DESC:FORM 2
THE PATENTS ACT, 1970 (39 OF 1970)
&
THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)

SYSTEM AND METHOD FOR ANOMALY DETECTION IN RADIO UNITS OF COMMUNICATION SYSTEMS

Jio Platforms Limited, an Indian company, having registered address at Office -101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad - 380006, Gujarat, India

The following complete specification particularly describes the disclosure and the manner in which it is performed.

SYSTEM AND METHOD FOR ANOMALY DETECTION IN RADIO UNITS OF COMMUNICATION SYSTEMS

TECHNICAL FIELD

[0001] The embodiments of the present disclosure generally relate to a field of telecommunications. More particularly, the present disclosure relates to a system and a method for identification of anomalies in Radio Units of telecom towers associated with 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] In the field of telecommunications, efficient operation of telecom towers is paramount for seamless connectivity. These towers house various critical components, including Radio Units, which play a pivotal role in transmitting and receiving signals to ensure uninterrupted communication for mobile users.

[0004] Recently, a concerning issue has emerged within the telecom network infrastructure i.e., anomalies in the Radio Units leading to a significant surge in energy consumption. Traditionally, the Radio Units are designed to operate within specified power thresholds to maintain optimal performance while minimizing energy expenditure. However, occurrence of the anomalies, characterized by deviations from expected behavior, has disrupted this equilibrium.

[0005] The anomalies are identified in several forms, ranging from sporadic spikes in energy consumption to sustained periods of elevated power usage. These deviations not only strain the tower's power supply infrastructure but also incur additional operational costs for telecom service providers. Moreover, the prolonged exposure to heightened energy levels poses a potential risk of equipment degradation and premature failure, further exacerbating the situation.

[0006] Identifying root cause of these anomalies presents a formidable challenge for telecom engineers and network operators. Possible factors contributing to the issue include faulty hardware components, software glitches, environmental factors, or even malicious interference. Without timely intervention and mitigation measures, the continued prevalence of the anomalous energy consumption in the Radio Units threatens to compromise network reliability, service quality, and operational efficiency. Considering the challenges, there is a need for a system and a method for the identification of the anomalies in the Radio Units of the telecom towers.

SUMMARY

[0007] 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.
[0008] According to an embodiment of the present disclosure, a method for anomaly detection in multiple Radio Units (RUs) in a wireless communication network is described. The method includes receiving communication data from each RU of the multiple RUs. The method further includes retrieving first data and second data from the communication data. The first data comprises information related to specification of a corresponding RU and Physical Resource Block (PRB) utilization of the corresponding RU. The second data comprises information related to energy consumption of the corresponding RU. Furthermore, the method includes identifying a plurality of RUs from the multiple RUs. The plurality of RUs have same first data amongst the multiple RUs. Furthermore, the method includes determining a value of energy consumption for each RU of the plurality of RUs using the second data for each RU of the plurality of RUs. Furthermore, the method includes determining at least one RU from the plurality of RUs as at least one anomalous RU, based on a determination that the value of the energy consumption of the at least one RU is beyond a predefined energy consumption range. Furthermore, the method includes determining at least one anomaly indicator from a set of anomaly indicators based on the second data, for each RU of the at least one anomalous RU.

[0009] In some aspects of the present disclosure, the method further includes generating a work order for each of the at least one anomalous RU based on the at least one anomaly indicator.

[0010] In some aspects of the present disclosure, the specification of the RU is associated with an equipment type for the RU and the PRB utilization of the RU is associated with data traffic associated with the RU.

[0011] In some aspects of the present disclosure, the information related to energy consumption of the RU comprises data elements related to a service performance value of the RU, an interference level of the RU, and a communication coverage area of the RU.

[0012] In some aspects of the present disclosure, the set of anomaly indicators comprises a performance indicator, an interference indicator, and a coverage area indicator.

[0013] In some aspects of the present disclosure, the performance indicator is triggered when the service performance value of the at least one anomalous RU is lower than a predefined performance value. Moreover, the interference indicator is triggered when the interference level of the at least one anomalous RU is higher than a predefined interference level. Furthermore, the coverage area indicator is triggered when the communication coverage area of the at least one anomalous RU is lower than a predefined communication coverage area.

[0014] According to another embodiment, a system of anomaly detection in the plurality of RUs in the wireless network is described. The system includes the multiple data and a data processing server communicatively coupled to each other. The multiple RUs are configured to transmit communication data to the data processing server. and a data processing server communicatively coupled to each other. The plurality of RUs is configured to transmit communication data to the data processing server. The data processing server includes a memory and a data processing circuitry. The data processing circuitry includes a data exchange engine, an anomaly detection engine, and an anomaly type detection engine. The data exchange engine is configured to receive the communication data from each RU of the multiple RUs. The data exchange engine is further configured to retrieve first data and second data from the communication data. The first data comprises information related to specification of a corresponding RU and Physical Resource Block (PRB) utilization of the corresponding RU. The second data comprises information related to energy consumption of the corresponding RU. The anomaly detection engine is configured to identify a plurality of RUs from the multiple RUs, where the plurality of RUs have same first data amongst the multiple RUs. The anomaly detection engine is further configured to determine a value of energy consumption for each RU of the plurality of RUs using the second data for each RU of the plurality of RUs. Furthermore, the anomaly detection engine is configured to determine at least one RU from the plurality of RUs as at least one anomalous RU, based on a determination that the value of the energy consumption of the at least one RU is beyond a predefined energy consumption range. The anomaly type detection engine is configured to determine at least one anomaly indicator from a set of anomaly indicators based on the second data, for each RU of the at least one anomalous RU.

BRIEF DESCRIPTION OF DRAWINGS

[0018] 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:

FIG. 1 illustrates a block diagram depicting a system for anomaly detection in Radio Units in a wireless communication network, in accordance with an exemplary embodiment of the present disclosure.
FIG. 2 illustrates a block diagram depicting a data processing server, in accordance with an exemplary embodiment of the present disclosure.

FIG. 3 presents a flow chart that depicts a method for anomaly detection in the Radio Units in the wireless communication network, in accordance with an exemplary embodiment of the present disclosure.

LIST OF REFERENCE NUMERALS

101 - Radio Unit cluster
102 - Radio Unit
104 - Data Processing Server
106 - Network
108 - Data Processing Circuitry
110 - Server Memory
112 - Communication Interface
113 - Database (External)
114 – User Device (External)
200 - Input-Output (I/O) Interface
202 - Console Host
203 - First Communication Bus
204 - Data Exchange Engine
206 - Anomaly Detection Engine
208 - Anomaly Type Detection Engine
210 – Notification Engine
212 - Work Order Engine
214 - Instructions Repository
216 - Specification Data Repository
218 - Physical Resource Block (PRB) Data Repository
220 - Regular Data Repository
222 - Anomaly Data Repository
226 - Second Communication Bus

DETAILED DESCRIPTION OF THE INVENTION

[0019] 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.

[0020] 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.

[0021] 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.”

[0022] The term “comprising,” when utilized, means “including, but not necessarily limited to;” it specifically indicates open-ended inclusion in the so-described one or more listed features, elements in a combination, unless otherwise stated with limiting language. Furthermore, to the extent that the terms “includes,” “has,” “have,” “contains,” and other similar words are used in either the detailed description, such terms are intended to be inclusive in a manner similar to the term “comprising.”

[0023] 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.

[0024] The description provided herein discloses exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the present disclosure. Rather, the foregoing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing any of the exemplary embodiments. Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it may be understood by one of the ordinary skilled in the art that the embodiments disclosed herein may be practiced without these specific details.

[0025] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein the description, the singular forms "a", "an", and "the" include plural forms unless the context of the invention indicates otherwise.

[0026] The terminology and structure employed herein are for describing, teaching, and illuminating some embodiments and their specific features and elements and do not limit, restrict, or reduce the scope of the present disclosure. Accordingly, unless otherwise defined, all terms, and especially any technical and/or scientific terms, used herein may be taken to have the same.

[0027] Various embodiments of the present disclosure illustrate a system and a method for anomaly detection in Radio Unit(s) of telecom towers in a wireless communication network. In some aspects of the present disclosure, the various embodiments of the present disclosure relate to identification of Radio Units where energy consumption significantly deviates from average energy consumption of all the Radio Units with same Physical Resource Block (PRB) utilization, indicating potential anomalies. In some aspects of the present disclosure, the system, by way of the method, performs operation(s) for assessing coverage area served by the Radio Units to determine potential performance degradation and identify areas of concern. In some aspects of the present disclosure, the system and the method provide operations for assessing coverage area served by the Radio Units to determine potential performance degradation and identify areas of concern. In some other aspects of the present disclosure, the system and the method provide operations for initiating corrective actions or generating work orders to address identified issues, ensuring timely resolution and optimization of network performance.

[0028] 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.

[0029] The various aspects including the example aspects are now described more fully with reference to the accompanying drawings, in which the various aspects of the disclosure are shown. The disclosure may, however, be embodied in different forms and should not be construed as limited to the aspects set forth herein. Rather, these aspects are provided so that this disclosure is thorough and complete, and fully conveys the scope of the disclosure to those skilled in the art. In the drawings, the sizes of components may be exaggerated for clarity.

[0030] FIG. 1 illustrates a block diagram that depicts a system 100 for anomaly detection in Radio Units in a wireless network, in accordance with exemplary embodiments of the present disclosure. The embodiments of the system 100 shown in FIG. 1 are for illustration only. Other embodiments of the system 100 may be used without departing from the scope of this disclosure.

[0031] The system 100 includes a Radio Unit cluster 101 comprising multiple Radio Units 102 (i.e., presented by way of first through fourth Radio Units 102a-102d) and a data processing server 104 communicatively coupled to each other by way of a network 106. The clustered architecture (i.e., the Radio Unit cluster 101) allows for scalable and distributed deployment of the Radio Units 102 (hereinafter interchangeably referred to and designated as ‘RUs 102’) to cover large geographical areas and support high volume of network traffic.

[0032] Each Radio Unit (hereinafter interchangeably referred to and designated as ‘the Radio Unit 102’) of the multiple RUs 102 may include structural and functional components, that when operated in cumulation may be configured to collectively provide wireless communication service(s). For example, the Radio Unit 102 may be equipped with transmitters, receivers, antennas, and data processors for transmitting and/or receiving data and/or signals. The Radio Unit 102 operates within specified frequency bands to provide wireless communication for a variety of user devices such as portable user devices (e.g., mobile phones, tablet PCs, smart watches, automobile communication systems etc.) and/or fixed electronic devices (e.g., smart television, fixed routers, data centers, etc.). The Radio Unit 102 may be configured to convert electrical signals to radio waves that may enable communication between various user devices. The Radio Unit 102 may further be configured to generate communication data comprising data and communication traffic details of a communication cell associated with the Radio Unit 102. Furthermore, the Radio Unit 102 may be configured to transmit (or share) the communication data to the data processing server 104.

[0033] Although, in the presented aspect of the present disclosure, FIG. 1 illustrates the Radio Units 102 having four Radio Units (i.e., the first through fourth Radio Units 102a-102d), it will be apparent to a person of ordinary skill in the art that the scope of the present disclosure is not limited to it. In various other aspects, the Radio Units 102 may include any number of Radio Units, without deviating from the scope of the present disclosure. In such a scenario, each Radio Unit of the Radio Units 102 may be structurally and functionally similar to the first through fourth Radio Units 102a-102d as disclosed herein.

[0034] The data processing server 104 may be a network of computers, a software framework, or a combination thereof, that may provide a generalized approach to create a server implementation. Examples of the data processing server 104 may include, but are not limited to, personal computers, laptops, mini-computers, mainframe computers, any non-transient and tangible machine that can execute a machine-readable code, cloud-based servers, distributed server networks, or a network of computer systems. The data processing server 104 may be realized through various web-based technologies such as, but not limited to, a Java web-framework, a .NET framework, a personal home page (PHP) framework, or any web-application framework. In other aspects of the present disclosure, the data processing server 104 may be configured to perform one or more data processing and/or storage operations to enable detection of anomaly in the RUs 102. The data processing server 104 may further facilitate the system 100 to store a backup of data associated with the RUs 102.

[0035] The data processing server 104 may include data processing circuitry 108, a server memory 110, and a communication interface 112. The data processing circuitry 108 may include processor(s) (such as data processing engines) configured with suitable logic, instructions, circuitry, interfaces, and/or codes for executing one or more operations of various operations performed by the data processing server 104 for computations and data processing related to detection of anomaly in the RUs 102. Examples of the data processing circuitry 108 may include, but are not limited to, an Application Specific integrated circuit (ASIC) processor, a Reduced Instruction Set Architecture (RISC) processor, a Complex Instruction Set Architecture (CISC) processor, a Field Programmable Gate Array (FPGA), and the like.

[0036] The server memory 110 may be configured to store the logic, instructions, circuitry, interfaces, and/or codes of the data processing circuitry 108 for executing various operations. The server memory 110 may further be configured to store data associated with the RUs 102 that may be utilized by various data processing engines (or the one or more processors) of the data processing circuitry 108 to determine anomaly in the Radio Unit 102. Aspects of the present disclosure are intended to include and/or otherwise cover any type of the data associated with the RUs 102, without deviating from the scope of the present disclosure. Examples of the server memory 110 may include but are not limited to, a Read-Only Memory (ROM), a Random-Access Memory (RAM), a flash memory, a removable storage drive, a Hard Disc Drive (HDD), a solid-state memory, a magnetic storage drive, a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), and/or an Electrically Erasable Programmable Read-Only Memory EEPROM.

[0037] Although FIG. 1 illustrates one example of the system 100, various changes may be made to FIG. 1. Further, the system 100 may include any number of components in addition to the components shown in FIG. 1. Further, various components in FIG. 1 may be combined, further subdivided, or omitted and additional components may be added according to particular needs. For example, in some aspects of the present disclosure, the data processing server 104 may be coupled to an external database 113 that provides data storage space to the data processing server. Examples of the external database 113 may include but are not limited to Oracle Database, Amazon Web Services (AWS) Database, and the like. The external database 113 may store information related to configuration parameters, details related to the Radio Units 102 and other relevant information needed for the operation of the data processing server 104. The external database 113 may be accessed and updated by the data processing server 104 as part of an anomaly detection process.

[0038] The data processing server 104 may retrieve communication data from the RUs 102 periodically, continuously, or on instance basis. In an exemplary scenario, the data processing server 104 may be triggered by an external user device 114 to initiate anomaly detection for the RUs 102. The external user device 114 may further be capable of displaying (or presenting) anomaly detection results determined by the data processing server to a user through a console (not shown) on the external user device hosted by the data processing server 104. The console on the external user device 114 may be configured as a computer-executable application, to be executed by the external user device 114. The console may include suitable logic, instructions, and/or codes for executing various operations and may be controlled by the data processing server 104. The one or more computer executable applications may be stored on the user device 114.

[0039] The communication interface 112 may be configured to enable the data processing server 104 to communicate with various entities of the system 100 (such as the RUs 102 and the data processing server 104, and in some scenarios the external database 113 and the external user device 114) via the network 106. Examples of the communication interface 112 may include, but are not limited to, a modem, a network interface such as an Ethernet card, a communication port, and/or a Personal Computer Memory Card International Association (PCMCIA) slot and card, an antenna, a radio frequency (RF) transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a coder-decoder (CODEC) chipset, a subscriber identity module (SIM) card, and a local buffer circuit. It will be apparent to a person of ordinary skill in the art that the communication interface 112 may include any device and/or apparatus capable of providing wireless or wired communications between the data processing server 104 and various other entities of the system 100.

[0040] The network 106 may include suitable logic, circuitry, and interfaces that may be configured to provide several network ports and several communication channels for transmission and reception of data related to operations of various entities of the system 100. Each network port may correspond to a virtual address (or a physical machine address) for transmission and reception of the communication data. For example, the virtual address may be an Internet Protocol Version 4 (IPV4) (or an IPV6 address) and the physical address may be a Media Access Control (MAC) address. The network 106 may be associated with an application layer for implementation of communication protocols based on one or more communication requests from the various entities of the system 100. The communication data may be transmitted or received via the communication protocols. Examples of the communication protocols may include, but are not limited to, Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Simple Mail Transfer Protocol (SMTP), Domain Network System (DNS) protocol, Common Management Interface Protocol (CMIP), Transmission Control Protocol and Internet Protocol (TCP/IP), User Datagram Protocol (UDP), Long Term Evolution (LTE) communication protocols, or any combination thereof. In some aspects of the present disclosure, the communication data may be transmitted or received via at least one communication channel of several communication channels in the network 106. The communication channels may include, but are not limited to, a wireless channel, a wired channel, a combination of wireless and wired channel thereof. The wireless or wired channel may be associated with a data standard which may be defined by one of a Local Area Network (LAN), a Personal Area Network (PAN), a Wireless Local Area Network (WLAN), a Wireless Sensor Network (WSN), Wireless Area Network (WAN), Wireless Wide Area Network (WWAN), a metropolitan area network (MAN), a satellite network, the Internet, an optical fiber network, a coaxial cable network, an infrared (IR) network, a radio frequency (RF) network, and a combination thereof. Aspects of the present disclosure are intended to include or otherwise cover any type of communication channel, including known, related art, and/or later developed technologies.

[0041] In operation, the data processing server 104 receives communication data from each RU of the multiple RUs 102. The data processing server 104 further retrieves first data and second data from the communication data. The first data comprises information about specification of a corresponding RU 102 and Physical Resource Block (PRB) utilization of the corresponding RU. In some aspects of the present disclosure, the information of the specification of RU 102 may be related to frequency band(s) of operation of the RU 102, a power consumption range of the RU 102, data storage capacity of the RU 102, model and make of the RU 102, and the like. The PRB utilization of the RU 102 may be associated with data traffic demand served at the corresponding RU 102. The second data comprises information about energy consumption of the corresponding RU 102. Thereafter, the data processing server 104 compares the first data of each RU of the RUs 102. Based on the comparison of the first data of each RU 102, the data processing server 104 identifies a plurality of RUs 102 from the multiple RUs 102 having same first data. The phrase “having same first data” as used herein is referred to as two or more data units, each having same or nearly same specification of a corresponding RU 102 and Physical Resource Block (PRB) utilization of the corresponding RU relative to the other(s). Further, the data processing server 104 determines a value of energy consumption for each RU of the plurality of RUs using the second data for each RU of the plurality of RUs 102 (having the same first data). Furthermore, the data processing server 104 determines at least one RU from the plurality of RUs 102 as ‘anomalous RU(s) 102’, based on a determination that the value of the energy consumption of the at least one RU is beyond a predefined energy consumption range. Furthermore, the data processing server 104 determines anomaly indicator(s) from a set of anomaly indicators based on the second data for each anomalous RU 102. In some aspects of the present disclosure, the data processing server 104 further generates a work order for each anomalous RU 102 based on the corresponding anomaly indicator(s).

[0042] FIG. 2 illustrates a block diagram depicting the data processing server 104, in accordance with an exemplary embodiment of the present disclosure. The data processing server 104 may include the data processing circuitry 108, the server memory 110, the communication interface 112, an Input-Output (I/O) interface 200, and a console host 202 coupled to each other via a first communication bus 203.

[0043] The I/O interface 200 may include suitable logic, circuitry, interfaces, and/or codes that may be configured to receive input(s) and present (or display) output(s) on the data processing server 104. For example, the I/O interface may have an input interface (not shown) and an output interface (not shown). The input interface may be configured to enable a user to provide input(s) to trigger (or configure) the data processing server 104 for performing data processing operation(s) for anomaly detection. Examples of the operation(s) for anomaly detection may include providing input(s) to initiate fetching of the communication data from the multiple RUs 102, configuring the data processing server 104 to fetch the communication data periodically, etc. Examples of the input interface may include, but are not limited to, a touch interface, a mouse, a keyboard, a motion recognition unit, a gesture recognition unit, a voice recognition unit, or the like. The output interface may be configured to display (or present) output(s) generated (or provided) by the data processing server 104 such as, but not limited to, details of the anomalous RU(s) 102. In some aspects of the present disclosure, the output interface may provide the output(s) based on an instruction provided by the user of the data processing server 104, by way of the input interface. Examples of the output interface may include, but are not limited to, a digital display, an analog display, a touch screen display, an appearance of a desktop, and/or illuminated characters. Aspects of the present disclosure are intended to include or otherwise cover any type of the input interface and output interface in the I/O interface 200, including known, related art, and/or later developed technologies without deviating from the scope of the present disclosure.

[0044] The console host 202 may include suitable logic, circuitry, interfaces, and/or codes that may be configured to enable the I/O interface 200 to receive input(s) and/or present output(s). In some aspects of the present disclosure, the console host 202 may include suitable logic, instructions, and/or codes for executing various operations of one or more computer executable applications to host a console on the external user device 114, by way of which a user can trigger the data processing server 104 to determine the anomalous RU(s) 102. In some other aspects of the present disclosure, the console host 202 may provide a Graphical User Interface for the data processing server 104 for user interaction.

[0045] The data processing circuitry 108 may include data processor(s) (e.g., data processing engines) as presented in FIG. 2. According to an exemplary embodiment, the data processing circuitry 108 may include a data exchange engine 204, an anomaly detection engine 206, an anomaly type detection engine 208, a notification engine 210, and a work order engine 212. Various engines in the data processing circuitry 108 may be communicatively coupled to each other by way of a second communication bus 226.

[0046] The data exchange engine 204 may be configured to enable transfer of data from the server memory 110 to various engines of the data processing circuitry 108. The data exchange engine 204 may further be configured to enable a transfer of the communication data from the multiple RUs 102 to the data processing server 104. Furthermore, the data exchange engine 204 may be configured to enable transfer of data and/or instructions between various other engines of the data processing circuitry 108. More particularly, the data exchange engine 204, based on data acquisition configuration of the data processing server 104, receives the communication data from each RU of the multiple RUs 102.

[0047] The data exchange engine 204 may further be configured to perform pre-filtering of the communication data to be analyzed for anomaly detection. Particularly, the data exchange engine 204 may retrieve the first data and the second data from the communication data. The first data comprises information about specification of a corresponding RU and Physical Resource Block (PRB) utilization of the corresponding RU. In some aspects of the present disclosure, the specification of the RU is associated with an equipment type for the RU and the PRB utilization of the RU is associated with data traffic associated with the RU. The second data comprises information about energy consumption of the corresponding RU. In some aspects of the present disclosure, the information related to energy consumption of the RU comprises data elements related to a service performance value of the RU, an interference level of the RU, and a communication coverage area of the RU. The service performance value may be indicative of service parameter(s) of the RU. Examples of the service performance parameter(s) of a RU may include, but are not limited to, throughput, efficiency, longevity of operation, physical state, etc. Aspects of the present disclosure may include, or otherwise cover any existing service performance parameter or associated with a later developed technology, without deviating from the scope of the present disclosure. The interference level indicates radio interference, disruption, or obstruction caused in the functioning of the RU due to electromagnetic radiation from external source(s) transmitting in the radio frequency spectrum. The communication coverage area is referred to as a geographic area where the RU can communicate. Typically, a lower than usual coverage area (based on the geographical landscape and transmission frequency) indicates low broadcasting performance of the RU.

[0048] The anomaly detection engine 206 may be configured to compare the first data of each RU of the multiple RUs 102. Based on the comparison, the anomaly detection engine 206 may identify the plurality of RUs 102 from the multiple RUs having same first data. In some aspects of the present disclosure, the anomaly detection engine 206 may be configured to group the multiple RUs 102 based on the first data of each RU of the multiple RUs 102. In a scenario, when the anomaly detection engine 206 identifies that the first data of each RU in the multiple RUs 102 is different, the anomaly detection engine 206 may generate an error notification to be rendered by the I/O interface 200.

[0049] The anomaly detection engine 206 may further be configured to determine the value of energy consumption of each RU of the plurality of RUs 102 (having the same first data) using the second data. Furthermore, the anomaly detection engine 206 may be configured to compare the value of energy consumption of each RU of the plurality of RUs with the predefined energy consumption range (e.g., 80% and 120% of an average energy consumption value of the plurality of RUs 102) to determine whether the energy consumption value of a RU of the plurality of RUs 102 is within or beyond the predefined energy consumption range. In some aspects of the present disclosure, the predefined energy consumption range is a calculated average energy consumption value for the plurality of Radio Units 102. In some aspects of the present disclosure, the anomaly detection engine 206 may be configured to detect anomalous RU(s) 102 from the plurality of RUs 102. Specifically, the anomaly detection engine 206 may filter out anomalous RU(s) 102 having energy consumption different from the average energy consumption of the plurality of RUs 102 (i.e., having the same first data). The difference in the energy consumption value of the anomalous RUs 102 (i.e., different from the average energy consumption value of the same RUs 102) indicates issue(s) in operational parameters of the RU(s) 102, such as related to service(s), interference level, performance, coverage area, and the like.

[0050] In a scenario, when the value of energy consumption for each RU of the plurality of RUs 102 is within the predefined energy consumption range, the anomaly detection engine 206 generates a non-anomalous RU notification that can be presented (or displayed) via the I/O interface 200. In another scenario, the anomaly detection engine 206 identifies RU(s) from the plurality of RUs 102 having the value of energy consumption beyond the energy consumption range as the anomalous RU(s) 102. The anomaly detection engine 206 may further be configured to share the second data of the anomalous RU(s) to the anomaly type detection engine 208 for further processing. Particularly, the second data of each anomalous RU 102 may include the information related to the energy consumption of the anomalous RU 102. The information related to the energy consumption of the anomalous RU 102 comprises data elements related to the service performance value of the anomalous RU 102, the interference level of the anomalous RU 102, and the communication coverage area of the anomalous RU 102.

[0051] Upon receiving the second data of the anomalous RU(s), the anomaly type detection engine 208 determines anomaly indicator(s) from the set of anomaly indicators for each anomalous RU 102, based on the information related to the energy consumption of the anomalous RU 102. In some aspects of the present disclosure, the set of anomaly indicators comprises a performance indicator, an interference indicator, and a coverage area indicator. In some aspects of the present disclosure, each anomaly indicator of the set of anomaly indicators may be presented as an alarm indicating an abnormality in the performance of the RU 102.

The performance indicator (e.g., performance alarm) is triggered for the anomalous RU(s) when a service performance value of the anomalous RU(s) is lower than a predefined performance value. The interference indicator (e.g., interference alarm) is triggered when an interference level of the anomalous RU(s) is higher than a predefined interference level. The coverage area indicator (e.g., coverage area alarm) is triggered when a communication coverage area of the anomalous RU is lower than a predefined communication coverage area. The anomaly type detection engine 208 may also be configured to derive a set of parameters such as performance, interference value, and coverage area of each anomalous RU 102. Moreover, the anomaly type detection engine 208 may analyze the set of parameters using the predefined average values (i.e., average performance value, average interference value, and average coverage area value).

[0052] The anomaly type detection engine 208 may further share the anomaly indicator(s) associated with each anomalous RU 102 to the notification engine 210 and the work order engine 212 for further operations. The notification engine 210 may be configured to generate notification(s) indicating an anomaly type for the corresponding anomaly indicator(s) for each anomalous RU 102. The work order engine 212 may be configured to generate the work order for each anomalous RU 102 based on the anomaly indicator(s).

[0053] Various engines of the data processing circuitry 108 are presented to illustrate the functionality driven by the data processing server 104. It will be apparent to a person having ordinary skill in the art that various engines in the data processing circuitry 108 are for illustrative purposes and not limited to any specific combination of hardware circuitry and/or software.

[0054] The server memory 110 may be configured to store data corresponding to the system 100. In some aspects of the present disclosure, the server memory 110 may be segregated into multiple repositories that may be configured to store a specific type of data. In the exemplary embodiment as presented through FIG. 2, the server memory 110 includes an instructions repository 214, a specification data repository 216, a PRB data repository 218, a regular data repository 220, and an anomaly data repository 222.

[0055] The instructions repository 214 is configured to store computer program instructions and/or codes for operation(s) of various components of the data processing server 104. For example, the instructions repository 214 may be configured to store computer program instructions corresponding to the operation(s) performed by various engines in the data processing circuitry 108. In an embodiment of the present disclosure, the instructions repository 214 may be configured as a non-transitory storage medium. Examples of the instructions repository 214 configured as the non-transitory storage medium includes hard drives, solid-state drives, flash drives, Compact Disk (CD), Digital Video Disk (DVD), and the like. Aspects of the present disclosure are intended to include or otherwise cover any type of non-transitory storage medium as the instructions repository 214, without deviating from the scope of the present disclosure. As will be appreciated, any such computer program instructions stored in the instructions repository 214 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 produce a machine, such that the computer program instructions which execute on the computer processor(s) or other programmable processing apparatus create means for implementing the function(s) specified.

[0056] The specification data repository 216 is configured to store specification details (such as type(s) of equipment) for each RU of the RUs 102. The PRB data repository 218 is configured to store details of Physical Resource Block(s) (such as traffic data) associated with each RU. The regular data repository 220 may be configured to store data corresponding to non-anomalous RUs from the RUs 102 that is used by various engines of the data processing circuitry 108 to determine anomaly. The anomaly data repository 222 is configured to store data associated with the anomalous RU(s) from the RUs 102.

[0057] It will be apparent to a person of ordinary skill in the art that the repositories in the server memory 110 are presented based on the functionality of the data processing server 104 and are not limited to those disclosed. The server memory 110 may have any configuration, combination and/or count of repositories without deviating from the scope of the present disclosure.

[0058] Although FIG. 2 illustrates one example of the data processing server 104, various changes may be made to FIG. 2. Further, the data processing server 104 may include any number of components in addition to those shown in FIG. 2, without deviating from the scope of the present disclosure. Further, various components in FIG. 2 may be combined, further subdivided, or omitted and additional components may be added according to particular needs.

[0059] FIG. 3 presents a flow chart that depicts a method 300 for anomaly detection in the RUs 102 in the wireless network 106, in accordance with an exemplary embodiment of the present disclosure.
[0060] At block 302, the data processing server 104 may receive the communication data from each RU of the multiple RUs 102.

[0061] At block 304, the data processing server 104 may perform pre-filtering of the communication data to be analyzed for anomaly detection. Particularly, the data processing server 104 may retrieve the first data and the second data from the communication data. The first data comprises information about specification of the corresponding RU 102 and Physical Resource Block (PRB) utilization of the corresponding RU 102. In some aspects of the present disclosure, the specification of the RU 102 is associated with the equipment type for the RU 102 and the PRB utilization of the RU 102 is associated with data traffic associated with the RU 102. The second data comprises information about energy consumption of the corresponding RU 102. In some aspects of the present disclosure, the information related to the energy consumption of the RU 102 comprises the data elements related to the service performance value of the RU 102, the interference level of the RU 102, and the communication coverage area of the RU 102.

[0062] At block 306, the data processing server 104 may compare the first data of each RU of the multiple RUs 102. The first predefined data of a RU 102 comprises a predefined specification and a predefined value of PRB utilization of the corresponding RU 102.

[0063] At block 308, the data processing server 104 may determine whether the first data of RUs from the multiple RUs 102 is same or different. When the data processing server 104 determines that the first data of more than one RUs 102 is same (i.e., matches with each other), the method 300 proceeds to block 312. Else when the data processing server 104 determines that that first data of all RUs of the multiple RUs 102 is different, the method 300 proceeds to block 310.

[0064] At block 310, the data processing server 104 may generate the error notification that can be rendered via the I/O interface 200 (or the external user device 114). The error notification may indicate a faulty communication data for the RU(s) 102.

[0065] At block 312, the data processing server 104 may identify the more than one RUs 102 having same first data as the plurality of RUs 102.

[0066] At block 314, the data processing server 104 may determine the value of energy consumption of each RU of the plurality of RUs 102 using the second data of the corresponding RU.

[0067] At block 316, the data processing server 104 may compare the value of energy consumption of each RU of the plurality of RUs 102 with the predefined energy consumption range. When the value of energy consumption of each RU of the plurality of RUs 102 is determined within the predefined energy consumption range, the method 300 proceeds to block 318. Else, when the value of energy consumption of RU(s) from the is beyond the predefined energy consumption range, the method 300 proceeds to block 320.

[0068] At block 318, the data processing server 104 may generates the non-anomalous RU notification that can be displayed (or presented) through I/O interface 200 or external user device 114. The non-anomalous RU notification may indicate no anomaly for the plurality of RUs 102. Moreover, the data processing server 104. Furthermore, the method 300 halts.

[0069] At block 320, the data processing server 104 may identify the RU(s) from the plurality of RUs 102 having the value of energy consumption beyond the predefined energy consumption range as the anomalous RU(s) 102.

[0070] At block 322, upon identification of the anomalous RU(s), the data processing server 104 may determine the anomaly indicator(s) for each anomalous RU 102 based on the respective second data. In some aspects of the present disclosure, the set of anomaly indicators comprises the performance indicator, the interference indicator, and the coverage area indicator. In some aspects of the present disclosure, the performance indicator may be triggered when the service performance value of the anomalous RU(s) is lower than the predefined performance value. The interference indicator may be triggered when the interference level of the anomalous RU(s) is higher than the predefined interference level. The coverage area indicator may be triggered when the communication coverage area of the anomalous RU(s) is lower than the predefined communication coverage area.

[0071] At block 324, the data processing server 104 may generate anomaly type notification for each anomalous RU 102 based on the determined anomaly indicator(s). The anomaly type notification may be displayed either by the I/O interface 200 (or the user device 114). Moreover, the data processing server 104 may also generates a work order for each anomalous RU 102 based on the corresponding anomaly indicator(s).

[0072] 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 providing the system 100 and the method 300 for identifying, analyzing, and addressing issues within the network, ultimately leading to improved service quality and user satisfaction. The system 100 provides a simple yet efficient technical solution to determine performance anomalies in RUs 102. Based on the analysis of non-complex data of the RUs (i.e., related to specifications of the RUs, Physical Resource Block (PRB) utilization of the RU, interference level of the RU, coverage area of the RU, and service performance of the RU), the system 100 determines anomalous RU(s) and type(s) of anomalies in the anomalous RU(s). Particularly, the system 100 identifies enhanced energy levels in anomalous RUs and provides work order(s) for the proactive resolution of the anomalies in the anomalous RU(s). The proactive resolution of anomalies in the RU(s) supports lowering of the risk of equipment degradation and premature equipment failure, resulting in a prolonged operational lifespan of the equipment and significantly reduced maintenance expenditure. Additionally, the proactive resolution of anomalous RU(s) controls the energy consumption by the RU(s) in the network and thus results in a significant reduction of energy expenditure. The controlled energy consumption and the reduced equipment degradation (or failure) helps in maintaining high levels of network reliability, service quality, and operational efficiency of the network.

[0073] 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.

[0074] 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.

[0075] In the present disclosure, each of the embodiments has been described with reference to numerous specific details which may vary from embodiment to embodiment. The foregoing description of the specific embodiments disclosed herein may reveal the general nature of the embodiments herein that others may, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications are intended to be comprehended within the meaning of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and is not limited in scope.
,CLAIMS:WE CLAIM:

1. A method (300) for anomaly detection in multiple Radio Units (RUs) (102) in a wireless communication network, the method (300) comprising:
receiving communication data from each RU of the multiple RUs (102);
retrieving first data and second data from the communication data, wherein the first data comprises information related to specification of a corresponding RU and Physical Resource Block (PRB) utilization of the corresponding RU, and the second data comprises information related to energy consumption of the corresponding RU;
identifying a plurality of RUs from the multiple RUs (102), wherein the plurality of RUs have same first data amongst the multiple RUs (102);
determining a value of energy consumption for each RU of the plurality of RUs using the second data for each RU of the plurality of RUs;
determining at least one RU from the plurality of RUs as at least one anomalous RU, based on a determination that the value of the energy consumption of the at least one RU is beyond a predefined energy consumption range; and
determining, for each RU of the at least one anomalous RU, at least one anomaly indicator from a set of anomaly indicators based on the second data.

2. The method (300) as claimed in claim 1, further comprises generating a work order for each of the at least one anomalous RU based on the at least one anomaly indicator.

3. The method (300) as claimed in claim 1, wherein the specification of the RU is associated with an equipment type for the RU and the PRB utilization of the RU is associated with data traffic associated with the RU.

4. The method (300) as claimed in claim 1, wherein the information related to energy consumption of the RU comprises data elements related to a service performance value of the RU, an interference level of the RU, and a communication coverage area of the RU.

5. The method (300) as claimed in claim 4, wherein the set of anomaly indicators comprises a performance indicator, an interference indicator, and a coverage area indicator.

6. The method (300) as claimed in claim 5, wherein:
the performance indicator is triggered when the service performance value of the at least one anomalous RU is lower than a predefined performance value;
the interference indicator is triggered when the interference level of the at least one anomalous RU is higher than a predefined interference level; and
the coverage area indicator is triggered when the communication coverage area of the at least one anomalous RU is lower than a predefined communication coverage area.

7. A system (100) of anomaly detection in multiple Radio Units (RUs) (102) in a wireless communication network, the system (100) comprising:
the multiple RUs (102) configured to transmit communication data; and
a data processing server (104) communicatively coupled with the plurality of RUs, and comprising data processing circuitry (108) coupled to a server memory (110), wherein the data processing circuitry (108) comprising:
a data exchange engine (204) to:
receive the communication data from each RU of the multiple RUs (102); and
retrieve first data and second data from the communication data, wherein the first data comprises information related to specification of a corresponding RU and Physical Resource Block (PRB) utilization of the corresponding RU, and the second data comprises information related to energy consumption of the corresponding RU;
an anomaly detection engine (206) configured to:
identify a plurality of RUs from the multiple RUs (102), wherein the plurality of RUs have same first data amongst the multiple RUs (102);
determine a value of energy consumption for each RU of the plurality of RUs using the second data for each RU of the plurality of RUs; and
determine at least one RU from the plurality of RUs as at least one anomalous RU, based on a determination that the value of the energy consumption of the at least one RU is beyond a predefined energy consumption range; and
an anomaly type detection engine (208) configured to:
determine, for each RU of the at least one anomalous RU, at least one anomaly indicator from a set of anomaly indicators based on the second data.

8. The system (100) as claimed in claim 7, wherein the data processing circuitry (108) further comprises a work order engine (212) configured to generate a work order for each RU of the at least one anomalous RU based on the at least one anomaly indicator.

9. The system (100) as claimed in claim 7, wherein the specification of the RU is associated with an equipment type for the RU and the PRB utilization of the RU is associated with data traffic associated with the RU.

10. The system (100) as claimed in claim 7, wherein the information related to energy consumption of the RU comprises data elements related to a service performance value of the RU, an interference level of the RU, and a communication coverage area of the RU.

11. The system (100) as claimed in claim 10, wherein the set of anomaly indicators comprises a performance indicator, an interference indicator, and a coverage area indicator.

12. The system (100) as claimed in claim 11, wherein:
the performance indicator is triggered when the service performance value of the at least one anomalous RU is lower than a predefined performance value;
the interference indicator is triggered when the interference level of the at least one anomalous RU is higher than a predefined interference level; and
the coverage area indicator is triggered when the communication coverage area of the at least one anomalous RU is lower than a predefined communication coverage area.