System and method for identifying passive data samples in a communication network

Abstract

Disclosed is a system (200) and method (500) for identifying passive data samples in a communication network (100). The system generates a unique device Identifier (ID) for each User Equipment (UE) (104) among a plurality of UEs based on attributes specific to the corresponding UE (104). The system receives massive volumes of passive data samples from a Software Development Kit (SDK) associated with an application installed on each UE (104). The received passive data samples is further mapped with a corresponding unique device ID among the generated unique device IDs, and thereafter the received passive data samples are identified based on the mapping to enable efficient identification, tracking, and analysis of the passive data samples.

Description

SYSTEM AND METHOD FOR IDENTIFYING PASSIVE DATA SAMPLES IN A COMMUNICATION NETWORKTECHNICAL FIELD

[0001] The embodiments of the present disclosure generally relate to the field of communication networks. More particularly, the present disclosure relates to a system and a method for identifying passive data samples in a communication network.BACKGROUND OF THE INVENTION

[0002] The subject matter disclosed in the background section should not be assumed or construed to be prior art merely due to its mention in the background section. Similarly, any problem statement mentioned in the background section or its association with the subject matter of the background section should not be assumed or construed to have been previously recognized in the prior art.

[0003] With recent advancements in communication networks, there is a massive increase in a number of users latched to a network. The increase in the number of users necessitates a need to monitor the network for improving performance of the network. To monitor the network, a number of applications have been developed and installed in a User Equipment (UE). These applications measure the network performance by monitoring essential or key performance metrics also referred to as Key Performance Indicators (KPIs) of the network. These applications conduct both active measurement and passive measurement. For active measurements, the applications actively initiate services and record the performance of each service instance. For passive measurements, the applications observe the services initiated by an end user and record the service performance.

[0004] In conventional systems, network operators perform passive measurements by collecting KPI data directly through network monitoring applications, as well as through crowd-sourced data. As the passive measurement data is flooded frommultiple UEs at the same time, the source of passive data is unknown during certain instances. Hence, to identify the source of the passive data is a major challenge, which leads to degradation of the network performance.

[0005] In light of the aforementioned challenges and considerations, there is a need for an improved system and a method for identifying the source of passive data samples in a communication network.SUMMARY

[0006] The following embodiments present a simplified summary in order to provide a basic understanding of some aspects of the disclosed invention. This summary is not an extensive overview, and it is not intended to identify key / critical elements or to delineate the scope thereof. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.

[0007] In an embodiment, a method for identifying passive data samples in a communication network is disclosed. The method includes generating, by a generation module for each User Equipment (UE) among a plurality of UEs in the communication network, the unique device ID based on one or more attributes of a corresponding UE among the plurality of UEs. The method further includes receiving, by a reception module, one or more passive data samples from an application installed on each UE among the plurality of UEs. Further, the method includes mapping, by an identification module, each passive data sample among the one or more passive data samples with a corresponding unique device ID among the generated unique device IDs. Furthermore, the method includes identifying, by the identification module, the one or more passive data samples based on the mapping.

[0008] In some aspects of the present disclosure, the method further includes storing, by a storage module, the one or more passive data samples in a database based on the unique device ID of the corresponding UE among the plurality of UEsand generating, by the generation module, a report by analyzing the one or more passive data samples.

[0009] In some aspects of the present disclosure, the one or more passive data samples indicates one or more Key Performance Indicators (KPIs) monitored by the application installed on the corresponding UE among the plurality of UEs. The one or more KPIs include at least one of Reference Signal Strength Indicator (RS SI), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal-to-Interference-Plus-Noise Ratio (SINR), latency, uplink throughput, downlink throughput, network payload, session setup success rate, session drop rate, or downlink average utilization.

[0010] In some aspects of the present disclosure, the one or more attributes of the UE include at least one of an equipment identity, an advertising identity, an International Mobile Equipment Identity (IMEI), a Media Access Control (MAC) address, a Bluetooth address, or a serial number.

[0011] In some aspects of the present disclosure, the identification of the one or more passive data samples indicates an identification of the corresponding UE among the plurality of UEs from which the one or more passive data samples are received.

[0012] In some aspects of the present disclosure, for mapping the received one or more passive data samples with the corresponding unique device ID, the method includes fetching, by the reception module, the one or more attributes of the corresponding UE from a data payload of the one or more passive data samples. Further the method includes determining, by the identification module, a correlation between the unique device ID of the corresponding UE with the one or more attributes fetched from the data payload. The method further includes mapping, by the identification module based on the determined correlation, the received one or more passive data samples with the unique device ID from which the one or more passive data samples are received.

[0013] In some aspects of the present disclosure, the unique device ID is a 15-digit key and includes a predefined prefix of two or more characters, and the one or more passive data samples is received from a Software Development Tool Kit (SDK) associated with the application installed on each UE among the plurality of UEs.

[0014] In another embodiment, a system for identifying of passive data samples in a communication network is disclosed. The system includes a generation module configured to generate, for each User Equipment (UE) among a plurality of UEs in the communication network, a unique device Identifier (ID) based on one or more attributes of a corresponding UE among the plurality of UEs. The system further includes a reception module configured to receive one or more passive data samples from an application installed on each UE among the plurality of UEs. Further, the system includes an identification module configured to map each passive data sample among the one or more passive data samples with a corresponding unique device ID among the generated unique device IDs and identify the one or more passive data samples based on the mapping.BRIEF DESCRIPTION OF DRAWINGS

[0015] Various embodiments disclosed herein will become better understood from the following detailed description when read with the accompanying drawings. The accompanying drawings constitute a part of the present disclosure and illustrate certain non-limiting embodiments of inventive concepts disclosed herein. Further, components and elements shown in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. For the purpose of consistency and ease of understanding, similar components and elements are annotated by reference numerals in the exemplary drawings.

[0016] FIG. 1 illustrates a diagram depicting an environment of a communication network, in accordance with an embodiment of the present disclosure.

[0017] FIG. 2 illustrates a block diagram of a system for identifying passive data samples in the communication network, in accordance with an embodiment of the present disclosure.

[0018] FIG. 3 illustrates a functional block diagram of one or more modules of the processor of the system, in accordance with an embodiment of the present disclosure.

[0019] FIG. 4 illustrates a diagram depicting communication between a plurality of web servers, a plurality of application servers, and a User Equipment (UE), in accordance with an embodiment of the present disclosure.

[0020] FIG. 5 illustrates a process flow diagram depicting a method for identifying passive data samples in the communication network, in accordance with an embodiment of the present disclosure.

[0021] FIG. 6 illustrates a schematic block diagram of a computing system for identifying passive data samples in the communication network, in accordance with an embodiment of the present disclosure.DETAILED DESCRIPTION OF THE INVENTION

[0022] Inventive concepts of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which examples of one or more embodiments of inventive concepts are shown. Inventive concepts may, however, be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Further, the one or more embodiments disclosed herein are provided to describe the inventive concept thoroughly and completely, and to fully convey the scope of each of the present inventive concepts to those skilled in the art. Furthermore, it should be noted that the embodiments disclosed herein are not mutually exclusive concepts. Accordingly, one or more components from one embodiment may be tacitly assumed to be present or used in any other embodiment.

[0023] The following description presents various embodiments of the present disclosure. The embodiments disclosed herein are presented as teaching examples and are not to be construed as limiting the scope of the present disclosure. The present disclosure should in no way be limited to the illustrative implementations, drawings, and techniques illustrated below, including the exemplary design and implementation illustrated and described herein, but may be modified, omitted, or expanded upon without departing from the scope of the present disclosure.

[0024] The following description contains specific information pertaining to embodiments in the present disclosure. The detailed description uses the phrases “in some embodiments” which may each refer to one or more or all of the same or different embodiments. The term “some” as used herein is defined as “one, or more than one, or all.” Accordingly, the terms “one,” “more than one,” “more than one, but not all” or “all” would all fall under the definition of “some.” In view of the same, the terms, for example, “in an embodiment” refers to one embodiment and the term, for example, “in one or more embodiments” refers to “at least one embodiment, or more than one embodiment, or all embodiments.”

[0025] The term “comprising,” when utilized, means “including, but not necessarily limited to;” it specifically indicates open-ended inclusion in the so-described one or more listed features, elements in a combination, unless otherwise stated with limiting language. Furthermore, to the extent that the terms “includes,” “has,” “have,” “contains,” and other similar words are used in either the detailed description, such terms are intended to be inclusive in a manner similar to the term “comprising.”

[0026] In the following description, for the purposes of explanation, various specific details are set forth 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 can each be used independently of one another or with any combination of other features.

[0027] The description provided herein discloses exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the present disclosure. Rather, the foregoing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing any of the exemplary embodiments. Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it may be understood by one of the ordinary skilled in the art that the embodiments disclosed herein may be practiced without these specific details.

[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein the description, the singular forms "a", "an", and "the" include plural forms unless the context of the disclosure indicates otherwise.

[0029] The terminology and structure employed herein are for describing, teaching, and illuminating some embodiments and their specific features and elements and do not limit, restrict, or reduce the scope of the present disclosure. Accordingly, unless otherwise defined, all terms, and especially any technical and / or scientific terms, used herein may be taken to have the same meaning as commonly understood by one having ordinary skill in the art.

[0030] The various aspects including the example aspects are now described more fully with reference to the accompanying drawings, in which the various aspects of the disclosure are shown. The disclosure may, however, be embodied in different forms and should not be construed as limited to the aspects set forth herein. Rather, these aspects are provided so that this disclosure is thorough and complete, and fully conveys the scope of the disclosure to those skilled in the art. In the drawings, the sizes of components may be exaggerated for clarity.

[0031] Various aspects of the present disclosure provide a system and a method for identifying passive data samples in a communication network based on a unique device Identifier (ID) of a User Equipment (UE) for easy analysis of data.

[0032] In another aspect of the present disclosure, the system and the method generate the unique device ID of the UE using one or more attributes associated with the UE. The unique device ID may be a unique key or unique identification number for identifying an end user device, for example, the UE of an end user.

[0033] In the present disclosure, various embodiments are described using terms such as extensible radio access network (xRAN), and open-radio access network (0-RAN)) that are commonly used in communication standards (e.g., 3rd generation partnership project (3 GPP), but these are merely examples for description. Various embodiments of the disclosure may also be easily modified and applied to other communication systems.

[0034] Several key terms used in the description play pivotal roles in facilitating the system functionality. In order to facilitate an understanding of the description, the key terms are defined below.

[0035] A “Network Management System (NMS)” in the present disclosure may represent a system that enables operators to monitor and configure communication networks. The NMS identifies, configures, monitors, updates, and troubleshoots network devices in the communication network.

[0036] “Key Performance Indicators” in the present disclosure may be quantifiable measurements of network parameters to monitor and analyze the performance of the network.

[0037] A “Reference Signal Received Power (RSRP)” in the present disclosure may represent a linear average of reference signal power in resource elements that carry cell-specific reference signals within considered measurement frequency bandwidth.

[0038] A“Received Signal Strength Indicator (RSSI)” in the present disclosure may be a measurement of total received power observed by the UE over a specific bandwidth. The measurement includes the power of a desired signal, interference,and noise. RSSI is used as an indicator of signal strength in conjunction with performance metrics like RSRP and Reference Signal Receive Quality (RSRQ).

[0039] The “RSRQ” in the present disclosure may be a quality metric represented as a ratio of the RSRP to the total RSSI in a measured bandwidth. In particular, the RSRQ indicates a quality of the signal relative to interference and noise.

[0040] A “ Signal -to-Interference-plus-Noise Ratio (SINR)” in the present disclosure may be a ratio of the signal power to the sum of interference and noise power, determining the minimum required value for successful packet reception in the communication networks.

[0041] An “International Mobile Station Equipment Identity (IMEI)” in the present disclosure may be a unique number allocated to each mobile station equipment for identifying the equipment in a Public Land Mobile Network (PLMN). IMEI may serve as a unique identifier for mobile devices, encompassing details such as the device's manufacturer, model, and serial number.

[0042] A “Media Access Control (MAC) address” in the present disclosure may be a unique identifier assigned to a Network Interface Controller (NIC) for communication within a network segment. The MAC address may be a hardware address, like a serial number, that distinguishes one device from another on the same network.

[0043] The term “Software Development Kit (SDK)” in the present disclosure may be a set of software-building tools for a specific platform. The SDK may be a collection of tools, libraries, and instructions that help developers in developing software applications.

[0044] A “passive data sample” in the present disclosure may be data samples collected by observing and analyzing network traffic without actively participating in the network or sending probes. The passive data sample may be collected fromexisting network traffic to assess performance, identify issues, and gain insights into network behavior.

[0045] A “crowdsourced data” in the present disclosure may refer to a collection of network performance information from a large number of users. The data may be gathered through various applications to provide insights into real-world user experience and network behavior across different locations and times.

[0046] A “Demilitarized Zone (DMZ)” in the present disclosure may refer to a subnetwork between a private internal network and an untrusted external network, like the internet. The DMZ may act as a buffer zone, allowing controlled access to specific services from the external network while protecting the internal network from potential threats.

[0047] A “non-DMZ” in the present disclosure may refer to a network that contains sensitive data and resources, like internal applications and critical infrastructure. The non-DMZ may be a separate network segment designed to expose specific services to the public internet while isolating them from the main internal network.

[0048] FIG. 1 illustrates a diagram depicting an environment of a communication network 100, in accordance with an embodiment of the present disclosure.

[0049] The wireless communication network 100 includes coverage regions 106-1 to 106-N (hereinafter cumulatively referred to as the coverage region 106). The coverage region 106 is served by one or more Base Stations (BSs) 102-1 to 102-N. Each base station among the BSs 102-1 to 102-N may have same or similar configuration and may also be referred to as “BS 102”. The BSs 102-1 to 102-N serves one or more User Equipment (UEs) 104-1 to 104-N in the coverage region 106. Each user equipment among the UEs 104-1 to 104-N may have same or similar configuration and may also be referred to as “UE 104”. The BSs 102-1 to 102-N are connected to a network 108 to provide one or more services to the UEs 104-1 to 104-N. The wireless communication network 100 further includes one or moreapplication servers 110-1 to 110-N (hereinafter cumulatively referred to as the server 110) connected to the network 108. The server 110 is configured to execute data processing and data storing operations to identifying passive data samples from the UE 104.

[0050] The BS 102 may be at least one relay, and at least one Distributed Unit (DU). Typically, the BS 102 may be a network infrastructure that provides wireless access to one or more terminals. The BS 102 has coverage defined to be a predetermined geographic area based on the distance over which a signal may be transmitted. The BS 102 may be referred to as, in addition to “base station”, “access point (AP)”, “evolved NodeB (eNodeB or eNB)”, “5G node (5th generation node)”, “next generation NodeB (gNB)”, “wireless point”, “transmission / reception point (TRP)”, “Radio Access Network (RAN)” or other terms having equivalent technical meanings.

[0051] The UE 104 may be, at least one DU, at least one Mobile Termination (MT) unit, and at least one relay. Typically, the term “user equipment” or “UE” can refer to any component such as “mobile station”, “subscriber station”, “remote terminal”, “wireless terminal”, “receive point”, or “end user device”.

[0052] The network 108 may include suitable logic, circuitry, and interfaces that may be configured to provide several network ports and several communication channels for transmission and reception of data related to operations of various entities of the wireless communication network 100. Each network port may correspond to a virtual address (or a physical machine address) for transmission and reception of the communication data. For example, the virtual address may be an Internet Protocol Version 4 (IPV4) (or an IPV6 address) and the physical address may be a Media Access Control (MAC) address. The network 108 may be associated with an application layer for implementation of communication protocols based on one or more communication requests from the various entities of the wireless communication network 100.

[0053] The communication data may be transmitted or received via the communication protocols. Examples of the communication protocols may include, but are not limited to, Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Simple Mail Transfer Protocol (SMTP), Domain Network System (DNS) protocol, Common Management Interface Protocol (CMIP), Transmission Control Protocol and Internet Protocol (TCP / IP), User Datagram Protocol (UDP), Long Term Evolution (LTE) communication protocols, or any combination thereof. In some aspects of the present disclosure, the communication data may be transmitted or received via at least one communication channel of several communication channels in the network 108. The communication channels may include, but are not limited to, a wireless channel, a wired channel, a combination of wireless and wired channel thereof. Examples of wired channels may include ethemet cables, coaxial cables, and fiber optic cables. Examples of wireless channels may include wireless fidelity (Wi-Fi), Bluetooth, cellular networks, and satellite communication. The wireless or wired channel may be associated with a data standard which may be defined by one of a Local Area Network (LAN), a Personal Area Network (PAN), a Wireless Local Area Network (WLAN), a Wireless Sensor Network (WSN), Wireless Area Network (WAN), Wireless Wide Area Network (WWAN), a metropolitan area network (MAN), a satellite network, the Internet, an optical fiber network, a coaxial cable network, an infrared (IR) network, a radio frequency (RF) network, and a combination thereof. Aspects of the present disclosure are intended to include or otherwise cover any type of communication channel, including known, related art, and / or later developed technologies.

[0054] The server 110 may be a network of computers, a software framework, or a combination thereof, that may provide a generalized approach to create a server implementation. Examples of the server 110 may include, but are not limited to, personal computers, laptops, mini-computers, mainframe computers, any nontransient and tangible machine that can execute a machine-readable code, cloudbased servers, distributed server networks, or a network of computer systems. The server 110 may be realized through various web-based technologies or any web-application framework. In other aspects of the present disclosure, the server 110 may be configured to execute one or more data processing and / or storage operations to identify the passive data samples received from the UE 104.

[0055] FIG. 2 illustrates a block diagram of a system 200 for identifying passive data samples in the communication network 100, in accordance with an embodiment of the present disclosure. The system 200 may include a network 108, the BS 102 connected to the network 108, the UE 104 connected to the network 108 via the BS 102, the server 110, a Network Management System (NMS) 230, and an external database 228.

[0056] The server 110 includes a communication interface 202, a processor 204, a memory 206 coupled to the processor 204, and a server database 208. The processor 204 may control the operation of the server 110. The processor 204 may include one or more modules 204-a (hereinafter also referred to as the “modules 204-a”). The processor 204 may also be referred to as a Central Processing Unit (CPU). The memory 206 may provide instructions and data to the processor 204 for performing functions of the server 110. The memory 206 may include a Random Access Memory (RAM), a Read-Only Memory (ROM) and a portion of the memory 206 may also include Non-Volatile Random Access Memory (NVRAM). The processor 204 may perform logical and arithmetic operations based on instructions stored within the memory 206. The communication interface 202 may allow transmission and reception of data between the server 110 and the network 108. The communication interface 202 may include a transmitter, a receiver, and a single or multiple transmit antennas electrically coupled to the transmitter and the receiver of the communication interface 202.

[0057] The communication interface 202 may be configured to enable the server 110 to communicate with various entities of the system 200 via the network 108. Examples of the communication interface 202 may include, but are not limited to, a modem, a network interface such as an Ethernet card, a communication port, and / or a Personal Computer Memory Card International Association (PCMCIA) slot andcard, an antenna, a radio frequency (RF) transceiver, one or more amplifiers, a coder-decoder (CODEC) chipset, a subscriber identity module (SIM) card, and a local buffer circuit. It will be apparent to a person of ordinary skill in the art that the communication interface 202 may include any device and / or apparatus capable of providing wireless or wired communications between the server 110 and various other entities of the system 200.

[0058] In some aspects of the present disclosure, the server 110 may be coupled to the external database 228 that provides data storage space to the server 110. The external database 228 may store information related to configuration parameters, the passive data samples received from the UE 104 and other relevant information needed for the operation of the server 110. The external database 228 may correspond to a centralized database system configured to store and manage structured data, such as network-related data and configurations. The external database 228 may be a relational database organizing related data such as in a table, or a non-relational database organizing graphical and time series data.

[0059] The UE 104 may include a user interface 210, a processor 212, a communication interface 214, and a memory 216 coupled to the processor 212. The processor 212 may control the operation of the UE 104. The processor 212 may also be referred to as the CPU. The memory 216 may provide instructions and data to the processor 212 for performing several functions. The processor 212 may perform logical and arithmetic operations based on instructions stored within the memory 216.

[0060] The memory 216 may include a Random Access Memory (RAM) 218, a Read-Only Memory (ROM) 220, and a portion of the memory 216 may also include non-volatile random-access memory (NVRAM). The memory 216 may include an Operating System (OS) 222 for serving as an interface between the hardware components and the UE 104. The memory 216 may comprise applications 224 and a database 226 to store data based on the applications 224. The OS 222 may provide functions to and support communication standards for the UE 104. The OS 222 mayalso provide a common programming platform or executing environment for the applications 224.

[0061] In one embodiment, the UE 104 may be installed with the application 224 for monitoring the passive data samples and forwarding the samples to the server 110. The application 224 may be integrated in the OS 222 of the UE 104. The application 224 may be configured to run in the background so that the operations of the UE 104 may not be impacted.

[0062] The communication interface 214 may allow transmission and reception of data between the UE 104 and the network 108. The communication interface 214 may include a transmitter, a receiver, and a single or multiple transmit antennas electrically coupled to the transmitter and the receiver of the communication interface 214. The one or more computer executable applications may be stored on the UE 104.

[0063] The user interface 210 may include suitable logic, circuitry, interfaces, and / or codes that may be configured to receive input(s) and present (or display) output(s) on the UE 104. For example, the user interface 210 may have an input interface and an output interface. The input interface may be configured to enable a user to provide input(s) to trigger (or configure) the UE 104 to perform various operations. Examples of the input interface may include, but are not limited to, a touch interface, a mouse, a keyboard, a motion recognition unit, a gesture recognition unit, a voice recognition unit, or the like. Aspects of the present disclosure are intended to include or otherwise cover any type of the input interface including known, related art, and / or later developed technologies without deviating from the scope of the present disclosure. The output interface may provide the output(s) based on an instruction provided via the user interface 210. Examples of the output interface of the user interface 210 may include, but are not limited to, a digital display, an analog display, a touch screen display, an appearance of a desktop, and / or illuminated characters.

[0064] The processors 204 and 212 may include one or more general purpose processors and / or one or more special purpose processors, a microprocessor, a digital signal processor, an application specific integrated circuit, a microcontroller, a state machine, or ay any type of programmable logic array. The processors 204 and 212 may include may include an intelligent hardware device including a general-purpose processor, such as, for example, and without limitation, a Central Processing Unit (CPU), an Application Processor (AP), a dedicated processor, or the like, a graphics-only processing unit such as a Graphics Processing Unit (GPU), a microcontroller, a Field-Programmable Gate Array (FPGA), a programmable logic device, a discrete hardware component, or any combination thereof.

[0065] The memories 206 and 216 may further include, but not limited to, non- transitory machine-readable storage devices such as hard drives, magnetic tape, floppy diskettes, optical disks, compact disc read-Only Memories (CD-ROMs), and magneto-optical disks, semiconductor memories, such as ROMs, RAMS, programmable read-only memories PROMs), erasable PROMs (EPROMs), electrically erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other type of media / machine-readable medium suitable for storing electronic instructions.

[0066] In addition, the memory may, in some examples, be considered a non- transitory storage medium. The "non -transitory" storage medium is not embodied in a carrier wave or a propagated signal. However, the term "non -transitory" should not be interpreted as the memory is non-movable. In some examples, the memory may be configured to store larger amounts of information. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in Random Access Memory (RAM) or cache). The memory may be an internal storage unit or an external storage unit of the server, cloud storage, or any other type of external storage.

[0067] FIG. 2 shows the BS 102 and the UE 104 to simplify the illustration as each BS among the one or more BSs 102-1 to 102-N have same or similar configurationand each user equipment among the one or more UEs 104-1 to 104-N have same or similar configuration.

[0068] Although FIG. 1 and FIG. 2 illustrate one example of the environment of the wireless communication network 100 and the system 200, various changes may be made to FIG. 1 and FIG. 2. For example, the system 200 may include any number of user devices in any suitable arrangement. Further, in another example, the server 110 may include any number of components in addition to the components shown in FIG. 2. Further, various components in FIG. 1 and FIG. 2 may be combined, further subdivided, or omitted and additional components may be added according to particular needs.

[0069] In some embodiments, the application 224 for monitoring the passive data samples of the network may be developed using a Software Development Kit (SDK) and installed in the UE 104. The passive data samples may include the KPIs comprising at least one of the RSSI, the RSRP, the RSRQ, the SINR, latency, uplink throughput, downlink throughput, network payload, session setup success rate, session drop rate, or downlink average utilization. The SDK integrated within the application 224 may collect network quality indicators or user behavior data. The passive data samples may be collected by trace ports or through the application 224 integrated using the SDK and installed in the UE 104. The application 224 may send the passive data samples in backend of the UE 104, without disturbing any operation of the other applications installed in the UE 104. The passive data samples including the KPIs may be measured by the application 224 and sent to the server 110 through the BS 102.

[0070] In one embodiment, the server 110 may receive millions of passive data samples, for example, the KPIs from the application 224 installed in the UE 104 via a web portal. Further, the server 110 may generate the unique device ID, for example, a 15-digit key starting from “DC”, using at least one identity of the UE 104. The unique device ID may be used to identify the received passive data samples of a particular UE 104 and analyze the samples conveniently to generate reports forthe passive data. The analysis of the samples may enable easy report generation for the passive data samples.

[0071] FIG. 3 illustrates a functional block diagram 300 of the modules 204-a of the processor 204 of the system 200, in accordance with an embodiment of the present disclosure. The modules 204-a may include a generation module 302, a reception module 304, an identification module 306, a storage module 308, and a transmission module 310. In an embodiment, the one or more modules 204-a may be combined to a single module, or each module of the one or more modules 204-a may be further subdivided into different modules with divided responsibilities.

[0072] In some embodiments, the identification module 306 may identify at least one identity of the UE 104 during a registration of the UE 104 in the network 108. The identification module 306 may utilize one or more attributes of the UE 104 to identify the UE 104. The identification module 306 may identify the UE 104 based on the one or more attributes comprising at least one of an equipment identity, an advertising identity, the IMEI, a MAC address, a Bluetooth address, or a serial number of the UE 104.

[0073] In some aspects of the present disclosure, the reception module 304 may receive the one or more attributes as part of a registration process or a specific request from the UE 104. When the application 224 is installed in the UE 104, the UE 104 may register to the server 110 seeking permissions for using the application 224. The server 110 may in turn request for various permissions from the UE 104 to allow the application 224 to utilize the processor 212 and the memory 216 of the UE 104.

[0074] In a non-limiting example, once the application 224 is installed in the UE 104, a messaging component within the server 110 may receive the IMEI of the UE 104 within a User Agent message. Additionally, some network elements like Home / Visitor Location Registers (HLR / VLRs) temporarily store the IMEI of the UE 104 during registration.

[0075] Once the application 224 is installed in the UE 104, the server 110 may receive at least one identity associated with the UE 104. The generation module 302 may generate the unique device ID for the UE 104 based on the one or more attributes associated with the identity of the UE 104. The generation module 302 may utilize the identity of the UE 104, for instance, the equipment identity, the IMEI, or the MAC address. The generation module 302 may utilize certain rules or algorithms to generate the unique device ID for the UE 104. For example, the generation module 302 may generate the unique device ID as a 15-digit key starting from “DC”, using at least one identity of the UE 104. The storage module 308 may store the one or more attributes associated with the identity of the UE 104 and the corresponding generated unique device ID of the UE 104 in the external database 228.

[0076] The reception module 304 may receive one or more passive data samples from the application 224 installed on each UE 104 among the one or more UEs 104- 1 to 104-N as a crowd-sourced data. The passive data samples may be the one or more KPIs monitored by the application 224 installed in each of the UE 104. The crowd-sourced data may comprise at least one of the RSSI, the RSRP, the RSRQ, the SINR, the latency, the uplink throughput, the downlink throughput, the network payload, the session setup success rate, the session drop rate, or the downlink average utilization measured or captured by the application 224 installed in the UE 104.

[0077] In a non-limiting example, the crowd-sourced data may comprise speed test results run by the one or more UEs 104-1 to 104-N. The UE 104 may perform the speed test by accessing a speed test application 224 installed in the UE 104 or by accessing a web portal to run the speed test. The application 224 or the web portal may be configured to send results of the speed test performed by the one or more UEs 104-1 to 104-N to the server 110 along with a time stamp and other related information.

[0078] Once the reception module 304 receives the one or more passive data samples from the application 224, the identification module 306 may may map the received one or more passive data samples with a corresponding unique device ID among the generated unique device IDs.

[0079] In some aspects of the present disclosure, to map each passive data sample among the one or more passive data samples with the corresponding unique device ID, the reception module 304 may fetch the one or more attributes of the corresponding UE 104 from a data payload of the one or more passive data samples. The identification module 306 may determine a correlation between the unique device ID of the corresponding UE 104 with the one or more attributes fetched from the data payload. The identification module 306 map, based on the determined correlation, the received one or more passive data samples with the unique device ID from which the one or more passive data samples are received.

[0080] In some aspects of the present disclosure, the one or more attributes associated with the UE 104 may be mapped to the generated unique device ID. When the application 224 is installed on the UE 104, the application 224 may communicate with the server 110 by sending device-level information that includes the one or more attributes including at least one of the equipment identity, the IMEI, or the MAC address of the UE 104. The application 224 may send the device-level information or other identifying information to the server 110. The server 110 may track the installation of the application 224.

[0081] In some aspects of the present disclosure, for installing the application 224 in the UE 104, the SDK may track the device-level information and communicate with the server 110. The server 110 may track the installation of the application 224. In a non-limiting example, for passive monitoring, the identification module 306 may identify the device-level information through network address information (like IP addresses and MAC addresses) embedded within the network packets or frames. Additionally, the application 224 may include unique identifiers within the data payload that the identification module 306 may use to track the application 224.

[0082] In some aspects of the present disclosure, the application 224 may embed the one or more attributes in the data payload. The identification module 306 may identify the one or more attributes received in the passive data samples and may derive the one or more attributes associated with the UE 104 from the passive data samples. The identification module 306 may use the one or more attributes fetched from the payload to search the external database 228. The correlation between the unique device ID and the one or more attributes present in the data payload may be determined by searching the one or more attributes of the UE 104 in the external database 228. The identification module 306 may match the unique device ID of the UE 104 from the one or more attributes derived from the data payload.

[0083] The identification module 306 may identify the received passive data samples based on the mapping of the unique device ID of the corresponding UE 104 among the one or more UEs 104-1 to 104-N. The identification of the one or more passive data samples may indicate an identification of the corresponding UE 104 among the one or more UEs 104-1 to 104-N from which the one or more passive data samples are received. The server 110 may analyze the passive data samples from each of the UE 104 based on the identification. The server 110 may utilize the passive data samples to monitor the performance of the network 108. Hence, it is important to identify from which UE 104 the passive data sample is received. Based on the identification, the performance of the network 108 may be monitored.

[0084] In some aspects of the present disclosure, the SDK of the UE 104 may be used for developing one or more applications 224. The identification module 306 may identify the UE 104 based on the one or more passive data samples received from the one or more applications 224 of the UE 104 based on the same unique device ID of the UE 104.

[0085] In some embodiments, the storage module 308 may store the received passive data samples in the external database 228 based on the unique device ID of the UE 104. The storage module 308 may store the incoming passive data samplesfrom the UE 104 in the external database 228 based on the unique device ID of the UE 104.

[0086] In a non-limiting example, the identification module 304 may identify the UE 104-1 on the basis of the IMEI number of the UE 104. The IMEI number of the UE 104-1 may be stored in the database 228. The generation module 302 may utilize the IMEI number of the UE 104-1 to generate the unique ID for the SDK installed in the UE 104-1. If the identification module 306 identifies the IMEI number of the UE 104-1 as XX-YYYYYY-ZZZZZZ-A, the generation module 302 may generate the unique device ID as DC-AAAAAA-BBBBBB-C for the UE 104-1. The storage module 308 may store the unique device ID of the UE 104-1 in the database 228. The reception module 304 receives one or more passive data samples from the application 224 installed on each of the UE 104-1, UE 104-2, the UE 104-3, and the UE 104-4. The identification module 306 may identify the one or more passive data samples from the application 224 of the UE 104-1 based on the unique device ID of the UE 104-1.

[0087] In a non-limiting example, the one or more passive data samples received from the UE 104-1, UE 104-2, the UE 104-3, and the UE 104-4 may be stored in the database 228 based on the unique device ID of each UE 104 as illustrated using Table 1 :Table 1 : One or more passive data samples stored in the database 228

[0088] From the table 1 , the server 110 may monitor the performance of the network 108 based on the one or more passive data samples. The server 110 may comprise information of both the values of the one or more KPIs received as the one or more passive data samples as well as the identity of the UE 104 from which the one or more samples are received.

[0089] The generation module 302 may generate a report by analyzing the one or more passive data samples. The report may comprise performance of each UE 104 based on the one or more passive data samples. The transmission module 310 may transmit the report to the NMS 230 for further analysis. The NMS 230 may analyze the passive data samples from the UE 104 to take further remedial actions to improve the performance of the network 108.

[0090] FIG. 4 illustrates a block diagram 400 depicting a communication between a load balancer 402, a plurality of web servers 404-1 to 404-N (hereinafter cumulatively referred to as the web server 404), a plurality of servers 110-1 to 110- N (hereinafter cumulatively referred to as the server 110), and the UE 104, in accordance with an embodiment of the present disclosure.

[0091] The load balancer 402 may be configured to balance and evenly distribute network service requests from the one or more UEs 104-1 to 104-N to the server 110. In particular, the load balancer 402 may be configured to act as a reverse proxy and may distribute network or application traffic across one or more servers 110. Further, the load balancer 402 may create balance between the load from the one or more UEs 104-1 to 104-N and may ensure that each server 110 receives an appropriate amount of data from the one or more UEs 104-1 to 104-N. More specifically, the load balancer 402 may prevent the server 110 from bearing too much load, thereby preventing failing of, or slowing down of the application.

[0092] The load balancer 402 may be a networking device or an application that distributes and balances the incoming traffic among the web server 404 to provide high availability, efficient utilization of servers, and high performance. The web server 404 may be a software component that delivers static data like images, files,and text in response to request received from the UE 104. The server 110 may extend the capabilities of the web server 404 by supporting dynamic content generation, application logic, and integration with various resources. The server 110 may provide a runtime environment to run application code and interact with other software components, like messaging systems and the external database 228.

[0093] The external database 228 may correspond to a centralized database system configured to store and manage structured data, such as network-related data and configurations. The external database 228 may be a relational database organizing related data such as in a table, or a non-relational database organizing graphical and time series data. The UE 104, the load balancer 402 and the web server 404 may be inside a Demilitarized Zone (DMZ). The web server 404 located in the DMZ may be bounded by firewalls, for providing secure communications between the UE 104 and back-end systems. The server 110 and the external database 228 may be inside a non-DMZ zone.

[0094] The application 224 installed in the UE 104 may obtain the passive data samples and may forward the passive data samples received from the UE 104 to the web server 404 via the load balancer 402. The application 224 may also be accessed by the web portal. In a non-limiting example, if the application 224 installed in the UE 104 is related to speed test, then the application 224 may be run on the UE 104 or may be accessed using the web portal to run the speed test on the UE 104.

[0095] The web server 404 may receive the passive data samples from the application 224 installed in the UE 104 and forward to the server 110. The server 110 may identify the passive data samples received from the UE 104 using at least one identity of the UE 104. The at least one identity of the UE 104 may be identified using the one or more attributes of the UE 104. The one or more attributes may comprise at least one of the equipment identity, the advertising identity, the IMEI, the MAC address, the Bluetooth address, or the serial number of the UE 104. The server 110 may generate a unique device ID for the UE 104. The server 110 maystore and analyze the passive data samples received from the UE 104 in the external database 228.

[0096] In some embodiments, the one or more attributes of the UE 104 may include location of the UE 104, IP addresses used by the UE 104, or access points used by the UE 104.

[0097] FIG. 5 illustrates a process flow diagram depicting a method 500 for identifying the passive data samples in the communication network 100, in accordance with an embodiment of the present disclosure. The method 500 comprises a series of operation steps indicated by blocks 502 through 506.

[0098] At block 502, the processor 204 may generate, for each UE 104 among the plurality of UEs 104-1 to 104-N in the communication network 100, the unique device ID based on one or more attributes of the corresponding UE 104 among the plurality of UEs 104-1 to 104-N.

[0099] In some aspects of the present disclosure, the unique device ID may be a 15- digit key and may include a predefined prefix of two or more characters.

[0100] At block 504, the processor 204 may receive one or more passive data samples from the application 224 installed on each UE 104 among the plurality of UEs 104-1 to 104-N.

[0101] In some aspects of the present disclosure, the one or more passive data samples is received from the SDK associated with the application 224 installed on each UE 104 among the plurality of UEs.

[0102] At block 506, the processor 204 may map each passive data sample among the one or more passive data samples with a corresponding unique device ID among the generated unique device IDs.

[0103] In some aspects of the present disclosure, for mapping the received one or more passive data samples with the corresponding unique device ID, the processor204 may fetch the one or more attributes of the corresponding UE 104 from the data payload of the one or more passive data samples. Further, the processor 204 may determine the correlation between the unique device ID of the corresponding UE 104 with the one or more attributes fetched from the data payload. The processor 204 may further map, based on the determined correlation, the received one or more passive data samples with the unique device ID from which the one or more passive data samples are received.

[0104] At block 508, the processor 204 may identify the one or more passive data samples based on the mapping of the unique device ID of the corresponding UE 104 among the plurality of UEs 104-1 to 104-N.

[0105] In some aspects of the present disclosure, the identification of the one or more passive data samples indicates the identification of the corresponding UE 104 among the plurality of UEs 104-1 to 104-N from which the one or more passive data samples are received.

[0106] In some aspects of the present disclosure, the processor 204 may store the one or more passive data samples received from the UE 104 in the external database 228 based on the unique device ID of the corresponding UE 104 among the plurality of UEs 104-1 to 104-N.

[0107] Further, the processor 204 may generate a report by analyzing the one or more passive data samples received from the UE 104. The report may comprise identified passive data samples of the UE 104 comprising the monitored KPIs experienced by individual UE 104. The monitored KPIs may comprise at least one of the RS SI, the RSRP, the RSRQ, the SINR, the latency, the uplink throughput, the downlink throughput, the network payload, the session setup success rate, the session drop rate, or the downlink average utilization

[0108] In some aspects of the present disclosure, the processor 204 may transmit the report to the NMS 230 for further analysis. The NMS 230 may take necessary remedial actions to improve the performance of the network 108. The report may be1 analyzed in the form of logs or graphs. The report may be displayed in the web portal.

[0109] FIG. 6 illustrates a schematic block diagram of a computing system 600 for identifying passive data samples in the wireless communication network 100, in accordance with an embodiment of the present disclosure.

[0110] The computing system 600 includes a network 602, a network interface 604, a processor 606 (similar in functionality to the processor 204 of FIG. 2), an Input / Output (I / O) interface 608 (similar in functionality to the communication interface 202 of FIG. 2), and a non-transitory computer readable storage medium 610 (hereinafter may also be referred to as the “storage medium 610” or the “storage media 610”). The network interface 604 includes wireless network interfaces such as Bluetooth, Wi-Fi, Worldwide Interoperability for Microwave Access (WiMAX), General Packet Radio Service (GPRS), or Wideband Code Division Multiple Access (WCDMA) or wired network interfaces such as Ethernet, or Universal Serial Bus (USB),.

[0111] The processor 606 may include various processing circuitry / modules and communicate with the storage medium 610 and the I / O interface 608. The processor 606 is configured to execute instructions stored in the storage medium 610 and to perform various processes. The processor 606 may include an intelligent hardware device including a general-purpose processor, such as, for example, and without limitation, the CPU, the AP, the dedicated processor, or the like, the graphics-only processing unit such as the GPU, the microcontroller, the FPGA, the programmable logic device, the discrete hardware component, or any combination thereof. The processor 606 may be configured to execute computer-readable instructions 610-1 stored in the storage medium 610 to cause the system 200 to perform various functions disclosed throughput the disclosure.

[0112] The storage medium 610 stores a set of instructions i.e., computer program instructions 610-1 (hereinafter may also be referred to as instructions 610-1) required by the processor 606 for controlling its overall operations. The storagemedia 610 may include an electronic storage medium, a magnetic storage medium, an optical storage medium, a quantum storage medium, or the like. For example, the storage media 610 may include, but are not limited to, hard drives, floppy diskettes, optical disks, ROMs, RAMs, EPROMs, EEPROMs, flash memory, magnetic or optical cards, solid-state memory devices, or other types of physical media suitable for storing electronic instructions. In one or more embodiments, the storage media 610 includes a Compact Disk-Read Only Memory (CD-ROM), a Compact Disk- Read / Write (CD-R / W), and / or a Digital Video Disc (DVD). In one or more implementations, the storage medium 610 stores computer program code configured to cause the computing system 600 to perform at least a portion of the processes and / or methods disclosed herein throughput the disclosure.

[0113] Embodiments of the present disclosure have been described above with reference to flowchart illustrations of methods and systems according to embodiments of the disclosure, and / or procedures, algorithms, steps, operations, formulae, or other computational depictions, which may also be implemented as computer program products. In this regard, each block or step of the flowchart, and combinations of blocks (and / or steps) in the flowchart, as well as any procedure, algorithm, step, operation, formula, or computational depiction can be implemented by various means, such as hardware, firmware, and / or software including one or more computer program instructions embodied in computer-readable program code. As will be appreciated, any such computer program instructions may be executed by one or more computer processors, including without limitation a general -purpose computer or special purpose computer, or other programmable processing apparatus to perform a group of operations comprising the operations or blocks described in connection with the disclosed method.

[0114] Further, these computer program instructions, such as embodied in computer-readable program code, may also be stored in one or more computer- readable memory or memory devices (for example, the memory 206 or the storage medium 610) that can direct a computer processor or other programmable processing apparatus to function in a particular manner, such that the instructions610-1 stored in the computer-readable memory or memory devices produce an article of manufacture including instruction means which implement the function specified in the block(s) of the flowchart(s).

[0115] It will further be appreciated that the term “computer program instructions” as used herein refer to one or more instructions that can be executed by the one or more processors (for example, the processor 204 or the processor 606) to perform one or more functions as described herein. The instructions 610-1 may also be stored remotely such as on a server, or all or a portion of the instructions can be stored locally and remotely.

[0116] Referring to the technical abilities and advantageous effect of the present disclosure, operational advantages that may be provided by above disclosed system and method may identify samples on the basis of unique device ID for easily identifying source of data and analyzing the data. The identification of the source of data enables easy report generation for the passive data samples. Another potential advantage of the present disclosure may take remedial actions on the network by analyzing the passive data samples from the UE, thereby improving the performance of the network.

[0117] Further, the present disclosure relates to a method for managing large volumes of passive data samples received from multiple user devices (UEs) in the communication network. To enable efficient identification, tracking, and analysis of the passive data samples, the method introduces the generation of the unique device ID or device-specific identifier based on one or more attributes of each UE. Each incoming passive data sample is then associated with the corresponding device identifier, allowing for accurate mapping and further processing, such as performance analysis and reporting. Also, the method is especially useful in large- scale deployments, where millions of passive samples are collected daily through a background SDK. By using generated device identifiers, the present disclosure avoids relying on sensitive or persistent device identifiers, thereby improving privacy, scalability, and data correlation accuracy.”

[0118] Those skilled in the art will appreciate that the methodology described herein in the present disclosure may be carried out in other specific ways than those set forth herein in the above disclosed embodiments without departing from essential characteristics and features of the present disclosure. The above-described embodiments are therefore to be construed in all aspects as illustrative and not restrictive.

[0119] The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Any combination of the above features and functionalities may be used in accordance with one or more embodiments.

[0120] In the present disclosure, each of the embodiments has been described with reference to numerous specific details which may vary from embodiment to embodiment. The foregoing description of the specific embodiments disclosed herein may reveal the general nature of the embodiments herein that others may, by applying current knowledge, readily modify and / or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications are intended to be comprehended within the meaning of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and is not limited in scope.LIST OF REFERENCE NUMERALS

[0121] The following list is provided for convenience and in support of the drawing figures and as part of the text of the specification, which describe innovations by reference to multiple items. Items not listed here may nonetheless be part of a given embodiment. For better legibility of the text, a given reference number is recitednear some, but not all, recitations of the referenced item in the text. The same reference number may be used with reference to different examples or different instances of a given item. The list of reference numerals is:100 - Wireless communication environment102 / 102-1 to 102-N - One or more Base Stations (BSs)104 / 104-1 to 104-N -One or more User Equipment (UEs)106-1 to 106-N - Coverage region108 - Network110 - Server200 - System for identifying passive data samples202 - Communication interface of the server 106204 - Processor of the server 106204-a - One or more modules of the processor 204206 - Memory of the server 106208 - Server database of the server 106210 - User Interface (UI) of the UE 104212 - Processor of the UE 104214 - Communication interface of the UE 104216 - Memory of the UE 104218 - Random Access Memory (RAM) in the memory 216220 - Read-Only Memory (ROM) in the memory 216222 - Operating System (OS) in the memory 216224 - Applications in the memory 216226 - Database in the memory 216228 - External database230 - Network Management System (NMS)300 - Functional block diagram of one or more modules 204-a302 - Generation module304 - Reception module306 - Identification module308 - Storage module310 - Transmission module400 - Block diagram depicting communication between various components402 - Load balancer 404 / 404-1 to 404-N - One or more web servers500 - Method for identifying passive data samples502-506 - Operation steps of the method 500600 - Block diagram of a computing system602 - Network 604 - Network interface606 - Processor608 - Input / Output (I / O) interface610 - Non-transitory computer-readable storage medium610-1 - Set of instructions

Claims

We Claim:

1. A method (500) for identifying passive data samples in a communication network, the method (500) comprising: generating (502), by a generation module (302) for each User Equipment (UE) (104) among a plurality of UEs in the communication network, a unique device Identifier (ID) based on one or more attributes of a corresponding UE (104) among the plurality of UEs; receiving (504), by a reception module (304), one or more passive data samples from an application installed on each UE (104) among the plurality of UEs; mapping (506), by an identification module (306), each passive data sample among the one or more passive data samples with a corresponding unique device ID among the generated unique device IDs; and identifying (508), by the identification module (306), the one or more passive data samples based on the mapping.

2. The method (500) as claimed in claim 1, further comprising: storing, by a storage module (308), the one or more passive data samples in a database based on the unique device ID of the corresponding UE (104) among the plurality of UEs; and generating, by the generation module (302), a report by analyzing the one or more passive data samples.

3. The method (500) as claimed in claim 1, wherein: the one or more passive data samples indicates one or more Key Performance Indicators (KPIs) monitored by the application installed on the corresponding UE (104) among the plurality of UEs; and the one or more KPIs include at least one of Reference Signal Strength Indicator (RSSI), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal-to-Interference-Plus-Noise Ratio (SINR),latency, uplink throughput, downlink throughput, network payload, session setup success rate, session drop rate, or downlink average utilization.

4. The method (500) as claimed in claim 1, wherein the one or more attributes of the UE include at least one of an equipment identity, an advertising identity, an International Mobile Equipment Identity (IMEI), a Media Access Control (MAC) address, a Bluetooth address, or a serial number.

5. The method (500) as claimed in claim 1, wherein the identification of the one or more passive data samples indicates an identification of the corresponding UE (104) among the plurality of UEs from which the one or more passive data samples are received.

6. The method (500) as claimed in claim 1, for mapping the received one or more passive data samples with the corresponding unique device ID, the method comprises: fetching, by the reception module (304), the one or more attributes of the corresponding UE (104) from a data payload of the one or more passive data samples; determining, by the identification module (306), a correlation between the unique device ID of the corresponding UE (104) with the one or more attributes fetched from the data payload; and mapping, by the identification module (306) based on the determined correlation, the received one or more passive data samples with the unique device ID from which the one or more passive data samples are received.

7. The method (500) as claimed in claim 1, wherein the unique device ID is a 15-digit key and includes a predefined prefix of two or more characters, andwherein the one or more passive data samples is received from a Software Development Tool Kit (SDK) associated with the application installed on each UE (104) among the plurality of UEs.

8. A system (200) for identifying passive data samples in a communication network, the system (200) comprising: a generation module (302) configured to generate, for each User Equipment (UE) (104) among a plurality of UEs in the communication network, the unique device Identifier (ID) based on one or more attributes of a corresponding UE (104) among the plurality of UEs; a reception module (304) configured to receive one or more passive data samples from an application installed on each UE (104) among the plurality of UEs; and an identification module (306) configured to: map each passive data sample among the one or more passive data samples with a corresponding unique device ID among the generated unique device IDs; and identify the one or more passive data samples based on the mapping.

9. The system (200) as claimed in claim 8, further comprises: a storage module (308) configured to store the one or more passive data samples in a database based on the unique device ID of the corresponding UE (104) among the plurality of UEs; and the generation module (302) configured to generate a report by analyzing the one or more passive data samples.

10. The system (200) as claimed in claim 8, wherein: the one or more passive data samples indicates one or more Key Performance Indicators (KPIs) monitored by the application installed on the corresponding UE among the plurality of UEs; andthe one or more KPIs include at least one of Reference Signal Strength Indicator (RSSI), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal-to-Interference-Plus-Noise Ratio (SINR), latency, uplink throughput, downlink throughput, network payload, session setup success rate, session drop rate, or downlink average utilization.

11. The system (200) as claimed in claim 8, wherein the one or more attributes of the UE include at least one of an equipment identity, an advertising identity, an International Mobile Equipment Identity (IMEI), a Media Access Control (MAC) address, a Bluetooth address, or a serial number.

12. The system (200) as claimed in claim 8, wherein the identification of the one or more passive data samples indicates an identification of the corresponding UE (104) among the plurality of UEs from which the one or more passive data samples are received.

13. The system (200) as claimed in claim 8, to map the received one or more passive data samples with the corresponding unique device ID, wherein: the reception module (304) configured to fetch the one or more attributes of the corresponding UE (104) from a data payload of the one or more passive data samples; the identification module (306) configured to determine a correlation between the unique device ID of the corresponding UE (104) with the one or more attributes fetched from the data payload; and the identification module (306) configured to map, based on the determined correlation, the received one or more passive data samples with the unique device ID from which the one or more passive data samples are received.

14. The system (200) as claimed in claim 8, wherein the unique device ID is a 15-digit key and includes a predefined prefix of two or more characters, andwherein the one or more passive data samples is received from a Software Development Tool Kit (SDK) associated with the application installed on each UE (104) among the plurality of UEs.

15. A computer program product comprising computer-executable instructions that are stored on a non-transitory computer-readable medium and that, when executed by at least one processor performs operations comprising: generating, for each User Equipment (UE) among a plurality of UEs in the communication network, a unique device Identifier (ID) based on one or more attributes of a corresponding UE among the plurality of UEs; receiving one or more passive data samples from an application installed on each UE among the plurality of UEs; mapping each passive data sample among the one or more passive data samples with a corresponding unique device ID among the generated unique device IDs; and identifying the one or more passive data samples based on the mapping.

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