A method and system for real-time prediction of intelligent shortwave frequency across frequency bands

Abstract

The invention discloses a method and system for real-time prediction of intelligent shortwave frequency across frequency bands. The method comprises the steps of: using historical sampling data to train a prediction model based on a neural network, and the prediction model is used to predict the communication quality of other frequencies according to the frequency characteristic information of a certain frequency; The range of the next available frequency; Obtain the frequency characteristic information at the short-wave communication interruption moment; Input the frequency characteristic information at the short-wave communication interruption moment into the prediction model to obtain the communication quality of each frequency in the range; Select the communication within the range The frequency with the best quality is selected as the next available frequency after shortwave communication is interrupted. The present invention takes other frequency points with high reliability of link establishment near the communication interruption frequency point as the prediction target, which can reduce the training complexity of the neural network when faced with a large amount of nonlinear data, and the prediction target is more suitable for the actual working equipment Operational needs.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and more particularly, relates to an intelligent short-wave frequency cross-frequency real-time prediction method and system. Background technique [0002] In actual short-wave communication, due to the instability of the short-wave channel itself, the communication link is often interrupted suddenly, and the selection of the next frequency with good communication effect largely depends on experience, and both real-time and reliability are required. To ensure that, in the face of sudden short-wave communication interruption, the processing method is limited. [0003] The frequency prediction method based on neural network can make real-time prediction of short-wave frequency by the nonlinear approximation ability of neural network. However, in actual use, the existing methods often need to acquire communication data of all frequency bands, and cannot perform cross-frequency band p...

AI Technical Summary

Problems solved by technology

However, the existing methods often need to obtain the communication data of the whole frequency band in actual use, and cannot make cross-band prediction based on the data of the used frequency band, and the practicability is not strong

At the same time, affected by the changeable short-wave channel, the communication data of the same frequency band obtained by the experiment will also change drastically in a short period of time. The data obtained by a single sampling is not representative, and the reliability of the training data is not strong.

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