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Hybrid Kalman/LMS decision feedback equalization strategy for terrestrial HDTV channels

机译:地面高清电视频道的混合Kalman / LMS决策反馈均衡策略

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An LMS decision feedback equalizer (DFE) with the Kalman algorithm used in training period is proposed for terrestrial HDTV broadcasting. The utilization of Kalman's algorithm is intended solely for fast startup and optimality of estimating the equalization coefficients. The LMS algorithm is employed in a decision-directed mode primarily due to its simplicity, robustness and good tracking behavior. The Kalman algorithm is implemented in a non-real-time manner (i.e. off-line), rather than real-time, to drastically reduce computational requirement for practical realization. The only penalty paid is an acceptable or tolerable small time delay. Simulation results show that this equalization strategy provides almost 3.0 dB signal-to-noise ratio (SNR) improvement at a BER of 3.0/spl times/10/sup -6/ with respect to the conventional LMS DFE scheme suggested by the Grand Alliance.
机译:针对地面高清电视广播,提出了一种在训练期间使用卡尔曼算法的LMS决策反馈均衡器(DFE)。卡尔曼算法的使用仅用于快速启动和估计均衡系数的最优性。 LMS算法由于其简单性,鲁棒性和良好的跟踪性能而被用于决策导向模式。卡尔曼算法以非实时方式(即,离线)而不是实时地实现,以大大减少实际实现的计算需求。所支付的唯一罚款是可接受的或可忍受的小延时。仿真结果表明,相对于大联盟提出的传统LMS DFE方案,这种均衡策略在BER为3.0 / spl乘以/ 10 / sup -6 /的BER下提供了近3.0 dB的信噪比(SNR)改善。

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