农业无线监测传感网中压缩感知的应用研究

Compressed Sensing in Agricultural Monitoring Wireless Sensor Networks

针对农业无线监测传感网络中节点能耗过快,影响整个网络寿命问题,文章提出一种新型高效的数据采集传输的方法。该方法将压缩感知理论应用到传感器节点,采用离散傅里叶变换方法采集稀疏信号,利用重构误差更小的ROMP算法重构原信号。通过MATLAB对温度进行仿真实验,研究结果表明,采用压缩感知理论后,不但能近乎完美地重构信号,且以接近10%的压缩率来采样数据,节点发送能耗相对传统压缩算法最高提高80%左右,因此有效地延长网络的生命周期。

In Agricultural Monitoring wireless sensor networks, the node energy consumption is so fast that affecting the entire wireless sensor network lifetime. This paper proposes a novel scheme of data transmission with high efficiency. Sensor nodes are applied to the theory of compressed sensingtheory. To collect the spare signal the method adopts discrete Fourier transform method, then using ROMP algorithm to reconstruct the original signal with a lower error rate. In this paper, we carry out simulation experiment on the temperature through MATLAB. The simulation results show that this method can keep perfect reconstruction of the signal, and close to 10% of the sampled data compression rate, thus greatly reducing the pressure of channel bandwidth, the node sends energy compared to traditional compression algorithms increased almost by 80%, while reducing the transmission node power, thus effectively prolonging the network lifetime.