Frequency Transformed Radiomap Data for Position Estimation
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Solution Overview
Problem
In urban and suburban areas, the large number of communication network nodes requires significant storage capacity and network resources for radiomap data, leading to high costs for users in storing and transferring radiomap information for position estimation.
Innovation Solution
Applying a discrete frequency transform to the original radiomap data set to obtain a frequency transformed radiomap data set, which can be reconstructed using an inverse discrete frequency transform, reducing storage and bandwidth requirements by decorrelating the data and allowing for offline position estimation in mobile terminals with limited storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radiomap data is stored in original form for position estimation, then position estimation accuracy is maintained, but storage capacity and network bandwidth consumption increase significantly
Solution Approach 1:
The patent applies a discrete frequency transform (such as Fourier transform or wavelet transform) to convert the radiomap data from spatial domain to frequency domain. This parameter transformation allows the data to be represented by a few dominant frequency coefficients, dramatically reducing storage requirements while preserving the essential spatial patterns needed for accurate position estimation. The transform changes the representation parameters from raw spatial measurements to frequency spectrum coefficients.
2Adaptability or versatility
If radiomap data is transferred to mobile terminals for offline position estimation, then positioning independence from network is achieved, but network bandwidth and data transfer costs increase
Solution Approach 1:
The patent extracts only the essential frequency transform coefficients from the complete radiomap data set, rather than transferring the entire original data set. These extracted coefficients capture the most significant spatial characteristics of the radio environment. By taking out only this compressed essential information, the system enables offline positioning at mobile terminals while minimizing network bandwidth consumption and data transfer costs.
3Loss of information
If complete radiomap data is stored at server, then data completeness is maintained, but storage costs and processing resources increase
Solution Approach 1:
The patent applies partial action by storing and processing only the most significant frequency coefficients rather than the complete radiomap data set. The frequency transform naturally separates important spatial information from less important details, allowing the system to work with a partial representation (the dominant coefficients) that retains sufficient information for accurate position estimation while dramatically reducing storage capacity requirements at the server.
Data Source
AI summary
It is disclosed to obtain a frequency transformed radiomap data set by applying a discrete frequency transform to an original radiomap data set. It is also disclosed to obtain a reconstructed radiomap data set by applying an inverse discrete frequency transform to a frequency transformed radiomap data set.