Channel environment self-adaptive spectrum sensing method based on Catboost algorithm

Abstract

The invention discloses a channel environment self-adaptive spectrum sensing method based on a Catboost algorithm, comprising the following specific steps: 1, a secondary user collecting an energy value in a current channel environment and sending the energy value to a secondary user serving as a fusion center; 2, the main user discontinuously sending the channel resource occupation condition to afusion center; 3, the fusion center constructing the information sent by the primary user and the secondary user into a data set, and further constructing a feature vector set; 4, the fusion center using a Catboost algorithm to train the model; 5, the secondary user continuing to send the energy value to the fusion center, and the energy value serving as a test vector and being input into the trained model; 6, the fusion center sending the available channel resources to all the secondary users after obtaining the result, and the secondary users making a response according to the judgment of the fusion center. According to the method, under the condition that the false alarm rate is 0.1, the detection rate is increased by 10% compared with an SVM, and meanwhile, the false classification rate and the false classification risk are also remarkably reduced.

Description

technical field [0001] The invention belongs to the technical field of wireless communication and artificial intelligence. Specifically, it relates to a channel environment adaptive spectrum sensing method based on the Catboost algorithm. Background technique [0002] A wireless sensor network is a wireless self-organizing and data-centric network, which is composed of a large number of micro-sensing nodes with computing and communication capabilities. Due to the characteristics of low overhead and low power consumption of wireless sensor networks, it has been applied in industrial agriculture and other fields. However, with the development of wireless communication technology, the scarcity of spectrum resources has become the biggest challenge facing the current wireless sensor network. Now the main wireless sensor network frequency band is 2.4GHz, in the industrial field such as wireless HART WIA-PA and ISA100.11 is based on the physical layer of IEEE 802.15.4. Widely u...

AI Technical Summary

Problems solved by technology

However, these works have improved the detection rate of spectrum sensing to a certain extent, but there is still room for improvement. First, the detection rate can continue to increase, and secondly, the misclassification rate and misclassification risk rate also need to continue to increase.

Images