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Data format classification for autonomous software defined radios

Show simple item record Simon, Marvin K. Divsalar, Dariush 2009-04-08T18:19:10Z 2009-04-08T18:19:10Z 2005-10-17
dc.identifier.citation IEEE Military Communication Conference, Atlantic City, New Jersey, October 17-20, 2005. en_US
dc.identifier.clearanceno 05-1244
dc.description.abstract We present maximum-likelihood (ML) coherent and noncoherent classifiers for discriminating between NRZ and Manchester coded (biphase-L) data formats for binary phase-shift-keying (BPSK) modulation. Such classification of the data format is an essential element of so-called autonomous software defined radio (SDR) receivers (similar to so-called cognitive SDR receivers in the military application) where it is desired that the receiver perform each of its functions by extracting the appropriate knowledge from the received signal and, if possible, with as little information of the other signal parameters as possible. Small and large SNR approximations to the ML classifiers are also proposed that lead to simpler implementation with comparable performance in their respective SNR regions. Numerical performance results obtained by a combination of computer simulation and, wherever possible, theoretical analyses, are presented and comparisons are made among the various configurations based on the probability of misclassification as a performance criterion. Extensions to other modulations such as QPSK are readily accomplished using the same methods described in the paper. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2005. en_US
dc.subject classification en_US
dc.subject formats en_US
dc.subject modulation en_US
dc.title Data format classification for autonomous software defined radios en_US
dc.type Preprint en_US

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