A Distributed Cooperative Spectrum Sensing Method Based on Max-Min Distance Clustering

Abstract

The invention discloses a method of maximum-minimum distance clustering-based distributed cooperation frequency spectrum sensing in a cognitive unmanned aerial vehicle network. A maximum-minimum distance clustering algorithm is utilized to divide cognitive unmanned aerial vehicles into a plurality of clusters, and cluster heads are selected in the clusters; all the cognitive unmanned aerial vehicles use energy detection to obtain sensing information of a main user; two-step fusion is carried out according to a clustering situation and the sensing information of all the cognitive unmanned aerial vehicles, and each cognitive unmanned aerial vehicle is enabled to obtain one piece of uniformly converged global sensing information; and a decision of whether the main user occupies a frequency spectrum is made according to the global sensing information. According to the method, communication of members in a cluster and a cluster head is ensured through dividing cognitive unmanned aerial vehicles with similar positions and similar mobility into the one cluster, the clustering algorithm reduces the number of information exchanges in distributed fusion, and detection efficiency is improved;and fusion of the global sensing information can be realized in a case of no fusion center through two-step fusion, the number of the sensing information exchanges is decreased, and fast and highly efficient frequency spectrum detection is realized.

Description

technical field [0001] The invention relates to a distributed cooperative spectrum sensing technology, in particular to a distributed cooperative spectrum sensing method based on maximum and minimum distance clustering. Background technique [0002] Spectrum sensing means that cognitive users obtain spectrum usage information in wireless networks through various signal detection and processing methods. Spectrum sensing technology can detect current spectrum information, find idle spectrum resources for reuse, and improve spectrum utilization. , to alleviate the contradiction between spectrum supply and demand caused by spectrum shortage. Since the detection performance is poor when a single cognitive user performs spectrum sensing, multiple cognitive users are used for cooperative spectrum sensing. For cognitive users with mobility, it is difficult to send all the sensing information to the fusion center for data fusion, while distributed frequency cooperation spectrum sens...

AI Technical Summary

Problems solved by technology

However, when the number of secondary users is large, multiple information exchanges are required to reach the convergence value, which increases the fusion delay and reduces the timeliness and accuracy of spectrum detection.

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