Binary sequences with good aperiodic autocorrelations using cross-entropy method

Authors:
Shaowei Wang;Jian Wang;Xiaoyong Ji;Yuhao Wang
Affiliations:
Department of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, P.R. China;Department of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, P.R. China;Department of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, P.R. China;Information Engineering School, Nanchang University, Nanchang, Jiangxi, P.R. China
Venue:
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Year:
2009

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A survey of the merit factor problem for binary sequences

SETA'04 Proceedings of the Third international conference on Sequences and Their Applications

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Abstract

Cross Entropy (CE) has been recently applied to combinatorial optimization problems with promising results. In this short paper a CE based algorithm is presented to search for binary sequences with good aperiodic autocorrelation properties. The algorithm proposed can explore and exploit the solution space efficiently. In most cases, it can frequently find out binary sequences with higher merit factor and lower peak sidelobe level very quickly.