Author :
Detert, T. ; Drauge, R. ; De Broeck, I. ; Sorger, U.
Abstract :
The technique presented here improves a previously proposed iterative channel data estimation (ICDE) technique in M-ary data transmission over time-variant frequency selective channels by using a proportionate sample adaptive filter for channel tracking on a per-survivor processing (PSP) basis. Henceforth, we call the approach using proportionate algorithm P-ICDE. The data detector is a simple M-algorithm with extended metric calculation that minimizes the expectation of the Euclidian distance between received signal and convolution of channel and data hypotheses. For low velocities, the technique can work with an initial channel estimate as data detector only, simply as M- algorithm with extended metric. Known techniques, such as delayed decision feedback sequence estimation (DDFSE), optionally with reduced state sequence estimation (RSSE) or adaptive state allocation (ASA), for comparison, reduce the complexity of the Viterbi detector by shortening of the channel impulse response or applying decision feedback on the trellis. In order to keep the performance loss low, a minimum-phase overall impulse response, achieved by an allpass approximating front-end prefilter (FEP), is crucial for these techniques. Our detector, however, works without FEP, which, if block adapted, would lead to severe degradation in fast fading. The detector can work with 3-5 states only, depending on the quality of the channel estimates, the multipath profile of the channel and the symbol constellation.
Keywords :
adaptive filters; channel coding; channel estimation; iterative methods; M-ary data transmission; Viterbi detector; channel tracking; front-end prefilter; iterative channel data estimation; proportionate sample adaptive filter; time-variant frequency selective channel; Adaptive filters; Convolution; Data communication; Delay estimation; Detectors; Frequency estimation; Iterative algorithms; State estimation; State feedback; Viterbi algorithm; Adaptive equalizers; Adaptive signal detection; Dispersive channels; Maximum likelihood detection; Sequential detection;