基于叠加训练序列的稀疏信道估计

对于稀疏多径衰落信道,提出了一种叠加训练序列和匹配跟踪算法相结合的信道估计方法.为了提高系统带宽效率,采用迭代的叠加训练估计信道响应,该方法将一低功率周期性的训练序列直接叠加于信息序列,利用接收数据的均值求得信道响应,不需要任何额外带宽资源.在许多无线通信环境中,信道呈现稀疏特性,利用该稀疏特性,采用匹配跟踪算法估计信道响应中的非0点,以此可以降低加性高斯白噪声引起的性能损失.通过计算机仿真表明,本文的方法可以达到很好信道估计性能.

Sparse Channel Estimation Based on Superimposed Training

For sparse multi-path fading channel, a channel estimation method using superimposed straining combined with matching pursuit (MP) algorithm is presented. In order to improve the efficiency of system bandwidth, an iterative superimposed straining based channel estimation method is presented. In this method, a periodic training sequence with low power is superimposed to the information sequence at transmitter. With the mean of received data, channel parameters can be estimated without consuming any extra system bandwidth at receiver. Channels with a sparse impulse response arise in a number of wireless communication environments, exploiting this characteristic, a matching pursuit (MP) algorithm is utilized to estimate the nonzero taps of channel coefficients, so performance loss caused by AWGN can be reduced. From the result of computer simulations,the proposed method can achieve good channel estimation performance is shown.