Channel Coding With Value-Based Hamming Distance Mapping
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Solution Overview
Problem
In digital wireless communication, especially in wireless earsets transmitting multimedia data without source coding, the existing channel coding methods result in high bit error rates due to similar Hamming distances between channel codes, which do not effectively differentiate between the significance of Most Significant Bits (MSBs) and Least Significant Bits (LSBs, leading to errors during transmission.
Innovation Solution
A method of channel coding that quantizes analog data into digital data, allocates channel codes such that the Hamming distance between pairs of channel codes is proportional to the difference in analog values, reducing bit error rates by prioritizing error correction for more significant bits and minimizing signal degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If general channel coding method is used with similar Hamming distances between channel codes, then device complexity is reduced, but bit error rate increases due to inability to differentiate between significant and insignificant bits
Solution Approach 1:
The patent applies local quality by differentiating the treatment of different bit positions within the channel code. Specifically, bits corresponding to MSBs are assigned different Hamming distance characteristics compared to bits corresponding to LSBs. This allows the system to provide enhanced error protection locally at critical bit positions without increasing overall system complexity, thereby reducing bit error rates for significant bits while maintaining a relatively simple channel coding configuration.
2Reliability
If channel codes are designed with varying Hamming distances to protect significant bits, then bit error rate for important bits is reduced, but device complexity increases
Solution Approach 1:
The patent implements parameter changes by systematically varying the Hamming distance parameter across different bit positions within the channel code. The Hamming distance is increased for bit positions corresponding to MSBs and decreased for bit positions corresponding to LSBs. This parameter differentiation allows the channel coding device to provide tailored error protection for significant bits, reducing their bit error rate while maintaining manageable device complexity through structured parameter variation.
Data Source
AI summary
A method of channel coding a digital communication system and a device using the same is provided. The method includes quantizing analog data to digital data, the digital data corresponding to a predetermined number of digital codes; allocating channel codes to the digital codes, as a Hamming distance between a pair of channel codes corresponding to any pair of the digital codes is proportional to a difference between analog values of the pair of the digital codes; and channel coding the digital data by using the channel codes which are allocated to the digital codes to generate channel coded digital data. Accordingly, digital data, such as multimedia digital data without source coding and the like, of which information significance is different may be effectively transmitted and received.