System and method for mitigating or eliminating service gaps through new site recommendations - Patents.com

Abstract

The method may include determining an area of ​​a service gap and an area of ​​a candidate site; multiplying the area of ​​the candidate site by a predetermined percentage to determine a threshold; if the service gap area is greater than or equal to the threshold, dividing the service gap area by the candidate site area to determine a number of recommended sites; determining a centroid and perimeter of the service gap; determining a perimeter segment distance by dividing the perimeter of the service gap by the number of recommended sites; generating a new site shape based on the centroid of the service gap, the points on the service gap boundary, and the perimeter segment distance; and determining recommended site locations based on the centroid of the new site shape.

Description

[Technical Field]

[0001] The present disclosure relates generally to mitigating or eliminating service gaps in network coverage through the determination and recommendation of new sites. [Background technology]

[0002] Network areas may include service gaps where there is low or no network coverage. Service gaps degrade the overall quality and performance of the network and are a source of dissatisfaction for network users or customers of telecommunication carriers. Therefore, eliminating or mitigating the adverse effects caused by service gaps is important for providing reliable and high-quality network performance. Related art systems have not been able to provide an efficient solution for mitigating or eliminating service gaps. Therefore, there is a need for an improved process for mitigating and / or eliminating service gaps. Summary of the Invention [Means for solving the problem]

[0003] According to embodiments, systems and methods are provided for generating information related to site recommendations that can be used to mitigate and / or eliminate service gaps, thereby improving the reliability and quality of network performance.

[0004] One method of determining the number of recommended sites may include determining an area of ​​a service gap, determining an area of ​​a candidate site, comparing the area of ​​the service gap with the area of ​​the candidate site to determine a comparison, and determining the number of recommended sites based on the comparison.

[0005] According to additional or alternative embodiments, an information processing system can determine the number of recommended sites. The information processing system can include at least one memory configured to store computer program code. The information processing system can also include at least one processor configured to access the at least one memory and operate under the instructions of the computer program code. The computer program code can include first determination code configured to cause at least one of the at least one processor to determine an area of ​​a service gap. The computer program code can include second determination code configured to cause at least one of the at least one processor to determine at least one of an area of ​​macro sites or an area of ​​micro sites. The computer program code can include comparison code configured to cause at least one of the at least one processor to compare the area of ​​the service gap with at least one of the area of ​​macro sites or the area of ​​micro sites to determine a comparison, and the computer program code can also include third determination code configured to cause at least one of the at least one processor to determine the number of recommended sites based on the comparison.

[0006] Additional aspects will be set forth in part in the description that follows, and in part will be obvious from the description, or may be learned by practice of the illustrated embodiments of the present disclosure.

[0007] These and other aspects, features, and aspects of embodiments of the present disclosure will become apparent from the following description taken in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram of a system according to one embodiment. [Figure 2] FIG. 2 is a diagram of components of the device of FIG. 1 according to one embodiment. [Figure 3A]FIG. 3A is a diagram of an operational flow of a system for identifying service gaps according to an example embodiment. [Figure 3B] FIG. 3B is a diagram of an operational flow of a system for identifying service gaps according to an example embodiment. [Figure 4] FIG. 4 is an illustration of a process for providing new site recommendations in accordance with an illustrative embodiment. [Figure 5] FIG. 5 is a flow diagram of a process for mitigating or eliminating a service gap through new site recommendation(s) in accordance with an illustrative embodiment. [Figure 6A] FIG. 6A is a diagram illustrating segmenting service gaps to determine recommended new site locations according to an exemplary embodiment. [Figure 6B] FIG. 6B is a diagram illustrating segmenting service gaps to determine recommended new site locations according to an exemplary embodiment. [Figure 6C] FIG. 6C is a diagram illustrating segmenting service gaps to determine recommended new site locations according to an exemplary embodiment. [Figure 6D] FIG. 6D is a diagram illustrating segmenting service gaps to determine recommended new site locations according to an exemplary embodiment. [Figure 6E] FIG. 6E is a diagram illustrating segmenting service gaps to determine recommended new site locations according to an exemplary embodiment. [Figure 7] FIG. 7 is a flowchart of a method for mitigating or eliminating service gaps through new site recommendations according to an example embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] The following detailed description of the exemplary embodiments refers to the accompanying drawings, in which the same reference numbers in different drawings may identify the same or similar elements.

[0010] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of implementations. Moreover, one or more features or components of one embodiment may be incorporated into or combined with another embodiment (or one or more features of another embodiment). Additionally, in the flowcharts and descriptions of operations provided below, it should be understood that one or more operations may be omitted, one or more operations may be added, one or more operations may be performed (at least partially) concurrently, and the order of one or more operations may be rearranged.

[0011] No element, act, or instruction used herein should be construed as critical or required unless expressly stated as such. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more." Where only one item is intended, the term "a" or similar language is used. Also, as used herein, terms such as "has," "have," "having," "include," and "including" are intended to be open-ended terms. Furthermore, the phrase "based on" is intended to mean "based at least in part on," unless specifically stated otherwise. Furthermore, phrases such as "at least one of [A] and [B]" or "at least one of [A] or [B]" should be understood to include A only, B only, or both A and B.

[0012] Figure 1 is a diagram of a system according to one embodiment, including a user device 110, a server device 120, and a network 130. The user device 110 and the server device 120 may be interconnected via the network 130, which may provide a wired connection, a wireless connection, or a combination of wired and wireless connections.

[0013] According to an embodiment, the user device 110 may include a computing device (e.g., a desktop computer, a laptop computer, a tablet computer, a handheld computer, a smart speaker, a server device, etc.), a mobile phone (e.g., a smartphone, a wireless phone, etc.), a camera device, a wearable device (e.g., smart glasses or a smart watch), or a similar device.

[0014] Server device 120 may include one or more devices. For example, server device 120 may be a server device, computing device, etc. that includes hardware such as a processor and memory, software modules, and combinations thereof that perform corresponding functions.

[0015] Network 130 may include one or more wired and / or wireless networks. For example, network 130 may include a cellular network (e.g., a fifth-generation (5G) network, a long-term evolution (LTE) network, a third-generation (3G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., a public switched telephone network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, an optical fiber-based network, etc., and / or a combination of these or other types of networks.

[0016] The number and arrangement of devices and networks shown in Figure 1 are provided as an example. In practice, there may be more devices and / or networks than those shown in Figure 1, fewer devices and / or networks, different devices and / or networks than those shown in Figure 1, or differently arranged devices and / or networks. Furthermore, two or more devices shown in Figure 1 may be implemented within a single device, or a single device shown in Figure 1 may be implemented as multiple distributed devices. Additionally, or instead, a set of devices (e.g., one or more devices) may perform one or more functions that are described as being performed by another set of devices.

[0017] Figure 2 is a diagram of components of one or more devices of Figure 1 according to one embodiment. The device 200 shown in Figure 2 may correspond to a user device 110 and / or a server device 120.

[0018] As shown in FIG. 2, device 200 may include a bus 210, a processor 220, a memory 230, a storage component 240, an input component 250, an output component 260, and a communication interface 270.

[0019] Bus 210 may include components that enable communication between components of device 200. Processor 220 may be implemented in hardware, software, firmware, or a combination thereof. Processor 220 may be implemented by one or more of a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), and another type of processing component. Processor 220 may include one or more processors that can be programmed to perform corresponding functions.

[0020] Memory 230 may include random access memory (RAM), read-only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions for use by processor 220.

[0021] Storage component 240 may store information and / or software related to the operation and use of device 200. For example, storage component 240 may include a hard disk (e.g., a magnetic disk, optical disk, magneto-optical disk, and / or solid-state disk), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium along with a corresponding drive.

[0022] Input components 250 may include components that enable device 200 to receive information, such as through user input (e.g., a touchscreen display, a keyboard, a keypad, a mouse, buttons, switches, and / or a microphone). Input components 250 may also include sensors for detecting information (e.g., a global positioning system (GPS) component, an accelerometer, a gyroscope, and / or an actuator).

[0023] Output components 260 may include components that provide output information from device 200 (eg, a display, a speaker, and / or one or more light emitting diodes (LEDs)).

[0024] Communications interface 270 may include transceiver-like components (e.g., a transceiver and / or a separate receiver and transmitter) that enable device 200 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. Communications interface 270 may enable device 200 to receive information from and / or provide information to another device. For example, communications interface 270 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, etc.

[0025] Device 200 may perform one or more processes described herein. Device 200 may perform operations based on processor 220 executing software instructions stored in a non-transitory computer-readable medium, such as memory 230 and / or storage component 240. A computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices.

[0026] Software instructions may be loaded into memory 230 and / or storage component 240 via communications interface 270, from another computer-readable medium, or from another device. When executed, the software instructions stored in memory 230 and / or storage component 240 may cause processor 220 to perform one or more processes described herein.

[0027] Additionally, or alternatively, hard-wired circuitry may be used in place of or in combination with software instructions to implement one or more processes described herein. Thus, the embodiments described herein are not limited to any specific combination of hardware circuitry and software.

[0028] As disclosed herein, systems, methods, and devices are provided that are configured to mitigate or eliminate service gaps in telecommunications networks by recommending new sites. Specifically, the methods, systems, and devices provide a method for easily recommending one or more sites to address a particular service gap and for additionally determining recommended locations for the one or more recommended sites.

[0029] "Service gap" and "service gap polygon" may be used interchangeably herein and may refer to a polygon generated on a coverage layer of a smart network, which polygon indicates one or more polygonal regions of poor coverage zones within the network. Systems, methods, and devices can periodically generate service gap polygons for each band, provide optimization suggestions for improving coverage, and track improvements in service gaps after the optimization suggestions are implemented. In some embodiments, the optimization suggestions may include recommending one or more new sites and further recommending new site locations for each recommended new site.

[0030] First, a service gap can be identified. The identified service gap may be referred to as a service gap of interest. One or more service gaps can be identified by generating a service gap polygon for each band. The generation of service gaps may occur repeatedly, for example, periodically. When identifying service gaps, the system may use various inputs. One input may include an integrated coverage layer. The integrated coverage layer may be a smart layer generated by overlaying planned forecast data with live test data and collecting samples from users. There may also be an updated integrated coverage layer for each band. Another input may include a site database. The site database may store information for all sites in the network, including latitude, longitude, orientation, band details, on-air status, on-air date and time, base station (e.g., eNB) identifier (ID), Evolved Universal Terrestrial Access Network (E-UTRAN) Cell Global Identifier (ECGI), antenna height, electrical tilt, mechanical tilt, transmit power, reference signal received power (RSRP), etc. The site database may include existing sites, sites under consideration for construction, and recommended sites, so the types of sites included in the site database are not particularly limited.

[0031] Other inputs may include clutter data including information about the morphology of the area (i.e., user or access density), boundaries which may include radio frequency (RF) cluster and region boundaries, best server plots predicting site coverage calculated during the planning stage (e.g., generated from a predictive tool for on-air sites), geolocation data which may be passively collected data collected using driving test tools such as net speed and used over a predetermined period of time (e.g., 7 days), cell-wise prevention measurement (PM) counter key performance indicators (KPIs) such as call drop rate, radio resource control (RRC) attempts, RRC re-establishment attempts, average control quality index (CQI), etc.

[0032] 3A and 3B are operational flow diagrams of a system for identifying service gaps according to an example embodiment. The system may include a NiFi component 302, a Spark component 304, an HBase component 306, a Hadoop Distributed File System (HDFS) component 308, a MySQL® component 310, a microservices component 312, and a representational state transfer (REST) ​​service component 314.

[0033] The NiFi component 302 includes a software design based on a flow-based programming model and can provide features notably including the ability to operate in a cluster. The NiFi component 302 can be used to ingest streaming data from third-party applications, such as boomer cell identification data from various Enhanced Messaging Service (EMS) applications.

[0034] The Spark component 304 may include a parallel processing framework for running large-scale data analysis applications across clustered computers. The Spark component 304 can handle both batch and real-time analytical and data processing workloads.

[0035] The HBase component 306 may include a column-oriented, non-relational database management system that runs on top of HDFS and can provide a fault-tolerant way to store sparse data sets.

[0036] The HDFS component 308 may be configured to store all raw data used by the system. All batch data sources may be initially stored in the HDFS component 308 and then processed using the Spark component 304. The HBase component 306 may also use the HDFS component 308 for its data storage infrastructure.

[0037] The MySQL component 310 can be configured to store processed data within the framework. The MySQL component 310 can be utilized for application programming interface (API) lookups and to supply any real-time user interface (UI) requirements. Aggregated and correlated data may also be stored in the MySQL component 310.

[0038] Microservice components 312 can be configured as an architectural style for building applications as a collection of highly maintainable and testable services that are loosely coupled, independently deployable, and may be organized around business capabilities.

[0039] The REST service component 314 may be a service that conforms to the Representational State Transfer (REST) ​​architecture.

[0040] At operation 350, the system triggers the spark component 304 via the NiFi component 302 to begin the process of identifying service gaps. At operation 352, the spark component 304 retrieves data, such as the input described above, from the HBase component 306. At operation 354, the spark component 304 retrieves geographic data and site data from the MySQL component 310. At operation 356, the microservices component 312 sends a request to the HBase component 306 to retrieve polygon data. At operation 358, the HBase component 306 sends the requested polygon data to the microservices component 312. At operation 360, the microservices component 312 sends the retrieved polygon data to the REST services component 314 for visualization of the polygon data. At operation 362, the spark component 304 sends master polygon data and statistical data generated from the retrieved data (e.g., input) to the MySQL component 310. At operation 364, the spark component 304 sends a report generated based on the retrieved data to the HDFS component 308 for storage. At operation 366, the microservices component 312 fetches the report from the HDFS component 308. At operation 368, the microservices component 312 sends the report to the REST services component 314 for visualization (e.g., generating a map showing service gaps or overlaying the service gaps on an existing map). At operation 370, the spark component 304 runs a process to identify service gaps (e.g., generate updated service gaps) at predetermined time intervals (e.g., daily, weekly, etc.) and sends the data to the HBase component 306.

[0041] 4 is a diagram of an overall process for mitigating or eliminating service gaps in a telecommunications network by recommending new sites, according to some embodiments. The process can include subprocesses such as an input acquisition subprocess 402, a new site recommendation subprocess 404, and a presentation subprocess 406.

[0042] At operation 410, the system reads geographic data. At operation 412, the system reads morphological data. At operation 414, the system reads integrated coverage layer data. At operation 416, the system generates polygons, for example, by (1) combining the integrated coverage layer data with geographic data, (2) combining the morphological data with geographic data, and / or (3) performing grouping based on geography. One or more generated polygons can represent one or more service gaps. In some embodiments, service gaps may be identified and represented using shapes other than polygons. For example, the system can generate any two-dimensional or three-dimensional shape to represent service gaps in the network. The service gaps, which may be in the form of polygons or any other shape, are then stored.

[0043] In operation 418, the system identifies candidate cells, for example, by (1) reading the generated polygon, (2) reading a graphical UI (GUI) generated based on the generated report, (3) reading on-air sites, (4) reading the combined parquet from HDFS, (5) reading BSP details, and / or (6) identifying BSP and geolocation sample cells. After the system identifies candidate cells, the system can save or store the candidate cells. Reading by the system can involve, for example, obtaining, analyzing, or performing operations on data. In some embodiments, candidate cells are first identified, and then a best server plot (BSP) for the candidate cells is generated, calculated, or determined.

[0044] In some embodiments, the best server plot (BSP) of the identified cell is compared to the service gap of interest, and this comparison can be used to determine whether to mitigate or eliminate the service gap via a new site recommendation or another process for mitigating or eliminating the service gap, such as tilt recommendation. For example, the amount of overlap between the BSP of the identified cell and the service gap area can be calculated or determined. If the amount of overlap is 50% or greater, the tilt recommendation process can be employed. If the amount of overlap is less than 50%, the new site recommendation process can be employed. Also, although a BSP comparison of the candidate cell against the area of ​​the service gap of interest is used, any criteria can be used to determine which and / or how many recommendation methods to employ. In some embodiments, both the new site recommendation process and the tilt recommendation process can be employed, either sequentially or simultaneously. While 50% is used as one exemplary threshold, any percentage threshold or other method of determining which service gap mitigation / elimination process to use can be used.

[0045] In operation 420, the system performs a process for whether to recommend one or more new sites to address the service gap of interest. In particular, the new site recommendation process may include (1) determining whether to recommend one or more new sites, (2) determining the number of new sites to recommend, and / or (3) determining recommended geographic locations of the one or more recommended new sites. In accordance with an example embodiment, new site recommendation is further described below with reference to Figures 5, 6A-6E, and 7.

[0046] At operation 422, the system generates one or more reports based on the recommendations, e.g., aimed at mitigating or eliminating one or more service gaps. At operation 424, the system displays the results. In some embodiments, the displayed results are for the reports generated regarding recommendations for mitigating or eliminating one or more service gaps.

[0047] Figure 5 is a flow diagram of a process for recommending cell sites. The process of Figure 5 consists of a series of operations beginning with operation 504, in which the area (area) of the service gap (i.e., the "service gap area") is calculated or determined. In one embodiment, the service gap of interest is a two-dimensional polygon with known edges and side lengths; therefore, geometric calculations can be used to determine the area of ​​the service gap of interest. However, as noted above, the shape of the service gap is not limited to a polygon or a two-dimensional shape. Thus, any shape, area, or volume of the service gap can be calculated using currently known or later-developed techniques. The process then proceeds to operation 506.

[0048] In operation 506, the area (area) of the potential new site is calculated or determined. The potential new site area may refer to the area of ​​wireless coverage that the potential new site can provide. Equation (1) is an example equation that may be used to calculate the potential new site area (area).

[0049] (1) Potential new site area = 3.14 × (site radius)^2

[0050] The site radius may refer to the maximum coverage distance measured from a potential new site. If the distance between the wireless device and the potential new site is greater than the site radius, the wireless device may not be able to maintain a stable connection with the potential new site. In contrast, if the distance between the wireless device and the potential new site is less than the site radius, the wireless device may be able to maintain a stable connection with the potential new site. In some embodiments, the potential new site area is a circular area around the potential new site, although the shape of the potential site area is not necessarily limited thereto. Therefore, other equations besides equation (1) above may be used to determine the potential new site area.

[0051] In some embodiments, a potential new site may be either a macro site or a micro site. In some embodiments, two potential new site areas are calculated: a first potential new site area associated with the potential new macro site and a second potential new site area associated with the potential new micro site. The macro site radius may be equal to 500 meters, and the micro site radius may be equal to 150 meters. Alternative macro site and micro site radii may be used, and thus the macro site and macro site radii are not limited. However, the macro site radius is generally longer than the micro site radius. Similarly, the area of ​​the potential macro site is generally larger than the area of ​​the potential micro site. The length of the new site radius and the associated size of the corresponding potential new site area may depend on the hardware configuration used by the potential new site. After one or more potential new site areas are determined, the process proceeds to operation 508.

[0052] In operation 508, the service gap area is compared to the potential new site area to determine whether to recommend any new sites. In some embodiments, the service gap area is compared to a predetermined percentage of the potential new site area, referred to as the threshold area. The threshold area may be the potential new site area multiplied by the predetermined percentage, as shown in equation (2) below.

[0053] (2) Threshold area = predetermined percentage × potential new site area

[0054] In one embodiment, the predetermined percentage may be 75%, and therefore the predetermined percentage in Equation 2 may be 75 divided by 100, i.e., (.75). Although 75% is one exemplary predetermined percentage, the predetermined percentage used to calculate the threshold region is not limited and may be any predetermined percentage.

[0055] In some embodiments, if the service gap area is determined to be less than the threshold area, it is determined that the service gap is too small to warrant the recommendation of a new site, and the process of new site recommendation proceeds to operation 510. At operation 510, it is determined that the number of new sites to recommend is zero, and the process ends. In contrast, if the service gap area is determined to be greater than or equal to the threshold area, it may be determined that the service gap is large enough to warrant the recommendation of at least one new site, and the process of new site recommendation continues to operation 512. Exemplary logic for determining whether to stop at operation 510 or proceed to operation 512 may be shown in equation (3) below.

[0056]

number

[0057] In some embodiments, there may be two threshold areas: a macro threshold area and a micro threshold area. The macro threshold area may be calculated by inputting the area of ​​potential new macro sites into the potential new site area variable in equation (2). This macro threshold area may then be compared to the service gap area using equation (3) above. If the service gap area is less than the macro threshold area, a micro threshold area may be calculated. The micro threshold area may be calculated by inputting the area of ​​potential new micro sites into the potential new site area variable in equation (2). The micro threshold area may then be compared to the service gap area using equation (3) above. If the service gap area is also less than the micro threshold area, the process proceeds to operation 510, where it is determined that the number of recommended new sites is zero, and the process ends.

[0058] In some embodiments, if the service gap area is smaller than the macro threshold area but larger than the micro threshold area, the process continues to operation 512, but only micro sites may be recommended. In other embodiments, if the service gap is larger than the macro threshold area, the process continues to operation 512, and either macro sites alone, micro sites alone, or a combination of macro and micro sites may be recommended, depending on the most efficient way to cover the particular geometry or shape of the service gap of interest.

[0059] Thus, even though equation (3) indicates "stop" when the service gap area is smaller than the threshold area, in some embodiments the process proceeds to recalculate equation (3) using one or more smaller threshold areas corresponding to progressively smaller potential new site areas associated with potential new sites having shorter new site radii. Although the above-described embodiments use one macro site and one micro site, operation 508 may be performed with any number of macro sites (e.g., multiple macro sites with different macro site radii) and / or any number of micro sites (e.g., multiple micro sites with different micro site radii).

[0060] As discussed above, if the service gap area is greater than or equal to the threshold area, the process proceeds to operation 512, where a non-zero positive number of new sites may be recommended. In some embodiments, the potential number of recommended new sites may be calculated or determined using either or both of equations (4) or (5) below.

[0061] (4) NumNewSites HQ = [service gap area ÷ potential new site area]

[0062] (5) NumNewSites CE = [service gap area ÷ potential new site area]

[0063] The variable "NumNewSites" in equation (4)HQ " indicates the number of recommended new sites for a high-quality network performance configuration. NumNewSites HQ To calculate , the service gap area is divided by the potential new site area, and the result of this division is input into a "ceiling function," which rounds the result up to the nearest integer. Thus, equation (4) includes the division of the service gap area and the potential new site area within parentheses to indicate the ceiling.

[0064] The variable "NumNewSites" in equation (5) CE " indicates the recommended number of new sites for cost-effective network configuration. NumNewSites CE To calculate NumNewSites, the service gap area is divided by the potential new site area, and the result of this division is then input into a "floor function" that rounds the result down to the nearest integer. Thus, equation (5) includes the division of the service gap area and the potential new site area within the parentheses that indicate the floor. NumNewSites CE can provide a number of new sites that are more cost-effective but may cover fewer service gap areas.

[0065] Conversely, NumNewSites HQ may be more costly but may provide a number of new sites that can cover more service gap areas and thereby provide more service gap mitigation or elimination. For example, NumNewSites CE or NumNewSites HQ The specific number of recommended new sites for either may depend on the specific needs of the service gap, budget, and / or geometric configuration. In some embodiments, if the fractional portion of the division result is equal to or greater than the fractional portion of some predetermined threshold (e.g., .5 or .7), the division result is rounded up to the nearest integer, and if the fractional portion of the division result is equal to or less than the fractional portion of the predetermined threshold, the division result is rounded down.

[0066] Operation 512 may include determining the number of new macro sites, determining the number of new micro sites, or both. The number of new macro sites may be determined by multiplying NumNewSites by the number of new micro sites using the potential new macro site area described above. HQ and NumNewSites CE Similarly, the number of new microsites can be determined by calculating either or both of NumNewSites HQ and NumNewSites CE The system may determine some or all of: (1) a recommended number of new macro sites for configuring high-quality network performance, (2) a recommended number of new macro sites for configuring a cost-effective network, (3) a recommended number of new micro sites for configuring high-quality network performance, and (4) a recommended number of new micro sites for configuring a cost-effective network.

[0067] As mentioned above, the number of recommended sites can be configured as a combination of the number of recommended macro sites and the number of recommended micro sites. In this system, the number of recommended macro sites and the number of recommended micro sites can be calculated simultaneously or sequentially using the following equations (6) and (7).

[0068] (6) NumNewSites MAC = Service gap area ÷ Macro site area

[0069] (7) NumNewSites MIC = Service gap area ÷ Microsite area

[0070] Specifically, we use Equation (6) to calculate the number of macro-recommended macro sites, NumNewSites MAC We can calculate the number of recommended microsites, NumNewSites, using equation (7). MIC can be calculated.

[0071] In some embodiments, equations (6) and / or (7) may include a ceiling function that rounds the final result up to the nearest integer, e.g., when configuring a high quality network performance is desired or required. In some embodiments, equations (6) and / or (7) may include a floor function that rounds the result down to the nearest integer, e.g., when configuring a cost-efficient network is desired or required.

[0072] Although equations (6) and (7) can be used to calculate the number of recommended macrosites and the number of recommended microsites, other equations or methods can be used to determine the number of macrosites and microsites to be associated and recommended.

[0073] In some embodiments, an artificial intelligence or machine learning (AI / ML) algorithm may be used to determine the optimal number of macro sites and micro sites to use in combination. The AI / ML algorithm may be trained on one or more datasets including various service gap shapes, sizes, and / or other characteristics. Each service gap entry in the training dataset may be associated with a corresponding optimal number of recommended macro sites and a recommended number of micro sites. After being trained on the dataset, the AI / ML algorithm may accept data related to the service gap of interest as input, and the AI / ML algorithm may respond by determining the number of recommended macro sites and / or micro sites based on the input data for the service gap of interest. In some embodiments, such an AI / ML algorithm may also be used to determine the optimal macro site and / or micro site area / radius, hardware specifications, configuration data, etc., and may result in optimal macro site and / or micro site recommendations.

[0074] After determining the number of new sites, the process may proceed to operation 514. At operation 514, the perimeter of the service gap is calculated or determined. The perimeter of the service gap may be the length of the boundary of the shape of the service gap. In some embodiments, the service gap is a generated polygon with known edge points and known side lengths. Thus, the perimeter of the service gap polygon may be the sum of multiple known side lengths of the service gap polygon. In other embodiments, the service gap may have an irregular shape, for example, with either rounded or non-linear boundaries. In some embodiments, the perimeter of a non-polygonal service gap may be determined by defining multiple points on the boundary of the non-polygonal service gap, connecting the points with lines that approximate the boundary of the non-polygonal service gap, and adding the lengths of these lines to approximate the perimeter of the non-polygonal service gap. The accuracy of the calculation of the perimeter of a non-polygonal service gap can be increased by increasing the number of points defined on the boundary of the non-polygonal service gap.

[0075] The process then proceeds to operation 516, where the distance of the perimeter segment is calculated or determined. The distance of the perimeter segment may be the length of a segment or section along the boundary of the service gap. This section may be used as one side of a new site polygon or shape, which is further described below with respect to Figures 6A-6E. In some embodiments, the distance of the perimeter segment may be calculated or determined using the following equation (8):

[0076] (8) Segment distance = perimeter of service gap ÷ number of sites

[0077] In equation (8), the distance of the perimeter segment is equal to the perimeter of the service gap divided by the number of recommended sites. The number of recommended sites used in equation (8) may be any number of recommended sites described above. In some embodiments, the system may determine multiple perimeter segment distances corresponding to different configurations of new sites, such as a configuration of recommended new sites with only macro sites, a configuration of recommended new sites with only micro sites, a configuration of recommended new sites with a combination of macro sites and micro sites, a high-quality configuration, a cost-effective configuration, etc.

[0078] The process may proceed to operation 518, where the centroid of the service gap is determined. In one embodiment, the centroid of the service gap is determined using a geometric decomposition method. The process may then proceed to operation 520, where a new site polygon is generated based on the centroid of the service gap and the perimeter segment distance. This process of generating new site polygons is further described below with respect to Figures 6A-6E. The process may proceed to operation 522, where the centroid of the new site polygon is determined based on the generated new site shape / polygon. Finally, the process ends at operation 524, where a recommended new site location is determined for each recommended new site, where the new site location is based on the centroid of the new site polygon.

[0079] 6A-6E illustrate an exemplary service gap 600 that is segmented into one or more new site polygons in the process of determining new site locations for recommended sites. FIG. 6A illustrates the service gap 600, which in this embodiment is an asymmetric polygon with eight sides. The techniques described herein can be used to calculate the area and perimeter of the service gap 600. For example, the area can be calculated by segmenting the service gap into smaller polygons, calculating the area of ​​each of the smaller polygons, and adding the smaller polygon areas together to obtain the area of ​​the service gap. The perimeter can also be calculated by adding together the lengths of the eight sides. The centroid 602 of the service gap polygon can be calculated, for example, using geometric decomposition. FIG. 6B illustrates the service gap 600 including the centroid 602.

[0080] An arbitrary point A on the service gap boundary can be defined. FIG. 6C shows one such arbitrary point A according to an exemplary embodiment. The arbitrary point A may be a starting point for determining the boundary of a new site polygon, as described further below. In some embodiments, point A may be specifically selected for one or more specific reasons and thus not be completely “arbitrary.” For example, a computer program or application can be used to find an optimal point to select as point A on the boundary of the service gap, and artificial intelligence and / or machine learning algorithms can be used to determine such an optimal point. For example, the program can run a process that tries a variety of different starting points and uses some criteria to determine which of the various different starting points produces the best results. The output to such a program can be the starting point that produced the best results, and this starting point can be used as starting point A.

[0081] After the number of recommended new sites, the perimeter of the service gap, and the centroid of the service gap are calculated or determined, for example, using the techniques described above, the system can determine a perimeter segment distance. The perimeter segment distance can be used to generate a perimeter segment along the boundary of the service gap, and this perimeter segment can be used as a segment boundary for one of the new site polygons. As mentioned above, the perimeter segment distance can be calculated or determined, for example, using equation (8) above.

[0082] In some embodiments, the system uses the calculated perimeter segment distance to define additional points along the service gap boundary. For example, the system may use point A as a starting point and move a distance equal to the perimeter segment distance in one direction along the boundary of the service gap polygon. After moving a distance equal to the perimeter segment distance in one direction along the boundary of the service gap polygon from point A, the system may define an additional point at that location on the service gap polygon boundary. The system may repeat this process of defining points along the service gap polygon boundary, with each defined point separated from the next defined point by a distance equal to the perimeter segment distance along the service gap polygon boundary. In the embodiment shown in FIG. 6D , because the number of recommended cell sites in this exemplary embodiment is five, four additional points (i.e., points B, C, D, and E) in addition to starting point A are defined along the perimeter of service gap polygon 600. The distance between each adjacent point along the service gap boundary is the same and equal to the perimeter segment distance.

[0083] Outer section 604 is a section defined by the service gap boundary between defined points A and B. Outer section 604 becomes one section of the boundary of new site polygon 606. The remaining boundary of new site polygon 606 consists of two lines: line 608 from point A to the service gap centroid, and line 610 from point B to the service gap centroid. FIG. 6D shows outer section 604 and lines 608 and 610 forming the boundary of new site polygon 606. Similarly, additional new site polygons can be created by connecting lines between the service gap centroid and each of lines C, D, and E. The boundary of each new site polygon includes a perimeter segment between adjacent boundary points and two lines connecting each of the adjacent boundary points to the service gap centroid. If the service gaps are polygonal, the new site polygons will also be polygonal, but if the service gaps have non-polygonal shapes, the "new site polygons" will not be polygonal. In such embodiments, the "new site polygons" may be referred to as "new site shapes" that have non-polygonal shapes on the perimeter of each new site shape.

[0084] After the new site polygons (or new site shapes) are generated, a centroid is generated for each new site polygon, for example, using geometric decomposition. Figure 6E shows the centroids for each of the new site polygons. For example, new site polygon 606 has centroid 612. The centroids of each of the new site polygons can be used to determine the recommended site locations of the recommended sites. In some embodiments, the centroids of the new site polygons are the locations of the recommended new sites.

[0085] In some embodiments, the centroid of the new site polygon must be changed or "corrected" to reflect the actual location on the map of the service gap of interest. For example, the centroid location of the new site polygon can be used to generate coordinates, e.g., latitude and longitude coordinates, of a recommended new site location, so that a new site built at such a recommended site location can mitigate or eliminate the service gap of interest. The coordinates may be GPS coordinates, or GLONASS, Beidou, Galileo, SBAS, quasi-zenith coordinates, or NavIC coordinates, or any other navigation system coordinates now known or later developed. While navigation system coordinates are one exemplary way of expressing the geographic location of a recommended new site, the method of expressing the geographic location of the recommended site is not limited thereto and may include any method of expressing a geographic location now known or later developed.

[0086] As described above, the result of the processes herein may be a recommendation of an optimal site location; however, for some reason, the recommended site location may be difficult or impossible to realize. For example, there may be existing infrastructure, undesirable terrain, or other factors that make it difficult, cost-infeasible, or expensive to build a new site at the recommended site location. To address this obstacle, the system may further include additional or alternative corrections to the recommended site location to move the recommended site location a distance from the initial recommended site location to a feasible site location. Thus, the system may include inputs or logic for determining instances of difficult, impossible, or undesirable locations or areas, and may use such inputs / logic to modify or correct the recommended site location to an adjusted recommended site location.

[0087] The above process of dividing the service gap area into a number of new site polygons and determining recommended site locations based on the centroids of the new site polygons can be repeated for a number of different configurations, e.g., a configuration in which only macro sites are recommended, a configuration in which only micro sites are recommended, a configuration in which a combination of macro sites and micro sites is recommended, a high-quality configuration, a cost-effective configuration, etc.

[0088] In embodiments where a combination of macro and micro sites are jointly recommended, the system may utilize two perimeter segment distances: one for the new site polygons corresponding to the recommended macro sites and one for the new site polygons corresponding to the recommended micro sites. Thus, there may be an additional step of adjusting the generated points along the perimeter of the service gap so that the new site polygons corresponding to the recommended macro sites are larger than the new site polygons corresponding to the recommended micro sites. In one embodiment, the ratio of the macro perimeter segment distance to the micro perimeter segment distance may be used for such adjustment. This ratio may be equal to some ratio that may be based on the macro radius and the micro radius, or the macro site area and the micro site area.

[0089] The results of one or more of these configurations producing recommended sites and variations of their locations can be generated into a report displayed in the GUI, which network providers can use to determine which configuration best achieves their business objectives.

[0090] Furthermore, this process can be repeated for multiple different service gaps in the network, and thus the techniques herein provide an efficient and cost-effective method of generating new site recommendations along with locations for such recommended sites. Such recommendations enable service providers to quickly and cost-effectively address service gaps in their networks, e.g., mitigate or eliminate the service gaps, and thus provide higher quality service to their customers.

[0091] 7 is a flowchart of a method for mitigating or eliminating service gaps through new site recommendations, according to an example embodiment. In operation 702, a service gap area and a candidate site area are determined. In operation 704, the candidate site area is multiplied by a predetermined percentage to determine a threshold value. In operation 706, if the service gap area is equal to or greater than the threshold value, the service gap area is divided by the candidate site area to determine the number of recommended sites. In operation 708, a centroid and perimeter of the service gap are determined. In operation 710, a perimeter segment distance is determined by dividing the perimeter of the service gap by the number of recommended sites. In operation 712, a new site shape is generated based on the centroid of the service gap, points on the service gap boundary, and the perimeter segment distance, and in operation 714, the locations of the recommended sites are determined based on the centroid of the new site shape.

[0092] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations.

[0093] Some embodiments may relate to systems, methods, and / or computer-readable media at any possible level of technical detail. The computer-readable media may include a computer-readable non-transitory storage medium (or media) having computer-readable program instructions for causing a processor to perform operations.

[0094] A computer-readable storage medium may be a tangible device capable of retaining and storing instructions for use by an instruction execution device. A computer-readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD), memory stick, floppy disk, mechanically encoded devices such as punch cards or ridge-in-groove structures with instructions recorded thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, should not be construed as a transitory signal per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses passing through a fiber optic cable), or electrical signals transmitted through wires.

[0095] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to each computing / processing device or to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers, or combinations thereof. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device.

[0096] The computer-readable program code / instructions for carrying out operations can be either source code or object-oriented programming languages ​​written in any combination of one or more programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or object code such as Smalltalk, C++, and procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions can execute entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA) can execute computer-readable program instructions by utilizing state information in the computer-readable program instructions to personalize the electronic circuitry to perform an aspect or operation.

[0097] These computer-readable program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, whereby the instructions, executing via the processor of the computer or other programmable data processing apparatus, produce means for implementing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams. These computer-readable program instructions may also be stored on a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that a computer-readable storage medium having instructions stored therein includes an article of manufacture containing instructions that implement aspects of the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0098] The computer-readable program instructions may also be loaded into a computer, other programmable data processing apparatus, or other device to cause the computer, other programmable apparatus, or other device to perform a series of operational steps to produce a computer-implemented process, such that the instructions executing on the computer, other programmable apparatus, or other device implement the function / act specified in one or more blocks of the flowcharts and / or block diagrams.

[0099] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer-readable media according to various embodiments. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing the specified logical function(s). The methods, computer systems, and computer-readable media may include additional, fewer, different, or differently arranged blocks compared to those shown in the figures. In some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the figures. For example, two blocks shown in succession may actually be executed concurrently or substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart diagrams, and combinations of blocks in the block diagrams and / or flowchart diagrams, may be implemented by a dedicated hardware-based system that performs the specified functions or operations or executes a combination of dedicated hardware and computer instructions.

[0100] It will be apparent that the systems and / or methods described herein may be implemented in various forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not intended to limit the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code, and it will be understood that software and hardware can be designed to implement the systems and / or methods based on the description herein.

[0101] The descriptions of various aspects and embodiments are presented for illustrative purposes and are not intended to be exhaustive or limited to the disclosed embodiments. While combinations of features are recited in the claims and / or disclosed herein, these combinations are not intended to limit the disclosure of possible implementations. Indeed, many of these features may be combined in ways not specifically recited in the claims and / or disclosed in the specification. While each dependent claim listed below may depend directly on only one claim, a disclosure of possible implementations includes each dependent claim in combination with all other claims in the claim set. Many modifications and variations will be apparent to those skilled in the art without departing from the scope of the described embodiments. The terminology used herein was selected to best explain the principles of the embodiments, practical applications, or technical improvements to technology found in the marketplace, or to enable those skilled in the art to understand the embodiments disclosed herein.

Claims

1. 1. A method for determining a number of recommended sites, the method comprising: determining areas of service gaps; determining the area of ​​the candidate site; determining a comparison between the area of ​​the service gap and the area of ​​the candidate site; and determining a number of recommended sites based on the comparison; method.

2. Comparing the area of ​​the service gap with the area of ​​the candidate site includes: determining a threshold by multiplying the area of ​​the candidate site by a predetermined percentage; and comparing the area of ​​the service gap to a threshold value. The method of claim 1.

3. determining the number of recommended sites, If the area of ​​the service gap is less than the threshold, determining that the number of recommended sites is zero. The method of claim 2.

4. determining the number of recommended sites, if the area of ​​the service gap is greater than or equal to the threshold, determining that the number of recommended sites is a non-zero positive integer; The method of claim 2.

5. determining the number of recommended sites, dividing the area of ​​the service gap by the area of ​​the candidate site; The method of claim 1.

6. determining a centroid of the service gap and a perimeter of the service gap; determining the distance of a perimeter segment of the service gap; determining a portion of the perimeter of the service gap corresponding to the perimeter segment; and determining a shape of the recommended site based on the centroid of the service gap and the portion of the perimeter of the service gap that corresponds to the perimeter segment; The method of claim 1.

7. determining the distance of the circumferential segment of the service gap; dividing the perimeter of the service gap by the number of recommended sites. The method of claim 6.

8. determining a centroid of the shape of the recommended site; and determining a recommended site location based on the centroid of the shape of the recommended site; The method of claim 6.

9. the candidate site is either a macrosite or a microsite; the number of recommended sites is either the number of recommended macrosites or the number of recommended microsites; The method of claim 1.

10. the number of recommended sites is a combination of the number of recommended macrosites and the number of recommended microsites; The method of claim 1.

11. An information processing system for determining a number of recommended sites, at least one memory configured to store computer program code; and at least one processor configured to access said at least one memory and to operate as instructed by said computer program code; The computer program code: first determination code configured to cause at least one of the at least one processor to determine an area of ​​a service gap; second determination code configured to cause at least one of the at least one processor to determine at least one of an area of ​​a macrosite or an area of ​​a microsite; comparison code configured to cause at least one of the at least one processor to compare the area of ​​the service gap with at least one of the area of ​​the macro site or the area of ​​the micro site to determine a comparison; and third determination code configured to cause at least one of the at least one processor to determine a number of recommended sites based on the comparison; Information processing system.

12. The comparison code instructs at least one of the at least one processor to: multiplying at least one of the area of ​​the macrosite or the area of ​​the microsite by a predetermined percentage to determine a threshold; and further configured to compare the area of ​​the service gap to the threshold. The information processing system according to claim 11.

13. the third decision code is further configured to cause at least one of the at least one processor to determine that the number of recommended sites is zero if the area of ​​the service gap is less than the threshold. The information processing system according to claim 12.

14. the third decision code is further configured to, if the area of ​​the service gap is greater than or equal to the threshold, cause at least one of the at least one processor to determine that the number of recommended sites is a non-zero positive integer. The information processing system according to claim 12.

15. further comprising division code configured to cause at least one of the at least one processor to divide the area of ​​the service gap by at least one of the area of ​​the macro site or the area of ​​the micro site. The information processing system according to claim 11.

16. fourth determination code configured to cause at least one of the at least one processor to determine a centroid of the service gap and a perimeter of the service gap; fifth decision code configured to cause at least one of the at least one processor to determine a distance of a perimeter segment of the service gap; sixth determination code configured to cause at least one of the at least one processor to determine a perimeter portion of the service gap corresponding to the perimeter segment; and and seventh determination code configured to cause at least one of the at least one processor to determine a shape of the recommended sites based on the centroid of the service gap and the portion of the perimeter of the service gap that corresponds to the perimeter segment. The information processing system according to claim 11.

17. the fifth decision code is further configured to cause at least one of the at least one processor to divide the perimeter of the service gap by the number of recommended sites.

17. The information processing system according to claim 16.

18. an eighth determination code configured to cause at least one of the at least one processor to determine a centroid of the shape of the recommended site; and a ninth determination code configured to cause at least one of the at least one processor to determine a recommended site location based on the centroid of the shape of the recommended site.

17. The information processing system according to claim 16.

19. the number of recommended sites is either the number of recommended macrosites or the number of recommended microsites; The information processing system according to claim 11.

20. The information processing system according to claim 1 , wherein the number of recommended sites includes a combination of a number of recommended macrosites and a number of recommended microsites.

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