On the symmetries and the capacity achieving input covariance matrices of multiantenna channels

  title={On the symmetries and the capacity achieving input covariance matrices of multiantenna channels},
  author={Mario D{\'i}az},
  journal={2016 IEEE International Symposium on Information Theory (ISIT)},
  • Mario Díaz
  • Published 30 January 2016
  • Computer Science, Mathematics
  • 2016 IEEE International Symposium on Information Theory (ISIT)
In this paper we study the capacity achieving input covariance matrices of a single user multiantenna channel based solely on the group of symmetries of its matrix of propagation coefficients. Our main result, which unifies and improves the techniques used in a variety of classical capacity theorems, uses the Haar (uniform) measure on the group of symmetries to establish the existence of a capacity achieving input covariance matrix in a very particular subset of the covariance matrices. This… Expand
Global Fluctuations of Random Matrices and the Second-Order Cauchy Transform
In this thesis we study the global fluctuations of random matrices (i.e., the covariance of two traces) from a second-order free probability perspective, putting a particular emphasis on blockExpand


On the Capacity of Block Multiantenna Channels
This paper proves an asymptotic capacity theorem that, in addition to reducing the optimization domain, does not depend on the dimension of the channel matrix. Expand
Capacity-achieving input covariance for single-user multi-antenna channels
The capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter is characterized and an iterative algorithm that exhibits remarkable properties is presented: universal applicability, robustness and rapid convergence. Expand
Capacity of a Gaussian MIMO channel with nonzero mean
We characterize the input covariance that maximizes the ergodic capacity of a flat-fading, multiple-input-multiple-output (MIMO) channel with additive white Gaussian noise, when the entries of theExpand
The strong asymptotic freeness of Haar and deterministic matrices
In this paper, we are interested in sequences of q-tuple of N-by-N random matrices having a strong limiting distribution (i.e. given any non-commutative polynomial in the matrices and their conjugateExpand
Asymptotic Freeness Almost Everywhere for Random Matrices
Voiculescu’s asymptotic freeness result for random matrices is improved to the sense of almost everywhere convergence. The asymptotic freeness almost everywhere is rst shown for standard unitaryExpand
Random Matrix Theory and ζ(1/2+it)
Abstract: We study the characteristic polynomials Z(U, θ) of matrices U in the Circular Unitary Ensemble (CUE) of Random Matrix Theory. Exact expressions for any matrix size N are derived for theExpand
Random Matrix Theory and Wireless Communications
A tutorial on random matrices is provided which provides an overview of the theory and brings together in one source the most significant results recently obtained. Expand
Capacity of Multi-antenna Gaussian Channels
  • E. Telatar
  • Computer Science
  • Eur. Trans. Telecommun.
  • 1999
The use of multiple transmitting and/or receiving antennas for single user communications over the additive Gaussian channel with and without fading is investigated, and formulas for the capacities and error exponents are derived. Expand
Representations of finite and compact groups
Groups and counting principles Fundamentals of group representations Abstract theory of representations of finite groups Representations of concrete finite groups. I: Abelian and Clifford groupsExpand
A matrix handbook for statisticians
An essential, one-of-a-kind book for graduate-level courses in advanced statistical studies including linear and nonlinear models, multivariate analysis, and statistical computing, and it also serves as an excellent self-study guide for statistical researchers. Expand