A Fast Convergent Optimal Channel Selection Method

Abstract

The invention discloses a fast-converging optimal channel selection method, which relates to the field of cognitive radio technology, and comprises the following steps: firstly, a state transition model based on G-E Markov channel is established, and according to the model, the channel under each time slot is obtained. channel state; then the optimal channel selection problem is defined as the MAB problem in machine learning, each channel is regarded as an arm in MAB, and the current optimal channel is calculated according to the difference in the return value of each arm . In the next iterative learning process, the channel confidence factor based on state statistics and the E‑E balance coefficient are innovatively added, and the maximum confidence upper bound g′ is calculated to update the income return of each arm; the cycle repeats until convergence To the optimal channel, the present invention can solve the problem of fast convergence and accurate channel selection of the system when multiple perceptual channels coexist.

Description

technical field [0001] The present invention relates to the field of cognitive radio technology, in particular to a method for fast and convergent optimal channel selection. Background technique [0002] With the rapid development of wireless communication services, wireless sensor networks have been widely used, such as smart home, smart city, environmental monitoring and other fields. The wireless sensor network is composed of a large number of micro sensor nodes, which use open frequency bands for communication, such as the ISM (Industrial Scientific Medical) frequency band. However, with the continuous increase of open devices, the network is seriously congested, and the reliability of communication is difficult to be guaranteed, which seriously affects the sustainable development of wireless sensor networks. In the case of the coexistence of multiple cognitive wireless channels, it can accurately and quickly converge to the optimal Optimal channel is a challenge faced ...

AI Technical Summary

Problems solved by technology

However, with the continuous increase of open devices, the network is seriously congested, and the reliability of communication is difficult to be guaranteed, which seriously affects the sustainable development of wireless sensor networks. In the case of the coexistence of multiple cognitive wireless channels, it can accurately and quickly converge to the optimal Optimal channel is a challenge faced by Cognitive Radio Sensor Network (CRSN), the traditional wireless channel selection method can realize the optimal channel selection problem

However, due to the large amount of calculation and time accumulation, the convergence speed cannot meet the requirements

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