Performance of Percent Gaussian Orthogonal Signaling Waveforms

作者: Alan J. Michaels , Chad Lau

DOI: 10.1109/MILCOM.2014.61

关键词:

摘要: Recent developments of secure digital chaotic spread spectrum communication systems have been based on the generalized ideals maximum channel capacity and maximal entropy/security, which result in a Gaussian-distributed noise like signal that is indistinguishable from naturally occurring (band limited) thermal noise. An implementation challenge associated with these waveforms peak-to average power ratio (PAPR) approximately an i.i.d Gaussian distributed random sequence, infinite tails distribution, modeled practically by distribution truncated to ±4.8s, peak excursions output can be 13-15 dB over power. To address this PAPR constraint, series "percent Gaussian" orthogonal signaling were developed, allowing parameterized waveform selection compactly trade improvements cyclostationary feature content, are bounded chaos constant amplitude zero autocorrelation (CAZAC) signal, all deliver security advantages traditional direct sequence (DSSS) waveforms. This paper presents underlying model for waveforms, derives set symbol error rate metrics. Discussion performance bounds also presented.

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