## 1 Introduction  
In recent years, visible-light communications (VLC) have developed rapidly, and their application has gradually expanded to outdoor, underwater, underground, and other environments [1]. Due to its high transmission rate, strong system reliability, and low communication delay, visible-light communication technology has become a key candidate technology for 6G mobile communications [2], showing great advantages. High-quality wireless access is one of the main research objectives of VLC systems; in order to achieve this goal, researchers usually focus on the visible-light communication system channel. [PERSON] et al. established a direct vision channel model for visible-light communications based on path loss and received optical power [3]. [PERSON] et al. proposed a visible-light channel model based on the Lambert-Phong reflection mode [4]. [PERSON] et al. established an indoor VLC channel model considering the reflectance of different surfaces [5]. [PERSON] et al. established a universal indoor VLC channel model based on MMCA [6]. [PERSON] et al. established a Gaussian-like luminescence model for a small-divergence angle transmitter [7]. [PERSON] et al. used ray tracing technology to measure and simulate the channel model of a \(2\times 2\) MIMO in a conference room with furniture in order to verify the correctness of the channel model generated using the OpticStudio ray tracing method [8]. With the advent of the era of big data and the rapid development of wireless communication technology, it is conservatively estimated that at least 70% of user terminal data visits are carried out in an indoor scene. Accordingly, the indoor VLC system is one of the most important application scenarios. In an actual indoor VLC system, on the basis of the characteristics of visible light, the existence or movement of obstacles can block the visible-light link and form a certain shadow area. Due to the influence of this shadow, the communication quality of all receiving terminals in the affected area deteriorates sharply and can even lead to communication interruption. In order to specifically explore the influence of shadows resulting from obstacles, [PERSON] et al. proposed a shadow ray tracking (SRT) algorithm [9]. [PERSON] et al. established a channel model for random shadow occlusion based on Poisson stochastic [10]. [PERSON] et al. adopted a method based on random geometry to model and analyze the shadow effect of human obstacles [11]. [PERSON] et al. established a channel model for shadow occlusion under a single light source [12]. [PERSON] et al. established a VLC AP switching model for indoor mobile users based on interrupt probability [13]. [PERSON] and [PERSON] adopted a nonsequential ray tracing method to obtain the channel impulse response and channel characteristics along the random trajectory of moving human obstacles [14]. [PERSON] et al. presented and analyzed the results of a study investigating the influence on the VLC system of human shadows under three different indoor conditions [15]. Similarly, to reduce the influence of shadows due to obstacles, [PERSON] et al. proposed a NutVLC system [16]. [PERSON] et al. proposed a load-balancing scheme combining Li-Fi and Wi-Fi networks [17]. [PERSON] et al. proposed an optical diffraction phenomenon to overcome the effect of shadows on an underwater VLC system [18]. [PERSON] et al. proposed the use of a multidirectional receiver to reduce the shadow effect of obstacles [19]. [PERSON] et al. proposed an increase in the number of light sources to reduce the shadow effect of indoor obstacles [20]. The above studies on the effect of shadows on indoor VLC systems mostly focused on environmental descriptions or analyses of experimental data; however, there remains a lack of systematic theoretical research on the effect of shadows on the channel model of an indoor VLC system. In addition, the above studies only considered the influence of the full shadow generated by obstacles. In reality, obstacles also produce a half shadow in the case of multiple light sources.