Deep Autoencoder-based Z-Interference Channels with Perfect and
  Imperfect CSI
Xinliang Zhang Mojtaba Vaezi
A deep autoencoder (DAE)-based structure for endto-end communication over the
two-user Z-interference channel (ZIC) with finite-alphabet inputs is designed
in this paper. The proposed structure jointly optimizes the two encoder/decoder
pairs and generates interference-aware constellations that dynamically adapt
their shape based on interference intensity to minimize the bit error rate
(BER). An in-phase/quadrature-phase (I/Q) power allocation layer is introduced
in the DAE to guarantee an average power constraint and enable the architecture
to generate constellations with nonuniform shapes. This brings further gain
compared to standard uniform constellations such as quadrature amplitude
modulation. The proposed structure is then extended to work with imperfect
channel state information (CSI). The CSI imperfection due to both the
estimation and quantization errors are examined. The performance of the DAEZIC
is compared with two baseline methods, i.e., standard and rotated
constellations. The proposed structure significantly enhances the performance
of the ZIC both for the perfect and imperfect CSI. Simulation results show that
the improvement is achieved in all interference regimes (weak, moderate, and
strong) and consistently increases with the signal-to-noise ratio (SNR). For
example, more than an order of magnitude BER reduction is obtained with respect
to the most competitive conventional method at weak interference when SNR>15dB
and two bits per symbol are transmitted. The improvements reach about two
orders of magnitude when quantization error exists, indicating that the DAE-ZIC
is more robust to the interference compared to the conventional methods.