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Broadband spectrum sensing algorithm based on maximum cross-correlation entropy criterion robust sparsity

A wide-band spectrum and cross-correlation technology, applied in the field of robust wide-band spectrum sensing, can solve problems such as difficulties and large amounts of calculations, and achieve the effects of eliminating influence, suppressing non-Gaussian noise, and improving convergence speed and convergence accuracy

Inactive Publication Date: 2019-07-12
XI AN JIAOTONG UNIV
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Problems solved by technology

If the sampling rate of the cognitive radio device is to reach the Nyquist sampling rate for full signal recovery, this requires high sampling equipment and a large amount of calculation, which is very difficult for most cognitive radio applications. difficult

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  • Broadband spectrum sensing algorithm based on maximum cross-correlation entropy criterion robust sparsity
  • Broadband spectrum sensing algorithm based on maximum cross-correlation entropy criterion robust sparsity
  • Broadband spectrum sensing algorithm based on maximum cross-correlation entropy criterion robust sparsity

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Embodiment Construction

[0030] The present invention will be further described below in conjunction with accompanying drawing.

[0031] The robust and sparse broadband spectrum sensing algorithm based on the maximum cross-correlation entropy criterion proposed by the present invention is represented by CIM-MCC. This algorithm is an online sparse estimation algorithm, which can effectively suppress the non-Gaussian noise impact characteristics and obtain robust learning performance. At the same time, the CIM-MCC algorithm introduces a sparse penalty term, which can greatly speed up the convergence speed of the algorithm.

[0032] A robust and sparse broadband spectrum sensing algorithm based on the maximum cross-correlation entropy criterion, the steps are as follows:

[0033] 1) Cognitive users sample at a sub-Nyquist sampling rate to obtain an M-dimensional undersampled signal as Its corresponding N-dimensional full sampling signal is set to Where N>M, the undersampling rate is R sn =M / N. Then...

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Abstract

The invention provides a broadband spectrum sensing algorithm based on a maximum cross-correlation entropy criterion robust sparsity, and solves the problem of broadband spectrum sensing in a non-Gaussian noise environment. According to the method, on one hand, the non-Gaussian noise is suppressed by using the robustness of the Maximum Correntropy Criterion (MCC), so that the adverse effect of thenon-Gaussian noise on the spectrum sensing algorithm is solved; on the other hand, Correntropy Induced Metric (CIM) is introduced to serve as a sparse penalty term of broadband spectrum estimation, sparse estimation is carried out through the sparsity of a spectrum, and the estimation speed of a spectrum vector is increased.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to a robust broadband spectrum sensing method. Background technique [0002] In order to make good use of wireless spectrum resources reasonably and effectively, governments of various countries currently adopt a fixed spectrum allocation strategy, that is, the wireless spectrum is divided into non-overlapping frequency bands according to frequency, and then one or several specific frequency bands are allocated to different services or system. In general, all wireless spectrum is divided into licensed spectrum and unlicensed spectrum. Authorized spectrum is the wireless spectrum authorized by the country for specific services or systems. It is used by specific systems and cannot be used by other non-authorized systems. Any unauthorized use is illegal and will be investigated for legal responsibility. A system user who is authorized to use the licensed spectrum is called an au...

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Application Information

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IPC IPC(8): H04B17/30H04B17/382
CPCH04B17/30H04B17/382
Inventor 曲桦徐西光赵季红闫飞宇
Owner XI AN JIAOTONG UNIV
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