Deterministic equivalents for certain functionals of large random matrices
arXiv:math/0507172 · doi:10.1214/105051606000000925
Abstract
Consider an random matrix where the entries are given by , the being independent and identically distributed, centered with unit variance and satisfying some mild moment assumption. Consider now a deterministic matrix A_n whose columns and rows are uniformly bounded in the Euclidean norm. Let . We prove in this article that there exists a deterministic matrix-valued function T_n(z) analytic in such that, almost surely, \[\lim_{n\to+\infty,N/n\to c}\biggl(\frac{1}{N}\operatorname {Trace}(Σ_nΣ_n^T-zI_N)^{-1}-\frac{1}{N}\operatorname {Trace}T_n(z)\biggr)=0.\] Otherwise stated, there exists a deterministic equivalent to the empirical Stieltjes transform of the distribution of the eigenvalues of . For each n, the entries of matrix T_n(z) are defined as the unique solutions of a certain system of nonlinear functional equations. It is also proved that is the Stieltjes transform of a probability measure , and that for every bounded continuous function f, the following convergence holds almost surely \[\frac{1}{N}\sum_{k=1}^Nf(λ_k)-\int_0^{\infty}f(λ)π_n(dλ)\mathop {\longrightarrow}_{n\to\infty}0,\] where the are the eigenvalues of . This work is motivated by the context of performance evaluation of multiple inputs/multiple output (MIMO) wireless digital communication channels. As an application, we derive a deterministic equivalent to the mutual information: \[C_n(σ^2)=\frac{1}{N}\mathbb{E}\log \det\biggl(I_N+\frac{Σ_nΣ_n^T}{σ^2}\biggr),\] where is a known parameter.
Published at http://dx.doi.org/10.1214/105051606000000925 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
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