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EP-4736508-A1 - SYSTEM AND METHOD FOR PERFORMING COVERAGE ANALYSIS IN A NETWORK

EP4736508A1EP 4736508 A1EP4736508 A1EP 4736508A1EP-4736508-A1

Abstract

The present disclosure provides system (108) and method (200) for daily coverage analysis based on crowd source data. The system includes a data collection module to collect data from users across various locations, a data analysis module to analyze the collected data to identify areas with weak or no signal coverage, and a network optimization module to optimize coverage by deploying additional infrastructure or adjusting antenna configurations based on the analyzed data. The system provides valuable insights into network performance and usage trends, helping network operators plan and prioritize network upgrades and investments more effectively. The system provides proactive identification of areas with weak or no signal coverage.

Inventors

  • BHATNAGAR, AAYUSH
  • BHATNAGAR, PRADEEP KUMAR
  • Sankaran, Sundaresh
  • AMBALIYA, Haresh B
  • SHARMA, ASHA
  • BHAKAR, Premprakash
  • MALVIYA, Gunjan
  • Tripathi, Anjali
  • GOYAL, RAHUL

Assignees

  • Jio Platforms Limited

Dates

Publication Date
20260506
Application Date
20240528

Claims (20)

  1. 1. A method for performing coverage analysis in a network (106), the method comprising: determining a grid of cells representing a geographic area covered by the network; collecting, by a data collection module (118), data associated with measurements from a plurality of data sources across a grid of cells in the network; obtaining, by a data analysis module (120), a plurality of network performance metrics from analysis of the collected data; enhancing, by a machine learning (ML) module (122), the plurality of network performance metrics by evaluating trends in the plurality of network performance metrics over a predefined period and filtering network performance metric anomalies; analyzing, by the data analysis module (122), the enhanced plurality of network performance metrics associated with the grid of cells to determine one or more cells of the grid covering portion of areas in the geographic area with a network coverage less than predefined coverage; identifying, by the data analysis module (122), a predetermined number of user equipments (UEs) in the determined one or more cells of the grid, , wherein the predefined number of user equipment (UE) in the grid is randomly selected from the users who are located within the grid of cells representing the geographic areas covered by the network; performing, by the data analysis module (122), a plurality of speed tests for defined time intervals through the identified UEs of the grid to obtain speed test results; and analyzing the speed test results by comparing the speed test results with the plurality of network performance metrics corresponding to the one or more cells of the grid and determining if the speed test results correspond to the one or more cells that lack network coverage in the one or more cells of the grid.
  2. 2. The method as claimed in claim 1, further comprising identifying a cell of the grid having inconsistent signal coverage.
  3. 3. The method as claimed in claim 1, further comprising identifying a cell of the grid based on a network coverage percentage of the cell being proximate to a network coverage percentage median of the grid of cells.
  4. 4. The method as claimed in claim 1 , further comprising identifying a cell of the grid having the network coverage percentage less than a predefined threshold, wherein the predefined threshold is a signal strength/power received, below which there is no network connectivity.
  5. 5. The method as claimed in claim 1, wherein the plurality of network performance metrics comprise a reference signal received power (RSRP), a received signal strength indicator (RSSI), a signal to interference and noise ratio (SINR), a reference signal received quality (RSRQ), a channel quality index (CQI), a physical cell identity (PCI), a block error ratio (BLER), and an uplink throughput and a downlink throughput.
  6. 6. The method as claimed in claim 1, , further comprising: determining, by the data analysis module (120), at least one network performance attribute associated with each cell of the grid of cells based on the enhanced plurality of network performance metrics, the speed test results and the predefined number of UE, wherein the network performance attribute comprises a coverage area, a coverage percentage, a network capacity, a data rate, a latency, a bandwidth, and a network energy usage.
  7. 7. The method as claimed in claim 1 further comprising: optimizing, by a network optimization module (124), the one or more serving cells by performing network optimization steps, wherein the network optimization comprises at least one of performing adjustments in antenna configurations, network switching, and infrastructure modification.
  8. 8. The method as claimed in claim 7 further comprising: generating, by the network optimization module (124), a work order to perform network optimization.
  9. 9. The method as claimed in claim 1, wherein the data sources include a plurality of network speed monitoring applications, an operational support system (OSS), a unified data repository (UDR), and a plurality of network functions.
  10. 10. The method as claimed in claim 1, wherein the network performance metric anomalies are filtered by identifying and filtering network performance metrics that are outliers in the trend.
  11. 11. The method as claimed in claim 1 further comprising: evaluating, by the data analysis module (120), network availability and quality of coverage of the network by analyzing the network performance metrics.
  12. 12. A system (108) for performing coverage analysis in a network (106) comprising: a data collection module (118) configured to data associated with measurements from a plurality of data sources across a grid of cells in the network; a data analysis module (120) configured to obtain a plurality of network performance metrics from analysis of the collected data; a machine learning (ML) module (122) configured to enhance accuracy of the plurality of network performance metrics by evaluating trends in the plurality of network performance metrics over a predefined period and filtering network performance metric anomalies; the data analysis module (120) configured to: perform a plurality of speed tests for every defined time intervals in the grid through a predefined number of user equipment (UE) of the grid to obtain speed test results, wherein the predefined number of user equipment (UE) in the grid are randomly selected from the users who are located within the grid of cells representing the geographic areas covered by the network; analyze the speed test results by correlating the speed test results with the enhanced plurality of network performance metrics; ascertain the enhanced plurality of network performance metrics by comparing the speed test results with the plurality of network performance metrics corresponding to the one or more cells of the grid and determining if the speed test results correspond to the one or more cells that lack network coverage in the one or more cells of the grid.
  13. 13. The system as claimed in claim 12, wherein the data analysis module (120) is configured to identify a cell of the grid having inconsistent signal coverage.
  14. 14. The system as claimed in claim 12, wherein the data analysis module (120) is configured to identify a cell of the grid based on a network coverage percentage of the cell being proximate to a network coverage percentage median of the grid of cells.
  15. 15. The system claimed as in claim 12, wherein the data analysis module (120) is configured to identify a cell of the grid having the network coverage percentage less than a predefined threshold, wherein the predefined threshold is a signal strength/power received below which there is no
  16. 16. The system as claimed in claim 12, wherein the plurality of network performance metrics comprise a reference signal received power (RSRP), a received signal strength indicator (RSSI), a signal to interference and noise ratio (SINR), a reference signal received quality (RSRQ), a channel quality index (CQI), a physical cell identity (PCI), a block error ratio (BLER), and an uplink throughput and a downlink throughput.
  17. 17. The system as claimed in claim 12, wherein the data analysis module (120) is configured to determine at least one network performance attribute associated with each cell of the grid of cells based on the enhanced plurality of network performance metrics, the speed test results and the predefined number of UE, and wherein the network performance attribute comprises a coverage area, a coverage percentage, a network capacity, a data rate, a latency, a bandwidth, and a network energy usage.
  18. 18. The system as claimed in claim 12, wherein a network optimization module (124) is configured to optimize the one or more serving cells by performing network optimization steps, wherein the network optimization comprises at least one of performing adjustments in antenna configurations, network switching, and infrastructure modification.
  19. 19. The system as claimed in claim 12, wherein the network optimization module (124) is configured to generate a work order to perform network optimization.
  20. 20. The system as claimed in claim 12, wherein the data sources include a plurality of network speed monitoring applications, an operational support system (OSS), a unified data repository (UDR), and a plurality of network functions.

Description

SYSTEM AND METHOD FOR PERFORMING COVERAGE ANALYSIS IN A NETWORK FIELD OF DISCLOSURE [0001] The present disclosure relates generally to a field of network optimization technology. In particular, the present disclosure pertains to a system and a method for daily coverage analysis based on crowd source data in telecom network. By collecting data from users across various locations, network operators can identify areas with weak or no signal, enabling them to optimize coverage by deploying additional infrastructure or adjusting antenna configurations. DEFINITIONS [0002] As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used to indicate otherwise. [0003] The expression ‘thematic map’ used hereinafter in the specification refers to a map that contains one or more thematic layers. [0004] These definitions are in addition to those expressed in the art. [0005] A grid represents a plurality of areas covered by a network. [0006] Noisy data points are a data set that contains extra meaningless data. Almost all data sets will contain a certain amount of unwanted noise. Noisy data can be filtered and processed into a higher quality data set. BACKGROUND OF DISCLOSURE [0007] 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. [0008] The telecommunications industry has undergone significant changes in recent years, with the rapid growth of mobile devices and the increasing demand for high-speed data services. This growth has placed significant pressure on network operators to provide reliable and consistent coverage to their customers. However, network coverage is often impacted by various factors such as topography, building materials, and interference from other sources. As a result, network operators often face challenges in providing consistent coverage across all areas. [0009] The fifth-generation (5G) network promises to revolutionize the telecommunications industry by providing faster data speeds, lower latency, and higher network capacity. However, the deployment of 5G networks has also posed significant challenges, particularly in terms of coverage analysis. One of the biggest challenges in 5G network coverage analysis is the limited coverage area. 5G networks operate on high-frequency bands, which have shorter wavelengths and limited range. As a result, 5G networks require more cell sites than 4G networks, making it more challenging to provide consistent coverage across all areas. Another challenge in 5G network coverage analysis is interference from other sources. 5G networks operate on higher frequencies, which are more susceptible to interference from buildings, trees, and other obstacles. This interference can result in inconsistent coverage and poor network performance. [0010] To provide consistent coverage across all areas, 5G networks require greater network densification. This means more cell sites, more antennas, and more infrastructure. However, network densification can be costly and time-consuming, making it challenging for network operators to deploy 5G networks at scale. Unlike 4G networks, there is currently no standardized testing methodology for 5G network coverage analysis. This makes it challenging for network operators to compare network performance across different vendors and technologies. [0011] Further, as of now, 6G and 7G networks are still in the conceptual stage, and there is limited information available about the specific challenges that these networks will face in terms of coverage analysis. However, based on the challenges faced by previous generations of networks, we can anticipate some of the problems that 6G and 7G networks may face in terms of coverage analysis. [0012] Hence, the challenges faced by 6G and 7G networks in terms of coverage analysis are likely to be similar to those faced by previous generations of networks, albeit on a larger scale. Network operators will need to proactively identify areas with weak or no signal coverage and optimize network performance to provide reliable and consistent coverage to their customers. [0013] There is, therefore, a need for a system and a method for daily coverage analysis based on crowd source data in telecom network. SUMMARY [0014] In an exemplary embodiment, a method for performing coverage analysis in a network is described. The method comprises determining a grid of cells representing a geographic area covered by a cellular network, and collecting, by a data collection module, data associated with measurements from a plurality o