Hierarchical cooperative combined spectrum sensing algorithm

Abstract

The invention relates to the field of cognitive radio communication and provides a multi-layer distributed combined spectrum sensing algorithm based on a Dirichlet process so as to realize dynamic spectrum sensing. The sensing data acquired by secondary users in a plurality of hierarchical centers is fused to search the optimized sensing information. The automatic data packet is realized by employing the Dirichlet process, a shared hyper-parameter and a corresponding divergent probability in each packet are estimated by a bayesian model, the hyper-parameter is acquired by employing a standard Viterbi algorithm, and the hyper-parameter is compared with a decision threshold value to acquire a final spectrum decision result so as to determine whether a channel is available. Due to the design, the space diversity information of the compressed sensing data is fully considered, and the uncertainty of an individual secondary user on the compressed sensing data is reduced, so that the normalized mean squared error performance is high, the compressed sensing data information in each hierarchical center can be effectively obtained through the algorithm, high accurate detection probability and low false alarm probability are acquired, and the spectrum sensing performance is improved.

Description

technical field [0001] The invention relates to the field of cognitive radio communication, in particular to the realization of spectrum sensing of primary and secondary users. Background technique [0002] With the rapid development of wireless communication technology, spectrum resources are becoming increasingly tight. Traditional wireless networks adopt a fixed spectrum allocation policy, which is regulated and allocated to specific operators and service providers through specialized agencies. However, the results show that the use of this allocation for communication spectrum is very inefficient. The spectrum shortage is largely due to the inefficient fixed spectrum allocation mechanism. Therefore, the researchers proposed cognitive radio technology. The basic idea is: in Under the premise of not causing harmful interference to the primary user PU (Primary User) who owns the spectrum, the secondary user SU (Secondary User) connects to the temporarily idle primary user ...

AI Technical Summary

Problems solved by technology

At present, spectrum sensing needs to face the following main challenges: First, the sampling process must satisfy the Nyquist law in order to recover information correctly at the receiving end, and the current digital-to-analog converter with a limited sampling rate is difficult to implement for high-frequency signals , and the sampling overhead is also very large; secondly, the traditional

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