This course aims to provide an introduction to the fundamental principles and techniques of digital communications. Lecture topics encompass sampling theorem, quantization, baseband transmission, matched filters, noise analysis, various digital modulation methods, and introduction to information theory. The course also includes laboratory component covering practical simulations in MATLAB, allowing students to gain hands-on experience and apply their theoretical knowledge in real-world scenarios.
MATLAB with Communications Toolbox (https://www.mathworks.com/products/communications.html)
Upon successful completion of this course, students will be able to:
(1) List the sampling theorem, pulse amplitude modulation, pulse code modulation, and quantization,
(2) Explain baseband transmission of digital signals and matched filter detection in baseband digital communication systems,
(3) Utilize the probability of error concept to investigate baseband transmission systems performance,
(4) Analyze the geometric representation of multidimensional signal waveforms, optimal receiver structures, decision regions, and union bound on error probability for bandpass transmission systems,
(5) Evaluate the information theory principles including entropy, source-coding theorem, and lossless data compression,
(6) Collaborate with peers in conducting experiments on digital communications.
(1) Proakis, J. G., & Salehi, M. (2015). Fundamentals of Communication Systems. Global Edition, 2nd Editon, Pearson.
(2) Haykin, S. (2014). Digital Communication Systems. 1st Edition, Wiley.
Haykin, S., & Moher, M. (2010). Communication Systems. Int. Student Version, 5th Edition, Wiley.
Test/Exam (70%), Lab Assignment (20%), Active Learning Exercises (10%)
| Workload | Hrs |
|---|---|
| Lectures | 28 |
| Course Readings | 28 |
| Lab Applications | 28 |
| Exams/Quizzes | 42 |
| Active Learning Exercises | 24 |