Cooperative Indoor UE Positioning Using 5G Fingerprints and RTT
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Solution Overview
Problem
In indoor environments where global navigation satellite system (GNSS) signals are unavailable, existing positioning technologies, such as 4G LTE, suffer from reduced accuracy and reliability due to limited cellular signal strength and vulnerability to environmental changes, making precise location determination challenging.
Innovation Solution
A high-accuracy positioning scheme utilizing 5G fingerprinting and device-to-device (D2D) communication, where vehicles leverage 5G received signal strength (RSS) fingerprints and RTT protocols to determine distances with other vehicles, and employ cooperative localization to enhance positioning accuracy by sharing location information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 4G LTE positioning is used in indoor environments, then positioning can be performed without GNSS signals, but positioning accuracy is reduced due to limited cellular signal strength and environmental changes
Solution Approach 1:
The patent combines multiple positioning techniques (fingerprinting, D2D communication, RTT measurements) into a unified positioning system. The ego UE integrates information from multiple sources including signal strength fingerprints, absolute positions of other UEs, and relative distance measurements to achieve high-accuracy positioning in indoor environments where GNSS is unavailable.
Solution Approach 2:
The patent introduces fingerprinting information as an intermediary to bridge the gap between limited cellular signals and accurate positioning. By pre-collecting and storing signal strength fingerprints at known locations, the system can match current measurements to determine position even when direct signal strength-based positioning would be inaccurate.
2Ease of operation
If fingerprinting-based positioning is used, then positioning can be performed using signal strength information, but accuracy is affected by environmental changes and signal variations
Solution Approach 1:
The patent implements feedback by continuously monitoring signal strength measurements and comparing them against stored fingerprint data. The system uses RTT measurements as feedback to verify and refine position estimates, and dynamically updates positioning calculations based on real-time measurements from multiple UEs to compensate for environmental changes.
Solution Approach 2:
The patent creates a composite positioning approach that merges fingerprinting data with D2D communication measurements. By combining multiple positioning methodologies rather than relying on a single technique, the system achieves robustness against environmental variations while maintaining ease of operation.
3Measurement precision
If D2D communication is used for cooperative localization, then positioning accuracy is improved through multiple reference points, but system complexity increases
Solution Approach 1:
The patent segments the positioning function into distinct components: fingerprinting for initial position estimation, RTT for distance measurement, and cooperative localization for refinement. Each UE independently performs these segmented tasks and shares results with others, reducing individual device complexity while achieving high collective accuracy.
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
The scheme provides reliable high-accuracy positioning by leveraging 5G D2D communication to complement RSS fingerprints, improving localization accuracy even in dynamic indoor environments and addressing real-time changes, thereby enhancing the precision of vehicle positioning.
Implementation Method 1
determining, using round trip time between the ego UE and the other UEs, first distances of the ego UE from each of the other UEs
Implementation Method 2
a fingerprint location based on signal strength information between the UE and n different femtocells
Data Source
AI summary
An ego user equipment (UE) receives absolute position and relative distance information for m other UEs at a timestamp and a fingerprint location based on signal strength information between the UE and n different femtocells. The ego UE determines, using round trip time between the ego UE and the other UEs, first distances of the ego UE from each of the other UEs. The ego UE determines, using the absolute position of the ego UE via fingerprinting information and absolute position of other UEs received through device-to-device (D2D) communication, second distances of the ego UE to each of the other UEs. The ego UE utilizes the fingerprint location as a current location of the UE responsive to a predefined threshold subset of discrepancies between the first distances and the second distances being within a predefined distance tolerance threshold.


