EEE5601 Digital CommunicationBahçeşehir UniversityDegree Programs MOLECULAR BIOLOGY AND GENETICSGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
MOLECULAR BIOLOGY AND GENETICS
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
EEE5601 Digital Communication Fall 3 0 3 12
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

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.

Learning Outcomes

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.

Course Content

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.

Weekly Detailed Course Contents

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

Sources

Course Notes / Textbooks: Proakis, Digital Communications, Fourth Edition, McGraw Hill
References:

Evaluation System

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

ECTS / Workload Table

Activities Number of Activities Workload
Course Hours 14 42
Project 4 50
Midterms 9 60
Final 4 48
Total Workload 200

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Utilize the wealth of information stored in computer databases to answer basic biological questions and solve problems such as diagnosis and treatment of diseases. 3
2) Acquire an ability to compile and analyze biological information, clearly present and discuss the conclusions, the inferred knowledge and the arguments behind them both in oral and written format. 4
3) Develop critical, creative and analytical thinking skills. 5
4) Develop effective communication skills and have competence in scientific speaking, reading and writing abilities in English and Turkish. 3
5) Gain knowledge of different techniques and methods used in genetics and acquire the relevant laboratory skills. 4
6) Detect biological problems, learn to make hypothesis and solve the hypothesis by using variety of experimental and observational methods. 4
7) Gain knowledge of methods for collecting quantitative and qualitative data and obtain the related skills. 3
8) Conduct research through paying attention to ethics, human values and rights. Pay special attention to confidentiality of information while working with human subjects. 5
9) Obtain basic concepts used in theory and practices of molecular biology and genetics and establish associations between them. 4
10) Search and use literature to improve himself/herself and follow recent developments in science and technology. 5
11) Be aware of the national and international problems in the field and search for solutions. 4