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 values of capacity. Due to the current standard restrictions, it is difficult to change the constellation both on the mapper or demapper side. In this case, one can optimize the constellation only on the mapper or the demapper side using original methodology. By the numerical calculating of capacity, we show that the optimal geometric constellation depends on SNR. Optimization is carried out by maximizing mutual information (MI). The MI function describes the amount of information being transmitted through the channel with the optimal encoding. To prove the effectiveness of this approach we provide numerical experiments in the modern physical level Sionna simulator using the realistic LDPC codes and the MIMO 5G OFDM channels.

翻译：在无线通信系统中,有多个信号传输阶段。其中有:绘制和映射将一个位数序列转换成一个复杂数字序列,反之亦然。这一操作由星座--系统 -- -- 由复杂平面上一组标签点进行。通常,星座的几何是固定的,星座点是统一的,例如,同一四面振动调节点(QAM)用于广泛的信号-音调比率(SNR)。通过消除星座的统一性,有可能实现更大的能力值。由于目前的标准限制,很难改变星座----在复杂平面上的星座----由一组有标签的点-星座---进行。在这种情况下,一个人只能利用原始方法优化地标的星座或星座侧的星座。根据对能力的计算,我们通过最大程度的相互信息来进行优化。MI函数描述通过频道传送的信息数量,并用最佳的编码来描述。在地图或地图-地图-地图-上,我们用现实的SDMDM 的物理实验提供Sion-DM的现代水平。</s>