Abstract—We investigate turbo equalization, or iterative equalization and decoding, as a receiver technology for systems where data is protected by an error-correcting code, shuffled by an interleaver, and mapped onto a signal constellation for transmission over a frequency-selective channel with unknown time-varying channel impulse response. The focus is the concept of soft iterative channel estimation, which is to improve the channel estimate over the iterations by using soft information fed back from the decoder from the previous iteration to generate “extended training sequences ” between the actual transmitted training sequences. Index Terms—Channel estimation, high-frequency communications, iterative channel estimation, turbo equalization.

A turbo equalization scheme consisting of an inner blind soft-in soft-out (SISO) equalizer and an outer SISO channel decoder is proposed and investigated. The receiver is suitable for wireless differential phase shift keying (DPSK) systems. The basic structure of the blind SISO equalizer consists of an iterative approximation of the joint maximum-likelihood (ML) solution with respect to (w.r.t.) channel estimation and sequence detection. The approximation is enhanced by adaptive channel estimation and by using a priori information delivered by the outer channel decoder. The DPSK/ISI super trellis is explicitly exploited for blind equalization rather than just doing differential decoding for resolving the problem of phase ambiguity. Phase ambiguity and shift ambiguity associated with trellis-based blind equalization are discussed for coded systems. Furthermore, new approaches are proposed to combat the phase ambiguity and the shift ambiguity.

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Abstract — In this paper, we present a low complexity turbo equalization receiver for data transmission over time-varying frequency-selective fading channels. In the receiver, an adaptive equalizer using nonlinear Kalman filters with delay is coupled with a soft-in soft-out (SISO) decoder to perform the reception process iteratively. The proposed adaptive equalizer jointly optimizes the estimates for channel taps and data symbols in each iteration with the assistance of aprioriinformation for the data symbols supplied by the SISO decoder. In this way, the correlation between the estimates of data symbols and channel taps is taken into account in the equalization process. This correlation is usually ignored in many other turbo equalizers with separated channel estimation and data equalization. The complexity of the proposed equalizer does not grow exponentially with the modulation constellation size, and is usually lower than that of many maximum a posteriori equalizers with joint channel estimation and data detection. Performance comparison with different types of turbo equalizers over different channel conditions by Monte Carlo simulations demonstrates the advantage of the proposed turbo equalizer for fast time-varying fading channels. Index Terms — Channel estimation, extended Kalman filters, frequency-selective fading, intersymbol interference, iterative

A subspace method for soft estimation of block-fading channels in turbo equalization