Rate Adaptive Autoencoder-based Geometric Constellation Shaping
Ognjen Jovanovic, Metodi P. Yankov, Francesco Da Ros, Darko Zibar
TL;DR
This paper introduces a rate-adaptive autoencoder approach for geometric constellation shaping that enhances transmission distance without extra hardware, optimizing bit-to-symbol mappings for improved communication efficiency.
Contribution
It presents a novel autoencoder-based method enabling rate adaptivity in geometric constellation shaping without added hardware complexity.
Findings
Achieves up to 300km transmission distance with optimized constellations.
Enables net rate adaptivity through learned bit-to-symbol mappings.
Improves performance over uniform QAM schemes.
Abstract
An autoencoder is used to optimize bit-to-symbol mappings for geometric constellation shaping. The mappings allow for net rate adaptivity without additional hardware complexity, while achieving up to 300km of transmission distance compared to uniform QAM.
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Taxonomy
TopicsCellular Automata and Applications · Advanced Materials and Mechanics · Advanced Surface Polishing Techniques