Neural Network Equalizers and Successive Interference Cancellation for Bandlimited Channels with a Nonlinearity
<|reference_start|>Neural Network Equalizers and Successive Interference Cancellation for Bandlimited Channels with a Nonlinearity: Neural networks (NNs) inspired by the forward-backward algorithm (FBA) are used as equalizers for bandlimited channels with a memoryless nonlinearity. The NN-equalizers are combined with successive interference cancellation (SIC) to approach the information rates of joint detection and decoding (JDD) with considerably less complexity than JDD and other existing equalizers. Simulations for short-haul optical fiber links with square-law detection illustrate the gains.<|reference_end|>
@article{plabst2024neural,
    title={Neural Network Equalizers and Successive Interference Cancellation for
  Bandlimited Channels with a Nonlinearity},
    author={Daniel Plabst, Tobias Prinz, Francesca Diedolo, Thomas Wiegart, Georg
  B"ocherer, Norbert Hanik, Gerhard Kramer},
    journal={arXiv preprint arXiv:2408.15767},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.15767},
    primaryClass={cs.IT eess.SP math.IT}
}