ECE535

Digital Communication Systems I
Spring
Catalog Data: 

Graduate Course Information

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ECE 435/535 Digital Communications

Designation:

Elective for ECE majors at the undergraduate level. Introductory course on digital communications for graduate level.

2013-14 Catalog Data:

ECE 435/535 – Digital Communications  (3 units)

Description:  The purpose of the course is to give students a comprehensive introduction to digital communication principles. The major part of the course is devoted to studying how to translate information into a digital signal to be transmitted, and how to retrieve the information back from the received signal in the presence of noise and intersymbol interference (ISI). Various digital modulation schemes are discussed through the concept of signal space. Analytical and simulation models for digital modulation systems are designed and implemented in the presence of noise and ISI.   Optimal receiver models for digital base-band and band-pass modulation schemes are covered in detail.

 

Course will contain a MATLAB (for undergraduate) and C/C++ (for graduate students) simulation project. The project will contain an individual and/or a group component.

Computer Usage:

MATLAB exercises (undergraduate students) and C/C++ exercises (graduate students)

Contribution to Professional Component:

Math and Basic Science:

0.5 units

Engineering Topics:

2 units

Does this course contain significant design experience?

0.5 units

 

GradingRegular grades are awarded for this course: A B C D E.

Usually offered:  Spring

Prerequisite(s): 
ECE340A
Textbook(s): 

S. Haykin, Digital Communication Systems. Wiley, 1st edition, 2014.

Course Learning Outcomes: 

By the end of this course, the student will be able to:

1.     Develop an understanding of what a digital communication system is and what components it is comprised of.

2.     Develop an understanding of digital modulation principles.

3.     Explain the strengths and weaknesses of the various modulation schemes.

4.     Develop an understanding of the effects of bandwidth limitations, linear amplitude and phase distortions and nonlinear distortions on signal waveforms.

5.     Explain basic principles of the design of practical modulators and demodulators.

6.     Compare complexity of various modulation-demodulation methods.

7.     Become familiar with the practical implications of first and second order moments on communication system analysis.

8.     Recognize various types of stochastic processes, namely: ergodic, stationary, and wide-sense stationary processes.

9.     Explain the effect that noise has on system performance.

10.  Be able to recognize various types of error control coding systems.

11.  Developed an appropriate level of mastery of MATLAB for analysis of digital communications systems.

12.  Distinguish among different digital modulation schemes: PSK, FSK, ASK, DPSK.

13.  Explain the basic properties of M-PSK, M-FSK and M-ary QAM.

14.  Understand transmission limitations under AWGN and ISI.

15.  Determine the signal constellation for a given set of signals.

16.  For any discrete memoryless source, determine the Huffman code.

17.  For any binary sequence, apply Lempel-Ziv algorithm.

18.  To determine the channel capacity of a discrete memoryless channel.

19.  Understand the basic properties of a linear block/cyclic code.

20.  Be able to encode and decode using Hamming code.

21.  Understand the fundamental principles of information theory.

Course Topics: 

1.     Introduction: communication process, multiple-access, networks, digital communications, linear modulation theory

2.     Bayesian Inference: Bayesian inference, parameter estimation, hypothesis testing, composite hypothesis testing

3.     Stochastic Processes: stochastic process definition, mean, correlation and covariance, transmission of a random process over a linear system, power spectral density, Gaussian process, white noise and narrowband noise.

4.     Signaling over AWGN channels: geometric representation of signals, vector representation of continuous AWGN channel, optimum receivers using coherent detection, error probability, phase-shift keying (using coherent detection), M-ary quadrature amplitude modulation, frequency-shift keying (using coherent detection), detection of signals with unknown phase (graduate students only), binary frequency-shift keying using noncoherent detection (graduate students only).

5.     Signaling over Band-Limited Channels: matched-filter receiver, intersymbol interference (ISI), signal design for zero ISI, ideal Nyquist pulse for distortionless baseband data transmission, raised-cosine spectrum, square-root raised-cosine spectrum, post-processing and eye pattern, adaptive equalization (graduate students only).

6.     Information Theory: uncertainty, information and entropy, source-coding theorem and lossless data compression, Lempel-Ziv algorithm, discrete memoryless channels, mutual information, channel capacity, channel coding theorem, capacity of a Gaussian channel

7.     Error-Control Coding:  error control coding principles and linear block codes.

Class/Laboratory Schedule: 

Two one hour and 15 min lecture sessions per week.

Approximately 10 homework (HW) problem sets during semester. Two in-class examinations plus a final examination. The final exam is mandatory.

Relationship to Student Outcomes: 

ECE 435/535 contributes directly to the following specific Electrical Engineering and Computer Engineering Student Outcomes of the ECE Department:

 

·  an ability to apply knowledge of mathematics, science, and engineering (High)

·  an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability (High)

·  an ability to identify, formulate, and solve engineering problems (High),

·  an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.  (Medium)

Prepared by: 
Ivan B. Djordjevic, Bane Vasic and Tamal Bose
Prepared Date: 
April 2013

University of Arizona College of Engineering