基于卡尔曼滤波算法的3G宽带CDMA信道估计

K. Shanmugan, M. Sánchez, L. de Haro, M. Calvo
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引用次数: 11

摘要

3G CDMA系统接收机中的许多信号处理操作依赖于对多径衰落信道的准确估计。如果信道估计不准确,RAKE接收机的性能和发射分集安排将显著降低。因此,设计3G系统的挑战之一是准确估计底层信道特性。针对3G系统提出的第一代信道估计算法依赖于使用导频符号。然而,通过仿真表明,可用于估计的导频符号数量少导致估计不佳,特别是在快速衰落条件下。本文介绍了一种将导频符号估计与信道模型相结合的信道估计卡尔曼滤波算法。本文建立了典型移动信道的ARMA模型,并利用该模型推导了卡尔曼滤波算法。通过仿真和分析表明,与仅基于导频符号的估计相比,卡尔曼滤波算法显著降低了信道估计的方差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Channel estimation for 3G wideband CDMA systems using the Kalman filtering algorithm
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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