Uplink Coordinated Multipoint Positioning for IoT Devices
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Solution Overview
Problem
Current wireless communication technologies lack a viable, accurate method for determining the position of Internet of Things (IoT) devices to meet industry accuracy requirements, particularly for narrowband IoT devices, due to limitations in existing power-based and timing-based positioning solutions, which often result in positional errors exceeding ±10 meters.
Innovation Solution
Implementing a coordinated multipoint (CoMP) process in network nodes to estimate the time difference of arrival (TDoA) of signals from IoT devices using both time and frequency domain signal processing, cross-correlating reference signals with neighbor signals to calculate precise device positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If legacy power-based positioning solutions (RSRP measurements) are used, then the positioning method is simple to implement, but the positioning accuracy is extremely poor (hundreds of meters)
Solution Approach 1:
The patent replaces power-based positioning (RSRP measurements) with timing-based positioning using Time Difference of Arrival (TDoA) measurements. This substitution fundamentally changes the measurement parameter from power to time, achieving positioning accuracy of better than ±50 meters while maintaining network-based implementation simplicity.
2Measurement precision
If legacy timing-based positioning solutions are used for 4G channels, then positioning accuracy improves to better than ±50 meters, but the solution is limited to 10 MHz or higher bandwidth channels and does not work for narrowband IoT devices
Solution Approach 1:
The patent changes the bandwidth parameter requirement by demonstrating that TDoA measurements can be performed successfully on narrowband IoT channels (1.08 MHz and 180 kHz) rather than requiring 10 MHz or higher bandwidth. This parameter change enables positioning accuracy of better than ±50 meters to extend to narrowband IoT devices while maintaining the same timing-based approach.
3Measurement precision
If 5G high order numerologies with wider channels are used, then positioning accuracy improves for high bandwidth devices, but there is little or no benefit for narrow band IoT devices
Solution Approach 1:
The patent segments the positioning analysis by separately evaluating performance for narrowband IoT devices (1.08 MHz and 180 kHz channels) versus wider 5G channels. This segmentation demonstrates that the proposed TDoA-based approach achieves positioning accuracy of better than ±50 meters for narrowband IoT devices without requiring high order numerologies, thereby making the solution adaptable to both narrowband and wideband devices.
4Measurement precision
If GPS receivers are used for location information, then outdoor positioning is possible, but indoor positioning does not work and power consumption is high
Solution Approach 1:
The patent introduces network-based TdoA measurements as an intermediary positioning method between the wireless device and the location server. This intermediary approach uses the cellular network infrastructure to perform positioning calculations, enabling both indoor and outdoor positioning capabilities while significantly reducing power consumption compared to GPS receivers.
5Measurement precision
If Wi-Fi is used for geolocation, then positioning is possible, but power consumption is high and network ubiquity is insufficient
Solution Approach 1:
The patent uses network-based TdoA measurements as an intermediary positioning method that leverages the existing cellular network infrastructure. This approach eliminates the need for Wi-Fi positioning, achieving geolocation capability with significantly lower power consumption while relying on the ubiquitous cellular network coverage.
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
This approach significantly improves positioning accuracy for IoT devices, reducing errors to below ±1 meter by leveraging advanced signal processing and network node coordination, thereby meeting industry standards for applications like collision avoidance and indoor location tracking.
Implementation Method 1
The time domain reference signal is cross-correlated with the time domain neighbor signals to determine a time difference of arrival for each of the plurality of time domain neighbor signals
Data Source
AI summary
A method and network node for uplink coordinated multipoint positioning are disclosed. According to one aspect, a method includes employing a coordinated multipoint function to decode data from a WD using signals received from the WD by the network node and from signals received from the WD by a plurality of cooperating network nodes. The method further includes converting the decoded WD data signal into a time domain reference signal and convert the signals received from the plurality of cooperating network nodes into time domain neighbour signals. The method also includes cross-correlating the time domain reference signal with the time domain neighbour signals to determine a time difference of arrival for each of the plurality of time domain neighbour signals. The method also includes calculating a position of the WD based on the time differences of arrival and based on locations of the cooperating network nodes.