Talk
Talk by Nilesh Kumar Jha
Title :-
Data Driven Approaches for Selected Applications in Wireless Communication Systems: From Classical to Deep Learning
Abstract :-
Enabled by enhanced hardware development, novel technologies, and algorithm development, wireless communication has become ubiquitous to modern technologies meeting their ever-increasing latency, connectivity and data rate requirements. However, as traditional algorithms and model designs approach saturation in their modelling, inference and robustness capabilities, significant research focus is given to data driven methods.
The seminar presents data-driven Bayesian signal processing methods for selected physical layer applications in the upcoming beyond fifth generation and sixth generation wireless communication systems where we first investigate traditional Bayesian machine learning, scaled through online/streaming machine learning using methods from approximate posterior inference for interference cancellation in over-the-air aggregation systems.
We then examine potential pitfalls in applying the above traditional approaches and their mitigation through tools from deep learning focussing on the algorithm deficit scenario in decentralized resource management for cell-free MIMO systems where algorithm design becomes complicated due to the system constraints, and the model deficit scenario in channel estimation for unmanned aerial vehicles where accommodating various spatio-temporal statistics via traditional Bayesian approaches is challenging.
SpeakerBio :-
Nilesh Kumar Jha received his B.Tech. degree in electrical engineering from the Indian Institute of Technology, Delhi, India, in 2018 and his Ph.D. from the Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR. His research interests include Bayesian signal processing, scalable machine learning, and deep learning for wireless communication systems.
Nilesh Kumar Jha received his B.Tech. degree in electrical engineering from the Indian Institute of Technology, Delhi, India, in 2018 and his Ph.D. from the Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR. His research interests include Bayesian signal processing, scalable machine learning, and deep learning for wireless communication systems.
- 21 - 21 November,2025
- 11:30 am - 12:30 pm
- SIT001