Low Coherence Sensing Matrices Based on Best Spherical Codes

Konferenz: SCC 2013 - 9th International ITG Conference on Systems, Communication and Coding
21.01.2013 - 24.01.2013 in München, Deutschland

Tagungsband: SCC 2013

Seiten: 6Sprache: EnglischTyp: PDF

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Lazich, Dejan E.; Zörlein, Henning; Bossert, Martin (Institute of Communications Engineering, Ulm University, 89081 Ulm, Germany)

A method for constructing low coherence sensing matrices based on best spherical codes is proposed. Such matrices are applied in Compressed Sensing (CS) to obtain measurements of a sparse vector. With the means of CS, it is possible to reconstruct the sparse vector from a small number of measurements. Several properties have been considered in order to determine the CS-suitability of matrices, e.g. the restricted isometry property or the coherence. By the proposed construction method, the coherence of the sensing matrix is optimized. Numerical simulation results demonstrating the p