论文标题
低功率通信信号增强物联网基于非本地均值denoising的方法
Low power communication signal enhancement method of Internet of things based on nonlocal mean denoising
论文作者
论文摘要
为了改善物联网低功率通信信号的传输效果并压缩低功率通信信号的增强时间，本文设计了一种基于非本地平均值denoisising的物联网的低功率通信信号增强方法。首先，一维通信层的残差是通过卷积核心预先处理的，以获得一维通信层的残差。然后，根据两种分类识别方法，实现了物联网低功率通信信号的降噪信号特征识别，使用了非本地平均降低噪声算法来消除物联网的低功率通信信号，并且根据欧洲距离方法计算了相似块之间的重量值。最后，通过非局部平均值denoising方法实现了物联网的低功率通信信号增强。实验结果表明，该方法的通信信号增强时间开销很低，始终小于2.6s。信号增强后的最低位错误率约为1％，信噪比最高为18 dB，这表明该方法可以实现信号增强。
In order to improve the transmission effect of low-power communication signal of Internet of things and compress the enhancement time of low-power communication signal, this paper designs a low-power communication signal enhancement method of Internet of things based on nonlocal mean denoising. Firstly, the residual of one-dimensional communication layer is pre processed by convolution core to obtain the residual of one-dimensional communication layer; Then, according to the two classification recognition method, the noise reduction signal feature recognition of the low-power communication signal of the Internet of things is realized, the non local mean noise reduction algorithm is used to remove the low-power communication signal of the Internet of things, and the weight value between similar blocks is calculated according to the European distance method. Finally, the low-power communication signal enhancement of the Internet of things is realized by the non local mean value denoising method. The experimental results show that the communication signal enhancement time overhead of this method is low, which is always less than 2.6s. The lowest bit error rate after signal enhancement is about 1%, and the signal-to-noise ratio is up to 18 dB, which shows that this method can achieve signal enhancement.
