This paper presents a comprehensive analysis of the information-energy capacity region for simultaneous lightwave information and power transfer (SLIPT) systems over lognormal fading channels. Unlike conventional studies that primarily focus on additive white Gaussian noise channels, we study the complex impact of lognormal fading, which is prevalent in optical wireless communication systems such as underwater and atmospheric channels. By applying the Smith's framework for these channels, we demonstrate that the optimal input distribution is discrete, characterized by a finite number of mass points. We further investigate the properties of these mass points, especially at the transition points, to reveal critical insights into the rate-power trade-off inherent in SLIPT systems. Additionally, we introduce a novel cooperative information-energy capacity learning framework, leveraging generative adversarial networks, to effectively estimate and optimize the information-energy capacity region under practical constraints. Numerical results validate our theoretical findings, illustrating the significant influence of channel fading on system performance. The insights and methodologies presented in this work provide a solid foundation for the design and optimization of future SLIPT systems operating in challenging environments.

翻译：本文全面分析了在对数正态衰落信道上同时进行光波信息与功率传输（SLIPT）系统的信息-能量容量域。不同于主要关注加性高斯白噪声信道的传统研究，我们研究了对数正态衰落的复杂影响——这种衰落广泛存在于水下及大气信道等光无线通信系统中。通过应用Smith框架分析此类信道，我们证明最优输入分布是离散的，且由有限个质量点表征。我们进一步探究了这些质量点的性质，特别是在过渡点处的特性，以揭示SLIPT系统固有的速率-功率权衡的关键机理。此外，我们引入了一种新颖的协同信息-能量容量学习框架，利用生成对抗网络在实际约束下有效估计并优化信息-能量容量域。数值结果验证了我们的理论发现，阐明了信道衰落对系统性能的显著影响。本文提出的见解与方法为在挑战性环境下设计与优化未来SLIPT系统奠定了坚实基础。