Performance file processing platform and method for extended pico base station

Abstract

The embodiment of the present invention discloses a performance file processing platform and method for an extended pico base station, the platform comprising: an acquisition module: regularly obtaining performance compression files reported by base stations; a decompression module: after obtaining the performance compression files, decompressing and storing them in a performance folder; a processing module: reading the content of each performance file into a temporary list object TempList; a creation module: creating an EXCEL file in the performance folder, and writing the performance data in the set TPMD corresponding to each performance file into the sheet1 page. The present invention can quickly analyze the base station performance data when a problem occurs in the network management system. The present invention provides a temporary storage space for locating base station performance optimization problems, thereby avoiding the loss of base station performance data. The performance data generated by the present invention displays key information to customers in an EXCEL format, provides intuitive data results, and facilitates customers to optimize the network and locate faults of base stations.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a performance file processing platform and method for an extended pico base station. Background Art

[0002] In order to improve the quality of indoor 5G network coverage, my country has built a large number of 5G extended pico base stations, which are also called distributed pico base stations. They are usually composed of baseband units, extension units and radio frequency remote units. They can achieve the expansion of pico base stations through cascading multiple extension units, and have the advantages of flexible expansion of multi-mode and multi-frequency. At the same time, the base station performance data reflects the operating quality of the base station, and plays an irreplaceable role in network optimization and troubleshooting of large-scale commercial networks. At present, the performance data of 5G extended pico base stations is collected regularly by the network management system (referred to as network management or network management platform) through the performance files reported by the base station, and displayed to users after parsing. Such performance files are generally defined in accordance with the TS32.594 protocol format specified by the 3GPP organization, and then packaged in XML files and passed to the network management system for processing.

[0003] However, when the network management system processes the performance file, if the network management system parses the performance file abnormally, although it can be reprocessed with the help of the performance supplement method (for example, the patent with application number CN202410206363.4 introduces this solution), when the network management as a whole is abnormal, this method cannot be implemented, and users cannot quickly understand the base station performance indicator data, and thus cannot optimize the network and troubleshoot faults.

[0004] In addition, base station performance files are generally generated as an XML performance file on a regular basis, and then packaged and reported to the network system at a certain reporting period. Currently, there is no third-party system that can quickly and conveniently assist network managers in processing performance files. Summary of the invention

[0005] The technical problem to be solved by the embodiments of the present invention is to provide a performance file processing platform and method for an extended pico base station, so as to facilitate users to optimize and troubleshoot the network.

[0006] In order to solve the above technical problems, an embodiment of the present invention proposes a performance file processing platform of an extended pico base station, including:

[0007] Collection module: regularly obtains performance compression files reported by base stations;

[0008] Decompression module: After obtaining the performance compressed file, decompress it and store it in a performance folder named with the combination of performance start time - performance end time + base station SN number;

[0009] Processing module: read the content of each performance file in the performance folder into the temporary list object TempList, use regular expressions to collect the key data jobId, endTime, measType and measValue in TempList into the set TPMD, and store the data in the set TPMD. The jobId is the task number of each set of performance indicator tasks, the endTime is the end time of the corresponding performance indicator item collection, the measType is the performance indicator type, and the measValue is the performance indicator value;

[0010] Create module: Create an EXCEL file in the performance folder and write the performance data in the set TPMD corresponding to each performance file into the sheet1 page.

[0011] Accordingly, an embodiment of the present invention further provides a performance file processing method for an extended pico base station, comprising:

[0012] Step 1: Regularly obtain the performance compression file reported by the base station;

[0013] Step 2: After obtaining the performance compressed file, decompress it and store it in a performance folder named with the combination of performance start time - performance end time + base station SN number;

[0014] Step 3: Read the content of each performance file in the performance folder into the temporary list object TempList, use regular expressions to collect the key data jobId, endTime, measType and measValue in TempList into the set TPMD, and store the data in the set TPMD. The jobId is the task number of each set of performance indicator tasks, the endTime is the end time of the corresponding performance indicator item collection, the measType is the performance indicator type, and the measValue is the performance indicator value;

[0015] Step 4: Create an EXCEL file in the performance folder and write the performance data in the set TPMD corresponding to each performance file into the sheet1 page.

[0016] The beneficial effects of the present invention are:

[0017] 1. The present invention can quickly analyze base station performance data when a problem occurs in the network management system.

[0018] 2. The present invention stores the reported data in the process of base stations, provides a temporary storage space for locating base station performance optimization problems, and avoids the loss of base station performance data.

[0019] 3. The present invention uses a regular expression method based on Python scripts to process, and the generated performance data displays key information to customers in EXCEL format, providing intuitive data results, which is convenient for customers to perform network optimization and fault location of base stations.

[0020] 4. The present invention has a simple architecture and can realize intuitive processing of performance files by users by only using simple Python scripts, and has high feasibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a structural diagram of a performance file processing platform of an extended pico base station according to an embodiment of the present invention.

[0022] Figure 2 It is a schematic diagram of a performance file list after a base station performance file compression package is decompressed in an embodiment of the present invention.

[0023] Figure 3 This is an example diagram of performance indicators in XML format in a base station performance file in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present invention will be further described in detail below in conjunction with the drawings and specific embodiments.

[0025] In the embodiments of the present invention, if there are directional indications (such as up, down, left, right, front, back, etc.), they are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0026] In addition, in the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0027] Please refer to Figure 1 The networking mode of the present invention is: the network management and the base station are connected through the network, the performance file processing platform of the present invention is deployed on a general server, and the server is connected to the base station and the network management platform through the network. The base station is a 5G extended pico base station. The network management is a network management system that can process 5G extended pico base stations.

[0028] Please refer to Figure 1 The performance file processing platform of the extended pico base station of the embodiment of the present invention includes a collection module, a decompression module, a processing module, and a creation module.

[0029] Collection module: Regularly obtains the performance compression files reported by base stations.

[0030] Decompression module: After obtaining the performance compressed file, decompress it and store it in a performance folder named with the combination of performance start time - performance end time + base station SN number. Figure 2 As shown, Figure 2 This is a schematic diagram of a performance file list after a base station performance file compression package is decompressed. The folder name is 20240414.0000+0800-20240414.0415+0800-CTSBU2303160001-NR. It means that the performance file collection start time under this performance folder is from 0:00 on April 14, 2024 to 04:15 on April 14, 2024, and the base station SN number is CTSBU2303160001-NR.

[0031] like Figure 3 As shown, Figure 3 This is an example diagram of performance indicators in XML format in the base station performance file, where jobId = 1, endTime is "2024-04-14T00:15:00+08:00", measType contains two indicators EE.BbuMeanPower and EE.NEMeanPower, and their corresponding values ​​are 185.000000 and 366.000000 respectively, and measObjLdn is "Type=gNB,gNBID=3407538".

[0032] In addition, it also has jobId = 2, endTime is "2024-04-14T00:15:00+08:00", measType contains three indicators EE.ChannelShutdownTimeRru, EE.CarrierShutdownTime and EE.SymbolShutdownTime, and the corresponding values ​​of the indicators are 0, 0 and 0 respectively, and measObjLdn is "Type=Cell,Mode=SA,gNBID=3407538,NrCI=31957275649,CUID=1".

[0033] The processing module traverses the performance files in the performance folder for processing. The processing module reads the content of each performance file in the performance folder into the temporary list object TempList, and uses regular expressions to collect the key data jobId, endTime, measType and measValue in TempList into the set TPMD. The jobId is the task number of each set of performance indicator tasks, and the endTime is the end time of the corresponding performance indicator item collection. The measType is the performance indicator type, that is, the name of the performance indicator. The measValue is the performance indicator value, that is, the value corresponding to measType.

[0034] As an implementation method, the jobId, endTime, measType and measValue are performance file keywords of the TS 32.594 protocol. measValue includes measObjLdn, and the field of measObjLdn indicates the object to which the performance statistics corresponding to each jobId belong.

[0035] As an implementation method, the measType includes one or more performance indicator type names, denoted as , where P k For a single performance indicator type, measValue contains the values ​​corresponding to one or more performance indicator names, recorded as , where VAL K is the value corresponding to a single performance indicator name. That is, each performance indicator P k The value is VAL K .

[0036] The processing module sorts the TPMD of each performance file in ascending order according to the endTime time corresponding to the performance file, and the set is , where TPMD j is the TPMD data of a single performance file. n is the number of performance files. Preferably, the endTime values ​​in all jobIds in a single performance file are consistent.

[0037] The processing module stores and processes the TPMD data, taking jobId as the key value, and stores jobId, endTime, measObjLdn, and Combined into a variable array TPSUB = [jobId, endTime, measObjLdn, , ], and then combine all variable arrays with jobId as key in descending order of jobId to form TPMD = , m is the number of jobIds in a single performance file.

[0038] Create module: Create an EXCEL file in the performance folder, and write the performance data in the set TPMD corresponding to each performance file into the sheet1 page. Specifically:

[0039] Traversal , RowIndex represents the current row, initialized to 1.

[0040] 1. Fill in the titles "Statistical Object" and "Indicator Name" in the zeroth column of the zeroth row and the first column of the zeroth row of the page respectively, and fill in endTime in the second column of the zeroth row.

[0041] 2. Then, traverse TPMD j In , TPSUB i The data is written into the pages of sheet1 in sequence. The specific method is:

[0042] 2.1 When j=1, traverse TPSUB i Corresponding and , according to TPSUB i measObjLdn、P k 、VAL k Sequentially, write to the zeroth column of the RowIndexth row, the first column of the RowIndexth row, and the second column of the RowIndexth row on the sheet1 page;

[0043] 2.2 When j > 1, traverse TPSUB i Corresponding and , according to TPSUB i P k 、VAL k Sequentially, write into the first column of the RowIndex row and the second column of the RowIndex row of sheet1 page.

[0044] Preferably, in the process of writing the above data into the sheet1 page, the RowIndex value increases by 1 each time a row of data is written into the sheet1 page.

[0045] When a problem occurs in the network management and the performance file of the base station cannot be processed, the user can quickly understand the performance data of the base station by querying the EXCEL table under the folder corresponding to the time period of the performance file processing platform of the present invention.

[0046] The performance file processing method of the extended pico base station according to the embodiment of the present invention includes steps 1 to 4.

[0047] Step 1: Regularly obtain the performance compression file reported by the base station.

[0048] Step 2: After obtaining the performance compressed file, decompress it and store it in a performance folder named with the combination of performance start time - performance end time + base station SN number.

[0049] Step 3: Traverse the performance files in the performance folder for processing.

[0050] (1) Read the file contents in the performance folder into the temporary list object TempList.

[0051] (2) Use regular expressions to obtain key information from TempList. The following is a regular expression defined in Python to obtain key performance information.

[0052] patterns = ' <job jobId="(\d+)" / > .+?' \

[0053] '<granPeriod.*?"(\S+)" / > .+?' \

[0054] ' <repperiod duration="(\S+)" / > .+?' \

[0055] '( <meastype p="\d+"> .*?< / meastype> .+?)' \

[0056] ' <measvalue measobjldn="(.*?)"> .+?' \

[0057] '( <r p="\d+"> .*?< / r> .+?)' \

[0058] '< / measvalue> '

[0059] ' <job jobId="(\d+)" / > .+?' means to get the value of jobId.

[0060] '<granPeriod.*?"(\S+)" / > .+?' means to get the time value of endTime,

[0061] '( <meastype p="\d+"> .*?< / meastype> .+?)' means to obtain all performance indicator names in measType.

[0062] <measvalue measobjldn="(.*?)">.+?' \

[0063] '( <r p="\d+"> .*?< / r> .+?)' \ These two lines of data represent the acquisition of all performance indicator values ​​in measObjLdn and measValue.

[0064] TPMD = re.findall(patterns, TempList, re.S) means using Python's re.findall function to collect all the key performance information in TempList at one time and store it in TPMD.

[0065] (3) Sort the key information of each performance file in ascending order according to the endTime value of the performance file. The set is: , where TPMD j is the TPMD data of a single performance file. n is the number of performance files.

[0066] (4) Store and process the TPMD data, using jobId as the key value, and store jobId, endTime, measObjLdn, and Combined into a variable array TPSUB = [jobId, endTime, measObjLdn, , ], then all variable arrays with jobId as key are combined in order from small to large jobId, and the resulting TPMD = , m is the number of jobIds in a single performance file.

[0067] For example: Figure 3 TPSUB corresponding to the two sets of jobId performance parameters i , after processing:

[0068] TPSUB1 = [1, "2024-04-14T00:15:00+08:00",

[0069] "Type=gNB,gNBID=3407538",

[0070] [EE.BbuMeanPower, EE.NEMeanPower],

[0071] [185.000000, 366.000000]]

[0072] TPSUB2 = [2, "2024-04-14T00:15:00+08:00",

[0073] "Type=Cell,Mode=SA,gNBID=3407538,NrCI=13957275649,CUID=1",

[0074] [EE.ChannelShutdownTimeRru, EE.CarrierShutdownTime,EE.SymbolShutdownTime],

[0075] [0, 0, 0]].

[0076] Step 4: Create an EXCEL file in the performance folder and write the performance data in the set TPMD corresponding to each performance file into the sheet1 page.

[0077] Traversal , RowIndex represents the current row, initialized to 1.

[0078] 1. Fill in the titles "Statistical Object" and "Indicator Name" in the zeroth column of the zeroth row and the first column of the zeroth row of the page respectively, and fill in endTime in the second column of the zeroth row.

[0079] 2. Then, traverse TPMD j In , TPSUB i The data is written into the pages of sheet1 in sequence. The method is:

[0080] 2.1 When j=1, traverse TPSUB i Corresponding and , according to TPSUB i measObjLdn、P k 、VAL k Sequentially, write to the zeroth column of the RowIndexth row, the first column of the RowIndexth row, and the second column of the RowIndexth row on the sheet1 page;

[0081] 2.2 When j > 1, traverse TPSUB i Corresponding and , according to TPSUB i P k 、VAL k Sequentially, write into the first column of the RowIndex row and the second column of the RowIndex row of sheet1 page.

[0082] When the above data is written to sheet1, the RowIndex value increases by 1 for each row of data written to sheet1.

[0083] Table 1 is an example of the effect of writing the performance data of jobId = 1 and 2 in two performance files into an EXCEL sheet page.

[0084]

[0085] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.< / measvalue>

Claims

1. A performance file processing platform for an extended pico base station, characterized in that: include: Collection module: regularly obtains performance compression files reported by base stations; Decompression module: After obtaining the performance compressed file, decompress it and store it in a performance folder named with the combination of performance start time - performance end time + base station SN number; Processing module: read the content of each performance file in the performance folder into the temporary list object TempList, use regular expressions to collect the key data jobId, endTime, measType and measValue in TempList into the set TPMD, and store the data in the set TPMD. The jobId is the task number of each set of performance indicator tasks, the endTime is the end time of the corresponding performance indicator item collection, the measType is the performance indicator type, and the measValue is the performance indicator value; Create module: Create an EXCEL file in the performance folder, and write the performance data in the set TPMD corresponding to each performance file into the sheet1 page; The jobId, endTime, measType and measValue are performance file keywords in the TS 32.594 protocol. measValue contains measObjLdn, and the field of measObjLdn indicates the object to which the performance statistics corresponding to each jobId belong; The measType contains one or more performance indicator type names, denoted as , where P k For a single performance indicator type, measValue contains the values ​​corresponding to one or more performance indicator names, recorded as , where VAL K It is the value corresponding to a single performance indicator name; The processing module sorts the set TPMD of each performance file in ascending order according to the endTime time corresponding to the performance file. The set is , where TPMD j is the aggregate TPMD data of a single performance file, and n is the number of performance files; The data of the set TPMD is stored and processed, with jobId as the key value, and jobId, endTime, measObjLdn, and Combined into a variable array TPSUB = [jobId, endTime, measObjLdn, , ], and then combine all variable arrays with jobId as key in descending order of jobId to form TPMD = , m is the number of jobIds in a single performance file; Creating a module traversal , RowIndex represents the current row, initialized to 1; Then fill in the title "Statistical Object" and "Indicator Name" in the zeroth column of the zeroth row and the first column of the zeroth row of sheet1 page, and fill in endTime in the second column of the zeroth row; Then traverse TPMD j In , TPSUB i The data is written into the pages of sheet1 in sequence, where: When j=1, traverse TPSUB i Corresponding and , according to TPSUB i measObjLdn、P k 、VAL k Sequentially, write to the zeroth column of the RowIndexth row, the first column of the RowIndexth row, and the second column of the RowIndexth row on the sheet1 page; When j > 1, traverse TPSUB i Corresponding and , according to TPSUB i P k 、VAL k Sequentially, write to the first column of the RowIndex row and the second column of the RowIndex row of sheet1 page; When writing data to sheet1, the RowIndex value increases by 1 for each row of data written to sheet1.

2. A performance file processing method for an extended pico base station, characterized in that: include: Step 1: Regularly obtain the performance compression file reported by the base station; Step 2: After obtaining the performance compressed file, decompress it and store it in a performance folder named with the combination of performance start time - performance end time + base station SN number; Step 3: Read the content of each performance file in the performance folder into the temporary list object TempList, use regular expressions to collect the key data jobId, endTime, measType and measValue in TempList into the set TPMD, and store the data in the set TPMD. The jobId is the task number of each set of performance indicator tasks, the endTime is the end time of the corresponding performance indicator item collection, the measType is the performance indicator type, and the measValue is the performance indicator value; Step 4: Create an EXCEL file in the performance folder and write the performance data in the set TPMD corresponding to each performance file into the sheet1 page; The jobId, endTime, measType and measValue are performance file keywords in the TS 32.594 protocol. measValue contains measObjLdn, and the field of measObjLdn indicates the object to which the performance statistics corresponding to each jobId belong; The measType contains one or more performance indicator type names, denoted as , where P k For a single performance indicator type, measValue contains the values ​​corresponding to one or more performance indicator names, recorded as , where VAL K It is the value corresponding to a single performance indicator name; In step 3, the set TPMD of each performance file is sorted in ascending order according to the endTime corresponding to the performance file, and the set is , where TPMD j is the aggregate TPMD data of a single performance file, and n is the number of performance files; The data of the set TPMD is stored and processed, with jobId as the key value, and jobId, endTime, measObjLdn, and Combined into a variable array TPSUB = [jobId, endTime, measObjLdn, , ], and then combine all variable arrays with jobId as key in descending order of jobId to form TPMD = , m is the number of jobIds in a single performance file; In step 4, first traverse , RowIndex represents the current row, initialized to 1; Then fill in the title "Statistical Object" and "Indicator Name" in the zeroth column of the zeroth row and the first column of the zeroth row of sheet1 page, and fill in endTime in the second column of the zeroth row; Then traverse TPMD j In , TPSUB i The data is written into the pages of sheet1 in sequence, where: When j=1, traverse TPSUB i Corresponding and , according to TPSUB i measObjLdn、P k 、VAL k Sequentially, write to the zeroth column of the RowIndexth row, the first column of the RowIndexth row, and the second column of the RowIndexth row on the sheet1 page; When j > 1, traverse TPSUB i Corresponding and , according to TPSUB i P k 、VAL k Sequentially, write to the first column of the RowIndex row and the second column of the RowIndex row of sheet1 page; When writing data to sheet1, the RowIndex value increases by 1 for each row of data written to sheet1.

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