High-dimensional damaged data wireless transmission method based on noise reduction auto-encoder

Abstract

The invention discloses a high-dimensional damaged data wireless transmission method based on a noise reduction auto-encoder. The method comprises model training and end-to-end transmission. In the model training, firstly, data preprocessing is performed on a historical perception data set, and the historical perception data set is divided based on a K-fold cross validation method; and then constructing a noise reduction auto-encoder model, and training the noise reduction auto-encoder model based on a proposed novel noise adding mode of introducing random Gaussian noise in batches. According to end-to-end transmission, firstly, a noise reduction auto-encoder obtained through training is divided into two parts to be deployed at a sending end and a receiving end, then, perception data of unknown type of noise interference is subjected to preprocessing and dimension reduction operation at the sending end, the data subjected to dimension reduction is transmitted to the receiving end, finally, reconstruction operation is executed at the receiving end, and reconstruction data of the undamaged perception data is obtained. According to the method, dimension reduction transmission, noise reduction processing and reconstruction of high-dimensional damaged sensing data can be effectively carried out, and noise interference is filtered and dimension reduction transmission is carried out when data collection is carried out in a severe environment.

Description

technical field [0001] The invention relates to the field of signal processing, in particular to a reliable transmission method for high-dimensional damaged data dimensionality reduction and noise reduction integration based on a noise reduction autoencoder in a wireless sensor network. Background technique [0002] With the rapid development of communication and information technology, the demand for information and the amount of data to be processed are also increasing. How to efficiently process a large amount of network data and minimize transmission, storage, and computing costs has become a major problem that we need to solve urgently. . Wireless sensor networks have been widely used in many fields, such as environmental monitoring, military reconnaissance, precision agriculture and so on. However, due to the size of the sensors, their computing, storage, and communication resources are very limited, and they cannot load the computing and transmission of huge amounts ...

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Problems solved by technology

[0006] The purpose of the present invention is to solve the situation that the wireless sensor network deployment environment is harsh, the starting node resources are limited, and the amount of data to be transmitted is large and damaged. The current network signal processing method has high calculation and design costs, is limited by the scene, accuracy and compression In order to solve the problem of low rate, a wireless transmission method of high-dimensional damaged data based on noise reduction autoencoder is proposed

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