Generative Learning for Wireless Communications

Part I - Introduction
1. Wireless Communications in the Era of Artificial Intelligence
2. Overview of Generative AI models and Potentials in Wireless Communications

Part II – Foundations of Generative Learning Models
3. Fundamentals of Generative Adversarial Nets
4. Fundamentals of Variational Auto Encoder
5. Introduction of Advanced Generative AI Models: Diffusion and Transformers

Part III – Generative AI for Physical Networking and Communication Theory
6. Generative AI for Channel Modeling and Estimation
7. Generative AI for Integrated Sensing and Communications
8. Generative AI for Spectrum Sensing and Coverage Estimation

Part IV – Generative AI for Data Transmission and Communication Architecture
9. Generative AI for Joint Source and Channel Coding
10. Generative AI for Data-Oriented Communications
11. Generative AI for Semantic and Task-Oriented Communications

Part V – Generative AI for Distributed Networking and Edge Computing
12. Generative AI Empowered Federated Learning
113. Generative AI for Mobile Edge Computing

Part VI – Generative AI for Emerging Technologies and Applications
14. Generative AI and Digital Twin
15. AI-Generated Content Service
16. Trustworthy Generative AI for Wireless Communications
17. Data Management for Generative AI in Wireless Communications

Part VII – Conclusion
18. Summary, Insights and Future Directions