Abstract

This paper addresses the problem of adaptive multiple-input multiple-output (MIMO) equalization of time-varying channels (TVC). The proposed technique is based on Kalman filtering and decision feedback equalization. The time-varying channels can be estimated and tracked using a Kalman filter type of algorithm. An equalization technique for MIMO channels is derived based on a novel decision feedback equalizer structure. Moreover, we present a method to estimate the measurement and state noise variances used by the Kalman filter because they are crucial parameters in obtaining a reliable performance. The performance of the algorithm is investigated in simulations using realistic channels generated based on the COST 207 model. The results show that the algorithm performs well even in low SNR conditions or in difficult channel conditions.

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