WO2025008980A1

WO2025008980A1 - Method and system for validating energy consumption using physical resource block in a communication system

Info

Publication number: WO2025008980A1
Application number: PCT/IN2024/050995
Authority: WO
Inventors: Brijesh Shah; Pradeep Kumar Bhatnagar; Aayush Bhatnagar; Nitin Awasthi; Mohammad Kalim; Ajeet Kumar Gupta; Gouranga Munain; Mayank Taran; Nitesh Kumar Chourasia
Original assignee: Jio Platforms Ltd
Current assignee: Jio Platforms Ltd
Priority date: 2023-07-05
Filing date: 2024-06-28
Publication date: 2025-01-09
Anticipated expiration: 2026-01-05

Abstract

The present disclosure relates to a method and a system for validating energy consumption using physical resource block. The disclosure encompasses: collecting a set of performance metrics for one or more cell sites in a network region; mapping each of the one or more cell sites to one sector and band based on the collected set of performance metrics; determining an average value of daily PRB utilization data for the mapped sector and band; computing total estimated power consumption for each site by aggregating a sector RRH power, a BBU power, an NE power, a microwave power, and a cabinet power based on the average value of daily PRB utilization data; comparing the computed total estimated power consumption with actual energy consumption data for each cell site; and identifying discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site.

Description

METHOD AND SYSTEM FOR VALIDATING ENERGY CONSUMPTION USING PHYSICAL RESOURCE BLOCK IN A COMMUNICATION SYSTEM

FIELD OF INVENTION

[0001] Embodiments of the present disclosure generally relate to network performance management systems. More particularly, embodiments of the present disclosure relate to validating energy consumption using physical resource block (PRB) in a communication system.

BACKGROUND

[0002] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.

[0003] Wireless communication technology has rapidly evolved over the past few decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice services. However, with the advent of the second-generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. 3G technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth-generation (4G) technology revolutionized wireless communication with faster data speeds, better network coverage, and improved security. Currently, the fifth-generation (5G) technology is being deployed, promising even faster data speeds, low latency, and the ability to connect multiple devices simultaneously. With each generation, wireless communication technology has become more advanced, sophisticated, and capable of delivering more services to its users.

[0004] The validation of cell site energy consumption can sometimes have deficiencies that need to be addressed for accurate analysis and decision-making. One common deficiency is the lack of granularity in data collection and monitoring. Energy consumption validation often relies on aggregated data, such as monthly or annual utility bills, which may not provide a detailed breakdown of energy usage by specific areas or equipment within a cell site. This limited granularity makes it challenging to identify specific areas of inefficiency or opportunities for improvement. To overcome this deficiency, more granular data collection methods, such as submetering or real-time monitoring, can be employed to capture energy usage at a more detailed level.

[0005] Another deficiency in the current existing solutions is the lack of benchmarking and comparison. Validating cell site energy consumption becomes more meaningful when it can be compared to industry standards or similar facilities. Without benchmarking, it becomes difficult to assess whether a cell site's energy consumption is efficient or if there is room for improvement. Benchmarking allows for identifying outliers and setting realistic energy reduction goals. By utilizing tools and resources that provide benchmarking data, cell site owners can gain insights into their energy performance and make informed decisions on energy efficiency measures.

[0006] Furthermore, in the current existing solutions in considering external factors can impact the validation of cell site energy consumption. Factors such as weather conditions, occupancy patterns, or production fluctuations can significantly influence energy usage but may not be accounted for in the validation process. Failing to consider these external factors can lead to inaccurate assessments of energy performance and hinder the identification of energy-saving opportunities. It is essential to incorporate these variables into the validation process to obtain a comprehensive understanding of a cell site's energy consumption and make informed energy management decisions.

[0007] Thus, there exists an imperative need in the art to address the major drawbacks in the existing solutions, which the present disclosure aims to address.

SUMMARY

[0008] This section is provided to introduce certain aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.

[0009] An aspect of the present disclosure may relate to a method for validating energy consumption using physical resource block (PRB) in a communication system. The method includes collecting, by a collecting unit, a set of performance metrics for one or more cell sites in a network region. Furthermore, the method includes mapping, by a mapping unit, each of the one or more cell sites to at least one sector and band based on the collected set of performance metrics. The method further encompasses determining, by a determining unit, an average value of daily PRB utilization data for the mapped sector and band. Further, the method includes computing, by a processing unit, total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) Power, a network elements (NE) Power, a microwave Power, and a cabinet Power based on the average value of daily PRB utilization data. The method further includes comparing, by a comparing unit, the computed total estimated power consumption with actual energy consumption data for each cell site. Thereafter, the method includes identifying, by an identifying unit, one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site.

[0010] In an exemplary aspect of the present disclosure, the actual energy consumption is determined based on at least one of switched mode power supply (SMPS) usage data, diesel generator (DG) usage data, and electricity bill data.

[0011] In an exemplary aspect of the present disclosure, the method further includes enriching, by the processing unit, the collected set of performance metrics by adding at least one of: a Geographic Information System (GIS) scope and one or more priority details for each of the one or more cell sites.

[0012] In an exemplary aspect of the present disclosure, the method further includes determining, by the processing unit, the average value of daily PRB Utilization for at least one of: each of the one or more cell Sites, Band, and Sector.

[0013] In an exemplary aspect of the present disclosure, the method further includes mapping, by the mapping unit, power consumption of each cell site to the average value of daily PRB utilization for each cell Site, Band, and Sector based on at least one of the PRB Utilization and the RRH power.

[0014] In an exemplary aspect of the present disclosure, the method further includes assigning, by the processing unit, a service type to each of the one or more cell sites, wherein the service type comprises at least one of long term evolution (LTE) only and LTE & 5G, and the BBU Power & Cabinet power is added based on the assigned service type. [0015] In an exemplary aspect of the present disclosure, the method further includes mapping, by the mapping unit, network equipment (NE) power consumption and microwave power consumption of each cell site to the power consumption of the corresponding one or more cell sites by utilizing data from Transport Inventory Dump and Microwave Equipment Power Consumption.

[0016] In an exemplary aspect of the present disclosure, the cell sites selected based on identified one or more discrepancies are prioritized for audit and corrective action including checking for unintended power tapping or changing faulty meters.

[0017] In an exemplary aspect of the present disclosure, the method further includes determining, by the processing unit, the Total Estimated energy consumption in Kilowatt-hours (KWH) based on PRB utilisation by multiplying the Total Estimated Power Consumption with 24.

[0018] In an exemplary aspect of the present disclosure, the method further includes determining, by the processing unit, the Total Estimated energy consumption in KWH based on the average value of a SMPS DC power, by multiplying the average value of the SMPS DC power with 24.

[0019] In an exemplary aspect of the present disclosure, the method further includes calculating, by the processing unit, a delta percentage between PRB and SMPS energy estimate by determining difference between the SMPS DC power average value and the total estimated power consumption based on load, divided by the SMPS DC power average value, multiplied by 100, to assess alignment between calculated and actual power draw based on load versus power supply characteristics. The method further includes calculating, by the processing unit, a delta percentage between SMPS-based estimated energy units and the energy units reported in electricity bill (EB Bill) by subtracting number of units consumed by diesel generators from the total estimated units based on SMPS, then dividing result by the consumption as per EB Bill, and multiplying by 100, to validate bill accuracy against estimated power consumption using SMPS data. The method further includes calculating, by the processing unit, a delta percentage between PRB-based estimated energy units and the energy units reported in the electricity bill by subtracting number of units consumed by diesel generators from the total estimated units based on load, then dividing result by the estimated power consumption as per EB Bill, and multiplying by 100, providing a comprehensive metric to detect the one or more discrepancies in energy billing versus estimated consumption based on PRB data. [0020] Another aspect of the present disclosure may relate to a system for validating energy consumption using physical resource block (PRB) in a communication system. The system includes a collecting unit configured to collect a set of performance metrics for one or more cell sites in a network region. The system further encompasses a mapping unit configured to map each of the one or more cell sites to at least one sector and band based on the collected set of performance metrics. The system further includes a determining unit configured to determine an average value of daily PRB utilization data for the mapped sector and band. Further, the system encompasses a processing unit configured to compute total estimated power consumption for each site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) Power, a network elements (NE) Power, a microwave Power, and a cabinet Power based on the average value of daily PRB utilization data. Furthermore, the system includes a comparing unit configured to compare the computed total estimated power consumption with actual energy consumption data for each cell site. The system further includes an identifying unit configured to identify one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the site.

[0021] Yet another aspect of the present disclosure may relate to a non-transitory computer readable storage medium storing instructions for validating energy consumption using physical resource block (PRB) in a communication system, the instructions include executable code which, when executed by one or more units of a system, causes: a collecting unit of the system to collect a set of performance metrics for one or more cell sites in a network region; a mapping unit of the system to map each of the one or more cell sites to at least one sector and band based on the collected set of performance metrics; a determining unit of the system to determine an average value of daily PRB utilization data for the mapped sector and band; a processing unit of the system to compute total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) Power, a network elements (NE) Power, a microwave Power, and a cabinet Power based on the average value of daily PRB utilization data; a comparing unit of the system to compare the computed total estimated power consumption with actual energy consumption data for each cell site; and an identifying unit of the system to identify one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site.

OBJECTS OF THE INVENTION [0022] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.

[0023] It is an object of the present disclosure to provide a system and a method for validation of cell site energy consumption using PRB utilization in a communication system.

[0024] It is another object of the present disclosure to provide a solution that facilitates in avoiding electricity bills scams due to fraudulent activities like theft of electricity, diesel from generators.

[0025] It is yet another object of the present disclosure to provide a solution to power and electricity bills audit through actual resources (PRB) utilization on cell site and selection of cell sites with higher metered units than the measured value.

DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Also, the embodiments shown in the figures are not to be construed as limiting the disclosure, but the possible variants of the method and system according to the disclosure are illustrated herein to highlight the advantages of the disclosure. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components or circuitry commonly used to implement such components.

[0027] FIG. 1 illustrates an exemplary block diagram representation of 5th generation core (5GC) network architecture.

[0028] FIG. 2 illustrates an exemplary block diagram of a computing device upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure.

[0029] FIG. 3 illustrates an exemplary block diagram of a system for validating energy consumption using physical resource block (PRB) utilization in a communication system, in accordance with exemplary implementations of the present disclosure. [0030] FIG. 4 illustrates a method flow diagram for validating energy consumption using physical resource block (PRB) utilization in a communication system, in accordance with exemplary implementations of the present disclosure.

[0031] FIG. 5 illustrates an exemplary process indicating validation of energy consumption using PRB utilization in a communication system, in accordance with exemplary implementations of the present disclosure.

[0032] The foregoing shall be more apparent from the following more detailed description of the disclosure.

DETAILED DESCRIPTION

[0033] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter may each be used independently of one another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above.

[0034] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.

[0035] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. [0036] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations may be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure.

[0037] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive — in a manner similar to the term “comprising” as an open transition word — without precluding any additional or other elements.

[0038] As used herein, a “processing unit” or “processor” or “operating processor” includes one or more processors, wherein processor refers to any logic circuitry for processing instructions. A processor may be a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a (Digital Signal Processing) DSP core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The processor may perform signal coding data processing, input/output processing, and/or any other functionality that enables the working of the system according to the present disclosure. More specifically, the processor or processing unit is a hardware processor.

[0039] As used herein, “a user equipment”, “a user device”, “a smart-user-device”, “a smartdevice”, “an electronic device”, “a mobile device”, “a handheld device”, “a wireless communication device”, “a mobile communication device”, “a communication device” may be any electrical, electronic and/or computing device or equipment, capable of implementing the features of the present disclosure. The user equipment/device may include, but is not limited to, a mobile phone, smart phone, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, wearable device or any other computing device which is capable of implementing the features of the present disclosure. Also, the user device may contain at least one input means configured to receive an input from at least one of a transceiver unit, a processing unit, a storage unit, a detection unit and any other such unit(s) which are required to implement the features of the present disclosure.

[0040] As used herein, “storage unit” or “memory unit” refers to a machine or computer-readable medium including any mechanism for storing information in a form readable by a computer or similar machine. For example, a computer-readable medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices or other types of machine-accessible storage media. The storage unit stores at least the data that may be required by one or more units of the system to perform their respective functions.

[0041] As used herein “interface” or “user interface refers to a shared boundary across which two or more separate components of a system exchange information or data. The interface may also be referred to a set of rules or protocols that define communication or interaction of one or more modules or one or more units with each other, which also includes the methods, functions, or procedures that may be called.

[0042] All modules, units, components used herein, unless explicitly excluded herein, may be software modules or hardware processors, the processors being a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASIC), Field Programmable Gate Array circuits (FPGA), any other type of integrated circuits, etc.

[0043] As used herein, ‘validating energy consumption’ refers to validating a precise estimation of the cell site's energy consumption against the actual energy consumption data collected from sources like switched mode power supplies (SMPS), diesel generators (DG), and electricity bills.

[0044] As used herein, ‘PRB utilization’ refers to the measurement of the percentage of available Physical Resource Blocks (PRBs) that are used to transmit data within a specific period. PRB utilization indicates the load and efficiency of the network by showing how much of the available spectrum resources are being consumed by active data transmission. It provides insights into network capacity, performance, and potential congestion, thereby helping network operators optimize resource allocation and manage network traffic effectively. [0045] As used herein, ‘cell site’ refers to a physical location in a mobile network where base station equipment is installed to provide wireless communication services to a geographic area, known as a cell or a cell site. The cell site includes antennas, transceivers, baseband units (BBUs), power supplies, and other infrastructure necessary to transmit and receive radio signals. It serves as a critical component in the network, enabling connectivity between mobile devices and the core network, thus facilitating voice, data, and multimedia services for users within the coverage area of the cell.

[0046] As used herein, 'sector' refers to a specific geographic coverage area within a cell site that is served by a set of antennas and associated radio equipment. Each sector covers a distinct portion of the cell site’s total coverage area and operates on a specific set of frequencies to manage and distribute the radio signal to mobile users. Sectors are designed to optimize coverage, capacity, and performance by targeting specific directions and reducing interference, often resulting in a cell site being divided into multiple sectors (e.g., three sectors each covering 120 degrees) to enhance overall network efficiency and user experience.

[0047] As used herein, ‘band’ refers to a specific range of frequencies allocated for use in mobile communication systems. Each band is characterized by its designated frequency range and is used for transmitting and receiving signals between mobile devices and cell sites. Bands facilitates organizing and managing the spectrum to ensure efficient and interference-free communication. Band are identified by numerical or alphabetical designations and are tailored for different technologies such as GSM, UMTS, LTE, and 5G NR, supporting various network services and functionalities.

[0048] As used herein, 'RRH' refers to a remote radio head. The RRH handles the radio frequency processing and transmission/reception of signals between the antenna and the baseband unit (BBU). The RRH is mounted close to the antenna to reduce signal loss and enhance the efficiency of the wireless communication system. The RRH is connected to the BBU via optical fibre, enabling flexible deployment and improved coverage, capacity, and performance of the cellular network.

[0049] As used herein, ‘BBU’ refers to a baseband unit, which is a critical component in the architecture of a cellular base station. The BBU is responsible for processing baseband signals, including encoding, decoding, modulation, and demodulation of the data to be transmitted and received by the radio units. The BBU manages the communication protocols and handles tasks such as signal processing, resource allocation, and controlling the interaction between the core network and the radio network. The BBU works in conjunction with remote radio heads (RRHs) to provide efficient and scalable network performance, particularly in advanced cellular networks like LTE and 5G.

[0050] As used herein, 'NE power' refers to the power consumption of Network Elements (NE) or network equipment (NE) in a telecommunications network. The NE power includes the electrical power required to operate various network components such as base stations, controllers, routers, and switches. NE power encompasses all aspects of energy usage necessary to maintain the functionality and performance of these elements, ensuring reliable communication and data transfer within the network.

[0051] As used herein, ‘microwave power’ refers to the electrical power used to operate microwave radio equipment, which transmits and receives data using microwave frequencies. The microwave power encompasses the energy required to support the functioning of microwave transmitters, receivers, and associated infrastructure, including power amplifiers, antennas, and transceivers. Microwave power facilitates in maintaining high-capacity, long-distance wireless communication links between cell sites, especially in backhaul networks, where it ensures reliable and efficient data transmission across the network.

[0052] As used herein, ‘cabinet power’ refers to the total electrical power consumed by all the equipment housed within a telecommunications cabinet. The cabinet power includes the power used by baseband units (BBUs), remote radio heads (RRHs), network elements (NEs), cooling systems, power supply units, and any other auxiliary equipment installed in the cabinet. Cabinet power facilitates in assessing the overall energy efficiency and operational cost of cell site infrastructure.

[0053] As used herein, 'SMPS usage data' refers to the data collected regarding the performance and operation of Switched Mode Power Supplies (SMPS) in a telecommunications network. The SMPS usage data includes parameters such as input and output voltage levels, current levels, power consumption, efficiency, and operating temperature. Additionally, SMPS usage data may include information on the duration and frequency of power supply usage, instances of power failures or irregularities, and maintenance or operational status reports. [0054] As used herein, ‘SMPS DC power’ is used to provide uninterrupted DC power supply to the telecommunication system for example radio unit, base station and etc.

[0055] As used herein, communication system refers to a system model that describes a communication exchange between two stations, transmitter, and receiver. Signals or information passes from source to destination through a channel.

[0056] As used herein, 'set of performance metrics' refers to a collection of quantitative data that reflects the performance and utilization of a communication system's resources. Examples of the set of performance metrics include, but is not limited to, Physical Resource Block (PRB) utilization, average daily PRB usage, throughput, signal strength indicators, call drop rates, handover success rates, and traffic volume. The set of performance metrics is collected from various cell sites and provide insight into the operational efficiency, resource allocation, and overall performance of the network, enabling more precise estimation and validation of energy consumption for the respective cell sites.

[0057] As used herein, enriching refers to the process of augmenting a dataset with additional information to enhance its value and usability for analysis. For example, enriching performance metrics data includes adding Geographic Information System (GIS) data to provide spatial context or incorporating priority details to indicate the importance or service level of each cell site. The enriching includes adding information about nearby infrastructure, demographic data, or historical performance trends, which collectively enable more comprehensive and accurate assessments of network performance and energy consumption.

[0058] As used herein, ‘DG usage data’ refers to the data related to the usage of Diesel Generators (DG) at cell sites. The DG usage data includes metrics such as the amount of diesel fuel consumed, the duration of DG operation, power output, and efficiency. The DG usage data facilitates in evaluating the dependency on diesel generators for power supply, especially in areas with unreliable grid electricity, and for managing operational costs, maintenance schedules, and environmental impact.

[0059] As used herein, 'electricity bill data' refers to detailed records of electrical energy consumption and associated costs for a cell site. The electricity bill data includes information on the total kilowatt-hours (kWh) consumed, peak demand charges, power factor penalties, and any additional fees or adjustments. The electricity bill data also encompasses timestamps, billing periods, and consumption patterns for validating and auditing the energy efficiency and operational costs of the cell site.

[0060] As used herein, 'geographic information system (GIS) scope' refers to the range and extent of geographic and spatial data managed and utilized within a network. The GIS scope includes the integration of location-based information such as cell site coordinates, coverage areas, topography, and infrastructure layouts. GIS scope encompasses the collection, analysis, and visualization of spatial data to support network planning, optimization, and management.

[0061] As used herein, ‘transport inventory dump’ refers to a comprehensive data record that contains detailed information about the transport network elements within a telecommunications infrastructure. The transport inventory dump includes inventory data of all transport-related equipment, such as routers, switches, microwave links, and fibre optic components, as well as their configurations, connections, and operational status. The Transport Inventory Dump is utilized for network management, performance monitoring, and planning, enabling operators to have a clear and up-to-date view of the transport network’s assets and their deployment within the network architecture.

[0062] As discussed in the background section, the current known solutions have several shortcomings. The validation of site energy consumption can sometimes have deficiencies that need to be addressed for accurate analysis and decision-making. One common deficiency is the lack of granularity in data collection and monitoring. Energy consumption validation often relies on aggregated data, such as monthly or annual utility bills, which may not provide a detailed breakdown of energy usage by specific areas or equipment within a cell site. This limited granularity makes it challenging to identify specific areas of inefficiency or opportunities for improvement. Another deficiency in the current existing solutions is the lack of benchmarking and comparison. Validating cell site energy consumption becomes more meaningful when it can be compared to industry standards or similar facilities. Without benchmarking, it becomes difficult to assess whether a cell site's energy consumption is efficient or if there is room for improvement. Benchmarking allows for identifying outliers and setting realistic energy reduction goals. Factors such as weather conditions, occupancy patterns, or production fluctuations can significantly influence energy usage but may not be accounted for in the validation process. Failing to consider these external factors can lead to inaccurate assessments of energy performance and hinder the identification of energy-saving opportunities. It is essential to incorporate these variables into the validation process to obtain a comprehensive understanding of a cell site's energy consumption and make informed energy management decisions.

[0063] Thus, there exists an imperative need in the art to address the major drawbacks in the existing solutions, which the present disclosure aims to address. The present disclosure aims to overcome the above-mentioned and other existing problems in this field of technology by providing method and system for validating energy consumption using physical resource block (PRB) utilization in a communication system.

[0064] FIG. 1 illustrates an exemplary block diagram representation of 5th generation core (5GC) network architecture, in accordance with exemplary implementation of the present disclosure. As shown in FIG. 1, the 5GC network architecture [100] includes a user equipment (UE) [102], a radio access network (RAN) [104], an access and mobility management function (AMF) [106], a Session Management Function (SMF) [108], a Service Communication Proxy (SCP) [110], an Authentication Server Function (AUSF) [112], a Network Slice Specific Authentication and Authorization Function (NSSAAF) [114], a Network Slice Selection Function (NSSF) [116], a Network Exposure Function (NEF) [118], a Network Repository Function (NRF) [120], a Policy Control Function (PCF) [122], a Unified Data Management (UDM) [124], an application function (AF) [126], a User Plane Function (UPF) [128], a data network (DN) [130], wherein all the components are assumed to be connected to each other in a manner as obvious to the person skilled in the art for implementing features of the present disclosure.

[0065] Radio Access Network (RAN) [104] is the part of a mobile telecommunications system that connects user equipment (UE) [102] to the core network (CN) and provides access to different types of networks (e.g., 5G network). It consists of radio base stations and the radio access technologies that enable wireless communication.

[0066] Access and Mobility Management Function (AMF) [106] is a 5G core network function responsible for managing access and mobility aspects, such as UE registration, connection, and reachability. It also handles mobility management procedures like handovers and paging.

[0067] Session Management Function (SMF) [108] is a 5G core network function responsible for managing session-related aspects, such as establishing, modifying, and releasing sessions. It coordinates with the User Plane Function (UPF) for data forwarding and handles IP address allocation and QoS enforcement. [0068] Service Communication Proxy (SCP) [110] is a network function in the 5G core network that facilitates communication between other network functions by providing a secure and efficient messaging service. It acts as a mediator for service-based interfaces.

[0069] Authentication Server Function (AUSF) [112] is a network function in the 5G core responsible for authenticating UEs during registration and providing security services. It generates and verifies authentication vectors and tokens.

[0070] Network Slice Specific Authentication and Authorization Function (NSSAAF) [114] is a network function that provides authentication and authorization services specific to network slices. It ensures that UEs can access only the slices for which they are authorized.

[0071] Network Slice Selection Function (NSSF) [116] is a network function responsible for selecting the appropriate network slice for a UE based on factors such as subscription, requested services, and network policies.

[0072] Network Exposure Function (NEF) [118] is a network function that exposes capabilities and services of the 5G network to external applications, enabling integration with third-party services and applications.

[0073] Network Repository Function (NRF) [120] is a network function that acts as a central repository for information about available network functions and services. It facilitates the discovery and dynamic registration of network functions.

[0074] Policy Control Function (PCF) [122] is a network function responsible for policy control decisions, such as QoS, charging, and access control, based on subscriber information and network policies.

[0075] Unified Data Management (UDM) [124] is a network function that centralizes the management of subscriber data, including authentication, authorization, and subscription information.

[0076] Application Function (AF) [126] is a network function that represents external applications interfacing with the 5G core network to access network capabilities and services. [0077] User Plane Function (UPF) [128] is a network function responsible for handling user data traffic, including packet routing, forwarding, and QoS enforcement.

[0078] Data Network (DN) [130] refers to a network that provides data services to user equipment (UE) in a telecommunications system. The data services may include but are not limited to Internet services, private data network related services.

[0079] FIG. 2 illustrates an exemplary block diagram of a computing device [200] (also referred to herein as a computer system [200]) upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure. In an implementation, the computing device [200] may also implement a method for validating energy consumption using physical resource block (PRB) utilization in a communication system utilising the system. In another implementation, the computing device [200] itself implements the method for validating energy consumption using physical resource block (PRB) utilization in a communication system using one or more units configured within the computing device [200], wherein said one or more units are capable of implementing the features as disclosed in the present disclosure.

[0080] The computing device [200] may include a bus [202] or other communication mechanism for communicating information, and a processor [204] coupled with bus [202] for processing information. The processor [204] may be, for example, a general-purpose microprocessor. The computing device [200] may also include a main memory [206], such as a random-access memory (RAM), or other dynamic storage device, coupled to the bus [202] for storing information and instructions to be executed by the processor [204], The main memory [206] also may be used for storing temporary variables or other intermediate information during execution of the instructions to be executed by the processor [204], Such instructions, when stored in non-transitory storage media accessible to the processor [204], render the computing device [200] into a special-purpose machine that is customized to perform the operations specified in the instructions. The computing device [200] further includes a read only memory (ROM) [208] or other static storage device coupled to the bus [202] for storing static information and instructions for the processor [204],

[0081] A storage device [210], such as a magnetic disk, optical disk, or solid-state drive is provided and coupled to the bus [202] for storing information and instructions. The computing device [200] may be coupled via the bus [202] to a display [212], such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for displaying information to a computer user. An input device [214], including alphanumeric and other keys, touch screen input means, etc. may be coupled to the bus [202] for communicating information and command selections to the processor [204], Another type of user input device may be a cursor controller [216], such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor [204], and for controlling cursor movement on the display [212], This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow the device to specify positions in a plane.

[0082] The computing device [200] may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware and/or program logic which in combination with the computing device [200] causes or programs the computing device [200] to be a special-purpose machine. According to one implementation, the techniques herein are performed by the computing device [200] in response to the processor [204] executing one or more sequences of one or more instructions contained in the main memory [206], Such instructions may be read into the main memory [206] from another storage medium, such as the storage device [210], Execution of the sequences of instructions contained in the main memory [206] causes the processor [204] to perform the process steps described herein. In alternative implementations of the present disclosure, hard-wired circuitry may be used in place of or in combination with software instructions.

[0083] The computing device [200] also may include a communication interface [218] coupled to the bus [202], The communication interface [218] provides a two-way data communication coupling to a network link [220] that is connected to a local network [222], For example, the communication interface [218] may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface [218] may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, the communication interface [218] sends and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

[0084] The computing device [200] can send messages and receive data, including program code, through the network(s), the network link [220] and the communication interface [218], In the Internet example, a server [230] might transmit a requested code for an application program through the Internet [228], the ISP [226], the Host [224], the local network [222] and the communication interface [218], The received code may be executed by the processor [204] as it is received, and/or stored in the storage device [210], or other non-volatile storage for later execution.

[0085] Referring to FIG. 3, an exemplary block diagram of a system [300] for validating energy consumption using physical resource block (PRB) utilization in a communication system, is shown, in accordance with the exemplary implementations of the present disclosure. The system [300] comprises at least one collecting unit [302], at least one mapping unit [304], at least one determining unit [306], at least one processing unit [308], at least one comparing unit [310] and at least one identifying unit [312], Also, all the components/ units of the system [300] are assumed to be connected to each other unless otherwise indicated below. Also, in FIG. 3 only a few units are shown, however, the system [300] may comprise multiple such units or the system [300] may comprise any number of said units, as required to implement the features of the present disclosure. Further, in an implementation, the system [300] may be present in a user device to implement the features of the present disclosure.

[0086] The system [300] is configured for validating cell site energy consumption using physical resource block (PRB) utilization in a communication system, with the help of the interconnection between the components/units of the system [300],

[0087] The system [300] includes a collecting unit [302], which is configured to collect a set of performance metrics for one or more cell sites in a network region. For example, in a telecom network spanning a large geographical area, the collecting unit [302] collects (such as daily), the set of performance metrics such as physical resource block (PRB) utilization from each of the one or more cell sites to get detailed insights into how resources are being utilized, which directly correlates with the energy consumption of the one or more cell sites. By tracking the PRB utilization, the system [300] can monitor and evaluate the operational efficiency of each of the one or more cell sites. The collecting unit [302] may access network management systems for realtime performance data, retrieving energy consumption records from electricity bills, and incorporating geographic information system (GIS) data for context and prioritization. For example, a cell site located in an urban area with high user density would likely show different performance metrics compared to the rural cell site, and the GIS data facilitate in determining the differences. [0088] The system [300] includes the mapping unit [304] communicatively coupled to the collecting unit [302], The mapping unit [304] is configured to map each of the one or more cell sites to at least one sector and band based on the collected set of performance metrics. For example, after the collecting unit [302] collects the set of performance metrics from the one or more cell sites within a network region, the mapping unit [304] then uses the set of performance metrics to determine which sector and frequency band each cell site corresponds to. For example, a network with one or more cell sites operating in both the 1800 MHz band for LTE and the 3500 MHz band for 5G. The mapping unit [304] takes the set of performance metrics collected by the collecting unit [302] and assigns them to the appropriate sector and band. For example, a cell site with high PRB utilization in the 1800 MHz band and moderate PRB utilization in the 3500 MHz band will have its data mapped accordingly. The mapping ensures that the set of performance metrics are correctly categorized, allowing for precise analysis and further processing. It would be appreciated by the person skilled in the art that by accurately mapping the set of performance metrics to sectors and bands, the system [300] can effectively calculate average daily PRB utilization, estimate power consumption, and identify discrepancies. Thereby ensuring that the data used in the calculations is representative of the actual operating conditions of each of the one or more cell sites.

[0089] The mapping unit [304] is further configured to map power consumption relative to the average value of daily PRB utilization for each cell Site, Band, and Sector based on the PRB Utilization and the RRH power. The mapping unit [304] is further configured to map network equipment (NE) power and microwave power consumption for each cell site by utilizing data from Transport Inventory Dump and Microwave Equipment Power Consumption. For example, a cell site that includes multiple network elements and microwave links. The mapping unit [304] uses the Transport Inventory Dump to determine the types and configurations of equipment(s) present at the cell site. For example, it identifies routers, switches, and other components, and then uses this information to estimate their power consumption. Simultaneously, the mapping unit [304] incorporates data from the Microwave Equipment Power Consumption records to estimate the power usage of microwave links operating at the cell site.

[0090] The system [300] includes the determining unit [306], which is communicatively coupled to the mapping unit [304], The determining unit [306] is configured to determine an average value of daily PRB utilization data for the mapped sector and band. For example, after the mapping unit [304] has associated the collected set of performance metrics with the appropriate sectors and bands for each cell site, the determining unit [306] determines the average daily PRB utilization. The average value of daily PRB utilization data smooths out any anomalies or spikes in utilization, providing a more stable basis for power consumption estimation. For example, a cell site that serves three sectors across two frequency bands. Each sector's PRB utilization might vary throughout the day due to factors such as user demand and network load. The determining unit [306] collects the PRB utilization data for each sector and band, and determines the total PRB utilization for the day, and then averages it out. For example, if Sector 1 has PRB utilizations of 70%, 60%, and 80% over three different times of the day, the determining unit [306] would calculate the average utilization for Sector 1 as (70% + 60% + 80%) / 3 = 70%. In an implementation of the present disclosure, in the 5^th generation core network, the determining unit [306] processes the daily PRB utilization data for each mapped sector and band. For example, if PRB utilization data is collected every hour, the determining unit [306] computes the average utilization for each sector and band over a 24-hour period. By utilizing an average PRB utilization, the system [300] ensures that the power consumption estimations are based on typical usage patterns rather than outliers or short-term fluctuations.

[0091] The system [300] includes the processing unit [308], which is communicatively coupled to the determining unit [306], The processing unit [308] is configured to compute total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) power, a network elements (NE) power, a microwave power, and a cabinet power based on the average value of daily PRB utilization data. For example, after the determining unit [306] determines the average daily PRB utilization for each sector and band, the processing unit [308] uses the average daily PRB utilization for each sector and band to estimate the power consumption of the various components of each cell site. It aggregates the power consumption of the RRH, BBU, NE, microwave, and cabinet based on how much they are used, which is indicated by the PRB utilization. For example, the average daily PRB utilization for a particular sector is 75%. The processing unit [308] would take this utilization rate and apply it to the power consumption metrics of the RRH, BBU, NE, microwave, and cabinet. For instance, if the RRH power consumption at full utilization is 100 watts, then at 75% utilization, the RRH would consume 75 watts. Similarly, the processing unit [308] would calculate the power consumed by the BBU, NE, microwave, and cabinet based on their respective utilization rates and power metrics. Additionally, the processing unit [308] may factor in different service types assigned to each cell site, such as Long Term Evolution (LTE) only or LTE & 5G. For example, a cell site that supports both LTE and 5G might have higher BBU and cabinet power consumption compared to a cell site that supports only LTE. The processing unit [308] adjusts its calculations accordingly to provide a more accurate estimation of total power consumption. [0092] The system [300] includes the comparing unit [310], which is communicatively coupled to the processing unit [308], The comparing unit [310] is configured to compare the computed total estimated power consumption with actual energy consumption data for each cell site. For example, once the processing unit [308] has computed the total estimated power consumption for a cell site by aggregating the power usage of various components such as the RRH, BBU, NE, microwave, and cabinet, this estimated value is passed to the comparing unit [310], The comparing unit [310] then retrieves the actual energy consumption data for the same cell site from various sources, such as electricity bills, switched mode power supply (SMPS) usage data, and diesel generator (DG) usage data. For example, the estimated power consumption for a cell site is 500 kilowatt-hours (kWh) based on the average daily PRB utilization data. The actual energy consumption data collected from the electricity bill for the same period shows a consumption of 550 kWh. The comparing unit [310] would analyse these figures to determine the difference between the estimated and actual values. The determined discrepancy may indicate an issue that needs further investigation.

[0093] The one or more cell sites, selected based on the identified one or more discrepancies, are prioritized for audit and corrective actions comprising at least one of checking for unintended power tapping, and changing faulty meters. For example, the comparing unit [310] can facilitate in highlighting discrepancies for prioritized audit and corrective action. For example, if a particular cell site consistently shows higher actual energy consumption than estimated, it may be flagged for a detailed audit to check for potential issues like unintended power tapping or faulty meters.

[0094] The system [300] further includes the identifying unit [312], which is communicatively coupled to the comparing unit [310], The identifying unit [312] is configured to identify one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site. For example, once the comparing unit [310] has compared the computed total estimated power consumption with the actual energy consumption data for each cell site, any differences between these values are flagged and passed to the identifying unit [312], The identifying unit [312] analyses the one or more discrepancies to determine their significance and potential causes. For example, the estimated power consumption for a cell site is calculated to be 500 kilowatt-hours (kWh) based on PRB utilization, while the actual consumption recorded from the electricity bill is 600 kWh. The identifying unit [312] would recognize this 100-kWh discrepancy and classify it for further investigation. It could categorize such discrepancies based on the magnitude and frequency of the occurrence, helping prioritize which cell sites need immediate attention.

[0095] The identifying unit [312] may also cross-reference additional data sources to understand the root causes of discrepancies. For instance, the identifying unit [312] could refer the diesel generator (DG) usage data to see if an unusually high amount of power were drawn from generators due to power outages, which might not have been accurately captured in the estimated consumption. Similarly, the identifying unit [312] might check for data entry errors, equipment malfunctions, or unauthorized power usage.

[0096] The processing unit [308] is further configured to determine Total Estimated energy consumption in Kilowatt-hours (KWH) based on PRB utilization by multiplying Total Estimated Power Consumption based on Load with 24. This calculation involves taking the total power consumption of a cell site, which includes various components such as the remote radio head (RRH) power, baseband unit (BBU) power, network elements (NE) power, microwave power, and cabinet power, and then estimating how much energy is consumed over a 24-hour period. For example, if the total estimated power consumption for a particular cell site is 10 kilowatts (KW) based on the load from the physical resource block (PRB) utilization data, the processing unit [308] multiplies this figure by 24 to determine the total estimated energy consumption for one day. In this case, the total estimated energy consumption would be 240 KWH (10 KW * 24 hours). The estimated energy consumption accurately reflects the actual usage patterns of the cell site, as it considers the daily fluctuations in load and usage. The processing unit [308] utilizes PRB utilization data to provide a precise estimate of the cell site's energy consumption for validating against the actual energy consumption data collected from sources like switched mode power supplies (SMPS), diesel generators (DG), and electricity bills.

[0097] The processing unit [308] is further configured to determine Total Estimated energy consumption in KWH Unit based on the average value of a SMPS DC power, by multiplying the average value of the SMPS DC power with 24. This approach involves taking the average direct current (DC) power provided by the switched mode power supply (SMPS) and calculating the total energy consumption over a 24-hour period. For example, if the average DC power value of the SMPS at a particular cell site is 5 kilowatts (KW), the processing unit [308] multiplies this figure (such as 5 kilowatts (KW)) by 24 to estimate the total energy consumption for one day. In this case, the total estimated energy consumption would be 120 KWH (5 KW * 24 hours). The energy consumption estimate is based on the consistent power supply provided by the SMPS, reflecting a more accurate daily energy usage pattern. The processing unit [308] utilizes the average value of the SMPS DC power to determine an estimate of the cell site's energy consumption, for validating against actual energy consumption data collected from other sources like electricity bills, diesel generators (DG), and metered data.

[0098] The processing unit [308] is further configured to compute a delta percentage between PRB and SMPS energy estimates by first determining the difference between the SMPS DC power average value and the total estimated power consumption based on load. The difference is then divided by the SMPS DC power average value, and the result is multiplied by 100. The purpose of this computation is to assess the alignment between the calculated and actual power draw based on load versus power supply characteristics.

[0099] For example, the SMPS DC power average value is 12 KW and the total estimated power consumption based on load is 10 KW.

[0100] For calculating the delta percentage between PRB and SMPS energy:

[0101] Firstly, Subtract the total estimated power consumption based on load from the SMPS DC power average value:

12 KW - 10 KW = 2KW

[0102] Secondly, divide the above result (i.e., 2KW) by the SMPS DC power average value. The step normalizes the difference to provide a relative measure.

2KW

0.1667

12KW

[0103] Lastly, convert the result into a percentage.

0.1667 X 100 = 16.77%

[0104] The delta percentage in the case is 16.67%. The percentage indicates the discrepancy between the estimated power consumption based on load and the actual power supplied by the SMPS. A lower delta percentage signifies that the estimated power consumption closely matches the actual power draw, indicating accurate estimations and proper alignment between load calculations and power supply characteristics. Conversely, a higher delta percentage would highlight a significant discrepancy, potentially indicating issues such as inaccuracies in load estimation or anomalies in power supply characteristics that may need further investigation.

[0105] The processing unit [308] is further configured to compute a delta percentage between SMPS-based estimated energy units and the energy units reported in the electricity bill (EB bill). The computation is performed to validate the accuracy of the electricity bill against the estimated power consumption using the SMPS data. The steps involved in this process include subtracting the number of units consumed by diesel generators from the total estimated units based on SMPS, then dividing the result by the consumption as per the EB bill, and finally multiplying by 100 to express the result as a percentage.

[0106] For example, the total estimated units based on SMPS is 1500 KWH, and the number of units consumed by diesel generators is 300 KWH. The consumption reported in the EB bill is 1100 KWH.

[0107] For calculating the delta percentage between SMPS-based estimated energy units and the energy units reported in the EB bill:

[0108] Firstly, subtract the diesel generator units. Remove the number of units consumed by diesel generators from the total estimated units based on SMPS.

1500KWH - 300KWH = 1200KWH

[0109] Secondly, divide the above result (i.e., 1200KWH) by the EB bill consumption. Calculate the ratio of the adjusted estimated units to the consumption reported in the EB bill.

1200KWH

1.0909

1100KWH

[0110] Lastly, subtract 1 and multiply by 100. Convert the ratio into a percentage to find the delta percentage.

(1.0909 - 1) X 100 = 9.09% [0111] In this case, the delta percentage is 9.09%, indicating that the SMPS-based estimate is 9.09% higher than what the EB bill reports. The discrepancy could signal potential issues such as inaccurate billing or measurement errors, prompting further investigation to ensure billing accuracy and detect any anomalies. The method provides a robust way to cross-verify energy consumption data and validate the accuracy of electricity bills against actual power usage recorded by the SMPS.

[0112] The processing unit [308] is further configured to compute a delta percentage between SMPS-based estimated energy units and the energy units reported in the EB bill by performing a series of calculations. The process begins by subtracting the number of units consumed by diesel generators from the total estimated units based on SMPS data. The resulting value is then divided by the consumption as per the EB bill, and the result is multiplied by 100 to convert it into a percentage. The computation aims to validate the accuracy of the electricity bill against the estimated power consumption using the SMPS data.

[0113] For example, the total estimated units based on SMPS is 2000 KWH, and the number of units consumed by diesel generators is 500 KWH.

[0114] For calculating the percentage between PRB-based estimated energy units and the energy units reported in the EB bill:

[0115] Firstly, subtract the diesel generator units. Remove the number of units consumed by diesel generators from the total estimated units based on SMPS.

2000KWH - 500KWH = 1500KWH

[0116] Secondly, divide the above result (i.e., 1500KWH) by the EB bill consumption. Calculate the ratio of the adjusted estimated units to the consumption reported in the EB bill.

1500KWH

- = 1.0714

1400KWH

[0117] Lastly, subtract 1 and multiply by 100. Convert the ratio into a percentage to find the delta percentage. (1.0714 - 1) X 100 = 7.14%

[0118] In this case, the delta percentage is 7.14%, indicating that the SMPS-based estimate is 7.14% higher than the consumption reported in the EB bill. The discrepancy suggests that there may be inaccuracies in the electricity bill or differences in power consumption recording, prompting further investigation to ensure billing accuracy and detect any potential issues. By computing this delta percentage, the system provides a robust method to cross-verify energy consumption data, enhancing the accuracy of electricity billing and identifying discrepancies for corrective actions.

[0119] Referring to FIG. 4, an exemplary method flow diagram [400] for validating cell site energy consumption using physical resource block (PRB) utilization in a communication system, in accordance with exemplary implementations of the present disclosure is shown. In an implementation the method [400] is performed by the system [300], Further, in an implementation, the system [300] may be present in a server device to implement the features of the present disclosure. Also, as shown in FIG. 4, the method [400] starts at step [402],

[0120] At step [404], the method comprises collecting, by a collecting unit [302], a set of performance metrics for one or more cell sites in a network region. The cell sites are selected based on identified one or more discrepancies are prioritized for audit and corrective action including checking for unintended power tapping or changing faulty meters. For example, in a telecom network spanning a large geographical area, the collecting unit [302] collects (such as daily), the set of performance metrics such as physical resource block (PRB) utilization from each of the one or more cell sites to get detailed insights into how resources are being utilized, which directly correlates with the energy consumption of the one or more cell sites. By tracking the PRB utilization, the system [300] can monitor and evaluate the operational efficiency of each cell sites. The collecting unit [302] may access network management systems for real-time performance data, retrieving energy consumption records from electricity bills, and incorporating geographic information system (GIS) data for context and prioritization. For example, a cell site located in an urban area with high user density would likely show different performance metrics compared to the rural cell site, and the GIS data facilitate in determining the differences.

[0121] Next, at step [406], the method encompasses mapping, by a mapping unit [304], each of the one or more cell sites to at least one sector and band based on the collected set of performance metrics. For example, after the collecting unit [302] collects the set of performance metrics from the one or more cell sites within a network region, the mapping unit [304] then uses the set of performance metrics to determine which sector and frequency band each cell site corresponds to. For example, a network with one or more cell sites operating in both the 1800 MHz band for LTE and the 3500 MHz band for 5G. The mapping unit [304] takes the set of performance metrics collected by the collecting unit [302] and assigns them to the appropriate sector and band. For example, a cell site with high PRB utilization in the 1800 MHz band and moderate PRB utilization in the 3500 MHz band will have its data mapped accordingly. The mapping ensures that the set of performance metrics are correctly categorized, allowing for precise analysis and further processing. It would be appreciated by the person skilled in the art that by accurately mapping the set of performance metrics to sectors and bands, the system [300] can effectively calculate average daily PRB utilization, estimate power consumption, and identify discrepancies. Thereby ensuring that the data used in the calculations is representative of the actual operating conditions of each of the one or more cell sites. The mapping unit [304] is further configured to map power consumption relative to the average value of daily PRB utilization for each cell Site, Band, and Sector based on the PRB Utilization and the RRH power. The mapping unit [304] is further configured to map network equipment (NE) power and microwave power consumption for each cell site by utilizing data from Transport Inventory Dump and Microwave Equipment Power Consumption. For example, a cell site that includes multiple network elements and microwave links. The mapping unit [304] uses the Transport Inventory Dump to determine the types and configurations of equipment(s) present at the cell site. For example, it identifies routers, switches, and other components, and then uses this information to estimate their power consumption. Simultaneously, the mapping unit [304] incorporates data from the Microwave Equipment Power Consumption records to estimate the power usage of microwave links operating at the cell site.

[0122] Next, at step [408], the method includes determining, by a determining unit [306], an average value of daily PRB utilization data for the mapped sector and band. For example, after the mapping unit [304] has associated the collected set of performance metrics with the appropriate sectors and bands for each cell site, the determining unit [306] determines the average daily PRB utilization. The average value of daily PRB utilization data smooths out any anomalies or spikes in utilization, providing a more stable basis for power consumption estimation. For example, a cell site that serves three sectors across two frequency bands. Each sector's PRB utilization might vary throughout the day due to factors such as user demand and network load. The determining unit [306] collects the PRB utilization data for each sector and band, and determines the total PRB utilization for the day, and then averages it out. For example, if PRB utilization data is collected every hour, the determining unit [306] computes the average utilization for each sector and band over a 24-hour period. By utilizing an average PRB utilization data, the system ensures that the power consumption estimates are based on typical usage patterns rather than outliers or short-term fluctuations.

[0123] Further, at step [410] the method includes computing, by a processing unit [308], total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) Power, a network elements (NE) Power, a microwave Power, and a cabinet Power based on the average value of daily PRB utilization data. For example, after the determining unit [306] determines the average daily PRB utilization for each sector and band, the processing unit [308] uses the average daily PRB utilization for each sector and band to estimate the power consumption of the various components of each cell site. It aggregates the power consumption of the RRH, BBU, NE, microwave, and cabinet based on how much they are used, which is indicated by the PRB utilization. For example, the average daily PRB utilization for a particular sector is 75%. The processing unit [308] would take this utilization rate and apply it to the power consumption metrics of the RRH, BBU, NE, microwave, and cabinet. For instance, if the RRH power consumption at full utilization is 100 watts, then at 75% utilization, the RRH would consume 75 watts. Similarly, the processing unit [308] would calculate the power consumed by the BBU, NE, microwave, and cabinet based on their respective utilization rates and power metrics. Additionally, the processing unit [308] may factor in different service types assigned to each cell site, such as Long Term Evolution (LTE) only or LTE & 5G. For example, a cell site that supports both LTE and 5G might have higher BBU and cabinet power consumption compared to a cell site that supports only LTE. The processing unit [308] adjusts its calculations accordingly to provide a more accurate estimation of total power consumption.

[0124] At step [412], the method includes comparing, by a comparing unit [310], the computed total estimated power consumption with actual energy consumption data for each cell site. For example, once the processing unit [308] has computed the total estimated power consumption for a cell site by aggregating the power usage of various components such as the RRH, BBU, NE, microwave, and cabinet, this estimated value is passed to the comparing unit [310], The comparing unit [310] then retrieves the actual energy consumption data for the same cell site from various sources, such as electricity bills, switched mode power supply (SMPS) usage data, and diesel generator (DG) usage data. For example, the estimated power consumption for a cell site is 500 kilowatt-hours (kWh) based on the average daily PRB utilization data. The actual energy consumption data collected from the electricity bill for the same period shows a consumption of 550 kWh. The comparing unit [310] would analyse these figures to determine the difference between the estimated and actual values. The determined discrepancy may indicate an issue that needs further investigation. The one or more cell sites, selected based on the identified one or more discrepancies, are prioritized for audit and corrective actions comprising at least one of checking for unintended power tapping, and changing faulty meters. For example, the comparing unit [310] can highlight discrepancies for prioritized audit and corrective action. For instance, if a particular cell site consistently shows higher actual energy consumption than estimated, it may be flagged for a detailed audit to check for potential issues like unintended power tapping or faulty meters.

[0125] Next at step [414], the method includes identifying, by an identifying unit [312], one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site. For example, once the comparing unit [310] has compared the computed total estimated power consumption with the actual energy consumption data for each cell site, any differences between these values are flagged and passed to the identifying unit [312], The identifying unit [312] analyses the one or more discrepancies to determine their significance and potential causes. For example, the estimated power consumption for a cell site is calculated to be 500 kilowatt-hours (kWh) based on PRB utilization, while the actual consumption recorded from the electricity bill is 600 kWh. The identifying unit [312] would recognize this 100 kWh discrepancy and classify it for further investigation. It could categorize such discrepancies based on the magnitude and frequency of the occurrence, helping prioritize which cell sites need immediate attention. The identifying unit [312] may also cross-reference additional data sources to understand the root causes of discrepancies. For example, the identifying unit [312] could refer the diesel generator (DG) usage data to see if an unusually high amount of power were drawn from generators due to power outages, which might not have been accurately captured in the estimated consumption. Similarly, the identifying unit [312] might check for data entry errors, equipment malfunctions, or unauthorized power usage. In an implementation of the present disclosure, in case significant discrepancies are found between the estimated and actual consumption values, identification of the discrepancy is done by the identifying unit [312] to identify potential causes to allow for an appropriate action to be taken to minimize the discrepancy.

[0126] Thereafter, the method [400] ends at step [416],

[0127] Referring to FIG. 5, it illustrates an exemplary process indicating for validating energy consumption using physical resource block (PRB) utilization in a communication system, in accordance with exemplary embodiments of the present disclosure. In an implementation the process [500] is performed by the system [300], Further, in an implementation, the system [300] may be present in a server device to implement the features of the present disclosure. Also, as shown in FIG. 5, the process [500] includes the following-

10128] At [502], a set of performance metrics from various data sources is collected. These data sources include, but are not limited only to, Network Element/Geographic Information System (GIS) (cell Site Inventory Check) [508], and others. The collecting unit [302] collects the set of performance metrics using performance management systems that collect per-day Key Performance Indicators (KPIs) for each cell. Further, at [502], the actual energy consumption from the cell site Switch Mode Power Supply (SMPS) is collected.

[0129] At [504], diesel generator (DG) energy consumption is collected. It involves monitoring the energy consumption of diesel generators, which are often used as backup power sources for cell sites.

[0130] At [506], metered energy consumption data from State Electricity Boards (SEBs) is gathered, which provides a further layer of actual consumption figures, which can be compared against the estimated values. The Metered Energy consumption from SEBs [506] is received from Long-Term Evolution System Management Radio (LSMR) [510],

[0131] At [512], the energy based on traffic data, such as radio and baseband usage are calculated. The calculated energy reflects the actual usage patterns of the cell site, which can vary significantly depending on the time of day and the number of active users.

[0132] At [514], the energy consumption based on device-rated power is considered, which includes power consumption figures for devices such as routers and microwaves.

[0133] At [516], the total estimated energy consumption is calculated, which is obtained based on combining the two energy calculations at [512] and at [514], The total estimated power consumption may also include the power consumption from RRH, BBU, NE, microwave, and cabinet power from all sectors.

[0134] At [518], a comparison of estimated and actual energy consumption is conducted. This involves comparing the total estimated cell site energy consumption at [516] with the actual energy consumption data collected from SMPS at [502], and DG energy consumption at [504], The comparison helps identify one or more discrepancies between the estimated energy and actual energy usage.

[0135] At [520], the process includes a comparison of actual energy consumption i.e., DG energy with metered energy. The comparison facilitates in determining consistency between different sources of actual consumption data and can help detect any anomalies or errors in the data.

[0136] At [522], lists of cell sites where SMPS energy consumption is more than expected is prepared. Simultaneously, lists of cell sites where metered energy consumption is more than expected is prepared at [524], The lists help prioritize cell sites for further investigation and corrective actions.

[0137] For instance, if a cell site is identified where SMPS energy consumption is higher than expected at [522], the action at [526] will involve checking the cell site inventory data to verify any extra load and inspecting for any unintended power tapping on the cell site.

[0138] Similarly, if metered energy consumption is higher than expected at [524], the action at [528] includes checking with the SEBs for excess metering or faulty meters and replacing meters if necessary. This step ensures accurate billing and prevents potential financial losses due to faulty metering.

[0139] The present disclosure further discloses a non-transitory computer readable storage medium storing instructions for validating cell site energy consumption using physical resource block (PRB) of radio, the instructions include executable code which, when executed by one or more units of a system, causes: a collecting unit [302] of the system to collect a set of performance metrics for one or more cell sites in a network region; a mapping unit [304] of the system to map each of the one or more cell sites to at least one sector and band based on the collected set of performance metrics; a determining unit [306] of the system to determine an average value of daily PRB utilization data for the mapped sector and band; a processing unit [308] of the system to compute total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) Power, a network elements (NE) Power, a microwave Power, and a cabinet Power based on the average value of daily PRB utilization data; a comparing unit [310] of the system to compare the computed total estimated power consumption with actual energy consumption data for each cell site; and an identifying unit power consumption and actual energy consumption to validate the energy consumption of the cell site.

[0140] Further, in accordance with the present disclosure, it is to be acknowledged that the functionality described for the various components/units can be implemented interchangeably. While specific embodiments may disclose a particular functionality of these units for clarity, it is recognized that various configurations and combinations thereof are within the scope of the disclosure. The functionality of specific units, as disclosed in the disclosure, should not be construed as limiting the scope of the present disclosure. Consequently, alternative arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.

[0141] As is evident from the above, the present disclosure provides a technically advanced solution for validating cell site energy consumption using physical resource block (PRB) of radio. The major technical advancements over existing art are power and electricity bills audit through actual resources (PRB) utilization on cell site. Further, selection of cell sites with higher metered units than the measured value and check on electricity bill scams due to fraudulent activities such as theft of electricity and diesel from generators. Additionally, a check on operational cost and reducing complexity of computation.

[0142] While considerable emphasis has been placed herein on the disclosed implementations, it will be appreciated that many implementations can be made and that many changes can be made to the implementations without departing from the principles of the present disclosure. These and other changes in the implementations of the present disclosure will be apparent to those skilled in the art, whereby it is to be understood that the foregoing descriptive matter to be implemented is illustrative and non-limiting.

Claims

We Claim:

1. A method for validating energy consumption using physical resource block (PRB) utilization in a communication system, the method comprising the steps of: collecting, by a collecting unit [302], a set of performance metrics for one or more cell sites in a network region; mapping, by a mapping unit [304], each of the one or more cell sites to at least one sector and band, associated with the corresponding one or more cell sites, based on the collected set of performance metrics; determining, by a determining unit [306], an average value of daily PRB utilization data for the mapped at least one sector and band; computing, by a processing unit [308], total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) power, a network elements (NE) power, a microwave power, and a cabinet power based on the average value of daily PRB utilization data; comparing, by a comparing unit [310], the computed total estimated power consumption with actual energy consumption data for each cell site; and identifying, by an identifying unit [312], one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site.

2. The method as claimed in claim 1, wherein the actual energy consumption is determined based on at least one of switched mode power supply (SMPS) usage data, diesel generator (DG) usage data, and electricity bill data.

3. The method as claimed in claim 1, further comprises enriching, by the processing unit [308], the collected set of performance metrics by adding at least one of: a Geographic Information System (GIS) scope and one or more priority details for each of the one or more cell sites.

4. The method as claimed in claim 1, wherein the method comprises determining, by the processing unit [308], the average value of daily PRB Utilization for at least one of: each of the one or more cell Sites, Band, and Sector.

5. The method as claimed in claim 1, further comprising mapping, by the mapping unit [304], power consumption of each cell site to the average value of daily PRB utilization for each cell Site, Band, and Sector based on at least one of the PRB Utilization and the RRH power.

6. The method as claimed in claim 1, wherein the method comprises assigning, by the processing unit [308], a service type to each of the one or more cell sites, wherein at least one of: the service type comprises at least one of Long Term Evolution (LTE) Only and LTE & 5G, and the BBU Power & Cabinet power are added based on an assigned service type.

7. The method as claimed in claim 1, further comprising mapping, by the mapping unit [304], network equipment (NE) power consumption and microwave power consumption of each cell site to the power consumption of the corresponding one or more cell sites by utilizing data from Transport Inventory Dump and Microwave Equipment Power Consumption.

8. The method as claimed in claim 1, wherein the cell sites selected based on identified one or more discrepancies are prioritized for audit and corrective action, wherein the audit and corrective action comprises performing at least one of checking for unintended power tapping or changing faulty meters.

9. The method as claimed in claim 1, wherein the method comprises determining, by the processing unit [308], the computed total estimated energy consumption in Kilowatt-hours (KWH) based on PRB utilisation by multiplying the computed Total Estimated Power Consumption with 24.

10. The method as claimed in claim 1, wherein the method comprises determining, by the processing unit [308], the computed Total Estimated energy consumption in KWH based on a SMPS DC power average value, by multiplying a SMPS DC power average value with 24.

11. The method as claimed in claim 10, further comprising calculating, by the processing unit [308] at least one of: a delta percentage between PRB and SMPS energy estimate by determining difference between the SMPS DC power average value and the computed total estimated power consumption based on load, divided by the SMPS DC power average value, multiplied by 100, to assess alignment between calculated and actual power draw based on load versus power supply characteristics; a delta percentage between SMPS-based estimated energy units and the energy units reported in electricity bill (EB Bill) by subtracting number of units consumed by diesel generators from total estimated units based on SMPS, then dividing result by the consumption as per EB Bill, and multiplying by 100, to validate bill accuracy against estimated power consumption using SMPS data; and a delta percentage between PRB-based estimated energy units and the energy units reported in the EB bill by subtracting number of units consumed by diesel generators from the total estimated units based on load, then dividing result by the estimated power consumption as per EB Bill, and multiplying by 100, providing a comprehensive metric to detect the one or more discrepancies in energy billing versus estimated consumption based on PRB data.

12. A system [300] for validating energy consumption using physical resource block (PRB) utilization in a communication system, the system [300] comprises: a collecting unit [302] configured to collect a set of performance metrics for one or more cell sites in a network region; a mapping unit [304] configured to map each of the one or more cell sites to at least one sector and band, associated with the corresponding one or more cell sites, based on the collected set of performance metrics; a determining unit [306] configured to determine an average value of daily PRB utilization data for the mapped at least one sector and band; a processing unit [308] configured to compute total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) Power, a network elements (NE) Power, a microwave Power, and a cabinet Power based on the average value of daily PRB utilization data; a comparing unit [310] configured to compare the computed total estimated power consumption with actual energy consumption data for each cell site; and an identifying unit [312] configured to identify one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site.

13. The system [300] as claimed in claim 12, wherein the actual energy consumption is determined based on at least one of switched mode power supply (SMPS) usage data, diesel generator (DG) usage data, and electricity bill data.

14. The system [300] as claimed in claim 12, wherein the processing unit [308] is configured to enrich the collected set of performance metrics by adding at least one of a Geographic Information System (GIS) scope and one or more priority details for each of the one or more cell sites.

15. The system [300] as claimed in claim 12, wherein the processing unit [308] is configured to determine the average value of daily PRB Utilization for at least one of each of the one or more cell Sites, Band, and Sector.

16. The system [300] as claimed in claim 12, wherein the mapping unit [304] is further configured to map power consumption of each cell site to the average value of daily PRB utilization for each cell Site, Band, and Sector based on at least one of the PRB Utilization and the RRH power.

17. The system [300] as claimed in claim 12, wherein the processing unit [308] is configured to assign a service type to each of the one or more cell sites, wherein at least one of the service type comprises at least one of Long Term Evolution (LTE) Only and LTE & 5G, and the BBU Power & Cabinet power is added based on an assigned service type.

18. The system [300] as claimed in claim 12, wherein the mapping unit [304] is configured to map network equipment (NE) power consumption and microwave power consumption of each cell site to the power consumption of the corresponding one or more cell sites by utilizing data from Transport Inventory Dump and Microwave Equipment Power Consumption.

19. The system [300] as claimed in claim 12, wherein the one or more cell sites, selected based on the identified one or more discrepancies, are prioritized for audit and corrective actions, wherein the audit and corrective action comprises at least one of checking for unintended power tapping, and changing faulty meters.

20. The system [300] as claimed in claim 12, wherein the processing unit [308] is configured to determine computed Total Estimated energy consumption in Kilowatt-hours (KWH) based on PRB utilisation by multiplying computed Total Estimated Power Consumption based on Load with 24.

21. The system [300] as claimed in claim 12, wherein the processing unit [308] is configured to determine computed Total Estimated energy consumption in KWH based on SMPS DC power average value, by multiplying the SMPS DC power average value with 24.

22. The system [300] as claimed in claim 21, wherein the processing unit [308] is configured to compute at least one of a delta percentage between PRB and SMPS energy estimate by determining difference between the SMPS DC power average value and the computed total estimated power consumption based on load, divided by the SMPS DC power average value, multiplied by 100, to assess alignment between calculated and actual power draw based on load versus power supply characteristics; a delta percentage between SMPS-based estimated energy units and the energy units reported in electricity bill (EB bill) by subtracting number of units consumed by diesel generators from total estimated units based on SMPS, then dividing result by the consumption as per EB bill, and multiplying by 100, to validate bill accuracy against estimated power consumption using SMPS data; and a delta percentage between PRB-based estimated energy units and the energy units reported in the EB bill by subtracting number of units consumed by diesel generators from the total estimated units based on load, then dividing result by the estimated power consumption as per EB bill, and multiplying by 100, providing a comprehensive metric to detect the one or more discrepancies in energy billing versus estimated consumption based on the PRB data.

23. A non-transitory computer-readable storage medium storing instruction for validating energy consumption using physical resource block (PRB) utilization in a communication system, the storage medium comprising executable code which, when executed by one or more units of a system, causes: a collecting unit [302] to collect a set of performance metrics for one or more cell sites in a network region; a mapping unit [304] to map each of the one or more cell sites to at least one sector and band, associated with the corresponding one or more cell sites, based on the collected set of performance metrics; a determining unit [306] to determine an average value of daily PRB utilization data for the mapped sector and band; a processing unit [308] to compute total estimated power consumption for each cell site by aggregating at least one of a sector remote radio head (RRH) power, a baseband unit (BBU) Power, a network elements (NE) Power, a microwave Power, and a cabinet Power based on the average value of daily PRB utilization data; a comparing unit [310] to compare the computed total estimated power consumption with actual energy consumption data for each cell site; and an identifying unit [312] configured to identify one or more discrepancies between the computed total estimated power consumption and actual energy consumption to validate the energy consumption of the cell site.