Tharm Ratnarajah

PROF

Accepting PhD Students

PhD projects

Full-Duplex Radio<br/>mmWave Communications<br/>Big Data Analytics and Machine Learning for Wireless Communications<br/>Interference Alignment<br/>Network Information Theory<br/>Random Matrix Theory and Stochastic Geometry

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Personal profile

Biography

Prof. Tharm. Ratnarajah is currently with the Institute for Digital Communications, University of Edinburgh, Edinburgh, UK, as a Professor in Digital Communications and Signal Processing. He was a Head of the Institute for Digital Communications during 2016-2018. His research interests include signal processing and information theoretic aspects of beyond 5G cellular networks, full-duplex radio, mmWave communications, big data analytics and machine learning for wireless communications, random matrix theory, stochastic geometry, statistical and array signal processing, interference alignment, physical layer secrecy, cognitive radio /licensed shared access and biomedical signal processing. He has published over 400 publications in these areas and holds four U.S. patents. He has supervised 15 PhD students and 20 post-doctoral research fellows and raised 11 million+ USD of research funding. He was the coordinator of the FP7 projects ADEL (3.7M€) in the area of licensed shared access for 5G wireless networks and HARP (4.6M€) in the area of highly distributed MIMO and FP7 Future and Emerging Technologies projects HIATUS (3.6M€) in the area of interference alignment and CROWN (3.4M€) in the area of cognitive radio networks. Dr Ratnarajah was an associate editor IEEE Transactions on Signal Processing, 2015-2017 and Technical co-chairs, The 17th IEEE International workshop on Signal Processing advances in Wireless Communications, Edinburgh, UK, 3-6, July, 2016. Dr Ratnarajah is a Fellow of Higher Education Academy (FHEA), U.K.

Ph.D. research projects available in the following areas:

Full-duplex radio;

mmWave communications;

Big data analytics and machine learning for wireless communications

Massive MIMO;

Interference alignment;

Network Information Theory;

Random matrix theory and stochastic geometry.

 

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