Robust blind channel identification and equalization based on multi-step predictors

This contribution deals with the problem of blind channel identification and equalization based on the (temporally or spatially) oversampled channel output. A novel algorithm is presented which builds on a multistep prediction (MSP) approach and can be viewed as a certain generalization of the initial linear prediction algorithm (LPA) proposed in 1994. Our algorithm improves on related works in that it is theoretically and practically unsensitive to the critical and expected problem of channel length mismatch. Moreover, the MSP scheme improves on the conventional LPA by increasing the robustness of this earlier algorithm. In contrast with the LPA, the proposed prediction scheme exploits the full channel structure, thus providing more statistical efficiency in channel identification. A direct symbol recovery algorithm (requiring no channel estimate) is also straightforwardly drawn from our approach.