基于自适应压缩感知的信道估计算法

传统方法压缩感知算法截取训练序列最后未被数据干扰固定部分作为观测矩阵,该方法为了抵抗最差的信道而浪费了大量的可用观测数据。在此基础上提出了一种自适应压缩感知的信道估计算法,首先对训练序列进行自适应检测,得到整个未受干扰的观测矩阵,再用压缩感知算法计算信道估计。仿真结果表明,这种基于自适应压缩感知的信道估计算法大幅提高了信道估计的准确性。

Channel Estimation Based on Adaptive Compressive Sensing

A lot of compressive sensing methods are applied in channel estimation for better performance.The accuracy of compres- sive sensing method is closely related to the observation matrix.The traditional method takes the fixed final part of the training sequence not interfered by the former valid data as observation matrix.In order to resist the worst channel, the traditional method will waste a lot of available observation sequence in practical scenarios.An adaptive compressive sensing-based channel estimation is proposed in this paper： the entire un-interfered training sequence is detected dynamically to obtain the whole un-interfered observation matrix and the compressive sensing method is used to calculate the channel estimation. The simulation results show that the proposed method can effectively improve the accuracy of channel estimation.