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Clustering cooperative spectrum sensing method and system based on dual-threshold energy detection

A technology of cooperative spectrum sensing and energy detection, which is applied in the field of clustering cooperative spectrum sensing methods and systems, and can solve problems such as poor detection performance, decreased detection performance, and large amount of information

Inactive Publication Date: 2013-11-27
PETROCHINA CO LTD +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the cooperative spectrum sensing technology, the clustering algorithm can solve the problem of detection performance degradation when the channel is fading, and can significantly improve the detection probability. The current clustering algorithm mainly uses single-threshold energy detection in the cluster. Single-threshold energy detection is simple and easy, but its detection performance is poor
Compared with single-threshold detection, double-threshold detection can improve the detection probability very well, but in the process of double-threshold detection, the amount of information to be transmitted is large, and the control channel occupied is relatively wide.

Method used

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  • Clustering cooperative spectrum sensing method and system based on dual-threshold energy detection
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  • Clustering cooperative spectrum sensing method and system based on dual-threshold energy detection

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Experimental program
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Effect test

Embodiment 1

[0094] The flowchart of the spectrum sensing method provided by the present invention is as follows image 3 As shown, the specific analysis is:

[0095] Step 101) Divide all sensing users in the sensing network into several clusters, and select the cluster head of each cluster, specifically:

[0096] When the channel between the perceived user and the fusion center is a fading channel, such as figure 2 As shown, several users with better channels to the fusion center can be selected as cluster head users, and the cluster head users will send the collaborative sensing results in the cluster to the data fusion center, which not only ensures the accuracy of information transmission, but also can Save the bandwidth of the sending channel.

[0097] The following clustering algorithm is based on the description of clustering and cluster head selection:

[0098] In order to describe the algorithm conveniently, define |k 1 -k 2 | for user k 1 and k 2 The Euclidean distance be...

Embodiment 2

[0169] In this embodiment, the clustering, the selection of cluster heads, and the cluster head’s spectrum occupancy scheme based on the detection information reported by the sensing users are the same as in Embodiment 1, but in this embodiment, not all sensing users in each cluster perceive the spectrum Usage. Such as Figure 4 Shown, improved step 102) further comprises:

[0170] Step 102-1) Select the number of sensing users participating in cooperation and sensing spectrum occupancy in each cluster, and optimize the cooperative detection probability based on dual-threshold energy detection of a cluster;

[0171] Step 102-2) Each cluster selects a corresponding number of sensing users according to the number of selected sensing users, and the selected sensing users send their local decision results or sensing information to the cluster head.

[0172] Step 102-1) in the above two steps is described in detail as follows: for optimizing the number of users participating in c...

Embodiment 3

[0191] Assuming that there is only one AU and one data fusion center in the spectrum detection area, and there are D sensing users in each cluster in the clustering network, and the noise and signal power of each sensing user are the same, the expected false alarm probability in a cluster is set as P F = 0.1.

[0192] Image 6 It is assumed that when the number of sensing users in a cluster in the network is 50, 100, and 150, the relationship between the detection probability and the number of users participating in the collaboration is shown in the figure below. It can be seen from the figure that as long as the total number of perceived users D in a cluster is known, an X can be found. 0 value such that P D The largest, and satisfy the condition 1≤X 0 ≤N. this x 0 The value is the optimal number of users participating in collaboration in a cluster.

[0193] Figure 7 Finding X is based on D=50 0 value, each "o" in the figure represents the calculated detection proba...

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Abstract

The invention provides a clustering cooperative spectrum sensing method and system based on dual-threshold energy detection. The method comprises the steps: (101), dividing all sensing users in a sensing network into a plurality of clusters, and selecting a cluster head of each cluster; (102), sensing the local spectrum occupation situation by the sensing users distributed in each cluster locally in the mode of adopting the dual-threshold energy detection, and obtaining detection information; (103) fusing the detection information reported by the sensing users inside each cluster by the cluster head, and making a judgment on the sensing result of each cluster by the cluster head; (104), sending the judged sensing result to a data fusion center by each cluster head, and making a final judgment on the spectrum occupation situation by the data fusion center, wherein the step (102) further comprises the steps of (102-1) determining the number of the sensing users who participate in the cooperation and sense the spectrum occupation situation in each cluster; (102-2) selecting the sensing users corresponding to the number according to the determined number of the users who participate in the cooperation and sensing by each cluster, and sending the local judgment result or sensing information to the cluster head by each cluster.

Description

technical field [0001] The present invention relates to the field of cognitive radio technology, in particular to a method and system for clustering cooperative spectrum sensing based on dual-threshold energy detection. Background technique [0002] Spectrum sensing is one of the key technologies in cognitive radio. Spectrum sensing technologies are divided into single-node sensing and cooperative sensing. In the cooperative spectrum sensing technology, the clustering algorithm can solve the problem of detection performance degradation when the channel is fading, and can significantly improve the detection probability. The current clustering algorithm mainly uses single-threshold energy detection in the cluster. Single-threshold energy detection is simple and easy, but its detection performance is poor. Compared with single-threshold detection, double-threshold detection can improve the detection probability very well, but in the process of double-threshold detection, the a...

Claims

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Application Information

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IPC IPC(8): H04W16/14
Inventor 王树彬刘慧琴刘散日那王洪月
Owner PETROCHINA CO LTD
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