Explore Radio Frequency Spectrum Sharing and Spectrum Superiority related concepts through interactive experiments and programming mini-projects.

These self-paced online courses introduce fundamental concepts and recent developments related to efficient, effective use of the radio frequency (RF) spectrum in constrained, congested, and contested (complex) RF environments.  Participants explore concepts in depth through interactive simulations to apply and extend knowledge gained through lectures and diverse supplemental learning resources.

In the final course, participants apply rule-based artificial intelligence as well as machine learning approaches in challenging, non-graded mini-projects.  In the mini-projects you will modify provided, user-editable transmission parameter adaptation code for use in simulated RF environments.  Mini-project goals include maintaining wireless link quality in fading channels and avoiding an interfering and/or higher-priority signal in a shared RF band.

Included courses (2.0 CEUs Total):

HLSI-01 (0.5 CEUs):  Fundamental Concepts for Wireless Communications (FCW)
HLSI-02 (0.5 CEUs):  Introduction to the Radio Frequency Spectrum and Spectrum Management (RFS)
HLSI-03 (0.3 CEUs):  Methods for Smart Control of Spectrum Agile Radio Frequency Systems (MSC)
HLSI-04 (0.7 CEUs):  Controller Implementation for Spectrum Agility (ISA)

Course resources:

  • Ungraded pre-quizzes for each module in courses HLSI-01 – HLSI-03.
  • Narrated slide presentations with closed captioning
  • Downloadable 2- and 3-per-page slide handouts
  • Video demonstrations produced using software defined radio (SDR) software and testbeds
  • Supplemental text notes
  • Interactive simulation exercises that let students observe changes in radio link performance in response to manual and participant-programmed control of transmission parameters
  • Links to external videos, simulations, and documents
  • Post-module graded quizzes or self-reflections as well as pre- and post-course surveys to help you assess knowledge gained and help us improve the courses and simulations


Course Sequence Topics

  • Wireless communication links
    • Systems and subsystems: transmitters, receivers, antennas
    • Wireless channels, noise and interference
    • Signals and their properties
    • Information capacity of a channel
    • Analog and digital modulation
    • Multiplexing, duplexing, and multiple access
    • Orthogonal frequency division multiplexing (OFDM)
    • Decibels and how to use them to simplify calculations
  • The RF spectrum, frequency agility, and spectrum management
    • Frequency-domain representation of signals
    • Wireless communication link performance metrics
    • Transmitter settings that can be adapted to optimize wireless link performance
    • RF spectrum management
    • Spectrum sharing/dynamic spectrum access with examples
    • 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
  • Software defined radio (SDR)
    • Concepts and definitions
    • Enabling technologies
    • Applications and examples
  • Artificial intelligence (AI)
    • 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
  • Machine learning (ML) techniques
    • 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)
  • Application of AI/ML to control 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
Enroll Now - Select a section to enroll in
Section Title
Hands-On Learning for Radio Frequency Spectrum Innovation
Online, self paced
Sep 12, 2022 to Dec 31, 2023
Contact Hours
569885 Registration $500.00
Section Notes

This course will utilize the Canvas learning management software to house digital course materials. No paper materials will be provided for this course. If registering with a .edu or .gov email address, please provide a secondary email for Canvas log-in credential set up.

Set up your Canvas account: You will receive an email from “Virginia Tech Guest Management Service” with the subject “Virginia Tech Guest Account Invitation.” Use this email to create your “Virginia Tech guest account,” which you will use to log in to Canvas. Your email address will be your log-in name. If you cannot find this email in your inbox, please try these steps:

- Look in your spam folder (Click the links for: how to find spam folder in Gmail, how to find spam folder in AOL, how to find spam folder in Yahoo)  
- Search your email for “Virginia Tech Guest Account Invitation”
- Search your email for “You have been invited to create a Virginia Tech guest account”

After creating your account, it may take 6 hours for your account to become active. You likely will not be able to log in right away. 

After waiting 6 hours, go to https://profdev-lms.tlos.vt.edu/ to view your Dashboard. You should see the HLSI  course. You can click into that course to proceed.

Can’t remember if you already set up your guest account? 
If you can’t remember whether or not you already set up your Canvas/Virginia Tech guest account or if you can’t remember your password, try going to https://profdev-lms.tlos.vt.edu/ and logging in. You may use the “I forgot my username or password” option to recover your forgotten username/password. Your username is your full email address you signed up with in registration.

Program Schedule: All modules are self-paced through Canvas.

This instance of the 4 Hands-On Learning for Radio Frequency Spectrum Innovation modules will close on August 31, 2023. All course modules must be completed by that time.

Refund and Cancellation Policy: Refund requests must be received 14 calendar days prior to the program start date. A $30 administrative fee will be deducted from all refunds. Requests should be sent by email or by initiating a drop request through the student portal in our online registration system. Please note: refunds will not be issued for no-shows or for cancellations received on or after the program start date. 

In the unlikely event that this program is cancelled or postponed due to insufficient enrollments or unforeseen circumstances, the university will fully refund registration fees but cannot be held responsible for any other expenses, including cancellation or change charges assessed by airlines, hotels, travel agencies, or other organizations.

Additional Information: If you have not received the email from Virginia Tech Guest Management Service to set up your Canvas account within 3 business days, please reach out to Cary Hoge (cdinkins@vt.edu) immediately and provide your First Name, Last Name, and an alternate email address.

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