## 1 Introduction  
Compared with underwater radio frequency (RF) communication and underwater acoustic communication, the underwater optical wireless communication (UOWC) system has many advantages including high bandwidth, low time latency, and great security [1]. UOWC is widely applied in marine resources exploration, environment monitoring, and marine defense [2, 3]. Especially for underwater Internet of Things (UIoT) scenarios, a strong robust communication system with high flexibility is necessary to realize information interaction between mobile nodes such as autonomous underwater vehicle (AUV) swarms, or between AUV and underwater fixed sensor networks. Therefore, the UOWC system based on the light-emitting diode (LED) light source has attracted more attention due to its advantages of large divergence angle, low system costs, and temperature insensitivity, which makes it more suitable for the high-speed interconnection of UIoT devices at short and medium ranges. In addition, LED light sources can be effectively compatible with underwater lighting equipment, and the progress of LED technology in recent years has enabled high-dynamic UOWC systems with small size and low power consumption [4]. Complex underwater channel environments, including absorption, scattering and turbulence effects, are the main constraints on the communication performance of UWOC systems [5, 6, 7]. Underwater channel modeling is the primary requirement for analyzing the transmission characteristics of optical signals under different seawater conditions. Commonly used methods of underwater channel modeling are based on the Beer-Lambert law and radiative transfer equation (RTE) [8]. The Beer-Lambert law is generally used to evaluate the transmission loss of the optical signal power without considering the scattering effect. The RTE method describes the energy conservation for light propagating over an absorbing and scattering medium [9]. However, RTE is expressed by an integro-differential equation, which makes it complicated to achieve analytical solutions. The Monte Carlo (MC) simulation evaluates the transmission characteristics of the system by tracking large numbers of photons, and has become the most widely used RTE numerical solution method in recent years due to its high flexibility and accuracy [10]. [PERSON] et al. proposed a method to model turbulence as a scattering phenomenon, and used double gamma function to simulate the frequency response of three different turbulence values in harbor seawater [11]. Combining the stochastic model with the lognormal turbulence model, the BER performance of the multiple-input single-output (MISO) UOWC systems was evaluated under weak turbulence, absorption, and scattering conditions [12]. A comprehensive channel model with absorption, scattering, and weak turbulence effects was considered, and the optimal power allocation policies were obtained to achieve smaller bit error rates (BERs) for both MISO and multiple-input multiple-output (MIMO) systems [13]. Most of the above studies are focused on point-to-point underwater link structures by using the MC simulation method. For underwater highly dynamic and complex channel scenarios, it is difficult to maintain the relative stability of the transceiver to ensure link alignment [14]. At the receiving terminal, a lens array structure was proposed to achieve effective convergence of received optical signals at different incident angles, which can improve the dynamic response range of the receiver [15]. On the other hand, common optimization methods focus on using LED arrays at the transmitting terminal to enhance the signal coverage, which can also alleviate the alignment requirements of UOWC systems over short and medium ranges. Therefore, for the LED array-based UOWC system, it is more important to improve the system robustness under complex dynamic seawater environments through the optimization of the LED array, which in turn reduces the alignment difficulty of the UOWC system. [PERSON] et al.