Course Description and Prerequisites
EE 512 is a graduate-level course covering the theory and practice of digital communication systems. Topics include source coding (sampling, quantization, compression), characterization of communication signals and systems, optimum receivers for additive white Gaussian noise (AWGN) channels, channel capacity and coding theory, and error-control coding using block and convolutional codes. The course makes extensive use of MATLAB/Simulink for system modeling. Prerequisites: EE 421G and engineering standing. Learning Outcomes
Upon completion, students should demonstrate the ability to:
EE 512 is a graduate-level course covering the theory and practice of digital communication systems. Topics include source coding (sampling, quantization, compression), characterization of communication signals and systems, optimum receivers for additive white Gaussian noise (AWGN) channels, channel capacity and coding theory, and error-control coding using block and convolutional codes. The course makes extensive use of MATLAB/Simulink for system modeling. Prerequisites: EE 421G and engineering standing. Learning Outcomes
Upon completion, students should demonstrate the ability to:
- Design modulation and optimum demodulation/detection methods for digital communications over an AWGN channel.
- Calculate error-rate performance for various modulation schemes in AWGN environments.
- Calculate channel capacity for several traditional channel models.
- Evaluate the performance of linear block and convolutional codes in AWGN environments.
- Fundamentals of Communication Systems, 2nd Ed., J. G. Proakis and M. Salehi, Pearson, 2014.
- Probabilistic Methods of Signal and System Analysis, G. R. Cooper and C. D. McGillem, Holt, Rinehart, and Winston, 1986.
- Source coding: sampling, quantization, and compression (Huffman coding)
- Characterization of communication signals and systems
- Modulation schemes (DFT-based, QAM, DPSK)
- Optimum receivers for AWGN channels
- Channel capacity and Shannon’s coding theorem
- Error-control coding: linear block codes and convolutional codes
- Three semester exams (15% each)
- Comprehensive final exam (30%)
- Simulink assignments (25%)
| Semester | Materials |
|---|---|
| Spring 2002 | Syllabus, two exams |
| Spring 2003 | Syllabus, exams (three semester + final), solutions, project reports |
| Spring 2004 | Syllabus, four exams with LaTeX source, project handouts |
| Spring 2005 | Syllabus, four exams with LaTeX source, five project assignments, homework, daily schedule |
| Spring 2008 | Syllabus, two exams, final exam, quiz, Simulink models |
| Spring 2020 | Practice exam, makeup exam, Simulink assignment, Exam III materials |
| Spring 2021 | Full Canvas-based syllabus, four exams, two assignments, Simulink assignment, 27 recorded Zoom lectures |
| Spring 2022 | Four sets of homework solutions |
| Spring 2024 | Final exam, Exam 03, Simulink models, constellation diagrams |
| Shared Resources | Instructor’s solutions manual, chapter-specific solutions, supplemental modulation notes, Simulink design document with LaTeX source, PowerPoint slides for chapters 2–14, source model Simulink files, Cooper and McGillem reference text |
