Artificial Intelligence Enabled Radio Propagation for Communications—Part II: Scenario Identification and Channel Modeling

Author:

Huang Chen1ORCID,He Ruisi2ORCID,Ai Bo1ORCID,Molisch Andreas F.3ORCID,Lau Buon Kiong4ORCID,Haneda Katsuyuki5ORCID,Liu Bo6ORCID,Wang Cheng-Xiang7ORCID,Yang Mi2,Oestges Claude8ORCID,Zhong Zhangdui2ORCID

Affiliation:

1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China

2. State Key Laboratory of Rail Traffic Control and Safety and the Key Laboratory of Railway Industry of Broadband Mobile Information Communications, Beijing Jiaotong University, Beijing, China

3. Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA

4. Department of Electrical and Information Technology, Lund University, Lund, Sweden

5. Department of Radio Science and Engineering, Aalto University, Espoo, Finland

6. School of Engineering, University of Glasgow, Glasgow, U.K.

7. Purple Mountain Laboratories, Nanjing, China

8. Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Universite Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

State Key Laboratory of Rail Traffic Control and Safety

Fundamental Research Funds for the Central Universities

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

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