Polar Code Precoding and Decoding with Local Feedback Loops
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Solution Overview
Problem
Polar codes used in communication systems face challenges in error correction due to high complexity decoding algorithms, particularly in systems that cannot afford increased computational resources, such as CRC-aided list decoding, which results in poor bit error rates and frame error rates.
Innovation Solution
The implementation of local feedback mechanisms in polar code decoding, specifically through successive-cancellation decoding with convolutional codes, reduces complexity by using bidirectional communication and error correction techniques like Viterbi-aided SC decoding, which corrects errors without significantly increasing computational demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CRC-aided list decoding is used to improve error correction capability, then bit error rate and frame error rate improve, but computational complexity increases significantly
Solution Approach 1:
The patent segments the decoding process into two distinct parts: a successive-cancellation decoder that performs initial decoding with low complexity, and a feedback mechanism that selectively corrects errors. This segmentation allows the system to achieve better error correction without requiring the full computational burden of CRC-aided list decoding across the entire decoding process.
Solution Approach 2:
The patent introduces a feedback mechanism where the successive-cancellation decoder's output is fed back to identify and correct decoding errors. This feedback loop enables the system to improve reliability by targeting only the erroneous portions of the decoded data, rather than performing exhaustive list decoding on all data, thus reducing overall computational complexity while maintaining improved error correction capability.
2Device complexity
If conventional successive-cancellation decoding is used to maintain low computational complexity, then device complexity remains low, but error correction capability deteriorates
Solution Approach 1:
The patent enhances conventional successive-cancellation decoding by adding a feedback mechanism that uses the decoded output to identify and correct errors. The feedback loop allows the simple successive-cancellation decoder to achieve better error correction performance by leveraging information from its own decoding process, thereby improving reliability without significantly increasing device complexity.
Solution Approach 2:
The successive-cancellation decoder performs self-correction by using its own decoding output as feedback to identify and correct its errors. This self-service mechanism enables the low-complexity decoder to improve its own error correction capability without requiring a completely different high-complexity decoding algorithm, thus maintaining low device complexity while improving bit error rate performance.
Data Source
AI summary
Disclosed are devices, systems and methods for precoding and decoding polar codes using local feedback are described. One example method for improving an error correction capability of a decoder includes receiving a noisy codeword vector of length n, the codeword having been generated based on a concatenation of a convolutional encoding operation and a polar encoding operation and provided to a communication channel prior to reception by the decoder, performing a successive-cancellation decoding operation on the noisy codeword vector to generate a plurality of polar decoded symbols (n), generating a plurality of information symbols (k) by performing a convolutional decoding operation on the plurality of polar decoded symbols, wherein k/n is a rate of the concatenation of the convolutional encoding operation and the polar encoding operation, and performing a bidirectional communication between the successive-cancellation decoding operation and the convolutional decoding operation.