WO2014032505A1 - Method and device for simulation test - Google Patents

Abstract

A method and device for simulation test are disclosed by the present invention. The method comprises: obtaining field data of a mobile communication system (201); processing the obtained field data and getting data applicable to simulation test (202); importing the processed data into the simulation test system (203); and using the simulation test system to execute system level simulation test according to the imported data (204). With the embodiments of the present invention, the simulation evaluation result can be closer to the real scene in the mobile communication system.

Description

 The present invention claims the priority of the Chinese patent application filed on August 30, 2012 by the Chinese Patent Office, the application number is 201210316941.7, and the invention name is "a simulation test method and device", the entire contents thereof This is incorporated herein by reference. Technical field

 The present invention relates to the field of wireless communications, and in particular, to a simulation test method and device. Background of the invention

 The mobile communication system is a large and complex system. It is difficult to describe it with a series of theoretical formulas and obtain accurate analytical solutions. Therefore, simulation becomes an effective and fast means to analyze mobile communication systems. Simulation can be divided into link level simulation and system level simulation. System level algorithms need to be evaluated using system level simulation. System-level simulations reflect the performance of various network performances and various system-level algorithms by modeling the behavior of a larger mobile communication network. Summary of the invention

 The embodiment of the invention provides a simulation test method and device, so that the simulation evaluation result is closer to the real scene of the mobile communication system. The simulation test method provided by the embodiment of the invention includes:

 Obtaining field data of the mobile communication system;

Processing the acquired external field data to obtain data suitable for the simulation test; and importing the processed data into the simulation test system; The system-level simulation test is performed using the simulation test system based on the imported data. The simulation test equipment provided by the embodiment of the invention includes:

 a data acquisition module, configured to acquire external field data of the mobile communication system;

 a data processing module, configured to process the acquired external field data to obtain data suitable for the simulation test;

 The data importing module is configured to import the processed data into the simulation test system; the simulation test module is installed with the simulation test system, and is used to perform system level simulation test according to the imported data by using the simulation test system. In the above embodiment of the present invention, the external field data is obtained from the external field of the mobile communication system, and the acquired external field data is processed to be processed, and the processed external field data is introduced into the system simulation test system for system level test, thereby making the simulation evaluation result Closer to the real scene of the mobile communication system, thereby reducing the network optimization time, and quickly setting the appropriate algorithm parameters after the device enters the field, and accelerating the process of the network entering the service state. BRIEF DESCRIPTION OF THE DRAWINGS

1 is a schematic diagram of a network model of a system simulation platform; FIG. 2 is a schematic flowchart of a system level simulation test method according to an embodiment of the present invention; FIG. 3 is a schematic diagram of a system switching algorithm test scenario according to an embodiment of the present invention; FIG. 5 is a schematic flowchart of obtaining geographic distribution data of users at each time point in the simulation time period in FIG. 1; FIG. 5 is a schematic flowchart of drawing an initial user distribution diagram in the first embodiment of the present invention; 6 is a schematic flowchart of a user mobility model in the first embodiment of the present invention; FIG. 7 is a schematic diagram of a data importing process in the first embodiment of the present invention; FIG. 7a is a schematic diagram of a user mobility model importing process in the first embodiment of the present invention; FIG. 9 is a schematic structural diagram of a simulation test device according to an embodiment of the present invention; FIG. 10 is a schematic structural diagram of a hardware of a simulation test device according to an embodiment of the present invention. Mode for carrying out the invention

In order to make the technical solutions and advantages of the present invention more comprehensible, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Figure 1 is a schematic diagram of a network model of a system simulation platform. The network topology in Figure 1 uses a 19-site Wrap Around model. The network contains 19 eNodeBs (evolved NodeBs, ie, evolved Node Bs), and several UEs (User Equipments) are randomly deployed in the network. At present, the test method for the system-level algorithm is: First, a system-level simulation is used to evaluate the performance of the system-level algorithm, and finally the actual network device is used for testing in the field. Among them, the test conducted in the field refers to the performance and functional test of the mobile communication network after it is completed and put into use, to ensure that the mobile communication network can meet the user's experience and needs after being put into use. Because the models used in current system-level simulation, such as user distribution, mobile model, and service source model, are quite different from the actual field application scenarios, system-level simulation cannot be accurate. Indeed, adequate algorithm performance evaluation and parameter optimization, some algorithm parameters determined by simulation are not applicable to the external field environment, so system-level simulation can not achieve the intended purpose, and many algorithm performance evaluation and parameter optimization work need to use external field test to optimize , the manpower, time and material costs that lead to field testing are all [high. In order to solve the above problem, the embodiment of the present invention introduces the data in the actual scene or the field measurement data in the simulation test system, so that the simulation evaluation is closer to the real scene, so that the algorithm can be more fully evaluated and optimized before the field test, and the algorithm is reduced. The cost of the field test has fully utilized the simulation verification function. The simulation test system here is constructed by modeling the behavior of a large-scale mobile communication network, and a virtual environment constructed in a computer for reflecting a realistic network environment, for example, a mobile language can be used to construct a mobile A system simulation platform for a wireless access network of a communication system, or a system simulation platform using some network simulation tools, such as a tool. If the system modeling is accurate, the simulation test system can effectively evaluate the performance of the real network (such as system capacity, coverage, etc.), which greatly reduces the cost of actual network testing. Various system-level algorithms (such as handover algorithms, interference coordination algorithms, etc.) can be implemented on the system simulation platform, and the performance and parameters of the system-level algorithms are simulated. The embodiments of the present invention are described in detail below with reference to the accompanying drawings. 2 is a schematic flowchart of a system level simulation test method according to an embodiment of the present invention. The process may include: Step 201: Acquire external field data of a mobile communication system. In the specific implementation, the external field data of the mobile communication system can be obtained according to the needs of the system-level simulation test, for example, in the actual application scenario of the mobile communication system (ie, the existing network, that is, already completed) The data of the mobile communication network), or the measured data when the field test is performed on the product. Since these data are obtained in the actual communication scenario rather than in the simulation environment, they are collectively referred to herein as external field data. The data in the actual application scenario of the mobile communication system can be obtained as follows: The output data of the operator is obtained from the O&M (Operations & Maintenance) system of the operator. The measured data of the product field test can be obtained as follows: Obtain some existing record data of the communication device, such as a network device (for example: terminal, base station, radio network controller, EPC (Evolved Packet Core), EPC) And device configuration information, logs, user tracking information, trace information of a certain area, system performance indicator statistics, etc. recorded in the operation and maintenance device; or, using test software and hardware to capture required data, such as using NBT (Nodeb Tester) , Node B test machine), drive test equipment or signaling analyzer, etc. record user-initiated call, service data transmission, signaling interaction, handover/cell reselection/channel reconfiguration, call drop or end call hang up, etc. Information such as signal strength and signal quality recorded during the process. The acquired external field data may include: one or any combination of geographic information, base station distribution, user traffic, performance indicators, user movement, and the like, wherein: the geographic information may include: parameters such as latitude and longitude or/and base station spacing; Including: antenna height, antenna orientation, or uniformity of base station distribution; user traffic information can include: peak rate, average rate, or service characteristics (delay, number) The performance indicator information may include: a signaling failure rate (such as what kind of signal strength, signal quality, or signaling failure in a geographical area, and the probability of signaling failure under different conditions), signaling delay, or Main process delay (such as access and handover, reconfiguration, cell reselection, measurement report delay) and other parameters; user mobility information may include: moving route, moving speed, or whether it needs to span different types of geographic regions or different Standard network, etc. Step 202: Process the acquired external field data to obtain data suitable for the simulation test system. In the specific implementation, the obtained external field data is analyzed and processed, and a form that the simulation test system can directly use is obtained. The analysis processing means may include one or any combination of the following:

(1) Filter user privacy information. General communication signaling may include some user privacy information, such as IMSI (International Mobile Subscriber Identification Number) / IMEI (International Mobile Equipment Identity), in which case the user needs to be Privacy information is removed from the field data.

(2) Set certain conditions to filter the external field data. For example, distinguishing data of a certain type of business user or a certain area over a period of time.

(3) External field data are classified according to certain principles. For example, data classification (such as urban scenes, indoor scenes, and suburban scenes) may be performed according to different application scenarios, or classified according to information content (such as geographic information, user service information, user movement information, network performance indicators, etc.). (4) Set the calculation formula or calculation program to perform statistics and calculation on the external field data, and output the abstract data model or the data that the simulation test system can directly use.

(5) Analyze the correlation between different types of data, and establish mapping relationships between different types of data, for example, corresponding to different geographical locations, the signal strength and signal quality actually obtained by the user. Step 203: Import the processed data into the simulation test system. For specific implementation, depending on the type or type of data, data can be imported using one of the following methods or any combination:

(1) Import an abstract data model. For example, the user traffic model is abstracted from the user traffic data and imported into the simulation test system, or the signaling delay model is abstracted by the performance indicators such as signaling delay and imported into the simulation test system;

(2) Import statistical experience values. For example, the empirical value is calculated based on the measured data and imported into the simulation test system;

(3) Establish a mapping relationship between data and import it into the simulation test system. For example, establishing a mapping relationship between data according to the correlation between data, and importing the mapping relationship into the simulation test system;

(4) Read data directly. For example, the geographic location information of the base station is directly imported into the simulation test system. Step 204, using the simulation test system to test according to the imported data. In the specific implementation, the algorithm and algorithm are performed on the system level simulation test system that imports the external field data. The parameter verification work, through repeated commissioning, obtains the most suitable parameters, and estimates the system performance, and the obtained simulation results can be compared with the subsequent field test results. Through the above process, it can be seen that the external field data of the mobile communication system is obtained from the data in the actual application scenario of the mobile communication system or the measured data of the external field test of the product, and the obtained external field data is processed to be processed, and the processed external field is processed. Data import system simulation test system or network rule network optimization software, tools for algorithm and device parameter test or network performance verification, thereby reducing network optimization time, quickly setting appropriate algorithm parameters after the device enters the field, speeding up the network to enter the service state the process of. In order to more clearly illustrate the specific implementation of the above embodiments of the present invention, a detailed description will be made below in conjunction with three specific test examples. Example 1: LTE (Long Term Evolution) system switching algorithm test test scenario is shown in Figure 3. There is a shopping mall near the edge of cell 1 and cell 2. Most users in the mall move back and forth within the mall. The switching parameter setting is not suitable. The switching boundary is located just near the shopping mall, which is easy to cause a 4 艮 high ping-pong switching rate. The ping-pong switching will seriously affect the user experience and increase the switching failure rate. Relying on the existing simulation test system can not solve the problem. This is because the user distribution and the movement model in the existing simulation test system are different from the actual scene. Therefore, the handover parameters obtained by the simulation cannot solve the problems in the actual application scenario, so it is necessary to The actual test is carried out in a real field environment, and the switching parameters are optimized by a complex process such as tracking signaling process and detection quality, but the manpower, time and material cost of the external field test required by the method are both high. For the scenario and test requirements, the embodiment shown in FIG. 2 can be used in the embodiment of the present invention. The test is specifically described as follows: In step 201, the LTE base station parameters (including the base station geographic location, the transmit power, the antenna parameters, etc.) of the area of the shopping mall (ie, the area around the shopping mall, here, the cell 1 and the cell 2) are obtained. And obtaining geographical distribution data of users in the area at each time point in a period of time. The process of acquiring the geographical location distribution data of the user in the area at each time point in a period of time (referred to as a simulation time period) may be as shown in FIG. 4, and includes the following steps 11 to 13: Step 11: determining the time for acquiring data The segment and the period length T, which is called the simulation time period, can select a time period with a large number of shopping mall users, such as 1:00 to 5:00 on weekends. The value of T is selected according to requirements. The smaller the value is, the larger the calculation accuracy is, but the larger the calculation amount is. Step 12: At the initial time point of the simulation time period, the geographic location data of the user in the area is used as the initial user. Distribution data; Step 13, every other period T, obtain the geographic location data of the user in the area at the corresponding time point until the end time point of the simulation time period is reached. In step 202, the initial user distribution map is drawn according to the initial user distribution data acquired in step 201, and the user movement model is calculated according to the user distribution data at each time point acquired in step 201. Wherein, the user profile can include user density within each grid. The process of drawing the initial user profile may be as shown in FIG. 5, and includes the following steps 14 to 17: Step 14: respectively obtaining the maximum and minimum longitude of the user distribution data at each time point. The value, and the maximum and minimum values of the latitude in the user distribution data at each time point; Step 15. According to the preset grid size, the area enclosed by the maximum and minimum latitude and longitude is divided into several grids; Step 16. Map each user to the corresponding grid according to their initial geographic location; Step 17. Count the user density on each grid. The unit of user density can be: user/grid. The calculation process of the user movement model may be as shown in FIG. 6 and includes the following steps 18 to 20: Step 18, for each user, respectively calculate the moving direction and moving speed of the same user in each cycle, that is, according to the same user. The geographic position of the user at the two time points (the interval between the two adjacent time points is Τ) is calculated, and the moving direction and moving speed of the user in the time period 计算 are calculated. Wherein, the moving direction can be represented by a moving direction angle. Specifically, the user's position at two adjacent time points t1 and t2 (the interval length of t1 and t2 is T) is sequentially expressed as: POS1(xl, yl) and POS2(x2, y2), then it can be calculated. Obtaining the moving speed of the user during the time period determined by these two times, ^

T, the moving direction angle is x2 - xl Step 19, and the calculation result is stored in the user movement model database. Specifically, the calculation result may be stored according to the geographical area to which the user belongs, for example, the calculation results belonging to the same geographical area are collectively stored, and the geographical area is identified. The size of the geographic area may be the same as the size of the aforementioned grid, or may be larger than the size of the aforementioned grid. For each user, the user's starting position within the time period T (ie, the geographic location corresponding to the starting time point of the time period T) The area is determined to be the geographic area to which the user belongs. Step 20: Calculate a user movement model of each area according to the user movement model database. Specifically, for each area, the user movement model is abstracted based on the moving speed and moving direction angle data of all users in the area. The process of abstracting the user's movement model may be: Probability Distribution Figure (PDF) according to the user's moving direction angle and moving speed, and using the statistical tool to obtain the measured data (including the user moving speed and the moving direction angle data). The probability distribution map is summed to obtain the corresponding quasi-sum curve, which is the user movement model. In step 203, if the simulation test system supports the real map, the data import process may include: import of base station parameters, import of initial user distribution data, and import of a user movement model. Specifically, the data import process may be as shown in FIG. 7, and includes the following steps 21 to 23: Step 21: Import base station parameters. Specifically, the base station parameters (including the base station geographic location, the transmit power, the antenna parameters, and the like) are directly read into the simulation test system; Step 22, the initial user distribution data is imported, that is, the initial user profile is read into the simulation test system, according to the initial The user profile is sprinkled into the user. Specifically, the following operations are performed for each grid in the initial user profile: obtaining location information corresponding to the coverage of each grid, including longitude region information and latitude region information, and determining the user density according to the grid The number of users in the grid 随机, randomly scattered in the grid. Step 23, import the user movement model. The specific import process may be as shown in FIG. 7a, that is, corresponding to each user, the following operations are performed from the start time point of the simulation time period: Step a, determining the area to which the user belongs according to the current user geographic location, and then proceeding to step b; Step b, calculating the user moving speed and moving direction angle according to the user movement model corresponding to the area determined in step a, and importing the generated user moving speed and moving direction angle into the simulation test system, and then proceeding to step c; Step c, determining whether the next time point is the end time point of the simulation time period, and if yes, ending the process, otherwise proceeding to step d; step d, calculating the user moving speed and moving direction angle according to step b, and At a time interval of one time point, the geographical position of the user at the next time point is calculated, and the process proceeds to step a. In step 204, the simulation test system starts the handover algorithm, performs the handover algorithm test according to the imported data and the configured multiple parameters (including the handover threshold, TimeToTrigger, etc.), and outputs the evaluation indexes such as the ping-pong handover rate and the handover failure rate, and selects the optimal. A set of parameters is used as the final used parameter. It is foreseeable that once the parameter setting is not suitable, when the grid of high user density crosses the switching boundary corresponding to the parameter value, the ping-pong switching rate will be 4艮 high. When the appropriate parameters are set, when the grid of high user density does not cross the switching boundary corresponding to the parameter value, the ping-pong switching rate will be greatly reduced. The method of the first example can be used for testing and solving similar problems, and it is convenient to repeat and configure various parameters to find problems. In the actual network, it is difficult to adjust the parameters to test and find problems, so compared with the existing ones in the actual network. The method of testing, using the solution of example one, can solve the problem faster, save costs, and get more optimized parameters. Example 2: Interference coordination algorithm test The interference coordination algorithm uses the UE RSRP (Reference Signal Receiving Power) measurement report to distinguish between the central user and the edge user. Once the user is determined to enter the edge from the center or enter the center from the edge, the RRC (Radio Resource Control) is used. Control) The connection reconfiguration process (that is, the RRC connection reconfiguration signaling procedure) reconfigures parameters such as the power of the UE. The failure probability of the measurement report and the RRC connection reconfiguration signaling process has a critical impact on the performance of the interference coordination algorithm, which affects the location information of the user and the gain of the interference coordination algorithm. For the scenario and the test requirement, the embodiment of the present invention can be tested by using the process shown in FIG. 2, and the specific description is as follows: In step 201, the number of times the UE measurement report is sent and the number of failures, and the RRC connection reconfiguration signaling are obtained. Data such as the number of transmissions and the number of failures. In step 202, the acquired data is classified to find the number of transmissions and failures of the RRC connection reconfiguration signaling triggered by the interference coordination algorithm, the number of transmissions and the number of failures of the UE measurement report triggered by the interference coordination algorithm, and calculate each The failure probability of the RRC connection reconfiguration signaling related to the interference coordination algorithm of the cell and the failure probability of the UE measurement report related to the interference coordination algorithm. In step 203, the failure probability of the RRC connection reconfiguration signaling related to the interference coordination algorithm and the failure probability of the UE measurement report are directly read into the simulation test system. Specifically, the implementation process may include: for each reconfiguration process, generating a random number ranging from 0 to 1. If the random number is smaller than the failure rate of the read RRC connection reconfiguration procedure (that is, the failure probability of the RRC connection reconfiguration signaling), the reconfiguration process is considered to be failed. In this case, the simulation is performed. The test system emulates the UE to reply to the operation of the RRC connection reconfiguration failure signaling to the base station; otherwise, the reconfiguration process is considered successful; in this case, the emulation test system emulates the UE to reply to the operation of the RRC connection reconfiguration success signaling to the base station; For each process of transmitting a UE measurement report, a uniformly distributed random number having a value ranging from 0 to 1 is generated. If the random number is smaller than the failure probability of the read UE measurement report, the UE measurement report is considered to be failed to be sent. In this case, the base station does not process the UE measurement report; otherwise, the UE measurement report is sent successfully. In this case, the operation of the UE to determine the location of the UE according to the UE measurement report is simulated by the simulation test system. In step 204, according to the imported data, the simulation test system simulates the interference coordination algorithm gain under different parameter configurations, and obtains the interference coordination algorithm gain conclusion according to the simulation result. As shown in the description of the second example, the failure probability data of the external field UE measurement report and the RRC connection reconfiguration signaling process are obtained, and the simulation platform is introduced into the simulation platform to perform the interference coordination algorithm test, so that the interference coordination algorithm can be more accurately evaluated in the actual system. Gain, reducing R&D costs and testing costs. Example 3: Business Source Test For the current emerging business, there is no classic business model. You can use the idea of this example 3 to collect business data from some existing networks and read these business data into the simulation test system. As a service source, the system can better guarantee the QoS (Quality of Service) of these services when designing the scheduling algorithm and resource configuration policy, so that it can adapt to the rapid development of existing services. For the scenario and test requirements, the embodiment of the present invention can be tested by using the process shown in FIG. 2, and the specific description is as follows: In step 201, user traffic data is obtained. Specifically, the packet capture software may be used on the terminal, such as the NBT, to capture user traffic data of a certain service for a certain period of time. The user traffic data includes the data packet size and the sending interval of the data packet, etc.; the complete service process may be included in the continuous time period of the service, and each complete service process has corresponding user traffic data. In step 202, the acquired user traffic data is stored in a form that can be used by the simulation test system, and unnecessary information other than the user traffic data is deleted to form a user traffic database. In the user traffic database, the user traffic data is stored separately according to the corresponding service process, for example, user traffic data belonging to the same service process is stored centrally, and the service process to which it belongs is identified. The user traffic database can contain user traffic data for multiple complete business processes. In step 203, the user traffic database is imported into the simulation test system, as shown in FIG. 8. The specific import process may include the following steps 31 to 36: Step 31, after the user establishes an RRC connection, that is, after the user enters the connection state, the slave user Select a complete business process in the traffic database, for example, you can randomly select a complete business process; Step 32, read the size and packet interval of the first data packet of the business process, generate the first data packet and import it into the simulation. Test system; Step 33: Determine whether the time interval from the time point when the previous data packet is imported to the current time point reaches the read time interval, and if yes, go to step 34, otherwise continue to wait. Step 34: Read the size and the interval of sending the next packet of the service process, and generate Correspondize the size of the packet and import it into the simulation test system. Step 35: Determine whether the business process ends. If yes, go to step 36; otherwise, go to step 33. In step 36, it is determined whether all the business processes have been read, and if so, the process ends, otherwise, the process proceeds to step 31. In step 204, according to the imported data, the simulation test system tests the algorithm related to the service source, such as the scheduling algorithm, simulates the algorithm performance and system performance under different algorithm strategies and parameter configurations, and finally obtains an algorithm adapted to the service source. Strategy and parameters. As can be seen from the above process of the third example, the third example can quickly obtain the traffic characteristics of the emerging service source, and is used for algorithm research and simulation analysis to adapt to the rapid development of the existing business. It will be apparent that existing network planning and optimization tools (including software and hardware) can be further improved by applying the embodiments of the present invention. Based on the same technical concept, an embodiment of the present invention further provides a simulation test device. FIG. 9 is a schematic structural diagram of a simulation test device according to an embodiment of the present invention. As shown in FIG. 9, the device may include: a data acquisition module 901, a data processing module 902, a data import module 903, and a simulation test module 904, where: The obtaining module 901 is configured to acquire external field data of the mobile communication system, and the data processing module 902 is configured to process the acquired external field data to obtain data suitable for the simulation test; The data importing module 903 is configured to import the processed data into the simulation test system. The simulation test module 904 is installed with a simulation test system for performing system level simulation test according to the imported data by the simulation test system. Specifically, the data obtaining module 901 can acquire the external field data of the mobile communication system by one or a combination of the following: obtaining the stored communication data from the operation and maintenance system; acquiring the recorded communication data from the communication device; and using the test tool to capture the communication data. Specifically, the external field data may include one or any combination of the following types of data: geographic information, base station parameters, user traffic parameters, performance indicator parameters, and user mobility parameters. Specifically, the data processing module 902 may process the acquired external field data by using one or a combination of the following methods: filtering user privacy information in the external field data; screening the external field data according to a preset condition; Principles are classified; statistics and calculations are performed on external field data according to preset calculation formulas or calculation procedures. Specifically, the data importing module 903 can import the processed data into the simulation test system by using one or a combination of the following methods: The empirical value is calculated according to the processed external field data, and the calculated empirical value is imported into the simulation test system; the corresponding data model is obtained according to the processed data abstraction, and the obtained data model is imported into the simulation test system; according to different types The relationship between the data establishes the mapping relationship between different types of data, and the established mapping relationship is imported into the simulation test system; the processed external field data is directly imported into the simulation test system. The above simulation test equipment can be used for system switching algorithm test, interference coordination algorithm test, service source test, and the like. When the simulation test device is used for the system switching algorithm test, the data acquisition module 901 may acquire the base station parameters in the specified area, and set the geographic location distribution data of the user in the area at each time point in the set time period; The module 902 may draw an initial user distribution map according to the geographical location distribution data of the user at the initial time point of the obtained set time period, and obtain a user movement model according to the obtained geographical distribution data of the user at each time point; The data importing module 903 can import the acquired base station parameters, the drawn initial user profile, and the statistically obtained user movement model into the simulation test system; the simulation test module 904 can use the simulation test system to communicate according to the imported data. The system switching algorithm is tested. Specifically, the data processing module 902 can perform data processing by using the processes shown in FIG. 5 and FIG. 6; the data importing module 903 can import data into the simulation test system by using the flow shown in FIG. 7. When the simulation test device is used for the interference coordination algorithm test, the data acquisition module 901 may obtain the number of times the number of transmissions and the number of failures of the measurement report of the user terminal (ie, the user equipment UE) are obtained. And the number of transmissions and the number of failures of the radio resource control RRC connection reconfiguration signaling; the data processing module 902 can classify the acquired data to find the number of transmissions and the number of failures of the RRC connection reconfiguration signaling triggered by the interference coordination algorithm, and the interference The number of transmissions and the number of failures of the UE measurement report triggered by the coordination algorithm are calculated, the failure probability of the RRC connection reconfiguration signaling related to the interference coordination algorithm and the failure probability of the UE measurement report are calculated; the data import module 903 may be related to the interference coordination algorithm. The failure probability of the RRC connection reconfiguration signaling and the failure probability of the UE measurement report are directly imported into the simulation test system; the simulation test module 904 can use the simulation test system to test the interference coordination algorithm under different parameter configurations according to the imported data. Specifically, the data importing module 903 is further configured to: for each reconfiguration process, generate a random number ranging from 0 to 1, and if the random number is smaller than a failure probability of the read RRC connection reconfiguration signaling, Simulating the user terminal to reply to the operation of the RRC connection reconfiguration failure signaling to the base station by using the simulation test system, otherwise simulating the user terminal to reply to the operation of the RRC connection reconfiguration success signaling to the base station through the simulation test system; and, for each time transmitting the UE measurement report a process of generating a uniformly distributed random number ranging from 0 to 1, and when the random number is greater than a failure probability of the read UE measurement report, simulating the base station according to the UE measurement report by the simulation test system Location operation. When the simulation test device is used for the service source test, the data acquisition module 901 may obtain user traffic data of the specified service within a set time period, where the set time period includes one or more complete service processes. The data processing module 902 can delete information other than the user traffic data from the acquired user traffic data, and store the user traffic data in the user traffic database according to the service process corresponding to the user traffic data; the data import module 903 can use the map. The process shown in FIG. 8 imports the processed data into the simulation test system; the simulation test module 904 can use the simulation test system to calculate the algorithm related to the service source according to the imported data. carry out testing. The modules in the foregoing embodiments of the present invention may be integrated into one or separate deployments; they may be combined into one module or further split into multiple sub-modules. The various modules in the foregoing embodiments of the present invention may be implemented by software (for example, machine readable instructions stored in a memory and executed by a processor), or may be implemented by hardware (for example, an Application Specific Integrated Circuit (ASIC)). Processor), or a combination of software and hardware. The embodiments of the present invention are not specifically limited. FIG. 10 is a hardware structural diagram of a simulation test device according to an embodiment of the present invention. As shown in FIG. 10, the device includes: a processor 1001, a memory 1002, at least one port 1003, and a bus 1004. The processor 1001 and the memory 1002 are interconnected by a bus 1004. The device can receive and transmit data through port 1003. The memory 1002 stores the machine readable instructions; the processor 1001 executes the machine readable instructions to: obtain the external communication data of the mobile communication system; process the acquired external field data, and obtain the simulation suitable for the simulation Tested data; the processed data is imported into the simulation test system; and the simulation test system is used to perform system level simulation test according to the imported data. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform one or any combination of the following: obtaining, from the operation and maintenance system, its stored communication data; Acquire the communication data recorded by the communication device; use the test tool to capture the communication data. In the embodiment of the present invention, the external field data includes one or any combination of the following types of data: geographic information: including latitude and longitude or base station spacing; base station parameters: including antenna height, antenna orientation, or uniformity of base station distribution; user traffic parameters : Includes peak rate, average rate, or service characteristics of user traffic; Performance indicator parameters: including signaling failure rate, signaling delay, or main process delay; User mobility parameters: including user movement route, movement speed, or whether to cross Different types of geographic regions or networks of different standards. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform one or any combination of the following: filtering user privacy information in the external field data; screening the external field data according to a preset condition; The pre-set principle is classified; the external field data is counted and calculated according to the preset calculation formula or calculation program. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform one or any combination of the following: The empirical value is calculated according to the processed external field data, and the calculated empirical value is imported into the simulation test system; the corresponding data model is obtained according to the processed external field data abstraction, and the obtained data model is imported into the simulation test system; The association between type data establishes the mapping relationship between different types of data, and imports the established mapping relationship into the simulation test system; directly imports the processed external field data into the simulation test system. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform the following operations: acquiring base station parameters within a specified area, and setting geographic location distribution data of the area at each time point within the time period According to the geographical distribution data of the user at the initial time point of the obtained set time period, the initial user distribution map is drawn, and the user movement model is obtained according to the obtained geographical distribution data of the user at each time point; The obtained base station parameters, the drawn initial user distribution map, and the statistically obtained user movement model are imported into the simulation test system; and the communication system switching algorithm is tested according to the imported data using the simulation test system. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform the following operations: For each user, according to the geographical distribution data of the user at each time point obtained, the moving direction and the moving speed angle of the user in the interval time between two adjacent time points are calculated; according to the area to which the user belongs, The calculation result of each user is stored in the user movement model database; wherein, the area to which the user belongs is the area where the geographic location corresponding to the starting time point of the user in the interval between two adjacent time points; Areas, abstracting the user movement model of the area according to the moving speed and moving direction angle data of all users in the area; for each user, starting from the starting time point of the set time period, performing the following steps Step a: determining the area to which the user belongs according to the current user's geographic location; Step b: calculating the user moving speed and the moving direction angle according to the user movement model corresponding to the area to which the user belongs in step a, and generating the user moving speed And the moving direction angle is imported into the simulation test system; step c, judging the next time point is For the end time point of the set time period, if yes, the import process is ended, otherwise step d is performed; step d, the user moving speed and the moving direction angle calculated according to step b and the time interval from the next time point, Calculate the geographic location of the user at the next point in time and perform step a. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform the following operations: acquiring the number of transmissions and failures of the user equipment UE measurement report, and the radio resources Controlling the number of transmissions and the number of failures of the RRC connection reconfiguration signaling; classifying the acquired data to find the number of transmissions and failures of the RRC connection reconfiguration signaling triggered by the interference coordination algorithm, and the UE measurement report triggered by the interference coordination algorithm The number of transmissions and the number of failures, the failure probability of RRC connection reconfiguration signaling related to the interference coordination algorithm and the failure probability of the UE measurement report related to the interference coordination algorithm are calculated; the RRC connection reconfiguration signaling related to the interference coordination algorithm The failure probability and the failure probability of the UE measurement report related to the interference coordination algorithm are directly imported into the simulation test system; the interference coordination algorithm under different parameter configurations is tested according to the imported data using the simulation test system. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform the following operations: for each reconfiguration process, generating a random number ranging from 0 to 1, if the random number is smaller than the read The failure probability of the RRC connection reconfiguration signaling related to the interference coordination algorithm is simulated by the emulation test system to return the RRC connection reconfiguration failure signaling to the base station, or the emulation test system emulates the UE to reply to the RRC connection reconfiguration success signal. The operation of the base station is performed; for each process of transmitting the UE measurement report, a uniformly distributed random number ranging from 0 to 1 is generated, and the random number is greater than the read UE measurement related to the interference coordination algorithm. When the probability of failure is reported, the operation of the UE to determine the location of the UE according to the UE measurement report is simulated by the simulation test system. The processor 1001 executes machine readable instructions stored in the memory 1002 to further perform the following operations: acquiring user traffic data of a specified service within a set time period, wherein the set time period includes one or more times a complete service process; deleting information other than the user traffic data from the obtained user traffic data, and storing the user traffic data in the user traffic database according to the service process corresponding to the user traffic data; the processor 1001 Executing the machine readable instructions stored in the memory 1002 to further perform the following operations: Step a, selecting a complete service process from the user traffic database; Step b, reading the size and packet interval of the first data packet of the service process , generating a first data packet and importing it into the simulation test system; step c, determining whether the time interval from the time point when the previous data packet is imported to the current time point reaches the read delivery interval, and if so, Execute step d, otherwise continue to wait; step d, read the next packet of the business process is large And sending a packet interval, generating a data packet of a corresponding size and importing it into the simulation test system; Step e, determining whether the service process ends; if yes, executing step f; otherwise, performing step c; Step f, determining whether all the business processes Have been read, and if so, end The process is imported, otherwise step a is performed; the algorithm related to the service source is tested according to the imported data using the simulation test system. It can be seen that when the machine readable instructions stored in the memory 1002 are executed by the processor 1001, the functions of the aforementioned data acquisition module 901, data processing module 902, data import module 903, and simulation test module 904 can be implemented. In summary, in the above embodiment of the present invention, the external field data is obtained from the external field of the mobile communication system, the acquired external field data is processed, and the processed external field data is imported into the system simulation test system for system level testing. Therefore, the simulation evaluation result is closer to the real scene of the mobile communication system, thereby reducing the network optimization time, and the suitable algorithm parameters can be quickly set after the device enters the field, and the process of the network entering the service state is accelerated. Hardware modules or units in various embodiments of the invention may be implemented mechanically or electronically. For example, a hardware module can include specially designed permanent circuits or logic devices (such as dedicated processors such as FPGAs or ASICs) for performing specific operations. The hardware modules may also include programmable logic devices or circuits (such as including general purpose processors or other programmable processors) that are temporarily configured by software for performing particular operations. The specific use of mechanical means, or the use of dedicated permanent circuits, or the use of temporarily configured circuits (such as software configuration) to implement hardware modules, can be determined based on cost and time considerations. Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus a necessary general hardware platform, that is, by machine-readable instructions to instruct related hardware, and of course It can be done through hardware, but in many cases the former is a better implementation. Based on such understanding, the technical solution of the present invention is essentially or It is said that the part contributing to the prior art can be embodied in the form of a software product stored in a storage medium, including a plurality of instructions for making a terminal device (which can be a mobile phone, a personal computer, a server) , or a network device, etc.) performs the methods described in various embodiments of the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM). The drawings in the embodiments of the present invention are only some embodiments, and the modules and steps are not necessary for implementing the present invention. The modules may be combined into one module or further divided into a plurality of sub-modules. The above description is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can also make several improvements and retouchings without departing from the principles of the present invention. The scope of protection of the invention should be considered.

Claims

claims

1. A simulation test method, characterized in that the method includes:

Obtain field data of mobile communication system;

Process the acquired field data to obtain data suitable for simulation testing; import the processed data into the simulation testing system;

Use the simulation test system to perform system-level simulation testing according to the imported data.

2. The method of claim 1, wherein the method of obtaining field data of the mobile communication system includes one or a combination of the following operations:

Obtain its stored communication data from the operation and maintenance system;

Obtain the communication data recorded by the communication device;

Use testing tools to capture communication data.

3. The method of claim 1, wherein the external field data includes one or any combination of the following types of data:

Geographic information: including latitude and longitude or distance between base stations;

Base station parameters: including antenna height, antenna orientation, or evenness of base station distribution; User traffic parameters: including peak rate, average rate or business characteristics of user traffic; Performance index parameters: including signaling failure rate, signaling delay or major Process delay; User movement parameters: including user movement route, movement speed, or whether it needs to span different types of geographical areas or networks of different standards.

4. The method of claim 1, wherein the method of processing the acquired field data includes one or any combination of the following operations:

Filter user privacy information in off-site data;

Filter field data according to preset conditions;

Classify field data according to preset principles; Perform statistics and calculations on field data according to preset calculation formulas or calculation programs.

5. The method of claim 1, wherein the method of importing the processed data into the simulation test system includes one or any combination of the following operations:

Calculate experience values based on the processed field data, and import the calculated experience values into the simulation test system;

Obtain the data model based on the processed field data abstraction, and import the obtained data model into the simulation test system;

Establish mapping relationships between different types of data based on the correlations between different types of data, and import the established mapping relationships into the simulation test system;

Import the processed field data directly into the simulation test system.

6. The method according to claim 1, characterized in that the obtaining of mobile communication system field data includes: obtaining base station parameters in a designated area, and users in the area at each time point within a set time period. Geographical distribution data;

The processing of the obtained field data includes: drawing an initial user distribution map based on the obtained user geographical location distribution data at the initial time point of the set time period, and drawing an initial user distribution map based on the obtained user geographical distribution data at each time point. Geographical location distribution data statistics are used to obtain user mobility models;

The process of importing the processed data into the simulation test system includes: importing the obtained base station parameters, the drawn initial user distribution map, and the statistically obtained user mobility model into the simulation test system;

Using the simulation test system to perform system-level simulation testing based on the imported data includes: using the simulation testing system to test the communication system switching algorithm based on the imported data.

7. The method of claim 6, wherein the user mobility model is obtained based on the obtained user geographical location distribution data statistics at each time point, including: For each user, based on the obtained geographical location distribution data of the user at each time point, calculate the moving direction and moving speed angle of the user within the interval between two adjacent time points;

According to the user's area, the calculation results of each user are stored in the user mobility model database; wherein, the user's area is the geographical location corresponding to the starting time point of the user within the interval between two adjacent time points. the area in which it is located;

For each area, based on the movement speed and movement direction angle data of all users in the area, the user movement model of the area is abstracted;

The step of importing the statistically obtained user mobility model into the simulation test system includes: For each user, starting from the starting time point of the set time period, perform the following steps:

Step a. Determine the area to which the user belongs based on the current user's geographical location;

Step b. Calculate the user's movement speed and movement direction angle based on the user movement model corresponding to the user's area determined in step a, and import the generated user movement speed and movement direction angle into the simulation test system;

Step c. Determine whether the next time point is the end time point of the set time period. If so, end the import process, otherwise perform step d;

Step d. Calculate the geographical location of the user at the next time point based on the user's movement speed and movement direction angle calculated in step b and the time interval from the next time point, and perform step a.

8. The method of claim 1, wherein the obtaining mobile communication system field data includes: obtaining the number of sending times and the number of failures of user equipment UE measurement reports, and sending radio resource control RRC connection reconfiguration signaling. times and failures;

The processing of the obtained field data includes: classifying the obtained data, finding out the number of sending times and the number of failures of RRC connection reconfiguration signaling triggered by the interference coordination algorithm, The number of transmissions and failures of UE measurement reports triggered by the interference coordination algorithm, calculating the failure probability of RRC connection reconfiguration signaling related to the interference coordination algorithm in each cell and the failure probability of UE measurement reports related to the interference coordination algorithm;

Importing the processed data into the simulation test system includes: directly importing the failure probability of RRC connection reconfiguration signaling related to the interference coordination algorithm and the failure probability of the UE measurement report related to the interference coordination algorithm into the simulation test system;

Using the simulation test system to perform system-level simulation tests based on the imported data includes: using the simulation test system to test interference coordination algorithms under different parameter configurations based on the imported data.

9. The method of claim 8, wherein the failure probability of RRC connection reconfiguration signaling related to the interference coordination algorithm and the failure probability of the UE measurement report related to the interference coordination algorithm are directly introduced into the simulation test system , include:

For each reconfiguration process, a random number with a value ranging from 0 to 1 is generated. If the random number is less than the read failure probability of RRC connection reconfiguration signaling related to the interference coordination algorithm, the simulation test system is simulated The operation of the user equipment replying the RRC connection reconfiguration failure signaling to the base station, otherwise the simulation test system is used to simulate the operation of the user equipment replying the RRC connection reconfiguration successful signaling to the base station;

For each process of sending a UE measurement report, a uniformly distributed random number ranging from 0 to 1 is generated, and when the random number is greater than the read failure probability of the UE measurement report related to the interference coordination algorithm, The simulation test system simulates the operation of the base station to determine the location of the user equipment based on the UE measurement report.

10. The method of claim 1, wherein the obtaining mobile communication system field data includes: obtaining user traffic data of a specified service within a set time period, wherein the set time period includes One or more complete courses of business;

The processing of the obtained field data includes: From the obtained user traffic data Delete information other than user traffic data, and store the user traffic data in a user traffic database according to the business process corresponding to the user traffic data;

The process of importing the processed data into the simulation test system includes:

Step a, select a complete business process from the user traffic database;

Step b, read the size and packet sending interval of the first data packet of the business process, generate the first data packet and import it into the simulation test system;

Step c, determine whether the time interval from the time point when the previous data packet was imported to the current time point reaches the read packet sending interval. If it reaches, perform step d, otherwise continue to wait;

Step d, read the next data packet size and packet sending interval of the business process, generate a data packet of the corresponding size and import it into the simulation test system;

Step e, determine whether the business process is over. If it is over, execute step f; otherwise, execute step c;

Step f, determine whether all business processes have been read, if so, end the import process, otherwise perform step a;

Using the simulation test system to perform system-level simulation testing based on the imported data includes: using the simulation testing system to test algorithms related to business sources based on the imported data.

11. A simulation test equipment, characterized by including:

Data acquisition module, used to acquire field data of mobile communication systems;

The data processing module is used to process the acquired field data to obtain data suitable for simulation testing;

The data import module is used to import the processed data into the simulation test system; the simulation test module is installed with a simulation test system and is used to perform system-level simulation tests based on the imported data through the simulation test system.

12. The simulation test equipment according to claim 11, characterized in that, the data acquisition module is also used to perform one or a combination of the following operations to obtain field data of the mobile communication system: obtain its stored communication data from the operation and maintenance system;

Obtain the communication data recorded by the communication device;

Use testing tools to capture communication data.

13. The simulation test equipment according to claim 11, characterized in that the external field data includes one or any combination of the following types of data:

Geographic information: including latitude and longitude or distance between base stations;

Base station parameters: including antenna height, antenna orientation, or evenness of base station distribution; User traffic parameters: including peak rate, average rate or business characteristics of user traffic; Performance index parameters: including signaling failure rate, signaling delay or major Process delay; User movement parameters: including user movement route, movement speed, or whether it needs to span different types of geographical areas or networks of different standards.

14. The simulation test equipment according to claim 11, characterized in that, the data processing module is also used to perform one or a combination of the following operations to process the acquired field data: filter user privacy information in the field data;

Filter field data according to preset conditions;

Classify field data according to preset principles;

Perform statistics and calculations on field data according to preset calculation formulas or calculation programs.

15. The simulation test equipment according to claim 11, characterized in that the data import module is also used to perform one or a combination of the following operations to import the processed data into the simulation test system:

Calculate experience values based on the processed field data, and import the calculated experience values into the simulation test system;

Obtain the data model based on the processed field data abstraction, and import the obtained data model into Enter the simulation test system;

Establish mapping relationships between different types of data based on the correlations between different types of data, and import the established mapping relationships into the simulation test system;

Import the processed field data directly into the simulation test system.

16. The simulation test equipment according to claim 11, characterized in that the data acquisition module is also used to obtain base station parameters in a designated area and users in the area at each time point within a set time period. Geographical distribution data;

The data processing module is also used to draw an initial user distribution map based on the obtained user geographical location distribution data at the initial time point of the set time period, and draw an initial user distribution map based on the obtained user geographical location distribution data at each time point. Obtain user movement model through statistics;

The data import module is also used to import the obtained base station parameters, the drawn initial user distribution map, and the statistically obtained user mobility model into the simulation test system; the simulation test module is also used to import the obtained base station parameters according to the imported data. The communication system switching algorithm is tested using the simulation test system.

17. The simulation test equipment according to claim 11, characterized in that the data acquisition module is further configured to obtain the number of sending times and the number of failures of user equipment UE measurement reports, and the sending of radio resource control RRC connection reconfiguration signaling. times and failures;

The data processing module is also used to classify the acquired data and find out the number of transmissions and failures of RRC connection reconfiguration signaling triggered by the interference coordination algorithm, and the number of transmissions and failures of UE measurement reports triggered by the interference coordination algorithm. times, calculate the failure probability of RRC connection reconfiguration signaling related to the interference coordination algorithm in each cell and the failure probability of the UE measurement report related to the interference coordination algorithm;

The data import module is also used to directly import the failure probability of RRC connection reconfiguration signaling related to the interference coordination algorithm and the failure probability of the UE measurement report related to the interference coordination algorithm into the simulation test system; The simulation test module is also used to use the simulation test system to test the interference coordination algorithm under different parameter configurations according to the imported data.

18. The simulation test equipment according to claim 11, characterized in that the data acquisition module is also used to obtain user traffic data of the specified service within a set time period, wherein the set time period includes One or more complete courses of business;

The data processing module is also configured to delete information other than user flow data from the obtained user flow data, and store the user flow data in a user flow database according to the business process corresponding to the user flow data;

The data import module is also used to perform the following steps to import the processed data into the simulation test system:

Step a, select a complete business process from the user traffic database;

Step b, read the size and packet sending interval of the first data packet of the business process, generate the first data packet and import it into the simulation test system;

Step c, determine whether the time interval from the time point when the previous data packet was imported to the current time point reaches the read packet sending interval. If it reaches, perform step d, otherwise continue to wait;

Step d, read the next data packet size and packet sending interval of the business process, generate a data packet of the corresponding size and import it into the simulation test system;

Step e, determine whether the business process is over. If it is over, execute step f; otherwise, execute step c;

Step f, determine whether all business processes have been read, if so, end the operation of the data import module, otherwise perform step a;

The simulation test module is used to use the simulation test system to test algorithms related to business sources according to the imported data.