Iterative equalization and decoding using reduced-state sequence estimation based soft-output algorithms
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We study and analyze the performance of iterative equalization and decoding (IED) using an M-BCJR equalizer. We use bit error rate (BER), frame error rate simulations and extrinsic information transfer (EXIT) charts to study and compare the performances of M-BCJR and BCJR equalizers on precoded and non-precoded channels. Using EXIT charts, the achievable channel capacities with IED using the BCJR, M-BCJR and MMSE LE equalizers are also compared. We predict the BER performance of IED using the M-BCJR equalizer from EXIT charts and explain the discrepancy between the observed and predicted performances by showing that the extrinsic outputs of the $M$-BCJR algorithm are not true logarithmic-likelihood ratios (LLR's). We show that the true LLR's can be estimated if the conditional distributions of the extrinsic outputs are known and finally we design a practical estimator for computing the true LLR's from the extrinsic outputs of the M-BCJR equalizer.
true LLRs' estimation
Tamma, Raja Venkatesh (2005). Iterative equalization and decoding using reduced-state sequence estimation based soft-output algorithms. Master's thesis, Texas A&M University. Texas A&M University. Available electronically from