IEEE Global Communications Conference
7–11 December 2021 // Madrid, Spain // Hybrid: In-Person and Virtual Conference
Connecting Cultures around the Globe


Session I - AI Radio Access (On-demand) 

RL Random Access for Delay-Constrained Heterogeneous Wireless Networks: A Two-User Case

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

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

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

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

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

Nasir Khan and Sinem Coleri (Koc University, Turkey)

Joint Topology and Computation Resource Optimization for Federated Edge Learning

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

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

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

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