Iterative LDPC Decoding with Soft Information to Limit Error Propagation
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Solution Overview
Problem
Iterative error detection schemes in magnetic hard disk drives often cause error propagation and have an unacceptable error floor, along with high complexity.
Innovation Solution
The implementation of an iterative decoder that performs multiple decoding iterations using soft decision post processors and minimum sum LDPC code decoders, which generates soft information and extrinsic information to correct errors with reduced error propagation and controllable error floor, while maintaining low complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If iterative error detection schemes are used in magnetic hard disk drives, then error correction capability is improved, but error propagation increases and error floor becomes unacceptable
Solution Approach 1:
The patent converts the harmful effect of error propagation into a beneficial feature by using the extrinsic information from unreliable bits to improve the decoding of reliable bits. The min-sum decoding algorithm processes extrinsic information in a way that transforms potential error propagation into enhanced error correction capability, where the information from previously decoded bits (even if potentially erroneous) is used to improve subsequent decoding iterations.
2Reliability
If iterative error detection schemes are used in magnetic hard disk drives, then error correction capability is improved, but complexity increases
Solution Approach 1:
The patent segments the decoding process into distinct functional blocks: a soft decision post processor that generates soft information, and a min-sum decoder that processes extrinsic information. This segmentation allows each block to perform a specialized function with optimized complexity, rather than using a single complex iterative decoder. The soft information and extrinsic information are processed separately in different iterations, reducing overall system complexity.
3Reliability
If soft decision decoding is used to exploit bit reliability, then error correction performance is improved, but computational complexity increases
Solution Approach 1:
The patent changes the parameter representation from hard decisions (binary 0/1) to soft information (log-likelihood ratios). By representing bit reliability as continuous values rather than discrete binary states, the system can exploit bit reliability information more effectively. The min-sum decoding algorithm operates on these soft parameters, allowing the system to achieve better error correction performance by processing reliability information in a computationally efficient manner.
Data Source
AI summary
Techniques are provided for iteratively decoding data recorded on a data storage device. An iterative decoder decodes the data using multiple decoding iterations to correct errors. In multiple iterations of the iterative decoder, a post processing block generates soft information, and a decoder applies a minimum sum decoding algorithm to a low density parity check (LDPC) code to generate extrinsic information based on the soft information and updated soft information.