Many of the signal processing operations in the receivers for 3G CDMA systems depend on accurate estimates of the multipath fading channel. The performance of RAKE receivers and transmit diversity arrangements will degrade significantly if channel estimates are not accurate. Hence, one of the challenges in the design of 3G systems is accurate estimation of the underlying channel characteristics. The first generation of channel estimation algorithms proposed for 3G systems relied on using the pilot symbols. However, it has been shown through simulations that the small number of pilot symbols available for estimation leads to poor estimates, especially in fast fading conditions. In this paper, we introduce a Kalman filter algorithm for channel estimation that combines pilot symbol based estimates with a channel model. We derive an ARMA model for a typical mobile channel with a Jakes Doppler spectrum and use this model to derive the Kalman filtering algorithm. Through simulation and analysis we show that the Kalman filter algorithm reduces the variance of the channel estimate significantly compared to an estimate based on pilot symbols alone.
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