Silicon Laboratories had seven patents in internet of things during Q2 2024. The patents filed by Silicon Laboratories Inc in Q2 2024 focus on techniques for accurately determining channel usage for low power signals across various communication protocols, optimizing Bluetooth synchronization between devices, and enabling cooperative sharing of resources in IoT networks through a framework. These techniques aim to improve sensitivity, reduce false alarm rates, and enhance network performance by efficiently utilizing available resources. GlobalData’s report on Silicon Laboratories gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Silicon Laboratories had no grants in internet of things as a theme in Q2 2024.
Recent Patents
Application: Signal identification for multi-channel and multi-protocol communications (Patent ID: US20240187036A1)
The patent by Silicon Laboratories Inc. describes techniques for efficiently detecting data transmission across various communication protocols using random data packets. The methods aim to enhance sensitivity and reduce false alarms by employing adaptive noise detection with an adjustable window size and cluster detection for specific protocols like BLE1M. The use of chip-based differentials and oversampled signals helps improve signal-to-noise ratio for Zigbee detection. The patent also outlines a method for detecting data in an oversampled received signal by correlating frequency deviation samples with predetermined chip sequences and determining the detection approach based on correlation values and threshold levels.
The patent further details a receiver equipped with a signal detection circuit that can perform one-symbol or two-symbol detection based on correlation values and threshold levels. The receiver includes a phase-to-frequency conversion circuit for generating frequency deviation samples and a clipping circuit for filtering the samples using a weighting function. Additionally, the patent discloses a method for detecting data in an oversampled received signal by converting phase samples to frequency samples, filtering the window with chip-based frequency deviation samples, and utilizing correlation with Direct Sequence Spread Spectrum symbols for detection. The method also involves generating clipped frequency deviation samples using a weighting function based on predetermined thresholds.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
