FORM 2
THE PATENTS ACT, 1970 (39 OF 1970) & THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
“SYSTEM AND METHOD FOR KEY PERFORMANCE INDICATOR (KPI) CALCULATION AND REPORTING”
We, Jio Platforms Limited, an Indian National, of Office - 101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad - 380006, Gujarat, India.
The following specification particularly describes the invention and the manner in which it is to be performed.

SYSTEM AND METHOD FOR KEY PERFORMANCE INDICATOR (KPI) CALCULATION AND REPORTING
FIELD OF THE DISCLOSURE
[0001] The present disclosure relates generally to the field of wireless communication systems. In particular, the present disclosure relates to for monitoring and analysing network performance. More particularly, the present disclosure relates to system and method for key performance indicator (KPI) calculation and reporting.
BACKGROUND OF THE DISCLOSURE
[0002] The following description of 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 be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0003] Wireless communication technology has rapidly evolved over the past few decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice services. However, with the advent of the second-generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. 3G technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth-generation (4G) technology revolutionized wireless communication with faster data speeds, better network coverage, and improved security. Currently, the fifth-generation (5G) technology is being

deployed, promising even faster data speeds, low latency, and the ability to connect multiple devices simultaneously. With each generation, wireless communication technology has become more advanced, sophisticated, and capable of delivering more services to its users.
[0004] Existing network management systems often rely on predefined KPIs and periodic reports, which do not provide real-time visibility into network performance. This hinders the ability to promptly identify and address performance issues as they occur. Prior art systems may have a fixed set of KPIs, which may not be suitable for all network environments or specific requirements. This lack of customization restricts the ability to monitor and analyze network performance based on individual needs. Generating aggregated reports based on KPIs can be a time-consuming and complex task in traditional systems. Network managers may face challenges in obtaining timely and meaningful reports to assess the overall performance and identify trends. Without a robust threshold monitoring mechanism, network managers may not receive timely notifications or alarms when KPI values deviate from acceptable levels. This delay in identifying performance issues can lead to prolonged network degradation or outages. Existing systems may face challenges in scaling up to manage large volumes of network data or in providing failover support in case of system failures. This can result in limitations in processing capacity and potential disruptions in KPI calculations. Prior art systems may lack comprehensive validation mechanisms to ensure the accuracy and integrity of KPI formulas. Additionally, managing and modifying KPI formulas during runtime may be cumbersome and error-prone.
[0005] These problems and limitations in the prior art necessitate the development of an improved network management system that addresses real-time calculation, customization, reporting efficiency, threshold monitoring, scalability, failover support, and validation and management of KPIs. The present disclosure aims to

overcome these drawbacks and provide a more advanced and comprehensive solution for network performance analysis and decision-making processes.
OBJECTS OF THE DISCLOSURE
[0006] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.
[0007] It is an object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting.
[0008] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that allows users to define an unlimited number of KPIs for a specific Network Element. This flexibility ensures that network performance can be thoroughly measured and analysed.
[0009] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that supports real¬time calculations of KPI values, ensuring immediate access to essential data for decision-making.
[0010] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that provides Min, Max, and Average aggregations of the calculated KPIs, offering a nuanced understanding of network performance.
[0011] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that enables Quarterly, Hourly, and Daily KPI trends to be visualized in charts. Additionally, the system allows for the generation of reports for these KPIs over a given time

duration. These reports can be specifically tailored to a list of Network instances or specific KPIs.
[0012] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that enables users to define a threshold value for any KPI. If any KPI value drops below the defined threshold, the system will raise an alarm, enabling proactive responses to potential network issues.
[0013] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that supports the configuration of Quarterly, Hourly, and Daily KPI reports, as well as the Min, Max, and Average aggregations at the KPI level.
[0014] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that is scalable, as KPI calculations for Network Elements can be distributed between worker nodes.
[0015] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that allows for the addition, deletion, and modification of KPI formulas directly from the user interface (UI) at runtime.
[0016] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that provides failover support, meaning if a worker node fails, the KPI calculation task is automatically shifted to another available worker node.
[0017] It is another object of the present disclosure to provide a system and method for key performance indicator (KPI) calculation and reporting that validates KPI

file containing one or more KPI definitions, wherein each KPI definition of the one
or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type,
and a threshold value. The method further comprises assigning, by an assignment
unit, at least one KPI profile to at least one worker node for processing, wherein the
5 at least one worker node is configured to determine one or more KPI values for a
plurality of network elements associated with the at least one KPI profile. The method further comprises retrieving, by a retrieving unit, via the at least worker node, counter data from a database corresponding to the one or more KPI definitions. The method further comprises determining, by a determination unit,
10 one or more KPI values for each network element of the plurality of network
elements based on the retrieved counter data and the received at least one KPI formula file. The method further comprises generating, by a generation unit, one or more aggregated KPI results from the determined one or more KPI values. The method further comprises comparing, by a comparator unit, the determined one or
15 more KPI values to the threshold value associated with the each KPI definition of
the one or more KPI definitions. And finally, the method comprises generating, by the generation unit, a KPI report, wherein the report comprises aggregated one or more KPI values for a predefined time period.
20 [0023] Further as per an aspect of the disclosure, the method further comprises
distributing, by a distribution unit, a task of KPI determination to a plurality of worker nodes, wherein the at least one worker node from the plurality of worker nodes is configured to determine the one or more KPI values for the plurality of network elements, and wherein in an event of a failure of at least one worker node
25 of the plurality of worker nodes, the KPI determination task of the failed at least
one worker node is automatically reassigned to other available worker nodes from the plurality of worker nodes.
[0024] Further as per an aspect of the disclosure, in the method, the aggregated KPI
30 results comprise at least a minimum value, a maximum value, and an average value.
7

[0025] Further as per an aspect of the disclosure, the method comprises defining, by the at least one worker node, the at least one KPI profile based on a criterion, wherein the criterion comprises network type and circle combination. 5
[0026] Further as per an aspect of the disclosure, the method comprises validating, by the transceiver unit, the received KPI formula file to ensure mathematical correctness of the KPI formula and absence of duplicate KPI definition.
10 [0027] Further as per an aspect of the disclosure, the method comprises storing, by
the database, the validated at least one KPI formula file.
[0028] Further as per an aspect of the disclosure, the method comprises receiving,
by the transceiver unit via the user interface, a report request specifying a time
15 duration and desired KPIs.
[0029] Further as per an aspect of the disclosure, the method comprises activating, by an activation unit, an alarm sequence if at least one determined KPI value of the one or more KPI values breaches corresponding threshold value. 20
[0030] Further as per an aspect of the disclosure, the method comprises displaying, by a display unit via the user interface, the generated KPI report.
[0031] Another aspect of the present disclosure relates to a system for key
25 performance indicator (KPI) calculation and reporting. The system comprises a
transceiver unit configured to receive, via a user interface, at least one KPI formula
file containing one or more KPI definitions, wherein each KPI definition of the one
or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type,
and a threshold value. The system further comprises an assignment unit connected
30 to at least the transceiver unit, and the assignment unit is configured to assign at
8

least one KPI profile to at least one worker node for processing, wherein the at least
one worker node is configured to determine one or more KPI values for a plurality
of network elements associated with the at least one KPI profile. The system further
comprises a retrieving unit connected to at least the assignment unit, and the
5 retrieving unit is configured to retrieve, via the at least one worker node, counter
data from a database corresponding to the one or more KPI definitions. The system further comprises a determination unit connected to at least the retrieving unit, and the determination unit configured to determine, one or more KPI values for each network element of the plurality of network elements based on the retrieved counter
10 data and the received at least one KPI formula file. The system further comprises a
generation unit connected to at least the determination unit, and the generation unit is configured to generate one or more aggregated KPI results from the determined one or more KPI values. The system further comprises a comparator unit connected to at least the generation unit, and the comparator unit is configured to compare the
15 determined one or more KPI values to the threshold value associated with the each
KPI definition of the one or more KPI definitions. And finally, the generation unit of the system is further configured to generate a KPI report, wherein the report comprises aggregated one or more KPI values for a predefined time period.
20 [0032] Another aspect of the present disclosure provides a user equipment (UE) for
key performance indicator (KPI) calculation and reporting, the UE comprises: a processor configured to: receive, via a user interface, at least one KPI formula file containing one or more KPI definitions, wherein each KPI definition of the one or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type,
25 and a threshold value; assign at least one KPI profile to at least one worker node for
processing, wherein the at least one worker node is configured to determine one or more KPI values for a plurality of network elements associated with the at least one KPI profile, wherein the key performance indicator (KPI) calculation and reporting is performed based on: retrieving, by a retrieving unit, via the at least worker node,
30 counter data from a database corresponding to the one or more KPI definitions;
9

determining, by a determination unit, in real-time , one or more KPI values for each
network element of the plurality of network elements based on the retrieved counter
data and the received at least one KPI formula file; generating, by a generation unit,
one or more aggregated KPI results from the determined one or more KPI values;
5 comparing, by a comparator unit, the determined one or more KPI values to the
threshold value associated with the each KPI definition of the one or more KPI definitions; and generating, by a generation unit, a KPI report, wherein the report comprises aggregated one or more KPI values for a predefined time period.
10 [0033] Further, an aspect of the present disclosure relates to a non-transitory
computer readable storage medium, storing instructions for key performance indicator (KPI) calculation and reporting. The instructions when executed by one or more units of a system configured for key performance indicator (KPI) calculation and reporting, cause a transceiver unit, via a user interface, to receive at
15 least one KPI formula file containing one or more KPI definitions and wherein
each KPI definition of the one or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type, and a threshold value. The instructions upon receipt further cause an assignment unit to assign at least one KPI profile to at least one worker node for processing, wherein the at least one worker node is configured
20 to determine one or more KPI values for a plurality of network elements associated
with the at least one KPI profile. The instructions upon assignment further cause a retrieving unit, via the at least worker node, to retrieve counter data from a database corresponding to the one or more KPI definitions. The instructions upon retrieval further cause a determination unit, to determine one or more KPI values for each
25 network element of the plurality of network elements based on the retrieved counter
data and the received at least one KPI formula file. The instructions upon determination further cause a generation unit, to generate one or more aggregated KPI results from the determined one or more KPI values. The instructions upon generation further cause a comparator unit to compare the determined one or more
30 KPI values to the threshold value associated with the each KPI definition of the one
10

or more KPI definitions. And finally, the instructions upon comparison further cause the generator unit to generate a KPI report, and wherein the report comprises aggregated one or more KPI values for a predefined time period.
5 BRIEF DESCRIPTION OF DRAWINGS
[0034] 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
10 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
15 electrical components, electronic components or circuitry commonly used to
implement such components.
[0035] FIG. 1A illustrates an exemplary block diagram representation of a 5th generation core (5GC) network architecture. 20
[0036] FIG. 1B illustrates an exemplary a block diagram of a system for key performance indicator (KPI) calculation and reporting, in accordance with exemplary embodiments of the present disclosure.
25 [0037] FIG. 2 illustrates an exemplary method flow indicating the process for key
performance indicator (KPI) calculation and reporting, in accordance with exemplary embodiments of the present disclosure.
11

[0038] FIG. 3 illustrates another exemplary system architecture for key performance indicator (KPI) calculation and reporting, in accordance with exemplary embodiments of the present disclosure.
5 [0039] FIG. 4 illustrates another exemplary process for key performance indicator
(KPI) calculation and reporting, in accordance with exemplary embodiments of the present disclosure.
[0040] FIG. 5 illustrates an exemplary block diagram of a computing device upon
10 which an embodiment of the present disclosure may be implemented.
[0041] The foregoing shall be more apparent from the following more detailed description of the disclosure.
15 DETAILED DESCRIPTION OF THE DISCLOSURE
[0042] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that
20 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 any of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be
25 fully addressed by any of the features described herein. Example embodiments of
the present disclosure are described below, as illustrated in various drawings in which like reference numerals refer to the same parts throughout the different drawings.
12

[0043] 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.
5 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.
[0044] It should be noted that the terms "mobile device", "user equipment", "user
10 device", “communication device”, “device” and similar terms are used
interchangeably for the purpose of describing the disclosure. These terms are not
intended to limit the scope of the disclosure or imply any specific functionality or
limitations on the described embodiments. The use of these terms is solely for
convenience and clarity of description. The disclosure is not limited to any
15 particular type of device or equipment, and it should be understood that other
equivalent terms or variations thereof may be used interchangeably without departing from the scope of the disclosure as defined herein.
[0045] Specific details are given in the following description to provide a thorough
20 understanding of the embodiments. However, it will be understood by one 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
25 circuits, processes, algorithms, structures, and techniques may be shown without
unnecessary detail in order to avoid obscuring the embodiments.
[0046] Also, it is noted that individual embodiments may be described as a process
which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure
30 diagram, or a block diagram. Although a flowchart may describe the operations as
13

a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. 5
[0047] 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
10 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—in a manner
15 similar to the term “comprising” as an open transition word—without precluding
any additional or other elements.
[0048] As used herein, an “electronic device”, or “portable electronic device”, or “user device” or “communication device” or “user equipment” or “device” refers
20 to any electrical, electronic, electromechanical and computing device. The user
device is capable of receiving and/or transmitting one or parameters, performing function/s, communicating with other user devices and transmitting data to the other user devices. The user equipment may have a processor, a display, a memory, a battery and an input-means such as a hard keypad and/or a soft keypad. The user
25 equipment may be capable of operating on any radio access technology including
but not limited to IP-enabled communication, Zig Bee, Bluetooth, Bluetooth Low Energy, Near Field Communication, Z-Wave, Wi-Fi, Wi-Fi direct, etc. For instance, the user equipment may include, but not limited to, a mobile phone, smartphone, virtual reality (VR) devices, augmented reality (AR) devices, laptop,
30 a general-purpose computer, desktop, personal digital assistant, tablet computer,
14

mainframe computer, or any other device as may be obvious to a person skilled in the art for implementation of the features of the present disclosure.
[0049] Further, the user device may also comprise a “processor” or “processing
5 unit” includes processing unit, wherein processor refers to any logic circuitry for
processing instructions. The processor may be a general-purpose processor, a
special purpose processor, a conventional processor, a digital signal processor, a
plurality of microprocessors, one or more microprocessors in association with a
DSP core, a controller, a microcontroller, Application Specific Integrated Circuits,
10 Field Programmable Gate Array circuits, any other type of integrated circuits, etc.
The processor may perform signal coding data processing, input/output processing, and/or any other functionality that enables the working of the system according to the present disclosure. More specifically, the processor is a hardware processor.
15 [0050] As portable electronic devices and wireless technologies continue to
improve and grow in popularity, the advancing wireless technologies for data transfer are also expected to evolve and replace the older generations of technologies. In the field of wireless data communications, the dynamic advancement of various generations of cellular technology are also seen. The
20 development, in this respect, has been incremental in the order of second generation
(2G), third generation (3G), fourth generation (4G), and now fifth generation (5G), and more such generations are expected to continue in the forthcoming time.
[0051] Radio Access Technology (RAT) refers to the technology used by mobile
25 devices/ user equipment (UE) to connect to a cellular network. It refers to the
specific protocol and standards that govern the way devices communicate with base
stations, which are responsible for providing the wireless connection. Further, each
RAT has its own set of protocols and standards for communication, which define
the frequency bands, modulation techniques, and other parameters used for
30 transmitting and receiving data. Examples of RATs include GSM (Global System
15

for Mobile Communications), CDMA (Code Division Multiple Access), UMTS
(Universal Mobile Telecommunications System), LTE (Long-Term Evolution),
and 5G. The choice of RAT depends on a variety of factors, including the network
infrastructure, the available spectrum, and the mobile device's/device's capabilities.
5 Mobile devices often support multiple RATs, allowing them to connect to different
types of networks and provide optimal performance based on the available network resources.
[0052] gNodeB" (gNB) refers to the base station component in 5G (fifth-
10 generation) wireless networks. It is an essential element of the Radio Access
Network (RAN) responsible for transmitting and receiving wireless signals to and
from user devices, such as smartphones, tablets, and Internet of Things (IoT)
devices. In 5G networks, there are similar components in other generations of
wireless networks. Here are a few examples: Base Transceiver Station (BTS): In
15 2G (second-generation) networks, the BTS serves as the base station responsible
for transmitting and receiving wireless signals. It connects mobile devices to the
cellular network infrastructure. NodeB: In 3G (third-generation) networks, the
NodeB is the base station component that enables wireless communication. It
facilitates the transmission and reception of signals between user devices and the
20 network. eNodeB: In 4G (fourth-generation) LTE (Long-Term Evolution)
networks, the eNodeB serves as the base station. It supports high-speed data
transmission, low latency, and improved network capacity. Access Point (AP): In
Wi-Fi networks, an access point functions as a central hub that enables wireless
devices to connect to a wired network. It provides a wireless interface for devices
25 to access the network and facilitates communication between them. The examples
illustrate the base station components in different generations of wireless networks,
such as BTS in 2G, NodeB in 3G, eNodeB in 4G LTE, and gNodeB in 5G. Each
component plays a crucial role in facilitating wireless connectivity and
communication between user devices and the network infrastructure.
30
16

[0053] As discussed in the background section, existing network management
systems often rely on predefined KPIs and periodic reports, which do not provide
real-time visibility into network performance. This hinders the ability to promptly
identify and address performance issues as they occur. Prior art systems may have
5 a fixed set of KPIs, which may not be suitable for all network environments or
specific requirements. This lack of customization restricts the ability to monitor and analyze network performance based on individual needs. Generating aggregated reports based on KPIs can be a time-consuming and complex task in traditional systems. Network managers may face challenges in obtaining timely and
10 meaningful reports to assess the overall performance and identify trends. Without
a robust threshold monitoring mechanism, network managers may not receive timely notifications or alarms when KPI values deviate from acceptable levels. This delay in identifying performance issues can lead to prolonged network degradation or outages. Existing systems may face challenges in scaling up to manage large
15 volumes of network data or in providing failover support in case of system failures.
This can result in limitations in processing capacity and potential disruptions in KPI calculations. Prior art systems may lack comprehensive validation mechanisms to ensure the accuracy and integrity of KPI formulas. Additionally, managing and modifying KPI formulas during runtime may be cumbersome and error-prone.
20
[0054] To overcome these and other inherent problems in the art, the present disclosure proposes a solution of a system and method for defining, calculating, and reporting Key Performance Indicators (KPIs) in real-time for 4G-5G networks, with a high degree of customization and flexibility. The proposed solution enables
25 network managers to define any number of KPIs tailored to specific network
elements, overcoming the limitations of fixed KPI sets in prior systems. By allowing real-time calculations and visualizations of KPIs, the system ensures immediate visibility into network performance, facilitating prompt troubleshooting and decision-making. Furthermore, the proposed solution integrates robust
30 validation mechanisms for KPI formulas, ensuring their mathematical correctness
17

and uniqueness, thus preventing errors that can lead to inaccurate performance
assessments. The system supports dynamic modifications to KPI formulas through
a user interface, allowing network managers to adapt KPI monitoring in response
to changing network conditions without downtime or complex reconfigurations.
5 The system's scalability is addressed through a distributed architecture where KPI
calculation tasks are divided among multiple worker nodes. This not only enhances
the system's capacity to manage large volumes of data but also provides failover
support, ensuring continuous operation even in the event of node failures.
Additionally, the system includes advanced threshold monitoring capabilities,
10 allowing for the configuration of multiple threshold levels and corresponding
alarms. This proactive monitoring enables network managers to receive instant alerts when performance deviates from set parameters, thereby minimizing the impact of network issues.
15 [0055] It would be appreciated by the person skilled in the art that the present
disclosure offers a comprehensive and adaptable solution for network performance management, addressing the shortcomings of existing systems by providing enhanced customization, real-time capabilities, scalability, and robust fault tolerance.
20
[0056] Hereinafter, exemplary embodiments of the present disclosure will be described with reference to the accompanying drawings.
[0057] Referring to FIG. 1A, an exemplary block diagram representation of 5th
25 generation core (5GC) network architecture, in accordance with exemplary
embodiment of the present disclosure. As shown in FIG. 1A, the 5GC network
architecture [100A] includes a user equipment (UE) [102u], a radio access network
(RAN) [104r], an access and mobility management function (AMF) [106a], a
Session Management Function (SMF) [108s], a Service Communication Proxy
30 (SCP) [110s], an Authentication Server Function (AUSF) [112a], a Network Slice
18

Specific Authentication and Authorization Function (NSSAAF) [114n], a Network
Slice Selection Function (NSSF) [116n], a Network Exposure Function (NEF)
[118n], a Network Repository Function (NRF) [120n], a Policy Control Function
(PCF) [122p], a Unified Data Management (UDM) [124u], an application function
5 (AF) [126a], a User Plane Function (UPF) [128u], a data network (DN) [130d],
wherein all the components are assumed to be connected to each other in a manner as obvious to the person skilled in the art for implementing features of the present disclosure.
10 [0058] The User Equipment (UE) [102u] interfaces with the network via the Radio
Access Network (RAN) [104r]; the Access and Mobility Management Function (AMF) [106a] manages connectivity and mobility, while the Session Management Function (SMF) [108s] administers session control; the service communication proxy (SCP) [110s] routes and manages communication between network services,
15 enhancing efficiency and security, and the Authentication Server Function (AUSF)
[112a] handles user authentication; the NSSAAF [114n] for integrating the 5G core network with existing 4G LTE networks i.e., to enable Non-Standalone (NSA) 5G deployments, the Network Slice Selection Function (NSSF) [116n], Network Exposure Function (NEF) [118n], and Network Repository Function (NRF) [120n]
20 enable network customization, secure interfacing with external applications, and
maintain network function registries respectively; the Policy Control Function (PCF) [122p] develops operational policies, and the Unified Data Management (UDM) [124u] manages subscriber data; the Application Function (AF) [126a] enables application interaction, the User Plane Function (UPF) [128u] processes
25 and forwards user data, and the Data Network (DN) [130d] connects to external
internet resources; collectively, these components are designed to enhance mobile broadband, ensure low-latency communication, and support massive machine-type communication, solidifying the 5GC as the infrastructure for next-generation mobile networks.
30
19

[0059] Radio Access Network (RAN) [104r] is the part of a mobile
telecommunications system that connects user equipment (UE) [102u] to the core
network (CN) and provides access to different types of networks (e.g., 5G network).
It consists of radio base stations and the radio access technologies that enable
5 wireless communication.
[0060] Access and Mobility Management Function (AMF) [106a] is a 5G core
network function responsible for managing access and mobility aspects, such as UE
registration, connection, and reachability. It also handles mobility management
10 procedures like handovers and paging.
[0061] Session Management Function (SMF) [108s] is a 5G core network function
responsible for managing session-related aspects, such as establishing, modifying,
and releasing sessions. It coordinates with the User Plane Function (UPF) [128u]for
15 data forwarding and handles IP address allocation and QoS enforcement.
[0062] Service Communication Proxy (SCP) [110s] is a network function in the 5G
core network that facilitates communication between other network functions by
providing a secure and efficient messaging service. It acts as a mediator for service-
20 based interfaces.
[0063] Authentication Server Function (AUSF) [112a] is a network function in the 5G core responsible for authenticating UEs during registration and providing security services. It generates and verifies authentication vectors and tokens.
25
[0064] Network Slice Specific Authentication and Authorization Function (NSSAAF) [114n] is a network function that provides authentication and authorization services specific to network slices. It ensures that UEs can access only the slices for which they are authorized.
30
20

[0065] Network Slice Selection Function (NSSF) [116n] is a network function responsible for selecting the appropriate network slice for a UE based on factors such as subscription, requested services, and network policies.
5 [0066] Network Exposure Function (NEF) [118n] is a network function that
exposes capabilities and services of the 5G network to external applications, enabling integration with third-party services and applications.
[0067] Network Repository Function (NRF) [120n] is a network function that acts
10 as a central repository for information about available network functions and
services. It facilitates the discovery and dynamic registration of network functions.
[0068] Policy Control Function (PCF) [122p] is a network function responsible for
policy control decisions, such as QoS, charging, and access control, based on
15 subscriber information and network policies.
[0069] Unified Data Management (UDM) [124u] is a network function that centralizes the management of subscriber data, including authentication, authorization, and subscription information. 20
[0070] Application Function (AF) [126a] is a network function that represents external applications interfacing with the 5G core network to access network capabilities and services.
25 [0071] User Plane Function (UPF) [128u] is a network function responsible for
handling user data traffic, including packet routing, forwarding, and QoS enforcement.
21

[0072] Data Network (DN) [130d] refers to a network that provides data services to user equipment (UE) in a telecommunications system. The data services may include but are not limited to Internet services, private data network related services.
5 [0073] FIG.1B illustrates an exemplary block diagram of a system [100] for key
performance indicator (KPI) calculation and reporting, in accordance with exemplary embodiments of the present disclosure. The present disclosure includes the system [100] comprising at least a transceiver unit [101], at least a user interface [102], at least an assignment unit [103], at least a worker node [104], at least a
10 retrieving unit [105], at least a database [106], at least a determination unit [107],
at least a generation unit [108], at least a comparator unit [109], at least a distribution unit [110], at least an activation unit [111], and at least a display unit [112] wherein all the components are assumed to be connected to each other in a manner as obvious to the person skilled in the art for implementing features of the
15 present disclosure. Also, in FIG. 1B only a few units are shown, however, the
system [100] may comprise multiple such units or the system [100] may comprise any such numbers of said units, as required to implement the features of the present disclosure. The system [100] components may be present at the same location or may be distributed at different locations. Also, a component of the system [100]
20 may comprise one or more sub-components which may be centralized or distributed
at various locations and may together be referred to as that particular component.
[0074] The system [100] for key performance indicator (KPI) calculation and
reporting comprises the transceiver unit [101]. The transceiver unit [101] is
25 configured to receive, via the user interface [102], at least one KPI formula
file/sheet containing one or more KPI definitions, wherein each KPI definition comprises a KPI name, a KPI formula, an aggregation type, and a threshold value. The KPI formula file/sheet may include details like:
30 KPI Name: The identifier for the KPI. For instance, "Packet Loss Rate."
22

KPI Formula: The mathematical equation that calculates the KPI. For example, "number of lost packets/total number of packets."
Aggregation Type: Defines how the KPI should be aggregated. Common types
include "average," "minimum," and "maximum."
5 Threshold Value: A predetermined value for the KPI that, if breached, triggers an
alert or alarm.
[0075] The transceiver unit [101] is further configured to validate the received KPI
formula file to ensure mathematical correctness of the KPI formula and absence of
10 duplicate KPI definition. The transceiver unit [101] is further configured to receive,
via the user interface [102], a report request specifying a time duration and desired KPIs.
[0076] Further, the assignment unit is communicatively coupled to the transceiver
15 unit [101]. The assignment unit [103] is configured to assign at least one KPI profile
to at least one worker node [104] for processing, wherein the at least one worker
node [104] is configured to determine/ calculate one or more KPI values for a
plurality of network elements associated with the at least one KPI profile. The KPI
profile is based on a criterion which may include but not limited to information such
20 as network type (e.g., 4G, 5G, Ethernet, etc.) and "circle combination," which refer
to a specific subset of the network infrastructure like a geographical region or a group of similar devices.
[0077] Furthermore, the retrieving unit [105] is communicatively coupled to the
25 assignment unit [103]. The retrieving unit [105] is configured to retrieve, via the at
least one worker node [104], counter data from a database [106] corresponding to
the one or more KPI definitions. The worker node [104], assigned the at least one
KPI profile by the assignment unit [103], facilitates in accessing the database [106]
to fetch the necessary counter data. Counter data corresponds to a range of metrics
30 collected from network elements that measure various aspects of network
23

performance and health. These metrics typically include data on traffic volume, error rates, utilization rates, session counts, latency measurements, and Quality of Service (QoS) metrics.
5 [0078] The determination unit [107] is communicatively coupled to the retrieving
unit [105]. The determination unit is configured to determine, in real-time, one or more KPI values for each network element of the plurality of network elements based on the retrieved counter data and the received at least one KPI formula file. When the at least one KPI profile is assigned to the at least one worker node [104],
10 the at least one worker node [104] may maintain a map (or index) of required
counters for each KPI in its memory cache. The counters data may include metrics like packet loss, bandwidth usage, response times, etc. These are the raw data points that will be used to calculate the KPIs. It is further noted that the database [106] is further configured to store the validated at least one KPI formula file.
15
[0079] For example, a telecommunications company monitors the performance of its 5G network. The company defines several KPIs, such as network latency, packet loss, and bandwidth utilization, uploading these formulas via the user interface. Once uploaded, worker nodes are assigned to specific network regions and start
20 retrieving performance data from the database in real-time. For example, if the
latency for a network segment exceeds the defined threshold, the system immediately calculates the KPI, detects the issue, and triggers an alarm to alert the network management team. The real-time calculation and instant alert enable the team to quickly identify and resolve issues, such as rerouting traffic to prevent
25 outages, thereby ensuring optimal network performance and customer satisfaction.
[0080] Next, the generation unit [108] is communicatively coupled to the
determination unit [107]. The generation unit [108] is configured to generate one
or more aggregated KPI results from the determined one or more KPI values. By
30 aggregating the KPI values, the generation unit [108] can provide summaries such
24

as minimum, maximum, and average values, or compile more complex statistical analyses depending on the configured aggregation types. For example, aggregated KPI results can highlight peak usage times, detect anomalies in traffic flow, or track the efficiency of network components over time. 5
[0081] The comparator unit [109] is communicatively coupled to the generation unit [108]. The comparator unit [109] is configured to compare the determined/ calculated one or more KPI values to the threshold value associated with the each KPI definition of the one or more KPI definitions. Each time the one or more KPI
10 values are determined by way of calculation, the one or more KPI values are
compared to the threshold value. If at least one determined KPI value of the one or more KPI values breaches corresponding threshold value i.e., if the at least determined KPI value does not meet or exceeds the threshold value, then an activation unit [111] is configured to activate an alarm sequence. This is done when
15 the at least one worker node [104] requests the activation unit [111] to raise the
alarm. The activation unit [111] may include but not limited a fault management [FM] system to raise the alarm. The at least one worker node [104] sends the details of the alarm (which signifies that the at least one determined KPI value of the one or more KPI values has breached the threshold value), along with the associated
20 alarm severity level, to the activation unit [111]. The activation unit [111] then
raises the alarm according to the severity indicated, thus notifying relevant parties to take necessary actions.
[0082] Thereafter, the generation unit [108] is further configured to generate a KPI
25 report, wherein the report comprises aggregated one or more KPI values for a
predefined time period. It is important to note that the users have the flexibility to request KPI report on a quarterly, hourly, or daily basis depending on their needs. The flexibility allows users to review KPI trends over different periods, enabling them to make informed decisions based on the network performance. It is further
25

important to note that a display unit [112] is configured to display, via the user interface [102], the generated KPI report.
[0083] Further, the system [100] comprises a distribution unit [110] which is
5 configured to distribute a task of KPI determination to a plurality of worker nodes,
wherein the at least one worker node [104] from the plurality of worker nodes, configured to determine the one or more KPI values for the plurality of network elements, and wherein in an event of a failure of at least one worker node [104] of the plurality of worker nodes, the KPI determination task of the failed at least one
10 worker node [104] is automatically reassigned to other available worker nodes from
the plurality of worker nodes. The distributed approach helps in balancing the load and enhancing the system's overall performance by leveraging multiple nodes to handle different segments of the network simultaneously. In the event of a failure of any worker node [104], the distribution unit [110] automatically reassigns the
15 KPI determination tasks of the failed node to other available worker nodes within
the plurality. This ensures that the KPI calculation process remains uninterrupted, maintaining the system's reliability and the accuracy of the network's performance monitoring. By redistributing tasks in real-time, the system minimizes downtime and maintains consistent oversight over network health, which is critical for
20 maintaining high service levels and operational efficiency.
[0084] FIG. 2 illustrates an exemplary method flow diagram indicating the method
[200] for key performance indicator (KPI) calculation and reporting, in accordance
with exemplary embodiments of the present disclosure. A method [200] for key
25 performance indicator (KPI) calculation and reporting begins at step [202] and
proceeds to step [204].
[0085] At step [204], the said method [200] comprises the steps of receiving, by a
transceiver unit [101] via a user interface [102], at least one KPI formula file
30 containing one or more KPI definitions, wherein each KPI definition of the one or
26

more KPI definitions comprises a KPI name, a KPI formula, an aggregation type,
and a threshold value. The KPI formula file/sheet may include details like:
KPI Name: The identifier for the KPI. For instance, "Packet Loss Rate."
KPI Formula: The mathematical equation that calculates the KPI. For example,
5 "number of lost packets/total number of packets."
Aggregation Type: Defines how the KPI should be aggregated. Common types include "average," "minimum," and "maximum."
Threshold Value: A predetermined value for the KPI that, if exceeded, triggers an alert or alarm.
10
[0086] Next at step [206], the method [200] comprises assigning, by an assignment unit [103], at least one KPI profile to at least one worker node [104] for processing, wherein the at least one worker node [104] is configured to determine one or more KPI values for a plurality of network elements associated with the at least one KPI
15 profile. The KPI profile is based on a criterion which may include but not limited
to information such as network type (e.g., 4G, 5G, Ethernet, etc.) and "circle combination," which refer to a specific subset of the network infrastructure like a geographical region or a group of similar devices.
20 [0087] Further at step [208], the method [200] encompasses retrieving, by a
retrieving unit [105], via the at least worker node [104], counter data from a database [106] corresponding to the one or more KPI definitions. The worker node [104], assigned the at least one KPI profile by the assignment unit [103], facilitates in accessing the database [106] to fetch the necessary counter data. Counter data
25 corresponds to a range of metrics collected from network elements that measure
various aspects of network performance and health. These metrics typically include data on traffic volume, error rates, utilization rates, session counts, latency measurements, and Quality of Service (QoS) metrics.
27

[0088] Furthermore, at step [210], the method [200] encompasses determining, by
a determination unit [107], in real-time, one or more KPI values for each network
element of the plurality of network elements based on the retrieved counter data
and the received at least one KPI formula file. When the at least one KPI profile is
5 assigned to the at least one worker node [104], the at least one worker node [104]
may maintain a map (or index) of required counters for each KPI in its memory
cache. The counters data may include metrics like packet loss, bandwidth usage,
response times, etc. These are the raw data points that will be used to calculate the
KPIs. It is further noted that the database [106] is further configured to store the
10 validated at least one KPI formula file.
[0089] Next at step [212], the method [200] comprises generating, by the
generation unit [108], one or more aggregated KPI results from the determined one
or more KPI values. By aggregating the KPI values, the generation unit [108] can
15 provide summaries such as minimum, maximum, and average values, or compile
more complex statistical analyses depending on the configured aggregation types. For example, aggregated KPI results can highlight peak usage times, detect anomalies in traffic flow, or track the efficiency of network components over time.
20 [0090] Now at step [214], the method [200] encompasses comparing, by a
comparator unit [109], the determined one or more KPI values to the threshold value associated with the each KPI definition of the one or more KPI definitions. Each time the one or more KPI values are determined by way of calculation, the one or more KPI values are compared to the threshold value. If at least one determined
25 KPI value of the one or more KPI values breaches corresponding threshold value
i.e., if the at least determined KPI value does not meet or exceeds the threshold value, then an activation unit [111] is configured to activate an alarm sequence. This is done when the at least one worker node [104] requests the activation unit [111] to raise the alarm. The activation unit [111] may include but not limited a
30 fault management [FM] system to raise the alarm. The at least one worker node
28

[104] sends the details of the alarm (which signifies that the at least one determined
KPI value of the one or more KPI values has breached the threshold value), along
with the associated alarm severity level, to the activation unit [111]. The activation
unit [111] then raises the alarm according to the severity indicated, thus notifying
5 relevant parties to take necessary actions.
[0091] Thereafter, at step [216], the method [200] comprises generating, by the generation unit [108], a KPI report, wherein the report comprises aggregated one or more KPI values for a predefined time period.
10
[0092] The method [200] also comprises displaying, by a display unit [112] via the user interface [102], the generated KPI report. It is important to note that the users have the flexibility to request KPI report on a quarterly, hourly, or daily basis depending on the requirement. The flexibility allows users to review KPI trends
15 over different periods, enabling them to make informed decisions based on the
network performance. It is further important to note that a display unit [112] is configured to display, via the user interface [102], the generated KPI report.
[0093] The method [200] terminates at step [218].
20
[0094] In an exemplary scenario, the method [200] can be implemented by the system [100] for key performance indicator (KPI) calculation and reporting. For example, a telecommunications company, company X, which manages a large-scale network spanning multiple cities (let's call them circles for this example). The
25 company wants to monitor the performance of its network in real-time and make
informed decisions based on this data. The network manager at Company X first defines several KPIs pertinent to their operations. These could include metrics like Packet Loss Rate, Bandwidth Utilization, call drop rates, and Latency. The KPIs are expressed as formulas using available counters on their network elements, such
30 as routers, switches, core nodes, and base stations. Once uploaded into the system,
29

it checks these formulas for mathematical correctness and any duplicates. This
ensures that the data that will be generated is accurate and reliable. The system then
starts calculating these KPIs in real-time, providing a continuous flow of
performance data to the network team at Company X. The system aggregates the
5 data into minimum, maximum, and average values for each KPI. This gives
Company X's network team a clear picture of the performance range and average performance of their network. Given the scale of Company X's network, the system distributes the calculation tasks across multiple worker nodes. This ensures efficiency and allows for scalability should Company X expand its network in the
10 future. Company X can also define specific KPI profiles for different types of
network or different circles. For example, they may want to monitor packet loss more closely in a high-traffic circle. They assign these profiles to the worker nodes accordingly. The system allows Company X's network team to generate specific reports, such as an hourly report of bandwidth utilization in a particular circle.
15 These reports can then be used to make informed decisions about resource
allocation or infrastructure investment. If Company X has defined a threshold for Packet Loss Rate, above which it could significantly impact service quality. If the Packet Loss Rate breaches this threshold, the system activates an alarm, allowing Company X to promptly identify and address the issue. In case a worker node fails
20 or goes offline, the system shifts the KPI calculation task to another available
worker node. This ensures that Company X's network performance monitoring continues uninterrupted, maintaining the reliability of the service. Through this system, Company X is able to proactively manage its network, swiftly address issues, and effectively plan for future growth and investment.
25
[0095] FIG.3 illustrates an exemplary a system architecture [300] for managing network performance indicators that includes key performance indicator (KPI) calculation and reporting, in accordance with exemplary embodiments of the present disclosure.
30
30

[0096] The system architecture [300] may be configured for managing and
monitoring network performance using Key Performance Indicators (KPIs). This
system provides a comprehensive solution for defining, calculating, and monitoring
network KPIs in real-time and includes various features to support robust, flexible,
5 and efficient network management through several specific steps:
[0097] Defining KPIs for a Network Element: Users can define any number of
KPIs for each Network Element. KPIs provide quantifiable measures of network
performance, facilitating data-driven decision-making. The user-defined KPIs can
10 be input via a KPI formula sheet uploaded through a user interface (UI). The system
supports the addition, deletion, or modification of KPI formulas in real-time.
[0098] KPI Formula Validation: Upon upload, the KPIM [304] validates each
KPI formula for mathematical correctness and checks for duplicate formulas. This
15 validation ensures the accuracy of the KPI calculations and prevents errors due to
duplicate or incorrect formulas.
[0099] Real-Time Calculation and Aggregation of KPI values: The KPIM
calculates KPI values in real-time, providing the most current performance data for
20 network elements. Additionally, it can generate aggregated KPI results, including
minimum, maximum, and average values, which can be visualized in quarterly, hourly, and daily KPI trends.
[0100] Distribution of KPI Calculation: The KPIM [304] distributes the
25 calculation of KPIs across multiple worker nodes. This feature enhances the
system's scalability and ensures that it can efficiently manage large-scale networks and significant increases in network data.
[0101] KPI Profile Management: Users can define KPI profiles that include
30 network type and circle combinations and assign these profiles to any worker node.
31

The assigned worker node then calculates the KPI values for the network elements in its assigned profile. Users can assign or unassign profiles in real-time.
[0102] KPI Reporting: Users can request reports for quarterly, hourly, and daily
5 KPIs over a given time duration. These reports can be generated for all KPIs or only
for specific KPIs and can cover a specific node type, circle, or a provided list of
network elements. The reporting process is distributed across worker nodes for
faster processing. Once complete, the reports are stored on an FTP path, and their
status is updated in the UI.
10
[0103] KPI Thresholds and Alarm Activation: Users can define threshold values
for each KPI. If a KPI value drops below the defined threshold, the KPIM [304]
activates an alarm sequence. Users can also define multiple thresholds with
associated alarm severities. If the KPI value doesn't meet the threshold, the worker
15 node requests the Fault Management (FM) system to raise an alarm, sending the
details of the alarm and its severity.
[0104] Failover Support: In case of a worker node failure, the KPIM [304]
automatically shifts the KPI calculation task to another available worker node,
20 ensuring continuous monitoring and calculation of KPIs.
[0105] As disclosed, Collector [310] is configured to collect Performance Measurement (PM) Data from the network elements. The PM Data is then either streamed [312] or directly passed on to the KPIM [304]. Users interact with the
25 system via the User Interface (UI) [302]. The user can define and upload KPI
formulas. The definitions include the KPI name, formula, aggregation type, and threshold values. After KPI formulas are uploaded, KPIM [304] validates these formulas for accuracy and checks for duplicates to ensure integrity in KPI calculations.
30
32

[0106] The validated KPI formulas are then stored in Database A [308], ensuring
that they are available for KPI calculation and reporting processes. KPIM [304]
uses these stored formulas to calculate KPIs in real-time as it retrieves PM Data
from the database B [316]. KPI Profiles are assigned via the UI [302], as part of the
5 KPI Profile Management comprises setting criterion based on network type and
circle combination. The profiles are assigned to worker node [104] for processing KPI values for associated network elements.
[0107] The real-time KPI values calculated by the KPIM [304] are then used to
10 generate aggregated results, such as minimum, maximum, and average values. The
generate aggregated results facilitates in visualizing KPI trends over different intervals such as quarterly, hourly, or daily. Upon completion, the reports are stored for retrieval, which can be done multiple times without recalculating, adding to the system's efficiency. 15
[0108] Moreover, the system features a robust alarm management process. When
KPIM [304] determines that a KPI value has dropped below the defined threshold,
it interacts with the Fault Management (FM) system [306] to raise an alarm, thus
facilitating quick response to potential network issues. Lastly, the system exhibits
20 fault tolerance through its failover support mechanism. If any worker node fails,
KPIM [304] automatically reassigns the KPI calculation tasks to another available worker node, ensuring continuous network monitoring and performance management, reflecting the system's scalability and reliability features.
25 [0109] Referring to FIG. 4 an exemplary process [400] indicating managing
network performance indicators, in accordance with exemplary embodiments of the present disclosure is shown. In an implementation the method [200] is performed by the server.
33

[0110] Following is the step-by-step procedure for defining KPI, live KPI calculation, KPI aggregated reports and raise alarms based on KPI threshold values:
[0111] KPI Upload and Validation Flow: A user, typically a network manager or
5 analyst, can upload a Key Performance Indicator (KPI) formula sheet through the
system's User Interface (UI). This sheet usually includes critical details like:
• KPI Name
• KPI Formula
• Aggregation Type 10 • Threshold Value
[0112] Once the KPI formula sheet is uploaded, the Key Performance Indicator
Management (KPIM) [304] system processes it. The system validates the
mathematical correctness of each KPI formula. This validation can check for syntax
15 errors, division by zero issues, and other potential mathematical problems that could
prevent the formula from being calculated accurately. The system checks to see if any of the uploaded KPIs are duplicates of ones that already exist in the database. This helps avoid redundancies and potential confusion.
20 [0113] Once the system validates all KPI formulas for mathematical correctness
and absence of duplicates, it stores them in the system's database. This provides a persistent, reliable record of KPIs that can be accessed and used for calculations as needed.
25 [0114] KPI Profile Management Flow: The user can use the UI to manage the
KPI formulas.
• This can involve:
o Adding New KPI Formulas: If the user needs to track a new metric, they can define a new KPI formula.
34

o Deleting Existing KPI Formulas: If a KPI is no longer relevant, the user can remove its formula from the system.
o Modifying Current KPI Formulas: If the way a KPI is calculated
needs to change (e.g., the inclusion of a new factor in the formula),
5 the user can modify the existing KPI formula.
[0115] Users can define KPI profiles that specify the context in which certain KPIs are to be calculated. A KPI profile might contain information such as network type (e.g., 4G, 5G, Ethernet, etc.) and "circle combination," which could refer to a
10 specific subset of the network infrastructure like a geographical region or a group
of similar devices. This enables a more granular approach in measuring network performance, allowing users to track KPIs within specific parts of the network. Once KPI profiles have been defined, the user can assign these profiles to specific worker nodes. These worker nodes are then responsible for calculating the KPI
15 values for the Network Elements associated with the given profile. For instance, if
a user defined a profile for a specific geographical region within a 5G network, the assigned worker node would calculate KPI values for the network devices in that region only. This allows for distributed processing, where the computational load of calculating KPIs is spread across multiple worker nodes, thereby increasing the
20 efficiency and scalability of the system.
[0116] The system offers the flexibility for users to assign or unassign KPI profiles
to worker nodes at runtime. This means that changes can be made while the system
is still operational, without requiring a full system shutdown or restart. For example,
25 if a worker node becomes overloaded, or if a new node is added to the system, the
user can easily redistribute the KPI profiles to balance the load or utilize the new resources. Similarly, if a specific KPI profile is no longer needed, the user can unassign it from its worker node, freeing up that node's resources for other tasks.
35

[0117] KPI Calculation Flow: When a KPI profile is assigned to a worker node,
the node will maintain a map (or index) of required counters for each KPI in its
memory cache. These counters may include metrics like packet loss, bandwidth
usage, response times, etc. These are the raw data points that will be used to
5 calculate the KPIs. At a certain interval, which we call a counter reset interval,
Performance Monitoring (PM) data is stored in the database. Once this happens, the
worker node fetches all of the required counter data that is necessary for the KPI
calculations. The counter reset interval could be set to a specific timeframe (e.g.,
every hour, every day), or it might be triggered by certain events (e.g., when the
10 counters reach a certain value).
[0118] Once the worker node has fetched the necessary PM data, it will calculate the KPIs for each Network Element (NE). A Network Element might be a device (e.g., a router, a switch, a server) or a connection line. Each NE's KPIs are calculated
15 individually to provide detailed insights into the performance of different parts of
the network. After the KPI for a Network Element has been calculated, the KPI data is added to a queue to be stored in the database. This queueing mechanism helps manage the flow of data to the database and can prevent the database from being overwhelmed by a large influx of data all at once. The KPI data is flushed from the
20 queue to the database for permanent storage. The interval at which this flushing
happens, as well as the batch size (the number of data points that are flushed at once), are configurable. This allows the system to be optimized based on the database's capacity and the network's performance requirements.
25 [0119] KPI Reports Flow: Users have the flexibility to request KPI reports on a
quarterly, hourly, or daily basis depending on their needs. This flexibility allows users to review KPI trends over different periods, enabling them to make informed decisions based on the network performance. The user can specify the parameters of the report. They can request a report for a specific type of node (a particular type
30 of network element), a particular 'circle' (which might represent a geographic area,
36

a department, or some other grouping of network elements), or a specified list of
network elements. This allows for a granular analysis of different sections of the
network. The report can contain all defined KPIs or only specific ones. This way,
users can focus on the KPIs that are most relevant to their current needs. Once a
5 report request is received by a KPIM [304], the processing begins. The user is
notified that the report generation has been initiated, keeping them informed about the progress of their request.
[0120] To expedite the generation of reports, especially when multiple report
10 requests are made, the tasks are distributed among available worker nodes for
parallel processing. This ensures that the system can handle multiple requests
simultaneously, leading to faster response times. When the report is completed, it
is moved (or 'dumped') to a File Transfer Protocol (FTP) location, where it can be
accessed by the user. The status of the report is updated in the user interface to
15 'completed', letting the user know that their report is ready. Users can download a
completed report multiple times without the need for the report to be recalculated each time. This is beneficial because it saves computational resources, and also allows users to access their reports quickly, whenever they need them.
20 [0121] KPI Raise Alarm Flow: Users have the ability to define a threshold value
for each KPI either at the time of its upload or later, as needed. The threshold is a value at which the user wants to be notified if the KPI crosses it. This helps in keeping the performance of the network in check and triggers proactive responses. The system allows the user to define multiple threshold values for each KPI, along
25 with corresponding levels of alarm severity if those thresholds are breached. This
enables the creation of a tiered warning system, where different actions might be taken based on the severity of the breach. Each time a KPI value is calculated, it is compared to the predefined threshold values. If a calculated KPI value does not meet or exceeds a specific threshold, the worker node requests the Fault
30 Management (FM) system to raise an alarm. This ensures that deviations in network
37

performance are promptly identified. The worker node in the KPIM [304] sends the
details of the alarm (which includes the KPI that has breached its threshold and the
current value of the KPI), along with the associated alarm severity level, to the FM
system. The FM system then raises the alarm according to the severity indicated,
5 thus notifying relevant parties to take necessary actions.
[0122] At step 402, the process initiates with the collection of Performance
Measurement (PM) data from network elements. Once collected, the PM data is
inserted into a database (DB), ensuring that the information is stored and made
10 accessible for subsequent KPI calculations and assessments.
[0123] Next, at step 404, the user uploads a KPI Formulas Sheet through the system's User Interface (UI). This sheet is then subjected to a validation process at step 406 to ensure the accuracy and appropriateness of the KPI formulas. 15
[0124] Following successful validation, the KPI Formulas are stored in the DB at step 408, which serves as a repository for these crucial components of the KPI calculation framework.
20 [0125] Simultaneously, at step 410, a KPI profile is created by the user, specifying
the node type and the network circle, which allows for customized and targeted monitoring of network segments.
[0126] The KPI profile is then assigned to a worker node at step 412, responsible
25 for the computation of the KPI values pertinent to the profile's parameters.
[0127] At this step 414, the system loads the necessary Key Performance Indicator (KPI) formulas into the cache memory of the worker node. The formulas are essential for calculating the KPIs for various network elements. 30
38

[0128] At step 416, the worker node loads a mapping of KPIs to the required
counter names into the worker node’s cache. This map details which counters (data
points like packet loss, bandwidth usage, etc.) are needed for each KPI formula.
Having this map in cache helps streamline the subsequent data retrieval and
5 calculation processes by aligning the required data inputs with the corresponding
KPIs.
[0129] At step 418, the worker nodes actively collect the counter data specified by the KPI formulas from the network elements.
10
[0130] At step 420, the collected Performance Monitoring (PM) data is stored in the database. Storing this data ensures that it is available for both real-time and historical KPI analysis, providing a comprehensive view of network performance over time.
15
[0131] Step 422 step involves the collection of specific counter data that pertains to the KPI formulas stored in the worker node's cache. The targeted data collection focuses on gathering only the relevant metrics needed for the predefined KPI calculations.
20
[0132] At step 424, using the collected counter data and the KPI formulas loaded earlier, the worker node calculates the KPI values for each network element. The calculation is performed in real-time to provide up-to-date information on network performance.
25
[0133] At step 426, once the KPI values are calculated, the system checks these values against predefined thresholds for identifying any potential issues or performance degradations in the network.
39

[0134] At step 428, if any KPI value breaches its threshold, the system initiates an alarm for alerting network managers and other relevant stakeholders to take necessary corrective actions to address the performance issue.
5 [0135] At step 430, the newly determined KPI values are inserted into the database.
This step ensures that the latest performance data is recorded and can be accessed for future reference, reporting, and analysis.
[0136] Thereafter, the process terminates at step 432.
10
[0137] FIG. 5 illustrates an exemplary block diagram of a computing device [500] (also referred to herein as a computer system [500]) upon which an embodiment of the present disclosure may be implemented. In an implementation, the computing device [500] implements the method for key performance indicator (KPI)
15 calculation and reporting, said system by utilising the system [100]. In another
implementation, the computing device [500] itself implements the method [200] for key performance indicator (KPI) calculation and reporting, said system using one or more units configured within the computing device [500], wherein said one or more units are capable of implementing the features as disclosed in the present
20 disclosure.
[0138] The computing device [500] may include a bus [502] or other communication mechanism for communicating information, and a processor [504] coupled with bus [502] for processing information. The processor [504] may be, for
25 example, a general purpose microprocessor. The computing device [500] may also
include a main memory [506], such as a random access memory (RAM), or other dynamic storage device, coupled to the bus [502] for storing information and instructions to be executed by the processor [504]. The main memory [506] also may be used for storing temporary variables or other intermediate information
30 during execution of the instructions to be executed by the processor [504]. Such
40

instructions, when stored in non-transitory storage media accessible to the processor
[504], render the computing device [500] into a special-purpose machine that is
customized to perform the operations specified in the instructions. The computing
device [500] further includes a read only memory (ROM) [508] or other static
5 storage device coupled to the bus [502] for storing static information and
instructions for the processor [504].
[0139] A storage device [510], such as a magnetic disk, optical disk, or solid-state drive is provided and coupled to the bus [502] for storing information and
10 instructions. The computing device [500] may be coupled via the bus [502] to a
display [512], such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for displaying information to a computer user. An input device [514], including alphanumeric and other keys, touch screen input means, etc. may be coupled to the
15 bus [502] for communicating information and command selections to the processor
[504]. Another type of user input device may be a cursor controller [516], such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor [504], and for controlling cursor movement on the display [512]. This input device typically has two degrees
20 of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow
the device to specify positions in a plane.
[0140] The computing device [500] may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware
25 and/or program logic which in combination with the computing device [500] causes
or programs the computing device [500] to be a special-purpose machine. According to one embodiment, the techniques herein are performed by the computing device [500] in response to the processor [504] executing one or more sequences of one or more instructions contained in the main memory [506]. Such
30 instructions may be read into the main memory [506] from another storage medium,
41

such as the storage device [510]. Execution of the sequences of instructions contained in the main memory [506] causes the processor [504] to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions. 5
[0141] The computing device [500] also may include a communication interface [518] coupled to the bus [502]. The communication interface [518] provides a two-way data communication coupling to a network link [520] that is connected to a local network [522]. For example, the communication interface [518] may be an
10 integrated services digital network (ISDN) card, cable modem, satellite modem, or
a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface [518] may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such
15 implementation, the communication interface [518] sends and receives electrical,
electromagnetic or optical signals that carry digital data streams representing various types of information.
[0142] The computing device [500] can send messages and receive data, including
20 program code, through the network(s), the network link [520] and the
communication interface 518. In the Internet example, a server [530] might transmit
a requested code for an application program through the Internet [528], the ISP
[526], the local network [522], host [524] and the communication interface [518].
The received code may be executed by the processor [504] as it is received, and/or
25 stored in the storage device [510], or other non-volatile storage for later execution.
[0143] Another aspect of the present disclosure provides a user equipment (UE) for
key performance indicator (KPI) calculation and reporting, the UE comprises: a
processor configured to: receive, via a user interface [102], at least one KPI formula
30 file containing one or more KPI definitions, wherein each KPI definition of the one
42

or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type,
and a threshold value; assign at least one KPI profile to at least one worker node
[104] for processing, wherein the at least one worker node [104] is configured to
determine one or more KPI values for a plurality of network elements associated
5 with the at least one KPI profile, wherein the key performance indicator (KPI)
calculation and reporting is performed based on: retrieving, by a retrieving unit [105], via the at least worker node [104], counter data from a database [106] corresponding to the one or more KPI definitions; determining, by a determination unit [107], in real-time , one or more KPI values for each network element of the
10 plurality of network elements based on the retrieved counter data and the received
at least one KPI formula file; generating, by a generation unit [108], one or more aggregated KPI results from the determined one or more KPI values; comparing, by a comparator unit [109], the determined one or more KPI values to the threshold value associated with the each KPI definition of the one or more KPI definitions;
15 and generating, by the generation unit [108], a KPI report, wherein the report
comprises aggregated one or more KPI values for a predefined time period.
[0144] Yet another aspect of the present disclosure relates to a non-transitory computer readable storage medium, storing instructions for key performance
20 indicator (KPI) calculation and reporting. The instructions when executed by one
or more units of a system [100] configured for key performance indicator (KPI) calculation and reporting, cause a transceiver unit [101], via a user interface [102], to receive at least one KPI formula file containing one or more KPI definitions and wherein each KPI definition of the one or more KPI definitions comprises a KPI
25 name, a KPI formula, an aggregation type, and a threshold value. The instructions
upon receipt further cause an assignment unit [103] to assign at least one KPI profile to at least one worker node [104] for processing, wherein the at least one worker node [104] is configured to determine one or more KPI values for a plurality of network elements associated with the at least one KPI profile. The instructions upon
30 assignment further cause a retrieving unit [105], via the at least worker node [104],
43

to retrieve counter data from a database [106] corresponding to the one or more KPI
definitions. The instructions upon retrieval further cause a determination unit [107],
to determine, in real-time, one or more KPI values for each network element of the
plurality of network elements based on the retrieved counter data and the received
5 at least one KPI formula file. The instructions upon determination further cause a
generation unit [108], to generate one or more aggregated KPI results from the
determined one or more KPI values. The instructions upon generation further cause
a comparator unit [109] to compare the determined one or more KPI values to the
threshold value associated with the each KPI definition of the one or more KPI
10 definitions. And finally, the instructions upon comparison further cause the
generator unit [108] to generate a KPI report, and wherein the report comprises aggregated one or more KPI values for a predefined time period.
[0145] As is evident from the above, the present disclosure provides a technically
15 advanced solution for monitoring and managing network performance through a
robust system that enables the dynamic definition, calculation, and reporting of Key Performance Indicators (KPIs) for 4G-5G networks. The system allows for real¬time monitoring and dynamic adjustment of network elements, ensuring high levels of network performance and responsiveness to issues as they arise. The invention
20 leverages a combination of front-end configurability and back-end processing
power to offer a scalable and flexible approach to network management. Network managers can define custom KPIs, configure aggregation settings, and set thresholds for performance alerts directly from the user interface, making the system highly adaptable to various operational needs. The system's ability to
25 distribute KPI calculation tasks across multiple worker nodes enhances its
scalability and reliability, particularly through features like automatic task reallocation in the event of node failures. Furthermore, the system's capability to generate timely and detailed reports on KPI trends helps network administrators make informed decisions based on comprehensive data analysis. By integrating
30 alarm mechanisms that trigger alerts when performance thresholds are breached,
44

the system ensures that potential issues are promptly addressed, thereby maintaining service quality and preventing network outages or degradations.
[0146] Further, in accordance with the present disclosure, it is to be acknowledged
5 that the functionality described for the various components/units can be
implemented interchangeably. While specific embodiments may disclose a
particular functionality of these units for clarity, it is recognized that various
configurations and combinations thereof are within the scope of the disclosure. The
functionality of specific units, as disclosed in the disclosure, should not be
10 construed as limiting the scope of the present disclosure. Consequently, alternative
arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.
15 [0147] While considerable emphasis has been placed herein on the disclosed
embodiments, it will be appreciated that many embodiments can be made and that many changes can be made to the embodiments without departing from the principles of the present disclosure. These and other changes in the embodiments of the present disclosure will be apparent to those skilled in the art, whereby it is to
20 be understood that the foregoing descriptive matter to be implemented is illustrative
and non-limiting.
45

I/We Claim:
1. A method [200] for key performance indicator (KPI) calculation and
reporting, said method [200] comprising the steps of:
receiving, by a transceiver unit [101] via a user interface [102], at least one KPI formula file containing one or more KPI definitions, wherein each KPI definition of the one or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type, and a threshold value;
assigning, by an assignment unit [103], at least one KPI profile to at least one worker node [104] for processing, wherein the at least one worker node [104] is configured to determine one or more KPI values for a plurality of network elements associated with the at least one KPI profile;
retrieving, by a retrieving unit [105], via the at least worker node [104], counter data from a database [106] corresponding to the one or more KPI definitions;
determining, by a determination unit [107], one or more KPI values for each network element of the plurality of network elements based on the retrieved counter data and the received at least one KPI formula file;
generating, by a generation unit [108], one or more aggregated KPI results from the determined one or more KPI values;
comparing, by a comparator unit [109], the determined one or more KPI values to the threshold value associated with the each KPI definition of the one or more KPI definitions; and
generating, by a generation unit [108], a KPI report, wherein the report comprises aggregated one or more KPI values for a predefined time period.
2. The method [200] as claimed in claim 1, wherein the method [200] further
comprises:
distributing, by a distribution unit [110], a task of KPI determination to a plurality of worker nodes, wherein the at least one worker node [104] from

the plurality of worker nodes, configured to determine the one or more KPI values for the plurality of network elements, and
wherein in an event of a failure of at least one worker node [104] of the plurality of worker nodes, the KPI determination task of the failed at least one worker node [104] is automatically reassigned to other available worker nodes from the plurality of worker nodes.
3. The method [200] as claimed in claim 1, wherein the aggregated KPI results comprise at least a minimum value, a maximum value, and an average value.
4. The method [200] as claimed in claim 1, wherein the method [200] comprises defining, by the at least one worker node [104], the at least one KPI profile based on a criterion, wherein the criterion comprises network type and circle combination.
5. The method [200] as claimed in claim 1, wherein the method [200] comprises validating, by the transceiver unit [101], the received at least one KPI formula file to ensure mathematical correctness of the KPI formula and absence of duplicate KPI definition.
6. The method [200] as claimed in claim 5, wherein the method [200] comprises storing, by the database [106], the validated at least one KPI formula file.
7. The method [200] as claimed in claim 1, wherein the method [200] comprises receiving, by the transceiver unit [101] via the user interface [102], a report request specifying a time duration and desired KPIs.
8. The method [200] as claimed in claim 1, wherein the method [200] comprises activating, by an activation unit [111], an alarm sequence if at least one

determined KPI value of the one or more KPI values breaches corresponding threshold value.
9. The method [200] as claimed in claim 1, wherein the method [200] comprises displaying, by a display unit [112] via the user interface [102], the generated KPI report.
10. A system [100] for key performance indicator (KPI) calculation and reporting, said system [100] comprising:
a transceiver unit [101] configured to receive, via a user interface [102], at least one KPI formula file containing one or more KPI definitions, wherein each KPI definition of the one or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type, and a threshold value;
an assignment unit [103] connected to at least the transceiver unit [101], the assignment unit [103] configured to assign at least one KPI profile to at least one worker node [104] for processing, wherein the at least one worker node [104] is configured to determine one or more KPI values for a plurality of network elements associated with the at least one KPI profile;
a retrieving unit [105] connected to at least the assignment unit [103], the retrieving unit [105] configured to retrieve, via the at least one worker node [104], counter data from a database [106] corresponding to the one or more KPI definitions;
a determination unit [107] connected to at least the retrieving unit [105], the determination unit [107] configured to determine, one or more KPI values for each network element of the plurality of network elements based on the retrieved counter data and the received at least one KPI formula file;
a generation unit [108] connected to at least the determination unit [107], the generation unit [108] configured to generate one or more aggregated KPI results from the determined one or more KPI values;

a comparator unit [109] connected to at least the generation unit [108], the comparator unit [109] configured to compare the determined one or more KPI values to the threshold value associated with the each KPI definition of the one or more KPI definitions; and
the generation unit [108] is further configured to generate a KPI report, wherein the report comprises aggregated one or more KPI values for a predefined time period.
11. The system [100] as claimed in claim 10, wherein the system [100] further
comprises:
a distribution unit [110] configured to distribute a task of KPI determination to a plurality of worker nodes, wherein the at least one worker node [104] from the plurality of worker nodes, configured to determine the one or more KPI values for the plurality of network elements, and
wherein in an event of a failure of at least one worker node [104] of the plurality of worker nodes, the KPI determination task of the failed at least one worker node [104] is automatically reassigned to other available worker nodes from the plurality of worker nodes.
12. The system [100] as claimed in claim 10, wherein the aggregated KPI results comprise at least a minimum value, a maximum value, and an average value.
13. The system [100] as claimed in claim 10, wherein the at least one worker node [104] is further configured to define the at least one KPI profile based on a criterion, wherein the criterion comprises at least one of network type and circle combination.
14. The system [100] as claimed in claim 10, wherein the transceiver unit [101] is further configured to validate the received at least one KPI formula file to

ensure mathematical correctness of the KPI formula and absence of duplicate KPI definition.
15. The system [100] as claimed in claim 14, wherein the database [106] is further configured to store the validated at least one KPI formula file.
16. The system [100] as claimed in claim 10, wherein the transceiver unit [101] is further configured to receive, via the user interface [102], a report request specifying a time duration and desired KPIs.
17. The system [100] as claimed in claim 10, wherein an activation unit [111] is configured to activate an alarm sequence if at least one determined KPI value of the one or more KPI values breaches corresponding threshold value.
18. The system [100] as claimed in claim 10, wherein a display unit [112] is configured to display, via the user interface [102], the generated KPI report.
19. A user equipment (UE) for key performance indicator (KPI) calculation and reporting, the UE comprises:
a processor configured to:
receive, via a user interface [102], at least one KPI formula file containing one or more KPI definitions, wherein each KPI definition of the one or more KPI definitions comprises a KPI name, a KPI formula, an aggregation type, and a threshold value;
assign at least one KPI profile to at least one worker node [104] for processing, wherein the at least one worker node [104] is configured to determine one or more KPI values for a plurality of network elements associated with the at least one KPI profile, wherein
the key performance indicator (KPI) calculation and reporting is performed based on:

retrieving, by a retrieving unit [105], via the at least worker node [104], counter data from a database [106] corresponding to the one or more KPI definitions;
determining, by a determination unit [107], in real-time , one or more KPI values for each network element of the plurality of network elements based on the retrieved counter data and the received at least one KPI formula file;
generating, by a generation unit [108], one or more aggregated KPI results from the determined one or more KPI values;
comparing, by a comparator unit [109], the determined one or more KPI values to the threshold value associated with the each KPI definition of the one or more KPI definitions; and
generating, by the generation unit [108], a KPI report, wherein the report comprises aggregated one or more KPI values for a predefined time period.