100791 - HLSI-002: Intelligent Control of Frequency-Agile RF Systems
Overview
In HLSI-002 Intelligent Control of Frequency-Agile RF Systems, students learn about selected approaches to smart control of frequency-agile radio frequency systems and apply that knowledge in simulations to demonstrate and achieve efficient, effective use of the radio frequency (RF) spectrum in complex RF environments.
Participants explore concepts in depth through interactive simulations to apply and extend knowledge gained through video lectures, text notes, example videos, and diverse supplemental learning resources.
In the final course participants will use rule-based artificial intelligence as well as machine learning approaches in challenging, non-graded, simulation-based mini-projects. In the mini-projects participants will modify the provided transmission parameter adaptation code to maintain wireless link quality in fading channels and avoid an interfering and/or higher-priority signal in a shared RF band.
Agenda/Schedule
Course Content:
1. Artificial intelligence (AI) Overview
- Reinforcement learning; Recurrent neural networks and long short-term memory (LSTM); Evolutionary generative adversarial networks; Knowledge based AI; Cognitive radio AI applications: Markov models; fuzzy logic; game theory; rule, case, and ontology-based systems; multi-agent systems; game theory; biology-inspired
2. Machine learning (ML) Overview
- Supervised Learning: Linear regression; Classification (logistic regression, support vector machines, kernel functions and parameter tuning, artificial neural networks,
- Unsupervised Learning: Clustering (K-means, hierarchical); Dimensionality reduction (Principal component analysis, Singular value decomposition)
3. Application of AI/ML to control frequency-agile wireless links
- Modulation and coding scheme selection based on channel conditions
- Use of observations and/or machine learning to understand behavior of and/or avoid interference to and from primary-user and other transmitters and receivers within a shared band of RF frequencies
- Primary and secondary users
- Spectrum sharing approaches: overlay, underlay, and interweave
- Spectrum access systems (SAS), TV white space (TVWS) database
- Defense-related RF spectrum concepts: electromagnetic battlespace, electromagnetic spectrum operations, electromagnetic maneuver warfare
Additional Information
The Hands-on Learning for Radio Frequency Spectrum Innovation program includes two courses:
• HLSI-001: Introduction to Wireless Communication Fundamentals and the Radio Frequency Spectrum
• HLSI-002: Intelligent Control of Frequency-Agile RF Systems
Purchase both as a bundle for a discounted price of $450 total ($225 per course).
Hands-on Learning for Radio Frequency Spectrum Innovation | Virginia Tech Continuing and Professional EducationSpeaker(s)/Instructor(s)
Dimitri Dessources is a PhD candidate in Virginia Tech’s Bradley Department of Electrical and Computer Engineering and the Wireless at Virginia Tech center who is investigating security-related aspects of 5G and 6G wireless systems. Mr. Dessources has also worked for major defense contractors and consultants and does additional consulting and educational work through Software Defined Radio Solutions (SDRS Wireless).
Dr. Carl Dietrich is a research faculty member who is also with the Bradley Department and Wireless at Virginia Tech. His research interests encompass multiple aspects of wireless communications including software defined radio, spectrum sharing, and application of multi-antenna systems, as well as engineering education and workforce development, Dietrich also provides educational and consulting services through SDRS Wireless.