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.

通过基于深度自编码器的结构，本文设计了一种用于两用户 Z 干扰信道的端到端通信的模型，该模型优化编码器 / 解码器对并生成能够根据干扰强度动态调整形状以最小化误码率的干扰感知星座。该结构在深度自编码器中引入了相位 / 象限分配层来保证平均功率限制，并使得该架构能够生成非均匀形状的星座，相比于标准的均匀星座（如正交振幅调制），获得了进一步的增益。该结构还可以与不完美的信道状态信息（CSI）一起工作，考虑了估计和量化误差所带来的 CSI 不完美性。模拟结果表明，在所有干扰强度范围（弱、中、强）和信噪比（SNR）上，DAE-ZIC 都显著提高了 ZIC 的性能，且该改进随着 SNR 的增加而持续增加。当 SNR > 15dB 且传输每个符号的比特数为两个时，在弱干扰下，与最有竞争力的传统方法相比，误码率可以降低一个数量级。当存在量化误差时，改进达到大约两个数量级，这表明 DAE-ZIC 相比于传统方法对干扰具有更强的鲁棒性。

基于深度自编码器的具有完美和不完美 CSI 的 Z 干扰信道

Deep Autoencoder-based Z-Interference Channels with Perfect and  Imperfect CSI

This paper studies the over-the-air computation (AirComp) in an orthogonal
frequency division multiplexing (OFDM) system with imperfect channel state
information (CSI), in which multiple single-antenna wireless devices (WDs)
simultaneously send uncoded signals to a multi-antenna access point (AP) for
distributed functional computation over multiple subcarriers. In particular, we
consider two scenarios with best-effort and error-constrained computation
tasks, with the objectives of minimizing the average computation mean squared
error (MSE) and the computation outage probability over the multiple
subcarriers, respectively. Towards this end, we jointly optimize the transmit
coefficients at the WDs and the receive beamforming vectors at the AP over
subcarriers, subject to the maximum transmit power constraints at individual
WDs. First, for the special case with a single receive antenna at the AP, we
propose the semi-closed-form globally optimal solutions to the two problems
using the Lagrange-duality method. It is shown that at each subcarrier, the
WDs' optimized power control policy for average MSE minimization follows a
regularized channel inversion structure, while that for computation outage
probability minimization follows an on-off regularized channel inversion, with
the regularization dependent on the transmit power budget and channel
estimation error. Next, for the general case with multiple receive antennas at
the AP, we present efficient algorithms based on alternating optimization and
convex optimization to find converged solutions to both problems.

本文研究了具有不完美信道状态信息的正交频分复用系统中，通过多个子载波同时发送信号进行分布式功能计算的无线设备的发射系数和访问点的接收波束成形向量的联合优化问题。

OFDM 系统中带有不完全信道状态信息的无线计算

Over-the-Air Computation in OFDM Systems with Imperfect Channel State  Information

A multiantenna multiuser broadcast channel with transmitter beamforming and
user selection is considered. Different from the conventional works, we
consider imperfect channel state information (CSI) which is a practical
scenario for multiuser broadcast channels. We propose a robust regularized
zero-forcing (RRZF) beamforming at the base station. Then we show that the RRZF
outperforms zero-forcing (ZF) and regularized ZF (RZF) beamforming even as the
number of users grows to infinity. Simulation results validate the advantage of
the proposed robust RZF beamforming.

研究了一种多天线多用户广播信道，考虑了不完美的信道状态信息，提出了基站上的稳健正则化零强制波束成形，使用 RRZF 的方案优于 ZF 和 RZF，仿真结果验证了提出的稳健 RZF 波束成形的优势。