压缩感知的UWB信道盲估计算法

针对超宽带系统采样速率过高难以实现的问题,利用信道稀疏性提出一种基于压缩感知的盲信道估计算法。将接收信号通过一个随机测量矩阵,利用测量信号的一阶统计量建立压缩感知的数学模型,最后利用正交匹配追踪(OMP)算法重构得到估计信道。算法只需很少测量值就可估计出信道,节省了大量的模数转换(ADC)资源,使系统实现成为可能。仿真结果表明算法具有良好的估计性能,且算法的误比特率(BER)性能相比利用准确信道只有2～3dB的差距。

A blind channel estimation algorithm for Ultra Wide-band channel based on compressive sensing

The sampling speed for the ultra wide band (UWB) channel is too high to realize with the existing sampling technology. To solve the problem, a novel blind channel estimation algorithm was presented based on the theory of compressive sensing. Firstly, some measurements are obtained which are linear combinations of the received signals multiplied by a random incoherent measurement matrix. Then, the mathematical model is established by exploiting the first statistics of the measurements. Finally, the orthogonal matching pursuit (OMP) algorithm is utilized to get the estimating channel parameters. With the proposed algorithm, the number of the measurements need for channel estimation is much smaller than that of the samples needed for the existing algorithms, which reduces the ADC resources greatly. The simulation result shows that the estimation performance of the algorithm is good, while the bit error rate (BER) is only 2~3dB higher than that of the exact channel.