Return
Multi-Level Distribution Matching
DOI:10.1109/LCOMM.2020.2993929.png)
Abstract
En 中文
A general distribution matching architecture based on a multi-level structure is presented. It allows to generate arbitrary symbol distributions using simple binary distribution matchers. This is particularly advantageous for large symbol alphabets, where non-binary distribution matching algorithms tend to have high complexity. Some examples for possible implementations are provided, and a specific realization based on polar codes, which enables joint shaping and channel coding for reliable data transmission with higher-order modulation, is discussed and evaluated in detail.
Keywords:
Decoding
Labeling
Complexity theory
Reliability
Entropy
Channel coding
Distribution matching
probabilistic shaping
multi-level coding
polar codes
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

