Polar Code Decoding With Trust Symbols and Hard Decisions
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Solution Overview
Problem
Polar codes face challenges in decoding efficiency, particularly with limited code lengths and in wireless communications, where successive cancellation decoding methods struggle to achieve optimal error correction performance compared to other codes like LDPC and Turbo codes.
Innovation Solution
The implementation of multiple-symbol combination based decoding for polar codes, which involves determining trust and doubt symbol positions and performing hard decisions based on reliability, reduces decoding complexity and improves error performance by exploiting symbol reliabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If successive cancellation decoding is used for polar codes, then decoding complexity is reduced, but error correction performance deteriorates compared to LDPC and Turbo codes
Solution Approach 1:
The decoding process is segmented into multiple stages with different decoding strategies. Trust symbols are decoded using simple hard decisions while doubt symbols undergo more complex processing, dividing the decoding task into manageable segments that balance complexity and performance
Solution Approach 2:
Different decoding qualities are applied to different symbol positions based on their reliability characteristics. Trust symbols receive basic hard decision decoding while doubt symbols receive enhanced processing, optimizing the overall error correction performance without uniformly increasing complexity across all symbols
2Productivity
If code length is limited for wireless communications, then transmission efficiency is improved, but error correction performance of polar codes deteriorates
Solution Approach 1:
The decoding approach changes parameters dynamically based on symbol reliability information. By identifying trust versus doubt symbols and applying appropriate decoding strategies, the system achieves better error correction performance at limited code lengths without sacrificing transmission efficiency
3Speed
If hard decision is performed at intermediate stages of decoding, then decoding speed is improved, but decoding accuracy deteriorates
Solution Approach 1:
Hard decisions are applied locally only to trust symbols at intermediate stages, while doubt symbols continue to receive soft decision processing. This selective application maintains decoding speed for reliable symbols while preserving accuracy for uncertain symbols
Data Source
AI summary
The present disclosure relates to multiple-symbol combination based decoding for general polar codes. Multiple-symbol combination based decoding of a received word that is based on a codeword involves determining whether all nodes at an intermediate stage of the multiple-symbol combination based decoding, which provide their outputs as inputs to a subset of nodes at a next stage of the multi-symbol combination based decoding, are associated with trust symbols in the received word that have a higher reliability of being successfully decoded than doubt symbols in the received word. A hard decision is performed in response to a positive determination.