Key Communication and Machine Learning Technologies for Intelligent Wireless Networks

Dr. Fang (Fiona) Fang
Monday, June 28, 2021
Zoom Meeting



Dr. Fang (Fiona) Fang received her Ph.D. degree in electrical engineering from the University of British Columbia (UBC), Canada, in 2018. From 2018 to 2020, she was a Research Associate in the Department of Electrical and Electronic Engineering at the University of Manchester, UK. She is currently an Assistant Professor in the Department of Engineering at Durham University, Durham (UK). Her current research interests include beyond 5G/6G wireless communications, machine learning, non-orthogonal multiple access (NOMA), intelligent reflecting surface (IRS) and multi-access edge computing (MEC). Dr. Fang served as a technical program committee (TPC) member for IEEE flagship conferences, e.g., IEEE GLOBECOM, IEEE ICC, etc. She received the Exemplary Reviewer Certificate of the IEEE Transactions on Communications in 2017. Currently, she is an Associate Editor of IEEE Open Journal of The Communications Society.


Driven by the explosively increasing intelligent applications such as intelligent transportation, future wireless networks particularly 6G must embrace intelligence and require the cooperation of communication and machine learning technologies. These technologies include non-orthogonal multiple access (NOMA), mobile edge computing (MEC) and intelligent reflecting surface (IRS), deep reinforcement learning, federated learning, etc. In this talk, I shall 1) introduce energy-efficient design in NOMA systems; 2) talk about the delay and energy consumption minimization for MEC networks; 3) present machine learning algorithms for intelligent wireless communications; 4) discuss future research plans on edge AI, federated learning, etc.

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