Multi user cooperative frequency spectrum sensing data fusion method and device

A technology of collaborative spectrum sensing and data fusion, applied in transmission monitoring, electrical components, transmission systems, etc., can solve problems such as noise uncertainty, and achieve the effect of solving the problem of noise uncertainty and achieving excellent spectrum sensing performance.

Inactive Publication Date: 2014-03-26
ZTE CORP
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a data fusion method and device for multi-user cooperative spectrum sensing to at least solve the problem of noise uncertainty in related technologies where multi-user cooperative spectrum sensing is realized based on an energy detection algorithm

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  • Multi user cooperative frequency spectrum sensing data fusion method and device
  • Multi user cooperative frequency spectrum sensing data fusion method and device
  • Multi user cooperative frequency spectrum sensing data fusion method and device

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Experimental program
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Embodiment 1

[0073] Step 1: Send spectrum sensing signaling.

[0074] In this step, the data fusion center notifies the 4 cognitive radio users within its coverage area to participate in spectrum sensing through the control channel (that is, K=4), and the number of antennas of each cognitive radio user is 4 (that is, M 1 =4, M 2 =4, M 3 =4, M 4 =4), the number of local signal samples corresponding to each cognitive radio user is 2160, 1080, 540, 270 (that is, N 1 =2160,N 2 =1080, N 3 =540, N 4 =270).

[0075] Step 2, calculating local spectrum sensing statistics.

[0076] In this step, the four cognitive radio users participating in spectrum sensing perform local spectrum sensing in the sensing time slot, and calculate their respective local spectrum sensing statistics T 1 ,T 2 ,T 3 ,T 4 .

[0077] First, the four cognitive radio users participating in spectrum sensing sample the received signal, and obtain the signal sample vector y corresponding to the four cognitive radio us...

Embodiment 2

[0094] Step 1: Send spectrum sensing signaling.

[0095] In this step, the data fusion center notifies the 4 cognitive radio users within its coverage area to participate in spectrum sensing through the control channel (that is, K=4), and the number of antennas of each cognitive radio user is 8, 6, 4, 2 ( i.e. M 1 =8, M 2 =6, M 3 =4, M 4 =2), the number of local signal samples corresponding to each cognitive radio user is 270 (that is, N 1 =270,N 2 =270,N 3 =270,N 4 =270).

[0096] Step 2, calculating local spectrum sensing statistics.

[0097] In this step, the four cognitive radio users participating in spectrum sensing perform local spectrum sensing in the sensing time slot, and calculate their respective local spectrum sensing statistics T 1 ,T 2 ,T 3 ,T 4 .

[0098] First, the four cognitive radio users participating in spectrum sensing sample the received signal, and obtain the signal sample vector y corresponding to the four cognitive radio users 1 (1),......

Embodiment 3

[0115] Step 1: Send spectrum sensing signaling.

[0116] In this step, the data fusion center notifies the 4 cognitive radio users within its coverage area to participate in spectrum sensing through the control channel (that is, K=4), and the number of antennas of each cognitive radio user is 4 (that is, M 1 =4, M 2 =4, M 3 =4, M 4 =4), the number of local signal samples corresponding to each cognitive radio user is 270 (that is, N 1 =270,N 2 =270, N 3 =270,N 4 =270).

[0117] Step 2, calculating local spectrum sensing statistics.

[0118] In this step, the four cognitive radio users participating in spectrum sensing perform local spectrum sensing in the sensing time slot, and calculate their respective local spectrum sensing statistics T 1 ,T 2 ,T 3 ,T 4 .

[0119] First, the four cognitive radio users participating in spectrum sensing sample the received signal, and obtain the signal sample vector y corresponding to the four cognitive radio users 1 (1),...,y 1 ...

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Abstract

The invention discloses a multi user cooperative frequency spectrum sensing data fusion method and device. The method comprises the steps that a data fusion center receives local frequency spectrum sensing data from a number of cognitive radio users; the local frequency spectrum sensing data comprise local frequency spectrum sensing statistics of the cognitive radio users; the local frequency spectrum sensing statistics are based on generalized likelihood ratio and are the logarithm of the radio of arithmetic mean to geometric mean, wherein the arithmetic mean and the geometric mean are the characteristic values of a sample covariance matrix of signals received by the cognitive radio users; and the data fusion center carries out data fusion on the local frequency spectrum sensing statistics of a number of cognitive radio users according to the local frequency spectrum sensing data. According to the invention, the basis is the generalized likelihood ratio, thus the application performance is not affected by noise uncertainty; and whether the impact of the noise uncertainty is considered or not, in the situation of large reliability difference of local frequency spectrum sensing, a better frequency spectrum sensing performance can be acquired compared with energy detection based on equal gain combination.

Description

technical field [0001] The present invention relates to the communication field, in particular, to a data fusion method and device for multi-user cooperative spectrum sensing. Background technique [0002] Cognitive Radio (CR) technology is proposed to solve the current problem of scarce spectrum resources, and spectrum sensing algorithm is one of the key technologies of cognitive radio. In order to avoid the cognitive radio system from causing harmful interference to licensed users, it is required that the spectrum sensing algorithm can reliably detect the signal of licensed users under low signal-to-noise ratio. [0003] Due to the fading characteristics of the wireless channel, relying only on the single-user spectrum sensing algorithm to detect the usage of the licensed spectrum by the primary user (PU) is not reliable. Research shows that multi-user cooperative spectrum sensing can significantly improve the sensing performance of licensed spectrum. [0004] Existing m...

Claims

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Application Information

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IPC IPC(8): H04B17/00H04W24/02H04B17/309H04B17/382
Inventor 罗军王斌李岩张力任龙涛周栋姜静
Owner ZTE CORP
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