CONFERENCE PROCEEDINGS
Advanced Search >
Home > Proceedings > Volume 10188 > Article
Translator Disclaimer
1 May 2017 Comparison of RF spectrum prediction methods for dynamic spectrum access
Jacob A. Kovarskiy; Anthony F. Martone; Kyle A. Gallagher; Kelly D. Sherbondy; Ram M. Narayanan
Author Affiliations +
Proceedings Volume 10188, Radar Sensor Technology XXI; 1018819 (2017) https://doi.org/10.1117/12.2262306
Event: SPIE Defense + Security, 2017, Anaheim, California, United States
Abstract
Dynamic spectrum access (DSA) refers to the adaptive utilization of today’s busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Jacob A. Kovarskiy, Anthony F. Martone, Kyle A. Gallagher, Kelly D. Sherbondy, and Ram M. Narayanan "Comparison of RF spectrum prediction methods for dynamic spectrum access", Proc. SPIE 10188, Radar Sensor Technology XXI, 1018819 (1 May 2017); doi: 10.1117/12.2262306; https://doi.org/10.1117/12.2262306
ACCESS THE FULL ARTICLE
PERSONAL SIGN IN
Full access may be available with your subscription
 
Forgot your username?
Forgot your password?
No SPIE account? Create an account
or Institutional Sign In via Shibboleth
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $14.40
Non-members: $18.00 ADD TO CART
PROCEEDINGS
 11 PAGES
DOWNLOAD PDF SAVE TO MY LIBRARY
SHARE
GET CITATION
< Previous Article
|
Next Article >
Advertisement
Advertisement
KEYWORDS
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top