MDCWC2024

Motivation

Due to the availability of high speed computing system, there is the huge scope to still raise the standard of wireless communication in terms of massive connectivity, capacity enhancement, ultra high reliability, low latency using Machine learning (ML), Deep learning (DL) and Computational intelligence (CI) algorithms.             

The course gives an opportunity on bringing out the wireless research community and machine learning research community to learn the relevant foundational course through this programme.

Learning Objectives

The course aims on strengthening the mathematical foundations involved in wireless communication, machine learning, deep learning and computational intelligence using illustrations using Matlab. Evening classes are offered to facilitate working professionals

About the course: The course is divided into two modules:

1. Module 1: Focuses on the fundamental mathematics behind various Machine Learning, Deep Learning, and Computational Intelligence algorithms.

2. Module 2: Concentrates on the mathematical modeling of the physical layer in wireless communication.

Participants can choose to enroll in Module 1, Module 2, or both, depending on their needs and interests 

Target Participants

UG students, PG students, Research Scholars, Faculty from Engineering colleges and universities, participants from Industry with relevant educational background.

Registration:

1.    Eligible participants can register through online portal.

2.    Upload related documents and pay the application fees online.

3.    Submit the completed form through mail to mdcwc2024@nitt.edu.

ONLINE Assessment and Verified certification:  

10 MCQ Quizzes will be conducted online individually for Module 1 and Module 2 through MSTEAM.

1.    “Course completion certificate” will be issued for those who scores greater than or equal to 60%

2.    “Course completion with distinction” will be issued for those who scores greater than or equal to 80%

3.    “Certificate of participation” will be issued for all the participants registered for the course.

Course fees:

For participants within India

Module 1: Rs 5000 (Including GST) per participant (15 days: 30 hours)

Module 2: Rs.5000 (Including GST) per participant (15 days: 30 hours)

Module 1+ Module 2: Rs.8000 (Including GST) per participant (30 days: 60 hours)

For participants outside India

Module 1: 100 USD (Including GST) per participant (15 days: 30 hours)

Module 2: 100 (Including GST) per participant (15 days: 30 hours)

Module 1+ Module 2: 150 USD (Including GST) per participant (30 days: 60 hours)

Syllabus  

Module 1: Parametric approach to Linear regression (Maximum Likelihood Estimation, Least square estimation) Regularization technique Linear regression (continued): Bayes technique ,Kernel smoothing  Gaussian process technique Illustrations on Linear regression Dimensionality reduction techniques: Principal Component Analysis, Linear Discriminant Analysis , Kernel Linear Discriminant Analysis, Independent Component Analysis Probabilistic discriminative model: Perceptron, Multiple class Logistic regression, Support Vector Machine  Probabilistic generative model: Gaussian Mixture Model (Combinational model)  Illustrations of Classification techniques Generative Model: Hidden Markov Model Artificial Neural Network illustrations of Hidden Markov Model and Artificial Neural Network Introduction to Deep learning techniques: Convolution Neural Network, Auto-encoder Generative Adversarial Network, Graph Neural Network, Long Short Term Memory, Recurrent Neural Network, Particle Swarm Optimization, Ant colony Optimization.  Case studies for wireless communication applications.

Module 2: Mathematical model of Time varying wireless channel model: Coherence time, Doppler spread, Coherence frequency and Delay spread. Rayleigh, Rician, kappa-mu, eta-mu model Illustrations: Case study using Flat Rayleigh fading model, Flat Rician fading model, and with known channel coefficient. Detection theory: Bayes, Mini-Max and Neyman-pearson technique, Estimation theory: MMSE, MMAE and MAP technique. Mathematical model of base band transmission and its spectral density computation. Relationship between Base and Band pass transmission. Computation of spectral density for PSK, QPSK, FSK, and MSK, Power Spectral estimation using periodogram, Barlett, Welch and the Blackman-Tuckey method. Illustrations on the computation of Power Spectral density. Multiple Input Multiple Output channel model and Massive MIMO, mmWave channel model, Ray tracing model, Beam forming. NOMA, Spatial Modulation, OFDM, Water filling algorithm. Illustrations on MDCWC 

About the Institute:

 The National Institute of Technology (formerly known as Regional Engineering College) Tiruchirappalli, situated in the heart of Tamil Nadu on the banks of the river Cauvery, was started as a joint and co-operative venture of the Government of India and the Government of Tamil Nadu during 1964 with a view to catering to the needs of man-power in technology for the Country. The College has subsequently been conferred with autonomy in financial and administrative matters to achieve rapid development. Because of this rich experience, this institution was granted Deemed University Status with the approval of the University Grants Commission, the All India Council for Technical Education and the Govt. of India in the year 2003 and was renamed as National Institute of Technology. NITT was registered under the Societies Registration Act XXVII of 1975. During 2007 by the act of parliament, NIT-T became an Institution of National Importance.

About the Department:

The Electronics and Communication Engineering (ECE) Department was established in the year 1968. The department offers Undergraduate (UG), Post Graduate (PG), M.S.(By Research) and Ph.D degree programs that provide students with the knowledge and tools they need to succeed in the Electronics and Communication Engineering. Research in the department focuses on high-impact various disciplines: Communication systems, Wireless networks, Signal and Image Processing, RF MEMS and MIC, Microwave antennas, Optical communication and Photonics, VLSI technologies 

Coordinators cum Speakers

Dr. E.S. Gopi

Co-Ordinator and Head, Pattern recognition and Computational intelligence Group,

Professor

Department of ECE

National Institute of Technology Tiruchirappalli

esgopi@nitt.edu

Dr. E. S. Gopi is an accomplished author, having penned 8 books and edited 3 publications by Springer, focusing on signal processing and pattern recognition. His extensive research output includes numerous papers in esteemed journals, book chapters, and conference proceedings. Boasting 25 years of teaching and research expertise, he currently holds the position of Professor in the Department of Electronics and Communication Engineering at the National Institute of Technology, Tiruchirappalli (Government of India). His authored works enjoy widespread adoption worldwide. One of his notable achievements is the recognition of his book, "Pattern Recognition and Computational Intelligence using MATLAB," by Book Authority, a premier source for book recommendations. He also serves as the series editor for Springer's "Signals and Communication Technology" series. Dr. Gopi's research prowess was demonstrated through his successful completion of a project offered by GTRE (DRDO), where he served as principal investigator, focusing on "Hunting representative sensors and constructing regression models for between-sensor outcomes using ML."In addition to his written contributions, Dr. Gopi is recognized for his instructional videos on topics such as "Pattern Recognition," "Statistical Theory of Communication," and "Linear Algebra and Stochastic Process," which have been well-received by students. He is actively involved in academic initiatives, serving as a Workshop, Tutorials & Symposia officer for the Machine Learning for Communications Emerging Technologies Initiative (IEEE ComSoc). Dr. Gopi has demonstrated leadership in academic events, having organized the first virtual international conference (MDCWC2020) at NIT, Tiruchirappalli, and edited its published proceedings published by Lecture notes in Electrical Engineering, Springer publications. He has also spearheaded numerous workshops, including MDCWC2021, featured as a special session during the IEEE Conference on ICIAfS2021, and MDCWC2021, the first long virtual workshop at NIT, Tiruchirappalli. Notably, he recently convened the second International conference on MDCWC2023 and the proceedings got published in Signals and Communication Technology series, Springer. An esteemed speaker, Dr. Gopi has delivered invited talks worldwide, including contributions to the Global Initiative of Academic Networks (GIAN) course on "Machine Learning for Wireless Communication" and as a speaker for the IEEE Training School in Machine Learning for Wireless Communication at TOMSK Polytechnic University. His diverse research interests encompass machine intelligence, pattern recognition, statistical signal processing, and computational intelligence.

URL: https://www.nitt.edu/home/academics/departments/ece/faculty/gopi/

          https://sites.google.com/view/gopi-es/home 

Dr. Sovanjyoti Giri

Assistant professor

Department of ECE

National Institute of Technology Tiruchirappalli

sovanjyoti@nitt.edu

Dr. Sovanjyoti Giri received the B. Tech. degree in Electronics and Communication Engineering from Kalyani Government Engineering College (West Bengal University of Technology, Kolkata) in 2012, and the M. Tech. degree in Communication Systems from Motilal Nehru National Institute of Technology Allahabad in 2014, and the Ph. D. degree in Electronics and Electrical Communication Engineering from Indian Institute of Technology Kharagpur in 2022. He is currently working as an Assistant Professor in the Department of Electronics and Communication Engineering at National Institute of Technology Tiruchirappalli from April 2024. He has one year of industry experience as a Patent Analyst in Dolcera Information Technology Services Pvt. Ltd., Hyderabad, where he analyzed various 4G, 5G, and 6G related patents (nearly 300 patents) in 2022. Regarding the previous teaching experiences before joining NIT Trichy, he worked at Dehradun Institute of Technology University, Uttarakhand as an Assistant Professor in 2015, at NIT Sikkim as a Temporary Faculty in 2023, and at Vellore Institute of Technology (Chennai Campus) as an Assistant Professor in 2024. His research interests include Complex Communication Networks, Next-Generation Wireless Communication, Internet of Things, Power Optimization in Wireless Sensor Networks, Information Theory, Next Generation Error Control Codes, Network Coding, Stochastic Analysis, Queuing theory, Linear Algebra, Combinatorial Analysis, Performance Evaluation of Wireless Systems etc. His research works were published in reputed journals and conferences of IEEE and MDPI (including IEEE TVT, IEEE Comm. Lett. and IEEE LCN). He has reviewed more than 50 journal papers for many reputed journals of IEEE, IETE and Wiley. He is a member of IEEE since 2018 (including memberships of IEEE ComSoc, CompSoc, ITSoc, VTSoc and SPSoc).

Note: In addition to the lectures delivered by the coordinators, 6 Invited talks from reputed Academic Institutions and Industries are planned to demonstrate the case study on the applications of MDC on wireless communication.