Hidden terminal identification method and device based on multi-dimensional network feature analysis, equipment and storage medium

Abstract

The application discloses a hidden terminal identification method and device based on multi-dimensional network feature analysis, equipment and storage medium, relates to the technical field of communication, and the method comprises the steps of collecting network state data of a plurality of associated terminals based on the network access equipment; using a preset sliding time window to analyze the network state data, identifying at least one potential victim terminal from the plurality of associated terminals; according to the network state data, performing network conflict correlation analysis on the potential victim terminal, and determining at least one potential interference terminal from the plurality of associated terminals; using the adjacent network access equipment to perform network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals. The application improves the accuracy of hidden terminal identification through the above scheme, and avoids the huge protocol overhead of the RTS / CTS mechanism of the associated terminal.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus, device and storage medium for identifying hidden terminals based on multidimensional network feature analysis. Background Technology

[0002] In wireless LANs, the problem of hidden terminals has long constrained network performance. Traditional solutions rely on globally enabling RTS / CTS (Request to Send / Clear to Send) mechanisms or making inferences based on statistics of packet loss rate and retransmission rate to attempt to solve or identify the hidden terminal problem.

[0003] However, traditional solutions have the following problems: the RTS / CTS mechanism introduces significant protocol overhead, reduces the overall network throughput, and the RTS / CTS mechanism can only avoid the hidden terminal problem, but cannot identify the hidden terminal; methods that rely on packet loss rate and retransmission rate cannot distinguish between hidden terminal collisions and physical layer interference (such as signal interference and multipath fading), resulting in a high false positive rate.

[0004] Therefore, it is necessary to propose a hidden terminal identification method to improve the accuracy of hidden terminal identification.

[0005] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main objective of this application is to provide a method, apparatus, device, and storage medium for identifying hidden terminals based on multidimensional network feature analysis, aiming to solve the technical problem of how to improve the accuracy of hidden terminal identification.

[0007] To achieve the above objectives, this application proposes a hidden terminal identification method based on multidimensional network feature analysis. The hidden terminal identification method is applied to a wireless local area network (WLAN), which includes at least one network access device. The hidden terminal identification method includes:

[0008] Based on the network access device, network status data of several associated terminals are collected, and the network status data includes network feature data of multiple dimensions.

[0009] The network status data is analyzed using a preset sliding time window to identify at least one potential victim terminal from the plurality of associated terminals;

[0010] Based on the network status data, a network conflict correlation analysis is performed on the potential victim terminals to identify at least one potential interference terminal from among the associated terminals.

[0011] The potential victim terminal and the potential interference terminal are monitored by a nearby network access device to verify whether they are hidden terminals.

[0012] In one embodiment, the step of analyzing the network status data using a preset sliding time window to identify at least one potential victim terminal from the plurality of associated terminals includes:

[0013] For any associated terminal, determine the network status data of the associated terminal within the preset sliding time window;

[0014] When the network status data of the associated terminal within the preset sliding time window meets the preset conditions, the associated terminal is determined to be a potential victim terminal.

[0015] In one embodiment, the network status data includes received signal strength, negotiation rate, retransmission rate, and error statistics. The preset conditions are that the received signal strength of the associated terminal within the preset sliding time window is greater than a first preset threshold, the negotiation rate is greater than a second preset threshold, the retransmission rate is greater than a third preset threshold, and the error statistics are greater than a fourth preset threshold.

[0016] The error statistics include at least one of the following: physical layer error count, fragmentation error rate, and ACK timeout count.

[0017] In one embodiment, the step of performing network conflict correlation analysis on the potential victim terminals based on the network status data, and determining at least one potential interfering terminal from the plurality of associated terminals, includes:

[0018] Based on the network status data of the potential victim terminal within the preset sliding time window, several first moments in which the performance degradation event of the potential victim terminal occurs are determined.

[0019] For any associated terminal, based on the network status data of the associated terminal within the preset sliding time window, several second moments in which the associated terminal exhibits transmission behavior are determined;

[0020] Determine the time overlap between the plurality of first moments and the plurality of second moments;

[0021] When the received signal strength of both the network access device and the associated terminal is greater than a first preset threshold and the time overlap is higher than a preset overlap threshold, the associated terminal is determined to be the potential interference terminal.

[0022] In one embodiment, the step of using a proximity network access device to perform network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals includes:

[0023] The gateway device instructs the nearby network access device to enter listening mode;

[0024] When the neighboring network access device detects the uplink messages between the potential victim terminal and the potential interference terminal, it confirms whether there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal.

[0025] When there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal, the potential victim terminal and the potential interference terminal are determined to be hidden terminals.

[0026] In one embodiment, after the step of performing network conflict correlation analysis on the potential victim terminals based on the network state data to determine at least one potential interfering terminal from the plurality of associated terminals, the method further includes:

[0027] The potential victim terminal is enabled through a conflict avoidance mechanism via a gateway device.

[0028] If the retransmission rate of the potential victim terminal decreases by more than a preset decrease threshold after the conflict avoidance mechanism is activated, then the potential victim terminal and the potential interference terminal are determined to be hidden terminals.

[0029] In one embodiment, after determining that the potential victim terminal and the potential interference terminal are hidden terminals, the method further includes:

[0030] Construct an interference topology view of the wireless local area network based on the hidden terminal;

[0031] The wireless LAN is optimized based on the interference topology view of the wireless LAN.

[0032] Furthermore, to achieve the above objectives, this application also provides a hidden terminal identification device, which is applied to a wireless local area network (WLAN) including at least one network access device. The hidden terminal identification device includes:

[0033] The data acquisition module is used to collect network status data of several associated terminals based on the network access device. The network status data includes network feature data in multiple dimensions.

[0034] The identification module is used to analyze the network status data using a preset sliding time window and identify at least one potential victim terminal from the plurality of associated terminals.

[0035] The determination module is used to perform network conflict correlation analysis on the potential victim terminals based on the network status data, and determine at least one potential interference terminal from the plurality of associated terminals.

[0036] The verification module is used to use a nearby network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal in order to verify whether the potential victim terminal and the potential interference terminal are hidden terminals.

[0037] In addition, to achieve the above objectives, this application also provides a hidden terminal identification device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the hidden terminal identification method as described above.

[0038] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the hidden terminal identification method described above.

[0039] One or more technical solutions proposed in this application have at least the following technical effects:

[0040] The hidden terminal identification method, apparatus, device, and storage medium based on multi-dimensional network feature analysis proposed in this application specifically involves: collecting network status data of several associated terminals based on the network access device, wherein the network status data includes network feature data of multiple dimensions; analyzing the network status data using a preset sliding time window to identify at least one potential victim terminal from the several associated terminals; performing network conflict correlation analysis on the potential victim terminal based on the network status data to determine at least one potential interference terminal from the several associated terminals; and using a nearby network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals.

[0041] This application collects network status data of associated terminals in real time through network access devices, and then uses a sliding time window to identify potential victim terminals with good signal quality but abnormal transmission performance. Then, through the potential victim terminals, it identifies potential interference terminals that are strongly correlated with the victim terminals from several associated terminals. Furthermore, it uses nearby network access devices to monitor the networks of potential victim terminals and potential interference terminals to verify whether they are hidden terminals. This improves the accuracy of hidden terminal identification and avoids the huge protocol overhead of associated terminals enabling RTS / CTS mechanisms. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating an embodiment of the hidden terminal identification method based on multidimensional network feature analysis provided in this application.

[0045] Figure 2 This is a flowchart illustrating Embodiment 2 of the hidden terminal identification method based on multidimensional network feature analysis provided in this application;

[0046] Figure 3 This is a flowchart illustrating Embodiment 3 of the hidden terminal identification method based on multidimensional network feature analysis provided in this application;

[0047] Figure 4 This is a flowchart illustrating Embodiment 4 of the Hidden Terminal Identification Method Based on Multidimensional Network Feature Analysis of this application;

[0048] Figure 5 This is a schematic diagram of the module structure of the hidden terminal identification device according to an embodiment of this application;

[0049] Figure 6 This is a schematic diagram of the device structure of the hardware operating environment involved in the hidden terminal identification method in this application embodiment.

[0050] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0051] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0052] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0053] The main solution of this application embodiment is as follows: Based on the network access device, network status data of several associated terminals are collected, and the network status data includes network feature data of multiple dimensions; the network status data is analyzed using a preset sliding time window to identify at least one potential victim terminal from the several associated terminals; based on the network status data, network conflict correlation analysis is performed on the potential victim terminal to determine at least one potential interference terminal from the several associated terminals; and a nearby network access device is used to conduct network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals.

[0054] Technical terms used in this application:

[0055] RTS / CTS (Request to Send / Clear to Send) mechanism: The RTS / CTS mechanism is a collision avoidance mechanism used in wireless local area networks (such as Wi-Fi). Before sending actual data, the sending node broadcasts a short RTS frame. Upon receiving this, the target receiving node responds with a CTS frame. This CTS frame is listened to by all nodes within the communication range, essentially acting as a "channel occupancy" announcement, informing neighboring nodes to remain silent temporarily, thereby reserving dedicated channel space for the upcoming data transmission.

[0056] In this embodiment, for ease of description, the hidden terminal identification device will be used as the execution subject in the following description.

[0057] In a wireless LAN, a hidden terminal refers to another transmitting node (such as STA B) that is within the coverage area of ​​a receiving node (such as an AP) but not within the coverage area of ​​a transmitting node (such as STA A).

[0058] In wireless LANs, the problem of hidden terminals has long constrained network performance. Traditional solutions rely on globally enabling RTS / CTS (Request to Send / Clear to Send) mechanisms or making inferences based on statistics of packet loss rate and retransmission rate to attempt to solve or identify the hidden terminal problem.

[0059] However, traditional solutions have the following problems: the RTS / CTS mechanism introduces significant protocol overhead, reduces the overall network throughput, and the RTS / CTS mechanism can only avoid the hidden terminal problem, but cannot identify the hidden terminal; methods that rely on packet loss rate and retransmission rate cannot distinguish between hidden terminal collisions and physical layer interference (such as signal interference and multipath fading), resulting in a high false positive rate.

[0060] Therefore, it is necessary to propose a hidden terminal identification method to improve the accuracy of hidden terminal identification.

[0061] This application provides a solution that collects network status data of associated terminals in real time through network access devices, then uses a sliding time window to identify potential victim terminals with good signal quality but abnormal transmission performance. Based on these potential victim terminals, potential interference terminals strongly correlated with the victim terminals are identified from a number of associated terminals. Furthermore, network monitoring of the potential victim terminals and potential interference terminals is conducted using nearby network access devices to verify whether they are hidden terminals. This improves the accuracy of hidden terminal identification while avoiding the significant protocol overhead of enabling RTS / CTS mechanisms on associated terminals.

[0062] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or hidden terminal identification device capable of performing the above functions. The following description uses a hidden terminal identification device as an example to illustrate this embodiment and the subsequent embodiments.

[0063] Based on this, embodiments of this application provide a hidden terminal identification method based on multidimensional network feature analysis, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the hidden terminal identification method of this application. The hidden terminal identification method is applied to a wireless local area network (WLAN), which includes at least one network access device. The hidden terminal identification method includes steps S110 to S140:

[0064] Step S110: Based on the network access device, collect network status data of several associated terminals, the network status data including network feature data of multiple dimensions;

[0065] It should be noted that this application proposes a method for solving the problem of identifying hidden terminals in wireless local area networks (WLANs). Therefore, the hidden terminal identification method involved in this application is applied to WLANs, which refer to computer network systems that use wireless communication technology to interconnect terminal devices and between terminal devices and the network, such as Wi-Fi (Wireless Fidelity) network systems.

[0066] Within a wireless local area network (WLAN), terminal devices need to communicate with each other through network access devices. Therefore, network access devices establish wireless connections with terminal devices, and multiple terminal devices are associated with a single network access device. A network access device refers to a device in a WLAN that provides network access functionality, including but not limited to access points (APs) conforming to standard communication protocols. Associated terminals are terminal devices that have established a wireless connection with the network access device and possess data transmission capabilities, such as smartphones, IoT sensors, or laptops. Associated terminals can be considered as STAs (Stations, clients) in the wireless network.

[0067] To locate hidden terminals within a wireless local area network (WLAN), the hidden terminal identification device needs to collect network status data from several associated terminals using a network access device. Specifically, the network access device continuously acquires network status data from each associated terminal device at a preset sampling frequency. This network status data includes multi-dimensional network characteristic data, which is then analyzed to identify the hidden terminals. The network status data refers to various data information reflecting the communication status of each terminal device associated with the network access device, including but not limited to the terminal device's Received Signal Strength Indication (RSSI), Signal-to-Noise Ratio (SNR), Tx / Rx Rate, packet retransmission count, and identification information (such as Media Access Control address).

[0068] Optionally, the network status data includes received signal strength, negotiation rate, retransmission rate, and error statistics. Optionally, the error statistics include at least one of physical layer error count, fragmentation error rate, and ACK timeout count.

[0069] Among them, received signal strength refers to the power intensity of the signal transmitted by the terminal reaching the network access device (such as AP), which is used to measure the quality of the terminal's transmitted signal.

[0070] The negotiation rate is the theoretical maximum transmission rate that the terminal and the AP dynamically negotiate based on channel quality. It is used to reflect the link negotiation capability between the terminal and the AP.

[0071] Physical layer error count refers to the number of physical layer decoding failures, reflecting the reliability of physical layer transmission.

[0072] Fragmentation error rate refers to the proportion of fragments that fail to pass verification during fragmented transmission.

[0073] The ACK (Acknowledgement) timeout count refers to the number of times data is sent without receiving an ACK from the receiver.

[0074] The retry rate is the proportion of data packets that are retransmitted after a failed transmission out of the total number of packets sent.

[0075] Signal-to-noise ratio (SNR) is the ratio of effective signal power to background noise power, reflecting the "cleanliness" of the signal.

[0076] Understandably, the collected data metrics need to include high-precision collection timestamps for subsequent data analysis.

[0077] Step S120: Analyze the network status data using a preset sliding time window to identify at least one potential victim terminal from the plurality of associated terminals;

[0078] Then, in order to select the hidden terminal from all associated terminals, the hidden terminal identification device needs to find "suspected victims," ​​or potential victim terminals, that may be affected by the hidden terminal problem. Specifically, this is done by maintaining a fixed-duration (e.g., 10 seconds) preset time window for each associated terminal, which is updated over time according to a preset step size. By analyzing the network status data of each associated terminal within the preset time window, potential victim terminals with good signal quality but abnormal transmission performance can be identified. Here, the step size refers to the time interval by which the window moves forward along the time axis each time.

[0079] In one implementable manner, step S120 includes steps A1-A2:

[0080] Step A1: For any associated terminal, determine the network status data of the associated terminal within the preset sliding time window;

[0081] Step A2: When the network status data of the associated terminal within the preset sliding time window meets the preset conditions, the associated terminal is determined to be a potential victim terminal.

[0082] In this embodiment, for any associated terminal, a preset time window with a fixed duration (e.g., 10 seconds) is maintained for the associated terminal and is updated over time according to a preset step size. Then, the network status data of the associated terminal within the preset sliding time window is determined.

[0083] When the network status data of an associated terminal meets preset conditions within a preset sliding time window, the associated terminal is identified as a potential victim terminal. The preset conditions refer to multi-dimensional threshold rules for determining potential victim terminals.

[0084] Optionally, the preset conditions include the following three types of conditions:

[0085] Signal quality condition: The received signal strength of the associated terminal within the preset sliding time window is greater than a first preset threshold;

[0086] Transmission anomaly condition: The negotiation rate of the associated terminal within the preset sliding time window is greater than the second preset threshold;

[0087] Physical layer error conditions: The retransmission rate of the associated terminal within the preset sliding time window is greater than the third preset threshold, and the error statistics index is greater than the fourth preset threshold.

[0088] Understandably, error statistics include at least one of the following: physical layer error count, fragmentation error rate, and ACK timeout count. Each error statistic corresponds to a fourth preset threshold used for conditional judgment. Therefore, as long as any one of the physical layer error count, fragmentation error rate, or ACK timeout count is greater than its corresponding fourth preset threshold, the physical layer error condition of "error statistics exceeding the fourth preset threshold" is met. The fourth preset threshold corresponding to each error statistic can be the same or different.

[0089] Specifically, when the network status data of the associated terminal meets the signal quality conditions within the preset sliding time window, it means that the received signal strength of the terminal is higher than the first preset threshold, indicating that the signal link quality between the terminal and the AP is good, and eliminating the possibility of transmission problems caused by weak signal.

[0090] When the network status data of the associated terminal meets the transmission anomaly conditions within the preset sliding time window, it means that the terminal's negotiation rate is higher than the second preset threshold, further confirming that the link quality is good and eliminating the possibility of low transmission efficiency caused by poor link negotiation capability.

[0091] When the retransmission rate of the associated terminal within the preset sliding time window is greater than the third preset threshold, it indicates that the retransmission rate of the terminal is abnormally high, which is a direct manifestation of the terminal's degraded transmission performance.

[0092] When the error statistics of the associated terminal within the preset sliding time window are greater than the fourth preset threshold, it means that the physical layer error count of the associated terminal within the preset sliding time window is greater than its corresponding fourth preset threshold (e.g., threshold {phy error count}) and / or the fragmentation error rate is greater than its corresponding fourth preset threshold (e.g., threshold {fragment error}) and / or the ACK timeout count (e.g., threshold {ack timeout}) and thus it indicates that the AP air interface has detected an abnormally high number of error frames, indicating that the data frame was damaged due to collision or interference during transmission.

[0093] When a hidden terminal starts sending data in the middle of a data frame transmission, it causes waveform superposition and distortion. The AP's physical layer chip cannot parse the subsequent bit stream, resulting in a physical error count. If the hidden terminal has a fragmentation mechanism enabled, the hidden terminal collision may only destroy one fragment, causing fragmentation verification to fail. When a hidden terminal collision occurs at the end of a frame or directly interferes with the ACK frame returned by the AP, the sender will record an ACK timeout because it cannot receive an acknowledgment. Due to the dynamic nature of the Wi-Fi network environment, a single hidden terminal collision may not necessarily trigger the above errors simultaneously. Therefore, it is only necessary to ensure that the error statistics of the associated terminal within the preset sliding time window are greater than the fourth preset threshold to ensure that hidden terminal collisions can be effectively identified.

[0094] Step S130: Based on the network status data, perform network conflict correlation analysis on the potential victim terminals to identify at least one potential interference terminal from the plurality of associated terminals.

[0095] It should be noted that a potential interfering terminal refers to other associated terminal devices identified as potentially causing interference or conflict with a potential victim terminal. The communication behavior of a potential interfering terminal (such as channel occupancy, data transmission timing, etc.) has a temporal correlation or logical causal relationship with the performance degradation of the potential victim terminal.

[0096] After identifying potential victim terminals, the hidden terminal identification device can further utilize the network status data of each associated terminal. By comparing and analyzing the network status data of the potential victim terminal within a specific time period (such as performance degradation time points, packet loss time distribution, etc.) with the network status data of other associated terminals within the same time period, it can determine whether there is a network conflict between the other associated terminals and the potential victim terminal, and thus identify at least one potential interference terminal from several associated terminals.

[0097] Step S140: Use a nearby network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals.

[0098] It should be noted that neighboring network access devices refer to other network access devices that are physically adjacent to or close to the current network access device within the wireless LAN, and whose wireless coverage overlaps with that of the current network access device.

[0099] To further verify whether the identified potential victim terminals and potential interference terminals are each other's hidden terminals, the hidden terminal identification device can use a nearby network access device to conduct network monitoring on the potential victim terminals and potential interference terminals. By confirming whether the potential victim terminals and potential interference terminals can both communicate directly with the network access device, but cannot directly hear each other's transmission signals, it can be verified whether the potential victim terminals and the potential interference terminals constitute a hidden terminal relationship and belong to a hidden terminal pair within the wireless local area network.

[0100] This application, through the aforementioned scheme, collects network status data of associated terminals in real time via network access devices. Then, it uses a sliding time window to identify potential victim terminals with good signal quality but abnormal transmission performance. Furthermore, based on these potential victim terminals, it identifies potential interference terminals strongly correlated with the victim terminals from among several associated terminals. Additionally, it uses nearby network access devices to monitor the networks of potential victim terminals and potential interference terminals to verify whether they are hidden terminals. This improves the accuracy of hidden terminal identification while avoiding the significant protocol overhead of enabling RTS / CTS mechanisms on associated terminals.

[0101] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the hidden terminal identification method of this application. The step of performing network conflict correlation analysis on the potential victim terminals based on the network status data, and determining at least one potential interfering terminal from the plurality of associated terminals, includes steps S210-S240:

[0102] Step S210: Based on the network status data of the potential victim terminal within the preset sliding time window, determine several first moments when the performance degradation event of the potential victim terminal occurs.

[0103] Step S220: For any associated terminal, based on the network status data of the associated terminal within the preset sliding time window, determine several second moments in which the associated terminal exhibits transmission behavior.

[0104] In order to identify potential interfering terminals (such as STA B) that have network conflicts with potential victim terminals (such as STA A), in-depth conflict correlation analysis can be performed using the network status data of the aforementioned associated terminals.

[0105] Specifically, after identifying a potential victim terminal, the system first analyzes the network status data of the potential victim terminal within a preset sliding time window to detect whether the potential victim terminal has experienced a performance degradation event. A performance degradation event refers to an abnormal event where the terminal encounters packet loss, retransmission, or acknowledgment timeout. The precise time point at which the performance degradation event is detected is then recorded as several "first moments".

[0106] Then, by analyzing the network status data of each associated terminal under the network access device within the same sliding time window, it is detected whether each associated terminal has transmission behavior. Transmission behavior refers to the action of a terminal sending uplink data frames to the network access device, including but not limited to the transmission control protocol data packets, address resolution protocol requests, and other payloads. The start time of each transmission behavior is then recorded as several second moments. It is understandable that each associated terminal can have multiple transmission behaviors; therefore, there are multiple corresponding second moments.

[0107] Step S230: Determine the time overlap between the plurality of first moments and the plurality of second moments;

[0108] Specifically, when there is a hidden terminal conflict between STA A and STA B, STA A is interfered with by STA B's transmission when it tries to send or receive signals. This indicates that there is a time competition between the data transmission activities of STA A and STA B. This is reflected in the fact that the packet loss rate (or retransmission rate, ACK timeout count) of STAA always spikes along with the data transmission activities of STAA.

[0109] Furthermore, by analyzing and determining the time overlap between several first moments and several second moments, that is, calculating the degree of overlap between the time when a potential victim terminal experiences packet loss (or high retransmission, ACK timeout, etc.) and the time when other associated terminals send high-throughput data, potential interfering terminals can be further screened from other associated terminals under the network access device.

[0110] Step S240: When the received signal strength of both the network access device and the associated terminal is greater than a first preset threshold and the time overlap is higher than a preset overlap threshold, the associated terminal is determined to be the potential interference terminal.

[0111] Specifically, when the received signal strength of a certain associated terminal is greater than a first preset threshold, the received signal strength of the network access device is also greater than the first preset threshold, the received signal strength of the potential victim terminal is also greater than the first preset threshold, and the time overlap calculated based on several second moments of the associated terminal is higher than a preset overlap threshold, the associated terminal can be determined to be a potential interference terminal.

[0112] Understandably, one potential victim terminal corresponds to at least one potential jamming terminal. Therefore, we can analyze other related terminals to determine at least one potential jamming terminal corresponding to a potential victim terminal.

[0113] Specifically, identifying potential interfering terminals (such as STA B) requires meeting the following conditions:

[0114] 1. STA A is the previously identified potential victim terminal, characterized by good received signal strength, high negotiation rate, and abnormally high retransmission rate.

[0115] 2. Performance degradation events of STA A (such as packet loss, retransmission, ACK timeout) highly overlap with the sending activities of STA B in time.

[0116] 3. The received signal strength of STA A, STA B and the serving AP is good.

[0117] The above-mentioned determination method, based on the fact that the received signal strengths of STA A, STA B and the serving AP are all good, further eliminates the problem of poor signal quality, reinforcing the conclusion that the network conflict is due to media access contention rather than link quality. The fact that the performance degradation events of STA A (such as packet loss, retransmission, ACK timeout) and the transmission activities of STA B highly overlap in time, specifically, for example, that STA A's physical layer error count, fragmentation error rate or ACK timeout count also increases significantly during STA B's transmission period, further corroborates the existence of hidden terminal conflicts.

[0118] The above-mentioned determination method cross-validates the multi-dimensional features of time dimension and network status data, which can accurately distinguish hidden terminal conflicts from other network faults (such as non-Wi-Fi interference, excessive AP load, terminal faults, etc.). It is precisely because other faults usually do not show such specific time correlation and multi-dimensional feature combination that the above-mentioned determination method can accurately identify the potential interfering terminal corresponding to the potential victim terminal.

[0119] This embodiment uses the above-described scheme to extract the transmission behavior time point of the associated terminal (i.e., the first moment) and the performance degradation event time point of the potential victim terminal (i.e., the second moment) based on a preset sliding time window. It then calculates the behavioral correlation by measuring the time overlap between the two. In addition, it combines the received signal strength threshold to eliminate signal attenuation interference. When the time overlap is higher than the preset threshold and the signal quality of both ends meets the standard, the associated terminal can be confirmed as a potential interference terminal, thereby accurately screening out the real interference source.

[0120] Based on the above embodiments of this application, in the third embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3The step of using a nearby network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals further includes steps S310~S330:

[0121] Step S310: Instruct the neighboring network access device to enter monitoring mode via the gateway device;

[0122] It should be noted that a gateway device refers to a network management device in a wireless LAN that has centralized control functions. It is responsible for coordinating the operation of multiple network access devices (such as access points), including wireless gateways, core routers, network controllers, and cloud management platforms. Specifically, the gateway device in the wireless LAN instructs nearby network access devices to enter a listening mode to monitor the signal transmission and reception data of potential victim terminals and potential interference terminals. Listening mode refers to the network access device's configuration of its wireless interface to capture all data frames on the wireless channel (regardless of whether the destination address of the data frame points to the network access device). In this mode, the device does not filter or respond to the captured data frames; it only passively receives signals and records data to obtain comprehensive communication information within its coverage area.

[0123] Step S320: When the neighboring network access device detects the uplink messages between the potential victim terminal and the potential interference terminal, it confirms whether there is a time conflict between the uplink messages between the potential victim terminal and the potential interference terminal.

[0124] Step S330: When there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal, the potential victim terminal and the potential interference terminal are determined to be hidden terminals.

[0125] Specifically, the uplink messages of potential victim terminals and potential interference terminals are monitored by a nearby network access device, and the precise arrival time of these uplink messages is recorded. Here, an uplink message refers to a data frame sent by a terminal to the network access device.

[0126] Then, by determining whether the time difference between the arrival of messages between the potential victim terminal and the potential interference terminal meets the preset time difference threshold, it is confirmed whether there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal.

[0127] Specifically, when the time difference between the arrival of messages between a potential victim terminal and a potential interference terminal meets a preset time difference threshold, it is confirmed that there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal, thereby verifying that the potential victim terminal and the potential interference terminal are hidden terminals in the wireless local area network.

[0128] Furthermore, after the step of determining that the potential victim terminal and the potential interference terminal are hidden terminals, the method further includes steps B1 to B2:

[0129] Step B1: Construct an interference topology view of the wireless local area network based on the hidden terminal;

[0130] Step B2: Optimize the wireless local area network (WLAN) based on the interference topology view of the WLAN.

[0131] Specifically, the hidden terminal identification device uses the previously identified hidden terminals to construct a multi-AP collaborative interference topology view for the wireless LAN. This interference topology view refers to a wireless LAN conflict relationship model described using a graph data structure, and may include:

[0132] 1. Node set: An abstract representation of the AP and terminal devices. Each node records the device's media access control address, physical location coordinates, and associated AP identifier.

[0133] 2. Set of conflicting edges: Undirected edges connect terminal nodes where there are hidden terminal conflicts.

[0134] Then, using the above interference topology view, perform at least one of the following optimization operations on the wireless LAN:

[0135] 1. Channel allocation optimization: Preset orthogonal channels are allocated to APs associated with conflicting terminals. If all channels are saturated, the conflicting terminal is migrated to a neighboring AP with a lower load.

[0136] 2. Protocol parameter adjustment: For multiple terminals that frequently experience hidden terminal conflicts, the RTS / CTS mechanism is forcibly enabled and automatically disabled after the conflict is resolved;

[0137] 3. Adjust the power of multiple terminals that frequently experience hidden terminal conflicts, or relocate their physical locations so that these terminals are no longer within the coverage area of ​​the same AP.

[0138] This embodiment uses the above-described scheme to enter a listening mode through a nearby network access device. The nearby network access device is used to determine whether there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal. This helps to verify whether the previously identified potential victim terminal and the potential interference terminal are hidden terminals in the wireless local area network. The above method improves the accuracy of hidden terminal identification and avoids the huge protocol overhead of enabling the RTS / CTS mechanism on associated terminals.

[0139] Based on the above embodiments of this application, in the fourth embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 4After the step of performing network conflict correlation analysis on the potential victim terminals based on the network status data to determine at least one potential interfering terminal from the plurality of associated terminals, the process includes steps S410 to S420:

[0140] Step S410: Enable conflict avoidance mechanism for the potential victim terminal through the gateway device;

[0141] Step S420: If the retransmission rate of the potential victim terminal decreases by more than a preset decrease threshold after the conflict avoidance mechanism is activated, then the potential victim terminal and the potential interference terminal are determined to be hidden terminals.

[0142] Understandably, after performing network conflict correlation analysis on the potential victim terminals based on network status data and identifying at least one potential interference terminal from several associated terminals, the hidden terminal identification device can also use the gateway device to actively detect the potential victim terminals and potential interference terminals to confirm whether the potential victim terminals and potential interference terminals are hidden terminals.

[0143] Specifically, the gateway device enables a conflict avoidance mechanism, namely the RTS / CTS mechanism, for potentially affected terminals. The RTS / CTS mechanism is designed to resolve media access conflicts between terminals that are not visible to each other. If the problem is alleviated after enabling this mechanism, it indicates that the previous performance degradation was indeed caused by hidden terminal conflicts.

[0144] If the retransmission rate of a potential victim terminal decreases by more than a preset threshold after the RTS / CTS mechanism is enabled, it means that the transmission performance of the potential victim terminal has improved after the RTS / CTS mechanism is enabled. This proves that the potential victim terminal is indeed affected by the hidden terminal conflict. Therefore, the previously identified potential victim terminal and the potential interference terminal are hidden terminals in the wireless local area network.

[0145] Furthermore, after the step of determining that the potential victim terminal and the potential interference terminal are hidden terminals, the method further includes steps B1 to B2:

[0146] Step B1: Construct an interference topology view of the wireless local area network based on the hidden terminal;

[0147] Step B2: Optimize the wireless local area network (WLAN) based on the interference topology view of the WLAN.

[0148] In the foregoing embodiments, steps B1 to B2 have been described in detail and will not be repeated here.

[0149] This embodiment, through the above-described scheme, specifically by enabling the RTS / CTS mechanism on the potential victim terminal, confirms whether the transmission performance of the potential victim terminal changes after enabling the RTS / CTS mechanism. This helps to confirm whether the previously identified potential victim terminal and the potential interference terminal are hidden terminals within the wireless local area network. By enabling the RTS / CTS mechanism only on the potential victim terminal, the problem of hidden terminals can be confirmed, without the need to enable the RTS / CTS mechanism on multiple associated terminals, thus avoiding huge protocol overhead. At the same time, it can accurately identify hidden terminals in the wireless local area network.

[0150] This application also provides a hidden terminal identification device, please refer to... Figure 5 The hidden terminal identification device is applied to a wireless local area network (WLAN), which includes at least one network access device. The hidden terminal identification device includes:

[0151] The acquisition module 10 is used to acquire network status data of several associated terminals based on the network access device, wherein the network status data includes network feature data of multiple dimensions.

[0152] The identification module 20 is used to analyze the network status data using a preset sliding time window and identify at least one potential victim terminal from the plurality of associated terminals.

[0153] The determination module 30 is used to perform network conflict correlation analysis on the potential victim terminals based on the network status data, and determine at least one potential interference terminal from the plurality of associated terminals.

[0154] The verification module 40 is used to use a nearby network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal in order to verify whether the potential victim terminal and the potential interference terminal are hidden terminals.

[0155] The hidden terminal identification device provided in this application employs the hidden terminal identification method based on multidimensional network feature analysis in the above embodiments, which can solve the technical problem of how to improve the accuracy of hidden terminal identification. Compared with the prior art, the beneficial effects of the hidden terminal identification device provided in this application are the same as those of the hidden terminal identification method based on multidimensional network feature analysis provided in the above embodiments, and other technical features in the hidden terminal identification device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0156] This application provides a hidden terminal identification device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the hidden terminal identification method based on multidimensional network feature analysis in the above embodiments.

[0157] The following is for reference. Figure 6 This document illustrates a structural schematic diagram of a hidden terminal identification device suitable for implementing embodiments of this application. The hidden terminal identification device in these embodiments may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 6 The hidden terminal identification device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0158] like Figure 6 As shown, the hidden terminal identification device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the hidden terminal identification device. The processing unit 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems can be connected to the input / output interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the hidden terminal identification device to communicate wirelessly or wiredly with other devices to exchange data. While the figures show hidden terminal identification devices with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0159] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0160] The hidden terminal identification device provided in this application employs the hidden terminal identification method based on multidimensional network feature analysis in the above embodiments, which can solve the technical problem of how to improve the accuracy of hidden terminal identification. Compared with the prior art, the beneficial effects of the hidden terminal identification device provided in this application are the same as those of the hidden terminal identification method based on multidimensional network feature analysis provided in the above embodiments, and other technical features in this hidden terminal identification device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0161] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0162] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0163] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the hidden terminal identification method based on multidimensional network feature analysis in the above embodiments.

[0164] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0165] The aforementioned computer-readable storage medium may be included in the hidden terminal identification device; or it may exist independently and not be assembled into the hidden terminal identification device.

[0166] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by a hidden terminal identification device, the hidden terminal identification device performs the following actions: Based on the network access device, it collects network status data from several associated terminals, the network status data including multi-dimensional network characteristic data; analyzes the network status data using a preset sliding time window to identify at least one potential victim terminal from the several associated terminals; performs network conflict correlation analysis on the potential victim terminal based on the network status data to determine at least one potential interference terminal from the several associated terminals; and uses a nearby network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals.

[0167] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0168] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0169] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0170] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described hidden terminal identification method, thereby solving the technical problem of how to improve the accuracy of hidden terminal identification. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the hidden terminal identification method based on multidimensional network feature analysis provided in the above embodiments, and will not be repeated here.

[0171] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for identifying hidden terminals based on multidimensional network feature analysis, characterized in that, The hidden terminal identification method is applied to a wireless local area network (WLAN), which includes at least one network access device. The hidden terminal identification method includes: Based on the network access device, network status data of several associated terminals are collected, and the network status data includes network feature data of multiple dimensions. The network status data is analyzed using a preset sliding time window to identify at least one potential victim terminal from the plurality of associated terminals; Based on the network status data, a network conflict correlation analysis is performed on the potential victim terminals to identify at least one potential interference terminal from among the associated terminals. The potential victim terminal and the potential interference terminal are monitored by a nearby network access device to verify whether they are hidden terminals.

2. The hidden terminal identification method based on multidimensional network feature analysis as described in claim 1, characterized in that, The step of analyzing the network status data using a preset sliding time window to identify at least one potential victim terminal from the plurality of associated terminals includes: For any associated terminal, determine the network status data of the associated terminal within the preset sliding time window; When the network status data of the associated terminal within the preset sliding time window meets the preset conditions, the associated terminal is determined to be a potential victim terminal.

3. The hidden terminal identification method based on multidimensional network feature analysis as described in claim 2, characterized in that, The network status data includes received signal strength, negotiation rate, retransmission rate, and error statistics. The preset conditions are that the received signal strength of the associated terminal within the preset sliding time window is greater than a first preset threshold, the negotiation rate is greater than a second preset threshold, the retransmission rate is greater than a third preset threshold, and the error statistics are greater than a fourth preset threshold. The error statistics include at least one of the following: physical layer error count, fragmentation error rate, and ACK timeout count.

4. The hidden terminal identification method based on multidimensional network feature analysis as described in claim 3, characterized in that, The step of performing network conflict correlation analysis on the potential victim terminals based on the network status data, and determining at least one potential interfering terminal from the plurality of associated terminals, includes: Based on the network status data of the potential victim terminal within the preset sliding time window, several first moments in which the performance degradation event of the potential victim terminal occurs are determined. For any associated terminal, based on the network status data of the associated terminal within the preset sliding time window, several second moments in which the associated terminal exhibits transmission behavior are determined. Determine the time overlap between the plurality of first moments and the plurality of second moments; When the received signal strength of both the network access device and the associated terminal is greater than a first preset threshold and the time overlap is higher than a preset overlap threshold, the associated terminal is determined to be the potential interference terminal.

5. The hidden terminal identification method based on multidimensional network feature analysis as described in claim 2, characterized in that, The step of using a proximity network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal to verify whether the potential victim terminal and the potential interference terminal are hidden terminals includes: The gateway device instructs the nearby network access device to enter listening mode; When the neighboring network access device detects the uplink messages between the potential victim terminal and the potential interference terminal, it confirms whether there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal. When there is a time conflict between the uplink messages of the potential victim terminal and the potential interference terminal, the potential victim terminal and the potential interference terminal are determined to be hidden terminals.

6. The hidden terminal identification method based on multidimensional network feature analysis as described in claim 5, characterized in that, After determining that the potential victim terminal and the potential interference terminal are hidden terminals, the method further includes: Construct an interference topology view of the wireless local area network based on the hidden terminal; The wireless LAN is optimized based on the interference topology view of the wireless LAN.

7. A hidden terminal identification device, characterized in that, The hidden terminal identification device is applied to a wireless local area network (WLAN), the WLAN including at least one network access device, and the hidden terminal identification device includes: The data acquisition module is used to collect network status data of several associated terminals based on the network access device. The network status data includes network feature data in multiple dimensions. The identification module is used to analyze the network status data using a preset sliding time window and identify at least one potential victim terminal from the plurality of associated terminals. The determination module is used to perform network conflict correlation analysis on the potential victim terminals based on the network status data, and determine at least one potential interference terminal from the plurality of associated terminals. The verification module is used to use a nearby network access device to conduct network monitoring on the potential victim terminal and the potential interference terminal in order to verify whether the potential victim terminal and the potential interference terminal are hidden terminals.

8. A hidden terminal identification device, characterized in that, The hidden terminal identification device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the hidden terminal identification method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the hidden terminal identification method as described in any one of claims 1 to 6.

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