## 6 Results and Discussions  
The BER performance of the received signals is analyzed at the medical center using BER plots for different weather conditions such as light haze, heavy haze, and heavy fog while considering the log-normal channel model. These conditions were simulated in this work by varying the value of the atmospheric attenuation coefficient (\(\alpha_{atm}\)). Therefore, the values of \(\alpha_{atm}\) for light haze, heavy haze, and heavy fog used in the simulation were  
Figure 3: BER versus (**a**,**c**,**e**) Received power plots for atmospheric attenuation of 2 dB/km, 11 dB/km, and 21 dB/km, respectively and (**b**,**d**,**f**) Q-factor plots for atmospheric attenuation of 2 dB/km, 11 dB/km, and 21 dB/km, respectively. A value of the \(C_{n}^{2}\) parameter equal to \(5\times 10^{-16}\) m\({}^{-2/3}\) was used. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Sr. No** & **Parameter** & **Value** \\ \hline
1 & Power of CW lasers & 10 dBm \\
2 & Data rate of sensors & 50 kbps \\
3 & Extinction ratio of MZMs & 30 dB \\
4 & Gain of optical amplifier & 25 dB \\
5 & Noise figure of optical amplifier & 4 dB \\
6 & Range of PSO channel & 1 km \\
7 & Refractive index structure parameter & \(5\times 10^{-16}\) m\({}^{-2/3}\) \\
8 & Receiver aperture diameter & 20 cm \\
9 & Transmitter aperture diameter & 5 cm \\
10 & Beam divergence & 2 mrad \\
11 & Responsivity of PDs & 0.9 A/W \\
12 & Bandwidth of OBPFs & 0.08 nm \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Important simulation parameters. 2 dB/km, 11 dB/km, and 21 dB/km, respectively [48]. Similarly, the weak turbulence regime was characterized by a \(C_{n}^{2}\) value of \(5\times 10^{-16}\) m\({}^{-2/3}\). The BER values were calculated using the statistical method in OptiSystem by observing the eye diagram of the received signal at the output of the lowpass filter (LPF), as shown in the inset of Figure 2. The optical power of the incident signal at the PD was varied using a variable optical attenuator (VOA) to determine its effect on the BER value of the received signal. The optical power was measured using a power meter before the PD. Figure 3 shows the BER and Q-factor versus the received optical power plots for different weather conditions. For simplicity, only four on-body sensors are randomly selected here to discuss their performance. The minimum value of optical power received at the PD that is required to achieve a BER of \(10^{-9}\) is called the receiver sensitivity. It can be seen from Figure 3a that the receiver sensitivity value of sensors 1, 2, 5, and 6 is around \(-21.5\) dBm for \(\alpha_{atm}\) = 2 dB/km. The receiver sensitivity value of sensors 1, 2, 5, and 6 becomes \(-19.6\) dBm for \(\alpha_{atm}\) = 11 dB/km, as shown in Figure 3c. A power penalty of around 1.9 dBm is observed on increasing the value of \(\alpha_{atm}\) from 2 dB/km to 11 dB/km. Similarly, Figure 3e shows that the receiver sensitivity of sensors 1, 2, 5, and 6 is around \(-17.5\) dBm. A penalty of 2.1 dBm is noticed on further increasing the value of \(\alpha_{atm}\) from 11 dB/km to 21 dB/km. It is evident that the receiver sensitivity values of the sensors degrade when increasing the value of \(\alpha_{atm}\). The Q-factor plots in Figure 3b,d,f show that the Q-factor values of the sensors typically increase when increasing the received optical power. However, the Q-factor value decreases on increasing the value of \(\alpha_{atm}\), corresponding to a fixed value of the received optical power. To further detail the performance of the sensors, we obtained the eye diagrams of sensor 1 and sensor 5 at the output of the LPFs for different values of \(\alpha_{atm}\); the value of \(C_{n}^{2}\) that we used was \(5\times 10^{-16}\) m\({}^{-2/3}\). It is evident from Figure 4 that intensity variations over the received signals increased upon increasing the value of atmospheric attenuation, which results in the eye diagrams of the received signals deteriorating and closing further.