## 2 Related Work
### Motivation  
As discussed previously, several studies have addressed the channel characterization and temporal response modeling of UWOC links. The Monte Carlo-based simulation method can provide the required precise representation of the underwater channel with high resolution as compared to experimental and analytical methods given that it uses the exact volume scattering phase functions and absorption coefficients [22]. It is also the most widely used technique for predicting the causes and effects of temporal and spatial dispersion in UWOC. In this work, we have designed a simple, scalable, and comprehensive statistical model based on Monte Carlo simulations. Our proposed model forms impulse responses of the laser-based underwater wireless optical communication link by first characterizing the channel and then generating a discrete histogram of the total received power. This histogram contains the received photons which are scattered more than once and have experienced absorption of varying degrees. We explore the temporal spreading of light with more realistic underwater conditions. Therefore, we use the Petzold's measured volume scattering phase functions to simulate multiple scattering. Additionally, we perform simulations to determine the performance of such systems in three different water types in terms of BER and average distance traveled by photons.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Study Type** & **Advantages** & **Limitations** & \\ \hline \multirow{7}{*}{Simulation-based Modeling} & - Flexible & & \\  & - Robust & & \\  & - Capable of imitating the optical propagation & & \\  & loss underwater. & & \\  & - Exploits statistical nature of the optical scattering & & \\  & channel by evaluating a large number of photons & & \\  & (generally \(10^{7}\)). & & - Time consuming \\  & - Variables, e.g., propagation distance, receiver & & - Resllective waves are usually not modeled. \\  & - Various, e.g., propagation distance, receiver & & \\  & - Aperture and FoV can be easily adjusted to real & & \\  & - The most general solutions for solving RTE. & & \\  & - Imitates open waters without wall boundaries. & & \\ \hline \multirow{7}{*}{Experimental Modeling} & - Measured channel capacity is different from & & \\  & & actual underwater channel capacity. & \\  & & - Surface reflective effects are not quantifiable. & \\  & & - Most of the variables of water tank experiment & \\  & - Experiments are mostly conducted in a laboratory & & - rate unalterable, e.g., transmission distance, \\  & - Experiments are mostly conducted in a laboratory & & - Initial system set up cost is high. \\  & - Surface waves can be generated. & & - Ignores the unknown system design aspects, e.g., amount of absorption due to tank wall coatings, and scattering function of the tank walls. \\  & - Ability to validate the other two methods. & & - Exact volume scattering function (VSF), initial beam conditions, and water albedo values are usually taken from other published work. \\  & & - Unable to deduce the effect of transmitter & \\  & - Capable of overcoming the challenges of & - Accurate solutions are restrained by a chain \\  & - Experimental methods & & - Accurate solutions are restrained by a chain \\  & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of the advantages and limitations of the three types of evaluation methods.