Title :
Spectral Distribution of Random Matrices From Binary Linear Block Codes
Author :
Babadi, Behtash ; Tarokh, Vahid
Author_Institution :
Sch. of Eng. & Appl. Sci., Harvard Univ., Cambridge, MA, USA
fDate :
6/1/2011 12:00:00 AM
Abstract :
Let C be a binary linear block code of length n, dimension k and minimum Hamming distance d over GF(2)n. Let d⊥ denote the minimum Hamming distance of the dual code of C over GF(2)n. Let ε:GF(2)n→{-1,1}n be the component-wise mapping ε(vi):=(-1)vi, for v=(v1,v2,...,vn) ∈ GF(2)n. Finally, for p <; n, let mmbΦC be a p × n random matrix whose rows are obtained by mapping a uniformly drawn set of size p of the codewords of C under ε. It is shown that for d⊥ large enough and y:=p/n ∈ (0,1) fixed, as n→∞ the empirical spectral distribution of the Gram matrix of [1/(√n)]mmbΦC resembles that of a random i.i.d. Rademacher matrix (i.e., the Marchenko-Pastur distribution). Moreover, an explicit asymptotic uniform bound on the distance of the empirical spectral distribution of the Gram matrix of [1/(√n)]mmbΦC to the Marchenko-Pastur distribution as a function of y and d⊥ is presented.
Keywords :
Hamming codes; binary codes; block codes; linear codes; random processes; Gram matrix; Marchenko-Pastur distribution; binary linear block codes; component-wise mapping; empirical spectral distribution; minimum Hamming distance; random matrices; Atmospheric measurements; Block codes; Covariance matrix; Hamming distance; Joints; Particle measurements; Symmetric matrices; Asymptotic spectral distribution; Marchenko–Pastur law; coding theory; random matrix theory; randomness of sequences;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2011.2137330