Test method, system and device, related equipment, storage medium and computer program product

Abstract

The invention discloses a test method, system and device, a first platform, a second platform, a storage medium and a computer program product. The method comprises the following steps: a first platform obtains test output information for the wireless network performance test, the test output information comprises first information, and the first information is used for indicating a test result associated with a test index in the test output information; determining a current test result by using the first information; an analysis result is generated according to the test result, the analysis result comprises second information or third information, the second information comprises related information of the to-be-optimized parameters, and the third information represents that the parameters corresponding to the test do not need to be optimized; and sending an analysis result to a second platform, wherein the analysis result is used for the second platform to generate a parameter adjustment instruction for next test of the performance of the wireless network.

Description

Technical Field

[0001] The present application relates to the field of wireless networks, and in particular to a scheduling method, system, apparatus, related equipment, storage medium, and computer program product. Background Art

[0002] In related technologies, when performing performance testing on base station equipment, all test-related parameters are tested through a complete traversal method (also known as a traversal test) to obtain test results, which are then manually analyzed to determine the optimal test results and corresponding parameter configurations.

[0003] However, when there are many parameters related to performance testing, using the traversal test solution for performance testing requires a large number of tests to traverse all possible parameter configurations in order to obtain the optimal test results, which results in low test efficiency. At the same time, the workload of manual analysis is large and the analysis efficiency is low. Summary of the Invention

[0004] To solve related technical problems, embodiments of the present application provide a testing method, system, apparatus, related equipment, storage medium, and computer program product.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] The present application provides a testing method, which is applied to a first platform and includes:

[0007] Acquire test output information for this wireless network performance test, where the test output information includes first information, where the first information is used to indicate a test result associated with a test indicator in the test output information;

[0008] Determine the test result using the first information;

[0009] Generate an analysis result using the test result of this time, wherein the analysis result includes second information or third information, wherein the second information includes relevant information of the parameter to be optimized, and the third information indicates that the parameter corresponding to this test does not need to be optimized;

[0010] The analysis result is sent to the second platform, where the analysis result is used by the second platform to generate a parameter adjustment instruction for the next test on the performance of the wireless network.

[0011] In the above solution, the use of the test results to generate analysis results includes:

[0012] When the test result does not meet the threshold requirement of the test indicator, generating the second information;

[0013] or,

[0014] When the test result of this time meets the threshold requirement of the test indicator, the third information is generated.

[0015] In the above solution, the test output information further includes fourth information, and the fourth information represents the parameter configuration associated with the test indicator in the test output information; and generating the second information includes:

[0016] The second information is generated using the fourth information.

[0017] The present application also provides a testing method, which is applied to the second platform and includes:

[0018] Receiving an analysis result of the wireless network performance test sent by the first platform, the analysis result including second information or third information, the second information including relevant information of the parameter to be optimized, and the third information indicating that the parameter corresponding to the test does not need to be optimized;

[0019] Do one of the following:

[0020] In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an optimization test order for each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information characterizing the correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1;

[0021] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0022] In the above solution, determining the optimization test order of each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters includes:

[0023] Sort by the weight of each parameter from high to low to get the sorting result;

[0024] The sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

[0025] In the above solution, determining the optimization test order of each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters includes:

[0026] For one or more parameter clusters, sort the parameter clusters from high to low according to the weight of each parameter cluster to obtain a first sorting result;

[0027] Based on the first sorting result, for each parameter cluster, sort the parameters in the parameter cluster from high to low according to the weight of each parameter in the parameter cluster to obtain a second sorting result;

[0028] The second sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

[0029] In the above solution, the method further includes:

[0030] During the testing process, the weight of each parameter is adjusted.

[0031] In the above solution, the adjustment of the parameter weights includes:

[0032] Determine the test results of the correlation between the test indicators before and after the parameter adjustment;

[0033] Determine the first factor using the test results associated with the determined test indicators;

[0034] The weight of the parameter is adjusted using the first factor.

[0035] In the above solution, the second information includes an optimization strategy for the parameter to be optimized; when generating the parameter adjustment instruction, the method includes:

[0036] The parameter adjustment instruction is generated using the optimization strategy.

[0037] In the above solution, the optimization strategy includes parameter configuration identifiers of the parameters to be optimized; the optimization strategy generates parameter adjustment instructions, including:

[0038] Determining an adjustment value of the parameter using the parameter configuration identifier of the parameter to be optimized;

[0039] The parameter adjustment instruction is generated according to the determined parameter adjustment value.

[0040] The embodiment of the present application further provides a testing system, comprising: a first platform and a second platform; wherein,

[0041] The first platform is configured to obtain test output information for the current wireless network performance test, the test output information including first information, the first information being used to indicate a test result associated with a test indicator in the test output information; determine the current test result using the first information; generate an analysis result using the current test result, the analysis result including second information or third information, the second information including relevant information about a parameter to be optimized, the third information indicating that the parameter corresponding to the current test does not need to be optimized; and send the analysis result to the second platform, the analysis result being used for the second platform to generate a parameter adjustment instruction for a next test of the performance of the wireless network;

[0042] The second platform is configured to receive the analysis result of the wireless network performance test sent by the first platform, and perform one of the following:

[0043] In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an optimization test order for each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information characterizing the correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1;

[0044] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0045] The present application also provides a testing device, which is provided on a first platform and includes:

[0046] an acquiring unit, configured to acquire test output information for this wireless network performance test, wherein the test output information includes first information, and the first information is used to indicate a test result associated with a test indicator in the test output information;

[0047] a determining unit, configured to determine a test result of this time using the first information;

[0048] a generating unit, configured to generate an analysis result using the test result, wherein the analysis result includes second information or third information, wherein the second information includes information related to the parameter to be optimized, and the third information indicates that the parameter corresponding to the test does not need to be optimized;

[0049] The sending unit is used to send the analysis result to the second platform, where the analysis result is used by the second platform to generate a parameter adjustment instruction for the next test on the performance of the wireless network.

[0050] The present application also provides a testing device, which is provided on a second platform and includes:

[0051] a receiving unit, configured to receive an analysis result of the wireless network performance test sent by the first platform, the analysis result including second information or third information, the second information including relevant information of the parameter to be optimized, and the third information indicating that the parameter corresponding to the test does not need to be optimized;

[0052] An execution unit that performs one of the following:

[0053] In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an order for optimizing each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information representing a correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1;

[0054] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0055] The embodiment of the present application further provides a first platform, including:

[0056] a first communication interface for obtaining test output information for the current wireless network performance test, the test output information including first information indicating a test result associated with a test indicator in the test output information; and sending an analysis result to a second platform, the analysis result being used by the second platform to generate a parameter adjustment instruction for a next test of the wireless network performance;

[0057] The first processor is used to use the first information to determine the test result of this time; and use the test result of this time to generate an analysis result, wherein the analysis result includes second information or third information, the second information includes relevant information of the parameters to be optimized, and the third information indicates that the parameters corresponding to this test do not need to be optimized.

[0058] The embodiment of the present application further provides a second platform, including:

[0059] a second communication interface, configured to receive an analysis result of the wireless network performance test sent by the first platform, the analysis result including second information or third information, the second information including relevant information of the parameter to be optimized, and the third information indicating that the parameter corresponding to the test does not need to be optimized;

[0060] The second processor is configured to perform one of the following:

[0061] In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an order for optimizing each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information representing a correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1;

[0062] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0063] The embodiment of the present application further provides a first platform, comprising: a first processor and a first memory for storing a computer program that can be run on the processor,

[0064] Wherein, the first processor is used to execute the steps of any one of the above-mentioned methods on the first platform side when running the computer program.

[0065] The embodiment of the present application further provides a second platform, comprising: a second processor and a second memory for storing a computer program that can be run on the processor,

[0066] Wherein, the second processor is used to execute the steps of any of the above-mentioned methods on the second platform side when running the computer program.

[0067] An embodiment of the present application also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-mentioned methods on the first platform side, or implements the steps of any of the above-mentioned methods on the second platform side.

[0068] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned methods on the first platform side, or implements the steps of any of the above-mentioned methods on the second platform side.

[0069] The test method, system, apparatus, related equipment, storage medium and computer program product provided by the embodiments of the present application are as follows: a first platform obtains test output information for this wireless network performance test, wherein the test output information includes first information, and the first information is used to indicate the test result associated with the test indicator in the test output information; uses the first information to determine the test result of this time; uses the test result of this time to generate an analysis result, wherein the analysis result includes second information or third information, the second information includes relevant information of the parameter to be optimized, and the third information indicates that the parameter corresponding to this test does not need to be optimized; sends the analysis result to the second platform, and the analysis result is used for the second platform to generate a parameter adjustment instruction for the next test of the performance of the wireless network; and after the second platform receives the analysis result for this wireless network performance test sent by the first platform, performs one of the following: when the analysis result includes the second information, uses the second information and the fourth information to determine the parameter to be optimized. One or more parameter clusters corresponding to the optimization parameter, and determine the optimization test order of each parameter contained in the one or more parameter clusters based on the weights of the N parameters contained in the one or more parameter clusters, for each parameter, adjust the parameter value based on the determined order, and use the adjusted parameter value of each parameter to generate a parameter adjustment instruction, the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information represents the correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information contains one or more parameter clusters, the parameters in each parameter cluster are completely different, and N is an integer greater than or equal to 1; when the analysis result contains the third information, based on the number of user access in this test, a parameter adjustment instruction is generated, the parameter adjustment instruction is used to instruct the wireless network to increase the number of user access when performing the next test, and test the performance of the wireless network based on the parameter value corresponding to this test. The solution provided by the embodiment of the present application is that the first platform analyzes the test results contained in the test output information, generates analysis results and sends the analysis results to the second platform, and then the second platform uses the received analysis results to generate parameter adjustment instructions, and through the parameter adjustment instructions, instructs the wireless network to increase the number of user access in the next test or adjust the parameter values corresponding to the next test according to the optimized test sequence. In this way, on the one hand, the test results contained in the test output information can be quickly and automatically analyzed by the first platform to obtain analysis results, without the need for manual analysis, and the analysis efficiency is high; on the other hand, the optimized test sequence of parameters can be adjusted by weights, that is, by setting corresponding weights, the parameters that can significantly improve performance can be optimized first, so that the test results can meet the test indicators after a smaller number of tests, thereby improving the test efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is a flow chart of the first testing method according to an embodiment of the present application;

[0071] Figure 2 This is a flow chart of the second testing method according to the embodiment of the present application;

[0072] Figure 3 Schematic diagram of the correspondence between optimization decision items and parameter clusters according to an embodiment of the present application;

[0073] Figure 4 This is a flow chart of the third testing method according to the embodiment of the present application;

[0074] Figure 5 This is a schematic diagram of the structure of an automated test system for a base station device used in this application example;

[0075] Figure 6 This is a flowchart of an example automated testing method for this application;

[0076] Figure 7 This is a schematic structural diagram of the first test device according to an embodiment of the present application;

[0077] Figure 8 This is a schematic diagram of the structure of the second test device according to the embodiment of the present application;

[0078] Figure 9 This is a schematic diagram of the first platform structure of the embodiment of the present application;

[0079] Figure 10 This is a schematic diagram of the second platform structure of the embodiment of the present application;

[0080] Figure 11 This is a schematic diagram of the test system structure of an embodiment of the present application. DETAILED DESCRIPTION

[0081] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0082] In related technologies, network-side equipment (specifically, base station equipment) needs to undergo a large number (also understood as multiple times) of repetitive functional and performance tests in the laboratory before commercial applications and field trials, in order to achieve functional and performance adjustment and optimization (also referred to as tuning).

[0083] Among them, the functional test of the base station equipment needs to test whether the current equipment meets the functional requirements. Therefore, the test output information of each test in the functional test may include: correct messages and other messages; wherein, the correct message indicates that the functional test has passed, and the other message indicates that the functional test has failed. Since the test output information of the functional test can be analyzed relatively easily (specifically, it can include judging whether the test output information contains the correct message), the test output information of the functional test can be analyzed in an automated manner during the functional test of the base station equipment; however, the performance test of the base station equipment needs to test the parameter combination that can make the performance of the base station equipment reach the optimal level, which involves the configuration and optimization of a large number of parameters (which can also be understood as test parameters). It is not possible to simply analyze the test output information of the performance test. Therefore, in the performance test of the base station equipment, the test output information is usually analyzed manually.

[0084] For example, in the related art, the specific implementation of the throughput performance test of the base station equipment may include: considering a small number of parameters related to the throughput performance test (such as 6 parameters), first arranging and combining the parameter values of all possible configurations of the 6 parameters to obtain multiple groups of parameter configurations, and the base station equipment can completely traverse each group of parameter configurations in a preset order, and use a set of parameter configurations to perform throughput performance testing in each test (this testing method can also be called a traversal test). In this way, the throughput performance of the base station equipment can be automatically tested, and the test results of multiple performance tests can be obtained. The test results can then be analyzed manually to determine the optimal test results and corresponding parameter configurations.

[0085] However, the solutions in the related art are only applicable to test scenarios with a small number of parameters (which can also be understood as the number of parameters that need to be optimized). For test scenarios with a large number of parameters, such as multi-user high-capacity test scenarios, the number of parameters involved in the performance test may be as many as dozens or even hundreds. At this time, if the performance test is performed by traversal testing, on the one hand, due to the large number of parameters, hundreds or even thousands of groups of parameter configurations may be formed through permutations and combinations. Traversing each group of parameter configurations for performance testing may cause the wireless network (which can also be understood as the network entity) to be overloaded, the test time is long, and the test efficiency is low; on the other hand, the traversal test may output a large amount of test output information, especially when the parameters to be optimized in the performance test are not single (which can also be understood as there are multiple parameters to be optimized). For example, in a multi-user high-capacity test scenario, while paying attention to multiple parameters to be optimized such as the number of online users, access success rate, cell throughput, etc., the traversal test may output thousands of test output information. If all the test output information is analyzed manually, the workload is large, which may result in low analysis efficiency.

[0086] Based on this, in various embodiments of the present application, the first platform analyzes the test results contained in the test output information, generates analysis results, and sends the analysis results to the second platform. The second platform then uses the received analysis results to generate parameter adjustment instructions, and through the parameter adjustment instructions, instructs the wireless network to increase the number of user accesses in the next test or adjust the parameter values corresponding to the next test according to the optimized test sequence. In this way, on the one hand, the first platform can quickly and automatically analyze the test results contained in the test output information to obtain analysis results without the need for manual analysis, and the analysis efficiency is high; on the other hand, the optimized test sequence of the parameters can be adjusted through weights, that is, by setting corresponding weights, the parameters that can significantly improve performance can be optimized first, so that the test results can meet the test indicators after a smaller number of tests, thereby improving the test efficiency.

[0087] The present application embodiment provides a testing method, such as Figure 1 As shown, applied to the first platform, the method includes:

[0088] Step 101: Acquire test output information for this wireless network performance test, where the test output information includes first information, and the first information is used to indicate a test result associated with a test indicator in the test output information;

[0089] Step 102: Determine the test result using the first information;

[0090] Step 103: Generate an analysis result using the test result of this time. The analysis result includes second information or third information. The second information includes relevant information of the parameter to be optimized. The third information indicates that the parameter corresponding to this test does not need to be optimized.

[0091] Step 104: Send the analysis result to the second platform, where the analysis result is used by the second platform to generate parameter adjustment instructions for the next test on the performance of the wireless network.

[0092] Here, the first platform can be specifically called a data analysis platform, which is installed on an electronic device. The electronic device can be specifically a general server, or a computer that meets the storage requirements and processing speed requirements. The embodiment of this application does not limit the name of the first platform, as long as its function is realized.

[0093] The wireless network may also be referred to as a network under test or a test network, and may specifically be an end-to-end network, which may include a core network, a base station (also referred to as a base station under test or gNB), a radio remote unit (RRU), a user equipment (also understood as a test terminal, which can be expressed in English as User Equipment, abbreviated as UE), etc. The user equipment may specifically include a mobile phone, a positioning tag, a customer premises equipment (CPE), etc. The wireless network performance test may specifically include a cell throughput test or a drop rate test, etc.

[0094] In actual application, in step 101, the first platform can obtain the test output information from the wireless network performing the performance test. The test output information may include the output information obtained by the performance test of the wireless network. The embodiment of the present application does not limit the name of the test output information. The test output information may specifically include: parameter configuration associated with the test indicator and test results associated with the test indicator (i.e., the first information). For example, when the performance being tested is cell throughput, the test results associated with the test indicator may include cell uplink throughput, cell downlink throughput, etc.

[0095] After the first platform obtains the first information, in step 102, the first platform can determine whether the first information meets a preset threshold. Specifically, the first information can be compared with the preset threshold to obtain a comparison result, and then the first information can be determined based on the comparison result to determine whether the first information meets the preset threshold. When the first information meets the preset threshold, the test result of this test indicates that the test meets the test indicator. When the first information does not meet the preset threshold, the test result of this test indicates that the test does not meet the test indicator. The preset threshold can also be called the threshold requirement of the test indicator or the test indicator threshold. The preset threshold can be set according to actual needs, and the embodiments of the present application do not limit this.

[0096] Based on this, in step 103, the first platform may use the test results of this time to perform analysis, and generate corresponding analysis results based on whether the test results of this time meet the test indicators.

[0097] Specifically, in one embodiment, the specific implementation of generating the analysis result by using the current test result may include:

[0098] When the test result does not meet the threshold requirement of the test indicator, generating the second information;

[0099] or,

[0100] When the test result of this time meets the threshold requirement of the test indicator, the third information is generated.

[0101] Among them, the threshold requirements of the test indicators can be set according to actual needs, and the embodiments of the present application do not limit this.

[0102] In the related art, when conducting a wireless network performance test, the performance of a small number of users (such as 10% of the users to be tested) accessing the wireless network is usually tested first to obtain the test results. When the test results do not meet the test indicators, the test-related parameters can be adjusted to repeat the test until the test results meet the test indicators; when the test results meet the test indicators, the number of users accessing the wireless network can be increased according to the preset value, and the test can be performed again until the number of accessed users reaches the preset value (which can also be understood as a preset upper limit, specifically 1200 users). In this way, when the test-related parameters need to be adjusted multiple times at the beginning of the test, the relevant data of a small number of accessed users can be processed. When the test results corresponding to the adjusted parameters meet the test indicators, the number of accessed users can be increased and the test-related parameters can be fine-tuned. This can effectively reduce the time required for the test and improve the test efficiency. Among them, the preset value can also be called the user number step, which can be set according to the actual test needs.

[0103] That is to say, when the test results of this time meet the threshold requirements of the test indicators, if the number of access users has not reached the preset value, the first platform can increase the number of access users and conduct the next test; wherein, before conducting the next test, there is no need to adjust the test parameters (which can also be understood as optimization), that is, the parameters of this test (which can also be understood as existing parameters) are used; if the number of access users has reached the preset value, the first platform can consider that the wireless network has been optimized. At this time, the parameters corresponding to this test can be used as the adjusted parameters, and the performance test of the wireless network is ended.

[0104] When the test result does not meet the threshold requirement of the test indicator, the first platform can use the test indicator and the preset association relationship to determine the parameters associated with the test indicator, and then determine the parameter configuration corresponding to the associated parameter in the test output information, and use the parameter configuration to generate the corresponding second information. The preset association relationship can be set according to actual needs, and can be specifically presented in the form of a mapping table. Each item in the mapping table contains the second information and one or more parameter configurations, and the second information is associated with the one or more parameter configurations. The embodiment of the present application does not limit the specific implementation of the preset association relationship.

[0105] Based on this, in one embodiment, the test output information further includes fourth information, where the fourth information represents a parameter configuration associated with the test indicator in the test output information; and generating the second information includes:

[0106] The second information is generated using the fourth information.

[0107] Wherein, in actual application, the fourth information can also be called a test log (log), which contains one or more (can also be understood as at least one) key fields associated with the test indicators, each key field can specifically include a phrase or a statement, and each key field can correspond to one or more parameter configurations. In step 103, the first platform can analyze the one or more key fields associated with the test indicators to generate second information, and the second information can specifically include one or more optimization judgment items, each optimization judgment item can specifically include relevant information of one or more parameters in the parameters to be optimized, and the relevant information of the parameters can also be understood as which parameters can be adjusted during the next test so that the test results of the next test can meet the threshold requirements of the test indicators as much as possible; the optimization judgment item can also include an optimization strategy for the corresponding parameter (i.e., how to adjust the parameters corresponding to the judgment item). That is, multiple optimization judgment items can be pre-set (can also be understood as defined) on the first platform, and the first platform can use the fourth information to determine one or more optimization judgment items among the multiple optimization judgment items, and use the determined one or more optimization judgment items as the second information.

[0108] For example, assuming that the wireless network performance test is to test the throughput of the wireless network, and the test indicators include the cell throughput, the key fields contained in the fourth information may specifically include: "Downlink Block Error Rate (BLER) <5%" and "The current downlink modulation and coding strategy (MCS) parameter value is already equal to the maximum MCS parameter value". At this time, the first platform can use the key fields to determine that the optimization decision item corresponding to the key fields is "MCS is limited, adjust the MCS parameter value to increase" (that is, the above-mentioned second information), and use the optimization decision item as the analysis result, so that the second platform can adjust the maximum MCS parameter value in the next test according to the received analysis result, and the adjustment strategy is to increase the maximum MSC parameter value. Among them, the first platform can use the correspondence between preset key fields and optimization judgment items and use the corresponding optimization judgment items as analysis results, or it can pre-define (also understood as constructing) an optimization judgment item set, each element in the set corresponds to an optimization judgment item, and use the key fields to match each element in the optimization judgment item set, and use the matched optimization judgment items as analysis results. The embodiment of this application does not limit the specific implementation method of determining the optimization judgment items corresponding to the key fields.

[0109] The first platform executes steps 101 to 103 to quickly and automatically analyze the test results contained in the test output information and obtain corresponding analysis results without the need for manual analysis, thereby improving analysis efficiency.

[0110] In actual application, in step 104, the first platform may send the analysis result to the second platform, so that the second platform can use the received analysis result to generate a parameter adjustment instruction (also referred to as a parameter configuration instruction) for the next test of the performance of the wireless network. In actual application, the first platform may send the analysis result to the second platform via dedicated signaling. The embodiment of the present application does not limit the specific implementation of the first platform sending the analysis result to the second platform.

[0111] Accordingly, the present application also provides a testing method, such as Figure 2 As shown, applied to the second platform, the method includes:

[0112] Step 201: Receive an analysis result of the wireless network performance test sent by the first platform, where the analysis result includes second information or third information, where the second information includes information related to parameters to be optimized, and the third information indicates that parameters corresponding to the test do not need to be optimized;

[0113] Step 202: Execute corresponding operations.

[0114] Specifically, in step 202, the second platform performs one of the following:

[0115] When the analysis result includes the second information, one or more parameter clusters (which may also be understood as at least one parameter cluster) corresponding to the parameter to be optimized are determined using the second information and the fourth information, and an optimization test order of each parameter included in the one or more parameter clusters is determined based on the weights of the N parameters included in the one or more parameter clusters. For each parameter, the parameter value is adjusted based on the determined order, and a parameter adjustment instruction is generated using the adjusted parameter value of each parameter. The parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test. The fourth information represents the correspondence between the second information and the one or more parameter clusters. The parameter cluster corresponding to the fourth information includes one or more parameter clusters, and the parameters in each parameter cluster are completely different. N is an integer greater than or equal to 1;

[0116] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0117] Here, the second platform can be specifically referred to as a test platform, which is mounted on an electronic device. The electronic device can be specifically a general server, or a computer that meets storage requirements and processing speed requirements. The embodiment of the present application does not limit the name of the second platform, as long as its function is realized.

[0118] In actual application, in step 201, the first platform analyzes the test results included in the test output information, and after obtaining the corresponding analysis results, the analysis results can be sent to the second platform.

[0119] When the analysis result includes the second information, and the test result of this test does not meet the test indicator, the second platform can use the second information and the fourth information to adjust the parameter value of the parameter to be optimized, and use the adjusted parameter value to generate a corresponding parameter adjustment instruction, so that the performance of the wireless network can be tested based on the adjusted parameter value when the wireless network is tested next time.

[0120] In actual applications, in test scenarios with a large number of parameters, to improve test efficiency and ensure that test results meet test criteria after fewer tests, the second platform can determine the optimization test order for the parameters to be optimized based on preset weights in step 202. The test criteria may be related to multiple parameters, that is, the parameter to be optimized may correspond to multiple parameters, and adjusting each of the multiple parameters can affect the test results associated with the test criteria.

[0121] Based on this, the parameters to be optimized can correspond to one or more parameter clusters (which can also be understood as parameter classes), and each parameter cluster contains one or more parameters. In this way, by pre-setting (which can also be understood as dividing or defining) parameter clusters on the second platform, and setting the correspondence between the second information and one or more parameter clusters (that is, the fourth information), the second platform can use the received second information and the correspondence to determine which parameters can be adjusted in the next test to optimize the performance of the wireless network, so that the test results of the next test can meet the test indicators as much as possible. Among them, the pre-set parameter cluster can also be understood as classifying the set of all test parameters to obtain multiple parameter clusters.

[0122] Exemplarily, a specific implementation of the pre-set parameter cluster may include: first, a parameter set Ω may be defined, where Ω includes M parameters associated with wireless network performance testing, where M is an integer greater than or equal to 1.

[0123] Then, a clustering rule is preset (which can also be understood as a clustering standard). The preset clustering rule can be related to at least one of parameter attributes, parameter characteristics, parameter features, correlation between parameters, etc. The N parameters can be classified using the clustering rule to obtain (which can also be understood as setting) a first-level parameter cluster = {parameter cluster A, parameter cluster B, ..., parameter cluster N}, where N is an integer greater than or equal to 1 and less than or equal to M. Each first-level parameter cluster contains one or more parameters, and the parameters in each first-level parameter cluster are completely different, and each parameter in Ω belongs to and only belongs to one first-level parameter cluster (which can also be understood as parameter cluster A + parameter cluster B + ... parameter cluster N = parameter set Ω).

[0124] After obtaining the first-level parameter cluster, one or more parameter clusters in the first-level parameter cluster can be clustered to set a multi-level parameter cluster. Specifically, when there is a parameter cluster containing more than θ (which can also be understood as the number of parameters in the parameter cluster is large, where θ is an integer greater than or equal to 1), or when the parameters contained in the parameter cluster can still be clustered according to the preset clustering rules (which can be called clear clustering rules, such as parameter functions, etc.), the parameters contained in the parameter cluster are further clustered. Assuming that parameter cluster A is further clustered, parameter cluster A contains Q parameters, the second-level parameter cluster corresponding to parameter cluster A can be set = {parameter cluster A1, parameter cluster A2, ..., parameter cluster Am}, where m is an integer greater than or equal to 1 and less than or equal to Q. Each second-level parameter cluster corresponding to parameter cluster A contains one or more parameters, the parameters in each second-level parameter cluster are completely different, and each parameter in parameter cluster A belongs to and only belongs to one second-level parameter cluster (which can also be understood as parameter cluster A1 + parameter cluster A2 + ... parameter cluster Am = parameter cluster A).

[0125] In a multi-user test scenario, assume that the parameter set Ω = {maximum MCS, maximum number of physical resource blocks (PRBs) allocated to each user in downlink, maximum number of layers in downlink, whether 256-quadrature amplitude modulation (QAM) is used in downlink, maximum number of PRBs allocated to each user in uplink, maximum number of layers in uplink, whether 256QAM is used in uplink, maximum number of scheduled users per transmission time interval (TTI) for uplink and downlink, media access control quality of service (MAC QoS) scheduling policy, scheduling request (SR) period, number of occupied symbols of physical downlink control channel (PDCCH), PDCCH aggregation level, maximum number of active users, power control switch, maximum transmit power, radio link control (RLC) mode, timer, sequence number (SN)}. Number) length, encryption and decryption}, the parameter set Ω can be divided according to the air interface protocol layer, and the first-level parameter cluster is set:

[0126] Parameter cluster A = {maximum MCS, maximum number of PRBs allocated to each user in downlink, maximum number of layers in downlink, whether 256QAM is used in downlink, maximum number of PRBs allocated to each user in uplink, maximum number of layers in uplink, whether 256QAM is used in uplink, SR period, number of symbols occupied by PDCCH, PDCCH aggregation level, maximum number of scheduled users per TTI in uplink and downlink, maximum number of active users, MAC QoS scheduling policy, power control switch, maximum transmit power}; parameter cluster B = {RLC mode, timer}; parameter cluster C = {SN length, encryption and decryption}. In this case, the parameter attribute of each parameter contained in parameter cluster A is a MAC layer parameter, the parameter attribute of each parameter contained in parameter cluster B is an RLC layer parameter, and the parameter attribute of each parameter contained in parameter cluster C is a PDCP layer parameter.

[0127] Parameter cluster A contains a large number of parameters, and there are differences and correlations between the parameters. We can continue clustering using clustering rules (which can also be understood as still having clear clustering rules) to set the second-level parameter cluster:

[0128] Parameter cluster A1 = {maximum number of PRBs allocated to each user, maximum number of layers, whether to use 256QAM, SR period, number of symbols occupied by PDCCH, PDCCH aggregation level}; parameter cluster A2 = {maximum MCS, maximum number of scheduled users per TTI for uplink and downlink, maximum number of activated users, MAC QoS scheduling policy}; parameter cluster A3 = {power control switch, maximum transmit power}. At this time, the parameter attribute of each parameter contained in parameter cluster A1 is a channel parameter, the parameter attribute of each parameter contained in parameter cluster A2 is a scheduling parameter, and the parameter attribute of each parameter contained in parameter cluster A3 is a function control (also referred to as power control) parameter.

[0129] The parameter cluster A1 can be further clustered to set the third-level parameter cluster:

[0130] Parameter cluster A11 = {maximum number of PRBs allocated to each user in downlink, maximum number of layers in downlink, whether 256QAM is used in downlink}; parameter cluster A12 = {maximum number of PRBs allocated to each user in uplink, maximum number of layers in uplink, whether 256QAM is used in uplink}; parameter cluster A13 = {SR period}; parameter cluster A14 = {number of symbols occupied by PDCCH, PDCCH aggregation level}. In this case, the parameter attribute of each parameter contained in parameter cluster A11 is a Physical Downlink Shared Channel (PDSCH) channel parameter, the parameter attribute of each parameter contained in parameter cluster A12 is a Physical Uplink Shared Channel (PUCCH) channel parameter, the parameter attribute of each parameter contained in parameter cluster A13 is a PDCCH channel parameter, and the parameter attribute of each parameter contained in parameter cluster A14 is a Physical Uplink Control Channel (PUCCH) channel parameter.

[0131] Through the above clustering step, the parameter set Ω can be defined as multiple parameter clusters, which can be specifically expressed as Ω = {A, B, C} = {A1, A2, A3, B, C} = {A11, A12, A13, A14, A2, A3, B, C}. Furthermore, a correspondence between each second information and one or more parameter clusters (which can also be understood as a correspondence rule between an optimization decision item and a parameter cluster) can be defined, and the correspondence can be used as the fourth information. For example, when the second information includes "MCS is limited, adjust the MCS parameter value to increase", the corresponding parameter cluster can be set to A2, which can specifically correspond to the "maximum MCS" parameter; when the second information includes "adjust the maximum number of PRBs allocated to each user to increase the parameter value", the corresponding parameter clusters can be set to A11 and A12, which can specifically correspond to the "maximum number of PRBs allocated to each user in the uplink" and "maximum number of PRBs allocated to each user in the downlink" parameters.

[0132] In actual application, the weights of the parameters can be set in advance according to actual needs, such as test indicators, test environment, etc. In this way, after the second platform uses the second information and the fourth information to determine one or more parameter clusters that need to be adjusted, the weights can be used to determine the optimized test order of each parameter (which can also be understood as the adjustment priority order of parameters during subsequent tests), and adjust the parameter value of each parameter based on the determined order, and then use the adjusted parameter value to generate parameter adjustment instructions.

[0133] The weights may be manually set before the first (also understood as initial) test, and the set initial values may be used as the original model.

[0134] Exemplarily, assume that the second platform determines that the parameter cluster corresponding to the parameter to be optimized contains three parameters, namely parameter 1, parameter 2, and parameter 3, and the weight values corresponding to parameter 1, parameter 2, and parameter 3 are a, b, and c, respectively, wherein 0<a<1, 0<b<1, 0<c<1, and a+b+c=1. Before the first test, the initial values of a, b, and c can be set by the tester based on experience, or randomly assigned using the second platform, and the sum of the initial values of a, b, and c is 1. Assume that in this test, a>b>c, that is, the weight value corresponding to parameter 1 is the largest. In this way, in the next test, the value of parameter 1 can be adjusted first for testing.

[0135] In actual application, the weights can be adjusted (also understood as correction or optimization) during each test, so that in the optimized test order of the parameters determined by the weights, the parameters with the earlier order can have a greater impact on the test results associated with the test indicators in the next test after adjustment, so that the test results of the next test are more likely to meet the test indicators, thereby reducing the number of tests and improving test efficiency.

[0136] Based on this, in one embodiment, the method may further include:

[0137] During the testing process, the weight of each parameter is adjusted.

[0138] Specifically, the weights of the parameters can be adjusted by reinforcement learning (which can also be understood as using a reinforcement learning algorithm). In other words, the impact of each parameter on the test results associated with the test indicator (which can also be understood as the impact on the test result indicator) can be determined, and the weight of each parameter can be adjusted using the impact.

[0139] Here, in actual application, the specific implementation process of using the reinforcement learning algorithm to learn the weights of parameters may include: adjusting the parameter values of each parameter respectively (specifically, it may include increasing the parameter value corresponding to the parameter by a fixed amount of change (specifically, it may include the minimum adjustment unit corresponding to the parameter)), determining the test results associated with the test indicators before and after the adjustment, and then determining the influence factor of the parameter (which can also be understood as the influence or degree of influence) based on the test results associated with the test indicators before the adjustment and the test results associated with the test indicators after the adjustment. When adjusting the weight of the parameter, the size of the weight of the parameter can be adjusted to be positively correlated with the size of the influence factor. In this way, the greater the influence factor, the greater the weight of the parameter. Since the optimization test order of the parameter with a larger weight is higher, when the parameter value is adjusted according to the optimization test order and the next test is performed, it can affect the test results associated with the test indicators to the greatest extent possible, so that the test results meet the test indicators as much as possible, thereby reducing the number of tests and improving the test efficiency.

[0140] Based on this, in one embodiment, adjusting the weight of the parameter includes:

[0141] Determine the test results of the correlation between the test indicators before and after the parameter adjustment;

[0142] Determine the first factor using the test results associated with the determined test indicators;

[0143] The weight of the parameter is adjusted using the first factor.

[0144] Here, the first factor may be specifically referred to as an influence factor or a reward factor. The embodiment of the present application does not limit the name of the first factor.

[0145] For example, based on the above example, assuming that the test indicator is cell throughput, when adjusting the weights of parameter 1, parameter 2, and parameter 3 contained in the parameter cluster, the parameter value of each parameter can be adjusted separately to obtain the cell throughput value before adjustment and the cell throughput value after adjustment corresponding to each parameter. The reward factor corresponding to each parameter is calculated using the reward function and the cell throughput values before and after adjustment. The reward factor corresponding to parameter 1 is R1, the reward factor corresponding to parameter 2 is R2, and the reward factor corresponding to parameter 3 is R3, wherein the reward factor corresponds to the parameter one-to-one. When the test indicator is cell throughput, the larger the test result corresponding to the cell throughput, the better. At this time, the reward function can be specifically expressed as formula (1):

[0146] R=(T t -T t-1 ) / T t-1 (1)

[0147] Among them, R represents the reward factor, Tt represents the adjusted cell throughput value, T t-1 represents the cell throughput value before adjustment.

[0148] Assume that after parameter 1 is adjusted, the cell throughput increases by 3% compared to before adjustment, then the reward factor R1 corresponding to parameter 1 = 3%; after parameter 2 is adjusted, the cell throughput increases by 3% compared to before adjustment, then the reward factor R2 corresponding to parameter 2 = 5%; after parameter 3 is adjusted, the cell throughput increases by 3% compared to before adjustment, then the reward factor R3 corresponding to parameter 3 = 2%; since R3 < R1 < R2, the weights corresponding to parameter 1, parameter 2, and parameter 3 can be adjusted accordingly so that the weights satisfy c < a < b and a + b + c = 1. In this way, the weight corresponding to parameter 2 is the largest and the optimization test order is the most forward. When the parameter value of parameter 2 is adjusted and the next test is performed, the cell throughput can be increased to the greatest extent, so that the cell throughput may meet the threshold of the test index, thereby reducing the number of tests and achieving an improvement in test efficiency.

[0149] It should be noted that when the larger the test result corresponding to the test index is, the better, for example, when the test index is the cell throughput, the reward factor can be calculated using formula (1); when the smaller the test result corresponding to the test index is, the better, for example, when the test index is the dropout rate, the reward factor can be calculated using formula (2):

[0150] R = -(T t - T t-1 ) / T t-1 (2)

[0151] where R represents the reward factor, T t represents the adjusted cell throughput value, T t-1 represents the cell throughput value before adjustment.

[0152] In actual application, the weights of the parameters can be set for each parameter cluster based on the test index. At this time, if the second platform determines a parameter cluster using the second information and the fourth information, the optimization test order of each parameter in the one parameter cluster can be directly determined using the weights corresponding to each parameter in the one parameter cluster.

[0153] Specifically, in one embodiment, determining the optimization test order of each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters may specifically include:

[0154] Sort according to the weights of each parameter from high to low to obtain a sorting result;

[0155] Use the sorting result as the optimization test order of each parameter included in the one or more parameter clusters.

[0156] If the second platform uses the second information and the fourth information to determine multiple parameter clusters, it can first determine the parameter cluster weights of different parameter clusters (which can also be understood as the weights of the parameter clusters or the weight values of the parameter clusters), and then, according to the sorting order of the parameter cluster weights, for each parameter cluster in turn, use the weight corresponding to each parameter in the parameter cluster to determine the optimization test order of each parameter.

[0157] Specifically, in one embodiment, determining the optimization test order of each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters may include:

[0158] For one or more parameter clusters, sort the parameter clusters from high to low according to the weight of each parameter cluster to obtain a first sorting result;

[0159] Based on the first sorting result, for each parameter cluster, sort the parameters in the parameter cluster from high to low according to the weight of each parameter in the parameter cluster to obtain a second sorting result;

[0160] The second sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

[0161] Here, it should be noted that the multiple parameter clusters may include parameter clusters of different levels. Since there is no weight relationship between parameter clusters of different levels or between parameters and parameter clusters, each level of weight can be preset accordingly for each level of parameter cluster. In this way, the second device can use the preset weight of each level to sort the parameter clusters of each level, obtain the first sorting result, and then determine the optimized test order of the parameters.

[0162] For example, Figure 3As shown, it is assumed that the first-level parameter cluster includes parameter cluster A, parameter cluster B, and parameter cluster C, wherein parameter cluster A includes second-level parameter clusters parameter cluster A1, parameter cluster A2, and parameter cluster A3, and parameter cluster A1 includes third-level parameter clusters parameter cluster A11, parameter cluster A12, parameter cluster A13, and parameter cluster A14. At this time, there is a weight relationship between parameter clusters A, parameter cluster B, and parameter cluster C, and a weight relationship between parameter clusters A1, parameter cluster A2, and parameter cluster A3. There is no weight relationship between parameter cluster A1 and parameter clusters B and parameter cluster C, and there is no weight relationship between parameter cluster A11 and parameter clusters A2 and parameter cluster A3. Optimization decision item 1 corresponds to parameter clusters A11, parameter cluster A12, parameter cluster A13, and parameter cluster A14, optimization decision item 2 corresponds to parameter clusters A2, parameter cluster A3, and parameter cluster B, and optimization decision item 3 corresponds to parameter cluster C. At this time, for optimization decision item 1, the weights corresponding to parameter clusters A11, A12, A13, and A14 can be used as first-level weights. The second platform can use the first-level weights to sort parameter clusters A11, A12, A13, and A14 to obtain a first sorting result, and then use the weight of each parameter in each parameter cluster to determine the second sorting result, thereby determining the optimization test order of the parameters. For optimization decision item 2, the weights corresponding to parameter clusters A and B can be used as first-level weights, and parameter clusters A2 and B can be sorted. The weight corresponding to parameter cluster A3 is used as the second-level weight. The second platform can first use the first-level weight to sort parameter cluster A and parameter cluster B, and then use the second-level weight to sort parameter cluster A2 and parameter cluster A3. The sorting results of the two sorts are used to determine the first sorting result, and then the weight of each parameter in each parameter cluster is used to determine the second sorting result, and then the optimization test order of the parameters is determined. For optimization judgment item 3, since optimization judgment item 3 only corresponds to parameter cluster C, the weight of each parameter in parameter cluster C can be directly used to determine the optimization test order of the parameters.

[0163] In actual application, the second information may also include an optimization strategy (also understood as an adjustment strategy) for the parameter to be optimized, such as "up", "down", "increase", "decrease", etc. The second platform can use the optimization strategy to determine how to adjust the parameter value of the parameter (also understood as determining the adjustment direction of the parameter value) and obtain the adjusted parameter value, so that the adjusted parameter value can be used to generate the corresponding parameter adjustment instruction.

[0164] Based on this, in one embodiment, the second information includes an optimization strategy for the parameter to be optimized; when generating the parameter adjustment instruction, the method may include:

[0165] The parameter adjustment instruction is generated using the optimization strategy.

[0166] Here, it should be noted that if the second information does not contain the optimization strategy for the parameter to be optimized, the second platform can make random adjustments based on the parameter value of the parameter to be optimized in this test (for example, increase it by one minimum unit or decrease it by one minimum unit) and optimize the parameter to be optimized through multiple tests.

[0167] In actual application, the second information can also directly indicate the adjustment value corresponding to the parameter to be optimized, and a corresponding parameter configuration identifier (which can also be understood as a parameter configuration ID) can be preset for each parameter adjustment value. The second platform can use the parameter configuration identifier to directly determine the adjustment value of the parameter (which can also be understood as the parameter value after the parameter adjustment), and then use the adjustment value of the parameter to generate a parameter adjustment instruction.

[0168] Specifically, in one embodiment, the optimization strategy includes a parameter configuration identifier of a parameter to be optimized; the optimization strategy generates a parameter adjustment instruction, including:

[0169] Determining an adjustment value of the parameter using the parameter configuration identifier of the parameter to be optimized;

[0170] The parameter adjustment instruction is generated according to the determined parameter adjustment value.

[0171] If the analysis result includes the third information and the test result of the current test meets the test criteria, the second platform may determine the number of access users for the next test based on the number of access users in the current test, and generate a parameter adjustment instruction based on the number of users in the next test, so that when the wireless network performs the next test, the number of access users corresponding to the parameter adjustment instruction is increased, and the performance of the wireless network is tested based on the parameter value corresponding to the current test. The second platform may determine the number of access users for the next test by increasing the number of access users by a preset value based on the number of access users in the current test. The preset value may also be referred to as a user number step size and may be set according to actual testing needs.

[0172] In actual application, the second platform can send the generated parameter adjustment instruction to the wireless network, specifically a base station in the wireless network. The wireless network can adjust the parameter value or increase the number of user access based on the parameter adjustment instruction and conduct the next test.

[0173] The present application also provides a testing method, such as Figure 4 As shown, the method includes:

[0174] Step 401: The first platform obtains test output information for this wireless network performance test, where the test output information includes first information, and the first information is used to indicate a test result associated with a test indicator in the test output information;

[0175] Step 402: The first platform uses the first information to determine the test result.

[0176] Step 403: The first platform generates an analysis result using the test result. The analysis result includes second information or third information. The second information includes information related to the parameter to be optimized. The third information indicates that the parameter corresponding to the test does not need to be optimized.

[0177] Step 404: The first platform sends the analysis result to the second platform, where the analysis result is used by the second platform to generate a parameter adjustment instruction for the next test of the performance of the wireless network.

[0178] Step 405: After receiving the analysis result of the wireless network performance test sent by the first platform, the second platform performs corresponding operations.

[0179] Specifically, in step 405, the second platform performs one of the following:

[0180] When the analysis result includes the second information, one or more parameter clusters (which may also be understood as at least one parameter cluster) corresponding to the parameter to be optimized are determined using the second information and the fourth information, and an optimization test order of each parameter included in the one or more parameter clusters is determined based on the weights of the N parameters included in the one or more parameter clusters. For each parameter, the parameter value is adjusted based on the determined order, and a parameter adjustment instruction is generated using the adjusted parameter value of each parameter. The parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test. The fourth information represents the correspondence between the second information and the one or more parameter clusters. The parameter cluster corresponding to the fourth information includes one or more parameter clusters, and the parameters in each parameter cluster are completely different. N is an integer greater than or equal to 1;

[0181] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0182] Here, it should be noted that the specific processing procedures of the first platform and the second platform have been described in detail above and will not be repeated here.

[0183] The test method provided in the embodiment of the present application is as follows: a first platform obtains test output information for this wireless network performance test, wherein the test output information includes first information, and the first information is used to indicate the test result associated with the test indicator in the test output information; the first information is used to determine the test result of this time; the test result of this time is used to generate an analysis result, and the analysis result includes second information or third information, wherein the second information includes relevant information of the parameters to be optimized, and the third information indicates that the parameters corresponding to this test do not need to be optimized; and the analysis result is sent to a second platform, and the analysis result is used for the second platform to generate parameter adjustment instructions for the next test of the performance of the wireless network. The second platform receives an analysis result for the wireless network performance test sent by the first platform, where the analysis result includes second information or third information, the second information includes relevant information about the parameter to be optimized, and the third information indicates that the parameter corresponding to the test does not need to be optimized; and performs one of the following: if the analysis result includes the second information, using the second information and fourth information to determine one or more parameter clusters corresponding to the parameter to be optimized, and determining an optimization test order for each parameter included in the one or more parameter clusters based on weights of N parameters included in the one or more parameter clusters; for each parameter, adjusting the parameter value based on the determined order; and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, where the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test; the fourth information indicates a correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information includes one or more parameter clusters, the parameters in each parameter cluster are completely different, and N is an integer greater than or equal to 1; and if the analysis result includes the third information, generating a parameter adjustment instruction based on the number of users accessing the test, where the parameter adjustment instruction is used to instruct the wireless network to increase the number of users accessing the test when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to the test. In the solution provided by the embodiment of the present application, the first platform analyzes the test results contained in the test output information, generates analysis results and sends the analysis results to the second platform. The second platform then uses the received analysis results to generate parameter adjustment instructions, and through the parameter adjustment instructions, instructs the wireless network to increase the number of user access in the next test or adjust the parameter values corresponding to the next test according to the optimized test sequence.In this way, on the one hand, the test results contained in the test output information can be quickly and automatically analyzed through the first platform to obtain analysis results without manual analysis, and the analysis efficiency is high; on the other hand, the optimization test order of parameters can be adjusted through weights, that is, by setting corresponding weights, the parameters that can significantly improve performance can be optimized first, so that the test results can meet the test indicators after a smaller number of tests, thereby improving the test efficiency.

[0184] The present application is described in further detail below with reference to application examples.

[0185] like Figure 5 As shown, the test system of this application example can be called an automated test system for base station equipment, and can specifically include: a data analysis platform (i.e., the above-mentioned first platform), a test platform (i.e., the above-mentioned second platform), and a wireless network (also referred to as a network under test), wherein the wireless network includes a core network, a base station under test, an RRU, and a test terminal. After the base station under test in the wireless network performs this test, the obtained test output information is sent to the data analysis platform; the data analysis platform analyzes the received test output information to obtain an analysis result (also referred to as a parameter optimization analysis result), and sends the analysis result to the test platform; the test platform generates a parameter adjustment instruction and a test instruction using the received analysis result, and sends the parameter adjustment instruction to the base station in the wireless network. The base station can adjust the parameter value using the received parameter adjustment instruction; the test instruction is sent to the test terminal in the wireless network, and the test terminal can initiate random access or initiate a service based on the instruction of the test instruction. In other words, the wireless network can perform subsequent tests according to the parameter adjustment instruction and the test instruction.

[0186] Combine Figure 5 , the process of the automated testing method provided by this application embodiment is as follows: Figure 6 As shown, the following steps are included:

[0187] Step 601: The data analysis platform (i.e., the first platform) receives test output information input from this round of testing (also referred to as optimization testing);

[0188] In actual application, the base station under test (ie, the base station in the above wireless network) may send the test output information of the current round of testing to the data analysis platform.

[0189] Step 602: The data analysis platform determines whether the test result associated with the test indicator in the test output information (i.e., the first information) meets the test indicator threshold (i.e., the threshold requirement of the test indicator);

[0190] Step 603: The data analysis platform generates analysis results and sends the analysis results to the test platform;

[0191] In actual application, when the test result meets the test indicator threshold, the analysis result is used to indicate that no optimization is required; when the test result does not meet the test indicator threshold, the analysis result includes an optimization decision item corresponding to the test indicator.

[0192] Step 604: The test platform receives the analysis results and generates parameter adjustment instructions and test instructions;

[0193] The parameter adjustment instruction is used to instruct the tested base station to adjust the parameter value, and the test instruction is used to instruct the test terminal to initiate random access or initiate a service.

[0194] In actual application, when the analysis results indicate that no optimization is required, the test platform can determine the number of user accesses for the next round of testing based on the user number step size and generate corresponding parameter adjustment instructions. At this time, the parameter adjustment instructions instruct the wireless network to increase the corresponding number of user accesses in the next round of testing; when the analysis results include optimization judgment items, the test platform can determine the corresponding parameter cluster based on the optimization judgment items, sort the parameters in the parameter cluster using preset weights, determine the optimization test order of the parameters in the parameter cluster according to the sorting results, determine the parameter adjustment values according to the determined order, and generate corresponding parameter adjustment instructions using the parameter adjustment values. At this time, the parameter adjustment instructions instruct the wireless network to adjust the parameter values of the corresponding parameters in the next round of testing.

[0195] During each test, parameter weights can be adjusted through reinforcement learning, enabling adjustments to be made before each test to more effectively improve base station performance. Specifically, the test results before and after each parameter adjustment can be determined, and the reward factor corresponding to the parameter can be determined using the test results. This reward factor can then be used to adjust the parameter weight.

[0196] It should be noted that the optimization decision item may correspond to one or more parameters, and each parameter may be adjusted to one or more parameter values. Accordingly, the test platform may determine a parameter adjustment instruction based on the optimization decision item, and the parameter adjustment instruction corresponds to multiple parameter configuration identifiers. In this way, after receiving the parameter adjustment instruction, the wireless network may perform a test for each parameter configuration identifier in the next round of testing, obtain multiple test results, and use the multiple test results as test output information. In other words, the test output information includes the test result corresponding to each parameter configuration identifier in the multiple parameter configuration identifiers.

[0197] For example, assuming that the performance being tested is throughput performance (i.e., the test indicator is throughput), and the adjusted parameter is the MCS parameter, the test platform uses the optimization judgment item to determine three parameter configuration identifiers A, B, and C, where the adjustment value of the MCS parameter corresponding to A is 18, the adjustment value of the MCS parameter corresponding to A is 19, and the adjustment value of the MCS parameter corresponding to A is 20. At this time, after the wireless network receives the parameter adjustment instruction corresponding to the parameter adjustment value, it can set the parameter value of the MCS parameter to 18, 19, and 20 respectively to perform three performance tests, obtain three test results, and use the three test results to determine the test output information, where each test result includes a test result related to throughput. The wireless network can send the test output information to the data analysis platform; the data analysis platform can use the test results related to throughput in the test output information (i.e., the above-mentioned first information) to determine (can also be understood as screening) the maximum (can also be understood as optimal) throughput, and then determine whether the maximum throughput meets the test indicator threshold, and generate corresponding analysis results, and send the analysis results and the parameter configuration identifier corresponding to the maximum throughput to the test platform; the test platform can use the parameter configuration identifier corresponding to the maximum throughput as the initial parameter for the next round of testing, and then use the initial parameters and analysis results to determine the parameter adjustment instructions for the next round of testing.

[0198] In actual application, in order to reduce test redundancy and improve test efficiency, a maximum number of optimization tests can be preset in the wireless network (which can also be understood as the maximum number of tests in each round of testing). When the number of tests in a round of testing of the wireless network reaches the preset maximum number of optimization tests, the current round of testing will be ended regardless of whether all parameter configuration identifiers have been traversed, and the test results of each test in this round of testing will be sent to the data analysis platform as test output information.

[0199] Step 605: The test platform sends a parameter adjustment instruction to the base station under test, and sends a test instruction to the test terminal.

[0200] Specifically, the test platform can send parameter adjustment instructions to the base station under test in the wireless network, and send the test instructions to the test terminal in the wireless network, so that the base station under test can use the parameter adjustment instructions to increase the number of user access or adjust the parameter value corresponding to the next test according to the optimized test sequence. At the same time, the test terminal can initiate random access or initiate a service based on the instructions of the test instructions. In this way, the wireless network can perform subsequent tests according to the parameter adjustment instructions and the test instructions.

[0201] The automated test method provided by the application example of this application is that, in a multi-user test scenario with a large number of optimization parameters and a large number of test results, the data analysis platform analyzes the test results contained in the test output information, generates and sends corresponding analysis results to the test platform, and the test platform uses the received analysis results to generate parameter adjustment instructions, and then the test platform can send parameter adjustment instructions to the wireless network so that the wireless network can increase the number of user access based on the parameter adjustment instructions or adjust the parameter values corresponding to the next test according to the optimized test sequence, and conduct the next test. In this way, on the one hand, the test results contained in the test output information can be quickly and automatically analyzed by the data analysis platform to obtain corresponding analysis results, without the need for manual analysis, and the analysis efficiency is high; on the other hand, the optimization test sequence of the parameters can be adjusted by weights, that is, by setting corresponding weights, the parameters that can significantly improve performance can be optimized first, so that the test results can meet the test indicators after a smaller number of tests. Compared with the solutions in the related art, the test efficiency is high;

[0202] At the same time, the clustering parameter optimization method based on weight sorting is used to determine the optimized test order of parameters, which can improve test efficiency by reducing the redundancy of massive parameter ergodic testing.

[0203] At the same time, by adjusting parameter weights through reinforcement learning, it is possible to adjust parameters that can more effectively improve base station performance before each test. In this way, each test can effectively improve base station performance (which can also be understood as a gradual increase in base station performance). After multiple tests, the test parameters can be automatically tuned. In other words, through reinforcement learning, it can be learned which parameters to optimize to effectively improve base station performance, so that parameter configurations with better performance can be obtained more quickly.

[0204] In order to implement the method on the first platform side of the embodiment of the present application, the embodiment of the present application also provides a testing device, which is set on the first platform, such as Figure 7 As shown, the device includes:

[0205] An acquiring unit 701 is configured to acquire test output information for this wireless network performance test, where the test output information includes first information indicating a test result associated with a test indicator in the test output information;

[0206] A determining unit 702 is configured to determine a test result using the first information;

[0207] A generating unit 703 is configured to generate an analysis result using the test result of this test, where the analysis result includes second information or third information, where the second information includes information related to the parameter to be optimized, and the third information indicates that the parameter corresponding to this test does not need to be optimized;

[0208] The sending unit 704 is configured to send the analysis result to the second platform, where the analysis result is used by the second platform to generate a parameter adjustment instruction for the next test on the performance of the wireless network.

[0209] In one embodiment, the generating unit 703 is specifically configured to:

[0210] When the test result does not meet the threshold requirement of the test indicator, generating the second information;

[0211] or,

[0212] When the test result of this time meets the threshold requirement of the test indicator, the third information is generated.

[0213] In one embodiment, the test output information further includes fourth information, where the fourth information represents a parameter configuration associated with the test indicator in the test output information; the generating unit 703 is specifically configured to:

[0214] The second information is generated using the fourth information.

[0215] In actual application, the obtaining unit 701 and the sending unit 704 may be implemented by a communication interface in the test device, and the determining unit 702 and the generating unit 703 may be implemented by a processor in the test device.

[0216] In order to implement the method on the second platform side of the embodiment of the present application, the embodiment of the present application also provides a testing device, which is set on the second platform, such as Figure 8 As shown, the device includes:

[0217] A receiving unit 801 is configured to receive an analysis result of the wireless network performance test sent by the first platform, the analysis result including second information or third information, the second information including relevant information of the parameter to be optimized, and the third information indicating that the parameter corresponding to the test does not need to be optimized;

[0218] The execution unit 802 is configured to execute one of the following:

[0219] In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an optimization test order for each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information characterizing the correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1;

[0220] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0221] In one embodiment, the execution unit 802 is specifically configured to:

[0222] Sort by the weight of each parameter from high to low to get the sorting result;

[0223] The sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

[0224] In one embodiment, the execution unit 802 is specifically configured to:

[0225] For one or more parameter clusters, sort the parameter clusters from high to low according to the weight of each parameter cluster to obtain a first sorting result;

[0226] Based on the first sorting result, for each parameter cluster, sort the parameters in the parameter cluster from high to low according to the weight of each parameter in the parameter cluster to obtain a second sorting result;

[0227] The second sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

[0228] In one embodiment, the measuring device further includes:

[0229] The adjustment unit is used to adjust the weight of each parameter during the test.

[0230] In one embodiment, the adjustment unit is specifically configured to:

[0231] Determine the test results of the correlation between the test indicators before and after the parameter adjustment;

[0232] Determine the first factor using the test results associated with the determined test indicators;

[0233] The weight of the parameter is adjusted using the first factor.

[0234] In one embodiment, the second information includes an optimization strategy for the parameter to be optimized; the execution unit 802 is specifically configured to:

[0235] The parameter adjustment instruction is generated using the optimization strategy.

[0236] In one embodiment, the optimization strategy includes a parameter configuration identifier of the parameter to be optimized; the execution unit 802 is specifically configured to:

[0237] Determining an adjustment value of the parameter using the parameter configuration identifier of the parameter to be optimized;

[0238] The parameter adjustment instruction is generated according to the determined parameter adjustment value.

[0239] In actual application, the receiving unit 801 can be implemented by a communication interface in the test device, and the executing unit 802 and the adjusting unit can be implemented by a processor in the test device.

[0240] It should be noted that the test device provided in the above embodiment only uses the division of the above program units as an example when performing testing. In actual applications, the above processing can be assigned to different program units as needed, that is, the internal structure of the device can be divided into different program units to complete all or part of the above-described processing. In addition, the test device provided in the above embodiment and the test method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0241] Based on the hardware implementation of the above program modules, and in order to implement the method of the first platform side of the embodiment of the present application, the embodiment of the present application also provides a first platform, such as Figure 9 As shown, the first platform 900 includes:

[0242] The first communication interface 901 is capable of exchanging information with other devices;

[0243] The first processor 902 is connected to the first communication interface 901 to realize information interaction with other devices, and is used to execute the methods provided by one or more technical solutions on the first platform side when running a computer program; the computer program is stored in the first memory 903.

[0244] Specifically, the first communication interface 901 is configured to obtain test output information for the current wireless network performance test, the test output information including first information indicating a test result associated with a test indicator in the test output information; and send an analysis result to the second platform, the analysis result being used by the second platform to generate a parameter adjustment instruction for the next performance test of the wireless network.

[0245] The first processor 902 is used to use the first information to determine the test results of this time; and use the test results of this time to generate an analysis result, and the analysis result includes second information or third information, the second information includes relevant information of the parameters to be optimized, and the third information indicates that the parameters corresponding to this test do not need to be optimized.

[0246] In one embodiment, the first processor 902 is specifically configured to:

[0247] When the test result does not meet the threshold requirement of the test indicator, generating the second information;

[0248] or,

[0249] When the test result of this time meets the threshold requirement of the test indicator, the third information is generated.

[0250] In one embodiment, the test output information further includes fourth information, where the fourth information represents a parameter configuration associated with the test indicator in the test output information; the first processor 902 is specifically configured to:

[0251] The second information is generated using the fourth information.

[0252] It should be noted that the specific processing process of the first processor 902 and the first communication interface 901 can be understood by referring to the above method.

[0253] Of course, in actual application, the various components in the first platform 900 are coupled together through the bus system 904. It is understood that the bus system 904 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 904 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 9 Various buses are labeled as bus system 904.

[0254] The first memory 903 in the embodiment of the present application is used to store various types of data to support the operation of the first terminal 900. Examples of such data include: any computer program used to operate on the first platform 900.

[0255] The methods disclosed in the above embodiments of the present application can be applied to the first processor 902 or implemented by the first processor 902. The first processor 902 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits or software instructions in the first processor 902. The above-mentioned first processor 902 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The first processor 902 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium located in the first memory 903. The first processor 902 reads the information in the first memory 903 and completes the steps of the above method in combination with its hardware.

[0256] In an exemplary embodiment, the first platform 900 may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to execute the aforementioned method.

[0257] Based on the hardware implementation of the above program modules, and in order to implement the method of the second platform side of the embodiment of the present application, the embodiment of the present application also provides a second platform, such as Figure 10 As shown, the second platform 1000 includes:

[0258] The second communication interface 1001 is capable of exchanging information with other devices;

[0259] The second processor 1002 is connected to the second communication interface 1001 to realize information interaction with other devices, and is used to execute the methods provided by one or more technical solutions on the second platform side when running a computer program; the computer program is stored in the second memory 1003.

[0260] Specifically, the second communication interface 1001 is configured to receive an analysis result of the wireless network performance test sent by the first platform, where the analysis result includes second information or third information, where the second information includes relevant information about the parameter to be optimized, and the third information indicates that the parameter corresponding to the test does not need to be optimized;

[0261] The second processor 1002 is configured to perform one of the following:

[0262] In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an optimization test order for each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information characterizing the correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1;

[0263] When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

[0264] In one embodiment, the second processor 1002 is specifically configured to:

[0265] Sort by the weight of each parameter from high to low to get the sorting result;

[0266] The sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

[0267] In one embodiment, the second processor 1002 is specifically configured to:

[0268] For one or more parameter clusters, sort the parameter clusters from high to low according to the weight of each parameter cluster to obtain a first sorting result;

[0269] Based on the first sorting result, for each parameter cluster, sort the parameters in the parameter cluster from high to low according to the weight of each parameter in the parameter cluster to obtain a second sorting result;

[0270] The second sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

[0271] In one embodiment, the second processor 1002 is further configured to:

[0272] During the testing process, the weight of each parameter is adjusted.

[0273] In one embodiment, the second processor 1002 is specifically configured to:

[0274] Determine the test results of the correlation between the test indicators before and after the parameter adjustment;

[0275] Determine the first factor using the test results associated with the determined test indicators;

[0276] The weight of the parameter is adjusted using the first factor.

[0277] In one embodiment, the second information includes an optimization strategy for the parameter to be optimized; and the second processor 1002 is specifically configured to:

[0278] The parameter adjustment instruction is generated using the optimization strategy.

[0279] In one embodiment, the optimization strategy includes a parameter configuration identifier of a parameter to be optimized; and the second processor 1002 is specifically configured to:

[0280] Determining an adjustment value of the parameter using the parameter configuration identifier of the parameter to be optimized;

[0281] The parameter adjustment instruction is generated according to the determined parameter adjustment value.

[0282] It should be noted that the specific processing process of the second processor 1002 and the second communication interface 1001 can be understood by referring to the above method.

[0283] Of course, in actual application, the various components in the second platform 1000 are coupled together through the bus system 1004. It can be understood that the bus system 1004 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 1004 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 10 Various buses are labeled as bus system 1004.

[0284] The second memory 1003 in the embodiment of the present application is used to store various types of data to support the operation of the second platform 1000. Examples of such data include: any computer program used to operate on the second platform 1000.

[0285] The methods disclosed in the above embodiments of the present application can be applied to or implemented by the second processor 1002. The second processor 1002 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits or software instructions in the second processor 1002. The above second processor 1002 may be a general-purpose processor, a DSP, or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc. The second processor 1002 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium located in the second memory 1003. The second processor 1002 reads the information in the second memory 1003 and, in conjunction with its hardware, completes the steps of the above method.

[0286] In an exemplary embodiment, the second platform 1000 may be implemented by one or more ASICs, DSPs, PLDs, CPLDs, FPGAs, general-purpose processors, controllers, MCUs, Microprocessors, or other electronic components to perform the aforementioned methods.

[0287] It can be understood that the memory (first memory 903, second memory 1003) of the embodiment of the present application can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a magnetic disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0288] In an exemplary embodiment, the present application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, which includes, for example, a first memory 903 storing a computer program, which can be executed by the first processor 902 of the first platform 900 to complete the steps of the first platform-side method. Another example includes a second memory 1003 storing a computer program, which can be executed by the second processor 1002 of the second platform 1000 to complete the steps of the second platform-side method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0289] In an exemplary embodiment, the embodiment of the present application also provides a computer program product, including a stored computer program, which can be executed by the first processor 902 of the first platform 900 to complete the steps described in the aforementioned first platform side method, or the computer program can be executed by the second processor 1002 of the second platform 1000 to complete the steps described in the aforementioned second platform side method.

[0290] In order to implement the method of the embodiment of the present application, the embodiment of the present application also provides a testing system, such as Figure 11 As shown, the system includes: a first platform 1101 and a second platform 1102.

[0291] Here, it should be noted that the specific processing procedures of the first platform 1101 and the second platform 1102 have been described in detail above and will not be repeated here.

[0292] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0293] In addition, the technical solutions described in the embodiments of the present application can be arbitrarily combined without conflict.

[0294] The above description is merely a preferred embodiment of the present application and is not intended to limit the scope of protection of the present application.

Claims

1. A testing method, characterized in that: Applied to the first platform, including: Acquire test output information for this wireless network performance test, where the test output information includes first information, where the first information is used to indicate a test result associated with a test indicator in the test output information; Determine the test result using the first information; Generate an analysis result using the test result of this time, wherein the analysis result includes second information or third information, wherein the second information includes relevant information of the parameter to be optimized, and the third information indicates that the parameter corresponding to this test does not need to be optimized; The analysis result is sent to the second platform, where the analysis result is used by the second platform to generate a parameter adjustment instruction for the next test on the performance of the wireless network.

2. The method according to claim 1, characterized in that The analysis results generated by utilizing the test results include: When the test result does not meet the threshold requirement of the test indicator, generating the second information; or, When the test result of this time meets the threshold requirement of the test indicator, the third information is generated.

3. The method according to claim 2, characterized in that The test output information further includes fourth information, where the fourth information represents a parameter configuration associated with a test indicator in the test output information; and generating the second information includes: The second information is generated using the fourth information.

4. A testing method, characterized in that: Applied to the second platform, including: Receiving an analysis result of the wireless network performance test sent by the first platform, the analysis result including second information or third information, the second information including relevant information of the parameter to be optimized, and the third information indicating that the parameter corresponding to the test does not need to be optimized; Do one of the following: In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an optimization test order for each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information characterizing the correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1; When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

5. The method according to claim 4, characterized in that The determining, based on the weights of the N parameters included in the one or more parameter clusters, an optimization test order for each parameter included in the one or more parameter clusters includes: Sort by the weight of each parameter from high to low to get the sorting result; The sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

6. The method according to claim 4, characterized in that The determining, based on the weights of the N parameters included in the one or more parameter clusters, an optimization test order for each parameter included in the one or more parameter clusters includes: For one or more parameter clusters, sort the parameter clusters from high to low according to the weight of each parameter cluster to obtain a first sorting result; Based on the first sorting result, for each parameter cluster, sort the parameters in the parameter cluster from high to low according to the weight of each parameter in the parameter cluster to obtain a second sorting result; The second sorting result is used as the optimized test order of each parameter included in the one or more parameter clusters.

7. The method according to claim 4, characterized in that The method further comprises: During the testing process, the weight of each parameter is adjusted.

8. The method according to claim 7, characterized in that The adjusting of the parameter weights includes: Determine the test results of the correlation between the test indicators before and after the parameter adjustment; Determine the first factor using the test results associated with the determined test indicators; The weight of the parameter is adjusted using the first factor.

9. The method according to any one of claims 4 to 8, characterized in that The second information includes an optimization strategy for the parameter to be optimized; When generating the parameter adjustment instruction, the method includes: The parameter adjustment instruction is generated using the optimization strategy.

10. The method according to claim 9, characterized in that The optimization strategy includes parameter configuration identifiers of parameters to be optimized; the optimization strategy generates parameter adjustment instructions, including: Determining an adjustment value of the parameter using the parameter configuration identifier of the parameter to be optimized; The parameter adjustment instruction is generated according to the determined parameter adjustment value.

11. A testing system, characterized in that: include: The first platform and the second platform; wherein, The first platform is configured to obtain test output information for the current wireless network performance test, the test output information including first information, the first information being used to indicate a test result associated with a test indicator in the test output information; determine the current test result using the first information; generate an analysis result using the current test result, the analysis result including second information or third information, the second information including relevant information about a parameter to be optimized, the third information indicating that the parameter corresponding to the current test does not need to be optimized; and send the analysis result to the second platform, the analysis result being used for the second platform to generate a parameter adjustment instruction for a next test of the performance of the wireless network; The second platform is configured to receive the analysis result of the wireless network performance test sent by the first platform, and perform one of the following: In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an optimization test order for each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information characterizing the correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1; When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

12. A testing device, characterized in that: Set up on the first platform, including: an acquiring unit, configured to acquire test output information for this wireless network performance test, wherein the test output information includes first information, and the first information is used to indicate a test result associated with a test indicator in the test output information; a determining unit, configured to determine a test result of this time using the first information; a generating unit, configured to generate an analysis result using the test result, wherein the analysis result includes second information or third information, wherein the second information includes information related to the parameter to be optimized, and the third information indicates that the parameter corresponding to the test does not need to be optimized; The sending unit is used to send the analysis result to the second platform, where the analysis result is used by the second platform to generate a parameter adjustment instruction for the next test on the performance of the wireless network.

13. A testing device, characterized in that: Set up on the second platform, including: a receiving unit, configured to receive an analysis result of the wireless network performance test sent by the first platform, the analysis result including second information or third information, the second information including relevant information of the parameter to be optimized, and the third information indicating that the parameter corresponding to the test does not need to be optimized; An execution unit that performs one of the following: In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an order for optimizing each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information representing a correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1; When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

14. A first platform, characterized in that: include: A first communication interface is configured to obtain test output information for the current wireless network performance test, wherein the test output information includes first information, and the first information is configured to indicate a test result associated with a test indicator in the test output information; Sending the analysis result to the second platform, where the analysis result is used by the second platform to generate a parameter adjustment instruction for the next test of the performance of the wireless network; The first processor is used to use the first information to determine the test result of this time; and use the test result of this time to generate an analysis result, wherein the analysis result includes second information or third information, the second information includes relevant information of the parameters to be optimized, and the third information indicates that the parameters corresponding to this test do not need to be optimized.

15. A second platform, characterized in that: include: a second communication interface, configured to receive an analysis result of the wireless network performance test sent by the first platform, the analysis result including second information or third information, the second information including relevant information of the parameter to be optimized, and the third information indicating that the parameter corresponding to the test does not need to be optimized; The second processor is configured to perform one of the following: In a case where the analysis result includes the second information, determining one or more parameter clusters corresponding to the parameter to be optimized using the second information and the fourth information, and determining an order for optimizing each parameter included in the one or more parameter clusters based on the weights of the N parameters included in the one or more parameter clusters, adjusting the parameter value for each parameter based on the determined order, and generating a parameter adjustment instruction using the adjusted parameter value of each parameter, wherein the parameter adjustment instruction is used to instruct the wireless network to test the performance of the wireless network based on the adjusted parameter value when performing the next test, the fourth information representing a correspondence between the second information and the one or more parameter clusters, the parameter cluster corresponding to the fourth information including one or more parameter clusters, the parameters in each parameter cluster being completely different, and N being an integer greater than or equal to 1; When the analysis result includes the third information, a parameter adjustment instruction is generated based on the number of user accesses in this test, and the parameter adjustment instruction is used to instruct the wireless network to increase the number of user accesses when performing the next test, and to test the performance of the wireless network based on the parameter value corresponding to this test.

16. A first platform, characterized in that: include: a first processor and a first memory for storing a computer program capable of being executed on the processor, Wherein, when the first processor is used to run the computer program, it executes the steps of the method according to any one of claims 1 to 3.

17. A second platform, characterized in that: include: a second processor and a second memory for storing a computer program capable of being executed on the processor, Wherein, when the second processor is used to run the computer program, it executes the steps of the method according to any one of claims 4 to 10.

18. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented, or the steps of the method according to any one of claims 4 to 10 are implemented.

19. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented, or the steps of the method according to any one of claims 4 to 10 are implemented.

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