Preconditioned and rank-flexible block conjugate gradient implementations of MIMO wiener decision feedback equalizers

Ingmar Groh, Guido Dietl, Wolfgang Utschick

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

7 Scopus citations

Abstract

In this paper, we present two extensions of the Block Conjugate Gradient (BCG) algorithm, a method which exploits the concept of block Krylov subspaces. First, we extend the BCG algorithm such that it is more flexible concerning the dimension of the block Krylov subspace. Second, a computationally efficient Preconditioned BCG (PBCG) algorithm is introduced which turns out to outperform the standard BCG algorithm concerning the complexity-performance ratio. Hence, we provide a powerful implementation for reduced-rank signal processing in the Minimum Mean Square Error (MMSE) sense. Simulation results show the gain in rank-flexibility and convergence speed.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesIV441-IV444
StatePublished - 2006
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: 14 May 200619 May 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
ISSN (Print)1520-6149

Conference

Conference2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
Country/TerritoryFrance
CityToulouse
Period14/05/0619/05/06

Fingerprint

Dive into the research topics of 'Preconditioned and rank-flexible block conjugate gradient implementations of MIMO wiener decision feedback equalizers'. Together they form a unique fingerprint.

Cite this