DocumentCode
3502292
Title
Rank minimization over finite fields
Author
Tan, Vincent Y F ; Balzano, Laura ; Draper, Stark C.
Author_Institution
Dept. of ECE, Univ. of Wisconsin-MadisonMadison, Madison, WI, USA
fYear
2011
fDate
July 31 2011-Aug. 5 2011
Firstpage
1195
Lastpage
1199
Abstract
This paper establishes information-theoretic limits in estimating a finite field low-rank matrix given random linear measurements of it. Necessary and sufficient conditions on the number of measurements required are provided. It is shown that these conditions are sharp. The reliability function associated to the minimum-rank decoder is also derived. Our bounds hold even in the case where the sensing matrices are sparse. Connections to rank-metric codes are discussed.
Keywords
decoding; matrix algebra; reliability; finite field low-rank matrix estimation; finite fields; information-theoretic limits; minimum-rank decoder; random linear measurements; rank minimization; reliability function; Decoding; Minimization; Noise measurement; Reliability; Sensors; Sparse matrices; Upper bound; Finite fields; Rank minimization; Rank-metric codes; Reliability function; Sparse measurement matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on
Conference_Location
St. Petersburg
ISSN
2157-8095
Print_ISBN
978-1-4577-0596-0
Electronic_ISBN
2157-8095
Type
conf
DOI
10.1109/ISIT.2011.6033722
Filename
6033722
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