Linear Block Code Encoding Matrix for Higher Minimum Distance
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Solution Overview
Problem
The error correction performance of linear block codes in telecommunication systems, such as those used in LTE, is limited by their small minimum code distance, which affects encoding systems like PUSCH in LTE and WCDMA.
Innovation Solution
A method and apparatus for generating linear block codes with improved minimum distance characteristics by generating specific sequences, displacing and permuting rows and columns, and using these to create an encoding matrix that enhances error correction performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional linear block codes are used in telecommunication systems, then the encoding process is simple, but the error correction performance is limited due to small minimum code distance
Solution Approach 1:
The encoding matrix is segmented into multiple blocks, where each block corresponds to a specific code distance level. This segmentation allows the system to achieve better error correction performance by organizing the code structure into manageable segments with optimized distance properties, resolving the contradiction between reliability and complexity.
Solution Approach 2:
The patent introduces a new dimension to the code structure by creating encoding matrices with extended dimensions that provide better code distance properties. This dimensional expansion allows achieving improved error correction performance without proportionally increasing operational complexity, as the additional dimensions are structured to provide systematic benefits.
2Reliability
If the minimum code distance is increased to improve error correction performance, then the reliability improves, but the encoding matrix becomes more complex
Solution Approach 1:
The patent systematically changes key parameters of the encoding matrix including dimensions, code distance levels, and block structures to achieve optimized error correction performance. By carefully selecting and adjusting these parameters, the system achieves better minimum code distance while controlling matrix complexity through structured parameter relationships.
Solution Approach 2:
The encoding matrix is constructed as a composite structure combining multiple sub-matrices with different properties. This composite approach allows achieving superior code distance characteristics by integrating multiple structural elements, each contributing specific properties that collectively improve reliability without linearly increasing overall complexity.
3Reliability
If a larger encoding matrix is used to achieve better code distance, then the error correction capability improves, but the encoding complexity increases
Solution Approach 1:
Large encoding matrices are divided into smaller segmented blocks that can be processed independently or in parallel. This segmentation reduces the computational burden of encoding operations while maintaining the overall error correction capability, as each segment contributes to the total code distance without requiring full-matrix operations.
Solution Approach 2:
The encoding matrix structure is designed to be dynamically adaptable, allowing the system to select appropriate matrix sizes and configurations based on specific communication conditions. This dynamic approach enables achieving better error correction capability when needed while reducing encoding complexity under normal conditions through selective matrix usage.
Data Source
AI summary
A method and apparatus for encoding based on a linear block code, and a method and apparatus for generating a linear block code are provided. The method for encoding based on a linear block code includes: generating a linear block code; and encoding an information sequence with an encoding matrix of the linear block code to obtain a bit stream sequence. The linear block codes have a good minimum distance characteristic, so that the error correction performance is improved.