基于理想自相关训练序列的双选信道估计方法

Doubly Selective Channel Estimation Based on Ideal Autocorrelation Sequence

高速移动下的无线宽带通信要经历时间和频率双选择性衰落,近些年来双选信道的估计越来越受到关注。该文利用复指数基扩展模型(BEM),提出一种基于理想自相关训练序列的双选信道估计方法,其训练序列的能量均匀分布,能够消除峰均比的问题。文中分析并证明了具有理想自相关特性等间隔放置的训练序列,能够使信道估计的MSE最小化。仿真表明与传统的zero-padding方式信道估计相比,在获得相同信道估计性能的情况下,采用该文信道估计方法的系统的峰均比有很大改善。

High data rates and high mobility-induced Doppler shifts introduce time- and frequency-selectivity in wireless links. Recently, doubly selective channel estimation has attracted much attention. In this paper, using a basis expansion channel model, a scheme based on ideal autocorrelation sequence is proposed for the estimation of doubly selective channel parameters. The training sequences have constant modulus so that large peak-to-average ratio problem can be avoided. It has been shown that the employment of this optimal pilot sequence can minimize Mean-Square Error （MSE） of the channel estimation. Simulation results demonstrate that the peak-to-average ratio of the proposed scheme is considerably improved compared to the existing zero-padding scheme for the same MSE performance .