Communication Systems


CMPE Degree: This course is Elective for the CMPE degree.

EE Degree: This course is Elective for the EE degree.

Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.

Technical Interest Group(s) / Course Type(s): Telecommunications

Course Coordinator: Chuanyi Ji

Prerequisites: (ECE 3020 [min C] or ECE 3040 [min C] or ECE 3084 [min C]) and (CEE/ISYE/MATH 3770 or ISYE 2027 or ECE 3077)

Corequisites: None.

Catalog Description

To present the fundamentals of modern digital communication systems and
evaluate their performance with realistic channel models.

Course Outcomes

  1. Work with the basics of random processes including ensemble and time averaging, deriving autocorrelation functions and power spectra, and the filtering of random processes.
  2. Describe fundamental elements and processes in digital transmission systems including matched filtering, baseband pulse shaping, intersymbol interference, noise, and equalization.
  3. Describe bandpass signals and systems and their representations, basic channel models, and signal space respresentations.
  4. Implement various types of binary and M-ary digital modulation schemes, including both single-carrier and multi-carrier modulation schemes, and basic spread spectrum techniques.
  5. Evaluate the performance of digital signaling on additive white Gaussian noise channels with various types of detectors, including coherent, non-coherent and differentially coherent detectors.
  6. Implement basic block and convolutional error correction coding and decoding schemes.

Student Outcomes

In the parentheses for each Student Outcome:
"P" for primary indicates the outcome is a major focus of the entire course.
“M” for moderate indicates the outcome is the focus of at least one component of the course, but not majority of course material.
“LN” for “little to none” indicates that the course does not contribute significantly to this outcome.

1. ( P ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics

2. ( LN ) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors

3. ( LN ) An ability to communicate effectively with a range of audiences

4. ( LN ) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts

5. ( LN ) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives

6. ( P ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions

7. ( M ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Strategic Performance Indicators (SPIs)

Not Applicable

Course Objectives

Topical Outline

Prerequisites: (ECE 3020 [min C] or ECE 3040 [min C] or ECE 3084 [min C]) and (CEE/ISYE/MATH 3770 or ISYE 2027 or ECE 3077)

Review of Probability and Random Processes
Basics of Probability
Statistical Averages
Some Useful Distributions
Random Processes
Statistical Characterization of Random Processes
Power Spectral Density
Random Processes Through Linear Systems
Gaussian Random Processes

Baseband Pulse Transmission
Matched Filters
Probability of Error due to Noise
Intersymbol Interference
Nyquist Pulse Shaping
Partial Response Signaling
M-ary PAM Transmission
Linear Equalizers
Adaptive Equalizers

Digital Bandpass Transmission
Representations of Bandpass Signals and Systems
Signal-space Representations
Detection of Known Signals in AWGN
Correlation and Matched Filter Receivers
Error Probability for Binary Signals
Detection of Signals with Unknown Phase
Differential Detection
M-ary Modulation Techniques

Spread Spectrum Modulation
Pseudo-noise Sequences
Direct-Sequence Spread Spectrum
Frequency-Hopped Spread Spectrum
Code Division Multiple Access

Information Theory - as time allows
Uncertainty, Information, Entropy
Source coding Theorem
Data Compaction
Discrete Memoryless Channel
Mutual Information
Channel Capacity

Error Control Coding - as time allows
Linear Block Codes
Convolutional Codes
The Viterbi Algorithm