Subword LDPC Coding With Different Matrices for Sequential Error Reduction
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Solution Overview
Problem
Existing communication systems using low-density parity check (LDPC) coding face challenges in reducing sequential bit errors in extrinsic codewords, which can inhibit proper detection and correction of channel errors, particularly when using identical interleaving/deinterleaving algorithms and encoder/decoder matrices in subword-processing paths.
Innovation Solution
Implementing different interleaving/deinterleaving algorithms and encoder/decoder matrices in subword-processing paths to increase the minimum distance between bit errors and reduce sequential bit errors in extrinsic codewords, thereby enhancing error correction capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If identical interleaving/deinterleving algorithms and encoder/decoder matrices are used in subword-processing paths, then system complexity is reduced and ease of manufacture is improved, but sequential bit errors occur in extrinsic codewords which reduces reliability
Solution Approach 1:
The patent applies local quality by using different encoder/decoder matrices for different subword-processing paths. Specifically, first subword encoders use a first encoder matrix while second subword encoders use a second encoder matrix, and similarly for decoders. This local differentiation in matrix selection across processing paths increases the minimum distance between bit errors in extrinsic codewords, thereby reducing sequential bit errors and improving overall reliability without requiring all paths to use different complex structures.
Solution Approach 2:
The patent segments the encoding and decoding processes into multiple independent subword-processing paths, each handling specific subwords. By dividing the overall processing into separate paths with dedicated encoders and decoders, the system can apply different matrices to different segments (subwords) while maintaining parallel processing efficiency. This segmentation allows the introduction of matrix variety to reduce sequential errors without fundamentally changing the parallel architecture.
2Reliability
If different encoder/decoder matrices are used in subword-processing paths, then sequential bit errors are reduced and reliability is improved, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent employs parameter changes by systematically varying the encoder and decoder matrices used in different subword-processing paths. Instead of using identical matrices throughout, the system changes the matrix parameters (different generator matrices for encoding, different parity-check matrices for decoding) across paths. This parameter variation increases the minimum Hamming distance between error patterns in extrinsic codewords, making sequential bit errors less likely while maintaining a structured approach that facilitates implementation.
3Productivity
If parallel processing is used with multiple subword encoders/decoders, then processing speed and productivity are improved, but the occurrence of sequential bit errors increases when identical matrices are used
Solution Approach 1:
The patent resolves the contradiction between parallel processing and sequential errors by applying local quality differentiation to the parallel paths. Each parallel subword-processing path uses locally optimized different matrices rather than identical matrices, ensuring that while processing occurs in parallel for high productivity, the local matrix variation in each path prevents the generation of sequential bit errors in extrinsic codewords.
Data Source
AI summary
In a communications system that demultiplexes user data words into multiple sub-words for encoding and decoding within different subword-processing paths, the minimum distance between bit errors in an extrinsic codeword can be increased by having corresponding subword encoders/decoders in the different subword-processing paths perform subword encoding/decoding with different encoder/decoder matrices.