Polar Code Construction Using Dynamic Sorting Indices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless communication systems, particularly those employing LTE technology, require enhancements in error correcting codes to improve reliability and efficiency for future networks, as current block codes like turbo codes and LDPC codes have limitations in performance and memory usage for constructing polar codes.
Innovation Solution
The method involves determining sets of parameters and sorting indices for data transmission to generate polar codes dynamically, eliminating the need for pre-defined vectors in memory, thus optimizing code construction for both traffic and control channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-defined vectors are stored in memory for polar code construction, then code construction can be performed, but memory requirements increase
Solution Approach 1:
The system generates sorting indices dynamically using a deterministic algorithm based on channel parameters (block length N, information block size K, and signal-to-noise ratio) without requiring pre-stored vectors. Both transmitter and receiver independently compute the same sorting indices, eliminating memory storage requirements while ensuring consistent polar code construction
Solution Approach 2:
The patent replaces the mechanical storage system (memory vectors) with a computational system (deterministic algorithm). Instead of retrieving pre-computed sorting indices from memory, the system computes them on-demand using mathematical relationships between channel parameters and bit-channel reliability, reducing memory usage to minimal lookup tables
2Reliability
If existing block codes like turbo codes and LDPC codes are used, then current wireless communication systems can operate, but performance and efficiency are limited for future networks
Solution Approach 1:
The patent employs polar codes which fundamentally change the coding parameters and mathematical structure compared to traditional turbo codes and LDPC codes. Polar codes achieve channel capacity through a different encoding mechanism based on channel polarization theory, providing superior error correction performance and spectral efficiency for future wireless networks
Data Source
AI summary
Methods and apparatus for constructing polar codes are provided. A transmitter determines at least one set of parameters corresponding to data to be transmitted, and a set of sorting indices corresponding to bits of the data to be transmitted based on the set of parameters, the set of sorting indices indicating a position set of the bits to be transmitted. The transmitter polar encodes the data based at least on the set of parameters and the set of sorting indices to generate a coded block of the data, and transmits the coded block of the data.