On the Wigner distribution of a class of complex spreading sequences

Wyk, D.J. van; Lotter, M.P.; Linde, L.P.

doi:10.1109/comsig.1993.365864

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Extending this evaluation of mis-matched signal reception performance even further, an evaluation of ‫ݖ‬ ఊ ሺ݊ሻ signal despreading was performed against a phase-and amplitude-compressed QPSK-based DSSS emulation ‫ݓ‬ሺ݊ሻ of ‫ݖ‬ሺ݊ሻ. 2 The resulting (limiting) distributions for these complexvalued symbol estimates are captured in Table 3. Each of these mis-matched symbol estimate distributions have been validated using an FPGA-accelerated signal statistics testbed, permitting rapid generation and processing of these Ȗ-parameterized signals.…”

Section: Percent Gaussian Waveforms: Mismatched Receptionmentioning

confidence: 99%

“…The most important use of these results is in predictive algorithms that adapt Ȗ over time. 2 The sequence ‫ݓ‬ሺ݊ሻ is constructed by bypassing the magnitude mapping and maintaining only 2 MSBs to the phase mapping within the BM transform.…”

Section: Percent Gaussian Waveforms: Mismatched Receptionmentioning

confidence: 99%

“…In designing a family of orthogonal spread spectrum waveform derived from digital chaotic circuits [1], recognition of the PAPR's impact on system implementation trades led to generalization of the Gaussian distributed "chaos waveform," to a phase coherent constant amplitude zero autocorrelation (CAZAC) waveform [2,3] and amplitude varying spreading sequence characteristics that retain the core benefits of random phase signals [4]. This paper presents an integrated model for a set of "percent Gaussian" waveforms, using an amplitude scaling parameter Ȗ that ranges from 0% (constant amplitude) to 100% (Gaussian distributed amplitude).…”

Section: Introductionmentioning

confidence: 99%

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Performance of Percent Gaussian Orthogonal Signaling Waveforms

Michaels¹,

Lau

2014

2014 IEEE Military Communications Conference

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

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Section: Percent Gaussian Waveforms: Mismatched Receptionmentioning

confidence: 99%

Section: Percent Gaussian Waveforms: Mismatched Receptionmentioning

confidence: 99%