Interference assessment method, apparatus, and storage medium

Abstract

The application provides an interference evaluation method and device and a storage medium, relates to the technical field of communication, and can determine the degree of interference influence of an area covered by RRU equipment and optical direct equipment. The method comprises the following steps: determining an interference coefficient of a coverage scene type of a target area, a target value of each parameter in a plurality of parameters, and a weight corresponding to the target value of each parameter; the target value is used for representing the parameter difference degree of the target area in a first coverage scene and a second coverage scene; the first coverage scene is a scene covered based on the RRU equipment and the optical direct equipment; the second coverage scene is a scene covered based on the RRU equipment; determining an interference value of the target area according to the interference coefficient, the target value of each parameter, and the weight corresponding to the target value of each parameter; the interference value is used for representing the degree of interference influence in the target area. The embodiments of the application are used in the interference evaluation process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, and particularly relates to an interference evaluation method and device and a storage medium. BACKGROUND

[0002] In a shopping mall, an office building, a hotel, a comprehensive building and the like, there are problems such as a complex indoor environment and a large coverage area, so a room distribution system is generally used for signal coverage. However, in the above scenarios, there is still a problem of poor coverage performance. In order to solve the above problem, a light direct device is used to pull the signal source of a base station far away and access an indoor distribution system to be used as a signal source of a room distribution system. In this way, in the above scenarios, there are two kinds of coverage of a remote radio unit (RRU) device and a light direct device, thereby improving the carrier frequency utilization rate, reducing the same frequency interference, and effectively accelerating the project construction progress.

[0003] However, in the area covered by the RRU device and the light direct device, how to determine the degree of interference influence is a problem that needs to be solved and researched. SUMMARY

[0004] The present application provides an interference evaluation method, device and storage medium, which can determine the degree of interference influence in the area covered by the RRU device and the light direct device.

[0005] To achieve the above object, the present application adopts the following technical scheme:

[0006] In a first aspect, the present application provides an interference evaluation method, which comprises: determining an interference coefficient of a coverage scene type of a target area, a target value of each parameter in a plurality of parameters, and a weight corresponding to the target value of each parameter; the target value is used to represent a parameter difference degree of the target area in a first coverage scene and a second coverage scene; the first coverage scene is a scene based on the RRU device and the light direct device for coverage; the second coverage scene is a scene based on the RRU device for coverage; determining an interference value of the target area according to the interference coefficient, the target value of each parameter, and the weight corresponding to the target value of each parameter; the interference value is used to represent the degree of interference influence in the target area.

[0007] In a possible implementation, determining the target value of each parameter in the plurality of parameters comprises: obtaining the plurality of parameters of each sampling point in the M sampling points in the target area in the first coverage scenario and in the second coverage scenario; performing the following operation on each parameter in the plurality of parameters to obtain the target value of each parameter: determining the target parameter of each sampling point in the first coverage scenario, and the difference between the target parameter of each sampling point in the second coverage scenario is the difference of the target parameter of each sampling point; the target parameter is any parameter in the plurality of parameters; and determining the average of the parameter difference of the M sampling points as the average of the difference of the target parameter.

[0008] In a possible implementation, determining the weight corresponding to the target value of each parameter comprises: determining data of a plurality of factors corresponding to the target value of each parameter; the data comprises: eigenvalue, variance explanation rate, and loading coefficient; performing the following operation on the target value of each parameter to obtain the weight corresponding to the target value of each parameter: determining the ratio of the loading coefficient corresponding to each factor in the plurality of factors of the average of the difference of the target parameter to the square root of the eigenvalue corresponding to each factor as the linear combination coefficient of each factor; the target parameter is any parameter in the plurality of parameters; performing weighted summation on a first value of each factor to obtain a second value, and determining the ratio of the sum of the variance explanation rates of the plurality of factors to the second value as a third value; the first value is the ratio of the linear combination coefficient to the variance explanation rate; and performing normalization processing on the third value to obtain the weight corresponding to the average of the difference of the target parameter.

[0009] In a possible implementation, the interference value of the target area satisfies the following formula:

[0010]

[0011] wherein, G is the interference value of the target area; I m is the interference coefficient of the coverage scenario type of the target area; W(i) is the target value of the i th parameter in the target values of the plurality of parameters; r(i) is the weight value corresponding to the target value of the i th parameter; and k is the number of the plurality of parameters.

[0012] In a second aspect, the present application provides an interference evaluation device, which comprises: a processing unit; the processing unit is used for determining the interference coefficient of the coverage scenario type of the target area, the target value of each parameter in the plurality of parameters, and the weight corresponding to the target value of each parameter; the target value is used for characterizing the parameter difference degree of the target area in the first coverage scenario and the second coverage scenario; the first coverage scenario is a scenario covered based on the RRU device and the optical direct device; the second coverage scenario is a scenario covered based on the RRU device; and the processing unit is further used for determining the interference value of the target area according to the interference coefficient, the target value of each parameter, and the weight corresponding to the target value of each parameter; and the interference value is used for characterizing the degree of influence of the target area affected by the interference.

[0013] In a possible implementation, the apparatus further includes: a communication unit; the communication unit is configured to acquire a plurality of parameters of each sampling point in the target area in the first coverage scenario and in the second coverage scenario; the processing unit is further configured to perform the following operation on each parameter in the plurality of parameters to obtain a target value of each parameter: determining a target parameter of each sampling point in the first coverage scenario, and a difference between the target parameter of each sampling point in the second coverage scenario is a difference value of the target parameter of each sampling point; the target parameter is any one of the plurality of parameters; determining an average value of the parameter difference values of the M sampling points as an average value of the difference values of the target parameters.

[0014] In a possible implementation, the processing unit is further configured to determine data of a plurality of factors corresponding to the target value of each parameter; the data includes: an eigenvalue, a variance explanation rate, and a loading coefficient; the processing unit is further configured to perform the following operation on the target value of each parameter to obtain a weight corresponding to the target value of each parameter: determining a ratio between a loading coefficient corresponding to each factor in a plurality of factors of the average value of the difference values of the target parameters and a square root of an eigenvalue corresponding to the factor as a linear combination coefficient of each factor; the target parameter is any one of the plurality of parameters; performing weighted summation on a first value of each factor to obtain a second value, and determining a ratio between the second value and a sum of variance explanation rates of the plurality of factors as a third value; the first value is a ratio of the linear combination coefficient and the variance explanation rate; performing normalization processing on the third value to obtain a weight corresponding to the average value of the difference values of the target parameters.

[0015] In a possible implementation, the interference value of the target area satisfies the following formula:

[0016]

[0017] wherein, G is the interference value of the target area; I m is an interference coefficient of a coverage scenario type of the target area; W(i) is a target value of an i-th parameter in the target values of the plurality of parameters; r(i) is a weight value corresponding to the target value of the i-th parameter; k is a number of the plurality of parameters.

[0018] In a third aspect, the present application provides an interference evaluation apparatus, the apparatus includes: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is configured to run a computer program or instructions to implement the interference evaluation method as described in the first aspect and any possible implementation of the first aspect.

[0019] In a fourth aspect, the present application provides a computer readable storage medium, the computer readable storage medium stores instructions, when the instructions run on a terminal, the terminal executes the interference evaluation method as described in the first aspect and any possible implementation of the first aspect.

[0020] In a fifth aspect, the present application provides a computer program product comprising instructions which, when the computer program product runs on an interference evaluation device, cause the interference evaluation device to perform the interference evaluation method as described in the first aspect and any possible implementation manner of the first aspect.

[0021] In a sixth aspect, the present application provides a chip, which comprises a processor and a communication interface, the communication interface and the processor are coupled, and the processor is configured to run a computer program or instructions to implement the interference evaluation method as described in the first aspect and any possible implementation manner of the first aspect.

[0022] Specifically, the chip provided in the present application further comprises a memory for storing the computer program or instructions.

[0023] The above technical solutions at least have the following beneficial effects: the interference evaluation method provided in the present application, the computing device determines the interference coefficient of the coverage scene type of the target area, the target value of each parameter in the plurality of parameters (i.e., used to represent the parameter difference degree of the target area in the first coverage scene and the second coverage scene, the first coverage scene is a scene covered based on the RRU device and the optical direct device, and the second coverage scene is a scene covered based on the RRU device), and the weight corresponding to the target value of each parameter, and determines the interference value (i.e., used to represent the degree of influence of the target area affected by the interference) of the target area according to the interference coefficient, the target value of each parameter, and the weight corresponding to the target value of each parameter. Based on the above, the computing device can first determine the difference degree of the parameters in different coverage scenes based on only the parameters in the RRU device coverage scene and the parameters in the RRU device and optical direct device coverage scene, and then determine the signal interference degree (i.e., the interference value) between the RRU device and the optical direct device based on the above difference degree and other parameters (such as the interference coefficient and the weight value). In order to facilitate the subsequent operation personnel to optimize the coverage more accurately and directly based on the above interference value, thereby ensuring the signal quality of the user equipment. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 A structural diagram of a communication system provided by an embodiment of the present application is provided;

[0025] Figure 2 A flowchart of an interference evaluation method provided by an embodiment of the present application is provided;

[0026] Figure 3 A flowchart of another interference evaluation method provided by an embodiment of the present application is provided;

[0027] Figure 4 A flowchart of another interference evaluation method provided by an embodiment of the present application is provided;

[0028] Figure 5 A schematic diagram of a load diagram provided by an embodiment of the present application;

[0029] Figure 6 A structural schematic diagram of an interference evaluation device provided by an embodiment of the present application;

[0030] Figure 7 A structural schematic diagram of another interference evaluation device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0031] The interference evaluation method, device and storage medium provided by the embodiments of the present application are described in detail below with reference to the drawings.

[0032] The term "and / or" in this document merely describes an association relationship of associated objects, and indicates that there can be three relationships, for example, A and / or B can represent the three cases of A alone, A and B together, and B alone.

[0033] The terms "first" and "second" and the like in the specification and drawings of the present application are used to distinguish different objects or to distinguish different treatments of the same object, and are not used to describe a specific order of the objects.

[0034] In addition, the terms "include" and "have" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include other steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device.

[0035] It should be noted that in the embodiments of the present application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design schemes. Rather, the use of "exemplary" or "for example" is intended to present relevant concepts in a concrete manner.

[0036] In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0037] As Figure 1 shown, Figure 1 A structural schematic diagram of a communication system provided by an embodiment of the present application is shown. The communication system includes a computing device 101, a terminal device 102, an RRU device 103, and an optical direct device 104.

[0038] The computing device 101 is configured to determine an interference coefficient of a coverage scene type of the target area, a target value of each of the plurality of parameters, and a weight corresponding to the target value of each of the plurality of parameters, and determine an interference value of the target area according to the interference coefficient, the target value of each of the plurality of parameters, and the weight corresponding to the target value of each of the plurality of parameters.

[0039] The target value is used to represent the parameter difference degree of the target area in the first coverage scene and the second coverage scene; the first coverage scene is a scene covered based on the RRU device 103 and the optical direct device 104; the second coverage scene is a scene covered based on the RRU device 103; and the interference value is used to represent the degree of influence of the interference in the target area.

[0040] The terminal device 102 is configured to provide the computing device 101 with each of the plurality of parameters.

[0041] The terminal device 102 is a device with wireless communication function, which can be deployed on land, including indoor or outdoor, handheld or vehicle-mounted, and can also be deployed on water surface (such as ships, etc.). It can also be deployed in the air (such as airplanes, balloons and satellites, etc.).

[0042] In some examples, the terminal device 102, also referred to as a user equipment (UE), a mobile station (MS), a mobile terminal (MT), and a terminal, is a device that provides voice and / or data connectivity to users in a mobile communication network. For example, the terminal device 102 includes a handheld phone, a car-mounted device, and so on. Currently, the terminal device 102 can be a mobile phone, a tablet computer, a notebook computer, a palm computer, a mobile internet device (MID), a wearable device (for example, a smart watch, a smart bracelet, a pedometer, and so on), a vehicle-mounted device (for example, a car, a bicycle, an electric vehicle, an airplane, a ship, a train, a high-speed rail, and so on), a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a smart home device (for example, a refrigerator, a television, an air conditioner, an electricity meter, and so on), a smart robot, a workshop device, a wireless terminal in self driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, or a wireless terminal in a smart home, a flight device (for example, a smart robot, a hot air balloon, a drone, an airplane), and so on. In a possible application scenario of the present application, the terminal device is a terminal device that usually works on the ground, for example, a vehicle-mounted device. In the present application, for ease of description, a chip, for example, a system on a chip (SOC), a baseband chip, or other chips with communication functions deployed in the above devices can also be referred to as the terminal device 102.

[0043] Optionally, the terminal device 102 can be an embedded communication device or a user handheld communication device, including a mobile phone, a tablet computer, and so on.

[0044] As an example, in the embodiments of the present application, the terminal device 102 can also be a wearable device. The wearable device can also be referred to as a wearable smart device, which is a general term for devices that are designed and developed by applying wearable technology to daily wear, such as glasses, gloves, watches, clothing, and shoes. The wearable device is a portable device that is directly worn on the body or integrated into the clothes or accessories of the user. The wearable device is not only a hardware device, but also a powerful function achieved through software support and data interaction, cloud interaction. The general wearable smart device includes a full function, a large size, and can realize complete or partial functions without relying on a smart phone, such as a smart watch or smart glasses, and focuses on a certain application function and needs to cooperate with other devices such as a smart phone, such as various smart bracelets and smart jewelry for monitoring vital signs.

[0045] In addition, the communication system described in the embodiments of the present application is used to more clearly illustrate the technical solutions of the embodiments of the present application, and does not constitute a limitation on the technical solutions provided by the embodiments of the present application. It is known to those skilled in the art that, with the evolution of network architecture and the appearance of new communication systems, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0046] In the scenarios of shopping malls, office buildings, hotels, and comprehensive buildings, there are problems such as complex indoor environment and large coverage area, so a distributed indoor system is generally used for signal coverage. However, there is still a problem of poor coverage in the above scenarios. In order to solve the above problem, the optical direct device is used to pull the signal source base station far away and access the indoor distribution system to be used as the signal source of the distributed system. In this way, the above scenarios exist two kinds of coverage of the radio remote unit (RRU) device and the optical direct device, thereby improving the carrier frequency utilization rate, reducing the same frequency interference, and effectively accelerating the project construction progress.

[0047] At present, a plurality of MDT data of a distributed network is acquired first, and the plurality of MDT data is clustered according to three-dimensional position information in the MDT data, to obtain a plurality of groups of MDT data based on three-dimensional position clustering of a user terminal. Then, the network quality of the distributed network at a position corresponding to each three-dimensional position classification is determined according to the network perception quality of the user terminal represented by each group of clustered MDT data, and the interference source of the distributed network is located according to the network quality of the distributed network at the position corresponding to each three-dimensional position classification. The above method can efficiently and accurately diagnose the distributed network by using the MDT data, cluster the MDT data based on the three-dimensional position, determine the network quality of the position corresponding to the three-dimensional position classification after clustering, and then locate the interference source of the distributed network.

[0048] However, the above method can only determine the interference source, and cannot evaluate the interference degree of the specified area. Therefore, how to determine the degree of interference influence in the area covered by the RRU device and the optical direct device is a problem that needs to be solved and researched.

[0049] In order to solve the problems existing in the prior art, the embodiment of the present application proposes an interference evaluation method, which can determine the degree of interference influence in the area covered by the RRU device and the optical direct device. As shown in the formula (1), the method comprises the following steps: Figure 2

[0050] S201, the computing device determines the interference coefficient of the coverage scene type of the target area, the target value of each parameter in the plurality of parameters, and the weight corresponding to the target value of each parameter.

[0051] The target value is used to represent the parameter difference degree of the target area in the first coverage scene and the second coverage scene. The first coverage scene is a scene covered based on the RRU device and the optical direct device. The second coverage scene is a scene covered based on the RRU device.

[0052] In an example, the plurality of parameters can include: reference signal receiving power (RSRP) in the 4G network, RSRP in the 5G network, signal to interference plus noise ratio (SINR) in the 4G network, SINR in the 5G network, download rate (rate) in the 4G network, and download rate in the 5G network.

[0053] Optionally, the interference coefficients corresponding to different coverage scene types are different. As shown in Table 1, the coverage scene types can include: large residential community ground parking level coverage scene type, shopping mall, office building, hotel, comprehensive building coverage scene type, elevator and building coverage scene type, and same floor coverage scene type. The above four coverage scene types are explained as follows:

[0054] The interference coefficient of the large residential community ground parking level coverage scene type is 1.3. The large residential community ground parking level coverage scene type has the characteristics of large underground parking area, large inter-floor span, and long feeder line, which will cause serious source power loss in this kind of coverage scene, and large power demand. In order to solve the above problems, the operator can use the optical direct device to pull the signal of the source base station far away, realize the hybrid networking of the optical direct device and the RRU device, thereby expanding the coverage area of the source base station, improving the carrier frequency utilization rate, ensuring the balance of power and capacity, and reducing the inter-cell interference. ​

[0055] The interference coefficient of the shopping mall, office building, hotel, and comprehensive building coverage scenario type is 1.5. The shopping mall, office building, hotel, and comprehensive building coverage scenario type is characterized by complex indoor environment and large coverage area. For the ordinary scenario in this scenario type, the operation personnel generally adopts a room distribution system for signal coverage. However, for the special scenario (for example, a single-story large hotel or office building scenario) in this scenario type, the operation personnel can use RRU equipment to cover the low floors (for example, 1st to 3rd floors) and use optical direct equipment to cover the high floors (for example, 4th to 16th floors) under the condition that the capacity meets the requirements. In this way, the coverage requirements are met, the utilization rate of the source carrier frequency is improved, the overall investment is reduced, and the construction speed is accelerated.

[0056] The interference coefficient of the elevator and building coverage scenario type is 1.2. For the elevator scenario in this scenario type, the operation personnel generally adopts RRU equipment for signal coverage. However, for the building scenario in this scenario type, the operation personnel can use optical direct equipment for coverage.

[0057] The interference coefficient of the same layer coverage scenario type is 1.8. For this scenario type, the operation personnel adopts RRU equipment and optical direct equipment for signal coverage.

[0058] Table 1

[0059]

[0060]

[0061] In S202, the computing device determines the interference value of the target area according to the interference coefficient of the coverage scenario type of the target area, the target value of each parameter, and the weight corresponding to the target value of each parameter.

[0062] The interference value is used to represent the degree of influence of the target area.

[0063] In one possible implementation, the interference value of the target area satisfies the following formula 1:

[0064]

[0065] Wherein, G is the interference value of the target area. I m is the interference coefficient of the coverage scenario type of the target area. W(i) is the target value of the i-th parameter in the target value of the plurality of parameters. r(i) is the weight value corresponding to the target value of the i-th parameter. k is the number of the plurality of parameters.

[0066] It should be noted that the k can be 3 in the case of only 4G network coverage or only 5G network coverage. The k can be 6 in the case of 4G network coverage and 5G network coverage.

[0067] Optionally, the greater the G is, the greater the signal interference of the optical direct device to the RRU device is. The computing device can set an interference threshold (for example, the interference threshold is 2), and if the G is less than the interference threshold, it indicates that the planning scheme of the target area is relatively appropriate, and the interference is within an acceptable range. If the G is greater than or equal to the interference threshold, it indicates that the planning scheme of the target area is not appropriate, and there is greater signal interference of the optical direct device to the RRU device, which should be avoided as much as possible in subsequent planning.

[0068] In a possible implementation manner, the computing device can know from the comparison between the interference values of the multiple target areas and the interference threshold that the situation of the RRU device and the optical direct device having an overlapping coverage area in the same floor is avoided as much as possible, and the high-value area is avoided as much as possible to be covered by the optical direct device alone.

[0069] The technical scheme at least has the following beneficial effects: The interference evaluation method provided in the application, the computing device determines the interference coefficient of the coverage scene type of the target area, the target value of each parameter in the multiple parameters (that is, used to represent the parameter difference degree of the target area in the first coverage scene and the second coverage scene, the first coverage scene is a scene of coverage based on the RRU device and the optical direct device, and the second coverage scene is a scene of coverage based on the RRU device), and the weight corresponding to the target value of each parameter, and determines the interference value (that is, used to represent the degree of influence of the target area affected by the interference) of the target area according to the interference coefficient, the target value of each parameter, and the weight corresponding to the target value of each parameter. Based on the above, the computing device can first determine the difference degree of the parameters in different coverage scenes based on the parameters in the RRU device coverage scene and the parameters in the RRU device and optical direct device coverage scene, and then determine the signal interference degree (that is, the interference value) between the RRU device and the optical direct device based on the difference degree and other parameters (for example, the interference coefficient and the weight value). In order to facilitate the subsequent operation personnel to optimize the coverage more accurately and directly based on the interference value, and to ensure the signal quality of the user equipment.

[0070] In an optional embodiment, as shown in S201, the computing device determines the target value of each parameter in the multiple parameters, and in Figure 2 Based on the method embodiment shown in the figure, the embodiment provides a possible implementation manner, as shown in Figure 3 , Figure 3The flow chart of another interference evaluation method provided in the present application, the implementation process of the target value of each parameter in the plurality of parameters determined by the computing device can include the following steps S301-S303.

[0071] S301, the computing device obtains a plurality of parameters of each sampling point in the target area in the first coverage scenario and the second coverage scenario.

[0072] For example, Table 2 shows the plurality of parameters of sampling point #1 in the first coverage scenario and the second coverage scenario. As shown in Table 2 below, in the first coverage scenario, the RSRP in the 4G network is-78.14, the RSRP in the 5G network is-79.45, the SINR in the 4G network is 23.8, the SINR in the 5G network is 26.27, the download rate in the 4G network is 76.24, and the download rate in the 5G network is 95.66. In the second coverage scenario, the RSRP in the 4G network is-80.99, the RSRP in the 5G network is-83.45, the SINR in the 4G network is 28.02, the SINR in the 5G network is 28.37, the download rate in the 4G network is 94.40, and the download rate in the 5G network is 105.34.

[0073] Table 2

[0074]

[0075] The computing device performs S302-S303 on each parameter in the plurality of parameters to obtain the target value of each parameter:

[0076] S302, the computing device determines the target parameter of each sampling point in the first coverage scenario, and the difference between the target parameter of each sampling point in the second coverage scenario is the difference of the target parameter of each sampling point.

[0077] Wherein, the target parameter is any one of the plurality of parameters.

[0078] For example, the computing device can determine the difference between the RSRP of sampling point #2 in the first coverage scenario of the 4G network and the RSRP of sampling point #2 in the second coverage scenario of the 4G network as the difference of the RSRP of sampling point #2 in the 4G network.

[0079] S303, the computing device determines the average value of the parameter difference of the M sampling points as the average value of the difference of the target parameter.

[0080] Exemplarily, Table 3 shows target values of a plurality of parameters. As shown in Table 3, compared with the first coverage scenario, in the second coverage scenario, the RSRP (D_RSRP_4G) in the 4G network decreases by 2.85 dBm, the SINR (D_SINR_4G) in the 4G network increases by 4.22 dB, the download rate (D_rate_4G) in the 4G network increases by 18.16 Mbps, the RSRP (D_RSRP_5G) in the 5G network decreases by 3.97 dBm, the SINR (D_SINR_5G) in the 5G network increases by 1.28 dB, and the download rate (D_rate_5G) in the 5G network increases by 6.04 Mbps.

[0081] Table 3

[0082] Element_4G D-value Element_5G D-value D_RSRP_4G -2.85 D_RSRP_5G -3.97 D_SINR_4G +4.22 D_SINR_5G +1.28 D_rate_4G +18.16 D_rate_5G +6.04

[0083] The technical solutions have at least the following beneficial effects: The interference evaluation method provided in the application, the computing device obtains a plurality of parameters of each sampling point in the target region in the first coverage scenario and the second coverage scenario, and performs the following operation on each parameter in the plurality of parameters to obtain a target value of each parameter: determining a target parameter of each sampling point in the first coverage scenario, a difference between the target parameter of each sampling point in the first coverage scenario and the target parameter of each sampling point in the second coverage scenario is a difference of the target parameter of each sampling point (that is, any parameter in the plurality of parameters), and determining an average value of the parameter difference of the M sampling points as an average value of the difference of the target parameter, which provides a data basis for the computing device to determine the interference value of the target region based on the target value.

[0084] In an optional embodiment, as shown in S201, the computing device determines a weight corresponding to the target value of each parameter, and in Figure 2 Based on the method embodiment shown, the embodiment provides a possible implementation manner, as shown in Figure 4 As shown, Figure 4 For the flowchart of another interference evaluation method provided in the application, the implementation process of the computing device determining the weight corresponding to the target value of each parameter can include the following steps S401 to S404.

[0085] S401, the computing device determines data of a plurality of factors corresponding to the target value of each parameter.

[0086] The data includes eigenvalues, variance explanation rates, cumulative variance explanation rates, and loading coefficients.

[0087] Optionally, the eigenvalues and variance explanation rates corresponding to the target values of different parameters are the same, but the eigenvalues and variance explanation rates of different factors are different.

[0088] For example, as shown in Table 4 below, the rotated eigenvalue corresponding to factor 1 is 2.87, the rotated eigenvalue corresponding to factor 2 is 2.609, and the rotated eigenvalue corresponding to factor 3 is 0.521. The rotated variance explained rate corresponding to factor 1 is 47.828%, the rotated variance explained rate corresponding to factor 2 is 43.481%, and the rotated variance explained rate corresponding to factor 3 is 8.69%. The rotated cumulative variance explained rate corresponding to factor 1 is 47.828%, the rotated cumulative variance explained rate corresponding to factor 2 is 91.31%, and the rotated cumulative variance explained rate corresponding to factor 3 is 100%.

[0089] Table 4

[0090]

[0091] Optionally, the load coefficients corresponding to the target values of different parameters are different, and the load coefficients of different factors are also different.

[0092] For example, as shown in Table 5 below, the load coefficient of factor 1 of D_RSRP_4G is 0.937, the load coefficient of factor 2 of D_RSRP_4G is 0.253, and the load coefficient of factor 3 of D_RSRP_4G is 0.24. The load coefficient of factor 1 of D_SINR_4G is -0.137, the load coefficient of factor 2 of D_SINR_4G is -0.987, and the load coefficient of factor 3 of D_SINR_4G is -0.086. The load coefficient of factor 1 of D_rate_4G is 0.666, the load coefficient of factor 2 of D_rate_4G is 0.719, and the load coefficient of factor 3 of D_rate_4G is 0.199. The load coefficient of factor 1 of D_RSRP_5G is 0.964, the load coefficient of factor 2 of D_RSRP_5G is 0.245, and the load coefficient of factor 3 of D_RSRP_5G is 0.108. The load coefficient of factor 1 of D_SINR_5G is -0.516, the load coefficient of factor 2 of D_SINR_5G is -0.781, and the load coefficient of factor 3 of D_SINR_5G is -0.352. The load coefficient of factor 1 of D_rate_5G is 0.578, the load coefficient of factor 2 of D_rate_5G is 0.62, and the load coefficient of factor 3 of D_rate_5G is 0.53.

[0093] Table 5

[0094]

[0095] In a possible implementation manner, before S201, the computing device needs to determine the number of the above factors in advance according to the components corresponding to each factor in the component score coefficient matrix.

[0096] Optionally, the above uses the ingredient score coefficient matrix (T) to establish a relationship equation between the factors and the parameters. The factor score matrix is calculated from the parameter matrix and the ingredient score coefficient matrix (T), which can satisfy the following formula 2 as follows:

[0097] S=A*T Formula 2

[0098] Wherein, S is the factor score matrix. A is the parameter matrix. T is the ingredient score coefficient matrix.

[0099] Optionally, the above parameter matrix (A) can satisfy the following formula 3:

[0100] A=[D_RSRP_4G D_SINR_4G D_rate_4G …… D_rate_5G] Formula 3

[0101] Exemplarily, as shown in the following Table 6, the ingredient of factor 1 of D_RSRP_4G is 0.813, the ingredient of factor 2 of D_RSRP_4G is -1.063, the ingredient of factor 3 of D_RSRP_4G is -1.438. The ingredient of factor 1 of D_SINR_4G is 0.063, the ingredient of factor 2 of D_SINR_4G is -0.813, the ingredient of factor 3 of D_SINR_4G is 2. The ingredient of factor 1 of D_rate_4G is 1.125, the ingredient of factor 2 of D_rate_4G is 0.5, the ingredient of factor 3 of D_rate_4G is 0.156. The ingredient of factor 1 of D_RSRP_5G is 0.125, the ingredient of factor 2 of D_RSRP_5G is -0.625, the ingredient of factor 3 of D_RSRP_5G is 0. The ingredient of factor 1 of D_SINR_5G is -0.25, the ingredient of factor 2 of D_SINR_5G is 0, the ingredient of factor 3 of D_SINR_5G is -1. The ingredient of factor 1 of D_rate_5G is -0.125, the ingredient of factor 2 of D_rate_5G is -0.375, the ingredient of factor 3 of D_rate_5G is 2.25.

[0102] Table 6

[0103]

[0104] Optionally, Figure 5 A load diagram provided by an embodiment of the present application is shown. The load diagram is obtained by Figure 5It can be known that the relationship between each factor and the load value is high, for example, the correlation and relevance between D_RSRP_4G and D_RSRP_5G, D_SINR_4G and D_SINR_5G, D_rate_4G and D_rate_5G, and we can name the three common factors as RSRP, SINR, and rate.

[0105] The computing device performs S402 to S404 on each target value of the plurality of parameters to obtain the weight corresponding to each target value of the plurality of parameters:

[0106] S402, the computing device determines the ratio of the load coefficient corresponding to each factor in the plurality of factors of the average value of the difference value of the target parameter to the square root of the eigenvalue corresponding to each factor, which is the linear combination coefficient of each factor.

[0107] Wherein, the target parameter is any one of the plurality of parameters.

[0108] For example, if the target parameter is D_RSRP_4G, the computing device can determine the linear combination coefficients of factor 1, factor 2, and factor 3 of D_RSRP_4G according to the load coefficients of the factors (e.g., factor 1, factor 2, and factor 3) of D_RSRP_4G and the rotated eigenvalues.

[0109] S403, the computing device performs weighted summation on the first value of each factor to obtain a second value, and determines the ratio of the second value to the sum of the variance explanation rates of the plurality of factors as a third value.

[0110] Wherein, the first value is the ratio of the linear combination coefficient to the variance explanation rate.

[0111] Optionally, the third value can also be referred to as a comprehensive score coefficient.

[0112] S404, the computing device performs normalization processing on the third value to obtain the weight corresponding to the average value of the difference value of the target parameter.

[0113] For example, as shown in Table 7 below, the weight of D_RSRP_4G is 16.25%, the weight of D_SINR_4G is 14.14%, the weight of D_rate_4G is 18.23%, the weight of D_RSRP_5G is 15.77%, the weight of D_SINR_5G is 17.90%, and the weight of D_rate_5G is 17.71%.

[0114] Table 7

[0115]

[0116] The technical scheme has at least the following beneficial effects: the interference evaluation method provided in the application, the computing device determines data of multiple factors corresponding to the target value of each parameter; the data includes eigenvalues, variance explanation rates, and loading coefficients, and the following operations are performed on the target value of each parameter to obtain the weight corresponding to the target value of each parameter: the ratio of the loading coefficient corresponding to each factor of the multiple factors of the average value of the difference value of the target parameter to the square root of the eigenvalue corresponding to each factor is the linear combination coefficient of each factor; the target parameter is any one of the multiple parameters; a first value of each factor is weighted and summed to obtain a second value, and the ratio of the second value to the sum of the variance explanation rates of the multiple factors is determined as a third value; the first value is the ratio of the linear combination coefficient to the variance explanation rate; the third value is normalized to obtain the weight corresponding to the average value of the difference value of the target parameter, which can provide data preparation for the computing device to determine the interference value of the target area based on the weight corresponding to the target value of each parameter in the subsequent.

[0117] It can be understood that the interference evaluation method described above can be implemented by an interference evaluation device. In order to realize the above functions, the interference evaluation device includes the hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, in combination with the modules and algorithm steps of each example described in the embodiments disclosed in the present application, the embodiments disclosed in the present application can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is realized by hardware or computer software driven hardware depends on the specific application and design constraints of the technical scheme. Professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments disclosed in the present application.

[0118] The embodiments disclosed in the present application can divide the functional modules according to the interference evaluation device generated by the above method examples, for example, each functional module can be divided according to each function, or two or more functions can be integrated in one processing module. The above integrated module can be realized in the form of hardware or in the form of a software functional module. It should be noted that the division of the modules in the embodiments disclosed in the present application is illustrative, and is only a logical functional division. When actually implemented, there can be another division method.

[0119] Figure 6 A structural schematic diagram of an interference evaluation device provided by the embodiments of the present application is shown in FIG. 6. Figure 6 As shown in FIG. 6, the interference evaluation device 60 can be used to execute the interference evaluation method shown in FIG. 5. Figure 2 - Figure 4 The interference evaluation device 60 includes a processing unit 601.

[0120] The processing unit 601 is configured to determine an interference coefficient of a coverage scene type of the target area, a target value of each of a plurality of parameters, and a weight corresponding to the target value of each of the plurality of parameters; the target value is used to represent a parameter difference degree of the target area in a first coverage scene and a second coverage scene; the first coverage scene is a scene in which coverage is performed based on an RRU device and an optical direct device; the second coverage scene is a scene in which coverage is performed based on the RRU device; the processing unit 601 is further configured to determine an interference value of the target area according to the interference coefficient, the target value of each of the plurality of parameters, and the weight corresponding to the target value of each of the plurality of parameters; the interference value is used to represent a degree of influence of interference in the target area.

[0121] In a possible implementation, the interference evaluation apparatus 60 further includes a communication unit 602; the communication unit 602 is configured to obtain the plurality of parameters of each of M sampling points in the target area in the first coverage scene and the second coverage scene; the processing unit 601 is further configured to perform the following operation on each of the plurality of parameters to obtain the target value of each of the plurality of parameters: determining a target parameter of each of the sampling points in the first coverage scene, and a difference value between the target parameter of each of the sampling points in the second coverage scene and the target parameter of each of the sampling points in the first coverage scene is a difference value of the target parameter of each of the sampling points; the target parameter is any one of the plurality of parameters; and determining an average value of the difference values of the target parameters of the M sampling points as an average value of the difference values of the target parameters.

[0122] In a possible implementation, the processing unit 601 is further configured to determine data of a plurality of factors corresponding to the target value of each of the plurality of parameters; the data includes an eigenvalue, a variance explanation rate, and a loading coefficient; the processing unit 601 is further configured to perform the following operation on the target value of each of the plurality of parameters to obtain the weight corresponding to the target value of each of the plurality of parameters: determining a ratio between a loading coefficient corresponding to each of the plurality of factors of the average value of the difference values of the target parameters and a square root of an eigenvalue corresponding to the factor as a linear combination coefficient of the factor; the target parameter is any one of the plurality of parameters; performing weighted summation on a first value of each of the factors to obtain a second value, and determining a ratio between the second value and a sum of variance explanation rates of the plurality of factors as a third value; the first value is a ratio between the linear combination coefficient and the variance explanation rate; and performing normalization processing on the third value to obtain a weight corresponding to the average value of the difference values of the target parameters.

[0123] In a possible implementation, the interference value of the target area satisfies the following formula:

[0124]

[0125] wherein G is the interference value of the target area; I m is the interference coefficient of the coverage scene type of the target area; W(i) is a target value of an i-th parameter in the target values of the plurality of parameters; and r(i) is a weight value corresponding to the target value of the i-th parameter.

[0126] In the case of implementing the functions of the above-mentioned integrated modules in the form of hardware, the embodiments of the present application provide a possible structural diagram of the interference assessment device involved in the above-mentioned embodiments. As shown in Figure 7 , an interference assessment device 70, for example, for performing the interference assessment method shown in Figure 2 - Figure 4 . The interference assessment device 70 comprises a processor 701, a memory 702, and a bus 703. The processor 701 and the memory 702 can be connected through the bus 703. Optionally, the interference assessment device 70 can further comprise a communication interface 704 and an input / output interface 705.

[0127] The processor 701 is the control center of the user equipment, which can be one processor or a general term of multiple processing elements. For example, the processor 701 can be a general central processing unit 702 (CPU), or other general-purpose processors, etc. Among them, the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0128] Optionally, the processor 701 can be implemented in the form of a general-purpose CPU, a microprocessor, an application-specific integrated circuit, or one or more integrated circuits, etc., for implementing interference assessment to realize the technical solutions provided by the embodiments of the present application.

[0129] As an example, in combination with Figure 6 , the functions implemented by the processing unit 601 in the interference assessment device are the same as those of the processor 701 in Figure 7 .

[0130] As an embodiment, the processor 701 can include one or more CPUs, for example, the CPU 0 and the CPU 1 shown in Figure 7 .

[0131] The memory 702 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage devices, or any other medium capable of carrying or storing desired program codes in the form of instructions or data structures and accessible by a computer, but not limited to this.

[0132] Optionally, the memory 702 can store the RSRP, SINR, rate average (Average), maximum (Maximum), minimum (Minimum), segmented interval percentage, total sampling points and other index data of the 4G network and 5G network collected by the wireless test device, and the operating system and other application programs, and the relevant program codes are stored in the memory 702 and called and executed by the processor 701.

[0133] As a possible implementation, the memory 702 can exist independently of the processor 701, and the memory 702 can be connected to the processor 701 through the bus 703, for storing instructions or program codes. When the processor 701 calls and executes the instructions or program codes stored in the memory 702, the map drawing method provided by the embodiment of the application can be implemented.

[0134] In another possible implementation, the memory 702 can also be integrated with the processor 701.

[0135] The bus 703 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus or the like. The bus can be divided into an address bus, a data bus, a control bus and the like. For the convenience of representation, Figure 7 Only one thick line is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0136] The communication interface 704 is used to connect with other devices through a communication network. The communication network can be an Ethernet, a wireless access network, a wireless local area network (WLAN) or the like. The communication interface 704 can include a communication unit 602 for receiving data, and can also include an acquisition unit and a sending unit.

[0137] Optionally, the communication interface 704 is used to connect a communication module to realize the communication interaction between the device and other devices. The communication module generally realizes the communication through a wired mode (such as optical fiber and network cable and the like) and a base station, which is convenient for remote data adjustment and extraction of base station operating parameters and background index data and the like, and can also be realized through a wireless mode to facilitate other mobile terminal devices to upload the test site data.

[0138] In one design, the communication interface in the interference evaluation device 70 provided by the embodiment of the application can also be integrated in the processor.

[0139] The input / output interface 705 is configured to connect with an input / output module to realize information input and output.

[0140] It should be noted that, Figure 7 The illustrated structure does not constitute a limitation on the interference assessment device 70. In addition to Figure 7 The interference assessment device 70 can include more or fewer components than those shown, or combine certain components, or different component arrangements, in addition to the illustrated components.

[0141] Through the description of the above embodiments, those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of functional modules is taken as an example, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0142] The computer readable storage medium, for example, can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to the processor, so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). In the embodiments of the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus.

[0143] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any change or replacement within the technical scope disclosed by the present application should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An interference assessment method, characterized in that: include: Obtain multiple parameters of each sampling point in the first coverage scenario and the second coverage scenario among M sampling points in the target area; The first coverage scenario is a scenario based on RRU equipment and optical direct equipment for coverage; The second coverage scenario is a scenario based on the RRU device for coverage; the optical direct device is used to pull the signal farther and access the indoor distribution system to serve as the signal source of the indoor distribution system; Performing the following operation on each parameter of the plurality of parameters to obtain a target value of each parameter: determining a target parameter of each sampling point in a first coverage scenario, wherein a difference between the target parameter of each sampling point in a second coverage scenario and the target parameter of each sampling point is the difference in the target parameter of each sampling point; The target parameter is any one of the multiple parameters; determining the average value of the parameter differences of the M sampling points as the average value of the target parameter differences; The target value is used to represent the parameter difference between the target area in the first coverage scenario and the second coverage scenario; Determining data of multiple factors corresponding to the target value of each parameter; the data includes: characteristic roots, variance explanation rates, and loading coefficients; The following operations are performed on the target value of each parameter to obtain the weight corresponding to the target value of each parameter: Determine the load coefficient corresponding to each factor in the multiple factors for the average value of the difference of the target parameter, and the ratio of the square root of the characteristic root corresponding to each factor is the linear combination coefficient of each factor; the target parameter is any parameter among the multiple parameters; Performing a weighted summation on the first value of each factor to obtain a second value, and determining a ratio of the second value to the sum of the variance explanation rates of the multiple factors as a third value; the first value is the ratio of the linear combination coefficient to the variance explanation rate; Normalizing the third value to obtain a weight corresponding to an average value of the difference of the target parameter; Determining an interference coefficient of a coverage scenario type of the target area; An interference value of the target area is determined according to the interference coefficient, the target value of each parameter, and the weight corresponding to the target value of each parameter; the interference value is used to characterize the degree of influence of the interference in the target area.

2. The method according to claim 1, characterized in that The interference value of the target area satisfies the following formula: Wherein, G is the interference value of the target area; I m is the interference coefficient of the coverage scene type of the target area; W(i) is the target value of the i-th parameter among the target values ​​of the multiple parameters; r(i) is the weight value corresponding to the target value of the i-th parameter; k is the number of the multiple parameters.

3. An interference assessment device, characterized in that: include: a communication unit and a processing unit; The communication unit is configured to obtain a plurality of parameters of each of the M sampling points in the target area in the first coverage scenario and the second coverage scenario; The first coverage scenario is a scenario based on RRU equipment and optical direct equipment for coverage; The second coverage scenario is a scenario based on the RRU device for coverage; the optical direct device is used to pull the signal farther and access the indoor distribution system to serve as the signal source of the indoor distribution system; The processing unit is further configured to perform the following operation on each parameter of the plurality of parameters to obtain a target value of each parameter: determining a target parameter of each sampling point in a first coverage scenario, wherein a difference between the target parameter of each sampling point in a second coverage scenario is a difference in the target parameter of each sampling point; The target parameter is any one of the multiple parameters; determining the average value of the parameter differences of the M sampling points as the average value of the target parameter differences; The target value is used to represent the parameter difference between the target area in the first coverage scenario and the second coverage scenario; The processing unit is further configured to determine data of multiple factors corresponding to the target value of each parameter; the data including: characteristic roots, variance explanation rates, and loading coefficients; The processing unit is further configured to perform the following operations on the target value of each parameter to obtain a weight corresponding to the target value of each parameter: determining a load coefficient corresponding to each factor in a plurality of factors of an average value of a difference value of the target parameter, and a ratio of a square root of a characteristic root corresponding to each factor to the load coefficient of each factor is a linear combination coefficient of each factor; the target parameter is any one of the plurality of parameters; performing a weighted summation on a first value of each factor to obtain a second value, and determining a third value as a ratio of the second value to the sum of variance explanation rates of the plurality of factors; the first value is a ratio of the linear combination coefficient to the variance explanation rate; and performing normalization processing on the third value to obtain a weight corresponding to the average value of the difference value of the target parameter; The processing unit is configured to determine an interference coefficient of a coverage scenario type of the target area; The processing unit is further used to determine the interference value of the target area based on the interference coefficient, the target value of each parameter, and the weight corresponding to the target value of each parameter; the interference value is used to characterize the degree of interference influence in the target area.

4. The device according to claim 3, characterized in that The interference value of the target area satisfies the following formula: Wherein, G is the interference value of the target area; I m is the interference coefficient of the coverage scene type of the target area; W(i) is the target value of the i-th parameter among the target values ​​of the multiple parameters; r(i) is the weight value corresponding to the target value of the i-th parameter; k is the number of the multiple parameters.

5. An interference assessment device, characterized in that: include: A processor and a communication interface; the communication interface is coupled to the processor, and the processor is used to run a computer program or instruction to implement the interference assessment method as described in any one of claims 1-2.

6. A computer-readable storage medium having instructions stored therein, characterized in that: When a computer executes the instruction, the computer executes the interference assessment method described in any one of claims 1-2.

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