IEEE International Conference on Communications
16–20 May 2022 // Seoul, South Korea // Hybrid: In-Person and Virtual Conference
Intelligent Connectivity for Smart World

WS-17: On-Demand Program

WS-17: Edge Artificial Intelligence for 6G

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Presentation Sessions (on-demand):

Session 1

Monday May 16, 2022, 09:00~17:00 (KST), WS 17-01: FEDERATED LEARNING FOR 6G

  1. Resource-Efficient and Delay-Aware Federated Learning Design under Edge Heterogeneity

David R Nickel (Purdue University, USA); Frank Po-Chen Lin (Purdue University, USA); Seyyedali Hosseinalipour (Purdue University, USA); Nicolò Michelusi (Arizona State University, USA); Christopher G. Brinton (Purdue University & Zoomi Inc., USA)

  1. Resource Consumption for Supporting Federated Learning Enabled Network Edge Intelligence

Yijing Liu (University of Electronic Science and Technology of China, China); Gang Feng (University of Electronic Science and Technology of China, China); Yao Sun (University of Glasgow, United Kingdom (Great Britain)); Xiaoqian Li (University of Electronic Science and Technology of China, China); Jianhong Zhou (Xihua University, China); Shuang Qin (University of Electronic Science and Technology of China, China)

  1. Grouped Federated Learning: A Decentralized Learning Framework with Low Latency for Heterogeneous Devices

Tong Yin (Northwestern Polytechnical University, China); Lixin Li (Northwestern Polytechnical University, China); Wensheng Lin (Northwestern Polytechnical University, China); Donghui Ma (Northwestern Polytechnical University, China); Zhu Han (University of Houston, USA)

  1. Federated Generative Adversarial Networks based Channel Estimation

Yiyu Guo (Queen Mary University of London, United Kingdom (Great Britain)); Zhijin Qin (Queen Mary University of London, United Kingdom (Great Britain)); Octavia A. Dobre (Memorial University, Canada)


Session 2

Monday May 16, 2022, 09:00~17:00 (KST), WS 17-02: LEARNING OVER WIRELESS EDGE NETWORKS

  1. Learning Multi-Objective Network Optimizations

Hoon Lee (Pukyong National University, Korea (South)); Sang Hyun Lee (Korea University, Korea (South)); Tony Q. S. Quek (Singapore University of Technology and Design, Singapore)

  1. Computation Offloading and Resource Allocation in F-RANs: A Federated Deep Reinforcement Learning Approach

Lingling Zhang (Southeast University, China); Yanxiang Jiang (Southeast University, China); Fu-Chun Zheng (Harbin Institute of Technology, Shenzhen, China & University of York, United Kingdom (Great Britain)); Mehdi Bennis (Centre of Wireless Communications, University of Oulu, Finland); Xiaohu You (National Mobile communication Research Lab., Southeast University, China)

  1. JMSNAS: Joint Model Split and Neural Architecture Search for Learning over Mobile Edge Networks

Yuqing Tian (Zhejiang University, China); Zhaoyang Zhang (Zhejiang University, China); Zhaohui Yang (University College London, United Kingdom (Great Britain)); Qianqian Yang (Zhejiang University, China)

  1. Energy-Efficient Classification at the Wireless Edge with Reliability Guarantees

Mattia Merluzzi (CEA-Leti, France); Claudio Battiloro (Sapienza University of Rome, Italy); Paolo Di Lorenzo (Sapienza University of Rome, Italy); Emilio Calvanese Strinati (CEA-LETI, France)

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