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 PROACTIVE INTERFERENCE MANAGEMENT IN A TELECOMMUNICATION NETWORK”
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.

5 METHOD AND SYSTEM FOR PROACTIVE INTERFERENCE MANAGEMENT IN
A TELECOMMUNICATION NETWORK
FIELD OF INVENTION
10 The present invention relates generally to the field of wireless communication systems. More particularly, the present invention relates to methods and systems for proactive interference management in a telecommunication network.
BACKGROUND
15
The following description of related art is intended to provide background information pertaining to the field of the invention. This section may include certain aspects of the art that may be related to various features of the present invention. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the
20 present invention, and not as admissions of prior art.
Wireless communication technology has rapidly evolved over the past few decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice
25 services. However, with the advent of the second-generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. Third generation (3G) technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth-generation (4G) technology revolutionized wireless communication with faster data speeds, better network coverage, and
30 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.
35 Despite the significant advancements in 5G technology, operators and service providers still face challenges in its implementation. One notable issue is tropospheric interference, which continues to pose a significant obstacle. The tropospheric interference is a major critical area for all operators as it gives major impact during the weather changes due to the tropospheric
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5 duct and that too for a very long distance up to 1000km. The tropospheric interference occurs when a Global Navigation Satellite Systems (GNSS) signal passes through troposphere which is a closest atmosphere to the Earth’s surface. Also, the troposphere may cause a delay in the GNSS signal, that results in a timing error. Further, this type of interference is particularly prevalent in regions with high humidity, such as near coastlines, and especially during adverse
10 weather conditions, such as heavy rain or snow.
There was a need in the state of the art to predict the tropospheric interference so that measures can be taken to rectify issues caused by such interference. Over the period of time, various solutions have been developed to improve the performance of communication devices and to
15 perform interference management in telecommunication network. However, there are certain challenges with existing solutions. The existing solutions for interference predictions in a network, in near real time lacks the precision, moreover the existing solutions fails to optimize a network performance as the existing solutions fails to provide a robust reliable communication infrastructure that can meet the evolving demands of modern
20 telecommunications hence there is a scope of further advancement.
Thus, there exists an imperative need in the art to perform proactive interference management in telecommunication network.
25 OBJECTS OF THE INVENTION
Some of the objects of the present invention, which at least one embodiment disclosed herein satisfies are listed herein below.
30 It is an object of the present invention to provide a system and a method for proactive interference management in telecommunication network.
It is another object of the present invention to provide a solution that helps to reduce the impact of interference well in advance causing no impact of interference on network in near real time 35 as well as customer experience.
3

5 It is yet another object of the present invention to provide a solution to perform predictive approach which gives the prediction of cells which has a high probability of becoming an aggressor cell and causing interference.
SUMMARY
10
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.
15 An aspect of the present disclosure relates to a method for proactive interference management in a telecommunication network. The method comprises receiving, by a receiving unit, a historical interference data on a periodic basis. Next, the method comprises processing, by a processing unit, the historical interference data to identify a pre-existing set of aggressor cells and a corresponding set of victim cells, based at least on a set of parameters. The method further
20 comprises determining, by a determination unit, an interference score corresponding to each pre-existing aggressor cell of the existing set of aggressor cells. The method further comprises filtering, by a filtering unit, a set of consistent aggressor cells and a corresponding set of victim cells from the pre-existing set of aggressor cells based at least on a configuration and the determined interference score. The method further comprising extracting, by an image
25 extraction unit, a set of images from a map depicting a forecast for a tropospheric ducting for a first pre-defined time period. Further, the method comprises overlaying, by a visual representation unit, the set of consistent aggressor cells and the corresponding set of victim cells on the extracted set of images to create a visual representation.
30 In an exemplary aspect of the present disclosure, the set of parameters comprises at least one of distance of the set of pre-existing aggressor cells from the corresponding set of victim cells and a confidence level threshold.
In an exemplary aspect of the present disclosure, the interference score is determined based at 35 least on a count of a set of victim cells associated with each of the set of pre-existing aggressor cells and interference consistency caused for at least a second pre-defined time period.
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5 In an exemplary aspect of the present disclosure, the method further comprising predicting, by a prediction unit using a trained model, the set of candidate aggressor cells and the corresponding set of victim cells based at least on processing of the visual representation.
In an exemplary aspect of the present disclosure, the method further comprising performing, 10 by the processing unit, down-tilting of the predicted set of candidate aggressor cells and the corresponding set of victim cells utilizing an Upper Side Lobe Suppression (USLS).
Another aspect of the present disclosure relates to a system for proactive interference management in a telecommunication network. The system comprises of a receiving unit,
15 configured to receive a historical interference data on a periodic basis. The system further comprises a processing unit connected at least with the receiving unit and the processing unit is configured to process the historical interference data to identify a pre-existing set of aggressor cells and a corresponding set of victim cells, based at least on a set of parameters. The system further comprises a determination unit connected at least with the processing unit,
20 and the determination unit is configured to determine an interference score corresponding to each pre-existing aggressor cell of the existing set of aggressor cells. The system further comprises a filtering unit connected at least with the determination unit and the filtering unit is configured to filter a set of consistent aggressor cells and corresponding set of victim cells from the pre-existing set of aggressor cells based at least on a configuration and the determined
25 interference score. The system further comprises an image extraction unit connected at least with the filtering unit and the image extraction unit is configured to extract a set of images from a map depicting forecast for a tropospheric ducting for a first pre-defined time period. The system further comprises a visual representation unit connected at least with the image extraction unit and the visual representation unit is configured to overlay the set of consistent
30 aggressor cells and the corresponding set of victim cells on the extracted set of images to create a visual representation.
Yet another aspect of the present disclosure may relate to a non-transitory computer readable storage medium storing instruction for proactive interference management in a 35 telecommunication network. The instructions include an executable code which, when executed by one or more units of the system, causes a transceiver unit to receive a historical interference data on a periodic basis; a processing unit to process the historical interference data to identify a pre-existing set of aggressor cells and a corresponding set of victim cells,
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5 based at least on a set of parameters; a determination unit to determine an interference score corresponding to each pre-existing aggressor cell of the existing set of aggressor cells; a filtering unit to filter a set of consistent aggressor cells and corresponding set of victim cells from the pre-existing set of aggressor cells based at least on a configuration and the determined interference score; an image extraction unit to extract a set of images from a map depicting
10 forecast for a tropospheric ducting for a first pre-defined time period; and a visual representation unit to overlay the set of consistent aggressor cells and the corresponding set of victim cells on the extracted set of images to create a visual representation.
BRIEF DESCRIPTION OF DRAWINGS
15
The accompanying drawings, which are incorporated herein, and constitute a part of this invention, illustrate exemplary embodiments of the disclosed methods and systems in 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
20 illustrating the principles of the present invention. 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 invention of such drawings includes invention of electrical components, electronic components or circuitry commonly used to implement such components.
25
FIG. 1 illustrates an exemplary block diagram [100] representation of 5th generation core (5GC) network architecture.
FIG.2A illustrates an exemplary block diagram of a system [200] for proactive interference 30 management in telecommunication network, in accordance with exemplary embodiments of the present invention.
FIG.2B illustrates an exemplary implementation of a system [200] for proactive interference management in telecommunication network, in accordance with exemplary embodiments of 35 the present invention.
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5 FIG.3 illustrates an exemplary method [300] flow diagram indicating the process for proactive interference management in telecommunication network, in accordance with exemplary embodiments of the present invention.
FIG. 4 illustrates an exemplary block diagram of a computing device [1000] upon which one 10 or more embodiments of the present disclosure may be implemented.
The foregoing shall be more apparent from the following more detailed description of the invention.
15 DETAILED DESCRIPTION
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 invention. It will be apparent, however, that embodiments of the present disclosure may be practiced without
20 these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein. Example embodiments of the present disclosure are described below,
25 as illustrated in various drawings in which like reference numerals refer to the same parts throughout the different drawings.
The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the invention. Rather, the ensuing description of the 30 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 spirit and scope of the invention as set forth. It should be 35 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 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
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5 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 departing from the scope of the invention as defined herein.
10 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 other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-15 known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
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. 20 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 re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure.
25 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
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 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.
35 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 parameters, performing function/s, communicating with other user devices
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5 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 communication, Zig Bee, Bluetooth, Bluetooth Low Energy, Near Field Communication, Z-Wave, Wi-Fi, Wi-Fi direct, etc. For instance, the user equipment may
10 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 computer, or any other device as may be obvious to a person skilled in the art for implementation of the features of the present invention.
15 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 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
20 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 invention. More specifically, the processor is a hardware processor.
25 As portable electronic devices and wireless technologies continue to improve and grow in popularity, the advancing wireless technologies for data transfer are also expected to evolve and replace the older generations of technologies. In the field of wireless data communications, the dynamic advancement of various generations of cellular technology are also seen. The development, in this respect, has been incremental in the order of second generation (2G), third
30 generation (3G), fourth generation (4G), and now fifth generation (5G), and more such generations are expected to continue in the forthcoming time.
One or more modules, units, components (including but not limited to processing unit, determination unit, filtering unit, image extraction unit, visual representation unit, prediction 35 unit) used herein may be software modules configured via hardware modules/processor, or hardware processors, the processors being a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller,
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5 Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc.
As discussed in the background section that tropospheric interference occurs when a Global Navigation Satellite Systems (GNSS) signal passes through troposphere which is a closest
10 atmosphere to the Earth’s surface. Also, the troposphere causes a delay in the GNSS signal, that results in a timing error. Further, over the period of time various solutions have been developed to improve the performance of communication devices and to perform interference management in telecommunication network. However, there are certain challenges with existing solutions. The existing solutions for interference predictions in a network, in near real
15 time, lacks the precision.
The present disclosure aims to overcome the above-mentioned and other existing problems in this field of technology by performing predictive approach which gives the prediction of cells that have a high probability of becoming aggressor cells and causing interference. The present
20 disclosure helps operators to act on interfering cells proactively to minimize the impact of interference. The present disclosure predicts the aggressors using previously reported consistent aggressors and image processing which provides the prediction of possible interference areas. Post identification of the probable aggressor s , t he p res en t d i sc lo s ur e i n i t i a t e s the down tilting of those aggressors using USLS (Upper side lobe suppression) to ensure the
25 power radiated above the horizon is minimal which ultimately helps to reduce the impact of interference well in advance causing no impact of interference on network as well as customer experience.
Hereinafter, exemplary embodiments of the present disclosure will be described with reference 30 to the accompanying drawings.
FIG. 1 illustrates an exemplary block diagram representation of 5th generation core (5GC) network architecture, in accordance with exemplary embodiment of the present disclosure. As shown in FIG. 1, the 5GC network architecture [100] includes a user equipment (UE) [102], a 35 radio access network (RAN) [104], an access and mobility management function (AMF) [106], a Session Management Function (SMF) [108], a Service Communication Proxy (SCP) [110], an Authentication Server Function (AUSF) [112], a Network Slice Specific Authentication and Authorization Function (NSSAAF) [114], a Network Slice Selection Function (NSSF) [116], a
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5 Network Exposure Function (NEF) [118], a Network Repository Function (NRF) [120], a Policy Control Function (PCF) [122], a Unified Data Management (UDM) [124], an application function (AF) [126], a User Plane Function (UPF) [128], a data network (DN) [130], wherein all the components are assumed to be connected to each other in a manner as obvious to the person skilled in the art for implementing features of the present disclosure.
10
Radio Access Network (RAN) [104] is the part of a mobile telecommunications system that connects user equipment (UE) [102] to the core network (CN) and provides access to different types of networks (e.g., 5G network). It consists of radio base stations and the radio access technologies that enable wireless communication.
15
Access and Mobility Management Function (AMF) [106] is a 5G core network function responsible for managing access and mobility aspects, such as UE registration, connection, and reachability. It also handles mobility management procedures like handovers and paging.
20 Session Management Function (SMF) [108] 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.
25 Service Communication Proxy (SCP) [110] 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.
Authentication Server Function (AUSF) [112] is a network function in the 5G core responsible 30 for authenticating UEs during registration and providing security services. It generates and verifies authentication vectors and tokens.
Network Slice Specific Authentication and Authorization Function (NSSAAF) [114] is a network function that provides authentication and authorization services specific to network 35 slices. It ensures that UEs can access only the slices for which they are authorized.
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5 Network Slice Selection Function (NSSF) [116] is a network function responsible for selecting the appropriate network slice for a UE based on factors such as subscription, requested services, and network policies.
Network Exposure Function (NEF) [118] is a network function that exposes capabilities and 10 services of the 5G network to external applications, enabling integration with third-party services and applications.
Network Repository Function (NRF) [120] is a network function that acts as a central repository for information about available network functions and services. It facilitates the 15 discovery and dynamic registration of network functions.
Policy Control Function (PCF) [122] is a network function responsible for policy control decisions, such as QoS, charging, and access control, based on subscriber information and network policies. 20
Unified Data Management (UDM) [124] is a network function that centralizes the management of subscriber data, including authentication, authorization, and subscription information.
Application Function (AF) [126] is a network function that represents external applications 25 interfacing with the 5G core network to access network capabilities and services.
User Plane Function (UPF) [128] is a network function responsible for handling user data traffic, including packet routing, forwarding, and QoS enforcement.
30 Data Network (DN) [130] 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.
Referring to FIG. 2A, an exemplary block diagram of a system [200] for proactive interference 35 management in a telecommunication network is depicted. The system [200] comprises at least a transceiver unit [202], at least a processing unit [204], at least a determination unit [206], at least a filtering unit [208], at least an image extraction unit [210], at least a visual representation unit [212], a prediction unit [214] and a storage unit [216]. Also, in FIG. 2 only a few units are
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5 shown, however, the system [200] may comprise multiple such units or the system [200] may comprise any such numbers of said units, as required to implement the features of the present invention. For ease of reference, FIG. 2A depicts units/components of the system [200] by way of representation of blocks and FIG. 2A do not represent the internal circuitry or connections of each component/unit of the system [200]. It will be appreciated by those skilled in the art
10 that disclosure of such drawings/block diagrams includes disclosure of electrical components and connections between said electronic components, and electronic components or circuitry commonly used to implement such components.
Further, in accordance with the present disclosure, it is to be acknowledged that the 15 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, 20 alternative arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.
Additionally, the processing unit [204], the determination unit [206], the filtering unit [208], 25 the image extraction unit [210], the visual representation unit [212] and the prediction unit [214] are processors. The processor may be a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a DSP (digital signal processor) core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable 30 Gate Array circuits, any other type of integrated circuits, etc.
Also, the transceiver unit [202] includes a transmitter having capabilities to transmit data/signals and optionally also a receiver unit having capabilities to receive data/signals.
35 The system [200] is configured to perform proactive interference management in a telecommunication network, such as the 5G network depicted in Fig. 1.
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5 In order to provide proactive interference management in the telecommunication network, the transceiver unit [202] is configured to receive a historical interference data on a periodic basis (for e.g., last 30 days). The historical interference data is the data associated with one or more cells in the telecommunication network and the historical interference data is a record of past instances of interference within the telecommunication network. Further the historical
10 interference data may include a plurality of data such as timestamps, interference type, severity, location, etc. Additionally, the historical interference data is received in the periodic basis which is pre-set by an operator or administrator of the system [200]. The historical interference data may be received from a storage unit [216] that is connected with the transceiver unit [202].
15 Upon receiving the historical interference data, the processing unit [204] which is connected at least with the transceiver unit [202], processes the historical interference data to identify a pre¬existing set of aggressor cells (i.e., interference causing cells) and a corresponding set of victim cells (i.e. interference experiencing cells), based at least on a set of parameters.
20 The present disclosure encompasses that the set of parameters comprises at least one of distance of the set of pre-existing aggressor cells from the corresponding set of victim cells; and a confidence level threshold. The confidence level threshold may refer to a measure of certainty or reliability applied to the identification of pre-existing aggressor cells and corresponding victim cells based on historical interference data.
25
Upon identification of the pre-existing set of aggressor cells and the corresponding set of victim cells, the determination unit [206] which is connected at least with the processing unit [204], determines an interference score corresponding to each pre-existing aggressor cell of the existing set of aggressor cells.
30
The present disclosure encompasses that the interference score is determined based at least on a count of a set of victim cells associated with each of the set of pre-existing aggressor cells and interference consistency caused for at least a second pre-defined time period. The second pre-defined time period is pre-set by the operator or administrator of the system [200].
35
The present disclosure encompasses that the interference score refers to severity and further indicates the number of cells impacted by the set of pre-existing aggressor cells within a specific timeframe.
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5
For example, in a telecommunication network having a plurality of cells, the processing unit [204] identifies count of cells, such as 5 cells as pre-existing aggressor cells which indicates that these cells may cause interference to the say 10 nearby cells which are corresponding set of victim cells. Further, the determination unit [206] analyses this count of 10 victim cells to
10 calculate the interference score for each of the 5 pre-existing aggressor cells.
Further, upon determination of the interference score, the filtering unit [208] which is connected at least with the determination unit [206], filters a set of consistent aggressor cells (i.e. consistently causing interference) and corresponding set of victim cells from the pre-15 existing set of aggressor cells based at least on a configuration and the determined interference score.
The present disclosure encompasses that the filtering of the set of consistent aggressor cells is done on the basis of reporting by the set of victim cells for a particular time period. For 20 example, in a time period of 7 days, the victim cell is reported another cell as the aggressor cell daily.
The set of consistent aggressor cells refers to a set of cells that consistently cause interference to nearby cells over a period of time which may be identified based on historical data as 25 regularly and persistently causing interference to other cells within the telecommunications network.
The configuration refers to a file that includes at least one of the specific settings and the parameters that may be used by the filtering unit [208] to determine which aggressor cells and
30 corresponding victim cells shall be filtered from the pre-existing set of aggressor cells based on their interference score. Additionally, the configuration file may include instructions or rules that are pre-defined by the operator. Furthermore, the configuration file may comprise a data related to time period such as one or more days, one or more months and alike. Also, the configuration file may include data related to a count of victim cells for each aggressor cells.
35 For instance, the configuration file may include a set of rules and a set of thresholds to identify or filter the set of consistent aggressor cells (i.e., consistently causing interference cells) and corresponding set of victim cells from the pre-existing set of aggressor cells.
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5 For example, the filtering unit [208] may filter out a top severity set of consistent aggressor cells (for instance consistent in last 7 days) and the corresponding set of victim cells from the pre-existing set of aggressor cells (for instance from last 7 days) based at least on a configuration file and the determined interference score.
10 Upon filtration, the image extraction unit [210] that is connected at least with the filtering unit [208], extracts a set of images from a map depicting forecast for a tropospheric ducting for a first pre-defined time period. For example, the image extraction unit [210] extracts a set of images from the map, based on a fixed training dataset, a set of top consistent values, a set of aggregators, and a set of data, depicting the forecast for tropospheric ducting for the next day
15 (i.e., the first pre-defined time period). The first pre-defined time period refers to a pre-defined timer period set by the operator or any administrator. The set of data may include open-source data related to forecasting of the tropospheric ducting, for e.g., Hepburn data.
The set of images refers to one or more geographic images from the map that represents forecast 20 for tropospheric ducting for pre-defined time period. The tropospheric ducting is a type of radio propagation that permits a transmission of very high frequencies (VHF) and above beyond a standard line of sight range.
The forecasting of tropospheric ducting involves a multifaceted approach that are known to
25 person in the skilled and integrates various meteorological data sources, numerical weather
prediction models, empirical models, remote sensing techniques, and specialized software. A
meteorological data from weather stations, satellites, and weather balloons provides essential
information on atmospheric parameters such as pressure, temperature, humidity, wind speed,
and direction. Numerical weather prediction models simulate the behaviour of the atmosphere,
30 predicting future conditions that may lead to tropospheric ducting events. Empirical models
leverage historical data to identify patterns and correlations between atmospheric conditions
and ducting occurrences. Remote sensing techniques, including radar and satellite imagery,
offer real-time insights into atmospheric dynamics that influence ducting phenomena.
Specialized software tools are developed to integrate and analyse these diverse data sources,
35 enabling the creation of accurate and timely forecasts of tropospheric ducting behaviour.
Thereafter, the visual representation unit [212] that is connected at least with the image extraction unit [210], overlays the set of consistent aggressor cells and the corresponding set
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5 of victim cells on the extracted set of images to create a visual representation, for proactive interference management in a telecommunication network.
Further, overlay refers to a technique for transposing the image or text over each other. The overlay may be done via one or more image overlaying techniques which may be known to
10 person skilled in the art. Moreover, in the present disclosure the visual representation unit [212] uses the one or more image overlaying techniques to combine the extracted set of images with the set of consistent aggressor cells and the corresponding set of victim cells for producing a clear and informative visual representation of the interference dynamics within the telecommunication network.
15
The present disclosure encompasses that the system [200] further comprises of a prediction 20 unit [214] configured to predict, using a trained model, a set of candidate aggressor cells and a corresponding set of victim cells based at least on processing of the visual representation received by the visual representation unit [212].
The trained model refers to a pre-trained model that is a machine learning (ML) model which 25 has been trained on a large dataset and may be fine-tuned for a specific task. The large dataset may relate to interference in the telecommunication network. Further, the trained model may be trained on an open source data such as Hepburn data, fixed training dataset [200e] and a set of consistent aggressors [200d].
30 Further, in addition to this, the processing unit [204] is configured to perform a down-tilting of the predicted set of candidate aggressor cells and the corresponding set of victim cells by utilizing an Upper Side Lobe Suppression (USLS).
The down-tilting refers to a technique of adjusting a direction or a focus of the predicted set of 35 candidate aggressor cells in downward direction that may reduce interference or improve signal reception in specific regions.
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5 Further, in the telecommunication architecture, a side lobe is a secondary lobe of radiation that occur alongside the main lobe in in antenna patterns and USLS refers to a technique or mechanism used to suppress or reduce these upper side lobes which ultimately reduces interference from one or more unwanted directions.
10 Referring to FIG. 2B, exemplary implementation of the system for proactive interference management in a telecommunication network is shown, in accordance with the exemplary embodiments of the present disclosure. The historical interference data on the periodic basis is received from the transceiver unit [202]. As shown in FIG. 2B, the historical interference data may be interference raw data [200a], which is further utilized by a consistent aggressor
15 processor [200b] and a fixed training data set processor [200c]. The consistent aggressor processor [200b] is similar to the processing unit [204], the determination unit [206], the filtering unit [208] of FIG. 2A. The consistent aggressor processor [200b] produces a set of consistent aggressors [200d] and the fixed training data set processor [200c] generates a fixed training data set [200e]. Thereafter, the set of consistent aggressors [200d] and the fixed
20 training data set [200e] along with a data [200j] is forwarded to a training data extractor [200f]. Further, the training data extractor [200f] generates a training data which is provided to a model generator [200g] to generate a model [200h] which is further operated on a simulator [200i] to produce a set of predicted aggressors [200k].
25 For instance, the interference raw data [200a] is processed on a daily basis to filter out a set of prominent aggressors based on distance and confidence levels. Subsequently, the fixed training data is prepared based on the last 30 days, comprising sets of aggressors and victims. Furthermore, the severity of consistent aggressors is determined using a score (i.e., interference score), calculated through consistency in the last 30 days, consistency in the last 7 days, and
30 the count of victims. Following this, a number of top severity consistent aggressors, based on the configuration file, are filtered out. Next, a set of images from map plotted data is processed. The map plotted data provides a forecast of tropospheric ducting for the next days. Finally, the filtered top severity consistent aggressors and their corresponding victims are mapped over the tropospheric interference duct image obtained from the plotted map to derive a set of predicted
35 aggressors and victim pairs.
18

5 Referring to FIG. 3, an exemplary method [300] for proactive interference management in telecommunication network, in accordance with exemplary embodiments of the present disclosure is shown.
In an implementation the method [300] is performed by the system [200]. As shown in FIG. 3, 10 the method [300] starts at step [302].
At step [304], the method of the present disclosure comprises receiving, by a transceiver unit [202], a historical interference data on a periodic basis (for e.g., last 30 days).
15 The historical interference data is a record of past instances of interference within the telecommunication network. Further the historical interference data may include a plurality of data such as timestamps, interference type, severity, location. Additionally, the historical interference data is received in the periodic basis which is pre-set by an operator or administrator of the system [200].
20
Further the present disclosure encompasses that the historical interference data may be received from a storage unit [216].
The method then proceed to next step [306], in which the method of the present disclosure 25 comprises processing, by a processing unit [204], the historical interference data to identify a pre-existing set of aggressor cells (i.e., interference causing cells) and a corresponding set of victim cells (i.e. interference experiencing cells), based at least on a set of parameters.
The present disclosure encompasses that the set of parameters comprises at least one of distance 30 of the set of pre-existing aggressor cells from the corresponding set of victim cells; and a confidence level threshold. The confidence level threshold may refer to a measure of certainty or reliability applied to the identification of pre-existing aggressor cells and corresponding victim cells based on historical interference data.
35 Upon identification of the pre-existing set of aggressor cells and the corresponding set of victim cells, the method then proceed to step [308], in which the method of the present disclosure comprises determining, by a determination unit [206], an interference score corresponding to each pre-existing aggressor cell of the existing set of aggressor cells.
19

5
The present disclosure encompasses that the interference score is determined based at least on a count of a set of victim cells associated with each of the set of pre-existing aggressor cells and interference consistency caused for at least a second pre-defined time period. The second pre-defined time period is pre-set by the operator.
10
For example, in a telecommunication network having a plurality of cells, the processing unit [204] identifies 5 cells as pre-existing aggressor cells which indicates that these 5 cells may cause interference to the say 10 nearby cells which are corresponding set of victim cells. Further, the determination unit [206] analyses this count of 10 victim cells to calculate the
15 interference score for each of the 5 pre-existing aggressor cell.
Further, upon determination of the interference score, the method proceeds to step [310], in
which the method of the present disclosure comprises filtering, by a filtering unit [208], a set
of consistent aggressor cells and a corresponding set of victim cells from the pre-existing set
20 of aggressor cells based at least on a configuration file and the determined interference score.
The set of consistent aggressor cells refers to a set of cells that consistently cause interference to nearby cells over a period of time which may be identified based on historical data as regularly and persistently causing interference to other cells within the telecommunications 25 network.
The configuration file refers to a file that includes at least one of the specific settings and the parameters that may be used by the filtering unit [208] to determine which aggressor cells and corresponding victim cells shall be filtered from the pre-existing set of aggressor cells based
30 on their interference score. Additionally, the configuration file may include instructions or rules that are pre-defined by the operator. For instance, the configuration file may include a set of rules and a set of thresholds to identify or filter the set of consistent aggressor cells (i.e., consistently causing interference cells) and corresponding set of victim cells from the pre¬existing set of aggressor cells.
35
For example, the filtering unit [208] may filter out a top severity set of consistent aggressor cells (for instance consistent in last 7 days) and the corresponding set of victim cells from the
20

5 pre-existing set of aggressor cells (for instance from last 7 days) based at least on a configuration file and the determined interference score.
Upon filtration, the method proceeds to step [312] in in which the method of the present disclosure comprises extracting, by an image extraction unit [210], a set of images from a map
10 depicting a forecast for a tropospheric ducting for a first pre-defined time period. For example, the image extraction unit [210] extracts a set of images from the map, based on a fixed training dataset, a set of top consistent values, a set of aggregators, and a set of data, depicting the forecast for tropospheric ducting for the next day (i.e., the first pre-defined time period). The first pre-defined time period refers to a pre-defined timer period set by the operator or any
15 administrator.
The set of images refers to one or more geographic images from the map that represents forecast for tropospheric ducting for pre-defined time period. The tropospheric ducting is a type of radio propagation that permits a transmission of very high frequencies (VHF) and above beyond a 20 standard line of sight range.
Thereafter, at step [314], the method of the present disclosure comprises overlaying, by a visual representation unit [212], the set of consistent aggressor cells and the corresponding set of victim cells on the extracted set of images to create a visual representation, for proactive 25 interference management in a telecommunication network.
Further, overlay refers to a technique for transposing the image or text over each other. The overlay may be done via one or more image overlaying techniques which may be known to person skilled in the art. Moreover, in the present disclosure the visual representation unit [212] 30 uses the one or more image overlaying techniques to combine the extracted set of images with the set of consistent aggressor cells and the corresponding set of victim cells for producing a clear and informative visual representation of the interference dynamics within the telecommunication network.
35 The present disclosure encompasses that the method further comprising predicting, by the prediction unit [214] using a trained model, a set of candidate aggressor cells and the corresponding set of victim cells based at least on processing of the visual representation.
21

5 The trained model refers to a pre-trained model that is a machine learning (ML) model which has been trained on a large dataset and may be fine-tuned for a specific task. The large dataset may relate to interference in the telecommunication network.
The present disclosure encompasses that the method further comprising performing, by the 10 processing unit [204], down-tilting of the predicted set of candidate aggressor cells and the corresponding set of victim cells utilizing an Upper Side Lobe Suppression (USLS).
The down-tilting refers to a technique of adjusting a direction or a focus of the predicted set of candidate aggressor cells in downward direction that may reduce interference or improve signal 15 reception in specific regions.
Further, in the telecommunication architecture, a side lobe is a secondary lobe of radiation that occur alongside the main lobe in in antenna patterns and USLS refers to a technique or mechanism used to suppress or reduce these upper side lobes which ultimately reduces 20 interference from one or more unwanted directions.
FIG. 4 illustrates an exemplary block diagram of a computing device [1000] upon which an embodiment of the present disclosure may be implemented. In an implementation, the computing device [1000] implements the method [300] for proactive interference management
25 in a telecommunication network using the system [200]. In another implementation, the computing device [1000] itself implements the method [300] for proactive interference management in a telecommunication network 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.
30
The computing device [1000] may include a bus [1002] or other communication mechanism for communicating information, and a hardware processor [1004] coupled with bus [1002] for processing information. The hardware processor [1004] may be, for example, a general-purpose microprocessor. The computer system [1000] may also include a main memory [1006],
35 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 be used for storing temporary variables or other intermediate information during execution of the instructions to be executed by the processor [1004]. Such
22

5 instructions, when stored in non-transitory storage media accessible to the processor [1004], render the computer system [1000] into a special-purpose machine that is customized to perform the operations specified in the instructions. The computer system [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].
10
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 computer system [1000] may be coupled via the bus [1002] to a display [1012], such as a cathode ray tube (CRT), for displaying information to a computer user. An input device [1014], including alphanumeric
15 and other keys, 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
20 two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow the device to specify positions in a plane.
The computer system [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
25 combination with the computer system [1000] causes or programs the computer system [1000] to be a special-purpose machine. According to one embodiment, the techniques herein are performed by the computer system [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
30 the storage device [1010]. Execution of the sequences of instructions contained in the main memory [1006] causes the processor [1004] to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions.
35 The computer system [1000] also may include a communication interface [1018] coupled to the bus [1002]. The communication interface [1018] provides a two-way data communication coupling to a network link [1020] that is connected to a local network [1022]. The local network [1022] is further connected to a host [1024]. For example, the communication interface [1018]
23

5 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 implemented. In any such implementation, the communication interface [1018]
10 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.
The computer system [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 15 Internet example, a server [1030] might transmit a requested code for an application program through the Internet [1028], the ISP [1026], 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.
20 The present disclosure may also encompass a non-transitory computer readable storage medium storing instruction for proactive interference management in a telecommunication network. The instructions include an executable code which, when executed by one or more units of the system, causes a transceiver unit [202] to receive a historical interference data on a periodic basis; a processing unit [204] to process the historical interference data to identify a
25 pre-existing set of aggressor cells and a corresponding set of victim cells, based at least on a set of parameters; a determination unit [206] to determine an interference score corresponding to each pre-existing aggressor cell of the existing set of aggressor cells; a filtering unit [208] to filter a set of consistent aggressor cells and corresponding set of victim cells from the pre¬existing set of aggressor cells based at least on a configuration file and the determined
30 interference score; an image extraction unit [210] to extract a set of images from a map depicting forecast for a tropospheric ducting for a first pre-defined time period; and a visual representation unit [212] to overlay the set of consistent aggressor cells and the corresponding set of victim cells on the extracted set of images to create a visual representation.
35 As is evident from the above, the present disclosure provides a technically advanced solution for proactive interference management in telecom network which provides a prediction of cells which have a high probability of becoming an aggressor cell which further may cause interference. The present solution includes processing of the historical interference data to
24

5 identify the pre-existing set of aggressor cells corresponding set of victim cells, based the set of parameters. Further, the interference score is determined which is corresponding to each pre¬existing aggressor cell of the existing set of aggressor cells. Thereafter, the set of consistent aggressor cells and the corresponding set of victim cells are filtered from the pre-existing set of aggressor cells based at least on a configuration file and the determined interference score.
10 After this, the set of images are extracted from the map depicting a forecast for a tropospheric ducting for next couple of days and finally the set of consistent aggressor cells and the corresponding set of victim cells are overlapped with the of victim cells on the extracted set of images to create a visual Furthermore, the present invention effectively mitigates the impact of interference well in advance, ensuring minimal disruption to both network operations and
15 customer experiences. By proactively addressing potential interference issues, this innovative solution safeguards the integrity and functionality of telecom networks, fostering uninterrupted service delivery and enhanced user satisfaction.
While considerable emphasis has been placed herein on the disclosed embodiments, it will be 20 appreciated that many embodiments can be made and that many changes can be made to the embodiments without departing from the principles of the present invention. These and other changes in the embodiments 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 and non-limiting. 25

5 We Claim
1. A method for proactive interference management in a telecommunication network, comprising:
receiving, by a transceiver unit [202], a historical interference data on a periodic
basis;
10 processing, by a processing unit [204], the historical interference data to identify
a pre-existing set of aggressor cells and a corresponding set of victim cells, based at least on a set of parameters;
determining, by a determination unit [206], an interference score corresponding
to each pre-existing aggressor cell of the pre-existing set of aggressor cells;
15 filtering, by a filtering unit [208], a set of consistent aggressor cells and a
corresponding set of victim cells from the pre-existing set of aggressor cells based at least on a configuration and the determined interference score;
extracting, by an image extraction unit [210], a set of images from a map
depicting a forecast for a tropospheric ducting for a first pre-defined time period;
20 and
overlaying, by a visual representation unit [212], the set of consistent aggressor cells and the corresponding set of victim cells on the extracted set of images to create a visual representation.
25 2. The method as claimed in claim 1, wherein the set of parameters comprises at least one of distance of the set of pre-existing aggressor cells from the corresponding set of victim cells; and a confidence level threshold.
3. The method as claimed in claim 1, wherein the interference score is determined based
30 at least on a count of a set of victim cells associated with each of the set of pre-existing
aggressor cells and interference consistency caused for at least a second pre-defined time period.
4. The method as claimed in claim 1, wherein the method further comprising predicting,
35 by a prediction unit [214] using a trained model, a set of candidate aggressor cells and
the corresponding set of victim cells based at least on processing of the visual representation.

5
5. The method as claimed in claim 4, wherein the method further comprising performing,
by the processing unit [204], down-tilting of the predicted set of candidate aggressor
cells and the corresponding set of victim cells utilizing an Upper Side Lobe Suppression
10 (USLS).
6. A system [200] for proactive interference management in a telecommunication
network, comprising:
15 a transceiver unit [202], configured to receive a historical interference
data on a periodic basis;
a processing unit [204] connected at least with the transceiver unit [202]
and the processing unit [204] configured to process the historical interference
data to identify a pre-existing set of aggressor cells and a corresponding set of
20 victim cells, based at least on a set of parameters;
a determination unit [206] connected at least with the processing unit [204] and the determination unit [206] configured to determine an interference score corresponding to each pre-existing aggressor cell of the existing set of aggressor cells;
25 a filtering unit [208] connected at least with the determination unit [206]
and the filtering unit [208] configured to filter a set of consistent aggressor cells and corresponding set of victim cells from the pre-existing set of aggressor cells based at least on a configuration and the determined interference score;
30 an image extraction unit [210] connected at least with the filtering unit
[208] and the image extraction unit [210] configured to extract a set of images from a map depicting forecast for a tropospheric ducting for a first pre-defined time period; and
a visual representation unit [212] connected at least the image extraction
35 unit [210] and the visual representation unit [212] configured to overlay the
27

5 set of consistent aggressor cells and the corresponding set of victim cells on
the extracted set of images to create a visual representation.
7. The system [200] as claimed in claim 6, wherein the set of parameters comprises at
least one of distance of the set of pre-existing aggressor cells from the corresponding
10 set of victim cells; and a confidence level threshold.
8. The system [200] as claimed in claim 6, wherein the interference score is determined
based at least on a count of a set of victim cells associated with each of the set of pre¬
existing aggressor cells and interference consistency caused for at least a second pre-
15 defined time period.
9. The system [200] as claimed in claim 6, wherein the system further comprises of a
prediction unit [214] configured to predict, using a trained model, a set of candidate
aggressor cells and corresponding set of victim cells based at least on processing of the
20 visual representation.
10. The system [200] as claimed in claim 9, wherein the processing unit [204] is configured
to perform down-tilting of the predicted set of candidate aggressor cells and the
corresponding set of victim cells utilizing an Upper Side Lobe Suppression (USLS).
25
(GARIMA SAHNEY)
IN/PA-1826
AGENT FOR THE APPLICANT(S)
OF SAIKRISHNA & ASSOCIATES