Random matrix theory and wireless communications
Communications and Information Theory
Journal of Multivariate Analysis
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In this paper, we improve known results on the convergence rates of spectral distributions of large-dimensional sample covariance matrices of size p × n. Using the Stieltjes transform, we first prove that the expected spectral distribution converges to the limiting Marcenko--Pastur distribution with the dimension sample size ratio y=yn=p/n at a rate of O(n- 1/2) if y keeps away from 0 and 1, under the assumption that the entries have a finite eighth moment. Furthermore, the rates for both the convergence in probability and the almost sure convergence are shown to be Op(n-2/5) and oa.s.(n-2/5+\eta), respectively, when y is away from 1. It is interesting that the rate in all senses is O(n-1/8) when y is close to 1.