## 4 Results and Discussion
### Computation Data Visualisation
The eye diagram in Figure 7f for Harbor water reveals that the ISI component level is higher than that for Coastal water for the same transmitted optical pulse \(h_{t}\) with a pulse width (pw) equals to 0.25/T. We conducted several runs for the Coastal water scenarios to quantify the ISI degradation to the signal. We noticed that \(h_{t}\) with pw = 0.5/T in Coastal water gets nearly the same filter output \(\tau_{f}\) for Harbor water with pw = 0.25. This reflects that even a narrow pw might not be enough to limit the impact of ISI in Harbor waters. One of the techniques to measure the system performance is provided by the extent of the eye-opening (O\({}_{\text{eye}}\)) in the eye diagram, which is typically affected by the dispersive and nonlinear effects accumulated inside the propagation channel [25]. Hence, to further examine the performance of the optimum filter unit \(h_{f}\), which is the solution of Equation (22), we used four water channel models of \(h_{c}\) [DGF, WDGF, BP, CEAPF] shown in Figure 2, at different transmitted pw values of \(h_{t}\) [0.1, 0.3, 0.5] to produce the eye diagrams of the \(\tau_{f}\), which is the output of the optimum filter \(h_{f}\) (see Figure 3). The assessment indicator of the \(\tau_{f}\) eye diagrams is based on the O\({}_{\text{eye}}\) which is marked in red in Figure 8 (for Coastal water) and Figure 9 (for Harbor water). The importance of O\({}_{\text{eye}}\) is that its value is proportional to the Q-Factor. The Q-Factor determines the BER of the receiver system [25; 29; 30; 31; 32]. We can draw three observations from Figures 8 and 9. First, O\({}_{\text{eye}}\) decreases with increasing the pw; second, within the same water channel, the h\({}_{c}\) models predict identical values of O\({}_{\text{eye}}\) at different pw values; and third is that the O\({}_{\text{eye}}\) reduction in Harbor water is relatively smaller than that of the Coastal water. Regarding the first observation, optimum filter h\({}_{t}\) reduces O\({}_{\text{eye}}\) by nearly 10-15% for a five-times increase in pw. In other words, we can conclude that the optimum h\({}_{f}\) manages the power dispersion correctly. The changes in pw values can be considered a pulse broadening simulation due to ISI impairment sources like scattering and scintillation. Hence, we can conclude that the proposed optimum filter h\({}_{f}\) efficiently deals with the ISI. Figure 10 shows the BER performance at the optical receiver system level, and the optimum filter \(h_{f}\) is part of it. Figure 10a is for Coastal water, and Figure 10b is for Harbor water. It is easy to observe that using the same transmitted power across different transmitted pw values, the Q-Factor decreases in the same manner that BER declines (i.e., better performance) with increasing power. Figure 8: Use Case III: Eye-opening (in red) for Coastal Water. The eye diagrams of the filter output \(r_{f}(t)\) (Equation (5a)) for \(s(t)\) (Equation (2)) pulse-width (pw) set {0.1, 0.3, 0.5} for four propagation channel models of \(h_{c}(t)\) [DGF, WDGF, BP, CEAPF]. Bit rate: 200 Mbit, water link span: 100 m.  
Figure 9: Use Case III: Eye-opening (in red) for Harbor Water. The eye diagrams of the filter output \(r_{f}(t)\) (Equation (5a)) for \(s(t)\) (Equation (2)) pulse-width (pw) set [0.1, 0.3, 0.5] for four propagation channel models of \(h_{c}(t)\) [DGF, WDCF, BP, CEAPF] bit rate: 200 Mbit, water link span: 100 m.  
We used BER vs. Q-Factor and Q-factor vs. Pulse Width to complement the eye diagrams instead of BER vs. OSNR because, in this paper, we are not discussing the UWOC link power budget. Also, the Q-factor, as discussed in [25; 30; 31; 32], is a suitable measure to investigate eye diagram behaviors.