AI-enabled 6G networks and applications

AI-enabled 6G networks and applications

Detalles Bibliográficos
Otros Autores: Gupta, Deepak, Ph.D., editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, New Jersey : Wiley [2023]
Materias:
Mobile communication systems.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009811332506719
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright Page
  • Contents
  • List of Contributors
  • Preface
  • About the Editors
  • Chapter 1 Metaheuristic Moth Flame Optimization Based Energy Efficient Clustering Protocol for 6G Enabled Unmanned Aerial Vehicle Networks
  • 1.1 Introduction
  • 1.2 The Proposed Model
  • 1.2.1 Network Model
  • 1.2.2 Algorithmic Procedure of MFO Algorithm
  • 1.2.3 Design of MMFO-EEC Technique
  • 1.3 Experimental Validation
  • 1.4 Conclusion
  • References
  • Chapter 2 A Novel Data Offloading with Deep Learning Enabled Cyberattack Detection Model for Edge Computing in 6G Networks
  • 2.1 Introduction
  • 2.2 The Proposed Model
  • 2.2.1 RNN Based Traffic Flow Forecasting
  • 2.2.2 ASCE Based Data Offloading
  • 2.2.3 SAE Based Cyberattack Detection
  • 2.2.4 CSO Based Parameter Optimization
  • 2.3 Performance Validation
  • 2.4 Conclusion
  • References
  • Chapter 3 Henry Gas Solubility Optimization with Deep Learning Enabled Traffic Flow Forecasting in 6G Enabled Vehicular Networks
  • 3.1 Introduction
  • 3.2 The Proposed Model
  • 3.2.1 Z-Score Normalization
  • 3.2.2 DBN Based Prediction Model
  • 3.2.3 HSGO Based Hyperparameter Optimization Model
  • 3.3 Experimental Validation
  • 3.4 Conclusion
  • References
  • Chapter 4 Crow Search Algorithm Based Vector Quantization Approach for Image Compression in 6G Enabled Industrial Internet of Things Environment
  • 4.1 Introduction
  • 4.2 The Proposed Model
  • 4.2.1 Overview of VQ
  • 4.2.2 LBG Model
  • 4.2.3 Process Involved in CSAVQ-ICIIoT Model
  • 4.3 Results and Discussion
  • 4.4 Conclusion
  • References
  • Chapter 5 Design of Artificial Intelligence Enabled Dingo Optimizer for Energy Management in 6G Communication Networks
  • 5.1 Introduction
  • 5.2 The Proposed Model
  • 5.2.1 Process Involved in DOA
  • 5.2.2 Steps Involved in Energy Management Scheme.
  • 5.3 Experimental Validation
  • 5.4 Conclusion
  • References
  • Chapter 6 Adaptive Whale Optimization with Deep Learning Enabled RefineDet Network for Vision Assistance on 6G Networks
  • 6.1 Introduction
  • 6.2 The Proposed Model
  • 6.2.1 Image Augmentation and Annotation
  • 6.2.2 RefineDet Based Object Detection
  • 6.2.3 Hyperparameter Tuning Using AWO Algorithm
  • 6.2.4 Distance Measurement
  • 6.3 Results and Discussion
  • 6.4 Conclusion
  • References
  • Chapter 7 Efficient Deer Hunting Optimization Algorithm Based Spectrum Sensing Approach for 6G Communication Networks
  • 7.1 Introduction
  • 7.2 Related Works
  • 7.3 The Proposed Model
  • 7.4 Experimental Validation
  • 7.5 Conclusion
  • References
  • Chapter 8 Elite Oppositional Hunger Games Search Optimization Based Cooperative Spectrum Sensing Scheme for 6G Cognitive Radio Networks
  • 8.1 Introduction
  • 8.2 Related Works
  • 8.3 The Proposed Model
  • 8.3.1 Design of EOHGSO Algorithm
  • 8.3.2 Application of EOHGSO Algorithm for CSS
  • 8.4 Experimental Validation
  • 8.5 Conclusion
  • References
  • Index
  • EULA.

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