Polar Code Decoding with Grouped Parallel Resource Reconstruction
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Solution Overview
Problem
Existing decoding algorithms for polar codes in 5G networks suffer from increased decoding time delay and resource occupation due to the iterative nature of calculating decoding results, especially for longer code lengths.
Innovation Solution
A method involving grouped parallel decoding by first and second decoding units, followed by merging and updating these units to reconstruct decoding resources while maintaining time delay unchanged, utilizing a preset decoding resource allocation table to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If common decoding algorithm is used for long polar codes, then decoding can be performed, but decoding time delay and occupied resources are obviously increased
Solution Approach 1:
The original data is divided into multiple groups, and each group is decoded independently by a separate first decoding unit in parallel. This segmentation allows multiple decoding operations to proceed simultaneously, increasing throughput without proportionally increasing time delay for each individual decoding path.
Solution Approach 2:
The patent transitions from sequential decoding in time domain to parallel decoding by introducing multiple decoding units operating simultaneously. This dimensional change from single-thread sequential processing to multi-thread parallel processing resolves the contradiction between throughput and time delay.
2Productivity
If common decoding algorithm is used for long polar codes, then decoding can be performed, but occupied resources are obviously increased
Solution Approach 1:
The patent merges the outputs from multiple first decoding units into a single second decoding unit. This merging allows the system to achieve parallel decoding throughput while consolidating resources through shared components in the second decoding unit, reducing overall resource occupation compared to having completely independent decoding chains.
Solution Approach 2:
The second decoding unit serves multiple functions by processing the merged outputs from all first decoding units. This multi-functional design allows a single resource to handle multiple decoding paths, improving resource utilization and reducing the total resources needed compared to dedicated decoding units for each path.
Data Source
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AI summary
A decoding method and device, an apparatus, and a storage medium are provided. The method includes: decoding grouped original data in parallel by a first decoding unit to obtain grouped decoded data (110); decoding merged grouped decoded data by a second decoding unit to obtain decoded data (120); and if the sum of the lengths of the decoded data is an integer multiple of an upper limit of the decoding times of the second decoding unit, updating the first decoding unit and the second decoding unit, and if the sum of the lengths of the decoded data is not an integer multiple of the upper limit of the decoding times of the second decoding unit, updating the second decoding unit to obtain the decoded data again, until the sum of the lengths of the decoded data is equal to a decoding length, and merging the decoded data to serve as a decoding result of the original data (130). In the method, by performing grouped decoding on the original data, the reconstruction of decoding resources is realized while maintaining the time delay basically unchanged.