Abstract
A non-iterative block processing algorithm for channel estimation is presented. This is suitable for time-division multiple access (TDMA) digital radio systems with a signal structure based on time-slots. Such channel estimator can be applied in conjunction with decision feedback equalizer, maximum likelihood sequence estimator (MLSE) or near-MLSE. A theoretical analysis of the estimator performances for slow and fast time-varying channels is presented. A procedure for determining the required training sequence length and the number of estimated coefficients in the channel impulse response is developed. Depending on channel characteristics, there is a particular length which yields optimum performances at the beginning of the data block. This length is analytically evaluated for constant amplitude zero-autocorrelation (CAZAC) sequences. Finally, the effects of channel estimation optimization are assessed by computer simulations.KeywordsChannel EstimationTraining SequenceChannel Impulse ResponseChannel EstimatorDecision Feedback EqualizerThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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