Geometric Constellation Shaping with Low-complexity Demappers for Wiener Phase-noise Channels

Mapper Side Geometric Shaping for QAM Constellations in 5G MIMO Wireless Channel with Realistic LDPC Codes

In wireless communication systems, there are many stages for signal transmission. Among them, mapping and demapping convert a sequence of bits into a sequence of complex numbers and vice versa. This operation is performed by a system of constellations~ -- by a set of labeled points on the complex plane. Usually, the geometry of the constellation is fixed, and constellation points are uniformly spaced, e.g., the same quadrature amplitude modulation (QAM) is used in a wide range of signal-to-noise ratio (SNR). By eliminating the uniformity of constellations, it is possible to achieve greater val…

Optimization of Geometric Constellation Shaping for Wiener Phase Noise Channels with Varying Channel Parameters

We present a novel method to investigate the effects of varying channel parameters on geometrically shaped constellations for communication systems employing the blind phase search algorithm. We show that introduced asymmetries significantly improve performance if adapted to changing channel parameters.

针对维纳相位噪声信道下Viterbi-Viterbi载波相位估计的优化几何星座整形

Optimized Geometric Constellation Shaping for Wiener Phase Noise Channels with Viterbi-Viterbi Carrier Phase Estimation

针对维纳相位噪声信道，提出通过几何星座整形修改发射星座，将标准V&V算法扩展到更高阶调制格式。

利用可微分盲相位搜索对 Wiener 相位噪声信道的星座整形进行端到端优化

End-to-end Optimization of Constellation Shaping for Wiener Phase Noise Channels with a Differentiable Blind Phase Search

本文通过可微分盲相位搜索实现 Wiener 相位噪声信道下几何与概率星座的端到端联合优化，提出无导频鲁棒调制方案，并在 64 进制系统中取得显著增益。

使用置信传播的维纳相位噪声信道的近似最大后验载波相位估计器

Approximate Maximum a Posteriori Carrier Phase Estimator for Wiener Phase Noise Channels using Belief Propagation

针对BPS算法在概率整形星座下次优的问题，提出基于置信传播的近似最大后验载波相位估计器，并与标准及改进BPS算法比较性能。

基于神经网络的单载波联合通信与感知：损失设计、星座成形与预编码

Neural Network-Based Single-Carrier Joint Communication and Sensing: Loss Design, Constellation Shaping and Precoding

本文研究单载波JCAS中高阶调制对感知性能的影响，用神经网络实现收发与感知模块，并借助Cramér-Rao界和互信息设计与SNR及快照数解耦的损失。