Online Course on
Machine Learning for 6G Wireless Communication
A structured online programme from IISc covers AI/ML for physical layer wireless communication, enhancing performance and adaptability, and prepares learners for 6G AI-native radio systems and related industry roles.
Course at a Glance
Know the Course Instructor
Prof. Sudhan Majhi
He received an M.Tech degree in computer science and data processing (CSDP) from Indian Institute of Technology (IIT) Kharagpur, India and a Ph.D. degree from Nanyang Technological University (NTU), Singapore. He has post-doctoral experience with the University of Michigan, Dearborn, USA, the Institute of Electronics and Telecommunications Rennes (IETR), France, and Nanyang Technological University, Singapore. He was an Assistant professor jointly with the Mathematics and Electrical Engineering department at IIT Patna. He was also an associate professor in the Department of Electrical Engineering at IIT Patna. Currently, he is a professor in Electrical Communication Engineering (ECE) at Indian Institute of Science, Bangalore. He is a fellow of Sir Visvesvaraya Young Faculty Research. He has received SERB-TETRA and SERB- STAR awards in 2022 and 2023, respectively. He was an Editor of IEEE Transactions on Vehicular Technology Journal, IEEE Communications Letters, IEEE Wireless Communications Letters and Circuits, Systems and Signal processing (CSSP) – Springer. His research interest is signal processing for 6G wireless communications.
Objectives of the Course
AI/ML has several applications in physical layer communication.
The 3GPP standards already adopted AI/ML as a study material for 6G wireless communications.
Brings adaptive-ness to the transmitter as well as the receiver and improves the performance and latency of the communication system.
6G AI Native radio also requires a solid knowledge of AI/ML for wireless communication; having this knowledge may help them find a job in these companies.
Course Syllabus
Introduction to Python: Basic of Python programming
Introduction to Machine Learning: Overview of supervised, semisupervised and unsupervised, Regression Model, SVM, KNN, CNN, DNN, RNN, LSTM, Transfer learning.
Introduction to Wireless: Python code on Single carrier system, OFDM, MIMO, OTFS system
Wireless Communications: LDPC code decoding, Modulation classification, channel estimation, CSI compression and feedback (based on 3GPP Standard), Beamforming and beam Management (based on 3GPP Standard), PAPR reduction, and Spectrum sensing
Wireless Communications: LDPC code decoding, Modulation classification, channel estimation, CSI compression and feedback (based on 3GPP Standard), Beamforming and beam Management (based on 3GPP Standard), PAPR reduction, and Spectrum sensing
Resource allocation: Resource allocation, Spectrum sharing, Power allocation.
Who Can Apply & Who Can Benefit?
Who Can Apply?
- B.E / B.Tech
- ME / M.Tech
- Phd relevant discipline (4th year BE/B.Tech also Eligible)
- Pre-requisites: Wireless Communication and Basic of Python
Who Can Benefit?
- Engineers or researchers working in wireless communication, IoT, or related fields who want to apply AI/ML techniques
- Academics & Researchers
- Tech Enthusiasts
Course Fee
Class Schedule
Reference Books
Ready to Enroll?
Apply online at iisc.online · New batches every semester