Temporal Properties of Enumerative Shaping: Autocorrelation and Energy Dispersion Index
Yunus Can G\"ultekin, Kaiquan Wu, Alex Alvarado
TL;DR
This paper investigates how enumerative amplitude shaping algorithms affect the effective SNR by analyzing their temporal autocorrelation and energy dispersion properties.
Contribution
It introduces a novel explanation of the algorithms' behavior through autocorrelation and energy dispersion metrics.
Findings
Effective SNR behavior explained by autocorrelation and energy dispersion.
Different algorithms exhibit distinct temporal properties impacting performance.
Analytical framework aids in designing better amplitude shaping methods.
Abstract
We study the effective SNR behavior of various enumerative amplitude shaping algorithms. We show that their relative behavior can be explained via the temporal autocorrelation function or via the energy dispersion index.
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Taxonomy
TopicsCellular Automata and Applications · Computer Graphics and Visualization Techniques · Computational Geometry and Mesh Generation