ECE 461 - Digital Communications

Semesters Offered

Digital CommunicationsECE461A67646LEC0930 - 1050 T R  3013 ECE Building Juan Alvarez

Official Description

Reliable communication of one bit of information over three types of channels: additive Gaussian noise, wireline, and wireless. Emphasis on the impact of bandwidth and power on the data rate and reliability, using discrete-time models. Technological examples used as case studies. Course Information: 3 undergraduate hours. 3 graduate hours. Prerequisite: ECE 210 and ECE 313.


ECE 461 is now ECE 361.

Course Goals

Course Goals and Instructional Objectives

ECE 461 is a senior/first-year-graduate-level course in the theory of digital communication systems. The prerequisite course is ECE 459--Communications I--which includes only a short survey of the field of digital communications. ECE 461 builds on this material to introduce the student to the most important methods for analyzing digital communication systems, and to elementary design ideas for digital communication systems. The goal is to provide the student with the technical skills to predict the performance of simple digital communication systems, and to apply these skills in designing simple communication systems and in determining the system parameters that must be used for such systems to achieve various performance criteria. ECE 461 serves as a co-requisite for ECE 463--Digital Communications Laboratory--as well as a prerequisite for the graduate course ECE 559--Topics in Communication Systems--when the topic happens to be advanced digital communication systems.

Instructional Objectives

At the end of this course, the student will be able to apply the skills learned in this course to solve the following types of problems in communication system analysis and design.

1. Design a coherent receiver for a specified signaling scheme including a description of the optimum matched filter, timing information, threshold settings, etc.

3. Analyze any given suboptimum receiver for a specified signaling scheme and compute the bit error rate (BER) achieved for any given signal-to-noise ratio (SNR)

3. Compute the bandwidth required by a given signaling scheme

4. Design a good code (convolutional code and turbo code) over the additive Gaussian noise channel

5. Describe pulse shaping filters to convert discrete signals to analog oes.

6. Design zero-forcing equalizers for communication systems operating over narrowband channels and compute the performance achieved

7. Describe a maximum-likelihood sequence demodulator and the Viterbi algorithm for searching the trellis

8. Design communication systems for achieving specified performance criteria, including choosing a signaling scheme, specifying the needed filters, samplers, thresholds etc.

These objectives mainly address Program Outcomes (1) and (2), and to a lesser extent (6).

Last updated

7/20/2018by James Andrew Hutchinson