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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.
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 |
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Article number | 7493612 |
Pages (from-to) | 1216-1220 |
Number of pages | 5 |
Journal | IEEE Signal Processing Letters |
Volume | 23 |
Issue number | 9 |
Early online date | 16 Jun 2016 |
DOIs | |
Publication status | Published - Sept 2016 |
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Dive into the research topics of 'Turbo equalization using partial Gaussian approximation'. Together they form a unique fingerprint.Projects
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Low Complexity Factor Graph Receiver Design for Bandwidth Efficient Communication Systems Over Doubly Selective Channels
Guo, Q. (Investigator 01)
ARC Australian Research Council
1/01/12 → 30/12/14
Project: Research