Session I - AI Radio Access (On-demand)
- RL Random Access for Delay-Constrained Heterogeneous Wireless Networks: A Two-User Case
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Danzhou Wu and Lei Deng (Shenzhen University, China); Zilong Liu (University of Essex, United Kingdom (Great Britain)); Yijin Zhang (Nanjing University of Science and Technology, China); Yunghsiang Sam Han (University of Electronic Science and Technology of China, China)
- End-to-End Learning of OFDM Waveforms with PAPR and ACLR Constraints
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Mathieu Goutay (Nokia Bell Labs France, France); Fayçal Ait Aoudia (NVIDIA, France); Jakob Hoydis (Nvidia, France); Jean-Marie Gorce (INSA-Lyon & CITI, Inria, France)
- Deep Learning Based OFDM Channel Estimation Using Frequency-Time Division and Attention Mechanism
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Ang Yang, Peng Sun, Tamrakar Rakesh and Bule Sun (vivo Communication Research Institute, China); Fei Qin (vivo Mobile Communication Technology Co., Ltd, Beijing, China)
- LWCNet: Lightweight Complex Neural Network for Real-Time Channel Estimation
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DongHa Bahn, Jae-Il Jung, Jun-Ik Jang, Changbae Yoon and Chanjong Park (Samsung Electronics, Korea (South))
- Subspace Based Hierarchical Channel Clustering in Massive MIMO
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Roberto Matheus Pinheiro Pereira (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA) & Universitat Politècnica de Catalunya, Spain); Xavier Mestre (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain); David Gregoratti (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Spain)
Session II - Distributed Learning & Smart Scheduling (On-demand)
- Deep Neural Network based Minimum Length Scheduling in Wireless Powered Communication Networks
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Nasir Khan and Sinem Coleri (Koc University, Turkey)
- Joint Topology and Computation Resource Optimization for Federated Edge Learning
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Shanfeng Huang (Southern University of Science and Technology, China & The University of Hong Kong, Hong Kong); Shuai Wang and Rui Wang (Southern University of Science and Technology, China); Kaibin Huang (The University of Hong Kong, Hong Kong)
- Distributed Learning for Time-varying Networks: A Scalable Design
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Jian Wang (Huawei Technologies, China); Yourui Huangfu and Rong Li (Huawei Technologies, Co. Ltd., China); Yiqun Ge (Huawei Technologies Canada Inc., Canada); Jun Wang (Huawei Technologies Co. Ltd, China)
- In-network Learning for Distributed Training and Inference in Networks
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Matei Catalin Moldoveanu (Université Gustave Eiffel & Huawei, France); Abdellatif Zaidi (Université Paris-Est, France)
- Deep Reinforcement Learning for Joint Spectrum and Power Allocation in Cellular Networks
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Yasar Sinan Nasir and Dongning Guo (Northwestern University, USA)
Session III - Invited Talks:
| 9:00 - 9:40 | Invited Talk I: From End-to-End to Semantic Communications based on Deep Learning
Prof. Geoffrey Ye Li, Imperial College London |
| 9:40 - 10:20 | Invited Talk II: Physics-Inspired Neural Network Design for Channel Representation and Prediction
Prof. Zhaoyang Zhang, Zhejiang University |
| 10:20 - 11:00 | Invited Talk III: Towards an AI related mathematical theory of Communication
Dr. Jean-Claude Belfiore, Huawei Technologies |
