Low power communication signal enhancement method of Internet of things based on nonlocal mean denoising

TL;DR

This paper proposes a low-power IoT communication signal enhancement method using nonlocal mean denoising, achieving low processing time, reduced error rate, and improved signal-to-noise ratio.

Contribution

It introduces a novel signal enhancement approach based on nonlocal mean denoising tailored for low-power IoT communication signals.

Findings

Enhancement time is consistently under 2.6 seconds.

Bit error rate after enhancement is approximately 1%.

Signal-to-noise ratio reaches up to 18 dB.

Abstract

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.