Title :
Combinatorial lower bound for list decoding of codes on finite-field Grassmannian
Author_Institution :
Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fDate :
July 31 2011-Aug. 5 2011
Abstract :
Codes constructed as subsets of the projective geometry of a vector space over a finite field have been shown to have applications as random network error correcting codes. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or equivalently, a subset of the vertices of the corresponding Grassmannian graph. These codes are referred to as codes on finite-field Grassmannian or more generally as subspace codes. In this paper, we study fundamental limits to list decoding codes on finite-field Grassmannian. By exploiting the algebraic properties of the Grassmannian graph, we derive a new lower bound on the code size for the first relaxation of bounded minimum distance decoding, that is, when the worst-case list size is restricted to two. We show that, even for small finite field size and code parameters, codes on finite-field Grassmannian admit significant improvements in code rate when compared to bounded minimum distance decoding.
Keywords :
decoding; error correction codes; graph theory; Grassmannian graph; algebraic property; bounded minimum distance decoding; code parameters; code rate; code size; codeword; combinatorial lower bound; finite field size; finite-field Grassmannian; fixed integer; fundamental limits; list decoding codes; projective geometry; random network error correcting codes; subspace codes; vector space; worst-case list size; Approximation methods; Decoding; Encoding; Geometry; Laboratories; Network coding;
Conference_Titel :
Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on
Conference_Location :
St. Petersburg
Print_ISBN :
978-1-4577-0596-0
Electronic_ISBN :
2157-8095
DOI :
10.1109/ISIT.2011.6033970