Wireless network evaluation method and device

Abstract

This application provides a wireless network assessment method and apparatus, relating to the field of communications technology. The method can comprehensively assess the network coverage of a target area where direct testing and assessment cannot be performed by obtaining test data from test areas surrounding the target area and correcting it with backend stored data. The method comprises: obtaining wireless network test data from multiple test areas; wherein the test areas are areas surrounding the target area; obtaining backend stored data from the target area; and determining a wireless network assessment result for the target area based on the test data and the backend stored data. This application is used in the wireless network assessment process.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a wireless network evaluation method and device. Background Art

[0002] When testing, analyzing, and optimizing wireless networks, you can conduct tests along major roads around the target area and conduct a comprehensive summary and analysis of the test conclusions.

[0003] However, due to actual on-site conditions or high-risk factors, it is impossible to enter the site to carry out related work, especially in residential areas, business areas, factory areas, engineering sites, special units, risk management and other conditions. Not all locations and all situations can be tested, resulting in the inability to efficiently and accurately implement many on-site tasks such as wireless network planning and design, wireless network optimization and evaluation, resulting in large-scale wireless network test vulnerabilities.

[0004] Alternatively, intelligent analysis and summary can be performed through a large amount of background storage data.

[0005] However, such analysis and summary results may contain significant errors and ignore issues such as on-site scenes, building obstructions, and deep coverage. Furthermore, background indicators are evaluated and calculated only at the base station cell level, without considering actual conditions. This leads to a certain probability of misjudgment or error, and there is no clear prediction of deep coverage issues or detailed geographical areas. As a result, there is a significant gap between the actual situation in terms of both accuracy and reliability.

[0006] Therefore, how to conduct comprehensive and multi-dimensional wireless network testing and evaluation for a large number of scenarios where on-site internal testing is not possible, so that the evaluation results are closer to the actual situation on site, has become a technical problem that needs to be solved urgently. Summary of the Invention

[0007] The present application provides a wireless network assessment method and apparatus, and proposes a method and approach for indirect and accurate assessment of a target area during wireless network assessment. This method enables indirect assessment of the wireless network in a restricted target area when, due to actual conditions of the on-site environment, it is not possible to conduct on-site testing and assessment. By testing the testable area surrounding the target area, the wireless network conditions within the target area are assessed accordingly, making the assessment results closer to the actual conditions within the target area and improving the accuracy of indirect wireless network assessment.

[0008] To achieve the above objectives, this application adopts the following technical solutions:

[0009] In a first aspect, the present application provides a wireless network evaluation method, which includes: obtaining wireless network test data of multiple test areas; wherein the test area is a surrounding area of ​​a target area; obtaining background storage data of the target area; and determining a wireless network evaluation result of the target area based on the test data and the background storage data.

[0010] Based on the first aspect, the present application tests and collects relevant data on the wireless network conditions (i.e., test data) of the surrounding environment of the target area or a specific location (i.e., the test area or the surrounding area), and implements corrections in combination with the background stored data, thereby achieving the effect of approximating the actual situation of the target area. The present application is suitable for fast and convenient on-site testing and evaluation, as well as for wireless network planning, design, optimization, testing, and evaluation in scenarios where it is impossible to enter the on-site internal testing. It can greatly improve the credibility of wireless network evaluation, greatly improve the efficiency of on-site planning optimization evaluation, and effectively solve the difficulties and limitations of on-site testing and evaluation.

[0011] In one possible implementation, multiple target sub-areas are determined based on the target area; a wireless network evaluation result of the target sub-area is determined based on the background storage data and test data of the target sub-area; and a wireless network evaluation result of the target area is determined based on the wireless network evaluation results of the multiple target sub-areas.

[0012] In a possible implementation, the beam of the target area is divided into multiple sub-beams according to a preset step size, and the area corresponding to each sub-beam is the target sub-area.

[0013] In one possible implementation, the free space transmission link loss of the target area is determined based on the distance between the test area and the base station, the height of the base station, the test data, and the background storage data; and the wireless network evaluation result of the target area is determined based on the free space transmission link loss of the target area.

[0014] In one possible implementation, the initial evaluation result of the target area is determined based on the distance between the test area and the base station, the distance between the target area and the base station, and the test data; and the wireless network evaluation result of the target area is determined based on the initial evaluation result of the target area and the background storage data.

[0015] In one possible implementation, the initial evaluation result of the target area is determined based on the distance between the test area and the base station, the distance between the target area and the base station, and the test data; and the wireless network evaluation result of the target area is determined based on the initial evaluation result of the target area and the background storage data.

[0016] In one possible implementation, the wireless network evaluation result for the first time period is determined based on the test data of the test area in the first time period and the background storage data of the target area in the first time period; or the wireless network evaluation result for the second time period is determined based on the test data of the test area in the second time period and the background storage data of the target area in the second time period; wherein the first time period is a time period in which the network load of the wireless network is greater than or equal to a preset threshold; and the second time period is a time period in which the network load of the wireless network is less than the preset threshold.

[0017] In the second aspect, the present application provides a communication device, including: a transceiver module, which obtains wireless network test data of multiple test areas; wherein the test area is the surrounding area of ​​the target area; the transceiver module is used to obtain background storage data of the target area; the processing module is also used to determine the wireless network evaluation result of the target area based on the test data and the background storage data.

[0018] In one possible implementation, the processing module is used to determine multiple target sub-areas based on the target area; determine the wireless network evaluation result of the target sub-area based on the background storage data and test data of the target sub-area; and determine the wireless network evaluation result of the target area based on the wireless network evaluation results of the multiple target sub-areas.

[0019] In a possible implementation, the processing module is further configured to divide the beam of the target area into a plurality of sub-beams according to a preset step size, and the area corresponding to each sub-beam is the target sub-area.

[0020] In one possible implementation, the processing module is further used to determine the free space transmission link loss of the target area based on the distance between the test area and the base station, the height of the base station, the test data, and the background storage data; and determine the wireless network evaluation result of the target area based on the free space transmission link loss of the target area.

[0021] In one possible implementation, the processing module is also used to determine the initial evaluation result of the target area based on the distance between the test area and the base station, the distance between the target area and the base station, and the test data; and determine the wireless network evaluation result of the target area based on the initial evaluation result of the target area and the background storage data.

[0022] In one possible implementation, the processing module is further used to determine the wireless network evaluation result of the first time period based on the test data of the test area in the first time period and the background storage data of the target area in the first time period; or to determine the wireless network evaluation result of the second time period based on the test data of the test area in the second time period and the background storage data of the target area in the second time period; wherein the first time period is a time period in which the network load of the wireless network is greater than or equal to a preset threshold; and the second time period is a time period in which the network load of the wireless network is less than the preset threshold.

[0023] In a third aspect, the present application provides a communication device comprising: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement the wireless network evaluation method described in the first aspect and any possible implementation of the first aspect.

[0024] In a fourth aspect, the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a computer, the computer executes the wireless network evaluation method described in the first aspect and any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of a communication system provided in an embodiment of the present application;

[0026] Figure 2 A schematic diagram of the composition of a communication device provided in an embodiment of the present application;

[0027] Figure 3 A flow chart of a wireless network evaluation method provided in an embodiment of the present application;

[0028] Figure 4 A schematic diagram of a wireless network field test provided in an embodiment of the present application;

[0029] Figure 5 A schematic diagram of a horizontal top view of a wireless network provided in an embodiment of the present application;

[0030] Figure 6 A schematic diagram of an overall analysis and evaluation of a wireless network provided in an embodiment of the present application;

[0031] Figure 7 A schematic diagram of a communication device provided in an embodiment of the present application;

[0032] Figure 8 A diagram showing the structure of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] Before describing the embodiments of the present application, the technical terms involved in the embodiments of the present application are described.

[0034] Network performance analysis: Network performance analysis is the foundation of network optimization, a prerequisite for selecting appropriate optimization measures, and the basis for evaluating optimization results. The goal of network optimization is to improve network performance and enhance user satisfaction. Due to the complexity of mobile networks, no performance indicator or performance evaluation method can fully evaluate network performance from the user's perspective. Each performance indicator or performance evaluation method can only reflect a single aspect of network operation quality. Therefore, optimization requires collecting performance data and analyzing network performance from multiple perspectives.

[0035] Measurement report (MR) data geography: This involves using MR messages and the MR positioning algorithm to accurately locate the longitude and latitude of each MR. All located MR data, including level and quality, is then presented on a geographic information system (GIS) map. This allows users to intuitively see the distribution of signal strength and voice quality on the map, providing a convenient basis for identifying and resolving problems.

[0036] Beamangle: This is the angle between the line connecting the two points where a perpendicular line intersects the main lobe edge at half the peak field strength of the main lobe and the vertex. The main lobe width and beam angle reflect the directivity of the antenna.

[0037] Rasterization: Rasterization is a data format that divides space into regular grids, each of which is called a cell. Each cell is assigned a corresponding attribute value to represent an entity. Spatial databases are an extremely important means of effectively managing geographic raster data.

[0038] Breakpoint (BP): The physical meaning of BP is defined by the Fresnel zone, which is a fictitious ellipsoidal area. BP is the distance between the sender and the receiver when the first Fresnel zone just touches the obstacle (i.e. the ground).

[0039] Line of sight (LOS): refers to the ability of the transmitting antenna and the receiving antenna to "see" each other.

[0040] Non-line of sight (NLOS): The most direct explanation of non-line of sight is that the line of sight between the two communicating points is blocked, and they cannot see each other, and more than 50% of the Fresnel zone is blocked.

[0041] Wireless network assessment, especially 5G network assessment implementation, has always faced significant challenges. Numerous practical difficulties and limitations exist during the actual frontier wireless network assessment process, hindering accurate wireless network testing and assessment. Furthermore, due to the complex on-site conditions, accurate judgments based on backend stored data analysis are difficult to make. This often necessitates on-site wireless network planning and design assessments, network optimization assessments, or temporary on-site emergency assessments for optimization and maintenance. Therefore, frontier assessment methods for closed-environment wireless networks have become both a key breakthrough and a challenge in wireless network assessment.

[0042] For example, manpower can be deployed to conduct detailed wireless network testing and assessment along major roads or inside large buildings.

[0043] However, due to the limitations of real-world wireless network testing and assessment, not all locations and situations can be tested, resulting in widespread wireless network testing vulnerabilities. Therefore, this type of testing and assessment is only suitable for wireless network assessments in large areas or high-value locations, and requires investment in manpower and resources.

[0044] In another example, intelligent analysis and summary can be performed through a large amount of background stored data, including measurement report (MR) data, minimization of drive-tests (MDT) data, network resource data, service quality data, network perception data, especially network coverage, network interference quality, etc., which relies entirely on background stored data analysis and evaluation.

[0045] However, such analysis and summary results rely solely on the base station data collected and stored in the background. This data is affected by multiple factors such as the number of users and usage habits, and is heavily dependent on user behavior. It is unstable and uncertain and cannot objectively reflect the boundary capabilities of the wireless network. It may also contain obvious errors and ignore issues such as on-site scenes, building obstructions, and deep coverage. At the same time, the background data is based on two-dimensional plane data and is not combined with the actual situation on site. Therefore, there is a certain probability of misjudgment or error, and there is no clear prediction of detailed geographical areas, which cannot reflect the complex three-dimensional scene conditions on site.

[0046] Furthermore, while currently mature MR geo-representation technology provides a relatively clear geographic representation of network coverage indicators, data is relatively scarce in areas with less-than-ideal wireless network coverage and fewer users. This leads to a certain degree of coverage misjudgment, and there are also errors in comprehensive parameters and overall regional network conditions. In the application of cutting-edge grid assessment, the use of MR data is not comprehensive, and feedback is often limited.

[0047] To address the aforementioned technical issues, this application proposes a wireless network assessment method. The method may include: obtaining wireless network test data from multiple test areas; where the test areas are areas surrounding a target area; obtaining backend stored data for the target area; and determining a wireless network assessment result for the target area based on the test data and the backend stored data.

[0048] In the embodiment of the present application, the test data that can be obtained around the target area is utilized, and at the same time, the background stored data is combined with the artificial intelligence algorithm to perform intelligent wireless network test evaluation and perform basic capability evaluation of the wireless network coverage of the target area.

[0049] By fully leveraging the specific conditions of the site, the system acquires as detailed on-site data as possible, combines this with comprehensive analysis and correction of backend stored data, and comprehensively assesses wireless network coverage in the target area. This system implements a grid-based wireless network assessment, closely approximating the true network capacity of the wireless network. This application addresses the indirect assessment method used for on-site wireless network assessments due to obstacles that prevent access, demonstrating both practical significance and technological advancement.

[0050] The following describes in detail the implementation of the embodiments of the present application in conjunction with the accompanying drawings.

[0051] Below is Figure 1 As an example, the system architecture provided by the embodiment of the present application is described.

[0052] Figure 1 A schematic diagram of a communication system provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the communication system may include a terminal device, a base station (or an access network device), and a server.

[0053] in, Figure 1 The terminal device can be located within the cell coverage of the base station and can be connected to the base station wirelessly. The terminal device can be a device with wireless transceiver functions or a chip or chip system that can be set in the device, which can allow the user to access the network and is a device for providing voice and / or data connectivity to the user. The terminal device can also be called user equipment (UE), subscriber unit (subscriber unit), terminal (terminal), mobile station (MS), mobile terminal (MT), etc.

[0054] For example, Figure 1The terminal device in the term "terminal device" may be a cellular phone, smartphone, wireless data card, mobile phone, personal digital assistant (PDA), tablet computer or computer with wireless transceiver function, wireless modem, handheld device, laptop computer. The terminal device may also be a wireless terminal used in industrial control, unmanned driving, telemedicine, smart grid, transportation safety, smart city, smart home, etc., without limitation.

[0055] in, Figure 1 The base station in this context can be any device deployed in an access network that can communicate wirelessly with terminal devices. Alternatively, a base station can be described as an access device that allows terminal devices to access the communication system wirelessly. It can also be a chip or chip system that can be installed in the above-mentioned devices, mainly used to implement functions such as wireless physical control, resource scheduling and wireless resource management, wireless access control, and mobility management. The base station can also be connected to the core network equipment wirelessly or wired. Specifically, the base station can be a device that supports wired access or a device that supports wireless access.

[0056] Exemplarily, the base station may be an access network (AN) / radio access network (RAN) device, which is composed of multiple AN / RAN nodes. The AN / RAN node may be: an access point (AP), a macro base station, a micro base station (or described as a small station), a relay station, an enhanced nodeB (eNB), a next generation eNB (ng-eNB), a next generation nodeB (gNB), a base station in a 5G communication system, a base station in a future mobile communication system, or an access node in a wireless-fidelity (WiFi) system, a transmission reception point (TRP), a transmission point (TP), etc.

[0057] in, Figure 1The server in the system can be a standalone server or a server cluster consisting of multiple servers. The server performs calibration and evaluation of test data and backend storage data, grid-based network coverage evaluation, and network coverage evaluation at different times.

[0058] It should be noted that the base station and server in the embodiments of the present application may be one or more chips, or a system on chip (SOC), etc. Figure 1 The figures are merely exemplary and the number of devices included is not limited. Figure 1 In addition to the devices shown, the communication system may also include other devices. Figure 1 The names of each device and each link in the Figure 1 In addition to the names shown, each device and each link can be named with other names without restriction.

[0059] When implementing it specifically, Figure 1 As shown: Each base station and server can use Figure 2 The structure shown, or including Figure 2 Parts shown. Figure 2 This is a schematic diagram of the composition of a communication device 200 provided in an embodiment of the present application. The communication device 200 can be a terminal device or a chip or system on chip in a terminal device; it can also be a chip or system on chip of a transceiver module or a processing module. Figure 2 As shown, the communication device 200 includes a processor 201 , a transceiver 202 and a communication line 203 .

[0060] Furthermore, the communication device 200 may further include a memory 204 , wherein the processor 201 , the memory 204 and the transceiver 202 may be connected via a communication line 203 .

[0061] The processor 201 is a central processing unit (CPU), a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 201 may also be other devices with processing functions, such as circuits, devices, or software modules, without limitation.

[0062] Transceiver 202 is used to communicate with other devices or other communication networks. The other communication networks may be Ethernet, radio access networks (RAN), wireless local area networks (WLAN), etc. Transceiver 202 may be a module, circuit, transceiver, or any device capable of communication.

[0063] The communication line 203 is used to transmit information between the components included in the communication device 200.

[0064] The memory 204 is used to store instructions, where the instructions may be computer programs.

[0065] The memory 204 may be a read-only memory (ROM) or other type of static storage device that can store static information and / or instructions, or a random access memory (RAM) or other type of dynamic storage device that can store information and / or instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, etc., without limitation.

[0066] It should be noted that memory 204 can exist independently of processor 201 or can be integrated with processor 201. Memory 204 can be used to store instructions, program code, or data. Memory 204 can be located within or outside of communication device 200, without limitation. Processor 201 is configured to execute instructions stored in memory 204 to implement the wireless network assessment method provided in the following embodiments of this application.

[0067] In one example, the processor 201 may include one or more CPUs, such as Figure 2 CPU0 and CPU1 in.

[0068] As an optional implementation, the communication device 200 includes multiple processors, for example, Figure 2 In addition to the processor 201, a processor 207 may also be included.

[0069] As an optional implementation, the communication apparatus 200 further includes an output device 205 and an input device 206. For example, the input device 206 is a keyboard, a mouse, a microphone, a joystick, or the like, and the output device 205 is a display screen, a speaker, or the like.

[0070] It should be noted that the communication device 200 can be a desktop computer, a portable computer, a network server, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system or a computer with a plurality of CPUs. Figure 2 In addition, Figure 2 The structure shown in the figure does not constitute a limitation on the communication device, except Figure 2 In addition to the components shown, the communication device may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0071] In the embodiment of the present application, the chip system can be composed of chips, or can include chips and other discrete devices.

[0072] In addition, the actions and terms involved in the various embodiments of this application can refer to each other without limitation. The message names or parameter names in the messages exchanged between the various devices in the embodiments of this application are only examples, and other names can also be used in specific implementations without limitation.

[0073] Combine Figure 1 The communication system shown, referring to Figure 3 , a wireless network evaluation method provided in an embodiment of the present application is described. The processing performed by a single execution entity (base station, server) shown in the embodiment of the present application can also be divided into multiple execution entities, and these execution entities can be logically and / or physically separated without restriction.

[0074] Figure 3 A flowchart of a wireless network evaluation method provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the method may include:

[0075] Step 301: Acquire wireless network test data of multiple test areas and background storage data of a target area.

[0076] The test area is the area surrounding the target area. The target area can also be called the target evaluation area, and the test area can also be called the reachable area around the target area.

[0077] The area around the target area where on-site measurement can be performed may be determined as the test area.

[0078] Exemplarily, the test data is obtained by performing on-site measurements through terminal equipment (such as mobile phones, computers, and other terminal devices) in the test area.

[0079] Exemplarily, the test data (YD) includes one or more of the following: network coverage level, network interference quality, main neighboring cells and their quality, network perception status, basic information of base stations, basic information of primary service cells, network main frequency band capabilities, bit error rate and block error rate. Surrounding area coverage (RSRPY), surrounding area interference (SINRY), surrounding area interference (RSRQY), ​​downlink speed (DL-speedY), uplink speed (UL-speedY), received signal strength indication (RSSIY), RankY, downlink block error rate (DL-BLERY), uplink block error rate (UL-BLERY), neighboring cell (NeiY), and neighboring cell level (NeisRsrpY).

[0080] Optionally, the wireless environment coverage level data of the test area obtained according to the actual situation on site include: surrounding area coverage (RSRPY), neighboring area (NeiY), neighboring area level (NeisRsrpY), and primary serving cell (PCellY).

[0081] For example, taking the target area as a single isolated building as an example, the test area can be a test by the tester based on the wireless network coverage of the target area (or described as the target evaluation area), testing the wireless network conditions of the surrounding reachable area (i.e., the test area). The test data can be the main service cell, pilot power, signal to interference plus noise ratio (SINR) interference, network rate, received signal strength indicator (RSSI), LTE reference signal receiving quality (RSRQ), main neighboring cells, neighboring cell power and other important information obtained by the test.

[0082] The background storage data is the wireless network data of the base station in the target area, which is actively reported by the terminal equipment in the target area.

[0083] Exemplarily, the background storage data (XD) includes one or more of the following: target area coverage (RSRPX), target area interference (RSRQX), uplink noise floor (NX), service connectivity rate (C-rateX), service drop rate (DL-rateX), downlink rate (DL-speedX), uplink rate (UL-speedX), uplink bit error rate (ULerrorbit-rateX), downlink bit error rate (DLerrorbit-rateX), channel quality indication (CQIX), busy hour (BusyhourX), RankX, and throughput (ThroughputX).

[0084] Optionally, the background coverage quality data obtained based on actual on-site conditions include: target area coverage (RSRPX).

[0085] Optionally, the server may also obtain on-site environmental survey data.

[0086] For example, the spatial environment around the test can be determined based on GPS positioning, and information can be obtained conveniently and efficiently.

[0087] Illustratively, the on-site environmental survey data may include one or more of the following: target area (AD) data, source parameter (BD) data.

[0088] The target area data (AD) may include one or more of the following: target area area (SA), target area altitude (HA), target area length (LA), target area width (WA), and target area type (StyleA).

[0089] Among them, the signal source can be the base station corresponding to the test data and the background storage data, and the signal source parameter (BD) data can include one or more of the following: signal source type (StyleB), downtilt angle (DowntiltB), azimuth angle (AzimuthB), station height (HB), vertical beam angle (VerticalB), horizontal beam angle (HorizontalB), multiple input multiple output (MIMO) capability (TRB).

[0090] Based on the four data points obtained above, a wireless network assessment is conducted. Based on the test terminal, multi-antenna testing obtains the optimal RSRP, SINR, and RSSI reference values ​​for corresponding points in the surrounding area, and then obtains RSRPY, SINRY, and RSSIY. It also obtains the neighboring cell (NeisY) and neighboring cell level (NeisRsrpY) for the corresponding area. Combining the coordinates and relative positions of the target area, test area, and signal source, the target location's primary serving cell, pilot signal RSRP, interference SINR, and traffic channel RSSI indicators are inferred.

[0091] Optionally, the background storage data is mainly actively reported by the terminal devices in the target area, which may have certain location deviations and insufficient samples. For example, the background storage data over a longer historical period can be obtained to obtain more background storage data and increase the number of samples.

[0092] Optionally, based on the target area and test data (such as major neighboring area data), confirm the surrounding coverage sites and screen out sites that are too far away and exceed a preset distance (such as 800 meters), thereby improving the correlation between the test data and the target area, thereby more accurately reflecting the network status of the target area and improving the accuracy of the evaluation results.

[0093] Step 302: Evaluate the wireless network in the target area based on the test data and the background stored data to obtain a wireless network evaluation result.

[0094] Optionally, an indirect assessment of wireless network coverage can be performed based on the test data and background storage data, combined with the locations and relative positions of the target area, test area, and signal source. The network coverage assessment for the target area can be calculated by using the classic link budget algorithm provided by the standard protocol and the test results of the test area as the input of the calculation model after calculation and deduction.

[0095] In a first possible implementation, the free space transmission link loss of the target area is determined based on the distance between the test area and the base station, the height of the base station, the test data, and the background storage data; and the wireless network evaluation result of the target area is determined based on the free space transmission link loss of the target area.

[0096] For example, Figure 4 As shown in the figure, taking the target area length as X, the test area length as B, the antenna downtilt angle as α, the antenna beam angle as β, the base station height as H, the distance from the base station to the test area as A, and the distance from the test area to the target area as C as an example, according to the test data of the test area, the coverage level of a point k in the test area is RSRPY, and the distance from the point k to the signal source is K. It can be seen that the wireless transmission distance of the point k is:

[0097]

[0098] According to the link calculation formula: Pr = Pt + Gt - L + Gr, where Pt is the transmit power, Gt is the transmit antenna gain, L is the free space transmission link loss, and Gr is the receive antenna gain. The free space transmission link loss L can be determined using the following formula:

[0099] L Uma-Los =20lg(F)+22lg(D 3D )+28 (2)

[0100]

[0101] L Uma-NLos =20lg(F)+39.08lg(D 3D )+13.54-0.6lg(h UT -1.5) (4)

[0102] Where F is the frequency in MHz, and D is the distance in kilometers. Therefore, given a constant distance, the higher the frequency, the greater the loss. During actual testing, it was discovered that the 5G network power levels do not strictly follow the distribution of the above formula. To accurately assess network power levels, the above formula needs to be modified by adding a correction factor, ΔR. The adjusted formula is as follows:

[0103] L=L Uma-LOS (or L Uma-NLOS )+ΔR (5)

[0104] Based on the correction formula, the test data and corresponding data of the above k points are:

[0105]

[0106]

[0107]

[0108] RSRPYk=Pt+Gt-Lk+Gr (9)

[0109] In the above formula, d BP According to the actual situation of the existing network, the calculation formula is approximately:

[0110]

[0111] According to the statistical data of the current network, d BP The value is about 100 meters, the range is 50 to 150 meters, h BS is the base station height, generally 25 meters; hUT is the user height, which is generally 1.5 meters and has a range of 1.5 to 25 meters. According to the above formula, all the values ​​of the target area in the test area are substituted into the above formula to obtain the average value of ΔR. The new formula is as follows:

[0112]

[0113] According to the above formula, the free space loss correction assessment coverage of the wireless network in the target area can be obtained, which is the wireless network assessment result.

[0114] The second possible implementation differs from the free-space transmission link loss assessment method mentioned above. Instead, it uses the continuous coverage characteristics of wireless networks for mathematical and statistical prediction. This method has better accuracy and reliability in some open and special scenarios.

[0115] Exemplarily, the initial evaluation result of the target area can be determined based on the distance between the test area and the base station, the distance between the target area and the base station, and the test data; and the wireless network evaluation result of the target area can be determined based on the initial evaluation result of the target area and the background storage data.

[0116] The basic principle of this method is that, according to the free space transmission link loss formula, the main loss difference between two points depends mainly on the distance between the two points and the signal source. The formula is:

[0117]

[0118] According to the above formula, it can be deduced that taking the test area as input, the corresponding target area to evaluate the data is as follows:

[0119]

[0120]

[0121]

[0122] RSRPXx=Pt+Gt-Lx+Gr (16)

[0123] Based on the coverage capability and beam angle range of the wireless network signal source, this method needs to be set to a certain applicable range based on the beam angle. Beyond the coverage range of the main lobe, the main coverage capability of the side lobe is weak and is not evaluated.

[0124] Among them, the corresponding main lobe coverage limit range is:

[0125]

[0126] According to the 5G network's urban macro base station attenuation model, if the test area and target area are on either side of the BP (BreakPoint), the corresponding evaluation items need to comprehensively consider the impact of multipath effects. The formulas need to be calculated separately. The corresponding formulas are as follows:

[0127]

[0128]

[0129] Derivation and solution:

[0130]

[0131] As can be seen from the above formula, after determining the location information of the base station and the terminal devices in the test area (such as the location information of point k mentioned above), the target area evaluation level can be reversely derived from the test area coverage level. Since the transition from line-of-sight to non-line-of-sight environments is rarely encountered in actual test and evaluation, it is not considered. The propagation loss model detailed in the protocol can be reasonably derived based on the clear location information of the signal source and terminal. The above formula can be used to complete the derivation of coverage levels across environments.

[0132] Based on the above Figure 3 The method shown, according to step 302, can implement vertical two-dimensional wireless network coverage evaluation. In addition, it can also implement horizontal dimension coverage capability evaluation based on the target sub-area, thereby realizing three-dimensional spatial coverage quality evaluation of the wireless network evaluation.

[0133] A plurality of target sub-areas may be determined in the target area according to a preset step size, and the wireless network evaluation result of the target area may be determined according to the evaluation results of the target sub-areas.

[0134] For example, Figure 5 Taking the horizontal dimension top view shown as an example, the evaluation of the wireless network presents regional characteristics on the horizontal scale, so the target area can be divided into several grids. According to the actual situation and area of ​​the test area, the algorithm is set to map a corresponding continuous wireless network coverage area (i.e., the target area) from the signal source to the test area and then to the evaluation target area, and the target area is divided into multiple target sub-areas according to the preset step size.

[0135] Exemplarily, the preset step size is 2-4 meters. According to the preset step size, the target area can be divided into grids of 2*2 meters to 4*4 meters (i.e., target sub-areas), and then a full-dimensional evaluation can be performed with the help of the vertical dimension evaluation capability.

[0136] Exemplarily, the target sub-region may be determined by beam division.

[0137] For example, according to a preset step size, the beam of the target area is divided into multiple sub-beams in the horizontal dimension, and the area corresponding to each sub-beam is the target sub-area.

[0138] This method makes full use of the multi-dimensionality of space to determine the wireless network situation in the target space and can realize the raster analysis and evaluation of the plane area.

[0139] According to formulas (11) and (12) of the above method, the wireless network conditions at the following three points can be obtained.

[0140] LOS non-BP scenario:

[0141]

[0142] BP scenario in LOS:

[0143]

[0144] NLOS scenario:

[0145]

[0146] RSRPXx=Pt+Gt-Lx+Gr (24)

[0147] It is obtained by averaging the values ​​of the points in the corresponding sub-beam area.

[0148] According to formulas (13) and (16), the wireless network conditions at the following three points can be obtained:

[0149]

[0150] RSRPXx=Pt+Gt-LX+Gr (26)

[0151] According to the above formula, the wireless network signals at three points near, mid and far are selected from different points in the test area, and the wireless network signals at the corresponding points in the area are derived respectively, which are also the wireless network conditions at the three points near, mid and far. The probability average is taken based on the obtained value, and compared with the MR data collected in the background, and the recommended values ​​for each evaluation are given respectively. The result closer to the background MR is the final recommended value. The coverage area of ​​the signal source of this method is also limited to certain extent. Based on the horizontal lobe angle γ, the signal source phase angle δ, and the arbitrary center normal point C, with the geographic north as 0 degrees, the limited range of the corresponding signal source is set as follows:

[0152]

[0153]

[0154] Based on the above formula, the coverage range azimuth angle limit condition is shown in Formula 8, and the corresponding center normal distance is shown in Formula 9. It can be obtained by accurately measuring the coordinates of longitude and latitude.

[0155] Through the above method, a grid-based evaluation of the target area is achieved, thereby realizing a three-dimensional wireless network coverage evaluation of the target area.

[0156] The above method, through a grid-based wireless network coverage assessment of the target area, implements an algorithmic model for indirect and accurate network coverage assessment of the target area, thereby achieving a three-dimensional wireless network coverage assessment of the target area. This provides a relatively accurate assessment and output of the basic network environment, including the primary service cell and interference conditions in the area.

[0157] Optionally, a fourth dimension can be added to the three-dimensional wireless network evaluation algorithm. Based on extensive testing, the time dimension (i.e., the fourth dimension) can be considered during actual wireless network evaluation.

[0158] For example, during the test, it can be determined whether the current test time is during the network's busy hours, distinguishing between network load periods. It can also be used to distinguish between busy and idle times based on the actual wireless network conditions. This allows for an accurate assessment of wireless network perception.

[0159] For example, the wireless network evaluation result for the first time period may be determined based on the test data of the test area in the first time period and the background storage data of the target area in the first time period; or the wireless network evaluation result for the second time period may be determined based on the test data of the test area in the second time period and the background storage data of the target area in the second time period.

[0160] The first time period is a time period when the network load of the wireless network is greater than or equal to a preset threshold; and the second time period is a time period when the network load of the wireless network is less than the preset threshold.

[0161] For example, the test time may be T:

[0162] T∈{T BUSY , T IDLE , T NORM} (29)

[0163] It also analyzes and evaluates wireless network interference. Through on-site testing and analysis of backend stored data, it provides a clearer picture of surrounding site coverage. Combining this with backend stored data, it provides a clearer picture of surrounding macro site coverage for the target area. After comparative analysis, the primary serving cell for target area x can be determined based on the evaluation results.

[0164] PCellx=Max{CELL1(RSRPXx),…,CELLn(RSRPXx)} (30)

[0165] Through the physical meaning of SINR and the corresponding derivation formula, the SINR value of the primary service cell of the wireless network in the target area can be obtained, and the primary service cell SINR calculation formula (32) is derived according to formula (31).

[0166]

[0167] Derived under this model:

[0168]

[0169] According to the above formula, the coverage level and interference situation of the target area can be obtained, and then the background storage data of the relevant time period can be counted according to the busy and idle time.

[0170] like Figure 6 As shown, the present application is based on a grid-based four-dimensional wireless network environment evaluation method that combines wireless network test data and background storage data, industrial parameters and other information, and outputs the overall perception and capabilities of the wireless network corresponding to the refined grid through an AI artificial intelligence predictive analysis algorithm. By testing the network in the test area surrounding the target area and collecting test data, combined with the background storage data of the target area, the network coverage evaluation results of the test area for the target area are obtained, thereby achieving the purpose of wireless network capability evaluation; the target area is then divided according to a preset step size, and a grid-based network coverage evaluation is performed on the target area, while distinguishing the network conditions during idle and busy times, thereby achieving an overall analysis and evaluation of the wireless network.

[0171] This application is aimed at the wireless network test optimization process, and innovates the methods and approaches in the cutting-edge test evaluation stage. Based on the accurate evaluation of the grid-based wireless network environment in the target area, it can predict the network grid capacity according to different time periods. The focus of this application is to use the maximum resource boundary actually available on site to obtain test data around the target area or at a specific location. Combined with the background storage data of the base station, the test data is used to effectively correct the background storage data, so as to get closer to the actual situation in the field area.

[0172] The embodiments of the present application can divide the functional modules of each device according to the above method examples. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiments of the present application is schematic and is only a logical function division. In actual implementation, there may be other division methods.

[0173] In the case of dividing each functional module into corresponding functional modules, Figure 7 A communication device is shown, which can perform the actions of a server.

[0174] The communication device 70 may include a transceiver module 701 and a processing module 702. Exemplarily, the communication device 70 may be a communication device, or a chip used in a communication device, or other combined device or component having the functions of the aforementioned communication device. When the communication device 70 is a communication device, the transceiver module 701 may be a transceiver, which may include an antenna and a radio frequency circuit, etc.; the processing module 702 may be a processor (or processing circuit), such as a baseband processor, which may include one or more CPUs. When the communication device 70 is a component having the functions of the aforementioned communication device, the transceiver module 701 may be a radio frequency unit; the processing module 702 may be a processor (or processing circuit), such as a baseband processor. When the communication device 70 is a chip system, the transceiver module 701 may be the input / output interface of the chip (e.g., a baseband chip); the processing module 702 may be the chip system's processor (or processing circuit), which may include one or more central processing units. It should be understood that the transceiver module 701 in the embodiment of the present application can be implemented by a transceiver or a transceiver-related circuit component; the processing module 702 can be implemented by a processor or a processor-related circuit component (or, referred to as a processing circuit).

[0175] For example, the transceiver module 701 can be used to perform Figures 3 to 6 All transceiver operations performed by the communication device in the embodiment shown, and / or other processes used to support the technology described herein; the processing module 702 can be used to perform Figures 3 to 6 All operations except for the transceiver operations performed by the communication device in the illustrated embodiment, and / or other processes for supporting the technology described herein.

[0176] As another possible implementation method, Figure 7 The transceiver module 701 in the embodiment can be replaced by a transceiver, which can integrate the functions of the transceiver module 701; the processing module 702 can be replaced by a processor, which can integrate the functions of the processing module 702. Figure 7 The illustrated communication device 70 may also include a memory.

[0177] Alternatively, when the processing module 702 is replaced by a processor and the transceiver module 701 is replaced by a transceiver, the communication device 70 involved in the embodiment of the present application can also be Figure 8 In the communication device 80 shown, the processor may be a logic circuit 801 and the transceiver may be an interface circuit 802. Figure 8 The illustrated communication device 80 may further include a memory 803 .

[0178] The embodiments of the present application also provide a computer program product, which, when executed by a computer, can implement the functions of any of the above method embodiments.

[0179] The embodiments of the present application also provide a computer program, which, when executed by a computer, can implement the functions of any of the above method embodiments.

[0180] The embodiment of the present application also provides a computer-readable storage medium. All or part of the processes in the above-mentioned method embodiments can be completed by a computer program to instruct the relevant hardware, and the program can be stored in the above-mentioned computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The computer-readable storage medium can be an internal storage unit of the terminal (including the data sending end and / or the data receiving end) of any of the above-mentioned embodiments, such as the hard disk or memory of the terminal. The above-mentioned computer-readable storage medium can also be an external storage device of the above-mentioned terminal, such as a plug-in hard disk equipped on the above-mentioned terminal, a smart memory card (smart media card, SMC), a secure digital (secure digital, SD) card, a flash card (flash card), etc. Further, the above-mentioned computer-readable storage medium can also include both the internal storage unit of the above-mentioned terminal and an external storage device. The above-mentioned computer-readable storage medium is used to store the above-mentioned computer program and other programs and data required by the above-mentioned terminal. The above-mentioned computer-readable storage medium can also be used to temporarily store data that has been output or is to be output.

[0181] It should be noted that the terms "first" and "second" in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. "First" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this embodiment, unless otherwise specified, "multiple" means two or more.

[0182] Furthermore, the terms "include," "comprise," and "have," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0183] It should be understood that in this application, "at least one (item)" refers to one or more. "Multiple" refers to two or more. "At least two (items)" refers to two or three and more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c, or at least one of a, b, and c, can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple. "When" and "if" both mean that corresponding measures will be taken under certain objective circumstances. It does not limit the time, nor does it require any judgment action when it is implemented, nor does it mean that there are other limitations.

[0184] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or implementation described as "exemplary" or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or implementations. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner to facilitate understanding.

[0185] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0186] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0187] The units described as separate components may or may not be physically separate, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0188] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0189] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

Claims

1. A wireless network evaluation method, characterized in that: The method comprises: Acquire wireless network test data of multiple test areas; wherein the test areas are surrounding areas of a target area; Obtaining backend storage data of the target area; Determine a wireless network evaluation result of the target area according to the test data and the background storage data.

2. The method according to claim 1, characterized in that The determining, based on the test data and the background stored data, a wireless network evaluation result of the target area includes: determining a plurality of target sub-regions according to the target region; Determining a wireless network evaluation result of the target sub-area according to the background storage data of the target sub-area and the test data; The wireless network evaluation result of the target area is determined according to the wireless network evaluation results of the multiple target sub-areas.

3. The method according to claim 2, characterized in that The determining of a plurality of target sub-regions according to the target region includes: According to a preset step size, the beam of the target area is divided into multiple sub-beams, and the area corresponding to each sub-beam is the target sub-area.

4. The method according to any one of claims 1 to 2, characterized in that The determining, based on the test data and the background stored data, a wireless network evaluation result of the target area includes: determining a free space transmission link loss of the target area according to a distance between the test area and a base station, a height of the base station, the test data, and the background stored data; A wireless network evaluation result of the target area is determined according to the free space transmission link loss of the target area.

5. The method according to any one of claims 1-2, characterized in that The determining, based on the test data and the background stored data, a wireless network evaluation result of the target area includes: determining an initial evaluation result of the target area according to the distance between the test area and the base station, the distance between the target area and the base station, and the test data; A wireless network evaluation result of the target area is determined according to the initial evaluation result of the target area and the background stored data.

6. The method according to any one of claims 1 to 3, characterized in that Determining a wireless network assessment result of the target area includes: Determining a wireless network evaluation result for the first time period based on test data of the test area in the first time period and background storage data of the target area in the first time period; or determining a wireless network evaluation result for the second time period based on the test data of the test area in the second time period and the background stored data of the target area in the second time period; The first time period is a time period when the network load of the wireless network is greater than or equal to a preset threshold; and the second time period is a time period when the network load of the wireless network is less than the preset threshold.

7. A communication device, characterized in that: include: A transceiver module, configured to obtain wireless network test data from a plurality of test areas, wherein the test areas are surrounding areas of a target area; A transceiver module, used for acquiring the background storage data of the target area; The processing module is used to determine the wireless network evaluation result of the target area according to the test data and the background storage data.

8. The device according to claim 7, characterized in that The processing module is specifically used to: determining a plurality of target sub-regions according to the target region; Determining a wireless network evaluation result of the target sub-area according to the background storage data of the target sub-area and the test data; The wireless network evaluation result of the target area is determined according to the wireless network evaluation results of the multiple target sub-areas.

9. The device according to claim 8, characterized in that The processing module determines a plurality of target sub-regions according to the target region, including: According to a preset step size, the beam of the target area is divided into multiple sub-beams, and the area corresponding to each sub-beam is the target sub-area.

10. The device according to claim 7, characterized in that The processing module is specifically used to: determining a free space transmission link loss of the target area according to a distance between the test area and a base station, a height of the base station, the test data, and the background stored data; A wireless network evaluation result of the target area is determined according to the free space transmission link loss of the target area.

11. The device according to claim 7, characterized in that The processing module is specifically used to: determining an initial evaluation result of the target area according to the distance between the test area and the base station, the distance between the target area and the base station, and the test data; A wireless network evaluation result of the target area is determined according to the initial evaluation result of the target area and the background stored data.

12. The device according to any one of claims 7 to 9, characterized in that: The processing module is further configured to: Determining a wireless network evaluation result for the first time period based on test data of the test area in the first time period and background storage data of the target area in the first time period; or determining a wireless network evaluation result for the second time period based on the test data of the test area in the second time period and the background stored data of the target area in the second time period; The first time period is a time period when the network load of the wireless network is greater than or equal to a preset threshold; and the second time period is a time period when the network load of the wireless network is less than the preset threshold.

13. A communication device, characterized in that: include: A processor and a communication interface; the communication interface is coupled to the processor, and the processor is configured to execute a computer program or instruction to implement the wireless network evaluation method according to any one of claims 1 to 6.

14. A computer-readable storage medium storing instructions, characterized in that: When a computer executes the instruction, the computer executes the wireless network evaluation method described in any one of claims 1 to 6.

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