Symbol Detection Threshold Determination for DC Variation
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Solution Overview
Problem
In amplitude-based modulation and demodulation communication systems, determining an optimal detection threshold for symbol detection is challenging, especially in reducing bit error rate (BER) and minimizing power consumption, as existing methods fail to effectively account for changes in the direct current (DC) component, leading to errors in symbol detection.
Innovation Solution
A method and apparatus that determine the detection threshold for symbol detection by using the most previously input sample value and the result of detecting the most previous symbol, setting representative values based on information in the packet header, and adjusting for changes in the DC component by alternating signal patterns, thereby minimizing BER.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed threshold is used for symbol detection, then the circuit structure is simple, but the bit error rate increases due to DC component variations
Solution Approach 1:
The patent applies preliminary action by using the most previously input sample value and the result of detecting the most previous symbol to pre-determine the threshold before current symbol detection. This allows the threshold to be adaptively set based on historical data, reducing bit error rate caused by DC component variations without requiring complex real-time adjustment mechanisms
Solution Approach 2:
The patent implements feedback by utilizing the result of detecting the most previous symbol to influence the threshold determination for current symbol detection. This feedback mechanism allows the system to adapt to DC component variations dynamically, improving reliability while maintaining relatively simple circuit structure
2Measurement precision
If adaptive threshold adjustment is implemented, then symbol detection accuracy improves, but power consumption increases
Solution Approach 1:
The patent uses preliminary action by determining the threshold in advance based on the most previously input sample value and previous symbol detection result, rather than performing complex real-time adaptive adjustments. This reduces computational overhead and power consumption while maintaining high symbol detection accuracy
Solution Approach 2:
The system applies self-service by using its own historical detection results and previous sample values to automatically determine the threshold, eliminating the need for external calibration or complex adaptive algorithms that would increase power consumption
Data Source
AI summary
A method of determining a threshold for symbol detection, includes receiving a most previously input sample value and a result of detecting a most previous symbol, and determining the threshold for the symbol detection of a currently input sample value based on the most previously input sample value and the result of detecting the most previous symbol.