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Decision-making method of spectrum sensing interval in cognitive radio network

A cognitive radio and spectrum sensing technology, applied in the decision-making field of spectrum sensing interval, can solve the problems of energy consumption, system throughput reduction, and the inability of secondary users to transmit data, and achieve the effect of reducing energy consumption and high throughput.

Inactive Publication Date: 2013-09-25
BEIJING JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In existing research, frequent spectrum sensing will cause a lot of energy consumption
In addition, during the spectrum sensing time, all secondary users cannot perform data transmission, resulting in reduced system throughput

Method used

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  • Decision-making method of spectrum sensing interval in cognitive radio network
  • Decision-making method of spectrum sensing interval in cognitive radio network
  • Decision-making method of spectrum sensing interval in cognitive radio network

Examples

Experimental program
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Embodiment 1

[0018] figure 1 It is a flowchart of a decision method for a spectrum sensing interval in a cognitive radio network provided by Embodiment 1 of the present invention. Such as figure 1 As shown, the method mainly includes the following steps:

[0019] Step 11. Obtain the current spectrum sensing result. If the current spectrum sensing result is spectrum busy, go to step 12; otherwise, go to step 13.

[0020] In the embodiment of the present invention, the current spectrum sensing results include spectrum busy and spectrum idle; the specific spectrum sensing process can be found in figure 2 , mainly including the following steps:

[0021] 1) Establish a spectrum sensing model. In this embodiment, the spectrum sensing process is established as a hidden Markov model;

[0022] where, taking the real state of the spectrum ( figure 2 The channel state q in 1 ,q 2 ,...,q n ) constitutes the hidden state of the hidden Markov model, with X={x 0 ,x 1} represents the hidden s...

Embodiment 2

[0063] In order to facilitate understanding of the present invention, below in conjunction with Figure 3-4 The current spectrum sensing results are further explained as spectrum busy and idle respectively.

example 1

[0065]If the current spectrum sensing result is that the spectrum is busy, and the length of a time slot in the system is 0.0794s, the time required for a secondary user to perform a spectrum sensing is 0.0224s, and the required energy is 10mJ; the spectrum bandwidth is W=10kHz , the path loss constant in the system is κ=1, the path loss exponent is μ=3, and the variance of Gaussian white noise is N 0 =-87dBm, the transmitting power of the secondary user is 10mW, the distance between the transmitting end of the secondary user and the receiving end is 50m, and the distance between the transmitting end of the secondary user and the receiving end of the authorized user is 150m.

[0066] Then calculate according to the method of step 12 among the embodiment one, concrete steps are as follows:

[0067] 1) The secondary user calculates the expected value f of the number of time slots where the spectrum state becomes idle within the spectrum sensing interval O (θ 1 ), where θ 1 =0...

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Abstract

The invention discloses a decision-making method of a spectrum sensing interval in a cognitive radio network. The method comprises the following steps: obtaining a current spectrum sensing result; if the current spectrum sensing result is that a spectrum is busy and the corresponding spectrum sensing interval is theta1, calculating an expected value fT(theta1) of a reduced throughput capacity according to an expected value fO(theta1) of an idle slot time quantity when a spectrum state in the spectrum sensing interval turns to be idle; then calculating sensing energy consumption fE(theta1) of each time slot in average; calculating an optimal spectrum sensing interval according to the calculated fT(theta1) and fE(theta1); if the current spectrum sensing result is that the spectrum is idle and the corresponding spectrum sensing interval is theta0, calculating an expected value gT(theta0) of a reduced throughput capacity and an expected value gI(theta0) of interference suffered by an authorized user according to an expected value gO(theta0) of an idle slot time quantity when a spectrum state in the spectrum sensing interval turns to be busy; then calculating sensing energy consumption gE(theta0) of each time slot in average; and calculating an optimal spectrum sensing interval according to the calculated gE(theta0), gT(theta0) and gI(theta0). With the adoption of the method disclosed by the invention, the energy consumption of the system is reduced and the system throughput capacity is improved.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a decision method for spectrum sensing interval in a cognitive radio network. Background technique [0002] In recent years, the problem of spectrum scarcity in wireless communication networks has become more and more serious. As a practical method, cognitive radio can solve this problem well. Cognitive radio technology allows secondary users to dynamically share spectrum resources of underutilized licensed users in a random manner. [0003] Spectrum sensing technology is an important technology in cognitive radio. Secondary users use spectrum sensing to discover idle spectrum occupied by unlicensed users, so as to realize dynamic spectrum sharing without interfering with authorized users' communication. In slotted systems, existing spectrum sensing methods require secondary users to sense the spectrum status at the beginning of each slot. However, in the existing method...

Claims

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Application Information

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IPC IPC(8): H04W16/14H04B17/00H04B17/382
CPCY02D30/70
Inventor 荆涛邢晓双周洁霍炎
Owner BEIJING JIAOTONG UNIV
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