Multi-Carrier Grip Detection for 5G Handsets
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Solution Overview
Problem
Current grip detection algorithms for 5G millimeter-wave mobile handsets are ineffective in GNSS use cases due to hand blockage, leading to significant signal loss and inability to transmit in specified frequency bands, as they rely on device transmissions, which are not applicable for GNSS protocols.
Innovation Solution
Implementing multi-carrier frequency grip detection using carrier-to-noise density ratio (C/NO), WiFi received signal strength indicator (RSSI), and Bluetooth RSSI, along with motion context and RF signal context, to detect grip conditions and adjust antenna tuning accordingly, even in the absence of device transmissions, for GNSS use cases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If device transmissions are used for grip detection, then grip detection accuracy is improved, but the method becomes inapplicable for GNSS use cases
Solution Approach 1:
The patent uses third-party transmitted signals (WiFi, Bluetooth, cellular) as intermediaries to detect grip conditions. Instead of relying on device transmissions, the system monitors signals from external sources that pass through or near the device, allowing grip detection without requiring the device to transmit itself.
Solution Approach 2:
The system employs multiple signal sources (WiFi RSSI, Bluetooth RSSI, cellular C/NO) to perform grip detection, making the solution universally applicable across different use cases including GNSS. This multi-functionality allows the same detection mechanism to work whether the device is transmitting or receiving signals.
2Reliability
If antenna module placement is optimized for hand grip mitigation, then signal loss is reduced, but device complexity increases
Solution Approach 1:
The patent implements dynamic antenna tuning that adjusts antenna characteristics in real-time based on detected grip conditions. Rather than relying solely on fixed optimized placement, the system continuously adapts antenna parameters to compensate for hand blockage, maintaining signal stability without requiring overly complex static designs.
Solution Approach 2:
The system uses grip detection feedback to dynamically adjust antenna tuning parameters. The detected grip condition information feeds back to the antenna control mechanism, allowing the antenna to self-optimize its performance based on actual usage conditions, reducing the need for pre-engineered complex placements.
3Reliability
If beamforming codebook is designed considering hand grip profiles, then antenna gain loss is reduced, but design complexity increases
Solution Approach 1:
The patent pre-calculates and stores multiple beamforming codebooks corresponding to different grip conditions. Rather than designing a single complex codebook that tries to handle all scenarios, the system prepares multiple simpler codebooks in advance for different grip profiles, selecting the appropriate one based on real-time detection.
Solution Approach 2:
The system dynamically selects and switches between different beamforming codebooks based on detected grip conditions. This dynamic adaptation allows the beamforming system to maintain optimal performance across various hand grip scenarios without requiring a single overly complex codebook design.
Data Source
AI summary
Systems and methods for multi-carrier frequency grip detection are described. For example, a method may include determining a first signal strength of a first signal received using a first antenna from a source device; determining a second signal strength of a second signal received using a second antenna from the source device; comparing the first signal strength with the second signal strength; and detecting a detuned condition for a device including the first antenna and the second antenna based on the comparison of the first signal strength with the second signal strength.