Parallel Polar Codes for Low-Latency Decoding Reliability
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Solution Overview
Problem
Conventional polar codes face challenges in achieving high throughput and low latency in practical implementations, particularly with short- and medium-length codes, due to high latency in decoding algorithms like SC and SCL, which hinder their effectiveness in high-throughput applications.
Innovation Solution
The use of multiple parallel polar codes that cooperate with each other, where information bits are distributed and split into protected and full rate sections, with frozen bits arranged to enhance coding gain and throughput, and employing repetition codes or BCH/Reed-Muller codes for protection in non-perfectly polarized channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional SC or SCL decoding algorithms are used for polar codes, then decoding performance approaches channel capacity as code length approaches infinity, but latency becomes too high for practical high-throughput applications with short- and medium-length codes
Solution Approach 1:
The patent divides the information bits into multiple subsets and encodes them using multiple parallel polar codes instead of a single code. This segmentation allows independent parallel decoding of each code, significantly reducing overall decoding latency while maintaining reliability through the combined error correction capability of multiple codes.
Solution Approach 2:
The patent transitions from a single sequential decoding process to a multi-dimensional parallel structure by using multiple polar codes simultaneously. This dimensional expansion enables concurrent processing of multiple code subsets, effectively reducing the time dimension (latency) while preserving the reliability function across all parallel codes.
2Productivity
If multiple parallel polar codes are used to reduce latency and increase throughput, then coding gain and reliability improve, but system complexity increases due to multiple encoding and decoding operations
Solution Approach 1:
The patent combines multiple polar codes into a unified parallel structure where information bits are distributed across codes and decoded simultaneously. This merging approach achieves higher throughput by utilizing multiple codes in parallel while managing complexity through systematic distribution and combination rules that allow efficient resource sharing and coordinated processing.
Data Source
AI summary
The disclosed systems, structures, and methods are directed to encoding and decoding information for transmission across a communication channel. The encoding method includes: distributing the information bits between m parallel polar codes such that each of the m parallel polar codes includes a subset of the information bits; splitting the subset of information bits in each of the m parallel polar codes into a protected information section and a full rate information section; protecting information bits in the protected information section of each of the m parallel polar codes; arranging a plurality of frozen bits in each of the m parallel polar codes; and generating a polar encoded codeword for each of the m parallel polar codes.