Next Generation Wireless Technologies

Electrical Engineering, IIT Kanpur

Academic Programs

About the Programme

The Next Generation Wireless Technologies (NGWT) program, formerly known as Communication Systems, is offered by the Department of Electrical Engineering Electrical Engineering, IIT Kanpur. This e-Masters program is tailored for professionals aiming to thrive in the rapidly evolving field of wireless communication. The curriculum blends strong theoretical foundations with practical applications, covering key areas such as Wireless Communication, Digital Communication Systems, Probability & Random Processes, and Applied Linear Algebra. Participants work on expert-guided projects, developing deep technical knowledge and industry-relevant skills. Ideal for working professionals, the program equips learners to lead in the domain of next-generation wireless technologies.

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Modules

Curriculum Template

Programme Cirriculum
Credit System Complete 12 modules 5 credits in each module Total 60 credits
Programme Duration 1 to 3 Years 12 weeks in each quarter Maximum 3 modules in each quarter
Examination System Min 2 quizes Multiple Projects Final Exam
Module dependency Chart Programme Structure

Faculty & Instructors



Alumni

Dr. Ketan Rajawat

Research Interest:
Optimization Algorithms, Algorithms for Big Data, Algorithms for Machine Learning and AI in Healthcare.
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Alumni

Dr. Abhishek K Gupta

Research Interest:
Wireless Communications, 5G/6G Technologies Quantum Communications, Stochastic Geometry
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Alumni

Dr. Aditya Jagannatham

Research Interest: 5G Wireless Networks, Massive MIMO Technology, mmWave MIMO Systems, NOMA, FBMC and LAA.
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Alumni

Dr. Rohit Budhiraja

Research Interest: Communications and Signal Processing, Wireless Systems Design, 5G, Massive MIMO and Convex Optimization..
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Alumni

Dr. Adrish Banerjee

Research Interest: Coding Theory, Wireless Communications, Applications of Machine Learning in Communications and Signal Processing and Molecular Communications.
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Alumni

Dr. A R Harish

Research Interest: Antennas, Radio Frequency Identification (RFID) and Computational Electromagnetics.
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Alumni

Dr. Tushar Sandhan

Research Interest: Applied Econometrics, Rural Economics, Empirical Finance, Commodity Markets and Consumer Behavior.
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Alumni

Dr. Vipul Arora

Research Interest: Machine Learning and Signal Processing and Optimization.
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Alumni

Dr. Subrahmanya Swamy Peruru

Research Interest: Wireless Networks, Artificial Intelligence and Probabilistic Graphical Models.
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Core

EE900

Applied LinearAlgebra forWirelessCommunication

Core

EE901

Probability andRandomProcesses

Elective

EE902

Advanced MLTechniques forWirelessTechnolog

Elective

EE903

MachineLearning forSignalProcessing

Elective

EE904

Deep Learning for Communications

Elective

EE905

Detection and Estimation Theory

Elective

EE906

Speech and Audio Coding for Communication

Elective

EE907

Basics of Convex Optimization

Elective

EE908

Convex Optimization in SPCOM

Elective

EE909

Estimation for Wireless Communications

Core

EE910

Digital Communication Systems I

Elective

EE911

Data Communication Networks

Elective

EE912

Simulation Techniques for Modern Wireless

Elective

EE913

Foundations of Information Theory and Data Compression

Elective

EE914

Error Control Codes: Theory and Practice

Elective

EE915

PYTHON-Based Machine Learning Simulation for Wireless Systems

Elective

EE916

Digital Communication Systems II

Elective

EE917

PYTHON-Based Simulation, Design and Analysis of Wireless Systems

Core

EE920

Wireless Communication

Elective

EE921

MIMO Wireless Communication

Elective

EE922

Simulation-Based Design of 5G-NR Wireless Standard

Elective

EE923

Analysis of Wireless Systems

Elective

EE924

Advanced Modulation and Multiple Access for Next Generation Wireless Systems

Elective

EE925

RF Systems for Communication

Elective

EE930

Detection for Wireless Communication and Machine Learning

Elective

EE931

Advanced Wireless Transceiver Processing Techniques

Elective

EE932

Introduction to Reinforcement

Elective

EE999

Project Module

Core

EE900

Applied LinearAlgebra forWirelessCommunication

Core

EE901

Probability andRandomProcesses

Core

EE910

Digital Communication Systems I

Core

EE920

Wireless Communication

Elective

EE902

Advanced MLTechniques forWirelessTechnolog

Elective

EE903

MachineLearning forSignalProcessing

Elective

EE904

Deep Learning for Communications

Elective

EE905

Detection and Estimation Theory

Elective

EE906

Speech and Audio Coding for Communication

Elective

EE907

Basics of Convex Optimization

Elective

EE908

Convex Optimization in SPCOM

Elective

EE909

Estimation for Wireless Communications

Elective

EE911

Data Communication Networks

Elective

EE912

Simulation Techniques for Modern Wireless

Elective

EE913

Foundations of Information Theory and Data Compression

Elective

EE914

Error Control Codes: Theory and Practice

Elective

EE915

PYTHON-Based Machine Learning Simulation for Wireless Systems

Elective

EE916

Digital Communication Systems II

Elective

EE917

PYTHON-Based Simulation, Design and Analysis of Wireless Systems

Elective

EE921

MIMO Wireless Communication

Elective

EE922

Simulation-Based Design of 5G-NR Wireless Standard

Elective

EE923

Analysis of Wireless Systems

Elective

EE924

Advanced Modulation and Multiple Access for Next Generation Wireless Systems

Elective

EE925

RF Systems for Communication

Elective

EE930

Detection for Wireless Communication and Machine Learning

Elective

EE931

Advanced Wireless Transceiver Processing Techniques

Elective

EE932

Introduction to Reinforcement

Elective

EE999

Project Module

All You Need to Know