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

Fee Information

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
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