Low complexity iterative equalization for severe time dispersive MIMO channels

Sajid Ahmed*, T. Ratnarajah, M. Sellathurai, Colin Cowan

*Corresponding author for this work

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

2 Scopus citations

Abstract

In this work, reduced complexity minimum mean squared error (MMSE) iterative equalization methods for a multiple-input multiple-output (MIMO) frequency selective channel are proposed. To combat the severe time dispersiveness of the channel OFDM is incorporated. Use of OFDM simplifies the challenging problem of equalization in a MIMO system, due to both inter-symbol-interference (ISI) and co-antenna interference (CAI). The iterative algorithms work in two stages. The first stage estimates the transmitted symbols using a low complexity MMSE equalizer, which accounts for the variance of the already estimated symbols. Then, the second stage finds the a posteriori probabilities of the estimated symbols to find their means and variances to use in the MMSE equalizer in the following iteration. Simulation results show the performance of the proposed iterative algorithm is better than the MMSE equalizer and close to the matched filter bound (MFB) at low computational cost.

Original languageEnglish (US)
Title of host publicationConference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages2102-2106
Number of pages5
DOIs
StatePublished - Dec 1 2006
Event40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States
Duration: Oct 29 2006Nov 1 2006

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
CountryUnited States
CityPacific Grove, CA
Period10/29/0611/1/06

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Low complexity iterative equalization for severe time dispersive MIMO channels'. Together they form a unique fingerprint.

Cite this