Modeling and Simulink of Optical Fiber Nonlinearity Compensation in DWDM System
Implementation Plan:
************************
Step 1: Initially, we construct a DWDM design with optical fibre connectivity configurations.
Step 2: Then, we collect the simulated raw optical signals and sensor readings data and preprocess using OSNR preprocessor technique.
Step 3: Next, we perform feature extraction using MSD (Mean Squared Deviation) Algorithm with NN to recognize the pattern based on collected data.
Step 4:Next, we train the data using the Supervised Multi-Level Regression (SMR-DWDM) algorithm to detect optimized BER / FWM.
Step 5: Next, we optimize and fine tune the communication data using the “FM-NCD” Algorithm for minimizing signal loss and signal distortion.
Step 6: Next, we detect and mitigate Nonlinear effects using MA-DFE (Magnitude Assisted Decision Feedback Equalizer) algorithm with LDSP technique.
Step 7: Finally, we plot performance metrics of the following
7.1: Input Optical Power (dBm) Vs Bit Error Rate (BER)
7.2: Input Optical Power (dBm) Vs Optical Signal-to-Noise Ratio (dB)
7.3: Input Optical Power (dBm) Vs Computational Complexity(%)
7.4: Input Optical Power (dBm) Vs Accuracy (%)
Software Requirements:
**************************
1. Development Tool: Matlab-R2023a or above
2. Operating System: Windows-10 (64-bit) or above
Note:
*******
1) If the proposed plan does not fully align with your requirements, please provide all necessary details—including steps, parameters, models, and expected outcomes—in advance. Kindly ensure that any missing configurations or specifications are clearly outlined in the plan before confirming.
2) If there’s no built-in solution for what the project needs, we can always turn to reference models, customize our own, different math models or write the code ourselves to fulfil the process.
3) If the plan satisfies your requirement, Please confirm with us.
4) Project based on Simulation only.
We perform with an Existing Approach Ref 4: Title:- Enhanced Performance of Artificial-Neural-Network-Based Equalization for Short-Haul Fiber-Optic Communications
