A novel adaptive receiver with enhanced channel tracking capability for TDMA-based mobile radio communications

The paper presents a novel fast-adaptive nonlinear receiver which exploits soft statistics for tracking the random fluctuations experienced by time di vision multiple access (TDMA) mobile radio links impaired by frequency-sele ctive time-variant multipath phenomena. The detection task is accomplished by an Abend-Fritchman-like symbol-by-symbol maximum likelihood (SbS-ML) det ector which delivers both hard decisions and soft statistics in form of a p osteriori probabilities (APP's) of the states of the intersymbol interferen ce (ISI) channel. In the proposed adaptive receiver, these APP's are employ ed in place of the conventional hard-detected data to feed an ad hoc develo ped nonlinear recursive Kalman-type channel estimator. Extensive computer s imulations show that the exploitation of these soft statistics enhances the tracking capability of the channel estimator so that the proposed receiver generally outperforms the usual ones based on adaptive maximum likelihood sequence estimators (MLSE's) for signal-to-noise ratio (SNR) values over 12 -13 dB. Furthermore, the experienced performance gap with respect to more c omplex per-survivor processing (PSP)-based multiestimator detectors appears generally small on slowly and moderately fast time-varying channels charac terized by values of the product Doppler bandwidth x signaling period BDTS below 5 x 10(-3).