Optimization Method for the Measurement Matrix of Compressive Sensing in Wireless Sensor Networks
DANG Xiao-chao1，2，LIU Yan-xing1，HAO Zhan-jun1，2
1（College of Computer Science and Engineering，Northwest Normal University，Lanzhou 730070，China）2（Gansu Province Internet of Things Engineering Research Center，Lanzhou 730070，China）
Abstract：Because of the limited hardware resources in wireless sensor network，the measurement matrix designed in traditional ways cannot meet the demand of data acquisition.Therefore，an hybrid algorithm which based on gradient descent of discrete wavelets transform datums is proposed in this paper，aims to optimize the original measurement matrix.This method can reduce the complexity of the data space，improve the convergence rate of the algorithm，and enhance the non correlation between the measurement matrix and sparse matrix.The experimental comparison and analysis indicate that the method has fast convergence speed，the data reconstruction success rate is significantly higher than that of traditional measurement methods，reduces the measurement matrix design and implementation difficulty，improves the ability to remove the noise，and it is suitable for application in the low sampling rate network environment.
2017, Vol. 38 
