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 OPTIMIZING NETWORK PERFORMANCE FOR A TARGET
AREA
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

SYSTEM AND METHOD FOR OPTIMIZING NETWORK PERFORMANCE FOR A TARGET AREA
RESERVATION OF RIGHTS
5 [0001] A portion of the disclosure of this patent document contains
material, which is subject to intellectual property rights such as but are not limited to, copyright, design, trademark, integrated circuit (IC) layout design, and/or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile 10 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.
15 FIELD OF INVENTION
[0002] The embodiments of the present disclosure generally relate to
communication network planning. More particularly, the present disclosure relates to a system and a method for optimizing a network performance for a target area.
20 BACKGROUND OF THE INVENTION
[0003] 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
25 only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0004] In the field of telecommunications and network planning, accurate
assessment of network performance and user experience are essential for providing optimal coverage and meeting user expectations. Network planning
30 engineers rely on various tools and models to predict and plan network coverage,
2

capacity, and performance. However, these tools suffer with poor accuracy and therefore fails to meet user expectations.
[0005] Traditionally, network coverage was being monitored by the means
of regular drive-testing on target routes and areas across a country, amounting to a 5 huge undertaking by network teams, which delays identification process of uncovered patch and mitigation for a particular area.
[0006] There is, therefore, a need in the art to provide a system and a
method that can overcome shortcoming associated with prior arts.
10 SUMMARY
[0007] In an exemplary embodiment, a method for optimizing a network
performance for a target area is described. The method includes receiving a first set of information pertaining to a target area from one or more computing devices associated with one or more users. The method includes sampling the target area
15 into a plurality of segments to identify a first set of grids corresponding to the target area. The method includes identifying a set of coverage parameters along the route based on the first set of grids. The method includes aggregating the set of coverage parameters to generate one or more actionable insights. The method includes identifying one or more uncovered patch locations along the route based
20 on the one or more actionable insights in response to aggregating.
[0008] In some embodiments, the method further includes performing a
coverage planning and optimization for the one or more uncovered patch
locations.
[0009] In some embodiments, the method further includes performing a
25 route coverage aggregation to estimate a coverage status on the target area.
[0010] In some embodiments, the one or more actionable insights includes
information associated with population distribution, area covered under different coverage categories, and details of the one or more uncovered patch locations.
3

[0011] In some embodiments, the method further includes utilizing the one
or more actionable insights for improving the network performance in the one or more uncovered patch locations.
[0012] In some embodiments, the method further includes receiving a
5 second set of information corresponding to a set of parameters, metrics, and Key
Performance Indicators (KPIs) associated with a plurality of grids.
[0013] In some embodiments, the first set of information includes a
longitudinal and latitudinal data and a geographical data associated with the target area, and wherein the geographical data includes an altitude, terrain features, and
10 land use classifications.
[0014] In some embodiments, the method further includes receiving the
first set of information in one of a real-time mode or a batch mode, from the one
or more computing devices.
[0015] In another exemplary embodiment, a system for optimizing a
15 network performance for a target area is described. The system includes receive a first set of information pertaining to a target area from one or more computing devices associated with one or more users. The processor is configured to sample the target area into a plurality of segments to identify a first set of grids corresponding to the target area. The processor is configured to identify a set of
20 coverage parameters along a route based on the first set of grids. The processor is configured to aggregate the set of coverage parameters to generate one or more actionable insights. The processor is configured to identify one or more uncovered patch locations along the route based on the one or more actionable insights in response to aggregation.
25 [0016] In some embodiments, the processor is further configured to
perform a coverage planning and optimization for the one or more uncovered patch locations.
[0017] In some embodiments, the processor is further configured to
perform a route coverage aggregation to estimate a coverage status on the target
30 area.
4

[0018] In some embodiments, the one or more actionable insights
comprise information associated with population distribution, area covered under
different coverage categories, and details of the one or more uncovered patch
locations.
5 [0019] In some embodiments, the processor is configured to utilize the one
or more actionable insights for improving the network performance in the one or more uncovered patch locations.
[0020] In some embodiments, the processor is further configured to
receive a second set of information corresponding to a set of parameters, metrics,
10 and Key Performance Indicators (KPIs) associated with a plurality of grids.
[0021] In some embodiments, the first set of information comprises a
longitudinal and latitudinal data and a geographical data associated with the target area, and wherein the geographical data includes an altitude, terrain features, and land use classifications.
15 [0022] In some embodiments, the processor is further configured to
receive the first set of information in one of a real-time mode or a batch mode, from the one or more computing devices.
[0023] The foregoing general description of the illustrative embodiments
and the following detailed description thereof are merely exemplary aspects of the
20 teachings of this disclosure and are not restrictive.
OBJECTS OF THE INVENTION
[0024] Some of the objects of the present disclosure, which at least one
25 embodiment herein satisfies are as listed herein below.
[0025] An object of the present disclosure is to provide a system and a
method for optimizing a network performance for a target area by estimating
network coverage parameters for the target area.
[0026] Another object of the present disclosure is to eliminate a need for a
30 constant drive testing to be performed.
5

[0027] An object of the present disclosure is to allow to keep a track of a
network coverage status on all roads of the target area, regularly.
[0028] An object of the present disclosure is to improve an accuracy of a
network coverage analysis of the target area.
5 [0029] An object of the present disclosure is to provide a system and a
method that is economical and easy to implement for optimizing the network performance for the target area.
10 LIST OF REFERENCE NUMERALS
100 - Network Architecture
102-1, 102-2…102-N - Users
104-1, 104-2…104-N - User Equipments (UEs)
106 - Network 15 108 - System
110 - Centralized Server
202 - One or more processor(s)
204 - Memory
206 - Interface(s) 20 208 - Processing Engine(s)
210 - Database
300 - Flow Diagram
302 - Sampling Step
304 - Grid Identification Step 25 306 - Coverage Planning and Optimization Step
308- Route Coverage Aggregation Step
500 - Computer System
510 - External Storage Device
520 - Bus 30 530 - Main Memory
540 - Read Only Memory
6

550 - Mass Storage Device 560 - Communication Port(s) 570 - Processor
5
BRIEF DESCRIPTION OF DRAWINGS
[0030] The accompanying drawings, which are incorporated herein, and
constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems which like reference numerals refer to the same
10 parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such
15 drawings includes the disclosure of electrical components, electronic components,
or circuitry commonly used to implement such components.
[0031] FIG. 1 illustrates an example network architecture for
implementing a proposed system optimizing a network performance of a target area, in accordance with an embodiment of the present disclosure.
20 [0032] FIG. 2 illustrates an example block diagram of a proposed system
optimizing a network performance of a target area, in accordance with an embodiment of the present disclosure.
[0033] FIG. 3 illustrates an example flow diagram representing a method
for optimizing a network performance of a target area, in accordance with an
25 embodiment of the present disclosure.
[0034] FIG. 4A is an exemplary representation of a target area divided into
a plurality of segments and a plurality of grids, in accordance with an embodiment
of the present disclosure.
[0035] FIG. 4B is a pictorial representation of an information associated of
30 a specific portion of the target area, in accordance with an embodiment of the present disclosure.
7

[0036] FIG. 4C illustrates a tabular representation of a coverage analysis
of a target area in a particular site, in accordance with an embodiment of the present disclosure.
[0037] FIG. 4D illustrates a tabular representation of details associated
5 with one or more uncovered patch locations, in accordance with an embodiment of the present disclosure.
[0038] FIG. 5 illustrates an example computer system in which or with
which the embodiments of the present disclosure may be implemented.
[0039] The foregoing shall be more apparent from the following more
10 detailed description of the disclosure.
DETAILED DESCRIPTION
[0040] In the following description, for explanation, various specific
details are outlined in order to provide a thorough understanding of embodiments
15 of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed
20 above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0041] 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
25 skilled in the art with an enabling description for implementing an exemplary
embodiment. It should be understood that various changes may be made in the
function and arrangement of elements without departing from the spirit and scope
of the disclosure as set forth.
[0042] Specific details are given in the following description to provide a
30 thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without
8

these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown 5 without unnecessary detail to avoid obscuring the embodiments.
[0043] Also, it is noted that individual embodiments may be described as a
process that is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in
10 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. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the
15 function to the calling function or the main function.
[0044] 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
20 not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be
25 inclusive like the term “comprising” as an open transition word without precluding any additional or other elements.
[0045] Reference throughout this specification to “one embodiment” or
“an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment
30 is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in
9

various places throughout this specification are not necessarily all referring to the
same embodiment. Furthermore, the particular features, structures, or
characteristics may be combined in any suitable manner in one or more
embodiments.
5 [0046] The terminology used herein is to describe particular embodiments
only and is not intended to be limiting the disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the
10 presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any combinations of one or more of the associated listed items.
15 [0047] Embodiments herein relate to a method for optimizing a network
performance for a target area by determining network metrics or network grid for the target area. In particular, a first set of information pertaining to the target area for which a set of coverage parameters is to be determined may be received. In addition, a second set of information corresponding to a set of parameters,
20 metrics, and KPIs associated with a plurality of grids of a tile, or a site may be received. The target area falls under a geographical region of the tile. The target area is sampled so as to segment the target area into the plurality of segments. Then, among the plurality of segments, a first set of grids are identified, which correspond to the plurality of segments. The first set of grids are identified by
25 mapping the plurality of segments with the plurality of grids. In this manner, the first set of grids associated with the target area are identified. Then the set of coverage parameters are identified based on the first set of grids. Upon identification of the set of coverage parameters corresponding to the first set of grids, the network performance for the target area can be easily determined. The
30 network performance may include but not limited to the set of parameters (e.g., a network traffic), one or more metrics or key performance parameters (KPIs).
10

[0048] The various embodiments throughout the disclosure will be
explained in more detail with reference to FIGS. 1-5.
[0049] FIG. 1 illustrates an exemplary network architecture 100 for
implementing a proposed system 108 for optimizing a network performance of a 5 target area, in accordance with embodiments of the present disclosure.
[0050] Referring to FIG. 1, the network architecture 100 includes one or
more computing devices or user equipment’s 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 the one or more users 102-1, 102-10 2…102-N may be collectively referred to as a user 102. Similarly, a person of ordinary skill in the art will understand that one or more user equipment’s 104-1, 104-2…104-N may be collectively referred to as a 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. 15 Although three user equipment’s 104 are depicted in FIG. 1, however any number of the user equipment’s 104 may be included without departing from the scope of the ongoing description.
[0051] In an embodiment, the user equipment 104 may include smart
devices operating in a smart environment, for example, an Internet of Things
20 (IoT) system. In such an embodiment, the user equipment 104 may include, but is
not limited to, smartphones, 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
25 television (TV), computers, smart security system, smart home system, other
devices for monitoring or interacting with or for the user 102 and/or entities (not
shown), 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
30 seamlessly with each other and/or with a central server or a cloud-computing
system or any other device that is network-connected.
11

[0052] In an embodiment, the user equipment 104 includes, but is not
limited to, a handheld wireless communication device (e.g., a mobile phone, a smartphone, a phablet device, and so on), a wearable computer device(e.g., a head-mounted display computer device, a head-mounted camera device, a 5 wristwatch 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 includes, but is not limited to, any
10 electrical, electronic, 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, a laptop, a general-purpose computer, a desktop, a personal digital assistant, a tablet computer, a mainframe computer, or any other computing device.
15 [0053] Further, in some embodiments, the user equipment 104 may
include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, a keyboard, and input devices for receiving input from the user 102, or an entity such as a touchpad, a touch-enabled screen, an electronic pen, and the like. A
20 person of ordinary skill in the art will appreciate that the user equipment 104 may not be restricted to the above-mentioned devices and various other devices may be used.
[0054] The user equipment 104 communicates with a system 108, for
example, a stale session management system, through a network 106. In an
25 embodiment, the network 106 includes at least one of a Fourth Generation (4G) network, a Fifth Generation (5G) network, a Sixth Generation (6G) network, or the like. The network 106 enables the user equipment 104 to communicate with other devices in the network architecture 100 and/or with the system 108. The network 106 includes a wireless card or some other transceiver connection to
30 facilitate this communication. In another embodiment, the network 106 is implemented as, or includes any of a variety of different communication
12

technologies such as a wide area network (WAN), a local area network (LAN), a
wireless network, a mobile network, a Virtual Private Network (VPN), the
Internet, the Public Switched Telephone Network (PSTN), or the like.
[0055] In another exemplary embodiment, a centralized server 110 may be
5 associated with the system 108. The centralized server 112 includes or comprise, by way of example but not limited to, one or more of: a stand-alone server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, a hardware running on a virtualized server, one or more processors executing code to function as a server,
10 one or more machines performing server-side functionality as described herein, at
least a portion of any of the above, some combination thereof.
[0056] The system (108) is configured to establish a plurality of sessions
corresponding to various nodes, i.e., the user equipment 104. In an example, the plurality of sessions includes an Access Management (AM) session, a Session
15 Management (SM) session, and a Receiver (Rx) session. The system 108 maintains a runtime user configurable stale session timer corresponding to each session of the plurality of sessions based on last message received. In an aspect, a runtime user configurable stale session timer is stored in a shared data layer (SDL) database, or in first level (L1) cache.
20 [0057] The system (108) identifies at least one stale session based on the
runtime user configurable stale session timer and generates session data corresponding to each session. The session data includes a flag indicating whether a session is stale or not. The system (108) transmits at least one update request and the session data to a specific node based on the determined session timer of
25 the specific node. In an example, the at least one update request is transmitted to the specific node through a hypertext transfer protocol 2 (HTTP2) interface. In an embodiment, the at least one update request is transmitted based on a configurable value. For example, the configurable value includes a predefined time, after the system is able to send the update request automatically.
30 [0058] The system 108 receives a response from the specific node. The
system 108 performs at least one operation on the session based on the received
13

response. The at least one operation includes termination of the session or retention of the session.
[0059] In an embodiment, the system 108 is configured to handle the stale
sessions based on different error codes received from a service communication
5 proxy (SCP) or timeouts received from a session management function (SMF).
[0060] In an embodiment, the system 108 is configured to hold a diameter
session even after receiving a session termination request-session termination
answer (STR-STA).
[0061] Although FIG. 1 shows exemplary components of the network
10 architecture 100, in other embodiments, the network architecture 100 may include fewer components, different components, differently arranged components, 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
15 of the network architecture 100.
[0062] FIG. 2 illustrates an exemplary block diagram 200 of the proposed
system 108, in accordance with an embodiment of the present disclosure. FIG. 2 is
explained in conjunction with FIG. 1.
[0063] In an aspect, the system 108 includes a processor(s) 202. The
20 processor(s) 202 are implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the processor(s) 202 are configured to fetch and execute computer-readable instructions stored in a memory 204 of the
25 system 108. The memory 204 is configured to store one or more computer-readable instructions or routines in a non-transitory computer-readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory 204 includes any non-transitory storage device including, for example, a volatile memory such as a Random-Access Memory
30 (RAM), or a non-volatile memory such as an Erasable Programmable Read-Only Memory (EPROM), a flash memory, and the like.
14

[0064] In an embodiment, the system 108 includes an interface(s) 206. The
interface(s) 206 may include a variety of interfaces, for example, interfaces for
data input and output devices, referred to as Input/Output devices, storage devices,
and the like. The interface(s) 206 facilitates communication through the system
5 108. The interface(s) 206 also provides a communication pathway for one or more
components of the system 108. Examples of such components include, but are not
limited to, processing unit/engine 208 and a database 210.
[0065] The processing engine 208 is implemented as a combination of
hardware and programming (for example, programmable instructions) to
10 implement one or more functionalities of the processing engine 208. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine 208 is processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing
15 engine 208 includes a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by processing resource (e.g., the one or more processor(s) 202), implement the processing engine 208. In such examples, the system 108 includes a machine-readable
20 storage medium storing instruction and the processing resource to execute the
instructions, or the machine-readable storage medium may be separate but
accessible to the system 108 and the processing resource. In other examples, the
processing engine 208 may be implemented by an electronic circuitry.
[0066] In an embodiment, the one or more processor(s) 202 may receive a
25 first set of information pertaining to a target area for which a set of coverage parameters are to be determined. The first set of information may be received from one or more computing devices, i.e., the user equipment 104 associated with one or more users, i.e., the user 102. This first set of information may include a longitudinal and latitudinal data, i.e., a longitude and latitude coordinates, that
30 precisely define boundaries or path of the target area. Additionally, the first set of information may include a geographical data such as an altitude, terrain features,
15

and land use classifications, which could influence the coverage analysis. The first
set of information may be transmitted from the one or more computing devices in
one of a real-time mode or a batch mode, ensuring that the processor 202 has the
most up-to-date and accurate depiction of the target area for analysis. The first set
5 of information can be gathered through various means including Global
Positioning System (GPS) devices, mobile applications, or uploaded files
containing necessary coordinates and specifications associated with the one or
more computing devices.
[0067] In an embodiment, the processor 202 may be configured to receive
10 a second set of information corresponding to a set of parameters, metrics, and Key Performance Indicators (KPIs) associated with a plurality of grids of a tile or a site. The target area falls under a geographical region of the tile, and each particular site or the tile may be segmented into a plurality of segments, or the plurality of grids. This second set of information could include detailed metrics,
15 associated with a signal strength, a data throughput, a latency, a coverage quality, and a user density within each grid. Similarly, the set of parameters may be a latency parameter, a signal strength parameter, a latency parameter, a coverage quality parameter, and the like. Additionally, the KPIs might encompass metrics such as call drop rates, data session success rates, and network congestion levels.
20 This information allows the processor(s) 202 to have a granular view of the network performance and coverage within the target area, segmented into specific, identifiable grids. The information for each grid can be obtained from various network monitoring tools and sources, including base stations, network management systems, and the one or more computing devices.
25 [0068] In an embodiment, the processor(s) 202 may be configured to
sample the target area into a plurality of segments. The sampling of the target area involves dividing the target area into smaller, uniform segments, which simplifies the analysis by focusing on discrete sections. The processor 202 may be configured to identify a first set of grids among the plurality of grids, which
30 correspond to these segments. The first set of grids are specific grids through which the target area passes, ensuring that the coverage analysis is precisely
16

targeted. Each grid in the first set of grids can represent a specific portion of the target area, allowing for detailed examination and assessment of the set of coverage parameters within the plurality of segments. This segmentation facilitates identification of areas with varying coverage levels, enabling a more 5 thorough and precise analysis of the network performance in different parts of the target area.
[0069] In an embodiment, based on the set of coverage parameters
identified corresponding to the first set of grids, the processor 202 may be configured to analyze the set of coverage parameters and generate one or more
10 actionable insights into user experience and network optimization opportunities. This analysis might include assessing the signal strength, identifying areas with weak or no coverage, and determining an overall quality of the network within each grid in the first set of grids. The processor(s) 202 can then aggregate the set of configuration parameters to generate the one or more actionable insights. The
15 one or more actionable insights may be generated in a form of a comprehensive report highlighting a coverage performance across the target area. Further, the processor 202 may perform a route coverage aggregation to estimate a coverage status on the target area. Based on the one or more actional insights, the processor 202 may identify one or more uncovered patch locations. In an embodiment, the
20 one or more uncovered patch locations may correspond to locations having low coverage of the network (also referred as low network coverage locations). The one or more actionable insights includes information associated with population distribution, area covered under different coverage categories (e.g., a high network coverage category, a medium network coverage category, a low network
25 coverage category, and the like), and details of the one or more uncovered patch locations.
[0070] Further, the processor(s) 202 may be configured to utilize the one
or more actionable insights for improving the network performance in the one or more uncovered patch locations. To improve the network performance, the
30 processor(s) 202 may perform a coverage planning and optimization for the one or more uncovered patch locations. The coverage planning and optimization may
17

include recommendations for network enhancements, such as optimizing a
placement of base stations, adjusting network configurations, or implementing
new technologies to improve coverage of the network in the target area.
Additionally, the analysis might identify specific areas where user experience is
5 suboptimal, providing actionable data for network planning and optimization
teams to address these issues effectively. The one or more actionable insights can
be crucial for strategic decision-making, enabling proactive measures to enhance
the network and improve customer satisfaction.
[0071] Although FIG. 2 shows exemplary components of the system 108,
10 in other embodiments, the system 108 may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. 2. Additionally, or alternatively, one or more components of the system 108 may perform functions described as being performed by one or more other components of the system 108.
15 [0072] FIG. 3 illustrates an example flow diagram 300 representing a
method for optimizing a network performance of a target area, in accordance with an embodiment of the present disclosure. FIG. 3 is explained in conjunction with FIGS. 1 and 2. In order to perform optimization of the network performance of the target area, initially at step 302, the first set of information pertaining to the target
20 area from the one or more computing devices (same as the user equipment 104) associated with the one or more users (same as the user 102). The first set of information may include, but is not limited to, the longitudinal and latitudinal data and the geographical data associated with the target area, and the geographical data includes the altitude, the terrain features, and the land use classifications. In
25 some embodiment, based on the first set of information received from the one or more computing devices, the target area may be identified. In addition to the first set of grids, a second set of information corresponding to the set of parameters, metrics, and Key Performance Indicators (KPIs) associated with the plurality of grids may also be received.
30 [0073] Upon receiving the first set of information, at step 304, the target
area is sampled into the plurality of segments. The sampling is done to improve an
18

accuracy of measurements and identification of the one or more uncovered patch locations. In an example, a route or the target area is sampled at 30 m intervals, and polygons are sampled at a 10 x 10 m grid level to account for changes in the coverage of the network in the target area. This step ensures that the target area is 5 divided into the plurality of segments, facilitating a more precise analysis of the set of coverage parameters. Further, based on the sampling of the target area, the first set of grids is identified corresponding to the target area. Further, based on the first set of grids, at step 306, the set of coverage parameters are identified along the route. This identification of each grid of the first set of grid involves
10 determining various network performance metrics such as the signal strength, the data throughput, the latency, and the coverage quality within each grid in the first set of grids.
[0074] Upon identification of the set of coverage parameters, at step 308,
the set of coverage parameters for each of the first set of grids are aggregated to
15 generate the one or more actionable insights. The aggregation of the set of coverage parameters corresponds to combining and analyzing the set of coverage parameters associated with each of the first set of grids to derive meaningful information, i.e., the one or more actionable insights about the network performance within the target area. The one or more actionable insights includes
20 information associated with population distribution, area covered under different coverage categories, and details of the one or more uncovered patch locations. In an embodiment, the route coverage aggregation is performed to estimate the overall coverage on the target area. This step involves compiling the aggregated set of coverage parameters to provide an overall estimate of the network coverage
25 for the target area. The route coverage aggregation considers a cumulative data from all the plurality of segments and the plurality of grids to generate a comprehensive coverage profile for the target area. This profile helps in understanding an extent of the network coverage, identifying any remaining gaps, and making informed decisions for future network improvements.
30 [0075] This aggregation process consolidates the first set of information to
provide a comprehensive view of the coverage across the target area. Further, at
19

step 310, the one or more uncovered patch locations along the route may be identified based on the one or more actionable insights in response to aggregation. Further, the one or more actionable insights are utilized for improving the network performance in the one or more uncovered patch locations. In an example, the one 5 or more uncovered patch locations in the route or the polygon corresponds to patch locations where there is consistently low coverage are identified. The one or more uncovered patch locations are areas that consistently report lower-than-expected network performance, indicating potential issues in the coverage of the network that need to be addressed.
10 [0076] Further, based on the identification of the one or more uncovered
patch locations with low coverage, coverage planning, and optimization are performed to improve the performance at the one or more uncovered patch locations. In other words, the one or more uncovered patch locations may correspond to locations with low network coverage. This involves developing and
15 implementing strategies to enhance the network coverage in the one or more uncovered patch locations low coverage. Such strategies may include adjusting placement and configuration of network infrastructure, deploying additional network resources, or optimizing existing network settings. The goal is to enhance the overall network performance and ensure better coverage in previously
20 identified problematic areas, i.e., the one or more uncovered patch locations.
[0077] FIGS. 4A is an exemplary representation 400A of a target area
divided into a plurality of segments and a plurality of grids, in accordance with an embodiment of the present disclosure. FIG. 4A is explained in conjunction with FIGS. 1 – 3.
25 [0078] In FIG. 4A a map of a target area divided into the plurality of
segments depicted via lines and the plurality of grids (e.g., an exemplary grid 402A). Each grid represents signal strength depicted via dash lines, allowing for detailed analysis of the set of coverage parameters within each grid. The plurality grids are shown with various types of dash lines indicating different levels of
30 signal strength to provide a coverage quality of the network, ranging from poor to excellent.
20

[0079] FIG, 4B is a pictorial representation 400B of an information
associated of a specific portion of the target area, in accordance with an
embodiment of the present disclosure. FIG. 4B is explained in conjunction with
FIGS. 1 – 4A.
5 [0080] FIG. 4B provides a detailed view of a specific portion, i.e., a macro
site 404B of the target area with the first set of grids overlaid. The target area includes a railway route 402b marked in special dashed lines, which traverses through the first set of grids. The macro site 404B, represented by icons, indicate locations of network infrastructure within the target area. A legend 406B indicates
10 the coverage quality in decibels (dBm), ranging from -140 dBm (poor coverage) to -40 dBm (excellent coverage). The 402b shows the coverage quality across the legend 406B.
[0081] FIG. 4C illustrates a tabular representation 400C of a coverage
analysis of a target area in a particular site, in accordance with an embodiment of
15 the present disclosure. FIG. 4C is explained in conjunction with FIGS. 1 – 4B.
[0082] FIG. 4C shows results of the coverage analysis, highlighting the
one or more uncovered patch locations along the railway route 402B via the tabular representation 400C. These one or more uncovered patch locations are areas where the coverage quality is below an acceptable threshold (e.g., -
20 105dBm), indicating poor or no network coverage. As depicted via the tabular representation, a first column 402C depicts a route ID 402C of each route. A second column 404C depicts a length greater 92.5% covered at -105dbm, a third column represents a length greater 95% covered at -105dbm. Similarly other columns, i.e., 406C, 408C, 410C, 412C, 414C, 416C, 418C, 420C, and 422C
25 depict various information associated with the one or more uncovered patch locations.
[0083] FIG. 4D illustrates a tabular representation 400D of details
associated with the one or more uncovered patch locations, in accordance with an embodiment of the present disclosure. FIG. 4D is explained in conjunction with
30 FIGS. 1 – 4C.
21

[0084] In FIG. 4D a summary of the coverage analysis for the target area
via the tabular representation 400C. The tabular representation 400C represents the set of coverage parameters associated with the target area, such as, a patch ID 402D, a patch length 404D, a patch starts latitude 406D, a patch starts longitude 5 408D a patch end latitude 410D, a patch end longitude 412D, a nearest Service Access Point Identifier (SAP ID) 414D, a site category 416D, and a site status 418D. In other words, the tabular representation 400C includes detailed information on population distribution, area covered under different coverage categories, and specific details about the one or more uncovered patch locations.
10 The tabular representation 400C helps in identifying the one or more uncovered
patch locations that require network improvements and provides the one or more
actionable insights for planning and optimization the overall network coverage
status on the target area.
[0085] FIG. 5 illustrates an example computer system (500) in which or
15 with which the embodiments of the present disclosure may be implemented.
[0086] As shown in FIG. 5, the computer system 500 may include an
external storage device 510, a bus 520, a main memory 530, a read-only memory 540, a mass storage device 550, a communication port(s) 560, and a processor(s) 570. A person skilled in the art will appreciate that the computer system 500 may
20 include more than one processor and communication ports. The processor 570 may include various modules associated with embodiments of the present disclosure. The communication port(s) 560 may be any of an RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or
25 future ports. The communication ports(s) (560) may be chosen depending on a
network, such as a Local Area Network (LAN), Wide Area Network (WAN), or
any network to which the computer system 500 connects.
[0087] In an embodiment, the main memory 530 may be Random Access
Memory (RAM), or any other dynamic storage device commonly known in the
30 art. The read-only memory 540 may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chip for storing static
22

information e.g., start-up or basic input/output system (BIOS) instructions for the
processor 570. The mass storage device 550 may be any current or future mass
storage solution, which can be used to store information and/or instructions.
Exemplary mass storage solutions include, but are not limited to, Parallel
5 Advanced Technology Attachment (PATA) or Serial Advanced Technology
Attachment (SATA) hard disk drives or solid-state drives (internal or external,
e.g., having Universal Serial Bus (USB) and/or Firewire interfaces).
[0088] In an embodiment, the bus 520 may be communicatively coupled
with the processor(s) 570 with the other memory, storage, and communication
10 blocks. The bus 520 may be, e.g. a Peripheral Component Interconnect PCI) / PCI Extended (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 570 to the computer system 500.
15 [0089] In another embodiment, operator and administrative interfaces, e.g.,
a display, keyboard, and cursor control device may also be coupled to the bus 520 to support direct operator interaction with the computer system 500. Other operator and administrative interfaces can be provided through network connections connected through the communication port(s) 560. Components
20 described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system 500 limit the scope of the present disclosure.
[0090] While considerable emphasis has been placed herein on the
preferred embodiments, it will be appreciated that many embodiments can be
25 made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the
30 disclosure and not as a limitation.
23

ADVANTAGES OF THE INVENTION
[0091] The present disclosure provides a system and a method for
optimizing a network performance of a target area by estimating coverage
parameters for the target area.
5 [0092] The present disclosure provides the system and the method that
eliminates a need for a constant drive testing to be performed.
[0093] The present disclosure provides the system and the method that
allow to keep a track of a coverage status on all roads regularly.
[0094] The present disclosure provides the system and the method that is
10 economical and easy to implement for optimizing the network performance of the
target area.
[0095] The present disclosure provides the system and the method to
improve an accuracy of a coverage analysis of the target area.
[0096] The present disclosure provides the system and the method that
15 provides network improvement and better customer experience.
24

We Claim:
1. A system (108) for optimizing a network performance for a target area, the
system (108):
a memory (204); and
5 a processor (202) coupled with the memory (204), configured to:
receive (302) a first set of information pertaining to the target area from one or more computing devices (104) associated with one or more users (102);
sample (304) the target area into a plurality of segments to
10 identify a first set of grids corresponding to the target area;
identify (306) a set of coverage parameters along a route based on the first set of grids;
aggregate (308) the set of coverage parameters to generate
one or more actionable insights; and
15 identify (310) one or more uncovered patch locations along
the route based on the one or more actionable insights in response to aggregation.
2. The system (108) as claimed in claim 1, wherein the processor (202) is
20 configured to perform a coverage planning and optimization for the one or
more uncovered patch locations.
3. The system (108) as claimed in claim 1, wherein the processor (202) is
configured to perform a route coverage aggregation to estimate a coverage
25 status on the target area.
4. The system (108) as claimed in claim 1, wherein the one or more
actionable insights comprise information associated with population
distribution, area covered under different coverage categories, and details
30 of the one or more uncovered patch locations.
25

5. The system (108) as claimed in claim 1, wherein the processor (202) is
configured to utilize the one or more actionable insights for improving the
network performance in the one or more uncovered patch locations.
5
6. The system (108) as claimed in claim 1, wherein the processor (202) is
configured to receive a second set of information corresponding to a set of
parameters, metrics, and Key Performance Indicators (KPIs) associated
with a plurality of grids.
10
7. The system (108) as claimed in claim 1, wherein the first set of
information comprises a longitudinal and latitudinal data and a
geographical data associated with the target area, and wherein the
geographical data includes an altitude, terrain features, and land use
15 classifications.
8. The system (108) as claimed in claim 1, wherein the processor (202) is
configured to receive the first set of information in one of a real-time
mode or a batch mode, from the one or more computing devices (104).
20
9. A method (300) for optimizing a network performance for a target
network, the method comprising:
receiving (302), by a processor (202), a first set of information
pertaining to a target area from one or more computing devices (104)
25 associated with one or more users (102);
sampling (304), by the processor (202), the target area into a plurality of segments to identify a first set of grids corresponding to the target area;
identifying (306), by the processor (202), a set of coverage
30 parameters along a route based on the first set of grids;
26

aggregating (308), by the processor (202), the set of coverage parameters to generate one or more actionable insights; and
identifying (310), by the processor (202), one or more uncovered
patch locations along the route based on the one or more actionable
5 insights in response to aggregating.
10. The method (300) as claimed in claim 9, performing, by the processor
(202), a coverage planning and optimization for the one or more
uncovered patch locations.
10
11. The method (300) as claimed in claim 9, performing, by the processor
(202), a route coverage aggregation to estimate a coverage status on the
target area.
15 12. The method (300) as claimed in claim 9, wherein the one or more
actionable insights comprise information associated with population distribution, area covered under different coverage categories, and details of the one or more uncovered patch locations.
20 13. The method (300) as claimed in claim 9, utilizing, by the processor (202),
the one or more actionable insights for improving the network performance in the one or more uncovered patch locations.
14. The method (300) as claimed in claim 9, receiving, by the processor (202),
25 a second set of information corresponding to a set of parameters, metrics,
and Key Performance Indicators (KPIs) associated with a plurality of grids.
15. The method (300) as claimed in claim 9, wherein the first set of
30 information comprises a longitudinal and latitudinal data and a
geographical data associated with the target area, and wherein the
27

geographical data includes an altitude, terrain features, and land use classifications.
16. The method (300) as claimed in claim 9, receiving, by the processor (202),
5 the first set of information in one of a real-time mode or a batch mode,
from the one or more computing devices (104).
17. A user equipment (UE) (104) communicatively coupled with a system
(108), the coupling comprises steps of:
10 receiving a connection request from the system (108);
sending an acknowledgment of the connection request to the system (108); and
transmitting a plurality of signals in response to the connection
request, wherein the system (108) is configured for optimizing network
15 performance for a target area, as claimed in claim 1.
Dated this 04 day of June 2024
~Digitally signed~
D. Jayaseelan Solomon
REG.NO:IN/PA-324
of De Penning & De Penning
Agent for the Applicants