Wireless Sensing Region Selection for Low-Complexity Super-Resolution
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Solution Overview
Problem
The computational complexity and low real-time performance of current super-resolution via compressed sensing technology in wireless communication systems hinder efficient target sensing.
Innovation Solution
A method where communication apparatuses share super-resolution capability information to determine a super-resolution region based on an optimal sensing resolution, allowing efficient super-resolution sensing within that region to reduce computational load while maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If super-resolution sensing is performed over the entire parameter search space, then sensing accuracy is improved, but computational complexity increases enormously and real-time performance deteriorates
Solution Approach 1:
The patent divides the entire parameter search space into multiple candidate regions based on preliminary detection results. Instead of performing super-resolution sensing across the full space, the system segments the search area and focuses computational resources only on promising candidate regions, thereby maintaining sensing accuracy while dramatically reducing computational complexity
Solution Approach 2:
The patent applies super-resolution sensing selectively to specific local regions (candidate regions) rather than uniformly across the entire parameter space. By concentrating computational effort on locally identified areas of interest, the system achieves high sensing accuracy where needed while avoiding unnecessary computations in other areas, thus resolving the contradiction between accuracy and complexity
2Measurement precision
If super-resolution sensing is performed over the entire parameter search space, then sensing accuracy is improved, but real-time performance deteriorates
Solution Approach 1:
The patent segments the parameter search space into candidate regions using preliminary detection, enabling the system to perform super-resolution sensing only on relevant portions. This segmentation approach maintains high sensing accuracy while reducing overall computation time, thereby improving real-time performance
Solution Approach 2:
The patent performs preliminary detection to identify candidate regions before executing super-resolution sensing. This preliminary action narrows down the search space in advance, allowing the main super-resolution process to focus only on promising areas, thus achieving both high accuracy and real-time performance by avoiding unnecessary computations
3Measurement precision
If comprehensive parameter search is performed, then sensing resolution is improved, but operation complexity increases
Solution Approach 1:
The patent segments the comprehensive parameter search into targeted candidate regions based on preliminary detection results. By dividing the search space and focusing super-resolution sensing only on identified candidate regions, the system achieves high sensing resolution while significantly reducing operational complexity compared to exhaustive search
Solution Approach 2:
The patent applies high-resolution sensing selectively to local candidate regions rather than uniformly across all parameters. This localized approach maintains sensing resolution in critical areas while reducing overall operational complexity by avoiding exhaustive search throughout the entire parameter space
Data Source
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AI summary
This application provides a sensing method and an apparatus, to reduce a computational amount of a communication system, relating to the field of wireless communication technologies. In the method, a first communication apparatus receives super-resolution capability information from i second communication apparatuses, where the super-resolution capability information indicates sensing resolution of the second communication apparatus, and i is an integer greater than or equal to 2. The first communication apparatus obtains information about a super-resolution region, where the super-resolution region is used by the i second communication apparatuses to perform super-resolution sensing, and the super-resolution region is determined by a third communication apparatus with optimal sensing resolution in the i second communication apparatuses. The first communication apparatus sends the information about the super-resolution region. Based on the foregoing solution, the first communication apparatus may determine the information about the super-resolution region, so that the second communication apparatus may perform super-resolution sensing in the super-resolution region, to reduce operation complexity and improve sensing efficiency while ensuring sensing accuracy as much as possible.