Polar Code Relaxation Scheme for Lower Encoding and Decoding Complexity
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Solution Overview
Problem
Polar codes, while effective for error correction, are computationally complex, particularly for medium to large block lengths, which limits their adaptation for high throughput regimes in wireless communication systems.
Innovation Solution
The proposed solution involves a relaxation scheme for polar codes, where certain polarization operations are omitted to reduce encoding and decoding complexity, while preserving error-correction performance. This is achieved by selecting nodes for relaxation based on their reliability, specifically using the most reliable and least reliable bit channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If polar codes are used for error correction, then error-correction performance is improved, but computational complexity increases
Solution Approach 1:
The patent segments the polar code structure by identifying and separating frozen bits (which do not require polarization operations) from information bits. This segmentation allows the encoder to skip unnecessary XOR operations for frozen bits, reducing computational complexity while preserving error-correction performance for the information bits.
Solution Approach 2:
The patent extracts and removes redundant polarization operations from the encoding process. By analyzing the generator matrix structure, it identifies that certain rows corresponding to frozen bits can be excluded from the polarization computation, thereby taking out unnecessary computational steps while maintaining the essential error-correction functionality.
2Reliability
If full polarization operations are performed, then error-correction performance is maintained, but encoding and decoding latency increases
Solution Approach 1:
The patent performs preliminary analysis of the generator matrix to pre-identify which polarization operations are redundant before actual encoding begins. By calculating the frozen bit positions in advance and marking them for exclusion, the system prepares a optimized encoding path that skips unnecessary operations during real-time transmission, reducing latency without compromising error-correction performance.
3Device complexity
If polarization operations are reduced, then computational complexity and latency are reduced, but error-correction performance may deteriorate
Solution Approach 1:
The patent applies local quality by treating frozen bits and information bits differently. Frozen bits are identified as having fixed values that do not require polarization processing, while information bits receive full polarization operations to maintain error-correction capability. This localized differentiation ensures that complexity reduction does not compromise the error-correction performance of the critical information bits.
Data Source
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AI summary
Systems, methods, and instrumentalities are described herein that may be used for reduced complexity polar encoding and decoding. There may be a set of encoding nodes to be used for polar encoding. An encoding node may be associated with a bit index and/or a relaxation level. A relaxation attribute may be selected for the encoding node. A relaxation group may be determined based on the relaxation attributes. The relaxation group may include two encoding nodes associated with consecutive bit indexes, an initial relaxation level, and the first relaxation attribute. A final relaxation level may be determined. Relaxation may be performed on the encoding nodes in the relaxation group. For example, an XOR operation between the encoding nodes may be omitted. Relaxation may be performed on the encoding nodes associated with each relaxation level up to the final relaxation level.