2.4 GHz CSI Sensing Engine Channel Diversity
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Solution Overview
Problem
CSI-based motion detection in the 2.4 GHz band faces challenges such as bandwidth limitations, interference, and congestion, which affect the performance of wireless devices that only support this frequency band for cost and power consumption reasons.
Innovation Solution
The implementation of a 2.4 GHz CSI sensing engine that enhances sampling rate, provides channel diversity through smart channel switching and time division, and employs interference mitigation using an ACI filter to rank channel subcarrier indexes, thereby improving detection accuracy despite congestion and interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If CSI-based motion detection is implemented in the 2.4 GHz band, then cost and power consumption are reduced, but bandwidth limitations, interference, and congestion affect detection performance
Solution Approach 1:
The patent segments the 2.4 GHz band into multiple subchannels and selectively activates only the subchannels with the best signal quality for CSI sampling. This segmentation allows the system to operate in the cost-effective 2.4 GHz band while mitigating interference by using only the cleanest frequency segments, thus maintaining detection performance despite the band's inherent congestion.
Solution Approach 2:
The system dynamically switches between different 2.4 GHz subchannels based on real-time signal quality assessment. By continuously monitoring and adapting to changing channel conditions, the system maintains reliable detection performance despite interference and congestion, while still operating in the low-power 2.4 GHz band.
2Measurement precision
If the sampling rate is increased to improve detection accuracy, then detection precision improves, but bandwidth consumption increases
Solution Approach 1:
The patent applies local quality by focusing sampling efforts only on the highest-quality subchannels within the 2.4 GHz band. Instead of uniformly sampling all subchannels at high rates, the system identifies and concentrates sampling resources on the 1-3 subchannels with the best signal-to-noise ratio, achieving high detection accuracy while minimizing total bandwidth consumption.
Solution Approach 2:
The system performs partial sampling by selecting only the most critical subchannels for detailed CSI analysis rather than sampling the entire frequency band. This partial action on the most informative subchannels provides sufficient detection accuracy without the excessive bandwidth consumption that would result from full-band high-rate sampling.
3Reliability
If channel diversity is provided through smart channel switching and time division, then detection reliability improves, but device complexity increases
Solution Approach 1:
The patent implements periodic channel quality assessment and subchannel selection, where the system periodically evaluates all 2.4 GHz subchannels and switches to the best available subchannels for sampling. This periodic approach provides channel diversity and maintains detection reliability while using simple, repeatable switching logic that doesn't significantly increase device complexity.
Solution Approach 2:
The system introduces an intermediary channel quality assessment mechanism that mediates between the available subchannels and the sampling process. This intermediary layer evaluates signal quality and makes switching decisions, providing channel diversity for reliable detection while keeping the actual switching logic simple and manageable.
Data Source
AI summary
Technologies directed to channel state information (CSI) sending in the 2.4 GHz band are described. A method includes receiving first CSI data representing channel properties of a first wireless channel used by first and wireless devices that operates in the 2.4 GHz band. The method receives second and third CSI data corresponding to second and third wireless channels. The method determines an inference probability of a motion or a non-motion condition in the geographical region based on an average probability of CSI samples from the first, second, and third CSI data.