Blind PRS Parameter Detection via Shallow and Deep Search Modes
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Solution Overview
Problem
Existing wireless communication systems face challenges in determining the positioning of mobile devices, especially indoors, where satellite signals are not available, and require alternative solutions like time difference of arrival (TDOA) and observed time difference of arrival (OTDOA) for accurate location services.
Innovation Solution
A method and apparatus for estimating positioning reference signal (PRS) energy in predetermined locations of each subframe of an incoming signal and blindly detecting PRS parameters, allowing mobile devices to determine their position without relying on satellite systems by using a combination of shallow and deep search modes to identify PRS configuration parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blind search is performed for PRS configuration parameters, then positioning capability in indoor environments is improved, but processing time and computational complexity increase
Solution Approach 1:
The blind search process is divided into two distinct phases: shallow search mode for initial PRS detection and deep search mode for precise parameter identification. This segmentation allows the system to perform quick initial positioning and then refine results only when necessary, reducing overall processing time while maintaining indoor positioning capability.
Solution Approach 2:
The shallow search mode performs preliminary detection of PRS signals and configuration parameters before initiating the more time-consuming deep search mode. By completing basic positioning tasks in advance, the system reduces the computational burden during subsequent deep search operations, thereby decreasing total processing time.
2Measurement precision
If blind search for PRS parameters is implemented, then positioning accuracy in satellite-denied areas is improved, but device complexity increases
Solution Approach 1:
The processing complexity is segmented into two functional modes: shallow search for basic PRS detection and deep search for accurate parameter identification. This division allows the device to handle positioning tasks with manageable complexity levels, achieving accurate positioning in satellite-denied areas without overwhelming computational requirements.
Solution Approach 2:
The shallow search mode performs partial detection actions that are sufficient for basic positioning, while the deep search mode applies more extensive analysis only when higher precision is required. This partial action approach reduces overall device complexity while maintaining the capability for accurate positioning when needed.
3Reliability
If PRS energy estimation is performed in all subframes, then positioning reliability is improved, but energy consumption increases
Solution Approach 1:
The energy consumption is segmented by performing PRS energy estimation selectively across different subframes based on the search mode requirements. The shallow search mode processes fewer subframes with lower energy consumption, while the deep search mode processes more subframes when higher reliability is needed, thus balancing energy usage with positioning reliability.
Solution Approach 2:
The system performs partial energy estimation actions in shallow search mode and excessive (more comprehensive) estimation in deep search mode. This partial action strategy reduces overall energy consumption while maintaining positioning reliability by applying full energy estimation only when necessary for accurate indoor positioning.
Data Source
AI summary
A method for blindly determining positioning reference signals in a wireless communication network determines a positioning reference signal (PRS) network configuration by estimating a PRS energy from predetermined locations of each subframe of an incoming signal. Such a method may also include blindly detecting PRS parameters based on the estimated PRS energy. The PRS energy may be peak energy responses for deep searches or verifications. The PRS energy may be a signal to signal plus noise ratio for shallow searches.