Adaptive CSI Packet Transmission for Presence Detection
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Solution Overview
Problem
Current technologies face challenges in accurately detecting presence in wireless networks using Channel State Information (CSI) packets, particularly in dynamically adjusting CSI packet transmission periods and resources to minimize interference with data packets while maintaining presence detection sensitivity.
Innovation Solution
The solution involves a system that combines metrics-based and machine-learning models to predict presence by weighing confidence values from network and link parameter data, dynamically adjusting CSI packet transmission periods and resources based on link conditions, and using decision trees to determine optimal CSI packet periods and resource configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CSI packet transmission frequency is increased to improve presence detection sensitivity, then presence detection accuracy is improved, but interference with data packets increases
Solution Approach 1:
The system dynamically adjusts the CSI packet transmission period based on detected presence status. When presence is detected, the transmission period is shortened to increase detection sensitivity. When no presence is detected, the transmission period is extended to reduce interference with data packets. This dynamic adjustment resolves the contradiction by making the transmission frequency adaptive rather than fixed.
Solution Approach 2:
The patent changes the transmission period parameter of CSI packets based on presence detection results. The system monitors presence status and adjusts the time interval between CSI packet transmissions accordingly, changing this key parameter to balance between detection accuracy and interference minimization.
2Measurement precision
If CSI packet transmission period is shortened to maintain presence detection sensitivity, then presence detection accuracy is improved, but network resource consumption increases
Solution Approach 1:
The system dynamically adjusts the CSI packet transmission period based on detected presence status. When presence is detected, the transmission period is shortened to increase detection sensitivity. When no presence is detected, the transmission period is extended to reduce interference with data packets. This dynamic adjustment resolves the contradiction by making the transmission frequency adaptive rather than fixed.
Solution Approach 2:
The patent implements periodic transmission of CSI packets with variable periods. Instead of continuous transmission, the system uses periodic transmissions where the period length is adjusted based on presence detection needs, reducing overall resource consumption while maintaining detection capability when needed.
3Reliability
If CSI packet transmission resources are increased to improve presence detection reliability, then presence detection accuracy is improved, but interference with data packets increases
Solution Approach 1:
The system dynamically adjusts the CSI packet transmission period based on detected presence status. When presence is detected, the transmission period is shortened to increase detection sensitivity. When no presence is detected, the transmission period is extended to reduce interference with data packets. This dynamic adjustment resolves the contradiction by making the transmission frequency adaptive rather than fixed.
Solution Approach 2:
The patent extracts CSI packet transmissions from continuous operation and implements them only when necessary for presence detection. By taking out the unnecessary transmissions and keeping only the essential ones, the system maintains detection reliability while minimizing interference with data packet transmissions.
Data Source
AI summary
Techniques for presence detection are described. In an example, system receives, from a first device connected with a computer network that is associated with a location, a first value of a first parameter associated with a link between the first device and a second device. The system determines, using a first prediction model and the first value, a first likelihood of presence at the location. The first prediction model is configured based at least in part on outputs of a second prediction model that uses a second parameter associated with the computer network. The system determines whether the presence is detected at the location based at least in part on the first likelihood.


