DESC:
FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
(See section 10 and rule 13)
1. TITLE OF THE INVENTION
METHOD AND SYSTEM FOR MONITORING A NETWORK
2. APPLICANT(S)
NAME NATIONALITY ADDRESS
JIO PLATFORMS LIMITED INDIAN OFFICE-101, SAFFRON, NR. CENTRE POINT, PANCHWATI 5 RASTA, AMBAWADI, AHMEDABAD 380006, GUJARAT, INDIA
3.PREAMBLE TO THE DESCRIPTION

THE FOLLOWING SPECIFICATION PARTICULARLY DESCRIBES THE NATURE OF THIS INVENTION AND THE MANNER IN WHICH IT IS TO BE PERFORMED.

FIELD OF THE INVENTION
[0001] The present invention relates to the field of telecommunications and network management, more particularly relates to a method and system of monitoring a network.
BACKGROUND OF THE INVENTION
[0002] The deployment and maintenance of 5G networks involve numerous challenges due to the unique characteristics of this advanced technology. One critical aspect that requires careful attention is the Radio Access Network (RAN), which plays a vital role in connecting user devices to the core network infrastructure.

[0003] The RAN comprises various components such as base stations, antennas, and backhaul connections. These components work together to facilitate wireless connectivity and data transmission between user devices and the network. The base stations act as access points that communicate with user devices, while the antennas transmit and receive wireless signals. The backhaul connections establish the link between the RAN and the core network, allowing data to flow seamlessly.

[0004] Monitoring and managing the performance of the RAN is crucial for maintaining optimal network operation and ensuring a smooth user experience. Prompt identification and resolution of issues within the RAN are essential to minimize service disruptions, improve network reliability, and meet user expectations.

[0005] However, the unique characteristics of 5G networks present additional challenges in monitoring and managing the RAN effectively. The high data transmission rates, low latency requirements, and massive device connectivity of 5G introduce complexities that need to be addressed for seamless operation.

[0006] Monitoring the performance of the RAN in a 5G environment requires collecting and analysing vast amounts of data in near real-time. This data includes information about signal strength, network congestion, latency, and other key performance indicators. To ensure optimal performance, network operators need access to actionable insights derived from this data to identify areas of improvement, detect anomalies, and proactively address issues.

[0007] Identifying and resolving issues within the RAN promptly is critical to prevent service disruptions and maintain a high-quality user experience. This requires efficient troubleshooting processes and tools that can pinpoint the root causes of problems accurately. Traditional methods of data collection and analysis, such as physical tapping or packet capturing, may not be well-suited for the dynamic and fast-paced nature of 5G networks.

[0008] Moreover, the security of network data is of utmost importance. The sensitive nature of the data collected from the RAN necessitates robust measures to ensure data privacy and protection from unauthorized access or interception.

[0009] To provide a seamless and uninterrupted 5G experience, it is essential to have near real-time insights into network degradation, failures, and their quick resolution. However, traditional methods of collecting and analyzing network data are inefficient and costly.

[0010] There is a need for an improved network monitoring and troubleshooting solution that can efficiently access actionable data, facilitate faster analysis, and serve as a foundation for automation and proactive issue detection in 5G networks.
SUMMARY OF THE INVENTION
[0011] One or more embodiments of the present invention provides a method and a system for monitoring a network.
[0012] In one aspect of the present invention, the method for monitoring the network is disclosed. The method includes the step of receiving the data pertaining to a user session in the network from one or more network elements. The received data includes at least one of call summary logs, signal strength, congestion in the network, and latency. The method further includes the step of validating the received data and segregating the validated data. The method further includes the step of decoding the validated data pertaining to the user session. The method further includes the step of parsing the decoded data to identify irregularities in the decoded data. Further, the method includes generating reports and insights based on parsing of the decoded data.
[0013] In one embodiment, upon decoding of the received data, the method includes the step of feeding the decoded data to a message broker unit. The method further includes the step of storing, by the one or more processors, the fed decoded data at the message broker unit.
[0014] In one embodiment, the method includes the step of performing data operations. The one or more operations include but not limited to, enrichment, stitching and data co-relation.

[0015] In another embodiment, upon enriching the method includes the step of analyzing the enriched data to monitor network performance, identify one or more anomalies, and optimize Key Performance Indicators (KPIs).
[0016] In another embodiment, the data includes at least one of call summary logs, signal strength, congestion in the network, and latency.
[0017] In yet another embodiment, upon generation of the insights and reports, the method comprises the step of transmitting, by the one or more processors, the generated insights and reports to at least one User Equipment (UE).
[0018] In another aspect of the present invention, the system of monitoring the network is disclosed. The system includes a receiving module configured to receive the data pertaining to a user session in the network from one or more network elements. The system further includes a validation unit configured to validate the received data. Further the system includes a segregation unit configured to segregate the validated data. Further the system includes a decoding module configured to decode the validated data pertaining to the user session. Further the system includes a parsing module configured to parse the decoded data to identify irregularities in the decoded data. Further the system includes a generation module configured to generate reports and insights based on parsing of the decoded data.
[0019] In yet another aspect of the invention, a non-transitory computer-readable medium having stored thereon computer-readable instructions is disclosed. The computer-readable instructions are executed by a processor. The processor is configured to receive data pertaining to a user session in the network from one or more network elements, validate the received data, segregate the validated data, decode the validated data pertaining to the user session, parse the decoded data to identify irregularities in the decoded data, and generate, reports and insights based on parsing of the decoded data.
[0020] In another aspect of the present invention, an User Equipment (UE) is disclosed. The UE includes one or more primary processors. The one or more primary processors are coupled with a memory. The memory stores instructions which when executed by the one or more primary processors causes the UE to display the reports, Key Performance Indicators (KPI’s) and call session data..
[0021] Other features and aspects of this invention will be apparent from the following description and the accompanying drawings. The features and advantages described in this summary and in the following detailed description are not all-inclusive, and particularly, many additional features and advantages will be apparent to one of ordinary skill in the relevant art, in view of the drawings, specification, and claims hereof. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes and may not have been selected to delineate or circumscribe the inventive subject matter, resort to the claims being necessary to determine such inventive subject matter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components, electronic components or circuitry commonly used to implement such components.
[0023] FIG. 1 is an exemplary block diagram of a communication system for monitoring a network, according to one or more embodiments of the present disclosure;
[0024] FIG. 2 is an exemplary block diagram of a system for monitoring a network, according to one or more embodiments of the present disclosure;
[0025] FIG. 3 is a schematic representation of the system of FIG. 2 communicably coupled with a User equipment (UE), according to one or more embodiments of the present disclosure;
[0026] FIG. 4 is an exemplary architecture which can be implemented in the system of the FIG. 2, according to one or more embodiments of the present disclosure;
[0027] FIG. 5 is a signal flow diagram for monitoring a network, according to one or more embodiments of the present disclosure; and
[0028] FIG. 6 is a flow diagram illustrating a method for monitoring a network, according to one or more embodiments of the present disclosure.
[0029] The foregoing shall be more apparent from the following detailed description of the invention.

DETAILED DESCRIPTION OF THE INVENTION
[0030] Some embodiments of the present disclosure, illustrating all its features, will now be discussed in detail. It must also be noted that as used herein and in the appended claims, the singular forms "a", "an" and "the" include plural references unless the context clearly dictates otherwise.
[0031] Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure including the definitions listed here below are not intended to be limited to the embodiments illustrated but is to be accorded the widest scope consistent with the principles and features described herein.
[0032] A person of ordinary skill in the art will readily ascertain that the illustrated steps detailed in the figures and here below are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0033] The present disclosure addresses the challenges faced in established technologies where deployment and maintenance of 5G networks involve numerous challenges due to the unique characteristics of the advanced technology. Traditional probing solutions often involve physical tapping of the network and packet capturing tools, which are inefficient, time-consuming, and pose data security concerns. The probing agent architecture eliminates the need for physical tapping and offers optimized data acquisition directly from network stations, reducing hardware infrastructure requirements, network congestion, and bandwidth consumption. The present invention eliminates the physical tapping, facilitates data security and provides near real-time network insights. Further the invention facilitates efficient troubleshooting, optimization, and proactive network management, contributing to a seamless and enhanced user experience in the 5G ecosystem.
[0034] Referring to FIG. 1, FIG. 1 illustrates an exemplary block diagram of a communication system 100 for monitoring a network, according to one or more embodiments of the present disclosure. The communication system 100 includes a network 105, a User Equipment (UE) 110, a server 115, and a system 120. The UE 110 aids a user to interact with the system 120. In an embodiment, the UE 110 is one of, but not limited to, any electrical, electronic, electro-mechanical or an equipment and a combination of one or more of the above devices such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device.
[0035] For the purpose of description and explanation, the description will be explained with respect to the UE 110, or to be more specific will be explained with respect to a first UE 110a, a second UE 110b, and a third UE 110c, and should nowhere be construed as limiting the scope of the present disclosure. Each of the first UE 110a, the second UE 110b, and the third UE 110c is configured to connect to the server 115 via the network 105. As per the illustrated embodiment, the communication system 100 includes one or more base stations 125. In alternate embodiments, the UE 110 may include a plurality of UEs as per the requirement. For ease of reference, each of the first UE 110a, the second UE 110b, and the third UE 110c, will hereinafter be collectively and individually referred to as the “User Equipment (UE) 110”.
[0036] Further, the communication system 100 includes the one or more base station 125. For the purpose of description and explanation, the description will be explained with respect to one or more base stations 125, or to be more specific will be explained with respect to a first base station 125a, a second base station 125b, and a third base station 125c, and should nowhere be construed as limiting the scope of the present disclosure. For ease of reference, each of the first base station 125a, the second base station 125b, and the third base station 125c, will hereinafter be collectively and individually referred to as the “base station 125”.
[0037] The first base station 125 includes, by way of example but not limitation, a cell site, cell phone tower, or cellular base station. Each of the first base station 125a, the second base station 125b, and the third base station 125c is a cellular-enabled mobile device site where antennas and electronic communications equipment are placed (typically on a radio mast, tower, or other raised structure) to create a cell, or adjacent cells, in the communication network. The structure typically supports an antenna and one or more sets of transmitters/receivers, digital signal processors, control electronics, a GPS receiver for timing, primary and backup electrical power sources, and sheltering.
[0038] The network 105 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 105 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.
[0039] The network 105 includes, 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. The network 105 may include, but is not limited to, a Third Generation (3G), a Fourth Generation (4G), a Fifth Generation (5G), a Sixth Generation (6G), a New Radio (NR), a Narrow Band Internet of Things (NB-IoT), an Open Radio Access Network (O-RAN), and the like.
[0040] The network 105 may also 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 105 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, a VOIP or some combination thereof.
[0041] The communication system 100 includes the server 115 accessible via the network 105. The server 115 may include by way of example but not limitation, one or more of a standalone server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof. In an embodiment, the entity may include, but is not limited to, a vendor, a network operator, a company, an organization, a university, a lab facility, a business enterprise side, a defense facility side, or any other facility that provides service.
[0042] The communication system 100 further includes the system 120 communicably coupled to the server 115 and the UE 110 via the network 105. The system 120 is adapted to be embedded within the server 115 or is embedded as the individual entity. However, for the purpose of description, the system 120 is illustrated as remotely coupled with the server 115, without deviating from the scope of the present disclosure.
[0043] Operational and construction features of the system 120 will be explained in detail with respect to the following figures.
[0044] FIG. 2 illustrates an exemplary block diagram of the system 120 for monitoring the network 105, according to one or more embodiments of the present disclosure.
[0045] As per the illustrated embodiment, the system 120 includes one or more processors 205, a memory 210, a user interface 215 and a database 220. For the purpose of description and explanation, the description will be explained with respect to one processor 205 and should nowhere be construed as limiting the scope of the present disclosure. In alternate embodiments, the system 120 may include more than one processor 205 as per the requirement of the network 105. The one or more processors 205, hereinafter referred to as the processor 205 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, single board computers, and/or any devices that manipulate signals based on operational instructions.
[0046] As per the illustrated embodiment, the processor 205 is configured to fetch and execute computer-readable instructions stored in the memory 210. The memory 210 may be configured to store one or more computer-readable instructions or routines in a non-transitory computer-readable storage medium which may be fetched and executed to display the enriched data to the user via the user interface in order to perform analysis. The memory 210 may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as disk memory, EPROMs, FLASH memory, unalterable memory, and the like.
[0047] In an embodiment, the user interface 215 includes a variety of interfaces, for example, interfaces for data input and output devices, referred to as Input/Output (I/O) devices, storage devices, and the like. In an embodiment, the user interface 215 includes a Graphical User Interface (GUI). The user interface 215 facilitates communication of the system 120. In one embodiment, the user interface 215 provides a communication pathway for one or more components of the system 120.
[0048] In an embodiment, the database 220 is one of, but not limited to, a centralized database, a cloud-based database, a commercial database, an open-source database, a distributed database, an end-user database, a graphical database, a No-Structured Query Language (NoSQL) database, an object-oriented database, a personal database, an in-memory database, a document-based database, a time series database, a wide column database, a key value database, a search database, a cache databases, and so forth. The foregoing examples of database 220 types are non-limiting and may not be mutually exclusive e.g., the database can be both commercial and cloud-based, or both relational and open-source, etc.
[0049] In order for the system 120 to monitor the network, the processor 205 includes one or more modules. In one embodiment, the one or more modules includes, but not limited to, a receiving module 225, a validation unit 230, a segregation unit 235, a decoding unit 240, a parsing module 245, a generation module 250, a feeding module 255, a storage module 260, an operating module 265, a analysing module 270, a transmittal unit 275 communicably coupled to each other.
[0050] The receiving module 225, the validation unit 230, the segregation unit 235, the decoding unit 240, the parsing module 245, the generation module 250, the feeding module 255, the storage module 260, the operating module 265, the analysing module 270, the transmittal unit 275 in an embodiment, may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processor 205. In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processor 205 may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for processor 205 may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the memory 210 may store instructions that, when executed by the processing resource, implement the processor 205. In such examples, the system 120 may comprise the memory 210 storing the instructions and the processing resource to execute the instructions, or the memory 210 may be separate but accessible to the system 120 and the processing resource. In other examples, the processor 205 may be implemented by electronic circuitry.
[0051] In one embodiment, the receiving module 225 is configured to receive the data pertaining to a user session in the network 105 from one or more network elements. The network elements refer to various components in the network 105, the network elements depict crucial roles in the functioning and management of the network 105. In one embodiment, the network elements in the network 105 includes, but are not limited to, the one or more base stations 125 such as for example gNodeB, core network components, the UE 110, network gateways. The user session refers to the duration taken by the UE 110 to establish and sustain a connection with the network 105 for the purpose of conducting data transmission. In an embodiment, the data includes at least one of call summary logs, signal strength, congestion in the network, and latency.
[0052] Upon receiving the data from the one or more network elements, the validation unit 230 is configured to validate the received data. In one embodiment the validation of the data may include, but not limited to, integrity, authenticity, and adherence to predefined standards.
[0053] Further, the system 120 includes the segregation unit 235 configured to segregate the validated data. The segregation unit 235 segregates the validated data based on specific criteria, such as the specific version of the respective network element such as the GnodeB. The version of the respective network element refers to the software version. The segregation of the data facilitates efficient handling, processing, and routing of data in the network 105.
[0054] Upon segregating the data, the validated data is transmitted to the decoding unit 240. The decoding unit 240 is configured to decode the validated data pertaining to the user session. The decoding unit 240 decodes the validated data byte by byte based on the version of the data received.
[0055] Upon decoding the validated data, the decoded data is transmitted to the parsing module 245. The parsing module 245 is configured to parse the decoded data to identify the irregularities in the decoded data. In one embodiment, the parsing refers to examining the decoded data to identify inconsistencies, errors, and deviations from expected standards. The parsing may include, but is not limited to, syntax analysis, semantic analysis, error detection and handling, data extraction. The irregularities may include, but are not limited to, missing fields, invalid data formats, inconsistent data, unexpected values. Due to parsing, advantageously facilitates in identifying and rectifying irregularities. The parsing of the decoded data facilitates the support for accuracy, reliability, and usability of data in the network 105.
[0056] Upon parsing the decoded data, further the decoded data is transmitted to the generation unit 250. The generation unit 250 is configured to generate reports and insights based on parsing of the decoded data. The generated reports and insights provide the network operator with the valuable information about the network 105 performance, anomalies, and potential issues. Further, the generated reports facilitate the user in troubleshooting, optimization, and proactive management of the network 105.
[0057] In one embodiment, the system 120 further includes the feeding module 255 configured to feed, the decoded data to a message broker unit. The storage module 260 is configured to store, the fed decoded data at the message broker unit. The message broker unit refers to a component for managing the flow of messages between one or more processers in the system 120. The message broker unit functions include but not limited to, message routing, protocol conversion, message queuing, load balancing, security enforcement, monitoring and logging.
[0058] In an embodiment, the system 120 further includes the operating module 245. The operating module 245 is configured to perform one or more operations on the decoded data. The one or more operations include at least one of enrichment, stitching, and data co-relation. In one embodiment, the enrichment refers to enhancing the decoded data with additional contextual information to facilitate the user comprehensive insights and analysis. Further the enriched data includes, but is not limited to, geographical coordinates, service types, application usage metrics, and network conditions to decoded data. In one embodiment, the stitching refers to correlating data from network 105 elements to create a unified view of events. In one embodiment, the data correlation refers to analyzing and identifying relationships between various data points to recognize patterns, trends, and irregularities in the network 105.
[0059] Upon performing the operations on the decoded data, the system 120 includes the analyzing module 270 configured to analyze the enriched data for monitoring the network 105 performance, identify one or more anomalies, and optimize Key Performance Indicators (KPIs). The anomalies refer to irregularities in the normal behavior of the network 105. In one embodiment, the anomalies may include, but not limited to, spike latency, packet loss, unusual traffic patterns, abnormal user behavior. The KPIs refer to metrics used to assess and measure the performance, efficiency, and quality of various aspects of the network 105 operation.
[0060] In an embodiment, the system 120 includes the transmittal unit 275. The transmittal unit is configured to transmit the generated insights and reports to the at least one UE 110. The generated insights and reports are made available to end-users via the user interface 215. The user interface 215 provides a user-friendly interface for visualizing, analyzing, and debugging the data to the end user such as a network operator.
[0061] FIG. 3 describes an embodiment of the system 120 of FIG. 2, according to various embodiments of the present invention. It is to be noted that the embodiment with respect to FIG. 3 will be explained with respect to the first UE 110a and the system 120 for the purpose of description and illustration and should nowhere be construed as limited to the scope of the present disclosure.
[0062] As mentioned earlier in FIG. 1, the UE 110 may include an external storage device, a bus, a main memory, a read-only memory, a mass storage device, communication port(s), and a processor. The exemplary embodiment as illustrated in FIG. 3 will be explained with respect to the first UE 110a without deviating from the scope of the present disclosure and limiting the scope of the present disclosure.
[0063] The UE 110a includes one or more primary processors 305 coupled with a memory unit 310 storing instructions which are executed by the one or more primary processors 305. Execution of the stored instructions by the one or more primary processors 305 enables the first UE 110a to request, call summary logs to the one or more processors. The call summary logs may include, but are not limited to, call start and end times, caller and recipient information, call duration, call type, quality metrics. In an embodiment, the UE 110a is associated to a network administrator, or technician at a network operator.
[0064] As per the illustrated embodiment, the system 120 includes the one or more processors 205, the memory 210, the user interface 215, and the database 220. The operations and functions of the one or more processors 205, the memory 210, the user interface 215, and the database 220 are already explained in FIG. 2. For the sake of brevity, a similar description related to the working and operation of the system 120 as illustrated in FIG. 2 has been omitted to avoid repetition.
[0065] FIG.4 is an exemplary architecture which can be implemented in the system 120 of the FIG.2 for monitoring a network, according to one or more embodiments of the present invention. The exemplary embodiment as illustrated in the FIG. 4 includes one or more GnodesBs 405, a probing agent 410, a conductor 415, a message broker unit 420, a normalizer 425, an AIDR writer 430, a GUI 435,a workflow 440, the database 220, a workflow 440,an Artificial Intelligence (AI)/Machine Learning (ML) module 445, , an ingestion layer 450 , a distributed file system 455, a computation engine 460, a computation layer 465, and an inventory system FMS 470.
[0066] In an embodiment, one or more GnondeBs 405 serve as the primary data source in the network 105. Further one or more GnodeBs can have different software versions. The one or more GnodeBs 405 is configured to generate call summary logs. The call summary logs refer to essential information about user sessions in the network 105. The information may include, but is not limited to, call release reason (CRR), clear code, subscriber details, signal strength, network congestion, latency, and other Key Performance Indicators (KPIs). Further the GnodeBs 405 transmits the generated call summary logs to the probing agent 410 via a Transmission Control Protocol (TCP). The TCP refers to networking protocol configured to transmit the data packets between the GnodeBs 405 and the probing agent 410 over the network 105.
[0067] Upon receiving the call summary data generated from one or more GnodeBs of different versions via the TCP, the probing agent 410 validates and segregates the received data based on the version of the GnodeBs 405. The call summary data from the one or more GnodeBs 405 is received as Hex dump stream over the TCP. Further the probing agent 410 consumes the call summary data byte by byte and stores it in message broker unit 420.
[0068] Upon validating and segregating the call summary data, the probing agent 410 transmits the call summary data to the conductor 415. The conductor 415 ingests and decodes the call summary data of multiple versions received from the probing agent 410 before feeding to the message broker unit 420. The conductor 415 is configured as the customized decoder component in the system 120. In an embodiment, the conductor 415 operates on byte indices to decode the call summary data. The conductor 415 features configurable versions that facilitates adjustments to accommodate changes in the length and position of fields within the decoded data. The configurations are illustrated by the user via the GUI 435, facilitating the accessibility for the user. Further by handling the different data versions, the conductor 415 facilitates seamless processing and compatibility across the system 120.
[0069] The collected call summary data from the probing agent 410 and the decoded data from the conductor 415 are securely stored in the message broker unit 420. The message broker unit 420 is configured as the publisher subscriber service to store the data. The message broker unit 420 act as an intermediary for data transmission and storage.
[0070] The normalizer 425 receives the decoded data from the message broker unit 420. The normalizer 425 performs real time enrichment, stitching, and data correlation operations on the collected data. Further the operations performed by the normalizer 425 facilitates the data by adding additional context, linking related information, and aligning the data for further analysis. Further the normalizer 425 optimizes the data for insights extraction and subsequent processing. In one embodiment, further the normalizer 425 is configured to receive rules from the user via the GUI 435. The rules may include, but are not limited to, data processing, data formatting and data transformation, data alignment based on the user request.
[0071] In one embodiment, the system 120 further includes Artificial Intelligence Data Records (AIDR) writer 430. The AIDR writer 430 continuously retrieves the data from the message broker unit 440 and stores it in the file system.
[0072] The GUI 435 serves as the interface for the users to interact with the call summary data in the system 120. In an embodiment, the user can request for any modifications to the call summary data via the GUI 435 to one or more processors. The GUI 435 facilitates the user to visualize, analyse, and debug the call summary data. Further the GUI 435 facilitates the user to gain insights into network performance, troubleshoot issues, and make informed decisions based on the data.
[0073] In an embodiment, the system 120 includes workflow 440. The workflow 440 is configured to receiving the requests from the GUI 435. The workflow 440 functions as the intermediary component between the GUI 435 and the computation engine 460. The workflow 440 directs the user requests to the computation engine 460 and fetches responses form the computation engine 460 for display in the GUI 435. In one embodiment, the workflow 440 stores, but not limited to, SIM-related data in the database for the reference and further analysis.
[0074] In an embodiment, the system 120 further includes the database 220. The database 220 is configured to store data. The data includes, but is not limited to meta data, subscriber level data, cell level data, policy related data and raw data from the one more processor of the system 120.
[0075] In one embodiment, the system 120 includes the AI/ML 445 module. The AI/ML module 445 is configured to monitor and train the data received from GnodeBs 405. Further the AI/ML module 445 utilizes the data stored in the database 220 and distributed file system 455 to detect anomalies, identify patterns, and recommend actions for network optimization. Further the AI/ML 335 module depicts proactive network management and enhanced network performance of the network 105.
[0076] In one embodiment, the system 120 includes the ingestion layer 450. The ingestion layer 450 is configured to fetch the data from the AIDR writer 430 and push it to the distributed file system 455. In one embodiment, further the ingestion layer 450 fetches the SIM details from FMS and transmits it to the workflow 440.
[0077] In one embodiment, the system 120 further includes distributed file system 455. The distributed file system 455 is configured to store the data from the ingestion layer 450, which computation layer 465 utilizes this data for the computation process.
[0078] In one embodiment, the system 120 includes a computation engine 460. The computation engine 460 receives requests from the workflow 440 for the particular call summary data types as requested by the user. In an embodiment the request includes, but not limited to KPI selected and/or aggregation by the user for a particular time period. Upon receiving the requests, the computation engine 465 assigns the task to the computation engine 460 for the computation of the requested call summary data. Further the computation engine 460 facilitates the user to define the polices via the GUI 435 to receive threshold breach notifications for all types of monitoring data via at least one of, but not limited to, SMS/mail. Further the computation engine 460 ensures efficient resource allocation and manages the execution of computations. In one embodiment, the computation engine 460 performs at least one of, aggregations on the data, KPI calculation on the data, segregations on the data. Further after the completion of the computation, the computation engine 460 fetches transmits to the workflow 460 for retrieval and display.
[0079] In one embodiment the system 120 includes computation layer 465. Upon the assignment of the computation task by the computation engine 460 regarding the requested data, the computation layer 465 operates on the data available in the database 220 and the distributed file system 455 generates the computed data for the requested data. In an embodiment, the computation of the data can be at either cell level or subscriber level.
[0080] In one embodiment, the system 120 further includes the (Fulfillment Management System) FMS 470. The FMS 470 is configured as the inventory system, designed to capture, request, and store subscriber level details.
[0081] FIG. 5 is a signal flow diagram for monitoring a network, according to one or more embodiments of the present invention. For the purpose of description, the signal flow diagram is described with the embodiments as illustrated in FIG. 2 and should nowhere be construed as limiting the scope of the present disclosure.
[0082] At step 505, the Gnodebs 505 receives the data pertaining to a user session from the network elements and transmits the received data to the probing agent 410. The data includes at least one of call summary logs, signal strength, congestion in the network, and latency.
[0083] At step 510, upon receiving the data, the probing agent 410 validates, and segregates based on the received data version. Further the probing agent 410 ensures compatibility and streamlined processing of the collected data and facilitating the efficient analysis in subsequent steps. Further the probing agent 410 transmits the validated and segregated data to the conductor 415.
[0084] At step 515, upon segregation and validation the data is transmitted to a decoding unit which is, the conductor 415. The conductor 415 is configured as the customized decoder component. The conductor 415 decodes the call summary log data of multiple versions received via the probing agent 410. Further the conductor 415 transmits the decoded data to the message broker unit 420 for storage. The conductor 415 facilitates further processing and analysis, ensuring compatibility and accessibility across the system.
[0085] At step 520, the decoded data is securely stored in the message broker unit 420. The message broker unit 420 serves as the publisher-subscriber service in the system 120. The message broker unit 420 is configured for reliable storage and transmission of the collected call summary data. Further the message broker unit 420 transmits the decoded data to the normalizer 425.
[0086] At step 525, upon receiving the decoded data from the message broker unit 420. The normalizer 425 performs real time enrichment, stitching, and data correlation operations. Further the enriched data is transmitted to the AI/ML module 330 for the further analysis.
[0087] At step 530, the AI/ML module 445 continuously analyzes the normalized and enriched data to monitor the network performance, identify anomalies, and optimize Key Performance Indicators (KPIs). The AI/ML 445 analysis provides real-time network intelligence. Further the AI/ML module 445 facilitates the identification and analysis of irregularities in the network 105. Upon analysis the AI/ML module 445 generates actionable insights and reports. Further the generated insights facilitate the network operators with valuable information about network performance, anomalies, and potential issues. Further the generated reports facilitate troubleshooting, optimization, and proactive management of the network 105, and ensuring a seamless user experience.
[0088] At step 535, the generated insights and reports are made available to end-users through a GUI 435. The GUI 435 provides a user-friendly interface for visualizing, analyzing, and debugging the data. End-users can interact with the data, gain insights into network performance, and make informed decisions based on the provided information.
[0089] At step 540, the GUI 435 displays the reports, KPI’s, call session data for the end user, that is the network administrator, or technician at a network operator. In an embodiment, the GUI 435 is deployed in the User Equipment (UE), which is indicated as the UE 110a in FIG. 3.
[0090] FIG. 6 is a flow diagram illustrating a method 500 for integrating Radio Access Network (RAN) data with the packet core data.
[0091] At step 605, the method 600 includes the step of receiving the data pertaining to a user session in the network from one or more network elements. The received data includes at least one of call summary logs, signal strength, congestion in the network, and latency.
[0092] At step 610, the method 600 includes the step of validating the received data. the validation of the data may include, but not limited to, integrity, authenticity, and adherence to predefined standards.
[0093] At step 615, the method 600 includes the step of segregating the validated data. The data is segregated based on the received data version from the network elements.
[0094] At step 620, the method 600 includes the step of decoding the validated data pertaining to the user session. The validated data is decoded byte by byte based on the version of the data received.
[0095] At step 625, the method 600 includes the step of parsing the decoded data to identify irregularities in the decoded data. The parsing helps in identifying and rectifying irregularities. parsing of the decoded data facilitates the support for accuracy, reliability, and usability of data in the network.
[0096] At step 630, the method 600 includes the step of generating reports and insights based on parsing of the decoded data. the reports and insights are generated based on parsing of the decoded data.
[0097] A person of ordinary skill in the art will readily ascertain that the illustrated embodiments and steps in description and drawings (FIG.1-6) are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments.
[0098] The present disclosure incorporates technical advancement that facilitates the collection, analysis, and management of RAN data in 5G networks. By eliminating physical tapping, enhancing data security, and providing near real-time network insights, the invention enables the efficient troubleshooting, optimization, and proactive network management, contributing to a seamless and enhanced user experience in the 5G ecosystem. The invention provides the network operators with near real-time network intelligence, empowering them to promptly identify and resolve network degradation or failure occurrences. Further the present invention supports the automation and predictive capabilities. Further the invention facilitates network troubleshooting, optimization, and the overall user experience.
[0099] The present invention provides various advantages, including optimal resource utilization and reduced execution time. The system eliminates the necessity for physically tapping network connections, further the system facilitates the reduced disruptions to network operations and mitigating security risks. The solution minimizes hardware infrastructure requirements, leading to cost savings and improved scalability. Further the system provides near real-time network intelligence, facilitating proactive identification and resolution of network issues, resulting in a seamless user experience. The solution further leverages advanced AI/ML algorithms and anomaly detection techniques to enhance network monitoring and troubleshooting capabilities, facilitating efficient data analysis and faster issue resolution.
[00100] The present invention offers multiple advantages over the prior art and the above listed are a few examples to emphasize on some of the advantageous features. The listed advantages are to be read in a non-limiting manner.

REFERENCE NUMERALS
[00101] Communication system – 100
[00102] Network – 105
[00103] User Equipment – 110
[00104] Server – 115
[00105] System – 120
[00106] Processor -205
[00107] Memory – 210
[00108] User Interface– 215
[00109] Database- 220
[00110] Receiving module – 225
[00111] Validation unit -230
[00112] Segregation unit -235
[00113] Decoding unit -240
[00114] Parsing module - 245
[00115] Generation module - 250
[00116] Feeding module -255
[00117] Storage module - 260
[00118] Operating module – 265
[00119] Analysing module - 270
[00120] Transmittal unit- 275
[00121] GnodeBs - 405
[00122] Probing agent - 410
[00123] Conductor – 415
[00124] Message broker unit 420
[00125] Normalizer – 425
[00126] AIDR writer – 430
[00127] GUI – 435
[00128] Workflow – 440
[00129] Artificial Intelligence /Machine Learning module - 445
[00130] Ingestion layer – 450
[00131] Distributed file system – 455
[00132] Computation engine – 460
[00133] Computation layer – 465
[00134] Fulfilment Management System - 470

,CLAIMS:CLAIMS
We Claim:
1. A method (600) of monitoring a network, the method comprising the steps of:
receiving (605), by one or more processors (205), data pertaining to a user session in the network (105) from one or more network elements;
validating (610), by the one or more processors (205), the received data;
segregating (615), by the one or more processors (205), the validated data;
decoding (620), by the one or more processor (205), the validated data pertaining to the user session;
parsing (625), by the one or more processors (205), the decoded data to identify irregularities in the decoded data; and
generating (630), by the one or more processors (205), reports and insights based on parsing of the decoded data.

2. The method (600) as claimed in claim 1, wherein upon decoding of the received data, the method comprises the steps of:
feeding (635), by the one or more processors (205), the decoded data to a message broker unit; and
storing (640), by the one or more processors (205), the fed decoded data at the message broker unit.

3. The method (600) as claimed in claim 2, performing data operations wherein the one or more one or more operations include enrichment, stitching and data co-relation.

4. The method (600) as claimed claim3, wherein upon enriching the method comprising the step of, analysing, by the one or more processors (205), the enriched data to monitor network performance, identify one or more anomalies, and optimize Key Performance Indicators (KPIs).

5. The method (600) as claimed in claim 1, wherein the data includes at least one of call summary logs, signal strength, congestion in the network, and latency.

6. The method (600) as claimed in claim 1, wherein the received data is segregated and validated based on at least one of version of the received data.

7. The method (600) as claimed in claim 1, wherein upon generation of the insight and reports, the method comprises the step of transmitting, by the one or more processors, the generated insight and reports to at least one User Equipment (110) (UE).

8. A system (120) for monitoring a network, the system comprising:
a receiving module (225) configured to receive, data pertaining to a user session in the network from one or more network elements;
a validation unit (230) configured to validate, the received data;
a segregation unit (235) configured to segregate, the validated data;
a decoding unit (240) configured to decode, the validated data pertaining to the user session;
a parsing module (245) configured to parse, the decoded data to identify irregularities in the decoded data; and
a generation module (250) configured to generate, reports and insights based on parsing of the decoded data.

9. The system (120) as claimed in claim 9, wherein the system comprises:
a feeding module (255) configured to feed, the decoded data to a message broker unit; and
a storage module (260) configured to store, the fed decoded data at the message broker unit.

10. The system as claimed in claim 9, wherein the system comprises an operating module configured to perform, one or more operations on the decoded data, the one or more operations include at least one of enrichment, stitching, and data co-relation.

11. The system (120) as claimed in claim 10, comprising an analysing module configured to analyse the enriched data to monitor network performance, identify one or more anomalies, and optimize Key Performance Indicators (KPIs).

12. The system (120) as claimed claim 9, wherein the data includes at least one of call summary logs, signal strength, congestion in the network, and latency

13. The system (120) as claimed in claim 9, wherein the received data is segregated and validated based on at least one of the version of the received data.

14. The system (120) as claimed in claim 7, wherein the system comprises a transmittal unit (275) configured to transmit, the generated insight and reports to at least one User Equipment (UE), upon generation of the insight and reports.

15. A User Equipment (UE), comprising:
one or more primary processors communicatively coupled to one or more processors, the one or more primary processors coupled with a memory, wherein said memory stores instructions which when executed by the one or more primary processors causes the UE to:
to display, the reports, KPI’s and call session data.; and
wherein the one or more processors is configured to perform the steps as claimed in claim 1.