Adaptive iterative detection for turbo codes on flat fading channels

Abstract

Several structures for adaptive iterative detection (AID) for fading channels have been described in the literature. One approach to AID, iterative detection with a decoupled estimator, has been proposed with hard decision feedback. Recently, it was noted that a soft decoder (e.g., turbo decoder) makes it possible to feed back soft information on data to the decoupled channel estimator. In this paper we present adaptive iterative detection with a decoupled channel estimator (decoupled-AID) based on hard or soft decision feedback from a turbo decoder. The performance of the decoupled-AID on two modulation methods (e.g., punctured-QPSK, 8PSK) is compared. As a decoupled channel estimator, the Wiener filter and Kalman filter are considered based on probabilistic channel models. A new feedback method, which uses partial soft information with or without amplitude normalization, is proposed.