Statistical characterization of the chordal product determinant of Grassmannian codes-Reference-Cited by-同舟云学术

Statistical characterization of the chordal product determinant of Grassmannian codes

Published:2023-04-27 Issue:3 Volume:12 Page:2406-2422
ISSN:2049-8772
Container-title:Information and Inference: A Journal of the IMA
language:en
Short-container-title:

Author:

Álvarez-Vizoso Javier¹^ORCID,Beltrán Carlos²³,Cuevas Diego¹,Santamaría Ignacio¹,Tuček Vít⁴,Peters Gunnar⁴

Affiliation:

1. Department of Communications Engineering, Universidad de Cantabria , Plaza de la Ciencia 1, 39005 Santander , Spain

2. Department of Mathematics , Statistics and Computing, , Av. de los Castros 48, 39005 Santander , Spain

3. Universidad de Cantabria , Statistics and Computing, , Av. de los Castros 48, 39005 Santander , Spain

4. Department of Wireless Algorithms, Huawei Technologies , 16440 Kista , Sweden

Abstract

Abstract We consider the chordal product determinant, a measure of the distance between two subspaces of the same dimension. In information theory, collections of elements in the complex Grassmannian are searched with the property that their pairwise chordal products are as large as possible. We characterize this function from an statistical perspective, which allows us to obtain bounds for the minimal chordal product and related energy of such collections.

Funder

Huawei Technologies

Ministerio de Universidades

Ministerio de Ciencia e Innovación

Agencia Estatal de Investigación

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computational Theory and Mathematics,Numerical Analysis,Statistics and Probability,Analysis

Link

https://academic.oup.com/imaiai/article-pdf/12/3/2406/51603034/iaad035.pdf

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