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

METHOD AND SYSTEM FOR SIGNAL TO INTERFERENCE AND NOISE RATIO (SINR)
ESTIMATION IN CELLULAR NETWORKS
TECHNICAL FIELD
5
[001] Embodiments of the present disclosure generally relate to the field of wireless communication systems. In particular, the present disclosure relates to signal to interference and noise ratio. More particularly, the present disclosure relates to system and method for signal to interference and noise ratio (SINR) estimation in cellular networks. 10
BACKGROUND
[002] The following description of the 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
15 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 admissions of the prior art.
[003] Wireless communication technology has rapidly evolved over the past few decades, with each
20 generation bringing significant improvements and advancements. The first generation of wireless
communication technology was based on analog technology and offered only voice services. However, with the advent of the second-generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. The third-generation (3G) technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The
25 fourth-generation (4G) technology revolutionized wireless communication with faster data speeds,
better network coverage, and improved security. Currently, the fifth-generation (5G) technology is being deployed, promising even faster data speeds, low latency, and the ability to connect multiple devices simultaneously. With each generation, wireless communication technology has become more advanced, sophisticated, and capable of delivering more services to its users.
30
[004] Despite having multiple advancements in the wireless communication technology over the time, there are some issues that are to be resolved. One of the issue is a poor prediction of customer experience compared to the actual field data. The estimated customer experience tends to be worse than what is experienced in reality, leading to a discrepancy between the predicted and actual customer
35 satisfaction levels. Another issue is that some of the prior art often shows better SINR statistics for
indoor environments compared to outdoor environments. This contradicts the practical understanding that outdoor SINR is typically lower due to factors such as reflections and interference from multiple
2

cells. The existing solutions lacks effective filtering criteria for identifying actual interferers that
significantly impact the SINR. Existing methods based on signal strength are not suitable, leading to
poor SINR estimations. This hampers accurate analysis and decision-making in network planning,
thereby necessitating the need for alternative approaches. Better estimation of SINR is very crucial for
5 the 5G access network in order to identify the benefits of Beamforming and allows operator to do better
Heterogeneous network planning.
[005] Thus, there exists an imperative need in the art for system and method for signal to interference
and noise ratio estimation in cellular networks, that aims to provide more accurate SINR estimations,
10 closer alignment with actual customer experiences, and better differentiation between indoor and
outdoor SINR statistics.
SUMMARY
15 [006] This section is provided to introduce certain aspects of the present disclosure in a simplified
form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[007] An aspect of the present disclosure may relate to a method for signal to interference and noise
20 ratio (SINR) estimation in cellular networks. The method comprising defining, by a defining unit, a
calculation radius for filtering potential interfering signals from a set of cells of a plurality of cells that
are beyond the calculation radius. The method further comprises simulating, by a display unit, a cluster
area incorporating a geometrical details of one of an indoor building polygon and an outdoor area. The
method further comprises creating, by a creating unit, a buffer polygon around the indoor building
25 polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon. The
method further comprises determining, by a determining unit, a signal to interference plus noise ratio
(SINR) for outdoor area based on the defined calculation radius. The method further comprises
determining, by the determining unit, a set of Key Performance Indicator (KPI) statistics for the indoor
building polygon, the outdoor area, and the buffer zone. The method further comprises estimating, by
30 a processing unit, a SINR-based customer experience for the indoor building and the outdoor areas
based on the determined set of KPI statistics, the estimation is indicative of actual customer experience
for enhanced heterogeneous network planning.
[008] In an exemplary aspect of the present disclosure, the calculation radius is determined based on
35 an average inter-site distance among the plurality of cells within a cellular network cluster.
3

[009] In an exemplary aspect of the present disclosure, the buffer polygon is created at a predetermined distance from the indoor building polygon, said distance being selected to optimize the representation of outdoor user experience adjacent to the building structures.
5 [010] In an exemplary aspect of the present disclosure, the SINR and the set of KPI statistics
facilitates assessing, by the processing unit, a suitability of the buffer zone for a Fixed Wireless Services (FWS) deployment, based on a radio frequency (RF) quality just outside the building walls.
[011] In an exemplary aspect of the present disclosure, the method comprises generating, by a
10 generating unit, a result comparison table, wherein the result comparison table reflects the quality of a
RF signals in the indoor building polygon, the outdoor area, and the buffer polygon based on the
calculated SINR values.
[012] In an exemplary aspect of the present disclosure, the result comparison table comprises one or
more SINR values represented in decibels for the indoor building polygons, the outdoor areas, and the
15 buffer polygon.
[013] In an exemplary aspect of the present disclosure, determining, by the determining unit, a width of the buffer zone polygon is based at least on density of the indoor building polygon in the cellular network cluster.
20
[014] Another aspect of the present disclosure may relate to a system for signal to interference and noise ratio (SINR) estimation in cellular networks. The system comprises a defining unit configured to define a calculation radius for filtering potential interfering signals from a set of cells of a plurality of cells that are beyond the calculation radius. Further, the system comprises a display unit connected to
25 at least the defining unit, wherein the display unit is configured to simulate a cluster area incorporating
a geometrical details of an indoor building polygon and an outdoor area. Further, the system comprises a creating unit connected to at least the display unit, wherein the creating unit is connected to configured to create a buffer polygon around the indoor building polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon. Further, the system comprises a determining unit
30 connected to at least the creating unit, wherein the determining unit is configured to determine a signal
to interference plus noise ratio (SINR) for the outdoor area based on the defined calculation radius. Further, the determining unit is configured to determine a set of Key Performance Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the buffer zone. The system further comprises a processing unit connected to at least the determining unit, wherein the processing unit is
35 configured to estimate a SINR-based customer experience for the indoor building and the outdoor areas
based on the determined set of KPI statistics, the estimation is indicative of actual customer experience for enhanced heterogeneous network planning.
4

[015] Yet another aspect of the present disclosure may relate to a non-transitory computer readable
storage medium storing instructions for signal to interference and noise ratio (SINR) estimation in
cellular networks, the instructions include executable code which, when executed by a one or more units
5 of a system, causes: a defining unit of the system to define a calculation radius for filtering potential
interfering signals from a set of cells of a plurality of cells that are beyond the calculation radius; a display unit of the system to simulate a cluster area incorporating a geometrical details of an indoor building polygon and an outdoor area; a creating unit of the system to create a buffer polygon around the indoor building polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor
10 building polygon; a determining unit of the system to: determine a signal to interference plus noise ratio
(SINR) for the outdoor area based on the defined calculation radius, and determine a set of Key Performance Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the buffer zone; and a processing unit of the system to estimate a SINR-based customer experience for the indoor building and the outdoor areas based on the determined set of KPI statistics, the estimation is indicative
15 of actual customer experience for enhanced heterogeneous network planning.
[016] Yet another aspect of the present disclosure may relate to a user equipment (UE) for signal to interference and noise ratio (SINR) estimation in cellular networks. The UE comprises a defining unit to define a calculation radius for filtering potential interfering signals from a set of cells of a plurality
20 of cells that are beyond the calculation radius; a display unit to simulate a cluster area incorporating a
geometrical details of an indoor building polygon and an outdoor area; a creating unit to create a buffer polygon around the indoor building polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon; a determining unit to: determine a signal to interference plus noise ratio (SINR) for the outdoor area based on the defined calculation radius, and determine a set of
25 Key Performance Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the
buffer zone; and a processing unit to estimate a SINR-based customer experience for the indoor building and the outdoor areas based on the determined set of KPI statistics, the estimation is indicative of actual customer experience for enhanced heterogeneous network planning
30 OBJECTS OF THE INVENTION
[017] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.
35 [018] It is an object of the present disclosure to provide a system and method for SINR estimation in
cellular networks.
5

[019] It is another object of the present disclosure to provide a system and method for SINR
estimation in cellular networks that improve the estimation of Signal-to-Interference-plus-Noise Ratio
(SINR) for indoor and outdoor environments within 5G networks. By achieving closer estimations to
the actual SINR reported in the field, the invention aims to provide a more accurate representation of
5 the customer experience.
[020] It is another object of the present disclosure to provide a system and method for SINR
estimation in cellular networks that uses distance as a criterion to filter out the least impacting
interferers. This unique approach helps to overcome limitations of traditional methods and allows for
10 more accurate SINR calculations.
[021] It is another object of the present disclosure to provide a system and method for SINR
estimation in cellular networks that enhance SINR stats comparison by properly selecting the outdoor
area for evaluation. This is accomplished by creating a buffer area surrounding building polygons,
15 which provides a more precise reflection of the outdoor RF quality.
[022] It is yet another object of the present disclosure to provide a system and method for SINR estimation in cellular networks that seeks to help network operators in more efficient and effective heterogeneous network planning.
[023] It is yet another object of the invention, to provide outdoor Buffer surrounding areas of building polygon concept which is very helpful for 5G network in other analysis as well. Such as Fixed Wireless Access where the customer experience just outside of the building wall is required to Identify the buildings suitable for FWA deployment.
DESCRIPTION OF THE DRAWINGS
[024] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like
30 reference numerals refer to the same parts throughout the different drawings. Components in the
drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Also, the embodiments shown in the figures are not to be construed as limiting the disclosure, but the possible variants of the method and system according to the disclosure are illustrated herein to highlight the advantages of the disclosure. It will be appreciated by those skilled
35 in the art that disclosure of such drawings includes disclosure of electrical components or circuitry
commonly used to implement such components.
6

[025] Fig. 1 illustrates an exemplary scenario diagram for signal to interference and noise ratio (SINR) estimation in cellular networks, in accordance with exemplary embodiments of the present disclosure.
5 [026] Fig. 2 illustrates an exemplary block diagram of a computing device upon which the features
of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure.
[027] Fig. 3 illustrates an exemplary block diagram of a system [300] for signal to interference and
10 noise ratio (SINR) estimation in cellular networks, in accordance with exemplary implementations of
the present disclosure.
[028] Fig. 4 illustrates an image representation of an exemplary cluster area for signal to interference
and noise ratio (SINR) estimation in cellular networks, in accordance with an embodiment of the present
15 disclosure.
[029] Fig. 5 illustrates a method [500] flow diagram for signal to interference and noise ratio (SINR) estimation in cellular networks in accordance with exemplary implementations of the present disclosure. 20
[030] The foregoing shall be more apparent from the following more detailed description of the disclosure.
[031] DETAILED DESCRIPTION
25
[032] 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 embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter may each be used independently of one another or with any
30 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.
[033] 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
35 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 spirit and scope of the disclosure as set forth.
7

[034] 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, processes, and other
5 components may be shown as components in block diagram form in order not to obscure the
embodiments in unnecessary detail.
[035] Also, it is noted that individual embodiments may be described as a process which is depicted
as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although
10 a flowchart may describe the operations as a sequential process, many of the operations may be
performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure.
[036] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[037] As used herein, a “processing unit” or “processor” or “operating processor” includes one or more processors, wherein processor refers to any logic circuitry for processing instructions. A processor may be a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a (Digital Signal Processing) 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, input/output processing, and/or any other functionality that enables the working of the system according to the present disclosure. More specifically, the processor or processing unit is a hardware processor.
35 [038] As used herein, “a user equipment”, “a user device”, “a smart-user-device”, “a smart-device”,
“an electronic device”, “a mobile device”, “a handheld device”, “a wireless communication device”, “a mobile communication device”, “a communication device” may be any electrical, electronic and/or
8

computing device or equipment, capable of implementing the features of the present disclosure. The
user equipment/device may include, but is not limited to, a mobile phone, smart phone, laptop, a
general-purpose computer, desktop, personal digital assistant, tablet computer, wearable device or any
other computing device which is capable of implementing the features of the present disclosure. Also,
5 the user device may contain at least one input means configured to receive an input from at least one of
a transceiver unit, a processing unit, a storage unit, a detection unit and any other such unit(s) which are required to implement the features of the present disclosure.
[039] As used herein, “storage unit” or “memory unit” refers to a machine or computer-readable
10 medium including any mechanism for storing information in a form readable by a computer or similar
machine. For example, a computer-readable medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices or other types of machine-accessible storage media. The storage unit stores at least the data that may be required by one or more units of the system to perform their respective functions. 15
[040] As used herein “interface” or “user interface refers to a shared boundary across which two or
more separate components of a system exchange information or data. The interface may also be referred
to a set of rules or protocols that define communication or interaction of one or more modules or one
or more units with each other, which also includes the methods, functions, or procedures that may be
20 called.
[041] All modules, units, components used herein, unless explicitly excluded herein, may be software
modules or hardware processors, the processors being a general-purpose processor, a special purpose
processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors,
25 one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application
Specific Integrated Circuits (ASIC), Field Programmable Gate Array circuits (FPGA), any other type of integrated circuits, etc.
[042] As used herein the transceiver unit include at least one receiver and at least one transmitter
30 configured respectively for receiving and transmitting data, signals, information, or a combination
thereof between units/components within the system and/or connected with the system.
[043] As discussed in the background section, the current known solutions have several shortcomings.
The present disclosure aims to overcome the above-mentioned and other existing problems in this field
35 of technology by providing a solution for signal to interference and noise ratio (SINR) estimation in
cellular networks. As mentioned in the background, due to a poor prediction of customer experience compared to the actual field data. The estimated customer experience tends to be worse than what is
9

experienced in reality, leading to a discrepancy between the predicted and actual customer satisfaction
levels. Another issue is that the prior art often shows better SINR statistics for an indoor environments
compared to an outdoor environments. This contradicts the practical understanding that the outdoor
SINR is typically lower due to factors such as reflections and interference from multiple cells. The
5 existing solutions lacks effective filtering criteria for identifying actual interferers that significantly
impact the SINR. Existing methods based on signal strength are not suitable, necessitating the need for
alternative approaches. Further, proper selection of the target outdoor area for SINR statistics
comparison is challenging in the existing solution. The entire outdoor area is typically considered,
leading to the poor prediction of the SINR due to the inclusion of cell edges with a worst SINR. This
10 hampers accurate analysis and decision-making in network planning. The present disclosure aims to
provide a technically advanced solution for signal to interference and noise ratio estimation in cellular networks. More particularly, the present disclosure discloses a novel solution for SINR estimation in the cellular networks.
15 [044] The 5th generation core (5GC) network architecture includes a user equipment (UE), a radio
access network (RAN), an access and mobility management function (AMF), a Session Management Function (SMF), a Service Communication Proxy, an Authentication Server Function (AUSF), a Network Slice Specific Authentication and Authorization Function (NSSAAF), a Network Slice Selection Function (NSSF), a Network Exposure Function (NEF), a Network Repository Function
20 (NRF), a Policy Control Function (PCF), a Unified Data Management (UDM), an application function
(AF), a User Plane Function (UPF), a data network (DN).
[045] Radio Access Network (RAN) is the part of a mobile telecommunications system that connects
user equipment (UE) to the core network (CN) and provides access to different types of networks (e.g.,
25 5G network). It consists of radio base stations and the radio access technologies that enable wireless
communication.
[046] Access and Mobility Management Function (AMF) is a 5G core network function responsible
for managing access and mobility aspects, such as UE registration, connection, and reachability. It also
30 handles mobility management procedures like handovers and paging.
[047] Session Management Function (SMF) is a 5G core network function responsible for managing session-related aspects, such as establishing, modifying, and releasing sessions. It coordinates with the User Plane Function (UPF) for data forwarding and handles IP address allocation and QoS enforcement. 35
10

[048] Service Communication Proxy (SCP) is a network function in the 5G core network that facilitates communication between other network functions by providing a secure and efficient messaging service. It acts as a mediator for service-based interfaces.
5 [049] Authentication Server Function (AUSF) is a network function in the 5G core responsible for
authenticating UEs during registration and providing security services. It generates and verifies authentication vectors and tokens.
[050] Network Slice Specific Authentication and Authorization Function (NSSAAF) is a network
10 function that provides authentication and authorization services specific to network slices. It ensures
that UEs can access only the slices for which they are authorized.
[051] Network Slice Selection Function (NSSF) is a network function responsible for selecting the
appropriate network slice for a UE based on factors such as subscription, requested services, and
15 network policies.
[052] Network Exposure Function (NEF) is a network function that exposes capabilities and services of the 5G network to external applications, enabling integration with third-party services and applications. 20
[053] Network Repository Function (NRF) is a network function that acts as a central repository for information about available network functions and services. It facilitates the discovery and dynamic registration of network functions.
25 [054] Policy Control Function (PCF) is a network function responsible for policy control decisions,
such as QoS, charging, and access control, based on subscriber information and network policies.
[055] Unified Data Management (UDM) is a network function that centralizes the management of subscriber data, including authentication, authorization, and subscription information. 30
[056] Application Function (AF) is a network function that represents external applications interfacing with the 5G core network to access network capabilities and services.
[057] User Plane Function (UPF) is a network function responsible for handling user data traffic,
35 including packet routing, forwarding, and QoS enforcement.
11

[058] Data Network (DN) refers to a network that provides data services to user equipment (UE) in a telecommunications system. The data services may include but are not limited to Internet services, private data network related services.
5 [059] As depicted in Fig. 1, a user equipment may have a set of cells available in vicinity, i.e., 102A,
102B, 102C and 104. Further, in an event for estimating a SINR for a user's equipment (UE) [102] based on implementing the solution of the present disclosure as disclosed herein, a nearest cell (such as 104) may be selected, i.e., the radio node 204 may be selected as a serving node for the user equipment [102]. Thus, the cells (102A, 102B and 102C) would be identified as interfering nodes.
10
[060] Further, to estimate the SNIR for the UE [102] the present solution may utilise a technique wherein, the SINR is determined based on result of a predefined expression such as SINR= SINR Signal Power / Interference Power + Noise Power. The interference power includes signals from nearby cells i.e., 102A, 102B and 102C, added together.
15
[061] Thus, the present solution as disclosed herein provides filtering based on distance for estimating the SINR that is really close to what we actually experience so as to understand how good the network is for a user of the UE, whether they're inside or outside.
[062] Fig. 2 illustrates an exemplary block diagram of a computing device [1000] upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure. In an implementation, the computing device [1000] may also implement a method for signal to interference and noise ratio (SINR) estimation in cellular networks utilising a system. In another implementation, the computing device [1000] itself implements the method for signal to interference and noise ratio (SINR) estimation in cellular networks using one or more units configured within the computing device [1000], wherein said one or more units are capable of implementing the features as disclosed in the present disclosure.
[063] The computing device [1000] may include a bus [1002] or other communication mechanism
30 for communicating information, and a hardware processor [1004] coupled with the bus [1002] for
processing information. The hardware processor [1004] may be, for example, a general purpose
microprocessor. The computing device [1000] may also include a main memory [1006], such as a
random access memory (RAM), or other dynamic storage device, coupled to the bus [1002] for storing
information and instructions to be executed by the processor [1004]. The main memory [1006] also may
35 be used for storing temporary variables or other intermediate information during execution of the
instructions to be executed by the processor [1004]. Such instructions, when stored in non-transitory storage media accessible to the processor [1004], render the computing device [1000] into a special-12

purpose machine that is customized to perform the operations specified in the instructions. The computing device [1000] further includes a read only memory (ROM) [1008] or other static storage device coupled to the bus [1002] for storing static information and instructions for the processor [1004].
5 [064] A storage device [1010], such as a magnetic disk, optical disk, or solid-state drive is provided
and coupled to the bus [1002] for storing information and instructions. The computing device [1000] may be coupled via the bus [1002] to a display [1012], such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for displaying information to a computer user. An input device [1014], including alphanumeric and other keys, touch
10 screen input means, etc. may be coupled to the bus [1002] for communicating information and command
selections to the processor [1004]. Another type of user input device may be a cursor control [1016], such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor [1004], and for controlling cursor movement on the display [1012]. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second
15 axis (e.g., y), that allow the device to specify positions in a plane.
[065] The computing device [1000] may implement the techniques described herein using customized
hard-wired logic, one or more ASICs or FPGAs, firmware and/or program logic which in combination
with the computing device [1000] causes or programs the computing device [1000] to be a special-
20 purpose machine. According to one implementation, the techniques herein are performed by the
computing device [1000] in response to the processor [1004] executing one or more sequences of one
or more instructions contained in the main memory [1006]. Such instructions may be read into the main
memory [1006] from another storage medium, such as the storage device [1010]. Execution of the
sequences of instructions contained in the main memory [1006] causes the processor [1004] to perform
25 the process steps described herein. In alternative implementations of the present disclosure, hard-wired
circuitry may be used in place of or in combination with software instructions.
[066] The computing device [1000] also may include a communication interface [1018] coupled to the bus [1002]. The communication interface [1018] provides a two-way data communication coupling
30 to a network link [1020] that is connected to a local network [1022]. For example, the communication
interface [1018] may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface [1018] may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be
35 implemented. In any such implementation, the communication interface [1018] sends and receives
electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.
13

[067] The computing device [1000] can send messages and receive data, including program code,
through the network(s), the network link [1020] and the communication interface [1018]. In the Internet
example, a server [1030] might transmit a requested code for an application program through the
5 Internet [1028], the ISP [1026], the Host [1024], the local network [1022] and the communication
interface [1018]. The received code may be executed by the processor [1004] as it is received, and/or stored in the storage device [1010], or other non-volatile storage for later execution.
[068] FIG. 3 illustrates an exemplary block diagram of a system [300] for signal to interference and
10 noise ratio (SINR) estimation in cellular networks is shown, in accordance with the exemplary
implementations of the present disclosure. The system [300] comprises at least one defining unit [308],
at least one display unit [310], at least one creating unit [312], at least one determining unit [314], at
least one processing unit [316], and at least one generating unit [318]. Also, all of the components/ units
of the system [300] are assumed to be connected to each other unless otherwise indicated below. As
15 shown in the figures all units shown within the system should also be assumed to be connected to each
other. Also, in Fig. 1 only a few units are shown, however, the system [300] may comprise multiple
such units or the system [300] may comprise any such numbers of said units, as required to implement
the features of the present disclosure. Further, in an implementation, the system [300] may be present
in a user device to implement the features of the present disclosure. The system [300] may be a part of
20 the user device / or may be independent of but in communication with the user device (may also referred
herein as a UE). In another implementation, the system [300] may reside in a server [304] or a network entity. In yet another implementation, the system [300] may reside partly in the server [304]/ network entity and partly in the user device.
25 [069] The system [300] is configured for signal to interference and noise ratio (SINR) estimation in
cellular networks, with the help of the interconnection between the components/units of the system [300].
[070] Further, in accordance with the present disclosure, it is to be acknowledged that the
30 functionality described for the various the components/units can be implemented interchangeably.
While specific embodiments may disclose a particular functionality of these units for clarity, it is
recognized that various configurations and combinations thereof are within the scope of the disclosure.
The functionality of specific units as disclosed in the disclosure should not be construed as limiting the
scope of the present disclosure. Consequently, alternative arrangements and substitutions of units,
35 provided they achieve the intended functionality described herein, are considered to be encompassed
within the scope of the present disclosure.
14

[071] Further, the defining unit [308] is configured to define a calculation radius for filtering potential interfering signals from a set of cells of a plurality of cells that are beyond the calculation radius. Further, as disclosed in the present disclosure herein,the calculation radius is determined based on an average inter-site distance among the plurality of cells within a cellular network cluster. 5
[072] The present disclosure encompasses one or more tool or a combination of a set of tools, designed for heterogeneous network planning in the cellular network such as a 5G network environment. Here, the defining unit [308] may correspond to one or more processor, for defining the calculationradius. Further, the defining unit [308] may compute the calculation radius based on the
10 average inter-site distance among the cells within a network cluster. Further, the inter-site distance may
represent a separation between the adjacent cell sites within the network cluster. It is to be noted that the cellular network cluster disclosed here are referred to a group of neighboring cells that share common resources and operate within a specific geographical area. The calculation radius may correspond to a boundary, determining a set of neighbouring cells are only to be considered for
15 interference analysis. Also, the cells present outside the calculation radius are excluded from the
assessment.
[073] For example: While considering a specific geographical area with multiple cell towers, the
defining unit [308] calculates the radius around each cell tower, considering the average distance to
20 neighbouring towers. The defining unit [308] further incorporates a relevant cell tower falling within
the calculation radius for performing interfering signals analysis.
[074] The system [300] further comprises a display unit [310] connected to at least the defining unit
[308] where the display unit [310] is configured to simulate a cluster area incorporating a geometrical
25 details of an indoor building polygon and an outdoor area.
[075] The display unit [310] may visualize the entire cluster area, which incorporates both the indoor
building polygon and an outdoor spaces i.e., the outdoor area. The display unit [310] utilizes a set of
tools to generate or simulate, depicting an entire cluster i.e., the cluster area. The simulation mainly
30 incorporates the geometrical details of the indoor building polygon i.e., indoor building areas
represented as polygons and the outdoor area.
[076] The system [300] further comprises a creating unit [312] connected to at least the display unit
[310], where the creating unit [312] is configured to create a buffer polygon around the indoor building
35 polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon.
Further, the buffer polygon is created at a predetermined distance from the indoor building polygon,
15

said distance being selected to optimize the representation of outdoor user experience adjacent to the building structures.
[077] The creating unit [312] mentioned here corresponds to at least one or more processor,
5 configured to generate the buffer polygon around the indoor building polygon. The buffer polygon may
serve as a protective zone surrounding the indoor building polygon. Further, the creating unit [312]
calculates the buffer polygon by extending a fixed distance outward from edges of the indoor building
polygon. Further, calculating the buffer polygon as disclosed by the present disclosure assists in
managing interference and optimizing user experience. The fixed distance may correspond to a pre-
10 determined distance that may vary depending on one building structure to another. The primary purpose
of the buffer polygon is to optimize outdoor user experience adjacent to the building structures, ensuring
that users or a user equipment (UE) near the building structure may receive strong and reliable signals.
[078] The system [300] further comprises a determining unit [314] connected to at least the creating
15 unit [312], where the determining unit [314] is configured to determine a signal to interference plus
noise ratio (SINR) for the outdoor area based on the defined calculation radius.
[079] The determining unit [314] mentioned here correspond to at least one or more processor,
configure to determine the SINR for the outdoor area. It is to be noted that the signal to interference
20 plus noise ratio (SINR) is a measure that indicates the quality of signal in a wireless communication.
The SINR is the ratio of the power of a certain signal to the sum of power of interference signals and noise.
[080] The determining unit [314] calculates the SINR based on defined calculation radius, where the
25 calculation radius may correspond to a range within which a signal strength is measured. The
determining unit [314] here calculates the SINR based on a distance parameter relative to the user equipment location within the cluster.
[081] For example: In a crowded urban environment where multiple cell towers transmit signals, the
30 determining unit [314] calculates the SINR for a UE present in the outdoor area based on a distance
parameter of the particular UE with respect to a cell tower associated with the UE while also considering a neighboring cell interference and a background noise.
[082] Further, the determining unit [314] is configured to determine a width of the buffer zone
35 polygon based on at least on density of the indoor building polygon in the cellular network cluster.
16

[083] For example: in case of a shopping mall, the creating unit [312] deploys the buffer zones around
its entrance to provide better connectivity for the UE that are present on inside the mall as well as
present outside the mall. It is to be noted that the buffer is primarily based on population density around
a specific geographical area, as in a dense urban area, the buffer zone might be larger to accommodate
5 more users. Meanwhile, there may be a small buffer zone in rural areas.
[084] In context of the above-mentioned example, the width of the buffer zone polygon is determined
by the density of the indoor building polygon within the cellular network cluster, such as higher
building density may require wider buffers to accommodate more users. Therefore, the buffer width is
10 proportional to the number of indoor structures and their spatial distribution.
[085] For example: In a business area consisting of multiple tall buildings, the buffer width is adjusted to handle high user demand during peak working hours.
15 [086] The determining unit [314] is further configured to determine a set of Key Performance
Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the buffer zone.
[087] Also, the determining unit [314] is configured to determine a set of Key Performance Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the buffer zone. The KPI statistics
20 for the SINR values are weighted by factors such as the number of users, the type of service being
accessed, or the time of day to produce a more nuanced customer experience estimation. Also, the KPI statistics includes a signal strength, a data speed, and a latency for accessing a network performance. The KPI statistics may further include include metrics like a RSRP (Reference Signal Received Power) metric, a RSRQ (Reference Signal Received Quality) metric, and a throughput metric.
25
[088] For example: The determining unit [314] is connected to a server [304] and/or a network entity [306] and calculates the KPI statics along with the SINR for the indoor building polygon, the outdoor area, and the buffer zone polygon. Further, the overall KPI statics may provide valuable insights into the performance of the network in a particular area, enabling authorized personnel holding the server
30 [304] to make informed decisions about a network optimization.
[089] The system [300] further comprises a processing unit [316] connected to at least the
determining unit [314], where the processing unit [316] is configured to estimate a SINR-based
customer experience for the indoor building and the outdoor areas based on the determined set of KPI
35 statistics. Further, as disclosed in the present disclosure herein, the estimation is indicative of actual
customer experience for enhanced heterogeneous network planning.
17

[090] The processing unit [316] mentioned here corresponds to at least one or more processor
configured to estimate the SINR-based customer experience for the indoor building polygon, the
outdoor zone, and the buffer zone polygon. The estimation mentioned here is derived from the set of
KPI statistics determined earlier. Also, the estimation reflects the actual user perception of network
5 quality. The SINR-based estimation provides an indicative measure for actual customer experience. The
customer experience here refers to the quality of service perceived by the end-users of the network entity [306]. The customer experience is crucial for enhanced heterogeneous network planning.
[091] It is to be noted that a Heterogenous Networks (HetNets) are a type of network architecture that
10 combines different types of cells and wireless technologies to improve network performance and user
experience.
[092] For example: a network entity [306] utilizes the processing unit [316] to estimate the quality of
service in a residential area (indoor building polygon, the outdoor area, and the buffer zone polygon)
15 based on the SINR and the KPI statistics. This information further can be used to optimize the network
configuration for that area, such as adjusting the power levels of the base stations or deploying additional small cells.
[093] Furthermore, the processing unit [316] is configured to determine a suitability of the buffer
20 zone for a Fixed Wireless Services (FWS) deployment, based on a radio frequency (RF) quality just
outside the building walls.
[094] The processing unit [316] is also configured to assess the suitability of the buffer zone for deploying Fixed Wireless Services (FWS). This determination is based on the Radio Frequency (RF)
25 quality just outside the building walls. Also, the FWS refers to the delivery of internet connectivity and
communication services using wireless radio systems rather than traditional wired networks such as home broadband. The processing unit [316] may consider the RF quality just outside building walls to determine if the buffer zone is suitable for the FWS deployment. Further, the RF quality is possibly measured in terms of parameters like signal strength, interference levels, etc.
30
[095] For example: the network entity [306] may plan to offer the FWS in a certain locality, may utilize the processing unit [316] to assess the RF quality in the buffer zone around a building. If the RF quality is found to be good, the buffer zone could be considered suitable for the FWS deployment. This enables the network entity [306] to provide high-quality wireless internet services to the building's
35 occupants and the surrounding area.
18

[096] The system [300] further comprises a generating unit [318] connected at least with the
processing unit [316], where the generating unit [318] is configured generate a result comparison table,
wherein the result comparison the table reflects the quality of a RF signals in the indoor building
polygon, the outdoor area, and the buffer polygon based on the calculated SINR values. Also, the result
5 comparison table comprises one or more SINR values represented in decibels for the indoor building
polygons, the outdoor areas, and the buffer polygon.
[097] The generating unit [318] mentioned here may correspond to at least one or more processor
configured to produce the result comparison table. This result comparison table reflects quality of the
10 Radio Frequency (RF) signals in three distinct areas: the indoor building polygon, the outdoor area, and
the buffer polygon. The quality of these RF signals is determined based on the calculated Signal to Interference plus Noise Ratio (SINR) values. The higher SINR values generally correlate with better data rates and fewer dropped calls.
15 [098] Further, the result comparison table comprises the SINR values represented in decibels (dB)
for the indoor building polygons, the outdoor areas, and the buffer polygon. Decibels are a logarithmic unit used to express the ratio of two values of a physical quantity, often power and/or intensity. Representing SINR values in decibels provides an easy way to compare signal qualities, as the decibel scale corresponds more closely to the human perception of changes in signal strength.
20
[099] For example: In case, a particular network entity [306] desires to assess the performance of their network in a certain locality. The generating unit [318], along with the processing unit [316], determining unit [314] and others, connected to the base server [304], provides the comparison by calculating the SINR for the indoor building polygon, the outdoor area, and the buffer polygon. These
25 SINR values, represented in decibels, are then compiled into the result comparison table. The table
provide a clear and concise overview of the RF signal quality in different areas of the certain locality, thereby helping the network entity [306] to make informed decisions about network optimization or expansion. Such as, if the SINR values in the buffer polygon are found to be low, the network entity [306] might decide to deploy additional small cells in that area to improve signal quality.
30
[100] Now, referring to FIG. 4, illustrating an exemplary scenario diagram [400] for signal to interference and noise ratio (SINR) estimation in cellular networks, for estimating the Signal-to-Interference-plus-Noise Ratio (SINR) in a 5G network that closely aligns with the actual reported SINR, which is a key aspect in evaluating the indoor and outdoor user experience.
35
19

[101] FIG. 5 illustrates an image representation of an exemplary cluster area for signal to interference and noise ratio (SINR) estimation in cellular networks, in accordance with an embodiment of the present disclosure.
5 [102] As depicted by the Figure 4, in the exemplary cluster area simulated by the display unit [310]
based on implementing the solution of the present disclosure as disclosed herein. Further, as disclosed by the present disclosure the simulated cluster area incorporates a geometrical details of one of an indoor building polygon depicted as [401] in the fig.4, an outdoor area i.e., an outdoor building polygon depicted as [402] in the fig.4, and an open area depicted as [403] in the fig.4.
10
[103] FIG. 5 illustrates an exemplary method flow diagram [500] for signal to interference and noise ratio (SINR) estimation in cellular networks in accordance with exemplary implementations of the present disclosure is shown. In an implementation the method [500] is performed by the system [300]. Further, in an implementation, the system [300] may be present in a server [304] device to implement
15 the features of the present disclosure. Also, as shown in Figure 5, the method [500] starts at step [502]
and proceeds to step [504].
[104] At step [504], the method [500] comprises defining, by a defining unit [308], a calculation
radius for filtering potential interfering signals from a set of cells of a plurality of cells that are beyond
20 the calculation radius. Further, as disclosed in the present disclosure herein, the calculation radius is
determined based on an average inter-site distance among the plurality of cells within a cellular network cluster.
[105] The method [500] states that, the defining unit [308] determines the calculation radius within
25 which the neighbouring cells are considered for signal interference filtering. The calculation radius
defines the spatial scope for assessing interference and allows the defining unit [308] focus on nearby
cells that significantly impact the SINR. Further, post determining calculation radius, the defining unit
[308] identifies and filter out signals that might interfere with the desired signal. It is to be noted that
the filtering the interfering signals ensures that only relevant signals contribute to the SINR estimation
30 and exclude irrelevant interference.
[106] For example: In a network cluster with multiple base stations (cells). The defining unit [308]
calculates the radius based on the average inter-site distance among the base stations. If the base stations
are closely spaced (small inter-site distance), the radius will be smaller and if the base stations are
35 farther apart, the radius will be larger. Also, the nearby base stations may transmit signals on the same
frequency. The defining unit [308] filters out signals from distant base stations that have minimal impact on the SINR.
20

[107] Next, the method [500] further proceeds to step [506]. Further, at step [506], the method [500] comprises simulating, by a display unit [310], the cluster area incorporating the geometrical details of one of an indoor building polygon and an outdoor area. 5
[108] The method [500] states that, the display unit [310] visualizes an entire cluster area, which incorporates both indoor building polygons and outdoor spaces. The display unit [310] utilizes a set of tools to generate or simulate, depicting the entire cluster. The simulation mainly incorporates the geometrical details of indoor building areas represented as polygons and the outdoor areas.
10
[109] For example, in case of a mall, the display unit [310] distinguishes each shop, hallway, or restroom corresponds to an indoor polygon, while the outdoor area represents as the mall entrance and the adjacent parking spaces. Here the entire cluster is stated as a combination of the indoor polygons and the outdoor areas.
15
[110] Next, the method [500] further proceeds to step [508]. Further, at step [508], the method [500] comprises creating, by a creating unit [312], a buffer polygon around the indoor building polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon. Further, as disclosed in the present disclosure herein, the buffer polygon is created at a predetermined distance
20 from the indoor building polygon, said distance being selected to optimize the representation of outdoor
user experience adjacent to the building structures.
[111] The method [500] further states that, the creating unit [312] generates a buffer polygon around the indoor building polygon. The buffer polygon may serve as a protective zone surrounding the indoor
25 building. Further, the creating unit [312] calculates the buffer polygon by extending a fixed distance
outward from the edges of the indoor building polygon. Further, calculating the buffer polygon as disclosed by the present disclosure assists in managing interference and optimizing user experience. The fixed distance may correspond to a pre-determined distance that may vary depending on one building structure to another. The primary purpose of the buffer polygon is to optimize outdoor user
30 experience adjacent to the building structures, ensuring that users near the building structure may
receive strong and reliable signals.
[112] For example: in the case of a hospital building, the creating unit [312] deploys buffer zones
around its entrance to provide better connectivity for the users that are present on both inside and outside
35 the hospital building.
21

[113] Next, the method [500] further proceeds to step [510]. Further, at step [510], determining, by a determining unit [314], a signal to interference plus noise ratio (SINR) for outdoor area based on the defined calculation radius.
5 [114] The method [500] states that, the determining unit [314] determines a SINR for the outdoor
area. The signal to interference plus noise ratio (SINR) is a measure that indicates the quality of signal
in a wireless communication. The SINR is the ratio of the power of a certain signal to the sum of power
of interference signals and noise. The determining unit [314] calculates the SINR based on defined
calculation radius, where the calculation radius may correspond to a range within which the signal
10 strength is measured. The determining unit [314] here calculates the SINR based on a distance
parameter relative to the user equipment location within the cluster.
[115] For example: if a user equipment (UE) is trying to connect to a base station. The SINR reflects
how well the signal of the UE stands out against other signals i.e., the interfering signals and a noise. If
15 the SINR is high, the connection quality is excellent, and if low, the user on the UE may struggle to
communicate effectively.
[116] Further the method [500] comprises steps of determining, by the determining unit [314], a width
of the buffer zone polygon is based at least on density of the indoor building polygon in the cellular
20 network cluster.
[117] For example: in the case of a hospital, the creating unit [312] deploys the buffer zones around
their entrance to provide better connectivity for the UE that are present inside the hospital as well as
present outside the hospital. It is to be noted that the buffer is primarily based on population density
25 around a specific geographical area, as in a dense urban area, the buffer zone might be larger to
accommodate more users. Meanwhile, there may be a small buffer zone in rural areas.
[118] In context of the above-mentioned example, the width of the buffer zone polygon is determined
by the density of the indoor building polygon within the cellular network cluster, such as higher
30 building density may require wider buffers to accommodate more users. Therefore, the buffer width is
proportional to the number of indoor structures and their spatial distribution.
[119] Next, the method [500] further proceeds to step [512]. Further , at step [512], determining, by
the determining unit [314], a set of Key Performance Indicator (KPI) statistics for the indoor building
35 polygon, the outdoor area, and the buffer zone.
22

[120] The method [500] states that, the determining unit [314] determines the set of Key Performance
Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the buffer zone. The
KPI statistics for the SINR values are weighted by factors such as the number of users, the type of
service being accessed, or the time of day to produce a more nuanced customer experience estimation.
5 Also, the KPI statistics includes a signal strength, a data speed, and a latency for accessing the network
performance. The KPI statistics may further include include metrics like a RSRP (Reference Signal Received Power) metric, a RSRQ (Reference Signal Received Quality) metric, and a throughput metric.
[121] For example: the set of KPI statics may provide crucial information regrinding the performance
10 of a specific network over a specific area, which may allow the network operators to act accordingly.
[122] Further, as disclosed the method [500] may further utilise the determining unit [314] to
determine the width of the buffer zone polygon based at least on density of the indoor building polygon
in the cellular network cluster. The determining unit [314] to determine the width of the buffer zone
15 polygon ensures that the width of the buffer zone ensures minimum distances between buildings and/or
network elements. The buffer zone width may depend on the indoor building density. More densely populated areas may require wider buffers to prevent interference.
[123] For example, while placing a cell tower location, if an indoor building has densely populated
20 areas, a large buffer ensures better signal propagation without interferences from neighbouring
structures.
[124] Next, the method [500] further proceeds to step [514]. Further, at step [514], estimating, by a processing unit [316], a SINR-based customer experience for the indoor building and the outdoor areas
25 based on the determined set of KPI statistics. Further, as disclosed in the present disclosure herein, the
estimation is indicative of actual customer experience for enhanced heterogeneous network planning. Further, the SINR and the set of KPI statistics facilitates assessing, by the processing unit [316], a suitability of the buffer zone for a Fixed Wireless Services (FWS) deployment, based on a radio frequency (RF) quality just outside the building walls.
30
[125] The method [500] states that, the processing unit [316] estimates a SINR-based customer experience for indoor building polygon, the outdoor zone, and the buffer zone polygon. The estimation mentioned here is derived from the set of KPI statistics determined earlier. Also, the estimation reflects the actual user perception of a network quality. The SINR-based estimation provides an indicative
35 measure for the actual customer experience. The customer experience here refers to the quality of
service perceived by the end-users of the network entity [306]. The customer experience is crucial for enhanced heterogeneous network planning.
23

[126] It is to be noted that a Heterogenous Networks (HetNets) are a type of network architecture that combines different types of cells and wireless technologies to improve network performance and user experience. 5
[127] Further, as disclosed the method [500] may further utilise the processing unit [316] to access
the suitability of the buffer zone for deploying the Fixed Wireless Services (FWS). This determination
is based on the Radio Frequency (RF) quality just outside the building walls. Also, the FWS refers to
the delivery of internet connectivity and communication services using wireless radio systems rather
10 than traditional wired networks such as home broadband. The processing unit [316] considers the RF
quality just outside building walls to determine if the buffer zone is suitable for the FWS deployment. Further, the RF quality is possibly measured in terms of parameters like a signal strength parameter, an interference levels parameter, etc.
15 [128] For example: a network entity [306] utilizes the processing unit [316] to estimate the quality of
service in an industrial area (indoor building polygon, the outdoor zone, and the buffer zone polygon) based on the SINR and the KPI statistics. This information further can be used to optimize the network configuration for that area, such as adjusting power levels of base stations or deploying additional small cells.
20
[129] Also, if the network entity [306] may plan to offer the FWS in the same industrial area, then the network entity utilize the processing unit [316] to assess the RF quality in the buffer zone around the particular area. If the RF quality is found to be good, the buffer zone could be considered suitable for the FWS deployment. This enables the network entity [306] to provide high-quality wireless internet
25 services to the occupants and the surrounding area.
[130] The present disclosure also encompasses generating, by a generating unit [318], a result
comparison table, wherein the result comparison table reflects the quality of RF signals in the indoor
building polygon, the outdoor area, and the buffer polygon based on the calculated SINR values, the
30 result comparison table comprises one or more SINR values represented in decibels for the indoor
building polygons, the outdoor areas, and the buffer polygon.
[131] The method [500] states that, the result comparison table reflects the quality of the Radio
Frequency (RF) signals in three distinct areas: the indoor building polygon, the outdoor area, and the
35 buffer polygon. The quality of these RF signals is determined based on the calculated Signal to
Interference plus Noise Ratio (SINR) values. The higher SINR values generally correlate with better data rates and fewer dropped calls.
24

[132] Further, the result comparison table comprises SINR values represented in decibels (dB) for the
indoor Further, the result comparison table comprises the SINR values represented in decibels (dB) for
the indoor building polygons, the outdoor areas, and the buffer polygon. Decibels are a logarithmic unit
5 used to express the ratio of two values of a physical quantity, often power and/or intensity. Representing
SINR values in decibels provides an easy way to compare signal qualities, as the decibel scale corresponds more closely to the human perception of changes in signal strength.
[133] For example: In case, a particular network entity [306] desires to assess the performance of
10 their network in a certain locality. The generating unit [318], along with the processing unit [316],
determining unit [314] and others, connected to the base server [304], provides the comparison by
calculating the SINR for the indoor building polygon, the outdoor area, and the buffer polygon. These
SINR values, represented in decibels, are then compiled into the result comparison table. The table
provide a clear and concise overview of the RF signal quality in different areas of the certain locality,
15 thereby helping the network entity [306] to make informed decisions about network optimization or
expansion. Such as, if the SINR values in the buffer polygon are found to be low, the network entity [306] might decide to deploy additional small cells in that area to improve signal quality.
[134] Thereafter, the method [500] terminates at step [516].
20
[135] The present disclosure further discloses a non-transitory computer readable storage medium storing instructions for signal to interference and noise ratio (SINR) estimation in cellular networks, the instructions include executable code which, when executed by a one or more units of a system [300], causes: a defining unit [308] to define a calculation radius for filtering potential interfering signals from
25 a set of cells of a plurality of cells that are beyond the calculation radius; a display unit [310] to simulate
a cluster area incorporating a geometrical details of an indoor building polygon and an outdoor area; a creating unit [312] to create a buffer polygon around the indoor building polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon; a determining unit [314] to: determine a signal to interference plus noise ratio (SINR) for the outdoor area based on the defined
30 calculation radius, and determine a set of Key Performance Indicator (KPI) statistics for the indoor
building polygon, the outdoor area, and the buffer zone; and a processing unit [316] to estimate a SINR-based customer experience for the indoor building and the outdoor areas based on the determined set of KPI statistics, the estimation is indicative of actual customer experience for enhanced heterogeneous network planning.
35
[136] Also, the present disclosure discloses a user equipment (UE) [102] comprising a defining unit [308] configured to define a calculation radius for filtering potential interfering signals from a set of
25

cells of a plurality of cells that are beyond the calculation radius. A display unit [310] configured to
simulate a cluster area incorporating a geometrical details of an indoor building polygon and an outdoor
area. A creating unit [312] configured to create a buffer polygon around the indoor building polygon,
the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon. A
5 determining unit [314] configured to: 1) determine a signal to interference plus noise ratio (SINR) for
the outdoor area based on the defined calculation radius, and 2) determine a set of Key Performance
Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the buffer zone. At last,
a processing unit [316] configured to estimate a SINR-based customer experience for the indoor
building and the outdoor areas based on the determined set of KPI statistics, the estimation is indicative
10 of actual customer experience for enhanced heterogeneous network planning.
[137] As is evident from the above, the present disclosure provides a technically advanced solution for signal to interference and noise ratio (SINR) estimation in cellular networks. The present solution improves the estimation of Signal-to-Interference-plus-Noise Ratio (SINR) for indoor and outdoor
15 environments within 5G networks. By achieving closer estimations to the actual SINR reported in the
field, the invention aims to provide a more accurate representation of the customer experience. The present solution uses distance as a criterion to filter out the least impacting interferers. This unique approach helps to overcome limitations of traditional methods and allows for more accurate SINR calculations. Further, the present solution enhances the SINR stats comparison by properly selecting
20 the outdoor area for evaluation. This is accomplished by creating a buffer area surrounding building
polygons, which provides a more precise reflection of the outdoor RF quality. Further, the present solution seeks to help network operators in more efficient and effective heterogeneous network planning.
25 [138] While considerable emphasis has been placed herein on the disclosed implementations, it will
be appreciated that many implementations can be made and that many changes can be made to the implementations without departing from the principles of the present disclosure. These and other changes in the implementations of the present disclosure will be apparent to those skilled in the art, whereby it is to be understood that the foregoing descriptive matter to be implemented is illustrative
30 and non-limiting.
26

We Claim:
1. A method [500] for signal to interference and noise ratio (SINR) estimation in cellular networks,
5 the method [500] comprising the steps of:
- defining, by a defining unit [308], a calculation radius for filtering potential interfering signals from a set of cells of a plurality of cells that are beyond the calculation radius;
- simulating, by a display unit [310], a cluster area incorporating a geometrical details of one of an indoor building polygon and an outdoor area;
10 - creating, by a creating unit [312], a buffer polygon around the indoor building polygon, the
buffer polygon corresponds to a buffer zone surrounding the indoor building polygon;
- determining, by a determining unit [314], a signal to interference plus noise ratio (SINR) for
outdoor area based on the defined calculation radius;
- determining, by the determining unit [314], a set of Key Performance Indicator (KPI)
15 statistics for the indoor building polygon, the outdoor area, and the buffer zone; and
- estimating, by a processing unit [316], a SINR-based customer experience for the indoor
building and the outdoor areas based on the determined set of KPI statistics, the estimation
is indicative of actual customer experience for enhanced heterogeneous network planning.
20 2. The method [500] as claimed in claim 1, wherein the calculation radius is determined based on
an average inter-site distance among the plurality of cells within a cellular network cluster.
3. The method [500] as claimed in claim 1, wherein the buffer polygon is created at a predetermined
distance from the indoor building polygon, said distance being selected to optimize the
25 representation of outdoor user experience adjacent to the building structures.
4. The method [500] as claimed in claim 1, wherein the SINR and the set of KPI statistics facilitates
assessing, by the processing unit [316], a suitability of the buffer zone for a Fixed Wireless
Services (FWS) deployment, based on a radio frequency (RF) quality just outside the building
30 walls.
5. The method [500] as claimed in claim 1, wherein the method [500] comprises generating, by a
generating unit [318], a result comparison table, wherein the result comparison table reflects the
quality of a RF signals in the indoor building polygon, the outdoor area, and the buffer polygon
35 based on the calculated SINR values.
27

6. The method [500] as claimed in claim 5, wherein the result comparison table comprises one or
more SINR values represented in decibels for the indoor building polygons, the outdoor areas, and the buffer polygon.
5 7. The method [500] as claimed in claim 1, further comprises determining, by the determining unit
[314], a width of the buffer zone polygon is based at least on density of the indoor building polygon in the cellular network cluster.
8. A system [300] for signal to interference and noise ratio (SINR) estimation in cellular networks,
said system [300] comprising:
- a defining unit [308] configured to define a calculation radius for filtering potential interfering signals from a set of cells of a plurality of cells that are beyond the calculation radius;
- a display unit [310] connected to at least the defining unit [308], wherein the display unit [310] is configured to simulate a cluster area incorporating a geometrical details of an indoor building polygon and an outdoor area;
- a creating unit [312] connected to at least the display unit [310], wherein the creating unit [312] is connected to configured to create a buffer polygon around the indoor building polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building polygon;
- a determining unit [314] connected to at least the creating unit [312], wherein the determining unit [314] is configured to:

• determine a signal to interference plus noise ratio (SINR) for the outdoor area based on the defined calculation radius, and
• determine a set of Key Performance Indicator (KPI) statistics for the indoor building polygon, the outdoor area, and the buffer zone; and
- a processing unit [316] connected to at least the determining unit [314], wherein the
processing unit [316] is configured to estimate a SINR-based customer experience for the
indoor building and the outdoor areas based on the determined set of KPI statistics, the
estimation is indicative of actual customer experience for enhanced heterogeneous network
planning.
9. The system [300] as claimed in claim 8, wherein the calculation radius is determined based on
an average inter-site distance among the plurality of cells within a cellular network cluster.
35
28

10. The system [300] as claimed in claim 8, wherein the buffer polygon is created at a predetermined
distance from the indoor building polygon, said distance being selected to optimize the representation of outdoor user experience adjacent to the building structures.
5 11. The system [300] as claimed in claim 8, the processing unit [316] is configured to determine a
suitability of the buffer zone for a Fixed Wireless Services (FWS) deployment, based on a radio frequency (RF) quality just outside the building walls.
12. The system [300] as claimed in claim 8, wherein the system [300] comprises a generating unit
10 [318] configured to generate a result comparison table, wherein the result comparison table
reflects the quality of a RF signals in the indoor building polygon, the outdoor area, and the buffer polygon based on the calculated SINR values.
13. The system [300] as claimed in claim 12, wherein the result comparison table comprises one or
15 more SINR values represented in decibels for the indoor building polygons, the outdoor areas,
and the buffer polygon.
14. The system [300] as claimed in claim 8, wherein the determining unit [314] is further configured
to determine, a width of the buffer zone polygon is based at least on density of the indoor building
20 polygon in the cellular network cluster.
15. A user equipment (UE) comprises:
a defining unit [308] configured to define a calculation radius for filtering potential
interfering signals from a set of cells of a plurality of cells that are beyond the calculation
25 radius;
a display unit [310] configured to simulate a cluster area incorporating a geometrical details of an indoor building polygon and an outdoor area;
a creating unit [312] configured to create a buffer polygon around the indoor building
polygon, the buffer polygon corresponds to a buffer zone surrounding the indoor building
30 polygon;
a determining unit [314] configured to:
• determine a signal to interference plus noise ratio (SINR) for the outdoor area based
on the defined calculation radius, and
• determine a set of Key Performance Indicator (KPI) statistics for the indoor building
35 polygon, the outdoor area, and the buffer zone; and
a processing unit [316] configured to estimate a SINR-based customer experience for the indoor building and the outdoor areas based on the determined set of KPI statistics, the
29

estimation is indicative of actual customer experience for enhanced heterogeneous network planning.
Dated this 3rd day of July 2023
5 (GARIMA SAHNEY)
IN/PA-1826 AGENT FOR THE APPLICANT(S) OF SAIKRISHNA & ASSOCIATES
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