US-20260128965-A1 - SYSTEMS AND METHODS FOR ESTIMATING WIRELESS NETWORK OUTAGE IMPACT OF A NETWORK ASSET

Abstract

A device may identify assets associated with potential network outages, may receive best serving plot information for an asset of the assets, and may receive asset plots for geographic areas associated with remaining assets. The device may identify a coverage band for the asset based on the best serving plot information, may determine coverage tiers for the geographic areas based on the asset plots, and may calculate next best serving assets for the geographic areas. The device may compute PDFs for the coverage band and the coverage tiers associated with next best serving assets, may compute an intersection of the PDFs, and may calculate an area under the intersection to generate a coverage overlap coefficient. The device may utilize the coverage overlap coefficient to scale KPIs of the asset and to generate updated KPIs of the asset, and may perform one or more actions based on the updated KPIs.

Inventors

• Ammara ESSA
• Hector Alejandro Garcia Crespo
• Matthew Kapala
• John N. Wakim
• Chad HOOPER
• Timothy E. Coyle

Assignees

• VERIZON PATENT AND LICENSING INC.

Dates

Publication Date

20260507

Application Date

20241104

Claims (20)

1. 1 . A method, comprising: identifying, by a device, assets associated with potential network outages; receiving, by the device, best serving plot information for an asset of the assets and at a geospatial level; receiving, by the device, asset plots for aggregate distinct geographic areas associated with remaining assets of the assets; identifying, by the device, a coverage band for the asset based on the best serving plot information; determining, by the device, coverage tiers for the geographic areas based on the asset plots; calculating, by the device, next best serving assets for the geographic areas based on the coverage band and the coverage tiers; computing, by the device, probability density functions (PDFs) for the coverage band and the coverage tiers associated with next best serving assets; computing, by the device, an intersection of the PDFs; calculating, by the device, an area under the intersection to generate a coverage overlap coefficient for the asset; utilizing, by the device, the coverage overlap coefficient to scale key performance indicators (KPIs) of the asset and to generate updated KPIs of the asset; and performing, by the device, one or more actions based on the updated KPIs.
2. 2 . The method of claim 1 , wherein performing the one or more actions comprises one or more of: scheduling the asset for maintenance based on the updated KPIs; generating a recommendation for the asset based on the updated KPIs; or identifying missing neighbor relationships between the assets based on the updated KPIs.
3. 3 . The method of claim 1 , wherein performing the one or more actions comprises one or more of: determining an anchoring impact on the assets based on the updated KPIs; identifying the assets with coverage overlap greater than a threshold based on the updated KPIs; or recommending parameter adjustments for the asset or the remaining assets to minimize an outage impact associated with the asset.
4. 4 . The method of claim 1 , wherein the asset is a battery backup system of network equipment.
5. 5 . The method of claim 1 , further comprising: prioritizing replacement of the asset to ensure continuous operation of network equipment associated with the asset.
6. 6 . The method of claim 1 , wherein the assets include wireless network sites.
7. 7 . The method of claim 1 , wherein the updated KPIs of the asset provide an indication of an impact associated with an outage of the asset.
8. 8 . A device, comprising: one or more processors configured to: identify assets associated with potential network outages; receive best serving plot information for an asset of the assets and at a geospatial level; receive asset plots for aggregate distinct geographic areas associated with remaining assets of the assets; identify a coverage band for the asset based on the best serving plot information; determine coverage tiers for the geographic areas based on the asset plots; calculate next best serving assets for the geographic areas based on the coverage band and the coverage tiers; compute probability density functions (PDFs) for the coverage band and the coverage tiers associated with next best serving assets; compute an intersection of the PDFs; calculate an area under the intersection to generate a coverage overlap coefficient for the asset; utilize the coverage overlap coefficient to scale key performance indicators (KPIs) of the asset and to generate updated KPIs of the asset, wherein the updated KPIs of the asset provide an indication of an impact associated with an outage of the asset; and perform one or more actions based on the updated KPIs.
9. 9 . The device of claim 8 , wherein the one or more processors are further configured to: calculate a criticality score for the asset based on the updated KPIs; and utilize the criticality score to prioritize maintenance scheduling for the asset.
10. 10 . The device of claim 8 , wherein the one or more processors are further configured to: identify changing network conditions or outage events associated with the asset; and dynamically update the coverage overlap coefficient and the updated KPIs in real-time based on the changing network conditions or the outage events.
11. 11 . The device of claim 8 , wherein the KPIs include metrics associated with one or more of call drop rates, data throughput, or network latency.
12. 12 . The device of claim 8 , wherein the one or more processors are further configured to: compare the coverage overlap coefficient across different bands and frequencies to account for spectrum-specific impacts on network performance.
13. 13 . The device of claim 8 , wherein the one or more processors are further configured to: utilize predictive analytics to forecast a potential outage impact of the asset; and adjust prioritization of maintenance of the asset based on the potential outage impact of the asset.
14. 14 . The device of claim 8 , wherein the one or more processors, to perform the one or more actions, are configured to: determine that a battery associated with the asset requires replacement based on the updated KPIs; and cause the battery to be replaced based on determining that the battery associated with the asset requires replacement.
15. 15 . A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising: one or more instructions that, when executed by one or more processors of a device, cause the device to: identify assets associated with potential network outages; receive best serving plot information for an asset of the assets and at a geospatial level; receive asset plots for aggregate distinct geographic areas associated with remaining assets of the assets; identify a coverage band for the asset based on the best serving plot information; determine coverage tiers for the geographic areas based on the asset plots; calculate next best serving assets for the geographic areas based on the coverage band and the coverage tiers; compute probability density functions (PDFs) for the coverage band and the coverage tiers associated with next best serving assets; compute an intersection of the PDFs; calculate an area under the intersection to generate a coverage overlap coefficient for the asset; utilize the coverage overlap coefficient to scale key performance indicators (KPIs) of the asset and to generate updated KPIs of the asset, wherein the KPIs include metrics associated with one or more of call drop rates, data throughput, or network latency; and perform one or more actions based on the updated KPIs.
16. 16 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the device to perform the one or more actions, cause the device to one or more of: schedule the asset for maintenance based on the updated KPIs; generate a recommendation for the asset based on the updated KPIs. identify missing neighbor relationships between the assets based on the updated KPIs; determine an anchoring impact on the assets based on the updated KPIs; identify the assets with coverage overlap greater than a threshold based on the updated KPIs; or recommend parameter adjustments for the asset or the remaining assets to minimize an outage impact associated with the asset.
17. 17 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to: calculate a criticality score for the asset based on the updated KPIs; and utilize the criticality score to prioritize maintenance scheduling for the asset.
18. 18 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to: identify changing network conditions or outage events associated with the asset; and dynamically update the coverage overlap coefficient and the updated KPIs in real-time based on the changing network conditions or the outage events.
19. 19 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to: compare the coverage overlap coefficient across different bands and frequencies to account for spectrum-specific impacts on network performance.
20. 20 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to: utilize predictive analytics to forecast a potential outage impact of the asset; and adjust prioritization of maintenance of the asset based on the potential outage impact of the asset.

Description

BACKGROUND Wireless networks are an indispensable part of modern communication infrastructures, providing connectivity to numerous devices and services. With the dynamic evolution of network technologies and the expansion of coverage areas, the integrity of wireless networks is paramount to consistent user experience. BRIEF DESCRIPTION OF THE DRAWINGS FIGS. 1A-1J are diagrams of an example associated with estimating wireless network outage impact of a network asset. FIG. 2 is a diagram of an example environment in which systems and/or methods described herein may be implemented. FIG. 3 is a diagram of example components of one or more devices of FIG. 2. FIG. 4 is a flowchart of an example process for estimating wireless network outage impact of a network asset. DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS The following detailed description of example implementations refers to the accompanying drawings. The same reference numbers in different drawings may identify the same or similar elements. Existing wireless infrastructure often faces challenges due to aging assets, such as battery backup systems for aspects of network elements, which are essential for maintaining network service during power outages. As equipment reaches the end of a service life, network operators must prioritize replacement of the equipment to ensure continuous operation. However, logistical constraints make it impractical to replace all aging equipment simultaneously. Thus, network operators must determine which assets (e.g., network sites) are most critical and should be prioritized for asset replacement. Decisions based on location categories (e.g., urban versus rural), a population covered, or network performance metrics may not fully capture a criticality of a particular site within a broader network context. Moreover, there exists an additional layer of complexity in analyzing a potential service impact when multiple sites experience simultaneous outages, which can leave a disproportionate effect on the network. Thus, current techniques for handling replacement or maintenance of network assets consume computing resources (e.g., processing resources, memory resources, communication resources, and/or the like), networking resources, and/or other resources associated with failing to provide a reliable, data-driven approach to quantifying impacts of network asset outages, generating suboptimal asset management and response strategies based on failing to accurately quantify impacts of network asset outages, especially in important scenarios, such as during natural disasters or high-demand events, and/or the like. Some implementations described herein provide a device (e.g., a management system) that estimates wireless network outage impact of a network asset. For example, the management system may identify assets associated with potential network outages, may receive best serving plot information for an asset of the assets and at a geospatial level, and may receive asset plots for aggregate distinct geographic areas associated with remaining assets of the assets. The management system may identify a coverage band for the asset based on the best serving plot information, may determine coverage tiers for the geographic areas based on the asset plots, and may calculate next best serving assets for the geographic areas based on the coverage band and the coverage tiers. The management system may compute probability density functions (PDFs) for the coverage band and the coverage tiers associated with next best serving assets, may compute an intersection of the PDFs, and may calculate an area under the intersection to generate a coverage overlap coefficient for the asset. The management system may utilize the coverage overlap coefficient to scale key performance indicators (KPIs) of the asset and to generate updated KPIs of the asset, and may perform one or more actions based on the updated KPIs. In this way, the management system estimates wireless network outage impact of a network asset. For example, the management system may identify wireless network sites as assets, and may obtain geospatial coverage data for the network sites. The management system may identify a coverage band for each network site, and may determine coverage tiers for the network sites. The management system may calculate next best service alternatives, and may compute PDFs for overlapping coverage areas. The management system may calculate an area under the PDFs to generate a coverage overlap coefficient, and may utilize the coverage overlap coefficient to adjust KPIs related to the network sites, which in turn informs maintenance schedules, replacement recommendations, or other optimization actions for the network sites. Thus, the management system may conserve computing resources, networking resources, and/or other resources that would have otherwise been consumed by failing to provide a reliable, data-driven approach to quantifying impacts of network asset outages,