Matched filter bounds for reduced-order multichannel models

We propose two matched filter bounds (MFBs) to characterize the performance of receivers using reduced-order channel models. The first one, whitened matched filter bound (WMFB), uses the channel model to perform the spatio-temporal matched filtering that yields data reduction from multichannel to single-channel form. The rest of the processing remains optimal. The second one, ISI canceller matched filter bound (ICMFB), on the other hand bounds the performance of the Viterbi algorithm with the reduced channel model. Two methods of obtaining reduced-order channel models are discussed to illustrate these measures: blind channel estimation by deterministic maximum likelihood estimation (which maximizes WMFB) and channel estimation by training sequence