Course Details

ELE677 - Signal Processing for Communications

2023-2024 Spring term information
The course is not open this term
ELE677 - Signal Processing for Communications
Program Theoretưcal hours Practical hours Local credit ECTS credit
MS 3 0 3 8
Obligation : Elective
Prerequisite courses : -
Concurrent courses : -
Delivery modes : Face-to-Face
Learning and teaching strategies : Lecture, Question and Answer, Problem Solving
Course objective : This course aims at giving the details of the channel estimation and equalisation techniques used in communication systems, and providing the details of the OFDM technique and topics related to next generation communication systems.
Learning outcomes : To teach the details of channel estimation and equalisation, and why they should be used, To discuss and teach several channel estimation and equalisation techniques, and their advantages and disadvantages, To teach the OFDM techniques, to discuss where and why it should be used, and its limitations.
Course content : Characterisation of communication channels, Channel estimation: Best Linear Unbiased Estimator (BLUE), Minimum Mean Square Error (MMSE) Estimator, Channel equalisation: Maximum Likelihood Sequence Detector (MLSD, Viterbi Algorithm), Zero Forcing (ZF) ve MMSE/DFE equalisers, adaptive equalisers, introduction to blind equalisation, OFDM: OFDM technique, channel estimation and equalisation in OFDM, topics related to OFDM (Peak-to-Average Power Ratio (PAPR), Intercarrier Interference (ICI), Adaptive Modulation)
References : Proakis, Digital Communications, McGrawHill; Molisch, Wireless Communications, Wiley; Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall; Haykin, Communication Systems, Wiley; Haykin, Adaptive Filter Theory, Prentice Hall; Goldsmith, Wireless Communications, Cambridge Univ. Press; Tse and Viswanath, Fundamentals of Wireless Communications, Cambridge Univ. Press; Proakis and Salehi, Communication Systems Engineering, Prentice Hall; Rappaport, Wireless Communications: Principles and Practice, Prentice Hall; Haykin and Moher, Modern Wireless Communications, Prentice Hall; Sklar, Digital Communications: Fundamentals and Applications, Prentice Hall; Oppenheim and Schafer, Discrete-Time Signal Processing, Prentice Hall; Hayes, ?The Viterbi Algorithm Applied to Digital Data Transmission?, IEEE Comm.Mag., pp. 26-32, May 2002; Casas, et al., DFE Tutorial,
Course Outline Weekly
Weeks Topics
1 Charateristics of Communication Channels
2 Channel Estimation
3 Channel Estimation
4 Channel Estimation
5 Channel Equalisation (MLSE+ZF)
6 Channel Equalisation (MMSE)
7 Channel Equalisation (DFE, Adaptive Equalization)
8 Midterm exam
12 Multiuser Communications
13 Multiuser Communications
14 Presentations of Term Projects
15 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 20
Presentation 0 0
Project 1 20
Seminar 0 0
Quiz 0 0
Midterms 1 20
Final exam 1 40
Total 100
Percentage of semester activities contributing grade success 60
Percentage of final exam contributing grade success 40
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 5 70
Presentation / Seminar Preparation 0 0 0
Project 0 0 0
Homework assignment 13 5 65
Quiz 0 0 0
Midterms (Study duration) 1 29 29
Final Exam (Study duration) 1 34 34
Total workload 43 76 240
Matrix Of The Course Learning Outcomes Versus Program Outcomes
Key learning outcomes Contribution level
1 2 3 4 5
1. Has general and detailed knowledge in certain areas of Electrical and Electronics Engineering in addition to the required fundamental knowledge.
2. Solves complex engineering problems which require high level of analysis and synthesis skills using theoretical and experimental knowledge in mathematics, sciences and Electrical and Electronics Engineering.
3. Follows and interprets scientific literature and uses them efficiently for the solution of engineering problems.
4. Designs and runs research projects, analyzes and interprets the results.
5. Designs, plans, and manages high level research projects; leads multidiciplinary projects.
6. Produces novel solutions for problems.
7. Can analyze and interpret complex or missing data and use this skill in multidiciplinary projects.
8. Follows technological developments, improves him/herself , easily adapts to new conditions.
9. Is aware of ethical, social and environmental impacts of his/her work.
10. Can present his/her ideas and works in written and oral form effectively; uses English effectively.
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest
General Information | Course & Exam Schedules | Real-time Course & Classroom Status
Undergraduate Curriculum | Minor Program For Non-departmental Students | Open Courses, Sections and Supervisors | Weekly Course Schedule | Examination Schedules | Information for Registration | Prerequisite and Concurrent Courses | Legal Info and Documents for Internship | Academic Advisors for Undergraduate Program | Information for ELE 401-402 Graduation Project | Virtual Exhibitions of Graduation Projects | Erasmus+ Program | Program Educational Objectives & Student Outcomes | ECTS Course Catalog | HU Registrar's Office
Graduate Curriculum | Open Courses and Supervisors | Weekly Course Schedule | Final Examinations Schedule | Schedule of Graduate Thesis Defences and Seminars | Information for Registration | ECTS Course Catalog - Master's Degree | ECTS Course Catalog - PhD Degree | HU Graduate School of Science and Engineering