Indoor distribution system monitoring method, apparatus and non-transitory storage medium

Abstract

The application discloses an indoor distribution system monitoring method and device and a nonvolatile storage medium. The method comprises the following steps: determining standing wave ratio data of an indoor distribution system; determining a first evaluation index of the indoor distribution system at a target time point according to the standing wave ratio data of the indoor distribution system in a first time period and the standing wave ratio data of the indoor distribution system in a second time period, wherein the second time period is located in the first time period; determining a second evaluation index of the indoor distribution system at the target time point according to the standing wave ratio data of the indoor distribution system in a third time period; and determining that the indoor distribution system has a fault in the case that at least one of the first evaluation index and the second evaluation index indicates that the indoor distribution system is abnormal. The application solves the technical problem of low accuracy in determining whether the indoor distribution system is abnormal due to the fact that the related art determines whether the indoor distribution system is abnormal by monitoring the related indexes of the regular users of the indoor distribution system.

Description

Technical Field

[0001] This application relates to the field of wireless communication, and more specifically, to a method, apparatus, and non-volatile storage medium for monitoring indoor distribution systems. Background Technology

[0002] In related technologies, a common method for determining the operational status of an indoor distributed system is to monitor relevant indicators of resident users to determine whether the system is malfunctioning. However, this method has low accuracy, leading to delays in identifying system anomalies and the possibility of false alarms.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides an indoor distribution system monitoring method, device, and non-volatile storage medium to at least solve the technical problem of low accuracy in determining whether an indoor distribution system is abnormal due to monitoring relevant indicators of resident users of the indoor distribution system.

[0005] According to one aspect of the embodiments of this application, an indoor distributed system monitoring method is provided, comprising: determining the standing wave ratio (SWR) data of the indoor distributed system, wherein the SWR data is used to represent the signal transmission quality of the indoor distributed system, and the SWR data includes the SWR monitoring values ​​of the indoor distributed system collected at a preset acquisition frequency; determining a first evaluation index of the indoor distributed system at a target time point based on the SWR data of the indoor distributed system in a first time period and the SWR data in a second time period, wherein the first evaluation index is used to represent the trend of the change of the SWR data of the indoor distributed system, the second time period is located in the first time period, and the SWR data in the second time period is included in the SWR data in the first time period, and the target time point is the end time point of the first time period and the second time period; determining a second evaluation index of the indoor distributed system at the target time point based on the SWR data of the indoor distributed system in a third time period, wherein the second evaluation index is used to represent the degree of change of the SWR data of the physical link, and the target time point is the end time point of the third time period; and determining that the indoor distributed system has a fault if at least one of the first evaluation index and the second evaluation index indicates that the indoor distributed system is abnormal.

[0006] Optionally, the VSWR data of the indoor distributed system in the first time period includes: VSWR data of the indoor distributed system at each time point in the first time period; the VSWR data of the indoor distributed system in the second time period includes: VSWR data of the indoor distributed system at each time point in the second time period; determining the first evaluation index of the indoor distributed system based on the VSWR data of the indoor distributed system in the first time period and the VSWR data of the indoor distributed system in the second time period includes: performing exponentially decreasing weighted moving average processing on the VSWR data of the first time period to obtain the first monitoring index, wherein the first monitoring index is used to represent the changing trend of the VSWR data of the indoor distributed system in the first time period, and the data of the VSWR data of the first time period that is closer to the target time point has a greater influence weight on the first monitoring index; performing exponentially decreasing weighted moving average processing on the VSWR data of the second time period to obtain the second monitoring index, wherein the second monitoring index is used to represent the changing trend of the VSWR data of the indoor distributed system in the second time period, and the data of the VSWR data of the second time period that is closer to the target time point has a greater influence weight on the second monitoring index; and determining the first evaluation index based on the difference between the second monitoring index and the first monitoring index.

[0007] Optionally, the exponentially decreasing weighted moving average processing is implemented using the following formula:

[0008] Where N represents each time point within the target time period, VSWR is the VSWR monitoring value collected at the time point corresponding to N, and the target time period is either the first time period or the second time period. The value of N can be any integer from 1 to M, where M is the total number of time points within the target time period. Furthermore, when N is M, and the target time period is the first time period, ... As the primary monitoring indicator, when the target time period is the second time period, It is the second monitoring indicator.

[0009] Optionally, determining the first evaluation indicator based on the difference between the first and second monitoring indicators includes: determining the indicator deviation value obtained by subtracting the first monitoring indicator from the second monitoring indicator for each time point within the fourth time period, wherein the target time point is the end time point of the fourth time period, and the duration of the fourth time period is shorter than the duration of the second time period; performing exponential smoothing on the indicator deviation values ​​corresponding to each time point within the fourth time period to obtain the average deviation value corresponding to the target time point; and determining the first evaluation indicator corresponding to the target time point based on the difference obtained by subtracting the average deviation value from the indicator deviation value corresponding to the target time point.

[0010] Optionally, the first evaluation index is determined by the following formula:

[0011] Where P is the first evaluation index, DIF is the index deviation value corresponding to the target time point, DEA is the average deviation, and K is the preset coefficient.

[0012] Optionally, determining the second evaluation index of the indoor distribution system at the target time point based on the VSWR data of the indoor distribution system during the third time period includes: determining the difference in VSWR monitoring values ​​at any time point other than the initial time point during the third time period, wherein the difference in VSWR monitoring values ​​at any time point is the VSWR monitoring value at any time point minus the VSWR monitoring value at the previous time point immediately adjacent to the arbitrary time point; and determining the second evaluation index based on the difference in VSWR data at any time point other than the initial time point.

[0013] Optionally, the second evaluation index is determined by the following formula:

[0014] In the above formula, This indicates the second evaluation indicator. This represents the sum of the differences in VSWR data that result in a positive value. .

[0015] Optionally, the indoor distribution system monitoring method further includes: if the first evaluation index is greater than the first preset threshold, determining that the first evaluation index indicates an abnormality in the indoor distribution system; if the second evaluation index is greater than the second preset threshold and the VSWR monitoring value at the target time point is greater than the third preset threshold, determining that the second evaluation index indicates an abnormality in the indoor distribution system.

[0016] According to another aspect of the embodiments of this application, an indoor distribution system monitoring device is also provided, comprising: a first processing module, configured to determine the standing wave ratio (SWR) data of the indoor distribution system, wherein the SWR data is used to represent the signal transmission quality of the indoor distribution system, and the SWR data includes the SWR monitoring value of the indoor distribution system collected at a preset acquisition frequency; a second processing module, configured to determine a first evaluation index of the indoor distribution system at a target time point based on the SWR data of the indoor distribution system in a first time period and the SWR data in a second time period, wherein the first evaluation index is used to represent the trend of the change of the SWR data of the indoor distribution system, the second time period is located in the first time period, and the SWR data in the second time period is included in the SWR data in the first time period, and the target time point is the end time point of the first time period and the second time period; a third processing module, configured to determine a second evaluation index of the indoor distribution system at the target time point based on the SWR data of the indoor distribution system in a third time period, wherein the second evaluation index is used to represent the degree of change of the SWR data of the physical link, and the target time point is the end time point of the third time period; and a fourth processing module, configured to determine that there is a fault in the indoor distribution system when at least one of the first evaluation index and the second evaluation index indicates that the indoor distribution system is abnormal.

[0017] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, wherein a program is stored in the non-volatile storage medium, wherein the program controls the device where the non-volatile storage medium is located to execute an indoor distribution system monitoring method when it runs.

[0018] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the program executes an indoor distribution system monitoring method during runtime.

[0019] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements an indoor distribution system monitoring method.

[0020] In this embodiment, the VSWR data of the indoor distribution system is determined. The VSWR data represents the signal transmission quality of the indoor distribution system and includes VSWR monitoring values ​​collected at a preset sampling frequency. A first evaluation index of the indoor distribution system at a target time point is determined based on the VSWR data of the indoor distribution system in a first time period and a second time period. The first evaluation index represents the trend of VSWR data change in the indoor distribution system. The second time period is within the first time period, and the VSWR data in the second time period is included in the VSWR data of the first time period. The target time point is the end time of both the first and second time periods. A second evaluation index of the indoor distribution system at the target time point is determined based on the VSWR data of the indoor distribution system in a third time period. The evaluation index, in which the second evaluation index is used to represent the degree of change in the VSWR data of the physical link, and the target time point is the end time point of the third time period; when at least one of the first evaluation index and the second evaluation index indicates that the indoor distribution system is abnormal, the method of determining the existence of a fault in the indoor distribution system is to determine its first evaluation index and the second evaluation index based on the VSWR data of the indoor distribution system, and to determine whether the indoor distribution system is abnormal based on the first evaluation index and the second evaluation index. This achieves the purpose of eliminating the interference of coverage blind spots or user tidal effects of the indoor distribution system on the judgment process, thereby achieving the technical effect of improving the judgment accuracy. In addition, it solves the technical problem of low judgment accuracy caused by related technologies that determine whether the indoor distribution system is abnormal by monitoring the relevant indicators of the permanent users of the indoor distribution system. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the structure of a computer terminal (mobile terminal) according to an embodiment of this application; Figure 2 This is a flowchart illustrating an indoor distributed system monitoring method according to an embodiment of this application; Figure 3 This is a schematic diagram of the first and second evaluation indicators when the backbone combiner of an indoor distribution system malfunctions, according to an embodiment of this application. Figure 4 This is a schematic diagram of the first and second evaluation indicators when the power divider of an indoor distribution system malfunctions, according to an embodiment of this application. Figure 5 This is a schematic diagram of the structure of an indoor distributed system monitoring device according to an embodiment of this application. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] Indoor distribution systems (hereinafter referred to as indoor distribution systems) are the main means used by operators to solve the problem of insufficient indoor deep coverage. Indoor distribution systems contain a large number of couplers, ceiling antennas, and splicing feeders. If the connections between these components become loose or fall off, or if the system is damaged, the user experience will be severely degraded.

[0025] Hospitals, large shopping malls, office buildings, and universities are typical deployment scenarios for indoor distributed systems (DCS), where user activity fluctuates significantly. These scenarios are prone to damaging the backbone of the DCS during periodic renovations, leading to a deterioration in user experience. Because indoor DCS systems have numerous backbones, damage to a small number of backbones has a limited impact on the overall performance indicators of the signal source. Furthermore, the user activity fluctuates significantly, causing large fluctuations in overall signal source indicators. Therefore, operators often cannot easily determine whether the indoor DCS is malfunctioning based on changes in common user performance indicators; problems are frequently only discovered after user complaints.

[0026] Currently, common industry monitoring methods include monitoring performance indicators such as RSRP (Reliability, Performance, and Response Rate) of resident users in indoor distributed systems, PRB (Public Relationship Management) utilization, and number of users. However, as mentioned above, the impact of a small number of damaged branches on the overall performance indicators of the signal source is limited, resulting in low monitoring accuracy. Furthermore, using resident user performance indicators to determine if an indoor distributed system is abnormal is prone to misjudgment due to performance degradation caused by coverage blind spots. For example, if an indoor distributed system has been installed in a commercial building and is functioning normally, but coverage blind spots exist, such as in a conference room, the performance indicators will deteriorate sharply when resident users enter the conference room, leading to algorithmic misjudgment. Therefore, accurately locating indoor distributed system faults and restoring / improving network quality before user complaints are received is a pressing issue for operators to address.

[0027] Specifically, the commonly used indoor distributed system monitoring methods in related technologies have the following problems that prevent accurate determination of whether the indoor distributed system is abnormal: Users will be affected when the branch is damaged. However, since there are many branches in the indoor distribution system, it is difficult to judge whether the system is abnormal based on the fluctuation of the user performance index of the signal source. The index usually does not show obvious degradation. Monitoring the performance metrics of resident users is used to determine whether an indoor distributed system is abnormal. However, indoor distributed systems often have coverage blind spots, and when users enter these blind spots, the relevant performance metrics deteriorate, leading to misjudgments. Even extending the monitoring period does not significantly improve accuracy. Commercial buildings, hospitals, and university teaching / dormitory buildings experience severe tidal effects, resulting in significant fluctuations in performance data and making performance indicator monitoring less reliable.

[0028] To address the aforementioned issues, this application embodiment no longer employs the monitoring approach that relies on user performance indicators, as is common in related technologies. Instead, it monitors the physical link signal transmission quality of the signal sources connected to the indoor distribution system and determines whether the indoor distribution system is abnormal based on the monitoring results. This approach can resolve the aforementioned issues, as detailed below.

[0029] According to an embodiment of this application, a method embodiment for monitoring an indoor distributed system is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, or similar computing devices. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing an indoor distributed system monitoring method is shown. Figure 1As shown, the computer terminal 10 (or mobile device 10) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0031] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0032] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the indoor distributed system monitoring method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned indoor distributed system monitoring method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0033] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0034] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0035] Under the above operating environment, this application provides a method for monitoring an indoor distributed system, such as... Figure 2 As shown, the method includes the following steps: Step S202: Determine the standing wave ratio (SWR) data of the indoor distribution system. The SWR data is used to represent the signal transmission quality of the indoor distribution system. The SWR data includes the SWR monitoring values ​​of the indoor distribution system collected at a preset acquisition frequency. In the technical solution provided in step S202, the standing wave ratio (SWR) data of the indoor distribution system includes the SWR data of the physical link of the signal source connected to the indoor distribution system, and the signal transmission quality of the indoor distribution system includes the signal transmission quality of the physical link.

[0036] It's important to note that the physical link signal transmission quality is often measured using the standing wave ratio (SWR). When the SWR is 1, the impedance of the feeder and antenna is perfectly matched, and all high-frequency energy is radiated by the antenna without any energy reflection. When the SWR is greater than 1, some energy is reflected as heat, causing the feeder to heat up. A higher SWR indicates poorer impedance matching, more signal reflection, weaker antenna signal strength, and a more severe degradation in communication quality. When the backbone of an indoor distribution system is damaged or the coupler connection to the feeder / antenna becomes loose, the SWR increases. Therefore, the SWR can be used as an important indicator for monitoring whether an indoor distribution system is malfunctioning.

[0037] However, although VSWR data itself can reflect the communication quality of physical links, directly relying on whether the VSWR data has increased to determine whether an indoor distributed system is abnormal still has the following problems: A common anomaly in indoor distributed systems is damage to the system backbone. In this case, the VSWR increases but does not reach the VSWR alarm threshold, so no VSWR alarm will be generated. Because the installation location of each signal source and the indoor environment of the building vary, there is no uniform standard for the VSWR of indoor distributed systems. For example, the VSWR of a normal indoor distributed system may be the same as that of a faulty indoor distributed system. Therefore, it is impossible to directly determine whether an indoor distributed system is abnormal based on a VSWR value that does not trigger a VSWR alarm.

[0038] Furthermore, the VSWR is not a fixed value. Even if the indoor distribution system is fault-free, the VSWR will still fluctuate slightly, making it impossible to determine whether the indoor distribution system is abnormal by using the traditional method of setting a percentage threshold for the change of a preset index.

[0039] Therefore, in order to accurately determine whether an indoor distributed system is abnormal, even when the standing wave ratio (SWR) rises but does not trigger an SWR alarm, and to avoid misjudgments due to small normal fluctuations in the SWR, the statistical characteristics of financial industry indicators can be utilized. The SWR can be processed using long-term and short-term exponentially decreasing weighted moving averages to form a moving average of divergence, and then the dispersion difference of the moving average of divergence can be exponentially smoothed. Here, the long-term corresponds to the first time period in this embodiment, and the short-term corresponds to the second time period. By analyzing the dispersion, convergence, and strength characteristics of the processed SWR, the abnormality of the indoor distributed system can be accurately determined.

[0040] In some embodiments of this application, the preset sampling frequency may be to collect the VSWR monitoring value once at a fixed time each day, or to collect it once every few hours. Alternatively, the VSWR monitoring value can also be obtained periodically from the network management system via API.

[0041] Step S204: Determine the first evaluation index of the indoor distribution system at the target time point based on the VSWR data of the indoor distribution system in the first time period and the VSWR data of the second time period. The first evaluation index is used to represent the trend of the VSWR data of the indoor distribution system. The second time period is located in the first time period, and the VSWR data in the second time period is included in the VSWR data in the first time period. The target time point is the end time point of the first time period and the second time period. In the technical solution provided in step S204, the VSWR data of the indoor distribution system in the first time period includes: VSWR data of the indoor distribution system at each time point in the first time period; the VSWR data of the indoor distribution system in the second time period includes: VSWR data of the indoor distribution system at each time point in the second time period; determining the first evaluation index of the indoor distribution system based on the VSWR data of the indoor distribution system in the first time period and the VSWR data of the indoor distribution system in the second time period includes: performing exponentially decreasing weighted moving average processing on the VSWR data in the first time period to obtain the first monitoring index, wherein the first monitoring index is used to represent the changing trend of the VSWR data of the indoor distribution system in the first time period, and the data closer to the target time point in the VSWR data in the first time period has a greater influence weight on the first monitoring index; performing exponentially decreasing weighted moving average processing on the VSWR data in the second time period to obtain the second monitoring index, wherein the second monitoring index is used to represent the changing trend of the VSWR data of the indoor distribution system in the second time period, and the data closer to the target time point in the VSWR data in the second time period has a greater influence weight on the second monitoring index; and determining the first evaluation index based on the difference between the second monitoring index and the first monitoring index.

[0042] In some embodiments of this application, the exponentially decreasing weighted moving average processing is implemented using the following formula:

[0043] Where N represents each time point within the target time period, such as N days or N hours. VSWR is the standing wave ratio monitoring value collected at the time point corresponding to N, and the target time period is either the first time period or the second time period. The value of N can be any integer from 1 to M, where M is the total number of time points within the target time period. Furthermore, when N is M, and the target time period is the first time period, ... As the primary monitoring indicator, when the target time period is the second time period, It is the second monitoring indicator.

[0044] After applying the exponentially decreasing weighted moving average to the VSWR data for the first and second time periods using the above formula, the first monitoring indicator can be obtained. Second monitoring indicators Furthermore, due to the fact that when performing exponentially decreasing weighted moving average processing, according to... (Duration of the first time period) The duration of the second time period assigns different weights to historical data within the period, ensuring that the impact of earlier indicators is not discarded while focusing on recent indicators. , It can reflect the long-term and short-term trends of the VSWR while maintaining a certain degree of stability.

[0045] Specifically, taking M=4 as an example, when N takes different values... The values ​​are as follows:

[0046]

[0047]

[0048]

[0049]

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056] In the above formula , , , These are the VSWR monitoring values ​​for days 1 to 4. It can be seen that the closer the time, the greater the weight of the VSWR, and the more timely the changes in the VSWR can be reflected.

[0057] As an optional implementation, the step of determining the first evaluation indicator based on the difference between the first monitoring indicator and the second monitoring indicator includes: determining the indicator deviation value obtained by subtracting the first monitoring indicator from the second monitoring indicator for each time point within the fourth time period, wherein the target time point is the end time point of the fourth time period, and the duration of the fourth time period is shorter than the duration of the second time period; performing exponential smoothing on the indicator deviation values ​​corresponding to each time point within the fourth time period to obtain the average deviation value corresponding to the target time point; and determining the first evaluation indicator corresponding to the target time point based on the difference obtained by subtracting the average deviation value from the indicator deviation value corresponding to the target time point.

[0058] In some embodiments of this application, the first evaluation index is determined by the following formula:

[0059] Where P is the first evaluation index, DIF is the index deviation value corresponding to the target time point, DEA is the average deviation, and K is a preset coefficient, which can be set to 2 for example.

[0060] It should be noted that, after obtaining the deviation value, the deviation value itself can intuitively reflect the relationship between the short-term and long-term trends of the standing wave ratio. When When the value is greater than 0, the short-term and long-term trends of the VSWR diverge, indicating a potential problem with the indoor distribution system. However, since the VSWR itself fluctuates, it is not possible to simply determine whether the indoor distribution system is abnormal based on the above relationship. Therefore, it is still necessary to calculate the first evaluation index P, also known as the VSWR energy value, using the above formula.

[0061] In some embodiments of this application, the exponential smoothing formula used in calculating DEA is as follows:

[0062] In the above formula, N represents the Nth time point in the fourth time period. This represents the DEA corresponding to the Nth time point. This represents the DEA corresponding to the (N-1)th time point, and takes the value of zero if N-1 does not exist. N takes any positive integer from 1 to 0, and 0 is the total number of time points in the fourth time period.

[0063] Step S206: Determine the second evaluation index of the indoor distribution system at the target time point based on the VSWR data of the indoor distribution system in the third time period. The second evaluation index is used to represent the degree of change of the VSWR data of the physical link. The target time point is the end time point of the third time period. In the technical solution provided in step S206, the step of determining the second evaluation index of the indoor distribution system at the target time point based on the VSWR data of the indoor distribution system in the third time period includes: determining the difference in VSWR monitoring values ​​corresponding to any time point other than the initial time point in the third time period, wherein the difference in VSWR monitoring values ​​corresponding to any time point is the VSWR monitoring value corresponding to any time point minus the VSWR monitoring value of the previous time point immediately adjacent to the arbitrary time point; and determining the second evaluation index based on the difference in VSWR data corresponding to any time point other than the initial time point.

[0064] In some embodiments of this application, the second evaluation index is determined by the following formula:

[0065] In the above formula, This indicates the second evaluation indicator. This represents the sum of the differences in VSWR data that result in a positive value. .

[0066] It should be noted that for some indoor distributed antenna systems (DAS), the VSWR may slowly increase over a long period due to component aging. In such cases, it is impossible to determine whether the system is faulty by monitoring the VSWR energy value; that is, the first evaluation indicator cannot be used to determine whether the system is faulty. In this situation, it is necessary to determine the second evaluation indicator by monitoring the relative strength of the long-term VSWR, and then use the second evaluation indicator to determine whether the indoor DAS is abnormal. It can intuitively reflect the strength of changes in the long-term standing wave ratio (VSWR). When the VSWR is higher than 1.5 and A reading above 80 indicates an abnormality in the indoor distribution system.

[0067] Step S208: If at least one of the first evaluation index and the second evaluation index indicates that the indoor distribution system is abnormal, it is determined that there is a fault in the indoor distribution system.

[0068] In the technical solution provided in step S208, the indoor distribution system monitoring method further includes: when the first evaluation index is greater than the first preset threshold, determining that the first evaluation index indicates an abnormality in the indoor distribution system; when the second evaluation index is greater than the second preset threshold and the VSWR monitoring value at the target time point is greater than the third preset threshold, determining that the second evaluation index indicates an abnormality in the indoor distribution system.

[0069] Specifically, APIs can be used to implement periodic VSWR updates on a daily or other timeframes, based on... , Calculate the mean square line of the VSWR. Then analyze the deviation values ​​of the mean square line. The system undergoes exponentially decreasing weighted shift smoothing of the period, and then the standing wave ratio energy value is calculated. If the value is greater than the first preset threshold, the indoor distribution system can be determined to be abnormal.

[0070] For non-mutation indoor distribution systems, the relative strength of the long-term standing wave ratio can be monitored to determine whether the indoor distribution system is abnormal. If the standing wave ratio is greater than the third preset threshold and the relative strength value is greater than the second preset threshold, then the indoor distribution system is determined to be abnormal.

[0071] To further demonstrate the monitoring effect of the indoor distribution system monitoring method provided in this application, two examples of monitoring indoor distribution systems using the method provided in this application are also provided in the embodiments of this application. In these two examples... , Take 7 and 3 respectively.

[0072] The diagrams of the first and second evaluation indicators corresponding to Example 1 are as follows: Figure 3 As shown. Among them. Figure 3 The top image shows a comparison of DEA and DIF, the middle image shows the first evaluation indicator, and the bottom image shows the second evaluation indicator. In this example, the VSWR of the indoor distributed antenna system (DAS) continuously increased. Since there was no significant change, it was impossible to determine if the system was abnormal by monitoring the VSWR energy value. On the 12th day, the VSWR exceeded 1.5 and the relative strength (RSRP) exceeded 80, both exceeding the thresholds, thus indicating an abnormality in the DAS. On-site verification confirmed that the dry combiner of the indoor DAS, although barely functional, was faulty, causing the VSWR to fluctuate and increase. After rectification, the RSRP improved from -105 dBm to -95 dBm, demonstrating a significant improvement.

[0073] The diagrams of the first and second evaluation indicators corresponding to Example 2 are as follows: Figure 4 As shown. Among them. Figure 4 The top image shows a comparison of DEA and DIF, the middle image shows the first evaluation indicator, and the bottom image shows the second evaluation indicator. The indoor distributed antenna system (DAS) suddenly experienced a rise in VSWR value without triggering a VSWR alarm. The VSWR energy value exceeded the threshold of 0.015, therefore, the DAS was determined to be malfunctioning. On-site verification revealed a fault in the power divider, which needed to be replaced.

[0074] By employing VSWR data of the indoor distributed antenna system (DAS), where VSWR data represents the signal transmission quality of the DAS, and includes VSWR monitoring values ​​of the DAS collected at a preset sampling frequency; based on the VSWR data of the DAS within a first time period and VSWR data within a second time period, a first evaluation index of the DAS at a target time point is determined, where the first evaluation index represents the trend of VSWR data change, the second time period is within the first time period, and the VSWR data in the second time period is included in the VSWR data in the first time period, and the target time point is the end time point of both the first and second time periods; based on the VSWR data of the DAS within a third time period, a second evaluation index of the DAS at the target time point is determined. The second evaluation index is used to represent the degree of change in the VSWR data of the physical link, and the target time point is the end time point of the third time period. When at least one of the first and second evaluation indices indicates that the indoor distribution system is abnormal, the method of determining the fault of the indoor distribution system is to determine its first and second evaluation indices based on the VSWR data of the indoor distribution system, and to determine whether the indoor distribution system is abnormal based on the first and second evaluation indices. This achieves the purpose of eliminating the interference of coverage blind spots or user tidal effects of the indoor distribution system on the judgment process, thereby achieving the technical effect of improving the judgment accuracy. This solves the technical problem of low judgment accuracy caused by related technologies that determine whether the indoor distribution system is abnormal by monitoring the relevant indicators of the permanent users of the indoor distribution system.

[0075] Furthermore, in the indoor distributed system monitoring method provided in this application embodiment, the statistical characteristics of financial industry indicators are utilized. First, the standing wave ratio (SWR) is processed using long-term and short-term exponentially decreasing weighted moving averages to form a moving average line of difference. Then, the dispersion difference of the moving average line of difference is exponentially smoothed. By analyzing the dispersion, aggregation, and strength characteristics of the processed SWR, automated and accurate monitoring of indoor distributed system faults is achieved, enabling the restoration of the indoor distributed system network quality before user complaints, thereby improving user satisfaction. Moreover, compared to monitoring schemes that require simultaneous monitoring of multiple different indicators with different long and short periods, the method provided in this application embodiment only requires one monitoring period, shortening the data acquisition time.

[0076] This application provides an indoor distributed system monitoring device. Figure 5 This is a schematic diagram of the device. (For example...) Figure 5As shown, the device includes: a first processing module 50, used to determine the standing wave ratio (SWR) data of the indoor distribution system, wherein the SWR data is used to represent the signal transmission quality of the indoor distribution system, and the SWR data includes the SWR monitoring values ​​of the indoor distribution system collected at a preset acquisition frequency; a second processing module 52, used to determine a first evaluation index of the indoor distribution system at a target time point based on the SWR data of the indoor distribution system in a first time period and the SWR data in a second time period, wherein the first evaluation index is used to represent the trend of the SWR data of the indoor distribution system, the second time period is located within the first time period, and the SWR data in the second time period is included in the SWR data in the first time period, and the target time point is the end time point of the first time period and the second time period; a third processing module 54, used to determine a second evaluation index of the indoor distribution system at the target time point based on the SWR data of the indoor distribution system in a third time period, wherein the second evaluation index is used to represent the degree of change of the SWR data of the physical link, and the target time point is the end time point of the third time period; and a fourth processing module 56, used to determine that there is a fault in the indoor distribution system when at least one of the first evaluation index and the second evaluation index indicates that the indoor distribution system is abnormal.

[0077] In some embodiments of this application, the standing wave ratio (SWR) data of the indoor distribution system in a first time period includes: SWR data of the indoor distribution system at various time points within the first time period; the SWR data of the indoor distribution system in a second time period includes: SWR data of the indoor distribution system at various time points within the second time period; the step of the second processing module 52 in determining a first evaluation index of the indoor distribution system based on the SWR data of the indoor distribution system in the first time period and the SWR data of the indoor distribution system in the second time period includes: performing exponentially decreasing weighted moving average processing on the SWR data in the first time period to obtain a first monitoring index, wherein the first monitoring index is used to represent the changing trend of the SWR data of the indoor distribution system in the first time period, and the data closer to the target time point in the SWR data in the first time period has a greater influence weight on the first monitoring index; performing exponentially decreasing weighted moving average processing on the SWR data in the second time period to obtain a second monitoring index, wherein the second monitoring index is used to represent the changing trend of the SWR data of the indoor distribution system in the second time period, and the data closer to the target time point in the SWR data in the second time period has a greater influence weight on the second monitoring index; and determining the first evaluation index based on the difference between the second monitoring index and the first monitoring index.

[0078] In some embodiments of this application, the exponentially decreasing weighted moving average processing is implemented using the following formula:

[0079] Where N represents each time point within the target time period, VSWR is the VSWR monitoring value collected at the time point corresponding to N, and the target time period is either the first time period or the second time period. The value of N can be any integer from 1 to M, where M is the total number of time points within the target time period. Furthermore, when N is M, and the target time period is the first time period, ... As the primary monitoring indicator, when the target time period is the second time period, It is the second monitoring indicator.

[0080] In some embodiments of this application, the step of the second processing module 52 determining the first evaluation index based on the difference between the first monitoring index and the second monitoring index includes: determining the index deviation value obtained by subtracting the first monitoring index from the second monitoring index at each time point within the fourth time period, wherein the target time point is the end time point of the fourth time period, and the duration of the fourth time period is shorter than the duration of the second time period; performing exponential smoothing on the index deviation values ​​corresponding to each time point within the fourth time period to obtain the average deviation value corresponding to the target time point; and determining the first evaluation index corresponding to the target time point based on the difference obtained by subtracting the average deviation value from the index deviation value corresponding to the target time point.

[0081] In some embodiments of this application, the first evaluation index is determined by the following formula:

[0082] Where P is the first evaluation index, DIF is the index deviation value corresponding to the target time point, DEA is the average deviation, and K is the preset coefficient.

[0083] In some embodiments of this application, the step of the third processing module 54 determining the second evaluation index of the indoor distribution system at the target time point based on the VSWR data of the indoor distribution system in the third time period includes: determining the difference in VSWR monitoring values ​​corresponding to any time point other than the initial time point in the third time period, wherein the difference in VSWR monitoring values ​​corresponding to any time point is the VSWR monitoring value corresponding to any time point minus the VSWR monitoring value of the previous time point immediately adjacent to the arbitrary time point; and determining the second evaluation index based on the difference in VSWR data corresponding to any time point other than the initial time point.

[0084] In some embodiments of this application, the second evaluation index is determined by the following formula:

[0085] In the above formula, This indicates the second evaluation indicator. This represents the sum of the differences in VSWR data that result in a positive value. .

[0086] In some embodiments of this application, the fourth processing module 56 is further configured to: determine that the first evaluation index indicates an abnormality in the indoor distribution system when the first evaluation index is greater than the first preset threshold; and determine that the second evaluation index indicates an abnormality in the indoor distribution system when the second evaluation index is greater than the second preset threshold and the VSWR monitoring value at the target time point is greater than the third preset threshold.

[0087] It should be noted that each module in the above-mentioned indoor distributed system monitoring device can be a program module (for example, a set of program instructions to implement a certain function) or a hardware module. For the latter, it can be manifested in the following forms, but is not limited to these: each of the above modules is manifested as a processor, or the functions of each of the above modules are implemented by a processor.

[0088] According to an embodiment of this application, a non-volatile storage medium is also provided, which stores a program. When the program runs, it controls the device containing the non-volatile storage medium to execute the following indoor distribution system monitoring method: determining the standing wave ratio (SWR) data of the indoor distribution system, wherein the SWR data is used to represent the signal transmission quality of the indoor distribution system, and the SWR data includes SWR monitoring values ​​of the indoor distribution system collected at a preset acquisition frequency; determining a first evaluation index of the indoor distribution system at a target time point based on the SWR data of the indoor distribution system in a first time period and the SWR data in a second time period, wherein the first evaluation index is used to represent the signal transmission quality of the indoor distribution system. The trend of VSWR data change of the indoor distributed system is defined as follows: the second time period is located within the first time period, and the VSWR data in the second time period is included in the VSWR data in the first time period; the target time point is the end time point of the first and second time periods. Based on the VSWR data of the indoor distributed system in the third time period, a second evaluation index of the indoor distributed system at the target time point is determined, wherein the second evaluation index is used to represent the degree of change of VSWR data of the physical link, and the target time point is the end time point of the third time period. If at least one of the first and second evaluation indices indicates an abnormality in the indoor distributed system, it is determined that there is a fault in the indoor distributed system.

[0089] According to an embodiment of this application, an electronic device is also provided, including: a memory and a processor. The processor is used to run a program stored in the memory, wherein the program executes the following indoor distribution system monitoring method: determining the standing wave ratio (SWR) data of the indoor distribution system, wherein the SWR data is used to represent the signal transmission quality of the indoor distribution system, and the SWR data includes the SWR monitoring values ​​of the indoor distribution system collected at a preset acquisition frequency; determining a first evaluation index of the indoor distribution system at a target time point based on the SWR data of the indoor distribution system in a first time period and the SWR data in a second time period, wherein the first evaluation index is used to represent the trend of the change of the SWR data of the indoor distribution system, the second time period is located in the first time period, and the SWR data in the second time period is included in the SWR data in the first time period, and the target time point is the end time point of the first time period and the second time period; determining a second evaluation index of the indoor distribution system at the target time point based on the SWR data of the indoor distribution system in a third time period, wherein the second evaluation index is used to represent the degree of change of the SWR data of the physical link, and the target time point is the end time point of the third time period; and determining that the indoor distribution system has a fault if at least one of the first evaluation index and the second evaluation index indicates an abnormality in the indoor distribution system.

[0090] According to an embodiment of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the following indoor distribution system monitoring method: determining the standing wave ratio (SWR) data of the indoor distribution system, wherein the SWR data is used to represent the signal transmission quality of the indoor distribution system, and the SWR data includes the SWR monitoring values ​​of the indoor distribution system collected at a preset acquisition frequency; determining a first evaluation index of the indoor distribution system at a target time point based on the SWR data of the indoor distribution system in a first time period and the SWR data in a second time period, wherein the first evaluation index is used to represent the changing trend of the SWR data of the indoor distribution system, the second time period is located within the first time period, and the SWR data in the second time period is included in the SWR data in the first time period, and the target time point is the end time point of the first time period and the second time period; determining a second evaluation index of the indoor distribution system at the target time point based on the SWR data of the indoor distribution system in a third time period, wherein the second evaluation index is used to represent the degree of change of the SWR data of the physical link, and the target time point is the end time point of the third time period; and determining that the indoor distribution system has a fault when at least one of the first evaluation index and the second evaluation index indicates an abnormality in the indoor distribution system.

[0091] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0093] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0095] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be represented in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0096] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A monitoring method for an indoor distributed monitoring system, characterized in that, include: Determine the standing wave ratio (SWR) data of the indoor distribution system, wherein the SWR data is used to represent the signal transmission quality of the indoor distribution system, and the SWR data includes the SWR monitoring values ​​of the indoor distribution system collected at a preset acquisition frequency; Based on the VSWR data of the indoor distribution system in a first time period and the VSWR data in a second time period, a first evaluation index of the indoor distribution system at a target time point is determined. The first evaluation index represents the trend of the VSWR data of the indoor distribution system. The second time period is located within the first time period, and the VSWR data in the second time period is included within the VSWR data in the first time period. The target time point is the end time point of both the first and second time periods. The VSWR data of the indoor distribution system in the first time period includes the VSWR data of the indoor distribution system at each time point within the first time period. The VSWR data of the indoor distribution system in the second time period includes the VSWR data of the indoor distribution system at each time point within the second time period. Based on the VSWR data of the indoor distribution system in the first time period and the VSWR data in the second time period, the first evaluation index of the indoor distribution system is determined as follows: The standing wave ratio (SWR) data within the first time period is processed by an exponentially decreasing weighted moving average to obtain a first monitoring index. The first monitoring index is used to represent the changing trend of the SWR data of the indoor distribution system within the first time period. Furthermore, the data in the SWR data within the first time period that are closer to the target time point have a greater influence weight on the first monitoring index. The standing wave ratio (SWR) data within the second time period is processed by an exponentially decreasing weighted moving average to obtain a second monitoring index. The second monitoring index is used to represent the changing trend of the SWR data of the indoor distribution system within the second time period. Furthermore, the data in the SWR data within the second time period that are closer to the target time point have a greater influence weight on the second monitoring index. The first evaluation indicator is determined based on the difference between the second monitoring indicator and the first monitoring indicator; Based on the VSWR data of the indoor distribution system in the third time period, a second evaluation index of the indoor distribution system at the target time point is determined, wherein the second evaluation index is used to represent the degree of change of the VSWR data of the physical link, and the target time point is the end time point of the third time period. The second evaluation index of the indoor distribution system at the target time point is determined based on the VSWR data of the indoor distribution system during the third time period, including: Determine the difference in VSWR monitoring values ​​for any time point other than the initial time point within the third time period, wherein the difference in VSWR monitoring values ​​for any time point is the VSWR monitoring value for any time point minus the VSWR monitoring value of the previous time point immediately adjacent to the VSWR. The second evaluation index is determined based on the difference in VSWR data at any time point other than the initial time point; If at least one of the first evaluation index and the second evaluation index indicates that the indoor distribution system is abnormal, it is determined that the indoor distribution system is faulty.

2. The indoor distributed monitoring system method according to claim 1, characterized in that, Determining the first evaluation indicator based on the difference between the second monitoring indicator and the first monitoring indicator includes: The index deviation value obtained by subtracting the first monitoring index from the second monitoring index at each time point within the fourth time period is determined, wherein the target time point is the end time point of the fourth time period, and the duration of the fourth time period is shorter than the duration of the second time period. The index deviation values ​​corresponding to each time point within the fourth time period are subjected to exponential smoothing to obtain the average deviation value corresponding to the target time point. The first evaluation index corresponding to the target time point is determined by subtracting the average deviation value from the index deviation value corresponding to the target time point.

3. The indoor distributed monitoring system method according to claim 2, characterized in that, The first evaluation index is determined by the following formula: , Wherein, P is the first evaluation index, DIF is the index deviation value corresponding to the target time point, DEA is the average deviation, and K is a preset coefficient.

4. The indoor distributed monitoring system method according to claim 1, characterized in that, The second evaluation index is determined by the following formula: , In the above formula, This represents the second evaluation indicator. This represents the sum of the differences in the VSWR data where the calculation result is a positive number. This represents the sum of the absolute values ​​of the differences in the VSWR data where the calculation result is negative.

5. The indoor distributed monitoring system method according to claim 1, characterized in that, The indoor distributed monitoring system method also includes: If the first evaluation index is greater than the first preset threshold, it is determined that the first evaluation index indicates that the indoor distribution system is abnormal; If the second evaluation index is greater than the second preset threshold and the VSWR monitoring value at the target time point is greater than the third preset threshold, the second evaluation index is determined to indicate that the indoor distribution system is abnormal.

6. An indoor distributed system monitoring device, characterized in that, include: The first processing module is used to determine the standing wave ratio (SWR) data of the indoor distribution system, wherein the SWR data is used to represent the signal transmission quality of the indoor distribution system, and the SWR data includes the SWR monitoring value of the indoor distribution system collected at a preset acquisition frequency. The second processing module is used to determine a first evaluation index of the indoor distribution system at a target time point based on the VSWR data of the indoor distribution system in a first time period and the VSWR data in a second time period. The first evaluation index is used to represent the trend of the VSWR data of the indoor distribution system. The second time period is located within the first time period, and the VSWR data in the second time period is included by the VSWR data in the first time period. The target time point is the end time point of the first time period and the second time period. The VSWR data of the indoor distribution system in the first time period includes: the VSWR data of the indoor distribution system at each time point in the first time period. The VSWR data of the indoor distribution system in the second time period includes: the VSWR data of the indoor distribution system at each time point in the second time period. The second processing module is further configured to perform exponentially decreasing weighted moving average processing on the VSWR data within the first time period to obtain a first monitoring index, wherein the first monitoring index is used to represent the changing trend of the VSWR data of the indoor distribution system within the first time period, and the data closer to the target time point in the VSWR data within the first time period has a greater influence weight on the first monitoring index; perform exponentially decreasing weighted moving average processing on the VSWR data within the second time period to obtain a second monitoring index, wherein the second monitoring index is used to represent the changing trend of the VSWR data of the indoor distribution system within the second time period, and the data closer to the target time point in the VSWR data within the second time period has a greater influence weight on the second monitoring index; and determine the first evaluation index based on the difference between the second monitoring index and the first monitoring index; The third processing module is used to determine a second evaluation index of the indoor distribution system at the target time point based on the standing wave ratio data of the indoor distribution system in the third time period. The second evaluation index is used to represent the degree of change of the standing wave ratio data of the physical link. The target time point is the end time point of the third time period. The third processing module is further configured to determine the difference in VSWR monitoring values ​​at any time point other than the initial time point within the third time period, wherein the difference in VSWR monitoring values ​​at any time point is the VSWR monitoring value at any time point minus the VSWR monitoring value at the previous time point immediately adjacent to the arbitrary time point; and to determine the second evaluation index based on the difference in VSWR data at any time point other than the initial time point. The fourth processing module is used to determine that the indoor distribution system is faulty when at least one of the first evaluation index and the second evaluation index indicates that the indoor distribution system is abnormal.

7. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores a program, wherein when the program is executed, it controls the device containing the non-volatile storage medium to perform the indoor distribution system monitoring method according to any one of claims 1 to 5.

8. An electronic device, characterized in that, include: A memory and a processor, the processor being configured to run a program stored in the memory, wherein the program, when running, executes the indoor distribution system monitoring method according to any one of claims 1 to 5.

9. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the indoor distribution system monitoring method according to any one of claims 1 to 5.

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