Clock Synchronization in Wireless Sensor Networks
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Solution Overview
Problem
Existing wireless sensors in body area networks face challenges in reducing power consumption and complexity while maintaining accurate data transmission of vital signs, particularly in synchronizing clocks across devices to ensure reliable communication and data analysis.
Innovation Solution
The method involves a clock synchronization process where a first apparatus transmits a clock synchronization signal to a second apparatus, receives packets of samples indicative of an input over time, and generates a second set of samples based on the first set of samples corresponding to the synchronized clock, enabling efficient data processing and communication in wireless sensor networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wireless sensors perform local data processing and clock synchronization, then data transmission accuracy is improved, but power consumption increases
Solution Approach 1:
The patent segments the processing functions between wireless sensors and a central collector. Sensors perform only sampling and local processing of their own data, while the collector performs centralized clock synchronization and coordinated processing across all sensors. This segmentation allows accurate data processing without requiring each sensor to consume high power for full synchronization functions.
Solution Approach 2:
The patent introduces a collector as an intermediary device that centralizes the clock synchronization function. Instead of each sensor directly synchronizing with every other sensor (which would consume high power), the collector acts as a mediator that receives data from all sensors and performs centralized time alignment, reducing the power consumption burden on individual battery-powered sensors.
2Device complexity
If wireless sensors implement distributed processing, then system complexity is reduced, but clock synchronization difficulty increases
Solution Approach 1:
The collector serves as an intermediary that centralizes the complex clock synchronization task. All sensors synchronize their clocks with the collector rather than with each other, which simplifies the synchronization protocol and reduces the difficulty of maintaining time coherence across the distributed network while keeping overall system complexity low.
Solution Approach 2:
Each sensor independently performs sampling and local data processing without requiring complex inter-sensor coordination. The sensors autonomously manage their own data acquisition and transmit to the collector, which handles the time synchronization service for all. This self-service approach reduces both system complexity and synchronization difficulty.
3Reliability
If wireless sensors transmit more frequent data packets, then data transmission reliability is improved, but power consumption increases
Solution Approach 1:
The patent implements periodic sampling at the sensors with coordinated time intervals through centralized clock synchronization. Data transmission occurs at regular, synchronized intervals rather than continuously or asynchronously, which improves transmission reliability through predictable timing while reducing power consumption compared to continuous transmission modes.
Data Source
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AI summary
Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications.