Wireless Positioning Signal Processing Using Combined Filter Responses
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wireless communication systems face challenges in achieving accurate positioning, particularly in noisy environments, as they require more factors to be considered for precise positioning, and existing methods struggle to determine channel characteristics effectively.
Innovation Solution
An apparatus and method that utilize assistance data to generate a transmit sequence, combine filter responses, and estimate channel characteristics by sampling time-domain signals, allowing for improved channel estimation and positioning accuracy, even in noisy conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional positioning methods are used, then the positioning can be performed with basic system requirements, but the positioning accuracy remains at meter level and cannot achieve centimeter level precision
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing combined filter responses that incorporate both transmit and receive filter characteristics. This preparation work is done before actual positioning measurements, allowing the system to use pre-computed filters rather than computing them in real-time during positioning operations. The combined filter responses are stored in memory and readily available when needed, significantly reducing processing complexity during actual positioning while enabling centimeter-level accuracy.
Solution Approach 2:
The patent implements dynamics by making the filter response adaptive to different positioning scenarios. The system dynamically selects and applies appropriate combined filter responses based on the specific positioning requirements and environmental conditions. This dynamic adaptation allows the system to optimize positioning accuracy for different situations without requiring complete re-computation of filters, balancing precision requirements with processing complexity.
2Measurement precision
If more factors are taken into account for accurate positioning, then positioning precision improves, but the processing complexity and computational burden increase significantly
Solution Approach 1:
The patent addresses this contradiction by performing the computationally intensive task of combining transmit and receive filter responses in advance, before actual positioning measurements are made. This preliminary computation eliminates the need to perform complex filter combinations during real-time positioning operations, thereby maintaining high positioning precision while preserving processing efficiency during critical measurement phases.
Solution Approach 2:
The patent uses copying by creating and storing copies of combined filter responses in memory. Instead of re-computing complex filter responses during each positioning operation, the system retrieves pre-computed copies, significantly reducing computational burden during actual positioning while maintaining the precision benefits of considering multiple factors.
3Reliability
If channel estimation is performed without considering filter responses, then the processing is simpler, but the positioning accuracy deteriorates in noisy environments
Solution Approach 1:
The patent resolves this contradiction by pre-computing combined filter responses that incorporate both transmit and receive filter characteristics before positioning measurements are made. This preliminary action ensures that the full complexity of filter processing is handled in advance, allowing reliable channel estimation in noisy environments during actual positioning operations without imposing real-time processing complexity burdens.
4Device complexity
If transmit filter response is obtained through approximation using predetermined pulse-shaping, then the system complexity is reduced, but the accuracy of channel characteristics determination may be compromised
Solution Approach 1:
The patent applies parameter changes by allowing flexibility in how the transmit filter response is obtained. The system can operate with approximated filter responses using predetermined pulse-shaping functions when simplicity is prioritized, or can use more accurate measured or pre-computed filter responses when higher precision is required. This parameter-based approach allows the system to adapt the level of accuracy versus complexity based on specific operational requirements.
Data Source
AI summary
To increase positioning accuracy, channel characteristics are determined taking into account receive filter response and transmit filter response. For example, upon receiving assistance data for positioning an apparatus, a transmit sequence is generated using the assistance data; and a combination of the transmit sequence is generated by combining the transmit sequence. Further, a receive filter response is determined, a transmit filter response is obtained, and a combined filter response is generated using the receive filter response and the transmit filter response. Reference signals received over a channel are measured by sampling them into a plurality of time-domain samples, and the channel is estimated from the plurality of time-domain samples using the combined filter response and the combination of the transmit sequence. Then, per channel characteristics, a value of the channel characteristics based on the channel estimated is determined.