Wakeup Pattern Correlation for Low-Power Multi-Stream Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
RFID systems for wireless keyless entry systems face challenges in power optimization and area efficiency due to continuous monitoring of radio frequency signals for wakeup patterns, which leads to high power consumption and resource inefficiency.
Innovation Solution
A power and area-optimized detector technology that transitions a microcontroller from a low-power mode to a high-power mode based on detected data streams by correlating wakeup pattern bits with multiple data streams, using a plurality of data packet layers, index registers, and comparators to generate a trigger condition, enabling efficient power management and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RFID transponders continuously monitor received radio frequency signals for wakeup patterns, then wakeup pattern detection reliability is improved, but power consumption increases
Solution Approach 1:
The system transitions the microcontroller between low-power sleep mode and active processing mode based on detected trigger conditions. The continuous monitoring is performed only by minimal circuitry, while full processing occurs periodically when wake patterns are detected, rather than maintaining full power continuously.
Solution Approach 2:
The monitoring function is segmented into two parts: a minimal always-on monitoring circuit that detects trigger conditions, and a full processing microcontroller that activates only when needed. This segmentation allows reliable detection while minimizing power consumption during idle periods.
2Adaptability or versatility
If multiple data streams are monitored simultaneously, then data stream processing capability is improved, but device complexity increases
Solution Approach 1:
Multiple data streams are merged into a single processing pipeline. The system monitors multiple streams simultaneously but processes them through shared resources (comparators, trigger logic, microcontroller) rather than dedicating separate processing paths to each stream, reducing overall device complexity.
Solution Approach 2:
The monitoring and processing components are designed to handle multiple data streams universally. The same comparators, trigger conditions, and microcontroller processing capabilities are applied across all N data streams, allowing versatile multi-stream processing without proportionally increasing complexity for each additional stream.
Data Source
AI summary
Described herein is a technology for a wakeup pattern-data stream correlation by a detector to provide a trigger condition for a microcontroller in a wakeup receiver (WuRX). For example, the detector includes a data packet layer with a plurality of index registers that are updated through sampling of data streams. A sample clock is coupled to each of the plurality of index registers to independently activate each of the plurality of index registers. A shared comparator will then compare the updated plurality of index registers to corresponding shift registers that are initialized with rotating wakeup pattern bits. Based upon a number of matching results, the detector generates a triggering signal that facilitates a low-power operating mode to a high-power operating mode change.