This paper presents design methods for highly efficient optimisation of geometrically shaped constellations to maximise data throughput in optical communications. It describes methods to analytically calculate the information-theoretical loss and the gradient of this loss as a function of the input constellation shape. The gradients of the \ac{MI} and \ac{GMI} are critical to the optimisation of geometrically-shaped constellations. It presents the analytical derivative of the achievable information rate metrics with respect to the input constellation. The proposed method allows for improved design of higher cardinality and higher-dimensional constellations for optimising both linear and nonlinear fibre transmission throughput. Near-capacity achieving constellations with up to 8192 points for both 2 and 4 dimensions, with generalised mutual information (GMI) within 0.06 bit/2Dsymbol of additive white Gaussian noise channel (AWGN) capacity, are presented. Additionally, a design algorithm reducing the design computation time from days to minutes is introduced, allowing the presentation of optimised constellations for both linear AWGN and nonlinear fibre channels for a wide range of signal-to-noise ratios.
翻译:本文介绍了高效优化几何形星座以最大限度地优化光学通信数据输送量的设计方法,介绍了作为输入星座形状函数分析计算信息-理论损失和这种损失的梯度的方法。 \ac{MI} 和\ac{GMI} 的梯度对于优化几何形星座至关重要。 它介绍了可实现的信息率指标在输入星座方面的分析衍生物。 提议的方法可以改进高基和高维星座的设计,以优化线性和非线性纤维传输量。 近能力在2维和4维中达到高达8192点的星座,在0.06位位/位/位/二代相位(GMI)的添加式白盖子噪声频道能力范围内实现一般化的相互信息。 此外,还引入了设计算法,将设计计算时间从几天缩短到几分钟,从而能够展示线性AWGN的优化星座和广范围信号至信标的非线性纤维信道的优化星座。