Contributing Scholar - Gaurav Sharma, University of Rochester

3 Semester Credit Hours

Course Description

Communication systems are at the heart of today’s information driven economy and support our modern-day lifestyles and even our very existence. From the familiar telephone that was invented over a century ago, to modern day cell phones, wireless networks, and Internet, as well as radio, television, cable and satellite systems, we now rely on electrical communication systems in almost all aspects of our lives. The course focuses on the technologies underlying these systems, which constitute the field of digital communications. 

Topics include digital transmission and reception, signal space representations, spectral analysis of digitally modulated waveforms, channel equalization, introductory concepts of information theory, and error correction coding.

Prerequisites

• One year of college-level calculus.
• A course in linear algebra and differential equations.
• A calculus-based course in probability theory and statistics.
• An undergraduate Communications course.
• A course in Linear Systems Theory.
• A course in Random Processes (NEEC 6501).
• Familiarity with MATLAB
• General prerequisite: Students must have the knowledge resulting from completing all coursework in the curriculum for a BS degree in Electrical Engineering from an ABET-accredited engineering program in the United States or a CEAB-accredited program in Canada, or the equivalent from a foreign institution; performance level in this coursework should be equivalent to a cumulative undergraduate GPA of 2.9 or better on 4.0 scale.
  

Course Objectives

The primary goal of the course is to provide the student an understanding of the principles, techniques, trade-offs, and fundamental limits in modern digital communication systems.  Upon successful completion of the course, students should be able to develop signal space representations for digital modulation methods and recognize representations published in the literature; compare the strengths, weaknesses, and requirements of different modulation techniques; comprehend the constraints of communicating over a bandlimited channel and the benefits of equalization, grasp the concept of channel capacity and the promise of coding; understand the basics of block and convolutional codes and implement decoding algorithms for these. In addition, the student should develop competency in modeling and analysis communication system elements and an appreciation for the inter-relations within the different elements in modern communication systems.

Course Topics