Multi-scale spectrum access method based on service requirements

Abstract

The invention discloses a multi-scale frequency spectrum access method based on business requirements. The method comprises the following steps: learning to establish a PST (Probabilistic Suffix Tree) state tree according to a binary sequence of channel using states; considering business requirement differences of a cognitive radio system, and utilizing PST in a length-variable Markov model to perform multi-scale prediction on the channel states, and then guiding a frequency spectrum access strategy. According to the method disclosed by the invention, the PST algorithm performs complex sequence data modeling, the method is simple and suitable for analysis, moreover, a learning process has good theoretical performance guarantee, and the prediction accuracy is high; and the multi-scale prediction is performed on the channel states by the PST according to cognitive business requirements, so that a secondary user can access a channel matched with the business requirements preferentially, collision rate between a primary user and a secondary user can be reduced effectively, QoS (Quality of Service) of wireless communication is improved, and the utilization ratio of frequency spectrum is increased.

Description

technical field [0001] The invention belongs to the technical field of multimedia communication, and relates to a spectrum prediction method and a spectrum access strategy based on a variable length longer than a Markov model in a cognitive radio system, and specifically refers to a multi-scale spectrum access method based on service requirements. Background technique [0002] With the rapid development of wireless communication services, the contradiction between the waste of a large amount of spectrum resources caused by the fixed spectrum allocation strategy and the shortage of spectrum resources has become increasingly obvious, so cognitive radio (CognitiveRadio, CR) technology emerged as the times require. The cognitive radio system realizes the effective sharing of spectrum resources by sensing and dynamically accessing the surrounding spectrum. Among them, the spectrum access technology is used to solve the problem of whether to access and how to access the idle spect...

AI Technical Summary

Problems solved by technology

[0003] There are various problems in the existing spectrum prediction algorithm based on Markov model: the state of the first-order Markov model at the next moment is only related to the current state, and the prediction ability is limited; The complexity grows exponentially; the training of the HMM model requires large training samples, which increases the complexity; the complexity of POMDP is high, and it is only suitable for small-scale problems

Existing spectrum access strategies have focused on issues such as the available spectrum range, channel conflict, and channel gain for secondary users. However, a certain type of cognitive service may have similar spectrum usage. , will not only affect the QoS of cognitive services, but also may reduce the utilization of spectrum holes

For example, connecting a secondary user with a longer service requirement to a channel with fewer continuous available time slots will cause the secondary user to frequently switch among multiple different channels; similarly, connecting a secondary user with a shorter service requirement to a continuous Channels with more available time slots will lead to problems such as low utilization of spectrum holes

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