Code Block Partitioning With CRC Control for 5G Channel Coding
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Solution Overview
Problem
In communications systems, particularly in 5G mobile communications, there is a challenge in processing information sequences to meet channel coding requirements, which affects coding and decoding performance due to varying channel conditions and interference.
Innovation Solution
An information processing method that segments input sequences into code blocks with specific lengths and structures, including cyclic redundancy check (CRC) and filler bits, to ensure code block lengths meet channel coding requirements, balance code rates, and reduce system performance fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the input sequence is divided into multiple code blocks without considering maximum code block length constraints, then the segmentation is simple, but the code blocks may not meet channel coding requirements and system performance fluctuates
Solution Approach 1:
The input sequence is segmented into multiple code blocks, where each code block's length is controlled to not exceed the maximum code block length Z. This segmentation ensures that each code block meets channel coding requirements while maintaining manageable processing complexity through systematic division
Solution Approach 2:
The method adjusts code block parameters (length, CRC bit inclusion, filler bits) based on the maximum code block length constraint Z. By dynamically setting code block lengths and adding filler bits or CRC bits as needed, the system ensures compliance with channel coding requirements while adapting to different input sequence lengths
2Adaptability or versatility
If code blocks are created with varying lengths to accommodate different input sizes, then flexibility is improved, but code rate imbalance and performance fluctuation occur
Solution Approach 1:
The method applies different local structures to code blocks based on their specific needs: some code blocks include CRC bit segments for error detection, while others include filler bit segments to reach optimal lengths. This local differentiation ensures each code block is optimally configured while maintaining overall system stability
Solution Approach 2:
The method preliminarily determines the maximum code block length Z from a code block length set before processing the input sequence. This preliminary parameter setting guides the subsequent segmentation and ensures that all code blocks are pre-configured to meet channel coding requirements, preventing performance fluctuations
3Reliability
If more code blocks are generated to process long input sequences, then complete processing is achieved, but the quantity of code blocks increases and processing overhead rises
Solution Approach 1:
The method dynamically determines the number of code blocks C based on the input sequence length B and maximum code block length Z using the formula C=┌B/(Z−L)┐. This dynamic calculation ensures the minimum necessary number of code blocks is created to completely process the input sequence, optimizing processing efficiency while ensuring complete coverage
Data Source
AI summary
This application discloses an information processing method. A communication device obtains an input sequence. The input sequence has a quantity B of information bits. The communication devices transforms the input sequence into one or more code blocks. The communication device encodes each of the code blocks individually, to obtain one or more encoded code blocks. Each of the code blocks has a code block length less than or equal to a maximum code block length. Each of the code blocks includes a segment of the input sequence and may include one or more cyclic redundancy check (CRC) bits corresponding to the segment of the input sequence. The encoded code blocks can meet various channel coding requirements.