Computationally Efficient Chaotic Spreading Sequence Selection for Asynchronous DS-CDMA

Anna Litviņenko; Artūrs Āboltiņš

doi:10.1515/ecce-2017-0011

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Computationally Efficient Chaotic Spreading Sequence Selection for Asynchronous DS-CDMA

Electrical, Control and Communication Engineering

Volume 13 (2017): Issue 1 (December 2017)

By: Anna Litviņenko and Artūrs Āboltiņš

Open Access

|Dec 2017

Abstract

The choice of the spreading sequence for asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems plays a crucial role for the mitigation of multiple-access interference. Considering the rich dynamics of chaotic sequences, their use for spreading allows overcoming the limitations of the classical spreading sequences. However, to ensure low cross-correlation between the sequences, careful selection must be performed. This paper presents a novel exhaustive search algorithm, which allows finding sets of chaotic spreading sequences of required length with a particularly low mutual cross-correlation. The efficiency of the search is verified by simulations, which show a significant advantage compared to non-selected chaotic sequences. Moreover, the impact of sequence length on the efficiency of the selection is studied.

References

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Articles in this issue

DOI: https://doi.org/10.1515/ecce-2017-0011 | Journal eISSN: 2255-9159 | Journal ISSN: 2255-9140

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Language: English

Page range: 75 - 80

Published online: Dec 29, 2017

Published in print: Dec 1, 2017

Published by: Riga Technical University

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

Baseband,

Binary sequences,

Chaotic communication,

Communication systems,

Direct-sequence code-division multiple access,

Minimization,

Wireless sensor networks

Related subjects:

Engineering,

Introductions and overviews,

Engineering, other

© 2017 Anna Litviņenko, Artūrs Āboltiņš, published by Riga Technical University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 13 (2017): Issue 1 (December 2017)