TEXTILE AND FASHION DESIGN | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
EEE5601 | Digital Communication | Spring | 3 | 0 | 3 | 12 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | Face to face |
Course Coordinator : | Assoc. Prof. SAEID KARAMZADEH |
Recommended Optional Program Components: | None |
Course Objectives: | AWGN kanal için bazı modülasyon/demodülasyon tekniklerini, temel sezim kuramını ve performans analizinin metodlarını detaylarıyla anlamak. |
The students who have succeeded in this course; 1. Describe digital communications, 2. Explain signal space representation, 3. Describe digital modulation schemes, 4. Gain knowledge noise calculations, 5. Understand single-user detection theory. |
This course starts with reviewing concepts of sampling, quantization and encoding. Then, it moves to source and channel coding, signal space representation, and digital modulation schemes. Upon visiting digital demodulation schemes, performance analysis of different schemes are carried out. In the second half of the course, basic estimation and detection techniques are introduced. Finally, the course ends with fading channel analysis. |
Week | Subject | Related Preparation |
1) | General model for a digital communication system | |
2) | Source and channel coding | |
3) | Signal Space Representation | |
4) | Digital modulation schemes, M-QAM | |
5) | Performance considerations, Bandwidth considerations, Practical considerations | |
6) | (Phase) noncoherent detection principles | |
7) | Differential detection, System constraints and trade-offs | |
8) | Comparison and discussion of previously mentioned methods. Midterm exam. | |
9) | General Concepts of Detection Theory, Bayesian Decision Theory | |
10) | The Likelihood Ratio Test and Its applications | |
11) | Optimal binary detection for the Gaussian vector channel | |
12) | Optimal detection for M-ary hypothesis tests | |
13) | BER calculations | |
14) | Introduction to fading channels |
Course Notes / Textbooks: | Proakis, Digital Communications, Fourth Edition, McGraw Hill |
References: |
Semester Requirements | Number of Activities | Level of Contribution |
Project | 1 | % 30 |
Midterms | 1 | % 30 |
Final | 1 | % 40 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 30 | |
PERCENTAGE OF FINAL WORK | % 70 | |
Total | % 100 |
Activities | Number of Activities | Workload |
Course Hours | 14 | 42 |
Project | 4 | 50 |
Midterms | 9 | 60 |
Final | 4 | 48 |
Total Workload | 200 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |