基于信号结构重构的UWB稀疏信道盲估计

针对跳时脉冲位置调制的超宽带（ultra wideband based on time hopping pulse position modulation，TH-PPM UWB）通信系统，提出一种新的稀疏信道盲估计算法。该算法首先对信号结构进行重构，把发射信号与信息符号之间的非线性模型转换为线性模型，简化了信号处理难度；然后基于重构后的线性模型，推导出接收信号一阶统计向量与信道向量之间的关系，结合UWB信道的稀疏特性，估计出UWB信道参数，避免了无谓的抽头估计，提高了估计精度。仿真结果表明：新算法的均方误差（mean squared error，MSE）性能优于基于一阶统计量的盲信道估计算法，其BER性能也仅比理想信道差约1 dB。

New sparse blind channel estimation for UWB systems based on shaping signal structure

A novel blind sparse channel estimation algorithm is proposed for TH-PPM ultra wide-band communications. Firstly, the nonlinear structure of transmit signal and information symbol is transformed into the linear model which simplifies the complexity of signal processing. Secondly the relationship between first-order statistics vector of received signal and channel parameter vector is derived based on the shaping signal structure .Then the sparse and cluster structure of UWB channel is used to avoid non-important zero taps' estimation which promotes the performance of channel estimation. Simulation results demonstrate that the MSE performance of the new algorithm is superior to first order statistical methods for blind channel identification, also its BER performance is only about 1dB worse than the ideal channel.