Hierarchical Distribution Matching: a Versatile Tool for Probabilistic Shaping
Stella Civelli, Marco Secondini
TL;DR
This paper introduces Hierarchical Distribution Matching (Hi-DM), a versatile probabilistic shaping technique that balances performance, complexity, and memory, demonstrated through three case studies.
Contribution
It presents a novel hierarchical distribution matching method for probabilistic shaping, highlighting its flexibility and efficiency compared to existing approaches.
Findings
Hi-DM achieves favorable trade-offs in performance and complexity.
Three case studies demonstrate its practical effectiveness.
Hi-DM offers a versatile tool for probabilistic shaping applications.
Abstract
The hierarchical distribution matching (Hi-DM) approach for probabilistic shaping is described. The potential of Hi-DM in terms of trade-off between performance,complexity, and memory is illustrated through three case studies.
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