Turbo Channel Estimation Using the ´Iterative Soft Interference Cancelation and Correlation´ (I-SICC)

We present a simple but efficientalgorithm that iteratively refines the channel estimate in a turbo equalizer exploiting soft feedback (a-posteriori likelihoods) from the decoder. This algorithm, denoted as ´Soft Interference Cancelation and Correlation´ (SICC), repeatedly performs an interference cancelation step followed by correlation with symbol estimates derived from the output of the decoder. The novelty lies in two facts: first, the moments of the likelihood ratio density at the decoder output are used to remove the bias of the estimate. Second, an iterative version (I-SICC) is proposed where a data block is evaluated repeatedly without activation of the channel decoder. It is shown that this variant significantly outperforms its non iterative version.