Cooperative sensing method for global frequency spectrum information of wireless cognitive network

Abstract

The invention discloses a cooperative sensing method for global frequency spectrum information of a wireless cognitive network. The method comprises the steps: quickly solving a probability density function approximate value of global power spectrum model coefficient vector of a main user signal in a specific no-shadow attenuation region through an iterative algorithm based on the variational Bayesian inference technology; obtaining the optimal values of three types information (position coordinates, occupied frequency bands and signal power of all occupied frequency bands) of each main user transmitter according to the maximum posterior probability rule, thereby obtaining a global frequency spectrum distribution diagram of the specific region, obtaining multi-dimensional information (time, space and frequency spectrum) of the frequency spectrum, and achieving the high-efficiency multiplexing of spare frequency spectrum from a user network.

Description

technical field [0001] The invention belongs to the field of wireless communication, and in particular relates to a cooperative sensing method for global spectrum information in a wireless cognitive network. Background technique [0002] With the rapid development and wide application of wireless communication technology, limited spectrum and inefficient and rigid spectrum allocation strategies make wireless spectrum resources increasingly scarce. In a certain area, a cognitive radio (Cognitive Radio, CR) technology that dynamically uses vacant licensed frequency bands is proposed to solve the above problems. It reduces or avoids the interference between the master-slave network, improves the overall capacity of the master-slave network, and greatly improves the utilization efficiency of existing spectrum resources, and has become one of the key technologies of the next generation wireless communication system. [0003] At present, the existing cooperative sensing technolog...

AI Technical Summary

Problems solved by technology

However, the cooperative sensing method based on the Lasso algorithm is a point estimation method, which can only give the optimal value of signal power at the position, frequency band and each occupied frequency point of the primary user transmitter, but cannot obtain the corresponding posteriori Probability density function

Moreover, the collaborative sensing method based on the Lasso algorithm will also be affected by local shallow minimum values ​​in practical applications, and often cannot obtain the true optimal value.

In addition, the wireless cognitive network needs to determine the position and frequency band of the primary user transmitter as quickly as possible, while the cooperative sensing method based on the Lasso algorithm requires additional calculation of the regularization factor, which affects its calculation speed

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