Holonomic Gradient Method for the Cumulative Distribution Function of the Largest Eigenvalue of a Complex Wishart Matrix with Noncentrality Matrix of Rank One

Yuta Fukasawa () and Akimichi Takemura ()
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Yuta Fukasawa: The Risk Data Bank of Japan, Limited
Akimichi Takemura: Shiga University, Faculty of Data Science

Chapter Chapter 6 in Recent Developments in Multivariate and Random Matrix Analysis, 2020, pp 83-101 from Springer

Abstract: Abstract We apply the holonomic gradient method for evaluation of the cumulative distribution function of the largest eigenvalue of a complex Wishart matrix with the noncentrality matrix of rank one. This problem appears in the context of Rician fading of multiple-input/multiple-output (MIMO) wireless communications systems. We also give a brief survey of the use of multivariate analysis in wireless communication and the holonomic gradient method for statistical problems of performance evaluation in wireless communication.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-56773-6_6

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DOI: 10.1007/978-3-030-56773-6_6

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