Method for Handling Handover Problems in Wireless Network Autonomous Driving

Abstract

The present application discloses a method for handling handover problems in wireless network autonomous driving, which relates to the field of wireless communication technologies and is applied to a mobile communication system. The mobile communication system includes each network cell, and the method includes: determining each abnormal neighboring cell pair in each network cell; for any one of the abnormal neighboring cell pairs in each abnormal neighboring cell pair, identifying its abnormal problem, where each abnormal neighboring cell pair includes each handover abnormal neighboring cell pair; determining the parameter to be adjusted for the abnormal neighboring cell pair and the adjustment content of the parameter according to the abnormal problem, obtaining a parameter adjustment plan and executing it; evaluating the execution result of the parameter adjustment plan, and in the case where 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. The present application solves the technical problem of poor optimization effect in the current network handover problem optimization process.

Description

Technical Field

[0001] This application relates to the field of wireless communication technologies, and particularly to a method, apparatus, electronic device, storage medium, and computer program product for handling handover 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 handover is required. This handover process is jointly completed by the network side and the mobile device carried by the vehicle and is achieved through a series of signaling interactions. However, during the interaction process, due to various reasons such as device failures, poor signal quality, insufficient network coverage, and software parameter configuration, handover failure problems may occur, which not only affect the user experience but may even endanger the user's life safety. Therefore, maintaining a good and stable wireless network handover is crucial.

[0003] To maintain a good and stable wireless network handover, it is necessary to solve the handover problems existing in the wireless network handover process. The existing handover problem optimization process usually relies on the personal experience of network optimization personnel to analyze and troubleshoot the problems existing in network handover. It not only takes a long time, has high costs, but also has low efficiency, and the optimization effects vary from person to person and cannot be guaranteed. Therefore, there is a problem of poor optimization effect in the current network handover problem optimization process. Summary of the Invention

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

[0005] To achieve the above objective, this application proposes a method for handling handover problems in wireless network autonomous driving, which is applied to a mobile communication system. The mobile communication system includes each network cell. The method for handling handover problems in wireless network autonomous driving includes:

[0006] Determine each abnormal neighbor cell pair in each network cell. For any abnormal neighbor cell pair among each abnormal neighbor cell pair, identify the abnormal problem of the abnormal neighbor cell pair, where each abnormal neighbor cell pair includes each handover abnormal neighbor cell pair;

[0007] Determine the parameters to be adjusted for the abnormal neighbor cell pair and the adjustment content of the parameters according to the abnormal problem, obtain a parameter adjustment plan, and execute the parameter adjustment plan;

[0008] Evaluate the execution result of the parameter adjustment scheme. When 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 as qualified.

[0009] In one embodiment, the step of determining the abnormal neighbor cell pairs in each network cell includes:

[0010] Determine the alarm cells in each network cell that meet the preset alarm trigger rule and the inflection point of the deterioration time of the alarm cells;

[0011] Take the average value of each handover metric in the preset number of days before the inflection point of the deterioration time as the dynamic threshold, and perform a trend analysis on each handover metric at the inflection point of the deterioration time according to the dynamic threshold to determine whether the alarm cell is a handover quality degradation cell;

[0012] Identify each target cell associated with the handover quality degradation cell, and determine each abnormal neighbor cell pair, where the abnormal neighbor cell pair is obtained by combining the handover quality degradation cell and the target cell.

[0013] In one embodiment, the abnormal problems include premature inter-frequency handover, late inter-frequency handover, premature intra-frequency handover, and late intra-frequency handover. The step of determining the parameters to be adjusted for the abnormal neighbor cell pair and the adjustment content of the parameters according to the abnormal problems includes:

[0014] When the abnormal problem is premature inter-frequency handover, adjust the offset of the handover quality degradation cell according to the difference between the offset of the handover quality degradation 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 handover quality degradation cell according to the inter-frequency handover trigger event type of the abnormal neighbor cell pair;

[0015] When the abnormal problem is late inter-frequency handover, adjust the offset of the handover quality degradation 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 handover quality degradation cell according to the inter-frequency handover trigger event type of the abnormal neighbor cell pair;

[0016] When the abnormal problem is premature intra-frequency handover, adjust the offset of the handover quality degradation cell, the intra-frequency handover time hysteresis, the intra-frequency handover amplitude hysteresis, and the intra-frequency handover offset;

[0017] When the abnormal problem is late intra-frequency handover, adjust the offset of the target cell and the offset of the handover quality degradation cell, the intra-frequency handover time hysteresis, the intra-frequency handover amplitude hysteresis, and the intra-frequency handover offset.

[0018] In one embodiment, the step of identifying the abnormal problem of the abnormal neighboring cell pair includes:

[0019] Detect the downlink frequency points of the abnormal neighboring cell pair, and determine the first handover problem type between the abnormal neighboring cell pairs. The first handover problem type includes intra-frequency handover failure and inter-frequency handover failure;

[0020] Collect the handover performance metric data of the abnormal neighboring cell pair, and analyze the handover performance metric data based on the parameter root cause identification algorithm to determine the second handover problem type between the abnormal neighboring cell pairs. The second handover problem type includes premature handover and late handover;

[0021] Combine the first handover problem type and the second handover problem type to determine the abnormal problem between the abnormal neighboring cell pairs. The abnormal problem includes premature inter-frequency handover, late inter-frequency handover, premature intra-frequency handover, and late intra-frequency handover.

[0022] In one embodiment, the step of executing the parameter adjustment scheme includes:

[0023] Construct a parameter modification instruction library based on the parameter adjustment scheme. For any parameter to be adjusted in the parameter modification scheme, generate a parameter modification instruction for the parameter according to the parameter modification instruction library and execute it;

[0024] In the case where the execution of the parameter modification instruction fails, determine the problem type that causes the execution failure;

[0025] If the problem type is the execution failure caused by network fluctuation, implement a secondary activation mechanism and resend the parameter modification instruction;

[0026] If the problem type is the execution failure caused by unreasonable parameter settings, implement a decision iteration mechanism, iteratively adjust the parameter, and execute the adjusted parameter adjustment scheme until the parameter reaches the preset range threshold.

[0027] In one embodiment, the step of evaluating the execution result of the parameter adjustment scheme, in the case where the execution result is unqualified, adjusting the parameter adjustment scheme according to the execution result, and based on the adjusted parameter scheme, returning to the step of evaluating the execution result of the parameter adjustment scheme until the execution result of the parameter adjustment scheme is evaluated as qualified includes:

[0028] In the short evaluation stage, if the performance index between the abnormal neighbor cell pairs deteriorates after executing the parameter modification instruction, the parameter is rolled back to the state before the parameter adjustment. If the preset short evaluation qualification condition is met, the long evaluation stage is entered for evaluation. If the preset short evaluation qualification condition is not met, the execution result is determined to be unqualified, the parameter is iteratively adjusted, the adjusted parameter adjustment plan is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighbor cell pairs reaches the preset success rate;

[0029] In the long evaluation stage, if the preset long evaluation qualification condition is not met, the execution result is determined to be unqualified, the parameter is iteratively adjusted, the adjusted parameter adjustment plan is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighbor cell pairs reaches the preset success rate.

[0030] In one embodiment, the method for handling handover problems in the wireless network autonomous driving further includes:

[0031] Receiving abnormal cell information transmitted by the autonomous driving vehicle, where the abnormal cell information includes the handover-out cell and the handover-in cell that are abnormal when the autonomous driving vehicle performs network handover during autonomous driving. The handover-out cell is the network cell that the autonomous driving vehicle records as about to leave, and the handover-in cell is the network cell that the autonomous driving vehicle records as about to enter;

[0032] Taking the handover-out cell and the handover-in cell in the abnormal cell information as a handover abnormal neighbor cell pair.

[0033] In addition, to achieve the above object, the present application also proposes a device for handling handover problems in wireless network autonomous driving, which is applied to a mobile communication system. The mobile communication system includes each network cell. The device for handling handover problems in wireless network autonomous driving includes:

[0034] A problem determination module, configured to determine each abnormal neighbor cell pair in each network cell, and for any one of the abnormal neighbor cell pairs in each abnormal neighbor cell pair, identify the abnormal problem of the abnormal neighbor cell pair, where each abnormal neighbor cell pair includes each network cell that is abnormal during network handover in autonomous driving;

[0035] A scheme generation module, configured to determine the parameter to be adjusted for the abnormal neighbor cell pair and the adjustment content of the parameter according to the abnormal problem, obtain a parameter adjustment plan, and execute the parameter adjustment plan;

[0036] An evaluation feedback module is used to evaluate the execution result of the parameter adjustment plan. In the case where the execution result is unqualified, the parameter adjustment plan is adjusted according to the execution result, and the steps of evaluating the execution result of the parameter adjustment plan are returned based on the adjusted parameter plan until the execution result of the parameter adjustment plan is evaluated as qualified.

[0037] In addition, to achieve the above object, the present application also proposes an electronic device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the method for handling handover problems in wireless network autonomous driving as described above.

[0038] In addition, to achieve the above object, 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, and when the computer program is executed by a processor, the steps of the method for handling handover problems in wireless network autonomous driving as described above are implemented.

[0039] In addition, to achieve the above object, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the method for handling handover problems in wireless network autonomous driving as described above are implemented.

[0040] The present application provides a method for handling handover problems in wireless network autonomous driving, which is applied to a mobile communication system. The mobile communication system includes each network cell. The method for handling handover problems in wireless network autonomous driving includes: determining each abnormal neighboring cell pair in each network cell, and for any one of the abnormal neighboring cell pairs in each abnormal neighboring cell pair, identifying the abnormal problem of the abnormal neighboring cell pair, where each abnormal neighboring cell pair includes each handover abnormal neighboring cell pair; determining the parameters to be adjusted for the abnormal neighboring cell pair and the adjustment content of the parameters according to the abnormal problem, obtaining a parameter adjustment plan, and executing the parameter adjustment plan; evaluating the execution result of the parameter adjustment plan, and in the case where the execution result is unqualified, adjusting the parameter adjustment plan according to the execution result, and returning the steps 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.

[0041] This 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 pairs that may cause handover problems, reduces the interference of human factors, improves the accuracy and efficiency of identification. For each identified pair of abnormal neighboring cell pairs, it further identifies the abnormal problems between them, determines the parameters to be adjusted and the adjustment content of the parameters according to these problems, forms a parameter adjustment plan, and executes the plan. It can perform parameter adjustment according to the specific situation of the abnormal problems, improves the pertinence and effectiveness of the adjustment. By evaluating the execution result of the parameter adjustment plan, if the evaluation result is unqualified, the parameter adjustment plan is adjusted according to the execution result, and the evaluation step is re-executed until the execution result evaluation is qualified, realizing continuous evaluation and feedback adjustment. It can adjust the parameter adjustment plan according to the feedback result, ensuring the effectiveness of the parameter adjustment plan and improving the optimization effect. Compared with the related solutions that rely on the personal experience of network optimization personnel, not only the troubleshooting period is long, the problem location cannot be quickly determined, but also effective optimization improvements may not be made for the located problems. This application uses automatic optimization of handover problems such as problem identification, root cause location, solution decision-making, automatic execution, and automatic evaluation. Through automatic processing, it greatly shortens the time for problem discovery and solution. At the same time, it reduces the dependence on manual labor, and through intelligent decision-making and execution, the optimization plan is more accurate and the effect is more obvious, thus making the network handover in autonomous driving more stable, reducing communication interruptions caused by handover failures, and enhancing the user's network perception experience in autonomous driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0044] Figure 1 It is a flowchart provided for the first embodiment of the handover problem processing method in the wireless network autonomous driving of the present application;

[0045] Figure 2 It is an iterative flowchart of the inter-frequency handover too early algorithm provided for the handover problem processing method in the wireless network autonomous driving of the present application;

[0046] Figure 3 It is an iterative flowchart of the inter-frequency handover too late algorithm provided for the handover problem processing method in the wireless network autonomous driving of the present application;

[0047] Figure 4 It is a schematic flowchart provided for the second embodiment of the method for handling handover problems in the wireless network automatic driving of the present application;

[0048] Figure 5 It is an overall flowchart of the handover problem optimization solution provided for the method for handling handover problems in the wireless network automatic driving of the present application;

[0049] Figure 6 It is a schematic diagram of the module structure of the handover problem handling device in the wireless network automatic driving of the embodiment of the present application;

[0050] Figure 7 It is a schematic diagram of the device structure of the hardware operating environment involved in the method for handling handover problems in the wireless network automatic driving of the embodiment of the present application.

[0051] The realization of the purpose, functional characteristics and advantages of the present application will be further described in combination with the embodiments with reference to the accompanying drawings. Specific embodiments

[0052] 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.

[0053] In order to better understand the technical solutions of the present application, the following will be described in detail in combination with the accompanying drawings of the specification and specific embodiments.

[0054] The embodiments of the present application are applied to a mobile communication system. The mobile communication system includes each network cell. The main solution is: determine each abnormal neighboring cell pair in each network cell, and for any one of the abnormal neighboring cell pairs in each abnormal neighboring cell pair, identify the abnormal problem of the abnormal neighboring cell pair, where each abnormal neighboring cell pair includes each handover abnormal neighboring cell pair; determine the parameters to be adjusted for the abnormal neighboring cell pair 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 plan. In the case where the execution result is unqualified, adjust the parameter adjustment plan according to the execution result, and return 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.

[0055] In this embodiment, for the convenience of description, the following will be described with the handover problem handling system as the execution subject.

[0056] In a mobile communication system, since the 4G technology adopts a cellular network structure, when it is applied to autonomous driving, network switching is required when a vehicle moves across cells. However, due to reasons such as equipment failure, poor signal, insufficient coverage, and software configuration, the handover may fail, affecting the user experience and life safety. Therefore, it is crucial to maintain a good and stable wireless network handover. The optimization of existing handover problems often relies on the experience of network optimization personnel, resulting in problems such as long cycles and low efficiency. Moreover, operators have to invest a large amount of manpower, material resources, and financial resources every year to carry out this work, which not only causes a large amount of cost consumption, but also the optimization effect of handover problems is not ideal.

[0057] This application provides a solution. Through automatic problem identification, automatic root cause location, automatic solution decision-making, automatic execution, and automatic evaluation, an end-to-end closed-loop automatic optimization system for handover problems is realized, and a handover parameter decision-execution-evaluation-decision iterative feedback optimization mechanism is used to effectively improve the optimization ability of parameter optimization solutions, effectively eliminating the problems of large randomness, low efficiency, and inability to guarantee the optimization effect in the optimization of existing handover problems by relying on manual experience, improving the optimization effect of wireless network handover problems, and thus improving the user experience in autonomous driving.

[0058] 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, a handover problem processing system, etc. that can implement the above functions. Hereinafter, taking the handover problem processing system as an example, this embodiment and the following embodiments will be described.

[0059] Based on this, the embodiment of this application provides a method for processing handover problems in wireless network autonomous driving, referring to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of the method for processing handover problems in wireless network autonomous driving of this application.

[0060] In this embodiment, it is applied to a mobile communication system, which includes each network cell. The method for processing handover problems in wireless network autonomous driving includes steps S01 to S03:

[0061] Step S01, determine each abnormal neighbor cell pair in each network cell. For any abnormal neighbor cell pair in each abnormal neighbor cell pair, identify the abnormal problem of the abnormal neighbor cell pair, where each abnormal neighbor cell pair includes each handover abnormal neighbor cell pair;

[0062] 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 an autonomous vehicle moves between these cells, in order to ensure the continuity and stability of communication, network handover 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 handover process, resulting in handover failure or performance degradation. Therefore, it is necessary to determine which neighbor cell pairs (i.e., two adjacent cells) have abnormal handovers and further identify the specific problems between these abnormal neighbor cell pairs.

[0063] Additionally, it should be noted that by deeply analyzing the network handover data (such as key indicators like handover success rate, handover failure rate, signal strength, signal quality, etc.) and comparing the data characteristics of normal handovers and abnormal handovers, each abnormal neighbor cell pair and potential abnormal problems can be identified. An abnormal neighbor cell pair refers to the combination of two adjacent cells that have abnormal handovers during the network handover process, including handover abnormal neighbor cell pairs, that is, each network cell with abnormal handovers during network handover in autonomous driving. It can also include each network cell with network handover problems in scenarios such as smart homes and smart cities. An abnormal problem refers to the specific problem that causes handover failure or performance degradation, such as signal interference, coverage blind spots, improper handover parameter settings, etc.

[0064] It can be understood that since existing solutions often rely on network optimization personnel to manually analyze network logs and data to identify abnormal handover areas, this method is time-consuming and laborious, and is easily affected by personal experience, with inaccurate positioning. Therefore, step S01 is carried out. Through automated monitoring and analysis, the handover data of each network cell is monitored in real time to quickly and accurately determine abnormal neighbor cell pairs, and the network handover data between abnormal neighbor cell pairs is analyzed by algorithms to accurately judge the specific reasons for handover failure, such as equipment failure, poor signal quality, insufficient network coverage, etc. This not only improves the positioning speed but also ensures the accuracy of positioning.

[0065] Step S02, determine the parameters to be adjusted for the abnormal neighbor cell pair according to the abnormal problem and the adjustment content of the parameters, obtain a parameter adjustment plan, and execute the parameter adjustment plan;

[0066] It should be noted that once the abnormal neighboring cell pairs and their existing abnormal problems are determined, the next step is to formulate a targeted parameter adjustment plan. The parameter adjustment plan refers to a parameter adjustment plan formulated according to the abnormal problems and aimed at optimizing the network handover performance. The system determines the network parameters to be adjusted (such as the same-frequency handover amplitude hysteresis, the different-frequency A3 offset, the cell offset, etc.) and the specific adjustment content according to the type of abnormal problems. The adjustment content is the specific content of the parameter adjustment plan determined for the abnormal problems, such as adjusting the cell offset, increasing the different-frequency A3 offset, etc. After formulating the parameter adjustment plan, it is necessary to execute these adjustments and monitor the changes in the network performance after the adjustment.

[0067] It can be understood that since the network optimization personnel in the existing solutions often manually adjust the network parameters based on experience, lacking a scientific basis and with the adjustment effect being difficult to predict, so step S02 is carried out. According to the abnormal problems identified in step S01, the parameters to be adjusted and their adjustment content are automatically recommended, and these adjustment plans are automatically executed without manual intervention, which not only improves the adjustment efficiency but also ensures the scientificity and accuracy of the adjustment.

[0068] Step S03, evaluate the execution result of the parameter adjustment plan. In the case where the execution result is unqualified, adjust the parameter adjustment plan according to the execution result, and return to the step of evaluating the execution result of the adjusted parameter plan until the execution result of the parameter adjustment plan is evaluated as qualified.

[0069] It should be noted that after executing the parameter adjustment plan, it is necessary to continuously monitor and evaluate the handover performance in the execution result to determine whether the adjustment is effective. The evaluation indicators include the handover success rate, the handover failure rate, the signal strength stability, the user satisfaction, etc. If the evaluation result shows that the parameter adjustment plan fails to achieve the expected effect (that is, the execution result is unqualified), then the parameter adjustment plan needs to be adjusted according to the evaluation result, and the evaluation step is re-executed. This process needs to be iterated multiple times until the optimal parameter configuration is found to make the handover performance reach a satisfactory standard.

[0070] It can be understood that since the network optimization personnel in the existing solutions usually manually evaluate the adjustment effect and manually adjust the parameters according to the evaluation result, lacking persistence and systematicness, it is difficult to continuously guarantee the optimization effect. So step S03 is carried out. By continuously monitoring the handover performance data, the execution result of the parameter adjustment plan is automatically evaluated. If the evaluation result is unqualified (that is, the handover problem still exists or the improvement is not obvious), then the parameter adjustment plan is automatically adjusted according to the evaluation result, and the evaluation step is re-executed until the handover performance reaches a satisfactory standard, which not only improves the evaluation efficiency but also ensures the persistence and reliability of the optimization.

[0071] In a feasible implementation, in step S01, the steps of determining abnormal neighbor cell pairs in each network cell include steps A01 to A03:

[0072] Step A01, determining the warning cells in each network cell that meet the preset warning trigger rule and the deterioration time inflection point of the warning cells;

[0073] It should be noted that for any network cell in each network cell, based on the preset warning trigger rule, judge the gear in which the handover attempt times are located. The handover attempt times refer to the number of requests for network handover between the current network cell and other network cells. According to the corresponding gear of the handover attempt times, compare whether the deterioration ratio of the handover success rate, the deterioration value of the handover success rate, and the deterioration value of the failure times of the network cell reach the corresponding thresholds. When each index reaches the corresponding threshold, it is determined that the current network cell meets the preset warning trigger rule and is determined as a warning cell.

[0074] In addition, after determining the warning cell, it is necessary to determine the deterioration time inflection point of the warning cell, that is, the time point when its performance begins to decline significantly. The system analyzes the historical data of the warning cell to find the time point when its performance index first deteriorates, that is, the time node when its handover performance index changes from the normal state to the abnormal state, and records this time point as the deterioration time inflection point.

[0075] Exemplarily, the preset warning trigger rule is shown in Table 1. When the handover attempt times of the network cell are 2000 times, it means that the corresponding gear of the current network cell is gear 3. If it is detected that the deterioration ratio of the handover success rate of the current network cell reaches 0.9, the deterioration value of the handover success rate reaches 10% and the deterioration value of the failure times reaches 50, it is determined that the current network cell is a warning cell.

[0076] Table 1

[0077]

[0078] Step A02, taking the average value of each handover index in the preset number of days before the deterioration time inflection point as the dynamic threshold, and performing a trend analysis on each handover index at the deterioration time inflection point according to the dynamic threshold to determine whether the warning cell is a handover quality poor cell;

[0079] It should be noted that before the deterioration time inflection point, a preset number of days (such as 15 days) is selected as the analysis basis to calculate the average value of the handover metrics. Within the preset number of days, the average value of the handover metrics of the network cells is extracted based on the outlier detection algorithm, including but not limited to the average values of key metrics such as handover success rate and failure times, and a dynamic threshold, that is, a dynamic threshold, is set according to the average value of the handover metrics within the preset number of days. This dynamic threshold reflects the normal performance level of the cell before deterioration and is used to determine whether the handover performance metrics at the deterioration time inflection point are abnormally fluctuating.

[0080] In addition, it should be noted that by trend analysis, the handover performance metrics at the deterioration time inflection point are compared with the dynamic threshold, the change trends of these metrics are analyzed, and it is determined whether the alarm cell is in a normal fluctuation or a sudden deterioration state. For example, if the handover metrics at the deterioration time inflection point are significantly lower / higher than the dynamic threshold and this decrease / increase is sudden and significant, then we can consider that this cell is a handover quality poor cell.

[0081] Step A03, identify each target cell associated with the handover quality poor cell, and determine each abnormal neighbor cell pair. The abnormal neighbor cell pair is obtained by combining the handover quality poor cell and the target cell.

[0082] It should be noted that after determining the handover quality poor cell, by analyzing the number of handover failures between the handover quality poor cell and its neighboring cells, the target cells highly associated with the handover quality poor cell are identified, and the handover quality poor cell and the target cell are combined into an abnormal neighbor cell pair.

[0083] 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 condition. For the network cell that meets the target cell judgment condition, it indicates that there is a significant correlation between this network cell and the handover quality poor cell, and it is regarded as the target cell.

[0084] Exemplarily, the target cell judgment condition is:

[0085]

[0086] Among them, is the number of handover failures of the neighbor cell pair, that is, the number of handover failures between the handover quality poor cell and each neighboring network cell, is the sum of the top 3 of the number of handover failures of the pairwise neighbor cell pairs, that is, the sum of the top three of the number of handover failures between the handover quality poor cell and each neighboring network cell. 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 this network cell and the handover quality poor cell, and it is determined as the target cell.

[0087] In this embodiment, by presetting the alarm trigger rule and combining with the real-time monitoring data, it is possible to accurately identify the cells that meet the alarm conditions, improve the accuracy of alarm cell identification, reduce false alarms and missed alarms, and provide a reliable basis for subsequent optimization work. Based on the dynamic threshold, trend analysis of the handover metrics at the inflection point of deterioration time can objectively and scientifically determine whether the alarm cell is a handover quality degradation cell. By comparing the actual value of the handover metrics with the dynamic threshold, it is possible to accurately identify the abnormal fluctuations of the metrics, avoid the subjectivity of manual judgment, and improve the accuracy and objectivity of the judgment of handover quality degradation cells, providing a scientific basis for the formulation of subsequent optimization plans. According to the number of handover failures between neighbor cell pairs, using the handover quality degradation problem object identification algorithm, it is possible to quickly locate the target cells highly related to the handover quality degradation cells. By calculating the ratio of the number of handover failures to the sum of the number of handover failures of the top 3 neighbor cell pairs, it is possible to accurately judge the existence and influence degree of abnormal neighbor cell pairs, improve the speed and accuracy of abnormal neighbor cell pair location, and provide clear guidance for the implementation of subsequent optimization measures.

[0088] In a feasible embodiment, the abnormal problems include premature inter-frequency handover, late inter-frequency handover, premature intra-frequency handover, and late intra-frequency handover. In step S02, the steps of determining the parameters to be adjusted for the abnormal neighbor cell pair and the adjustment content of the parameters according to the abnormal problems include steps A11 to A14:

[0089] Step A11, when the abnormal problem is premature inter-frequency handover, according to the difference between the offset of the handover quality degradation cell and the offset of the target cell, adjust the offset of the handover quality degradation cell, and according to the inter-frequency handover trigger event type of the abnormal neighbor cell pair, adjust the handover decision threshold of the target cell and the handover decision threshold of the handover quality degradation cell;

[0090] It should be noted that when the abnormal problem is premature inter-frequency handover, it means that there is a premature handover phenomenon in the abnormal neighbor cell pair compared with the inter-frequency network handover under normal conditions, and there is room for optimization of the handover parameters of this neighbor cell pair. For the handover quality degradation cell, it is necessary to lower its handover-out speed, while for the target cell, it is necessary to increase its handover-in speed.

[0091] Additionally, it should be noted that to reduce the handover speed of poor-quality handover source cells and increase the handover-in speed of target cells, according to the difference in the offsets between the poor-quality handover source cells and the target cells, the offset of the poor-quality handover source cells is reduced. The offset refers to the priority of a cell in the handover decision. By adjusting the offset, the possibility of a cell being selected as a handover target can be changed. At the same time, the type of inter-frequency handover trigger event is judged. The types of inter-frequency handover trigger events include A3 event (handover is triggered based on the quality of a neighboring cell being higher than a certain threshold of the serving cell), A4 event (inter-frequency handover is triggered based on the quality of the serving cell being lower than a certain threshold), and A5 event (inter-frequency handover is triggered based on the quality of a neighboring cell being higher than a certain threshold and the quality of the serving cell being lower than a certain threshold), etc. These event types determine the trigger conditions for handover. For the identified type of inter-frequency handover trigger event, the handover decision threshold of the target cell is increased to make it more difficult to be handed over to, and the handover decision threshold of the poor-quality handover source cell is reduced to make it more difficult to be handed over out. The handover decision threshold is a threshold used to determine whether a handover should occur. For example, the inter-frequency A3 offset determines the degree of quality difference between the serving cell and the neighboring cell when a handover is triggered. When the value of the parameter to be adjusted has been adjusted to the set range threshold, it is determined that the parameter reaches the convergence condition and the optimization process ends.

[0092] Exemplarily, in the case where the abnormal problem is premature inter-frequency handover, the first parameter to be adjusted is the offset of the poor-quality handover source cell, and the optimization rule is:

[0093]

[0094] Among them, is the offset of the poor-quality handover source cell, is the offset of the target cell, is the adjustment value between the offset of the poor-quality handover source cell and the offset of the target cell. When the cell offset > -6dB, if the difference between the current value of the offset of the poor-quality handover source cell and the target value of the offset of the poor-quality handover source cell (referring to the ideal value or expected value that the cell offset is expected to reach, usually set based on network planning, optimization strategies, or specific service requirements) is greater than 4dB, it is adjusted downward by 4dB. If the difference between the current value of the offset of the poor-quality handover source cell and the target value of the offset of the poor-quality handover source cell is less than or equal to 4dB, the current value of the offset of the poor-quality handover source cell is directly adjusted to -6dB, and the absolute value of the cell offset is not less than -6dB.

[0095] Then, the type of inter-frequency handover trigger event between the poor-quality handover source cell and the target cell is judged through the inter-frequency handover trigger event type judgment condition, including A3 event, A4 event, and A5 event. Taking the A3 event as an example, the judgment condition is:

[0096]

[0097] Among them, the frequency for switching the poor-quality cell is , and the frequency of the target cell is , is the difference between the target cell and the poor-quality cell to be switched . When is not lower than the A3 decision threshold ( ), , that is, the inter-frequency handover trigger event type is A3 event. Similarly, A4 and A5 events can be determined.

[0098] After determining the inter-frequency handover trigger event type (assuming the inter-frequency handover trigger event is 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. Among them, 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 condition for triggering the A3 event, so as to consider the signal difference between different frequencies during inter-frequency handover. RSRP (Reference Signal Received Power) is an index to measure the strength of the wireless signal. The inter-frequency RSRP trigger threshold based on coverage is used to determine when to perform inter-frequency handover considering coverage. When the RSRP of the serving cell is lower than this threshold, it may trigger a handover to a cell on another frequency. The optimization formula is as follows:

[0099]

[0100]

[0101] Among them, is the A3 offset before adjustment, is the A3 offset after adjustment, is the adjustment difference of the A3 offset. For the optimization of the inter-frequency A3 offset of the target cell, it is judged whether the inter-frequency A3 offset of the target cell is less than 3dB. If the inter-frequency A3 offset is less than 0dB, it is directly adjusted to 0dB. If it is greater than or equal to 0dB and less than 2dB, it is adjusted to 2dB. If it is greater than or equal to 2dB, it is adjusted to 3dB. When the inter-frequency A3 offset < 3dB, it is adjusted upward in steps of 0.5dB based on the current setting, not higher than 3dB.

[0102] Similarly, for the optimization of the A4 threshold (inter-frequency RSRP trigger threshold based on coverage) of the target cell, it is judged whether the A4 threshold of the target cell is less than -95dBm. When the A4 threshold of the target cell is less than -95dBm, the A4 threshold of the target cell is optimized in the range of (current setting value, -95]dBm in steps of 1dB.

[0103] For handover of poor-quality cells, the parameters to be adjusted include the A3-based inter-frequency A2 RSRP triggering threshold and the A4 / A5-based inter-frequency A2 RSRP triggering threshold, in order to lower the handover decision threshold for poor-quality cells. Among them, the A2 event means that the signal quality of the serving cell is lower than a specific RSRP threshold. The inter-frequency A2 RSRP triggering threshold is used in the inter-frequency handover scenario. When the RSRP of the serving cell is lower than this threshold, it may trigger a measurement report and then consider handover. The A3-based inter-frequency A2 RSRP triggering threshold refers to the RSRP threshold used to trigger the A2 event when considering the A3 event. The A4 / A5-based inter-frequency A2 RSRP triggering threshold refers to the RSRP threshold used to trigger the A2 event when considering the A4 or A5 event. The tuning formula is as follows:

[0104]

[0105]

[0106] Among them, is the A3-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells, is the A3-based inter-frequency A2 RSRP triggering threshold for the target cell, is the adjustment difference of the A3-based inter-frequency A2 RSRP triggering threshold. For the tuning of the A3-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells, it is judged whether the A3-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells is greater than -105 dBm. When the A3-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells is greater than -105 dBm, the A3-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells is tuned in the range of [-105, current setting value) dB with a step of 2 dB.

[0107] Similarly, for the tuning of the A4 / A5-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells, it is judged whether the A4 / A5-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells is greater than -105 dBm. When the A4 / A5-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells is greater than -105 dBm, the A4 / A5-based inter-frequency A2 RSRP triggering threshold for handover of poor-quality cells is tuned in the range of [-105, current setting value) dB with a step of 2 dB.

[0108] Exemplarily, for the purpose of facilitating the understanding of the technical concept or technical principle of the present application, please refer to Figure 2 , Figure 2An iteration flowchart of the cross-frequency handover too early algorithm is provided. In the case where the abnormal problem is cross-frequency handover too early, first, the offset of the handover poor-quality cell is optimized downward, and the type of the cross-frequency handover trigger event is judged. For A3 events and A4 / A5 events, the handover decision threshold of the target cell is increased and the handover decision threshold of the handover poor-quality cell is decreased.

[0109] Step A12, in the case where the abnormal problem is cross-frequency handover too late, adjust the offset of the handover 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 handover poor-quality cell according to the type of the cross-frequency handover trigger event of the abnormal neighbor cell pair;

[0110] It should be noted that in the case where the abnormal problem is cross-frequency handover too late, it indicates that there is a phenomenon of too late handover in the abnormal neighbor cell pair compared with the cross-frequency network handover under normal circumstances. There is room for optimization of the handover parameters of this neighbor cell pair. For the handover poor-quality cell, it is necessary to increase its handover-out speed, while for the target cell, it is necessary to decrease its handover-in speed.

[0111] In addition, it should be noted that in order to increase the handover-out speed of the handover poor-quality cell and decrease the handover-in speed of the target cell, at the same time, adjust the offsets of the handover poor-quality cell and the target cell to improve the handover timing. Increase the offset of the handover poor-quality cell and decrease the offset of the target cell. At the same time, judge the type of the cross-frequency handover trigger event. For the identified type of the cross-frequency handover trigger event, decrease the handover decision threshold of the target cell to make it easier to be handed over in, and increase the handover decision threshold of the handover poor-quality cell to make it easier to be handed over out. When the parameter value to be adjusted has been adjusted to the set range threshold, it is determined that the parameter reaches the convergence condition and the optimization process ends.

[0112] Exemplarily, in the case where the abnormal problem is cross-frequency handover too late, the parameters adjusted first are the offsets of the handover poor-quality cell and the target cell, and the optimization rules are:

[0113]

[0114]

[0115] Among them, the offset of the handover poor-quality cell is , and the offset of the target cell is , When the offset of the current poor-quality cell to the target cell (hereinafter referred to as the first offset) < 6 dB, if the first offset is less than 0, directly adjust the first offset 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 (which refers to the ideal value that the source cell is expected to offset relative to the target cell, usually set based on network planning, optimization strategies or specific service requirements, aiming to ensure the balance of network coverage, capacity and quality, etc.) is greater than or equal to 2, adjust it upward by 2 dB. 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 is less than 2 dB, adjust it upward by 1 dB. The absolute value of the cell offset is not higher than 6 dB, and at the same time, adjust the offset of the target cell. If the first offset is greater than 0, directly adjust the first offset 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 2 dB, adjust it downward by 2 dB. 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 2 dB, adjust it downward by 1 dB. The neighboring cell offset is not lower than -6 dB.

[0116] Then, judge the type of the inter-frequency handover trigger event between the poor-quality cell for handover and the target cell through the inter-frequency handover trigger event type judgment condition. For the same or similar content above, you can refer to the above introduction and will not be elaborated hereinafter.

[0117] After determining the type of inter-frequency handover trigger event, for the target cell, the parameters 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 optimization of the inter-frequency A3 offset of the target cell, when the inter-frequency A3 offset of the target cell is greater than 3 dB, if the difference between the current inter-frequency A3 offset of the target cell and the A3 offset target value (referring to the inter-frequency A3 offset value 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 4 dB, it is adjusted downward by 4 dB; if the difference between the current inter-frequency A3 offset of the target cell and the A3 offset target value is less than or equal to 4 dB, it is directly adjusted to 3 dB. For the optimization of the A4 threshold of the target cell, when the A4 threshold of the target cell is greater than -105 dBm, it is judged whether the difference between the current A4 threshold of the target cell and the A4 threshold target value (referring to the A4 threshold 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 or equal to 10 dB. If it is greater than or equal to 10 dB, it is modified downward in steps of 5 dB and the modification stops after 10 dB; if it is less than 10 dB, it is directly modified to -105 dBm. For the optimization of the A5 threshold of the target cell: when the A5 threshold of the target cell is greater than -105 dBm, it is judged whether the difference between the current A5 threshold of the target cell and the A5 threshold target value (referring to the A5 threshold 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 or equal to 10 dB. If it is greater than or equal to 10 dB, it is modified downward in steps of 5 dB and the modification stops after 10 dB; if it is less than 10 dB, it is directly modified to -105 dBm.

[0118] For the handover cell with poor quality, the parameters 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 of the handover cell with poor quality. For the increase of the inter-frequency A4A5 trigger threshold of the handover cell with poor quality, the optimization formula is as follows:

[0119]

[0120] Among them, is the current trigger threshold of the handover cell with poor quality, It is the adjusted triggering threshold for switching poor-quality cells. For the optimization of the inter-frequency A2 RSRP triggering threshold based on A3 of the source cell, when the inter-frequency A2 RSRP triggering threshold based on A3 of the source cell is less than -95 dBm, it is adjusted upward in steps of 2 dB, not higher than -95 dBm; for the optimization of the inter-frequency A2 RSRP triggering threshold based on A4 / A5 of the source cell, when the inter-frequency A2 RSRP triggering threshold based on A4 / A5 of the source cell is less than -95 dBm, it is adjusted upward in steps of 2 dB, not higher than -95 dBm; for the optimization of the inter-frequency A2 RSRP triggering threshold based on A4 / A5 of the source cell, when the inter-frequency A2 RSRP triggering threshold based on A4 / A5 of the source cell is less than -95 dBm, it is adjusted upward in steps of 2 dB, not higher than -95 dBm; and the inter-frequency handover A5 RSRP threshold 1 is adjusted synchronously, adjusted upward in steps of 2 dB from the current parameter setting value, not greater than -95 dBm.

[0121] Exemplarily, for the purpose of facilitating the understanding of the technical concept or technical principle of the present application, please refer to Figure 3 , Figure 3 An iterative flowchart of the inter-frequency handover too late algorithm is provided. In the case where the abnormal problem is that the inter-frequency handover is too late, first, the offset of the handover poor-quality cell is optimized upward, the offset of the target cell is optimized downward, and the type of the inter-frequency handover trigger event is judged, and the target cell handover decision threshold is lowered and the handover poor-quality cell handover decision threshold is raised are realized for A3 events and A4 / A5 events.

[0122] Additionally, it should be noted that in the case where the abnormal problem is early inter-frequency handover or late inter-frequency handover, the adjustable inter-frequency handover parameters include, but are not limited to, inter-frequency A1A2 amplitude hysteresis, inter-frequency A1A2 time hysteresis, inter-frequency handover amplitude hysteresis, inter-frequency handover time hysteresis, load-based inter-frequency RSRP trigger threshold, connected-state frequency offset, etc. Among them, the amplitude hysteresis is used to reduce frequent handovers caused by signal fluctuations. The inter-frequency A1A2 amplitude hysteresis means that in inter-frequency handover, A1 (the serving cell signal quality is higher than a certain threshold) and A2 events use this hysteresis to smooth the handover decision. The time hysteresis is similar to the amplitude hysteresis, but it is time-based. The inter-frequency A1A2 time hysteresis means that before triggering an A1 or A2 event, the signal conditions must be continuously satisfied for a certain period of time, which helps to reduce handovers caused by instantaneous signal fluctuations. The inter-frequency handover amplitude hysteresis is an amplitude hysteresis parameter used for inter-frequency handover, which is used to smooth the handover decision and reduce unnecessary handovers. The inter-frequency handover time hysteresis, corresponding to the inter-frequency handover amplitude hysteresis, is a time-based hysteresis parameter used to ensure that the handover 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 handover 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 a handover to another frequency cell to balance the load. The connected-state frequency offset is a parameter used to adjust the handover tendency between different frequencies. It can affect the handover decision in the connected state, making the UE (User Equipment) more inclined to handover to the frequency with a higher offset value, which helps to optimize network performance and resource utilization.

[0123] Step A13, in the case where the abnormal problem is early intra-frequency handover, adjust the offset of the handover quality-poor cell, intra-frequency handover time hysteresis, intra-frequency handover amplitude hysteresis, intra-frequency handover offset;

[0124] It should be noted that in the case where the abnormal problem is early intra-frequency handover, it indicates that there is an early handover phenomenon in the abnormal neighboring cell pair compared with the intra-frequency network handover under normal circumstances. There is room for optimization of the handover parameters of this neighboring cell pair, and it is necessary to increase the handover speed of the handover quality-poor cell.

[0125] Additionally, it should be noted that to increase the handover speed of poor-quality handover cells, the offset of the poor-quality handover cells is adjusted to lower the handover trigger condition, and the intra-frequency handover time hysteresis of the poor-quality handover cells (the time hysteresis of the intra-frequency handover measurement event (such as A3 event)) is increased to delay the handover timing, and the intra-frequency handover amplitude hysteresis of the poor-quality handover cells (the hysteresis of the intra-frequency handover measurement event, used to reduce the number of intra-frequency handover event triggers caused by wireless signal fluctuations) is increased to improve the stability of handover, and the intra-frequency handover bias of the poor-quality handover cells (the bias value when the neighboring cell quality is higher than the serving cell quality in intra-frequency handover) is increased to promote the handover to the target cell. Among them, the intra-frequency handover time hysteresis means waiting for a period of time to perform the handover after the handover condition is met to avoid frequent handovers. The intra-frequency handover amplitude hysteresis is used to increase the stability of handover and prevent handovers from being triggered due to minor quality fluctuations. The intra-frequency handover bias is used to adjust the sensitivity of intra-frequency handover. When the value of the parameter to be adjusted has been adjusted to the set range threshold, it is determined that the parameter reaches the convergence condition and the optimization process ends.

[0126] Exemplarily, in the case where the abnormal problem is early intra-frequency handover, when the offset of the poor-quality handover cell is greater than -6 dB, it is adjusted downward in steps of 1 dB, not less than -6 dB; when the intra-frequency handover time hysteresis of the poor-quality handover cell is less than 160 ms, the intra-frequency handover time hysteresis is adjusted to 160 ms; when the intra-frequency handover amplitude hysteresis of the poor-quality handover cell is less than 1 dB, it is adjusted upward in steps of 0.5 dB, not higher than 1 dB; when the intra-frequency handover bias of the poor-quality handover cell is less than 1 dB, it is adjusted upward in steps of 0.5 dB, not higher than 1 dB.

[0127] Step A14, in the case where the abnormal problem is late intra-frequency handover, adjust the offset of the target cell and the offset, intra-frequency handover time hysteresis, intra-frequency handover amplitude hysteresis, and intra-frequency handover bias of the poor-quality handover cell.

[0128] It should be noted that in the case where the abnormal problem is late intra-frequency handover, it indicates that there is a phenomenon of late handover in the abnormal neighboring cell pair compared with the intra-frequency network handover under normal conditions. There is room for optimization of the handover parameters for this neighboring cell pair. It is necessary to lower the handover speed of the poor-quality handover cell and increase the handover speed of the target cell being accessed.

[0129] Additionally, it should be noted that to lower the handover speed of the poor-quality handover cell and increase the handover speed of the target cell being accessed, the offsets of both the poor-quality handover cell and the target cell are adjusted simultaneously to improve the handover timing, reduce the intra-frequency handover time hysteresis of the poor-quality handover cell to advance the handover timing, reduce the intra-frequency handover amplitude hysteresis of the poor-quality handover cell to lower the stability requirement of handover, and reduce the intra-frequency handover bias of the poor-quality handover cell to promote the handover to a more suitable cell.

[0130] Exemplarily, in the case where the abnormal problem is that the same-frequency handover is too late, when the offset from the handover poor-quality cell to the target cell is < 0 dB, it is adjusted upward in 1 dB steps, not exceeding 0 dB. At the same time, the offset from the target cell to the handover poor-quality cell is adjusted downward in 1 dB steps based on the current parameter setting value, not less than -6 dB; when the same-frequency handover time hysteresis of the handover poor-quality cell > 320 ms, the same-frequency handover time hysteresis is adjusted to 320 ms; when the same-frequency handover amplitude hysteresis of the handover poor-quality cell > 1 dB, it is adjusted downward in 0.5 dB steps, not less than 1 dB; when the same-frequency handover offset of the handover poor-quality cell > 1 dB, it is adjusted downward in 0.5 dB steps, not less than 1 dB.

[0131] In this embodiment, by performing precise parameter adjustment for specific handover problems, the pertinence and effectiveness of parameter adjustment are ensured. Through iterative adjustment of parameters, the optimal parameter combination can be gradually found, the handover success rate can be improved, the network instability phenomenon caused by handover problems can be reduced, the problem of poor optimization effect existing in the current network handover problem optimization process is solved, and the network stability and user experience are improved.

[0132] In a feasible embodiment, in step S01, the steps of identifying the abnormal problem of the abnormal neighboring cell pair include steps A21 to A23:

[0133] Step A21, detecting the downlink frequency points of the abnormal neighboring cell pair, and determining the first handover problem type between the abnormal neighboring cell pairs. The first handover problem type includes same-frequency handover failure and different-frequency handover failure;

[0134] It should be noted that the downlink frequency point information of the abnormal neighboring cell pair is collected. The downlink frequency point refers to the frequency point at which the radio base station transmits signals and is a key parameter for distinguishing same-frequency and different-frequency handovers. By comparing the downlink frequency points of the abnormal neighboring cell pair, if the downlink frequency points of the abnormal neighboring cell pair are the same, the handover between the abnormal neighboring cell pairs belongs to the same-frequency handover. If they are different, it belongs to the different-frequency handover. According to the result of the frequency point comparison, the system determines the first handover problem type. If the handover failure occurs between the same-frequency neighboring cell pairs, it is classified as the same-frequency handover failure. If it occurs between the different-frequency neighboring cell pairs, it is classified as the different-frequency handover failure.

[0135] 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 pairs. The second handover problem type includes handover too early and handover too late;

[0136] It should be noted that the system collects handover performance metric data related to network handover from network logs or performance monitoring systems. The handover performance metric data are various metric data reflecting network handover performance, including but not limited to the number of intra-eNodeB inter-frequency handover out attempts, the number of inter-eNodeB inter-frequency handover out attempts, the number of successful inter-eNodeB inter-frequency handover out attempts, the number of successful intra-eNodeB inter-frequency handover out attempts, etc. The collected handover performance metric data are cleaned and sorted to ensure data accuracy and integrity. A parameter root cause identification algorithm is used to analyze the preprocessed handover performance metric data. The parameter root cause identification algorithm is an algorithm based on machine learning or statistical analysis, used to identify the root cause of handover problems. By comprehensively considering the handover performance metric data and combining preset thresholds and conditions, it is determined whether there are problems of premature or late handover. According to the results of algorithm analysis, the system further determines the second type of handover problem, that is, premature handover or late handover.

[0137] In addition, it should be noted that premature handover usually occurs when the signal quality of the neighboring cell is not good enough or not stable enough, and the eNodeB (Evolved Node B, that is, a 4G base station) initiates a handover. The manifestations and determination methods of premature handover mainly include:

[0138] ① Handover failure and reconnection to the source cell: After the source cell issues a handover command, due to poor signal quality of the target cell, the user equipment (UE) fails to hand over to the target cell. Subsequently, the UE initiates an RRC (Radio Resource Control) connection reestablishment in the source cell, which is usually because the signal quality of the target cell is insufficient to support a stable communication connection.

[0139] ② Reconnection to the source cell after downlink out-of-sync: Although the UE successfully hands over to the target cell, it immediately experiences downlink out-of-sync (that is, the UE cannot maintain synchronization with the target cell), and then initiates an RRC connection reestablishment in the source cell.

[0140] ③ Frequent handover: The UE hands over from the target cell to another cell within a short period of time (such as within 5 seconds), which may also be a sign of premature handover.

[0141] Late handover means that the UE experiences RLF (Radio Link Failure) in the source cell and, during RRC reestablishment, reconnects to a non-source cell. The manifestations and determination methods of late handover mainly include:

[0142] ① Reconnection to a non-source cell after RLF: This is the direct manifestation of late handover. When the UE experiences RLF in the source cell, if it has exceeded the signal coverage range of the source cell at this time, the RRC reestablishment may succeed to another cell (non-source cell).

[0143] ② Decrease in handover success rate: Although a too-late handover does not directly affect the calculation formula of the handover success rate (handover success rate = (number of successful handovers - number of successful handovers executed for handover out to the source cell after reconstruction) / number of handover attempts), a too-late handover will increase the occurrence probability of RLF, thus indirectly leading to a decrease in the handover success rate.

[0144] ③ Degradation of user perception: A too-late handover may cause the user to encounter interruptions or delays during the network handover process, thus affecting the user experience.

[0145] Step A23, determine the abnormal problems between abnormal neighbor cell pairs by combining the first handover problem type and the second handover problem type. The abnormal problems include premature inter-frequency handover, too-late inter-frequency handover, premature intra-frequency handover, and too-late intra-frequency handover.

[0146] It should be noted that the first handover problem type (intra-frequency handover failure / inter-frequency handover failure) and the second handover problem type (premature handover / too-late handover) determined in steps A21 and A22 are combined. According to the combined result, the system determines the specific abnormal problem type between abnormal neighbor cell pairs, such as premature inter-frequency handover, too-late inter-frequency handover, premature intra-frequency handover, too-late intra-frequency handover, etc.

[0147] In addition, it should be noted that after the identification of abnormal problems, the system will output data related to abnormal neighbor cell pairs and the recognition result of parameter root causes. The data related to abnormal neighbor cell pairs includes but is not limited to the time of index degradation, regional information, corresponding equipment manufacturers, the number of handover pairs with TOP problems, the CGI of the handover quality-deteriorated cell, and the CGI of the target cell, etc. Among them, the time of index degradation refers to the time point when a certain network performance index (such as signal quality, throughput, delay, etc.) begins to decline or becomes unsatisfactory. The regional information is used to describe the geographical location where the problem occurs, 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 problem equipment. The number of handover pairs with TOP problems refers to the number of handover neighbor cell pairs with the most serious or common problems during the network handover process. The source cell CGI and the target cell CGI respectively refer to the identifiers used to identify the handover quality-deteriorated cell and the target cell. CGI (Cell Global Identifier) is an identifier used to uniquely identify a cell in a mobile communication network; the recognition result of parameter root causes includes but is not limited to the source cell CGI, the target cell CGI, whether there are handover parameter problems, the handover failure type, and the handover early / late type, etc. The handover failure type includes intra-frequency / inter-frequency, and the handover early / late type includes premature / too-late.

[0148] Exemplarily, in the case where the first handover problem type is inter-frequency handover failure, if the proportion of the number of handover failures in the inter-frequency neighboring cell pair is relatively high and there is an early handover phenomenon, it is considered that the second handover problem type of this neighboring cell pair is early handover, that is, the abnormal problem is early inter-frequency handover. The judgment conditions for early inter-frequency handover include:

[0149] ① The neighboring cell pair has an early and failed handover:

[0150] The number of early handovers out between specific two cells > 500, and the number of early handovers out between specific two cells / the number of handover attempts out between specific two cells > 50%, and the number of successful handovers out between specific two cells / the number of handover attempts out between specific two cells < 95%, and the number of handover attempts out between specific two cells - the number of successful handovers out between specific two cells > 500.

[0151] ② The proportion of the number of handover failures in the neighboring cell pair to the total number of handover failures in the cell > 20%:

[0152] (The number of handover attempts out between specific two cells - the number of successful handovers out between specific two cells) / (the number of inter-frequency handover attempts out within the eNodeB + the number of inter-frequency handover attempts out between eNodeBs + the number of handover attempts out between FDD / TDD modes within the eNodeB + the number of handover attempts out between FDD / TDD modes between eNodeBs - the number of successful inter-frequency handovers out between eNodeBs - the number of successful inter-frequency handovers out within the eNodeB - the number of successful handovers out between FDD / TDD modes between eNodeBs - the number of successful handovers out between FDD / TDD modes within the eNodeB) > 20%.

[0153] Among them, eNodeB (Evolved Node B) is a radio base station in the LTE (Long Term Evolution) network and also a network element of the LTE radio 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 communication.

[0154] If the proportion of the number of handover failures in the inter-frequency neighboring cell pair is relatively high and there is a late handover phenomenon, it is considered that the second handover problem type of this neighboring cell pair is late handover, that is, the abnormal problem is late inter-frequency handover. The judgment conditions for late inter-frequency handover include:

[0155] ① The neighboring cell pair has a late and failed handover:

[0156] The number of late handovers between specific two cells > 500, and the number of late handovers between specific two cells / the number of handover attempts between specific two cells > 50%, and the number of successful handovers between specific two cells / the number of handover attempts between specific two cells < 95%, and the number of handover attempts between specific two cells - the number of successful handovers between specific two cells > 500.

[0157] ② The proportion of the number of handover failures between neighboring cell pairs in the total number of handover failures of the cell > 20%:

[0158] (The number of handover attempts between specific two cells - the number of successful handovers between specific two cells) / (the number of inter-frequency handover attempts within the eNodeB + the number of inter-frequency handover attempts between eNodeBs + the number of handover attempts between FDD / TDD modes within the eNodeB + the number of handover attempts between FDD / TDD modes between eNodeBs - the number of successful inter-frequency handovers between eNodeBs - the number of successful inter-frequency handovers within the eNodeB - the number of successful handovers between FDD / TDD modes between eNodeBs - the number of successful handovers between FDD / TDD modes within the eNodeB) > 20%.

[0159] In the case where the first handover problem type is intra-frequency handover failure, if the proportion of the number of handover failures between intra-frequency neighboring cell pairs is relatively high and there is an early handover phenomenon, then it is considered that the second handover problem type of this neighboring cell pair is early handover, that is, the abnormal problem is intra-frequency early handover. The judgment conditions for intra-frequency early handover include:

[0160] ① The neighboring cell pair has an early and failed handover:

[0161] The number of early handovers between specific two cells > 500 and the number of early handovers between specific two cells / the number of handover attempts between specific two cells > 50% and the number of successful handovers between specific two cells / the number of handover attempts between specific two cells < 95% and the number of handover attempts between specific two cells - the number of successful handovers between specific two cells > 500.

[0162] ② The proportion of the number of handover failures between neighboring cell pairs in the total number of handover failures of the cell > 20%:

[0163] (The number of handover attempts between specific two cells - the number of successful handovers between specific two cells) / (the number of intra-frequency handover attempts between eNodeBs + the number of intra-frequency handover attempts within the eNodeB - the number of successful intra-frequency handovers between eNodeBs - the number of successful intra-frequency handovers within the eNodeB) > 20%.

[0164] If the proportion of the number of handover failures between intra-frequency neighboring cell pairs is relatively high and there is a late handover phenomenon, then it is considered that the second handover problem type of this neighboring cell pair is late handover, that is, the abnormal problem is intra-frequency late handover. The judgment conditions for intra-frequency late handover include:

[0165] ①The handover to the neighboring cell pair is too late and fails:

[0166] The number of times of too late handover between specific two cells > 500, and the number of times of too late handover between specific two cells / the number of handover attempt times between specific two cells > 50%, and the number of successful handover times between specific two cells / the number of handover attempt times between specific two cells < 95%, and the number of handover attempt times between specific two cells - the number of successful handover times between specific two cells > 500.

[0167] ②(The same - frequency handover amplitude hysteresis > 1dB, or the same - frequency handover offset > 1dB, or the same - frequency handover time hysteresis > 320ms, or the cell offset < - 3dB.

[0168] In this embodiment, through the detection of the downlink frequency point, the same - frequency and different - frequency handover problems are accurately distinguished, the accuracy of handover problem recognition is improved, providing a clear direction for the implementation of subsequent optimization measures. Through algorithm analysis, the problems of too early or too late handover can be accurately identified, the automation degree of handover problem recognition is improved, solving the problem of relying on manual experience judgment and insufficient accuracy in traditional methods, and improving the optimization efficiency. Through comprehensive judgment, the specific types of handover problems can be comprehensively and accurately identified, providing a scientific basis for the implementation of subsequent optimization measures, significantly improving the optimization effect of network handover problems, solving the problem of poor optimization effect existing in the current network handover optimization process, and improving network performance and user experience.

[0169] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as that in the above - mentioned first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 4 , in step S02, the steps of executing the parameter adjustment scheme include steps S11 - S14:

[0170] Step S11, construct a parameter modification instruction library based on the parameter adjustment scheme. For any parameter to be adjusted in the parameter modification scheme, generate a parameter modification instruction for the parameter according to the parameter modification instruction library and execute it;

[0171] It should be noted that based on the switching parameter adjustment scheme, the system analyzes and identifies the parameters to be adjusted and their target values. According to the characteristics of the parameter type, equipment manufacturer, network mode, etc., the corresponding parameter modification instructions are selected or generated from the preset templates and stored in the parameter modification instruction library. Since the parameter modification instruction library stores the modification instruction templates for different parameters, different equipment manufacturers, and different network modes, it can support multiple equipment manufacturers and ensure the compatibility and accuracy of the instructions. When a certain parameter needs to be adjusted, the system retrieves or generates the corresponding parameter modification instruction 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 instruction to the target device. At the same time, key information such as the instruction sending time and device response is recorded for subsequent result analysis and exception handling. After the network management system returns the parameter execution result, the system analyzes the result. The analysis content includes but is not limited to whether the parameter is successfully modified, the modified value, and whether the optimization target is achieved. The system presents the analysis result to the user in an intuitive way, such as through charts, logs, etc.

[0172] Step S12, in the case where the parameter modification instruction execution fails, determine the type of problem that causes the execution failure;

[0173] It should be noted that the system monitors the execution and sending status of the interface in real time and detects whether there is an abnormality. If it is found that the execution fails, the exception handling process is immediately started. By analyzing the failure reason, the system determines the type of problem, such as the execution failure caused by network fluctuations or the execution failure caused by unreasonable parameter settings.

[0174] In addition, it should be noted that the system predicts the type of problem that causes the execution failure through the problem analysis model. The problem analysis model is trained by historical problem types. For the predicted result, the user can evaluate it. At the same time, the evaluation result will be feedback to the problem analysis model to improve the accuracy of the model prediction.

[0175] Step S13, if the type of problem is the execution failure caused by network fluctuations, implement the secondary activation mechanism and resend the parameter modification instruction;

[0176] It should be noted that for the execution failure caused by network fluctuations, the system implements the secondary activation mechanism. This mechanism includes but is not limited to strategies such as resending the parameter modification instruction, increasing the retry times, and adjusting the retry interval. Through secondary activation, the system resends the parameter modification instruction to try to overcome the interference caused by network fluctuations and ensure that the instruction can be successfully sent and executed.

[0177] Step S14, if the type of problem is the execution failure caused by unreasonable parameter settings, implement the decision iteration mechanism, iteratively adjust the parameters, and execute the adjusted parameter adjustment scheme until the parameters reach the preset range threshold.

[0178] It should be noted that for the execution failure caused by unreasonable parameter settings, the system implements a decision iteration mechanism. The decision iteration mechanism automatically adjusts the parameter value and generates a new parameter modification plan according to the current parameter value, the parameter iteration step size, and the 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 result. If the parameter value still does not reach the preset range threshold, the iteration continues; if it reaches or exceeds the preset range threshold, the iteration stops and the optimization is confirmed to be successful. The preset range threshold refers to the reasonable range that the parameter should reach and is used to judge whether the parameter adjustment is successful.

[0179] In addition, it should be noted that when the number of times of iteratively adjusting the parameter reaches the preset adjustment times, the iterative adjustment of the parameter stops, and the parameter value is restored to the state before modification or the previous stable state to ensure the stability of the network and the normal use of users.

[0180] Exemplarily, if the current abnormal problem is premature same-frequency handover, the parameter adjusted for the parameter adjustment plan is the offset of the handover poor-quality cell, and the corresponding preset range threshold is -6 dB. At this time, when the offset of the handover poor-quality cell is greater than -6 dB, one iteration adjusts downward in steps of 1 dB. When it is adjusted to -6 dB, it is considered that the parameter value has been adjusted to the preset range threshold and the convergence condition has been reached, and the optimization process of this parameter stops.

[0181] In this embodiment, by constructing a parameter modification instruction library, the automatic generation of parameter modification instructions is realized, which greatly improves the work efficiency and accuracy. And the parameter modification instruction library can support multiple device manufacturers to ensure the compatibility and accuracy of the instructions. By calling the OMC interface of the device manufacturer, the parameter instruction issuance and execution for different device manufacturers are realized, solving the compatibility problem. By parsing the parameter execution result returned by the network management, the immediate feedback of the execution result is realized, providing a basis for subsequent optimization decisions. By analyzing the reasons for the execution failure, the accurate classification of the problem types is realized. By implementing the secondary activation mechanism and resending the parameter modification instructions, the execution failure problem caused by network fluctuations is solved. By implementing the decision iteration mechanism and iteratively adjusting the parameter value until the parameter reaches the preset range threshold, the execution failure problem caused by unreasonable parameter settings is solved. By iteratively adjusting the parameter value and gradually approaching the optimal parameter configuration, the optimization effect is improved.

[0182] In a feasible implementation, in step S03, the execution result of the parameter adjustment scheme is evaluated. When the execution result is unqualified, the parameter adjustment scheme is adjusted according to the execution result, and the step of returning the execution result of evaluating the parameter adjustment scheme based on the adjusted parameter scheme is performed until the execution result of the parameter adjustment scheme is evaluated as qualified. The steps include steps B01 to B02:

[0183] Step B01, in the short evaluation stage, if the performance index between abnormal neighbor cell pairs deteriorates after the execution of the parameter modification instruction, the parameter is rolled back to the state before the parameter adjustment. If the preset short evaluation qualified condition is met, the long evaluation stage is entered for evaluation. If the preset short evaluation qualified condition is not met, it is determined that the execution result is unqualified, the parameter is 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 abnormal neighbor cell pairs reaches the preset success rate.

[0184] It should be noted that the short evaluation stage is mainly used to quickly judge whether the parameter adjustment scheme is initially effective. When the parameter modification instruction is executed, if the basic performance indexes such as the handover of the handover quality-poor cell and its target cell deteriorate (that is, the performance becomes worse), the system will automatically trigger the parameter rollback mechanism to restore the previously adjusted parameter value to the state before the parameter adjustment, avoiding further degradation of the network performance due to incorrect parameter adjustment. After the parameter is rolled back, the system records the result of this adjustment and executes the next parameter optimization scheme until the process ends.

[0185] In addition, it should be noted that after the parameter execution is successful, the system will monitor the handover success rate of the cell to judge whether the preset short evaluation qualified condition is met. Exemplarily, if the handover success rate of the cell for 4 consecutive 15-minute periods is greater than 95%, it is determined that the short evaluation stage of the cell is evaluated as qualified and the long-term evaluation stage is entered. If the cell does not meet the above conditions (that is, the handover success rate is unstable or lower than the standard) within 3 hours after the parameter adjustment scheme is executed, it is determined that the short evaluation stage of the cell is evaluated as unqualified, and parameter iterative optimization is performed. The system will adjust the parameter again and re-execute the evaluation process until the handover success rate reaches the preset success rate.

[0186] Step B02, in the long evaluation stage, if the preset long evaluation qualified condition is not met, it is determined that the execution result is unqualified, the parameter is 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 abnormal neighbor cell pairs reaches the preset success rate.

[0187] It should be noted that the long evaluation stage is used to further verify the long-term effect of the parameter adjustment plan. Before the start of the long evaluation stage, the system will first optimize and adjust the network handover problems caused by other non-parameter reasons. After the handover problems are assigned to the root causes such as faults, coverage, interference, and neighboring cells for wireless network optimization, once it is monitored that the optimization measures are completed, the system will enter the long evaluation stage for evaluation.

[0188] In addition, it should be noted that the system continuously monitors indicators such as the handover success rate of the cell, the call handover ratio, and the handover success rate of VOLTE users to determine whether the preset long evaluation passing conditions are met. Exemplarily, if the handover success rate of the cell is greater than 95% for three consecutive days, and there is no alarm for the call handover ratio and the handover success rate of VOLTE users, it is determined that the evaluation in the long evaluation stage of the cell is qualified, and the automatic handover optimization process ends. If the cell does not meet the above conditions (that is, the long-term performance is unstable or lower than the standard), it is determined that the evaluation in the long evaluation stage of the cell is unqualified, and iterative optimization is performed. The system will adjust the parameters again and re-execute the evaluation process until the handover success rate reaches the preset success rate.

[0189] In this embodiment, by combining short evaluation and long evaluation, the problem of poor optimization effect in the current network handover problem optimization process is effectively solved. In the short evaluation, by monitoring the changes in performance indicators between abnormal neighboring cell pairs, it can be timely found whether the parameter adjustment has caused performance degradation or preliminary improvement. In the long evaluation, through continuous monitoring and evaluation for multiple days, it can be more accurately judged whether the adjustment plan has brought long-term performance improvement. By real-time monitoring and evaluating the changes in performance indicators, and timely parameter iterative optimization, this process ensures the stability and improvement of network performance, and improves the optimization efficiency of network handover problems.

[0190] In a feasible embodiment, the handover problem handling method in wireless network autonomous driving further includes steps B11 to B12:

[0191] Step B11, receiving abnormal cell information transmitted by the autonomous driving vehicle. Among them, the abnormal cell information includes the handover-out cell and the handover-in cell that are abnormal when the autonomous driving vehicle performs network handover during autonomous driving. The handover-out cell is the network cell that the autonomous driving vehicle records as about to leave, and the handover-in cell is the network cell that the autonomous driving vehicle records as about to enter.

[0192] 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 problems during the network handover 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 handover problems caused by factors such as network coverage, signal strength, and interference during the driving of the autonomous driving vehicle, including but not limited to cell ID, problem type (such as handover failure, handover delay, etc.), occurrence time, etc. After receiving these data, the system will parse them and extract key information, such as the handover-out cell ID, handover-in cell ID, problem type (such as handover failure, signal loss, etc.), occurrence time, etc. The handover-out cell refers to the network cell where the autonomous driving vehicle is currently located and is about to leave, which is the starting point of the handover process. The handover-in cell refers to the new network cell that the autonomous driving vehicle is about to enter, which is the target of the handover 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.

[0193] Step B12: Use the handover-out cell and handover-in cell in the abnormal cell information as a handover abnormal neighbor cell pair.

[0194] It should be noted that after the system parses the handover-out cell and handover-in cell information, it will match them as a pair of handover abnormal neighbor cell pairs and store them in the database for unified management of the handover abnormal neighbor cell pairs, including recording information such as the time, location, and reason of the abnormality for subsequent analysis and optimization. A handover abnormal neighbor cell pair refers to a pair of adjacent network cells that have abnormal situations during the network handover process.

[0195] In this embodiment, by receiving the abnormal cell information transmitted by the autonomous driving vehicle in real time, the system can quickly obtain the abnormal situations during the network handover process, providing timely and comprehensive data support for subsequent analysis and optimization. By accurately identifying the handover-out cell (the network cell that the autonomous driving vehicle is about to leave) and the handover-in cell (the network cell that the autonomous driving vehicle is about to enter), the system can more accurately locate the occurrence location of the network handover abnormality, providing a precise target for subsequent optimization measures.

[0196] Exemplarily, to help understand the technical concept or technical principle of this application, please refer to Figure 5 , Figure 5The overall flowchart of the handover problem optimization solution is provided. First, by identifying the poor-quality handover cells, the abnormal cells with network handover problems are found. Then, the root cause of the poor-quality handover cells is located to analyze the cause of the problem, such as equipment failure, poor signal quality, insufficient network coverage, or unreasonable handover parameter settings. Then, a solution decision is made for the poor-quality handover cells. According to the results of the root cause identification, it is automatically decided which parameters need to be adjusted and the adjustment step size, such as adjusting parameters like handover amplitude hysteresis, handover offset, handover time hysteresis, etc. The automatically determined parameter adjustment solution is executed, and the parameter adjustment solution is evaluated. According to the evaluation results, the solution is iteratively optimized until the evaluation result of the parameter adjustment solution is qualified, and then the optimization process is stopped.

[0197] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the method for handling handover problems in the wireless network autonomous driving of this application. Based on this technical concept, more forms of simple transformations are within the protection scope of this application.

[0198] This 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 each network cell. Please refer to Figure 6 , the device for handling handover problems in wireless network autonomous driving includes:

[0199] A problem determination module 10, configured to determine each abnormal neighbor cell pair in each network cell. For any abnormal neighbor cell pair in each abnormal neighbor cell pair, identify the abnormal problem of the abnormal neighbor cell pair, where each abnormal neighbor cell pair includes each handover abnormal neighbor cell pair;

[0200] A solution generation module 20, configured to determine the parameters to be adjusted for the abnormal neighbor cell pair and the adjustment content of the parameters according to the abnormal problem, obtain a parameter adjustment solution, and execute the parameter adjustment solution;

[0201] An evaluation feedback module 30, configured to evaluate the execution result of the parameter adjustment solution. In the case where the execution result is unqualified, adjust the parameter adjustment solution according to the execution result, and return to the step of evaluating the execution result of the parameter adjustment solution based on the adjusted parameter solution until the execution result of the parameter adjustment solution is evaluated as qualified.

[0202] Optionally, the problem determination module 10 is further configured to:

[0203] Determine the alarm cells in each network cell that meet the preset alarm trigger rule and the inflection point of the deterioration time of the alarm cells;

[0204] Use the average value of each handover index in the preset number of days before the inflection point of the deterioration time as the dynamic threshold, and perform a trend analysis on each handover index at the inflection point of the deterioration time according to the dynamic threshold to determine whether the alarm cell is a poor-quality handover cell;

[0205] Identify each target cell associated with the poor-quality cell to be switched, and determine each abnormal neighboring cell pair, where the abnormal neighboring cell pair is obtained by combining the poor-quality cell to be switched and the target cell.

[0206] Optionally, the abnormal problems include premature inter-frequency handover, late inter-frequency handover, premature intra-frequency handover, and late intra-frequency handover. The scheme generation module 20 is further configured to:

[0207] In the case where the abnormal problem is premature inter-frequency handover, adjust the offset of the poor-quality cell to be switched according to the difference between the offset of the poor-quality cell to be switched 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 to be switched according to the inter-frequency handover trigger event type of the abnormal neighboring cell pair;

[0208] In the case where the abnormal problem is late inter-frequency handover, adjust the offset of the poor-quality cell to be switched 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 to be switched according to the inter-frequency handover trigger event type of the abnormal neighboring cell pair;

[0209] In the case where the abnormal problem is premature intra-frequency handover, adjust the offset of the poor-quality cell to be switched, the intra-frequency handover time hysteresis, the intra-frequency handover amplitude hysteresis, and the intra-frequency handover bias;

[0210] In the case where the abnormal problem is late intra-frequency handover, adjust the offset of the target cell and the offset of the poor-quality cell to be switched, the intra-frequency handover time hysteresis, the intra-frequency handover amplitude hysteresis, and the intra-frequency handover bias.

[0211] Optionally, the problem determination module 10 is further configured to:

[0212] Detect the downlink frequency points of the abnormal neighboring cell pair, and determine the first handover problem type between the abnormal neighboring cell pairs, where the first handover problem type includes intra-frequency handover failure and inter-frequency handover failure;

[0213] Collect the handover performance metric data of the abnormal neighboring cell pair, and analyze the handover performance metric data based on the parameter root cause identification algorithm to determine the second handover problem type between the abnormal neighboring cell pairs, where the second handover problem type includes premature handover and late handover;

[0214] Combine the first handover problem type and the second handover problem type to determine the abnormal problem between the abnormal neighboring cell pairs, where the abnormal problem includes premature inter-frequency handover, late inter-frequency handover, premature intra-frequency handover, and late intra-frequency handover.

[0215] Optionally, the scheme generation module 20 is further configured to:

[0216] Build a parameter modification instruction library based on the parameter adjustment plan. For any parameter to be adjusted in the parameter modification plan, generate a parameter modification instruction for the parameter according to the parameter modification instruction library and execute it;

[0217] In the case where the execution of the parameter modification instruction fails, determine the type of problem that causes the execution to fail;

[0218] If the type of problem is the execution failure caused by network fluctuation, then implement a secondary activation mechanism and resend the parameter modification instruction;

[0219] If the type of problem is the execution failure caused by unreasonable parameter settings, then implement a decision iteration mechanism, iteratively adjust the parameters, and execute the adjusted parameter adjustment plan until the parameters reach the preset range threshold.

[0220] Optionally, the evaluation feedback module 30 is further configured to:

[0221] In the short evaluation stage, if the performance index between abnormal neighbor cell pairs deteriorates after executing the parameter modification instruction, then roll back the parameters to the state before parameter adjustment. If the preset short evaluation qualification condition is met, then enter the long evaluation stage for evaluation. If the preset short evaluation qualification condition is not met, then determine that the execution result is unqualified, iteratively adjust the parameters, execute and evaluate the adjusted parameter adjustment plan, and determine that the evaluation result is qualified when the handover success rate between abnormal neighbor cell pairs reaches the preset success rate;

[0222] In the long evaluation stage, if the preset long evaluation qualification condition is not met, then determine that the execution result is unqualified, iteratively adjust the parameters, execute and evaluate the adjusted parameter adjustment plan, and determine that the evaluation result is qualified when the handover success rate between abnormal neighbor cell pairs reaches the preset success rate.

[0223] Optionally, the handover problem processing device in the wireless network autonomous driving further includes a receiving and processing module 40, and the receiving and processing module 40 is further configured to:

[0224] Receive the abnormal cell information transmitted by the autonomous driving vehicle;

[0225] Determine the network cells that are abnormal during network handover in each network cell according to the abnormal cell information, and determine a parameter adjustment plan for the network cells;

[0226] Execute the parameter adjustment plan and adjust the parameter adjustment plan according to the feedback execution result until the execution result evaluation of the parameter adjustment plan is qualified.

[0227] The handover problem processing device in wireless network autonomous driving provided by this application adopts the handover problem processing method in wireless network autonomous driving in the above-mentioned embodiment, and 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 this application are the same as those of the handover problem processing method in wireless network autonomous driving provided by the above-mentioned embodiment, and other technical features in the handover problem processing device in wireless network autonomous driving are the same as the features disclosed in the method of the above-mentioned embodiment, which will not be elaborated here.

[0228] This application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; 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 handover problem processing method in wireless network autonomous driving in the first embodiment above.

[0229] Refer to the following Figure 7 , which shows a schematic structural diagram of an electronic device suitable for implementing the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, PADs (Portable Application Description: tablet computers), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The electronic device shown is only an example and should not impose any limitations on the functions and usage scopes of the embodiments of this application.

[0230] As Figure 7As shown, the electronic device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in the read-only memory 1002 or a program loaded from the storage device 1003 into 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 may 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 may allow the electronic device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows an electronic device having various systems, it should be understood that it is not required to implement or have all the shown systems. Instead, more or fewer systems may be implemented or had.

[0231] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts may be implemented as computer software programs. 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 includes program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from the network through the communication device, or installed from the storage device 1003, or installed from the read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are performed.

[0232] The electronic device provided by the present application adopts the method for handling handover problems in wireless network autonomous driving in the above-mentioned embodiments, and 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 the present application are the same as those of the method for handling handover problems in wireless network autonomous driving provided by the above-mentioned embodiments, and other technical features in the electronic device are the same as those disclosed in the method of the previous embodiment, and will not be elaborated herein.

[0233] It should be understood that each part disclosed in the present application may be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0234] The above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present application, and all of them should be covered by the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claimed rights.

[0235] 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 handover problems in wireless network autonomous driving in the above embodiments.

[0236] The computer-readable storage medium provided by 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 the computer-readable storage medium may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0237] The above computer-readable storage medium may be included in an electronic device; or it may exist separately without being assembled into the electronic device.

[0238] The above computer-readable storage medium carries one or more programs, which, when executed by an electronic device, enable a handover problem handling device in wireless network autonomous driving to be applied to a mobile communication system. The mobile communication system includes each network cell, and can determine each abnormal neighbor cell pair in each network cell. For any abnormal neighbor cell pair in each abnormal neighbor cell pair, identify the abnormal problem of the abnormal neighbor cell pair, where each abnormal neighbor cell pair includes each handover abnormal neighbor cell pair; determine the parameter to be adjusted for the abnormal neighbor cell pair and the adjustment content of the parameter according to the abnormal problem, obtain a parameter adjustment plan, and execute the parameter adjustment plan; evaluate the execution result of the parameter adjustment plan. In the case where the execution result is unqualified, adjust the parameter adjustment plan according to the execution result, and return to the step of evaluating the execution result of the adjusted parameter plan until the execution result of the parameter adjustment plan is evaluated as qualified.

[0239] Computer program code for performing the operations of the present application may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone 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., connected through the Internet using an Internet service provider).

[0240] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0241] The modules described in the embodiments of the present application can be implemented in software or in hardware. In some cases, the name of the module does not constitute a limitation on the unit itself.

[0242] The readable storage medium provided by the present application is a computer-readable storage medium, and the computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the method for handling handover problems in the above-mentioned wireless network autonomous driving, 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 computer-readable storage medium provided by the present application are the same as those of the method for handling handover problems in the wireless network autonomous driving provided in the above embodiments, and will not be elaborated here.

[0243] The present application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the steps of the method for handling handover problems in the wireless network autonomous driving as described above.

[0244] The computer program product provided by the present application 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 computer program product provided by the present application are the same as those of the method for handling handover problems in the wireless network autonomous driving provided in the above embodiments, and will not be elaborated here.

[0245] The above are only some embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structural transformation made using the description and drawings of the present application under the technical concept of the present application, or any direct / indirect application in other related technical fields, is 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, which includes various network cells. The method for handling handover problems in the wireless network autonomous driving includes: Determine each abnormal neighboring cell pair in the various network cells. For any abnormal neighboring cell pair among the various abnormal neighboring cell pairs, identify the abnormal problem of the abnormal neighboring cell pair. Among them, the various abnormal neighboring cell pairs include each handover abnormal neighboring cell pair, and the abnormal neighboring cell pair also includes a handover quality-poor cell and a target cell. The target cell is a network cell whose ratio of the handover failure times of the neighboring cell pair to the sum of the handover failure times of the top 3 pairs of neighboring cell pairs is greater than or equal to 20%. The handover failure times of the neighboring cell pair are the handover failure times between the handover quality-poor cell and each network cell adjacent to the handover quality-poor cell. The sum of the handover failure times of the top 3 pairs of neighboring cell pairs is the sum of the top three handover failure times between the handover quality-poor cell and each network cell adjacent to the handover quality-poor cell; According to the abnormal problem, determine the network parameters that need to be adjusted for the abnormal neighboring cell pair and the adjustment content of the network parameters, obtain a parameter adjustment plan, and execute the parameter adjustment plan. Among them, the abnormal problems include premature inter-frequency handover, late inter-frequency handover, premature intra-frequency handover, and late intra-frequency handover; Evaluate the execution result of the parameter adjustment plan. In the case where the execution result is unqualified, adjust the parameter adjustment plan according to the execution result, and based on the adjusted parameter plan, return to the step of evaluating the execution result of the parameter adjustment plan until the execution result of the parameter adjustment plan is evaluated as qualified; Among them, the step of determining the abnormal neighboring cell pairs in the various network cells includes: For any network cell in the various network cells, judge the gear where the handover attempt times of the network cell are located based on a preset alarm trigger rule. According to the gear, compare whether the handover success rate degradation ratio, the handover success rate degradation value, and the failure times degradation value of the network cell reach the corresponding thresholds. In the case where the handover success rate degradation ratio, the handover success rate degradation value, and the failure times degradation value all reach the corresponding thresholds, determine that the network cell meets the preset alarm trigger rule, determine that the network cell is an alarm cell, and determine the degradation time inflection point of the alarm cell; Take the average value of each handover index in the preset number of days before the degradation time inflection point as the dynamic threshold, and perform a trend analysis on each handover index of the degradation time inflection point according to the dynamic threshold to determine whether the alarm cell is a handover quality-poor cell; Identify each target cell associated with the handover quality-poor cell and determine each abnormal neighboring cell pair.

2. The method for handling handover problems in wireless network autonomous driving according to claim 1, wherein , The step of determining the network parameters that need to be adjusted for the abnormal neighboring cell pair and the adjustment content of the network parameters according to the abnormal problem includes: When the abnormal problem is early inter-frequency handover, adjust the offset of the handover poor-quality cell according to the difference between the offset of the handover 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 handover poor-quality cell according to the inter-frequency handover trigger event type of the abnormal neighbor cell pair; When the abnormal problem is late inter-frequency handover, adjust the offset of the handover 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 handover poor-quality cell according to the inter-frequency handover trigger event type of the abnormal neighbor cell pair; When the abnormal problem is early intra-frequency handover, adjust the offset of the handover poor-quality cell, the intra-frequency handover time hysteresis, the intra-frequency handover amplitude hysteresis, and the intra-frequency handover offset; When the abnormal problem is late intra-frequency handover, adjust the offset of the target cell and the offset of the handover poor-quality cell, the intra-frequency handover time hysteresis, the intra-frequency handover amplitude hysteresis, and the intra-frequency handover offset.

3. The method for handling handover problems in wireless network autonomous driving according to claim 2, characterized in that , the steps of identifying the abnormal problem of the abnormal neighbor cell pair include: Detect the downlink frequency points of the abnormal neighbor cell pair, and determine the first handover problem type between the abnormal neighbor cell pairs, where the first handover problem type includes intra-frequency handover failure and inter-frequency handover failure; Collect the handover performance index data of the abnormal neighbor cell pair, and analyze the handover performance index data based on the parameter root cause identification algorithm to determine the second handover problem type between the abnormal neighbor cell pairs, where the second handover problem type includes early handover and late handover; Combine the first handover problem type and the second handover problem type to determine the abnormal problem between the abnormal neighbor cell pairs, where the abnormal problem includes early inter-frequency handover, late inter-frequency handover, early intra-frequency handover, and late intra-frequency handover.

4. The method for handling handover problems in wireless network autonomous driving according to claim 1, wherein , the steps of executing the parameter adjustment scheme include: Build a parameter modification instruction library based on the parameter adjustment scheme. For any parameter to be adjusted in the parameter modification scheme, generate a parameter modification instruction for the parameter according to the parameter modification instruction library and execute it; When the execution of the parameter modification instruction fails, judge the problem type that causes the execution failure; If the problem type is the execution failure caused by network fluctuation, then implement a secondary activation mechanism and resend the parameter modification instruction; If the problem type is the execution failure caused by unreasonable parameter settings, then implement a decision iteration mechanism, iteratively adjust the parameter, and execute the adjusted parameter adjustment scheme until the parameter reaches the preset range threshold.

5. The method for handling handover problems in wireless network autonomous driving according to claim 4, wherein , the steps of evaluating the execution result of the parameter adjustment scheme, and when the execution result is unqualified, adjusting the parameter adjustment scheme according to the execution result, and based on the adjusted parameter scheme, returning to the step of evaluating the execution result of the parameter adjustment scheme until the execution result of the parameter adjustment scheme is evaluated as qualified include: In the short evaluation stage, if the performance metrics between the abnormal neighbor cell pairs deteriorate after executing the parameter modification instruction, the parameters are rolled back to the state before parameter adjustment. If the preset short evaluation passing criteria are met, the long evaluation stage is entered for evaluation. If the preset short evaluation passing criteria are not met, the execution result is determined to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment plan is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighbor cell pairs reaches the preset success rate; In the long evaluation stage, if the preset long evaluation passing criteria are not met, the execution result is determined to be unqualified, the parameters are iteratively adjusted, the adjusted parameter adjustment plan is executed and evaluated, and the evaluation result is determined to be qualified when the handover success rate between the abnormal neighbor cell pairs reaches the preset success rate.

6. The method for handling handover problems in wireless network autonomous driving according to claim 1, characterized in that , the handover problem handling method in the wireless network autonomous driving further includes: Receiving abnormal cell information transmitted by an autonomous driving vehicle, where the abnormal cell information includes the handover-out cell and the handover-in cell that are abnormal when the autonomous driving vehicle performs network handover during autonomous driving. The handover-out cell is the network cell that the autonomous driving vehicle records as about to leave, and the handover-in cell is the network cell that the autonomous driving vehicle records as about to enter; Using the handover-out cell and the handover-in cell in the abnormal cell information as a handover abnormal neighbor cell pair.

7. An electronic device, characterized in that , the device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the handover problem handling method in the wireless network autonomous driving according to any one of claims 1 to 6.

8. A storage medium, characterized in that , the storage medium 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 handover problem handling method in the wireless network autonomous driving according to any one of claims 1 to 6 are implemented.

9. A computer program product, characterized in that , the computer program product includes a computer program. When the computer program is executed by a processor, the steps of the handover problem handling method in the wireless network autonomous driving according to any one of claims 1 to 6 are implemented.

Images