Adaptive Bayesian and EM-based detectors for frequency-selective fading channels
نویسندگان
چکیده
In this paper, the problem of adaptive maximum a posteriori (MAP) symbol detection for the uncoded transmission as well as the problem of adaptive soft-input soft-output (SISO) demodulation for the coded transmission of data symbols over the time-varying frequency-selective channel are explored within the framework of the expectation-maximization (EM) algorithm. In particular, several recursive forms of the classical Baum-Welch (BW) algorithm and its Bayesian counterpart (often referred to a Bayesian EM algorithm) are derived in an unified way. In contrast to the earlier developments of the BW and BEM algorithms, the formulations derived in this paper lead to computationally attractive algorithms which avoid matrix inversions while using sequential processing over the time and trellis branch indices. Moreover, it is shown how these recursive versions of the BW and BEM algorithms can be integrated with the well-known forward–backward processing SISO algorithms resulting in adaptive SISOs with embedded soft decision directed (SDD) channel estimators. An application of the proposed algorithms to the iterative “turbo-processing” receivers illustrates how these SDD channel estimators can efficiently exploit the extrinsic information obtained as feedback from the SISO decoder in order to enhance their estimation accuracy.
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عنوان ژورنال:
- IEEE Trans. Communications
دوره 51 شماره
صفحات -
تاریخ انتشار 2003