Iterative channel estimation and coded symbol detection for dispersive channels

We propose two pilot symbol aided iterative algorithms for channel re-estimation to be used in iterative detection and decoding (turbo-detection) of signals transmitted over frequency selective channels. The first algorithm is based on the expectation-maximization (EM) algorithm that makes use of a signal decomposition to compute separate dosed form recursion expressions for the channel coefficient re-estimates. The a posterior conditional channel state probabilities required by the EM-based turbo-estimation can be easily provided by the forward-backward trellis search performed by the soft-in soft-out (SISO) ISI decoding task. The second algorithm is based on the well-known bootstrap algorithm where soft information from the outer decoder is used to make hard decisions on transmitted coded data, and the detected coded data are used in the channel turbo-estimation process via the conventional linear pseudo-inverse method. Both of the proposed channel turbo-estimation algorithms are naturally embedded in the framework of the turbo-detector, bringing almost no overhead to the receiver complexity