Autoencoder-based end-to-end learning optimizes geometric constellation shapes and bit mappings, achieving up to 0.2 bits per QAM symbol GMI gain across data rates under transceiver impairments.
Bandwidth effi- cient and rate-matched low-density parity-check coded modulation
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End-to-end Learning for GMI Optimized Geometric Constellation Shape
Autoencoder-based end-to-end learning optimizes geometric constellation shapes and bit mappings, achieving up to 0.2 bits per QAM symbol GMI gain across data rates under transceiver impairments.