Compensation of coherent optical communication systems using PSO-optimized SVM

With the explosive growth of data volume, the computational complexity of using digital signal processing methods to compensate for optical fiber dispersion and nonlinear effects is rising rapidly. This paper proposes using a support vector machine (SVM) algorithm to address this challenge in QPSK systems. For nonlinear compensation, Particle Swarm Optimization (PSO) is utilized instead of the traditional grid search method to optimize parameters. The performance of the PSO-SVM method is compared with Dispersion Compensation and Digital Backpropagation (DBP) algorithms. Results indicate that PSO-SVM outperforms both alternatives, providing a more effective solution for managing nonlinear effects in optical communication systems.