Adaptive, iterative, reduced-rank equalization for MIMO channels

Yakun Sun; Michael L. Honig; Vinayak Tripathi

Adaptive, iterative, reduced-rank equalization for MIMO channels

Yakun Sun^*, Michael L. Honig, Vinayak Tripathi

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

7 Scopus citations

Abstract

We present an adaptive iterative (turbo) Decision-Feedback Equalizer (DFE) for Multi-Input Multi-Output (MIMO) channels with Intersymbol Interference (ISI) and multiple receiver antennas. After initial training, the filters are computed directly from the received data and soft outputs of the MAP decoder according to a Least Squares (LS) cost criterion. The performance is compared with reduced-rank LS estimation methods, based on the Multi-stage Wiener Filter (MSWF). Numerical results show that the reduced-rank turbo DFE provides a substantial performance improvement relative to the full-rank turbo DFE with limited training. In addition, the reduced-rank filters can significantly reduce the computational complexity when the number of filter coefficients is large.

Original language	English (US)
Pages	1029-1033
Number of pages	5
State	Published - Dec 1 2002
Event	2002 MILCOM Proceedings; Global Information GRID - Enabling Transformation Through 21st Century Communications - Anaheim, CA, United States Duration: Oct 7 2002 → Oct 10 2002

Other

Other	2002 MILCOM Proceedings; Global Information GRID - Enabling Transformation Through 21st Century Communications
Country/Territory	United States
City	Anaheim, CA
Period	10/7/02 → 10/10/02

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

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title = "Adaptive, iterative, reduced-rank equalization for MIMO channels",

abstract = "We present an adaptive iterative (turbo) Decision-Feedback Equalizer (DFE) for Multi-Input Multi-Output (MIMO) channels with Intersymbol Interference (ISI) and multiple receiver antennas. After initial training, the filters are computed directly from the received data and soft outputs of the MAP decoder according to a Least Squares (LS) cost criterion. The performance is compared with reduced-rank LS estimation methods, based on the Multi-stage Wiener Filter (MSWF). Numerical results show that the reduced-rank turbo DFE provides a substantial performance improvement relative to the full-rank turbo DFE with limited training. In addition, the reduced-rank filters can significantly reduce the computational complexity when the number of filter coefficients is large.",

author = "Yakun Sun and Honig, {Michael L.} and Vinayak Tripathi",

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T1 - Adaptive, iterative, reduced-rank equalization for MIMO channels

AU - Sun, Yakun

AU - Honig, Michael L.

AU - Tripathi, Vinayak

PY - 2002/12/1

Y1 - 2002/12/1

N2 - We present an adaptive iterative (turbo) Decision-Feedback Equalizer (DFE) for Multi-Input Multi-Output (MIMO) channels with Intersymbol Interference (ISI) and multiple receiver antennas. After initial training, the filters are computed directly from the received data and soft outputs of the MAP decoder according to a Least Squares (LS) cost criterion. The performance is compared with reduced-rank LS estimation methods, based on the Multi-stage Wiener Filter (MSWF). Numerical results show that the reduced-rank turbo DFE provides a substantial performance improvement relative to the full-rank turbo DFE with limited training. In addition, the reduced-rank filters can significantly reduce the computational complexity when the number of filter coefficients is large.

AB - We present an adaptive iterative (turbo) Decision-Feedback Equalizer (DFE) for Multi-Input Multi-Output (MIMO) channels with Intersymbol Interference (ISI) and multiple receiver antennas. After initial training, the filters are computed directly from the received data and soft outputs of the MAP decoder according to a Least Squares (LS) cost criterion. The performance is compared with reduced-rank LS estimation methods, based on the Multi-stage Wiener Filter (MSWF). Numerical results show that the reduced-rank turbo DFE provides a substantial performance improvement relative to the full-rank turbo DFE with limited training. In addition, the reduced-rank filters can significantly reduce the computational complexity when the number of filter coefficients is large.

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M3 - Paper

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T2 - 2002 MILCOM Proceedings; Global Information GRID - Enabling Transformation Through 21st Century Communications

Y2 - 7 October 2002 through 10 October 2002

ER -

Adaptive, iterative, reduced-rank equalization for MIMO channels

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ASJC Scopus subject areas

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