LDPC List Decoding Using Parity-Bit Extension and LLR Ranking
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently decoding low-density parity-check (LDPC) codes, particularly in high-speed data transmission and storage, where errors can render data unusable, and existing decoders may not operate efficiently at different coding rates required by modern wireless standards like New Radio (NR).
Innovation Solution
The method involves receiving log-likelihood ratios (LLRs) corresponding to bits of a code word, selecting parity bits to extend the code word, generating sets of LLRs for all possible combinations of parity bit values, and decoding these sets to generate candidate messages, with one message selected based on reliability metrics for accurate decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If list decoding is used to improve error correction capability, then reliability is improved, but device complexity increases due to generating and evaluating multiple candidate messages
Solution Approach 1:
The decoding process is segmented into distinct stages: generating candidate messages by extending the code word with parity bits, decoding each candidate, evaluating reliability metrics, and selecting the best candidate. This segmentation allows the complex list decoding task to be broken down into manageable steps, improving implementability while maintaining error correction capability.
Solution Approach 2:
The code word is preliminarily extended with parity bits before decoding to create multiple candidate messages. This preliminary action prepares the candidates in advance with all necessary information, so that during the evaluation phase, only reliability metrics need to be computed and compared, reducing the overall computational burden during the critical selection phase.
2Manufacturing precision
If multiple candidate messages are generated and decoded to improve decoding accuracy, then manufacturing precision is improved, but productivity decreases due to increased processing time
Solution Approach 1:
Instead of generating and fully decoding all possible candidate messages (excessive action), the method generates a limited list of candidate messages by extending the code word with a specific number of parity bits. This partial action approach achieves sufficient decoding accuracy for practical applications while avoiding the prohibitive computational cost of exhaustive search, thus balancing accuracy with decoding speed.
3Reliability
If the code word is extended with parity bits to generate multiple candidates, then reliability is improved, but loss of time increases due to additional processing steps
Solution Approach 1:
The method changes the parameter of code word length by extending it with a controlled number of parity bits to create multiple candidate messages. By carefully selecting the number of parity bits added, the system achieves improved decoding reliability through multiple candidates while controlling the time overhead, as the extension operation is computationally efficient compared to full decoding of all possible candidates.
Data Source
AI summary
Certain aspects of the present disclosure generally relate to methods and apparatus for decoding low density parity check (LDPC) codes, and more particularly to an efficient list decoder for list decoding low density parity check (LDPC) codes.