AI-enabled 6G networks and applications / / edited by Deepak Gupta, [and four others]

• Pubblicazione: Hoboken, New Jersey : , : Wiley, , [2023]; ©2023
• Descrizione fisica: 1 online resource (179 pages)
• Disciplina: 621.384
• Soggetto topico: Mobile communication systems
• Persona (resp. second.): GuptaDeepak, Ph.D.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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.
• Titolo autorizzato: AI-enabled 6G networks and applications
• ISBN: 1-119-81272-0; 1-119-81270-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910830135403321
• Lo trovi qui: Univ. Federico II