Polar Code Decoding with Low-Reliability Bit Inversion
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Solution Overview
Problem
Current polar code decoding methods, particularly successive cancellation decoding, suffer from high error propagation due to their sequential nature, leading to suboptimal error rates with increased complexity and resource demands.
Innovation Solution
A novel inversion decoding method that prioritizes the first erroneous bit in a frame for correction, using a new metric that considers the reliability of previous decisions, reduces the number of inversions required to achieve lower error rates with lower complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If successive cancellation decoding is used for polar codes, then decoding can be performed sequentially with manageable complexity, but error propagation occurs leading to high error rates
Solution Approach 1:
The patent applies inversion by reversing the conventional approach: instead of sequentially decoding from the first bit and accepting errors, it identifies unreliable bits through a new metric and inverts their decision order, decoding from least reliable to most reliable. This inversion of the decoding sequence reduces error propagation while maintaining manageable complexity.
Solution Approach 2:
The patent changes the parameter of decoding sequence by introducing a new metric that reorders bits based on their reliability rather than their position in the transmitted frame. This parameter change transforms the fixed sequential order into a dynamic order based on channel conditions, reducing error rates without significantly increasing complexity.
2Reliability
If conventional inversion methods are used to correct erroneous bits, then error rates can be reduced, but the average number of inversions increases leading to higher latency
Solution Approach 1:
The patent changes the parameter used to select bits for inversion by introducing a new metric that better predicts which bits are likely to be erroneous. This metric considers both the channel reliability and the position in the decoding sequence, enabling more accurate identification of bits that need inversion and reducing the average number of inversions required.
Solution Approach 2:
The patent enables the decoding process to self-correct by using the new metric to automatically identify and invert erroneous bits without requiring external intervention or multiple decoding passes. The metric itself guides the inversion process, making the system self-optimizing and reducing latency.
3Reliability
If more inversions are performed to achieve lower error rates, then reliability improves, but computational complexity and resource demands increase
Solution Approach 1:
The patent changes the fundamental parameter of bit selection from position-based to metric-based ordering. By sorting bits according to the new reliability metric rather than their original position, the system achieves lower error rates with fewer inversions, reducing the computational complexity associated with trial-and-error inversion methods.
Solution Approach 2:
The patent performs preliminary ordering of bits based on the new metric before the actual decoding and inversion process. This preliminary action organizes the bits in an optimal sequence that minimizes the number of inversions needed, reducing overall computational complexity while improving reliability.
Data Source
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AI summary
The invention relates to a polar code decoding method in which a first decoding attempt by successive cancellation (510) is performed and in the case where the decoded frame is erroneous (520), an ordered list of bit positions to be tested in the frame is generated (530), the order relation being given by a metric of first error, the value of this metric depending on the reliability of the decision about the bit as well as on the reliability of the decisions about the bits preceding it in the frame. For each of the positions of the list, an inversion (550) of the bit and a decoding of the subsequent bits (560) are undertaken, doing so as long as the list has not been exhausted or the frame has not been decoded without error. In case of failure, a new decoding attempt based on a double-inversion of bits can be envisaged.