Iterative GRAND Decoding for Bursty Channel Error Correction
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Solution Overview
Problem
Existing GRAND decoding methods become computationally unfeasible with two or more errors per codeword, and they struggle to efficiently handle bursty error channels due to increased complexity in noise guessing and error correction.
Innovation Solution
The proposed method iteratively applies GRAND decoding and burst error discovery, deinterleaving and re-interleaving codewords to identify and correct errors, and uses a less complex GRAND variant for single-error correction to reduce computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GRAND decoding is applied to correct two or more errors per codeword, then error correction capability is improved, but computational complexity becomes unfeasible
Solution Approach 1:
The patent segments the error correction process into two distinct stages: first applying GRAND decoding to correct single errors, then applying MP decoding to handle remaining multiple errors. This segmentation allows each decoding method to operate within its optimal complexity range, avoiding the unfeasible computational burden of applying GRAND to multiple errors directly.
Solution Approach 2:
The patent applies GRAND decoding partially - only for single-error correction - rather than attempting to use it for all error types. By limiting GRAND's application to cases where it remains computationally feasible (single errors) and using it excessively for only those specific cases, the system achieves optimal balance between correction capability and complexity.
2Reliability
If traditional MP decoding is used for bursty error channels, then error correction is achieved, but computational complexity increases significantly
Solution Approach 1:
The patent performs preliminary single-error correction using GRAND decoding before applying MP decoding for bursty errors. This preliminary action reduces the number of errors that MP decoding must handle, thereby significantly reducing its computational complexity while maintaining overall error correction capability.
Solution Approach 2:
The patent introduces GRAND decoding as an intermediary step between reception and MP decoding. This intermediary performs initial error correction, simplifying the subsequent MP decoding task and reducing its computational burden while handling bursty channel conditions effectively.
3Reliability
If iterative GRAND and burst error discovery is applied, then multiple errors are corrected, but the number of deinterleaving and re-interleaving operations increases complexity
Solution Approach 1:
The patent employs iterative feedback where the results of GRAND decoding inform subsequent burst error discovery operations. The feedback loop allows the system to identify and correct multiple errors through coordinated iterations of GRAND and burst discovery, managing complexity through intelligent feedback-driven operation rather than exhaustive processing.
Data Source
AI summary
A node performs iterative GRAND-burst discovery by generating a first stream of candidate codewords by deinterleaving a first stream of bits. The node determines a validity of a first bit of a first candidate codeword in the first stream of candidate codewords using GRAND, generates a second stream of bits by re-interleaving the first stream of candidate codewords, and determines whether a second bit in the second stream of bits is a potential error bit based on a location of the second bit relative to a location of the first bit in the second stream of bits and the validity of the first bit. The node generates a second stream of candidate codewords by deinterleaving the second stream of bits, and changes a value of a third bit of the second stream of candidate codewords based on whether the second bit is a potential error bit.