Opportunity spectrum access method based on sideband observation information multi-arm tiger machine model

Abstract

The invention discloses an opportunity spectrum access method based on a sideband observation information multi-arm tiger machine model. The method comprises the following steps: firstly, aiming at asecondary user access problem under the conditions that cognitive network channel information is unknown and channel perception is imperfect, carrying out detection perception on N channels, and selecting a channel problem suitable for access to be modeled as MABP-SI model; sensing all authorized channels by a secondary user, recording a sensing observation result, updating a probability vector, and recording a channel set which is sensed to be idle; creating a candidate set of spatial probability vector estimated values, and selecting an estimated value of an idle probability vector; judgingwhether the idle channel set is empty or not at the time slot t: if the set is empty, not accessing the secondary user to any channel, and if the set is not empty, selecting k authorized channels withthe maximum coefficient to access; and finally, updating t to t + 1, and circulating. According to the method, the income loss of channel access under the statistical asymptotic condition is reduced,and the method has the advantage of statistical asymptotic effectiveness.

Description

technical field [0001] The invention relates to the technical field of spectrum access, in particular to an opportunistic spectrum access method based on a sideband observation information multi-armed bandit model. Background technique [0002] In recent years, with the rapid development of wireless networks, spectrum resources are more congested and the frequency conflict of low utilization is becoming more and more prominent. How to improve the utilization of current resources through spectrum opportunity access has become a research hotspot. The core idea of ​​spectrum opportunistic access is that in cognitive wireless networks, secondary users can use their real-time spectrum sensing capabilities to identify and prioritize idle channels for opportunistic access based on the sensing results without affecting the normal work of spectrum licensed users. , in order to achieve the purpose of improving spectrum utilization and effectively alleviate the problem of scarcity of w...

AI Technical Summary

Problems solved by technology

[0005] 1. Poor adaptability to the actual environment

Most of the existing methods are perceptual access methods when the statistical information is known, and they cannot run in problems where the statistical information is unknown or difficult to obtain in time

The premise of existing methods is the consistency of sensing and accessing channels, that is, the number of sensing and accessing channels is the same, but in reality, the large difference between the received and transmitted energy of the secondary user makes there exist multiple sensing channels under the condition of limited power energy. channel, select the case of accessing the preferred part of the channel, the traditional method does not consider this case

[0006] 2. The method has poor asymptotic statistical properties

Restricted by the statistical model, the optimal performance is mainly based on the cumulative gain loss as a time logarithmic function, the balance efficiency of the channel sensing and access process is not high, and the characteristics of practical problems are insufficiently studied

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