Convolutional Polar Code Decoding With Reduced List Complexity
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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 uses a time-varying puncturing pattern and convolutional codes to reduce list sizes and computational complexity, providing balanced error correction and local error correction capabilities, thereby improving decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional polar coding methods are used, then error correction capability can be achieved, but implementation complexity and required list sizes increase
Solution Approach 1:
The patent segments the polar code decoding process into multiple stages with different list sizes. Instead of using a uniformly large list size throughout decoding, the method divides decoding into stages where early stages use smaller list sizes and later stages use larger list sizes, thereby reducing overall complexity while maintaining error correction capability
Solution Approach 2:
The patent implements dynamic list size adjustment during the decoding process. The list size is adapted based on the decoding stage and channel conditions, allowing the decoder to use smaller lists when possible and increase list size only when necessary to correct errors, thus optimizing the trade-off between complexity and reliability
2Reliability
If larger list sizes are used to improve error correction, then decoding accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies partial action by using sufficient but not excessive list sizes. Instead of always using the maximum possible list size, the method uses the minimum necessary list size at each decoding stage to achieve the required error correction performance, thereby reducing computational complexity while maintaining adequate decoding accuracy
3Reliability
If conventional polar codes are used, then basic error correction is achieved, but performance in high-mobility environments is insufficient
Solution Approach 1:
The patent changes key parameters of the polar code system including code rate, block length, and list size based on channel conditions and mobility scenarios. This allows the system to adapt to high-mobility environments by selecting parameters that provide sufficient error correction capability while maintaining spectral efficiency
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.