CoSaMP algorithm of compressed sensing based on wavelet tree model
基于小波树模型的CoSaMP压缩感知算法

Due to network bandwidth limitation and energy consumption of sensor nodes in wireless sensor networksWSN, people usually want to reconstruct the original signal from little data in practical application. Compressed sensing CS theory has provided a solution for the problem above. Using CS theory, this paper launched the application research on sensed data in WSN. Aiming at the problem of more measurements and lower reconstruction accuracy in traditional CoSaMP algorithm, exploiting the structure characteristic of connected wavelet tree formed by the wavelet coefficients of signal, this paper proposed CoSaMP algorithm based on wavelet tree model. Applied the proposed algorithm to simulation experiments of CS on sensed data in WSN, and compared with the CS performance of traditional CoSaMP algorithm. Comparison results show that the proposed algorithm has a better performance of CS on sensed data in WSN within a certain range.