Abstract: A novel Least Square（LS）-based blind channel estimation algorithm is proposed for the Ultra Wide-Band（UWB） communications by exploiting the first-order statistics of the received signals.Firstly，the cyclic convolution property of the received signals’ statistics is exploited to formulate the question of channel estimation，as the model is established in one symbol’s interval，the complexity of the algorithm is relative low.Then the Least Square（LS） algorithm is used to estimate the parameters of the taps.Simulation results demonstrate that the Minimum Squared Error（MSE） and Bit-Error Ratio（BER） performances of the proposed algorithm are almost the same as that of the Data-Aided ML（DA-ML） and Data-Aided LS（DA-LS） algorithms，but its complexity is decreased and the transmission efficiency is improved at the same time.

Key words: Ultra Wide-Band（UWB）, Least Square algorithm, blind channel estimation, first-order statistics

摘要： 针对超宽带系统的离散信道模型，利用接收信号的一阶统计量，提出一种基于最小二乘（LS）的盲信道估计算法。利用接收信号的循环卷积特性，在一个符号间隔内建立模型，最后利用LS算法求解。仿真表明，该算法与基于导频序列的ML估计方法和LS估计方法相比，均方误差（MSE）性能相差不大，但计算复杂度明显降低，同时提高了系统传输效率。

关键词: 超宽带, 最小二乘算法, 信道盲估计, 一阶统计量