Soft-Iterative Channel Estimation: Methods and Performance Analysis

In this paper, we propose a soft-iterative approach for the estimation of block-fading channels based on multiblock (MB) processing. Coded transmission over fading channels is usually performed by interleaving the code word over a large time interval and arranging it into data packets (or blocks) that include also pilot symbols to allow the estimation of the time-varying channel. In this paper, we propose to exploit this block-based structure, and also the inherent latency of soft-iterative receivers due to data interleaving, to improve the channel estimate accuracy. Within the observed frame of blocks, the MB approach uses the invariance of some multipath features, such as delays and mean powers, to estimate the covariance matrix of the channel vector and to identify the corresponding channel subspace. Here, the MB method is extended to incorporate soft information, which is available in iterative receiver structures. The performance of this soft-iterative method is derived in terms of mean square error of the estimate by using a general framework that applies also to other soft-based methods in the literature. A performance comparison is carried out among these estimation methods, both analytically and by numerical simulations, showing the benefits of the proposed approach on the turbo equalizer convergence.