Sensor-Assisted 5G Positioning for NLOS Conditions
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Solution Overview
Problem
5G positioning accuracy is compromised by non-line of sight (NLOS) conditions due to multipath problems and hidden peak detection challenges, leading to reduced precision and increased computational complexity.
Innovation Solution
A system and method utilizing 5G positioning with NLOS information, incorporating a backend server, user equipment (UE) with sensors, and transmission and reception points (TRPs) to enhance positioning accuracy by computing preliminary locations, gathering NLOS information, and generating refined positioning estimates through feedback modules and reliability adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 5G positioning methods are used, then the system is simple to implement, but positioning accuracy deteriorates under NLOS conditions due to multipath problems and hidden peak detection
Solution Approach 1:
The patent introduces sensors (cameras, LiDAR, IMU) as intermediary devices that detect environmental features and provide NLOS information. These sensors act as mediators between the TRPs and the positioning algorithm, enabling the system to distinguish LOS from NLOS paths and improve positioning accuracy without fundamentally changing the 5G positioning infrastructure
Solution Approach 2:
The patent implements feedback mechanisms where sensor-derived NLOS information is fed back to the positioning module to adjust weight assignments for different TRP measurements. The system continuously refines positioning estimates by incorporating feedback from both signal measurements and sensor data, creating an iterative improvement loop that enhances accuracy
2Area of stationary object
If multiple TRPs are deployed to improve positioning coverage, then coverage area increases, but computational complexity increases due to need to process signals from multiple sources
Solution Approach 1:
The patent performs preliminary actions by having sensors pre-detect environmental features and pre-determine NLOS probabilities before the actual positioning calculation. This advance preparation of NLOS information allows the positioning module to efficiently process signals from multiple TRPs without excessive computational burden during the critical positioning phase
3Measurement precision
If sensor data is integrated to improve positioning accuracy, then positioning precision improves, but power consumption increases due to additional sensor operations
Solution Approach 1:
The patent applies partial action by selectively using sensor data only when NLOS conditions are detected or when they can provide meaningful improvement. The system does not continuously operate all sensors at full capacity, but rather activates them strategically to provide just enough NLOS information to improve positioning accuracy without excessive power consumption
Data Source
AI summary
A system using positioning with non-line of sight information from sensors is provided. The system includes a plurality of TRPs, a UE, and a backend server. The TRPs are distributed in a target region. The UE is placed within the target region and the UE comprises at least one sensor for gathering surrounding information at the target region. The backend server comprises a signal receiver, a positioning module, a signal emitter, and a feedback module. The signal receiver is configured to receive first SRSs. The positioning module is configured to compute a preliminary location of the UE according to the first SRS signals. The signal emitter sends a location signal containing the preliminary location of the UE to the UE. The feedback module is configured to receive second SRSs and NLOS information from the UE and to generate at least one positioning estimation result by positioning the UE.