Sub-Codeword Soft-Decision Decoding With Iteration Skipping
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Solution Overview
Problem
In high-speed optical transmission systems, soft-decision FEC decoding consumes excessive power due to unnecessary decoding iterations, leading to inefficient performance and high power consumption.
Innovation Solution
A decoding method that introduces a turn-off identifier for each sub-codeword to skip unnecessary soft decision decoding iterations based on valid hard decision results, reducing power consumption and improving decoding efficiency by storing and reusing valid hard decision results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If soft-decision FEC decoding is performed repeatedly to ensure decoding accuracy, then decoding reliability is improved, but power consumption increases significantly
Solution Approach 1:
The patent implements dynamic decoding by introducing a turn-off identifier that allows the decoder to adaptively skip iterations for sub-codewords that have already been successfully decoded. This creates a dynamic decoding process where the number of iterations varies per sub-codeword based on its decoding status, rather than uniformly iterating through all sub-codewords. The turn-off identifier acts as a dynamic control mechanism that adjusts the decoding behavior in real-time, enabling the system to maintain high reliability for successfully decoded sub-codewords while reducing power consumption by avoiding redundant iterations.
2Measurement precision
If multiple decoding iterations are performed to correct remaining bit errors, then decoding precision is improved, but unnecessary power consumption increases
Solution Approach 1:
The patent segments the codeword into multiple sub-codewords and applies different decoding strategies to each segment based on its individual decoding status. By dividing the overall decoding task into independent sub-tasks, the system can identify and stop decoding for segments that have been successfully decoded (using the turn-off identifier), while continuing to iterate on segments that still require error correction. This segmentation approach ensures decoding precision for problematic segments without wasting energy on already-successful segments.
Solution Approach 2:
The patent applies partial action by performing full multiple iterations only on sub-codewords that require error correction, while performing no iterations (skipping) on sub-codewords that have already been successfully decoded. This partial application of the iteration process avoids excessive action on already-decoded sub-codewords, thereby maintaining decoding precision where needed while eliminating unnecessary power consumption where not needed.
3Use of energy by moving object
If hard-decision FEC is used to reduce power consumption and complexity, then power consumption is reduced, but transmission system performance enhancement is smaller
Solution Approach 1:
The patent creates a dynamic hybrid decoding approach that combines elements of both hard-decision and soft-decision FEC. By introducing the turn-off identifier, the system dynamically switches between full soft-decision iteration and skipping iterations based on the decoding status of each sub-codeword. This dynamic mechanism allows the system to achieve performance enhancement close to soft-decision FEC for sub-codewords needing correction, while consuming power closer to hard-decision FEC for sub-codewords that are already successfully decoded, thus resolving the contradiction between power consumption and performance enhancement.
Data Source
AI summary
This application discloses example decoding methods, example decoders, and example decoding apparatuses. One example decoding method includes performing soft decision decoding on a first sub-codeword in a plurality of sub-codewords to obtain a hard decision result. It is determined whether to skip a decoding iteration. In response to determining not to skip the decoding iteration, a first turn-off identifier corresponding to the first sub-codeword is set to a first value based on the hard decision result. The first turn-off identifier indicates whether to perform soft decision decoding on the first sub-codeword in a next decoding iteration. The soft decision decoding is not performed on the first sub-codeword in the next decoding iteration when a value indicated by the first turn-off identifier is the first value. The hard decision result is stored.