Polar Code Channel Ranking for Accurate Reliability Sorting
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Solution Overview
Problem
Current polar code encoding methods face challenges in achieving ideal encoding/decoding performance, particularly in medium and short packet transmissions, due to high calculation complexity and limited code length, and suffer from inaccurate polarized channel reliability sorting, which affects overall performance in emerging communication scenarios like 5G.
Innovation Solution
A polar code encoding method that calculates and uses a reliability ranking of polarized channels by transforming channel sequence numbers into reliability weights, allowing for more accurate estimation of channel reliability and improved sequence selection for encoding, thereby enhancing encoding performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional turbo code or LDPC code is used for channel coding, then encoding/decoding can be performed, but calculation complexity is high and performance is limited for medium and short packet transmission
Solution Approach 1:
The patent transforms channel sequence numbers into reliability weights through a mapping function, changing the parameter representation from simple indices to weighted reliability values. This allows the polar code encoder to prioritize channels based on calculated reliability metrics, improving decoding performance without adding complex hardware structures.
Solution Approach 2:
The patent performs preliminary reliability calculation and channel sorting before the actual encoding/decoding process. By pre-computing the reliability weights and establishing the channel sequence in advance, the system avoids complex real-time calculations during transmission, reducing overall computational complexity while maintaining high performance.
2Device complexity
If polar code encoding is used to reduce calculation complexity, then encoding/decoding complexity is reduced, but polarized channel reliability sorting accuracy is not ideal
Solution Approach 1:
The patent introduces a reliability weight parameter that transforms simple channel sequence numbers into weighted values representing channel reliability. This parameter transformation enables more accurate channel ordering by capturing subtle reliability differences that simple indexing cannot represent, thereby improving sorting accuracy while maintaining the low complexity of polar code structures.
Solution Approach 2:
The patent implements a feedback mechanism where reliability weights are calculated based on channel characteristics and used to adjust the encoding sequence. This closed-loop approach allows the system to continuously optimize channel ordering based on reliability metrics, improving sorting accuracy without requiring complex iterative algorithms during real-time operation.
Data Source
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AI summary
This application relates to the field of communications technologies, and discloses a polar code encoding method and apparatus, to improve polarized channel reliability calculation and sorting accuracy. The method includes: obtaining a first sequence used to encode K to-be-encoded bits, where the first sequence includes sequence numbers of N polarized channels, the sequence numbers of the N polarized channels are arranged in the first sequence based on reliability of the N polarized channels, K is a positive integer, N is a mother code length of a polar code, N is a positive integer power of 2, and K ≤ N; selecting sequence numbers of K polarized channels from the first sequence in descending order of reliability; and placing the to-be-encoded bits based on the selected sequence numbers of the K polarized channels, and performing polar code encoding on the to-be-encoded bits.