人工智慧無線通訊
Artificial Intelligence Wireless
| 節 | 週四 |
|---|---|
A 18:30–19:20 | 人工智慧無線通訊 3 節連堂 |
B 19:30–20:20 | |
C 20:30–21:20 |
* 根據陽明交大上課時間表所列
Evolution for Wireless Communication AI Wireless or Wireless AI Applications Mathematical Fundamentals in AI Wireless Physical Layer Communication in AI Wireless Network Management in AI Wireless Network Operation in AI Wireless Large Language Model for GenAI Wireless Applications Part I: Spectrum Intelligence and Adaptive Resource Management 1. Machine Learning for Spectrum Access and Sharing 2. Reinforcement Learning for Resource Allocation in Cognitive Radio Networks 3. Machine Learning for Spectrum Sharing in Millimeter-Wave Cellular Networks 4. Deep Learning–Based Coverage and Capacity Optimization 5. Machine Learning for Optimal Resource Allocation 6. Machine Learning in Energy Efficiency Optimization 7. Deep Learning Based Traffic and Mobility Prediction 8. Machine Learning for Resource-Efficient Data Transfer in Mobile Crowdsensing Part II Transmission Intelligence and Adaptive Baseband Processing 9. Machine Learning–Based Adaptive Modulation and Coding Design 10. Neural Networks for Signal Intelligence: Theory and Practice 11. Neural Network–Based Wireless Channel Prediction Part III Network Intelligence and Adaptive System Optimization 12. Machine Learning for Digital Front-End: Comprehensive Overview 13. Neural Networks for Full-Duplex Radios: Self-Interference Cancellation 14. Machine Learning for Context-Aware Cross-Layer Optimization 15. Physical-Layer Location Verification by Machine Learning 16. Deep Multi-Agent Reinforcement Learning for Cooperative Edge Caching
無線通訊、Python 程式Coding (Pytorch/TensorFlow) 、機器學習或深度學習
無
1. Assignments: 20% 2. Mid-Term: 30% 3. Final Exam 30% 4. Project 20%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Overview of AI in Wireless Communications |
| 第 2 週 | RFSoC SDR-Based for Wireless Communications: Theory, Practices, and Applications |
| 第 3 週 | RFSoC SDR-Based for Wireless Communications: Network Resilient Platform |
| 第 4 週 | AI in Radio Resource Management (I) – Resource Allocation in Cognitive Radio Networks |
| 第 5 週 | AI in Radio Resource Management (II) – Adaptive Spectrum Sharing |
| 第 6 週 | AI in Radio Resource Management (III) – Joint-Sensing in ISAC |
| 第 7 週 | AI in Transmission Intelligence (I) – Channel Prediction & Adaptive Modulation |
| 第 8 週 | AI in Transmission Intelligence (II) – Adaptive Link-Level Transmission & Ray Tracing |
| 第 9 週 | AI in Transmission Intelligence (III) – AI in Network Intelligence (I) – System Integration and System Optimization |
| 第 10 週 | AI in Network Intelligence (II) – Machine Learning for Cross-Layer Optimization |
| 第 11 週 | AI in Network Intelligence (III) – GenAI for Wireless Systems |
| 第 12 週 | Mid-Term Exams : Final project Proposal (by students) |
| 第 13 週 | Advanced Topics (I) – O-RAN/AI-RAN : Overview, Practices, and Applications |
| 第 14 週 | Advanced Topics (II) – 6G SatCom : Overview, Practices, and Applications |
| 第 15 週 | Advanced Topics (III) – GenAI in Wireless : Theory, Practices, and Applications |
| 第 16 週 | Final-Term Exams : Final project Presentation (by students) |
本課程並無指定教科書,但是有多本相關參考書。 1. Key Technologies for 5G Wireless Systems, Vincent W. S. Wong, Robert Schober, Derrick W. K. Ng, Li-Chun Wang, Cambridge 2017. 2. SDR with Zynq Ultrascale+ RFSoC, AMD, 2022. https://www/RFSoCbook.com 3. Shaping future 6G networks: Needs, impacts, and technologies. John Wiley & Sons, 2021.
- 地點
- ED312
- 時間
- 每週三晚上18:30~21:00
- 聯絡方式
- wang@nycu.edu.tw