Network evaluation method and related devices

Abstract

The application provides a network evaluation method and related equipment, wherein the network evaluation method comprises: obtaining first information of a target service in a target area, the first information comprising a service guarantee rate; determining demand rate information of the target service according to the first information; and determining cell demand information of the target service according to the demand rate information. The data acquisition of the network evaluation method is simpler and takes less time, thereby improving the efficiency of network evaluation.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of communication, and in particular to a network evaluation method and related device. BACKGROUND

[0002] The network slice is composed of a wireless sub-network slice, a transmission sub-network slice and a core sub-network slice.

[0003] In the wireless sub-network slice creation process, a survey process needs to be performed. In a given slice coverage area, the load performance indicators of the existing wireless network need to be monitored to determine the satisfaction of the slice service demand. At present, there is no existing load performance indicator for reference for newly opened services. The satisfaction of the existing wireless network to the second service needs to be determined manually, which is high in labor cost and time-consuming. SUMMARY

[0004] Embodiments of the present application aim to provide a network evaluation method, an information processing method, a recording method and a device, and solve the problem of high labor cost and long time consumption in network evaluation in the prior art.

[0005] To solve the above problem, in a first aspect, embodiments of the present application provide a network evaluation method, characterized in that it comprises:

[0006] obtaining first information of a target service in a target area, the first information comprising a service guarantee rate;

[0007] determining demand rate information of the target service according to the first information;

[0008] determining cell demand information of the target service according to the demand rate information.

[0009] In a second aspect, embodiments of the present application provide a network evaluation device, characterized in that it comprises:

[0010] a first obtaining module for obtaining first information of a target service in a target area, the first information comprising a service guarantee rate;

[0011] a first determining module for determining demand rate information of the target service according to the first information;

[0012] a second determining module for determining cell demand information of the target service according to the demand rate information.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and capable of running on the processor, and when the computer program is executed by the processor, the steps of the network evaluation method described above are implemented.

[0014] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the network evaluation method described above are implemented.

[0015] In the embodiment of the present application, by obtaining the first information of the target service, the first information includes the service guarantee rate, the first information can be determined before or at the beginning of network operation, and according to the first information, the demand rate of the target service can be determined, and then the cell demand of the target service can be determined. The service guarantee rate is relatively easy to obtain, and the demand of the target service for the cell can be determined without manual evaluation. Compared with the network evaluation method in the related art, the data acquisition is simpler, the labor cost is reduced, the time consumption is shorter, and the efficiency of network evaluation is improved. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the description of the embodiments of the present application will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0017] Figure 1 is a service slice opening process;

[0018] Figure 2 is a flowchart of the network evaluation method provided by the embodiment of the present application;

[0019] Figure 3 is a schematic diagram of a network evaluation method provided by the embodiment of the present application;

[0020] Figure 4 is a flowchart of a network evaluation method provided by the embodiment of the present application;

[0021] Figure 5 is a structural diagram of the network evaluation device provided by the embodiment of the present application;

[0022] Figure 6 is a structural diagram of the electronic device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0023] With reference to the drawings and embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of the present application.

[0024] The terms "first", "second", and the like in this application are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device including a series of steps or units does not necessarily have to include only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product, or device. In addition, "and / or" is used in this application to represent at least one of the connected objects, for example, A and / or B and / or C represents 7 cases including A alone, B alone, C alone, A and B both exist, B and C both exist, A and C both exist, and A, B and C all exist.

[0025] In the embodiments of the present application, the words "exemplary" or "for example" are used to represent an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words "exemplary" or "for example" are used to present the relevant concept in a specific way.

[0026] For the convenience of understanding, some contents related to the embodiments of the present application are described as follows:

[0027] 1) Slice service, the slice service refers to classification of services based on different application scenarios, and multiple logical networks are divided on independent physical networks to serve different application scenarios. Different slice services have different priorities, and the resources and quality of service provided by the network are also different. Taking the 5th Generation Mobile Communication Technology (5G) as an example, the application scenarios of 5G slice services can include mobile broadband, massive Internet of Things, and mission-critical Internet of Things, mobile broadband includes, for example, 4K / 8K ultra-high-definition video, holographic projection, Augmented Reality (AR) / Virtual Reality (VR), etc., massive Internet of Things includes, for example, measurement, construction, agriculture, logistics, smart city / home, etc., and mission-critical Internet of Things includes, for example, unmanned driving, automatic factory, smart grid, etc. Among them, the opening process of the slice service is, for example,Figure 1 as shown:

[0028] Step 101, a communication service management function (CSMF) acquires user end-to-end service requirements.

[0029] Step 102, the CSMF sends a service order to a slice management function (NSMF).

[0030] Step 103, the NSMF decomposes the end-to-end service requirements.

[0031] Step 104, the NSMF performs network resource exploration and evaluation, and selects appropriate professional subnet slices for the service.

[0032] Step 105, the NSMF sends each professional subnet slice service request to a subnet slice management function (NSSMF).

[0033] Step 106, the NSSMF generates network element configurations for each professional subnet slice.

[0034] Step 107, the NSSMF sends network element service configurations to the network element.

[0035] Step 108, the network element sends a response reply of the network element service configuration to the NSSMF.

[0036] Step 109, the NSSMF sends a subnet slice creation result reply to the NSMF.

[0037] Step 110, the NSMF sends a service opening / slice creation result reply to the CSMF.

[0038] 2) Exclusive service, exclusive service refers to a service that allocates resources exclusively to the service, and is dedicated to the private network. The slice service can include exclusive slice service, and the exclusive slice service can include exclusive slice service.

[0039] 3) Shared service, shared service refers to a service that allocates resources that can be shared with other services. The slice service can include shared slice service, and the shared slice service can include preferred slice service and exclusive slice service. The preferred slice service is a public network service, i.e., a service based on a general network architecture, and the exclusive slice service is a public network dedicated service, i.e., a wireless network enhanced coverage provided on the basis of a public network.

[0040] It should be noted that the network evaluation method provided in the embodiments of the present application can be applied to a 5G network, a 4th Generation Mobile Communication Technology (4G) network, or a network of any other subsequent mobile communication technology, and is not limited here.

[0041] Please refer to Figure 2 , Figure 2 is a flowchart of a network evaluation method provided by the embodiments of the present application.

[0042] As Figure 2 shown, the network evaluation method can include the following steps:

[0043] Step 201, obtaining first information of a target service in a target area.

[0044] The first information includes a service guarantee rate.

[0045] In this step, the target area refers to an area for network evaluation. In actual applications, a certain area needs to be delimited for network evaluation, which can be a residential area, an industrial park, or a geographic area, and the specific area can be determined according to actual conditions, which is not limited here.

[0046] The target service can include one or more services that have been opened in the target area, or one or more services to be opened in the target area. The service type of the target service can be a dedicated service, a shared service, or a To Customer (ToC) public service. The application scenario of the target service can be unmanned driving, smart city / family, VR / AR, etc., and the specific application scenario can be determined according to actual conditions, which is not limited here.

[0047] The first information can include any information that can represent the service characteristics of the target service, which can include but is not limited to the service type, the application scenario of the service, the busy time, the user coverage range, etc., and is not limited here. The service guarantee rate can represent the minimum data transmission rate of the target service. In specific implementation, the service guarantee rate can be determined according to the service demand of the target service. Optionally, each service corresponds to a service model, and the service guarantee rate of the target service can be determined based on the service model of the target service.

[0048] Step 202, determining demand rate information of the target service according to the first information.

[0049] In this step, the demand rate information of the target service can include any information that can represent the rate demand characteristics of the target service. According to the service characteristics of the target service, the requirement of the target service for the rate can be determined. In an optional implementation, the demand rate information includes a demand rate, and the demand rate can be determined based on the service guarantee rate, for example, the demand rate is equal to the service guarantee rate, or the demand rate can be determined based on the service guarantee rate and considering the influencing factors of the service.

[0050] In step 203, the cell demand information of the target service is determined according to the demand rate information.

[0051] In this step, the cell demand information of the target service can include any information that can represent the cell demand characteristics of the target service. According to the demand of the target service for the rate, the demand of the target service for the cell can be determined. In an optional implementation, the cell demand information includes the demand cell number, that is, the number of cells required by the service, and further, the cell demand information can include but is not limited to the number of base stations, the location of the base station, the performance of the base station, etc., which can be determined according to the actual situation and is not limited here.

[0052] Since the related art needs to collect the network load performance indicators of the base station cells in the network operation process to evaluate the demand of the service in the network for the network capacity, or to locate the areas or cells with insufficient capacity based on the existing wireless side expansion rules and user complaints, etc. to perform regional reheat. This method needs network operation for a period of time, so that the evaluation of the service demand has obvious lag. In the case where there is no data for reference in the early stage of network operation, manual judgment of service demand is required.

[0053] The network evaluation method provided by the embodiment of the present application can determine the demand rate of the target service according to the first information including the service guarantee rate, and further determine the cell demand of the target service, without manual judgment, that is, the demand of the target service for the cell can be determined. Compared with the network evaluation method in the related art, the labor cost is reduced, and the efficiency of network evaluation is improved. In addition, the related information does not need to be collected after network operation for evaluation, but the service demand can be evaluated and predicted in the early stage of network operation, the network cell deployment is completed in the early stage, the reheat work in the later stage is reduced, and the network operation cost is reduced.

[0054] Optionally, the service guarantee rate comprises at least one of a service uplink guarantee rate and a service downlink guarantee rate. In this embodiment, the service guarantee rate can be determined according to the service characteristics. For example, if the target service is mainly uplink service, the service guarantee rate can be the service uplink guarantee rate; or if the target service is mainly downlink service, the service guarantee rate can be the service downlink guarantee rate; or if the uplink service and the downlink service of the target service are balanced, the service guarantee rate can comprise the service downlink guarantee rate and the service uplink guarantee rate.

[0055] Optionally, in the case where the service guarantee rate comprises the service uplink guarantee rate and the service downlink guarantee rate, the cell demand information of the target service is determined according to the demand rate information, comprising:

[0056] The uplink demand cell number and the downlink demand cell number are determined according to the service uplink guarantee rate and the service downlink guarantee rate of the target service, respectively.

[0057] The maximum demand cell number between the uplink demand cell number and the downlink demand cell number is determined as the demand cell number of the target service.

[0058] In this embodiment, the uplink demand cell number and the downlink demand cell number of the target service are determined respectively, and the larger value between them is determined as the demand cell number of the target service, so as to ensure that the determined cell number can meet the uplink service and the downlink service of the target service.

[0059] It should be noted that the uplink demand cell number can be determined based on uplink data, and the downlink demand cell number can be determined based on downlink data. The implementation manners of determining the uplink demand cell number and the downlink demand cell number can be the same or different, which can be determined according to actual conditions, and is not limited herein.

[0060] Optionally, the target service comprises a service to be opened in a target area, and in the case where the service to be opened is a slice service, the network evaluation method can be executed in step 104 shown in the figure, i.e., before opening a new slice service in the target area, the network resources of the target area can be evaluated based on the network evaluation method provided in this embodiment. Figure 1

[0061] In this embodiment, there are two cases: case one, the service to be opened is a dedicated service; and case two, the service to be opened is a shared service. The above two cases will be described respectively as follows:

[0062] Case one

[0063] ​In the present case, the service to be opened is a dedicated service, and therefore the network resources of the existing cells in the target area cannot be allocated to the service to be opened, and a new cell needs to be built in the target area to provide network resources for the service to be opened.

[0064] Optionally, the target service includes a first type of service, and the first type of service is a service to be opened in the target area; before determining the demand rate information of the target service according to the first information, the method further includes:

[0065] determining user information of the target area, wherein the user information includes an active user number;

[0066] determining the demand rate information of the target service according to the first information, including:

[0067] determining a first demand rate of the target service according to the service guarantee rate and the active user number.

[0068] In the present embodiment, the first type of service can be a dedicated service to be opened in the target area, and since the first type of service is a dedicated service, the total number of services opened in the target area is 1.

[0069] The user information can include any information that can represent the characteristics of the users in the target area, and in addition to the active user number, can include but is not limited to a total user number, a user activation ratio, an online user number, a connection user average peak ratio, a maximum connection user number, etc., without limitation. The active user number can represent the effective user number of the first type of service in the target area, i.e., the number of users who can use the first type of service. The active user number can be equal to the total user number in the target area, or can be less than the total user number in the target area.

[0070] In an optional embodiment, determining the user information of the target area includes:

[0071] obtaining a total user number, a user activation ratio, and a preset user development coefficient in the target area;

[0072] determining the active user number according to the total user number, the user activation ratio, and the user development coefficient.

[0073] In the present embodiment, the active user number can be determined based on the total user number, the user activation ratio, and the user development coefficient. Specifically, the total user number, the user activation ratio, and the user development coefficient can be multiplied to obtain the active user number.

[0074] The total user number can be determined by counting the resident population in the target area, or can be directly obtained from a radio access network element management system (OMC), and the specific method can be determined according to actual conditions, without limitation.

[0075] The user activation ratio can represent the relationship between the number of users activating network services in the target area and the total number of users, and the user activation ratio can be the same for different types of services. Alternatively, the user activation ratio can be determined according to the ratio of the number of radio resource control (RRC) connected users in the target area to the number of issued mobile communication cards. The number of RRC connected users can refer to the number of users in the target area who have activated mobile communication cards, and the number of issued mobile communication cards can be the number of mobile communication cards produced by the operator, for example, 1000 mobile communication cards are produced in the target area, and 900 users have activated the cards, so the user activation ratio is 0.9. The number of RRC connected users and the number of issued mobile communication cards can be determined based on the data of the services activated in the target area, which is not limited here.

[0076] The user development coefficient can represent the development trend of users under the service, which can be determined according to the service development plan and the actual situation. For example, if the to-be-activated exclusive service has a short time limit and is only activated in a specific time period, the user development coefficient can be determined as 1; or if the to-be-activated exclusive service has a long time limit and even needs to expand the service coverage and the number of users in the future, the user development coefficient can be determined as 1.2 or 1.5.

[0077] In this embodiment, since the to-be-activated exclusive service needs to build a new cell, there is no historical network operation data to refer to, and the service demand can be evaluated based on the user information in the target area, thereby improving the accuracy of network evaluation. Specifically, the first demand rate of the first type of service is determined according to the service guarantee rate and the number of activated users. The first demand rate can represent the total rate requirement value of the first type of service, and the cell demand information of the first type of service is determined accordingly.

[0078] In this embodiment, optionally, determining the first demand rate includes two implementation manners:

[0079] In the first implementation manner, the service guarantee rate is multiplied by the number of activated users to obtain the first demand rate.

[0080] In the second implementation manner, the user information further includes the RRC connected user number average peak ratio, and the first information further includes the service duty cycle.

[0081] The first demand rate of the first type of service is determined according to the service guarantee rate and the number of activated users, including:

[0082] The first demand rate of the first type of service is determined according to the product of at least one of the service guarantee rate, the number of activated users, the RRC connected user number average peak ratio, and the service duty cycle.

[0083] In the embodiment, on the basis of the first embodiment, considering the case that multiple users in the target area simultaneously perform the first type of service and the duty cycle of the first type of service, in order to improve the accuracy of the first demand rate, the RRC connection user number average peak ratio and the service duty cycle are introduced. The RRC connection user number refers to the RRC layer online user number, the RRC connection user number average peak ratio refers to the ratio of the average value to the peak value of the RRC connection user number, and the service duty cycle refers to the ratio of the service performing time to the total time. The RRC connection user number average peak ratio and the service duty cycle can be determined based on the data of the services opened in the target area, and are not limited herein.

[0084] Specifically, the service guarantee rate, the active user number, and the RRC connection user number average peak ratio can be multiplied to obtain the first demand rate; or the service guarantee rate, the active user number, and the service duty cycle can be multiplied to obtain the first demand rate; or the service guarantee rate, the active user number, the RRC connection user number average peak ratio, and the service duty cycle can be multiplied to obtain the first demand rate. The specific method can be determined according to actual conditions, and is not limited herein.

[0085] In an optional embodiment, the cell demand information of the target service is determined according to the demand rate information, including:

[0086] The single-cell peak throughput of the target area is obtained.

[0087] The demand cell number of the first type of service is determined according to the quotient of the first demand rate and the single-cell peak throughput.

[0088] In the embodiment, the single-cell peak throughput can be determined based on the performance of the base station to be deployed in the target area, and can be obtained from the operator or the related equipment manufacturer. In the case that the quotient of the first demand rate and the single-cell peak throughput is an integer, the demand cell number of the first type of service can be equal to the quotient of the first demand rate and the single-cell peak throughput. In the case that the quotient of the first demand rate and the single-cell peak throughput is not an integer, the demand cell number of the first type of service can be the quotient of the first demand rate and the single-cell peak throughput rounded up. For example, if the quotient of the first demand rate and the single-cell peak throughput is 3.4, the demand cell number of the first type of service is determined to be 4.

[0089] In an optional embodiment, the first demand rate includes at least one of a first uplink demand rate and a first downlink demand rate, and the first demand rate can be determined according to the service characteristics. For example, if the first type of service is mainly uplink service, the first demand rate can be the first uplink demand rate; or if the first type of service is mainly downlink service, the first demand rate can be the first downlink demand rate; or if the uplink service and the downlink service of the first type of service are balanced, the first demand rate can include the first downlink demand rate and the first downlink demand rate.

[0090] In the case where the first demand rate includes the first uplink demand rate and the first downlink demand rate, the demand cell number of the first type of service is the larger one of the uplink demand cell number and the downlink demand cell number of the first type of service.

[0091] An exemplary embodiment in this case is described below.

[0092] In this embodiment, the first type of service is taken as an example of the 5G exclusive slice service to be opened, as shown in FIG. 1, the network evaluation method comprises the following steps: Figure 3

[0093] Step one, calculate the user activation ratio.

[0094] User activation ratio = RRC connected state user number ÷ number of users with a number.

[0095] Among them, the RRC connected state user number and the number of users with a number of 5G have no historical data to learn at the beginning of network construction, which can be obtained by referring to the data estimation of 4G long term evolution (Long Term Evolution, LTE).

[0096] Step two, calculate the number of active users.

[0097] Active user number = total user number × user activation ratio × user development coefficient.

[0098] Among them, the total user number is the total user number in the target area, which can be directly obtained from OMC, and the target area can be the park covered by the slice service to be opened. The user activation ratio is obtained according to step one, and the user development coefficient is estimated according to the business development plan and the actual situation, which can be 1, 1.2 or 1.5, and the specific value can be determined according to the actual situation.

[0099] Step three, calculate the uplink / downlink demand rate.

[0100] Uplink / downlink demand rate = service uplink / downlink guarantee rate × active user number × RRC connected user average peak ratio × service uplink / downlink duty cycle.

[0101] ​Wherein, the service uplink / downlink guarantee rate is determined according to service demand, the activated user number is obtained according to step two, and the 5G RRC connection user average peak ratio and 5G service uplink / downlink duty cycle have no historical data to learn at the initial stage of network construction, and can be estimated by referring to the data of 4G LTE. It should be noted that in this step, the uplink demand rate and the downlink demand rate need to be calculated respectively, the uplink demand rate is determined based on the corresponding uplink data, and the downlink demand rate is determined based on the corresponding downlink data.

[0102] Step four, calculate the uplink / downlink demand cell number.

[0103] Uplink / downlink demand cell number = uplink / downlink demand rate ÷ single cell uplink / downlink peak throughput.

[0104] Wherein, the uplink / downlink demand rate is obtained according to step three, and the single cell uplink / downlink peak throughput can be obtained from the operator or the relevant equipment manufacturer due to the difference of equipment manufacturers and equipment performance. It should be noted that in this step, the uplink demand cell number and the downlink demand cell number need to be calculated respectively, the uplink demand cell number is determined based on the uplink data, and the downlink demand cell number is determined based on the downlink data.

[0105] Step five, determine the demand cell number.

[0106] Demand cell number = MAX(uplink demand cell number, downlink demand cell number).

[0107] Step six, cell division.

[0108] In this step, the wireless side personnel audits and decides based on the demand cell number obtained in step five, divides the cells, and plans the base station position.

[0109] Case two

[0110] In this case, the to-be-opened service is a shared service, and the network resources of the existing cells in the target area can be allocated to the to-be-opened service. It is necessary to evaluate whether the existing cells in the target area can meet the total demand of the to-be-opened service after the to-be-opened service is opened.

[0111] Optionally, the target service includes a second type of service and a third type of service, the second type of service is a service opened in the target area, and the third type of service is a service to be opened in the target area.

[0112] According to the first information, the demand rate information of the target service is determined, including:

[0113] According to a service guarantee rate of the service in the first cell, a second demand rate of the service in the first cell is determined, the first cell is any cell in a target region and associated with the third type of service, the service in the first cell includes N second type of services and M third type of services in the target service, N and M are positive integers.

[0114] In the embodiment, the second type of service can be a shared service opened in the target region, and the third type of service can be a shared service to be opened in the target region. Since the second type of service has been opened in the target region, at least one cell in the target region has been planned to provide network resources for the second type of service. Before the third type of service is opened in the target region, it is necessary to determine the cell associated with the third type of service, i.e., the cell possibly covered by the third type of service, which is recorded as a target coverage cell, and determine whether the cell can meet the service demand after the third type of service is opened, cell by cell.

[0115] The first cell is any cell in the target coverage cell, and the service in the first cell includes N second type of services and M third type of services in the target service. It can be understood that, assuming that the total number of services in the target service is K, N and M are positive integers less than K, and the sum of N and M is less than or equal to K. In the case where the target region only includes the first cell, the sum of N and M is equal to K. In the case where the target region includes other cells in addition to the first cell, the sum of N and M is less than K.

[0116] In the embodiment, according to the service guarantee rate of the service in the first cell, the second demand rate of the service in the first cell is determined. The second demand rate can represent a total rate requirement value of the service in the first cell, and the total cell demand information of the existing second type of service and the newly opened third type of service in the first cell after the third type of service is opened is determined in turn, and then it is determined whether the first cell can meet the service demand after the third type of service is opened.

[0117] In an optional embodiment, according to the demand rate information, the cell demand information of the target service is determined, including:

[0118] The peak throughput of the first cell is obtained;

[0119] According to the ratio of the second demand rate to the peak throughput, it is determined whether the first cell meets the service demand;

[0120] In the case where it is determined that the first cell does not meet the service demand, the number of demand cells of the service in the first cell is determined according to the ratio.

[0121] In the embodiment, if the ratio of the second demand rate to the peak throughput is 1 or less than 1, the first cell can meet the service demand. If the ratio of the second demand rate to the peak throughput is greater than 1, the first cell cannot meet the service demand.

[0122] If it is determined that the first cell cannot meet the service demand, the number of required cells for the service in the first cell can be determined according to the ratio. Specifically, the ratio can be rounded up to obtain the number of required cells for the service in the first cell. For example, if the ratio is 1.2, the number of required cells for the service in the first cell is determined to be 2, and one more cell needs to be added to the first cell to meet the service demand of the N second services and the M third services.

[0123] In an optional embodiment, the second demand rate includes at least one of a second uplink demand rate and a second downlink demand rate, and the second demand rate can be determined according to the service characteristics. For example, if the service in the first cell is mainly uplink service, the second demand rate can be the second uplink demand rate; or if the service in the first cell is mainly downlink service, the second demand rate can be the second downlink demand rate; or if the uplink service and the downlink service in the first cell are balanced, the second demand rate can include the second uplink demand rate and the second downlink demand rate.

[0124] In the case where the second demand rate includes the second uplink demand rate and the second downlink demand rate, the above ratio includes a first ratio and a second ratio. The first ratio is the ratio of the second uplink demand rate to the single-cell uplink peak throughput, and the second ratio is the ratio of the second downlink demand rate to the single-cell downlink peak throughput. If both the first ratio and the second ratio are 1 or less than 1, the first cell can meet the service demand. If the first ratio or the second ratio is less than 1, the first cell cannot meet the service demand.

[0125] The following describes an embodiment for determining the second demand rate in the embodiment:

[0126] Optionally, two embodiments are included:

[0127] In the first embodiment, the service guarantee rate of each service of the N second services and the service guarantee rate of each service of the M third services are added to obtain the second demand rate.

[0128] In the two embodiments, the second demand rate of the service in the first cell is determined according to the service guarantee rate of the service in the first cell, including:

[0129] The first concurrent weight coefficient of each service of the N second services is determined, and the second concurrent weight coefficient of each service of the M third services is determined.

[0130] The second demand rate is determined according to the service guarantee rate of each of the N second-type services, the first concurrency weight coefficient of each of the N second-type services, the service guarantee rate of each of the M third-type services, and the second concurrency weight coefficient of each of the M third-type services.

[0131] In the embodiment, on the basis of the first embodiment, the first concurrency weight coefficient and the second concurrency weight coefficient are introduced to improve the accuracy of the second demand rate, considering the concurrency of multiple services that can exist due to the coexistence of multiple services in the first cell. The first concurrency weight coefficient is used to represent the importance or priority of each second-type service in the first cell in service concurrency, and the second concurrency weight coefficient is used to represent the importance or priority of each third-type service in the first cell in service concurrency.

[0132] In an optional embodiment, the second demand rate is determined according to the service guarantee rate of each of the N second-type services, the first concurrency weight coefficient of each of the N second-type services, the service guarantee rate of each of the M third-type services, and the second concurrency weight coefficient of each of the M third-type services, including:

[0133] The service guarantee rate of each of the N second-type services and the first concurrency weight coefficient of each of the N second-type services are weighted and summed to obtain a first weighted sum value;

[0134] The service guarantee rate of each of the M third-type services and the second concurrency weight coefficient of each of the M third-type services are weighted and summed to obtain a second weighted sum value;

[0135] The first weighted sum value and the second weighted sum value are added to obtain the second demand rate.

[0136] In the embodiment, the calculation formula of the second demand rate is as follows:

[0137]

[0138] speed i, speed j, β i, and β j are as defined above. i speed i is the service guarantee rate of the i th second-type service, i = 1, 2, 3, …, N, β i is the first concurrency weight coefficient of the i th second-type service. i speed i is the service guarantee rate of the i th second-type service, i = 1, 2, 3, …, N, β i is the first concurrency weight coefficient of the i th second-type service. n+j speed j is the service guarantee rate of the j th third-type service, j = 1, 2, 3, …, m, β j is the second concurrency weight coefficient of the j th third-type service. n+j speed j is the service guarantee rate of the j th third-type service, j = 1, 2, 3, …, m, β j is the second concurrency weight coefficient of the j th third-type service.

[0139] It should be noted that the concurrent weight coefficient is not only related to the characteristics of each second type of service or each third type of service itself, but also related to the cell where each second type of service or each third type of service is located. For example, the first concurrent weight coefficients of service 1 in cell 1 and service 1 in cell 2 can be the same or different, which is determined according to the actual situation.

[0140] The following describes an embodiment of determining the first concurrent weight coefficient:

[0141] The first concurrent weight coefficient can be pre-set based on the cell characteristics of the first cell and the characteristics of each second type of service in the first cell.

[0142] Alternatively, the first concurrent weight coefficient of each service in the N second type of services is determined, comprising:

[0143] Obtaining usage information of each service in the N second type of services in the first cell;

[0144] According to the usage information, the first concurrent weight coefficient of each service in the N second type of services is determined;

[0145] The usage information includes at least one of the physical resource block (PRB) utilization, the radio link layer control protocol (RLC) layer data throughput, the total throughput, and the RRC connection user number.

[0146] The PRB utilization can include at least one of uplink PRB utilization and downlink PRB utilization. The RLC layer data throughput can include at least one of uplink RLC layer data throughput and downlink RLC layer data throughput. The total throughput refers to the total throughput of uplink data and downlink data. The RRC connection user number can include at least one of the RRC connection real-time user number, the RRC connection average user number, and the RRC connection peak user number.

[0147] In this embodiment, a first database can be established for each base station in the first cell or the target area, and the first database is used to record the performance data of the base station. In this way, by obtaining the performance data corresponding to each second type of service in the first cell, the usage information of each second type of service in the first cell is determined, and then according to the usage information, the performance of each second type of service in the first cell is analyzed to determine the first concurrent weight coefficient of each second type of service in the first cell.

[0148] The fields of the performance data include, but are not limited to, at least one of uplink / downlink PRB utilization, uplink / downlink RLC layer data throughput, total throughput, and number of RRC connection users. In addition, at least one of a base station identifier, a service type carried by the base station, and a timestamp can also be included. The service type carried by the base station can include types of various slice services, or can include ToC (To Consumer) public network services, without limitation.

[0149] In a specific implementation, one piece of performance data of the base station can be recorded every first time interval. The first time interval can be 15 minutes, 30 minutes, etc. Here, 15 minutes is taken as an example for illustration. Then, 96 pieces of data can be obtained for each second type of service per day.

[0150] Further, to reduce the amount of data and improve network evaluation efficiency, optionally, the self-busy time of each base station per day can be determined based on the total throughput, and then the usage information of each second type of service in the first cell can be obtained based on the performance data corresponding to the self-busy time. The self-busy time refers to a time period corresponding to the maximum PRB utilization or maximum traffic of the base station, which is determined according to actual conditions, without limitation. In this way, only one piece of data is obtained for each second type of service per day, greatly reducing the amount of data, and the data corresponding to the busiest time can better reflect the maximum service demand of the second type of service.

[0151] Further, to avoid occasionality and ensure that the coverage of the sample data is more comprehensive, a plurality of pieces of data in a second time interval can be obtained for each second type of service. The second time interval can be 30 days, 60 days, or 180 days. Here, 180 days is taken as an example for illustration. Then, 180 pieces of performance data can be obtained for each second type of service.

[0152] In an optional implementation, before determining the first concurrent weight coefficient of each service in the N second types of services according to the usage information, the following further includes:

[0153] Determining a third weight coefficient of each information in the usage information.

[0154] Determining the first concurrent weight coefficient of each service in the N second types of services according to the usage information includes:

[0155] Determining the first concurrent weight coefficient of each service in the N second types of services according to the usage information and the third weight coefficient of each information in the usage information.

[0156] In this way, by determining the third weight coefficient of each usage information, the first concurrency weight coefficient of each second type of service can be determined in a quantitative manner based on weighted calculation, and the accuracy and efficiency are improved. It should be noted that since the order of magnitude of each usage information may be different, the usage information can be standardized and / or normalized before weighted calculation.

[0157] The following describes an embodiment of determining the third weight coefficient:

[0158] The third weight coefficient can be pre-set according to the nature and meaning of each usage information.

[0159] Alternatively, the third weight coefficient of each information in the usage information is determined, including:

[0160] Perform principal component analysis based on the usage information to obtain principal components, principal component contribution rates, and principal component cumulative variance contribution rates of the usage information;

[0161] Determine a principal component matrix based on the principal component contribution rates and the principal component cumulative variance contribution rates, and obtain principal component loading values based on the principal component matrix;

[0162] Determine the coefficient of each information in the usage information in different principal component linear combinations based on the principal component matrix and the principal component loading values;

[0163] Determine the third weight coefficient of each information in the usage information based on the coefficient of each information in the usage information in different principal component linear combinations.

[0164] Since there is a certain correlation between different usage information, there is a certain overlap in reflecting the concurrency weight of different usage information. The overlapping components between the usage information can be eliminated by the principal component analysis (PCA) method to obtain a set of two-by-two unrelated comprehensive information, and each comprehensive information still retains the information of the original usage information. The third weight coefficient of the usage information determined in this way can eliminate the mutual influence between the usage information, thereby improving the accuracy.

[0165] In an example, the implementation is as follows:

[0166] Suppose there are 3 existing services in the first cell, and the performance data of each base station in the past 180 days is extracted every day from the busy time, and the performance data is the usage information. Each performance data includes: ① uplink PRB utilization rate, ② downlink PRB utilization rate, ③ uplink RLC layer data throughput, ④ downlink RLC layer data throughput, ⑤ total throughput, and ⑥ RRC average user number. Among them, the third weight coefficient of the uplink is calculated using ①, ③, ⑤, and ⑥, and the third weight coefficient of the downlink is calculated using ②, ④, ⑤, and ⑥.

[0167] Taking the uplink data as an example, each base station needs to extract 180 pieces of data, each piece of data including four values of ①, ③, 5 and 6, and the performance data matrix in the first cell is x ij , i = 1, 2, …, n; j = 1, 2, …, p, n represents the number of rows, each row corresponds to a piece of data of an existing service, then n = 180 * 3 = 540, p represents the number of columns, each column corresponds to a performance data field, then for uplink data or downlink data, p = 4.

[0168] The specific process is as follows:

[0169] a) First, the performance data matrix x ij is standardized.

[0170]

[0171] Among them, S j is the sample standard deviation.

[0172] b) Calculate the correlation coefficient matrix of the standardized matrix Z ij , and the coefficient matrix R is as follows:

[0173]

[0174] Among them,

[0175] c) Solve the characteristic equation |λI-R| = 0, find the eigenvalue λ, and sort the eigenvalues in descending order, i.e. λ1≥λ2≥…,≥λ p ≥0.

[0176] d) Calculate the principal component contribution rate and the principal component cumulative variance contribution rate, as follows:

[0177]

[0178]

[0179] Then, extract the components with a principal component cumulative variance contribution rate ≥0.95 to replace the original ①, ③, 5 and 6.

[0180] e) Determine the component matrix to obtain the principal component load number.

[0181] f) Based on the component matrix, calculate the coefficients of the four performance indicators in different linear combinations of principal components, i.e. the principal component load number divided by the square root of the corresponding eigenvalue.

[0182] j) calculating a comprehensive score coefficient, specifically, the formula is: cumulative (linear combination coefficient * variance explanation rate) / cumulative variance explanation rate, that is, the linear combination coefficient is multiplied by the variance explanation rate respectively, and then accumulated, and divided by the cumulative variance explanation rate, that is, the comprehensive score coefficient is obtained.

[0183] e) normalizing the comprehensive score coefficient to obtain the performance index weight value α i , (i = 1, 2, 3, 4).

[0184] The following describes an embodiment of determining the second concurrency weight coefficient:

[0185] The second concurrency weight coefficient can be preset based on the cell characteristics of the first cell and the characteristics of each third type of service in the first cell.

[0186] Alternatively, the second concurrency weight coefficient of each service in the M third type of services is determined, including:

[0187] The similarity between each service in the N second type of services and the first service is determined, wherein the first service is any service in the M third type of services;

[0188] The first concurrency weight coefficient of the second service is determined as the second concurrency weight of the first service, and the second service is the service with the highest similarity to the first service in the N second type of services.

[0189] In this embodiment, the first service is any one third type of service in the first cell. Since the first service is a service to be opened in the first cell, there is no base station data to be used as a reference, and therefore, by comparing the similarity between the first service and each second type of service, the first concurrency weight coefficient of the second type of service with higher similarity can be determined as the second concurrency weight coefficient of the first service.

[0190] In an optional embodiment, the similarity between each service in the N second type of services and the first service is determined, including:

[0191] The first feature information of the first service is obtained, and the second feature information of each service in the N second type of services is obtained;

[0192] The similarity between each service in the N second type of services and the first service is determined according to the similarity between the first feature information and each second feature information;

[0193] The first feature information or the second feature information includes at least one of the service type, the service deployment scene, the busy time, the number of users, and the service guarantee rate.

[0194] The service type can include at least one of public network service, public network dedicated service, and ToC public network service. The service deployment scenario can include at least one of VR / AR, ultra-high-definition video, Internet of Vehicles, remote medical treatment, smart power, smart factory, smart security, and smart park. The busy time refers to a time period corresponding to the maximum PRB utilization rate or the maximum traffic of the service. The interval of the time period can be 15 minutes, 30 minutes, etc. Here, 15 minutes is taken as an example for illustration. The user number refers to the total number of users covered by the service.

[0195] In the embodiment, a second database can be established for each service in the first cell or the target area. The second database is used to record the characteristic data of the service. It should be noted that a second database needs to be established for the same service in different cells. In this way, by obtaining the characteristic data corresponding to each service in the first cell, the first characteristic information of the first service and the second characteristic information of each second service can be determined, and then the similarity calculation is performed.

[0196] The fields of the characteristic data include, but are not limited to, at least one of the service type, the service deployment scenario, the busy time, the user number, and the service guarantee rate. In addition, for the service that has been opened, the first concurrent weight coefficient can also be included. The service type and the service deployment scenario can be represented by specific numerical values, for example, as shown in Table 1. The busy time can be represented as a floating-point number in the 24-hour system with two decimal places, such as 20.15, 22.30, etc.

[0197] Table 1: Service type and service deployment scenario value table

[0198]

[0199] In a specific implementation, the similarity between the first characteristic information and each second characteristic information can be determined based on the Euclidean distance calculation formula, which is simple and efficient. It can be understood that the similarity between the first characteristic information and each second characteristic information can also be determined based on other similarity calculation methods, which can be determined according to actual conditions and is not limited here.

[0200] It should be noted that since the number of orders of magnitude of each characteristic information can be different, the standardization and / or normalization of each characteristic information can be performed before the similarity calculation.

[0201] In an example, the implementation is as follows:

[0202] a) Standardize each characteristic information. Specifically, the logarithm can be taken uniformly, that is:

[0203] lnx1, lnx2, lnx3, lnx4, lnx5

[0204] b) calculate the Euclidean distance between the characteristic information (lnx1, lnx2, lnx3, lnx4, lnx5) of the first service and the characteristic information (lnx 1i , lnx 2i , lnx 3i , lnx 4i , lnx 5i ) of each second service, that is:

[0205]

[0206] b) The obtained d i is a number greater than 0, in order to better reflect the similarity between the two slice services, it can be reduced to (0, 1], that is:

[0207]

[0208] Wherein, the smaller the distance sim i between the first service and the second service, the higher the similarity.

[0209] The following introduces an exemplary embodiment in this case:

[0210] In this embodiment, taking cell 1 as an example, it is assumed that the slice services opened in cell 1 are service 1, service 2, …, and service n, and the slice service to be opened is service n+1. As shown in Figure 4 , the flow of the network evaluation method is as follows:

[0211] Step 401, constructing a base station performance database.

[0212] The index field of the base station performance database includes: cell identity certificate identification number (Identity Document, ID), service type carried, time stamp, base station uplink / downlink PRB utilization rate, base station uplink / downlink RLC layer data throughput, total throughput, and base station RRC connection average user number.

[0213] The database records one piece of data every 15 minutes.

[0214] Step 402, determining the base station self-busy time based on the base station performance database.

[0215] In this step, the total throughput in step one can be used to determine that the 15 minutes with the maximum total throughput of each base station per day is the base station self-busy time.

[0216] Step 403, establishing a mathematical model to determine the first concurrent weight coefficient of n opened slice services.

[0217] In this step, the performance data of each base station is extracted every day from the busy time in the past 180 days, and each performance data includes: ① uplink PRB utilization, ② downlink PRB utilization, ③ uplink RLC layer data throughput, ④ downlink RLC layer data throughput, ⑤ total throughput, and ⑥ RRC average user number. Among them, the third weight coefficient of the uplink is calculated using ①, ③, ⑤, and ⑥, and the third weight coefficient of the downlink is calculated using ②, ④, ⑤, and ⑥.

[0218] Here, taking the uplink data as an example, each base station needs to extract 180 pieces of data, and each piece of data includes ①, ③, ⑤, and ⑥ four values, then the performance data matrix x of n opened slice services is: ij It is a 180*n*4 matrix, i=1, 2, …, 180*n; j=1, 2, 3, 4.

[0219] 1) Determine the uplink weight coefficient α of the four performance indicators ①, ③, ⑤, and ⑥ i ,(i=1, 2, 3, 4).

[0220] The specific method can refer to the exemplary embodiments of the third weight coefficient described in the above embodiments.

[0221] 2) Determine the first uplink concurrent weight coefficient β of n opened slice services i ,(i=1, 2, …, n) based on the performance data of n opened slice services in the busiest time in cell 1, the following matrix is obtained:

[0222]

[0223] Among them, v i1 represents the uplink PRB utilization of each opened slice service in cell 1, v i2 represents the uplink RLC layer data throughput of each opened slice service in cell 1, v i3 represents the total throughput of each opened slice service in cell 1, and v i4 represents the RRC average user number of each opened slice service in cell 1.

[0224] v ij is multiplied by the uplink weight coefficient α of the four performance indicators ①, ③, ⑤, and ⑥ i ,(i=1, 2, 3, 4), and α i can be represented as a column vector, which is as follows:

[0225]

[0226] Then, the uplink concurrent weight coefficient β of n second type services i ,(i=1, 2, …, n) is:

[0227]

[0228] Step 404, determine the second concurrency weight coefficient of the slice service to be opened.

[0229] 1) Establish a service feature library of the whole network slice service.

[0230] The feature fields of the service feature library include: ① slice service type, ② slice service deployment scenario, ③ busy time, ④ user number, ⑤ service uplink and downlink guarantee rate, and ⑥ service concurrency weight coefficient.

[0231] 2) Determine the similarity of the slice service to be opened and each service in the n opened slice services.

[0232] Using the Euclidean distance calculation formula, based on the data of fields ①, ②, ③, ④ and ⑤, the similarity of the slice service to be opened and each service in the n opened slice services is calculated.

[0233] The specific similarity calculation method can refer to the related exemplary embodiments in the above embodiments.

[0234] 3) Determine the second concurrency weight coefficient of the slice service to be opened.

[0235] The ⑥ of the opened slice service with the smallest similarity distance is taken as the second concurrency weight coefficient of the slice service to be opened.

[0236] Step 405, estimate the terminal activity range of the slice service to be opened, and determine the target coverage cell of the slice service to be opened.

[0237] Step 406, calculate the uplink demand rate and downlink demand rate of cell 1.

[0238] Taking the uplink demand rate as an example, the uplink demand rate of cell 1 is:

[0239]

[0240] Wherein, when i≤n, speed i is the service uplink guarantee rate of the ith opened slice service, β i is the first uplink concurrency weight coefficient of the first second type service. When i=n+1, speed n+1 is the service uplink guarantee rate of the slice service to be opened, β n+1 is the second uplink concurrency weight coefficient of the slice service to be opened.

[0241] Step 407, determine whether cell 1 meets the service demand of the n opened slice services and the slice service to be opened.

[0242] If:

[0243] and

[0244] Then, the cell 1 meets the service demand of the n opened slice services and the to-be-opened slice service.

[0245] If:

[0246] or

[0247] Then, the cell 1 does not meet the service demand of the n opened slice services and the to-be-opened slice service.

[0248] In the case of not meeting, the number of cells required by the n opened slice services and the to-be-opened slice service is determined according to the following formula:

[0249]

[0250] The specific number of required cells is the value of the above formula rounded up, if the value of the above formula is 1.2, the number of cells required by the n opened slice services and the to-be-opened slice service is 2, and one more cell is required on the basis of the cell 1 to meet the service demand.

[0251] Referring to Figure 5 , Figure 5 is the structural diagram of the network evaluation device provided by the embodiment of the application.

[0252] As shown in Figure 5 , the network evaluation device 500 comprises:

[0253] The first acquisition module 501 is configured to acquire first information of a target service in a target area, wherein the first information comprises a service guarantee rate.

[0254] The first determination module 502 is configured to determine demand rate information of the target service according to the first information.

[0255] The second determination module 503 is configured to determine cell demand information of the target service according to the demand rate information.

[0256] Optionally, the service guarantee rate comprises a service uplink guarantee rate and a service downlink guarantee rate.

[0257] The second determination module 503 comprises:

[0258] The first determination unit is configured to determine the number of uplink demand cells of the target service according to the service uplink guarantee rate of the target service, and determine the number of downlink demand cells of the target service according to the service uplink guarantee rate of the target service.

[0259] The second determining unit is configured to determine the maximum demand cell number between the uplink demand cell number and the downlink demand cell number as the demand cell number of the target service.

[0260] Optionally, the target service includes a first type of service, and the first type of service is a service to be opened in the target area.

[0261] The network evaluation apparatus 500 further includes:

[0262] The third determining module is configured to determine user information of the target area, and the user information includes an active user number.

[0263] The first determining module 502 is specifically configured to:

[0264] determine a first demand rate of the first type of service according to the service guarantee rate and the active user number.

[0265] Optionally, the user information further includes a radio resource control (RRC) connection user number average peak ratio, and the first information further includes a service duty cycle.

[0266] The first determining module 502 is specifically configured to:

[0267] determine a first demand rate of the first type of service according to a product of the service guarantee rate and at least one of the active user number, the RRC connection user number average peak ratio, and the service duty cycle.

[0268] Optionally, the first determining module 502 includes:

[0269] The first obtaining unit is configured to obtain a total user number, a user activation ratio, and a preset user development coefficient in the target area.

[0270] The third determining unit is configured to determine the active user number according to the total user number, the user activation ratio, and the user development coefficient.

[0271] Optionally, the second determining module 503 includes:

[0272] The fourth determining unit is configured to obtain a single-cell peak throughput of the target area.

[0273] The fifth determining unit is configured to determine a demand cell number of the first type of service according to a quotient of the first demand rate and the single-cell peak throughput.

[0274] Optionally, the target service includes a second type of service and a third type of service, the second type of service is a service opened in the target area, and the third type of service is a service to be opened in the target area.

[0275] The first determining module 502 is specifically configured to:

[0276] determine a second demand rate of the intra-first-cell service according to a service guarantee rate of the intra-first-cell service, the first cell being any cell in the target region that already exists and is associated with the third type of service, the intra-first-cell service including N second type of services and M third type of services in the target service, N and M being positive integers.

[0277] Optionally, the first determining module 502 includes:

[0278] a sixth determining unit configured to determine a first concurrency weight coefficient of each service in the N second type of services and a second concurrency weight coefficient of each service in the M third type of services;

[0279] a seventh determining unit configured to determine the second demand rate according to the service guarantee rate of each service in the N second type of services, the first concurrency weight coefficient of each service in the N second type of services, the service guarantee rate of each service in the M third type of services, and the second concurrency weight coefficient of each service in the M third type of services.

[0280] Optionally, the sixth determining unit includes:

[0281] a first obtaining sub-unit configured to obtain usage information of each service in the N second type of services in the first cell;

[0282] a first determining sub-unit configured to determine the first concurrency weight coefficient of each service in the N second type of services according to the usage information;

[0283] The usage information includes at least one of a physical resource block utilization rate, a radio link layer control protocol (RLC) layer data throughput, a total throughput, and a number of RRC connection users.

[0284] Optionally, the network evaluation apparatus 500 further includes:

[0285] a fourth determining module configured to determine a third weight coefficient of each information in the usage information;

[0286] The first determining sub-unit is specifically configured to:

[0287] determine the first concurrency weight coefficient of each service in the N second type of services according to the usage information and the third weight coefficient of each information in the usage information.

[0288] Optionally, the fourth determining module includes:

[0289] The first analysis unit is configured to perform principal component analysis based on the usage information to obtain principal components, principal component contribution rates, and principal component cumulative variance contribution rates of the usage information.

[0290] The first analysis unit is configured to determine a principal component matrix based on the principal component contribution rates and the principal component cumulative variance contribution rates, and obtain principal component load values based on the principal component matrix.

[0291] The second analysis unit is configured to determine coefficients of each information in the usage information in different principal component linear combinations based on the principal component matrix and the principal component load values.

[0292] The fourth analysis unit is configured to determine third weight coefficients of each information in the usage information based on the coefficients of each information in the usage information in different principal component linear combinations.

[0293] Optionally, the sixth determination unit comprises:

[0294] The second determination sub-unit is configured to determine the similarity of each service in the N second-type services to the first service, wherein the first service is any service in the M third-type services.

[0295] The third determination sub-unit is configured to determine the first concurrency weight coefficient of the second service as the second concurrency weight of the first service, wherein the second service is the service in the N second-type services that is most similar to the first service.

[0296] Optionally, the third determination sub-unit is specifically configured to:

[0297] The first characteristic information of the first service is obtained, and the second characteristic information of each service in the N second-type services is obtained.

[0298] The similarity of each service in the N second-type services to the first service is determined according to the similarity of the first characteristic information to each second characteristic information.

[0299] The first characteristic information or the second characteristic information comprises at least one of a service type, a service deployment scenario, a busy time, a number of users, and a service guarantee rate.

[0300] Optionally, the seventh determination unit is specifically configured to:

[0301] The service guarantee rates of each service in the N second-type services and the first concurrency weight coefficients of each service in the N second-type services are weighted and summed to obtain a first weighted sum value.

[0302] The service guarantee rate of each service in the M third type services and the second concurrency weight coefficient of each service in the M third type services are weighted and summed to obtain a second weighted sum value;

[0303] The first weighted sum value and the second weighted sum value are added to obtain the second demand rate.

[0304] Optionally, the first determining module 502 comprises:

[0305] The second acquisition unit is configured to acquire a peak throughput of the first cell.

[0306] The eighth determining unit is configured to determine whether the first cell satisfies the service demand according to a ratio of the second demand rate to the peak throughput.

[0307] The ninth determining unit is configured to determine the demand cell number of the services in the first cell according to the ratio in a case where it is determined that the first cell does not satisfy the service demand.

[0308] The network evaluation device 500 can realize the processes of the corresponding method embodiments and achieve the same beneficial effects, and thus, details are not repeated here. Figure 2 The corresponding method embodiments, and achieve the same beneficial effects, and thus, details are not repeated here.

[0309] The embodiment of the present application also provides an electronic device. Please refer to Figure 6 The electronic device 600 can comprise a processor 601, a memory 602, and a computer program 6021 stored in the memory 602 and executable on the processor 601, and the computer program 6021 can realize Figure 2 The corresponding method embodiments, and achieve the same beneficial effects, and thus, details are not repeated here.

[0310] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiment methods can be completed by program instructions related to hardware, and the program can be stored in a readable medium. The embodiment of the present application also provides a readable storage medium, and the readable storage medium stores a computer program, and the computer program is executable by a processor to realize Figure 3 Or Figure 4 The corresponding method embodiments, and achieve the same beneficial effects, and thus, details are not repeated here.

[0311] The storage medium, such as a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0312] The above is the preferred embodiment of the present application, it should be noted that for those skilled in the art, without departing from the principles of the present application, can make several improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A network evaluation method characterized by, include: Obtain first information about the target service within the target area, the first information including the service guarantee rate; the target service includes a first type of service, the first type of service being the service to be activated within the target area; Based on the first information, determine the demand rate information of the target service; Based on the demand rate information, determine the cell demand information for the target service; Before determining the demand rate information of the target service based on the first information, the method further includes: Determine user information for the target region, the user information including the number of active users; determine the demand rate information for the target service based on the first information, including: determining a first demand rate for the first type of service based on the service guarantee rate and the number of active users; The step of determining the cell demand information for the target service based on the demand rate information includes: Obtain the peak throughput of a single cell in the target area; determine the number of cells required for the first type of service based on the quotient of the first demand rate and the peak throughput of the single cell.

2. The method of claim 1, wherein, The service guarantee rate includes the service uplink guarantee rate and the service downlink guarantee rate; The step of determining the cell demand information for the target service based on the demand rate information includes: Based on the uplink guaranteed rate of the target service, determine the number of cells required for uplink of the target service, and based on the downlink guaranteed rate of the target service, determine the number of cells required for downlink of the target service. The maximum number of cells in demand between the number of uplink demand cells and the number of cells in demand downlink is determined as the number of cells in demand for the target service.

3. The method of claim 1, wherein, The user information also includes the average peak-to-average ratio of the number of connected users under Radio Resource Control (RRC), and the first information also includes the service duty cycle. Determining the first demand rate for the first type of service based on the service guarantee rate and the number of activated users includes: The first demand rate for the first type of service is determined by multiplying the service guarantee rate by at least one of the following: the number of active users, the average peak-to-average ratio of the number of RRC connected users, and the service duty cycle.

4. The method according to claim 1, characterized in that, The user information for determining the target area includes: Obtain the total number of users, user activation ratio, and preset user development coefficient within the target area; The number of activated users is determined based on the total number of users, the user activation ratio, and the user development coefficient.

5. The method according to claim 1, characterized in that, The target services include a second type of service and a third type of service. The second type of service refers to services that have already been activated within the target area, and the third type of service refers to services that are yet to be activated within the target area. The step of determining the demand rate information of the target service based on the first information includes: Based on the service guarantee rate of the services in the first cell, the second demand rate of the services in the first cell is determined. The first cell is any existing cell in the target area that is associated with the third type of service. The services in the first cell include N second type services and M third type services in the target services, where N and M are positive integers.

6. The method according to claim 5, characterized in that, The step of determining the second demand rate of services within the first cell based on the service guarantee rate of services within the first cell includes: Determine the first concurrency weight coefficient for each of the N second-class services, and determine the second concurrency weight coefficient for each of the M third-class services; The second demand rate is determined based on the service guarantee rate of each of the N second-class services, the first concurrency weight coefficient of each of the N second-class services, the service guarantee rate of each of the M third-class services, and the second concurrency weight coefficient of each of the M third-class services.

7. The method according to claim 6, characterized in that, Determining the first concurrency weight coefficient for each of the N second-category services includes: Obtain the usage information of each of the N second-category services in the first cell; Based on the usage information, determine the first concurrency weight coefficient for each of the N second-category services; The usage information includes at least one of the following: physical resource block utilization, radio link layer control protocol (RLC) layer data throughput, total throughput, and number of RRC connected users.

8. The method according to claim 7, characterized in that, Before determining the first concurrency weight coefficient for each of the N second-category services based on the usage information, the method further includes: Determine the third weighting coefficient for each piece of information in the usage information; The step of determining the first concurrency weight coefficient for each of the N second-category services based on the usage information includes: Based on the usage information and the third weight coefficient of each piece of information in the usage information, the first concurrency weight coefficient of each of the N second-class services is determined.

9. The method according to claim 8, characterized in that, Determining the third weighting coefficient for each piece of information in the usage information includes: Principal component analysis was performed based on the usage information to obtain the principal components, principal component contribution rates, and cumulative variance contribution rates of the usage information. The principal component matrix is ​​determined based on the principal component contribution rate and the principal component cumulative variance contribution rate, and the principal component loading values ​​are obtained based on the principal component matrix. Based on the principal component matrix and the principal component loading values, determine the coefficients of each piece of information in the usage information in different linear combinations of principal components; Based on the coefficients of each piece of information in the usage information in different principal component linear combinations, the third weight coefficient of each piece of information in the usage information is determined.

10. The method according to claim 6, characterized in that, The determination of the second concurrency weight coefficient for each of the M third-category services includes: Determine the similarity between each of the N second-class services and the first service, wherein the first service is any one of the M third-class services; The first concurrency weight coefficient of the second service is determined as the second concurrency weight of the first service, and the second service is the service with the highest similarity to the first service among the N second-class services.

11. The method according to claim 10, characterized in that, Determining the similarity between each of the N second-category services and the first service includes: Obtain the first feature information of the first service, and obtain the second feature information of each of the N second-class services; Based on the similarity between the first feature information and each of the second feature information, the similarity between each of the N second-class services and the first service is determined; The first feature information or the second feature information includes at least one of the following: business type, business deployment scenario, self-busy time, number of users, and business guarantee rate.

12. The method according to claim 6, characterized in that, The step of determining the second demand rate based on the service guarantee rate of each of the N second-class services, the first concurrency weight coefficient of each of the N second-class services, the service guarantee rate of each of the M third-class services, and the second concurrency weight coefficient of each of the M third-class services includes: The first weighted sum is obtained by weighting and summing the service guarantee rate of each of the N second-class services and the first concurrency weight coefficient of each of the N second-class services; The service guarantee rate of each of the M third-class services and the second concurrency weight coefficient of each of the M third-class services are weighted and summed to obtain the second weighted sum value; The second demand rate is obtained by adding the first weighted sum and the second weighted sum.

13. The method according to claim 5, characterized in that, The step of determining the cell demand information for the target service based on the demand rate information includes: Obtain the peak throughput of the first cell; Based on the ratio of the second demand rate to the peak throughput, determine whether the first cell meets the service requirements; If it is determined that the first cell does not meet the service requirements, the number of cells in the first cell that require the service is determined based on the ratio.

14. A network evaluation device, characterized in that, include: The first acquisition module is used to acquire first information about a target service within a target area, the first information including the service guarantee rate; the target service includes a first type of service, the first type of service being a service to be activated within the target area; The first determining module is used to determine the demand rate information of the target service based on the first information; The second determining module is used to determine the cell demand information of the target service based on the demand rate information. The device further includes: The third determining module is used to determine the user information of the target area, the user information including the number of active users; The first determining module is specifically used for: Based on the service guarantee rate and the number of activated users, determine the first demand rate for the first type of service; The second determining module includes: The fourth determining unit is used to obtain the peak throughput of a single cell in the target area; The fifth determining unit is used to determine the number of cells required for the first type of service based on the quotient of the first demand rate and the peak throughput of the single cell.

15. The apparatus according to claim 14, characterized in that, The service guarantee rate includes the service uplink guarantee rate and the service downlink guarantee rate; The second determining module includes: The first determining unit is configured to determine the number of uplink demand cells for the target service based on the uplink guarantee rate of the target service, and to determine the number of downlink demand cells for the target service based on the downlink guarantee rate of the target service. The second determining unit is used to determine the maximum number of demand cells among the number of uplink demand cells and the number of downlink demand cells as the number of demand cells for the target service.

16. The apparatus according to claim 14, characterized in that, The user information also includes the average peak-to-average ratio of the number of connected users under Radio Resource Control (RRC), and the first information also includes the service duty cycle. The first determining module is specifically used for: The first demand rate for the first type of service is determined by multiplying the service guarantee rate by at least one of the following: the number of active users, the average peak-to-average ratio of the number of RRC connected users, and the service duty cycle.

17. The apparatus according to claim 14, characterized in that, The first determining module includes: The first acquisition unit is used to acquire the total number of users, user activation ratio and preset user development coefficient in the target area; The third determining unit is used to determine the number of activated users based on the total number of users, the user activation ratio, and the user development coefficient.

18. The apparatus according to claim 14, characterized in that, The target services include a second type of service and a third type of service. The second type of service refers to services that have already been activated within the target area, and the third type of service refers to services that are yet to be activated within the target area. The first determining module is specifically used for: Based on the service guarantee rate of the services in the first cell, the second demand rate of the services in the first cell is determined. The first cell is any existing cell in the target area that is associated with the third type of service. The services in the first cell include N second type services and M third type services in the target services, where N and M are positive integers.

19. The apparatus according to claim 18, characterized in that, The first determining module includes: The sixth determining unit is used to determine the first concurrency weight coefficient of each service in the N second-class services, and to determine the second concurrency weight coefficient of each service in the M third-class services; The seventh determining unit is used to determine the second demand rate based on the service guarantee rate of each of the N second-class services, the first concurrency weight coefficient of each of the N second-class services, the service guarantee rate of each of the M third-class services, and the second concurrency weight coefficient of each of the M third-class services.

20. The apparatus according to claim 19, characterized in that, The sixth determining unit includes: The first acquisition subunit is used to acquire usage information of each of the N second-type services in the first cell; The first determining subunit is used to determine the first concurrency weight coefficient of each of the N second-type services based on the usage information; The usage information includes at least one of the following: physical resource block utilization, radio link layer control protocol (RLC) layer data throughput, total throughput, and number of RRC connected users.

21. The apparatus according to claim 20, characterized in that, The device further includes: The fourth determining module is used to determine the third weighting coefficient for each piece of information in the usage information; The first determining subunit is specifically used for: Based on the usage information and the third weight coefficient of each piece of information in the usage information, the first concurrency weight coefficient of each of the N second-class services is determined.

22. The apparatus according to claim 21, characterized in that, The fourth determining module includes: The first analysis unit is used to perform principal component analysis based on the usage information to obtain the principal components, principal component contribution rates, and principal component cumulative variance contribution rates of the usage information. The first analysis unit is used to determine the principal component matrix based on the principal component contribution rate and the principal component cumulative variance contribution rate, and to obtain the principal component loading value based on the principal component matrix. The second analysis unit is used to determine the coefficients of each piece of information in the usage information in different linear combinations of principal components based on the principal component matrix and the principal component loading values. The fourth analysis unit is used to determine the third weight coefficient of each piece of information in the usage information based on the coefficients of each piece of information in different principal component linear combinations.

23. The apparatus according to claim 19, characterized in that, The sixth determining unit includes: The second determining subunit is used to determine the similarity between each of the N second-class services and the first service, wherein the first service is any one of the M third-class services; The third determining subunit is used to determine the first concurrency weight coefficient of the second service as the second concurrency weight of the first service, wherein the second service is the service with the highest similarity to the first service among the N second-class services.

24. The apparatus according to claim 23, characterized in that, The third determining subunit is specifically used for: Obtain the first feature information of the first service, and obtain the second feature information of each of the N second-class services; Based on the similarity between the first feature information and each of the second feature information, the similarity between each of the N second-class services and the first service is determined; The first feature information or the second feature information includes at least one of the following: business type, business deployment scenario, self-busy time, number of users, and business guarantee rate.

25. The apparatus according to claim 19, characterized in that, The seventh determining unit is specifically used for: The first weighted sum is obtained by weighting and summing the service guarantee rate of each of the N second-class services and the first concurrency weight coefficient of each of the N second-class services; The service guarantee rate of each of the M third-class services and the second concurrency weight coefficient of each of the M third-class services are weighted and summed to obtain the second weighted sum value; The second demand rate is obtained by adding the first weighted sum and the second weighted sum.

26. The apparatus according to claim 18, characterized in that, The first determining module includes: The second acquisition unit is used to acquire the peak throughput of the first cell; The eighth determining unit is used to determine whether the first cell meets the service requirements based on the ratio of the second demand rate to the peak throughput. The ninth determining unit is used to determine the number of cells in the first cell that require services, based on the ratio, when it is determined that the first cell does not meet service requirements.

27. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method as described in any one of claims 1 to 13.

28. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 13.

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