System and method for detecting performance degradation or outage in a communication network

Abstract

Disclosed is a system (200) and a method (500, 600) for detecting performance degradation or outage in a communication network. Based on trace data, a group of serving cells is identified corresponding to a pre-defined set of user devices among a plurality of user devices (120). A dominance percentage of each serving cell among the plurality of user devices, a set of dominant serving cells and a set of top serving cells among the identified group of serving cells serving a pre-defined set of user devices is determined. Outage alarm information corresponding to the identified group of serving cells is fetched. One or more user device among the pre- defined set of user devices is classified as one of a user device with complete outage or a user device with non-optimal outage based on determination of outage of the set of top serving cell and the set of dominant serving cell.

Description

SYSTEM AND METHOD FOR DETECTING PERFORMANCE DEGRADATION OR OUTAGE IN A COMMUNICATION NETWORK TECHNICAL 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 detecting performance degradation or outage 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 because of 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] There has been an ever-increasing demand for a reliable communication network due to exponentially increasing number of users of smart devices connected with each other across the globe for sharing information with each other. Although network operators have tried to meet the increased demand by expanding network resources and utilizing existing network resources to a maximum capability, still the users continue to experience a degradation in performance of the communication network in terms of higher call drops and higher latency in the communication network. Moreover, outage of network resources can significantly affect performance of the communication network, resulting in issues such as network congestion, service deterioration, handover failures, and disruptions to network monitoring and management. Such degradation in performance of the communication network can ultimately lead to revenue loss for network operators and negatively impacts the customer experience.

[0004] Currently, when a network resource experiences an outage, the network traffic is rerouted to a next available network resource, typically a neighboring cellwith a higher rank. The next available network resource continues to share burden of serving the network traffic on behalf of the network resource facing the outage, however in doing so, performance of the next available network resource itself gets degraded and the next best network resource operates sub optimally.

[0005] For enhancing user experience and optimizing the performance of the communication network, network operators rely on traditional methods of network optimization based on network performance reports which are generated based on data collected from serving cells serving a plurality of User Equipment (UEs). However, a significant drawback associated with the traditional methods is that an actual impact of performance degradation or outage of the serving cells on users or geographical areas cannot be identified. The traditional methods fail to provide an extent of performance degradation and exact user devices for which performance degradation or outage occurred. Therefore, it gets difficult for network operators to identify the serving cells facing performance degradation or outage that have to be serviced on priority that could increase Quality of Service (QoS) of the communication network in a most effective manner.

[0006] However, it can be challenging to determine which particular user devices are completely without service versus the user devices served by suboptimal serving cells. Furthermore, the traditional methods present other challenges to the network operators such as the network operators face difficulties in identifying a particular user device that is completely without service or are being served by sub optimal serving cells, thus impeding efforts to optimize the performance of the communication network effectively.

[0007] In light of the above-mentioned drawbacks and shortcomings of the traditional methods of network optimization, there lies a need for an improved system and method for detecting network degradation or outages and also identifying its impact on users.SUMMARY

[0008] 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.

[0009] In one embodiment, disclosed herein is a method for detecting performance degradation or outage in a communication network. The method comprises obtaining, by an acquisition module from a data collection entity, trace data associated with a plurality of user devices served by a plurality of serving cells in the communication network. Based on the trace data, the method comprises identifying, by a processing module, a group of serving cells from the plurality of serving cells serving a pre-defined set of user devices among the plurality of user devices. Further, the method comprises determining, by the processing module in a pre-defined time-period, a dominance percentage of each serving cell among the group of serving cells corresponding to the pre-defined set of user devices. Furthermore, the method comprises determining, by the processing module based on the determined dominance percentage, a set of dominant serving cells among the group of serving cells and a set of top serving cells among the group of serving cells. Thereafter, the method comprises classifying, by the processing module as one of a first user device or a second user device, one or more user devices among the predefined set of user devices served by the set of dominant serving cells and the set of top serving cells based on a determination of an outage at one or more of the set of top serving cells and the set of dominant serving cells.

[0010] In one aspect, the method further comprises fetching, by the processing module, performance data corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells. The performance data includes one or more of values of a plurality of Key Performance Indicators (KPIs) associated with each serving cell and alarm information corresponding to each serving cell. Further, the determination of the outage at the one or more of the set oftop serving cells and the set of dominant serving cells is based on the performance data. The one or more user devices among the pre-defined set of user devices served are identified for the classification based on of the outage.[Oil] In one aspect, the alarm information comprises one or more outage alarms. The outage at the one or more of the set of top serving cells and the set of dominant serving cells is determined based on a mapping of the one or more outage alarms corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells, and a comparison of a corresponding value of the plurality of KPIs with a corresponding pre-defined threshold value.

[0012] In one aspect, the dominance percentage of each serving cell is determined based on a ratio of a number of samples of the trace data corresponding to each serving cell among the group of serving cells and a total number of samples of the trace data collected from the pre-defined set of user devices.

[0013] In one aspect, the set of dominant serving cells have a dominance percentage greater than a first pre-defined dominance percentage, the set of top serving cells have a dominance percentage greater than a second pre-defined dominance percentage, and the second pre-defined dominance percentage is greater than the first pre-defined dominance percentage.

[0014] In one aspect, the first user device is served by the set of dominant serving cells that are simultaneously facing the outage. The second user device is served by at least one top serving cell that is facing the outage, and at least one dominant serving cell among the set of dominant serving cells is operational. The first user device corresponds to a user device with complete outage impacted due to the outage at the group of serving cells, and the second user device corresponds to a user device with non-optimal outage impacted due to a degradation in performance of the group of serving cells.

[0015] In one aspect, the trace data includes one or more of positional information of the plurality of user devices, identity information of the plurality of serving cells,serving area information associated with the plurality of serving cells, and performance metrics associated with the plurality of serving cells and the plurality of the user devices.

[0016] In one aspect, the method comprises sending, by the processing module, information corresponding to the classification of the first user device and the second user device to a Network Management Entity (NME) for performing Root Cause Analysis (RCA) of performance degradation or outage corresponding to one or more of the set of top serving cells and the set of dominant serving cells and corrective actions for recovery of the set of top serving cells and the set of dominant serving cells.

[0017] In another embodiment, disclosed herein is a system for detecting performance degradation or outage in a communication network. The system comprises an acquisition module and a processing module. The acquisition module is configured to obtain, from a data collection entity, trace data associated with a plurality of user devices served by a plurality of serving cells in the communication network. The processing module is configured to identify, based on the trace data, a group of serving cells from the plurality of serving cells serving a pre-defined set of user devices. Further, the processing module is configured to determine, in a predefined time-period, a dominance percentage of each serving cell among the group of serving cells corresponding to the pre-defined set of user devices. Furthermore, the processing module is configured to determine, based on the determined dominance percentage, a set of dominant serving cells among the group of serving cells and a set of top serving cells among the group of serving cells. Thereafter, the processing module is configured to classify as one of a first user device or a second user device, one or more user devices among the pre-defined set of user devices served by the set of dominant serving cells and the set of top serving cells based on a determination of an outage at one or more of the set of top serving cells and the set of dominant serving cells.

[0018] In one aspect, the processing module is further configured to fetch performance data corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells. The performance data includes one or more of values of a plurality of Key Performance Indicators (KPIs) associated with each serving cell and alarm information corresponding to each serving cell. The determination of the outage at the one or more of the set of top serving cells and the set of dominant serving cells is based on the performance data. The one or more user devices among the pre-defined set of user devices served are identified for the classification based on the determination of the outage.

[0019] In one aspect, the alarm information comprises one or more outage alarms. The outage at the one or more of the set of top serving cells and the set of dominant serving cells is determined based on a mapping of the one or more outage alarms corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells, and a comparison of a corresponding value of the plurality of KPIs with a corresponding pre-defined threshold value.

[0020] In one aspect, the dominance percentage of each serving cell is determined based on a ratio of a number of samples of the trace data corresponding to each serving cell among the group of serving cells and a total number of samples of the trace data collected from the pre-defined set of user devices.

[0021] In one aspect, the first user device is served by the set of dominant serving cells that are simultaneously facing the outage. The second user device is served by at least one top serving cell that is facing the outage, and at least one dominant serving cell among the set of dominant serving cells is operational. The first user device corresponds to a user device with complete outage impacted due to the outage at the group of serving cells, and the second user device corresponds to a user device with non-optimal outage impacted due to a degradation in performance of the group of serving cells.

[0022] In one aspect, the trace data includes one or more of positional information of the plurality of user devices, identity information of the plurality of serving cells,serving area information associated with the plurality of serving cells, and performance metrics associated with the plurality of serving cells and the plurality of the user devices.

[0023] In one aspect, the processing module is further configured to send information corresponding to the classification of the first user device and the second user device to a Network Management Entity (NME) for performing Root Cause Analysis (RCA) of performance degradation or outage corresponding to one or more of the set of top serving cells and the set of dominant serving cells and corrective actions for recovery of the set of top serving cells and the set of dominant serving cells.BRIEF DESCRIPTION OF DRAWINGS

[0024] 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. 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. In the drawings:

[0025] FIG. 1 illustrates a block diagram depicting an exemplary environment of a wireless communication network, in accordance with an embodiment of the present disclosure.

[0026] FIG. 2 illustrates a system for detecting communication network performance degradation or outage for a user device, in accordance with an embodiment of the present disclosure.

[0027] FIG. 3 illustrates a block diagram depicting a detailed system architecture of the server, in accordance with an embodiment of the present disclosure.

[0028] FIG. 4 illustrates a block diagram depicting an example system architecture of a Network Management Entity (NME), in accordance with an embodiment of the present disclosure.

[0029] FIG. 5 illustrates an exemplary method for detecting performance degradation or outage for the user device in the communication network, in accordance with an embodiment of the present disclosure.

[0030] FIG. 6 illustrates an exemplary method for detecting performance degradation or outage in a grid in the communication network, in accordance with an embodiment of the present disclosure.DETAILED DESCRIPTION OF THE INVENTION

[0031] 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.

[0032] 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.

[0033] 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.”

[0034] 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 or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.”

[0035] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features.

[0036] 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, itmay be understood by one of the ordinary skilled in the art that the embodiments disclosed herein may be practiced without these specific details.

[0037] 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 and in the appended claims, the singular forms "a", "an", and "the" include plural forms unless the context of the invention indicates otherwise.

[0038] 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 and the appended claims. Accordingly, unless otherwise defined, all terms, and especially any technical and / or scientific terms, used herein may be taken to have the same.

[0039] In the disclosure, various embodiments are described using terms used in communication standards (e.g., 3rd Generation Partnership Project (3GPP), Extensible Radio Access Network (xRAN), and Open-Radio Access Network (O-RAN)), but these are merely examples for description. Various embodiments of the disclosure may also be modified and applied to other communication systems.

[0040] In order to facilitate an understanding of the disclosed invention, a number of terms are defined below.

[0041] Quality of Service (QoS) in the field of telecommunications can be defined as a set of specific requirements provided by a network to users, which are necessary in order to achieve the required functionality of an application (service). The users specify their performance requirements in form of QoS parameters such as delay or packet loss.

[0042] A serving cell may refer to a radio cell or an access point to which User Equipment (UE) is currently connected or from which the UE receives primary wireless communication services.

[0043] A small cell may refer to a low-power cellular radio access node with a limited coverage area, typically ranging from 10 meters to a few hundred meters.

[0044] A macro cell may refer to a high-power cellular radio access nodes that provide wide-area coverage, typically with a range of several kilometers, and are often mounted on towers or tall buildings.

[0045] A micro cell may refer to medium-power access nodes with coverage areas smaller than the macro cells but larger than femto or pico cells, generally used in urban areas to support a higher user density.

[0046] A coverage region may refer to a geographical area within which a wireless communication node, such as a Base Station (BS), the small cell, a repeater, or an access point, is capable of providing reliable wireless communication services to UE. The boundaries of the coverage region may vary based on factors such as transmission power, antenna configuration, environmental conditions, and network topology.

[0047] “Outage” in a serving cell may refer to a condition in which the cell becomes entirely unavailable for service delivery, resulting in a complete loss of connectivity for all users within its coverage area. The outage may be triggered by hardware malfunction, software failure, power disruption, or severe interference, and is characterized by the absence of traffic activity or the inability of the cell to establish or maintain connections.

[0048] “Performance degradation” in a serving cell may refer to a condition a state in which the serving cell remains operational but fails to deliver service at the expected quality levels. The performance degradation may occur as reduced throughput, increased latency, elevated call drop rates, or diminished signal quality, often arising from congestion, interference, or suboptimal resource allocation.

[0049] An object of the present disclosure is to provide a system and a method for detecting performance degradation or outage in the communication network usingtrace data collected from a particular user device. Another object of the present disclosure is to provide a system and a method that monitors impact on users of serving cells facing performance degradation or outages. Another object of the present disclosure is to provide a system and a method that monitors impact on geographical region of serving cells facing performance degradation or outages.

[0050] Yet another object of the present disclosure is to provide a reliable system and a method for assessing QoS provided by the communication network based on user experience. Still another object of the present disclosure is to provide an efficient system and method for improving the QoS provided by the communication network to the particular user device by monitoring impact of serving cells facing degraded performances.

[0051] The following description provides specific details of certain aspects of the disclosure illustrated in the drawings to provide a thorough understanding of those aspects. It should be recognized, however, that the present disclosure can be reflected in additional aspects and the disclosure may be practiced without some of the details in the following description.

[0052] Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings. FIG. 1 through FIG. 6, discussed below, and the one or more embodiments used to describe the principles of the present disclosure are by way of illustration only and should not be construed in any way to limit the scope of the present disclosure. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged system or device.

[0053] FIG. 1 illustrates a block diagram depicting an exemplary environment of a wireless communication network 100, in accordance with an embodiment of the present disclosure. The embodiment of the wireless communication network 100 shown in FIG. 1 is for illustration only. Other embodiments of the wireless communication network 100 may be used without departing from the scope of this disclosure. The wireless communication network 100 may comprise a plurality ofnodes 110-1 through 110-n (cumulatively referred to as “nodes 110” and alternatively referred to as “serving cells 110”) connected to a plurality of user devices 120-1 through 120-n (cumulatively referred to as “user devices 120”) through a network 130.

[0054] The nodes 110 may include one of at least one Base Station (BS), at least one relay, and at least one Distributed Unit (DU). The BS may be a network infrastructure that provides wireless access to one or more terminals. The base station provides coverage to a plurality of predetermined geographic areas based on distance over which a signal may be transmitted. Examples of the BS include, but are not limited to, a macro cell, a femtocell, wireless “Access Point (AP),” “evolved NodeB (eNodeB) (eNB),” “5th Generation (5G) node,” “next generation NodeB (gNB),” “wireless point,” “Transmission / Reception Point (TRP) ” The BS may provide wireless access in accordance with wireless communication protocols, e.g., 5G / NR 3GPP New Radio interface / access (NR), LTE, LTE-A, High Speed Packet Access (HSPA), Wi-Fi 802.11a / b / g / n / ac, etc. Aspects of the present disclosure are intended to include, or otherwise cover, any technology (known or later developed) bearing same or similar characteristics as of the above-mentioned BS, without deviating from the scope of the present disclosure. The serving cells 110 may also include the small cells, the macro cells, the micro cells, the indoor serving cells, and the outdoor serving cells. The serving cells 110 may experience degraded performance when a value of one or more Key Performance Indicators (KPIs) corresponding to the serving cells 110 falls below a pre-defined threshold value of the KPI. The KPIs may refer to quantifiable measures that reflect a behavioral state of the User Equipment (UE) and serving cells 110.

[0055] Typically, the term “user devices” can refer to any component such as “UEs” “mobile station,” “subscriber station,” “remote terminal,” “wireless terminal,” “receive point,” or “end user device.” The user devices 120 may correspond to, but is not limited to, any of mobile devices, tablets, or other portable Internet of Things (IOT) devices utilized by users to access services provided by the network 130. The user devices 120 may also include Fixed Wireless Access (FWA) device used toaccess services provided by the network 130. The FWA device is a wireless connection enabling device such as a Customer Premise Equipment (CPE) mounted either inside or outside a premises that provides broadband access to a specific location such as a home or enterprise premises. Multiple users in the home or enterprise premises may access the services of the network 130 through the FWA device.

[0056] The user devices 120 may be served by one or more of the plurality of serving cells 110. The user devices 120 may communicate with the serving cells 110 to avail services of the serving cells 110 through the network 130. The network 130 may include wired connections, wireless connections such as a proprietary Internet Protocol (IP) network, a local area network, a wide area network, or other wireless communication protocols such as 5th Generation 5G / New Radio (NR), Long Term Evolution (LTE), Long Term Evolution Advanced (LTE-A), Worldwide Interoperability for Microwave Access (WiMAX), High Speed Packet Access (HSPA), Wi-Fi 802.11a / b / g / n / ac, or a combination of wired and wireless connections.

[0057] The serving cells 110 and the user devices 120 also communicate with a server 140 through the network 130. The network 130 may be divided into different coverage regions. The coverage region may comprise multiple serving cells 110 and the user devices 120. The user devices 120 may be served by one or more serving cells 110 in one or more coverage regions.

[0058] Although FIG. 1 illustrates one example of an environment of a communication network, various changes may be made to FIG. 1. For example, the environment may include any number of serving cells 110 and any number of user devices 120 in any suitable arrangement. Further, the serving cells 110 may communicate directly with any number of user devices 120 and provide the user devices 120 with wireless broadband access to the network 130. Further, each of the serving cells 110 may also communicate directly with the server 140. Further, theserving cells 110 may provide access to other or additional external networks, such as external telephone networks or other types of data networks.

[0059] FIG. 2 illustrates a system 200 for detecting communication network performance degradation or outage for the user device, in accordance with an embodiment of the present disclosure. The embodiments of the system 200 shown in FIG. 2 are for illustration only. Other embodiments of the system 200 may be used without departing from the scope of this disclosure.

[0060] As shown in FIG. 2, the system 200 may include the plurality of nodes 110, the plurality of user devices 120, the network 130, the server 140, a Network Management Entity (NME) 210, a data collection entity 220, a database 230, and a performance management entity 240. The server 140 is configured to communicate with the user device 120, the NME 210, the nodes 110, the data collection entity 220, the database 230, and the performance management entity 240 via the network 130. It must be understood that there may be a plurality of user devices in the system 200, but for the sake of brevity only one user device 120 has been shown as an example in FIG. 2.

[0061] The user device 120 is configured to establish a session with the serving cells 110 to avail services of the serving cells 110 in the communication network 100. During the session, the user device 120 is configured to interact with the network 130 and capture samples of data corresponding to the communication network 100. The user device 120 sends the data to the data collection entity 220, periodically, on demand from the server 140, or after an event. The data sent by each of the user device 120 may be referred to as trace data.

[0062] The trace data may be related to the user device 120 latched to the serving cell 110 during the session. The trace data includes positional information of the plurality of the user devices 120, identity information of the plurality of serving cells 110, serving area information associated with the plurality of serving cells 110, and performance metrics associated with the serving cells 110 and the plurality of the user device 120 in the communication network 100. The positional informationcomprises latitudinal and longitudinal position information of the plurality of user devices 120. The positional information may be captured by Global Positioning Sensors (GPS) provided in the user device 120, at a time of data collection. The performance metrics may include information associated with a nature of service availed by the user devices 120, information associated with the serving cells 110, and signal strength received by the user devices 120. The trace data may additionally include hardware configuration of the user device 120 such as a model number of the user device 120, International Mobile Equipment Identity (IMEI) of the user device 120, International Mobile Subscriber Identity (IMSI) of the user device 120.

[0063] The data collection entity 220 may be a server or a group of servers configured to collect and store the trace data corresponding to the plurality of user devices 120. The group of servers may be one or more of a cloud-based server, an application server, a content server, a host server, a web server, a database server, or a server hosted over a desktop computer. The group of servers may be hosted locally or over a cloud network. In one embodiment, the data collection entity 220 may be a database configured to store the samples of the trace data and communicate with the server 140.

[0064] Further, the data collection entity 220 is communicatively coupled with the server 140. The server 140 obtains the collected trace data corresponding to the user devices 120 periodically, on demand, or after an event-based trigger from the data collection entity 220. In one embodiment, the server 140 may obtain the collected trace data periodically, at an hourly, daily or weekly basis. The server 140 processes the trace data to identify a group of serving cells from the serving cells 110 serving the user devices 120.

[0065] In one embodiment, the user device 120 may correspond to the FWA devices. The server 140 processes the trace data associated with a plurality of user devices 120 in the communication network 100 over the pre-defined time-period. The pre-defined set of user devices may include one or more FWA devices. Upon processing the trace data, the server 140 identifies the group of serving cells servinga pre-defined set of user devices among the plurality of user devices during a predefined time-period. The pre-defined time-period may be a day, a week, or a fortnight.

[0066] The server 140 further determines a dominance percentage of each serving cell among the identified group of serving cells corresponding to the pre-defined set of user devices. The dominance percentage indicates a dominance of one or more serving cells among the identified group of serving cells in serving a majority of the user devices among the pre-defined set of user devices 120 in the pre-defined time period. The dominance percentage is determined based on a ratio of samples of the trace data served by each serving cell and the total samples.

[0067] Based on the determined dominance percentage of each serving cell, the server 140 determines one or more dominant serving cells among the identified group of serving cells. The dominant serving cells may correspond to the serving cells having a dominance percentage greater than a first pre-defined dominance percentage. Similarly, the server 140 determines one or more top serving cells among the identified group of serving cells. The top serving cells may correspond to the serving cells having a dominance percentage greater than a second pre-defined dominance percentage. The second pre-defined dominance percentage may be greater than the first pre-defined dominance percentage.

[0068] Furthermore, the server 140 fetches performance data corresponding to the identified group of serving cell from the performance management entity 240. The performance management entity 240 may be a server, a group of servers or a storage medium configured to collect and store the performance data corresponding to the plurality of serving cells 110. The performance data may include values of a plurality of KPIs corresponding to the identified group of serving cell. In an embodiment, the performance data may further include alarm information corresponding to on-going or live outage alarms raised by the serving cells.

[0069] In another embodiment, the plurality of KPIs may be associated with outage in the serving cells 110. The plurality of KPIs may indicate performance of theserving cells 110, and may include, but not limited to, capacity of the serving cell 110, throughput of the serving cell 110, a count of user devices 120 served by the serving cell 110 in a pre-defined time period, a number of call drops in a location served by the serving cell 110, a call setup success rate achieved by the serving cell 110, an availability of the serving cell 110, a number of data calls served by the serving cell 110, a count of handovers performed by the serving cell 110, and interference between the serving cell 110 and a neighboring serving cell.

[0070] In an embodiment, to identify the serving cells 110 experiencing a performance outage, the server 140 may determine, based on comparison of values of one or more of the plurality of the KPIs with a corresponding pre-defined threshold value, and determine the serving cells 110 whose values falls below the pre-defined threshold value of at least one KPI among the plurality of the KPIs. The threshold value of one or more of the plurality of KPIs may be pre-defined by the network operator based on operating conditions in the wireless communication network 100 or existing policies in a geographical area in the wireless communication network 100. The performance outage in the serving cells 110 may occur due to software malfunctioning, hardware malfunctioning, backhaul issues, and other issues in the network 130 leading to outage of the serving cells 110.

[0071] In another embodiment, to identify the serving cells 120 experiencing a performance outage, the server 140 may utilize the alarm information to identify serving cells experiencing the performance outage. The server 140 may identify the serving cells 110 corresponding to which the performance data comprises one or more live outage alarms. The server 140 may determine the outage at the one or more of the set of top serving cells and the set of dominant serving cells is determined based on a mapping of the one or more outage alarms corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells. The mapping of the one or more outage alarms corresponding to each serving cell includes matching the matching the one or more outage alarms corresponding to each serving cell raising the one or more outage alarms among the set of dominant serving cells and the set of top serving cells.

[0072] The server 140, based on the live outage alarms or the values of the KPIs among the fetched performance data, determines serving cells among the identified group of serving cells facing performance outage. Further, based on the serving cells facing performance outage, the server 140 identifies one or more user devices among the pre-defined set of user devices 120 being served by the serving cells facing performance outage. The identified one or more user devices among the predefined set of user devices 120 may correspond to user devices impacted with performance outage.

[0073] Based on the identification of the one or more user devices 120 impacted due to performance outage in the serving cells, the server 140 may classify the one or more user devices among the pre-defined set of user devices 120 as a user device with complete outage (alternatively referred to as “first user device”) and a user device with non-optimal outage (alternatively referred to as “second user device”), based on a determination of the outage at one or more of the set of top serving cells and the set of dominant serving cells. The user device with complete outage may include the user devices such as FWAs impacted due to all dominant serving cells that are simultaneously facing the outage. The user device with complete outage may be facing a total loss of service.

[0074] The user device with non-optimal outage may include the user devices such as FWAs impacted due to impacted due to a degradation in performance of the group of serving cells. The user device with non-optimal outage may be served by at least one top serving cell that is facing the outage, and at least one dominant serving cell among the set of dominant serving cells is operational. The user device with non-optimal outage may be operating at sub-optimal QoS level with degraded performance of the communication network and not at a best performance of the communication network.

[0075] The server 140 may further be connected to a storage medium for storing and managing the trace data collected from the data collection entity 220. Storage medium may generally be one or more of, without limitation, disk drives, hard-diskarrays, solid state storage devices, Network Attached Storage (NAS) devices, tape libraries or other magnetic, non-tape storage devices, and optical media storage devices. In an embodiment, the storage medium may be integrated within the server 140.

[0076] In one embodiment, the storage medium may form a part of a Distributed File System (DFS). The DFS may allow the server 140 seamless data access and retrieval as needed for processing and storage. The DFS is configured to provide a scalable and fault-tolerant storage system, capable of handling entire operation specific data across distributed clusters of files associated with the server 140.

[0077] In other embodiments, the storage medium may correspond to the database 230 for storing large volumes of records of the trace data. The trace data stored in the database 230 may be accessed and updated by the server 140. The database 230 may also store records of the serving cells 110 deployed in a geographical region. The database 230 is further configured to be utilized for storage the performance metrics associated with the identified group of serving cells.

[0078] In one embodiment, the database 230 may be implemented as a centralized database, Relational Database Management System (RDBMS), Non-Relational Database Management System, and Hierarchical Database Management System, and Network Database Management System. In another embodiment, the database 230 may also be an in-memory database including a distributed in-memory data storage of the server 140.

[0079] Furthermore, information corresponding to the classified performance user device with complete outage among the pre-defined set of user devices 120 is provided to the NME 210. The NME 210 may be managed by network administrators for taking a remedial action on the communication network 100 based on the identified dominant serving cells and / or top serving cells affecting a maximum number of user device among the pre-defined set of user devices 120.

[0080] Although FIG. 2 illustrates one example of the system 200, various changes may be made to FIG. 2. Further, the system 200 may include any number of components in addition to the components shown in FIG. 2. Further, various components in FIG. 2 may be combined, further subdivided, or omitted and additional components may be added according to particular needs. A detailed description of the method for detecting performance outage in the communication network is described further below.

[0081] FIG. 3 illustrates a block diagram depicting a detailed system architecture of the server 140, in accordance with an embodiment of the present disclosure. The embodiment of the server 140 as shown in Fig. 3 is for illustration only. However, the server 140 may come in a wide variety of configurations, and Fig. 3 does not limit the scope of the present disclosure to any particular implementation of the server 140.

[0082] As shown in Fig. 3, the server 140 includes an Input-Output (I / O) interface 302, one or more processors 304 (hereinafter may also be referred to as “processor 304” or “at least one processor 304”), a memory 306, a network communication manager 308, a communication interface 310, and a plurality of modules / units 312 (collectively referred to as the modules 312). Components of the server 150 are coupled to each other via a communication bus 314.

[0083] The I / O interface 302 may include suitable logic, circuitry, interfaces, and / or codes that may be configured to receive input(s). For example, the VO interface 302 may have an input interface and an output interface. The I / O interface 302 may be configured to enable the user to provide the user input(s) to trigger (or configure) the server 140 to perform various operations for detecting performance degradation or outage in the communication network 100. Examples of the input interface may include, but are not limited to, a touch interface, a mouse, and a keyboard, and the output interface includes a digital display, an analog display, or a touch screen display. Aspects of the present disclosure are intended to include or otherwise coverany type of the I / O interface 302 including known, related art, and / or later developed technologies without deviating from the scope of the present disclosure.

[0084] The processor 304 may include processing circuitry, logic, interface(s), and / or code(s), and may be configured to communicate with the I / O interface 302, the memory 306, the network communication manager 308, the communication interface 310, and the modules 312, via the communication bus 314. Examples of the communication bus 314 may include, but are not limited to, a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), Universal Serial Bus (USB), and a Front Side Bus (FSB). Aspects of the present disclosure are intended to include or otherwise cover any type of coupling means present or related to later developed technologies, that may be configured to for connect the processor 304 to the other subsystems of the server 140, as the communication bus 314, without deviating from the scope of the present disclosure.

[0085] The processor 304 may include various processing circuitry configured to execute instructions 306-1 (hereinafter also referred to as “a set of instructions 306-1”) stored in the memory 306 and to perform various processes. The processor 304 may also include a plurality of processing engines i.e., information processing units for detecting performance degradation or outage in the communication network 100. The processor 304 may be configured to handle a set of tasks or computations executed by the processor 304 in a distributed computing environment. For an example, the processor 304 is configured to execute programs and processes to execute instruction(s) or code(s) stored in the memory 306 pertaining to detection of performance degradation or outage in the communication network 100. The processor 304 is further configured to move data into or out of the memory 306 as required by an execution process of the server 140.

[0086] Examples of the processor 304 may include, but are not limited to, a Central Processing Unit (CPU), an Application Processor (AP), a dedicated processor, agraphics-only processing unit such as a Graphics Processing Unit (GPU), a programmable logic device, or any combination thereof.

[0087] The memory 306 is configured to store the set of instructions 306-1 required by the processor 304 for controlling overall operations of the server 140. A part of the memory 306 may include a Random -Access Memory (RAM), a cache memory, or a Read-Only Memory (ROM). The memory 306 may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of Electrically Programmable Memories (EPROM) or Electrically Erasable and Programmable (EEPROM) Memories. In addition, the memory 306 may, in some examples, be implemented using 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 that the memory 306 is non-movable. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in RAM or cache). The memory 306 can be an internal storage unit or it can be an external storage unit of the server 140, cloud storage, or any other type of external storage. In some embodiments, when the memory 306 is external to the server 150, the memory 306 may be removably attached to the server 140. Aspects of the present disclosure are intended to include or otherwise cover any data storage medium as ‘the memory 306’, without deviating from the scope of the present disclosure.

[0088] In an embodiment, the module(s) 312 may be implemented as a combination of hardware and software programming (for example, programmable instructions) to implement one or more functionalities of the server 140. In non-limiting examples, described herein, such combinations of hardware and software programming may be implemented in several different ways, without deviating from the scope of the present disclosure. The module(s) 312 may include suitable logic, circuitry, interfaces, and / or codes. For example, the programming for the module(s) 312 may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the module(s) 312 maycomprise a processing resource (for example, one or more processors), to execute such instructions. In an embodiment, the module(s) 312 may be combined to a single module or each module of the module(s) 312 may be further subdivided into different modules.

[0089] In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the module(s) 312. In such examples, the server 140 may also comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the server 140 and the processing resource. In other examples, the module(s) 312 may be implemented using an electronic circuitry.

[0090] In one or more embodiments, the module(s) 312 may include one or more modules such as an acquisition module 312-2, a processing module 312-4, and other modules (not shown in Fig. 3). The other modules may include a visualization generation module. Each of the module(s) 312 are communicatively coupled with each other.

[0091] In an embodiment, the processor 304, using the acquisition module 312-2, is configured to obtain, from the data collection entity 220, the trace data associated with the user devices 120 served by the plurality of serving cells 110 in the communication network 100. The trace data includes positional information of the user devices 120, identity information of the plurality of serving cells 110, serving area information associated with the plurality of serving cells 110, and performance metrics associated with the plurality of serving cells 110 and the plurality of the user devices 120 in the communication network 100.

[0092] The processor 304, using the processing module 312-4, identifies the group of serving cells from the plurality of serving cells 110 serving the pre-defined set of user devices. The pre-defined set of user devices may include a specific FWA or a set of FWAs corresponding to which an impact of performance degradation or outage is to be determined. The processing module 312-4 may identify the group ofserving cells based on the positional information of the pre-defined set of user devices 120, the serving area information associated with the serving cells 110, and the identity information of the serving cells 110 obtained from the trace data. In an embodiment, the processing module 312-4 may map the positional information of the pre-defined set of user devices 120 with the serving area information associated with the serving cells 110, and the identity information of the serving cells 110 obtained from the trace data.

[0093] Furthermore, the processor 304, using the processing module 312-4, determines the dominance percentage of each serving cell among the identified group of serving cells in the pre-defined time-period corresponding to the predefined set of user devices. For example, the dominance percentage of each serving cell in serving the pre-defined set of user devices may be determined for a week. Based on the dominance percentage determined for each serving cell, the processor 304, using the processing module 312-4, determines the set of dominant serving cells among the identified group of serving cells and the set of top serving cells among the identified group of serving cells.

[0094] The processor 304, using the processing module 312-4, determines whether at least one of the set of top serving cells and the set of dominant serving cells are facing outages. The determination of whether at least one of the set of top serving cells and the set of dominant serving cells are facing outages may be made by fetching performance data corresponding to each serving cell among the set of top serving cells and the set of dominant serving cells. Based on the performance data, the processor 304, using the processing module 312-4, identifies the one or more user devices among the pre-defined set of user devices among the pre-defined set of user devices served by one or more of the set of dominant serving cells and the set of top serving cells facing outages. Further, the processor 304, using the processing module 312-4, classifies the identified one or more user devices among the predefined set of user devices served by one or more of the set of dominant serving cells and the set of top serving cells as one of user device with complete outage or the user device with non-optimal outage.

[0095] The processor 304, may further refer to a repository of possible resolutions for the identified root cause of degradation in the serving cells stored in the database 312. Based on the possible resolutions, the processor 304 may provide the one or more recommendations to the user for corrective actions that may be performed on the identified group of serving cells. The generated plan may include, but not limited to, recommendations related to configuration parameter adjustments, hardware upgrades, antenna reorientation, and software upgrades associated with the identified serving cells. The processor 304, may further monitor performance of the identified group of serving cells and based on the performance of the identified group of serving cells, the processor 304 may validate that the root cause of degradation has been resolved and that the corrective actions are effective.

[0096] Furthermore, the processor 304, using the visualization generation module, is configured to generate visualization data for displaying information corresponding to the classification of user devices or grids impacted due to performance degradation or outage in the communication network 100. The visualization data may include information corresponding to the user devices or grids impacted due to performance degradation or outage, the identity information of the group of serving cells and the serving area information associated with the group of serving cells having degraded performance or outages. In another embodiment, the processor 304 may compile the visualization data in form of a report or in a map view and display to the user. In yet another embodiment, the visualization data may be shared as a notification with the user.

[0097] The network communication manager 308 may include suitable logic, circuitry, interfaces, and / or codes that may be configured to enable the I / O interface 302 to receive input(s) and / or render output(s). In some aspects of the present disclosure, the network communication manager 308 may include suitable logic, instructions, and / or codes for executing various operations of one or more computer executable applications to host a console on an external user device, by way of which a user can trigger the server 140 to detect performance degradation or outage in the communication network 100.

[0098] The communication interface 310 may manage communications with the NME 210, the network 130, the data collection entity 220, and the performance management entity 240. For example, the communication interface 310 may manage the reception of the trace data directly from the UEs 120 or through the data collection entity 220. The communication interface 310 may also manage the reception of the performance data from the performance management entity 240. The communication interface 310 may include an electronic circuit specific to a standard that enables wired or wireless communication. The communication interface 310 is configured for communicating with external devices via one or more networks. Further, the communication interface 310 may also provide a communication pathway for one or more components of the server 140. Examples of such components include, but are not limited to, the module(s) 312, the data collection entity 220, and the performance management entity 240.

[0099] Although FIG. 3 illustrates one example of server 140, various changes may be made to FIG. 3. For example, the server 140 may include any number of components in addition to the components shown in FIG. 3. Further, various components in FIG. 3 may be combined, further subdivided, or omitted and additional components may be added according to particular needs.

[0100] In an alternate embodiment, each module / unit of the module(s) / unit(s) 312 (i.e., the acquisition module 312-2, the processing module 312-4, and the visualization generation module) is configured to independently perform various operations of the processor 304, as described herein, without deviating from the scope of the present disclosure.

[0101] FIG. 4 illustrates a block diagram depicting an example system architecture 400 of the NME 210, in accordance with an embodiment of the present disclosure. In a configuration, the NME 210 may further include a User Interface (UI) for intuitive interaction, data processing units for real-time analysis, and storage units for data archiving. The embodiment of the NME 210 illustrated in FIG. 4 is for illustration only and other configurations of the NME 210 are possible.

[0102] As shown in FIG. 4, the NME 210 may be a user device including a desktop computer, a portable computing devices such as laptops, tablet computers, handheld computer, mobile phones, wearable computers, or any other device suitable to provide front end services. The NME 210 includes a processor 402, a memory 404, a Graphical User Interface (GUI) 406 for accessing different functionalities of the system, and a communication unit 408. Although not shown in FIG. 4, the NME 210 may also include, a touchscreen, and a display. The server 140 may control the overall operation of the NME 210.

[0103] The one or more components of the NME 210 are communicatively coupled with the processor 402 (described below) for accessing different functionalities of the system 200. The processor 402 may include various processing circuitry and configured to execute programs or computer readable instructions stored in the memory 404. The processor 402 may also 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 microcontroller, a Field-Programmable Gate Array (FPGA), a programmable logic device, a discrete hardware component, or any combination thereof. In some cases, the processor 402 may be configured to operate a memory array using a memory controller. In some cases, a memory controller may be integrated into the processor 402. The processor 402 may be configured to execute computer-readable instructions stored in a memory (e.g., the memory 404) to cause the NME 210 to perform various functions (e.g., for displaying the visualization data received from the server 140). The processor 402 is configured to execute programs and instructions stored in the memory 404. The processor 402 is further configured to move data into or out of the memory 404 as required by an executing process.

[0104] The memory 404 is communicatively coupled to the processor 402. A part of the memory 404 may include a RAM, and another part of the memory 404 may include a flash memory or other ROM. The memory 404 is configured to store a set of instructions required by the processor 402 for controlling overall operations ofthe NME 210. The memory 404 may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of EPROM or EEPROM memories. In addition, the memory 404 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 that the memory 404 is non-movable. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in the RAM or cache). The memory 404 can be an internal storage unit or it can be an external storage unit of the NME 210, cloud storage, or any other type of external storage.

[0105] More specifically, the memory 404 may store computer-readable instructions including instructions that, when executed by a processor (e.g., the processor 402) cause the NME 210 to perform various functions described herein. In some cases, the memory 404 may contain, among other things, a BIOS which may control basic hardware or software operation such as the interaction with peripheral components or devices.

[0106] The server 140 may control, through a UI framework, the GUI 406 of the NME 210 to display the visualization data indicating information corresponding to classified one or more user devices among the pre-defined set of user devices 120 impacted due to performance degradation or outage in the communication network 100. The server 140 may further display, via the GUI 406, the visualization data indicating one or more grids facing performance degradation or outage corresponding to a geographical region. Alternatively, the server 140 may display, via the GUI 406, the visualization data indicating that there are no user device with complete outage or user device with non-optimal outage. Similarly, the server 140 may display, via the GUI 406, the visualization data indicating that information that there are no outage grids or non-optimal grids.

[0107] The server 140 may also control the GUI 406 to display the visualization data as the report including an identity information of the one or more user devices and the serving area information associated with the dominant set of serving cells and / or top service cells facing performance degradation or outages. The report may be displayed on the GUI 406 in one or more of a pictorial format, a graphical format, and a tabular format.

[0108] The communication unit 408 may include one or more antennas, one or more of Radio Frequency (RF) transceivers, a transmit processing circuitry, and a receive processing circuitry. The communication unit 408 may be configured to receive incoming signals, such as signals transmitted by the server 140, and the NME 210. The communication unit 408 may down-convert the incoming signals to generate baseband signals which may be sent to the receiver processing circuitry. The receiver processing circuitry may transmit the processed baseband signals to the processor 402 for further processing. The transmit processing circuitry may receive analog or digital data from the processor 402 and may encode, multiplex, and / or digitize the outgoing baseband data to generate processed baseband signals. The communication unit 408 may further receive the outgoing processed baseband from the transmit processing circuitry and up-converts the baseband signals to Radio Frequency (RF) signals that may be transmitted to the server 140.

[0109] The NME 210 may be deployed as a software application on a dedicated server, a cloud-based solution, or a hybrid system, depending on the communication network requirements. The NME 210 may be utilized by network administrators of the network operations team for receiving information corresponding to the classification of user devices or grid impacted due to performance degradation or outage in the communication network 100. Additionally, the NME 210 may be integrated with network monitoring tools, database management systems, and security modules to provide a holistic view of the performance of dominant serving cells in form of the network performance report. Upon retrieving the performance metrics analysis of the serving cells 110 and information of the user devices and grids facing outage, the server 140 is configured to control the GUI 406 to providean intuitive control to the network administrators to manage display of graphical elements such as charts, diagrams, or highlighted text that enhance the comprehension and presentation of the report.

[0110] Although FIG. 4 illustrates one example of NME 210, various changes may be made to FIG. 4. For example, various components in FIG. 4 could be combined, further subdivided, or omitted, and additional components could be added according to particular needs. As a particular example, the processor 402 may be divided into multiple processors, such as one or more CPUs and one or more GPUs. Further, while FIG. 4 illustrates the NME 210 configured as a mobile telephone or smartphone, the NME 210 may also be configured to operate as other types of mobile or stationary devices.

[0111] FIG. 5 illustrates an exemplary method 500 for detecting performance degradation or outage for the user device in the communication network, in accordance with an embodiment of the present disclosure. The method 500 comprises a series of operations steps indicated by blocks 502 through 516 performed by the server 140. The method 500 begins at block 502.

[0112] At step 502, the processor 304, using the acquisition module 312-2, collects the trace data from the pre-defined set of the user devices 120 via the data collection entity 220 over a pre-defined time period, say a week, and stores the trace data in the database 230. The pre-defined set of user devices 120 may include the user devices operating in the geographical location during the pre-defined time period. In one embodiment, the trace data may be collected from the user devices 120 over the pre-defined time-period. In a non-limiting example, the trace data may include samples of information about the user device 120 and event-based information experienced by the user while accessing services of the network 130. Using the trace data, the server 140 may particularly identify, among other information, information related to location of the user device 120 and the performance metrics of the user devices 120 and the serving cells 110.

[0113] At step 504, the processor 304, using the processing module 312-4, identifies the group of serving cells from the serving cells 110 serving the pre-defined set of user devices 120. The serving cells may be identified based on the positional information of the pre-defined set of user devices 120 obtained from the trace data. Corresponding to the positional information of the pre-defined set of user devices 120, the serving cells serving the pre-defined set of user devices 120 by mapping the serving area information associated with the serving cells 110 and the identity information of the serving cells 110 obtained from the trace data.

[0114] At step 506, the processor 304, using the processing module 312-4, processes the samples of the trace data to determine the dominance percentage of each serving cell among the identified group of serving cells. The dominance percentage for the serving cell is determined based on a ratio of the number of samples of the trace data served by the serving cell and the total samples corresponding to the pre-defined set of user devices 120.

[0115] Based on the dominance percentage of each serving cell among the identified group of serving cells, the processor 304, using the processing module 312-4, identifies the set of dominant serving cells among the identified group of serving cells and the set of top serving cells among the identified group of serving cells. The set of dominant serving cells may correspond to the serving cells having a dominance percentage greater than the first pre-defined dominance percentage. The set of top serving cells may correspond to the serving cells having a dominance percentage equal to or greater than a second pre-defined dominance percentage. The second pre-defined dominance percentage may be equal to or greater than the first pre-defined dominance percentage. Values of the first pre-defined dominance percentage and the second pre-defined dominance percentage may be configured by the network operators’ team.

[0116] In one embodiment, before processing of the samples of the trace data, the processing module 312-4 may perform pre-processing operations over the trace data. The pre-processing operations may include operations such as data cleaningand data validation. The trace data may be cleaned to remove inconsistent, incomplete, duplicate, and inaccurate samples of the trace data. The processing module 312-4, may then validate the trace data for ensuring consistency of the samples of the trace data.

[0117] At step 508, the processor 304, using the processing module 312-4, fetches performance data corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells from the performance management entity 240. In an embodiment, from the performance data, the processing module 312-4 may utilize the alarm information to determine whether at least one of the set of top serving cells and the set of dominant serving cells are facing outages.

[0118] At step 510, based on the alarm information fetched corresponding to the set of dominant serving cells and the set of top serving cells, the processor 304, using the processing module 312-4, determines whether the alarm information comprises one or more live outage alarms corresponding to the at least one of the set of top serving cells and the set of dominant serving cells. Based on the determination of the one or more live outage alarms, the processor 304, using the processing module 312-4, determines that the at least one of the set of top serving cells and the set of dominant serving cells are facing outages, based on the mapping of the one or more outage alarms corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells.

[0119] At step 512, based on determination that at least one of the set of top serving cells and the set of dominant serving cells are facing outages, the processor 304, using the processing module 312-4, identifies the one or more user devices among the pre-defined set of user devices 120 served by one or more of the set of dominant serving cells and the set of top serving cells facing outages and impacted due to performance degradation or outage in the at least one of the set of top serving cells and the set of dominant serving cells.

[0120] The processor 304, using the processing module 312-4, further then classifies the identified the one or more user devices among the pre-defined set ofuser devices 120 facing performance outage into user device with complete outage and non-optimal outage user device. In one or more embodiments of the present disclosure, the user device with complete outage may include the FWAs impacted due to outage among the group of serving cells in the communication network 100. The user device with complete outage corresponds to user devices served by the set of dominant serving cells facing outage simultaneously. In one or more embodiments of the present disclosure, the user device with non-optimal outage may include the FWAs impacted due to degradation in performance of the group of serving cells in the communication network 100. The user device with non-optimal outage corresponds to at least one top serving cell facing outage alarms when other dominant serving cells are operational. The method then proceeds to step 514.

[0121] For an example, a group of four serving cells are identified to serve a predefined set of FWAs. The processor 304 determines the dominance percentage corresponding to each of the four serving cells. In a scenario, a first serving cell of the four serving cells may have a dominance percentage of 38%, a second serving cell of the four serving cells may have a dominance percentage of 30%, a third serving cell of the four serving cells may have a dominance percentage of 28%, and a fourth serving cell of the four serving cells may have a dominance percentage of 10%. Further, the processor 304 identifies the set of dominant serving cells among the identified group of serving cells and the set of top serving cells among the identified group of serving cells. The processor 304 determines that when the first pre-defined dominance percentage is 25% and the second pre-defined dominance percentage is 35%, the first serving cell is a top serving cell. Similarly, the first serving cell, the second serving cell, and the third serving cell are the dominant serving cells. The processor 304 determines that the group of serving cells comprises three dominant serving cells and one top serving cell.

[0122] In a scenario, when out of the four serving cells, the first serving cell, the second serving cell, and the third serving cell are facing outage, one or more FWAs among the pre-defined set of FWAs is classified as the user device with complete with outage.

[0123] In a scenario, when out of the four serving cells, the first serving cell is facing outage, one or more FWAs among the pre-defined set of FWAs is classified as the user device with non-optimal outage.

[0124] At step 514, the processor 304, using the processing module 312-4, sends information corresponding to the user device with complete outage and the user device with non-optimal outage to the NME 210. The network operations team may then prioritize to perform Root Cause Analysis (RCA) of degradation of performance corresponding to the serving cells affecting the user device with complete outage and the non-optimal outage user device, recovery and / or optimization of the one or more of the top serving cells and the set of dominant serving cells, and corrective actions for recovery of the set of top serving cells and the set of dominant serving cells. The network operations team may further take necessary action to prioritize for brining into operation the serving cells affecting a majority of user devices.

[0125] However, based on determination at step 512 that at none of the set of top serving cells and the set of dominant serving cells are facing outages, the method proceeds to step 516. At step 516, the server 140 sends information corresponding to none of the one or more user devices among the pre-defined set of user devices 120 facing outages or non-optimal outages.

[0126] In another embodiment, the system and the method may be utilized for detecting performance degradation or outage in the communication network using trace data collected from user devices of a particular geographic region. The server 140 is configured to divide a coverage region or a geographical region into a plurality of grids covering a pre-defined area. The server 140 processes the trace data collected from user devices 120 operating in the coverage region over the predefined time-period corresponding to the plurality of grids. The trace data is mapped on the plurality of grids based on the positional information. Upon processing the trace data, the server 140 identifies the group of serving cells serving the userdevices 120 operating in the plurality of grids. The pre-defined time-period may be a day, a week, or a fortnight.

[0127] The server 140 selects a pre-defined grid from the plurality of grids. The server 140 further determines a dominance percentage of each serving cell among the identified group of serving cells in the pre-defined grid. The dominance percentage is determined based on a ratio of a number of samples of the trace data served by each serving cell and the total samples obtained from the pre-defined grid. The dominance percentage for a serving cell indicates one or more serving cells among the group of serving cells that serves a majority of the user devices 120 corresponding to the pre-defined grid in the pre-defined time-period.

[0128] FIG. 6 illustrates an exemplary method 600 for detecting performance degradation or outage in a grid in the communication network, in accordance with an embodiment of the present disclosure. The method 600 comprises a series of operations steps indicated by blocks 602 through 618 performed by the server 140. The method 600 begins at block 602.

[0129] At step 602, the processor 304, using the processing module 312-4, may divide the coverage region or the geographical region into the plurality of grids. Each of the plurality of grids may cover a pre-defined area (AxA meters). For example, area of a grid may be 60x60 m. The term “grid” refers to a predefined spatial unit into which a larger geographical area is divided for the purpose of data analysis and coverage evaluation. Each grid corresponds to a fixed area (e.g., 100m x 100m) and serves as a container for collecting and processing network performance data from wireless nodes or devices within its boundaries. The grids may correspond to non-overlapping square regions defined using geographical coordinates or network coverage maps.

[0130] At step 604, the processor 304, using the acquisition module 312-2, obtains the trace data from the user devices 120 from at least one pre-defined grid among the plurality of grids over the pre-defined time-period from the coverage region. The trace data may be collected from the user devices 120 via the data collection entity220 over the pre-defined time period, say a week, and stores the trace data in the database 230, and mapped over the plurality of grids. In a non-limiting example, the trace data may include samples of information about the user device 120 and eventbased information experienced by the user while accessing services of the network 130. Using the trace data, the server 140, may particularly identify, among other information, information related to location of the user device 120 and the performance metrics of the serving cells 110 and the user device 120. The trace data is mapped to the plurality of grids in the coverage region.

[0131] At step 606, the processor 304, using the processing module 312-4, identifies the group of serving cells from the serving cells 110 serving the user devices 120 in at the least one pre-defined grid among the plurality of grids. The group of serving cells may be identified based on the trace data.

[0132] At step 608, the processor 304, using the processing module 312-4, processes the samples of the trace data to identify the dominance percentage of each serving cell among the identified group of serving cells in the at least one predefined grid. The dominance percentage for the serving cell is determined based on a ratio of number of samples of the trace data served by each serving cell and the total samples corresponding to the pre-defined grid.

[0133] Based on the dominance percentage of each serving cell among the identified group of serving cells, the processor 304, using the processing module 312-4, identifies the set of dominant serving cells among the identified group of serving cells and the set of top serving cells among the identified group of serving cells in the at least one pre-defined grid. The set of dominant serving cells may correspond to the serving cells having a dominance percentage greater than the first pre-defined dominance percentage. The set of top serving cells may correspond to the serving cells having a dominance percentage equal to or greater than the second pre-defined dominance percentage. The second pre-defined dominance percentage may be equal to or greater than the first pre-defined dominance percentage. Values of the first pre-defined dominance percentage and the second pre-defineddominance percentage may be configured by a network operators’ team. Similarly, corresponding to each grid among the plurality of grids from the coverage region, the dominance percentage of each serving cells may be determined.

[0134] At step 610, the processor 304, using the processing module 312-4, fetches the performance data from the performance management entity 240, corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells in the pre-defined grid. The processor 304, using the processing module 312-4, may utilize alarm information from the performance data to identify whether the at least one pre-defined grid is impacted with performance outage.

[0135] At step 612, based on the alarm information and the dominance percentage of the identified group of serving cells, the processor 304, using the processing module 312-4, determines whether at least one of the set of top serving cells and the set of dominant serving cells in the at least one pre-defined grid is facing outages.

[0136] Based on determination that at least one of the set of top serving cells and the set of dominant serving cells are facing outages, the processor 304, using the processing module 312-4, determines that the at least one pre-defined grid is facing performance degradation or outage. Similarly, based on the alarm information fetched corresponding to the set of dominant serving cells and the set of top serving cells in the identified group of serving cells, one or more grids among the plurality of grids impacted with performance outage is identified.

[0137] At step 614, the processor 304, using the processing module 312-4, further classifies the identified at least one pre-defined grid facing performance outage into complete outage and non-optimal outage grid. The complete outage grid may include a grid served by the set of dominant serving cells facing outage simultaneously and impacted due to outage among the group of serving cells in the communication network 100. The non-optimal outage grid may include a gird served by at least one top serving cell facing outage when serving cells among the set of dominant serving cells are operational and impacted due to degradation in performance of the group of serving cells in the communication network 100.Similarly, the processor 304, using the processing module 312-4, further classifies the identified one or more grids facing performance outage into complete outage and non-optimal outage grids.

[0138] For an example, a group of four serving cells are identified to serve a grid. The group of serving cells may comprise three dominant serving cells and one top serving cell. A first serving cell of the four serving cells may have a dominance percentage of 42%, a second serving cell of the four serving cells may have a dominance percentage of 37%, a third serving cell of the four serving cells may have a dominance percentage of 28%, and a fourth serving cell of the four serving cells may have a dominance percentage of 5%. When the first pre-defined dominance percentage is 25% and the second pre-defined dominance percentage is 35%, the first serving cell is a top serving cell. Similarly, the first serving cell, the second serving cell, and the third serving cell are the dominant serving cells.

[0139] In a scenario, when out of the four serving cells, the first serving cell, the second serving cell, and the third serving cell are facing outage, the grid is classified as complete outage grid.

[0140] In a scenario, when out of the four serving cells, the first serving cell is facing outage, the grid is classified as non-optimal outage grid.

[0141] At step 616, the processor 304, using the processing module 312-4, sends information corresponding to the complete outage grid and the non-optimal outage grid to the NME 210. The network operations team may then prioritize to perform Root Cause Analysis (RCA) of degradation of performance corresponding to the serving cells affecting the complete outage grid and the non-optimal outage grid, recovery and / or optimization of the one or more of the top serving cells and the set of dominant serving cells, and corrective actions for recovery of the set of top serving cells and the set of dominant serving cells. The network operations team may further take necessary action to prioritize for brining into operation the serving cells affecting a majority of users in various grids.

[0142] However, based on determination at step 612 that none of the set of top serving cells and the set of dominant serving cells are facing outages, the method proceeds to step 618. At step 618, the server 140 sends information corresponding to none of the one or more grids facing outages or non-optimal outages.

[0143] Now, referring to the technical abilities and advantageous effect of the present disclosure, operational advantages that may be provided by one or more embodiments may include identifying impact of the serving cells undergoing a service affecting issues or outage in the communication network. Identification of performance degradation or outage in the communication network further enables the network operation team to analyze and perform a quick corrective action on serving cells facing outages affecting a majority of user devices for enhancing user experience. Another notable advantage offered by the present disclosure includes identification of the serving cells undergoing service affecting issues or outages in the communication network that have an overlapping impact on various FWAs.

[0144] Embodiments of the present technology may be described herein with reference to flowchart illustrations of methods and systems according to embodiments of the technology, 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 methods.

[0145] 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 306) that can direct a computer processor or other programmable processing apparatus to function in a particular manner, such that the instructions 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).

[0146] 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 304) to perform one or more functions as described herein. The instructions may also be stored remotely such as on a server, or all or a portion of the instructions can be stored locally and remotely.

[0147] 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 invention. The above-described embodiments are therefore to be construed in all aspects as illustrative and not restrictive.

[0148] 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.

[0149] 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 disclosedherein 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

[0150] 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 recited near 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 - Exemplary communication network110 - Plurality of serving cells120 - Plurality of user devices130 - Network140 - Server200 - System for detecting communication network performance degradation or outage for the user device210 - Network Management Entity (NME)220 - Data collection entity230 - Database240 - Performance management entity302 - Input-Output (I / O) interface304 - Processor(s)306 - Memory306-1 - Instructions308 - Network communication manager310 - Communication interface312 - Plurality of modules / units312-2 - Acquisition Module312-4 - Processing Module314 - Communication bus400 - System architecture of the NME402 - Processor404 - Memory406 - Graphical user interface408 - Communication unit500 - Method for detecting communication network performance degradation or outage for the user device502-514 - Operation steps of the method 500600 - Method for detecting performance degradation or outage in a grid the communication network602-616 - Operation steps of the method 600

Claims

WE CLAIM:

1. A method (500, 600) for detecting performance degradation or outage in a communication network, the method (500, 600) comprising:obtaining, by an acquisition module (312-2) from a data collection entity (220), trace data associated with a plurality of user devices (120) served by a plurality of serving cells (110) in the communication network;identifying, by a processing module (312-4) based on the trace data, a group of serving cells from the plurality of serving cells (110) serving a pre-defined set of user devices among the plurality of user devices (120);determining, by the processing module (312-4) in a pre-defined timeperiod, a dominance percentage of each serving cell among the group of serving cells corresponding to the pre-defined set of user devices;determining, by the processing module (312-4) based on the determined dominance percentage, a set of dominant serving cells among the group of serving cells and a set of top serving cells among the group of serving cells; andclassifying, by the processing module (312-4) as one of a first user device or a second user device, one or more user devices among the predefined set of user devices served by the set of dominant serving cells and the set of top serving cells based on a determination of an outage at one or more of the set of top serving cells and the set of dominant serving cells.

2. The method (500, 600) as claimed in claim 1, further comprising:fetching, by the processing module (312-4), performance data corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells, whereinthe performance data includes one or more of values of a plurality of Key Performance Indicators (KPIs) associated with each serving cell and alarm information corresponding to each serving cell,the determination of the outage at the one or more of the set of top serving cells and the set of dominant serving cells is based on the performance data, andthe one or more user devices among the pre-defined set of user devices served are identified for the classification based on of the outage.

3. The method (500, 600) as claimed in claim 2, whereinthe alarm information comprises one or more outage alarms, and the outage at the one or more of the set of top serving cells and the set of dominant serving cells is determined based on a mapping of the one or more outage alarms corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells, and a comparison of a corresponding value of the plurality of KPIs with a corresponding predefined threshold value.

4. The method (500, 600) as claimed in claim 1, wherein the dominance percentage of each serving cell is determined based on a ratio of a number of samples of the trace data corresponding to each serving cell among the group of serving cells and a total number of samples of the trace data collected from the pre-defined set of user devices.

5. The method (500, 600) as claimed in claim 1, wherein:the set of dominant serving cells have a dominance percentage greater than a first pre-defined dominance percentage;the set of top serving cells have a dominance percentage greater than a second pre-defined dominance percentage; andthe second pre-defined dominance percentage is greater than the first pre-defined dominance percentage.

6. The method (500, 600) as claimed in claim 1, wherein:the first user device is served by the set of dominant serving cells that are simultaneously facing the outage,the second user device is served by at least one top serving cell that is facing the outage, and at least one dominant serving cell among the set of dominant serving cells is operational,the first user device corresponds to a user device with complete outage impacted due to the outage at the group of serving cells, and the second user device corresponds to a user device with non-optimal outage impacted due to a degradation in performance of the group of serving cells.

7. The method (500, 600) as claimed in claim 1, wherein the trace data includes one or more of positional information of the plurality of user devices (120), identity information of the plurality of serving cells (110), serving area information associated with the plurality of serving cells (110), and performance metrics associated with the plurality of serving cells (110) and the plurality of the user devices.

8. The method (500, 600) as claimed in claim 1, comprising sending, by the processing module (312-4), information corresponding to the classification of the first user device and the second user device to a Network Management Entity (NME) (210) for performing Root Cause Analysis (RCA) of performance degradation or outage corresponding to one or more of the set of top serving cells and the set of dominant serving cells and corrective actions for recovery of the set of top serving cells and the set of dominant serving cells.

9. A system (200) for detecting performance degradation or outage in a communication network, the system (200) comprising:an acquisition module (312-2) configured to obtain, from a data collection entity (220), trace data associated with a plurality of user devices (120) served by a plurality of serving cells (110) in the communication network; anda processing module (312-4) configured to:identify, based on the trace data, a group of serving cells from the plurality of serving cells (110) serving a pre-defined set of user devices;determine, in a pre-defined time-period, a dominance percentage of each serving cell among the group of serving cells corresponding to the pre-defined set of user devices;determine, based on the determined dominance percentage, a set of dominant serving cells among the group of serving cells and a set of top serving cells among the group of serving cells; and classify as one of a first user device or a second user device, one or more user devices among the pre-defined set of user devices served by the set of dominant serving cells and the set of top serving cells based on a determination of an outage at one or more of the set of top serving cells and the set of dominant serving cells.

10. The system (200) as claimed in claim 9, the processing module (312-4) is further configured to:fetch performance data corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells, wherein the performance data includes one or more of values of a plurality of Key Performance Indicators (KPIs) associated with each serving cell and alarm information corresponding to each serving cell,the determination of the outage at the one or more of the set of top serving cells and the set of dominant serving cells is based on the performance data, andthe one or more user devices among the pre-defined set of user devices served are identified for the classification based on the determination of the outage.

11. The system (200) as claimed in claim 10, wherein:the alarm information comprises one or more outage alarms, andthe outage at the one or more of the set of top serving cells and the set of dominant serving cells is determined based on a mapping of the one or more outage alarms corresponding to each serving cell among the set of dominant serving cells and the set of top serving cells, and a comparison of a corresponding value of the plurality of KPIs with a corresponding predefined threshold value.

12. The system (200) as claimed in claim 9, wherein the dominance percentage of each serving cell is determined based on a ratio of a number of samples of the trace data corresponding to each serving cell among the group of serving cells and a total number of samples of the trace data collected from the pre-defined set of user devices.

13. The system (200) as claimed in claim 9, wherein:the set of dominant serving cells have a dominance percentage greater than a first pre-defined dominance percentage;the set of top serving cells have a dominance percentage greater than a second pre-defined dominance percentage; andthe second pre-defined dominance percentage is greater than the first pre-defined dominance percentage.

14. The system (200) as claimed in claim 9, wherein:the first user device is served by the set of dominant serving cells that are simultaneously facing the outage,the second user device is served by at least one top serving cell that is facing the outage, and at least one dominant serving cell among the set of dominant serving cells is operational,the first user device corresponds to a user device with complete outage impacted due to the outage at the group of serving cells, and the second user device corresponds to a user device with non-optimal outage impacted due to a degradation in performance of the group of serving cells.

15. The system (200) as claimed in claim 9, wherein the trace data includes one or more of positional information of the plurality of user devices (120), identity information of the plurality of serving cells (110), serving area information associated with the plurality of serving cells (110), and performance metrics associated with the plurality of serving cells (110) and the plurality of the user devices.

16. The system (200) as claimed in claim 9, wherein the processing module (312-4) is further configured to send information corresponding to the classification of the first user device and the second user device to a Network Management Entity (NME) (210) for performing Root Cause Analysis (RCA) of performance degradation or outage corresponding to one or more of the set of top serving cells and the set of dominant serving cells and corrective actions for recovery of the set of top serving cells and the set of dominant serving cells.

17. 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:obtaining, from a data collection entity, trace data associated with a plurality of user devices served by a plurality of serving cells in a communication network;identifying, based on the trace data, a group of serving cells from the plurality of serving cells serving a pre-defined set of user devices among the plurality of user devices;determining, in a pre-defined time-period, a dominance percentage of each serving cell among the group of serving cells corresponding to the pre-defined set of user devices;determining, based on the determined dominance percentage, a set of dominant serving cells among the group of serving cells and a set of top serving cells among the group of serving cells; andclassifying, as one of a first user device or a second user device, one or more user devices among the pre-defined set of user devices served by the set of dominant serving cells and the set of top serving cells based on a determination of an outage at one or more of the set of top serving cells and the set of dominant serving cells.

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