MDCWC 2022

ONLINE WORKSHOP

30th May to 24th June 2022 (Total contact hours = 60)

Co-ordinator: Dr. E.S. Gopi

Link to the summary on MDCWC2022


ONLINE Workshop on Machine Learning, Deep learning and Computational intelligence for wireless communication (with Illustrations using MATLAB) (MDCWC 2022)

Duration

30th May to 24th June 2022 [Evening classes from 6.00 P.M. to 9.00 P.M.] (Excluding Saturday and Sunday)

About the course

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.

Participants will also get the chance to get the paper published in the Machine Learning for wireless Communication with Simulation Illustrations, Signals and Communication Technology series, springer publications, Co-Edited by the event Co-ordinator Link

(Papers will be subjected to regular Review process)

Total number of hours: 60


Theory

Illustrations

Module 1

15 Hours

15 Hours

Module 2

15 Hours

15 Hours


Target Audience:


Who can attend: UG, PG, Scholars, Faculty from Engineering colleges and universities and participants from Industry. Participants are strongly encouraged to have Matlab software installed in their system to execute the code described during the illustration session.

Maximum of participants

30 for each module (Based on First Come First Served)

Registration fee

(Including GST)

Category

UG,PG Research Scholars, Faculty

Industrial participants

Module 1

Rs. 6000


Rs.8000

Module 2

Rs.6000


Rs.8000

Both Modules

Rs.10000


Rs.14,000

Online portal

Webex (Link will be shared for the registered participants)

Registration

Registration fee needs to be paid through SBI portal

Once registration is done, Google form needs to be filled for the completion of registration.

Course contents will be based on the book authored/edited by the co-ordinator

Tentative Schedule Time duration:6.00 to 9.00 P.M.

Module 1 (Machine Learning, Deep learning and Computational intelligence)

30th May 6.00 to 6.30 P.M.

Introduction to the workshop

30th May 6.30 to 9.00 P.M.

Parametric approach to Linear regression (Maximum Likelihood Estimation, Least square estimation)

Regularization technique

31st May

Linear regression (continued): Bayes technique ,Kernel smoothing

Gaussian process technique

1st June and 2nd June

Illustrations on Linear regression

3rd June

Dimensionality reduction techniques:

Principal Component Analysis, Linear Discriminant Analysis , Kernel Linear Discriminant Analysis, Independent Component Analysis

6th June

Probabilistic discriminative model: Perceptron, Multiple class Logistic regression, Support Vector Machine

Probabilistic generative model: Gaussian Mixture Model (Combinational model)

7th June

Illustrations of Classification techniques

8th June

Generative Model: Hidden Markov Model

Artificial Neural Network

9th June

illustrations of Hidden Markov Model and Artificial Neural Network

10th June

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

Module 2 (Digital Signal Processing for Wireless Communication )

13th June

Mathematical model of Time varying wireless channel model: Coherence time, Doppler spread, Coherence frequency and Delay spread Rayleigh, Rician, kappa-mu, eta-mu model

14th June

Illustrations: Case study using Flat Rayleigh fading model ,Flat Rician fading model, Rician fading model and with known channel coefficient

15th June

Detection theory: Bayes, Mini-Max and Neyman-pearson technique

Estimation theory: MMSE, MMAE and MAP technique

16th June

Case study on Bayes, Mini-Max and Neyman-pearson techniques

Case study on MMSE,MMAE and MAP techniques

17th June

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,MSK,Power Spectral estimation using periodogram, Barlett, Welch and the Blackman-Tuckey method

20th June

Illustrations on the computation of Power Spectral density

21th June

Multiple Input Multiple Output channel model and Massive MIMO, mmWave channel model, Ray tracing model, Beam forming

22th June

NOMA,Spatial Modulation,OFDM,Water fill algorithm

23th June

Illustrations on MIMO, Ray tracing model and Beam forming, NOMA, Spatial Modulation OFDM, Water fill algorithm

24th June

Machine learning algorithms in Wireless communication

Guest speakers:

1.Dr.Aditya Niga, IIT Mandi on "Deep learning and its applications in wireless communications:

2.Dr.Maheswaran, NIT,Tiruchirappalli on "Transmit diversity schemes for spatial modulation

3. Dr. K.P. Naveen, IIT Tripati on "Co-existence of LTE and WiFi using techniques from Q-Learning"

4. Dr.Satyam Agarwal, IIT Ropar on "Machine learning in signal demodulation"

5. Dr.Sudhir kumar,IIT Patna on "Interplay of Machine learning and IOT Networks"

6. Dr.Swaminathan, IIT Indore on "Blind reconstruction of channel encoder for future generation communication"

7.Dr.Udit Satija, IIT Patna on "Machine learning for modulation classification, emitter identification and IOT application"

About the course instructor:



Dr. E.S. Gopi is a senior IEEE member with two decades of teaching and research experience. He has sole authored seven books and five book chapters published by springer. He has several papers in international journals and conferences to his credit. He is also the coordinator for the Pattern Recognition and Computational Intelligence Laboratory and the COMPSIG newsletter. He is the editor for the proceedings of the international conference on “Machine Learning, Deep leaning and Computational intelligence for wireless communication” (MDCWC2020). He is one of the series editor for the book series on “Signals and Communication”, Springer publications. His book on “Pattern recognition and Computational intelligence using Matlab” is being recognized as one of the best Pattern recognition book by Book authority. He is currently executing the project on Machine learning for GTRE (DRDO). He is currently editing the book on “Machine Learning for wireless Communication with Simulation Illustrations, Signals and Communication Technology series, springer publications. He also serves as the Workshops, Tutorials & Symposia officer for Machine Learning For Communications Emerging Technologies Initiative (IEEE ComSoc). He is the co-ordinator and Head of the Pattern recognition and the Computational intelligence laboratory. His research interests include pattern recognition, signal processing, and computational intelligence. He is currently working as an Associate Professor in the Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli.


Registration (First Come First Served Basis)

Step 1: Registration needs to done through SBI i-collect: https://www.onlinesbi.com/sbicollect/icollecthome.htm

Academia module I and II

Proceed->Select: State:Tamil Nadu, Institution:Educational Instituttions->Select: CONFERENCE AND WORKSHOP NIT TRICHY- >MDCWC2022 ACADEMIA MODULE I and II

Academia module I or II

Proceed->Select: State:Tamil Nadu, Institution:Educational Instituttions->Select: CONFERENCE AND WORKSHOP NIT TRICHY- >MDCWC2022 ACADEMIA MODULE I or II

Industry module I and II

Proceed->Select: State:Tamil Nadu, Institution:Educational Instituttions->Select: CONFERENCE AND WORKSHOP NIT TRICHY- >MDCWC2022 INDUSTRY MODULE I and II

Industry module I or II

Proceed->Select: State:Tamil Nadu, Institution:Educational Instituttions->Select: CONFERENCE AND WORKSHOP NIT TRICHY- >MDCWC2022 INDUSTRY MODULE I or II

Step 2: Fill the google form https://forms.gle/qvpivshj7gp79Gun7 (Don't forget to upload the receipt generated from SBI i-collect in the google form)

Step 3:You will get an acknowledgement from mdcwc2022@gmail.com for final confirmation of the registration process.

Supporting team members:

Rajasekharreddy poreddy <sekharpraja@gmail.com> ,

Vinodha k <vinodhakamaraj@gmail.com>,

Neema m <neemamnair@gmail.com> ,

Simy Baby <simybaby@gmail.com>