FORM 2
THE PATENTS ACT, 1970 (39 of 1970) THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(See section 10; rule 13)
TITLE OF THE INVENTION
SYSTEM AND METHOD FOR DEFINING KPI METRICS FOR WIRELESS NETWORK
APPLICANT
JIO PLATFORMS LIMITED
of Office-101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad -
380006, Gujarat, India; Nationality : India
The following specification particularly describes
the invention and the manner in which
it is to be performed

RESERVATION OF RIGHTS
[0001] A portion of the disclosure of this patent document contains material
which is subject to intellectual property rights such as, but are not limited to, copyright, design, trademark, integrated circuit (IC) layout design, and/or trade 5 dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (herein after referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner. 10
TECHNICAL FIELD
[0002] The present disclosure relates to a field of network coverage
platforms, and specifically to a system and a method for defining Key Performance Indicator (KPI) metrics through a front-end mechanism for a wireless network, for 15 example, a Fifth Generation/Sixth Generation (5G/6G) network.
BACKGROUND
[0003] The following description of related art is intended to provide
background information pertaining to the field of the disclosure. This section may 20 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.
[0004] In general, Key Performance Indicator (KPI) metrics are used to
25 measure performance or progress of a wireless network. Continuous tracking of the KPI metrics may not only help in assessing the quality of the network but also the network utilization. The KPI metrics may be derived by defining a formula with one or more counters along with some mathematical operations.
2

[0005] Conventional methods may measure the performance or the progress
of the network, but do not view the counters of interest of each category and define the KPI metrics formula to create, modify, and delete the KPIs.
[0006] There is, therefore, a need in the art to improve state of creating,
5 modifying, and deleting the KPIs by overcoming the deficiencies of the prior arts.
OBJECTS OF THE PRESENT DISCLOSURE
[0007] It is an object of the present disclosure to define Key Performance
Indicator (KPI) metrics through a front-end mechanism for a 5G/6G network.
10 [0008] It is an object of the present disclosure to provide a KPI editor
interface to continuously track the KPI metrics for the 5G/6G network to assess quality of the network and the network utilization.
[0009] It is an object of the present disclosure to fetch and aggregate
Performance Management (PM) counter data from one or more servers of one or 15 more geography, periodically, for a pre-configured period (for example, every 15 minutes).
[0010] It is an object of the present disclosure to populate PM counters for
user-selected filters of one or multiple of family, category, domain, vendor, etc.
[0011] It is an object of the present disclosure to define KPI formula, for
20 one or more PM counters, with pre-aggregating and computing of corresponding KPI values at node level and time level.
[0012] It is an object of the present disclosure to provide a user-friendly
Graphical User Interface (GUI) for users to view counters of interest of each category and also define the KPI metrics formula to create, modify, and delete the 25 KPIs efficiently.
[0013] It is an object of the present disclosure to pull PM counter data from
different sources for a configurable regular time-period (for example, 15 minutes)
3

and using a distributed file system to compute/prepare data to be fetched using microservices.
[0014] It is an object of the present disclosure to aggregate counter data
based on user selected node and time level using microservices. 5
SUMMARY OF THE PRESENT DISCLOSURE
[0015] The present disclosure discloses a system for defining Key
Performance Indicators (KPIs) metrics for a wireless network. The system comprises a processor and a performance management (PM) module coupled to the
10 processor. The PM module is configured to obtain a user-defined KPI formula. The KPI formula includes one or more PM counters pertaining to one or more networks. Based on the KPI formula, the PM module is configured to fetch PM counter data from a plurality of servers. The PM counter data is fetched for a plurality of geographical locations. Upon fetching the PM counter data, the PM module is
15 configured to populate the one or more PM counters with the PM counter data. The PM module is further configured to aggregate, using a microservice, the PM counter data based on user-selected node and time level to compute the KPIs. In addition, the PM module is configured to compose a unified PM counter data depicting the KPIs corresponding to the one or more networks.
20 [0016] In an embodiment, to obtain the user-defined KPI formula, the PM
module is configured to receive user input with respect to a plurality of fields associated with the one or more networks and receive an indication of a type of aggregation for each of the PM counters in time and space domain.
[0017] In an embodiment, to fetch the PM counter data, the PM module is
25 configured to fetch the PM counter data of each of the one or more PM counters from the servers. In addition, the PM module is configured to combine the PM counter data, in the CSV format, pertaining to a particular PM counter and fetched from different servers, to provide combined data in a single view.
4

[0018] In an embodiment, the PM module is further configured to store the
computed KPIs at different frequency and hierarchical levels.
[0019] In an embodiment, the PM module is further configured to fetch the
PM counter data using microservices through a distributed file system.
5 [0020] In an embodiment, the pre-configured period to fetch the PM counter
data is 15 minutes.
[0021] The present disclosure also discloses a method for defining Key
Performance Indicators (KPIs) metrics for a wireless network. The method includes obtaining a user-defined KPI formula. The KPI formula includes one or more PM
10 counters pertaining to one or more networks. The method further includes based on the KPI formula, fetching PM counter data from servers. The PM counter data is fetched for a plurality of geographical locations. In addition, the method includes upon fetching the PM counter data, populating the one or more PM counters with the PM counter data. The method further includes aggregating, using a
15 microservice, the PM counter data based on user-selected node and time level to compute the KPIs. In addition, the method includes composing a unified PM counter data depicting the KPIs corresponding to the one or more networks.
[0022] In an embodiment, obtaining the user-defined KPI formula
comprises receiving user input with respect to a plurality of fields associated with 20 the one or more networks and receiving an indication of a type of aggregation for each of the PM counters in time and space domain.
[0023] In an embodiment, fetching the PM counter data comprises fetching
the PM counter data of each of the one or more PM counters from the servers. In addition, fetching the PM counter data includes combining the PM counter data, 25 pertaining to a particular PM counter and fetched from different servers, to provide combined data in a single view.
[0024] In an embodiment, the method further comprises storing the
computed KPIs at different frequency and hierarchical levels.
5

[0025] In an embodiment, fetching the PM counter data comprises fetching
the PM counter data using microservices through a distributed file system.
[0026] The present disclosure discloses a computer program product
comprising a non-transitory computer-readable medium comprising instructions 5 that, when executed by one or more processors, cause the one or more processors to obtain a user-defined KPI formula. The KPI formula includes one or more PM counters pertaining to one or more networks. In addition, the instructions cause the one or more processors to, fetch PM counter data from a plurality of servers based on the KPI formula. The PM counter data is fetched for a plurality of geographical
10 locations. The instructions further cause the one or more processors to, upon fetching the PM counter data, populate the one or more PM counters with the PM counter data. In addition, the instructions cause the one or more processors to aggregate using a microservice, the PM counter data based on user-selected node and time level to compute the KPIs. The instructions also cause the one or more
15 processors to compose a unified PM counter data depicting the KPIs corresponding to the one or more networks.
BRIEF DESCRIPTION OF THE DRAWINGS
[0027] In the figures, similar components and/or features may have the
20 same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
25 [0028] The diagrams are for illustration only, which thus is not a limitation
of the present disclosure, and wherein:
[0029] FIG. 1 illustrates an exemplary network architecture (100) in which
or with which embodiments of the present disclosure may be implemented.
6

[0030] FIG. 2 illustrates an exemplary architecture (200) of a Key
Performance Indicator (KPI) metrics definition system, in accordance with an embodiment of the present disclosure.
[0031] FIG. 3 illustrates an exemplary block diagram (300) of a
5 Performance Management (PM) data flow mechanism, in accordance with an embodiment of the present disclosure.
[0032] FIG. 4 illustrates an exemplary flow diagram (400) of KPI editor
design flow mechanism, in accordance with an embodiment of the present disclosure.
10 [0033] FIG. 5 illustrates an exemplary flow diagram (500) of KPI formula
creation, in accordance with an embodiment of the present disclosure.
[0034] FIG. 6 illustrates an exemplary flow diagram (600) of end-to-end
KPI computation, in accordance with an embodiment of the present disclosure.
[0035] FIG. 7 illustrates an exemplary representation (700) of node and time
15 aggregation, in accordance with an embodiment of the present disclosure.
[0036] FIG. 8A illustrates an exemplary schematic diagram (800A) of KPI
editor User Interface (UI), in accordance with an embodiment of the present disclosure.
[0037] FIG. 8B illustrates an exemplary schematic diagram (800B) of new
20 KPI creation, in accordance with an embodiment of the present disclosure.
[0038] FIG. 8C illustrates an exemplary schematic diagram (800C) of KPI
creation for wireless fidelity (WIFI) domain, in accordance with an embodiment of the present disclosure.
[0039] FIG. 8D illustrates an exemplary schematic diagram (800D) of
25 selection of counters for KPI definition, in accordance with an embodiment of the present disclosure.
7

[0040] FIG. 8E illustrates an exemplary schematic diagram (800E) of
defining, validating and saving the formula to create the KPI, in accordance with an embodiment of the present disclosure.
[0041] FIG. 9 illustrates an exemplary computer system (900) in which or
5 with which embodiments of the present disclosure may be implemented.
[0042] FIG. 10 illustrates an exemplary flow diagram (1000) of a method
for defining Key Performance Indicators (KPIs) metrics for a wireless network, in accordance with an embodiment of the present disclosure.
10 LIST OF REFERENCE NUMERALS
100 – Network architecture
102-1, 102-2…102-N – Users
104-1, 104-2…104-N – User Equipments
106 – Network 15 108– System
200- Architecture
202 – Performance Management (PM) module
204 – Mediation module
206 – Computation module 20 208 – Presentation module
210 – Prediction module
212 – Database
300- Block Diagram
310 – KPI Editor 25 320 – Edge Node Servers
400- Flow Diagram
402 – Application Server
404 – Micro service
406 – Database 30 500 – Flow Diagram
8

600 – Flow Diagram
602 – EMS Server
604 – Edge Node
606 – Hadoop Distributed File System (HDFS) 5 608 – Spark System
610 – HBase table
612 – Database
614 – Microservices
700 – Schematic Diagram 10 800A – Schematic Diagram
800B – Schematic Diagram
800C – Schematic Diagram
800D – Schematic Diagram
800E – Schematic Diagram 15 900- Computer system
910 – External Storage Device
920 – Bus
930 – Main Memory
940 – Read Only Memory 20 950 – Mass Storage Device
960 – Communication Port
970 – Processor
1000 – Flowchart
25 DETAILED DESCRIPTION
[0043] The following is a detailed description of embodiments of the
disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the 30 contrary, the intention is to cover all modifications, equivalents, and alternatives
9

falling within the spirit and scope of the present disclosure as defined by the appended claims.
[0044] Generally, Key Performance Indicator (KPI) metrics may be used to
measure performance or progress of a wireless network. Continuous tracking of the 5 KPI metrics may help in assessing the quality of the network and also the network utilization. The KPI metrics may be derived by defining a formula with one or more counters along with some mathematical operations.
[0045] The proposed disclosure provides a Graphical User Interface (GUI)
for users to view the counters of interest of each category and also define the KPI 10 metrics formula to create, modify, and delete the KPIs. This interface may be referred as a KPI editor. The KPI editor interface may be used for continuous KPI tracking for assessing the network quality and the network utilization.
[0046] The proposed disclosure pulls Performance Management (PM)
counter data from different sources for a configurable regular time-period (for
15 example, 15 minutes, 1 hour, 6 hours, etc.) and compute/prepares data to be fetched using microservices using a distributed file system. In examples, the preconfigured period may be need-based or random. The proposed disclosure uses microservices to create, store, and retrieve the KPIs efficiently. The proposed disclosure populates PM counters for user-selected filters of one or multiple of family, category, domain,
20 vendor, etc. The proposed disclosure defines KPI formula for one or more PM counters with pre-aggregating and computing of corresponding KPI values at node level and time level. Further, the proposed disclosure provides the GUI to select, create, and store multivendor-multi-technology KPIs using microservices based on user-selected domain (Radio Access Network (RAN), Wireless Fidelity (Wi-Fi),
25 etc.) and vendors or aggregation levels. The proposed disclosure aggregates counter data based on user selected node and time level using microservices. The proposed disclosure composes a unified PM counter data corresponding to different domains (for e.g., RAN, Wi-Fi, CORE, Internet Protocol (IP), transport and Fibre to the x (FTTX) etc.).
10

[0047] Various embodiments of the present disclosure will be explained in
detail with reference to FIGs. 1-10.
[0048] FIG. 1 illustrates an exemplary network architecture (100) in which
or with which embodiments of the present disclosure may be implemented.
5 [0049] Referring to FIG. 1, the network architecture (100) may include one
or more user equipments (104-1, 104-2…104-N) associated with one or more users (102-1, 102-2…102-N) in an environment. A person of ordinary skill in the art will understand that one or more users (102-1, 102-2…102-N) may be individually referred to as the user (102) and collectively referred to as the users (102). Similarly,
10 a person of ordinary skill in the art will understand that one or more user equipments (104-1, 104-2…104-N) may be individually referred to as the user equipment (104) and collectively referred to as the user equipment (104). A person of ordinary skill in the art will appreciate that the terms “computing device(s)” and “user equipment” may be used interchangeably throughout the disclosure. Although three user
15 equipments (104) are depicted in FIG. 1, however any number of the user equipments (104) may be included without departing from the scope of the ongoing description.
[0050] In an embodiment, the user equipment (104) may include smart
devices operating in a smart environment, for example, an Internet of Things (IoT)
20 system. In such an embodiment, the user equipment (104) may include, but is not limited to, smart phones, smart watches, smart sensors (e.g., mechanical, thermal, electrical, magnetic, etc.), networked appliances, networked peripheral devices, networked lighting system, communication devices, networked vehicle accessories, networked vehicular devices, smart accessories, tablets, smart television (TV),
25 computers, smart security system, smart home system, other devices for monitoring or interacting with or for the users (102) and/or entities, or any combination thereof. A person of ordinary skill in the art will appreciate that the user equipment (104) may include, but is not limited to, intelligent, multi-sensing, network-connected devices, that can integrate seamlessly with each other and/or with a central server
30 or a cloud-computing system or any other device that is network-connected.
11

[0051] In an embodiment, the user equipment (104) may include, but is not
limited to, a handheld wireless communication device (e.g., a mobile phone, a smart phone, a phablet device, and so on), a wearable computer device(e.g., a head-mounted display computer device, a head-mounted camera device, a wristwatch 5 computer device, and so on), a Global Positioning System (GPS) device, a laptop computer, a tablet computer, or another type of portable computer, a media playing device, a portable gaming system, and/or any other type of computer device with wireless communication capabilities, and the like. In an embodiment, the user equipment (104) may include, but is not limited to, any electrical, electronic,
10 electro-mechanical, or an equipment, or a combination of one or more of the above devices such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, wherein the user equipment (104) may include one or more in-built or externally coupled accessories
15 including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, a keyboard, and input devices for receiving input from the user (102) or the entity such as touch pad, touch enabled screen, electronic pen, and the like. A person of ordinary skill in the art will appreciate that the user equipment (104) may not be restricted to the mentioned devices and various other devices may be
20 used.
[0052] Referring to FIG. 1, the user equipment (104) may communicate
with a system (108), for example, a KPI metrics definition system, through a network (106). In an embodiment, the network (106) may include at least one of a Fifth Generation (5G) network, or the like. The network (106) may enable the user
25 equipment (104) to communicate with other devices in the network architecture (100) and/or with the system (108). The network (106) may include a wireless card or some other transceiver connection to facilitate this communication. In another embodiment, the network (106) may be implemented as, or include any of a variety of different communication technologies such as a wide area network (WAN), a
30 local area network (LAN), a wireless network, a mobile network, a Virtual Private
12

Network (VPN), the Internet, the Public Switched Telephone Network (PSTN), or the like.
[0053] In accordance with embodiments of the present disclosure, the
system (108) may be designed and configured for providing a KPI editor interface 5 for continuous KPI tracking for assessing network quality and network utilization efficiently.
[0054] Although FIG. 1 shows exemplary components of the network
architecture (100), in other embodiments, the network architecture (100) may include fewer components, different components, differently arranged components, 10 or additional functional components than depicted in FIG. 1. Additionally, or alternatively, one or more components of the network architecture (100) may perform functions described as being performed by one or more other components of the network architecture (100).
[0055] FIG. 2 illustrates an exemplary architecture (200) of a KPI metrics
15 definition system (108), in accordance with an embodiment of the present disclosure.
[0056] With respect to FIG. 2, the KPI metrics definition system (108) may
include a Performance Management (PM) module (202). The PM module (202) may handle any domain namely RAN, Wi-Fi, CORE, IP, Transport and FTTX with 20 minimal change in the GUI. Similarly, in the RAN, the PM module (202) may support existing technologies like 5G and future technologies like 6G with least development efforts. The PM module (202) may include a mediation module (204), a computation module (206), a presentation module (208), a prediction module (210), and a database (212).
25 [0057] The PM module (202) may obtain a user-defined KPI formula. The
KPI formula includes one or more PM counters pertaining to one or more networks. The PM counters are components managed by the PM module (202) that tracks and displays various performance metrics from servers associated with one or more vendors, one or more technologies, etc. the PM counter supports the PM module
13

(202) to monitor and manage the performance by collecting data on the KPIs, goals, and other relevant metric. The PM module (202) may be based on the KPI formula and may fetch PM counter data from a plurality of servers. In one example, the plurality of servers may be Element Management System (EMS) servers. In some 5 examples, the plurality of servers may be network management servers. The PM counter data may be fetched periodically after a pre-configured period for a plurality of geographical locations. For example, the PM module (202) may periodically fetch PM statistics (i.e., various counters of different categories) from different vendors of 5G EMS, for example, RAN EMS and Wi-Fi-EMS.
10 [0058] In an implementation, as the scale of the network is large, the
vendors deploy multiple EMS catering for different geographies. The PM module (202) may fetch the PM counter data of each of the one or more PM counters in a Comma-Separated Values (CSV) format from the EMS servers. The PM module (202) may then combine the PM counter data, in the CSV format, pertaining to a
15 particular PM counter and fetched from different EMS servers, to provide complete data in a single view. For example, the PM module (202) may fetch PM counter data from different EMS of same vendor or multiple vendors (for example, RAN EMS servers 220-1, 220-2…) and align it in a way that complete data is available at a single view. Upon fetching the PM counter data, the PM module (202) may
20 populate the one or more PM counters with the PM counter data. In examples, the PM module (202) may identify the servers (for example, RAN EMS servers 220-1, 220-2…) and systems where PM data is stored. In aspects, the PM module (202) may communicate with the servers and systems through their corresponding APIs. In examples, the PM module (202) may use scripts to query these APIs. For
25 example, the PM module (202) may use PowerShell script, Bash script, python script, etc. In some examples, the PM module (202) may use simple network management protocol (SNMP) to obtain PM data from network devices. In aspects, where the servers or the system use database to store the PM counter data, in such scenarios, the PM module (202) may use database queries to obtain the PM counter
30 data. In examples, the PM module (202) may store the populated data into a centralized repository such as database (212) which could include a data warehouse,
14

a time-series database, or any other centralized data store. The PM module (202) may normalize that PM counter data from different sources to make the data formats and units consistent.
[0059] Thereafter, using the mediation module (204), the PM module (202)
5 may aggregate, using a microservice, the PM counter data based on user-selected node and time level to compute the KPIs.
[0060] The computation module (206) may compute all counters that have
been aggregated for both time and space domain and also compute KPIs on every, for example, 15 minutes, 1 hour, etc., time period. Finally, the PM module (202) 10 may compose a unified PM counter data depicting the KPIs corresponding to the one or more networks.
[0061] In an example, to obtain the user-defined KPI formula, the PM
module (202) may be configured to receive user input with respect to a plurality of fields associated with the one or more networks and receive an indication of a type 15 of aggregation for each of the PM counters in time and space domain. For example, a KPI editor module which is a user-friendly UI interface may be developed within the PM module (202). The KPI editor module may provide the user a platform to define KPI formula and specify the type of aggregation for each of the counters (sum, max, average, etc.) in both time and space domain.
20 [0062] The KPI formula may be defined by using one or more counters
along with some mathematical operations. The KPI formula may also be used to define KPIs using the defined KPIs formula, definitions and aggregated KPI information (222).
[0063] The computed KPIs may be stored at different frequency and
25 hierarchical levels which are further being used by other analytical modules of the platform, for example, the presentation module (208) and the prediction module (210). The presentation module (208) may use the report definitions (224), and the prediction module (210) may use business inputs (226). The PM module (202) through the presentation module (208) may generate KPI values for reports,
15

network management platforms, and network elements that need KPI information. In examples, the KPI values in the reports and other modules are also presented in network management platform (228). The reports and the KPI information may be stored in database (212). In examples, the KPI computation may be performed and 5 stored at node hierarchy and time hierarchy levels (an example is shown in FIG. 7). Other hierarchy levels not disclosed herein such as network level, operational level, network segment level, service level, customer level, site level, device level, time-based level, and functional level, are contemplated herein.
[0064] The database (212) may comprise data that may be either stored or
10 generated as a result of functionalities implemented by any of the components of the PM module (202) or the system (108).
[0065] Although FIG. 2 shows the exemplary architecture (200) of the KPI
metrics definition system, in other embodiments, the system architecture (200) may include fewer components, different components, differently arranged components, 15 or additional functional components than depicted in FIG. 2. Additionally, or alternatively, one or more components of the system architecture (200) may perform functions described as being performed by one or more other components of the system architecture (200).
[0066] FIG. 3 illustrates an exemplary block diagram (300) of a PM data
20 flow mechanism, in accordance with an embodiment of the present disclosure.
[0067] With respect to FIG. 3, PM counters may be populated in a KPI
editor (310) as per user selection of a domain (RAN, Wi-Fi). The options may be incorporated to select a 5G vendor if multiple vendors exist in a particular domain and also a software version. On selecting a counter family/category, the PM 25 counters may be populated, and the user may select the requisite counters and define the KPI formula. Depending upon the KPI and type of counters, the user may have the option of selecting the type of aggregation (Sum, Max, Min, Avg., etc.) both at node level and time level.
16

[0068] Edge node servers (330) may fetch periodically (periodicity may be
defined by vendor to vendor) PM counter files of each family in, for example, a Comma-Separated Values (CSV) format from its EMS. All the CSV files from different EMS of the same 5G vendor may be combined in such a way that complete 5 data may be available in a single view. To elaborate with an implementational example, the PM counter data may be obtained using shell script (334) by edge node (330) through a task queue (332). The PM counter data may be stored in a file system (336), for example in a compressed format. For example, a tape archive (TAR) or a compressed form (for example, GZIP format) format for compressing
10 the PM counter data. The PM counter data in the files may be processed using an analytics engine (340). The analytics engine may include a data parsing unit (342) to parse the PM counter data to analyses the PM counter data and to obtain extract counter time periods. A counter processing unit (344) of the analytics engine (340) further processes the PM counter data. A data validation unit (346) of the analytics
15 engine (340) is configured to validate the PM counter data. A KPI calculation unit (348) of the analytics engine (340) performs KPI calculation using the PM counter data. The KPI information is communicated to microservices (350) through Representational State Transfer (REST) APIs (352) and/or to a database (214). The REST API communicates through hyper text transfer protocol (HTTP) requests to
20 perform database functions like creating, reading, updating and deleting records (also known as CRUD) associated with the microservice (350). A user-defined KPI formula may be obtained through a KPI editor (310) by the microservices, which processes the KPI information to generate KPI dashboards (360), KPI reports (362) and reports on site performance (364). In implementations, the generated KPI
25 information may be stored in the database (212).
[0069] The counters of different families may be aggregated based on the
definition in time domain. The KPI metrics may be defined through a front-end mechanism through user-friendly GUI by using one or more counters and applying mathematical operations. After aggregating the counters, the KPIs may be 30 calculated as per the defined formula. In examples, the KPI calculation may be performed on hourly, daily, weekly, or on demand basis. In some examples, the
17

user may define the frequency of the calculations. In an example, hourly computation of KPIs may be done and stored in a database. Similarly, the computation and aggregations may be done for different frequencies like Daily/Weekly/Base Band Frequency Hopping (BBH)/NBH etc. The computed 5 KPIs may be fetched in the form as per the user preference through the front-end mechanism using a report template. The computed KPIs may be stored in the database.
[0070] FIG. 4 illustrates an exemplary flow diagram (400) of KPI editor
design flow mechanism, in accordance with an embodiment of the present 10 disclosure. With respect to FIG. 4, an application server (402) may use micro service (404) to create KPIs. The micro service (404) may store a KPI configuration in a database (406) and retrieve the KPIs from the database (406).
[0071] FIG. 5 illustrates an exemplary flow diagram (500) of KPI formula
creation, in accordance with an embodiment of the present disclosure. With respect
15 to FIG. 5, in step 502, a UI (552) may define KPI formula and store the KPI formula in a database at 502. At 504, a KPI formula creation request may be sent by the PM KPI formula REST (554) to PM KPI formula service (556) (for example, also referred to as KPI formula definition (222)) (at step 504) and a KPI creation response may be received from the PM KPI formula service (556) (step 506). Upon
20 receiving the KPI creation response, the PM KPI formula service (556) communicate instructions to a PM KPI formula data access object (DAO) (558), a PM counter variable DAO (560), a formula counter mapping DAO (562) to generate KPI formula details (at step 508), defined counter information (at step 510) and mapping of KPI formula and counters (at step 512), respectively. The DAO as
25 discussed may define an abstract API to perform the CRUD operations. The KPI formula generated by the PM KPI formula DAO (558), the counter variables generated by the PM counter variable DAO (560) and the counter mapping generated by the formula counter mapping DAO (562) may be saved in the database (212) in step 512, step 514 and step 516, respectively.
18

[0072] FIG. 6 illustrates an exemplary flow diagram (600) of end-to-end
KPI computation, in accordance with an embodiment of the present disclosure. With respect to FIG. 6, an edge node (604) may execute shell script, for example, every 15 minutes (as an example) to pull data from an EMS server (602) (in step 5 652). In examples, the edge node may be a physical or virtual machine located at the edge of a network. The edge node (604) may compress data files and write to file system such as, for example, a Hadoop distributed file system (HDFS) (606) (in step 654). The file system (606) may read quarterly data files and send to an analytics engine (608) (in step 656). The analytics engine (608) may be the same
10 analytics engine (340) of FIG. 3. The analytics engine (608) may read, for example, quarterly data files from the file system (606), parse the quarterly data files, compute hourly counters, and write to a database table (610) such as HBase (in step 658). The HBase is a database management system used on, for example, the HDFS. In embodiments, other database system can be used as alternatives. The
15 computed counters may be stored in the database table (610). In examples, the computer counters may be stored by placing the counters in tables which are divided into regions, which may be contiguous rows or distributed. As tables in memory fills up, the tables are flushed as HFiles (for example, internal file format of HBase). The analytics engine (608) may read KPI configuration information stored in a
20 database (612) (in step 660). Further, the analytics engine (608) may retrieve hourly data and dashboard data using microservices (614), in step 662 and in step 664, respectively.
[0073] FIG. 7 illustrates an exemplary schematic diagram (700) of node and
time aggregation, in accordance with an embodiment of the present disclosure. An 25 illustration of how the aggregation is done on the 15 minutes files for 96 quarters is shown in FIG. 7. Pre-aggregation of the counters may be performed at node hierarchy and time hierarchy, based on the type of aggregation selected for node and time.
[0074] FIG. 8A illustrates an exemplary schematic diagram (800A) of KPI
30 editor, in accordance with an embodiment of the present disclosure. With respect
19

to FIG. 8A, a GUI interface may be provided to users to view the counters of interest of each category and also define the KPI metrics formula to create, modify, and delete the KPIs. The GUI interface may be referred to as the KPI editor. The KPI editor may include KPI names, node type, domains, technologies, vendors, and the 5 like as depicted in FIG. 8A.
[0075] FIG. 8B illustrates an exemplary schematic diagram (800B) of new
KPI creation, in accordance with an embodiment of the present disclosure. With respect to FIG. 8B, for new KPI creation, the user may need to give name of the KPI, select the appropriate domain, technology, node type, vendor, software 10 version, and counter category. KPI creation from RAN domain is depicted in FIG. 8B.
[0076] FIG. 8C illustrates an exemplary schematic diagram (800C) of KPI
creation for Wi-Fi domain, in accordance with an embodiment of the present disclosure. With respect to FIG. 8C, for KPI creation for Wi-Fi domain, the user 15 may need to provide name of the KPI, select the domain as Wi-Fi, and select the technology, node type, vendor, software version, and counter category per requirement.
[0077] FIG. 8D illustrates an exemplary schematic diagram (800D) of
selection of counters for KPI definition, in accordance with an embodiment of the 20 present disclosure. With respect to FIG. 8D, the counters may be selected, and proper node and time aggregation may be applied for defining KPI metrices for the network.
[0078] FIG. 8E illustrates an exemplary schematic diagram (800E) of
defining, validating and saving the formula to create the KPI, in accordance with 25 an embodiment of the present disclosure. With respect to FIG. 8E, the KPI formula may be defined, validated, and saved to create the KPI.
[0079] FIG. 9 illustrates an exemplary computer system (900) in which or
with which embodiments of the present disclosure may be implemented.
20

[0080] As shown in FIG. 9, the computer system (900) may include an
external storage device (910), a bus (920), a main memory (930), a read only memory (940), a mass storage device (950), a communication port (960), and a processor (970). A person skilled in the art will appreciate that the computer system 5 (900) may include more than one processor (970) and communication ports (960). Processor (970) may include various modules associated with embodiments of the present disclosure.
[0081] In an embodiment, the communication port (960) may be any of an
RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, 10 a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. The communication port (960) may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system (900) connects.
[0082] In an embodiment, the memory (930) may be Random Access
15 Memory (RAM), or any other dynamic storage device commonly known in the art. Read-only memory (940) may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or Basic Input/Output System (BIOS) instructions for the processor (970).
20 [0083] In an embodiment, the mass storage device (950) may be any current
or future mass storage solution, which may be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or
25 external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g., an array of disks (e.g., SATA arrays).
[0084] In an embodiment, the bus (920) communicatively couples the
processor(s) (970) with the other memory, storage and communication blocks. The
30 bus (920) may be, e.g., a Peripheral Component Interconnect (PCI)/PCI Extended
21

(PCI-X) bus, Small Computer System Interface (SCSI), Universal Serial Bus (USB) or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor (970) to the computer system (900).
5 [0085] Optionally, operator and administrative interfaces, e.g., a display,
keyboard, joystick, and a cursor control device, may also be coupled to the bus (920) to support direct operator interaction with the computer system (900). Other operator and administrative interfaces may be provided through network connections connected through the communication port (960). Components 10 described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system (900) limit the scope of the present disclosure.
[0086] FIG. 10 illustrates an exemplary flow diagram (1000) of a method
for defining Key Performance Indicators (KPIs) metrics for a wireless network, in 15 accordance with an embodiment of the present disclosure. The flow diagram (1000) includes steps which are defined below.
[0087] At step 1002, the method 1000 may include obtaining a user-defined
KPI formula. In an example, the PM module (202) is configured to obtain the user-defined KPI formula.
20 [0088] At step 1004, the method 1000 may include fetching, by the PM
module (202), PM counter data from a plurality of servers, based on the KPI formula. The PM counter data is fetched periodically after a pre-configured period for a plurality of geographical locations.
[0089] At step 1006, the method 1000 may include upon fetching, by the
25 PM module (202), the PM counter data, populating the one or more PM counters with the PM counter data.
[0090] At step 1008, the method 1000 may include aggregating using a
micro service (350), the PM counter data based on user-selected node and time level to compute the KPIs.

[0091] At step 1010, the method 1000 may include composing, by the PM
module (202), a unified PM counter data depicting the KPIs corresponding to the one or more networks.
[0092] While the foregoing describes various embodiments of the present
5 disclosure, other and further embodiments of the present disclosure may be devised without departing from the basic scope thereof. The scope of the present disclosure is determined by the claims that follow. The present disclosure is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the present disclosure when
10 combined with information and knowledge available to the person having ordinary skill in the art.
[0093] The present disclosure provides technical advancement related to the
monitoring wireless networks. This advancement addresses the limitations of existing technology where performance was not measured at detailed levels and
15 categories, leading to non-optimal performance of the network. The disclosure provides ways for defining KPI by operators and allowing a monitoring the wireless network on granular and/or at finer levels. This leads to identifying underperforming parameters of the wireless parameters that can be tracked and corrected, which further leads to a better performing wireless network, which offers
20 significant improvements in terms of managing various parameters, leading to consistent services and better utilization of resources.
ADVANTAGES OF THE PRESENT DISCLOSURE
[0094] The present disclosure defines Key Performance Indicator (KPI)
25 metrics through a front-end mechanism for a 5G/6G network.
[0095] The present disclosure provides a KPI editor interface to define the
KPI metrics for the 5G/6G network which are required to assess quality of the network and the network utilization.
[0096] The present disclosure fetches and aggregates Performance
30 Management (PM) counter data from one or more servers of one or more

geography, periodically, for a pre-configured period (for example, every 15 minutes, every 1 hour, every 6 hours, etc.).
[0097] The present disclosure populates PM counters for user-selected
filters of one or multiple of family, category, domain, vendor, etc.
5 [0098] The present disclosure defines KPI formula, for one or more PM
counters, with pre-aggregating and computing of corresponding KPI values at node level and time level.
[0099] The present disclosure provides a user-friendly Graphical User
Interface (GUI) for users to view counters of interest of each category and also 10 define the KPI metrics formula to create, modify, and delete the KPIs by privileged users.
[00100] The present disclosure pulls PM counter data from different EMS
sources for a configurable regular time-period (for example, 15 minutes) and using a distributed file system to compute/prepare data to be fetched using microservices.
15 [00101] The present disclosure aggregates counter data based on user
selected node and time level using microservices.

We claim:
1. A system (108) for defining Key Performance Indicators (KPIs) metrics for
5 a wireless network, the system comprising:
a processor;
a performance management (PM) module (202) coupled to the processor, the PM module (202) is configured to:
obtain a user-defined KPI formula, wherein the KPI formula includes
10 one or more PM counters pertaining to one or more networks;
based on the KPI formula, fetch PM counter data from a plurality of servers (602), wherein the PM counter data is fetched for a plurality of geographical locations;
upon fetching the PM counter data, populate the one or more PM
15 counters with the PM counter data;
aggregate, using a microservice, the PM counter data based on user-selected node and time level to compute the KPIs; and
compose a unified PM counter data depicting the KPIs corresponding to the one or more networks. 20
2. The system (108) as claimed in claim 1, wherein to obtain the user-defined
KPI formula, the PM module (202) is configured to:
receive user input with respect to a plurality of fields associated with the one
or more networks; and
25 receive an indication of a type of aggregation for each of the PM counters in
time and space domain.
3. The system (108) as claimed in claim 1, wherein to fetch the PM counter
data, the PM module (202) is configured to:
30 fetch the PM counter data of each of the one or more PM counters from the
servers (602); and

combine the PM counter data pertaining to a particular PM counter and fetched from different servers (602), to provide combined data in a single view.
4. The system (108) as claimed in claim 1, wherein the PM module (202) is
5 further configured to store the computed KPIs at different frequency and
hierarchical levels.
5. The system (108) as claimed in claim 1, wherein the PM module (202) is
configured to fetch the PM counter data using microservices through a distributed
10 file system.
6. A method (1000) for defining Key Performance Indicators (KPIs) metrics
for a wireless network, the method (1000) comprising:
obtaining, by a performance management (PM) module (202), a user-defined 15 KPI formula, wherein the KPI formula includes one or more PM counters pertaining to one or more networks;
based on the KPI formula, fetching, by the PM module (202), PM counter
data from a plurality of servers (602), wherein the PM counter data is fetched
periodically after a pre-configured period for a plurality of geographical locations;
20 upon fetching the PM counter data, populating, by the PM module (202), the
one or more PM counters with the PM counter data;
aggregating, by the PM module (202), using a microservice, the PM counter data based on user-selected node and time level to compute the KPIs; and
composing, by the PM module (202), a unified PM counter data depicting the 25 KPIs corresponding to the one or more networks.
7. The method (1000) as claimed in claim 7, wherein obtaining the user-
defined KPI formula comprises:
receiving, by the PM module (202), user input with respect to a plurality of 30 fields associated with the one or more networks; and

receiving, by the PM module (202), an indication of a type of aggregation for each of the PM counters in time and space domain.
8. The method (1000) as claimed in claim 7, wherein fetching the PM counter
5 data comprises:
fetching, by the PM module (202), the PM counter data of each of the one or more PM counters from the servers (602); and
combining, by the PM module (202), the PM counter data pertaining to a particular PM counter and fetched from different servers (602), to provide a 10 combined data in a single view.
9. The method (1000) as claimed in claim 7, further comprising storing, by the
PM module (202), the computed KPIs at different frequency and hierarchical levels.
15 10. The method (1000) as claimed in claim 7, wherein fetching the PM counter data comprises fetching the PM counter data using microservices through a distributed file system.
11. A user equipment (UE) (104) communicatively coupled with a network 20 (106), the coupling comprises steps of:
receiving, by the network (106), a connection request from the UE (104);
sending, by the network (106), an acknowledgment of the
connection request to the UE (104); and
25 transmitting a plurality of signals in response to the connection
request, wherein the transmission comprises defining Key Performance Indicators (KPIs) as defined in a method (1000) for defining KPIs metrics for a wireless network of claim 6.