I. Introduction
In Recent years, optical wireless communication (OWC) has become an increasingly promising candidate for next-generation communications (6G) [1], [2]. Since ensuring complete coverage of signals is crucial for integrated ground, airborne, and satellite networks in 6G era, optical wireless communication stands out as an effective solution for free-space data transmission due to its cost-effectiveness, easy deployment, high bandwidth, and enhanced security benefits [3], [4], [5]. However, in practical applications, OWC systems will be affected and damaged in many ways. Geometric loss, pointing error, atmospheric attenuation and turbulence effects are all important challenges in its actual deployment and application [6]. Taking free space optical (FSO) communication as an example, atmospheric turbulence is the main factor affecting its transmission performance and has always been a long-term problem that needs to be solved [7]. Channel modeling constitutes an indispensable phase in the realm of OWC system research and optimization [8]. A meticulously crafted, realistic approximation of the OWC channel model plays a pivotal role in steering system design towards enhanced performance outcomes. Traditional channel modeling techniques invariably resort to approximating the channel through parametric models grounded in theoretical assumptions and specific channel effects [9]. However, traditional channel models often only include simplified assumptions that ignore effects such as scattering and depolarization [10], resulting in limited performance when considering multiple complex channel effects and poor accuracy in real channels.