Wireless link quality prediction method based on LSTM neural network

A wireless link quality and prediction method technology, applied in the field of quality prediction based on LSTM neural network wireless communication link reliability confidence interval, can solve the problem of low wireless link quality prediction accuracy

Active Publication Date: 2020-05-19
ELECTRIC POWER RES INST OF STATE GRID ANHUI ELECTRIC POWER +1
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Problems solved by technology

[0009] The purpose of the present invention is to propose a more reasonable prediction method in order to solve the shortcomings of the low prediction accuracy of wireless link quality in the above-mentioned technical solutions

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  • Wireless link quality prediction method based on LSTM neural network
  • Wireless link quality prediction method based on LSTM neural network
  • Wireless link quality prediction method based on LSTM neural network

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Embodiment Construction

[0068] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0069] Basic method flow diagram of the present invention is as figure 1 shown. It can be seen from the figure that the present invention includes a training stage of the LSTM neural network model and a wireless link quality prediction application stage based on the training result.

[0070] The specific steps of this embodiment are as follows.

[0071] Step 1, LSTM neural network model training phase

[0072] Step 1.1, set the structure and parameters of the LSTM neural network model

[0073] Let the input of the LSTM neural network model be the input data x of this training t , the output data h of the previous training t-1 and the state data c of the previous training t-1 ;

[0074] Let the output of the LSTM neural network model be the output data h of this training t and the state data c of this training t , the output data h of ...

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Abstract

The invention discloses a wireless link quality prediction method based on an LSTM neural network. The prediction method comprises the following steps: a wireless communication device collects and stores a wireless link quality signal-to-noise ratio signal sequence as a communication link quality original signal sequence; a mean filtering method is adopted to decompose the communication link quality original signal sequence into a stable sequence and a noise sequence, the noise sequence calculates a noise standard deviation, training and prediction application are performed on the two parts ofdesigned LSTM neural network models respectively, and finally a confidence interval of a required communication link is calculated. The predicted lower bound is compared with the lowest communicationreliability requirement of the intelligent power grid to judge whether the lowest communication reliability standard is met or not. The method can be widely applied to the field of wireless sensor networks, effectively predicts the link quality, and improves the stability and reliability of link transmission.

Description

technical field [0001] The present invention relates to a wireless link quality prediction method based on LSTM neural network, in particular to a quality prediction method based on LSTM neural network wireless communication link reliability confidence interval. [0002] technical background [0003] There are usually multiple transmission paths to choose between wireless sensor network nodes. By predicting the wireless link quality between adjacent nodes and selecting the adjacent node with the best link to forward data, it can not only improve the reliability of communication, but also reduce the risk of communication errors. Delay caused by failed retransmissions. Therefore, accurately predicting the quality of wireless links is an effective way to improve the communication reliability of wireless sensor networks. [0004] Wireless link quality is a kind of non-stationary random time series with time-varying, random and nonlinear. At present, the prediction methods for t...

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Application Information

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IPC IPC(8): H04W24/02H04W24/06
CPCH04W24/02H04W24/06
Inventor 丁津津孙伟高博李鹏宇李奇越汪玉李远松李帷韬孙辉张峰汪勋婷何开元陈洪波
Owner ELECTRIC POWER RES INST OF STATE GRID ANHUI ELECTRIC POWER
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