# ONLINE COURSE ON MACHINE LEARNING FOR 6G WIRELESS COMMUNICATION (3:1)

**Source**: https://cce.iisc.ac.in/cce-proficience/machine-learning-6g-wireless-communication-mj-2026/
**Parent**: https://cce.iisc.ac.in/cce-proficience/

[APPLY NOW](https://iisc.online/admissions/home.html)

# CCE-PROFICIENCE MAY – JULY 2026

**Duration**

4th May to 29th July 2026

**Schedule**

Monday and Wednesday

8PM to 9:30 PM

**Course offered**

Online

**Exam Duration**

31 July to 9 August 2026

Classes Start

~4 May 2026

# Objectives of the Course

AI/ML has several applications in physical layer communication. It brings adaptive-ness to the transmitter as well as the receiver and improves the performance and latency of the communication system. The 3GPP standards already adopted AI/ML as a study material for 6G wireless communications. 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.

# 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,

**Signal Estimation and Detection**: AL/ML based Parameter estimation, IF estimation, symbol rate estimation, STO and CFO estimation.

**Resource allocation**: Resource allocation, Spectrum sharing, Power allocation.

# Minimum Qualification required by the candidates

BE/B Tech ME/M Tech and Phd relevant discipline (4th year BE/B Tech also Eligible)

# Pre-requisites

Wireless Communication and basic of python.

# Reference Books

1. I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning, MIT Press, 2016

2. Y. C. Eldar, A. Goldsmith, D. Gündüz, and H. V. Poor, Machine Learning and Wireless Communications, Cambridge University Press, 1st edition, 2022.

3. F.-L. Luo, Machine Learning for Future Wireless Communications, Wiley-IEEE Press, 2020

4. R. He and Z. Ding, Applications of Machine Learning in Wireless Communications. London, U.K.: The Institution of Engineering and Technology, 2019.

5. M. Viswanathan, Digital Modulations using Python. Independently published, 2019.

##### Course Plan

**Week 1-4:** 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, GANs, Transfer learning, RL.

**Week 5-6:** Introduction to Wireless: Python code on Single carrier system, OFDM, MIMO, OTFS system.

**Week 7-9:** 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.

**Week 10-12:** Signal Estimation and Detection: AL/ML based Parameter estimation, IF estimation, symbol rate estimation, STO and CFO estimation. Spectrum sharing and resource allocation: Resource allocation, Spectrum sharing, Power allocation.

[DOWNLOAD BROCHURE](https://cce.iisc.ac.in/wp-content/uploads/2026/03/ML-6G-wireless-may-july-2026-final.pdf)

# Know The Facilitators

#### Prof. Sudhan Majhi

Professor

**SP 1.05, Dept. of ECE,**

**Indian Institute of Science**

# Course Fee

|  |  |
| --- | --- |
| **Particulars** | **Amount** |
| Course Fee | 20,000 |
| Application Fee | 300 |
| GST@18% | 3,654 |
| Total | 23,954 |