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Spectral Distribution of Random Matrices From Binary Linear Block Codes

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2 Author(s)
Babadi, B. ; Sch. of Eng. & Appl. Sci., Harvard Univ., Cambridge, MA, USA ; Tarokh, Vahid

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.

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Information Theory, IEEE Transactions on  (Volume:57 ,  Issue: 6 )