Multilevel Bitwise Error Correction for Unequal Bit Reliability
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Solution Overview
Problem
Multi-level systems face inefficiencies and performance degradation due to the assumption of equal bit error probabilities in bitwise operations, which is not valid, leading to suboptimal error correction and reduced effectiveness of non-symbol bitwise error correcting codes.
Innovation Solution
Customized error correction power is applied to each bit in a multi-level system based on its individual probability of error, using different convolutional codes or encoding systems for each bit, and varying encryption or compression levels to optimize performance and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If equal error correction power is applied to all bits in multi-level systems, then the system maintains simplicity in error correction implementation, but the error correction effectiveness deteriorates because bits actually have different error probabilities
Solution Approach 1:
The patent applies different error correction powers to different bits based on their individual error probabilities. Specifically, bits with higher error probabilities receive stronger error correction, while bits with lower error probabilities receive weaker correction. This local differentiation optimizes error correction effectiveness without uniformly increasing system complexity.
Solution Approach 2:
The patent changes the error correction parameter (correction power) according to the error probability of each bit. By adjusting the correction power parameter dynamically based on bit characteristics, the system achieves optimized error correction while maintaining reasonable implementation complexity through parameterization rather than structural complexity.
2Reliability
If different error correction powers are applied to each bit based on its error probability, then the error correction effectiveness improves, but the system complexity increases due to multiple encoding systems
Solution Approach 1:
The patent implements local quality by assigning different error correction powers to different bits within the same data stream. Each bit position is analyzed for its error probability, and the corresponding error correction power is adjusted locally, rather than applying uniform correction across all bits. This approach improves reliability while keeping the overall system architecture relatively simple.
Solution Approach 2:
The patent introduces dynamic adjustment of error correction parameters based on the characteristics of each bit. The error correction power is not fixed but is dynamically determined by the error probability of each bit position. This dynamic approach allows the system to adapt to varying error conditions without requiring multiple static encoding systems.
3Productivity
If multi-level encoding is used to increase data transmission efficiency, then the productivity improves, but the error probability distribution becomes uneven across bits leading to suboptimal error correction
Solution Approach 1:
The patent addresses the non-uniform error distribution in multi-level encoding by applying local quality differentiation. Each bit position in the multi-level encoded data is evaluated for its specific error probability, and error correction is applied locally with appropriate power levels. This ensures that bits with higher error probabilities (which naturally occur in multi-level systems) receive enhanced correction while maintaining overall data transmission efficiency.
Solution Approach 2:
The patent changes the error correction parameters based on the position and characteristics of each bit within the multi-level encoded data structure. By adjusting the correction power parameter according to the error probability of each bit position, the system maintains high data transmission efficiency while achieving uniform error correction effectiveness across all bits.
Data Source
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AI summary
A system uses multi-level encoding where each symbol of a plurality of symbols represents more than one bit of information in a user data symbol stream for transfer using a multilevel transmission channel. The user data symbols are represented in a digital bitwise form such that each symbol is presented as a plurality of bits and each bit is subject to a different probability of error. An error correction procedure is applied based on the different error probability that is associated with each bit in the plurality. The channel can be configured to support a mosaic tile structure, each tile containing a channel symbol such that a selected tile has a collective error probability that is different from other tiles. Customized coding can be applied to the tile structure to allocate a selected amount of error correction power to the selected tile based on an overall available correction power.