ECE 59500 - Advanced Digital Communications with AI
Course Details
Lecture Hours: 3 Credits: 3
Areas of Specialization:
- Communications, Networking, Signal & Image Processing
Counts as:
- EE Elective
- CMPE Selective - Special Content
Normally Offered:
Each Spring
Campus/Online:
On-campus and online
Requisites:
ECE 54400, Digital Communications
Requisites by Topic:
Graduate-level probability theory, basic digital signal processing, Fourier transforms, digital RF transmission of information, basic Python programming, basic MATLAB/Simulink tool knowledge
Catalog Description:
Advanced Digital Communications is taking advantage of two industry trends, the software defined radio (SDR) and the ability of Artificial Intelligence (AI) to automatically classify Radio Frequency (RF) spectrum features. These trends allow radio receivers to identify, track and receive digital communications data in real time.
Required Text(s):
- Digital Communication Systems , First Edition , Haykin, Simon , Wiley , 2013 , ISBN No. 978-0471647355
- Software Defined Radio using MATLAB & Simulink and the RTL-SDR. , Stewart, Robert W. and Barlee, Kenneth W. and Atkinson, Dale S. W. and Crockett, Louise H. , Strathclyde Academic Media , 2015 , ISBN No. 978-0-9929787-2-3
Recommended Text(s):
None.
Learning Outcomes
A student who successfully fulfills the course requirements will have demonstrated an ability to:
- Identify and differentiate common digital modulation types and explain their applications in software-defined radio (SDR) and artificial intelligence (AI) systems. [
- Apply foundational SDR concepts to analyze and process radio frequency (RF) signals.
- Implement basic AI classifiers to recognize and categorize RF signal patterns.
- Integrate SDR techniques with AI approaches to enhance signal analysis and interpretation. [
- Describe emerging and advanced topics in the field.
Lecture Outline:
| 1 | 1 |
|---|---|
| 1 | Review of Digital Communications |
| 2 | Software Defined Radio |
| 3 | AI Classifiers for Digital Communications |
| 4 | Advanced Topics in AI |
Assessment Method:
Homework, lab projects, exams. (10/2025)