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Deep Learning of the Physical Layer for BICM Systems
Publikationstyp
Conference Paper
Date Issued
2020-10
Sprache
English
Institut
TORE-URI
Volume
2020-October
Article Number
9195252
Citation
IEEE Workshop on Signal Processing Systems (SiPS 2020)
Contribution to Conference
Publisher DOI
Scopus ID
We demonstrate that training of autoencoder-based communication systems on the bit-wise mutual information allows seamless integration with practical bit metric decoding receivers, as well as joint optimization of constellation shaping and labeling. Additionally, we present a fully differentiable neural iterative demapping and decoding structure which achieves significant gains on additive white Gaussian noise channels. Going one step further, we show that careful code design can lead to further performance improvements. Finally, we implement the end-to-end system on software-defined radio and train it on the actual channel.