Complex Autoencoder Approach to Constant Envelope Waveform Coding
Paul Gorday, Nurgün Erdöl, Hanqi Zhuang · 2021
This paper proposes a new complex autoencoder suitable for learning spectrally efficient, constant envelope waveform coding. In contrast to prior work, we model the encoder output layer as a phase modulation layer with a complex exponential activation function. In addition, we model the decoder with a complex-valued feature detection layer that may be coherent or noncoherent. The complex topology leads to noncoherent waveform coding methods not obtained in prior studies. The paper provides a mathematical framework for training the proposed autoencoder along with illustrative examples that demonstrate its ability to learn improved spectral efficiency relative to traditional orthogonal and biorthogonal modulations.