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.

翻译：本文针对有限字符集输入的双用户Z-干扰信道（ZIC），设计了一种基于深度自编码器（DAE）的端到端通信架构。该架构联合优化两组编码器/解码器对，生成能根据干扰强度动态调整星座形状的干扰感知星座图，以最小化误码率（BER）。在DAE中引入同相/正交（I/Q）功率分配层，既可确保平均功率约束，又能使架构生成非均匀形状的星座图。与正交幅度调制等标准均匀星座相比，该设计可带来额外增益。随后将该架构扩展至非完美信道状态信息（CSI）场景，并分别考察了由估计误差和量化误差导致的CSI不完善性。将所提DAE-ZIC方法与旋转星座等两种基线方法进行性能对比，结果表明在完美与非完美CSI条件下，该架构均能显著提升ZIC性能。仿真结果显示，在所有干扰机制（弱、中、强干扰）下均能实现性能改善，且改善幅度随信噪比（SNR）持续增大。例如，在弱干扰场景下，当每符号传输2比特且SNR>15dB时，相较于最具竞争力的传统方法可实现超过一个数量级的误码率降低。当存在量化误差时，性能提升可达约两个数量级，表明相较于传统方法，DAE-ZIC对干扰具有更强的鲁棒性。