Base Station Almanac Localization via Cell Grouping and Multilateration
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Solution Overview
Problem
Existing methods for creating base station almanacs require manual deployment of specialized equipment and operator assistance, which can be costly and impractical, especially for independent generation without direct operator support, leading to imprecise mobile device positioning and potential delays in emergency responses.
Innovation Solution
A method using a compute node to determine estimated positions of cellular base stations and parameters through multilateration with RF signals received by a receiver at known positions, iteratively grouping cells and sectors to improve geometric dilution of precision, and updating the base station almanac without operator assistance, utilizing GNSS and INS for precise location data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual deployment of specialized equipment is used to create base station almanacs, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system performs self-localization by having mobile devices determine their own positions using base station signals, eliminating the need for manual deployment of specialized measurement equipment. The base stations effectively serve themselves by providing signals that enable their own location determination through multilateration.
Solution Approach 2:
Instead of using expensive specialized equipment to measure base station locations, the system uses copies of base station signals received by multiple mobile devices to calculate locations through multilateration, replacing physical measurement tools with signal-based virtual measurements.
2Reliability
If operator assistance is required for almanac generation, then reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system enables independent generation of base station almanacs by mobile devices without requiring operator assistance. Mobile devices autonomously collect signals, perform multilateration calculations, and contribute to almanac creation, making the process self-sufficient and eliminating dependency on network operators.
Solution Approach 2:
The system uses feedback from multiple mobile device measurements to continuously refine and validate base station location estimates. By aggregating data from numerous devices and iteratively improving accuracy through validation against known positions, the system maintains reliability while operating independently.
3Measurement precision
If conventional multilateration is used for positioning, then positioning capability is provided, but measurement precision deteriorates due to geometric dilution of precision
Solution Approach 1:
The system segments the cellular network into groups of co-located cells and bases stations, organizing them hierarchically. By grouping cells that share the same physical location, the system reduces the number of independent parameters in multilateration calculations and improves geometric distribution for better positioning accuracy.
Solution Approach 2:
The system transitions from two-dimensional base station location data to three-dimensional positioning by incorporating altitude information from barometric pressure sensors and terrain data. This additional vertical dimension enhances positioning precision, particularly for emergency responses where elevation is critical.
4Reliability
If frequent updates of base station almanac are performed, then reliability is improved, but loss of time increases
Solution Approach 1:
Instead of completely regenerating the entire base station almanac with each update, the system performs partial updates by only recalculating and transmitting changes for affected base stations. This selective updating approach maintains almanac currency while significantly reducing processing time and network overhead.
Solution Approach 2:
The system pre-processes and validates base station location data during idle periods before updates are needed. By performing preliminary calculations and organizing data structures in advance, the system minimizes actual update time when almanac refreshes are required, balancing currency with processing efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and efficient generation of base station almanacs independently, improving mobile device positioning accuracy and reducing costs by eliminating the need for operator involvement, thus enhancing network performance and emergency response times.
Implementation Method 1
determining, by a compute node, a plurality of estimated positions for a plurality of cells within a region using cellular signals received by a receiver at a plurality of known receiver positions
Implementation Method 2
These distances are typically calculated based on the time of arrival (TOA), time difference of arrival (TDOA), or received signal strength (RSS) of the signals
Data Source
AI summary
A method involves determining estimated positions for multiple cells within a region using cellular signals received by a receiver at multiple known receiver positions. Multiple first cell groups are determined using the multiple cells. Respective estimated positions are determined for each cell group of the first cell groups. Each cell group of the first cell groups is validated using the respective estimated position of each cell group and the known receiver positions. Multiple second cell groups are generated based on the cell group validation. An estimated position of each cell group of the second cell groups is used as an estimated position of a respective base station within the region, and a base station almanac is updated using a respective estimated position for each of the base stations.