designs and efficient algorithms to support edge intelligence for ISAC. It serves as a reference for researchers, industry professionals, and graduate students in related fields.

     

     

     

      



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