EC857 Machine Learning for Wireless Communication
Course Name:
EC857 Machine Learning for Wireless Communication
Programme:
M.Tech (CE)
Category:
Elective (Ele)
Credits (L-T-P):
(3-1-0) 4
Content:
Introduction and motivation, ML tools used in communication system design, Source coding using deep learning, Channel coding using deep learning, Evaluation metrics, Experimental set up, Channel coding via machine learning, Channel estimation, Feedback and Signal Detection (SISO and MIMO), Radio resource allocation in smart radio environments, Reinforcement learning for physical layer communication, Channel capacity estimation using ML techniques, Wireless networks resource optimization using machine learning.
References:
Yonina Eldar, Andrea Goldsmith, Deniz Gunduz and Vincent Poor, “Machine Learning and Wireless
Communications”, Cambridge University Press, 2022.
Ruisi He and Ruisi Zhiguo Ding, “Applications of Machine Learning in Wireless Communication”, IET
Publications, 2019.
Le Liang, Shi Jin, Hao Ye and Geoffrey Ye Li, “Wireless Communications and Machine Learning”, Cambridge
University Press, 2025.
Department:
Electronics and Communication Engineering(ECE)