Convolutional Polar Coding With Smaller List Decoding
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Solution Overview
Problem
Current polar coding methods in communication systems face challenges in reducing implementation complexity and enhancing error correction capabilities, particularly in high-mobility environments, where they often require high computational resources and list sizes that can be inefficient.
Innovation Solution
The implementation of convolutional precoding and decoding of polar codes, which involves using a time-varying puncturing pattern for convolutional codes to reduce list sizes and computational complexity, and employing a convolutional code as an additional layer of protection to provide local error correction and balanced error protection across bit-channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional polar coding methods are used, then error correction capability can be maintained, but implementation complexity and list size requirements increase
Solution Approach 1:
The patent segments the polar code into multiple segments and applies convolutional precoding to each segment independently. This segmentation approach reduces the overall list size required for decoding while maintaining error correction capability, as each segment can be decoded with a smaller list size compared to decoding the entire code block at once.
Solution Approach 2:
The patent introduces convolutional precoding as an intermediary layer between the information bits and the polar encoding process. This intermediary convolutional code provides local error correction capability and balances error distribution across bit-channels, thereby reducing the complexity of the subsequent polar decoding operation while maintaining or improving overall error correction performance.
2Reliability
If larger list sizes are used to improve error correction, then reliability increases, but computational complexity increases
Solution Approach 1:
The patent applies convolutional precoding in advance before polar encoding to pre-process the information bits and balance error distribution. This preliminary action reduces the burden on the subsequent decoding stage, allowing for smaller list sizes and reduced computational complexity while maintaining error correction capability.
Solution Approach 2:
The patent changes the parameter of list size from large to small by introducing convolutional precoding. The convolutional code modifies the error characteristics of the input data, transforming a problem that would require large list sizes into one that can be solved with smaller lists, thereby reducing computational complexity and power consumption.
3Device complexity
If convolutional precoding is applied, then list size is reduced by at least 50%, but additional encoding steps are required
Solution Approach 1:
The convolutional precoding process operates on segmented portions of the data stream, allowing for parallel processing and efficient implementation. The segmentation enables the encoding process to be broken down into manageable stages that can be optimized for throughput while achieving the 50% list size reduction.
4Reliability
If convolutional precoding with time-varying puncturing pattern is used, then error protection is balanced across bit-channels, but device complexity increases
Solution Approach 1:
The patent employs a time-varying puncturing pattern in the convolutional precoding process, where the puncturing pattern changes over time to adapt to different error characteristics of bit-channels. This dynamic approach balances error protection across channels by applying different puncturing rates to different time intervals or code blocks, optimizing reliability while managing complexity through structured variation rather than fully adaptive complex schemes.
Data Source
AI summary
Devices, systems and methods for convolutional precoding and decoding of polar codes are disclosed. An example method for error correction in a data processing system includes receiving a noisy codeword, the codeword having been generated based on an outer stream decodable code and an inner polar code and provided to a communication channel or a storage channel prior to reception by the decoder, the stream decodable code characterized by a trellis, and performing, based on the trellis, a list-decoding operation on the noisy codeword vector to generate a plurality of information symbols, the list-decoding operation being configured to traverse through a plurality of states at one or more stages of a plurality of decoding stages.