Wearable Signal Decoding via Waveform Shaping and Interval Mapping
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Solution Overview
Problem
Conventional earphone communication systems require complex digital circuits for signal demodulation and decoding, leading to increased costs and complexity.
Innovation Solution
A method and apparatus that utilize a decoding algorithm to simplify the digital circuit structure by performing waveform shaping, acquiring time interval eigenvalues, and applying a mapping relation to decode signals, thereby eliminating the need for complex carrier recovery modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional carrier recovery modules and digital circuits are used for signal demodulation and decoding, then signal transmission reliability is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent extracts and removes the complex carrier recovery module from the signal processing system. Instead of using traditional carrier recovery circuits, the invention directly processes the modulated signal through waveform shaping and time interval analysis to achieve demodulation, thereby eliminating the disturbing complex component while maintaining decoding functionality
Solution Approach 2:
The patent replaces the mechanical/electrical carrier recovery system with a computational approach using waveform shaping algorithms and time interval eigenvalue analysis. This substitution transforms the physical circuit-based solution into a software/mathematics-based solution, reducing hardware complexity
2Reliability
If conventional carrier recovery modules and digital circuits are used for signal demodulation and decoding, then signal transmission reliability is improved, but manufacturing cost increases
Solution Approach 1:
The patent extracts and removes the complex carrier recovery module from the signal processing system. Instead of using traditional carrier recovery circuits, the invention directly processes the modulated signal through waveform shaping and time interval analysis to achieve demodulation, thereby eliminating the disturbing complex component while maintaining decoding functionality
Solution Approach 2:
The patent employs computationally efficient algorithms that can be implemented with lower-cost processors or even dedicated simple decoding circuits. The waveform shaping and time interval analysis methods require less sophisticated hardware compared to traditional carrier recovery systems, enabling cost-effective manufacturing
3Device complexity
If waveform shaping and time interval eigenvalue analysis are used for signal decoding, then device complexity is reduced, but signal processing precision requirements increase
Solution Approach 1:
The patent applies preliminary waveform shaping processing to the received signal before performing time interval analysis. This preprocessing step transforms the signal into a standardized form with clearly defined transitions, making subsequent time interval measurements more robust and less sensitive to noise, thereby reducing the precision burden on the final measurement stage
Solution Approach 2:
The patent uses the time interval eigenvalues obtained from waveform analysis as feedback to refine the decoding process. By analyzing the distribution and characteristics of multiple time intervals, the system can identify patterns and correct measurement variations, effectively compensating for precision limitations through statistical processing
Data Source
AI summary
The present disclosure discloses a method of transmitting a signal, a wearable communication device and a terminal device. The method includes: receiving, by a wearable communication device, a modulated wave signal transmitted by a terminal device; demodulating the modulated wave signal to obtain a to-be-decoded signal; performing a waveform shaping process on the to-be-decoded signal to obtain a square wave signal, where a high level in the square wave signal is configured to represent a first preset value, and a time interval is existed between two high levels corresponding to any two adjacent first preset values; acquiring time interval eigenvalues in the square wave signal; acquiring a one-to-one mapping relation of the interval eigenvalues and a plurality of coding sequences; and performing, according to the time interval eigenvalues and the mapping relation, a first decoding process and a second decoding process on the square wave signal to obtain original data.