Polar Code Reliability Ordering for Lower-Complexity 5G Encoding
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Solution Overview
Problem
Existing polar codes face challenges in achieving ideal encoding/decoding performance for future wireless communications systems like 5G due to suboptimal reliability ordering of polarized channels, leading to high computational complexity and difficulty in supporting varying bit rates.
Innovation Solution
A method for polar code encoding that determines the order of reliability for polarized channels by selecting sequence numbers based on descending reliability, reducing computational complexity by mapping information bits to channels with higher reliability without considering channel parameters or bit rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing polar codes use traditional reliability ordering methods, then encoding/decoding can be performed, but the accuracy of reliability ordering for polarized channels is insufficient, leading to suboptimal encoding/decoding performance
Solution Approach 1:
The patent changes the parameter of reliability ordering by introducing a new ordering sequence that considers both channel reliability and bit rate requirements. Instead of using traditional fixed reliability ordering, the method dynamically adjusts the ordering based on the specific communication scenario, thereby improving both the accuracy of reliability assessment and the overall encoding/decoding performance for 5G scenarios like eMBB, mMTC, and URLLC.
2Reliability
If polar code encoding considers channel parameters and bit rates dynamically, then encoding/decoding performance can be optimized, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-determining the ordering sequence of polarized channels based on reliability metrics before actual encoding occurs. This pre-computed ordering is then reused across different encoding operations, avoiding the need to recalculate complex channel parameters and bit rate adjustments in real-time, thus maintaining optimized performance while reducing computational complexity during actual encoding/decoding operations.
Data Source
AI summary
This application relates to the field of wireless communications technologies, and discloses an encoding method and apparatus, to improve accuracy of reliability calculation and ordering for polarized channels. 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 first sequence is same as a second sequence or a subset of the second sequence, the second sequence comprises sequence numbers of Nmax polarized channels, and the second sequence is the sequence shown in Sequence Q11 or Table Q11, K is a positive integer, N is a positive integer power of 2, n is equal to or greater than 5, K≤N, Nmax=1024; selecting sequence numbers of K polarized channels from the first sequence; and performing polar code encoding on K the to-be-encoded bits based on the selected sequence numbers of the K polarized channels.