Songyang Zhang,
Shuai Zhang,
Chuan Huang
Generative Learning for Wireless Communications
Fundamentals and Applications
Paperback Engels 2026 9780443414978Levertijd ongeveer 9 werkdagen
Gratis verzonden
Samenvatting
Generative learning (GL) has emerged as an essential tool for data processing and network optimization in the broad area of next-generation communication systems. Generative Learning for Wireless Communications: Fundamentals and Applications provides a comprehensive and systematic tutorial for applying generative learning models to wireless communications. It explains the core concepts of state-of-the-art generative learning models, including generative adversarial nets, variational autoencoder, and other advanced models, such as transformers and diffusion models, and then shows their application to specific areas in wireless communications.
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Inhoudsopgave
Part I - Introduction<br>1. Wireless Communications in the Era of Artificial Intelligence<br>2. Overview of Generative AI models and Potentials in Wireless Communications<br><br>Part II – Foundations of Generative Learning Models<br>3. Fundamentals of Generative Adversarial Nets<br>4. Fundamentals of Variational Auto Encoder<br>5. Introduction of Advanced Generative AI Models: Diffusion and Transformers<br><br>Part III – Generative AI for Physical Networking and Communication Theory<br>6. Generative AI for Channel Modeling and Estimation<br>7. Generative AI for Integrated Sensing and Communications<br>8. Generative AI for Spectrum Sensing and Coverage Estimation<br><br>Part IV – Generative AI for Data Transmission and Communication Architecture<br>9. Generative AI for Joint Source and Channel Coding<br>10. Generative AI for Data-Oriented Communications<br>11. Generative AI for Semantic and Task-Oriented Communications<br><br>Part V – Generative AI for Distributed Networking and Edge Computing<br>12. Generative AI Empowered Federated Learning<br>113. Generative AI for Mobile Edge Computing<br><br>Part VI – Generative AI for Emerging Technologies and Applications<br>14. Generative AI and Digital Twin<br>15. AI-Generated Content Service<br>16. Trustworthy Generative AI for Wireless Communications<br>17. Data Management for Generative AI in Wireless Communications<br><br>Part VII – Conclusion<br>18. Summary, Insights and Future Directions
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