Cell-Level Mobile Data Distribution Using Terminal Position Estimates
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Solution Overview
Problem
Existing methods for distributing aggregated mobile communication network data at the cell level to the geographic level are unrealistic and result in gross errors due to assumptions of uniform or exponential distribution, failing to accurately reflect the actual geographic position of individuals, especially on small scales.
Innovation Solution
A method involving geographic position estimates from a subset of mobile terminals, distributed on tessellated tiles, allows calculating a general distribution map, which then generates a cell-specific distribution map that accurately reflects the geographic position of individuals, enabling precise distribution of cell-level data even on smaller scales than the network cell size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform or exponential distribution functions are used to distribute cell-level aggregated data to geographic level, then the distribution process is simple and easy to implement, but the accuracy of reflecting actual geographic position of individuals is poor, resulting in gross errors
Solution Approach 1:
The patent introduces an intermediary component: a subset of mobile terminals that provide actual geographic position measurements. These position estimates act as a mediator between the cell-level aggregated data and the geographic distribution, enabling the system to learn and adapt to real user location patterns without requiring complex centralized processing of all user data.
Solution Approach 2:
The patent changes the parameter of distribution from fixed theoretical models (uniform/exponential) to dynamic parameters derived from actual mobile terminal position estimates. By using real position data from a subset of terminals, the distribution parameters adapt to actual user behavior patterns, significantly improving accuracy while maintaining computational efficiency.
2Device complexity
If cell-level aggregated data is distributed without considering actual user position distribution, then the processing complexity is low, but the reliability of the distributed data for practical applications is poor
Solution Approach 1:
The system uses self-service by leveraging the position estimation capabilities that already exist in mobile terminals. Instead of requiring complex external positioning infrastructure, the solution utilizes the terminals' own positioning functions to provide the distribution reference data, reducing overall system complexity while improving reliability.
Solution Approach 2:
The patent implements feedback by using actual position estimates from mobile terminals to continuously improve the distribution accuracy. The system learns from real user location patterns and adjusts the distribution accordingly, creating a feedback loop that enhances reliability without proportionally increasing processing complexity.
3Device complexity
If a subset of mobile terminals is used to provide position estimates, then the system complexity and data processing load are reduced, but sufficient coverage and representativeness of the position data must be maintained
Solution Approach 1:
The patent applies partial action by using only a subset of mobile terminals for position estimation rather than all terminals. This subset approach reduces system complexity and data processing requirements while still providing sufficient statistical representativeness for accurate geographic distribution, avoiding the need for excessive data collection from every terminal.
Data Source
AI summary
A method distributes cell-level aggregated data available from a mobile communication network and aggregated at the level of single network cells. The method subdivides a geographic area in geographic area portions, and causes mobile terminals situated in the geographic area to calculate and provide respective geographic position estimates to a data processing system. An overall number of geographic position estimates are distributed by assigning to each geographic area portion a respective number of geographic position estimates. Cell-level aggregated data relating to a network cell is received, and for each network cell, covered geographic area portions are determined. The cell-level aggregated data of the network cell is distributed according to a respective distribution factor. A distribution map of the cell-level aggregated data is generated in which to each of the geographic area portions of the geographic area of interest a respective quota of the cell-level aggregated data is assigned.