针对传统LMMSE算法需要知道信道特性的问题,提出了一种加权系数平均法改进的小波域LMMSE信道估计算法.运用离散小波变换对LS初始估计和预滤波处理后的信号实行阈值量化去噪处理,然后结合时域信道能量分布的稀疏性特征,利用加权系数平均法求出各子载波的频域响应,从而克服了传统LMMSE算法需要预先知晓信道统计特性的缺陷.对算法的BER和MSE性能进行实验仿真,结果表明:文中所提改进算法的信道估计整体性能显然会更优于LS、SVD-LMMSE以及加权平均改进后的LMMSE算法.另外,在信噪比较低且信道统计特性未可知的状况下,文中算法要优于传统的LMMSE算法,并能够较好地降低噪声的影响,有效提升信道估计的精确度.%In view of the problem that the traditional LMMSE channel estimation algorithm is required to know the characteristics of the channel statistical.An improved LMMSE channel estimation algorithm based on weighted average method in wavelet domain is proposed.The DWT is used to quantify the threshold of the signal after LS channel estimation and pre-filter in this algorithm.Then,together with the time-domain channel sparse characteristics of the energy distribution.And,the weighted coefficient average method is used to get the frequency response of each subcarrier.Thus,the problem that the traditional LMMSE algorithm must be required to know the characteristics of the channel statistical is solved.Aim at the BER and the MSE performance of this algorithm,its performance is simulated.The simulation results show that:the performance of the improved algorithm is better than the traditional LS,SVD-LMMSE and the improved LMMSE algorithm by the weighted average method.Besides,under the condition of low SNR and unknown the channel statistical properties,this algorithm is better than the traditional LMMSE algorithm.It shows that this improved algorithm can preferably reduce the effect of noise,and improve the accuracy of channel estimation effectively.
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