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On meeting the peak correlation bounds
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2014 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 62, no 5, 1210-1220 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we study the problem of meeting peak periodic or aperiodic correlation bounds for complex-valued sets of sequences. To this end, the Welch, Levenstein, and Exponential bounds on the peak inner-product of sequence sets are considered and used to provide compound peak correlation bounds in both periodic and aperiodic cases. The peak aperiodic correlation bound is further improved by using the intrinsic dimension deficiencies associated with its formulation. In comparison to the compound bound, the new aperiodic bound contributes an improvement of more than 35% for some specific values of the sequence length n and set cardinality m. We study the tightness of the provided bounds by using both analytical and computational tools. In particular, novel algorithms based on alternating projections are devised to approach a given peak periodic or aperiodic correlation bound. Several numerical examples are presented to assess the tightness of the provided correlation bounds as well as to illustrate the effectiveness of the proposed methods for meeting these bounds.

Place, publisher, year, edition, pages
2014. Vol. 62, no 5, 1210-1220 p.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-215143DOI: 10.1109/TSP.2014.2300064ISI: 000332034500014OAI: oai:DiVA.org:uu-215143DiVA: diva2:686314
Funder
EU, European Research Council, 228044Swedish Research Council
Available from: 2014-02-11 Created: 2014-01-11 Last updated: 2017-12-06Bibliographically approved

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Soltanalian, MojtabaStoica, Peter

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