Construction method of electromagnetic spectrum map

Abstract

The invention provides a method for constructing an electromagnetic spectrum map, which comprises the following steps of defining the spatial similarity between any two sensors by using a negative square distance, and updating an attraction degree matrix and an affiliation degree matrix through an iterative process so as to determine the clustering center of the sensors; kriging estimation groupsof different unknown points are established through classes of sensors; calculating an experimental variation function for different Kriging estimation groups, fitting theoretical variation functionsin the different Kriging estimation groups, calculating common Kriging weights of measured values of all sensing points in the Kriging estimation groups, and further calculating common Kriging estimated values; repeating the above steps for many times to estimate the observation value of any position where no sensor is arranged in the area, thereby obtaining the distribution condition of the observation value in the whole area, and achieving the construction of an electromagnetic spectrum map. According to the method, affinity propagation clustering is applied to randomly arranged sensor clustering, so that the electromagnetic spectrum map construction precision and construction efficiency are greatly improved.

Description

technical field

[0001] The present invention relates to the technical field of communication, in particular, to a method for constructing an electromagnetic spectrum map. Background technique

[0002] The electromagnetic spectrum map represents the spatial distribution of electromagnetic spectrum information, including signal power, field strength, and channel gain. Taking into account the differences in the spatial distribution of electromagnetic spectrum resources, compared with traditional spectrum sensing methods, electromagnetic spectrum maps are more conducive to improving the utilization of limited spectrum resources. Therefore, in cognitive radio, electromagnetic spectrum management, signal coverage prediction and smart city and other fields have broad application prospects.

[0003] Due to the influence of various factors such as cost, number of sensors, and deployment locations, only local and scattered electromagnetic spectrum monitoring data can be obtained at t...

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