Eigenvalue Distributions of Sums and Products of Large Random Matrices via Incremental Matrix Expansions

dc.creatorPeacock, Matthew J. M.
dc.creatorCollings, Iain B.
dc.creatorHonig, Michael L.
dc.date2005-11-15
dc.date.accessioned2026-07-07T08:15:45Z
dc.date.available2026-07-07T08:15:45Z
dc.descriptionThis 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 signal-to-interference-ratio of a multiuser CDMA system with a minimum mean-square error linear receiver.
dc.descriptionSubmitted to Trans IT
dc.identifierhttps://arxiv.org/abs/cs/0511054
dc.identifierhttp://arxiv.org/abs/cs/0511054
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/133551
dc.subjectInformation Theory
dc.titleEigenvalue Distributions of Sums and Products of Large Random Matrices via Incremental Matrix Expansions
dc.typetext

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