Trellis-Assisted Bit-Flipping Decoder for Irregular LDPC Codes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Bit flipping (BF) decoders struggle with low error correction capability and inefficiency in handling irregular low-density parity-check (LDPC) codes, leading to prolonged decoding times or failure in correcting small error sets, while min-sum (MS) decoders are slow and costly in terms of power and chip area.
Innovation Solution
A trellis-assisted BF decoder is used to enhance error correction by concurrently executing multiple trellis decoders to resolve unsatisfied check nodes, improving decoding efficiency without additional latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If bit flipping (BF) decoding is used for LDPC code decoding, then decoding speed is improved, but error correction capability deteriorates
Solution Approach 1:
The decoding process is segmented into two distinct parts: a BF decoder that handles the majority of decoding tasks at high speed, and a trellis decoder that specifically handles the remaining unsatisfied check nodes. This segmentation allows each decoder to operate in its optimal performance regime, with the BF decoder providing speed and the trellis decoder providing enhanced error correction capability for difficult cases.
Solution Approach 2:
The trellis decoder acts as an intermediary that receives unsatisfied check node information from the BF decoder and provides refined bit value determinations back to the BF decoder. This intermediary role allows the system to leverage both decoders' strengths without requiring the BF decoder to handle all error correction tasks alone.
2Reliability
If irregular LDPC codes are used to improve MS decoder performance, then error correction capability is improved, but BF decoder performance deteriorates
Solution Approach 1:
The system applies different decoding strategies to different parts of the code structure. The BF decoder handles variable nodes with sufficient information locally, while the trellis decoder provides enhanced processing for specific unsatisfied check nodes. This local quality approach allows irregular codes to maintain their error correction advantages while the BF decoder continues to operate efficiently on suitable portions of the decoding task.
3Reliability
If more complex decoding algorithms are used to improve error correction capability, then reliability is improved, but computation cost increases
Solution Approach 1:
Instead of applying the computationally intensive trellis decoding algorithm to all check nodes, the system applies it only to the subset of unsatisfied check nodes that remain after BF decoding. This partial action approach provides the necessary error correction enhancement while minimizing the additional computation cost and power consumption associated with the more complex algorithm.
Data Source
AI summary
Techniques related to improving the error correction performance of a bit-flipping (BF) decoder for decoding a codeword using one or more trellis decoders are described. In some examples, the BF decoder can identify a set of unsatisfied check nodes among a set of check nodes that can be decoded using a trellis decoder. The trellis decoder can perform trellis decoding on the set of unsatisfied check nodes and variable nodes connected to the set of unsatisfied check nodes to determine bit values of the variable nodes to resolve the set of unsatisfied check nodes identified by the BF decoding. The BF decoder can use the bit values of the variable nodes determined by the trellis decoding in a next iteration of the BF decoding to decode the codeword.