  A deep autoencoder (DAE)-based end-to-end communication over the two-user
Z-interference channel (ZIC) with finite-alphabet inputs is designed in this
paper. The design is for imperfect channel state information (CSI) where both
estimation and quantization errors exist. The proposed structure jointly
optimizes the encoders and decoders to generate interferenceaware
constellations that adapt their shape to the interference intensity in order to
minimize the bit error rate. A normalization layer is designed to guarantee an
average power constraint in the DAE while allowing the architecture to generate
constellations with nonuniform shapes. This brings further shaping gain
compared to standard uniform constellations such as quadrature amplitude
modulation. The performance of the DAE-ZIC is compared with two conventional
methods, i.e., standard and rotated constellations. The proposed structure
significantly enhances the performance of the ZIC. Simulation results confirm
bit error rate reduction in all interference regimes (weak, moderate, and
strong). At a signal-to-noise ratio of 20dB, the improvements reach about two
orders of magnitude when only quantization error exists, indicating that the
DAE-ZIC is highly robust to the interference compared to the conventional
methods.
