DVB_RCS satellite channel dynamic distribution method based on predicating of wavelet neural network

Abstract

The invention relates to a DVB_RCS satellite channel dynamic distribution method based on predicating of a wavelet neural network. In terms of the multiple-scale features of satellite network flow, firstly, a wavelet neural network flow predicating algorithm is used for predicating real-time arrived flow of user stations of the next cycle and sending the real-time arrived flow to a gateway station; secondly, the gateway station performs distribution as needed according to the real-time access data rate of all the user stations in each channel application distribution cycle. The access data rate in the next cycle predicated by all the user stations serves as weight allocation residual capacitance. The DVB_RCS satellite channel dynamic distribution method based on predicating of the wavelet neural network is characterized in that in terms of the multiple-scale features of satellite service flow such as long relevance, self similarity and the multiple fractal property, the flow of the next moment is predicated with the wavelet neural network, the predication accuracy of the flow is improved, service time slots are reasonably distributed, service time delay is effectively shortened, the service quality of the users is ensured and the channel resource utilization rate is improved.

Description

technical field [0001] The invention belongs to the field of satellite communication, in particular to a DVB_RCS satellite channel dynamic allocation method based on wavelet neural network prediction. Background technique [0002] Satellite bandwidth resources are tight, and the main purpose of multiple access is to maximize and most effectively utilize satellite bandwidth resources. Multiple access methods mainly include fixed allocation, random allocation, and on-demand allocation. Fixed allocation method, when the number of terminals increases or the business is not too balanced, this access method is no longer applicable, especially for sudden business. The access mode is assigned randomly. When the traffic volume increases, collisions will occur, which will cause an increase in transmission delay (especially for geostationary satellites), and continuous retransmission will lead to performance degradation. [0003] The method of on-demand allocation is to send a reserv...

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Problems solved by technology

[0007] The technical problem to be solved by the present invention: In view of the multi-scale characteristics of satellite service traffic such as long-term correlation, self-similarity and multi-fractality, the existing on-board prediction method is not accurate enough, the present invention provides a DVB_RCS The channel allocation method based on wavelet neural network prediction for broadband satellites can improve the accuracy of traffic forecasting, reasonably allocate business time slots, effectively shorten business delays, ensure user service quality, and improve channel resource utilization

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