Dynamic Network Optimization Using Geolocation and Modeling
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Solution Overview
Problem
Current network optimization techniques fail to leverage detailed user information and geolocation data to provide customized and precise resource allocation in wireless communication networks, leading to suboptimal performance and inefficient resource utilization.
Innovation Solution
A dynamic network optimization system using geolocation and network modeling that adjusts configuration parameters such as transmit power, antenna tilts, and handover thresholds based on real-time user data and historical patterns to improve network capacity, coverage, and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If high-powered base stations are used to cover large geographical areas, then network coverage is improved, but network resource allocation efficiency deteriorates
Solution Approach 1:
The patent segments the network optimization into multiple dimensions including geographical location, user behavior patterns, device characteristics, and time-based trends. By dividing the optimization problem into these discrete segments, the system can allocate resources more efficiently within each segment while maintaining overall network coverage.
Solution Approach 2:
The patent implements local quality by providing customized network configurations tailored to specific geographical locations, user groups, and time periods. Instead of uniform network parameters across the entire coverage area, the system adjusts parameters locally based on detailed user information and environmental factors, thereby improving resource allocation efficiency without sacrificing coverage.
2Measurement precision
If detailed user information and geolocation data are collected and processed, then network optimization precision is improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-processing and storing user information, device characteristics, and behavioral patterns in advance. This pre-computation allows the system to quickly retrieve and apply optimized parameters without performing complex real-time analysis, thereby reducing system complexity while maintaining high optimization precision.
Solution Approach 2:
The patent uses copying by creating virtual models or representations of user behavior patterns and network conditions. Instead of processing raw detailed data continuously, the system creates simplified copies or profiles that capture essential characteristics, reducing computational complexity while preserving optimization precision.
Data Source
AI summary
Techniques for dynamic network optimization using geolocation and network modeling are disclosed. In one particular exemplary embodiment, the techniques may be realized as a system for network optimization. The system may comprise a data collection system configured to collect geolocated subscriber records from a plurality of mobile devices. The system may also comprise a SON optimization system communicatively coupled to the data collection system via a network. The SON optimization system may comprise at least one pre-processor configured to receive and process geolocated subscriber records from the data collection system. The SON optimization system may further comprise a network simulator configured to perform network simulation analysis based on the processed geolocated subscriber records, and provide a new network configuration based on the network simulation analysis, wherein the new network configuration is estimated to improve network performance.