2008
DOI: 10.1109/tit.2008.920221
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Eigenvalue Distributions of Sums and Products of Large Random Matrices Via Incremental Matrix Expansions

Abstract: This paper uses an incremental matrix expansion approach to derive asymptotic eigenvalue distributions (a.e.d.'s) of sums and products of large random matrices. We show that the result can be derived directly as a consequence of two common assumptions, and matches the results obtained from using R-and S-transforms in free probability theory. We also give a direct derivation of the a.e.d. of the sum of certain random matrices which are not free. This is used to determine the asymptotic signalto-interference-rat… Show more

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Cited by 42 publications
(14 citation statements)
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“…Gaussian entries. In [7], Peacock et al extend the asymptotic result of [6] in the context of multi-user communications by considering a K-user MAC with channels H 1 , . .…”
Section: Introductionmentioning
confidence: 99%
“…Gaussian entries. In [7], Peacock et al extend the asymptotic result of [6] in the context of multi-user communications by considering a K-user MAC with channels H 1 , . .…”
Section: Introductionmentioning
confidence: 99%
“…By Bai and Silverstein's Lemma [31]- [33], we have −→ 1 [33]. It follows from the Markov inequality and the Borel-Cantelli lemma [34]…”
mentioning
confidence: 99%
“…The sums of pseudo-hermitian matrices were considered in [3]. The paper [12] is devoted to sums of the eigenvalues of random matrices. In the paper [6], non-selfadjoint operators in a Hilbert space are considered.…”
Section: Introduction and Statement Of The Main Resultsmentioning
confidence: 99%