| Course Type | Elective Course |
|---|
| Course Level | Doctorate Of Science |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Characterization of fading channels; coherence time and coherence bandwidth.
- Detection and estimation of signal parameters in AWGN channels
- Carrier and symbol synchronization.
- Estimation of channel gains.
- Channel capacity, source and channel coding.
- Multi-user communications, multiple access and queueing theory.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | Estimation theory. Binary and M'ary hypothesis tests. Detection theory. Stochastic processes. Karhunen-Loeve transform. Detection and estimation of signal parameters under white and colored noise. Detection of continuous waveforms. Optimum, linear and implementable processors. Wiener-Hopf equation and its solution. Optimum receivers. Carrier and symbol synchronization. Detection of carrier phase and symbol timing. ML detectors. Channel capacity, coding theory. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Digital signaling over fading channels. |
|
2nd Week |
Frequency non-selective and selective fading channels |
|
3rd Week |
Coherent detection, non-coherent detection. |
|
4th Week |
Detection and estimation of signal parameters in Additive White Gaussian Noise channels. |
|
5th Week |
Optimum linear realisable processor. Optimum receivers. |
|
6th Week |
Carrier and symbol synchronisation. |
|
7th Week |
Carrier phase estimation. Symbol timing estimation. |
|
8th Week |
Midterm Exam |
|
9th Week |
Channel tap weight estimation. Performance of optimum |
|
10th Week |
Receiver. ML estimators. Discrete memoryless channels. |
|
11th Week |
Channel capacity, data compaction, data compression, Continuous ensembles. Source and channel coding theorem. |
|
12th Week |
Multiuser communications, multiple access techniques, capacity of multiple access methods. |
|
13th Week |
Random access methods, queuing theory and applications. |
|
14th Week |
Markov chains and queuing theory. Network of queues. |
|
| Recommended or Required Reading | Digital Communications, J. Proakis, McGraw-Hill, 4e. |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
- Problem Solving
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
35 |
| Assignment |
1 |
15 |
| Quiz |
1 |
10 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
3 |
3 |
| Preparation for Quiz |
0 |
0 |
0 |
| Individual or group work |
14 |
8 |
112 |
| Preparation for Final exam |
1 |
40 |
40 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
30 |
30 |
| Laboratory (including preparation) |
0 |
0 |
0 |
| Final exam |
1 |
3 |
3 |
| Homework |
2 |
35 |
70 |
| Total Work Load | 300 |
| Total Work Load / 30 (h) | 10 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
