Polar Code SCL Path Sorting With Deferred LLR Updates
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Solution Overview
Problem
Current Polar Code Successive Cancellation List (SCL) decoders face significant latency issues due to inefficient buffer management and data exchange processes, which hinder their performance in achieving low decoding complexity and bit error performance, especially at longer block sizes.
Innovation Solution
The proposed solution involves selective replacement and deferred update techniques in SCL decoder operations, where only changed LLR statistics are updated, and in-place calculation and multicast of bit estimates are performed to reduce data transfer and processing bottlenecks, along with optimized sorting algorithms to minimize latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional buffer management and data exchange processes are used in SCL decoders, then decoding operation can proceed, but significant latency is introduced due to inefficient data movement and processing
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing path metric differences between consecutive decoding stages. These differences are computed in advance and stored in buffers, allowing the decoder to quickly update path metrics without performing full recalculations during the decoding process, thereby reducing latency while maintaining decoding efficiency
Solution Approach 2:
The patent segments the path metric update process into two parts: (1) pre-computed path metric differences stored in buffers, and (2) real-time updates during decoding. This segmentation allows the system to separate time-consuming calculations from the critical decoding path, reducing overall latency while preserving decoding throughput
2Reliability
If full buffer updates are performed at each decoding stage, then path metric accuracy is maintained, but memory transfer overhead increases significantly
Solution Approach 1:
The patent extracts only the essential information needed for path metric updates—the differences between consecutive path metrics—and stores only these differences in buffers. This extraction approach maintains path metric accuracy by preserving the critical update information while eliminating redundant data transfers, thereby reducing memory overhead and energy consumption
Solution Approach 2:
The patent applies local quality by updating path metrics selectively based on local changes in the decoding process. Instead of uniformly updating all path metrics at every stage, the system performs updates only where path metric differences indicate changes are necessary, optimizing the balance between accuracy and resource usage
3Measurement precision
If path metrics are updated for all paths at each stage, then decoding accuracy is maintained, but processing complexity increases
Solution Approach 1:
The patent applies partial action by updating path metrics only for paths where the pre-computed differences indicate necessary changes, rather than uniformly updating all paths at every decoding stage. This selective approach maintains decoding accuracy for critical paths while reducing overall processing complexity and resource requirements
Data Source
AI summary
Various embodiments are described of a system and method for improved SCL decoder operation. In particular, various embodiments are described which improve the efficiency of the buffer management based on updated path metric statistics. In some embodiments, the SCL decoder may perform selective replacement to limit the extent of LLR updates per row only to the statistics that have changed since the previous update cycle. In some embodiments, the SCL decoder may perform deferred updates, which may involves in-place calculation of both ûφ=0 and ûφ=1 bit estimate (LLR) updates based on the row from which the updated row will be derived.