Low-complexity MMSE receivers based on weighted matrix polynomials in frequency-selective mimo systems

Guido Dietl, Ingmar Groh, Wolfgang Utschick

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Compared to the Matrix Wiener Filter (MWF), reduced-rank signal processing in the Minimum Mean Square Error (MMSE) sense is a well-known method for the design of low-complexity receivers. In this paper, we reveal the relationship between different reduced-rank receivers based on weighted matrix polynomials approximating the MWF in a Krylov subspace, viz., the Multi-stage Matrix WF (MSMWF), the parallel implementation of Multi-Stage Vector WFs (MSVWFs), and Polynomial Expansion (PE). Besides, we present PE where the weights are approximated based on Random Matrix (RM) theory assuming the application to a frequency-selective Multiple-Input Multiple-Output (MIMO) system. Simulation results show that the MSMWF outperforms the considered reduced-rank methods if their order of computational complexity is the same.

Original languageEnglish
Title of host publicationProceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Pages699-702
Number of pages4
DOIs
StatePublished - 2005
Event8th International Symposium on Signal Processing and its Applications, ISSPA 2005 - Sydney, Australia
Duration: 28 Aug 200531 Aug 2005

Publication series

NameProceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Volume2

Conference

Conference8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Country/TerritoryAustralia
CitySydney
Period28/08/0531/08/05

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