超宽带通信压缩感知信道估计与信号检测方法

针对超宽带信号在采样速率过高时难以采样的问题,利用信号稀疏性提出一种基于压缩感知的信道估计和信号检测算法(CS算法).将信号重复送入随机滤波器后发送,对接收信号进行欠采样,利用调制信号、滤波器、信道的圆周卷积关系建立压缩感知的数学模型,从而可采用基追踪算法实现信道估计和信号检测.仿真结果表明,CS算法所需的采样数据量仅为最小二乘算法的1/3或更少,而在中等信噪比(15~25 dB)的情况下,估计性能可以提高约4.5 dB,且可以准确检测出原始信号.

Ultra Wide-Band Channel Estimation and Signal Detection Through Compressed Sensing

A novel algorithm (CS algorithm) for channel estimation and signal detection is proposed to resolve the problem of excessively high sampling rate of the ultra-wideband signals. The algorithm is based on the compressed sensing (CS) theory. The modulated signal is transmitted after random-filtering, and the received signal is sub-sampled. The mathematical model of CS is developed by cyclic convolution of the modulated signals, the random filter and the channel, so the basic pursuit algorithm can be utilized to perform the task of channel estimation and signal de-tection. Simulation results show that the number of the sampling data required by the proposed algorithm is only one-third or less of the number of the sampling data needed by the least squares algorithm, while the estimation performance is improved by 4.5 dB under the moderate signal-to-noise ratio (15～25 dB) condition, and that the original transmitted signals are correctly detec-ted.