Advanced Digital Communications


CMPE Degree: This course is Not Applicable for the CMPE degree.

EE Degree: This course is Not Applicable 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: John R Barry

Prerequisites: ECE 6602

Corequisites: None.

Catalog Description

The theory and practice of efficient digital communications over linear dispersive channels, including adaptive equalization and synchronization.

Course Outcomes

Not Applicable

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. ( Not Applicable ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics

2. ( Not Applicable ) 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. ( Not Applicable ) An ability to communicate effectively with a range of audiences

4. ( Not Applicable ) 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. ( Not Applicable ) 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. ( Not Applicable ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions

7. ( Not Applicable ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Strategic Performance Indicators (SPIs)

Outcome 1 (Students will demonstrate expertise in a subfield of study chosen from the fields of electrical engineering or computer engineering):
1. Understand and explain the performance-complexity tradeoff in equalizer design

Outcome 2 (Students will demonstrate the ability to identify and formulate advanced problems and apply knowledge of mathematics and science to solve those problems):

Outcome 3 (Students will demonstrate the ability to utilize current knowledge, technology, or techniques within their chosen subfield):
1. Use analytic tools to predict the complexity and performance of various equalization strategies for a given channel.

Course Objectives

Topical Outline

1. Deterministic DSP Review
a. Minimum Phase, All-pass, Monic
b. Spectral Factorization Theorem
c. Relate Geometric Mean to Spectral Factorization
2. Stochastic DSP Review
a. Review Autocorrelation and PSD
b. Innovations Representation of Random Process
c. Linear Prediction, Noise Whitening, and Spectral Factorization
3. PAM and Intersymbol Interference
a. Overview of PAM System with ISI
b. Equivalent Complex Baseband Model for Passband Channels
c. Nyquist Pulse Shapes, Raised-cosine Pulses
d. Eye Diagrams
4. Optimal Symbol-by-Symbol Equalization
a. Linear Equalization
b. Decision-Feedback Equalization
5. Finite-Tap, Adaptive Equalization
a. MMSE Equalizers
b. Deterministic Gradient Algorithm
c. Stochastic Gradient Algorithm
d. Recursive Least Squares
e. Adaptive DFE
f. Fractionally-Spaced Equalization
6. Carrier Recovery
a. Continuous-Time and Discrete-Time Phase-Locked Loops
b. Phase Detectors and VCO's
c. Decision-directed Carrier Recovery
d. Power-of-n Carrier Recovery
7. Timing Recovery
a. Spectral-line Methods
b. MMSE Methods
c. Non-fractionally-spaced Methods
8. Advanced Equalization Techniques
a. Transmitter Equalization
b. Tomlinson-Harashima Precoding
c. Partial Response
d. Multicarrier Modulation over ISI Channels
e. Relationship to Water Pouring Capacity
f. Combined Coding and Equalization: Multicarrier vs Precoding
9. Maximum-Likelihood Sequence Detection
a. The MF and Whitened-MF Yield Sufficient Statistics
b. The Viterbi Algorithm
10. Multiple-Input Multiple-Output
a. Single-user Point-to-Point
b. Multiuser
c. Linear MIMO Detection
d. Successive-Interference Cancellation: DFE
e. Rayleigh Fading and Diversity for MIMO
f. Sphere Decoding
11. Project
a. Software implementation of receiver, including practical effects such as downconversion, resampling, carrier recovery, timing recovery, and adaptive equalization