## 3 Design of Proposed Intelligent FSO System
### Transmitter Module  
At the transmitter module, a 10 Gbps electrical signal is encoded on a bit stream produced by a Pseudo-Random Bit Sequence Generator (PRBSG) and modulated by an optical carrier generated from continuous wave (CW) laser operating at 1550 nm via a Mach-Zehnder Modulator (MZM), which facilitates high-speed modulation while preserving signal integrity and enabling reliable optical data transmission. Real-time feedback from the received eye diagram, a switching mechanism in the project, is employed to dynamically choose between transmission with or without optical amplification. A booster optical amplifier with a maximum gain of 25 dB is activated if any of the following conditions are met: the classified BER value is larger than \(10^{-4}\), the BER predicted from the eye diagram using LeNet is larger than \(10^{-4}\), or the Q-factor predicted from the eye diagram using either LeNet (for first dataset) or Wide ResNet (for the second dataset) is below the  
Figure 4: Layout of proposed intelligent FSO system. specified threshold. The amplification setup adopts a dual-stage configuration, comprising a pre-channel optical amplifier with a maximum gain of 25 dB and a post-channel amplifier offering up to 10 dB gain. This adaptive approach enhances transmission reliability by dynamically adjusting the gain in the system to accommodate the fluctuation of atmospheric conditions. Additionally, after the signal is transmitted using the selected amplifier configuration, the receiver monitors the actual BER of the received signal in real time. If this measured BER exceeds the predefined threshold, the system infers that the initial prediction may have been based on a suboptimal or corrupted eye diagram input. In such cases, the system can either request retransmission with an adjusted amplifier configuration or prompt the re-capture of the eye diagram for reanalysis. This feedback pathway ensures that the system adapts dynamically to unforeseen signal degradation and maintains the desired quality of service. The operational logic of the switching mechanism is summarized in Algorithm 1. ```
Input: received eye diagram (I) Output: Amplifier configuration decision
1: Initialize:
2: Define BER and Q-factor thresholds as: \(BER_{th}=10^{-4}\) and \(Q_{th}=4.07\)
3:Acquire eye diagram:  Capture the received eye diagram from the receiver. 4:Valid input:  Check if eye diagram is valid  If invalid:  Request re-acquisition or apply error-handling procedure  Return to step 3
5:Predict performance metrics:  a. For BER:  Classification of BER \(\leftarrow\) CNN (eye diagram)  Predicted BER \(\leftarrow\) LeNet (eye diagram dataset1)  b. For Q-factor  Predicted BER \(\leftarrow\) LeNet (eye diagram dataset1)  Predicted BER \(\leftarrow\) Wide ResNet (eye diagram dataset2)
6:Evaluate conditions:
7:If any of the following conditions are satisfied:  Classified BER \(=\) 0 (larger than \(BER_{th}\))  Predicted BER \(>BER_{th}\)  Predicted Q \(-\) factor \(<Q_{th}\)
8:Then  Select dual-stage amplification -Pre-channel amplifier: Max. gain = 25 dB -Post-channel amplifier: Max. gain = 10 dB
9:Else:  Transmit without amplification
10:Configure transmission:  Apply the selected amplifier configuration
11:Transmit signal  Launch the modulated optical signal through the FSO channel

### FSO Channel

The modulated optical signal is subsequently transmitted through the FSO channel. The proposed framework is adaptable to various atmospheric conditions, including haze, fog, rain, snow, and cloud cover. In this particular investigation, the focus is placed on dry snow and cloud scenarios, aligning with deployment in regions frequently affected by snowfall. The impact of snow-induced attenuation on FSO performance is analyzed by distinguishing between two types of snowfall: dry snow and wet snow.