Self-service operation and maintenance method serving 5G private network industry application

Abstract

A self-service operation and maintenance method serving 5G private network industry application performs application integration on network states, particularly integrates 5G industry private network management data, builds a network operation and maintenance platform serving enterprise users, and changes the current situation that the network operation state in an operator is invisible to the enterprise users so as to meet the self-service operation and maintenance requirements of the enterprises. The method is characterized by comprising the following steps of: 1, accessing network states of various specialties of the 5G industry private network distributed on different network management systems by using a data acquisition module, integrating and converging according to services, and constructing a network management data layer of the 5G industry private network; step 2, according to service requirements, performing association calculation on data in the 5G industry private network management data layer, and constructing a service capability layer; and step 3, packaging the business capability in the business capability layer into an application layer, wherein the application layer comprises a self-service operation and maintenance PC large screen and a self-service operation and maintenance APP page.

Description

Technical Field

[0001] This invention relates to the field of 5G private network operation and maintenance technology, and in particular to a self-service operation and maintenance method for 5G private network industry applications. By integrating network status applications, especially integrating 5G industry private network management data, a network operation and maintenance platform serving enterprise users is built. This changes the current situation where the network operation status within the operator is invisible to enterprise customers, thereby meeting the self-service operation and maintenance needs of enterprises and greatly ensuring the business production of enterprise users. Background Technology

[0002] In the 5G private network business field (5G, 5th Generation Mobile Communication Technology), network quality is closely related to enterprise production activities. Network anomalies often lead to serious impacts such as production halts or even shutdowns. To ensure smooth production, enterprises typically organize relevant operation and maintenance teams to maintain and support the network. However, due to information asymmetry and the limitations of operators' specialized knowledge, enterprise operation and maintenance teams find it difficult to effectively carry out network operation and maintenance work. Specifically, information asymmetry refers to the inability to communicate the network quality status of the 5G private network with the enterprise's network platform on the operator's internal network management network. Furthermore, since the network status of various specialties within the 5G private network is distributed across different network management systems (including transmission, wireless, and core specialties), it is necessary to integrate and aggregate various network statuses according to business needs and output content that is easy for enterprise users to understand and use to better support enterprise network operation and maintenance work. Based on the above requirements and problems, this invention integrates network status applications and provides a self-service operation and maintenance method for 5G private network industry applications to meet the self-service operation and maintenance needs of enterprises.

[0003] After searching, the relevant existing technologies are listed below:

[0004] Patent document CN202310838271.3, "A 5G Private Network Empowerment Platform," proposes a 5G private network empowerment platform that enables the integration of 5G networks and other network facilities into an infrastructure that connects the network with applications. Based on the requirements of 5G private networks, including infrastructure fixed-mobile convergence, multi-type resource scheduling and service orchestration, network digital twins and fault early warning, private network sharing, and edge capability openness, the platform realizes an infrastructure based on the integration of 5G networks and other network facilities. It specifically forms network application templates, orchestrates network, computing, data, and operation and maintenance services, and encapsulates various service capabilities for use within the private network, between private networks, and uplink service centers for capability invocation and agile application development. This addresses four key issues in the platformization of 5G private network services: infrastructure fixed-mobile convergence, multi-type infrastructure resource scheduling and service orchestration, network digital twins and fault early warning, private network sharing, and edge capability openness mechanisms.

[0005] Although the above technical solutions have achieved certain results in their respective application scenarios, there are also some obvious problems as follows: (1) In terms of network operation and maintenance capabilities, although the above solutions mention network operation and maintenance services, they are only microservices in the business platform and cannot provide targeted empowerment for network operation and maintenance. They do not provide detailed network operation and maintenance work elements, methods or processes, and cannot meet the needs of enterprise network operation and maintenance. (2) In terms of the implementation of self-service operation and maintenance technology, the above solutions do not mention the relevant implementation technologies and implementation content. Summary of the Invention

[0006] This invention addresses the shortcomings or defects in existing technologies by providing a self-service operation and maintenance method for 5G private network industry applications. By integrating network status applications, especially integrating 5G industry private network management data, a network operation and maintenance platform serving enterprise users is built. This changes the current situation where the network operation status within operators is invisible to enterprise customers, thereby meeting the self-service operation and maintenance needs of enterprises and greatly ensuring the business production of enterprise users.

[0007] The technical solution of the present invention is as follows:

[0008] A self-service operation and maintenance method for 5G private network industry applications, characterized by the following steps:

[0009] Step 1: Use the data acquisition module to access the network status of various specialties of the 5G industry private network distributed on different network management systems and integrate and aggregate them according to the business to build a 5G industry private network management data layer.

[0010] Step 2: Based on business needs, perform correlation calculations on the data in the 5G industry private network management data layer to construct the business capability layer;

[0011] Step 3: Encapsulate the business capabilities in the business capability layer into an application layer. The application layer includes a self-service operation and maintenance PC screen and a self-service operation and maintenance APP page. By making the network operation status inside the operator visible to enterprise users, the self-service operation and maintenance needs of enterprise users are met, thereby ensuring the business production of enterprise users.

[0012] In step 1, the data sources and data types in the 5G industry private network management data layer include: cell base stations, UPF core network elements, transmission network elements, leased lines, and service platforms; the data types include: project information, SIM card activation information, network resources, network performance, and network alarms.

[0013] Step 2 includes the following service capability layer: service model analysis, leased line status analysis, alarm monitoring, alarm statistics, wireless network quality monitoring, transmission network quality monitoring, core network quality monitoring, alarm query, monitoring map, and service topology.

[0014] Step 3 involves using a browser to request a self-service operation and maintenance PC dashboard page from the 5G private network industry operation and maintenance platform through the enterprise operation and maintenance platform, and the 5G private network industry operation and maintenance platform returning the self-service operation and maintenance PC dashboard page to the browser through the enterprise operation and maintenance platform.

[0015] Step 3 includes using a mobile terminal to request a self-service operation and maintenance APP page from the 5G private network industry operation and maintenance platform through the enterprise operation and maintenance platform, and the 5G private network industry operation and maintenance platform returning the self-service operation and maintenance APP page to the mobile terminal through the enterprise operation and maintenance platform.

[0016] Step 2 involves the following association calculations: the alarm data module and the cell-level performance module are associated with the cell resource module using unique cell identifiers; the tracking area dimension performance module is associated with the cell resource module using tracking area identifiers; the slice-level performance module is associated with the cell resource module using slice service identifiers; the transmission network element port dimension performance module is associated with the transmission network resource module using transmission device port names; the UPF slice dimension performance module and the UPF performance module are associated with the UPF resource module using unique UPF network management identifiers; the UPF slice dimension performance module is associated with the project information module using slice service identifiers; and the leased line resource module is associated with the leased line performance module using leased line service identifiers.

[0017] The technical effects of the present invention are as follows: (1) The key point of the present invention is that the current 5G industry private network is a kind of enterprise private network, and the network operation status inside the operator is invisible to enterprise customers. However, the network status is crucial to the production work of enterprises. The present invention innovatively integrates the network management data of the 5G industry private network, builds a network operation and maintenance platform for enterprise users, and opens it to enterprise customers, which greatly protects the business production of enterprises. (2) The network management scope mentioned in the present invention includes card opening and account opening, cell base station, UPF network element, transmission network element, leased line, and service platform. These are the key contents of realizing the operation and maintenance method of the present invention. The present invention integrates the resources, performance and alarm data of these network components, outputs business scale analysis, network quality, alarm monitoring and other contents, and carries out multi-angle, real-time and all-round operation and maintenance management of the network. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the self-service operation and maintenance architecture involved in implementing the self-service operation and maintenance method for 5G private network industry applications according to the present invention. Figure 1UPF stands for User Plane Function.

[0019] Figure 2 This is a schematic diagram of the data layer model relationships involved in implementing the self-service operation and maintenance method for 5G private network industry applications according to the present invention. Figure 2 In the ciphertext, PK is the primary key, FK is the foreign key, NR-CELL is the New Radio Cell, UPF is the User Plane Function, L3VPN is the Layer 3 Virtual Private Network, RMUID is the Resource Object Global Identifier, and DNN is the Data Network Name.

[0020] Figure 3 This is an application access sequence diagram involved in implementing the self-service operation and maintenance method for 5G private network industry applications according to the present invention. Figure 3 The process includes step 1, where the browser / APP requests the PC large screen page (PC is a computer) from the 5G private network industry operation and maintenance platform through the enterprise operation and maintenance platform; and step 2, where the 5G private network industry operation and maintenance platform returns the PC large screen page / APP page to the browser / APP through the enterprise operation and maintenance platform. Detailed Implementation

[0021] The following is in conjunction with the attached diagram ( Figures 1-3 The invention will be described in the following sections and examples.

[0022] Figure 1 This is a schematic diagram of the self-service operation and maintenance architecture involved in implementing the self-service operation and maintenance method for 5G private network industry applications according to the present invention. Figure 2 This is a schematic diagram of the data layer model relationships involved in implementing the self-service operation and maintenance method for 5G private network industry applications according to the present invention. Figure 3 This is an application access sequence diagram involved in implementing a self-service operation and maintenance method for 5G private network industry applications according to the present invention. (Reference) Figures 1 to 3 As shown, a self-service operation and maintenance method for 5G private network industry applications includes the following steps: Step 1, using a data acquisition module to access and integrate the network status of various specialties of the 5G private network distributed on different network management systems according to services, and construct a 5G private network management data layer; Step 2, according to business needs, performing correlation calculations on the data in the 5G private network management data layer to construct a business capability layer; Step 3, encapsulating the business capabilities in the business capability layer into an application layer, which includes a self-service operation and maintenance PC screen and a self-service operation and maintenance APP page. By making the network operation status inside the operator visible to enterprise users, the self-service operation and maintenance needs of enterprise users are met, thereby ensuring the business production of enterprise users.

[0023] In Step 1, the data sources and data types in the 5G industry private network management data layer include: cell base stations, UPF core network elements, transmission network elements, leased lines, and service platforms; the data types include: project information, SIM card activation information, network resources, network performance, and network alarms. Step 2, the service capability layer, includes: service model analysis, leased line status analysis, alarm monitoring, alarm statistics, wireless network quality monitoring, transmission network quality monitoring, core network quality monitoring, alarm query, monitoring map, and service topology.

[0024] Step 3 includes using a browser to request a self-service maintenance PC dashboard page from the 5G private network industry maintenance platform through the enterprise maintenance platform, and the 5G private network industry maintenance platform returning the self-service maintenance PC dashboard page to the browser through the enterprise maintenance platform. Step 3 also includes using a mobile terminal to request a self-service maintenance APP page from the 5G private network industry maintenance platform through the enterprise maintenance platform, and the 5G private network industry maintenance platform returning the self-service maintenance APP page to the mobile terminal through the enterprise maintenance platform.

[0025] Step 2 involves the following association calculations: the alarm data module and the cell-level performance module are associated with the cell resource module using unique cell identifiers; the tracking area dimension performance module is associated with the cell resource module using tracking area identifiers; the slice-level performance module is associated with the cell resource module using slice service identifiers; the transmission network element port dimension performance module is associated with the transmission network resource module using transmission device port names; the UPF slice dimension performance module and the UPF performance module are associated with the UPF resource module using unique UPF network management identifiers; the UPF slice dimension performance module is associated with the project information module using slice service identifiers; and the leased line resource module is associated with the leased line performance module using leased line service identifiers.

[0026] This invention relates to the field of 5G industry private network technology and quality, and further to the field of comprehensive operation and maintenance application of 5G private networks in the industry. It is a self-service operation and maintenance device and method based on the 5G network quality system.

[0027] This invention provides specific solutions, including the required network management resources and specific application capabilities, to deliver practical value to users.

[0028] This invention proposes a self-service operation and maintenance device for 5G private network industry applications, the main technical implementation architecture of which is as follows: Figure 1 It is divided into 3 layers.

[0029] The overall strategy of this invention is to first build a data layer function by using a data acquisition module, then combine the data layer function with business needs to form a business capability layer, and finally encapsulate the business capabilities into a large screen and APP application to form a self-service tool for users.

[0030] The first step is to connect with relevant network management systems and build data layer capabilities.

[0031] Data access is achieved through SFTP (Secure File Transfer Protocol) and HTTP (Hypertext Transfer Protocol) interfaces. The data includes...

[0032] Table 1: Community Resources

[0033]

[0034] Table 2: UPF Resources

[0035]

[0036]

[0037] Table 3: Transmission Network Resources

[0038] English name Chinese name Character type province_id Province character city_id City character l3vpn_point_name L3VPN Access Point Name (L3VPN, Layer 3 Virtual Private Network) character l3vpn_point_id L3VPN Access Point Identifier character customer_name Customer Name character customer_id Customer Code character project_name Project Name character factory Factory area character a_trans_ne Name of A-end transmission equipment character a_trans_port A-end transmission device port name character a_trans_ne_rmuid A-end transmission device RMUID character a_trans_port_rmuid A-end transmission device port RMUID character z_equip_one Z-end device 1 name character z_port_one Z-end device 1 port name character z_equip_two Z-end device 2 name character z_port_two Z-end device 2 port name character z_equip_one_rmuid Z-end device 1RMUID character z_port_one_rmuid Z-end device 1 port RMUID character z_equip_two_rmuid Z-end device 2RMUID character z_port_two_rmuid Z-end device 2-port RMUID character

[0039] Table 4: Dedicated Line Resources

[0040]

[0041]

[0042] Table 5: Project Information

[0043]

[0044]

[0045] Table 6: Cell-level performance

[0046]

[0047]

[0048] Table 7: Slice-level performance

[0049]

[0050]

[0051] Table 8: UPF Performance

[0052]

[0053] Table 9: UPF Slice Dimensional Performance

[0054]

[0055]

[0056] Table 10: Tracking Region Dimension Performance

[0057] parameter Parameter Description Data types serviceCode Province Code character tac Tracking area identifier, associated with radio resources character AMF_AttInitReg_Ta Number of initial registration requests by tracking zone numerical values AMF_SuccInitReg_Ta Number of initial registration successes by tracking zone numerical values AMF_PagAtt_Ta Number of paging requests by tracking area numerical values AMF_FirstPagingSucc_Ta Number of paging responses per tracking area numerical values AMF_SecondPagingSucc_Ta Number of secondary paging responses in the tracking area numerical values granularity Time granularity numerical values statisticalTime Statistical time time

[0058] Table 11: Performance of Transmission Network Element Port Dimensions

[0059] parameter Parameter Description Data types serviceCode Province Code character rmuid Port acquisition identifier, associated transmission resources character inErrors Number of received error messages numerical values inPkts Number of received messages numerical values outOctets Number of bytes sent numerical values inOctets Number of bytes received numerical values granularity Time granularity numerical values statisticalTime Statistical time time

[0060] Table 12: Dedicated Line Performance

[0061]

[0062]

[0063] Table 13: Alarm Data

[0064]

[0065]

[0066] Using the data from Table 1 (cell resources), Table 2 (UPF resources), Table 3 (transmission network resources), Table 4 (leased line resources), Table 5 (project information), Table 6 (cell-level performance), Table 7 (slice-level performance), Table 8 (UPF performance), Table 9 (UPF slice-dimensional performance), Table 10 (tracking area-dimensional performance), Table 11 (transmission network element port-dimensional performance), Table 12 (leased line performance), and Table 13 (alarm data), a data layer model is constructed. See Table 13 for the data layer model relationships. Figure 2 .

[0067] The second step is to perform correlation calculations on the data based on business needs and build a business capability layer.

[0068] Business scale analysis:

[0069] We summarize and analyze the number of DNNs, business slices, and card issuances, including changes in the number by province and time period.

[0070] Dedicated line status analysis:

[0071] Statistical analysis was performed on the total number of dedicated lines, the number of normal lines, and the number of abnormal lines.

[0072] Normal / Abnormal Dedicated Line Count: Dedicated lines with activity alarms in the last 2 hours are considered abnormal; otherwise, they are considered normal. The count is based on the product instance identifier and the associated province and city.

[0073] Statistical analysis of leased line performance was conducted at time granularities of 15 minutes, hours, and days, including: traffic (MB / GB…), uplink bandwidth utilization (%), downlink bandwidth utilization (%), uplink speed (Mbps / kbps…), downlink speed (Mbps / kbps…) and their trend changes.

[0074] Query the dedicated line resource table to obtain the dedicated line product instance identifier and the province, city, and factory area information to which it belongs. Use the product instance identifier to query the dedicated line performance table to obtain all dedicated line performance data, which is then aggregated according to the dimensions of dedicated line, province, and country.

[0075] Flow rate (accurate to two decimal places), algorithm: inflow flow rate + outflow flow rate, with unit conversion;

[0076] Uplink bandwidth utilization, downlink bandwidth utilization, uplink speed, downlink speed; Algorithm: Calculate the average.

[0077] For 15-minute, hourly, and daily granularities, the number of 5-minute granularities within the period needs to be summed before calculating using the formula above.

[0078] Wireless network quality monitoring:

[0079] Statistical analysis was performed on the number of base stations, the number of normal stations, and the number of abnormal stations.

[0080] Statistical analysis of wireless network performance was performed at time granularities of 15 minutes, hours, and days, including: wireless connection success rate (%), wireless call drop rate (%), handover success rate (%), average uplink PRB utilization (%), average downlink PRB utilization (%), RRC connection success rate (%), RRC connection reconstruction rate (%), uplink traffic data volume at slice RLC layer (Mb), downlink traffic data volume at slice RLC layer (Mb), QoSFlow establishment success rate in slice (%), and QoSFlow call drop rate (%).

[0081] Number of base stations: Statistics on base station names, categorized by associated province and city.

[0082] Normal / Abnormal Base Station Count: Base stations with activity alarms in the last 2 hours are considered abnormal; otherwise, they are considered normal. The count is based on the base station name and the associated province and city.

[0083] For hourly and daily granularity, the number of granularities within the 15-minute intervals needs to be summed before calculating according to the formula.

[0084] Cell-level metrics aggregation at the base station, province, and national levels: Query the cell resource table to obtain the cell n_cgi and its associated province, base station, city, and factory information (n_cgi, NR Cell Global Identifier, NR, New Radio). Use n_cgi to query the cell performance table to obtain all cell performance data, and aggregate them according to the base station, province, and national levels.

[0085] Slice-level metrics aggregation by province and national dimension: Query the project resource table to obtain the slice service identifier and its province, city, and factory information. Query the slice-level wireless performance table to obtain all slice performance data, and aggregate it by province and national dimension.

[0086] Wireless disconnection rate (accurate to 4 decimal places):

[0087] Algorithm: ΣgNB request release context count - Σ normal gNB request release context count) / (Σ initial context establishment success count + Σ legacy context count + Σ handover success count + Σ RRC connection reconstruction success count (non-source cell)) * 100%.

[0088] Wireless connection success rate (accurate to 4 decimal places):

[0089] Algorithm: RRC connection establishment success rate * QoS Flow connection establishment success rate * NG interface UE-related logical signaling connection establishment success rate;

[0090] RRC connection establishment success rate = Σ number of successful RRC connection establishments / Σ number of RRC connection establishment requests * 100%;

[0091] QoS Flow establishment success rate = Σ number of successful Flow establishments / Σ number of Flow establishment requests * 100%;

[0092] Success rate of establishing NG interface UE-related logical signaling connection = ΣNumber of successful establishment of NG interface UE-related logical signaling connection / ΣNumber of NG interface UE-related logical signaling connection establishment requests * 100%.

[0093] Switching success rate (accurate to 4 decimal places):

[0094] Algorithm: (Total number of successful NG handovers between gNBs + Total number of successful Xn handovers between gNBs + Total number of successful DU handovers within CUs + Total number of successful handovers within DUs) / (Total number of NG handover preparation requests between gNBs + Total number of Xn handover preparation requests between gNBs + Total number of DU handover execution requests within CUs + Total number of DU handover execution requests within DUs) * 100%.

[0095] Average uplink PRB utilization (accurate to 4 decimal places):

[0096] Algorithm: Σ Uplink PUSCH PRB occupied / Σ Uplink PUSCH PRB available * 100%.

[0097] Downlink PRB average utilization (accurate to 4 decimal places):

[0098] Algorithm: Σ Downlink PUSCH PRB Occupied Number / Σ Downlink PUSCH PRB Available Number * 100%.

[0099] RRC connection reconstruction ratio (accurate to 4 decimal places):

[0100] Algorithm: ΣRRC connection reconstruction success count (non-source cell) / (ΣRRC connection reconstruction request count + ΣRRC connection establishment request count) * 100%.

[0101] RRC connection success rate (accurate to 4 decimal places):

[0102] Algorithm: (ΣRRC connection establishment successes / ΣRRC connection establishment requests) * 100%.

[0103] Uplink traffic data volume at the sliced ​​RLC layer, downlink traffic data volume at the sliced ​​RLC layer (accurate to two decimal places):

[0104] To sum the raw data directly, note that the unit (bits) conversion is multiplication and division by 1000.

[0105] QosFlow success rate in slices (accurate to 4 decimal places):

[0106] Algorithm: (ΣFlow establishment success rate / ΣFlow establishment request rate) * 100%.

[0107] QoSFlow call drop rate (accurate to 4 decimal places):

[0108] Algorithm: (Σ number of abnormal releases of QoS Flow for network slices within the cell / (Σ number of abnormal releases of QoS Flow for network slices within the cell + Σ number of normal releases of QoS Flow for network slices within the cell) * 100%.

[0109] Transmission network quality monitoring:

[0110] Provides statistical analysis of transmission error rate (%), uplink traffic (MB), and downlink traffic (MB), including 15-minute, hourly, and daily granularity;

[0111] For hourly and daily granularity, the number of granularities within the 15-minute intervals needs to be summed before calculating according to the formula.

[0112] Port-level metrics aggregation by province and country: Query the transmission network resource table to obtain the port rmid and its province, city, and factory information at the AZ end. Use the port rmid to query the transmission network performance table to obtain all port performance data, and aggregate them by province and country.

[0113] Transmission error rate (accurate to 4 decimal places):

[0114] Algorithm: sum(inErrors) / sum(inPkts)*100%.

[0115] Uplink traffic (accurate to two decimal places):

[0116] Algorithm: sum(outOctets from A side + inOctets from Z side) / number of data items in A, Z, and Z sides);

[0117] The Z-end requires summing ports Z1 and Z2;

[0118] Units must support automatic conversion; the conversion of byte counts should be multiplied or divided by 1024.

[0119] Downlink traffic (accurate to two decimal places):

[0120] Algorithm: sum(A-side inOctets + Z-side outOctets) / number of data points in A, Z, and Z sides);

[0121] The Z-end requires summing ports Z1 and Z2;

[0122] Units must support automatic conversion; the conversion of byte counts should be multiplied or divided by 1024.

[0123] Core network quality monitoring:

[0124] Statistical analysis was performed on the total number of UPFs, the number of normal values, and the number of outliers.

[0125] Analyze UPF metrics, including: UPF total throughput (Mbps), UPF throughput utilization (%), N6 interface received traffic (MB), N6 interface transmitted traffic (MB), session establishment success rate (%), initial registration success rate (%), and paging success rate (%), supporting 15-minute, hourly, and daily granularity.

[0126] UPF Count: Statistics on UPF names, categorized by associated province and city.

[0127] Normal / Abnormal UPF Count: UPFs with activity alerts in the last 2 hours are considered abnormal; otherwise, they are considered normal. The count is based on the UPF name and the associated province and city.

[0128] UPF overall throughput: Get the maximum data throughput in the UPF resource data.

[0129] For hourly and daily granularity, the number of granularities within the 15-minute intervals needs to be summed before calculating using the formula above.

[0130] UPF dimensional metrics aggregate UPF, provincial, and national metrics: UPF resource table, obtain UPF name, RUMUID, UPF total throughput, and information on the province, city, and factory to which it belongs; use RMUID to query the UPF performance table to obtain all UPF performance data, aggregated according to UPF, provincial, and national dimensions.

[0131] Slice-level metrics aggregation by province and national dimension: Query the project resource table to obtain the slice service identifier and its province, city, and factory information. Query the slice-level wireless performance table to obtain all slice performance data, and aggregate it by province and national dimension.

[0132] The tracking area-based performance metrics are aggregated by province and country: Query the cell resource table to obtain the cell tac and its associated province, city, and factory area information (tac, Tracking Area Code). Use the tac to query the tracking area performance table to obtain all tracking area performance data, and aggregate them by province and country.

[0133] UPF throughput utilization (%) (accurate to two decimal places):

[0134] Algorithm: Σ(Number of bytes received by N6 interface * 8 + Number of bytes sent by N6 interface * 8) / ΣUPF total throughput * Granularity of numerator * 100%.

[0135] If the molecular particle size is 15 minutes, then 15 * 60 is needed, which is converted to seconds.

[0136] The throughput unit is Mbps, which needs to be converted to bps before calculation.

[0137] PFCP session establishment success rate (%) (accurate to two decimal places):

[0138] Algorithm: ΣPFCP session establishment success count / ΣPFCP session establishment request count * 100%.

[0139] PFCP session modification success rate (%) (accurate to two decimal places):

[0140] Algorithm: ΣPFCP session modification success count / ΣPFCP session modification request count * 100%.

[0141] N6 port received traffic (accurate to 2 decimal places):

[0142] Algorithm: Number of bytes received by the ΣN6 interface;

[0143] Units must support automatic conversion; the conversion of byte counts should be multiplied or divided by 1024.

[0144] N6 port data transmission traffic (accurate to 2 decimal places):

[0145] Algorithm: Number of bytes sent via the ΣN6 interface;

[0146] Units must support automatic conversion; the conversion of byte counts should be multiplied or divided by 1024.

[0147] Session establishment success rate per segment (SMF) (%) (accurate to two decimal places):

[0148] Algorithm: Σ number of successful session establishments per slice / Σ number of session establishment requests per slice * 100%.

[0149] Initial registration success rate (%) by tracking area (accurate to two decimal places):

[0150] Algorithm: Σ number of successful initial registrations in the tracking zone / Σ number of initial registration requests in the tracking zone * 100%.

[0151] Paging success rate in the tracking area (%) (accurate to two decimal places):

[0152] Algorithm: (Σ number of successful first paging attempts in the tracking area + Σ number of successful second paging attempts in the tracking area / Σ total number of paging attempts in the tracking area * 100%)

[0153] Alarm monitoring:

[0154] Perform statistical analysis on the current number of alarms, the number of new alarms today, and the average clearing time (hours);

[0155] Drill down the alarm list using statistical data, including: alarm name, device type, device name (translated name), province of origin, alarm level, alarm time, and impact on business operations (the impact of the event on business).

[0156] 5G alarm-related service methods:

[0157] Filter 5G device alarms by associating the alarm scope and network element type (such as AMF, Access and Mobility Management Function; SMF, Session Management Function) with the alarm location object type in the alarm data;

[0158] Then, using the alarm location object name or alarm location object SDN, associate the cell name and cell N-CGI of the cell resources, the base station name and base station RMUID, and the UPF name and UPF RMUID of the UPF resources. Cell alarms need to be attributed to the base station, meaning subsequent alarm outputs and statistics will be used as relevant base station data.

[0159] After establishing the connection, further information such as the cell, base station, UPF's associated project, customer, and province is linked.

[0160] 5G transmission alarm associated service method:

[0161] 5G transmission alarms are now restricted from being reported to the provincial level for alarms belonging to the current enterprise's 5G private network. They can be output without being associated with any business, and information such as the province and city in the alarm can be directly obtained.

[0162] Dedicated line alarm association service method:

[0163] The dedicated line has been associated with the business. You can associate the dedicated line resource with the product instance identifier in the alarm, and then obtain information such as the customer, province, and city.

[0164] Current alarm count: alarms that occurred within the last 24 hours are included. Alarms whose clearing time has not been filled in are counted based on the consecutive message sequence number (centralized fault alarm serial number) and the province and city fields of the associated project.

[0165] New additions today: alarms that occurred on the same day are retrieved from the alarm data and are counted based on the consecutive message sequence number (centralized fault alarm serial number) and the province and city fields of the associated project.

[0166] Average clearing time (hours): Using alarm data from the past month, the average clearing time = Σ alarm clearing time / total number of alarms cleared; alarm clearing time = alarm clearing time - event occurrence time, accurate to two decimal places, and is calculated based on the consecutive message sequence number (centralized fault alarm serial number) and the province and city fields of the associated project.

[0167] Create a network element device name translation configuration table (used by other modules). When outputting alarm data, it is necessary to output according to the configured network element name to facilitate understanding by enterprise users. Network elements include UPF, base station, transmission network elements, etc., without limiting the type.

[0168] If no matching network element name is found, the original network element name will be output.

[0169] The alarm query output list includes fields such as: alarm title (in link form), device type, device name (device translated name), alarm level, alarm time, and alarm status. The fields displayed in the list can be configured.

[0170] The default alarm list is sorted in descending order by alarm time (event occurrence time) and supports pagination.

[0171] The output and statistics of alarms need to be configured through an alarm translation configuration table to facilitate understanding and use by enterprise users. Alarms are matched according to the standard alarm number (network management alarm ID), and alarms that do not match are not output or counted.

[0172] Alarm statistics:

[0173] It supports outputting statistics such as total number of alarms (last month), number of alarms occurring, number of active alarms, number of alarm orders (last month), and average clearing time (hours) (last month), and supports switching to other time periods to view trend analysis.

[0174] Total alarm count: This count is based on alarm data from the past month, using consecutive message sequence numbers (centralized fault alarm serial numbers) and the province and city fields of the associated projects.

[0175] Alarm dispatch count: Take alarms from the alarm data of the past month that have a non-empty work order number, and count them based on the consecutive message sequence number (centralized fault alarm serial number) and the province and city fields of the associated project.

[0176] Average clearing time: Using alarm data from the past month, the average clearing time = Σ alarm clearing time / total number of alarms; alarm clearing time = alarm clearing time - event occurrence time, accurate to two decimal places, and is statistically calculated based on the consecutive message sequence number (centralized fault alarm serial number) and the province and city fields of the associated project.

[0177] Alarm occurrence count: Data on events occurring on the current day / month is collected from the alarm data and counted based on the sequence number of consecutive messages (centralized fault alarm serial number) and the province and city fields of the associated projects.

[0178] Surveillance map:

[0179] The map regions are highlighted according to the provinces where the company's business is located, while the map regions that are not business provinces are disabled.

[0180] The map displays provinces and regions in a persistent floating display, along with data for base stations (number of alarm devices / total number of devices), UPF (number of alarm devices / total number of devices), and leased lines (number of alarm devices / total number of devices). For detailed data, please refer to the alarm statistics section.

[0181] Based on the province and city of the dedicated line AZ end, the map areas of each province and city are connected by fly lines. By default, the dedicated line fly line connection is displayed with the customer's headquarters as the center. Clicking on the map of other provinces will switch the fly line to the dedicated line from the current province to other provinces. If a province has multiple city points, there should be multiple map points. The fly line color is green to indicate that the dedicated line has no alarms, and red to indicate that there are alarms.

[0182] When a province or region is selected on the map, related applications can filter the current data and indicate (province) after the relevant module title.

[0183] Business Topology:

[0184] The network connection relationships of services are presented in a topological manner, and related network elements are associated with them.

[0185] Supports network element alarm bubbling rendering.

[0186] Render the bubbling color (red, orange, yellow, blue) according to the highest alarm level.

[0187] It supports displaying the number of alarms in a bubble format, with a maximum display of 99+.

[0188] Supports querying of bubbling update alarm monitoring applications.

[0189] Alarms are associated with the alarm location object by the network element name in the topology.

[0190] The third step is to open it up to enterprise operations and maintenance through the APP and application interface.

[0191] Table 14: Page List

[0192]

[0193] according to Figure 3 The content and process are described as follows:

[0194] 1) Enterprise users log in to access the enterprise operation and maintenance platform, and the system completes login authentication and permission management.

[0195] 2) When a user accesses a PC screen / APP page, the enterprise operation and maintenance platform converts the URL (Uniform Resource Locator), calculates the token, etc., and sends a request to the 5G private network industry operation and maintenance platform.

[0196] 3) The 5G private network industry operation and maintenance platform verifies the legitimacy of the request and returns a page after successful verification.

[0197] 4) The enterprise operation and maintenance platform displays and outputs the page.

[0198] This invention proposes a self-service network operation and maintenance device for 5G private network industry users. Its key feature is that, as a type of enterprise private network, the network operation status within the operator's network is invisible to enterprise customers, yet the network status is crucial to the enterprise's production operations. This solution innovatively integrates 5G private network management data, building a network operation and maintenance platform that serves enterprise users and is open to them, greatly ensuring the enterprise's business operations.

[0199] The network management scope mentioned in this invention includes 5G private network services, cell base stations, UPF network elements, transmission network elements, leased lines, and service platforms. These are the key components of the operation and maintenance device. The solution integrates the resource, performance, and alarm data of these network components to output service scale analysis, network quality, alarm monitoring, and other content, enabling multi-angle, real-time, and comprehensive operation and maintenance management of the network.

[0200] The 5G private network industry self-service network operation and maintenance platform built by this invention provides services to enterprise customers through PC large screen pages and APP applications.

[0201] Contents not described in detail in this specification are prior art known to those skilled in the art. It is hereby indicated that the above description is intended to help those skilled in the art understand this invention, but does not limit the scope of protection of this invention. Any equivalent substitutions, modifications, improvements, and / or simplifications of the above descriptions that do not depart from the essential content of this invention fall within the scope of protection of this invention.

Claims

1. A self-service operation and maintenance method for 5G private network industry applications, characterized in that, Includes the following steps: Step 1: Use the data acquisition module to access the network status of various specialties of the 5G industry private network distributed on different network management systems and integrate and aggregate them according to the business to build a 5G industry private network management data layer. Step 2: Based on business needs, perform correlation calculations on the data in the 5G industry private network management data layer to construct the business capability layer; Step 3: Encapsulate the business capabilities in the business capability layer into an application layer. The application layer includes a self-service operation and maintenance PC screen and a self-service operation and maintenance APP page. By making the network operation status inside the operator visible to enterprise users, the self-service operation and maintenance needs of enterprise users are met, thereby ensuring the business production of enterprise users.

2. The self-service operation and maintenance method for 5G private network industry applications according to claim 1, characterized in that, In step 1, the data sources and data types in the 5G industry private network management data layer include: cell base stations, UPF core network elements, transmission network elements, leased lines, and service platforms; the data types include: project information, SIM card activation information, network resources, network performance, and network alarms.

3. The self-service operation and maintenance method for 5G private network industry applications according to claim 1, characterized in that, Step 2 includes the following service capability layer: service model analysis, leased line status analysis, alarm monitoring, alarm statistics, wireless network quality monitoring, transmission network quality monitoring, core network quality monitoring, alarm query, monitoring map, and service topology.

4. The self-service operation and maintenance method for 5G private network industry applications according to claim 1, characterized in that, Step 3 involves using a browser to request a self-service operation and maintenance PC dashboard page from the 5G private network industry operation and maintenance platform through the enterprise operation and maintenance platform, and the 5G private network industry operation and maintenance platform returning the self-service operation and maintenance PC dashboard page to the browser through the enterprise operation and maintenance platform.

5. A self-service operation and maintenance method for 5G private network industry applications according to claim 1, characterized in that, Step 3 includes using a mobile terminal to request a self-service operation and maintenance APP page from the 5G private network industry operation and maintenance platform through the enterprise operation and maintenance platform, and the 5G private network industry operation and maintenance platform returning the self-service operation and maintenance APP page to the mobile terminal through the enterprise operation and maintenance platform.

6. A self-service operation and maintenance method for 5G private network industry applications according to claim 1, characterized in that, Step 2 involves the following association calculations: the alarm data module and the cell-level performance module are associated with the cell resource module using unique cell identifiers; the tracking area dimension performance module is associated with the cell resource module using tracking area identifiers; the slice-level performance module is associated with the cell resource module using slice service identifiers; the transmission network element port dimension performance module is associated with the transmission network resource module using transmission device port names; the UPF slice dimension performance module and the UPF performance module are associated with the UPF resource module using unique UPF network management identifiers; the UPF slice dimension performance module is associated with the project information module using slice service identifiers; and the leased line resource module is associated with the leased line performance module using leased line service identifiers.

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