CN116015505A - Method and device for reliably sensing user selection in cognitive wireless network - Google Patents
Method and device for reliably sensing user selection in cognitive wireless network Download PDFInfo
- Publication number
- CN116015505A CN116015505A CN202211709359.7A CN202211709359A CN116015505A CN 116015505 A CN116015505 A CN 116015505A CN 202211709359 A CN202211709359 A CN 202211709359A CN 116015505 A CN116015505 A CN 116015505A
- Authority
- CN
- China
- Prior art keywords
- user
- sensing
- perceived
- credibility
- users
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000001149 cognitive effect Effects 0.000 title claims abstract description 55
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000001228 spectrum Methods 0.000 claims abstract description 152
- 230000008447 perception Effects 0.000 claims abstract description 30
- 238000010187 selection method Methods 0.000 claims abstract description 8
- 238000004590 computer program Methods 0.000 claims description 14
- 238000012163 sequencing technique Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 230000002452 interceptive effect Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005242 forging Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Mobile Radio Communication Systems (AREA)
Abstract
The invention provides a reliable perception user selection method in a cognitive wireless network, which comprises the following steps: according to the weight of each sensing user, determining the sensing user corresponding to the first set in the current spectrum sensing period from a plurality of sensing users; updating the weight of the corresponding perceived user in the first set in the current spectrum perceived period according to the global judgment result; determining the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, wherein the union set of the second set and the first set comprises all perceived users in the current spectrum sensing period in the cognitive wireless network; and continuously acquiring the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the perceived user with high credibility is finally used as a reliable target user. The method provided by the invention can select users with high reliability to participate in sensing, and improves the frequency spectrum sensing performance and the network security performance.
Description
Technical Field
The present invention relates to the field of radio technologies, and in particular, to a method and apparatus for reliably sensing user selection in a cognitive wireless network.
Background
In the currently fixedly allocated spectrum, a large amount of spectrum is not used, which causes great waste of spectrum resources. The Cognitive Radio (CR) can find the unoccupied frequency bands by sensing the wireless spectrum environment, and dynamically access the frequency bands without interfering with the Primary User (PU), thereby improving the spectrum utilization rate, which makes the CR the most promising technology for solving the current shortage of spectrum resources. The purpose of spectrum sensing is to monitor and detect the activity of PU signals on a particular frequency band, which may be used by the CR system when the presence of a free spectrum is detected; when the PU signal is detected to reappear, the CR system must exit the spectrum for a prescribed time. Through spectrum sensing, CR can avoid interfering PU and improve spectrum utilization.
Due to the openness of the wireless channel and the adoption of a frequency spectrum cognitive access mechanism, the cognitive wireless network is extremely vulnerable to frequency spectrum perception data forging (Spectrum sensing data falsification, abbreviated as SSDF) attack in a frequency spectrum perception stage, an attacker sends the forged frequency spectrum perception data to a Fusion Center (FC), and the Fusion Center is misled to make an erroneous frequency spectrum judgment result, so that the purpose of monopolizing frequency spectrum or causing frequency spectrum resource waste is achieved.
Most of the existing detection algorithms for resisting the SSDF attacks consider that an attacker adopts a simple 'always attack' strategy, which causes low algorithm efficiency for probability type SSDF attackers. Therefore, under the attack of probability type SSDF, how to select reliable users with higher detection performance to participate in sensing in real time so as to improve spectrum sensing performance and network security performance is a key problem to be solved.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a method and a device for reliably sensing user selection in a cognitive wireless network.
A reliable perception user selection method in a cognitive wireless network comprises the following steps:
acquiring the weight of each sensing user in a plurality of sensing users in a current spectrum sensing period;
according to the weight of each sensing user, determining a sensing user corresponding to a first set in a current spectrum sensing period from the plurality of sensing users, wherein the sensing users in the first set are sensing users selected to participate in cooperative spectrum sensing;
updating the weight of the corresponding perceived user in the first set in the current spectrum perceived period according to the global judgment result;
determining the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, wherein the union set of the second set and the first set comprises all perceived users in the current spectrum sensing period in the cognitive wireless network;
and continuously acquiring the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the perceived user with the credibility larger than a certain preset credibility is finally used as a reliable target user.
Further, in the method for selecting reliable sensing users in a cognitive wireless network as described above, determining, from the plurality of sensing users, the sensing user corresponding to the first set in the current spectrum sensing period according to the weight of each sensing user includes:
determining the probability of each sensing user participating in cooperative spectrum sensing in the current spectrum sensing period according to the weight of each sensing user in the current spectrum sensing period;
and sequencing the probabilities in order from large to small, selecting the first M sensing users with larger probability of being selected to participate in spectrum sensing in the current spectrum sensing period, and taking the number of the first M sensing users with larger probability as the first set.
Further, in the method for reliably sensing user selection in a cognitive wireless network as described above, updating the weights of the corresponding sensing users in the first set in the current spectrum sensing period according to the global decision result includes:
if the global judgment result is that the PU does not exist, accessing the corresponding perceived user in the first set into the idle frequency spectrum of the PU so as to participate in cooperative frequency spectrum perception;
determining unit rewards obtained by the corresponding perception users in the current spectrum sensing period through reference and cooperative spectrum sensing;
and updating the weight of the corresponding perceived user in the first set according to the unit consideration.
Further, as described above, the method for reliably sensing user selection in a cognitive wireless network, continuously obtaining the credibility of each sensing user in the first set and the credibility of each sensing user in the second set in each spectrum sensing period until the credibility converges, includes:
the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period are continuously obtained,
and sequencing the credibility corresponding to each perceived user in the first set and the second set in order from small to large, and selecting the perceived user with the credibility greater than the preset credibility as the target user of the next spectrum sensing period.
Further, in the method for reliably sensing user selection in the cognitive wireless network, under the condition that the global judgment result is that the PU exists, each sensing user in the first set is kept silent until the next spectrum sensing period starts.
Further, according to the reliable perception user selection method in the cognitive wireless network, the formula corresponding to the weight of the updated perception user is as follows:
wherein ,
is the ith s Weights corresponding to sensing users participating in spectrum sensing, i s ＝1,2,...,M；α∈(0,1]Indicates learning rate,/->
A unit consideration corresponding to each perceived user in the current spectrum sensing period is given; />
To perceive the probability that a user is selected to participate in cooperative spectrum sensing in a respective spectrum sensing period, i=1, 2.
A reliable perceived user selection device in a cognitive wireless network, comprising:
the acquisition unit is used for acquiring the weight of each perceived user in the plurality of perceived users in the current spectrum perceived period;
the determining unit is used for determining the sensing users corresponding to a first set in the current spectrum sensing period from the plurality of sensing users according to the weight of each sensing user, wherein the sensing users in the first set are the sensing users selected to participate in cooperative spectrum sensing;
the updating unit is used for updating the weight of the corresponding sensing user in the first set in the current spectrum sensing period according to the global judgment result;
the determining unit is further configured to determine the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, where the union set of the second set and the first set includes all perceived users in the current spectrum sensing period in the cognitive wireless network;
the obtaining unit is further configured to continuously obtain the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the perceived user with the credibility greater than a certain preset credibility is finally used as a reliable target user.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the reliable perception user selection method in any one of the cognitive wireless networks when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of reliably perceiving user selection in a cognitive wireless network as any one of the above.
The invention also provides a computer program product comprising a computer program which when executed by a processor implements a method of reliably perceived user selection in a cognitive wireless network as described in any of the above.
According to the reliable perception user selection method in the cognitive wireless network, the target user is comprehensively determined through the credibility of each perception user participating in spectrum perception and the credibility of each perception user not participating in spectrum perception, so that the perception user with the front credibility can be accessed into the PU network by the system, and the probability of the SSDF attack is reduced.
Drawings
Fig. 1 is a schematic diagram of a cognitive wireless network structure model according to the present invention;
fig. 2 is a flowchart of a method for reliably sensing user selection in a cognitive wireless network according to the present invention;
fig. 3 is a second flowchart of a method for reliably sensing user selection in a cognitive wireless network according to the present invention;
FIG. 4 is a graph showing the variation of reliability of a part of a reliable user and an SSDF attacker with sensing time, obtained by the method of the invention;
FIG. 5 is a comparison of receiver operating characteristics for different algorithms;
fig. 6 is a schematic structural diagram of a reliable sensing user selection device in a cognitive wireless network provided by the invention;
fig. 7 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the present invention will be clearly and completely described below, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a schematic diagram of a cognitive wireless network structure model of the present invention, as shown in fig. 1, where the model includes a primary user network (PU network) and 1 secondary user network (CR network), where the CR network and the PU network coexist in an operating frequency band of the PU, and in order to avoid interference to the PU network, the CR network accesses a free spectrum opportunistically by using a cooperative spectrum sensing result. The PU network consists of one PU transmitter and multiple PU receivers, the CR network consists of one secondary user base station (also acting as FC) and N SUs, and the CR network is located within the PU network coverage area. Some users in the CR network are malicious users, and the malicious users report forged spectrum sensing results to the FC, so that the FC is misled to make wrong spectrum judgment.
Fig. 2 is a flowchart of a method for reliably sensing user selection in a cognitive wireless network, as shown in fig. 2, the method includes the following steps:
step 201: and acquiring the weight of each perceived user in a plurality of perceived users in the current spectrum perceived period.
Specifically, the weight omega of each perceived user at the moment t in the CR network is initialized i (t)＝1,i＝1,2,...,N.。
Step 202: and determining the sensing users corresponding to the first set in the current spectrum sensing period from the plurality of sensing users according to the weight of each sensing user, wherein the sensing users in the first set are the sensing users selected to participate in cooperative spectrum sensing.
The following describes how to implement a process of determining, from the plurality of perceived users, a perceived user corresponding to the first set in the current spectrum sensing period:
determining the probability of each sensing user participating in cooperative spectrum sensing in the current spectrum sensing period according to the weight of each sensing user in the current spectrum sensing period; and selecting the first M sensing users with larger probability of being selected to participate in spectrum sensing in the current spectrum sensing period, and taking the number of the first M sensing users with larger probability as the first set. .
According to the method for selecting the reliable sensing users in the cognitive wireless network, the attribute of each sensing user is learned by utilizing the spectrum sensing data of each sensing user, and the user with high reliability is selected from the sensing users to participate in cooperative spectrum sensing, so that the system can access the most reliable sensing user into the PU network according to the previous experience, and therefore the SSDF attack is resisted.
Step 203: and updating the weight of the corresponding perceived user in the first set in the current spectrum perceived period according to the global judgment result.
Specifically, the global decision result is a decision that the PU exists or does not exist in the current spectrum sensing period made by the FC. When the global judgment result is that the PU exists, the PU network is occupied, the CR network cannot be accessed, and the next spectrum sensing period needs to be waited. When the global judgment result is that the PU is not present, the PU network is not occupied, the corresponding frequency spectrum is idle, the CR network can access the idle frequency spectrum by utilizing the cooperative frequency spectrum sensing result, and the CR network waits for receiving the data transmission result confirmation information ACK.
The following describes how to update the implementation procedure of the weights of the corresponding perceived users in the first set in the current spectrum sensing period according to the global decision result:
if the global judgment result is that the PU does not exist, accessing the corresponding perceived user in the first set into the idle frequency spectrum of the PU so as to participate in cooperative frequency spectrum perception; determining unit rewards obtained by the corresponding perception users in the current spectrum sensing period through reference and cooperative spectrum sensing; and updating the weight of the corresponding perceived user in the first set according to the unit consideration.
Wherein the unit consideration is obtained by adopting the following formula:
wherein ,
representing the received ith s Reporting results of the SU participating in sensing in the t-th sensing time slot, g (t) represents channel state of PU, g (t) =1 represents that the t-th time slot PU exists, otherwise, PU does not exist, and g (t) =0.
Step 204: and determining the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, wherein the union set of the second set and the first set comprises a plurality of perceived users in the current spectrum sensing period.
The credibility of the user is perceived, and a calculation formula is as follows
Step 205: and continuously acquiring the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the credibility converges, and taking the perceived user with the credibility larger than a certain preset credibility as a reliable target user.
Specifically, the basis for judging the reliability convergence is as follows:
and continuously acquiring the credibility of each sensing user in the first set and the credibility of each sensing user in the second set in each spectrum sensing period, sequencing the credibility corresponding to each sensing user in the first set and the second set in a sequence from small to large, and selecting the sensing user with the credibility greater than the preset credibility as the target user of the next spectrum sensing period.
According to the method for selecting the reliable sensing users in the cognitive wireless network, the target users are comprehensively determined through the credibility of each sensing user participating in spectrum sensing and the credibility of each sensing user not participating in spectrum sensing, so that the system can access the sensing user with the front credibility into the PU network, and the reliable spectrum sensing is realized.
The following describes the detailed method steps of the reliable perception user selection method in the cognitive wireless network provided by the invention:
fig. 3 is a second flowchart of a method for reliably sensing user selection in a cognitive wireless network, as shown in fig. 3, the method includes the following steps:
step 1: initializing weight w of each perceived user at time t in CR network i (t) and confidence level ρ i (t), i=1, 2,..n, N is the total number of perceived users in the CR network. Wherein the credibility is defined as (1)
Step 1: calculating probability p that the ith perceived user is selected to participate in cooperative spectrum perception at the t moment i (t)，
i=1, 2, …, N, calculated as formula (2)
Wherein the parameters are
Step 2: the number M of users participating in cooperative spectrum sensing according to the need is calculated according to p i (t) sorting from big to small, selecting the first M with larger p i The perception users of (t) participate in the cooperative spectrum perception, and the respective perception results are reported to the FC.
Step 3: the FC makes a global decision as to whether the PU is present using hard decision criteria.
Step 4: if the global result of cooperative spectrum sensing in the step 3 is that the PU does not exist, the cognitive user accesses the idle spectrum of the PU under the coordination of the FC and waits for receiving the data transmission acknowledgement information ACK to obtain the real state of the PU channel.
Step 5: if the global result of the cooperative spectrum sensing in the step 3 is that the PU exists, each cognitive user keeps a silent state until the next spectrum sensing period starts, and at the moment, the global judgment result of the cooperative spectrum sensing is used as an approximate PU channel state result.
Step 6: calculating a unit consideration obtained by the user selected to participate in perception according to formula (3)
wherein ,
representing the received ith s Reporting results of the SU participating in sensing in the t-th sensing time slot, g (t) represents channel state of PU, g (t) =1 represents that the t-th time slot PU exists, otherwise, PU does not exist, and g (t) =0.
Step 7: the weight of M users participating in perception is updated, and the update formula is shown as formula (4)
Where α ε (0, 1) represents the learning rate, which determines the ratio of current observations to weight adjustments.
Step 8: and (3) calculating the credibility of each perceived user after the weight is updated according to the formula (1).
Step 9: repeating the steps 2 to 8, and circularly calculating the credibility rho of each perceived user at the next moment i (t+1),i＝1,2,...,N。
Fig. 4 is a graph showing the reliability of a part of reliable users and SSDF attacker obtained by the method of the present invention, and as can be seen from fig. 4, the reliability of all users tends to converge and SU approximately passes 500 sensing time slots 1 ～SU 4 Is far more reliable than SU 37 ～SU 40 The method provided by the invention can be used for selecting reliable perception users to participate in cooperative spectrum perception. Fig. 5 is a comparison of receiver operating characteristics for different algorithms, and it can be seen from fig. 5 that a reliable perceived user can be selected using the method of the present inventionParticipate in cooperative spectrum sensing.
The reliable sensing user selection device in the cognitive wireless network provided by the invention is described below, and the reliable sensing user selection device in the cognitive wireless network described below and the reliable sensing user selection method in the cognitive wireless network described above can be correspondingly referred to each other.
Fig. 6 is a schematic structural diagram of a device for reliably sensing user selection in a cognitive wireless network, as shown in fig. 6, where the device includes:
an obtaining unit 601, configured to obtain weights of each of a plurality of sensing users in a current spectrum sensing period;
a determining unit 602, configured to determine, according to the weights of the sensing users, a sensing user corresponding to a first set in a current spectrum sensing period from the plurality of sensing users, where the sensing user in the first set is a sensing user selected to participate in cooperative spectrum sensing;
an updating unit 603, configured to update weights of corresponding perceived users in the first set in the current spectrum sensing period according to the global decision result;
the determining unit 602 is further configured to determine the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, where a union set of the second set and the first set includes all perceived users in the current spectrum sensing period in the cognitive wireless network;
the obtaining unit 601 is further configured to continuously obtain the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the credibility converges, and take the perceived user with the high credibility as a reliable target user.
Fig. 7 illustrates a physical schematic diagram of an electronic device, as shown in fig. 7, which may include: processor 710, communication interface 720, memory 730, and communication bus 740, wherein processor 710, communication interface 720, memory 730 communicate with each other via communication bus 740. Processor 710 may invoke logic instructions in memory 730 to perform a method of reliably perceiving user selection in a cognitive wireless network, the method comprising
Acquiring the weight of each sensing user in a plurality of sensing users in a current spectrum sensing period;
according to the weight of each sensing user, determining a sensing user corresponding to a first set in a current spectrum sensing period from the plurality of sensing users, wherein the sensing users in the first set are sensing users selected to participate in cooperative spectrum sensing;
updating the weight of the corresponding perceived user in the first set in the current spectrum perceived period according to the global judgment result;
determining the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, wherein the union set of the second set and the first set comprises all perceived users in the current spectrum sensing period in the cognitive wireless network;
and continuously acquiring the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the credibility converges, and taking the perceived user with the credibility larger than a certain preset credibility as a reliable target user.
Further, the logic instructions in the memory 730 described above may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-only memory (ROM), a random access memory (RAM, randomAccessMemory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, where the computer program product includes a computer program, where the computer program can be stored on a non-transitory computer readable storage medium, and when the computer program is executed by a processor, the computer can execute the method for reliably sensing user selection in the cognitive wireless network provided by the above methods.
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program that, when executed by a processor, is implemented to perform the method of reliably perceiving user selection in a cognitive wireless network provided by the above methods.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A reliable perception user selection method in a cognitive wireless network is characterized by comprising the following steps:
acquiring the weight of each sensing user in a plurality of sensing users in a current spectrum sensing period;
according to the weight of each sensing user, determining a sensing user corresponding to a first set in a current spectrum sensing period from the plurality of sensing users, wherein the sensing users in the first set are sensing users selected to participate in cooperative spectrum sensing;
updating the weight of the corresponding perceived user in the first set in the current spectrum perceived period according to the global judgment result;
determining the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, wherein the union set of the second set and the first set comprises all perceived users in the current spectrum sensing period in the cognitive wireless network;
and continuously acquiring the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the perceived user with the credibility larger than a certain preset credibility is finally used as a reliable target user.
2. The method for reliably sensing user selection in a cognitive wireless network according to claim 1, wherein determining, from the plurality of sensing users, the sensing user corresponding to the first set in the current spectrum sensing period according to the weight of each sensing user comprises:
determining the probability of each sensing user participating in cooperative spectrum sensing in the current spectrum sensing period according to the weight of each sensing user in the current spectrum sensing period;
and sequencing the probabilities in order from large to small, selecting the first M sensing users with larger probability of being selected to participate in spectrum sensing in the current spectrum sensing period, and taking the number of the first M sensing users with larger probability as the first set.
3. The method for reliably perceived user selection in a cognitive wireless network of claim 1, wherein updating the weights of the respective perceived users in the first set within the current spectrum sensing period according to the global decision result comprises:
if the global judgment result is that the PU does not exist, accessing the corresponding perceived user in the first set into the idle frequency spectrum of the PU so as to participate in cooperative frequency spectrum perception;
determining unit rewards obtained by the corresponding perception users in the current spectrum sensing period through reference and cooperative spectrum sensing;
and updating the weight of the corresponding perceived user in the first set according to the unit consideration.
4. The method for reliably sensing user selection in a cognitive wireless network according to claim 1, wherein the continuously obtaining the credibility of each sensing user in the first set and the credibility of each sensing user in the second set in each spectrum sensing period until the credibility converges comprises:
the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period are continuously obtained,
and sequencing the credibility corresponding to each perceived user in the first set and the second set in order from small to large, and selecting the perceived user with the credibility greater than the preset credibility as the target user of the next spectrum sensing period.
5. The method for reliably perceived user selection in a cognitive wireless network of claim 1, wherein each perceived user in the first set is kept silent until a next spectrum sensing period begins if the global decision result is PU present.
6. The method for reliably sensing user selection in a cognitive wireless network according to claim 1, wherein the formula corresponding to the weight of the updated sensing user is:
wherein ,
is the ith s Weights corresponding to sensing users participating in spectrum sensing, i s ＝1,2,...,M；α∈(0,1]Indicates learning rate,/->
A unit consideration corresponding to each perceived user in the current spectrum sensing period is given; />
To perceive the probability that a user is selected to participate in cooperative spectrum sensing in a respective spectrum sensing period, i=1, 2.
7. A reliable-aware user selection apparatus in a cognitive wireless network, comprising:
the acquisition unit is used for acquiring the weight of each perceived user in the plurality of perceived users in the current spectrum perceived period;
the determining unit is used for determining the sensing users corresponding to a first set in the current spectrum sensing period from the plurality of sensing users according to the weight of each sensing user, wherein the sensing users in the first set are the sensing users selected to participate in cooperative spectrum sensing;
the updating unit is used for updating the weight of the corresponding sensing user in the first set in the current spectrum sensing period according to the global judgment result;
the determining unit is further configured to determine the credibility of each perceived user in the first set after the weight is updated and the credibility of each perceived user in the second set in the current spectrum sensing period, where the union set of the second set and the first set includes all perceived users in the current spectrum sensing period in the cognitive wireless network;
the obtaining unit is further configured to continuously obtain the credibility of each perceived user in the first set and the credibility of each perceived user in the second set in each spectrum sensing period until the perceived user with the credibility greater than a certain preset credibility is finally used as a reliable target user.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a method of reliably perceived user selection in a cognitive wireless network as claimed in any one of claims 1 to 6 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements a method of reliably perceived user selection in a cognitive wireless network according to any of claims 1 to 6.
10. A computer program product comprising a computer program which, when executed by a processor, implements a method of reliably perceived user selection in a cognitive wireless network as claimed in any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211709359.7A CN116015505A (en) | 2022-12-29 | 2022-12-29 | Method and device for reliably sensing user selection in cognitive wireless network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211709359.7A CN116015505A (en) | 2022-12-29 | 2022-12-29 | Method and device for reliably sensing user selection in cognitive wireless network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116015505A true CN116015505A (en) | 2023-04-25 |
Family
ID=86026356
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211709359.7A Pending CN116015505A (en) | 2022-12-29 | 2022-12-29 | Method and device for reliably sensing user selection in cognitive wireless network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116015505A (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101459445A (en) * | 2008-12-29 | 2009-06-17 | 浙江大学 | Cooperative spectrum sensing method in cognitive radio system |
| WO2011082527A1 (en) * | 2010-01-07 | 2011-07-14 | 上海贝尔股份有限公司 | Method and node for cognizing cooperative spectrum of cognitive wireless network |
| CN102624464A (en) * | 2011-01-26 | 2012-08-01 | 龚牡丹 | Method for decreasing influence of malicious users on cooperative spectrum sensing based on historical performance |
| CN103117820A (en) * | 2013-01-23 | 2013-05-22 | 南通大学 | Reliability-based weighted collaboration spectrum detection method |
| CN103178910A (en) * | 2013-02-27 | 2013-06-26 | 浙江大学 | Credibility based cognitive radio network stratified cooperative spectrum sensing method |
| CN106255066A (en) * | 2016-09-23 | 2016-12-21 | 宁波大学 | Coordinating cognition wireless network multi-user communication dynamic decision method |
| CN106961311A (en) * | 2017-03-13 | 2017-07-18 | 南通大学 | Cognition wireless network cooperative spectrum detection method based on sensing node degree of belief |
| CN108322276A (en) * | 2018-01-18 | 2018-07-24 | 南京信息工程大学 | A kind of frequency spectrum perception accuracy rate lift technique based on D-S evidence theory |
| CN113905384A (en) * | 2021-05-31 | 2022-01-07 | 西北工业大学 | Multi-agent cooperative spectrum sensing and accessing method for cognitive radio |
-
2022
- 2022-12-29 CN CN202211709359.7A patent/CN116015505A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101459445A (en) * | 2008-12-29 | 2009-06-17 | 浙江大学 | Cooperative spectrum sensing method in cognitive radio system |
| WO2011082527A1 (en) * | 2010-01-07 | 2011-07-14 | 上海贝尔股份有限公司 | Method and node for cognizing cooperative spectrum of cognitive wireless network |
| CN102624464A (en) * | 2011-01-26 | 2012-08-01 | 龚牡丹 | Method for decreasing influence of malicious users on cooperative spectrum sensing based on historical performance |
| CN103117820A (en) * | 2013-01-23 | 2013-05-22 | 南通大学 | Reliability-based weighted collaboration spectrum detection method |
| CN103178910A (en) * | 2013-02-27 | 2013-06-26 | 浙江大学 | Credibility based cognitive radio network stratified cooperative spectrum sensing method |
| CN106255066A (en) * | 2016-09-23 | 2016-12-21 | 宁波大学 | Coordinating cognition wireless network multi-user communication dynamic decision method |
| CN106961311A (en) * | 2017-03-13 | 2017-07-18 | 南通大学 | Cognition wireless network cooperative spectrum detection method based on sensing node degree of belief |
| CN108322276A (en) * | 2018-01-18 | 2018-07-24 | 南京信息工程大学 | A kind of frequency spectrum perception accuracy rate lift technique based on D-S evidence theory |
| CN113905384A (en) * | 2021-05-31 | 2022-01-07 | 西北工业大学 | Multi-agent cooperative spectrum sensing and accessing method for cognitive radio |
Non-Patent Citations (6)
| Title |
|---|
| YUANHUA FU 等: "Entropy-Based Weighted Decision Combining for Collaborative Spectrum Sensing Over Byzantine Attack", IEEE WIRELESS COMMUNICATIONS LETTERS, 1 July 2019 (2019-07-01), pages 1528 * |
| 刘全;郭云玮;高俊;刘思洋;: "抗SSDF攻击的EWSPRT协作频谱感知方案", 电讯技术, no. 03, 20 March 2011 (2011-03-20) * |
| 曹津平;李伟;张翼英;: "一种应用于电力无线专网的基于信任度的协作频谱感知算法", 电信科学, no. 03, 20 March 2015 (2015-03-20) * |
| 李丽娟;: "一种基于加权的分组协作感知算法", 电子世界, no. 10, 30 May 2013 (2013-05-30) * |
| 李超;任国春;王呈贵;王玉博;: "分簇认知无线电网络中的加权合作频谱感知技术", 军事通信技术, no. 02, 25 June 2013 (2013-06-25) * |
| 黄堂森: "协作频谱感知中基于可靠度原则的节点选择方法研究", 光电子·激光, 15 July 2020 (2020-07-15) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR101120239B1 (en) | Methods and apparatus for channel estimation and rate feedback in a peer to peer network | |
| CN107623554B (en) | Cooperation spectrum sensing method based on trust value and cognitive wireless network | |
| US9998308B2 (en) | Electronic device, method and computer-readable medium for sensing spectrum usage in a cognitive radio communication system | |
| US11522638B2 (en) | Artificial intelligence fault localization in 5G and 6G messages | |
| US9148477B2 (en) | Methods and apparatus for communicating in a wireless system | |
| US20230300017A1 (en) | AI-Based Correction of Corrupted 5G/6G Messages | |
| WO2016110262A1 (en) | System and method for adaptive back-off time determination | |
| CN103684626A (en) | Multi user cooperative frequency spectrum sensing data fusion method and device | |
| CN109039412A (en) | A kind of safe transmission method of physical layer based on random wave bundle figuration | |
| Ling et al. | Trust and reputation management in cognitive radio networks: a survey | |
| Biswas et al. | Mitigation of the spectrum sensing data falsifying attack in cognitive radio networks | |
| CN116015505A (en) | Method and device for reliably sensing user selection in cognitive wireless network | |
| CN109150623B (en) | Method for resisting SSDF attack of malicious user based on round robin reputation value | |
| Zhang et al. | Ensemble learning based robust cooperative sensing in full-duplex cognitive radio networks | |
| Parmar et al. | Gaussian mixture model based anomaly detection for defense against Byzantine attack in cooperative spectrum sensing | |
| CN110768935A (en) | SSDF attack resisting method based on evidence theory and fuzzy entropy | |
| CN108616318B (en) | Secure spectrum sensing method | |
| Chouhan et al. | Defending Against Byzantine Attacks in CRNs: PCA-Based Malicious User Detection and Weighted Cooperative Spectrum Sensing | |
| Ye et al. | Evidence-theory-based collaborative spectrum sensing with efficient creditability evaluation in cognitive radio networks | |
| Awan et al. | An Improved Cooperative Spectrum Sensing Scheme for Emulation Attacker Detection in Cognitive Radio Network | |
| Anandh et al. | Novel STD-ACP for detecting energy and threshold value in the network | |
| Zhang et al. | Communication Anti-jamming Method Based on POMDP Model under Limited State Information Conditions | |
| KR101595926B1 (en) | Cooperative sensing method for minimizing the feedback overhead by using iNOR rule in CR, and apparatus thereof | |
| CN118264348A (en) | Collaborative spectrum sensing method for resisting SSDF attack based on combination of clustering and evidence theory | |
| Zhu et al. | Dynamic sliding window‐cooperative spectrum sensing against massive SSDF attack in interweave cognitive internet of things |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |