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Undersampled spectrum sensing method based on detection of residual correlation matrix

A correlation matrix and spectrum sensing technology, applied in the fields of undersampling spectrum sensing, undersampling spectrum sensing, broadband spectrum sensing, and spectrum sensing based on residual correlation matrix detection, which can solve the problem of insufficient reconstruction, increase the probability of missed detection, and cannot accurately Obtain the termination conditions of the iterative process and other issues to achieve the effects of reducing the probability of missed detection and false alarm, stabilizing perception performance, and excellent detection performance

Inactive Publication Date: 2019-03-19
XIDIAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the time-varying nature of spectrum usage and the dynamic variation of channel gain, such information (such as the sparsity of received signals or the power of background noise) is difficult to be accurately perceived by cognitive radio users in practical cognitive radio scenarios
Therefore, in the absence of prior knowledge such as background noise or signal power, the termination condition of the iterative process cannot be accurately obtained, which may lead to two types of support set recovery errors: (1) Insufficient reconstruction, that is, reconstructed The support set is only a subset of the true support set; (2) over-recovery, that is, the restored support set exceeds the true support set
These two kinds of errors will have a bad impact on the performance of undersampled spectrum sensing. The former will increase the probability of missed detection, resulting in the failure of the primary user signal to be detected in the wide frequency band, so that the cognitive user performs data transmission on the frequency band occupied by the primary user. , affecting the communication performance of the primary user; and the latter increases the probability of false alarms, which reduces the utilization rate of a large number of frequency bands not occupied by the primary user

Method used

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  • Undersampled spectrum sensing method based on detection of residual correlation matrix
  • Undersampled spectrum sensing method based on detection of residual correlation matrix
  • Undersampled spectrum sensing method based on detection of residual correlation matrix

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Embodiment 1

[0031] In the face of increasingly tight radio spectrum resources, in order to meet the increasing demands of today’s wireless communications and improve spectrum utilization, spectrum sensing is required. The under-sampling spectrum sensing method is applicable to different multi-band signal models, supports rapid signal change detection and hardware implementation Advantages such as simple topology. The traditional under-sampling spectrum sensing method needs to know the spectrum occupancy information or noise power level of the primary user signal as a priori information, and then detect the available free spectrum in the wide band, and monitor the signal activity of the primary user to ensure that the primary user is again When using the spectrum, cognitive users can quickly exit the corresponding frequency band, and maximize the utilization of spectrum resources without interfering with authorized users. However, due to the time-varying characteristics of spectrum usage an...

Embodiment 2

[0047] The under-sampling spectrum sensing method based on residual correlation matrix detection is the same as that in embodiment 1, the detection statistics described in step (6) It can be converted into the ratio of the branch energy of the g-th branch in the τ-th iteration to the branch energy of the h-th branch in the τ-th iteration, expressed as:

[0048]

[0049] among them, Is the branch energy of the g-th branch in the τth iteration, Is the branch energy of the h-th branch in the τth iteration, Y i τ (k),i=1, 2,...,m,k=0,1,...,N-1 is the discrete Fourier transform of the sampled samples of each branch in the τth iteration, and i represents the branch The serial number, k represents the frequency component. The invention converts the derivation of the detection statistics into the branch energy ratio, reduces the calculation cost, and makes the under-sampling spectrum sensing based on multiple cosets more practical.

Embodiment 3

[0051] The under-sampling spectrum sensing method based on residual correlation matrix detection is the same as in embodiment 1-2, and the threshold is determined in step (7) The calculation is: when the primary user signal does not exist, the received signal only contains noise, that is, the input signal x(t)=ω(t), assuming that ω(t) is the mean value is 0, and the variance is Gaussian white noise, its decision threshold The calculation is as follows:

[0052] (7a) Calculate the discrete Fourier transform of the compressed measurement sample Statistical characteristics: When the primary user signal does not exist, the input signal spectrum is 0 with a mean value and a variance Using the mean and variance of the input signal spectrum to calculate the statistical characteristics of the branch sample compression measurement sample frequency spectrum, the discrete random variable of, provides calculation preconditions for calculating the mean value, variance and correlation coeffi...

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Abstract

The invention discloses an undersampled spectrum sensing method based on detection of a residual correlation matrix, and solves the problem the prior art must depends on prior information that is notprone to sense. The scheme of the invention comprises the steps of sampling an input signal; acquiring a measurement matrix A and a residual matrix V; initializing a signal recovery parameter; computing a column index value I<tau> most correlated to the current residual matrix; acquiring a middle residual matrix FORMULA; acquiring a corrected residual matrix V<tau>; acquiring a detection statisticFORMULA; computing a judgment threshold FORMULA; and comparing the detection statistic FORMULA with the judgment threshold FORMULA, to acquire a signal support set. According to the method provided by the invention, the undersampled spectrum sensing is converted into binary judgment, the iterations are controlled via residual detection, the judgment threshold is not affected by noise, the excellent detection performance still can be acquired without the prior knowledge and with the extremely low noise to signal ratio and the relatively low false alarm probability, the number of sampling timesis increased and the detection performance can be significantly improved. The method is practical, low in missing and false alarm probability and low in complexity; and the sensing performance is less affected by the noise power, so as to be relatively stable.

Description

Technical field [0001] The present invention belongs to the field of communication technology, and relates to spectrum sensing technology, and further relates to under-sampling spectrum sensing, specifically an under-sampling spectrum sensing method based on residual correlation matrix detection, which can be used for broadband spectrum sensing in cognitive radio. Background technique [0002] In order to meet the increasing demands of today's wireless communications, broadband spectrum sensing has become an effective method to improve spectrum utilization. However, when performing wideband spectrum sensing in cognitive radio, there are some bottlenecks, such as the scarcity and power consumption of high-sampling rate analog-to-digital converters, the limited size of buffer memory, and the global speed constraints of signal processing. Compressed sensing theory provides a new theoretical basis for solving these problems. With only a few non-adaptive linear measurement sample poin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04B17/382
CPCH04B17/382
Inventor 齐佩汉彭佳蓉李赞严少虎刘仕奇吴晗关磊郝本建石嘉王凡毛维安都毅
Owner XIDIAN UNIV
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