Polar Code Outer-Subcode Decoding for Lower Delay
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Solution Overview
Problem
Existing polar code decoding algorithms suffer from high decoding delays and complexity, particularly when code rates approach 0 or 1, limiting throughput in communications systems.
Innovation Solution
The proposed method involves distributing information bits across outer-code subcodes with specific thresholds, allowing for decoding using classic algebraic codes instead of polar decoding, thereby reducing decoding delays and improving throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SC or SCL decoding algorithms are used for polar codes, then decoding performance is good for short codes, but decoding delay becomes very long when code length is large
Solution Approach 1:
The patent divides the polar code decoding process into multiple parallel subcode decoding units. Each subcode processes a portion of the encoded bits simultaneously, transforming the single long sequential decoding path into multiple shorter parallel paths. This segmentation reduces the overall decoding delay while maintaining acceptable decoding performance.
Solution Approach 2:
The patent introduces parallelism as a new dimension to the decoding process. Instead of processing bits sequentially in one dimension, multiple decoding operations are executed simultaneously in parallel dimensions, effectively reducing the time dimension of the decoding delay.
2Loss of time
If outer-code subcodes are decoded in parallel to reduce decoding delay, then decoding delay is reduced, but decoding complexity increases when code rate approximates 0.5
Solution Approach 1:
The patent applies different decoding strategies to different subcodes based on their local characteristics (code rates). Subcodes with extreme code rates (close to 0 or 1) are decoded using simple parallel methods, while subcodes with intermediate code rates (close to 0.5) are handled with more sophisticated algorithms. This local adaptation optimizes the balance between parallelism benefits and complexity costs.
Solution Approach 2:
The patent dynamically adjusts the decoding approach for different subcodes based on their code rates. The decoding complexity is adaptively modulated according to the specific characteristics of each subcode, allowing the system to exploit parallelism where beneficial while avoiding excessive complexity where unnecessary.
Data Source
AI summary
Encoding methods and apparatuses are provided. The method includes: obtaining to-be-encoded information including K information bits and a mother code length N; determining, based on K and N, a set I corresponding to subchannels of the information bits, where information bits corresponding to subchannel sequence numbers in I are distributed in X outer-code subcodes including X1 first-type outer-code subcodes, quantities of information bits in the X1 first-type outer-code subcodes are P1, P2, . . . , and PX1, Pi (i=1, 2, . . . , X1) is one of K1, K2, . . . , and Km, which are greater than a first threshold LB and less than a second threshold HB, 1=<m <(HB−LB−1), LB+1<HB, HB<=a length B of an outer-code subcode, X, HB, and B are positive integers, and LB is an integer>=0; and performing encoding based on I.