KR101850621B1 - Cooperative spectrum sensing method and the apparatus - Google Patents

Abstract

Disclosed are a cooperative spectrum sensing method and a device thereof. The method of sensing a cooperative spectrum in a fusion center connected with N (natural number) sensor nodes includes: a step (a) of obtaining sensing channel information and a signal-to-noise ratio for a wireless feedback channel from each of the sensor nodes; a step (b) of calculating a local threshold value reflecting a channel environment by using the sensing channel information and the signal-to-noise ratio in order to transmit the value to each of the sensor nodes; a step (c) of receiving a sensing result, according to a spectrum sensing of a primary user (PU) using the local threshold value, from each of the sensor nodes; and a step (d) of lastly determining whether to use a frequency band of the PU by collecting the sensing result of each of the sensor nodes. As such, the present invention is capable of maximizing detection probability or minimizing false alarm and non-detection probability in cooperative spectrum sensing.

Description

[0001] The present invention relates to a cooperative spectrum sensing method,

The present invention relates to a cooperative spectrum sensing method and apparatus.

In the conventional cooperative spectrum sensing, a fusion rule has been developed in the direction of maximizing the detection probability or minimizing the probability of detection and non-detection probability. At the beginning of the research, a study was made on a perfect feedback channel that regards the channel between the sensor node and the fusion center as a noiseless channel. The most common convergence rules are Likelihood Ratio Test (LRT), Chair-Varshney (CV), Maximum Ratio Combining (MRC) and Equal Gain Combining (EGC).

For example, in case of spectrum sensing at each sensor node and using LRT convergence rules in fusion center, the optimal channel parameters are obtained by using the sensor signal to noise ratio (SNR), feedback channel SNR, threshold at each sensor node, Lt; RTI ID = 0.0 > a < / RTI > Using this information, optimal parameters to be used in sensor nodes and convergence centers are obtained.

However, in the conventional cooperative spectrum sensing, a proposal or a performance analysis for a new fusion rule is mostly performed for a SNR of a given sensing channel and a feedback channel.

In other words, various convergence rules have been proposed, but there is insufficient study on the operation method that can be used in real environment.

The present invention provides a cooperative spectrum sensing method and apparatus capable of minimizing the detection probability of cooperative spectrum sensing or minimizing the probability of non-detection and the probability of non-detection.

According to an aspect of the present invention, there is provided a cooperative spectrum sensing method capable of minimizing the detection probability of cooperative spectrum sensing or minimizing the probability of non-detection and the probability of non-detection.

According to an embodiment of the present invention, a cooperative spectrum sensing method in a fusion center connected to N (natural number) sensor nodes comprises the steps of: (a) acquiring a sensing channel information from each sensor node and a signal- ; (b) obtaining a local threshold reflecting the channel environment using the sensing channel information and the SNR, and transmitting the local threshold to each sensor node; (c) receiving sensing results according to spectral sensing of a primary user (PU) using the local threshold from each of the sensor nodes; And (d) collecting the sensing results of the sensor nodes and finally determining whether the PU uses the frequency band.

The sensing channel information is at least one of a signal-to-noise ratio and a noise variance for a sensing channel between each sensor node and the PU.

The sensing result is a result of the quantization using the local threshold after each sensor node performs spectrum sensing on the PU.

The quantization is quantized to the L-level and quantized to the real value.

In the step (b), at least one of the global threshold value and the quantization level may be further obtained.

In the step (b), an error alarm probability according to the global threshold value and the quantization level is minimized using the sensing channel information and the SNR, and the detection probability according to the global threshold value and the quantization level is maximized At least one of the local threshold, the global threshold, and the quantization level may be calculated to satisfy an objective function.

The objective function is defined by the following equation,

는 L-레벨 양자화 기반의 검출 확률을 나타내며,

는 전역 문턱치를 나타내고,

는 L-레벨 양자화 기반의 오보 경보 확률을 나타내며,

는 오보 경보 확률의 상한(upper bound)을 나타낸다. here,

Represents the detection probability of the L-level quantization-based detection,

Represents a global threshold value,

Indicates an error alarm probability based on L-level quantization,

Represents the upper bound of the false alarm probability.

The step (d) may include: calculating a determination statistic value according to a fusion rule using sensing results of the sensor nodes; And comparing the judgment statistic value with the global threshold value to determine whether the PU uses the frequency band.

According to another embodiment of the present invention, there is provided a cooperative spectrum sensing method in a fusion center connected to N (natural number) sensor nodes, comprising: (a) acquiring a sensing channel information from each sensor node and a signal- ; (b) reading the local threshold value corresponding to the sensing channel information and the signal-to-noise ratio from the optimization parameter look-up table and transmitting the same to each sensor node; (c) receiving sensing results according to spectral sensing of a primary user (PU) using the local threshold from each of the sensor nodes; And (d) collecting the sensing results of the sensor nodes and finally determining whether the PU uses the frequency band.

According to another aspect of the present invention, there is provided an apparatus capable of minimizing the detection probability of cooperative spectrum sensing or minimizing the probability of false detection and the probability of non-detection.

According to an embodiment of the present invention, a fusion center for cooperative spectrum sensing, comprising: a communication unit for acquiring sensing channel information and a signal-to-noise ratio for a wireless feedback channel from each sensor node; A calculation unit for deriving a local threshold value of each sensor node using the sensing channel information and the SNR; And an analyzing unit for collecting, from each of the sensor nodes, a sensing result according to spectrum sensing of a primary user (PU) using a local threshold transmitted to each sensor through the communication unit, and finally determining whether the PU uses a frequency band A fusion center can be provided.

According to another embodiment of the present invention, there is provided a fusion center for cooperative spectrum sensing, comprising: a communication unit for obtaining sensing channel information and a signal-to-noise ratio for a wireless feedback channel from each sensor node; A memory for storing an optimization parameter look-up table; A processor for reading out the obtained sensing channel information and a local threshold corresponding to the S / N ratio from the optimization parameter look-up table and transmitting the same to each sensor node through the communication unit; And an analysis unit for collecting a sensing result according to spectrum sensing of a primary user (PU) using the local threshold value from each of the sensor nodes, and finally determining whether or not to use the frequency band of the PU.

By providing the cooperative spectrum sensing method and apparatus according to an embodiment of the present invention, when information on each channel is obtained and cooperative spectrum sensing is performed based on the information on each channel, optimum parameters capable of having the maximum detection probability can be obtained , And cooperative spectrum sensing is performed by using the cooperative spectrum sensing. Thus, a high detection probability can be secured according to the channel environment change.

1 schematically illustrates a system configuration for cooperative spectrum sensing according to an embodiment of the present invention;
2 is a flow chart illustrating a cooperative spectrum sensing method according to an embodiment of the present invention;
3 is a flow chart illustrating a cooperative spectrum sensing method according to another embodiment of the present invention.
4 is a diagram illustrating a maximum detection probability according to a quantization level according to an embodiment of the present invention.
FIGS. 5 and 6 are graphs comparing performance according to the fusion rule of the present invention.
FIG. 7 and FIG. 8 are graphs showing a difference in detection probability and a difference in false alarm probability when the sensing channel SNR is wrongly estimated in the cooperative spectrum sensing according to an embodiment of the present invention.
9 and 10 are graphs showing differences in detection probability and false alarm probability when the feedback channel SNR is erroneously estimated in the cooperative spectrum sensing according to an embodiment of the present invention.
11 is a graph showing convergence rates of convergence rules in the optimization process in the cooperative spectrum sensing according to an embodiment of the present invention.
12 is a block diagram schematically illustrating an internal configuration of a fusion center according to an embodiment of the present invention;

As used herein, the singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. In this specification, the terms "comprising ", or" comprising "and the like should not be construed as necessarily including the various elements or steps described in the specification, Or may be further comprised of additional components or steps. Also, the terms "part," " module, "and the like described in the specification mean units for processing at least one function or operation, which may be implemented in hardware or software or a combination of hardware and software .

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a diagram schematically showing a system configuration for cooperative spectrum sensing according to an embodiment of the present invention. Referring to FIG.

Referring to FIG. 1, a system for cooperative spectrum sensing according to an exemplary embodiment of the present invention includes a PU 110, at least one sensor node 120, and a fusion center 130.

Hereinafter, the PU, the sensor node, and the fusion center will be referred to as an electronic device having at least one of a communication function, a memory and a processor in order to facilitate understanding and explanation.

That is, the PU and the sensor node may be a terminal having a communication function, and the fusion center may be a server. Hereinafter, although they are referred to as a PU, a sensor node, and a convergence center, it should be understood that this should be extended to a terminal or a server.

The PU 110 represents a primary user. The PU 110 should be understood as a user equipment that is allocated a channel.

Accordingly, the PU 110 may have priority over the target channel or frequency band that the sensor node 120 desires to use. That is, the PU 110 can use a destination channel to which the PU 110 has priority at any time.

The sensor node 120 is a device that desires to use the target channel (frequency band) of the PU 110. Here, the sensor node 120 is a device that is not allocated a channel, unlike the PU 110. That is, the sensor node 120 may utilize the frequency band of the PU according to whether the frequency of the PU 110 is used or not. That is, the sensor node 120 can use the target channel only when the PU 110 does not use the target channel (frequency band).

The sensor node 120 according to an exemplary embodiment of the present invention is a cooperative spectrum sensor node that performs spectrum sensing on a frequency used by the PU 110 and transmits a determination result to a convergence center 130 through a wireless channel do. Here, the plurality of sensor nodes 120 can cooperatively sense the PU 110 at the same time.

The plurality of sensor nodes 120 according to an exemplary embodiment of the present invention performs cooperative spectrum sensing based on L-level quantization. For the L-level quantization-based cooperative spectral sensing, (L-1) local thresholds are required at each sensor node 120.

As a result, the local threshold value is applied to each sensor node 120 differently, and each sensor node 120 performs quantization using the local threshold value and transmits the L-level symbol corresponding to the result to the fusion center 130 have.

Accordingly, the fusion center 130 can collect the L-level symbols from each sensor node 120 and compare the L-level symbols with the global threshold values to make a final determination as to whether or not the PU 110 uses the frequency. This will be described in more detail below.

2 is a flowchart illustrating a cooperative spectrum sensing method according to an embodiment of the present invention.

In step 210, each sensor node 120 transmits a sensing request signal to the convergence center 130. At this time, each sensor node 120 may transmit a sensing request signal to the fusion center 130 using the SRS signal.

Each sensor node 120 can measure the SNR and noise variance of the sensing channel between the sensor node 120 and the PU 110 periodically or non-periodically, and then store the measured SNR and noise variance.

When there is a request for use of the frequency spectrum by any one of the plurality of sensor nodes, each sensor node 120 may transmit a sensing request signal to the convergence center 130 using the SRS signal.

When each sensor node 120 transmits the sensing request signal to the convergence center 130 using the SRS signal, information about the sensing channel (hereinafter, referred to as sensing channel information) may be transmitted together. Here, the sensing channel information may be at least one of an SNR and a noise variance for a sensing channel.

Of course, it is natural that each sensor node 120 may transmit sensing channel information to the fusion center 130 separately from the SRS signal.

In step 215, the fusion center 130 obtains the SNR and the sensing channel information for the feedback channel according to the sensing request signal of each sensor node 120. Here, the feedback channel refers to a wireless channel between each sensor node 120 and the fusion center 130.

Next, in step 220, the fusion center 130 derives an optimal parameter according to the fusion rule using the SNR and the sensing channel information for the obtained feedback channel. Here, the parameter may be at least one of a local threshold, a quantization level, and a global threshold.

For example, the convergence center 130 minimizes the false alarm probability based on the global threshold value and the quantization level using the sensing channel information and the SNR, adjusts the objective probability to maximize the detection probability according to the global threshold value and the quantization level, Can be derived.

This will be more clearly understood from the following description.

Cooperative spectrum sensing according to an embodiment of the present invention is cooperative spectrum sensing based on L-level quantization as described above.

The decision statistics of the L-level quantization-based fusion rule can be calculated using Equation (1).

는 센서 노드 i로부터 수신한 센싱 결과를 양자화 레벨 각 구간에 매핑하여 얻은 값이다.Here, i represents an index of each sensor node,

Is a value obtained by mapping the sensing result received from the sensor node i to each section of the quantization level.

)은 실수일 수 있다.Here, each quantization level interval (

) May be a real number.

)를 이용하여 PU의 주파수 대역 사용 유무에 대한 최종 판단을 수행할 수 있다. The convergence center 130 according to an embodiment of the present invention maps the sensing results received from the N sensor nodes to the quantization level sections and then outputs the determination statistics values and the global threshold values (

) Can be used to make a final decision as to whether the PU uses the frequency band.

), 전역 문턱치를 결정하기 위해, 융합 규칙의 검출 확률을 유도하면 수학식 2와 같다.(L-1) local threshold values to be used by each sensor node and a quantization level interval

), The probability of detection of the fusion rule is derived to determine the global threshold, as shown in Equation (2).

는 융합 센터에서 센서 노드로부터 수신한 센싱 결과를 매핑한 결과가 j번째 양자화 구간으로 판단된 총 수를 나타낸다. here,

Represents the total number of j-th quantization intervals obtained by mapping the sensing result received from the sensor node in the fusion center.

을 만족한다. therefore,

.

과

가 주어진 경우,

는

과

을 만족하는 모든

벡터의 집합을 나타낸다.

and

Lt; / RTI >

The

and

All that satisfy

Represents a set of vectors.

은

을 i번째 센서 노드와 융합 센터 사이의 무선 피드백 채널의 SNR(

)에 대해 평균을 취한 결과를 나타낸다. Also,

silver

(SNR) of the wireless feedback channel between the i-th sensor node and the fusion center

). The results are shown in FIG.

이다.Also,

to be.

라 가정하고,

이고,

라고 가정할 때,

을 나타낸다. The local threshold used by each sensor node is

However,

ego,

Assuming that,

.

는 i번째 센서에서 스펙트럼 센싱한 결과를 나타내고,

는 PU의 신호가 있을 때를 나타낸다.

Represents the result of spectral sensing at the i-th sensor,

Indicates when there is a signal of the PU.

는 피드백 채널 SNR (

)이 주어진 경우, 심볼 오류 확률을 나타내며,

은 피드백 채널 SNR(

)이 주어진 경우, 센서 노드에서

심볼을 전송하였으나, 융합 센터에서 매핑한 결과

일 확률을 나타낸다.

Lt; RTI ID = 0.0 > SNR (

) Is given, it represents the symbol error probability,

Lt; RTI ID = 0.0 > SNR (

) Is given, the sensor node

Symbol, but the mapping result from the fusion center

Probability.

(PU 신호가 없을 때) PU 신호가 있다고 오판하는 결과로 수학식 3과 같이 나타낼 수 있다.By deriving the probability of false alarms in a similar way,

(When there is no PU signal), it can be expressed as Equation 3 as a result of misjudging that there is a PU signal.

이고,

이며,

는 피드백 채널 SNR(

)에 대하여

의 평균을 취한 결과를 나타낸다. here,

ego,

Lt;

Lt; RTI ID = 0.0 > SNR (

)about

Of the average value.

), 양자화 레벨 구간(

) 및 전역 문턱치를 구할 수 있다.Optimization is performed under the NP criterion using the detection probability formula and the false alarm probability formula (i.e., Equations 2 and 3) to obtain (L-1) local threshold values

), A quantization level interval (

) And the global threshold value.

This objective function can be expressed by Equation (4).

이고,

이다. here,

ego,

to be.

는 오보 경보 확률의 상한값(upper bound)를 나타낸다. 센싱 채널 정보(예를 들어, 센싱 채널의 SNR)이 주어진 경우 로컬 문턱치(

)는

의 함수 관계로 나타낼 수 있으므로, 목적함수 식과 같이 나타낼 수 있다.

Represents the upper bound of the false alarm probability. Given the sensing channel information (e.g., the SNR of the sensing channel), the local threshold

)

And can be expressed as an objective function expression.

Accordingly, when the SNR of the sensing channel and the SNR of the feedback channel are given, it is possible to derive an optimal parameter (local threshold, quantization level section, global threshold) satisfying the objective function of Equation (4).

In step 225, the fusion center 130 transmits a local threshold to each sensor node.

In step 230, each sensor node 120 performs spectral sensing for the PU, performs quantization using the local threshold value, and transmits the result (i.e., sensing result) to the fusion center 130.

In step 235, the fusion center 130 compares the sensing results received from the sensor nodes 120 and derives a determination statistic value according to the fusion rule.

Since the method of deriving the judgment statistic value according to the fusion rule is the same as that described above, a duplicate explanation will be omitted.

In step 240, the fusion center 130 makes a final decision as to whether or not to use the frequency band of the PU using the derived decision statistics and the global threshold. The convergence center 130 can transmit the final determination result to each sensor node, and thus the spectrum use of each sensor node can be determined.

) PU가 주파수 대역을 사용하는 것으로 판단할 수 있다.For example, if the judgment statistic value derived in accordance with the fusion rule is greater than the global threshold value (

) It can be judged that the PU uses the frequency band.

) PU가 주파수 대역을 사용하지 않는 것으로 판단할 수 있다. On the other hand, if the judgment statistic value derived according to the fusion rule is smaller than the global threshold value

) It can be determined that the PU does not use the frequency band.

Referring to FIG. 2, an optimal parameter (at least one of a local threshold, a quantization level, and a global threshold) according to a fusion rule is derived using SNRs for a sensing channel and a feedback channel in real time, and cooperative spectrum sensing is performed based thereon . As described above, by using the SNR for the sensing channel and the feedback channel in real time, optimal parameters according to the convergence rule are derived and the cooperative spectrum sensing is performed, thereby providing a high detection probability according to the channel environment change.

3 is a flowchart illustrating a cooperative spectrum sensing method according to another embodiment of the present invention.

In step 310, the fusion center 130 derives optimal parameters according to the fusion rule using the sensing channel information of the sensing channel and the SNRs of the feedback channel, respectively, and stores them in the optimization parameter look-up table.

That is, the convergence center 130 derives optimal parameters for each of the sensing channel information and the feedback channel in advance, and then, when there is a request for spectrum use by the sensor node, the fusion center 130 obtains information (for example, , A local threshold, a global threshold, and a quantization level) can be read and utilized.

That is, each sensing channel information and optimum parameters for the SNR of each feedback channel may be derived before the spectrum use request, and then stored in a table form, and the required information may be read and utilized.

The method for deriving the optimal parameters using the sensing channel information and the SNR of the feedback channel is the same as that described with reference to FIG. 2, so that redundant description is omitted.

In step 315, each sensor node 120 transmits a sensing request signal to the fusion center 130.

Accordingly, in step 320, the fusion center 130 obtains the SNR and the sensing channel information of the feedback channel of each sensor node 120, respectively.

In step 325, the fusion center 130 reads the SNR of the feedback channel and the parameters corresponding to the sensing channel information in the optimization parameter look-up table. Here, the parameter may be at least one of a local threshold, a global threshold, and a quantization level, as described above.

In step 330, the fusion center 130 transmits a local threshold among the read parameters to each sensor node 120.

In step 335, each sensor node 120 performs spectral sensing for the PU, performs quantization using the local threshold, and transmits the result (i.e., sensing result) to the fusion center 130.

In step 340, the fusion center 130 compares the sensing results received from the sensor nodes 120 and derives a determination statistic value according to the fusion rule.

Since the method of deriving the judgment statistic value according to the fusion rule is the same as that described above, a duplicate explanation will be omitted.

In step 345, the fusion center 130 makes a final decision as to whether or not to use the frequency band of the PU using the derived decision statistics and the global threshold.

에 상관없이 4 레벨 양자화 기반의 협력 스펙트럼 센싱의 최대 검출 성능이 나머지 레벨의 양자화 기반의 협력 스펙트럼 센싱의 성능과 같거나 뛰어난 것을 알 수 있다.4 is a diagram illustrating a maximum detection probability according to a quantization level according to an embodiment of the present invention. Referring to Figure 4,

It can be seen that the maximum detection performance of the cooperative spectrum sensing based on the 4-level quantization is equal to or superior to the performance of the cooperative spectrum sensing based on the quantization based on the remaining levels.

5 and 6 are graphs comparing performance according to the fusion rule of the present invention.

As shown in FIGS. 5 and 6, regardless of the number of sensor nodes, the performance of the fusion rule of the present invention is the same as that of the CV fusion rule, and the performance is superior to that of the remaining fusion rules except LRT.

However, in the case of LRT and CV, probability distribution according to the quantization level and local threshold value is required in the fusion fitter due to the nature of the fusion rule. This is a disadvantage in that there is a disadvantage that additional information must be transmitted from the sensor node in order to know the sensor node information at the fusion center.

On the other hand, the convergence rule according to the embodiment of the present invention shows that the detection performance is as good as that of CV, even though there is no additional information amount required in the fusion center.

FIGS. 7 and 8 are graphs showing differences in detection probability and false alarm probability when the sensing channel SNR is erroneously estimated in the cooperative spectrum sensing according to an embodiment of the present invention.

As shown in FIGS. 7 and 8, the fusion rules according to an embodiment of the present invention are very insensitive to the SNR errors of the sensing channel, but are sensitive to the LRT and CV fusion rules.

9 and 10 are graphs showing differences in detection probability and false alarm probability when the feedback channel SNR is erroneously estimated in the cooperative spectrum sensing according to an embodiment of the present invention.

It can be seen that the LRT fusion rules operate more dull than the fusion rules and CV fusion rules of the present invention. The actual optimization is performed in the fusion center, and the fusion center can reduce the error by measuring the SNR of the feedback channel using the SRS signal. However, in the case of the sensing channel SNR, a value measured at the sensor node is received through the wireless channel, and the error may be large.

Thus, it can be seen that the convergence rule of the present invention, which operates more insensitively to the sensing channel SNR error, is a more realistic technique.

FIG. 11 is a graph illustrating a convergence rate of convergence rules in the optimization process in the cooperative spectrum sensing according to an embodiment of the present invention.

In the conventional and the cooperative spectrum sensing of the present invention, optimization problem is solved by using DE (differential evolution) fusion rule. DE is an optimization problem solving method that converges to an optimal value through iterative decoding as the evolutionary algorithm changes into an excellent factor through gene transformation.

When DE is used to find the optimal parameters of each fusion rule, it can be seen that the convergence speed of the conventional and the convergence rules of the present invention are all similar.

FIG. 12 is a block diagram schematically illustrating an internal configuration of a fusion center according to an embodiment of the present invention.

12, a fusion center 130 according to an embodiment of the present invention includes a communication unit 1210, a calculation unit 1215, an analysis unit 1220, a memory 1225, and a processor 1230, do.

The communication unit 1210 is a means for transmitting and receiving data with another device.

For example, the communication unit 1210 may receive at least one of an SRS signal and sensing channel information from each sensor node 120 through a feedback channel. In addition, the communication unit 1210 may transmit a local threshold to each sensor node under the control of the processor 1230. [

The calculation unit 1215 calculates a parameter according to the fusion rule using the sensing channel information and the SNR of the feedback channel. The SNR of the feedback channel can be measured according to the reception of the SRS signal. Further, the parameter may be at least one of a local threshold, a global threshold, and a quantization level, as described above.

The analysis unit 1220 is a means for determining whether or not to use the frequency band of the PU that has collected the sensing result according to the spectrum sensing of the PU (primary user) using the local threshold transmitted to each sensor node from each sensor node.

The method of determining whether to use the frequency band of the PU by using the sensing result collected from each sensor node is the same as that described with reference to FIG. 2 and FIG. 3, and thus a duplicate description will be omitted.

The memory 1225 is a means for storing various algorithms necessary for performing cooperative spectrum sensing according to an embodiment of the present invention, various data derived from the process, and the like.

The processor 1230 may include internal components (e.g., a communication unit 1210, a computing unit 1215, an analysis unit 1220, a memory 1225, etc.) of the fusion center 130 according to an embodiment of the present invention. ).

In FIG. 12, the cooperative spectrum sensing is performed by optimizing according to the convergence rule according to the real-time channel environment (i.e., deriving an optimal parameter).

However, in another embodiment, after optimizing each sensing channel information and SNR of each feedback channel (i.e., deriving an optimal parameter), it is stored in a table (optimum parameter look-up table) , Sensing channel information and SNR of the feedback channel), and then performs cooperative spectrum sensing using the extracted parameters. This is the same as that described with reference to FIG. 3, so duplicate descriptions will be omitted. However, if the optimum parameters according to the SNRs of the feedback channels are derived and stored in the table in advance, the processor 1230 calculates the optimal channel parameters corresponding to the actual channel environments (sensing channel information and feedback channel) After the parameters are extracted from the table, it is possible to control the local threshold value to be transmitted to each sensor node through the communication unit.

On the other hand, the components of the above-described embodiment can be easily grasped from a process viewpoint. That is, each component can be identified as a respective process. Further, the process of the above-described embodiment can be easily grasped from the viewpoint of the components of the apparatus.

In addition, the above-described technical features may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the medium may be those specially designed and constructed for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware device may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

It will be apparent to those skilled in the art that various modifications, additions and substitutions are possible, without departing from the spirit and scope of the invention as defined by the appended claims. Should be regarded as belonging to the following claims.

110: PU
115: sensor node
120: Convergence Center
1210:
1215:
1220:
1225: Memory
1230: Processor

Claims (12)

A cooperative spectrum sensing method in a fusion center connected to N (natural number) sensor nodes,
(a) obtaining sensing channel information and a signal-to-noise ratio for a wireless feedback channel from each sensor node;
(b) obtaining a local threshold reflecting the channel environment using the sensing channel information and the SNR, and transmitting the local threshold to each sensor node;
(c) receiving sensing results according to spectral sensing of a primary user (PU) using the local threshold from each of the sensor nodes; And
(d) collecting the sensing results of the sensor nodes, and finally determining whether the PU uses the frequency band,
As a result of the sensing,
Wherein each sensor node performs spectral sensing for the PU and quantizes the local threshold using the local threshold.
The method according to claim 1,
Wherein the sensing channel information is at least one of a signal-to-noise ratio and a noise variance for a sensing channel between each sensor node and the PU.
delete The method of claim 1, wherein the quantization is quantized to an L-level,
And the quantized values are real-valued.
The method of claim 1, wherein, in step (b)
Wherein at least one of a global threshold and a quantization level is further obtained.
6. The method of claim 5, wherein, in step (b)
Wherein the probability of false alarm based on the global threshold value and the quantization level is minimized by using the sensing channel information and the SNR, and the local threshold and the detection probability according to the quantization level are maximized, Wherein the at least one of the threshold, the global threshold, and the quantization level is calculated.
The method according to claim 6,
Wherein the objective function is defined by the following equation.

here,

Represents the detection probability of the L-level quantization-based detection,

Represents a global threshold value, Indicates an error alarm probability based on L-level quantization,

Is indicative of an upper bound of the false alarm probability.
6. The method of claim 5, wherein step (d)
Calculating a determination statistic value according to a fusion rule using a sensing result of each sensor node; And
And comparing the determination statistic value with the global threshold value to determine whether the PU uses the frequency band.
A cooperative spectrum sensing method in a fusion center connected to N (natural number) sensor nodes,
(a) obtaining sensing channel information and a signal-to-noise ratio for a wireless feedback channel from each sensor node;
(b) reading the local threshold value corresponding to the sensing channel information and the signal-to-noise ratio from the optimization parameter look-up table and transmitting the same to each sensor node;
(c) receiving sensing results according to spectral sensing of a primary user (PU) using the local threshold from each of the sensor nodes; And
(d) collecting the sensing results of the sensor nodes, and finally determining whether the PU uses the frequency band,
As a result of the sensing,
Wherein each sensor node performs spectral sensing for the PU and quantizes the local threshold using the local threshold.
A computer-readable recording medium having recorded thereon a program code for performing the method according to claim 1 or 9.
In a fusion center for cooperative spectrum sensing,
A communication unit for obtaining sensing channel information and a signal-to-noise ratio for a wireless feedback channel from each sensor node;
A calculation unit for deriving a local threshold value of each sensor node using the sensing channel information and the SNR; And
And an analyzer for collecting, from each of the sensor nodes, a sensing result according to spectrum sensing of a primary user (PU) using local thresholds transmitted to the sensors through the communication unit, and finally determining whether or not to use the frequency band of the PU,
As a result of the sensing,
Wherein each of the sensor nodes performs spectral sensing on the PU and then quantizes the local threshold value using the local threshold value.
In a fusion center for cooperative spectrum sensing,
A communication unit for obtaining sensing channel information and a signal-to-noise ratio for a wireless feedback channel from each sensor node;
A memory for storing an optimization parameter look-up table;
A processor for reading out the obtained sensing channel information and a local threshold corresponding to the S / N ratio from the optimization parameter look-up table and transmitting the same to each sensor node through the communication unit; And
And an analysis unit for collecting a sensing result according to spectrum sensing of a primary user (PU) using the local threshold value from each sensor node, and finally determining whether or not to use the frequency band of the PU,
As a result of the sensing,
Wherein each of the sensor nodes performs spectral sensing on the PU and then quantizes the local threshold value using the local threshold value.

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