System and method for golden auto correction for multi-vendors

Abstract

The present disclosure provides a method for generating work orders (WOs) for 5 network nodes. The method allows a processing engine (208) to receive a plurality of parameters from the network nodes. The method uses a work order (WO) module (212) for (i) analyzing the plurality of received parameters to extract a first set of parameters causing discrepancies, (ii) generating one or more WOs based on the extracted first set of parameters and an exclusion list, (iii) 10 executing the generated one or more WOs once it is determined that the one or more WOs belong to the NSA type, and (iv) sending one or more WOs approval requests corresponding to the one or more WOs to a set of approvers if it is determined that the one or more WOs belong to the SA type and executing the one or more WOs within a scheduled time based on the approvals.

Description

SYSTEM AND METHOD FOR GOLDEN AUTO CORRECTION FOR MULTI-VENDORSRESERVATION OF RIGHTS

[0001] A portion of the disclosure of this patent document contains material, which is subject to intellectual property rights such as but are not limited to, copyright, design, trademark, integrated circuit (IC) layout design, and / or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner.TECHNICAL FIELD

[0002] The present disclosure relates to the field of network security and infrastructure. More precisely, it relates to a system for a work order module which will extract a list of parameters that are not compliant with particular golden parameter settings defined by network teams and then auto-generate work orders for executing / implementing changes with / without approval.BACKGROUND

[0003] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admission of the prior art.

[0004] Network discrepancies or blockages can cause a lot of harm to the users such as unwanted latencies, lags, and even corruption of data. Signal degradation refers to a decrease in the quality or strength of a network signal. It can result in issues like dropped calls, poor call quality, or slow data speeds. Signal degradation can be caused by factors such as distance from the cell tower, obstacles blocking the signal, or interference from other electronic devices.Network congestion occurs when there is excessive traffic or high demand on the network infrastructure. This can lead to slower data speeds, increased latency, and delays in data transmission. Network congestion often happens during peak usage times or in densely populated areas. Packet loss happens when data packets being transmitted across the network fail to reach their intended destination. It can occur due to network congestion, faulty network equipment, or issues with the physical transmission medium. Packet loss can result in disruptions to voice calls, video streaming, or data.

[0005] Automated systems may occasionally misidentify network discrepancies or generate false alarms, leading to unnecessary corrective actions or overlooking actual issues. This can result in inefficient use of resources and increased operational costs. Automated systems primarily rely on data and algorithms to detect and rectify network discrepancies. However, they may not always have access to contextual information or a comprehensive understanding of the network environment. This can limit their ability to accurately assess the impact of certain issues or make informed decisions on corrective actions. Automated systems are designed based on predefined rules or algorithms. They may struggle to adapt to new or unforeseen network scenarios, emerging technologies, or complex network configurations. This can result in delays or limitations in addressing novel network discrepancies.

[0006] While automation can streamline processes, there are instances where human intervention and expertise are still required. Complex network issues or situations that involve multiple factors may necessitate human analysis and decision-making. Over-reliance on automated processes alone may overlook critical nuances or fail to address certain network discrepancies effectively. Automated systems heavily rely on accurate and up-to-date data for effective detection and rectification. If the data is incomplete, inaccurate, or not properly synchronized, it can lead to erroneous decisions and ineffective corrections. Automated processes, if not carefully designed and tested, may inadvertently trigger cascading effects on the network. Incorrect or faulty corrective actions can introduce new issues or worsen existing ones, leading to network instability or degradation. To mitigate these drawbacks, it is important to strike a balance between automated processes and human oversight. Regular monitoring, periodic reviews, and incorporating feedback from network engineers can helprefine and improve automated systems, ensuring they are robust, adaptable, and reliable in addressing network discrepancies.

[0008] There is, therefore, a need to overcome the above drawbacks and limitations in the current practices to provide a safe and efficient solution for automatically correcting any discrepancies or lags in a given network system. In the system in the present disclosure, Golden Auto Correction (GAC) is a term used to refer to an automated process for identifying and rectifying issues or discrepancies in a telecom operator’s network infrastructure. It is a proactive approach to maintaining network quality and performance. The GAC system continuously monitors various parameters and performance metrics of the network, such as signal strength, call drops, data throughput, and other key indicators. When an issue is detected, the GAC system automatically initiates corrective actions to rectify the problem. The system involves a combination of sophisticated algorithms, machine learning techniques, and real-time data analysis to identify patterns, anomalies, or trends in network performance. Based on the analysis, the GAC system can trigger actions such as adjusting network configurations, optimizing radio resources, or initiating maintenance activities to improve network performance and user experience. Overall, the GAC system is designed to ensure that the telecom operator’s network maintains high standards of quality, reliability, and performance by automating the identification and resolution of network issues.OBJECTS OF INVENTION

[0009] Some of the objects of the present disclosure that at least one embodiment herein satisfies are listed herein below.

[0010] It is an object of the present disclosure to overcome the above limitations and drawbacks of the existing methods for identifying discrepancies in a network.

[0011] It is an object of the present disclosure to avoid issues such as dropped calls, poor call quality, or slow data speeds.

[0012] It is an object of the present disclosure to continuously monitor network parameters, performance metrics, and data streams to quickly detect deviations from expected or normal behavior.

[0013] It is an object of the present disclosure to leverage algorithms, machine learning techniques, and historical data to differentiate between genuine network anomalies and normal variations.

[0014] It is an object of the present disclosure to analyze relevant network data, event logs, and other available information to identify the underlying cause of the issue.

[0015] It is an object of the present disclosure to monitor in real-time to provide timely alerts and notifications, allowing network operators or users to take immediate actions or initiate automated corrective measures.

[0016] It is an object of the present disclosure to analyze historical data to identify recurring issues, seasonal variations, or long-term trends that may impact network performance.

[0017] It is an object of the present disclosure to provide actionable information, recommendations, or automated interventions based on the analysis of network data for 4G / 5G / 6G technology.

[0018] It is an object of the present disclosure to initiate corrective actions automatically or provide recommendations for network engineers to act upon.SUMMARY

[0019] In an exemplary embodiment, the disclosure discloses a method for generating work orders (WOs) for network nodes. The method comprising receiving, by a processing engine, a plurality of parameters from the network nodes. The method comprising analyzing, by a work order (WO) module, the plurality of received parameters to extract a first set of parameters causing one or more discrepancies. The method comprising receiving, by the WO module, an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs. The method comprising generating, by the WO module, the one or more WOs based on the extracted first set of parameters and the received exclusion list. The method comprising determining, by the WO module, whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type. The method comprising, in response to determining that the generated one or more WOs belong to the NSA type, executing, by the WO module, the generated one or more WOs. Themethod comprising, in response to determining that the generated one or more WOs belong to the SA type, performing, by the WO module, following steps (i) sending one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers, and (ii) executing, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.

[0020] In an embodiment, a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.

[0021] In an embodiment, the status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.

[0022] In an embodiment, the predefined time is user configurable.

[0023] In an exemplary embodiment, the present disclosure discloses a system for generating work orders (WOs) for network nodes. The system comprising a processing engine configured to receive a plurality of parameters from the network nodes. The processing engine of the system comprising a work order (WO) module configured to analyze the plurality of received parameters to extract a first set of parameters causing one or more discrepancies. The WO module of the system is configured to receive an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs. The WO module of the system is configured to generate the one or more WOs based on the extracted first set of parameters and the received exclusion list. The WO module of the system is configured to determine whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type. The WO module of the system is configured to, in response to determining that the generated one or more WOs belong to the NSA type, execute the generated one or more WOs. The WO module of the system is configured to, in response to determining that the generated one or more WOs belong to the SA type, perform the following steps (i) send one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers, and (ii) execute, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.

[0024] In an embodiment, the system includes an administration module for managing user roles and controlling their access to an execution status of the WOs belonging to the SA type.

[0025] In an embodiment, the administration module allows an administrator to enable or disable a WO creation option, wherein the WO creation option is in a form of a slider.

[0026] In an embodiment, a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.

[0027] In an embodiment, the status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.BRIEF DESCRIPTION OF DRAWINGS

[0028] The specifications of the present disclosure are accompanied with drawings of the system and method to aid in better understanding of the said disclosure. The drawings are in no way limitations of the present disclosure, rather are meant to illustrate the ideal embodiments of the said disclosure.

[0029] In the figures, similar components and / or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label, irrespective of the second reference label.

[0030] FIG. 1A illustrates an exemplary network architecture (100) for implementing a proposed system, in accordance with an embodiment of the present disclosure.

[0031] FIG. IB illustrates a generalized block diagram of the entire GAC system, in accordance with an embodiment of the present disclosure.

[0032] FIG. 2 illustrates an exemplary block diagram of all the modules in the processing engine of the system, in accordance with an embodiment of the present disclosure.

[0033] FIG. 3 illustrates an exemplary flow diagram of the GAC system, in accordance with an embodiment of present disclosure.

[0034] FIGS. 4A-4B illustrate instances of the administrator pages of the network management system (NMS), in accordance with an embodiment of the present disclosure.

[0035] FIG. 5A-5B illustrate instances of a parameters list in the GAC system, in accordance with an embodiment of the present disclosure.

[0036] FIGS. 6A-6C illustrate instances of the WO list in the NMS portal, in accordance with an embodiment of the present disclosure.

[0037] FIGS. 7A-7D illustrates sample approval emails in the GAC system, in accordance with an embodiment of the present disclosure.

[0038] FIGS. 8A-8C illustrate the report wizard of the GAC system, in accordance with an embodiment of the present disclosure.

[0039] FIG. 9 illustrates an exemplary computer system in which or with which embodiments of the present disclosure can be utilized.

[0040] FIG. 10 illustrates an exemplary flow diagram for a method for generating WOs for network nodes in accordance with an embodiment of the present disclosure.LIST OF REFERENCE NUMERALS100 - Network architecture150 - Flowchart200 - Modules of a system202 - Processor(s)204 - Memory206 - Interface(s)208 - Processing engine210 - Administration module212 - Work order module214 - Other modules216 - Database300 - Flowchart400 - Network management system (NMS) administrator pages500 - Parameters lists in the NMS600 - WO list in the NMS700 - Approval emails800 - Report wizard900 - Computer system902 - Input devices904 - Central Processing Unit906 - Data flow and control flow908 - Output Devices910 - Secondary storage devices912 - Control unit914 - Arithmetic and Logical Unit916 - Memory unit1000 - Flow diagramDETAILED DESCRIPTION

[0041] In the following description, for explanation, various specific details are outlined in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.

[0042] The ensuing description provides exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.

[0043] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood byone of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well- known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.

[0044] Also, it is noted that individual embodiments may be described as a process that is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be rearranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.

[0045] The word “exemplary” and / or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and / or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive like the term “comprising” as an open transition word without precluding any additional or other elements.

[0046] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, orcharacteristics may be combined in any suitable manner in one or more embodiments.

[0047] The terminology used herein is to describe particular embodiments only and is not intended to be limiting the disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any combinations of one or more of the associated listed items.

[0048] The various embodiments throughout the disclosure will be explained in more detail with reference to FIGS. 1-10.

[0049] The present disclosure relates to the field of network security and infrastructure. More precisely, it relates to a system for a work order module which will extract a list of parameters that are not compliant with particular golden parameter settings defined by network teams and then auto generate work orders for executing / implementing changes with / without approval.

[0050] FIG. 1A illustrates an exemplary network architecture (100) for implementing a proposed system, in accordance with an embodiment of the present disclosure.

[0051] As illustrated in FIG. 1A, one or more computing devices (104-1, 104-2. . . 104-N) may be connected to a system (108) through a network (106). A person of ordinary skill in the art will understand that one or more computing devices (104-1, 104-2. .. 104-N) may be collectively referred to as computing devices (104) and individually referred to as computing devices (104). One or more users (102-1, 102-2. .. 102-N) may provide one or more requests to the system (108). A person of ordinary skill in the art will understand that the one or more users (102-1, 102-2. . . 102-N) may be collectively referred as users (102) and individually referred as a user (102). Further, the computing devices (104) may also be referred as a UE (104) or as UEs (104) throughout the disclosure. In an embodiment the system (108) may be interchangeably referred as anetwork exposure function and a predefined interface for handling the one or more requests from the users (102).

[0052] In an embodiment, the computing device (104) may include, but not be limited to, a mobile, a laptop, etc. Further, the computing device (104) may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, audio aid, microphone, or keyboard. Furthermore, the computing device (104) may include a mobile phone, smartphone, virtual reality (VR) devices, augmented reality (AR) devices, a laptop, a general-purpose computer, a desktop, a personal digital assistant, a tablet computer, and a mainframe computer. Additionally, input devices for receiving input from the users (102), such as a touchpad, touch- enabled screen, electronic pen, and the like, may be used.

[0053] In an embodiment, the network (106) may include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. The network (106) may also include, by way of example but not limitation, one or more of a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public -Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof.

[0054] FIG. IB illustrates a generalized block diagram of the entire GAC system, in accordance with an embodiment of the present disclosure.

[0055] As illustrated, in FIG. IB, the generalized block diagram (150) illustrates a high-level functionality of the GAC system to be developed around 4G / 5G / 6G for the configuration management of all the vendors. In an embodiment, in block (152), the present disclosure extracts one or more parameters that are not compliant with golden parameter settings defined by network teams. In other words, the extracted parameters are not performing in expected range of thresholds or key performance indicators that are considered as optimal. In an embodiment, golden parameters may include parameters like frequency parameters, time division duplex (TDD) frame configurationparameters, link adaptation configuration parameters, network configuration parameters, etc. In block (154), the present disclosure automatically creates / generates WOs as non-service affecting (NSA) WOs and / or service affecting (SA) WOs. In examples, the NSA WOs are WOs when implemented does not impact the services provided by a service provider. The WO implementation includes performing steps or process to perform changes in network to improve the performance such that the parameters or key performance indicators are in optimal state. In examples, the SA WOs are the work orders which when implemented can impact the services provided by the service provider. In block (156), the present disclosure allows executing / implementing the created NSA / SA WOs with / without approval to make the required changes in the nodes of the NMS. In an embodiment, block (152) may also include an exclusion / exception list of parameters that need to be excluded while creating the WOs. In example, the parameters in exclusion list may not be critical or impact the services when they are less than optimal. In an embodiment, block (156) may also include checking the expiry of the created WOs before executing them automatically.

[0056] In an embodiment, the customers / users will receive WOs that are automatically generated daily with respect to the discrepancies found in the golden parameter audit of 4G / 5G / 6G nodes for all the vendors. In an embodiment, based on received WOs, there may be a need to take action for the approvals on the basis of the type of WOs (e.g., SA WOs). In an embodiment, the NSA WOs will be executed in an automated manner whereas the SA WOs will be executed based on the defined approvals from circle, and / or region and / or network operations center (NOC) teams.

[0057] In an embodiment, the GAC system generates WOs on a near realtime basis for the telecom operator’s element management system (EMS) nodes. However, for the generation of the automated WOs, the golden audit that is completed by a predefined time (e.g., 8 AM or within 6 hours) every day will be taken as input data. An exclusion of SAP IDs or exceptional parameters needs to be provided before the creation of the automated WOs. The exceptional parameters and SAP IDs (that need to be excluded from WO information) are maintained and updated by an administrator. The parameters are held in a file that contains the SAP ID, Parameter type, category, and name. On the networkmanagement system (NMS), the administrator can log in and access the WO list and whichever data is uploaded before a predefined time (e.g., 11:00 AM) will be considered for changes, the GAC system also obtains approval from the user for any kind of change in the WO and generates a report that contains a WO summary.

[0058] FIG. 2 illustrates an exemplary block diagram of all the modules in the processing engine of the GAC system, in accordance with an embodiment of the present disclosure.

[0059] As illustrated, in FIG. 2, a block diagram of the GAC system (200) is disclosed. The GAC system (200) is referred to as the system (108) in FIG. 1. The GAC system (200) includes a system a processing engine (208) that further includes an administration module (210), a work order (WO) module (212), and other modules (214) for the execution of various processes. The GAC system (200) also includes processor(s) (202), memory (204), and interface (206) for executing the programming instructions related to the creation and execution of the WOs. The database (216) stores all the data from the various modules and also stores the information related to the interface of the network management system. The NMS administrator page can only be accessed by the administrators for editing the WO list and for making the parameter changes.

[0060] In an embodiment, the processing engine (208) receives the parameters of network nodes from the EMS of different telecom operators / vendors. The WO module (212) of the GAC system for 4G, 5G, 6G or future networks allows extracting and analysing relevant parameters of the network nodes to detect discrepancies and trigger corrective actions. The specific parameters that are extracted may vary based on the network technology and the goals of the GAC system. The WO module (212) extracts signal strength measurements from network devices, such as cell towers and user equipment (UE). Significant deviations in signal strength can indicate coverage gaps, interference, or issues with antenna configurations. The WO module (212) obtains signal quality parameters, such as Signal-to-Noise Ratio (SNR), Signal Quality Index (SQI), or Block Error Rate (BLER) to assess the integrity of received signals. Poor signal quality can lead to data errors, call drops, or degraded user experience. The WO module (212) obtains the data throughput and data rates experienced by users in the network. The WO module (212)analyses parameters like average and peak throughput, packet latency, and packet loss rates. The deviations from expected throughput levels can indicate congestion, capacity limitations, or performance issues. In an embodiment, the WO module (212) can also determine whether the created WO belongs to SA or NSA.

[0061] In an embodiment, the WO module (212) also facilitates the creation, management, and execution of the WOs within the system based on the type of WOs as SA or NSA. It provides the necessary tools and functionalities to define, assign, track, and complete WOs related to network discrepancy detection and automated correction. While the specific features and capabilities can vary depending on the implementation, the users with appropriate permissions can create new WOs within the GAC system. Users can specify the details of the WOs, including the type of discrepancy, affected network components, priority level, and any specific instructions or requirements. The WO module (212) allows authorized personnel to assign WOs to specific teams or individuals responsible for executing the tasks. It ensures that the right resources are allocated to address the detected discrepancies. It enables real-time tracking of the status of WOs. Users can monitor the progress of each WO, including its current status (e.g., pending, in progress, on hold, completed), start and end dates, and any associated milestones. The WO module (212) may offer reporting and analytics features to generate insights into WO execution. It can provide metrics such as WO completion time, success rates, resource utilization, or discrepancies resolved. These reports assist in performance monitoring and identifying areas for improvement.

[0062] In an embodiment, the administration module (210) in the GAC system for 4G, 5G, 6G networks or beyond provides the necessary tools and functionalities to manage and administer the GAC system itself. The administration module (210) allows administrators to manage user accounts and roles within the GAC system. The administration module (210) may also allow the administrator to enable or disable a WO creation option (e.g., a slider or any other mechanism) which is checked before creating the WOs automatically. It enables user authentication, creation, modification, and deletion of user accounts. In examples, the administrator may be a program. User roles and permissions can be defined to control access and actions within the GAC system.The administrators can configure and customize various settings of the GAC system through the administration module (210). This includes defining system parameters, thresholds, algorithms, and rules used for discrepancy detection, analysis, and automated correction. The administration module (210) provides tools for managing data within the GAC system. This includes data storage configuration, database management, data backup and restoration, and data archiving. The administration module (210) also logs and audits system activities, user actions, and configuration changes. This facilitates system troubleshooting, security auditing, and compliance with regulatory requirements.

[0063] FIG. 3 illustrates an exemplary flow diagram of the GAC, in accordance with an embodiment of present disclosure.

[0064] Referring to FIG. 3, the exemplary flow diagram (300) of the GAC system includes creating an exclusion list of all the parameters having SAP IDs (302) that are maintained by the administrator. This list can only be updated till a specific predefined time (e.g., 11 am) for the purpose of organizational management. Only the administrator can access the list and create respective WOs for SAs and NSAs. For example, in step (304), the WO creation option is checked to confirm whether its enabled or disabled. If the WO creation option is disabled, WO cannot be created (306). On the other hand, if the WO creation option is enabled, WO can be created by the GAC system. In step 308, GAC further determines whether the created WO belongs to SA or NSA. For an NSA WO, it will be executed immediately and automatically without any approval (310). However, the SA WO will require level (LI) and / or level (L2) and / or level (L3) approval(s) (312). If a particular SA WO is not approved within a predefined time (e.g., by 11 :30 pm) (314), it will be considered as expired (316). Otherwise, the SA WO will be executed between a scheduled time (318) (e.g., between midnight and 6 am). If the SA WO execution is not completed within the scheduled time (320) (e.g., between midnight and 6 am), the SA WO is considered as expired (324), and if SA WO is executed within that scheduled time, the execution is considered as a successful completion (322). In an embodiment, the disclosure may also include validation mechanisms for verifying the effectiveness of the GAC system.

[0065] In an embodiment, in a 4G network, the GAC system and method continuously monitors network performance, collects data from network elements such as base stations, and analyses performance metrics and KPIs. It can detect anomalies or discrepancies in areas such as call quality, data throughput, or coverage. The system generates WOs for automated correction, which may involve adjusting network parameters, optimizing handover algorithms, or addressing interference issues. GAC for 4G helps in maintaining high-quality connections, improving data speeds, and enhancing overall network performance. The GAC system for 5G networks monitors key performance indicators specific to 5G, such as latency, throughput, and connection reliability. It analyses massive amounts of data from various 5G network components, including base stations, edge servers, and network slices. The system identifies discrepancies in network slicing, beamforming, or radio resource management and generates WOs for automated correction. GAC for 5G ensures efficient resource allocation, optimal network slicing configuration, and seamless handovers, leading to enhanced user experiences in the 5G ecosystem.

[0066] In an embodiment, while 6G is still in the development phase, the GAC system can be envisioned for this advanced network technology. The GAC for 6G can be built upon the capabilities of previous generations and adapt to the unique characteristics and requirements of 6G networks. GAC system can monitor and analyze performance metrics specific to 6G, such as ultra-low latency, massive connectivity, and intelligent network management. The GAC system can detect discrepancies related to advanced features like holographic communications, terahertz frequency utilization, and intelligent resource scheduling. Automated WOs generated by the GAC system can enable the correction of these discrepancies, ensuring optimal performance and the realization of the full potential of 6G networks.

[0067] FIGS. 4A-4B illustrate instances of the administrator pages of the NMS, in accordance with an embodiment of the present disclosure.

[0068] As illustrated, in FIGS. 4A and 4B, instances of the administrator pages (400) are disclosed. In FIG. 4A, a path to the administrator page for WO creation is disclosed. Only the data (e.g., in the form of an excel sheet) which is entered before a specific predefined time (e.g., by 11 am) will be considered for any changes to be made in the WO creation. The user can use an option on theadministrator page to start / stop the generation of the WO s. In an embodiment, if the option is disabled, the user will only see a red box, and if the option is enabled a UI box will appear as illustrated in FIG. 4B. For the sake of consistency, the templates added before the specific predefined time (e.g., 11 AM) will be considered for the WO creation. In an embodiment, the user can upload and download the list of parameters in the form of a spread sheet (e.g., an excel sheet, or a CSV format document). An automated download will also be triggered once the entries have been uploaded successfully. A delete icon will appear against each entry, and the customer can delete the individual entry after confirming a pop-up message.

[0069] In an embodiment, the WOs typically encompass a range of activities related to network infrastructure deployment, maintenance, customer service, etc. The telecom network operator generates WOs for network expansion, where new cell towers, base stations, or fiber optic cables are deployed to extend network coverage and capacity in specific areas. These WOs involve tasks such as site surveys, tower installation, equipment configuration, and integration. When the telecom network operator introduces new technologies or enhances existing network infrastructure, the WOs are generated for network upgrades. This may involve replacing or upgrading equipment, implementing new software releases, or optimizing network settings to improve performance and support advanced features.

[0070] FIG. 5A-5B illustrate instances of a parameters list in the GAC system, in accordance with an embodiment of the present disclosure.

[0071] Referring to FIG. 5A and FIG. 5B, examples of parameters / entries (500) are disclosed. In an embodiment, each entry is associated with an SAP ID so that the user can search entries on the basis of the SAP IDs. The “Total Sites”, as shown in FIG. 5A and FIG. 5B, represents the total number of the SAP ID’s present in the entire list. If in case, the SAP ID repeats with the same parameter category / type then it is marked as duplicate but in case if SAP ID repeats with a different parameter category / type it will be considered as a change. The “Total Parameters” represents the total number of parameters that are excluded from the WO creation. During the upload, if only a parameter category is mentioned and no parameter name is mentioned against that category name, then the total number of parameters that exist against that category will be taken into accountand that complete list of parameters present within that category will be excluded from the WOs. In an embodiment, the user can also upload the above list without the SAP ID information, in that case, the parameter category / parameter name if defined will become applicable for exclusion from all the WOs generated for all the 5G nodes / SAP ID’s. After WO creation, it will be listed under the path.

[0072] In an embodiment, the parameters included in WOs within the NMS administrator portal may vary based on the specific workflows, processes, and requirements established by the system. A unique identifier is assigned to each WO for tracking and reference purposes. There is a WO description which provides a brief description or summary of the work to be performed or provides an overview of the task or project. The geographical location or site where the WO needs to be executed includes relevant address details. The priority level assigned to the WO indicates its urgency or importance compared to other tasks is also included.

[0073] In an embodiment, a 5G GAC aims to optimize network coverage, capacity, and quality by identifying and resolving issues in a proactive and efficient manner. The 5G GAC module continuously monitors key performance indicators (KPIs) and network parameters in real-time. This includes metrics related to signal strength, signal quality, data rates, latency, handover success rates, and other 5G-specific performance indicators. The GAC system utilizes sophisticated algorithms and machine learning techniques to analyse the monitored data and detect anomalies or discrepancies. It compares the observed network behavior against expected patterns and predefined thresholds to identify deviations that require attention. Based on an analysis and an identified root cause, the GAC system automatically initiates corrective actions to address the detected discrepancies. These actions may include, but are not limited to, optimizing network parameters, adjusting resource allocation, rerouting traffic, triggering equipment resets, or other appropriate measures to restore optimal network performance. The GAC system aims to continuously optimize the 5G network performance by iteratively monitoring, detecting, and correcting the discrepancies. It adapts to changing network conditions, user demands, and emerging patterns to ensure ongoing improvements in coverage, capacity, and quality.

[0074] FIGS. 6A-6C illustrate instances of the WO list in the NMS portal, in accordance with an embodiment of the present disclosure.

[0075] As illustrated, in FIGS. 6A-6C, the various instances of the WO list in the NMS (600) are disclosed. For example, as illustrated in FIG. 6A, some WOs are pending for approval from the user, some are being executed and some are completed, aborted or expired in the system. In FIG. 6B, an example of a WO that has been changed 5000 times and with a success count of 3500 and a failed count of 500 is disclosed and other 1000 instances are also in progress. In FIG. 6C, a list of all the WOs and their respective vendors is disclosed. The list contains details such as the task of the WO, the last modification date and time, the completion status of the tasks and the region, start and end dates of the task, etc. There are some other options as well displayed on the NMS portal like scheduling the WOs, the RET changes, a trace port activation among others.

[0076] In an embodiment, once the WO is created “status” indicates “Pending for LI approval”. Other WO statuses may also include the following information:

[0077] Once “LI Approves”, the status may indicate as “Pending for L2 approval”.

[0078] Once “L2 Approves”, the status may indicate as “Pending for L3 Approval”.

[0079] Once “L3 Approves”, the status may indicate as “Pending for Execution”.

[0080] Once WO is in “Execution”, the status may indicate as “In Progress”.

[0081] Once WO execution is “Complete”, the status may indicate as “Completed”.

[0082] Once WO is “Aborted”, the status may indicate as “Aborted by Creator / Executor” along with his / fer name.

[0083] Once WO is “Rejected” at any stage, the status may indicate as “Rejected by L1 / L2 / L3” along with his / fer name.

[0084] Once WO is “Expired”, the status may indicate as “Expired”.

[0085] These various stages of execution of the WO are easier to keep track with a naming nomenclature. The WO listing page also includes a global search option which allows searching on the basis of a WO name. A minimum 3 characters may need to be inserted to search on the WO name. A refresh buttonon the WO listing page with the search button is also available to check the updated WO Execution status. To download a report, there is a three-dot option available with named “Report” against all WO IDs, and by default, this option is disabled, and as the WO execution is completed, it will be automatically enabled. After execution of the WO, a WO summary sheet is updated with the result (pas s / f ailed).

[0086] In an embodiment, various other specifications are included in the WO creation and maintenance. A “Remark” column can be added in the report which describes a description of the result. A parameter classification SA or NSA can be taken from a dictionary file that gets drafted for every node type and related software release that gets introduced in the network, based on the new configuration information available. In examples, the dictionary file serves as a comprehensive repository of parameters having a master list of parameters. Each parameter within this file is associated with various attributes. One such attribute is the ‘Service Impacting’ attribute. A change in the value of a parameter marked as ‘ Service Impacting’ necessitates the reboot of either the individual cell or the entire node. This action results in a pre-planned service outage. The disclosed dictionary file encompasses such attributes for all included parameters, providing a systematic approach to managing network parameters and their impacts.

[0087] The parameter classification of NSA and SA can be done with this available information and WOs can further be generated. There are two different types of WOs to be created for both SA and NSA respectively. The NSA execution time of the WOs can be a specific customizable predefined time (e.g., 11 AM) i.e., at the predefined time, all the NSA WOs will start executing automatically. In an embodiment, the timing for the start of execution of WOs is configurable. The SA WO execution can also be performed at a specific customizable predefined time (e.g., between 12 AM to 6 AM). For NSA and SA WOs, parameter change execution needs to be aborted / hard stopped by a predefined customed time (e.g., 6 AM). In such a scenario, if it is not completed then it is reflected as failed with a reason for pending changes for the respective nodes in a status report and the reason will be marked as planned event expired (e.g., “PE Expired - Partially executed”). In the case of SA WOs, as per the approval flow, if the final approval of the WO ID generated is not complete tilla predefined time (e.g., 11:30 PM), then status of the WO will be marked as “WO expired - Pending Approval”. In the WO listing page, only WOs approved by LI approver are made visible to L2 and WOs approved by L2 is made visible to L3 approvers. Therefore, the final statuses may include any of the following: “Completed”, or “Pending” or “In Progress”.

[0088] In an embodiment, the cell DB admin role can have access to an auto WO creation start / stop functionality, a GAC parameter template, and an SAP ID and parameter exclusion from the auto WO functionality. The NSA WO will automatically be executed as soon as the triggering time is reached without any approvals. All the approvals for the SA WOs need to be in place before a specific predefined time (e.g., 11 :30 PM). Otherwise, WOs may get expired with a reason marked as “WO Expired - Pending Approval”.

[0089] In an embodiment, the following approver roles needs to be made available for approving the WOs for SA category. For example, a role “deputy chief technology officer” (CTO) (e.g., LI approver) is the first WO approval stage. The WO cancellation of some SAP IDs can be done completely or partially, along with the reason provided by the LI approver. LI approver has the access rights for changing the predefined execution time of the SA WOs (e.g., within 12AM to 6 AM) only. LI approver’s access to the WO execution status report after execution of the WO and notifications for approvals / modifications in WO details from subsequent approvers are also disclosed. The zonal approver (L2 approver) role is at the second stage of the WO approval. A WO cancellation can be done completely, along with the reason mentioned by the zonal approver. L2 approver also has access rights for changing the predefined execution time of the SA WOs (e.g., between 12 AM to 6 AM) only. L2 approver’s access to the WO execution status report after execution of the WO and notifications for approvals / modifications in WO details from subsequent approvers is also disclosed. The NOC executor (L3 approver) role is the final WO approval stage before execution. A WO cancellation can also be done completely with the reason provided by the NOC executor. L3 approver also has the access rights for changing the predefined execution time of the SA WOs (e.g., between 12 AM to 6 AM) only. This role provides access to the WO execution status report after execution and notifications about the final approval of WO along with the first approver and the second approver.

[0090] FIGS. 7A-7D illustrates sample approval emails in the GAC system, in accordance with an embodiment of the present disclosure.

[0091] As illustrated, in FIGS. 7A-7D, approval emails (700) for the GAC are disclosed. In FIGS. 7A-7C, a first stage mail can be sent to an LI approver. As soon LI approves the WO, it will further go to L2 for the next stage of approval, and the further mail proceeds to L3. For example, the first stage pending approval email, as shown in FIG. 7A, consists of seeking approval for further action on the WO and goes to a second stage pending approval email for approving the WO as shown in FIG. 7B and so on. In the final approver email, as illustrated in FIG. 7D, as soon as the WO is executed then a final mail can be sent to all level approvers. The main purpose of these emails is to gain the requisite permissions and to inform the respective administrators and users about the status of the WO.

[0092] In an embodiment, the permissions required for the execution of WOs in the GAC system may vary based on the specific implementation and organizational structure. For a WO creation, the users or roles with appropriate permissions should be able to create new WOs in the GAC system. This permission allows authorized individuals to initiate new tasks, projects, or maintenance activities. Permissions can be used to assign WOs to specific personnel or teams responsible for executing the tasks. This ensures that the right individuals are assigned the appropriate WOs based on their expertise, availability, or workload. Permissions are also required to close WOs once the assigned tasks or projects are successfully completed. This permission allows authorized individuals to finalize the WOs, update completion status, and archive or close them in the GAC system. The specific permissions and their granularity within the GAC system depend on the system's design, security protocols, and organizational requirements.

[0093] FIGS. 8A-8C illustrate the report wizard of the GAC system, in accordance with an embodiment of the present disclosure.

[0094] Referring to FIGS. 8A-8C, instances of the report and dashboard (800) for WO summary is disclosed. FIG. 8A shows the path to the WO list and FIG. 8B and FIG. 8C show the options to edit the options for the WO. The report can have as 5G GAC WO summary on the UI screen of the dashboard. The report shall be auto populated and editable in the UI screen and have a date rangeselection where the user can select to and from date range. The sample report can contain a WO ID, status, serial numbers, creation and approval times, execution times, and pass or fail instances. The dashboard may include key metrics related to WOs, such as average execution time, average delay, or WO completion rate. These metrics help assess the efficiency and performance of the GAC system in executing WOs. A visual representation of the WO timeline can be included in the dashboard, showing the start and end dates of WOs. This allows users to track the duration of each WO and identify any delays or bottlenecks in the execution process. The dashboard can also provide insights into the distribution of WOs among different teams or individuals. This helps monitor workload distribution, identify resource imbalances, and ensure equitable distribution of tasks.

[0095] FIG. 9 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized, in accordance with an embodiment of present disclosure.

[0096] Referring to FIG. 9, a block diagram of an exemplary computer system is disclosed.The computer system includes input devices (902) connected through VO peripherals. The system also includes a Central Processing Unit (CPU) (904), and Output Devices (908), connected through the VO peripherals. The CPU (904) is also attached to a memory unit (916) along with an Arithmetic and Logical Unit (ALU) (914), a control unit, (912), along with secondary storage devices (910) such as Hard Disks and a Secure Digital Card (SD). The data flow and control flow (906) are indicated by a straight and dashed arrow respectively. The CPU consists of data registers that hold the data bits, pointers, cache, Random Access Memory (RAM) (204), and a main processing unit containing the processing engine (208). The system also consists of communication buses that are used to transport the data internally in the system.

[0097] In an embodiment, a processor (202) of the system is used to process all the data that is required for generating the WOs automatically. A person skilled in the art will appreciate that the system may include more than one processor (202) and communication ports for ease of function. Examples of processors (202) include, but are not limited to, an Intel® Itanium® or Itanium 2 processor (s), or AMD® Opteron® or Athlon MP® processor (s), Motorola®lines of processors, FortiSOC™ system on a chip processor 202 or other future processors. The processor (202) may include various modules associated with embodiments of the present invention. The input component can also include communication ports, ethernet ports, gigabit ports, parallel port, or another Universal Serial Bus (USB). The communication port can also be chosen depending on a specific network such as a Wide Area Server (WAN), Local Area Network LAN), or a Personal Area Network (PAN). The communication port can be a RS-232 port that can be used with the remote dialling and internet connection options of the system. A Gigabit port can be used to connect the system to the internet at all times. And the Gigabit port can use copper or fibre for connection.

[0098] It is to be appreciated by a person skilled in the art that while various embodiments of the present disclosure have been elaborated for the GAC system for 4G / 5G / 6G network vendors. However, the teachings of the present disclosure are also applicable for other types of applications as well, and all such embodiments are well within the scope of the present disclosure. However, the system and method for sign language conversion is also equally implementable in other industries as well, and all such embodiments are well within the scope of the present disclosure without any limitation.

[0099] In an exemplary embodiment, the present invention discloses a method for generating work orders (WOs) for network nodes. The method comprising receiving, by a processing engine, a plurality of parameters from the network nodes. The method comprising analyzing, by a work order (WO) module, the plurality of received parameters to extract a first set of parameters causing one or more discrepancies. The method comprising receiving, by the WO module, an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs. The method comprising generating, by the WO module, the one or more WOs based on the extracted first set of parameters and the received exclusion list. The method comprising determining, by the WO module, whether the generated one or more WOs belong to a nonservice affecting (NSA) type or a service affecting (SA) type. The method comprising, in response to determining that the generated one or more WOs belong to the NSA type, executing, by the WO module, the generated one ormore WOs. The method comprising, in response to determining that the generated one or more WOs belong to the SA type, performing, by the WO module, following steps (i) sending one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers, and (ii) executing, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time (for example, before midnight or within 6 hours). In examples, the one or more WOs approval requests may be sent over one or more communication channels including, but not limited to automated email (as shown in FIG. 7A- FIG. 7D), automated call, and short message service (SMS).

[0100] In an embodiment, a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.

[0101] In an embodiment, the status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.

[0102] In an embodiment, the predefined time is user configurable.

[0103] In an exemplary embodiment, the present invention discloses a system for generating work orders (WOs) for network nodes. The system comprising a processing engine configured to receive a plurality of parameters from the network nodes. The processing engine of the system comprising a work order (WO) module configured to analyze the plurality of received parameters to extract a first set of parameters causing one or more discrepancies. The WO module of the system is configured to receive an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs. The WO module of the system is configured to generate the one or more WOs based on the extracted first set of parameters and the received exclusion list. The WO module of the system is configured to determine whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type. The WO module of the system is configured to, in response to determining that the generated one or more WOs belong to the NSA type, execute the generated one or more WOs. The WO module of the system is configured to, in response to determining that the generated one or more WOs belong to the SA type, perform the following steps (i) send one or more WOsapproval requests corresponding to the generated one or more WOs to a set of approvers, and (ii) execute, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.

[0104] In an embodiment, the system includes an administration module for managing user roles and controlling their access to an execution status of the WOs belonging to the SA type.

[0105] In an embodiment, the administration module allows an administrator to enable or disable a WO creation option, wherein the WO creation option is in a form of a slider.

[0106] In an embodiment, a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.

[0107] In an embodiment, the status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.

[0108] Fig. 10 illustrates an exemplary flow diagram for a method (1000) for generating WOs for network nodes in accordance with an embodiment of the present disclosure.

[0109] At step (1002), the method receives a plurality of parameters from the network nodes.

[0110] At step (1004), the method analyzes the plurality of received parameters to extract the first set of parameters causing one or more discrepancies.

[0111] At step (1006), the method receives an exclusion list related to the received plurality of parameters. In an embodiment, the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs.

[0112] At step (1008), the method generates the one or more WOs based on the extracted first set of parameters and the received exclusion list.

[0113] At step (1010), the method determines whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type.

[0114] At step (1012), the method, in response to determining that the generated one or more WOs belong to the NSA type, executes the generated one or more WOs.

[0115] At step (1014), the method, in response to determining that the generated one or more WOs belong to the SA type, performs the following steps.

[0116] At step (1016), the method sends one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers.

[0117] At step (1018), the method executes, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.

[0118] Moreover, in interpreting the specification, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refer to at least one of something selected from the group consisting of A, B, C . . . .and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.

[0119] While considerable emphasis has been placed herein on the preferred embodiments it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the disclosure and not as a limitation.ADVANTAGES OF THE INVENTION

[0120] The disclosure provides a system for GAC for various 4G / 5G / 6G and advanced network technology vendors.

[0121] The disclosure provides a system for automating the process of detecting, analysing, and correcting network discrepancies by leveraging advanced algorithms and machine learning techniques.

[0122] The disclosure provides a system for network issues to be identified and addressed before they cause significant impact or disruption to network services.

[0123] The disclosure provides a system for the efficient resolution of network discrepancies and helps prevent revenue losses due to network downtime or subop timal performance.

[0124] The disclosure provides a system for helping maintain high network quality and performance standards.

[0125] The disclosure provides a system for monitoring and managing discrepancies across a wide range of network technologies (4G, 5G, 6G) and network components.

[0126] The disclosure provides a system for collecting and analysing a vast amount of network data, providing valuable insights for decision making.

[0127] The disclosure provides a system that enforces consistency in the execution of WOs, minimizing variations and reducing the chances of errors or misconfigurations.

[0128] The disclosure provides a system that facilitates continuous improvement efforts by providing data and insights into network performance.

Claims

CLAIMS1. A method (1000) for generating work orders (WOs) for network nodes, the method (1000) comprising: receiving (1002), by a processing engine (208), a plurality of parameters from the network nodes; analyzing (1004), by a work order (WO) module (212), the plurality of received parameters to extract a first set of parameters causing one or more discrepancies; receiving (1006), by the WO module (212), an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs; generating (1008), by the WO module (212), the one or more WOs based on the extracted first set of parameters and the received exclusion list; determining (1010), by the WO module (212), whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type; in response to determining that the generated one or more WOs belong to the NSA type, executing (1012), by the WO module (212), the generated one or more WOs; and in response to determining that the generated one or more WOs belong to the SA type, performing (1014), by the WO module (212), following steps: sending (1016) one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers; and executing (1018), in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.

2. The method (1000) as claimed in claim 1, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.

3. The method (1000) as claimed in claim 1, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.

4. The method (1000) as claimed in claim 2, wherein the predefined time is user configurable.

5. The method (1000) as claimed in claim 1, wherein the plurality of parameters comprise frequency parameters, time division duplex (TDD) frame configuration parameters, link adaptation configuration parameters, network configuration parameters, Signal-to-Noise Ratio (SNR), Signal Quality Index (SQI), and Block Error Rate (BLER), wherein the first set of parameters is a subset of the plurality of parameters, and wherein the exclusion list includes a parameters that are excluded from changes through generation of one or more WOs, and wherein the parameters of the exclusion list comprises the second set of parameters.

6. A system (200) for generating work orders (WOs) for network nodes, the system (200) comprising: a processing engine (208) configured to receive a plurality of parameters from the network nodes, the processing engine (208) comprises: a work order (WO) module (212) configured to analyze the plurality of received parameters to extract a first set of parameters causing one or more discrepancies; the WO module (212) is configured to: receive an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs; generate the one or more WOs based on the extracted first set of parameters and the received exclusion list;determine whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type; in response to determining that the generated one or more WOs belong to the NSA type, execute the generated one or more WOs; in response to determining that the generated one or more WOs belong to the SA type: send one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers; and execute, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.

7. The system (200) as claimed in claim 6, wherein the system (200) includes an administration module (210) for managing user roles and controlling their access to an execution status of the WOs belonging to the SA type.

8. The system (200) as claimed in claim 6, wherein the administration module (210) allows an administrator to enable or disable a WO creation option, wherein the WO creation option is in a form of a slider.

9. The system (200) as claimed in claim 6, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if they are not approved within a predefined time.

10. The system (200) as claimed in claim 6, wherein a status of the one or more WOs belonging to the SA type is indicated as expired if the execution of the one or more WOs belonging to the SA type is not completed within the scheduled time.

11. A computer program product comprising a non-transitory computer- readable medium comprising instructions that, when executed by one or moreprocessors, cause the one or more processors to perform a method for generating work orders (WOs) for network nodes, the method comprising: receiving, by a processing engine (208), a plurality of parameters from the network nodes; analyzing, by a work order (WO) module (212), the plurality of received parameters to extract a first set of parameters causing one or more discrepancies; receiving, by the WO module (212), an exclusion list related to the received plurality of parameters, wherein the exclusion list includes a second set of parameters that need to be excluded in generating one or more WOs; generating, by the WO module (212), the one or more WOs based on the extracted first set of parameters and the received exclusion list; determining, by the WO module (212), whether the generated one or more WOs belong to a non-service affecting (NSA) type or a service affecting (SA) type; in response to determining that the generated one or more WOs belong to the NSA type, executing, by the WO module (212), the generated one or more WOs; and in response to determining that the generated one or more WOs belong to the SA type, performing, by the WO module (212), following steps: sending one or more WOs approval requests corresponding to the generated one or more WOs to a set of approvers; and executing, in response to receiving one or more approvals from the set of approvers, the generated one or more WOs within a scheduled time.

12. A user equipment (UE) (104) communicatively coupled with a system (108), the coupling comprises steps of: receiving, by the system (108), a connection request; sending an acknowledgment of the connection request to the UE (104); andtransmitting a plurality of signals in response to the connection request to the system (108), wherein the system (108) configured to perform a method (1000) for generating work orders (WOs) for network nodes as claimed in claim 1.

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