System and method for correcting antenna misalignment in a sectors
Patent Information
- Authority / Receiving Office
- EP · EP
- Patent Type
- Applications
- Current Assignee / Owner
- JIO PLATFORMS LTD
- Filing Date
- 2024-06-05
- Publication Date
- 2026-05-06
Smart Images
Figure IN2024050682_09012025_PF_FP_ABST
Abstract
Description
SYSTEM AND METHOD FOR CORRECTING ANTENNA MISALIGNMENT IN A SECTORSRESERVATION OF RIGHTS
[0001] A portion of the disclosure of this patent document contains material, which is subject to intellectual property rights such as, but are not limited to, copyright, design, trademark, Integrated Circuit (IC) layout design, and / or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner.FIELD OF INVENTION
[0002] The embodiments of the present disclosure generally relate to network planning and optimization. More particularly, the present disclosure relates to a system and a method for correcting antenna misalignment in a sector.BACKGROUND OF THE INVENTION
[0003] The following description of 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 be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0004] In the field of telecommunications and network planning, mobile network deployment is a crucial process for the effective utilization of resources in a network. One of the key elements in mobile network deployment is the antenna system. The alignment of the antenna system ensures that cellular networks provide comprehensive coverage and consistent service quality. By strategically placing cells, operators can minimize coverage gaps, reduce signalinterference, and ensure that users have reliable connectivity across the service area.
[0005] Moreover, antenna alignment in a cell plays a crucial role in facilitating seamless handover processes as users move across different cells. Proper alignment ensures that users experience minimal interruption in service when transitioning from one cell to another.
[0006] However, in some cases, the antenna system is not properly aligned due to sectors not being correctly azimuthal. Such antenna misalignment can cause interference between adjacent cells. In addition, failure to align antennas can affect network performance and reduce throughput. Misalignment issues can stem from various factors, including incorrect installation, environmental changes, and physical obstructions.
[0007] Patent document number CN114221717B titled “Base Station Antenna Azimuth Angle Calibration Method and Device” discloses obtaining an original azimuth angle of an antenna to be calibrated, obtaining sample data associated with the antenna including key performance index (KPI) for handover between a target cell and a neighbor cell, measurement report (MR) data, and drive test minimization (MDT) data; analyzing from multiple angles to obtain judgment results; and analyzing the judgment results to obtain the calibrated azimuth angle of the antenna. The method improves calibration accuracy by considering multiple factors.
[0008] Patent document number CN110536310B titled “Method for Identifying Antenna Reverse Connection Based on User Data” discloses collecting user data and working parameter data, combining these data through several algorithms to correct the azimuth angle, calculating the predicted azimuth angle of each cell and the difference between the predicted azimuth angle and the working parameter azimuth angle, and processing the data to judge whether the antennas of the cells are reversely connected or not. This method combines multiple algorithms to ensure stability of data prediction in different regions.
[0009] Conventional systems and methods face difficulty in the selection and management of multiple radio nodes in an optimized manner. There is, therefore, a need in the art to provide a method and a system that can overcome the shortcomings of the existing prior arts.
[0010] There is, therefore, a need in the art to provide a system and a method that can mitigate the problems associated with the prior arts.OBJECTS OF THE INVENTION
[0011] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0012] An object of the present disclosure is to provide a system and a method for correcting antenna misalignment in sectors.
[0013] Another object of the present disclosure is to minimize call drops, maintain service continuity, and enhance the user experience during mobility.
[0014] An object of the present disclosure is to minimize interference effects and improve network reliability and performance.
[0015] Another object of the present disclosure is to reduce unnecessary overlap or gaps in coverage and optimize the use of network resources.
[0016] An object of the present disclosure is to optimize the use of infrastructure and minimize the number of required sites.
[0017] Another object of the present disclosure is to determine the optimal placement and configuration of cells to efficiently handle user demand.
[0018] An object of the present disclosure is to maximize network capacity, improve data speeds, and support a higher number of concurrent users.SUMMARY
[0019] The present disclosure discloses a method for correcting antenna misalignment in sectors. The method includes receiving, by a user data collection module, a plurality of user records of a plurality of user equipments. The method includes receiving gathering, by a processing module, the plurality of user records for a defined duration. The method includes calculating, by the processing module, at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location. The method includes implementing, by the processing module, a dynamic cone rotation of a first degree and identifying at least three non-overlapping cones having a maximum number of user records. The method includes determining, by the processing module, a center angle by computing user records within the identified at least three nonoverlapping cones. The method includes retrieving, by the processing module, a current azimuth angle of the antenna from a database and comparing the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle. The deviation is an indicative of a degree of misalignment. The method includes generating at least one signal, by the processing module, for aligning the antenna based on the degree of misalignment.
[0020] In an embodiment, the method includes swapping, by the processing module, when the degree of misalignment exceeds a predetermined threshold, a sector of the antenna with a sector of another antenna.
[0021] In an embodiment, the plurality of user records includes the at least one location data, quality parameters, radio frequency (RF) condition, signal strength, a serving cell identifier (cell ID), and a serving sector identifier (sector ID).
[0022] In an embodiment, the plurality of user records is collected from a plurality of speed testing servers, and a plurality of user devices.
[0023] In an embodiment, each user record includes a user geolocation and a plurality of quality parameters.
[0024] In an embodiment, the method includes segregating, by the processing module, the gathered user records based on the user geolocation associated with each user record.
[0025] In an embodiment, the first degree is 30 degree.
[0026] In an embodiment, the method includes adjusting the dynamic cone rotation by shifting the dynamic cone with a second degree, wherein second degree is 5 degree.
[0027] In an embodiment, the center angle is calculated by identifying the high-density areas within the identified cones and computing an average of the bearing angles in the respective areas.
[0028] In an embodiment, the method includes generating, by the processing module, a report for initiating a field audit based on the degree of misalignment.
[0029] The present disclosure discloses a system for correcting antenna misalignment in sectors. The system includes a user data collection module and a processing unit. The user data collection module is configured to receive a plurality of user records of a plurality of user equipments. The processing module is configured to gather the plurality of user records for a defined duration. The processing module is configured to calculate at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location. The processing module is configured to implement a dynamic cone rotation of a first degree and identify at least three non-overlapping cones having a maximum number of user records. The processing module is configured to determine a center angle by computing user records within the identified at least three nonoverlapping cones. The processing module is configured to retrieve a current azimuth angle of the antenna from a database and compare the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle. The deviation is an indicative of a degree ofmisalignment. The processing module is configured to generate at least one signal for aligning the antenna based on the degree of misalignment.
[0030] In an embodiment, the processing module is configured to swap a sector of the antenna with a sector of another antenna when the degree of misalignment exceeds a predetermined threshold.
[0031] In an embodiment, the plurality of user records includes the at least one location data, quality parameters, radio frequency (RF) condition, signal strength, a serving cell identifier (cell ID), and a serving sector identifier (sector ID).
[0032] In an embodiment, the plurality of user records is collected from a plurality of speed testing servers, and a plurality of user devices.
[0033] In an embodiment, each user record includes a user geolocation and a plurality of quality parameters.
[0034] In an embodiment, the processing module is configured to segregate the gathered user records based on the user geolocation associated with each user record.
[0035] In an embodiment, the first degree is 30 degree.
[0036] In an embodiment, the processing module (208) is configured to adjust the dynamic cone rotation by shifting the dynamic cone with a second degree, wherein second degree is 5 degree.
[0037] In an embodiment, the center angle is calculated by identifying the high-density areas within the identified cones and computing an average of the bearing angles in the respective areas.
[0038] In an embodiment, the processing module is configured to generate a report based on the degree of misalignment to initiate a field audit.
[0039] The present disclosure discloses user equipment that is configured to correct antenna misalignment in sectors. The user equipment includes a processor, and a computer readable storage medium storing programming instructions for execution by the processor. Under the programming instructions, the processor is configured to receive a plurality of user records of a plurality of user equipments. Under the programming instructions, the processor is configured to gather the plurality of user records for a defined duration and calculate at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location. Under the programming instructions, the processor is configured to implement a dynamic cone rotation of a first degree and identify at least three non-overlapping cones having a maximum number of user records. Under the programming instructions, the processor is configured to determine a center angle by computing user records within the identified at least three nonoverlapping cones. Under the programming instructions, the processor is configured to retrieve a current azimuth angle of the antenna from a database and compare the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle. The deviation is an indicative of a degree of misalignment. Under the programming instructions, the processor is configured to generate at least one signal for aligning the antenna based on the degree of misalignment.BRIEF DESCRIPTION OF DRAWINGS
[0040] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems 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. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of suchdrawings includes the disclosure of electrical components, electronic components, or circuitry commonly used to implement such components.
[0041] FIG. 1 illustrates an example network architecture for implementing a system for correcting antenna misalignment in sectors, in accordance with an embodiment of the present disclosure.
[0042] FIG. 2 illustrates an example block diagram of the system, in accordance with an embodiment of the present disclosure.
[0043] FIG. 3 illustrates an exemplary representation of a current conical region and a next conical region covered by the antenna, in accordance with an embodiment of the present disclosure.
[0044] FIG. 4 illustrates an exemplary flow chart for a method of detecting misalignment of the antenna in the sector, in accordance with an embodiment of the present disclosure.
[0045] FIG. 5 illustrates another exemplary flow chart diagram representing the method of detecting misalignment of the antenna in the sector, in accordance with an embodiment of the present disclosure.
[0046] FIGS. 6A-6B illustrate exemplary representations of a user interface for current azimuth angle (stored in a database) and the center angle (field measurement), respectively, in accordance with an embodiment of the present disclosure.
[0047] FIGS. 7A-7B illustrate exemplary representations of the user interface for the current alignment of antennas prior to sector swapping and alignment of the antenna after sector swapping, respectively, in accordance with an embodiment of the present disclosure.
[0048] FIG. 8 illustrates an example computer system in which or with which the embodiments of the present disclosure may be implemented.
[0049] FIG. 9 illustrates an exemplary flowchart for the method of correcting antenna misalignment in sectors, in accordance with an embodiment of the present disclosure.
[0050] The foregoing shall be more apparent from the following more detailed description of the disclosure.LIST OF REFERENCE NUMERALS100 - Network Architecture102-1, 102-2... 102-N - Users104-1, 104-2. . . 104-N - User Equipments106 - Network108 - System112 - Centralized Server202 - One or more processor(s)204 - Memory206 - Interface(s)208 - Processing Module210 - Database210 - User data collection module213 - Other modules214 - Database302 - Antenna304 - First angle306 - Second angle308 - Current conical region310 - Next conical region800 - Example computer system810 - External storage device820 - Bus830 - Main memory840 - Read-only memory (ROM)850 - Mass storage device860 - Communication port(s)870 - ProcessorDETAILED DESCRIPTION
[0051] In the following description, for explanation, various specific details are outlined in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0052] 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.
[0053] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well- known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.
[0054] Also, it is noted that individual embodiments may be described as a process that 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 can be performed in parallel or concurrently. In addition, the order of the operations may be rearranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0055] 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 like the term “comprising” as an open transition word without precluding any additional or other elements.
[0056] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0057] The terminology used herein is to describe particular embodiments only and is not intended to be limiting the disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any combinations of one or more of the associated listed items.
[0058] Embodiments herein relate to a system and a method for correcting antenna misalignment in a sector. In order to correct antenna misalignment, a degree of misalignment is determined. In particular, the user records such as user location (longitudinal, latitudinal), RSRP are received. Based on the received data, the center angle of alignment of antenna is identified. The center angle is identified by:• selecting a conical geographical region having a predetermined cone angle such as 30 degree and identifying the number of user samples in the selected geographical region, that having the RSRP above a particular threshold.• selecting another geographical conical region (with the same cone angle) with a deviation of predefined angle e.g. 5 degrees from the current position, wherein the other geographical conical region can be obtained by rotating the current conical geographical region by the deviation about a vertex of the cone. The vertex of the cone refers to the location of the antenna / cell.• Repeating the steps to cover the entire spherical region about that vertex.• identifying the area in which we have maximum RSRP.• identifying the center angle based on the identified conical region having the maximum RSRP.
[0059] In an embodiment, upon identification of the center angle, the actual angle may be compared with the center angle to determine a degree of misalignment, the degree of misalignment is the angle deviation by which the antenna should be aligned in order to achieve the maximum RSRP.
[0060] In an embodiment, the system may include one or more actuators such as motors configured at the antenna system. Upon identification of the center angle, the system can send signals to the one or more actuators to align the antenna with the degree of misalign so as to achieve maximum RSRR
[0061] The various embodiments throughout the disclosure will be explained in more detail with reference to FIGS. 1-9.
[0062] FIG. 1 illustrates an exemplary network architecture in which or with which a system (108) for correcting antenna misalignment in sectors is implemented, in accordance with embodiments of the present disclosure. Sectors typically refer to a division of a cell site's coverage area into distinct directional zones. Each sector is served by its own set of antennas, which are aimed to cover a specific portion of the cell's coverage area. The sectors allow more efficient use of the available radio frequency spectrum and increase the capacity and performance of the network by reducing interference and enabling more targeted transmission of data to and from users within each sector.
[0063] Referring to FIG. 1, the network architecture (100) includes one or more computing devices or user equipments (104-1, 104-2. .. 104-N) associated with one or more users (102-1, 102-2. .. 102-N) in an environment. A person of ordinary skill in the art will understand that one or more users (102-1, 102- 2... 102-N) may be individually referred to as the user (102) and collectively referred to as the users (102). Similarly, a person of ordinary skill in the art will understand that one or more user equipments (104-1, 104-2. .. 104-N) may be individually referred to as the user equipment (104) and collectively referred to as the user equipment (104). A person of ordinary skill in the art will appreciate that the terms “computing device(s)” and “user equipment” may be usedinterchangeably throughout the disclosure. Although three user equipments (104) are depicted in FIG. 1, however any number of the user equipments (104) may be included without departing from the scope of the ongoing description.
[0064] In an embodiment, the user equipment (104) includes smart devices operating in a smart environment, for example, an Internet of Things (loT) system. In such an embodiment, the user equipment (104) may include, but is not limited to, smart phones, smart watches, smart sensors (e.g., mechanical, thermal, electrical, magnetic, etc.), networked appliances, networked peripheral devices, networked lighting system, communication devices, networked vehicle accessories, networked vehicular devices, smart accessories, tablets, smart television (TV), computers, smart security system, smart home system, other devices for monitoring or interacting with or for the users (102) and / or entities, or any combination thereof. A person of ordinary skill in the art will appreciate that the user equipment (104) may include, but is not limited to, intelligent, multisensing, network-connected devices, that can integrate seamlessly with each other and / or with a central server or a cloud-computing system or any other device that is network-connected.
[0065] In an embodiment, the user equipment (104) includes, but is not limited to, a handheld wireless communication device (e.g., a mobile phone, a smart phone, a phablet device, and so on), a wearable computer device(e.g., a head-mounted display computer device, a head-mounted camera device, a wristwatch computer device, and so on), a Global Positioning System (GPS) device, a laptop computer, a tablet computer, or another type of portable computer, a media playing device, a portable gaming system, and / or any other type of computer device with wireless communication capabilities, and the like. In an embodiment, the user equipment (104) includes, but is not limited to, any electrical, electronic, electro-mechanical, or an equipment, or a combination of one or more of the above devices such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device,wherein the user equipment (104) may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, a keyboard, and input devices for receiving input from the user (102), or the entity (110) such as touch pad, touch enabled screen, electronic pen, and the like. A person of ordinary skill in the art will appreciate that the user equipment (104) may not be restricted to the mentioned devices and various other devices may be used.
[0066] In an embodiment, the network (106) includes at least one of a Fifth Generation (5G) network, 6G network, or the like. The network (106) enables the user equipment (104) to communicate with other devices in the network architecture (100) and / or with the system (108). The network (106) includes a wireless card or some other transceiver connection to facilitate this communication. In another embodiment, the network (106) is implemented as, or include any of a variety of different communication technologies such as a wide area network (WAN), a local area network (LAN), a wireless network, a mobile network, a Virtual Private Network (VPN), the Internet, the Public Switched Telephone Network (PSTN), or the like.
[0067] In another exemplary embodiment, the centralized server (112) includes or comprise, by way of example but not limitation, one or more of: a stand-alone server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof.
[0068] In an embodiment, the system 108 may receive a set of information pertaining to the user records, such as but not limited to user location (longitudinal, latitudinal) and reference Signal Received Power (RSRP). Based on the set of information, the center angle of alignment of the antenna is identified. The center angle of alignment of the antenna may refer to the center angle of theantenna for the primary serving direction of the antenna.
[0069] In an embodiment, an optimized angle is identified based on the set of information (user records). To identify the optimized angle, a conical region with cone angle of a first predetermined cone angle is selected and determine the quality parameters such as RSRP for the conical region. Then, the next conical region having the same cone angle as the current conical region is selected by rotating the current conical region with a second predetermined angle (sector degree), and then the quality parameters for the next conical region are determined. In this way, the next conical region may be achieved by rotating the current conical region with a second predetermined angle in order to achieve the next conical region. The process of the rotation of conical region with a second predetermined angle is repeated to cover the entire spherical region covered by the corresponding antenna. The first predetermined angle indicates a solid angle at the vertex of cone, whereas a second predetermined angle indicate a solid angle by which the current conical region needs to rotate about the vertex of cone to achieve the next conical region.
[0070] In an embodiment, the system may identify the conical region having the maximum RSRP and accordingly, identify the center angle of the antenna to provide optimized network performance.
[0071] In an embodiment, the system may retrieve a current azimuth angle of the antenna system through a database. The system may then compare the current azimuth angle with the center angle to determine a degree of misalignment. Based on the degree of misalignment, useful insights can be generated.
[0072] In an embodiment, if the degree of misalignment exceeds a predetermined threshold, the system may determine whether a sector of the antenna needs to be swapped with a sector of the other antenna. Swapping sectors of antennas involves reassigning the directional coverage areas of antennas between different physical base stations or access points in a wirelesscommunication network. Each sector typically represents a specific directional coverage zone served by a set of antennas. In an aspect, the predetermined threshold refers to a predefined value or limit set in advance, which serves as a reference point for making decisions or taking actions. In an example, the predetermined threshold lies a range of 30 degree to 60 degree. In another example, the predetermined threshold is configurable depending on the user requirements. Sector swapping is required in cases where adjusting the antenna system may not be able to correct the misalignment. In such cases, the sector or region covered by the two antenna systems may be swapped in order to correct the misalignment.
[0073] In an embodiment, the system may include one or more actuators, such as motors configured to rotate the antenna. Upon identification of the center angle, the system can send signals to the one or more actuators to align the antenna with the degree of misalign so as to achieve maximum RSRP.
[0074] In an embodiment, if the degree of misalignment is less than a defined value, it is determined that there is no need to change the alignment of the antenna. The antenna can be said to be properly aligned.
[0075] FIG. 2 illustrates an example block diagram (200) of the system (108), in accordance with an embodiment of the present disclosure.
[0076] Referring to FIG. 2, in an embodiment, the system (108) may include one or more processor(s) (202). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and / or any devices that process data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the system (108). The memory (204) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share datapackets over a network service. The memory (204) may comprise any non- transitory storage device including, for example, volatile memory such as randomaccess memory (RAM), or non-volatile memory such as erasable programmable read only memory (EPROM), flash memory, and the like.
[0077] In an embodiment, the system (108) may include an interface(s) (206). The interface(s) (206) may comprise a variety of interfaces, for example, interfaces for data input and output devices (VO), storage devices, and the like. The interface(s) (206) may facilitate communication through the system (108). The interface(s) (206) may also provide a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, processing module (208) and a database (210). Further, the processing module (208)processing module (208) may include one or more engine(s) such as, but not limited to, an input / output engine, an identification engine, and an optimization engine.
[0078] In an embodiment, the processing module (208) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing module (208). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing module (208) may be processorexecutable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing module (208) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing module (208). In such examples, the system may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine -readable storage medium may be separate but accessible to the system and the processing resource. In other examples, the processing module (208) may be implemented by electroniccircuitry.
[0079] The processing module (208) comprises several modules, including but not limited to a user data collection module (210) and other modules (213). The user data collection module (210) is configured to receive the user records (geolocated user measurements) of the plurality of user equipments. In an aspect, the receiving unit (202) is configured to receive the user records directly from the user equipment, a plurality of network modules or any other sources (third party source). In an example, the user records may also be stored in cloud-based services, either provided by the network operator or third-party service providers. These could include storage services, databases, and content delivery networks. In another example, the user records may be received from subscriber data management (SDM) systems. The SDM systems manage subscriber data across different generations of networks and may integrate with 5G core network functions to ensure seamless service continuity. The received user records include a user geolocation and a plurality of quality parameters, such as Reference Signal Received Power (RSRP).
[0080] The processing module is configured to gather the plurality of user records for a defined duration. In an example, the plurality of user records includes the at least one location data, radio frequency (RF) condition, quality parameters, signal strength, a serving cell identifier (cell ID), and a serving sector identifier (sector ID). In an example, the RF condition may include signal strength, multipath fading, interference, shadowing, doppler shift and channel capacity. The signal quality refers to the power level of the radio signal received by the receiver. It is influenced by factors such as distance from the transmitter, obstacles in the propagation path, and interference from other sources. The signal quality also includes parameters like Signal-to-Noise Ratio (SNR) and Signal-to- Interference-plus-Noise Ratio (SINR). These metrics indicate the level of unwanted noise and interference present in the received signal, affecting the ability of the receiver to decode the transmitted data accurately. In wireless communication, signals can reach the receiver through multiple paths due toreflections, diffractions, and scattering caused by obstacles in the propagation environment. Multipath fading can lead to signal fading and distortion, impacting communication performance. In an example, the interference from other nearby transmitters operating on the same or adjacent frequencies can degrade the quality of the received signal. This interference can be caused by other cellular base stations, Wi-Fi routers, electronic devices, etc. In an area, shadowing occurs when large objects such as buildings, trees, or terrain block or attenuate the radio signal, causing variations in signal strength and coverage in different areas. In wireless communication, the doppler shift occurs when there is relative motion between the transmitter and the receiver, causing a shift in the frequency of the received signal. This effect is especially significant in mobile communication scenarios, where either the transmitter or the receiver (or both) is in motion. Also, RF conditions determine the maximum data rate or channel capacity that can be achieved over the communication link. Factors such as bandwidth availability, modulation scheme, and coding rate influence the achievable data rate under given RF conditions.
[0081] The processing module (208) collects geolocation data and quality parameters from various sources over a specified duration, such as one week. These sources include a plurality of speed testing servers and a plurality of user devices. This comprehensive data collection process provides an extensive view of network performance from diverse user perspectives and locations, enabling the system to compile robust and varied information regarding the coverage area.
[0082] The processing module is configured to calculate at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location. Bearing is a direction or angle measurement used to map the direction of one point relative to another. For each user measurement (user or user record), the processing module (208) calculates the bearing angle, which is the direction from the user's location to the serving cell. This calculation is essential for understanding the orientation of the user relative to the cell, thus aiding in determining the coverage area. By calculating bearing angles, the system can mapout the directions from which the cell receives signals, facilitating the identification of the primary serving direction.
[0083] The processing module is configured to implement a dynamic cone rotation of a first degree. In beamforming, antennas focus radio frequency (RF) energy in specific directions to improve signal quality and capacity. Dynamic cone rotation involves adjusting the orientation of these antenna beams dynamically based on factors such as the location of users, their movement, and the overall network conditions. By continuously adapting the direction of the antenna beams, dynamic cone rotation enables more precise targeting of signals towards users, maximizing throughput, minimizing interference, and enhancing the overall performance of the wireless network.
[0084] The processing module (208) creates a dynamic cone with an angle of approximately 30 degrees (first degree). This cone is subsequently rotated in increments of about 5 degrees (second degree) around the serving cell. During this rotation, the system identifies the areas with the highest density of measurements (user records collected from that area). The system then selects the top three nonoverlapping cones with the maximum number of measurements. This approach ensures that data is analyzed in focused segments, thereby enhancing the accuracy of the alignment process by concentrating on the most significant areas of user activity.
[0085] The processing module is configured to determine a center angle by computing user records within the identified at least three non-overlapping cones. The center angle is determined by computing the measurements within the high- density areas identified during the cone rotation step. The center angle represents the optimal direction in which the antenna should be aligned to effectively cover the maximum number of users. The center angle is calculated by averaging the bearing angles within the identified high-density areas. This calculation ensures that the antenna alignment is based on the most reliable and dense data points.
[0086] The processing module is configured to retrieve a serving cellazimuth angle (also referred as current azimuth angle) of the antenna from a database. The azimuth angle represents the direction that the antenna is currently facing (the direction in which the antenna is placed). This information is critical for comparing the existing alignment with the optimal alignment derived from user records.
[0087] The processing module (208) compares the current azimuth angle with the center angle to determine a deviation (the degree of misalignment) between the center angle and the current azimuth angle. The deviation between these two angles indicates the extent of the misalignment and the necessary adjustments for the antenna. This comparison is essential for identifying any discrepancies in the current antenna alignment.
[0088] The processing module (208) compares the current azimuth angle with the center angle to determine the degree of misalignment. The deviation between these two angles indicates the extent of the misalignment and the necessary adjustments for the antenna. This comparison is essential for identifying any discrepancies in the current antenna alignment.
[0089] The processing module is configured to generate at least one signal for aligning the antenna based on the degree of misalignment.
[0090] If the degree of misalignment exceeds the predetermined threshold, the processing module (208) initiates the sector swap, wherein the sector of the antenna is exchanged with a sector of another antenna. This measure ensures that severe misalignments are corrected efficiently.
[0091] The other modules (213) may include functionalities such as generating reports to initiate a field audit based on the identified degree of misalignment. These reports provide actionable insights for network operators to implement corrective measures. Using advanced algorithms and analytical techniques, the processing unit carefully analyzes the user data records to measure misalignment. The processing unit is configured to condense the analysed data togenerate a report(s) that prompt field audits. By identifying areas of concern accurately, these reports provide network operators with actionable insights needed to implement targeted corrective measures.
[0092] Each report produced by the processing unit offers a detailed evaluation of the performance metrics related to antenna sectors, including signal strength, coverage patterns, interference levels, and alignment with network objectives. Through thorough analysis, the reports highlight deviations from optimal performance standards, flagging sectors that require closer examination through field audits. Equipped with this information, network operators can execute strategic interventions to realign antenna sectors and optimize network performance.
[0093] The actionable insights presented in these reports enable network operators to make informed decisions about corrective measures. Whether it involves adjusting antenna configurations, fine-tuning frequency allocations, or upgrading equipment, the network operators can use the recommendations outlined in the reports to address misalignment issues effectively. By proactively tackling these challenges, the network operators can improve network reliability, reduce service disruptions, and ultimately provide an exceptional user experience.
[0094] Additionally, the processing module (208) can verify other cells in the same band of the same eNodeB (eNB) for potential sector swaps if significant misalignment is detected. This step helps in maintaining network consistency and performance across different cells.
[0095] The system architecture (200) described in FIG. 2 ensures precise antenna alignment by utilizing the user records and advanced processing techniques, thereby enhancing network performance and service quality. Although FIG. 2 shows exemplary components of the system (108), in other embodiments, the system (108) may include fewer components, different components, differently arranged components, or additional functional components than depicted in FIG. 2. Additionally, or alternatively, one or more components of thesystem (108) may perform functions described as being performed by one or more other components of the system (108).
[0096] FIG. 3 illustrates an exemplary representation (300) of a current conical region and the next conical region covered by the antenna, in accordance with an embodiment of the present disclosure.
[0097] The antenna (302) is depicted at the center of the conical regions. The current conical region (308) represents the area covered by the antenna at a specific orientation. The current conical region (308) is defined by a first angle (304) and a second angle (306), which delineates the boundaries of the cone.
[0098] The first angle (304) is an initial angle at which the current conical region (308) begins. The second angle (306) is the angle at which the current conical region (308) ends. These angles are critical for determining the coverage area of the antenna (302) at its current orientation.
[0099] The next conical region (310) represents the area that will be covered by the antenna when it is rotated to the next position. This rotation is performed in increments of about 5 degrees. The dashed lines in FIG. 3 indicates the movement from the current conical region (308) to the next conical region (310).
[0100] The dynamic cone rotation process involves shifting the coverage area of the antenna (302) from the current conical region (308) to the next conical region (310). This process is essential for identifying high-density areas within the coverage region and determining the optimal alignment of the antenna (302).
[0101] By analyzing the measurements within these conical regions, the system can accurately compute the center angle for optimal antenna alignment. This ensures that the antenna (302) provides the best possible coverage and performance.
[0102] FIG. 4 illustrates an exemplary flow chart for the method (400) ofdetecting misalignment of antenna in a sector, in accordance with an embodiment of the present disclosure.
[0103] The method begins with collecting geo-located user measurements (user records) from various sources over a duration of one week. This data provides comprehensive information about the network's performance from different user perspectives and locations (at step 402).
[0104] Next, the method involves the computation of the bearing angle for each measurement with respect to the serving cell location. In an example, the bearing angle is the direction from the user's location to the serving cell, which is crucial for understanding the orientation and coverage area of the cell (at step 404).
[0105] The method then proceeds to move a dynamic cone about 30 degrees in 5-degree steps. During this process, the system identifies and selects the top three non-overlapping cones with the maximum number of measurements (at step 406). This step focuses the analysis on the areas with the highest density of user measurements.
[0106] The center angle is computed using the measurements identified in the high-density areas within the selected cones. This center angle represents the optimal direction in which the antenna should be aligned to maximize coverage and performance (at step 408).
[0107] The method continues by calculating the deviation between the derived center angle and the serving cell azimuth angle stored in the database. This deviation indicates the degree of misalignment of the antenna (at step 410).
[0108] If a significant misalignment is detected, the method includes further checks (412) for other cells within the same band and associated with the same eNodeB (eNB) for potential sector swaps. This step ensures that any severe misalignment issues are addressed comprehensively across related cells (at step412).
[0109] The method concludes with the generation of a report to initiate a field audit based on the identified misalignment. This report provides actionable insights and detailed information for network operators to take corrective measures and ensure optimal antenna alignment (at step 414).
[0110] The block diagram (400) detailed in FIG. 4 provides a structured and systematic approach for detecting and addressing antenna misalignment, leveraging user records and advanced analytical techniques to enhance network performance and service quality.
[0111] FIG. 5 illustrates another exemplary flow chart diagram representing a method of detecting misalignment of antenna in the sector, in accordance with an embodiment of the present disclosure.
[0112] The process begins at step (502) with the collection of one week of valid user measurements, including latitude and longitude (Lat / Lon) data from sources such as plurality of speed testing servers, and a plurality of user devices.
[0113] At step (504), the system fetches information for each sample, specifically the latitude and longitude and the name of the serving cell.
[0114] In step (506), the system creates a unique set for all Cell Identifiers (Cis) appearing in the drive log data, referred to as Set 1.
[0115] The method then proceeds to step (508), where the system filters cells having more than a predefined number (Z) of valid samples. Cells with fewer than Z valid samples are ignored at step (510).
[0116] For the cells with valid samples, step (512) involves calculating the bearing angle between each sample and the serving cell. The direction is measured from the serving cell to the sample.
[0117] At step (514), the system calculates the center angle from all usermeasurements. This involves determining the average direction that most measurements point towards, indicating the primary coverage direction.
[0118] Step (516) involves storing the computed bearing angles from each Cell Identifier (CI) to the samples in a separate sheet, referred to as Set 2.
[0119] Moving to step (518), for each CI in Set 1, the system computes the center angle by extracting the Ythand Xthpercentile values for the calculated bearing angles from Set 2. In an example, the X represents a value of 95. In an example, the Y represents a value of 5.
[0120] Step (520) involves computing the center angle using these Ythand Xthpercentile values.
[0121] At step (522), the system checks for quadrant correction. If the computed Ythpercentile and Xthpercentile values are both in Quadrant 1 (0 degrees to 90 degrees) and Quadrant 4 (270 degrees to 360 degrees), the cells are flagged for quadrant correction.
[0122] If quadrant correction is needed, step (524) corrects the center angle by adding 180 degrees. The corrected angles are then compiled into a list at step (528).
[0123] If quadrant correction is not needed, step (526) involves calculating the center angle as the average of the Xthand Y* percentile computed bearing angles.
[0124] The system then checks if further center angle correction is required at step (530). If the center angle is equal to or exceeds 360 degrees, step (532) corrects the angle by subtracting 360 degrees.
[0125] At step (534), the corrected center angles are kept as is for the respective cells.
[0126] Step (536) involves compiling a list of corrected azimuth angles forall respective cells.
[0127] At step (538), the system maps the planned azimuth (serving cell azimuth angle) from the database against each cell.
[0128] The method continues to step (540), where the deviation in azimuth is calculated as the maximum of the absolute values of the differences between the center angle (corrected) and the planned azimuth.
[0129] At step (542), the system checks the number of misaligned sectors in a particular band of the site. If more than one sector is misaligned, step (544) applies conditions to determine the extent of deviation.
[0130] Step (544) involves evaluating each CI for deviation. If the deviation in azimuth is less than P degrees, no action is required. In an example, the P represents a value of 10. For deviations between P and Q degrees, the system flags a database mismatch with a field value. In an example, the Q represents a value of 60. For deviations equal to or exceeding Q degrees, the system suggests a re-survey.
[0131] Step (546) involves evaluating each CI for deviation. If the deviation in azimuth is less than P degrees, no action is required (step 548). In an example, the P represents a value of 10. For deviations between P and R degrees, the system flags a database mismatch with a field value (step 550). In an example, the R represents a value of 45. For deviations equal to or exceeding R degrees, the system suggests a re-survey (step 552).
[0132] Step (554) applies additional conditions if more than C% of the measurements of one cell (a) are falling in +d deg of second cell’s (b) azimuth and more than C % measurement of one cell (b) are falling in +D degrees of second cell’s (c) azimuth and more than C % measurement of one cell (c) are falling in + d degrees of second cell’s (a) azimuth of the same site or vice versa than it will be considered as a cyclic swap. This condition identifies cyclic swaps. In an example,the C represents a value of 40. In an example, the D represents a value of 20.
[0133] Step (558) applies additional conditions if more than C% measurement of one cell falls within + D degrees of another cell’s azimuth of the same site and vice versa than a sector swap will be considered.
[0134] The method concludes at step (556) with the generation of a "Sector Misalignment Report" and a work order containing necessary recommendations to correct the identified issues.
[0135] FIG. 6A illustrates an exemplary representation (600) of the serving cell azimuth angle of the antenna (stored in the database). In an example, the database is configured to store a number of information related to the antenna. In an aspect, the number of information may include azimuth, electrical tilt, mechanical tilt, and an antenna height. In an example, the azimuth has a value of “A”, and the electrical tilt has a value of “B”. Further, the mechanical tilt has a value of “C”, and the antenna height has a value of “D”.
[0136] FIG. 6B illustrates an exemplary representation (650) of the current angle of the center angle (field measurement). In an example, the current filed measurement includes various values regarding the azimuth, deviation and a swape type. For example, the azimuth has a value of “A”, and the deviation has a value of “E”.
[0137] FIG. 7A illustrates an exemplary representation (700) of the user interface indicating current alignment of antennas prior to sector swapping. For example, FIG. 7A illustrates a number of information (stored in the database) corresponding to sector 1, sector 2, and sector 3. In an aspect, the number of information may include azimuth, electrical tilt, mechanical tilt, and an antenna height. In an example, the azimuth has a value of “X / Y / Z”, and the electrical tilt has a value of “P / Q / R” information corresponding to sector 1, sector 2, and sector 3, respectively. Further, the mechanical tilt has a value of “A / B / C”, and the antenna height has a value of “E / F / G” information corresponding to sector 1,sector 2, and sector 3, respectively.
[0138] FIG. 7B illustrates an exemplary representation (750) of the user interface, indicating the current alignment of antennas after sector swapping. In an example, FIG. 7 A illustrates a number of information (current field measurement) corresponding to sector 1, sector 2, and sector 3. In an aspect, the number of information may include azimuth, deviation, and a type of swap. In an example, the azimuth has a value of “X / Y / Z”, and the deviation has a value of “A / B / C” information corresponding to sector 1, sector 2, and sector 3, respectively.
[0139] As illustrated in FIGS. 7A and 7B, upon determination of the degree of misalignment, the antenna associated with sectors 1, 2, and 3 may be aligned by swapping the sector between them in order to achieve the proper alignment for all the antennas simultaneously.
[0140] FIG. 8 illustrates an example computer system (800) in which or with which the embodiments of the present disclosure may be implemented.
[0141] As shown in FIG. 8, the computer system (800) may include an external storage device (810), a bus (820), a main memory (830), a read-only memory (840), a mass storage device (850), a communication port(s) (860), and a processor (870). A person skilled in the art will appreciate that the computer system (800) may include more than one processor and communication ports. The processor (870) may include various modules associated with embodiments of the present disclosure. The communication port(s) (860) may be any of an RS-232 port for use with a modem-based dialup connection, a 10 / 100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. The communication ports(s) (860) may be chosen depending on a network, such as a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (800) connects.
[0142] In an embodiment, the main memory (830) may be Random Access Memory (RAM), or any other dynamic storage device commonly known in theart. The read-only memory (840) may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chip for storing static information e.g., start-up or basic input / output system (BIOS) instructions for the processor (870). The mass storage device (850) may be any current or future mass storage solution, which can be used to store information and / or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and / or Firewire interfaces).
[0143] In an embodiment, the bus (820) may communicatively couple the processor(s) (870) with the other memory, storage, and communication blocks. The bus (820) may be, e.g. a Peripheral Component Interconnect PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), Universal Serial Bus (USB), or the like, for connecting expansion cards, drives, and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor (870) to the computer system (800).
[0144] In another embodiment, operator and administrative interfaces, e.g., a display, keyboard, and cursor control device may also be coupled to the bus (820) to support direct operator interaction with the computer system (800). Other operator and administrative interfaces can be provided through network connections connected through the communication port(s) (860). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system (800) limit the scope of the present disclosure.
[0145] FIG. 9 illustrates an exemplary flowchart for a method (900) of correcting antenna misalignment in sectors, in accordance with an embodiment of the present disclosure.
[0146] The method (900) begins with receiving, by a user data collection module, a plurality of user records of a plurality of user equipments, at step (902).In an example, each user record includes a user geolocation and a plurality of quality parameters.
[0147] Next, the method involves gathering, by a processing module, the plurality of user records for a defined duration, at step (904). The records are collected over the defined duration, such as one week, to ensure a comprehensive dataset.
[0148] The method proceeds with calculating, by the processing module, at least one bearing angle for each measurement (user record) in relation to the user geolocation, at step (906). The bearing angle for each user record is based on the user geolocation in relation to a serving cell location. The bearing angle is the direction from the user's location to the serving cell, which helps in understanding the orientation and coverage area of the cell.
[0149] The processing module then implements a dynamic cone rotation of a first degree (a first determined angle) and identifies the at least three nonoverlapping cones having a maximum number of user records, at step (908). The processing module (208) is configured to adjust (move) the dynamic cone rotation by shifting the dynamic cone with a second degree. This step focuses the analysis on areas with the highest density of user measurements. In an example, the first degree is 30 degree. In an example, the second degree is 5 degree.
[0150] The method continues with determining, by the processing module, a center angle by computing measurements (user records) within the identified at least three non-overlapping cones, at step (910). In an example, the processing module determines high-density areas within the identified cones. The center angle, or center angle, represents an optimal direction for antenna alignment.
[0151] Subsequently, the method involves retrieving, by the processing module, a serving cell azimuth angle of the antenna from a database and comparing the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle, at step (912).The deviation is indicative of a degree of misalignment.
[0152] Based on the degree of misalignment, the processing module generates at least one signal for aligning the antenna based on the degree of misalignment, at step (914) such that the alignment of the antenna matches with the center angle, ensuring optimal coverage.
[0153] In an embodiment, the plurality of user records is collected from a plurality of speed testing servers, and a plurality of user devices. Speed testing servers are platforms or systems designed to measure the speed and performance of an internet connection. They typically work by uploading and downloading data to and from a remote server and measuring the time it takes for the data to transfer.
[0154] In an embodiment, method of claim 1, further includes segregating, by the processing module (208), the gathered user records based on the user geolocation associated with each user record.
[0155] In an embodiment, the center angle is calculated by identifying the high-density areas within the identified cones and computing an average of the bearing angles in the respective areas.
[0156] In an embodiment, the method of claim 1 further includes generating, by the processing module (208), a report for initiating a field audit based on the degree of misalignment.
[0157] Finally, the method includes swapping, by the processing module, when the degree of misalignment exceeds a predetermined threshold, a sector of the antenna with a sector of another antenna, at step (916). This step ensures that significant misalignments are corrected effectively, thereby improving network performance.
[0158] It is to be noted that above embodiments are explained considering RSRP as an exemplary quality parameter. However, the above embodiments canbe explained in any other quality parameters, which are within the scope of present disclosure.
[0159] The present disclosure discloses a user equipment that is configured to correct antenna misalignment in sectors. The user equipment includes a processor, and a computer readable storage medium storing programming instructions for execution by the processor. Under the programming instructions, the processor is configured to receive a plurality of user records of a plurality of user equipments. Under the programming instructions, the processor is configured to gather the plurality of user records for a defined duration and calculate at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location. Under the programming instructions, the processor is configured to implement a dynamic cone rotation of a first degree and identify at least three non-overlapping cones having a maximum number of user records. Under the programming instructions, the processor is configured to determine a center angle by computing user records within the identified at least three non-overlapping cones. Under the programming instructions, the processor is configured to retrieve a current azimuth angle of the antenna from a database and compare the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle. The deviation is an indicative of a degree of misalignment. Under the programming instructions, the processor is configured to generate at least one signal for aligning the antenna based on the degree of misalignment.
[0160] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the disclosure and not as a limitation.ADVANTAGES OF THE INVENTION
[0161] The present disclosure provides a system and a method for correcting antenna misalignment in a sector.
[0162] The present disclosure provides a system and a method that minimize call drops, maintain service continuity, and enhance the user experience during mobility.
[0163] The present disclosure provides a system and a method that minimize interference effects and improve network reliability and performance.
[0164] The present disclosure provides a system and a method that reduce unnecessary overlap or gaps in coverage and optimize the use of network resources.
[0165] The present disclosure provides a system and a method that optimize the use of infrastructure and minimize minimizing the number of required sites.
[0166] The present disclosure provides a system and a method that determine the optimal placement and configuration of cells to efficiently handle user demand.
[0167] The present disclosure provides a system and a method that maximize network capacity, improve data speeds, and support a higher number of concurrent users.
Claims
CLAIMS1. A method (900) for correcting antenna misalignment in sectors, the method comprising: receiving (902), by a user data collection module (210), a plurality of user records of a plurality of user equipments; gathering (904), by a processing module (208), the plurality of user records for a defined duration; calculating (906), by the processing module (208), at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location; implementing (908), by the processing module (208), a dynamic cone rotation of a first degree, and identifying at least three nonoverlapping cones having a maximum number of user records; determining (910), by the processing module (208), a center angle by computing user records within the identified at least three nonoverlapping cones; retrieving (912), by the processing module (208), a current azimuth angle of the antenna from a database (214) and comparing the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle, wherein the deviation is an indicative of a degree of misalignment; and generating (914), by the processing module (208), at least one signal for aligning the antenna based on the degree of misalignment.
2. The method (900) of claim 1, further comprising swapping, by the processing module (208), when the degree of misalignment exceeds apredetermined threshold, a sector of the antenna with a sector of another antenna.
3. The method (900) of claim 1, wherein the plurality of user records includes the at least one location data, quality parameters, radio frequency (RF) condition, signal strength, a serving cell identifier (cell ID), and a serving sector identifier (sector ID).
4. The method (900) of claim 1, wherein the plurality of user records is collected from a plurality of speed testing servers, and a plurality of user devices.
5. The method (900) of claim 1, wherein each user record includes a user geolocation and a plurality of quality parameters.
6. The method (900) of claim 1, further comprising segregating, by the processing module (208), the gathered user records based on the user geolocation associated with each user record.
7. The method (900) of claim 1, wherein the first degree is 30 degree.
8. The method (900) of claim 1, further comprising adjusting the dynamic cone rotation by shifting the dynamic cone with a second degree, wherein the second degree is 5 degree.
9. The method (900) of claim 1, wherein the center angle is calculated by identifying the high-density areas within the identified cones and computing an average of the bearing angles in the respective areas.
10. The method (900) of claim 1, further comprising generating, by the processing module (208), a report for initiating a field audit based on the degree of misalignment.
11. A system (108) for correcting antenna misalignment in sectors, the system comprising:a user data collection module (210) configured to receive a plurality of user records of a plurality of user equipments; a processing module (208) configured to: gather the plurality of user records for a defined duration; calculate at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location; implement a dynamic cone rotation of a first degree and identify at least three non-overlapping cones having a maximum number of user records; determine a center angle by computing user records within the identified at least three non-overlapping cones; retrieve a current azimuth angle of the antenna from a database and compare the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle, wherein the deviation is an indicative of a degree of misalignment; and generate at least one signal for aligning the antenna based on the degree of misalignment.
12. The system (108) of claim 11, wherein the processing module (208) is configured to swap a sector of the antenna with a sector of another antenna when the degree of misalignment exceeds a predetermined threshold.
13. The method (900) of claim 11, wherein the plurality of user records includes the at least one location data, quality parameters, radio frequency (RF) condition, signal strength, a serving cell identifier (cell ID), and a serving sector identifier (sector ID).
14. The system (108) of claim 11, wherein the plurality of user records is collected from a plurality of speed testing servers, and a plurality of user devices.
15. The system (108) of claim 11, wherein each user record includes a user geolocation and a plurality of quality parameters.
16. The system (108) of claim 11, the processing module (208) is configured to segregate the gathered user records based on the user geolocation associated with each user record.
17. The system (108) of claim 11, wherein the first degree is 30 degree.
18. The system (108) of claim 11, wherein the processing module (208) is configured to adjust the dynamic cone rotation by shifting the dynamic cone with a second degree, wherein the second degree is 5 degree.
19. The system (108) of claim 11, wherein the center angle is calculated by identifying the high-density areas within the identified cones and computing an average of the bearing angles in the respective areas.
20. The system (108) of claim 11, the processing module (208) is configured to generate a report based on the degree of misalignment to initiate a field audit.
21. A user equipment (104) configured to correct antenna misalignment in sectors, the user equipment (104) comprising: a processor; and a computer readable storage medium storing programming instructions for execution by the processor, the programming instructions to:receive a plurality of user records of a plurality of user equipments; gather the plurality of user records for a defined duration; calculate at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location; implement a dynamic cone rotation of a first degree, and identify at least three non-overlapping cones having a maximum number of user records; determine a center angle by computing user records within the identified at least three non-overlapping cones; retrieve a current azimuth angle of the antenna from a database and compare the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle, wherein the deviation is an indicative of a degree of misalignment; and generate at least one signal for aligning the antenna based on the degree of misalignment.
22. A computer program product comprising a non-transitory computer- readable medium comprising instructions that, when executed by one or more processing modules, cause the one or more processors to execute a method for correcting antenna misalignment in sectors, the method comprising: receiving a plurality of user records of a plurality of user equipments; gathering the plurality of user records for a defined duration;calculating at least one bearing angle for each user record based on a user geolocation in relation to a serving cell location; implementing a dynamic cone rotation of a first degree and identifying at least three non-overlapping cones having a maximum number of user records; determining a center angle by computing user records within the identified at least three non-overlapping cones; retrieving a current azimuth angle of the antenna from a database and comparing the center angle with the current azimuth angle to determine a deviation between the center angle and the current azimuth angle, wherein the deviation is an indicative of a degree of misalignment; and generating at least one signal for aligning the antenna based on the degree of misalignment.