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The aim of this paper is to improve the tracking performance of rapidly time-varying channels. This paper proposes a novel channel estimation scheme using nonuniform amplitude division based least mean square (LMS) algorithm motivated by the work of Shimamura et al. The estimators are arranged in a parallel fashion. The coefficient vectors for each estimator are calculated with the nonuniform classification...
This paper presents a novel tracking technique for rapidly time-varying channels. The proposed scheme supposes multiple linear transversal filters (estimators), which are constructed in a parallel structure. The coefficient vectors for each estimator are adapted by the least mean square (LMS) algorithm according to the information of the channel coefficient values. Computer simulation results show...
For the purpose of estimation of rapidly time variant multipath channels, we propose a novel channel estimation technique. The proposed scheme supposes multiple linear transversal filters, which are constructed in a parallel structure. The estimator coefficients for the proposed estimation scheme are adapted by the least mean square (LMS) algorithm and the recursive least squares (RLS) algorithm....
For the purpose of equalization of rapidly time variant multipath channels, we derive novel adaptation schemes based on the least mean square (LMS) algorithm. In two methods proposed in this paper, instead of a coefficient vector, a coefficient matrix is prepared for a linear transversal equalizer (LTE). Based on the estimated channel impulse response, the equalizer coefficients are selected and updated...
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