Course Syllabus
ECE 660 – Modulation Theory
Department:
Course Number:
Course Title:
Credit Hours:
Electrical and Computer Engineering
ECE 660
Modulation Theory
3
Course Description: This course covers digital modulation techniques on a unified basis consistent with
modern information theory. The discussion of information and statistical communication theory is limited
to developing concepts and criteria for comparing the modulation techniques. Software tools will be
integrated into the course to aid in the comparisons.
Prerequisite by Topic: ECE 650 (or equivalent knowledge of probability/random processes). ECE 460
(or equivalent knowledge of analog modulation). Students should have a strong background in
probability and random processes. Knowledge of linear system theory (particularly Fourier Transforms
and filtering concepts) and a basic knowledge of communications (including analog, frequency and phase
modulation for analog systems) is also required.
Text, References and Software:
Text:
Digital Communications, Proakis, John G., McGraw-Hill, Inc., 2001.
Textbook Web Site: http://www.mhhe.com/engcs/electrical/proakis/
Reference:
Modern Quadrature Amplitude Modulation, Webb & Hanzo, IEEE Press, 1995 (or Pentech
Press Limited, 1994: ISBN 0-7273-1701-6)
Software:
Matlab, Excel, Systemview or Mathcad; and Powerpoint
Course Objectives: After completing this course, students should be able to:
1. use appropriate software tools to determine the spectral characteristics and the sensitivity to ISI
for a given digital modulation technique;
2. compare and contrast two given digital modulation techniques, citing the
advantages/disadvantages of each;
3. choose an appropriate modulation technique given the required data rate for the system and a
description of the channel;
4. apply modulation and coding trade-offs to make efficient use of available spectrum and
transmitted power; and
5. state the Shannon-Hartley Theorem (and its limiting form), and compute the capacity of a channel
given the signal-to-noise ratio and the bandwidth.
Topics Covered/Course Outline:
 Signal Space Concepts and Representation of Signals and Noise
 Classification of Signals (memoryless vs. w/memory, linear vs. nonlear, orthogonal, biorthogonal, L-orthogonal, simplex, and partial response)
 Digital Modulation Techniques
 Classical
 Amplitude Shift Keying (ASK)
 Phase Shift Keying (PSK)
o
Binary Phase Shift Keying (BPSK the required data rate for the system)
o
Quaternary Phase Shift Keying (QPSK)




o
M-ary Phase Shift Keying (MPSK)
 Frequency Shift Keying (FSK)
 Quadrature Amplitude Modulation (QAM)

Advanced Digital Modulation Techniques
 Differential Phase Shift Keying (DPSK)
 Continuous Phase FSK (CPFSK)
 Continuous Phase Modulation (CPM)
 Minimum Shift Keying (MSK)
o Gaussian MSK (GMSK)
 Offset or staggered QPSK (OQPSK or SQPSK)
 /4-QPSK
 Differential /4-QPSK (D-/4-QPSK)
 Orthogonal Frequency Division Modulation (OFDM)
 Discrete Multitone (DMT)
 Trellis-Coded Modulation (TCM)
 Star QAM and Star-Differential QAM (Star D-QAM)
 Variable Rate QAM
Optimum Receivers
Shannon-Hartley Theorem
Concepts and Metrics for Comparison
 Power spectra, spectral characterizations, sidelobe regrowth
 Bandwidth efficiency (bps/Hz)
 Performance in AWGN (and sometimes fading)
 Sensitivity to Intersymbol Interference (ISI)
Comparison Tools (in Matlab and/or SystemView by Elanix)
 Eye Diagrams
 Scatter Diagrams (signal & noise)
 Signal Space Diagrams with Transitions
 Phase Tree
 Spectrum Analyzer
Oral Reports: Each student will be required to present an oral report to the class (using Powerpoint or
any software presentation tool) covering one of the digital modulation techniques or software tools listed
above in the section Topics to be Covered.
Relationship to Program Outcomes: This course supports the achievement of the following outcomes:
a) Ability to apply knowledge of advanced principles to the analysis of electrical and computer
engineering problems.
b) Ability to apply knowledge of advanced techniques to the design of electrical and computer
engineering systems.
c) Ability to apply the appropriate industry practices, emerging technologies, state-of-the-art design
techniques, software tools, and research methods of solving electrical and computer engineering
problems.
d) Ability to use the appropriate state-of-the-art engineering references and resources, including IEEE
research journals and industry publications, needed to find the best solutions to electrical and computer
engineering problems.
e) Ability to communicate clearly and use the appropriate medium, including written, oral, and electronic
communication methods.
f) Ability to maintain life-long learning and continue to be motivated to learn new
subjects.
g) Ability to learn new subjects that are required to solve problems in industry without being dependent
on a classroom environment.
h) Ability to be competitive in the engineering job market or be admitted to an
excellent Ph. D. program.
Prepared by:
Debbie van Alphen
November 8, 2002