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End-to-End Learning of Joint Geometric and Probabilistic Constellation Shaping
Published 9 Dec 2021 in cs.IT, cs.AI, eess.SP, and math.IT | (2112.05050v1)
Abstract: We present a novel autoencoder-based learning of joint geometric and probabilistic constellation shaping for coded-modulation systems. It can maximize either the mutual information (for symbol-metric decoding) or the generalized mutual information (for bit-metric decoding).
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