Systems and methods for detecting and mitigating periodic and transient interference in a network
US-12052060-B2 · Jul 30, 2024 · US
US12328150B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12328150-B2 |
| Application number | US-202418756029-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 27, 2024 |
| Priority date | Feb 28, 2022 |
| Publication date | Jun 10, 2025 |
| Grant date | Jun 10, 2025 |
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A device may receive time domain PRB data associated with a plurality of base stations of a network, and may transform the time domain PRB data into frequency domain PRB data. The device may identify, based on the frequency domain PRB data, periodic interference patterns associated with the network, and may process periodic data associated with the periodic interference patterns, with a clustering model, to identify clusters of periodic interference patterns. The device may utilize a time offset analysis to link clusters and identify a transient periodic interferer, and may process cluster data associated with the clusters and the transient periodic interferer, and public transportation data, with a machine learning model, to predict a route associated with the transient periodic interferer. The device may perform one or more actions based on the route associated with the transient periodic interferer.
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What is claimed is: 1. A method, comprising: processing, by a device, interference patterns associated with a network, to identify clusters of interference patterns; utilizing, by the device, an analysis to relate clusters and identify a transient interferer; processing, by the device, data associated with the clusters and the transient interferer, and transportation data, to predict a route associated with the transient interferer; and performing, by the device, one or more actions based on the route associated with the transient interferer. 2. The method of claim 1 , further comprising: identifying the interference patterns based on frequency domain physical resource block (PRB) data. 3. The method of claim 1 , wherein utilizing the analysis to relate the clusters and identify the transient interferer comprises: identifying adjacencies of the clusters; and linking adjacent clusters together. 4. The method of claim 1 , wherein processing the interference patterns comprises: processing the interference patterns to determine related interference patterns; and performing a cross-correlation of the related interference patterns to identify the clusters of interference patterns. 5. The method of claim 1 , wherein the network is associated with a plurality of base stations. 6. The method of claim 1 , wherein the interference patterns are periodic. 7. The method of claim 1 , wherein the transient interferer is periodic. 8. A device, comprising: one or more memories; and one or more processors, coupled to the one or more memories, configured to: process data associated with interference patterns related to a network to identify clusters of interference patterns; utilize an analysis to associate clusters and identify a transient interferer; process data associated with the clusters and the transient interferer, and transportation data to predict a route associated with the transient interferer; and perform one or more actions based on the route associated with the transient interferer. 9. The device of claim 8 , wherein the one or more processors are further configured to: identify the interference patterns based on frequency domain physical resource block (PRB) data. 10. The device of claim 8 , wherein the one or more processors, to utilize the analysis to associate the clusters and identify the transient interferer, are configured to: identify adjacencies of the clusters; and link adjacent clusters together. 11. The device of claim 8 , wherein the one or more processors, to process the interference patterns, are configured to: process the interference patterns to determine related interference patterns; and perform a cross-correlation of the related interference patterns to identify the clusters of interference patterns. 12. The device of claim 8 , wherein the network is associated with a plurality of base stations. 13. The device of claim 8 , wherein the interference patterns are periodic. 14. The device of claim 8 , wherein the transient interferer is periodic. 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: process data associated with interference patterns related to a network to identify clusters of interference patterns; utilize an analysis to associate clusters and identify a transient interferer; process cluster data associated with the clusters and the transient interferer, and transportation data to predict a route associated with the transient interferer; and perform one or more actions based on the route associated with the transient interferer. 16. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, when executed by the one or more processors, further cause the device to: identify the interference patterns based on frequency domain physical resource block (PRB) data. 17. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the device to utilize the analysis to associate the clusters and identify the transient interferer, cause the device to: identify adjacencies of the clusters; and link adjacent clusters together. 18. The non-transitory computer-readable medium of claim 15 , wherein the network is associated with a plurality of base stations. 19. The non-transitory computer-readable medium of claim 15 , wherein the interference patterns are periodic. 20. The non-transitory computer-readable medium of claim 15 , wherein the transient interferer is periodic.
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