A sea area wireless network coverage optimization method, device and equipment based on multi-source big data

By integrating multi-source big data and using interpretable artificial intelligence models, the problems of measurement data drift and cause analysis in the assessment of wireless network coverage in marine areas have been solved, enabling precise geographical anchoring and intelligent optimization of wireless networks in marine areas, and improving the level of refinement in assessment and optimization.

CN122372931APending Publication Date: 2026-07-10CHINA UNITED NETWORK COMM GRP CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA UNITED NETWORK COMM GRP CO LTD
Filing Date
2026-04-20
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing technologies for assessing wireless network coverage in marine areas suffer from spatial drift of measurement data, limited assessment dimensions, lack of precise geographical anchoring and causal analysis, resulting in a lack of refinement and closed-loop verification in optimization schemes.

Method used

By integrating multi-source big data, including wireless network data, ship trajectory data, and geographic information data, spatiotemporal matching and spatial overlay are performed to identify weak coverage areas and generate closed-loop optimization schemes. Multidimensional feature datasets and interpretable artificial intelligence models are used to generate refined cause attribution and optimization strategies.

Benefits of technology

It enables precise geographic anchoring and intelligent optimization of wireless networks in the sea area, reduces assessment costs, improves the normalization of assessments and the accuracy and effectiveness of optimization solutions, and ensures that optimization solutions meet actual business needs and have closed-loop verification.

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Abstract

This invention discloses a method, apparatus, and device for optimizing marine wireless network coverage based on multi-source big data. The method includes: acquiring multi-source marine data; generating a set of measurement reports carrying ship movement trajectory characteristics within a preset time window and spatial buffer; associating the measurement report set with user service data to construct a multi-dimensional feature dataset; identifying weak coverage areas in the marine area from the multi-dimensional feature dataset, and spatially overlaying these weak coverage areas with geographic information data to determine the geographic causes of the weak coverage areas; using the location information, geographic causes, and service experience requirements corresponding to the user service data of the weak coverage areas as constraints, generating candidate optimization schemes using a preset optimization strategy mapping model and verifying them; and outputting the candidate optimization schemes as the final network optimization schemes after successful verification. This method can improve the intelligence and refinement of marine network optimization.
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