Sensing node determination method and device, storage medium and program product

Abstract

The invention provides a sensing node determination method and device, a storage medium and a program product, relates to the technical field of communication, and can solve the problem that communication requirements and interference sensing requirements cannot be met at the same time. The method comprises the following steps: acquiring received signal strength RSS data of an interference source received by N sensing nodes in a target area under the condition that signal interference exists in the target area; based on the RSS data, taking M sensing nodes in the N sensing nodes as nodes for interference source positioning; the positioning precision of the M sensing nodes on the interference source is greater than a precision threshold; n is a positive integer, and M is a positive integer smaller than N. According to the invention, communication requirements and interference sensing requirements can be met simultaneously.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, device, storage medium and program product for determining a perception node. Background Art

[0002] In wireless communication systems, wireless communications are often affected by various interferences, which may come from other wireless devices, environmental noise, or malicious attacks. Interference not only degrades communication quality, but may also cause connection interruptions, seriously affecting user experience and service continuity.

[0003] Synaesthesia integration refers to a new information processing technology that realizes the coordination of perception and communication functions based on software and hardware resource sharing or information sharing. This technology is used to superimpose radar-like perception capabilities while transmitting signals on wireless channels, and detect and track surrounding objects by sensing the signals transmitted on the wireless channels. When facing communication interference, the communication equipment in the communication system can locate the interference source through this technology.

[0004] However, when wireless communication is affected by various interferences, due to the limited communication and perception resources in the communication system, the communication equipment will also affect the normal communication of the current communication system when locating the interference source, and cannot meet both communication needs and interference perception needs at the same time. Summary of the invention

[0005] The present application provides a perception node determination method, device, storage medium and program product, which can simultaneously meet communication requirements and interference perception requirements.

[0006] In order to achieve the above objectives, this application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a method for determining a perception node, the method comprising: in the presence of signal interference in a target area, obtaining received signal strength RSS data of the interference source received by N perception nodes in the target area; based on the RSS data, using M perception nodes out of the N perception nodes as nodes for locating the interference source; the positioning accuracy of the M perception nodes for the interference source is greater than an accuracy threshold; N is a positive integer, and M is a positive integer less than N.

[0008] Based on the above technical solution, when there is signal interference in the target area, the sensing node determination device can obtain the RSS data of the interference source received by the N sensing nodes in the target area, and based on the RSS data, use M sensing nodes among the N sensing nodes as nodes for locating the interference source. Among them, the positioning accuracy of the M sensing nodes for the interference source is greater than the accuracy threshold, N is a positive integer, and M is a positive integer less than N. In this way, the present application can reduce the number of sensing nodes used for perception from N to M while meeting the interference perception requirements, thereby reducing the number of sensing nodes used for positioning perception, thereby reducing the use of sensing resources and improving resource utilization, so as to avoid affecting the normal communication of the communication system, and can meet the communication requirements and interference perception requirements at the same time.

[0009] In combination with the above-mentioned first aspect, in a possible implementation method, the accuracy threshold is determined by the positioning accuracy and accuracy coefficient of N sensing nodes for the interference source; the positioning accuracy of multiple sensing nodes for the interference source is determined by the RSS data of the interference source received by the multiple sensing nodes.

[0010] In combination with the first aspect above, in a possible implementation, the method includes: determining the positioning accuracy of the N sensing nodes for the interference source based on the RSS data of the interference source received by the N sensing nodes; determining the accuracy threshold through the positioning accuracy and accuracy coefficient of the N sensing nodes for the interference source; determining multiple node combinations based on the N sensing nodes; the node combination is composed of one or more nodes among the N sensing nodes; according to the accuracy threshold, the sensing nodes of the target combination in the multiple node combinations are used as nodes for locating the interference source; the target combination is composed of M sensing nodes.

[0011] In combination with the above first aspect, in a possible implementation manner, the target combination satisfies a resource usage condition.

[0012] In combination with the first aspect above, in a possible implementation, the resource usage condition includes: a node combination among multiple node combinations whose positioning accuracy is greater than an accuracy threshold and whose corresponding perception resource usage is the least.

[0013] In combination with the first aspect above, in a possible implementation, the RSS data satisfies the following formula:

[0014]

[0015] Among them, D n is the RSS data of the nth sensing node, ρ represents the path loss factor, |d n | is the distance between the nth sensing node and the interference source; σ n Represents the noise error, with a mean of 0 and a variance of δ n =λn 2 Gaussian distribution, C0 is the average RSS received by the sensing node at the reference distance d0;

[0016] The positioning accuracy of multiple sensing nodes for interference sources satisfies the following formula:

[0017]

[0018] Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, ξ' represents the estimated position of the interference source; φ n =c1ln|d n |+c2, |d n | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor, C0 is the average RSS received by the sensing node at the reference distance d0;

[0019] Alternatively, the positioning accuracy of multiple sensing nodes for interference sources satisfies the following formula:

[0020]

[0021] Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, e n is the unit direction vector of the nth sensing node pointing to the interference source, λ n is the standard deviation of the noise error, |d n | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor;

[0022] The accuracy threshold satisfies the following formula:

[0023] A=α|F| max

[0024] Among them, α is the precision coefficient, |F| max is the positioning accuracy of N sensing nodes for the interference source.

[0025] In a second aspect, the present application provides a sensing node determination device, the device comprising: a processing unit and a communication unit;

[0026] The communication unit is used to obtain received signal strength RSS data of the interference source received by N sensing nodes in the target area when there is signal interference in the target area;

[0027] The processing unit is used to use M sensing nodes among N sensing nodes as nodes for locating interference sources based on RSS data; the positioning accuracy of the M sensing nodes for the interference source is greater than the accuracy threshold; N is a positive integer, and M is a positive integer less than N.

[0028] In combination with the above-mentioned second aspect, in a possible implementation method, the accuracy threshold is determined by the positioning accuracy and accuracy coefficient of N sensing nodes for the interference source; the positioning accuracy of multiple sensing nodes for the interference source is determined by the RSS data of the interference source received by the multiple sensing nodes.

[0029] In combination with the above-mentioned second aspect, in a possible implementation method, the processing unit is used to: determine the positioning accuracy of the N sensing nodes for the interference source based on the RSS data of the interference source received by the N sensing nodes; determine the accuracy threshold through the positioning accuracy and accuracy coefficient of the N sensing nodes for the interference source; determine multiple node combinations based on the N sensing nodes; the node combination is composed of one or more nodes among the N sensing nodes; according to the accuracy threshold, the sensing nodes of the target combination in the multiple node combinations are used as nodes for locating the interference source; the target combination is composed of M sensing nodes.

[0030] In combination with the above second aspect, in a possible implementation manner, the target combination satisfies a resource usage condition.

[0031] In conjunction with the second aspect above, in a possible implementation, the resource use condition includes:

[0032] The node combination whose positioning accuracy is greater than the accuracy threshold and whose corresponding sensing resource usage is the least among multiple node combinations.

[0033] In combination with the second aspect above, in a possible implementation, the RSS data satisfies the following formula:

[0034]

[0035] Among them, D n is the RSS data of the nth sensing node, ρ represents the path loss factor, |d n | is the distance between the nth sensing node and the interference source; σ n Represents the noise error, with a mean of 0 and a variance of δ n =λ n 2 Gaussian distribution, C0 is the average RSS received by the sensing node at the reference distance d0;

[0036] The positioning accuracy of multiple sensing nodes for interference sources satisfies the following formula:

[0037]

[0038] Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, ξ' represents the estimated position of the interference source; φ n =c1ln|d n |+c2, |dn | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor, C0 is the average RSS received by the sensing node at the reference distance d0;

[0039] Alternatively, the positioning accuracy of multiple sensing nodes for interference sources satisfies the following formula:

[0040]

[0041] Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, e n is the unit direction vector of the nth sensing node pointing to the interference source, λ n is the standard deviation of the noise error, |d n | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor;

[0042] The accuracy threshold satisfies the following formula:

[0043] A=α|F| max

[0044] Among them, α is the precision coefficient, |F| max is the positioning accuracy of N sensing nodes for the interference source.

[0045] In a third aspect, the present application provides a perception node determination device, which includes: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run a computer program or instruction to implement the method described in any of the above embodiments.

[0046] In a fourth aspect, the present application provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal, the terminal executes the method described in any of the above embodiments.

[0047] In a fifth aspect, the present application provides a computer program product, which includes computer program instructions. When the computer program instructions are executed by a processor, the method described in any of the above embodiments is implemented.

[0048] In a sixth aspect, the present application provides a chip, the chip comprising a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run a computer program or instruction to implement the method described in any of the above embodiments.

[0049] Specifically, the chip provided in the present application also includes a memory for storing computer programs or instructions.

[0050] It should be noted that the above computer instructions may be stored in whole or in part on a computer-readable storage medium, wherein the computer-readable storage medium may be packaged together with the processor of the device, or may be packaged separately from the processor of the device, which is not limited in this application.

[0051] The descriptions of the second to sixth aspects of the present application can refer to the detailed description of the first aspect; and the beneficial effects of the descriptions of the second to sixth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.

[0052] In this application, the name of the above-mentioned perception node determination device does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. As long as the functions of each device or functional module are similar to those of this application, they fall within the scope of the claims of this application and their equivalent technologies.

[0053] These and other aspects of the present application will become more apparent from the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 An architecture diagram of a communication system provided in an embodiment of the present application;

[0055] Figure 2 A scene diagram of low-orbit satellite communication provided in an embodiment of the present application;

[0056] Figure 3 A flowchart of a method for determining a sensing node provided in an embodiment of the present application;

[0057] Figure 4 A flowchart of another method for determining a sensing node provided in an embodiment of the present application;

[0058] Figure 5 A flowchart of a traversal algorithm provided in an embodiment of the present application;

[0059] Figure 6 A structural diagram of a sensing node determination device provided in an embodiment of the present application;

[0060] Figure 7 A structural diagram of another perception node determination device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0062] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0063] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0064] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0065] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0066] In the description of the present application, unless otherwise specified, “plurality” means two or more.

[0067] In wireless communication systems, wireless communications are often affected by various interferences, which may come from other wireless devices, environmental noise, or malicious attacks. Interference not only degrades communication quality, but may also cause connection interruptions, seriously affecting user experience and service continuity.

[0068] Synaesthesia integration refers to a new information processing technology that realizes the coordination of perception and communication functions based on software and hardware resource sharing or information sharing. This technology is used to superimpose radar-like perception capabilities while transmitting signals on wireless channels, and detect and track surrounding objects by sensing the signals transmitted on the wireless channels.

[0069] Take low-orbit satellite communications as an example. With the rapid development of low-orbit satellite communication technology and telepathy integration, thousands of low-orbit satellites will be launched every year, which will lead to an increasingly complex electromagnetic environment in orbital space. At the same time, the available space between tens of thousands of low-orbit satellites will become increasingly tight, and spectrum resources will become increasingly crowded. When the low-orbit satellite system is networked and operated, external electromagnetic interference will seriously affect the system capacity. Therefore, it is necessary to locate the interference source in the environment. By locating the interference source, targeted measures can be taken, such as adjusting the antenna direction, changing the transmission power, etc. to suppress interference and improve communication quality and system performance.

[0070] The relevant interference source positioning solution mainly uses highly maneuverable drones for perception. By dynamically adjusting the distribution of drone swarms in the airspace, the spectrum data collected by each drone sensing node is changed to improve the interference positioning accuracy.

[0071] However, this solution is not suitable for the perception scenarios of devices that cannot move or have weak mobility. Taking low-orbit satellite communications as an example, although low-orbit satellites have certain dynamic characteristics, the orbital positions of each satellite are relatively fixed, and it is difficult to change the satellite topology in a period of time. Therefore, the above solution of adjusting the position of each device to obtain interference spectrum data in space and thus improve the accuracy of interference source positioning cannot be applied.

[0072] Therefore, when wireless communication is affected by various interferences, due to the limited communication and perception resources in the communication system, the communication equipment will also affect the normal communication of the current communication system when locating the interference source, and cannot meet both communication needs and interference perception needs at the same time.

[0073] In view of this, in the technical solution provided by the present application, when there is signal interference in the target area, the sensing node determination device can obtain the RSS data of the interference source received by the N sensing nodes in the target area, and based on the RSS data, use M sensing nodes among the N sensing nodes as nodes for locating the interference source. Among them, the positioning accuracy of the M sensing nodes for the interference source is greater than the accuracy threshold, N is a positive integer, and M is a positive integer less than N. In this way, the present application can reduce the number of sensing nodes used for perception from N to M while meeting the interference perception requirements, thereby reducing the number of sensing nodes used for positioning perception, thereby reducing the use of sensing resources and improving resource utilization, so that the normal communication of the communication system can be avoided from being affected, and the communication requirements and interference perception requirements can be met at the same time.

[0074] The implementation of the embodiments of the present application will be described in detail below in conjunction with the accompanying drawings.

[0075] Figure 1 This is an architecture diagram of a communication system provided in an embodiment of the present application. Figure 1As shown, the communication system includes: a sensing node determination device 101 and a sensing node 102.

[0076] Among them, the sensing node determination device 101 is connected to the sensing node 102. The number of the sensing node determination device 101 and the sensing node 102 can be one or more, which is not limited in this application.

[0077] The technical solutions of the embodiments of the present application can be applied to various communication systems, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal frequency division multiple access (OFDMA), single carrier frequency division multiple access (SC-FDMA) and other systems. The term "system" can be interchangeable with "network". The CDMA system can implement wireless technologies such as universal terrestrial radio access (UTRA) and CDMA2000. UTRA can include wideband CDMA (WCDMA) technology and other CDMA variant technologies. CDMA2000 can cover interim standard (IS) 2000 (IS-2000), IS-95 and IS-856 standards. The TDMA system can implement wireless technologies such as global system for mobile communication (GSM). The OFDMA system can implement wireless technologies such as evolved universal radio terrestrial access (evolved UTRA, E-UTRA), ultra mobile broadband (ultra mobile broadband, UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE802.20, Flash OFDMA, etc. UTRA and E-UTRA are UMTS and UMTS evolution versions. 3GPP's long term evolution (long term evolution, LTE) and various versions based on LTE evolution are new versions of UMTS using E-UTRA. The communication system can also be a 5G communication system, a new radio (new radio, NR) 5G-A (5.5G) system, and a 6G communication system. In addition, the communication system can also be applicable to future-oriented communication technologies, and the technical solutions provided in the embodiments of the present application are applicable.

[0078] The sensing node determination device 101 and the sensing node 102 are both communication devices in the communication system, wherein the sensing node 102 has sensing capability. The communication devices in the communication system may include terminals, access network devices, and the like.

[0079] A terminal is a device with wireless communication capabilities that can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted. It can also be deployed on the water (such as ships, etc.). It can also be deployed in the air (such as airplanes, balloons, and satellites, etc.). A terminal is also called user equipment (UE), mobile station (MS), mobile terminal (MT), and terminal equipment, etc. It is a device that provides voice and / or data connectivity to users. For example, terminals include handheld devices with wireless connection capabilities, vehicle-mounted devices, etc. At present, the terminal can be: a mobile phone, a tablet computer, a laptop computer, a PDA, a mobile internet device (MID), a wearable device (such as a smart watch, a smart bracelet, a pedometer, etc.), an in-vehicle device (such as a car, a bicycle, an electric car, an airplane, a ship, a train, a high-speed rail, etc.), a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a smart home device (such as a refrigerator, a TV, an air conditioner, an electric meter, etc.), an intelligent robot, a workshop device, a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, or a wireless terminal in a smart home, a flying device (such as an intelligent robot, a hot air balloon, a drone, an airplane, and a satellite), etc. In a possible application scenario of the present application, the terminal device is a terminal device that often works on the ground, such as an in-vehicle device. In this application, for the sake of convenience, chips deployed in the above-mentioned devices, such as system-on-a-chip (SOC), baseband chips, etc., or other chips with communication functions may also be referred to as terminals.

[0080] The access network device is a device located at the access network side of the above-mentioned communication system and having a wireless transceiver function or a chip or chip system that can be set in the device. The access network equipment includes, but is not limited to: access points (APs) in WiFi systems, such as home gateways, routers, servers, switches, bridges, etc., evolved NodeBs (eNBs), radio network controllers (RNCs), NodeBs (NBs), base station controllers (BSCs), base transceiver stations (BTSs), home base stations (e.g., home evolved NodeBs, or home NodeBs, HNBs), base band units (BBUs), wireless relay nodes, wireless backhaul nodes, transmission points (TRPs or TPs), etc., and may also be 5G base stations, such as gNBs in new radio (NR) systems, or transmission points (TRPs or TPs), one or a group of (including multiple antenna panels) antenna panels of a base station in a 5G system, or network nodes constituting gNBs or transmission points, such as baseband units (BBUs), or distributed units (DUs), road side units with base station functions (road side Access network equipment also includes base stations in different networking modes, such as master evolved NodeB (MeNB), secondary eNB (SeNB, or secondary gNB, SgNB). Access network equipment also includes different types, such as ground base stations, aerial base stations, and satellite base stations.

[0081] In some embodiments, the perception node determination device 101 may also be deployed on the perception node 102. For example, the perception node determination device 101 and the perception node 102 may be the same communication device. The perception node determination device 101 may also be a module on the perception node 102, or a protocol layer in the communication system.

[0082] The sensor node determination device 101 is used to schedule the sensor nodes 102 in the communication system.

[0083] Exemplarily, the sensing node determining device 101 may obtain data collected by the sensing node 102, such as spectrum data.

[0084] The sensing node 102 is used to provide sensing and communication capabilities.

[0085] In some embodiments, when signal interference exists, the sensing node determination device 101 may schedule the sensing node 102 to locate the interference source.

[0086] For example, take the communication scenario of low-orbit satellite as an example. Figure 2 As shown, the sensing node 102 can be a low-orbit satellite, and the sensing node determination device 101 can be a ground base station (not shown in the figure) or can also be a low-orbit satellite. Multiple low-orbit satellites in the current area are subject to signal interference from interference sources. For example, the electromagnetic waves sent by the interference source interfere with the electromagnetic wave signals received and sent by the low-orbit satellites. The signal interference includes main lobe interference and side lobe interference. At this time, multiple low-orbit satellites in the current area can collect sampling data of the signal of the interference source. For example, the sampling data can be signal data in the time-frequency space domain, corresponding to the three dimensions of time, frequency, and wave position respectively. Among them, the communication resources in the frequency domain are composed of frequency bands (BAND1, BAND2, BADN3, etc.), the communication resources in the time domain are composed of time slots (t1, t2, t3, etc.), and the communication resources in the space domain are composed of wave positions (wave position 1, wave position 2...wave position N). Among them, Figure 2 The resource block filled with the middle line is the interfered resource block. In the process of large-scale inter-sensory low-orbit satellite system sensing the interference source, there are differences in the sampled data (such as RSS data from the interference source) obtained by the low-orbit satellites in different directions, and the arrival time and arrival frequency of the interference signal to the low-orbit satellites in different directions are also different. The low-orbit satellite system can use this difference to jointly estimate the position of the interference source. For the low-orbit satellites in the large-scale low-orbit constellation, not every satellite The data collected can determine or even affect the interference source positioning result. Therefore, in the embodiment of the present application, some low-orbit satellites can be selected from the low-orbit satellites in the current system for interference source positioning, so that the interference source positioning accuracy can be guaranteed while reducing the use of perception resources, optimizing the use of perception resources, and flexibly replacing perception resources and communication resources, enhancing the flexibility of system resource allocation.

[0087] It should be pointed out that the various embodiments of the present application can learn from or refer to each other. For example, the same or similar steps, method embodiments, system embodiments and device embodiments can all refer to each other without limitation.

[0088] Figure 3 This is a flow chart of a method for determining a sensing node provided in an embodiment of the present application. Figure 3 As shown, the method comprises the following steps:

[0089] Step 301: When there is signal interference in a target area, the sensing node determination device obtains RSS data of interference sources received by N sensing nodes in the target area.

[0090] In some embodiments, the RSS data is related to the distance between the sensing node and the interference source, that is, the stronger the RSS of the interference source received by the sensing node, the closer the distance between the sensing node and the interference source is. Correspondingly, the weaker the RSS of the interference source received by the sensing node, the farther the distance between the sensing node and the interference source is.

[0091] For example, in a target area with a spatial size of (X, Y, Z), there are N sensing nodes, and the location set of the sensing nodes can be obtained by Indicates that the RSS data of N sensing nodes can be obtained through {D1,D2,...,D n ,D N}, taking a single interference source as an example, the estimated position of the interference source can be expressed as ξ', and the distance vector from the nth sensing node to the interference source can be expressed as d n .

[0092] In some embodiments, the RSS data satisfies the following Formula 1:

[0093]

[0094] Among them, D n is the RSS data of the nth sensing node, ρ represents the path loss factor, |d n | is the distance between the nth sensing node and the interference source, σ n Represents the noise error, with a mean of 0 and a variance of δ n =λ n 2 Gaussian distribution, C0 is the average RSS received by the sensing node at the reference distance d0.

[0095] It should be understood that d in the above formula 1 n is a variable and the other parameters are constants, so the above formula 1 can be adjusted in the following way.

[0096] In some embodiments, RSS data satisfies the following formula 2:

[0097] D n =c1ln|d n |+c2+σ n Formula 2

[0098] For the relevant parameters, please refer to the description of the above formula 1.

[0099] In some embodiments, the number of interference sources may be one or more. When the number of interference sources is more than one, the sensing node may receive RSS data of each interference source, and the sensing node determination device may obtain RSS data of each interference source from N sensing nodes in the target area.

[0100] Step 302: The sensing node determination device uses M sensing nodes among the N sensing nodes as nodes for locating interference sources based on RSS data.

[0101] Among them, the positioning accuracy of the M sensing nodes for the interference source is greater than the accuracy threshold, N is a positive integer, and M is a positive integer less than N.

[0102] In one example, the sensing node determination device can select a sensing node with a higher signal strength for the interference source from the N sensing nodes based on the RSS data for interference source location. Since the RSS is related to the distance between the sensing node and the interference source, that is, the distance between the sensing node with a higher signal strength and the interference source is closer, the interference source location can be ensured by using a closer sensing node to ensure the accuracy of the interference source location, while reducing the number of nodes used for interference source location can avoid communication being affected.

[0103] In another example, the sensing node determination device may determine the positioning accuracy of the sensing node for the interference source based on the RSS data, and select M sensing nodes from N sensing nodes to locate the interference source according to the positioning accuracy, thereby achieving optimal allocation of resources.

[0104] Based on the above technical solution, when there is signal interference in the target area, the sensing node determination device can obtain the RSS data of the interference source received by the N sensing nodes in the target area, and based on the RSS data, use M sensing nodes among the N sensing nodes as nodes for locating the interference source. Among them, the positioning accuracy of the M sensing nodes for the interference source is greater than the accuracy threshold, N is a positive integer, and M is a positive integer less than N. In this way, the present application can reduce the number of sensing nodes used for perception from N to M while meeting the interference perception requirements, thereby reducing the number of sensing nodes used for positioning perception, thereby reducing the use of sensing resources and improving resource utilization, so as to avoid affecting the normal communication of the communication system, and can meet the communication requirements and interference perception requirements at the same time.

[0105] As a possible embodiment, the accuracy threshold is determined by the positioning accuracy and accuracy coefficient of the N sensing nodes for the interference source, and the positioning accuracy of the multiple sensing nodes for the interference source is determined by the RSS data of the interference source received by the multiple sensing nodes.

[0106] In some embodiments, combined with the above formula 2, the noise errors of each sensing node are uncorrelated, so φ can be n =c1ln|d n |+c2, at this time, the positioning accuracy of multiple sensing nodes for the interference source satisfies the following formula 3:

[0107]

[0108] Where |F| is the positioning accuracy, P is the number of multiple sensing nodes, and ξ' represents the estimated location of the interference source. Represented as φ n Jacobian matrix of the partial derivatives of ξ'.

[0109] Exemplarily, the above formula 3 can be generated by Fisher information matrix (FIM). The positioning accuracy of any combination of N sensing nodes can be obtained by the above formula 3. Similarly, when there are multiple interference sources, the positioning accuracy for each interference source can be determined by the above formula 3.

[0110] In some embodiments, combined with the above formula 3, let At this time, the positioning accuracy of multiple sensing nodes for the interference source satisfies the following formula 4:

[0111]

[0112] Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, e n is the unit direction vector of the nth sensing node pointing to the interference source, λ n is the standard deviation of the noise error, |d n | is the distance between the nth sensing node and the interference source, and ρ represents the path loss factor.

[0113] Based on the above formula 3 or formula 4, when the interference source is located through N sensing nodes, the positioning accuracy |F| is the largest. When the sensing resource of the sensing node n among the N sensing nodes is not called, that is, D n = 0, the corresponding positioning accuracy |F| decreases. That is to say, when locating the interference source, the more sensing nodes are used for positioning, the higher the corresponding positioning accuracy. However, there are differences in the sampling data collected by the sensing nodes at different locations, and the arrival time and frequency of the interference signal to the sensing nodes at different locations are also different. As the number of sensing nodes increases, the marginal benefit of positioning accuracy will gradually decrease, resulting in a waste of resources.

[0114] Since there are a large number of sensing nodes in a target area, not every sensing node’s sensing data has a critical impact on the sensing result. At the same time, using all sensing nodes for interference source positioning will also affect the normal communication of the target area. Therefore, within the range allowed by the system accuracy, the resource call of the sensing nodes can be appropriately reduced to improve efficiency.

[0115] In some embodiments, the accuracy threshold satisfies the following formula 5:

[0116] A=α|F| max Formula 5

[0117] Among them, α is the precision coefficient, |F| max is the positioning accuracy of the N sensing nodes for the interference source. The accuracy coefficient can be adjusted according to the actual situation, and this application does not limit this. For example, the accuracy coefficient can be α=0.9.

[0118] Based on the above technical solution, the positioning accuracy in the present application can be evaluated by RSS data. In this way, the sensing node determination device can determine the positioning accuracy corresponding to multiple sensing nodes through RSS data, so as to select suitable M sensing nodes from N sensing nodes to locate the interference source.

[0119] As a possible embodiment of the present application, Figure 3 The embodiment shown, as Figure 4 As shown, the above step 302 can be implemented through the following steps 401 to 404.

[0120] Step 401: The sensing node determination device determines the positioning accuracy of the N sensing nodes for the interference source based on the RSS data of the interference source received by the N sensing nodes.

[0121] Exemplarily, the positioning accuracy can be determined by the above formula 3 or formula 4.

[0122] In a possible implementation, the sensing node determination device may determine the distance vector between each sensing node and the interference source based on the RSS data of the interference source received by the N sensing nodes, and further determine the positioning accuracy of the N sensing nodes for the interference source through the distance vector.

[0123] For example, the distance vector d can be obtained by the above formula 1 or formula 2: n , and then determine the positioning accuracy of N sensing nodes to the interference source through Formula 3 or Formula 4.

[0124] Step 402: The sensing node determination device determines an accuracy threshold through the positioning accuracy and accuracy coefficient of N sensing nodes for the interference source.

[0125] Exemplarily, the accuracy threshold can be determined by the above formula 5.

[0126] Step 403: The sensing node determination device determines a plurality of node combinations based on the N sensing nodes.

[0127] The node combination is composed of one or more nodes among the N sensing nodes.

[0128] It should be understood that the above node combination corresponds to a resource deployment solution. Taking M sensing nodes as an example, the corresponding resource deployment solution can be expressed as Among them, e n is the unit direction vector of the nth sensing node pointing to the interference source.

[0129] Step 404: The sensing node determination device uses the sensing node of the target combination among the multiple node combinations as a node for locating the interference source according to the accuracy threshold.

[0130] Among them, the target combination consists of M sensing nodes.

[0131] In some embodiments, the target combination satisfies the resource usage condition.

[0132] Exemplarily, the resource usage conditions include:

[0133] The node combination whose positioning accuracy is greater than the accuracy threshold and whose corresponding sensing resource usage is the least among multiple node combinations.

[0134] Exemplarily, the resource deployment scheme corresponding to the target combination satisfies the following formula 6

[0135]

[0136] Among them, e n is the unit direction vector of the nth sensing node pointing to the interference source, and M is the number of sensing nodes in the node combination that meets the accuracy threshold A and has the least usage of corresponding sensing resources.

[0137] Exemplarily, in the present application, the sensing node determination device can select M sensing nodes from N sensing nodes through a traversal algorithm to locate the interference source. Figure 5 As shown, the traversal algorithm includes the following steps:

[0138] Step 501: The sensing node determination device obtains sensing information of N sensing nodes and algorithm parameters of the traversal algorithm.

[0139] The sensing information of the sensing node includes the location information of the sensing node, RSS data, the initial estimated location of the interference source, etc. The algorithm parameters of the traversal algorithm include the prior parameter c1 and the accuracy coefficient α, etc.

[0140] The interference source may be one or more. Taking K interference sources as an example, the initial estimated positions of K interference sources can be expressed as The positions of N sensor nodes can be expressed as

[0141] Step 502: The sensing node determination device calculates the positioning accuracy of N sensing nodes for the interference source.

[0142] The positioning accuracy at this time is the positioning accuracy when the sensing resources are not released. The sensing node determination device can calculate the positioning accuracy through the various parameters obtained in step 501.

[0143] Step 503: The sensing node determination device traverses each sensing node among the currently selected multiple sensing nodes and releases the sensing resources of the sensing node.

[0144] For example, during the first round of traversal, the sensing node determination device releases the sensing resources of each sensing node from the N sensing nodes one by one, thereby obtaining N node combinations.

[0145] Step 504: The sensing node determination device calculates the corresponding positioning accuracy after the sensing resources are currently released.

[0146] For example, in the first round of traversal, the sensing node determination device sets the RSS data D of the currently selected sensing node to 0 during traversal, and calculates the positioning accuracy |F| at this time, thereby obtaining a resource deployment plan when the sensing node is removed.

[0147] Step 505: The sensing node determination device determines whether the positioning accuracy |F| at this time is greater than or equal to the accuracy threshold α|F| max .

[0148] When the value is greater than or equal to the accuracy threshold, the sensing node determination device executes the following step 506 .

[0149] Step 506: The sensing node determination device releases the sensing resources of the selected sensing node according to the current resource deployment plan.

[0150] Afterwards, the sensing node device executes the above step 503 according to the combination after releasing the sensing node, and continues the second round of traversal process.

[0151] When the accuracy is less than the threshold, the sensing node determination device executes the following step 507 .

[0152] Step 507: The sensing node determination device outputs the resource deployment plan with the highest positioning accuracy obtained in the previous round of traversal.

[0153] In the current traversal process, there is no longer any position that satisfies the positioning accuracy |F| greater than or equal to the accuracy threshold αF max When a resource deployment plan is found, it means that further optimization is no longer possible. Therefore, the resource deployment plan with the highest positioning accuracy in the previous round of traversal is the optimal deployment plan.

[0154] In addition, the above process takes one interference source as an example. When there are multiple interference sources, the perception node determination device can perform calculations for each interference source separately to obtain the corresponding positioning accuracy, and perform the above traversal process. When the positioning accuracy corresponding to each interference source meets the above conditions, a deployment plan is determined that can ensure the positioning accuracy of each interference source and release more resources for communication.

[0155] The embodiment of the present application can divide the perception node determination device into functional modules or functional units according to the above method example. For example, each functional module or functional unit can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules or functional units. Among them, the division of modules or units in the embodiment of the present application is schematic, which is only a logical function division. There may be other division methods in actual implementation.

[0156] Figure 6 The structure diagram of a sensing node determination device 60 is shown. The sensing node determination device 60 comprises:

[0157] The communication unit 602 is used to obtain received signal strength RSS data of the interference source received by N sensing nodes in the target area when there is signal interference in the target area;

[0158] The processing unit 601 is used to use M sensing nodes among N sensing nodes as nodes for locating interference sources based on RSS data; the positioning accuracy of the M sensing nodes for the interference source is greater than the accuracy threshold; N is a positive integer, and M is a positive integer less than N.

[0159] In a possible implementation, the accuracy threshold is determined by the positioning accuracy and accuracy coefficient of the N sensing nodes for the interference source; the positioning accuracy of the multiple sensing nodes for the interference source is determined by the RSS data of the interference source received by the multiple sensing nodes.

[0160] In one possible implementation, the processing unit 601 is used to: determine the positioning accuracy of the N sensing nodes for the interference source based on the RSS data of the interference source received by the N sensing nodes; determine the accuracy threshold through the positioning accuracy of the N sensing nodes for the interference source and the accuracy coefficient; determine multiple node combinations based on the N sensing nodes; the node combination is composed of one or more nodes among the N sensing nodes; according to the accuracy threshold, the sensing nodes of the target combination in the multiple node combinations are used as nodes for locating the interference source; the target combination is composed of M sensing nodes.

[0161] In a possible implementation manner, the target combination satisfies the resource usage condition.

[0162] In a possible implementation, the resource usage condition includes:

[0163] The node combination whose positioning accuracy is greater than the accuracy threshold and whose corresponding sensing resource usage is the least among multiple node combinations.

[0164] In a possible implementation, the RSS data satisfies the following formula:

[0165]

[0166] Among them, D n is the RSS data of the nth sensing node, ρ represents the path loss factor, |d n | is the distance between the nth sensing node and the interference source; σ n Represents the noise error, with a mean of 0 and a variance of δ n =λ n 2 Gaussian distribution, C0 is the average RSS received by the sensing node at the reference distance d0;

[0167] The positioning accuracy of multiple sensing nodes for interference sources satisfies the following formula:

[0168]

[0169] Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, ξ' represents the estimated position of the interference source; φ n =c1ln|d n |+c2, |d n | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor, C0 is the average RSS received by the sensing node at the reference distance d0;

[0170] Alternatively, the positioning accuracy of multiple sensing nodes for interference sources satisfies the following formula:

[0171]

[0172] Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, e n is the unit direction vector of the nth sensing node pointing to the interference source, λ n is the standard deviation of the noise error, |d n | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor;

[0173] The accuracy threshold satisfies the following formula:

[0174] A=α|F| max

[0175] Among them, α is the precision coefficient, |F| max is the positioning accuracy of N sensing nodes for the interference source.

[0176] When implemented by hardware, the communication unit in the embodiment of the present application can be integrated on the communication interface, and the processing unit can be integrated on the processor. Figure 7 shown.

[0177] Figure 7 Another possible structural diagram of the sensing node determination device involved in the above embodiment is shown. The sensing node determination device 70 includes: a processor 702 and a communication interface 703. The processor 702 is used to control and manage the actions of the sensing node determination device 70. The communication interface 703 is used to support the communication between the sensing node determination device 70 and other network entities. The sensing node determination device 70 may also include a memory 701 and a bus 704, and the memory 701 is used to store program codes and data of the sensing node determination device 70.

[0178] Among them, the memory 701 can be a memory in the perception node determination device 70, etc., and the memory may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a read-only memory, a flash memory, a hard disk or a solid-state drive; the memory may also include a combination of the above types of memory.

[0179] The processor 702 may be a processor that implements or executes various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of the present application. The processor 702 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of the present application. The processor 702 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0180] The bus 704 may be an Extended Industry Standard Architecture (EISA) bus, etc. The bus 704 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0181] Figure 7 The sensing node determination device 70 in the embodiment may also be a chip. The chip includes one or more than two (including two) processors 702 and a communication interface 703.

[0182] In some embodiments, the chip further includes a memory 701, which may include a read-only memory and a random access memory and provide operation instructions and data to the processor 702. A portion of the memory 701 may also include a non-volatile random access memory (NVRAM).

[0183] In some implementations, the memory 701 stores the following elements, execution modules or data structures, or a subset thereof, or an extended set thereof.

[0184] In the embodiment of the present application, the corresponding operation is performed by calling the operation instruction stored in the memory 701 (the operation instruction may be stored in the operating system).

[0185] Through the description of the above implementation methods, technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0186] An embodiment of the present application provides a computer program product comprising instructions. When the computer program product is run on a computer, the computer is enabled to execute the perception node determination method in the above method embodiment.

[0187] An embodiment of the present application also provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a computer, the computer executes the perception node determination method in the method flow shown in the above method embodiment.

[0188] Among them, the computer readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0189] Since the perception node determination device, computer-readable storage medium, and computer program product in the embodiments of the present application can be applied to the above-mentioned method, the technical effects that can be obtained can also refer to the above-mentioned method embodiments, and the embodiments of the present application will not be repeated here.

[0190] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0193] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for determining a sensing node, characterized in that: The method comprises: In the case where there is signal interference in the target area, obtaining received signal strength RSS data of the interference source received by N sensing nodes in the target area; Based on the RSS data, M sensing nodes among the N sensing nodes are used as nodes for locating interference sources; the positioning accuracy of the M sensing nodes for the interference source is greater than an accuracy threshold; N is a positive integer, and M is a positive integer less than N.

2. The method according to claim 1, characterized in that The accuracy threshold is determined by the positioning accuracy and accuracy coefficient of the N sensing nodes for the interference source; the positioning accuracy of multiple sensing nodes for the interference source is determined by the RSS data of the interference source received by the multiple sensing nodes.

3. The method according to claim 2, characterized in that The method of using M sensing nodes among the N sensing nodes as nodes for locating interference sources based on the RSS data includes: Determine the positioning accuracy of the N sensing nodes for the interference source based on the RSS data of the interference source received by the N sensing nodes; Determine the accuracy threshold by the positioning accuracy and accuracy coefficient of the N sensing nodes for the interference source; Determine a plurality of node combinations based on the N sensing nodes; the node combinations are composed of one or more nodes among the N sensing nodes; According to the accuracy threshold, the sensing nodes of the target combination among the multiple node combinations are used as nodes for locating interference sources; the target combination is composed of the M sensing nodes.

4. The method according to claim 3, characterized in that: The target combination satisfies the resource usage condition.

5. The method according to claim 4, characterized in that The resource use conditions include: A node combination among the multiple node combinations whose positioning accuracy is greater than the accuracy threshold and whose corresponding usage of perception resources is the least.

6. The method according to claim 2, characterized in that The RSS data satisfies the following formula: Among them, D n is the RSS data of the nth sensing node, ρ represents the path loss factor, |d n | is the distance between the nth sensing node and the interference source; σ n Represents the noise error, with a mean of 0 and a variance of δ n =λ n 2 Gaussian distribution, C0 is the average RSS received by the sensing node at the reference distance d0; The positioning accuracy of the multiple sensing nodes for the interference source satisfies the following formula: Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, ξ' represents the estimated position of the interference source; φ n =c1 ln|d n |+c2, |d n | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor, C0 is the average RSS received by the sensing node at the reference distance d0; Alternatively, the positioning accuracy of the multiple sensing nodes for the interference source satisfies the following formula: Among them, |F| is the positioning accuracy, P is the number of multiple sensing nodes, e n is the unit direction vector of the nth sensing node pointing to the interference source, λ n is the standard deviation of the noise error, |d n | is the distance between the nth sensing node and the interference source; ρ represents the path loss factor; The accuracy threshold satisfies the following formula: A=α|F| max Where α is the precision coefficient, |F| max is the positioning accuracy of the N sensing nodes for the interference source.

7. A sensing node determination device, characterized in that: including a processing unit and a communication unit; The communication unit is used to obtain received signal strength RSS data of interference sources received by N sensing nodes in the target area when there is signal interference in the target area; The processing unit is used to use M of the N sensing nodes as nodes for locating interference sources based on the RSS data; the positioning accuracy of the M sensing nodes for the interference source is greater than an accuracy threshold; N is a positive integer, and M is a positive integer less than N.

8. A sensing node determination device, characterized in that: include: A processor and a communication interface; the communication interface is coupled to the processor, and the processor is used to run a computer program or instruction to implement the perception node determination method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions. When a computer executes the instructions, the computer executes the perception node determination method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product comprises computer program instructions, and when the computer program instructions are executed by a processor, the method for determining a perception node according to any one of claims 1 to 6 is implemented.

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