Non-Binary Polar Code Decoding Hardware for Low-Latency SC
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Solution Overview
Problem
Non-binary polar codes (NBPCs) face challenges in fast decoding, making them impractical for real-life applications due to high latency, despite their potential for improved latency and error rate performance compared to binary polar codes.
Innovation Solution
An application-specific hardware device is developed for decoding non-binary polar codes using a successive cancellation decoding routine, which involves permutation operations and Extended Min-Sum operations, applied in a binary tree structure to efficiently decode encoded non-binary data symbols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If successive cancellation decoding is applied to non-binary polar codes, then error rate performance is improved, but decoding latency increases making it impractical for real-life applications
Solution Approach 1:
The decoding process is segmented into identifying and processing special nodes (super-nodes) separately from regular nodes. Special nodes are detected based on patterns in the binary tree structure, and dedicated simplified decoding routines are applied to them, while regular nodes use standard successive cancellation decoding. This segmentation enables parallel processing paths that reduce overall latency while maintaining error rate performance.
Solution Approach 2:
The system performs preliminary identification of special nodes before full decoding begins. By pre-processing the binary tree structure to locate special nodes and prepare their specific decoding routines, the system avoids computational delays during the main decoding phase, thereby reducing total decoding latency while preserving the error rate benefits of NBPCs.
2Productivity
If non-binary polar codes are used instead of binary polar codes, then latency and error rate performance are improved, but computational complexity increases
Solution Approach 1:
Different decoding approaches are applied to different parts of the code structure. Special nodes receive simplified decoding routines tailored to their specific patterns, while regular nodes use standard successive cancellation. This local differentiation reduces overall computational complexity without sacrificing the performance benefits of non-binary polar codes, as each node type is processed with the most efficient appropriate method.
Solution Approach 2:
The system changes the parameter of decoding complexity by introducing variable decoding routines based on node type. Instead of uniformly applying complex non-binary successive cancellation to all nodes, the complexity parameter is adjusted locally - simplified routines for special nodes and standard routines for regular nodes - thereby reducing average computational complexity while maintaining high decoding speed for critical path nodes.
3Ease of operation
If standard successive cancellation decoding is applied to all nodes in the binary tree, then decoding is straightforward to implement, but latency is high due to sequential processing
Solution Approach 1:
The binary tree is segmented into special nodes and regular nodes based on structural patterns. This segmentation enables the system to apply different decoding strategies: simplified routines for special nodes that can be processed faster, and standard routines for regular nodes. The segmentation maintains implementation simplicity through clear node classification rules while reducing latency through optimized processing paths.
Solution Approach 2:
Instead of applying full successive cancellation decoding to every node, the system applies simplified decoding routines to special nodes - a partial action sufficient for those specific node types. This partial approach reduces latency for the critical special nodes without requiring complete redesign of the decoding algorithm, thus maintaining ease of implementation while improving overall decoding speed.
Data Source
AI summary
An application-specific hardware device and methods for decoding data and methods are disclosed. The data includes a plurality of encoded non-binary data symbols, the application-specific hardware device receives the plurality of encoded non-binary data symbols, each encoded non-binary data symbol being received through a corresponding channel, determines, for each encoded non-binary data symbol, a log-likelihood ratio vector, applies a successive cancellation decoding routine to the plurality of log-likelihood ratio vectors, the successive cancellation decoding routine comprising one or more groups of operations to be applied to subsets of the plurality of log-likelihood ratio vectors and generates a plurality of decoded non-binary data symbols based on a result of the successive cancellation decoding routine.