Switching problem processing method in wireless network automatic driving

Abstract

The invention discloses a method for handling a switching problem in wireless network automatic driving, relates to the technical field of wireless communication, is applied to a mobile communication system, the mobile communication system comprises network cells, and comprises the following steps: determining each abnormal adjacent cell pair in each network cell, and for any one abnormal adjacent cell pair in each abnormal adjacent cell pair, determining an abnormal adjacent cell pair in each abnormal adjacent cell pair; abnormal problems are identified, and each abnormal neighbor cell pair comprises each switching abnormal neighbor cell pair; determining parameters needing to be adjusted and parameter adjustment contents of the abnormal neighbor cell pair according to the abnormal problem, obtaining a parameter adjustment scheme and executing the parameter adjustment scheme; and evaluating the execution result of the parameter adjustment scheme, adjusting the parameter adjustment scheme according to the execution result under the condition that the execution result is unqualified, and returning to the step of executing the execution result of the evaluation parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated to be qualified. The technical problem that the optimization effect is poor in the current network switching problem optimization process is solved.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a method, device, electronic device, storage medium and computer program product for handling switching problems in wireless network autonomous driving. Background Art

[0002] In the field of autonomous driving, wireless communication technologies such as 4G have been widely used. For 4G technology, a cellular network structure is adopted, which includes multiple cells. When a vehicle moves from one cell to another, in order to ensure the continuity and stability of communication, network switching is required. This switching process is completed by the network side and the mobile devices carried by the vehicle through a series of signaling interactions. However, during the interaction process, switching failures may occur due to various reasons such as equipment failure, poor signal quality, insufficient network coverage, and software parameter configuration, which not only affects the user experience, but may even affect the user's life safety. Therefore, it is very important to maintain good and stable wireless network switching.

[0003] In order to maintain good and stable wireless network switching, it is necessary to solve the switching problems existing in the wireless network switching process. The existing switching problem optimization process usually relies on the personal experience of network optimization personnel to analyze and troubleshoot the problems existing in network switching, which is not only time-consuming and costly, but also inefficient. The optimization effect varies from person to person and cannot be guaranteed. Therefore, there is a problem of poor optimization effect in the current network switching problem optimization process. Summary of the invention

[0004] The main purpose of this application is to provide a method for handling switching problems in wireless network autonomous driving, aiming to solve the technical problem of poor optimization effect in the current network switching problem optimization process.

[0005] To achieve the above-mentioned purpose, the present application proposes a method for handling handover problems in wireless network autonomous driving, which is applied to a mobile communication system, wherein the mobile communication system includes network cells, and the method for handling handover problems in wireless network autonomous driving includes: Determine each abnormal neighboring cell pair in each network cell, and for any pair of abnormal neighboring cell pairs among the abnormal neighboring cell pairs, identify an abnormal problem of the abnormal neighboring cell pair, wherein the abnormal neighboring cell pairs include each switching abnormal neighboring cell pair; Determine the parameters of the abnormal neighboring area to be adjusted and the adjustment content of the parameters according to the abnormal problem, obtain a parameter adjustment plan, and execute the parameter adjustment plan; Evaluate the execution result of the parameter adjustment scheme, and if the execution result is unqualified, adjust the parameter adjustment scheme according to the execution result, and return to the step of evaluating the execution result of the parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated to be qualified.

[0006] In one embodiment, the step of determining abnormal neighboring cell pairs in each network cell includes: Determine the alarm cells that meet the preset alarm triggering rules in each network cell and the degradation time inflection point of the alarm cell; The average value of each switching indicator of the preset number of days before the degradation time inflection point is used as a dynamic threshold, and the trend analysis of each switching indicator at the degradation time inflection point is performed according to the dynamic threshold to determine whether the warning cell is a cell with poor switching quality; Identify each target cell associated with the handover poor quality cell, and determine each abnormal neighboring cell pair, wherein the abnormal neighboring cell pair is obtained by combining the handover poor quality cell and the target cell.

[0007] In one embodiment, the abnormal problem includes early inter-frequency switching, late inter-frequency switching, early intra-frequency switching, and late intra-frequency switching. The step of determining the parameters to be adjusted for the abnormal neighboring cell pair and the adjustment content of the parameters according to the abnormal problem includes: In the case where the abnormal problem is premature inter-frequency switching, adjusting the offset of the switching poor-quality cell according to the difference between the offset of the switching poor-quality cell and the offset of the target cell, and adjusting the switching decision threshold of the target cell and the switching decision threshold of the switching poor-quality cell according to the type of inter-frequency switching trigger event of the abnormal neighboring cell pair; In the case where the abnormal problem is that the inter-frequency handover is too late, adjusting the offset of the handover poor quality cell and the offset of the target cell, and adjusting the handover decision threshold of the target cell and the handover decision threshold of the handover poor quality cell according to the type of inter-frequency handover triggering event of the abnormal neighboring cell pair; When the abnormal problem is premature intra-frequency switching, adjust the offset of the switching poor quality cell, intra-frequency switching time hysteresis, intra-frequency switching amplitude hysteresis, and intra-frequency switching bias; When the abnormal problem is that the intra-frequency switching is too late, adjust the offset of the target cell and the offset of the switching poor quality cell, the intra-frequency switching time delay, the intra-frequency switching amplitude delay, and the intra-frequency switching bias.

[0008] In one embodiment, the step of identifying the abnormal problem of the abnormal neighboring area pair includes: Detecting the downlink frequency of the abnormal neighboring cell pair, and determining a first switching problem type between the abnormal neighboring cell pair, wherein the first switching problem type includes a same-frequency switching failure and an inter-frequency switching failure; Collecting handover performance indicator data of the abnormal neighboring cell pair, and analyzing the handover performance indicator data based on a parameter root cause identification algorithm to determine a second handover problem type between the abnormal neighboring cell pair, where the second handover problem type includes handover too early and handover too late; In combination with the first switching problem type and the second switching problem type, the abnormal problems between the abnormal neighboring cell pairs are determined, and the abnormal problems include early inter-frequency switching, late inter-frequency switching, early intra-frequency switching, and late intra-frequency switching.

[0009] In one embodiment, the step of executing the parameter adjustment scheme includes: Building a parameter modification instruction library based on the parameter adjustment scheme, and for any parameter to be adjusted in the parameter modification scheme, generating and executing a parameter modification instruction for the parameter according to the parameter modification instruction library; In the event that the parameter modification instruction fails to execute, determining the type of problem that caused the execution failure; If the problem type is execution failure caused by network fluctuation, a secondary activation mechanism is implemented to resend the parameter modification instruction; If the problem type is execution failure caused by unreasonable parameter setting, a decision iteration mechanism is implemented to iteratively adjust the parameters and execute the adjusted parameter adjustment plan until the parameters reach a preset range threshold.

[0010] In one embodiment, the step of evaluating the execution result of the parameter adjustment scheme, adjusting the parameter adjustment scheme according to the execution result if the execution result is unqualified, and returning to the step of evaluating the execution result of the parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated as qualified includes: In the short evaluation phase, if the performance index between the abnormal neighboring cell pairs deteriorates after executing the parameter modification instruction, the parameters are rolled back to the state before the parameter adjustment, and if the preset short evaluation qualification condition is met, the long evaluation phase is entered for evaluation, and if the preset short evaluation qualification condition is not met, the execution result is determined to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighboring cell pairs reaches the preset success rate; In the long evaluation phase, if the preset long evaluation qualification condition is not met, the execution result is judged to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is judged to be qualified when the switching success rate between the abnormal neighboring cell pairs reaches a preset success rate.

[0011] In one embodiment, the method for handling handover problems in wireless network autonomous driving further includes: Receiving abnormal cell information transmitted by the autonomous driving vehicle, wherein the abnormal cell information includes an abnormally switched-out cell and switched-in cell when the autonomous driving vehicle switches networks during autonomous driving, the switched-out cell is a network cell that the autonomous driving vehicle is about to leave, and the switched-in cell is a network cell that the autonomous driving vehicle is about to enter, as recorded; The switching-out cell and the switching-in cell in the abnormal cell information are used as a switching abnormal neighbor cell pair.

[0012] In addition, to achieve the above-mentioned purpose, the present application also proposes a switching problem processing device in wireless network autonomous driving, which is applied to a mobile communication system, wherein the mobile communication system includes network cells, and the switching problem processing device in wireless network autonomous driving includes: a problem determination module, configured to determine each abnormal neighboring cell pair in each of the network cells, and for any pair of abnormal neighboring cell pairs among the abnormal neighboring cell pairs, identify an abnormal problem of the abnormal neighboring cell pair, wherein the abnormal neighboring cell pairs include each network cell in which an abnormality occurs during network switching in autonomous driving; A scheme generating module, used to determine the parameters to be adjusted for the abnormal neighboring area and the adjustment content of the parameters according to the abnormal problem, obtain the parameter adjustment scheme, and execute the parameter adjustment scheme; An evaluation feedback module is used to evaluate the execution result of the parameter adjustment scheme, and if the execution result is unqualified, adjust the parameter adjustment scheme according to the execution result, and return to the step of evaluating the execution result of the parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated to be qualified.

[0013] In addition, to achieve the above-mentioned purpose, the present application also proposes an electronic device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for handling switching problems in wireless network autonomous driving as described above.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method for handling switching problems in wireless network autonomous driving are implemented as described above.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the method for handling switching problems in wireless network autonomous driving as described above.

[0016] The present application provides a method for handling switching problems in wireless network autonomous driving, which is applied to a mobile communication system, wherein the mobile communication system includes network cells, and the method for handling switching problems in wireless network autonomous driving includes: determining each abnormal neighboring cell pair in each network cell, and for any pair of abnormal neighboring cell pairs in each abnormal neighboring cell pair, identifying abnormal problems of the abnormal neighboring cell pairs, wherein each abnormal neighboring cell pair includes each switching abnormal neighboring cell pair; determining parameters to be adjusted for the abnormal neighboring cell pairs and parameter adjustment content according to the abnormal problems, obtaining a parameter adjustment plan, and executing the parameter adjustment plan; evaluating the execution result of the parameter adjustment plan, and if the execution result is unqualified, adjusting the parameter adjustment plan according to the execution result, and returning to the step of executing the evaluation result of the parameter adjustment plan based on the adjusted parameter plan, until the execution result of the parameter adjustment plan is evaluated as qualified.

[0017] The present application automatically identifies each abnormal neighboring cell pair in each network cell of a mobile communication system, quickly and accurately locates the abnormal neighboring cell pair that may cause a switching problem, reduces interference from human factors, and improves the accuracy and efficiency of identification. For each pair of abnormal neighboring cell pairs identified, the abnormal problems between them are further identified, and the parameters to be adjusted and the parameter adjustment content are determined based on these problems, a parameter adjustment plan is formed, and the plan is executed, so that the parameters can be adjusted according to the specific circumstances of the abnormal problems, thereby improving the pertinence and effectiveness of the adjustment. By evaluating the execution results of the parameter adjustment plan, if the evaluation results are unqualified, the parameter adjustment plan is adjusted according to the execution results, and the evaluation steps are re-executed until the execution results are evaluated as qualified, thereby achieving continuous evaluation and feedback adjustment, and the parameter adjustment plan can be adjusted according to the feedback results, thereby ensuring the effectiveness of the parameter adjustment plan and improving the optimization effect. Compared with related solutions that rely on the personal experience of network optimization personnel, not only is the troubleshooting cycle long and unable to quickly locate the problem, but also it may not be possible to make effective optimization improvements for the located problems. This application uses problem identification, root cause location, solution decision-making, automatic execution and automatic evaluation to automatically optimize switching problems. Through automated processing, the time for problem discovery and resolution is greatly shortened. At the same time, it reduces dependence on manual labor, and through intelligent decision-making and execution, the optimization plan is more accurate and the effect is more obvious, thereby making network switching in autonomous driving more stable, reducing communication interruptions caused by switching failures, and improving users' network perception experience in autonomous driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the description are used to explain the principles of the present application.

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 A flowchart of a method for handling handover problems in wireless network autonomous driving provided in the present application; Figure 2 The iterative flow chart of the premature inter-frequency switching algorithm provided for the method for handling the switching problem in wireless network autonomous driving of this application; Figure 3 An iterative flow chart of the late inter-frequency switching algorithm provided for the method for handling the switching problem in wireless network autonomous driving in this application; Figure 4A flow chart of the second embodiment of the method for handling the handover problem in wireless network autonomous driving of the present application; Figure 5 The overall flow chart of the switching problem optimization solution provided for the switching problem handling method in wireless network autonomous driving of this application; Figure 6 A schematic diagram of the module structure of a device for handling handover problems in wireless network autonomous driving according to an embodiment of the present application; Figure 7 A schematic diagram of the device structure of the hardware operating environment involved in the method for handling switching problems in wireless network autonomous driving in an embodiment of the present application.

[0021] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0022] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0023] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0024] The embodiment of the present application is applied to a mobile communication system, which includes network cells. The main solution is: determining each abnormal neighboring cell pair in each network cell, and for any pair of abnormal neighboring cell pairs in each abnormal neighboring cell pair, identifying abnormal problems of the abnormal neighboring cell pairs, wherein each abnormal neighboring cell pair includes each switching abnormal neighboring cell pair; determining parameters to be adjusted for the abnormal neighboring cell pairs and parameter adjustment content according to the abnormal problems, obtaining a parameter adjustment plan, and executing the parameter adjustment plan; evaluating the execution result of the parameter adjustment plan, and if the execution result is unqualified, adjusting the parameter adjustment plan according to the execution result, and returning to the step of evaluating the execution result of the parameter adjustment plan based on the adjusted parameter plan, until the execution result of the parameter adjustment plan is evaluated as qualified.

[0025] In this embodiment, for ease of description, the switching problem handling system is used as the execution subject for explanation below.

[0026] In the mobile communication system, since 4G technology uses a cellular network structure, when it is applied to autonomous driving, network switching is required when the vehicle moves across cells. However, switching failures may occur due to equipment failures, poor signals, insufficient coverage, software configuration, etc., affecting user experience and life safety. Therefore, it is very important to maintain a good and stable wireless network switching. The optimization of existing switching problems often relies on the experience of network optimization personnel, and there are problems such as long cycles and low efficiency. In addition, operators have to invest a lot of manpower, material resources, and financial resources every year to carry out this work, which not only causes a lot of cost consumption, but also the optimization effect of switching problems is not ideal.

[0027] The present application provides a solution, which realizes an end-to-end closed-loop automatic optimization system for switching problems through automatic problem identification, automatic root cause location, automatic solution decision, automatic execution and automatic evaluation, and uses a switching parameter decision-execution-evaluation-decision iterative feedback optimization mechanism to effectively improve the parameter optimization solution optimization capability, effectively eliminate the problems of relying on manual experience adjustment in the existing switching problem optimization, which is highly arbitrary, inefficient and cannot guarantee the optimization effect, improves the optimization effect of wireless network switching problems, and thus improves the user experience in autonomous driving.

[0028] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a switching problem processing system, etc. The following takes the switching problem processing system as an example to illustrate this embodiment and the following embodiments.

[0029] Based on this, the embodiment of the present application provides a method for handling switching problems in wireless network autonomous driving, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the method for handling handover problems in wireless network autonomous driving of the present application.

[0030] In this embodiment, the method is applied to a mobile communication system, the mobile communication system includes various network cells, and the handover problem processing method in wireless network automatic driving includes steps S01 to S03: Step S01, determining each abnormal neighboring cell pair in each network cell, and for any pair of abnormal neighboring cell pairs among the abnormal neighboring cell pairs, identifying abnormal problems of the abnormal neighboring cell pairs, wherein each abnormal neighboring cell pair includes each switching abnormal neighboring cell pair; It should be noted that the mobile communication system refers to the 4G mobile communication system, which is a cellular network structure. In the 4G mobile communication system, the network is divided into multiple cells, namely network cells, which are the smallest service units in the mobile communication system. Each network cell is served by a specific base station. When the self-driving vehicle moves between these cells, in order to ensure the continuity and stability of communication, network switching is required. However, due to various reasons (such as equipment failure, poor signal quality, insufficient network coverage, improper software parameter configuration, etc.), problems may occur during the switching process, resulting in switching failure or performance degradation. Therefore, it is necessary to determine which neighboring cell pairs (i.e., two adjacent cells) have switching anomalies, and further identify the specific problems between these abnormal neighboring cell pairs.

[0031] In addition, it should be noted that through in-depth analysis of network switching data (such as key indicators such as switching success rate, switching failure rate, signal strength, signal quality, etc.), and by comparing the data characteristics of normal switching and abnormal switching, various abnormal neighboring cell pairs and potential abnormal problems can be identified. An abnormal neighboring cell pair refers to a combination of two adjacent cells that have an abnormality during the network switching process, including abnormal switching neighboring cell pairs, that is, each network cell where an abnormality occurs during network switching in autonomous driving, and can also include each network cell where network switching problems occur in scenarios such as smart homes and smart cities. Abnormal problems refer to specific problems that lead to switching failures or performance degradation, such as signal interference, coverage blind spots, improper switching parameter settings, etc.

[0032] It is understandable that, since existing solutions often rely on network optimization personnel to manually analyze network logs and data to identify abnormal switching areas, this method is time-consuming and labor-intensive, and is easily affected by personal experience and inaccurately positioned. Therefore, step S01 is performed to monitor the switching data of each network cell in real time through automated monitoring and analysis, quickly and accurately determine abnormal neighboring cell pairs, and analyze the network switching data between abnormal neighboring cell pairs through algorithms to accurately determine the specific reasons for the switching failure, such as equipment failure, poor signal quality, insufficient network coverage, etc., which not only improves the positioning speed, but also ensures the accuracy of positioning.

[0033] Step S02, determining the parameters to be adjusted for the abnormal neighboring area and the adjustment content of the parameters according to the abnormal problem, obtaining the parameter adjustment plan, and executing the parameter adjustment plan; It should be noted that once the abnormal neighboring cell pairs and the abnormal problems they exist in are identified, the next step is to formulate targeted parameter adjustment plans. Parameter adjustment plans refer to parameter adjustment plans formulated based on abnormal problems and aimed at optimizing network switching performance. The system determines the network parameters that need to be adjusted (such as same-frequency switching amplitude hysteresis, heterofrequency A3 bias, cell offset, etc.) and the specific adjustment content based on the type of abnormal problem. The adjustment content is the specific content of the parameter adjustment plan determined for the abnormal problem, such as adjusting the cell offset, increasing the heterofrequency A3 bias, etc. After formulating the parameter adjustment plan, these adjustments need to be executed and the changes in network performance after the adjustments need to be monitored.

[0034] It is understandable that in existing solutions, network optimization personnel often manually adjust network parameters based on experience, which lacks scientific basis and makes the adjustment effect difficult to predict. Therefore, step S02 is performed to automatically recommend parameters that need to be adjusted and their adjustment contents based on the abnormal problems identified in step S01, and automatically execute these adjustment plans without human intervention, which not only improves the adjustment efficiency but also ensures the scientificity and accuracy of the adjustment.

[0035] Step S03, evaluating the execution result of the parameter adjustment scheme. If the execution result is unqualified, adjusting the parameter adjustment scheme according to the execution result, and returning to the step of evaluating the execution result of the parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated to be qualified.

[0036] It should be noted that after executing the parameter adjustment plan, the switching performance in the execution results needs to be continuously monitored and evaluated to determine whether the adjustment is effective. The evaluation indicators include switching success rate, switching failure rate, signal strength stability, user satisfaction, etc. If the evaluation results show that the parameter adjustment plan fails to achieve the expected effect (that is, the execution result is unqualified), the parameter adjustment plan needs to be adjusted according to the evaluation results and the evaluation steps need to be re-executed. This process requires multiple iterations until the optimal parameter configuration is found so that the switching performance reaches satisfactory standards.

[0037] It is understandable that, since in the existing schemes, network optimization personnel usually manually evaluate the adjustment effect and manually adjust the parameters according to the evaluation results, there is a lack of continuity and systematicness, and the optimization effect is difficult to ensure continuously. Therefore, step S03 is performed to automatically evaluate the execution result of the parameter adjustment scheme by continuously monitoring the switching performance data. If the evaluation result is unqualified (i.e., the switching problem still exists or the improvement is not obvious), the parameter adjustment scheme is automatically adjusted according to the evaluation result, and the evaluation step is re-executed, and it continues until the switching performance reaches a satisfactory standard. This not only improves the evaluation efficiency, but also ensures the continuity and reliability of the optimization.

[0038] In a feasible implementation manner, in step S01, the step of determining abnormal neighboring cell pairs in each network cell includes steps A01 to A03: Step A01, determining the alarm cells and the degradation time inflection point of the alarm cells in each network cell that meet the preset alarm triggering rules; It should be noted that, for any one of the network cells, the gear of the number of switching attempts is determined based on the preset alarm trigger rules. The number of switching attempts refers to the number of requests for network switching between the current network cell and other network cells. According to the gear corresponding to the number of switching attempts, the switching success rate degradation ratio, switching success rate degradation value and failure number degradation value of the network cell are compared to see whether they reach the corresponding thresholds. When each indicator reaches the corresponding threshold, it is determined that the current network cell meets the preset alarm trigger rules and is determined to be an alarm cell.

[0039] In addition, after determining the alarm cell, it is necessary to determine the degradation time inflection point of the alarm cell, that is, the time point when its performance begins to decline significantly. The system analyzes the historical data of the alarm cell to find the time point when its performance indicator first deteriorates, that is, the time node when its switching performance indicator changes from a normal state to an abnormal state, and records this time point as the degradation time inflection point.

[0040] Exemplarily, the preset alarm triggering rules are shown in Table 1. When the number of switching attempts of a network cell is 2000, it means that the corresponding gear of the current network cell is gear 3. If it is detected that the switching success rate degradation ratio of the current network cell reaches 0.9, the switching success rate degradation value reaches 10% and the failure number degradation value reaches 50, the current network cell is determined to be an alarm cell.

[0041] Table 1

[0042] Step A02, taking the average value of each switching indicator for a preset number of days before the degradation time inflection point as a dynamic threshold, and performing trend analysis on each switching indicator at the degradation time inflection point according to the dynamic threshold to determine whether the alarm cell is a poor quality switching cell; It should be noted that before the inflection point of the degradation time, a preset number of days (such as 15 days) is selected as the analysis basis for calculating the average value of the switching index. Within the preset number of days, the average value of the switching index of the network cell is extracted based on the outlier detection algorithm, including but not limited to the average values ​​of key indicators such as the switching success rate and the number of failures, and a dynamic threshold, i.e., a dynamic threshold, is set according to the average value of the switching index within the preset number of days. This dynamic threshold reflects the normal performance level of the cell before degradation and is used to determine whether the switching performance indicator at the inflection point of the degradation time is an abnormal fluctuation.

[0043] In addition, it should be noted that by comparing the switching performance indicators of the degradation time inflection point with the dynamic threshold through trend analysis, analyzing the changing trends of these indicators, it is determined whether the alarm cell is in a normal fluctuation or a sudden degradation state. For example, if the switching indicator of the degradation time inflection point is significantly lower / higher than the dynamic threshold, and this decline / increase is sudden and significant, then we can consider the cell to be a cell with poor switching quality.

[0044] Step A03, identifying each target cell associated with the handover poor quality cell, and determining each abnormal neighbor cell pair, where the abnormal neighbor cell pair is obtained by combining the handover poor quality cell and the target cell.

[0045] It should be noted that after determining the switching quality cell, by analyzing the number of switching failures between the switching quality cell and its neighboring cells, the target cell that is highly associated with the switching quality cell is identified, and the switching quality cell and the target cell form an abnormal neighboring cell pair.

[0046] In addition, it should be noted that when identifying the target cell, it is necessary to determine whether the network cell meets the target cell judgment conditions. For network cells that meet the target cell judgment conditions, it means that there is a significant correlation between the network cell and the switching quality poor cell, and it is regarded as the target cell.

[0047] Exemplarily, the target cell determination condition is:

[0048] in, is the number of handover failures between neighboring cells, that is, the number of handover failures between a cell with poor handover quality and each of its neighboring network cells. It is the sum of the top 3 switching failures of each pair of neighboring cells, that is, the sum of the top three switching failures between the switching quality poor cell and each of its adjacent network cells. If the proportion of a certain network cell is greater than or equal to 20%, it is determined that there is a significant correlation between the network cell and the switching quality poor cell, and it is determined as the target cell.

[0049] In this implementation, by presetting alarm triggering rules and combining with real-time monitoring data, the cells that meet the alarm conditions can be accurately identified, the accuracy of alarm cell identification is improved, false alarms and missed alarms are reduced, and a reliable basis is provided for subsequent optimization work. Based on the dynamic threshold, the trend analysis of the switching index at the inflection point of the degradation time is performed, and it is possible to objectively and scientifically determine whether the alarm cell is a cell with poor switching quality. By comparing the actual value of the switching index with the dynamic threshold, the abnormal fluctuation of the index can be accurately identified, the subjectivity of manual judgment is avoided, and the accuracy and objectivity of the judgment of the cell with poor switching quality are improved, providing a scientific basis for the formulation of subsequent optimization plans. According to the number of switching failures of neighboring cell pairs, the object identification algorithm of the switching quality problem is used to quickly locate the target cell that is highly related to the cell with poor switching quality. By calculating the ratio of the number of switching failures to the sum of the number of switching failures of the TOP3 neighboring cell pairs, the existence of abnormal neighboring cell pairs and the degree of their influence can be accurately determined, which improves the speed and accuracy of locating abnormal neighboring cell pairs and provides clear guidance for the implementation of subsequent optimization measures.

[0050] In a feasible implementation manner, the abnormal problem includes early inter-frequency switching, late inter-frequency switching, early intra-frequency switching, and late intra-frequency switching. In step S02, the step of determining the parameters to be adjusted for the abnormal neighboring cell pair and the adjustment content of the parameters according to the abnormal problem includes steps A11 to A14: Step A11, when the abnormal problem is that the inter-frequency handover is too early, the offset of the poor quality cell is adjusted according to the difference between the offset of the poor quality cell and the offset of the target cell, and the handover decision threshold of the target cell and the handover decision threshold of the poor quality cell are adjusted according to the type of inter-frequency handover triggering event of the abnormal neighboring cell pair; It should be noted that when the abnormal problem is premature inter-frequency switching, it means that the abnormal neighboring cell pair has a premature switching phenomenon compared with the inter-frequency network switching under normal circumstances. There is room for optimization of the switching parameters of the neighboring cell pair. For cells with poor switching quality, the switching speed needs to be lowered, and for the target cell, the speed of being cut in needs to be increased.

[0051] In addition, it should be noted that in order to reduce the speed of switching out of the poor quality cell and increase the speed of the target cell being cut in, the offset of the poor quality cell is reduced according to the difference between the offset of the poor quality cell and the target cell. The offset refers to the priority of the cell in the switching decision. By adjusting the offset, the possibility of the cell being selected as the switching target can be changed. At the same time, the type of inter-frequency switching trigger event is determined. The inter-frequency switching trigger event types include A3 events (switching is triggered based on the quality of the neighboring cell being higher than a certain threshold of the serving cell), A4 events (inter-frequency switching is triggered based on the quality of the serving cell being lower than a certain threshold) and A5 events (inter-frequency switching is triggered based on the quality of the neighboring cell being higher than a certain threshold). The handover decision threshold is used to determine whether the handover should occur. For example, the inter-frequency A3 offset determines the degree of quality difference between the serving cell and the neighboring cell that triggers the handover. When the parameter value to be adjusted has been adjusted to the set range threshold, it is determined that the parameter has reached the convergence condition and the tuning process ends.

[0052] For example, when the abnormal problem is that the inter-frequency handover is too early, the first parameter to be adjusted is the handover poor quality cell offset, and the tuning rule is:

[0053] in, is the offset for switching to a poor quality cell, is the offset of the target cell, It is the adjustment value between the switching poor quality cell and the target cell offset. When the cell offset is >-6dB, if the difference between the current value of the switching poor quality cell offset and the target value of the switching poor quality cell offset (referring to the ideal value or expected value that the cell offset is expected to reach, usually set based on network planning, optimization strategy or specific business needs) is greater than 4dB, adjust downward by 4dB. If the difference between the current value of the switching poor quality cell offset and the target value of the switching poor quality cell offset is less than or equal to 4dB, directly adjust the current value of the switching poor quality cell offset to -6dB, and the absolute value of the cell offset is not less than -6dB.

[0054] Then, the type of the inter-frequency handover trigger event between the poor quality cell and the target cell is determined by the inter-frequency handover trigger event type judgment condition, including A3 event, A4 event and A5 event. Taking A3 event as an example, the judgment condition is:

[0055] Among them, the frequency of switching to poor quality cells is , the frequency of the target cell is , The target cell and the poor quality cell for handover The difference between the values Not less than the A3 judgment threshold ( )hour, , that is, the type of heterodyne switching trigger event is A3 event. Similarly, A4 and A5 events can be determined.

[0056] After determining the type of inter-frequency handover trigger event (assuming that the inter-frequency handover trigger event is an A3 event), the parameters that need to be adjusted for the target cell include the inter-frequency A3 offset value and the inter-frequency RSRP trigger threshold based on coverage, in order to increase the handover decision threshold of the target cell. The A3 event means that the signal quality of the serving cell is lower than a threshold, and the signal quality of the neighboring cell is higher than the threshold plus an offset value. The inter-frequency A3 offset value is used to adjust the conditions for triggering the A3 event so that the signal difference between different frequencies can be considered during inter-frequency handover. RSRP (reference signal received power) is an indicator of wireless signal strength. The inter-frequency RSRP trigger threshold based on coverage is used to determine when to perform inter-frequency handover based on coverage considerations. When the RSRP of the serving cell is lower than this threshold, it may trigger a switch to a cell of another frequency. The tuning formula is as follows:

[0057]

[0058] in, is the A3 bias before adjustment, is the adjusted A3 bias, It is the adjustment difference of A3 bias. For the inter-frequency A3 bias optimization of the target cell, determine whether the inter-frequency A3 bias of the target cell is less than 3dB. If the inter-frequency A3 bias is less than 0dB, adjust it to 0dB directly. If it is greater than or equal to 0dB and less than 2dB, adjust it to 2dB. If it is greater than or equal to 2dB, adjust it to 3dB. When the inter-frequency A3 bias is <3dB, adjust it upward in 0.5dB steps based on the current setting, not higher than 3dB.

[0059] Similarly, for the target cell A4 threshold (inter-frequency RSRP trigger threshold based on coverage) optimization, it is determined whether the target cell A4 threshold is less than -95dBm. When the target cell A4 threshold is less than -95dBm, the target cell A4 threshold is optimized in the range of (current setting value, -95]dBm with a step size of 1dB.

[0060] For handover of poor quality cells, the parameters that need to be adjusted include the A3-based heterofrequency A2 RSRP trigger threshold and the A4A5-based heterofrequency A2 RSRP trigger threshold, in order to lower the handover decision threshold for poor quality cells. The A2 event refers to the signal quality of the serving cell being lower than a specific RSRP threshold. The heterofrequency A2 RSRP trigger threshold is used for heterofrequency handover scenarios. When the RSRP of the serving cell is lower than this threshold, a measurement report may be triggered, and handover may be considered. The A3-based heterofrequency A2 RSRP trigger threshold refers to the RSRP threshold used to trigger the A2 event when considering the A3 event. The A4A5-based heterofrequency A2 RSRP trigger threshold refers to the RSRP threshold used to trigger the A2 event when considering the A4 or A5 event. The tuning formula is:

[0061]

[0062] in, To switch to a poor quality cell, the inter-frequency A2 RSRP trigger threshold based on A3 is used. The target cell's A2 RSRP trigger threshold based on A3. is the adjustment difference of the inter-frequency A2 RSRP trigger threshold based on A3. For the optimization of the inter-frequency A2 RSRP trigger threshold based on A3 for the switching quality cell, it is determined whether the inter-frequency A2 RSRP trigger threshold based on A3 for the switching quality cell is greater than -105dBm. When the inter-frequency A2 RSRP trigger threshold based on A3 for the switching quality cell is greater than -105dBm, the inter-frequency A2 RSRP trigger threshold based on A3 for the switching quality cell is optimized within the range of [-105, current setting value) dB with a step size of 2dB.

[0063] Similarly, for the handover poor quality cell based on A4A5 inter-frequency A2 RSRP trigger threshold optimization, determine whether the handover poor quality cell based on A4A5 inter-frequency A2 RSRP trigger threshold is greater than -105dBm. When the handover poor quality cell based on A4A5 inter-frequency A2 RSRP trigger threshold is greater than -105dBm, optimize the handover poor quality cell based on A4A5 inter-frequency A2 RSRP trigger threshold within the range of [-105, current setting value) dB with a step size of 2dB.

[0064] For example, to help understand the technical concept or technical principle of this application, please refer to Figure 2 , Figure 2An iterative flow chart of the premature inter-frequency switching algorithm is provided. When the abnormal problem is premature inter-frequency switching, the offset of the switching poor quality cell is first adjusted downward, and the type of the inter-frequency switching triggering event is determined, which is divided into A3 event and A4 / A5 event to achieve an increase in the target cell switching decision threshold and a decrease in the switching decision threshold for the poor quality cell.

[0065] Step A12, when the abnormal problem is that the inter-frequency handover is too late, adjust the offset of the poor quality cell and the offset of the target cell, and adjust the handover decision threshold of the target cell and the handover decision threshold of the poor quality cell according to the type of inter-frequency handover trigger event of the abnormal neighboring cell pair; It should be noted that when the abnormal problem is that the inter-frequency switching is too late, it means that the abnormal neighboring cell pair has a switching phenomenon too late compared with the inter-frequency network switching under normal circumstances. There is room for optimization of the switching parameters of the neighboring cell pair. For the cell with poor switching quality, the switching speed needs to be increased, and for the target cell, the speed of being cut in needs to be reduced.

[0066] In addition, it should be noted that in order to increase the speed of switching out the poor quality cell and lower the speed of cutting into the target cell, the offsets of the poor quality cell and the target cell are adjusted at the same time to improve the switching timing, increase the offset of the poor quality cell, and lower the offset of the target cell. At the same time, the type of heterofrequency switching trigger event is judged, and based on the identified heterofrequency switching trigger event type, the switching decision threshold of the target cell is lowered to make it easier to be cut in, and the switching decision threshold of the poor quality cell is increased to make it easier to be switched out. When the parameter value to be adjusted has been adjusted to the set range threshold, it is determined that the parameter has reached the convergence condition and the tuning process is ended.

[0067] Exemplarily, when the abnormal problem is that the inter-frequency handover is too late, the first parameter to be adjusted is the offset between the handover poor quality cell and the target cell, and the tuning rule is:

[0068]

[0069] Among them, the offset of switching to a poor quality cell is , the offset of the target cell is ,When the current handover quality cell's offset to the target cell (referred to as the first offset) is less than 6dB, if the first offset is less than 0, the first offset is directly adjusted to 0; if the first offset is greater than or equal to 0, and the difference between the current value of the first offset and the target value of the first offset (refers to the ideal value that the source cell is expected to reach relative to the target cell, which is usually set based on network planning, optimization strategies or specific business requirements to ensure a balance in network coverage, capacity and quality) is greater than or equal to 2, it is adjusted upward by 2dB; if the first offset is greater than or equal to 0, and the first offset is greater than or equal to 1, the first offset is adjusted upward by 1dB; if the first offset is greater than or equal to 0, and the first offset is greater than or equal to 1, the first offset is adjusted upward by 1dB; if the first offset is greater than or equal to 1 .... If the difference between the current value of the offset and the target value of the first offset is less than 2dB, adjust it upward by 1dB. The absolute value of the cell offset is not higher than 6dB. At the same time, adjust the offset of the target cell. If the first offset is greater than 0, adjust the first offset directly to 0. If the first offset is less than or equal to 0, and the difference between the current value of the first offset and the target value of the first offset is greater than or equal to 2dB, adjust it downward by 2dB. If the first offset is less than or equal to 0, and the difference between the current value of the first offset and the target value of the first offset is less than 2dB, adjust it downward by 1dB. The neighboring cell offset is not less than -6dB.

[0070] Then, the type of the inter-frequency switching trigger event between the poor-quality cell and the target cell is determined through the inter-frequency switching trigger event type judgment condition. For the same or similar contents as above, please refer to the above introduction and will not be repeated later.

[0071] After determining the type of inter-frequency handover triggering event, for the target cell, the parameters that need to be adjusted include the inter-frequency A3 offset value, A4 threshold, and A5 threshold, so as to lower the handover decision threshold of the target cell. For the target cell inter-frequency A3 offset optimization, when the target cell's inter-frequency A3 offset is greater than 3dB, if the difference between the current target cell's inter-frequency A3 offset and the A3 offset target value (referring to the inter-frequency A3 offset value that is expected to be achieved during the optimization process, usually determined based on network performance analysis, user experience requirements or specific network planning goals) is greater than 4dB, adjust downward by 4dB. If the difference between the current target cell's inter-frequency A3 offset and the A3 offset target value is less than or equal to 4dB, adjust directly to 3dB. For the target cell A4 threshold optimization, when the target cell's A4 threshold is greater than -105dBm, determine the current target cell's A4 threshold and A4 threshold. Whether the target value (referring to the A4 threshold that is expected to be achieved during the tuning process, which is usually determined based on network performance analysis, user experience requirements or specific network planning goals) is greater than or equal to 10dB. If it is greater than or equal to 10dB, it is modified downward in steps of 5dB and stops at 10dB; if it is less than 10dB, it is directly modified to -105dBm; For target cell A5 threshold tuning: When the A5 threshold of the target cell is greater than -105dBm, determine whether the A5 threshold of the current target cell and the A5 threshold target value (referring to the A5 threshold that is expected to be achieved during the tuning process, which is usually determined based on network performance analysis, user experience requirements or specific network planning goals) are greater than or equal to 10dB. If it is greater than or equal to 10dB, it is modified downward in steps of 5dB and stops at 10dB; if it is less than 10dB, it is directly modified to -105dBm.

[0072] For handover to poor quality cells, the parameters that need to be adjusted include the inter-frequency A2 RSRP trigger threshold based on A3 and the inter-frequency A2 RSRP trigger threshold based on A4A5, so as to increase the handover decision threshold for poor quality cells. For the increase of the inter-frequency A4A5 trigger threshold for handover to poor quality cells, the tuning formula is as follows:

[0073] in, is the current trigger threshold for switching to a poor quality cell, For the adjusted trigger threshold for switching to a cell with poor quality, for the source cell's A3-based heterofrequency A2 RSRP trigger threshold optimization, when the source cell's A3-based heterofrequency A2RSRP trigger threshold is less than -95dBm, adjust it upward in steps of 2dB, not higher than -95dBm; for the source cell's A4A5-based heterofrequency A2 RSRP trigger threshold optimization, when the source cell's A4A5-based heterofrequency A2 RSRP trigger threshold is less than -95dBm, adjust it upward in steps of 2dB, not higher than -95dBm; for the source cell's A4A5-based heterofrequency A2 RSRP trigger threshold optimization, when the source cell's A4A5-based heterofrequency A2 RSRP trigger threshold is less than -95dBm, adjust it upward in steps of 2dB, not higher than -95dBm; and the heterofrequency switching A5 RSRP threshold 1 is adjusted synchronously, and adjusted upward in steps of 2dB at the current parameter setting value, not greater than -95dBm.

[0074] For example, to help understand the technical concept or technical principle of this application, please refer to Figure 3 , Figure 3 An iterative flow chart of the late inter-frequency switching algorithm is provided. When the abnormal problem is that the inter-frequency switching is too late, the offset of the switching poor quality cell is first adjusted upward, and the offset of the target cell is adjusted downward. The type of the inter-frequency switching triggering event is determined, and the A3 event and A4 / A5 event are divided into the target cell switching decision threshold lowered and the poor quality cell switching decision threshold increased.

[0075] In addition, it should be noted that when the abnormal problem is that the inter-frequency switching is too early or too late, the inter-frequency switching parameters that can also be adjusted include but are not limited to inter-frequency A1A2 amplitude hysteresis, inter-frequency A1A2 time hysteresis, inter-frequency switching amplitude hysteresis, inter-frequency switching time hysteresis, load-based inter-frequency RSRP trigger threshold, connected state frequency offset, etc., among which, amplitude hysteresis is used to reduce frequent switching due to signal fluctuations, and inter-frequency A1A2 amplitude hysteresis means that in inter-frequency switching, A1 (the signal quality of the serving cell is higher than a certain threshold) and A2 events use this hysteresis to smooth the switching decision. Time hysteresis is similar to amplitude hysteresis, but it is based on time. Inter-frequency A1A2 time hysteresis means that before triggering the A1 or A2 event, the signal condition must continue to meet a certain length of time, which helps to reduce the cause of instantaneous signal fluctuations. Switching, the amplitude hysteresis of inter-frequency switching is the amplitude hysteresis parameter used for inter-frequency switching, which is used to smooth switching decisions and reduce unnecessary switching. The time hysteresis of inter-frequency switching, corresponding to the amplitude hysteresis of inter-frequency switching, is a time-based hysteresis parameter used to ensure that the switching decision is based on signal conditions that last for a period of time. The load-based inter-frequency RSRP trigger threshold refers to the RSRP threshold used to trigger inter-frequency switching while considering the network load. When the load of the serving cell is too high, even if the RSRP value is still within an acceptable range, it may trigger switching to a cell of another frequency to balance the load. The connected state frequency offset is a parameter used to adjust the switching tendency between different frequencies. It can affect the switching decision in the connected state, making the UE (user equipment) more inclined to switch to a frequency with a higher offset value, which helps to optimize network performance and resource utilization.

[0076] Step A13, when the abnormal problem is that the same-frequency switching is too early, adjust the offset of the switching poor quality cell, the same-frequency switching time delay, the same-frequency switching amplitude hysteresis, and the same-frequency switching bias; It should be noted that when the abnormal problem is premature switching of the same frequency, it means that the abnormal neighboring cell pair has switched too early compared with the same frequency network switching under normal circumstances. There is room for optimization of the switching parameters of the neighboring cell pair, and the speed of switching out the cell with poor switching quality needs to be increased.

[0077] In addition, it should be noted that in order to increase the speed of switching out the cell with poor switching quality, the offset of the cell with poor switching quality is adjusted to reduce the switching triggering conditions, increase the intra-frequency switching time hysteresis of the cell with poor switching quality (the time hysteresis of the intra-frequency switching measurement event (such as the A3 event)) to delay the switching timing, increase the intra-frequency switching amplitude hysteresis of the cell with poor switching quality (the hysteresis of the intra-frequency switching measurement event, which is used to reduce the number of triggering intra-frequency switching events due to wireless signal fluctuations), improve the stability of the switching, and increase the intra-frequency switching bias of the cell with poor switching quality (the bias value of the neighboring cell quality being higher than the serving cell in the intra-frequency switching) to promote the switching to the target cell, wherein the intra-frequency switching time hysteresis refers to waiting for a period of time before executing the switching after the switching conditions are met to avoid frequent switching, the intra-frequency switching amplitude hysteresis is used to increase the stability of the switching to prevent the switching from being triggered due to slight quality fluctuations, and the intra-frequency switching bias is used to adjust the sensitivity of the intra-frequency switching. When the parameter value to be adjusted has been adjusted to the set range threshold, it is determined that the parameter has reached the convergence condition and the tuning process is terminated.

[0078] Exemplarily, when the abnormal problem is premature intra-frequency switching, when the offset of the switching quality cell is greater than -6dB, it is adjusted downward in steps of 1dB and not lower than -6dB; when the intra-frequency switching time hysteresis of the switching quality cell is less than 160ms, the intra-frequency switching time hysteresis is adjusted to 160ms; when the intra-frequency switching amplitude hysteresis of the switching quality cell is less than 1dB, it is adjusted upward in steps of 0.5dB and not higher than 1dB; when the intra-frequency switching bias of the switching quality cell is less than 1dB, it is adjusted upward in steps of 0.5dB and not higher than 1dB.

[0079] Step A14, when the abnormal problem is that the intra-frequency switching is too late, adjust the offset of the target cell and the offset of the switching poor quality cell, the intra-frequency switching time delay, the intra-frequency switching amplitude delay, and the intra-frequency switching bias.

[0080] It should be noted that when the abnormal problem is late switching of the same frequency, it means that the abnormal neighboring cell pair has a switching phenomenon too late compared with the same frequency network switching under normal circumstances. There is room for optimization of the switching parameters of the neighboring cell pair. It is necessary to reduce the speed of switching out cells with poor switching quality and increase the speed of switching into the target cell.

[0081] In addition, it should be noted that in order to lower the speed of switching out of the poor quality cell and increase the speed of switching into the target cell, the offset of the poor quality cell and the target cell is adjusted at the same time to improve the switching timing, reduce the co-frequency switching time hysteresis of the poor quality cell, advance the switching timing, reduce the co-frequency switching amplitude hysteresis of the poor quality cell, reduce the switching stability requirements, reduce the co-frequency switching bias of the poor quality cell, and promote switching to a more suitable cell.

[0082] Exemplarily, when the abnormal problem is that the intra-frequency switching is too late, when the offset of the switching quality cell to the target cell is <0dB, it is adjusted upward in steps of 1dB, not higher than 0dB, and at the same time, the offset of the target cell to the switching quality cell is adjusted downward in steps of 1dB from the current parameter setting value, not lower than -6dB; when the intra-frequency switching time hysteresis of the switching quality cell is >320ms, the intra-frequency switching time hysteresis is adjusted to 320ms; when the intra-frequency switching amplitude hysteresis of the switching quality cell is >1dB, it is adjusted downward in steps of 0.5dB, not lower than 1dB; when the intra-frequency switching bias of the switching quality cell is >1dB, it is adjusted downward in steps of 0.5dB, not lower than 1dB.

[0083] In this implementation, accurate parameter adjustment is performed for specific switching problems to ensure the pertinence and effectiveness of parameter adjustment. Through iterative adjustment of parameters, the optimal parameter combination can be gradually found to improve the switching success rate and reduce network instability caused by switching problems. This solves the problem of poor optimization effect in the current network switching problem optimization process and improves network stability and user experience.

[0084] In a feasible implementation, in step S01, the step of identifying abnormal problems of abnormal neighboring area pairs includes steps A21 to A23: Step A21, detecting the downlink frequency of the abnormal neighboring cell pair, determining the first switching problem type between the abnormal neighboring cell pair, the first switching problem type including the same-frequency switching failure and the different-frequency switching failure; It should be noted that the downlink frequency information of the abnormal neighboring cell pairs is collected. The downlink frequency refers to the frequency point of the wireless base station transmitting the signal. It is a key parameter to distinguish between the same-frequency and different-frequency switching. The downlink frequency points of the abnormal neighboring cell pairs are compared. If the downlink frequency points of the abnormal neighboring cell pairs are the same, the switching between the abnormal neighboring cell pairs is the same frequency switching. If they are different, it is a different frequency switching. According to the result of the frequency comparison, the system determines the first switching problem type. If the switching failure occurs between the same-frequency neighboring cell pairs, it is classified as the same-frequency switching failure. If it occurs between the different-frequency neighboring cell pairs, it is classified as the different-frequency switching failure.

[0085] Step A22, collecting the handover performance index data of the abnormal neighboring cell pair, and analyzing the handover performance index data based on the parameter root cause identification algorithm to determine the second handover problem type between the abnormal neighboring cell pair, the second handover problem type including handover too early and handover too late; It should be noted that the system collects switching performance indicator data related to network switching from the network log or performance monitoring system. The switching performance indicator data is various indicator data reflecting the network switching performance, including but not limited to the number of heterogeneous frequency switching attempts within the eNodeB, the number of heterogeneous frequency switching attempts between eNodeBs, the number of successful heterogeneous frequency switching between eNodeBs, the number of successful heterogeneous frequency switching within the eNodeB, etc. The collected switching performance indicator data are cleaned and sorted to ensure the accuracy and completeness of the data, and the pre-processed switching performance indicator data are analyzed using the parameter root cause identification algorithm. The parameter root cause identification algorithm is an algorithm based on machine learning or statistical analysis, which is used to identify the root cause of the switching problem. By comprehensively considering the switching performance indicator data and combining the preset thresholds and conditions, it is determined whether there is a problem of switching too early or too late. According to the results of the algorithm analysis, the system will further determine the second switching problem type, that is, switching too early or switching too late.

[0086] In addition, it should be noted that premature switching usually occurs when the signal quality of the neighboring cell is not good enough or not stable enough, and the eNodeB (evolved Node B, i.e. 4G base station) initiates the switching. The manifestations and judgment methods of premature switching mainly include: ① Handover failure and reestablishment back to the source cell: After the source cell sends a handover command, the user equipment (UE) fails to switch to the target cell due to poor signal quality of the target cell. The UE then initiates RRC (radio resource control) connection reestablishment in the source cell. This is usually because the signal quality of the target cell is not sufficient to support a stable communication connection.

[0087] ② Rebuilding back to the source cell after downlink synchronization loss: Although the UE successfully switches to the target cell, downlink synchronization loss occurs immediately (that is, the UE cannot keep synchronized with the target cell), and then RRC connection reconstruction is initiated in the source cell.

[0088] ③ Frequent switching: UE switches from the target cell to another cell within a short period of time (e.g., within 5 seconds), which may also be a sign of premature switching.

[0089] Late switching means that the UE has an RLF (Radio Link Failure) in the source cell, and during RRC reestablishment, it is reestablished to a non-source cell. The manifestations and determination methods of late switching mainly include: ① Reconstruction to a non-source cell after RLF: This is a direct manifestation of late handover. When the UE has RLF in the source cell, if it is out of the signal coverage of the source cell at this time, RRC reconstruction may be successful to another cell (non-source cell).

[0090] ② Decreased handover success rate: Although handover too late will not directly affect the handover success rate calculation formula (handover success rate = (number of handover successes - number of successful handover executions to reestablish the source cell) / number of handover attempts), handover too late will increase the probability of RLF, thereby indirectly leading to a decrease in the handover success rate.

[0091] ③ Reduced user perception: Switching too late may cause users to experience interruptions or delays during the network switching process, thus affecting the user experience.

[0092] Step A23, combining the first switching problem type and the second switching problem type to determine abnormal problems between abnormal neighboring cell pairs, the abnormal problems include early inter-frequency switching, late inter-frequency switching, early intra-frequency switching, and late intra-frequency switching.

[0093] It should be noted that the first switching problem type (switching failure in the same frequency / switching failure in different frequency) and the second switching problem type (switching too early / switching too late) determined in steps A21 and A22 are integrated. Based on the integrated results, the system determines the specific abnormal problem type between the abnormal neighboring cell pairs, such as different frequency switching too early, different frequency switching too late, same frequency switching too early, same frequency switching too late, etc.

[0094] In addition, it should be noted that after the abnormal problem is identified, the system will output the relevant data of the abnormal neighboring cell pairs and the parameter root cause identification results. The relevant data of the abnormal neighboring cell pairs include but are not limited to the indicator degradation time, regional information, corresponding equipment manufacturers, the number of switching pairs with TOP problems, the CGI of the switching poor quality cell and the CGI of the target cell, etc. Among them, the indicator degradation time refers to the time point when a certain network performance indicator (such as signal quality, throughput, latency, etc.) begins to decline or becomes unsatisfactory. The regional information is used to describe the geographical location of the problem, which can be specific to a certain city, region, or even street. The corresponding equipment manufacturer refers to the manufacturer or supplier that produces or provides the problematic equipment. The number of switching pairs with TOP problems refers to the number of switching neighboring cell pairs with the most serious or most common problems that occur during the network switching process. The source cell CGI and the target cell CGI refer to the identifiers used to identify the switching poor quality cell and the target cell, respectively. CGI (Cell GlobalIdentifier is an identifier used to uniquely identify a cell in a mobile communication network; the parameter root cause identification results include but are not limited to the source cell CGI, the target cell CGI, whether there is a handover parameter problem, the handover failure type and the handover early and late type, etc. The handover failure type includes the same frequency / different frequency, and the handover early and late type includes too early / too late.

[0095] Exemplarily, in the case where the first switching problem type is an inter-frequency switching failure, if the number of switching failures of the inter-frequency neighboring cell pair accounts for a high proportion and there is a phenomenon of premature switching, it is considered that the second switching problem type of the neighboring cell pair is premature switching, that is, the abnormal problem is premature inter-frequency switching, and the judgment conditions for premature inter-frequency switching include: ① The neighbor cell switching is too early and fails: The number of premature switches between two specific cells is >500, and the number of premature switches between two specific cells / the number of switch-out attempts between two specific cells is >50%, and the number of successful switches between two specific cells / the number of switch-out attempts between two specific cells is <95%, and the number of switch-out attempts between two specific cells - the number of successful switches between two specific cells is >500.

[0096] ② The proportion of neighboring cell handover failures to the total cell handover failures is > 20%: (Number of handover attempts between two specific cells - Number of successful handovers between two specific cells) / (Number of intra-eNodeB heterofrequency handover attempts + Number of inter-eNodeB heterofrequency handover attempts + Number of intra-eNodeB FDD / TDD mode handover attempts + Number of inter-eNodeB FDD / TDD mode handover attempts - Number of inter-eNodeB heterofrequency handover successes - Number of intra-eNodeB heterofrequency handover successes - Number of inter-eNodeB FDD / TDD mode handover successes - Number of inter-eNodeB FDD / TDD mode handover successes within the eNodeB)>20%.

[0097] Among them, eNodeB (Evolved Node B) is a wireless base station in the LTE (Long Term Evolution) network and a network element of the LTE wireless access network, responsible for all functions related to the air interface. FDD (Frequency-division Duplex) mode and TDD (Time-division Duplex) mode are two duplex communication modes in mobile communications.

[0098] If the number of handover failures of the inter-frequency neighboring cell pair is high and there is a phenomenon of handover being too late, it is considered that the second handover problem type of the neighboring cell pair is handover being too late, that is, the abnormal problem is inter-frequency handover being too late. The judgment conditions for inter-frequency handover being too late include: ① The neighbor cell switching is too late and fails: The number of late switches between two specific cells is >500, and the number of late switches between two specific cells / the number of switch-out attempts between two specific cells is >50%, and the number of successful switches between two specific cells / the number of switch-out attempts between two specific cells is <95%, and the number of switch-out attempts between two specific cells - the number of successful switches between two specific cells is >500.

[0099] ② The proportion of neighboring cell handover failures to the total cell handover failures is > 20%: (Number of handover attempts between two specific cells - Number of successful handovers between two specific cells) / (Number of intra-eNodeB heterofrequency handover attempts + Number of inter-eNodeB heterofrequency handover attempts + Number of intra-eNodeB FDD / TDD mode handover attempts + Number of inter-eNodeB FDD / TDD mode handover attempts - Number of inter-eNodeB heterofrequency handover successes - Number of intra-eNodeB heterofrequency handover successes - Number of inter-eNodeB FDD / TDD mode handover successes - Number of inter-eNodeB FDD / TDD mode handover successes within the eNodeB)>20%.

[0100] In the case where the first switching problem type is intra-frequency switching failure, if the number of switching failures of the intra-frequency neighboring cell pair is high and there is a premature switching phenomenon, it is considered that the second switching problem type of the neighboring cell pair is premature switching, that is, the abnormal problem is premature intra-frequency switching. The judgment conditions for premature intra-frequency switching include: ① The neighbor cell switching is too early and fails: The number of premature switch-outs between two specific cells is >500 and the number of premature switch-outs between two specific cells / the number of switch-out attempts between two specific cells is >50% and the number of successful switch-outs between two specific cells / the number of switch-out attempts between two specific cells is <95% and the number of switch-out attempts between two specific cells - the number of successful switch-outs between two specific cells is >500.

[0101] ② The proportion of neighboring cell handover failures to the total cell handover failures is > 20%: (Number of handover attempts between two specific cells - number of successful handovers between two specific cells) / (Number of same-frequency handover attempts between eNodeBs + number of same-frequency handover attempts within an eNodeB - number of successful same-frequency handovers between eNodeBs - number of successful same-frequency handovers within an eNodeB)>20%.

[0102] If the number of handover failures of the same-frequency neighboring cell pair is high and there is a phenomenon of handover being too late, it is considered that the second handover problem type of the neighboring cell pair is handover being too late, that is, the abnormal problem is the same-frequency handover being too late. The judgment conditions for the same-frequency handover being too late include: ① The neighbor cell switching is too late and fails: The number of late switches between two specific cells is >500, and the number of late switches between two specific cells / the number of switch-out attempts between two specific cells is >50%, and the number of successful switches between two specific cells / the number of switch-out attempts between two specific cells is <95%, and the number of switch-out attempts between two specific cells - the number of successful switches between two specific cells is >500.

[0103] ②(Same-frequency handover amplitude hysteresis>1dB, or same-frequency handover offset>1dB, or same-frequency handover time hysteresis>320ms, or cell offset<-3dB.

[0104] In this implementation, by detecting the downlink frequency point, the same-frequency and different-frequency switching problems are accurately distinguished, the accuracy of identifying the switching problem is improved, and a clear direction is provided for the implementation of subsequent optimization measures. Through algorithm analysis, the problem of switching too early or too late can be accurately identified, the degree of automation of identifying the switching problem is improved, and the problem of relying on manual experience judgment and insufficient accuracy in the traditional method is solved, and the optimization efficiency is improved. Through comprehensive judgment, the specific type of the switching problem can be comprehensively and accurately identified, which provides a scientific basis for the implementation of subsequent optimization measures, significantly improves the optimization effect of the network switching problem, solves the problem of poor optimization effect in the current network switching optimization process, and improves network performance and user experience.

[0105] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 4 In step S02, the steps of executing the parameter adjustment scheme include steps S11 to S14: Step S11, constructing a parameter modification instruction library based on the parameter adjustment scheme, and for any parameter to be adjusted in the parameter modification scheme, generating and executing a parameter modification instruction for the parameter according to the parameter modification instruction library; It should be noted that, based on the switching parameter adjustment scheme, the system analyzes and identifies the parameters that need to be adjusted and their target values, and selects or generates corresponding parameter modification instructions from preset templates according to the characteristics of the parameter type, equipment manufacturer, network standard, etc., and stores them in the parameter modification instruction library. Since the parameter modification instruction library stores modification instruction templates for different parameters, different equipment manufacturers, and different network standards, it can support multiple equipment manufacturers to ensure the compatibility and accuracy of the instructions. When a parameter needs to be adjusted, the system retrieves or generates the corresponding parameter modification instructions from the parameter modification instruction library according to the requirements in the parameter adjustment scheme. By calling the OMC interface of the equipment manufacturer, the system sends the parameter modification instructions to the target device. At the same time, it records key information such as the time of issuing the instructions and the response of the equipment for subsequent result analysis and exception handling. After the network management system returns the parameter execution result, the system parses the result. The analysis content includes but is not limited to whether the parameter is successfully modified, the modified value, whether the optimization goal is achieved, etc. The system presents the analysis results to the user in an intuitive manner, such as through charts, logs, etc.

[0106] Step S12, in the case where the parameter modification instruction fails to execute, determining the type of problem that caused the execution failure; It should be noted that the system monitors the execution status of the interface in real time and detects whether there are any exceptions. If the execution fails, the exception handling process is started immediately. By analyzing the cause of the failure, the system determines the type of problem, such as execution failure caused by network fluctuations or execution failure caused by unreasonable parameter settings.

[0107] In addition, it should be noted that the system predicts the type of problem that causes execution failure through the problem analysis model. The problem analysis model is trained by historical problem types. Users can evaluate the predicted results. At the same time, the evaluation results will be fed back to the problem analysis model to improve the accuracy of the model's prediction.

[0108] Step S13: If the problem type is execution failure caused by network fluctuation, a secondary activation mechanism is implemented to resend the parameter modification instruction; It should be noted that in response to execution failures caused by network fluctuations, the system implements a secondary activation mechanism, which includes but is not limited to strategies such as resending parameter modification instructions, increasing the number of retries, and adjusting the retry interval. Through secondary activation, the system resends parameter modification instructions to try to overcome the interference caused by network fluctuations and ensure that the instructions can be successfully issued and executed.

[0109] Step S14: If the problem type is execution failure caused by unreasonable parameter setting, the decision iteration mechanism is implemented to iteratively adjust the parameters and execute the adjusted parameter adjustment plan until the parameters reach the preset range threshold.

[0110] It should be noted that in response to execution failures caused by unreasonable parameter settings, the system implements a decision-making iteration mechanism. The decision-making iteration mechanism automatically adjusts the parameter value and generates a new parameter modification plan based on the current parameter value, parameter iteration step and preset range threshold (i.e., the reasonable value range of the parameter). The system iteratively executes the adjusted parameter modification plan and continuously monitors the execution results. If the parameter value still does not reach the preset range threshold, the iterative adjustment continues; if it reaches or exceeds the preset range threshold, the iteration is stopped and the optimization is confirmed to be successful. The preset range threshold refers to the reasonable range that the parameter should reach, which is used to determine whether the parameter adjustment is successful.

[0111] In addition, it should be noted that when the number of iterative parameter adjustments reaches the preset number of adjustments, the iterative parameter adjustment is stopped and the parameter value is restored to the state before the modification or the last stable state to ensure the stability of the network and the normal use of the user.

[0112] Exemplarily, if the current abnormal problem is premature intra-frequency switching, the parameter adjusted for the parameter adjustment scheme is the offset of switching to a poor-quality cell, and the corresponding preset range threshold is -6dB. At this time, when the offset of switching to a poor-quality cell is greater than -6dB, an iteration is adjusted downward in steps of 1dB. When it is adjusted to -6dB, it is considered that the parameter value has been adjusted to the preset range threshold, and the convergence condition has been reached, and the parameter tuning process is stopped.

[0113] In this implementation, by constructing a parameter modification instruction library, the automatic generation of parameter modification instructions is achieved, which greatly improves work efficiency and accuracy. The parameter modification instruction library can support multiple equipment manufacturers to ensure the compatibility and accuracy of the instructions. By calling the equipment manufacturer's OMC interface, the parameter instructions of different equipment manufacturers are issued and executed, which solves the compatibility problem. By parsing the parameter execution results returned by the network management, instant feedback of the execution results is achieved, which provides a basis for subsequent optimization decisions. By analyzing the reasons for execution failure, accurate classification of problem types is achieved. By implementing a secondary activation mechanism, parameter modification instructions are resent, which solves the execution failure problem caused by network fluctuations. By implementing a decision iteration mechanism, parameter values ​​are iteratively adjusted until the parameters reach the preset range threshold, which solves the execution failure problem caused by unreasonable parameter settings. By iteratively adjusting parameter values, the optimal parameter configuration is gradually approached, which improves the optimization effect.

[0114] In a feasible implementation manner, in step S03, the execution result of the parameter adjustment scheme is evaluated. If the execution result is unqualified, the parameter adjustment scheme is adjusted according to the execution result, and the step of returning to execute the step of evaluating the execution result of the parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated as qualified includes steps B01 to B02: Step B01, in the short evaluation phase, if the performance index between the abnormal neighboring cell pairs deteriorates after executing the parameter modification instruction, the parameters are rolled back to the state before the parameter adjustment, and if the preset short evaluation qualification condition is met, the long evaluation phase is entered for evaluation, and if the preset short evaluation qualification condition is not met, the execution result is determined to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighboring cell pairs reaches the preset success rate; It should be noted that the short evaluation phase is mainly used to quickly determine whether the parameter adjustment plan is initially effective. After the parameter modification instruction is executed, if the basic performance indicators such as switching of poor-quality cells and their target cells deteriorate (that is, the performance becomes worse), the system will automatically trigger the parameter rollback mechanism to restore the previously adjusted parameter values ​​to the state before the parameter adjustment, so as to avoid further degradation of network performance due to incorrect parameter adjustment. After the parameter rollback, the system records the results of this adjustment and executes the next parameter optimization plan until the process ends.

[0115] In addition, it should be noted that after the parameters are successfully executed, the system will monitor the switching success rate of the cell to determine whether it meets the preset short evaluation qualification conditions. For example, if the switching success rate of the cell is greater than 95% for 4 consecutive 15-minute periods, the cell is judged to have passed the short evaluation phase and enters the long-term evaluation phase. If the cell does not meet the above conditions within 3 hours after the parameter adjustment plan is executed (that is, the switching success rate is unstable or below the standard), the cell is judged to have failed the short evaluation phase and the parameters are iteratively optimized. The system will adjust the parameters again and re-execute the evaluation process until the switching success rate reaches the preset success rate.

[0116] Step B02: In the long evaluation phase, if the preset long evaluation qualification condition is not met, the execution result is judged to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is judged to be qualified when the switching success rate between the abnormal neighboring cell pairs reaches the preset success rate.

[0117] It should be noted that the long evaluation phase is used to further verify the long-term effect of the parameter adjustment plan. Before the start of the long evaluation phase, the system will first optimize and adjust the network switching problems caused by other non-parameter reasons. After the switching problem is transferred to the root causes such as failure, coverage, interference, and neighboring areas for wireless network optimization, once the optimization measures are monitored to be completed, the system will enter the long evaluation phase for evaluation.

[0118] In addition, it should be noted that the system continuously monitors indicators such as the cell's switching success rate, call switching ratio, and VOLTE user switching success rate to determine whether the preset long-evaluation qualification conditions are met. For example, if the cell's switching success rate is greater than 95% for three consecutive days, and there are no alarms in the call switching ratio and VOLTE user switching success rate, then the cell is judged to have passed the long evaluation stage and the automatic switching optimization process ends. If the cell does not meet the above conditions (i.e., the long-term performance is unstable or below the standard), then the cell is judged to have failed the long evaluation stage and iterative optimization is performed. The system will adjust the parameters again and re-execute the evaluation process until the switching success rate reaches the preset success rate.

[0119] In this implementation, the problem of poor optimization effect existing in the current network switching problem optimization process is effectively solved by combining short evaluation and long evaluation. In the short evaluation, by monitoring the changes in performance indicators between abnormal neighboring cell pairs, it is possible to promptly discover whether parameter adjustment has brought about performance degradation or initial improvement. In the long evaluation, through continuous monitoring and evaluation for multiple days, it is possible to more accurately determine whether the adjustment plan has brought about long-term performance improvement. Through real-time monitoring and evaluation of performance indicator changes, as well as timely parameter iterative optimization, this process ensures the stability and improvement of network performance and improves the optimization efficiency of network switching problems.

[0120] In a feasible implementation, the method for handling handover problems in wireless network autonomous driving further includes steps B11-B12: Step B11, receiving abnormal cell information transmitted by the autonomous driving vehicle, wherein the abnormal cell information includes abnormally switched-out cells and switched-in cells when the autonomous driving vehicle switches networks during the autonomous driving, wherein the switched-out cell is a network cell that the autonomous driving vehicle is about to leave, and the switched-in cell is a network cell that the autonomous driving vehicle is about to enter, as recorded; It should be noted that the wireless network autonomous driving system needs to establish a stable communication connection with the autonomous driving vehicle to ensure that the vehicle can transmit data to the system in real time. When the autonomous driving vehicle encounters a problem during the network switching process, it will send a data packet containing abnormal cell information to the system. Abnormal cell information refers to the cell information corresponding to the network switching problem caused by factors such as network coverage, signal strength, interference, etc. during the driving process of the autonomous driving vehicle, including but not limited to cell ID, problem type (such as switching failure, switching delay, etc.), occurrence time, etc. After receiving this data, the system will parse it and extract key information, such as the switching out cell ID, switching in cell ID, problem type (such as switching failure, signal loss, etc.), occurrence time, etc. The switching out cell refers to the network cell where the autonomous driving vehicle is currently located and is about to leave. It is the starting point of the switching process. The switching in cell refers to the new network cell that the autonomous driving vehicle is about to enter. It is the target of the switching process. The parsed abnormal cell information will be stored in the system's database for subsequent analysis and processing. At the same time, the system will record the occurrence frequency and trend of this information to provide a reference for subsequent optimization work.

[0121] Step B12: The switching-out cell and the switching-in cell in the abnormal cell information are used as a switching abnormal neighbor cell pair.

[0122] It should be noted that after the system parses the information of the switched-out cell and the switched-in cell, it will match them as a pair of abnormal switching neighboring cell pairs and store them in the database. The abnormal switching neighboring cell pairs will be managed uniformly, including recording the time, location, cause and other information of the abnormality, so as to facilitate subsequent analysis and optimization. The abnormal switching neighboring cell pair refers to a pair of adjacent network cells where abnormal conditions occur during the network switching process.

[0123] In this implementation, by receiving abnormal cell information transmitted by the autonomous driving vehicle in real time, the system can quickly obtain abnormal situations in the network switching process, providing timely and comprehensive data support for subsequent analysis and optimization. By accurately identifying the switching-out cell (the network cell that the autonomous driving vehicle is about to leave) and the switching-in cell (the network cell that the autonomous driving vehicle is about to enter), the system can more accurately locate the location where the network switching anomaly occurs, providing precise targets for subsequent optimization measures.

[0124] For example, to help understand the technical concept or technical principle of this application, please refer to Figure 5 , Figure 5 An overall flow chart of the switching problem optimization solution is provided. First, through identification of cells with poor switching quality, abnormal cells with network switching problems are found. Then, the root cause of the cells with poor switching quality is located and the cause of the problem is analyzed, such as equipment failure, poor signal quality, insufficient network coverage, or unreasonable switching parameter settings. Then, a solution decision is made for the cells with poor switching quality. According to the result of the root cause identification, it is automatically decided which parameters to adjust and the adjustment step size, such as adjusting the switching amplitude hysteresis, switching bias, switching time hysteresis and other parameters. The parameter adjustment plan decided is automatically executed, and the parameter adjustment plan is evaluated. According to the evaluation result, the plan is iteratively optimized until the evaluation result of the parameter adjustment plan is qualified, and the optimization process is stopped.

[0125] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the method for handling switching problems in wireless network autonomous driving of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0126] The present application also provides a device for handling handover problems in wireless network autonomous driving, which is applied to a mobile communication system. The mobile communication system includes various network cells. Please refer to Figure 6 ,The switching problem processing device in wireless network automatic driving includes: The problem determination module 10 is used to determine each abnormal neighboring cell pair in each network cell, and for any pair of abnormal neighboring cell pairs among the abnormal neighboring cell pairs, identify the abnormal problem of the abnormal neighboring cell pair, wherein each abnormal neighboring cell pair includes each switching abnormal neighboring cell pair; A scheme generating module 20 is used to determine the parameters to be adjusted for the abnormal neighboring area and the content of the parameter adjustment according to the abnormal problem, obtain the parameter adjustment scheme, and execute the parameter adjustment scheme; The evaluation feedback module 30 is used to evaluate the execution result of the parameter adjustment scheme. When the execution result is unqualified, the parameter adjustment scheme is adjusted according to the execution result, and the step of evaluating the execution result of the parameter adjustment scheme is returned based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated to be qualified.

[0127] Optionally, the problem determination module 10 is further used to: Determine the alarm cells that meet the preset alarm triggering rules in each network cell and the degradation time inflection point of the alarm cell; The average value of each switching index of the preset number of days before the degradation time inflection point is used as the dynamic threshold, and the trend analysis of each switching index at the degradation time inflection point is performed according to the dynamic threshold to determine whether the alarm cell is a cell with poor switching quality; The target cells associated with the handover poor quality cell are identified, and the abnormal neighboring cell pairs are determined. The abnormal neighboring cell pairs are obtained by combining the handover poor quality cell and the target cell.

[0128] Optionally, the abnormal problem includes early inter-frequency switching, late inter-frequency switching, early intra-frequency switching, and late intra-frequency switching. The solution generation module 20 is further used to: In the case where the abnormal problem is premature inter-frequency switching, the offset of the poor quality cell is adjusted according to the difference between the offset of the poor quality cell and the offset of the target cell, and the switching decision threshold of the target cell and the switching decision threshold of the poor quality cell are adjusted according to the type of inter-frequency switching trigger event of the abnormal neighboring cell pair; When the abnormal problem is that the inter-frequency handover is too late, the offset of the poor quality cell and the offset of the target cell are adjusted, and the handover decision threshold of the target cell and the handover decision threshold of the poor quality cell are adjusted according to the type of inter-frequency handover triggering event of the abnormal neighboring cell pair; When the abnormal problem is premature intra-frequency switching, adjust the offset of the poor quality cell, intra-frequency switching time delay, intra-frequency switching amplitude delay, and intra-frequency switching bias; When the abnormal problem is that the intra-frequency switching is too late, adjust the offset of the target cell and the offset of the switching poor quality cell, the intra-frequency switching time delay, the intra-frequency switching amplitude hysteresis, and the intra-frequency switching bias.

[0129] Optionally, the problem determination module 10 is further used to: Detecting the downlink frequency of the abnormal neighboring cell pair, determining the first switching problem type between the abnormal neighboring cell pair, the first switching problem type including the same-frequency switching failure and the different-frequency switching failure; Collecting handover performance indicator data of abnormal neighboring cell pairs, and analyzing the handover performance indicator data based on a parameter root cause identification algorithm to determine a second handover problem type between the abnormal neighboring cell pairs, the second handover problem type including premature handover and late handover; The abnormal problems between abnormal neighboring cell pairs are determined in combination with the first switching problem type and the second switching problem type. The abnormal problems include early heterofrequency switching, late heterofrequency switching, early intrafrequency switching, and late intrafrequency switching.

[0130] Optionally, the solution generation module 20 is further used to: A parameter modification instruction library is constructed based on the parameter adjustment scheme. For any parameter to be adjusted in the parameter modification scheme, a parameter modification instruction of the parameter is generated and executed according to the parameter modification instruction library. In the case of failure in executing a parameter modification instruction, determine the type of problem that caused the execution failure; If the problem type is execution failure caused by network fluctuation, a secondary activation mechanism is implemented to resend the parameter modification instruction; If the problem type is execution failure caused by unreasonable parameter settings, the decision iteration mechanism is implemented to iteratively adjust the parameters and execute the adjusted parameter adjustment plan until the parameters reach the preset range threshold.

[0131] Optionally, the evaluation feedback module 30 is further used to: In the short evaluation phase, if the performance indicators between the abnormal neighboring cell pairs deteriorate after executing the parameter modification instruction, the parameters are rolled back to the state before the parameter adjustment. If the preset short evaluation qualification conditions are met, the long evaluation phase is entered for evaluation. If the preset short evaluation qualification conditions are not met, the execution result is determined to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighboring cell pairs reaches the preset success rate; In the long evaluation phase, if the preset long evaluation qualification conditions are not met, the execution result is judged to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is judged to be qualified when the switching success rate between the abnormal neighboring cell pairs reaches the preset success rate.

[0132] Optionally, the switching problem processing device in wireless network autonomous driving further includes a receiving processing module 40, and the receiving processing module 40 is further used to: Receive abnormal cell information transmitted by autonomous driving vehicles; Determine the network cell in each network cell where an abnormality occurs during network switching according to the abnormal cell information, and determine a parameter adjustment plan for the network cell; Execute the parameter adjustment plan and adjust the parameter adjustment plan according to the feedback of the execution results until the execution results of the parameter adjustment plan are evaluated as qualified.

[0133] The handover problem processing device in wireless network autonomous driving provided by the present application adopts the handover problem processing method in wireless network autonomous driving in the above embodiment, which can solve the technical problem of poor optimization effect in the current network handover problem optimization process. Compared with the prior art, the beneficial effects of the handover problem processing device in wireless network autonomous driving provided by the present application are the same as the beneficial effects of the handover problem processing method in wireless network autonomous driving provided by the above embodiment, and the other technical features of the handover problem processing device in wireless network autonomous driving are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0134] The present application provides an electronic device, the electronic device comprising: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for handling switching problems in wireless network autonomous driving in the above-mentioned embodiment 1.

[0135] Reference below Figure 7 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic device in the embodiments of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, PADs (Portable Application Description: tablet computers), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0136] like Figure 7As shown, the electronic device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory 1002 or the program loaded from the storage device 1003 to the random access memory 1004. In the random access memory 1004, various programs and data required for the operation of the electronic device are also stored. The processing device 1001, the read-only memory 1002 and the random access memory 1004 are connected to each other through a bus 1005. The input / output interface 1006 is also connected to the bus. Generally, the following systems can be connected to the input / output interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a microphone, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the electronic device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have instead.

[0137] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above functions defined in the method of the embodiment disclosed in the present application are executed.

[0138] The electronic device provided by this application adopts the handover problem processing method in wireless network autonomous driving in the above embodiment, which can solve the technical problem of poor optimization effect in the current network handover problem optimization process. Compared with the prior art, the beneficial effects of the electronic device provided by this application are the same as the beneficial effects of the handover problem processing method in wireless network autonomous driving provided by the above embodiment, and the other technical features in the electronic device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0139] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0140] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0141] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the method for handling switching problems in wireless network autonomous driving in the above-mentioned embodiment.

[0142] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0143] The computer-readable storage medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0144] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by an electronic device, the switching problem processing device in wireless network automatic driving is applied to a mobile communication system. The mobile communication system includes each network cell, and each abnormal neighboring cell pair in each network cell can be determined. For any pair of abnormal neighboring cell pairs in each abnormal neighboring cell pair, the abnormal problem of the abnormal neighboring cell pair is identified, wherein each abnormal neighboring cell pair includes each switching abnormal neighboring cell pair; according to the abnormal problem, the parameters to be adjusted for the abnormal neighboring cell pair and the adjustment content of the parameters are determined to obtain a parameter adjustment plan, and the parameter adjustment plan is executed; the execution result of the parameter adjustment plan is evaluated, and when the execution result is unqualified, the parameter adjustment plan is adjusted according to the execution result, and based on the adjusted parameter plan, the step of executing the evaluation result of the parameter adjustment plan is returned until the execution result of the parameter adjustment plan is evaluated as qualified.

[0145] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0146] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a portion of a code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified functions or operations, or can be implemented with a combination of dedicated hardware and computer instructions.

[0147] The modules involved in the embodiments described in this application can be implemented by software or hardware. The name of the module does not constitute a limitation on the unit itself in some cases.

[0148] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned method for handling switching problems in wireless network autonomous driving, and can solve the technical problem of poor optimization effect in the current network switching problem optimization process. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the method for handling switching problems in wireless network autonomous driving provided in the above-mentioned embodiment, and will not be repeated here.

[0149] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for handling switching problems in wireless network autonomous driving.

[0150] The computer program product provided by this application can solve the technical problem of poor optimization effect in the current network switching problem optimization process. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the switching problem processing method in wireless network automatic driving provided by the above embodiment, and will not be repeated here.

[0151] The above descriptions are only some embodiments of the present application, and do not limit the patent scope of the present application. All equivalent structural transformations made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for handling handover problems in wireless network autonomous driving, characterized in that , applied to a mobile communication system, the mobile communication system includes various network cells, and the method for handling handover problems in wireless network autonomous driving includes: Determine each abnormal neighboring cell pair in each network cell, and for any pair of abnormal neighboring cell pairs among the abnormal neighboring cell pairs, identify an abnormal problem of the abnormal neighboring cell pair, wherein the abnormal neighboring cell pairs include each switching abnormal neighboring cell pair; Determine the parameters of the abnormal neighboring area to be adjusted and the adjustment content of the parameters according to the abnormal problem, obtain a parameter adjustment plan, and execute the parameter adjustment plan; Evaluate the execution result of the parameter adjustment scheme, and if the execution result is unqualified, adjust the parameter adjustment scheme according to the execution result, and return to the step of evaluating the execution result of the parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated to be qualified.

2. The method for handling handover problems in wireless network autonomous driving according to claim 1, characterized in that , the step of determining abnormal neighboring cell pairs in each network cell includes: Determine the alarm cells that meet the preset alarm triggering rules in each network cell and the degradation time inflection point of the alarm cell; The average value of each switching indicator of the preset number of days before the degradation time inflection point is used as a dynamic threshold, and the trend analysis of each switching indicator at the degradation time inflection point is performed according to the dynamic threshold to determine whether the warning cell is a cell with poor switching quality; Identify each target cell associated with the handover poor quality cell, and determine each abnormal neighboring cell pair, wherein the abnormal neighboring cell pair is obtained by combining the handover poor quality cell and the target cell.

3. The method for handling handover problems in wireless network autonomous driving as claimed in claim 2, characterized in that The abnormal problems include early inter-frequency switching, late inter-frequency switching, early intra-frequency switching, and late intra-frequency switching. The step of determining the parameters to be adjusted for the abnormal neighboring cell pair and the adjustment content of the parameters according to the abnormal problems includes: In the case where the abnormal problem is premature inter-frequency switching, adjusting the offset of the switching poor-quality cell according to the difference between the offset of the switching poor-quality cell and the offset of the target cell, and adjusting the switching decision threshold of the target cell and the switching decision threshold of the switching poor-quality cell according to the type of inter-frequency switching trigger event of the abnormal neighboring cell pair; In the case where the abnormal problem is that the inter-frequency handover is too late, adjusting the offset of the handover poor quality cell and the offset of the target cell, and adjusting the handover decision threshold of the target cell and the handover decision threshold of the handover poor quality cell according to the type of inter-frequency handover triggering event of the abnormal neighboring cell pair; When the abnormal problem is premature intra-frequency switching, adjust the offset of the switching poor quality cell, intra-frequency switching time hysteresis, intra-frequency switching amplitude hysteresis, and intra-frequency switching bias; When the abnormal problem is that the intra-frequency switching is too late, adjust the offset of the target cell and the offset of the switching poor quality cell, the intra-frequency switching time delay, the intra-frequency switching amplitude delay, and the intra-frequency switching bias.

4. The method for handling handover problems in wireless network autonomous driving as claimed in claim 3, characterized in that ,The step of identifying the abnormal problem of the abnormal neighboring area pair includes: Detecting the downlink frequency of the abnormal neighboring cell pair, and determining a first switching problem type between the abnormal neighboring cell pair, wherein the first switching problem type includes a same-frequency switching failure and an inter-frequency switching failure; Collecting handover performance indicator data of the abnormal neighboring cell pair, and analyzing the handover performance indicator data based on a parameter root cause identification algorithm to determine a second handover problem type between the abnormal neighboring cell pair, where the second handover problem type includes handover too early and handover too late; In combination with the first switching problem type and the second switching problem type, the abnormal problems between the abnormal neighboring cell pairs are determined, and the abnormal problems include early inter-frequency switching, late inter-frequency switching, early intra-frequency switching, and late intra-frequency switching.

5. The method for handling handover problems in wireless network autonomous driving as claimed in claim 1, characterized in that , the step of executing the parameter adjustment scheme includes: Building a parameter modification instruction library based on the parameter adjustment scheme, and for any parameter to be adjusted in the parameter modification scheme, generating and executing a parameter modification instruction for the parameter according to the parameter modification instruction library; In the event that the parameter modification instruction fails to execute, determining the type of problem that caused the execution failure; If the problem type is execution failure caused by network fluctuation, a secondary activation mechanism is implemented to resend the parameter modification instruction; If the problem type is execution failure caused by unreasonable parameter setting, a decision iteration mechanism is implemented to iteratively adjust the parameters and execute the adjusted parameter adjustment plan until the parameters reach a preset range threshold.

6. The method for handling handover problems in wireless network autonomous driving as claimed in claim 5, characterized in that , the step of evaluating the execution result of the parameter adjustment scheme, adjusting the parameter adjustment scheme according to the execution result when the execution result is unqualified, and returning to the step of evaluating the execution result of the parameter adjustment scheme based on the adjusted parameter scheme until the execution result of the parameter adjustment scheme is evaluated as qualified includes: In the short evaluation phase, if the performance index between the abnormal neighboring cell pairs deteriorates after executing the parameter modification instruction, the parameters are rolled back to the state before the parameter adjustment, and if the preset short evaluation qualification condition is met, the long evaluation phase is entered for evaluation, and if the preset short evaluation qualification condition is not met, the execution result is determined to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighboring cell pairs reaches the preset success rate; In the long evaluation phase, if the preset long evaluation qualification condition is not met, the execution result is judged to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment scheme is executed and evaluated, and the evaluation result is judged to be qualified when the switching success rate between the abnormal neighboring cell pairs reaches a preset success rate.

7. The method for handling handover problems in wireless network autonomous driving according to claim 1, characterized in that ,The method for handling switching problems in wireless network autonomous driving also includes: Receiving abnormal cell information transmitted by the autonomous driving vehicle, wherein the abnormal cell information includes an abnormally switched-out cell and switched-in cell when the autonomous driving vehicle switches networks during autonomous driving, the switched-out cell is a network cell that the autonomous driving vehicle is about to leave, and the switched-in cell is a network cell that the autonomous driving vehicle is about to enter, as recorded; The switching-out cell and the switching-in cell in the abnormal cell information are used as a switching abnormal neighbor cell pair.

8. An electronic device, characterized in that The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for handling handover problems in wireless network autonomous driving as described in any one of claims 1 to 7.

9. A storage medium, characterized in that , the storage medium is a computer-readable storage medium, a computer program is stored on the storage medium, and when the computer program is executed by the processor, the steps of the method for handling switching problems in wireless network autonomous driving are implemented as described in any one of claims 1 to 7.

10. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the method for handling switching problems in wireless network autonomous driving are implemented as described in any one of claims 1 to 7.

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