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Blind sequence-length estimation of low-SNR cyclostationary sequences


Vlok, JD and Olivier, JC, Blind sequence-length estimation of low-SNR cyclostationary sequences, IET Communications, 8, (9) pp. 1578-1588. ISSN 1751-8628 (2014) [Refereed Article]

Copyright Statement

Copyright 2014 The Institution of Engineering and Technology

DOI: doi:10.1049/iet-com.2013.0616


Several existing direct-sequence spread spectrum (DSSS) detection and estimation algorithms assume prior knowledge of the symbol period or sequence length, although very few sequence-length estimation techniques are available in the literature. This study presents two techniques to estimate the sequence length of a baseband DSSS signal affected by additive white Gaussian noise. The first technique is based on a known autocorrelation technique which is used as reference, and the second technique is based on principal component analysis. Theoretical analysis and computer simulation show that the second technique can correctly estimate the sequence length at a lower signal-to-noise ratio than the first technique. The techniques presented in this study can estimate the sequence length blindly which can then be fed to semi-blind detection and estimation algorithms.

Item Details

Item Type:Refereed Article
Keywords:algorithms, Gaussian noise (electronic), packet networks, principal component analysis, signal detection, white noise
Research Division:Engineering
Research Group:Electrical engineering
Research Field:Electrical engineering not elsewhere classified
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Olivier, JC (Professor JC Olivier)
ID Code:98986
Year Published:2014
Web of Science® Times Cited:11
Deposited By:Engineering
Deposited On:2015-03-11
Last Modified:2018-03-17

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