Spectrum sensing is one of the most challenging problems in cognitive radio systems. The spectrum of interest needs to be characterized and unused frequencies should be identified for possible exploitation in a simple and fast way, allowing the radio to catch up with the changing transmission parameters. A sensing method is presented where primary users are identified by matching the features extracted from the received signal to the a priori information about primary users' transmission characteristics. For estimation of some signal parameters, the cyclostationarity of the transmission spectrum is explored by using a suboptimal maximum likelihood (ML) estimator. The proposed algorithms can be used in cognitive radio for identifying various transmissions and for electronic surveillance.
Yucek, Tevfik and Arslan, Huseyin, "Method for OFDM signal identification and parameter estimation" (2012). USF Patents. 314.
University of South Florida