Ordered Sub-Channel Sequences for Polar Code Reliability
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Solution Overview
Problem
Polar codes in wireless communications face challenges in efficiently selecting sub-channels for information bits and frozen bits, particularly in achieving reliable decoding with limited code lengths and varying channel conditions, leading to suboptimal performance compared to other error correction codes like LDPC and Turbo codes.
Innovation Solution
A method for selecting sub-channels based on ordered sequences that represent the reliability of sub-channels, using a sub-channel processing module to determine the most reliable sub-channels for information bits and less reliable sub-channels for frozen bits, optimizing sub-channel allocation for polar coding in wireless communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional sub-channel selection methods are used for polar codes, then the encoding and decoding process is simple, but the decoding performance is suboptimal compared to LDPC and Turbo codes
Solution Approach 1:
The patent segments the sub-channel selection process into multiple stages: first determining a base sequence based on code length and code rate, then generating the final ordered sequence by combining the base sequence with an interleaving sequence. This segmentation allows the system to achieve optimal decoding performance through structured selection while maintaining implementation simplicity through modular processing.
Solution Approach 2:
The patent performs preliminary determination of the base sequence using pre-defined rules based on code length and code rate parameters. This preliminary action prepares the foundation for subsequent sequence generation, enabling the system to achieve optimal performance without complex real-time calculations during actual encoding/decoding operations.
2Reliability
If code length is increased to improve polar code performance, then channel capacity approaches are better achieved, but computational complexity and processing time increase
Solution Approach 1:
The patent implements dynamic sequence generation where the base sequence and interleaving sequence are adaptively determined based on code length and code rate parameters. This dynamic approach allows the system to optimize sub-channel selection for different code lengths without requiring exhaustive search, achieving near-capacity performance with reduced processing time compared to static or brute-force methods.
Solution Approach 2:
The patent changes key parameters (base sequence, interleaving sequence) based on code length and code rate to optimize performance. By adjusting these parameters dynamically rather than using fixed sequences, the system achieves better channel capacity approach for longer codes while maintaining efficient processing through parameter-based optimization rather than structural complexity increases.
3Productivity
If more sub-channels are allocated to information bits to increase data rate, then throughput improves, but error correction capability deteriorates
Solution Approach 1:
The patent applies local quality by assigning different sub-channels with different reliabilities to different bit types (information bits vs. frozen bits) based on the ordered sequence. High-reliability sub-channels are allocated to information bits to maximize data rate, while low-reliability sub-channels are allocated to frozen bits to maintain error correction capability. This localized optimization achieves both high throughput and strong error correction performance simultaneously.
Data Source
AI summary
An ordered number sequence may be determined based on an ordered sub-channel sequence specifying an order of N sub-channels that are defined by a code and that have associated reliabilities for input bits at N input bit positions. The ordered number sequence represents the ordered sub-channel sequence as a sequence of fewer than N numbers. The numbers in the ordered number sequence indicate the sub-channels, by representing numbers of the sub-channels for example, from different subsets of the N sub-channels, that appear in the order specified by the ordered sub-channel sequence. Using ordered number sequences, longer ordered sub-channel sequences could be constructed from smaller ordered sub-channel sequences, and/or sub-channels that to be selected from a longer ordered sub-channel sequence could be divided into two or more parts, with each part to be selected from shorter ordered sub-channel sequences.