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Low-density parity-check (LPDC) decoders assume the channel estateinformation (CSI) is known and they have the true a posteriori probability(APP) for each transmitted bit. But in most cases of interest, the CSI needs tobe estimated with the help of a short training sequence and the LDPC decoderhas to decode the received word using faulty APP estimates. In this paper, westudy the uncertainty in the CSI estimate and how it affects the bit error rate(BER) output by the LDPC decoder. To improve these APP estimates, we propose aBayesian equalizer that takes into consideration not only the uncertainty dueto the noise in the channel, but also the uncertainty in the CSI estimate,reducing the BER after the LDPC decoder.

Channel Decoding with a Bayesian Equalizer