Turbo equalization using partial Gaussian approximation

C. Zhang; Z. Wang; C.N. Manchon; P. Sun; Qinghua Guo; B.H. Fleury

doi:10.1109/LSP.2016.2581841

Turbo equalization using partial Gaussian approximation

C. Zhang, Z. Wang, C.N. Manchon, P. Sun, Qinghua Guo, B.H. Fleury

Research output: Contribution to journal › Article

2 Citations (Scopus)

Abstract

© 1994-2012 IEEE.
This letter deals with turbo equalization for coded data transmission over intersymbol interference (ISI) channels. We propose a message-passing algorithm that uses the expectation propagation rule to convert messages passed from the demodulator and decoder to the equalizer and computes messages returned by the equalizer by using a partial Gaussian approximation (PGA). We exploit the specific structure of the ISI channel model to compute the latter messages from the beliefs obtained using a Kalman smoother/equalizer. Doing so leads to a significant complexity reduction compared to the initial PGA implementation. Results from Monte Carlo simulations show that the proposed approach leads to a significant performance improvement compared to state-of-the-art turbo equalizers and allows for trading performance with complexity.

Original language	English
Pages (from-to)	1216-1220
Journal	IEEE Signal Processing Letters
Volume	23
Issue number	9
Early online date	16 Jun 2016
DOIs	https://doi.org/10.1109/LSP.2016.2581841
Publication status	Published - Sep 2016

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Low Complexity Factor Graph Receiver Design for Bandwidth Efficient Communication Systems Over Doubly Selective Channels

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Cite this

Zhang, C., Wang, Z., Manchon, C. N., Sun, P., Guo, Q., & Fleury, B. H. (2016). Turbo equalization using partial Gaussian approximation. IEEE Signal Processing Letters, 23(9), 1216-1220. https://doi.org/10.1109/LSP.2016.2581841

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AB - © 1994-2012 IEEE.This letter deals with turbo equalization for coded data transmission over intersymbol interference (ISI) channels. We propose a message-passing algorithm that uses the expectation propagation rule to convert messages passed from the demodulator and decoder to the equalizer and computes messages returned by the equalizer by using a partial Gaussian approximation (PGA). We exploit the specific structure of the ISI channel model to compute the latter messages from the beliefs obtained using a Kalman smoother/equalizer. Doing so leads to a significant complexity reduction compared to the initial PGA implementation. Results from Monte Carlo simulations show that the proposed approach leads to a significant performance improvement compared to state-of-the-art turbo equalizers and allows for trading performance with complexity.

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