Iterative Equalizer Based on Kalman Filtering and Smoothing for MIMO-ISI Channels

Sangjoon Park, Sooyong Choi

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


This paper proposes an iterative equalizer based on Kalman filtering and smoothing (IEKFS) for multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels. A state-space model with a priori information and the corresponding Kalman filtering (KF) and Kalman smoothing (KS) operations are developed. The KF operations perform a linear minimum mean-square error (MMSE) equalization procedure with soft interference cancellation. In addition, the KF and KS operations produce and exchange the updated extrinsic information. During this IEKFS process, the soft estimate of a desired symbol does not participate in the equalization procedures for the desired symbol; only the feedback information of the other transmit symbols is used. Therefore, the proposed IEKFS performs iterative linear MMSE equalization based on the Kalman framework and turbo principle. The complexity of the IEKFS is linear with respect to the number of transmit signal vectors in a transmission block, and simulation results show that the IEKFS can achieve near-optimum bit error rate performances approaching the matched filter bound (MFB) of the channel in various environments.

Original languageEnglish
Article number7160764
Pages (from-to)5111-5120
Number of pages10
JournalIEEE Transactions on Signal Processing
Issue number19
Publication statusPublished - 2015 Oct 1

Bibliographical note

Publisher Copyright:
© 1991-2012 IEEE.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering


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