Course10810319164 lectures
Simulation Of Communication Systems Using Matlab
Prof. Ribhu · IIT Guwahati
About
This is course is meant to introduce students to the idea of modelling and simulation of communication systems exhibiting while highlighting the underlying stochastic behavior of these systems. The key objectives of this course are twofold:
1.To introduce the importance of Monte Carlo methods for analyzing the behavior of communication systems.
2. To encourage students to model and analyze stochastic systems around them.
By the end of this course, the students will be able to confidently program in MATLAB and develop programming models for simulating communication systems.
Intended audience: Undergraduate and postgraduate students of electronics and communication engineering
Prerequisites: Need to know basic probability theory and programming
Lectures
Week 1: Introduction
- Lec :1 Introduction
- Lec 2: Basics of MATLAB
- Lec 3: Data Types
- Lec 4: Floating Point Numbers
- Lec 5: Scripts and Flow of Control
- Lec 6: The For Loop
Week 2: Matrices and Signals
- Lec 7: Arrays
- Lec 8: Indexing
- Lec 9: Some Results from Linear Algebra
- Lec 10: Matrix Multiplication
- Lec 11: Eigenvalues and Eigenvectors
- Lec 12: Complex Numbers
- Lec 13: Hermitian Matrices
- Lec 14: Matrix Inversion
Week 3: Matrices and Signals
- Lec 15: Signals
- Lec 16: Convolution
- Lec 17: Probability
- Lec 18: Bayes Theorem
- Lec 19: Random Varibles
- Lec 20: Clinical Trials I
- Lec 21: Clinical Trials II
Week 4: Monte Carlo Methods
- Lec 22: Random Numbers
- Lec 23: Random Disttributions
- Lec 24: Histograms
- Lec 25: Histograms II
- Lec 26: Functions of Random Variables
- Lec 27: Generating Random Disttributions
- Lec 28: Laws of Large numbers
Week 5: Random Processes
- Lec 29: Random Processes
- Lec 30: Properties of Random Processes
- Lec 31: Power Spectra
- Lec 32: Signals and Noise
Week 6: Random Processes
- Lec 33: Stochastic Models
- Lec 34: The AR-1 Process
- Lec 35: Stochastic Models II
- Lec 36: Yule Walker Equations
- Lec 37: Markov Chains I
Week 7: Random Processes
- Lec 38: Markov Chains II
- Lec 39: Markov Chains III
- Lec 40: Analog to Digital Coversion
- Lec 41: K Means
- Lec 42: Correlation
Week 8: Source Coding
- Lec 43: Predictive Coding
- Lec 44: Image Compression
- Lec 45: Transform Domain Compression
- Lec 46: Multi Resolution Coding
- Lec 47: Introduction to Communications
Week 9: Digital Communication
- Lec 48: Low Pass and BandPass Signals
- Lec 49: Signal Spaces
- Lec 50: PAM
- Lec 51: Detection
- Lec 52: Effects of AWGN
Week 10: Digital Communication
Week 11: Digital Communication
- Lec 57: Choosing Constellations
- Lec 58: Orthogonal Signalling
- Lec 59: Non-Coherent Dection 1
- Lec 60: Non-Coherent Detection 2
- Lec 61: DPSK
Week 12: Digital Communication
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Guwahati
- Department
- Electrical Engineering
- Teacher
- Prof. Ribhu
- Level
- Undergraduate
- Language
- English
- Subjects
- Engineering
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed