Professor Ding

Zhiguo Ding

Fellow of the IEEE,
Web of Science Highly Cited Researcher

Address: School of Electrical and Electronic Engineering,
The University of Manchester, Manchester,
M13 9PL, UK
Phone: +44 (0)1613064779
Email: zhiguo.ding@manchester.ac.uk

Brief Bio

Zhiguo Ding received his B.Eng in Electrical Engineering from the Beijing University of Posts and Telecommunications in 2000, and the Ph.D degree in Electrical Engineering from Imperial College London in 2005. He is currently a Professor in Communications at University of Manchester and Khalifa University. Previously, he had been working in Queen's University Belfast, Imperial College, Newcastle University and Lancaster University. From Oct. 2012 to Sept. 2024, he has also been an academic visitor in Prof. Vincent Poor's group at Princeton University.
Dr Ding' research interests are machine learning, B5G networks, cooperative and energy harvesting networks and statistical signal processing. His h-index is over 100 and his work receives 50,000+ Google citations. He is serving as an Area Editor for the IEEE TWC and OJ-COMS, an Editor for IEEE TVT, COMST, and OJ-SP, and was an Editor for IEEE TCOM, IEEE WCL, IEEE CL and WCMC. He received the best paper award of IET ICWMC-2009 and IEEE WCSP-2014, the EU Marie Curie Fellowship 2012-2014, the Top IEEE TVT Editor 2017, IEEE Heinrich Hertz Award 2018, IEEE Jack Neubauer Memorial Award 2018, IEEE Best Signal Processing Letter Award 2018, Alexander von Humboldt Foundation Friedrich Wilhelm Bessel Research Award 2020, IEEE SPCC Technical Recognition Award 2021, and IEEE VTS Best Magazine Paper Award 2023. He is a Web of Science Highly Cited Researcher in two disciplines (2019-2023), an IEEE ComSoc Distinguished Lecturer, and a Fellow of the IEEE.

News

Our recent works about NOMA are listed as follows:

- Hybrid NOMA downlink transmission
( the link for the paper , codes at Github).

- Utilizing Imperfect Resolution of Near-Field Beamforming: A Hybrid-NOMA Perspective
( the link for the paper , codes at Github).

- Resolution of near-field beamforming and its impact on NOMA
( the link for the paper , codes at Github).

- NOMA-Based Coexistence of Near-Field and Far-Field Massive MIMO Communications
( the link for the paper , codes at Github).

- New multi-user CR-NOMA and its impact on age of information (AoI)
( the link for the paper , codes at Github).

- Apply NOMA to reduce age of information (AoI) of grant-free transmission
( the link for the paper , codes at Github).

- Understanding the benefit of using NOMA to reduce age of information (AoI)
( the link for the paper , codes at Github).

To Prospective Students:

I am always looking for self-motivated students who want to pursue a PhD degree in the general area of wireless communications. Please drop me an email with your CV.

@2023 Frank Ding. This work is licensed under CC BY NC ND 4.0