IEEE International Conference on Communications
14-23 June 2021 // Virtual / Montreal
Connectivity – Security – Privacy

Program

Keynote Speakers:

  • Prof. Wei Yu, University of Toronto.

  • Prof. Zhi Ding, University of California Davis.

  • Prof. Walid Saad, Virginia Tech.

 

Presentation Sessions:

On-demand Program

Session 1: Edge Learning 1

Moderator: Mingzhe Chen

  1. Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation, Shaoming Huang and Yong Zhou (ShanghaiTech University, China); Ting Wang (East China Normal University & Shanghai Key Laboratory of Trustworthy Computing, China); Yuanming Shi (ShanghaiTech University, China)
  2. On the Convergence Time of Federated Learning Over Wireless Networks Under Imperfect CSI, Francesco Pase, Marco Giordani and Michele Zorzi (University of Padova, Italy)
  3. Over-the-air Learning Rate Optimization for Federated Learning, Chunmei Xu (Southeast University, China); Shengheng Liu (Southeast University & Purple Mountain Laboratories, China); Yongming Huang (Southeast University, China); Chongwen Huang and Zhaoyang Zhang (Zhejiang University, China)
  4. Communication-efficient Federated Learning Through 1-Bit Compressive Sensing and Analog Aggregation, Xin Fan (Beijing Jiaotong University, China); Yue Wang (George Mason University, USA); Yan Huo (Beijing Jiaotong University, China); Zhi Tian (George Mason University, USA)
  5. Federated Learning in Multi-antenna Wireless Networks, Zhendong Song and Hongguang Sun (Northwest A&F University, China); Howard Yang (ZJU-UIUC Institute, China); Xijun Wang (Sun Yat-sen University, China); Tony Q. S. Quek (Singapore University of Technology and Design, Singapore)

On-demand Program

Session 2: Edge Learning 2

Moderator: Shiqiang Wang

  1. Reconfigurable Intelligent Surface Assisted Federated Learning with Privacy Guarantee, Yuhan Yang and Yong Zhou (ShanghaiTech University, China); Ting Wang (East China Normal University & Shanghai Key Laboratory of Trustworthy Computing, China); Yuanming Shi (ShanghaiTech University, China)
  2. Optimal Design of Hybrid Federated and Centralized Learning in the Mobile Edge Computing Systems, Wei Hong (Beijing Xiaomi Mobile Software, China); Xueting Luo and Zhongyuan Zhao (Beijing University of Posts and Telecommunications, China); Mugen Peng (Beijing University of posts & Telecommunications, China); Tony Q. S. Quek (Singapore University of Technology and Design, Singapore)
  3. An Edge Federated MARL Approach for Timeliness Maintenance in MEC Collaboration, Zheqi Zhu, Shuo Wan and Pingyi Fan (Tsinghua University, China); Khaled Letaief (Hong Kong University of Science and Technology, Hong Kong)
  4. Deep Reinforcement Learning for Offloading and Shunting in Hybrid Edge Computing Network, Jiadong Zhang, Wenxiao Shi, Ruidong Zhang and Sicheng Liu (Jilin University, China)
  5. Joint Resource Allocation for Efficient Federated Learning in Internet of Things Supported by Edge Computing, Jianyang Ren (Beijing University of Posts and Telecommunications, China); Junshuai Sun (China Mobile Research Institution, China); Hui Tian (Beijng university of posts and telecommunications, China); Wanli Ni (Beijng University of Posts and Telecommunications, China); Gaofeng Nie (Beijing University of Posts and Telecommunications, China); Yingying Wang (CMCC, China)

On-demand Program

Session 3: Edge Learning 3

Moderator: Zhaohui Yang

  1. Radio Environment Map Enhanced Intelligent Reflecting Surface Systems Beyond 5G, Kai Zhang, Jian Zhao, Pei Liu and Changchuan Yin (Beijing University of Posts and Telecommunications, China)
  2. Generative Machine Learning for Resource-Aware 5G and IoT Systems, Nico Piatkowski (Fraunhofer IAIS, Germany); Johannes S Mueller-Roemer (Fraunhofer Institute for Computer Graphics Research & TU Darmstadt, Germany); Peter Hasse (Fraunhofer FOKUS, Germany); Adam Bachorek (Fraunhofer IESE, Germany); Tim Werner (Fraunhofer IOSB-AST, Germany); Pascal Birnstill (Fraunhofer IOSB, Germany); Andreas Morgenstern (Fraunhofer IESE); Lutz Stobbe (Fraunhofer Institute for Reliability and Microintegration IZM, Germany)
  3. DeepRAT: A DRL-Based Framework for Multi-RAT Assignment and Power Allocation in HetNets, Abdulmalik Alwarafy, Bekir S Çiftler and Mohamed M. Abdallah (Hamad Bin Khalifa University (HBKU), Qatar); Mounir Hamdi (Hamad Bin Khalifa University, Qatar)
  4. Coordinated Hyper-Parameter Search for Edge Machine Learning in Beyond-5G Networks, Hasan Farooq, Julien Forgeat, Shruti Bothe, Maxime Bouton and Meral Shirazipour (Ericsson, USA); Per Karlsson (Ericsson, Sweden)

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