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 DETERMINING AN OPERATIVE STATUS OF A BASE GRID
FOR NETWORK ANALYSIS
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
2
SYSTEM AND METHOD FOR DETERMINING AN OPERATIVE
STATUS OF A BASE GRID FOR NETWORK ANALYSIS
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.
FIELD OF INVENTION
15 [0002] The present disclosure generally relates to systems and methods for
grid creation in a wireless telecommunications network. More particularly, the
present disclosure relates to a system and a method for determining an operative
status of a base grid for network analysis and analyzing geographical locations.
DEFINITION
20 [003] As used in the present disclosure, the following terms are generally
intended to have the meaning as set forth below, except to the extent that the
context in which they are used to indicate otherwise.
[004] The expression ‘base grid (degree grid, a coordinate grid or a
latitude-longitude grid)’, used hereinafter in the specification refers to a system of
25 lines used to define and locate positions on the Earth's surface based on latitude
and longitude coordinates. The base grid is a reference framework that divides the
Earth's surface into a grid of horizontal lines (latitude) and vertical lines
(longitude) to establish precise locations. The base grid is a fundamental concept
3
in network design and refers to the underlying structure used to organize and
connect network devices. The base grid typically consists of a collection of
horizontal and vertical lines or segments, often arranged in a grid-like pattern, on
which various network elements such as routers, switches, and access points are
5 placed. The purpose of the base grid is to provide a scalable and organized way to
connect network devices and to facilitate efficient traffic flow.
[005] The expression ‘International Mobile Subscriber Identity (IMSI)’,
used hereinafter in the specification refers to a unique 15-digit number that
identifies every user in a Global System for Mobile communication (GSM) and
10 Universal Mobile Telecommunication system (UMTS) network.
[006] These definitions are in addition to those expressed in the art.
BACKGROUND OF THE INVENTION
[0007] The following description of the related art is intended to provide
background information pertaining to the field of the disclosure. This section may
15 include certain aspects of the art that may be related to various features of the
present disclosure. However, it should be appreciated that this section is used only
to enhance the understanding of the reader with respect to the present disclosure,
and not as admission of the prior art.
[0008] Traditional network planning often relies on static assumptions
20 about network usage patterns and traffic demands. Further, traditional network
planning may assume predictable traffic volumes and fixed user behaviour, which
may limit the ability to accurately anticipate and respond to dynamic changes in
network requirements. Traditional network planning methods may rely on
historical data or limited periodic measurements, which may not reflect real-time
25 network conditions. This may result in suboptimal network designs that do not
effectively address current or future demands. Traditional network planning may
be rigid and less adaptable to changing requirements or unforeseen events.
Traditional network planning is challenging to modify or expand the network
infrastructure once implemented, leading to potential inefficiencies and
4
difficulties in scaling the network to accommodate growth or evolving
technologies. Traditional network planning methods use coarse-grained spatial
models, assuming uniform network conditions across larger geographic areas.
This approach overlooked localized variations in demand, coverage, or capacity
5 requirements, resulting in suboptimal network designs at a more granular level.
[0009] Further, traditional network planning methods are not fully
considering the potential of emerging technologies and their impact on network
requirements. This may limit the ability to leverage innovative solutions or
optimize network designs to take advantage of advancements such as
10 virtualization, cloud computing, or software-defined networking. Traditional
network planning methods may involve limited stakeholder engagement,
excluding valuable insights and perspectives from end-users, service providers, or
other relevant parties. This may lead to network designs that do not align with
user needs or fail to consider specific requirements of different stakeholders.
15 Traditional network planning methods may not incorporate dynamic optimization
techniques that continuously monitor and adjust network configurations based on
real-time conditions. This may result in sub-optimal utilization of network
resources and inefficient allocation of capacity.
[0010] There is, therefore, a need in the art to provide a system and a
20 method that can mitigate the problems associated with the prior arts.
OBJECTS OF THE INVENTION
[0011] It is an object of the present disclosure to provide a system and a
method that is configured to perform accurate coverage analysis by overlaying
network coverage data and aid in identifying coverage gaps, dead zones, and areas
25 with weak signal strength, enabling network planners to optimize coverage and
improve service quality.
[0012] It is an object of the present disclosure to provide a system and a
method that helps in assessing network capacity requirements by analyzing
population density, traffic patterns, and user demands at different geographic
30 locations.
5
[0013] It is an object of the present disclosure to provide a system and a
method that assists in site selection for network infrastructure deployment and
help in identifying suitable locations that maximize coverage, minimize
interference, and comply with regulatory requirements.
5 [0014] It is an object of the present disclosure to provide a system and a
method that aids in optimizing network performance by analyzing network
parameters like signal strength, signal interference, and handover patterns in
different geographic areas.
[0015] It is an object of the present disclosure to provide a system and a
10 method that assists in strategic network expansion planning by identifying
underserved or unserved areas where network coverage can be extended to reach a
larger customer base.
[0016] It is an object of the present disclosure to provide a system and a
method that enables real-time network monitoring by integrating network
15 performance data with geographic information. I
[0017] It is an object of the present disclosure to provide a system and a
method that helps in visualizing network metrics on maps, identifying areas
experiencing service disruptions, and facilitate proactive troubleshooting and
maintenance.
20 SUMMARY
[0018] The present disclosure discloses a system for determining an
operative status of a base grid for network analysis. The system includes a server
and a processing unit. The server is configured to store a plurality of data samples
received from a plurality of user equipments residing in a geographic area defined
25 by a plurality of base grids. The processing unit is configured to cooperate with
the server to receive the plurality of data samples. The processing unit is further
configured to group the plurality of data samples into one or more groups based
on at least one of an international mobile subscriber identity (IMSI) level and a
map level. The processing unit is further configured to aggregate the plurality of
30 grouped data samples of each group corresponding to each radio-frequency (RF)
6
parameter of a set of RF parameters to determine a plurality of key performance
indicators (KPIs) corresponding to each base grid. The processing unit is further
configured to display the determined plurality of KPIs representing the operative
status of the base grid on a displaying screen.
5 [0019] In an embodiment, each of the plurality of base grids has a
predefined size.
[0020] In an embodiment, the displaying screen is a map application.
[0021] In an embodiment, the set of RF parameters includes a reference
signal received power (RSRP), a signal to noise interference ratio (SINR), a
10 reference signal received quality (RSRQ), and a throughput.
[0022] In an embodiment, the plurality of user equipments includes an
indoor user equipment, and an outdoor user equipment.
[0023] In an embodiment, for the IMSI level-based grouping, the
processing unit is configured to extract an international mobile subscriber identity
15 (IMSI) from the plurality of data samples associated with each of the user
equipment, group the plurality of data samples based on the extracted IMSI of
each user equipment on a predefined frequency to generate an IMSI wise data,
aggregate the IMSI wise data corresponding to each RF parameter of the set of RF
parameters to determine the plurality of KPIs for the extracted IMSI, and plot the
20 determined plurality of KPIs for the extracted IMSI on the map application.
[0024] In an embodiment, the server is configured to store the plurality of
received data samples for a predefined time along with a time stamp.
[0025] In an embodiment, the operative status is a congested status or a
non-congested status.
25 [0026] The present disclosure discloses a method of determining an
operative status of a base grid for network analysis. The method includes storing,
in a server, a plurality of data samples received from a plurality of user
equipments residing in a geographic area defined by a plurality of base grids. The
7
method includes grouping, by a processing unit, the plurality of data samples into
one or more groups based on at least one of an international mobile subscriber
identity (IMSI) level or a map level. The method includes aggregating the
plurality of grouped data samples of each group corresponding to each radio5 frequency (RF) parameter of a set of RF parameters to determine a plurality of
key performance indicators (KPIs) corresponding to each base grid. The method
includes displaying the generated plurality of KPIs representing the operative
status of the base grid on a displaying screen.
[0027] In an embodiment, for the IMSI level-based grouping the method
10 further comprising following steps extracting an international mobile subscriber
identity (IMSI) from the plurality of data samples associated with each of the user
equipment. The method includes grouping the plurality of data samples based on
the extracted IMSI of each user equipment on a predefined frequency to generate
an IMSI wise data. The method includes aggregating the IMSI wise data
15 corresponding to each radio-frequency (RF) parameter of the set of RF parameters
to determine the plurality of key performance indicators (KPIs) for the extracted
IMSI. The method includes plotting the determined plurality of KPIs for the
extracted IMSI on the map application.
[0028] In an embodiment, the method further comprising storing the
20 plurality of received data samples for a predefined time along with a time stamp.
[0029] In an embodiment, the operative status is a congested status, or a
non-congested status.
[0030] In an embodiment, the method further comprising aggregating data
on the IMSI level to provide a real time health state of each IMSI within the base
25 grid.
[0031] In an embodiment, the method further comprising summarizing
data on different levels, thereby reducing the number of data points to be
processed and displayed, resulting in improvement in performance and scalability.
8
[0032] In an embodiment, the health state includes an active state, an
inactive state, a barred state, and a roaming state.
[0033] In an embodiment, the method further comprising identifying a real
time issue with a specific user based on each IMSI based on the determined
5 plurality of KPIs.
[0034] In an embodiment, the real time issue includes a service
provisioning issue, a roaming related issue, a network congestion, and an
authentication failure issue.
[0035] The present disclosure discloses a user equipment (UE) configured
10 to determine an operative status of at least one base grid for network analysis. The
user equipment includes a processing unit, and a computer readable storage
medium storing programming instructions for execution by the processing unit.
Under the instructions, the processing unit is configured to store a plurality of data
samples received from a plurality of user equipments residing in a geographic area
15 defined by a plurality of base grids. Under the instructions, the processing unit is
configured to group the plurality of data samples into one or more groups based
on at least one of an international mobile subscriber identity (IMSI) level or a map
level. Under the instructions, the processing unit is configured to aggregate the
plurality of grouped data samples of each group corresponding to each radio20 frequency (RF) parameter of a set of RF parameters to determine a plurality of
key performance indicators (KPIs) corresponding to a base grid. Under the
instructions, the processing unit is configured to display the generated plurality of
KPIs representing an operative status of the base grid on a displaying screen.
BRIEF DESCRIPTION OF DRAWINGS
25 [0036] 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
parts throughout the different drawings. Components in the drawings are not
necessarily to scale, emphasis instead being placed upon clearly illustrating the
9
principles of the present disclosure. Some drawings may indicate the components
using block diagrams and may not represent the internal circuitry of each
component. It will be appreciated by those skilled in the art that disclosure of such
drawings includes the disclosure of electrical components, electronic components,
5 or circuitry commonly used to implement such components.
[0037] FIG. 1 illustrates an example network architecture for
implementing a system for determining an operative status of a base grid for
network analysis, in accordance with an embodiment of the present disclosure.
[0038] FIG. 2 illustrates an example block diagram of the system, in
10 accordance with an embodiment of the present disclosure.
[0039] FIG. 3 illustrates an example flow diagram illustrating steps
performed by the system, in accordance with an embodiment of the present
disclosure.
[0040] FIG. 4 illustrates an example representation of a map-based KPI
15 visualization for a reference signal received power (RSRP) layer, in accordance
with an embodiment of the present disclosure.
[0041] FIG. 5 illustrates an example representation of an international
mobile subscriber identity (IMSI) based RSRP layer, in accordance with an
embodiment of the present disclosure.
20 [0042] FIG. 6 illustrates an exemplary computer system in which or with
which the system may be implemented, in accordance with an embodiment of the
present disclosure.
[0043] FIG. 7 illustrates an example flow diagram illustrating steps of a
method of determining an operative status of a base grid for network analysis, in
25 accordance with an embodiment of the present disclosure.
[0044] The foregoing shall be more apparent from the following more
detailed description of the disclosure.
LIST OF REFERENCE NUMERALS
100 – Network Architecture
30 102-1, 102-2…102-N – Users
10
104-1, 104-2…104-N – User Equipments
108 – System
202 – Server
204 – Processing unit
5 206 – Memory
208 – A Plurality of Interfaces
210 – Database
212 – Data Parameter Engine
610 – External Storage Device
10 620 – Bus
630 – Main Memory
640 – Read Only Memory
650 – Mass Storage Device
660 – Communication Port
15 670 – Processor
BRIEF DESCRIPTION OF THE INVENTION
[0045] In the following description, for the purposes of explanation,
various specific details are set forth in order to provide a thorough understanding
of embodiments of the present disclosure. It will be apparent, however, that
20 embodiments of the present disclosure may be practiced without these specific
details. Several features described hereafter can each be used independently of
one another or with any combination of other features. An individual feature may
not address any of the problems discussed above or might address only some of
the problems discussed above. Some of the problems discussed above might not
25 be fully addressed by any of the features described herein. Example embodiments
of the present disclosure are described below, as illustrated in various drawings in
which like reference numerals refer to the same parts throughout the different
drawings.
[0046] The ensuing description provides exemplary embodiments only,
30 and is not intended to limit the scope, applicability, or configuration of the
11
disclosure. Rather, the ensuing description of the exemplary embodiments will
provide those skilled in the art with an enabling description for implementing an
exemplary embodiment. It should be understood that various changes may be
made in the function and arrangement of elements without departing from the
5 spirit and scope of the disclosure as set forth.
[0047] Specific details are given in the following description to provide a
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
these specific details. For example, circuits, systems, networks, processes, and
10 other components may be shown as components in block diagram form in order
not to obscure the embodiments in unnecessary detail. In other instances, wellknown circuits, processes, algorithms, structures, and techniques may be shown
without unnecessary detail in order to avoid obscuring the embodiments.
[0048] Also, it is noted that individual embodiments may be described as a
15 process that is depicted as a flowchart, a flow diagram, a data flow diagram, a
structure diagram, or a block diagram. Although a flowchart may describe the
operations as a sequential process, many of the operations can be performed in
parallel or concurrently. In addition, the order of the operations may be rearranged. A process is terminated when its operations are completed but could
20 have additional steps not included in a figure. A process may correspond to a
method, a function, a procedure, a subroutine, a subprogram, etc. When a process
corresponds to a function, its termination can correspond to a return of the
function to the calling function or the main function.
[0049] The word “exemplary” and/or “demonstrative” is used herein to
25 mean serving as an example, instance, or illustration. For the avoidance of doubt,
the subject matter disclosed herein is not limited by such examples. In addition,
any aspect or design described herein as “exemplary” and/or “demonstrative” is
not necessarily to be construed as preferred or advantageous over other aspects or
designs, nor is it meant to preclude equivalent exemplary structures and
30 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
12
either the detailed description or the claims, such terms are intended to be
inclusive like the term “comprising” as an open transition word without
precluding any additional or other elements.
[0050] Reference throughout this specification to “one embodiment” or
5 “an embodiment” or “an instance” or “one instance” means that a particular
feature, structure, or characteristic described in connection with the embodiment
is included in at least one embodiment of the present disclosure. Thus, the
appearances of the phrases “in one embodiment” or “in an embodiment” in
various places throughout this specification are not necessarily all referring to the
10 same embodiment. Furthermore, the particular features, structures, or
characteristics may be combined in any suitable manner in one or more
embodiments.
[0051] The terminology used herein is to describe particular embodiments
only and is not intended to be limiting the disclosure. As used herein, the singular
15 forms “a”, “an”, and “the” are intended to include the plural forms as well, unless
the context indicates otherwise. It will be further understood that the terms
“comprises” and/or “comprising,” when used in this specification, specify the
presence of stated features, integers, steps, operations, elements, and/or
components, but do not preclude the presence or addition of one or more other
20 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. It should be noted that the terms “mobile device”,
“user equipment”, “user device”, “communication device”, “device” and similar
terms are used interchangeably for the purpose of describing the invention. These
25 terms are not intended to limit the scope of the invention or imply any specific
functionality or limitations on the described embodiments. The use of these terms
is solely for convenience and clarity of description. The invention is not limited to
any particular type of device or equipment, and it should be understood that other
equivalent terms or variations thereof may be used interchangeably without
30 departing from the scope of the invention as defined herein.
13
[0052] As used herein, an “electronic device”, or “portable electronic
device”, or “user device” or “communication device” or “user equipment” or
“device” refers to any electrical, electronic, electromechanical, and computing
device. The user device is capable of receiving and/or transmitting one or
5 parameters, performing function/s, communicating with other user devices, and
transmitting data to the other user devices. The user equipment may have a
processor, a display, a memory, a battery, and an input-means such as a hard
keypad and/or a soft keypad. The user equipment may be capable of operating on
any radio access technology including but not limited to IP-enabled
10 communication, Zig Bee, Bluetooth, Bluetooth Low Energy, Near Field
Communication, Z-Wave, Wi-Fi, Wi-Fi direct, etc. For instance, the user
equipment may include, but not limited to, a mobile phone, smartphone, virtual
reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose
computer, desktop, personal digital assistant, tablet computer, mainframe
15 computer, or any other device as may be obvious to a person skilled in the art for
implementation of the features of the present disclosure.
[0053] Further, the user device may also comprise a “processor” or
“processing unit” includes processing unit, wherein processor refers to any logic
circuitry for processing instructions. The processor may be a general-purpose
20 processor, a special purpose processor, a conventional processor, a digital signal
processor, a plurality of microprocessors, one or more microprocessors in
association with a DSP core, a controller, a microcontroller, Application Specific
Integrated Circuits, Field Programmable Gate Array circuits, any other type of
integrated circuits, etc. The processor may perform signal coding data processing,
25 input/output processing, and/or any other functionality that enables the working of
the system according to the present disclosure. More specifically, the processor is
a hardware processor.
[0054] As portable electronic devices and wireless technologies continue
to improve and grow in popularity, the advancing wireless technologies for data
30 transfer are also expected to evolve and replace the older generations of
technologies. In the field of wireless data communications, the dynamic
14
advancement of various generations of cellular technology are also seen. The
development, in this respect, has been incremental in the order of second
generation (2G), third generation (3G), fourth generation (4G), and now fifth
generation (5G), and more such generations are expected to continue in the
5 forthcoming time.
[0055] While considerable emphasis has been placed herein on the
components and component parts of the preferred embodiments, it will be
appreciated that many embodiments can be made and that many changes can be
made in the preferred embodiments without departing from the principles of the
10 disclosure. These and other changes in the preferred embodiment as well as other
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 interpreted merely as illustrative of the disclosure and
not as a limitation.
15 [0056] At present, when planning a wireless network, there are several
coverage challenges that need to be considered. To plan a wireless network, a lot
of considerations and methods such as site survey, user requirements, capacity
planning, frequency planning are performed and considered. To date, in a wireless
communication system, a mobile station has been performing communication
20 with a base station that forms a cell in which the mobile station exists. The mobile
station changes a base station to another base station while moving in accordance
with the position thereof. However, at the time of design and displacement of a
base station, depending on transmission power and direction of an antenna, there
may arise an area (hereinafter referred to as a “coverage hole”) in which
25 communication quality of any base station does not reach a value that is allowed
to communicate with the mobile station. In order to detect a coverage hole or to
provide a continuous network coverage, a designer of a base station divides an
area into a plurality of grids (sub-areas) and sets up one evaluation point in each
of these grids. Next, the designer measures communication qualities of
30 neighbouring base stations at each of the evaluation points. Multiple iterations are
required with varying inputs to arrive at the best wireless network. This traditional
15
approach is manual, tedious, and poses several challenges. The general base grids
show the network capabilities but fail to address the issues faced by each
individual in a particular grid. Hence, a system and a method are required to
address the aforementioned issue.
5 [0057] The various embodiments throughout the disclosure will be
explained in more detail with reference to FIG. 1- FIG. 7.
[0058] FIG. 1 illustrates an example network architecture (100) for
implementing a system (referred as “system 108”) for determining an operative
status of a base grid for network analysis, in accordance with an embodiment of
10 the present disclosure. In an example, the operative status is a congested status, or
a non-congested status. In the context of a network, "congested status" typically
refers to a situation where there is an unusually high volume of traffic or demand
on the network resources, leading to degraded performance or service disruptions.
Conversely, a "non-congested status" implies that the network is operating within
15 normal parameters without significant traffic or capacity issues. The operative
status can be either congested or non-congested, depending on the current
condition of the network or system. If the network is experiencing congestion, the
operative status may be classified as congested. If there are no congestion issues
and the network is operating smoothly, the operative status would be considered
20 non-congested.
[0059] In an aspect, the congested state occurs during peak hours, when
there is a surge in call volume, a common occurrence during morning and evening
commutes or lunch breaks. This influx of calls strains network infrastructure like
base stations and switches, leading to congestion. Consequently, users may endure
25 call drops and degraded call quality, including static or echoes. Moreover, data
services suffer, with users experiencing slower speeds or difficulties accessing
online content. In densely populated areas, events such as concerts or emergencies
like natural disasters exacerbate congestion, overwhelming the network with
concentrated demand. The network's struggle to handle this surge impacts users,
30 making placing calls, sending messages, or accessing vital information
challenging.
16
[0060] In another aspect, the non-congested state occurs during off-peak
hours, typically late at night or early morning. In the non-congested state, the
network experiences a substantial reduction in traffic compared to peak times.
With fewer users active on the network, ample capacity exists within the
5 infrastructure to accommodate the decreased demand. Consequently, users enjoy
optimal call quality and data speeds during these periods, experiencing minimal
risk of congestion-related issues like call drops or slow internet speeds. Similarly,
in rural or less densely populated areas, mobile networks benefit from fewer
subscribers compared to urban centres.
10 [0061] As illustrated in FIG. 1, one or more computing devices (104-1,
104-2…104-N) may be connected to the system through a network (106). A
person of ordinary skill in the art will understand that the one or more computing
devices (104-1, 104-2…104-N) may be collectively referred as computing devices
(104) and individually referred as a computing device (104). One or more users
15 (102-1, 102-2…102-N) may provide one or more requests to the system (108). A
person of ordinary skill in the art will understand that the one or more users (102-
1, 102-2…102-N) may be collectively referred as users (102) and individually
referred as a user (102). Further, the computing devices (104) may also be referred
as a user equipment (UE) (104) or as UEs (104) throughout the disclosure.
20 [0062] In an embodiment, the computing device (104) may include, but
not be limited to, a mobile, a laptop, etc. Further, the computing device (104) may
include one or more in-built or externally coupled accessories including, but not
limited to, a visual aid device such as a camera, audio aid, microphone, or
keyboard. Furthermore, the computing device (104) may include a mobile phone,
25 smartphone, virtual reality (VR) devices, augmented reality (AR) devices, a
laptop, a general-purpose computer, a desktop, a personal digital assistant, a tablet
computer, and a mainframe computer. Additionally, input devices for receiving
input from the user (102) such as a touchpad, touch-enabled screen, electronic
pen, and the like may be used.
30 [0063] In an embodiment, the network (106) may include, by way of
example but not limitation, at least a portion of one or more networks having one
17
or more nodes that transmit, receive, forward, generate, buffer, store, route,
switch, process, or a combination thereof, etc. one or more messages, packets,
signals, waves, voltage or current levels, some combination thereof, or so forth.
The network (106) may also include, by way of example but not limitation, one or
5 more of a wireless network, a wired network, an internet, an intranet, a public
network, a private network, a packet-switched network, a circuit-switched
network, an ad hoc network, an infrastructure network, a Public-Switched
Telephone Network (PSTN), a cable network, a cellular network, a satellite
network, a fiber optic network, or some combination thereof.
10 [0064] In an embodiment, the system (108) is configured to receive a
plurality of data samples from the plurality of user equipments residing in a
residing in a geographic area. The geographic area is defined by a plurality of base
grids. In an aspect, each of the plurality of base grids has a predefined size (area).
In an aspect, the predefined size may be a 500 m² area. The predefined size is
15 configurable and may vary depending on the requirements of the network
providers. In 5G networks, the base grid is the arrangement of cell sites or base
stations that provide coverage and facilitate communication between multiple user
equipments and the network. The size of the base grid can vary depending on
factors such as population density, terrain, and network capacity requirements. In
20 areas with high population density and heavy network usage, such as urban areas,
the base grid might have smaller cell sizes to accommodate the high demand for
data and connectivity. The predefined size of the base grid in 5G networks can
vary based on the deployment strategy of the network operator and the
requirements of the specific area being covered. The plurality of data samples
25 (geo located data) may include details such as network traffic patterns,
international mobile subscriber identity (IMSI), packet headers, throughput rates,
latency measurements, error rates, device configurations, routing tables, reference
signal received power (RSRP), a signal to noise interference ratio (SINR), a
reference signal received quality (RSRQ), a throughput, Quality of Service (QoS)
30 parameters, throughput, a latitude, a longitude, network topology maps, security
logs, and performance metrics like upload speed and download speed. Analyzing
18
these data samples, the system enables network administrators and engineers to
identify bottlenecks, security threats, and performance issues and optimize
network efficiency and reliability. The system (108) is configured to group the
plurality of data samples into one or more groups based on at least one of an
5 international mobile subscriber identity (IMSI) level and a map level. After
grouping the plurality of data samples, the system (108) is configured to aggregate
the plurality of grouped data samples of each group corresponding to each radiofrequency (RF) parameter of a set of RF parameters to determine a plurality of
key performance indicators (KPIs) corresponding to each base grid. In an aspect,
10 the system (108) is configured to aggregate the received plurality of data samples
to generate a plurality of points such that at least one polygons representing a base
grid can be generated. In an example, the plurality of user equipments is an indoor
user equipment, and an outdoor user equipments. In an embodiment, the set of RF
parameters includes reference signal received power (RSRP), reference signal
15 received quality (RSRQ), received signal strength indicator (RSSI), signal to
interference noise ratio (SINR), throughput, channel quality index (CQI), physical
cell identity (PCI), block error ratio (BLER), downlink throughput, and uplink
throughput.
[0065] In an aspect, based on the received plurality of data samples, the
20 system is configured to define an area of each base grid. The system is configured
to group and aggregate data received from the plurality of user equipments into
one or more groups based on at least one of an international mobile subscriber
identity (IMSI) level and a map level. IIn an example, the system is configured to
divide the data into two groups further including a first group having RF attributes
25 (having RSRP, RSRQ, and SINR) and a second group having non-RF attributes
(throughput, latitude, and longitude).
[0066] Further, the system is configured to process the aggregated data to
generate the plurality of base grids including a plurality of key performance
indicators (KPIs)(also known as a plurality of key metrics). The plurality of key
30 metrics shows performance at different levels of granularity. The system is
19
configured to display the generated key metrics on a displaying screen. In an
aspect, the displaying screen is a map application.
[0067] In an embodiment, the system (108) extracts an IMSI based data
and a map-based data. Further, the system (108) receives the predefined grid size
5 based on a geographical area.
[0068] In an operative aspect, in the IMSI level-based aggregation
includes the data is aggregated IMSI wise for all RF attributes for each base grid
on a predefined frequency. Further, the aggregated data is plotted IMSI wise on a
map application.
10 [0069] In an embodiment, the IMSI data (data is aggregated IMSI wise)
include but not limited to RSRP, SINR, RSRQ, a throughput, a Latitude, and a
Longitude.
[0070] In an embodiment, the system (108) aggregates the IMSI based
data for at least one RF parameter associated with the predefined grid for a
15 predefined period. In an embodiment, the system (108) visualizes the IMSI based
data to identify quality and coverage issues associated with the geographical
location of the predefined grid. In an embodiment, the system (108) visualizes the
IMSI based data to determine a user experience associated with the one or more
users (102) during real-time.
20 [0071] In an embodiment, the system (108) is configured to employ base
data aggregation grouping. Data can be categorized and summarized using base
data aggregation grouping, which enables users to quickly comprehend important
metrics and analyze performance at varying levels of detail. Additionally, by
utilizing IMSI level identification and plotting, it is possible to identify real-time
25 issues with specific users, even if the network is functioning properly but the user
is facing multiple difficulties.
[0072] In an operative aspect, in the map level-based aggregation, the data
is aggregated for all RF attributes (RSRP, RSRQ, SINR) for each grid on the
predefined frequency. Further, the RF attributes aggregated data is plotted to
30 identify an area based on coverage and quality. In an example, the predefined
frequency is daily and a weekly level.
20
[0073] In an aspect, the system (108) provides an accurate coverage
analysis by overlaying a network coverage data with geographic features such as
terrain, buildings, and vegetation. The system (108) identifies coverage gaps, dead
zones, and areas with weak signal strength, enabling network planners to optimize
5 coverage and improve service quality.
[0074] In an embodiment, the system (108) is configured to determine
network capacity requirements by analyzing population density, traffic patterns,
and user demand at different geographic locations. The system (108) allows
network planners to identify high-traffic areas and allocate network resources
10 effectively to ensure optimal performance and avoid congestion.
[0075] In an embodiment, the system (108) is configured to assist in site
selection for network infrastructure deployment, such as cell towers or base
stations. The system (108) considers factors like population density, land use, road
networks, and existing infrastructure to identify suitable locations that maximize
15 coverage, minimize interference, and comply with regulatory requirements.
[0076] In an embodiment, the system (108) is configured to generate an
optimizing network performance by analyzing network parameters like signal
strength, signal interference, and handover patterns in different geographic areas.
The system (108) is configured to identify areas with suboptimal performance,
20 enabling network engineers to adjust and fine-tune network configurations for
improved service quality.
[0077] In an embodiment, the system (108) is configured to generate
strategic network expansion planning by identifying underserved or unserved
areas where network coverage can be extended to reach a larger customer base.
25 The system (108) is configured to utilize demographic data, population trends,
and market demand to guide network expansion strategies.
[0078] In an embodiment, the system (108) is configured to generate realtime network monitoring by integrating network performance data with
geographic information. The system (108) is configured to visualize network
30 metrics on maps, identify areas experiencing service disruptions, and facilitate
proactive troubleshooting and maintenance.
21
[0079] FIG. 2 illustrates an example block diagram (200) of the system
(108), in accordance with an embodiment of the present disclosure.
[0080] Referring to FIG. 2, in an embodiment, the system (108) includes a
server (202) and a processing unit (204).
5 [0081] The server (202) is configured to receive the plurality of data
samples from the plurality of user equipments residing in a geographic area. The
geographic area is defined by the plurality of base grids. In an example, each of
the plurality of base grids has a predefined size. In an embodiment, the plurality of
user equipments includes an indoor user equipment, and an outdoor user
10 equipment. In an aspect, the server (202) is configured to store the received
plurality of data samples in a database. In an aspect, the server (202) is configured
to store the plurality of data samples for a predefined time along with a time
stamp. In an example, the predefined time may lie in a range of 7-15 days.
[0082] The processing unit (204) is configured to cooperate with the server
15 (202) to receive the plurality of data samples. The processing unit (204) is further
configured to group the plurality of data samples into one or more groups. The
processing unit (204) is configured to group the plurality of data samples based on
an international mobile subscriber identity (IMSI) level, on a map level or a
combination thereof. The processing unit (204) is configured to aggregate the
20 plurality of grouped data samples of each group corresponding to each RF
parameter of a set of RF parameters. In an aspect, the set of RF parameters
includes a reference signal received power (RSRP), a signal to noise interference
ratio (SINR), a reference signal received quality (RSRQ), and a throughput. The
processing unit (204) is configured to aggregate the plurality of grouped data
25 samples corresponding to each RF parameter for determining the plurality of KPIs
corresponding to each base grid. The plurality of KPIs represents the operative
status of the base grid. The processing unit (204) is further configured to display
the determined plurality of KPIs a displaying screen. For example, the displaying
screen is a map application.
30 [0083] In an operative aspect, for the IMSI level-based grouping, the
processing unit (204) is configured to extract an international mobile subscriber
22
identity (IMSI) associated with each of the user equipment from the plurality of
data samples. After extracting the IMSI associated with each of the user
equipment, the processing unit (204) groups the plurality of data samples based on
the extracted IMSI of each user equipment on a predefined frequency to generate
5 an IMSI wise data. For example, for IMSI “qwe”, the processing unit (204)
groups all the data which are related to the IMSI “qwe”, thereby creating a
plurality of groups corresponding the plurality of groups based on the IMSI. The
processing unit (204) aggregates the IMSI wise data corresponding to each RF
parameter of the set of RF parameters to determine the plurality of KPIs for the
10 extracted IMSI. For example, for calculating a value for RSRP KPI corresponding
to a RSRP parameter, the processing unit (204) extracts a plurality of RSRP
values from the IMSI wise data (having plurality of data samples) and is further
configured to determine the value for RSRP KPI for applying at least one
mathematical operation on the plurality of extracted RSRP values. In an example,
15 the at least one mathematical operation is an average operation, a mean operation.
The processing unit (204) is configured to plot the determined plurality of KPIs
for the extracted IMSI on the map application.
[0084] The processing unit (204) is implemented as one or more
microprocessors, microcomputers, microcontrollers, digital signal processors,
20 central processing units, logic circuitries, and/or any devices that process data
based on operational instructions. Among other capabilities, the processing unit
(204) is configured to fetch and execute computer-readable instructions stored in a
memory (206) of the system (108). The memory (206) is configured to store one
or more computer-readable instructions or routines in a non-transitory computer
25 readable storage medium, which is fetched and executed to create or share data
packets over a network service. The memory (206) may comprise any nontransitory storage device including, for example, volatile memory such as randomaccess memory (RAM), or non-volatile memory such as erasable programmable
read only memory (EPROM), flash memory, and the like.
30 [0085] In an embodiment, the system (108) may include an interface(s)
(208). The interface(s) (208) may comprise a variety of interfaces, for example,
23
interfaces for data input and output devices (I/O), storage devices, and the like.
The interface(s) (208) may facilitate communication through the system (108).
The interface(s) (208) may also provide a communication pathway for one or
more components of the system (108). Examples of such components include, but
5 are not limited to, processing unit (204) and a database (210). Further, the
processing unit (204) may include a data parameter engine (212) and other
engine(s). In an embodiment, the other engine(s) may include, but not limited to, a
data ingestion engine, an input/output engine, and a notification engine.
[0086] In an embodiment, the processing unit (204) is implemented as a
10 combination of hardware and programming (for example, programmable
instructions) to implement one or more functionalities of the processing unit
(204). In examples described herein, such combinations of hardware and
programming is implemented in several different ways. For example, the
programming for the processing unit (204) is processor-executable instructions
15 stored on a non-transitory machine-readable storage medium and the hardware for
the processing unit (204) may comprise 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
the processing resource, implement the processing unit (204). In such examples,
20 the system (108) may comprise the machine-readable storage medium storing the
instructions and the processing resource to execute the instructions, or the
machine-readable storage medium is separate but accessible to the system (108)
and the processing resource. In other examples, the processing unit (204) is
implemented by electronic circuitry.
25 [0087] In an embodiment, the processing unit (204) receives an input via
the data parameter engine (212). The input is received from the one or more
computing devices (104) associated with the one or more users (102). The
processing unit (204) may store the input in the database (210). The input is based
on a network parameters associated with the computing device (104). The data
30 includes a plurality of aggregated RF parameters from the one or more users (102)
based on the predefined grid.
24
[0088] In an embodiment, the processing unit (204) extracts the IMSI
based data and the map-based data from the server (202).
[0089] In an embodiment, the data includes but not limited to a RSRP, a
signal to noise interference ratio (SINR), a reference signal received quality
5 (RSRQ), a throughput, a Latitude, and a Longitude.
[0090] In an embodiment, the processing unit (204) aggregates the IMSI
based data for one or more RF parameters associated with the predefined grid for
the predefined period.
[0091] In an embodiment, the processing unit (204) visualizes the IMSI
10 based data to identify quality and coverage issues associated with the
geographical location of the predefined grid.
[0092] In an embodiment, the processing unit (204) visualizes the IMSI
based data to determine a user experience associated with the one or more users
(102) during real-time.
15 [0093] Although FIG. 2 shows exemplary components of the system
(108), 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
20 performed by one or more other components of the system (108).
[0094] FIG. 3 illustrates an example flow diagram (300) illustrating steps
performed by the system (108), in accordance with an embodiment of the present
disclosure.
[0095] At step 302: The system (108) initializes a process for determining
25 an operative status of the base grid for network analysis. In an aspect, the process
includes a step of creating the plurality of base grids for degree grid
implementation and grid aggregation.
[0096] At step 304: The system (108) receives the plurality of data
samples (geo located data) of a particular user (based on IMSI) from the server
30 (202) associated with the user (102). In an example, the geo located data includes
25
RSRP, SINR, RSRQ, throughput, latitude, longitude, and events related to the
user equipment.
[0097] At step 306: The system (108) determines a grid geography in a
predefined size. In an example, the geographic area where the user resides is
5 defined by the plurality of base grids. In an example, a network area may be
divided into the plurality of base grids, where each base grid has a predefined size
(area).
[0098] At step 308: The system (108) aggregates the data (IMSI based
data) based on the IMSI for all RF parameters (RF attributes) for each base grid.
10 [0099] At step 310: The system (108) aggregates the map-based data for
all the RF attributes of each base grid.
[00100] At step 312: The system (108) aggregates the IMSI based data on
daily and a weekly level.
[00101] At step 314: The system (108) aggregates the map-based data on
15 daily and a weekly level.
[00102] At step 316: The system (108) plots the IMSI based data on a map
to check user experience on a daily and a weekly basis.
[00103] At step 318: The system (108) plots the RF attributes data (RSRP,
RSRQ, SINR) based on the map-based data to identify coverage and quality
20 issues area.
[00104] At step 320: The system (108) fills null grid (where no data
reported with the planning data) associated with the map-based data.
[00105] At step 322: The system (108) terminates the process associated
with the IMSI based data and the map-based data.
25 [00106] FIG. 4 illustrates an exemplary representation (400) of a map-based
KPI visualization for a reference signal received power (RSRP) layer, in
accordance with an embodiment of the present disclosure.
[00107] In an embodiment, the system (108) aggregates data using the
IMSI based data and the map-based data. As illustrated in FIG. 4, the system
30 (108) generates a map based on RF key performance indicators (KPIs) (RSRP,
RSRQ, SINR) where the map-based KPIs is aggregated to a predefined grid size.
26
Further, the system (108) uses the input data upon a non-availability of the data
for the null grids.
[00108] FIG. 5 illustrates an exemplary representation (500) of an
international mobile subscriber identity (IMSI) based RSRP layer, in accordance
5 with an embodiment of the present disclosure.
[00109] As illustrated in FIG. 5, in an embodiment, the system (108)
visualizes the IMSI based data for each predefined base grid. The data collected
for each predefined grid corresponding to the user equipment based on IMSI is
known as IMSI wise data. The IMSI wise data is further processed for generating
10 RF KPIs (Key Performance Indicators) and providing valuable insights into the
user experience journey. By utilizing the IMSI wise data, it is possible to plot the
user experience journey on the mapping application, as demonstrated in FIG.5. In
an embodiment, the aggregation of IMSI based data provides a real time health
status of each IMSI within the predefined grid. Further, the IMSI level
15 identification and plotting by the system (108) assists in identifying a real time
issue with the user (102).
[00110] FIG. 6 illustrates an example computer system (600) in which or
with which the embodiment of the present disclosure is implemented.
[00111] As shown in FIG. 6, the computer system (600) may include an
20 external storage device (610), a bus (620), a main memory (630), a read-only
memory (640), a mass storage device (650), a communication port(s) (660), and a
processor (670). A person skilled in the art will appreciate that the computer
system (600) may include more than one processor and communication ports. The
processor (670) may include various modules associated with embodiments of the
25 present disclosure. The communication port(s) (660) is 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 future ports. The communication ports(s) (660) is chosen depending on a
network, such as a Local Area Network (LAN), Wide Area Network (WAN), or
30 any network to which the computer system (600) connects.
27
[00112] In an embodiment, the main memory (630) is Random Access
Memory (RAM), or any other dynamic storage device commonly known in the
art. The read-only memory (640) is any static storage device(s) e.g., but not
limited to, a Programmable Read Only Memory (PROM) chip for storing static
5 information e.g., start-up or basic input/output system (BIOS) instructions for the
processor (670). The mass storage device (650) is 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
Advanced Technology Attachment (PATA) or Serial Advanced Technology
10 Attachment (SATA) hard disk drives or solid-state drives (internal or external,
e.g., having Universal Serial Bus (USB) and/or Firewire interfaces).
[00113] In an embodiment, the bus (620) may communicatively couple the
processor(s) (670) with the other memory, storage, and communication blocks.
The bus (620) is, e.g. a Peripheral Component Interconnect PCI) / PCI Extended
15 (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
(670) to the computer system (600).
[00114] In another embodiment, operator, and administrative interfaces,
20 e.g., a display, keyboard, and cursor control device may also be coupled to the bus
(620) to support direct operator interaction with the computer system (600). Other
operator and administrative interfaces can be provided through network
connections connected through the communication port(s) (660). Components
described above are meant only to exemplify various possibilities. In no way
25 should the aforementioned exemplary computer system (600) limit the scope of
the present disclosure.
[00115] FIG. 7 illustrates an example flow diagram illustrating steps of a
method (700) of determining the operative status of the base grid for network
analysis, in accordance with an embodiment of the present disclosure.
30 [00116] At step (702), the server (202) is configured to store the plurality of
data samples received from a plurality of user equipments residing in the
28
geographic area defined by the plurality of base grids. In an example, the plurality
of data samples includes various details associated with the user equipment and
the environment associated with the user equipment, such as network traffic
patterns, international mobile subscriber identity (IMSI), packet headers,
5 throughput rates, latency measurements, error rates, device configurations, routing
tables, RSRP, SINR, RSRQ, a throughput, QoS parameters, throughput, a latitude,
a longitude, upload speed, and download speed.
[00117] At step (704), the processing unit (204)is configured to group the
plurality of data samples into one or more groups based on at least one of an
10 international mobile subscriber identity (IMSI) level or a map level.
[00118] At step (706), the processing unit (204)is configured to aggregate
the plurality of grouped data samples of each group corresponding to each radiofrequency (RF) parameter of the set of RF parameters to determine the plurality of
key performance indicators (KPIs) corresponding to each base grid. For the IMSI
15 level-based grouping, the processing unit (204) is configured to extract the IMSI
from the plurality of data samples associated with each of the user equipment and
grouped the plurality of data samples based on the extracted IMSI of each user
equipment to generate an IMSI wise data. In an example, the processing unit
(204) is configured to group the data on a predefined frequency. In an example,
20 the predefined frequency is weekly or daily. The processing unit (204) is
configured to aggregate the IMSI wise data corresponding to each radio-frequency
(RF) parameter to determine the plurality of key performance indicators (KPIs)
for the extracted IMSI. The processing unit (204) is configured to plot the
determined plurality of KPIs for the extracted IMSI on the map application.
25 [00119] At step (708), the processing unit (204) is configured to display the
generated plurality of KPIs representing the operative status of the base grid on
the displaying screen.
29
[00120] In an embodiment, the method (700) further comprising storing the
plurality of received data samples for a predefined time along with a time stamp.
In an example, the predefined time may lie in a range of 7-15 days.
[00121] In an embodiment, the method includes a step of gathering data at
5 the International Mobile Subscriber Identity (IMSI) level to provide a real-time
health status of each IMSI within the base grid. This data includes information
about various network parameters such as signal strength, data usage, and call
quality. By collecting this data at the IMSI level, the method can identify and
isolate issues affecting individual users, enabling swift resolution of problems.
10 [00122] In another embodiment, the method includes a step of summarizing
data at various levels to reduce the number of data points that must be processed
and displayed, resulting in improved performance and scalability. This
summarization process involves aggregating data from individual IMSIs to higher
levels such as cell towers, clusters, or regions. By reducing the number of data
15 points, the method improves the efficiency of data processing and visualization. In
an example, the health status comprises various states such as an active state, an
inactive state, a barred state, and a roaming state. The active state indicates that
the user is currently using the network and has a valid subscription. The inactive
state indicates that the user has not used the network for a specified period and
20 may require reactivation. The barred state indicates that the user has been blocked
from accessing the network due to billing or security issues, and the roaming state
indicates that the user is currently using a network other than their home network.
In another embodiment, the method includes a step of identifying a real-time issue
with a specific user based on each IMSI, determined by a plurality of Key
25 Performance Indicators (KPIs). These KPIs include various network parameters
such as call drops, data throughput, and latency. By analyzing these KPIs, the
method can pinpoint the root cause of network issues affecting individual users,
enabling swift resolution of problems. In an example, the real-time issue may
include service provisioning issues, roaming-related issues, network congestion,
30 and authentication failures. Service provisioning issues may occur when a user
30
does not have the correct subscription or has exhausted their data quota. Roamingrelated issues may occur when a user travels and cannot access the network due to
a lack of roaming agreements. Network congestion may occur when the network
is unable to handle the volume of traffic, resulting in slow data speeds or dropped
5 calls. Authentication failures may occur when the user's identity cannot be
verified, preventing access to the network. By identifying these issues in realtime, the method can improve the overall reliability and performance of the
network.
[00123] In an aspect, the present disclosure discloses a user equipment (UE)
10 which is configured to determine the operative status of the base grid for network
analysis. The UE includes a processing unit, and a computer readable storage
medium storing programming instructions for execution by the processing unit.
Under the instructions, the processing unit is configured to store the plurality of
data samples received from the plurality of user equipments residing in the
15 geographic area defined by the plurality of base grids. Under the instructions, the
processing unit is configured to group the plurality of data samples into one or
more groups based on at least one of an international mobile subscriber identity
(IMSI) level or a map level. Under the instructions, the processing unit is
configured to aggregate the plurality of grouped data samples of each group
20 corresponding to each radio-frequency (RF) parameter of the set of RF parameters
to determine a plurality of key performance indicators (KPIs) corresponding to a
base grid. Under the instructions, the processing unit is configured to display the
generated plurality of KPIs representing an operative status of the base grid on a
displaying screen of the UE.
25 [00124] The present disclosure is configured to provide wireless network
planning and design of 5G networks. The system (108) can be extended to other
technologies as well such as Wi-Fi, and various areas where base grids are
required. The system (108) is helpful for telecom operators to assess and improve
network coverage and quality of service. It could aid in identifying areas with
30 poor coverage, both indoors and outdoors, and help plan for network optimization.
31
[00125] The method and system of the present disclosure may be
implemented in a number of ways. For example, the methods and systems of the
present disclosure may be implemented by software, hardware, firmware, or any
combination of software, hardware, and firmware. The above-described order for
5 the steps of the method is for illustration only, and the steps of the method of the
present disclosure are not limited to the order specifically described above unless
specifically stated otherwise. Further, in some embodiments, the present
disclosure may also be embodied as programs recorded in a recording medium,
the programs including machine-readable instructions for implementing the
10 methods according to the present disclosure. Thus, the present disclosure also
covers a recording medium storing a program for executing the method according
to the present disclosure.
[00126] While the foregoing describes various embodiments of the present
disclosure, other and further embodiments of the present disclosure may be
15 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 combined with information and knowledge available to the
20 person having ordinary skill in the art.
ADVANTAGES OF THE INVENTION
[00127] The present disclosure provides a system and a method that
provides valuable insights about a base grid regarding geographic distribution of
network usage, allowing for more accurate network planning and optimization.
25 [00128] The present disclosure provides a system and a method where a
base grid identifies areas with poor signal strength, coverage gaps, or high
interference thereby improving service quality, optimizing signal propagation, and
reducing dropped calls or data loss.
[00129] The present disclosure provides a system and a method that assists
30 in selecting optimal sites for network infrastructure deployment, such as towers,
32
base stations, or small cells. The system considers factors like population density,
terrain, and existing infrastructure, operators may strategically position network
assets to maximize coverage, minimize signal interference, and optimize network
capacity.
5 [00130] The present disclosure provides a system and a method where a
base grid enables operators to gain insights into the spatial distribution of their
customer base. This information can be used for targeted marketing campaigns,
personalized offers, and location-based services leading to customer satisfaction.
[00131] The present disclosure provides a system and a method where a
10 base grid provides real-time monitoring of network performance by integrating
geospatial data with network performance metrics and identifies areas
experiencing service degradation or congestion and prioritizes troubleshooting
efforts.
[00132] The present disclosure provides a system and a method where a
15 base grid helps optimize the allocation of network resources, such as spectrum,
bandwidth, and capacity. By understanding the spatial distribution of network
demands, operators may allocate resources based on actual usage patterns,
resulting in more efficient resource utilization, improved network efficiency, and
cost savings.
20 [00133] The present disclosure provides a system and a method where a
base grid provides operators with a competitive edge by enabling them to
understand their network coverage and performance in comparison to competitors.
By identifying areas of competitive advantage or weakness, operators can
strategically invest in network expansion, service enhancements, or targeted
25 marketing to gain market share and retain customers.
[00134] The present disclosure provides a system and a method where a
base grid allows for the consolidation and summarization of large volumes of data
into a structured format. The system simplifies data analysis process by providing
a concise overview of key metrics and trends at different levels of aggregation.
30 [00135] The present disclosure provides a system and a method where a
base grid provides a clear and organized representation of complex information
33
and promotes better data interpretation and facilitates decision-making based on
the summarized information.
[00136] The present disclosure provides a system and a method where a
hierarchical structure of an aggregated grouping of the base grid enables efficient
5 data navigation and exploration.
[00137] The present disclosure provides a system and a method where the
aggregated grouping of the base grid summarizes data at different levels of
aggregation, reduces the number of data points to be processed and displayed.
This improves performance and scalability, allowing users to analyze and
10 visualize large volumes of data efficiently.
[00138] The present disclosure provides a system and a method where the
aggregated grouping of the base grid offers customization options to tailor the
display and analysis based on specific requirements. Further, the system provides
flexibility to users to focus on relevant aspects of the data and adapt the base grid
15 to suit their analysis needs.
[00139] The present disclosure provides a system and a method where
aggregated grouping of the base grid provides a visually appealing and concise
representation of data, making it suitable for communication and presentation
purposes. Hence, the users may generate reports, dashboards, or visualizations
20 based on the aggregated base grid, facilitating data-driven communication to
stakeholders.

34
We Claim:
1 A system (108) for determining an operative status of a base grid for
network analysis, the system (108) comprising:
a server (202) configured to store a plurality of data samples
5 received from a plurality of user equipments residing in a geographic area
defined by a plurality of base grids; and
a processing unit (204) configured to cooperate with the server to
receive the plurality of data samples and is further configured to:
group the plurality of data samples into one or more groups
10 based on at least one of an international mobile subscriber identity
(IMSI) level and a map level;
aggregate the plurality of grouped data samples of each
group corresponding to each radio-frequency (RF) parameter of a
set of RF parameters to determine a plurality of key performance
15 indicators (KPIs) corresponding to each base grid; and
display the determined plurality of KPIs representing the
operative status of the base grid on a displaying screen.
2 The system (108) as claimed in claim 1, wherein each of the plurality of
base grids has a predefined size.
20 3 The system (108) as claimed in claim 1, wherein the displaying screen is a
map application.
4 The system (108) as claimed in claim 1, wherein the set of RF parameters
includes a reference signal received power (RSRP), a signal to noise
interference ratio (SINR), a reference signal received quality (RSRQ), and
25 a throughput.
5 The system (108) as claimed in claim 1, wherein the plurality of user
equipments includes an indoor user equipment, and an outdoor user
equipment.
35
6 The system (108) as claimed in claim 1, wherein for the IMSI level-based
grouping, the processing unit (204) is configured to:
extract an international mobile subscriber identity (IMSI)
associated with each of the user equipment from the plurality of data
5 samples;
group the plurality of data samples based on the extracted IMSI of
each user equipment on a predefined frequency to generate an IMSI wise
data;
aggregate the IMSI wise data corresponding to each RF parameter
10 of the set of RF parameters to determine the plurality of KPIs for the
extracted IMSI; and
plot the determined plurality of KPIs for the extracted IMSI on the
map application.
7 The system (108) as claimed in claim 1, wherein the server (202) is
15 configured to store the plurality of received data samples for a predefined
time along with a time stamp.
8 The system (108) as claimed in claim 1, wherein the operative status is a
congested status, or a non-congested status.
9 A method (700) of determining an operative status of a base grid for
20 network analysis, the method comprising:
storing (702), in a server, a plurality of data samples received from
a plurality of user equipments residing in a geographic area defined by a
plurality of base grids;
grouping (704), by a processing unit (204), the plurality of data
25 samples into one or more groups based on at least one of an international
mobile subscriber identity (IMSI) level or a map level;
36
aggregating (704), by the processing unit (204), the plurality of
grouped data samples of each group corresponding to each radiofrequency (RF) parameter of a set of RF parameters to determine a
plurality of key performance indicators (KPIs) corresponding to each base
5 grid; and
displaying (706), by the processing unit (204), the generated
plurality of KPIs representing the operative status of the base grid on a
displaying screen.
10 The method (700) as claimed in claim 9, further comprising following
10 steps for the IMSI level-based grouping:
extracting an international mobile subscriber identity (IMSI)
associated with each of the user equipment from the plurality of data
samples;
grouping the plurality of data samples based on the extracted IMSI
15 of each user equipment on a predefined frequency to generate an IMSI
wise data;
aggregating the IMSI wise data corresponding to each radiofrequency (RF) parameter of the set of RF parameters to determine the
plurality of key performance indicators (KPIs) for the extracted IMSI; and
20 plotting the determined plurality of KPIs for the extracted IMSI on
the map application.
11 The method (700) as claimed in claim 9, further comprising storing the
plurality of received data samples for a predefined time along with a time
stamp.
25 12 The method (700) as claimed in claim 9, wherein the operative status is a
congested status, or a non-congested status.
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13 The method (700), as claimed in claim 10, further comprising aggregating
data on the IMSI level to provide a real-time health state of each IMSI
within the base grid.
14 The method (700) as claimed in claim 10, further comprising summarizing
5 data on different levels, thereby reducing the number of data points to be
processed and displayed, resulting in improvement in performance and
scalability.
15 The method (700) as claimed in claim 13, wherein the health state includes
an active state, an inactive state, a barred state, and a roaming state.
10 16 The method (700), as claimed in claim 10, further comprising identifying a
real-time issue with a specific user based on each IMSI based on the
determined plurality of KPIs.
17 The method (700) as claimed in claim 16, wherein the real-time issue
includes a service provisioning issue, a roaming-related issue, network
15 congestion, and an authentication failure issue.
18 A user equipment (UE) configured to determine an operative status of a
base grid for network analysis, the UE comprising:
a processing unit; and
a computer readable storage medium storing programming
20 instructions for execution by the processing unit, the programming
including instructions to:
store a plurality of data samples received from a plurality of
user equipments residing in a geographic area defined by a
plurality of base grids;
25 group the plurality of data samples into one or more groups
based on at least one of an international mobile subscriber identity
(IMSI) level or a map level;
aggregate the plurality of grouped data samples of each
group corresponding to each radio-frequency (RF) parameter of a
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set of RF parameters to determine a plurality of key performance
indicators (KPIs) corresponding to a base grid; and
display the generated plurality of KPIs representing an
operative status of the base grid on a displaying screen.
5
10
Dated this 21 day of May 2024