LARGE INFORMATION PLUS NOISE RANDOM MATRIX MODELS AND CONSISTENT SUBSPACE ESTIMATION IN LARGE SENSOR NETWORKS

DOI10.1142/S2010326311500067zbMath1248.15029arXiv1106.5119OpenAlexW2157532148MaRDI QIDQ2884853

Walid Hachem, Xavier Mestre, Pascal Vallet, Philippe Loubaton, Jamal Najim

Publication date: 18 May 2012

Published in: Random Matrices: Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1106.5119

zbMATH Keywords

consistencyregularizationquadratic formcovariance matrixPoincaré inequalitysingular valuesrandom matrix modelsMUSIClocalization of the eigenvaluessubspace estimationGaussian information plus noise matrixinformation plus noise modellarge sensor networks

Mathematics Subject Classification ID

Point estimation (62F10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Eigenvalues, singular values, and eigenvectors (15A18) Random matrices (algebraic aspects) (15B52) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (8)

Analysis of the limiting spectral measure of large random matrices of the separable covariance type ⋮ Random matrix theory in statistics: a review ⋮ A CLT for linear spectral statistics of large random information-plus-noise matrices ⋮ On the inference about the spectral distribution of high-dimensional covariance matrix based on high-frequency noisy observations ⋮ Cauchy noise loss for stochastic optimization of random matrix models via free deterministic equivalents ⋮ Identifiability of parametric random matrix models ⋮ SOME REMARKS ON THE DOZIER–SILVERSTEIN THEOREM FOR RANDOM MATRICES WITH DEPENDENT ENTRIES ⋮ On generalized expectation-based estimation of a population spectral distribution from high-dimensional data

Cites Work

• Analysis of the limiting spectral distribution of large dimensional information-plus-noise type matrices
• The largest eigenvalues of finite rank deformation of large Wigner matrices: Convergence and nonuniversality of the fluctuations
• An inequality for the multivariate normal distribution
• On the empirical distribution of eigenvalues of large dimensional information-plus-noise-type matrices
• Deterministic equivalents for certain functionals of large random matrices
• A new application of random matrices: \(\operatorname{Ext} (C_{\text{red}}^*(F_2))\) is not a group
• The estimation of frequency
• MUSIC, maximum likelihood, and Cramer-Rao bound
• Modified Subspace Algorithms for DoA Estimation With Large Arrays
• On the Capacity Achieving Covariance Matrix for Rician MIMO Channels: An Asymptotic Approach
• A Simple Approach to the Global Regime of Gaussian Ensembles of Random Matrices
• Distributions of Matrix Variates and Latent Roots Derived from Normal Samples

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