Joint Singular Value Distribution of Two Correlated Rectangular Gaussian Matrices and Its Application
Shuangquan Wang, Ali Abdi
Abstract
Let H=(hij) and G=(gij) be two m× n, m≤ n, random matrices, each with i.i.d complex zero-mean unit-variance Gaussian entries, with correlation between any two elements given by E[hijgpq]=ρδipδjq such that |ρ|<1, where denotes the complex conjugate and δij is the Kronecker delta. Assume \sk\k=1m and \rl\l=1m are unordered singular values of H and G, respectively, and s and r are randomly selected from \sk\k=1m and \rl\l=1m, respectively. In this paper, exact analytical closed-form expressions are derived for the joint probability distribution function (PDF) of \sk\k=1m and \rl\l=1m using an Itzykson-Zuber-type integral, as well as the joint marginal PDF of s and r, by a bi-orthogonal polynomial technique. These PDFs are of interest in multiple-input multiple-output (MIMO) wireless communication channels and systems.
Create a lesson
Related papers
Distribution-constrained optimal multiple stopping: the Root-type solution
Shuoqing Deng, Daxin Huang
Universality and sharp thresholds for ellipsoid fitting
Frederic Koehler, Youngtak Sohn
Local Laws and Edge Universality for Noncentral Sample Covariance Matrices
Can Hu, Jiang Hu, Zhidong Bai
Well-posedness and regularity of stochastic heat equations on moving domains
Chongyang Ren, Tusheng Zhang
Traveling Waves in Equity Markets with Rank-Based Entry and Exit
Graeme Baker, Caroline Smyth
An approximate zero bias transformation for random sums: Applications to sampling with outliers, auto insurance, and generative AI
Wasamon Jantai, Nathakhun Wiroonsri