ACADEMICS
Course Details

ELE730 - Digital Communications I

2022-2023 Fall term information
The course is open this term
Supervisor(s)
Name Surname Position Section
Prof.Dr. Cenk Toker Supervisor 1
Weekly Schedule by Sections
Section Day, Hours, Place
All sections Wednesday, 09:00 - 11:45, SS

Timing data are obtained using weekly schedule program tables. To make sure whether the course is cancelled or time-shifted for a specific week one should consult the supervisor and/or follow the announcements.

ELE730 - Digital Communications I
Program Theoretıcal hours Practical hours Local credit ECTS credit
PhD 3 0 3 10
Obligation : Elective
Prerequisite courses : -
Concurrent courses : -
Delivery modes : Face-to-Face
Learning and teaching strategies : Lecture, Question and Answer, Problem Solving
Course objective : The aim is to give an in-depth understanding of the topics below to the students; - Receiver design in AWGN, - Digital modulation techniques with coherent and noncoherent detection, - Channel coding; block and convolutional coding , - Spread spectrum transmission; frequency hopping and direct-sequence SS systems and applications.
Learning outcomes : A student completing the course successfully will understand and solve problems related to digital modulations, be able to compare relative (dis)advantages of different modulation techniques, understand and solve problems related to channel coding, be able to design communication systems combining various modulation and coding techniques understand and solve problems related to spread spectrum transmission and apply his knowledge in the domains including multiple access (CDMA), ranging, AJ.
Course content : Coherent and noncoherent demodulation; Maximum likelihood vs MAP decoding. Synchronization (frequency, phase and time) Matched filter and correlation receiver, Digital modulation techniques; M-ASK, M-PSK, M-FSK. Comparison of modulation techniques; Shannon?s capacity theorem Channel coding; error detection vs. error correction coding; ARQ systems; block and convolutional coding. Examples: turbo coding and LDPC Spread spectrum transmission; frequency hopping and direct-sequence SS systems and applications. CDMA, ranging, AJ and LPI.
References : Şafak, M., Digital Communications, Lecture notes, 2012; Proakis, J., Digital Communications (4th ed.), McGraw Hill, 2000; Haykin, S., Communication Systems (4th ed.), Wiley, 2001; Sklar, B., Digital Communications (2nd ed.), Prentice Hall, 2001
Course Outline Weekly
Weeks Topics
1 Optimum receiver in AWGN channel, matched-filter and correlation receivers. Optimum detector. Maximum likelihood and MAP detection.
2 Antipodal and orthogonal signaling. Symbol error probability of M-ary orthogonal and biorthogonal signaling, simplex and binary-coded signaling
3 M-ary PSK, differentially-encoded PSK (DEPSK), Differential PSK (DPSK)
4 M-ary PAM, M-ary QAM, Noncoherent M-ary FSK. Comparison of modulation techniques, Shannon?s capacity theorem
5 Fundamentals of error control coding. Error detecting vs. correcting codes, random error vs. burst error correcting codes. Hard-decision vs. soft-decision decoding. Hamming vs. Euclidean distance
6 Linear block codes. Generator and parity check matrices, syndrome decoding. Examples of commonly used block codes. Cyclic codes, generator and parity polynomials, encoder and syndrome calculator.
7 Midterm Exam I
8 Examples of cyclic codes: Hamming, BCH, RS, CRC and LDPC codes. ARQ and hybrid ARQ techniques, throughput, delay and packet error probabilities
9 Convolutional codes, code tree, state and trellis diagrams. Hard-decision vs. soft-decision decoding. Viterbi algorithm. Interleaving. Turbo codes
10 Fundamentals of spread spectrum. Concept of spreading. Pseudo random (PN) codes. Kasami and Gold sequences.
11 Direct-sequence spread spectrum, processing gain, AJ, LPI, multipath rejection, ranging. Example: GPS system
12 Midterm Exam II
13 CDMA. Spreading and multiple-access capabilities of 2G and 3G systems
14 Frequency-hopping spread spectrum. Fast vs. slow hopping. Performance evaluation in AWGN channel. AJ performance. Multi-user FH systems.
15 Preparation to Final exam
16 Final exam
Assessment Methods
Course activities Number Percentage
Attendance 0 0
Laboratory 0 0
Application 0 0
Field activities 0 0
Specific practical training 0 0
Assignments 6 5
Presentation 0 0
Project 0 0
Seminar 1 5
Quiz 0 0
Midterms 2 40
Final exam 1 50
Total 100
Percentage of semester activities contributing grade success 50
Percentage of final exam contributing grade success 50
Total 100
Workload and ECTS Calculation
Course activities Number Duration (hours) Total workload
Course Duration 14 3 42
Laboratory 0 0 0
Application 0 0 0
Specific practical training 0 0 0
Field activities 0 0 0
Study Hours Out of Class (Preliminary work, reinforcement, etc.) 14 9 126
Presentation / Seminar Preparation 1 12 12
Project 0 0 0
Homework assignment 6 4 24
Quiz 0 0 0
Midterms (Study duration) 1 30 30
Final Exam (Study duration) 1 30 30
Total workload 37 88 264
Matrix Of The Course Learning Outcomes Versus Program Outcomes
Key learning outcomes Contribution level
1 2 3 4 5
1. Has highest level of knowledge in certain areas of Electrical and Electronics Engineering.
2. Has knowledge, skills and and competence to develop novel approaches in science and technology.
3. Follows the scientific literature, and the developments in his/her field, critically analyze, synthesize, interpret and apply them effectively in his/her research.
4. Can independently carry out all stages of a novel research project.
5. Designs, plans and manages novel research projects; can lead multidisiplinary projects.
6. Contributes to the science and technology literature.
7. Can present his/her ideas and works in written and oral forms effectively; in Turkish or English.
8. Is aware of his/her social responsibilities, evaluates scientific and technological developments with impartiality and ethical responsibility and disseminates them.
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest
General Information | Course & Exam Schedules | Real-time Course & Classroom Status
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