A Novel Hybrid Whale Optimization Algorithm-Based SLM (HWOA-SLM) for PAPR Reduction in Optical IM/DD OFDM Systems

This paper presents a comprehensive analysis and simulation of a cost-effective optical Intensity-Modulation/Direct-Detection (IM/DD) Orthogonal Frequency Division Multiplexing (OFDM) system. Implemented via a MATLABR2024a and OptiSystem 23 co-simulation environment, the study evaluates a 4-QAM modulated link over a 120 km transmission distance, providing detailed investigations into signal spectral properties and constellation characteristics. To address the critical performance limitation posed by high Peak-to-Average Power Ratio (PAPR), a novel Hybrid Whale Optimization Algorithm with Selective Mapping (HWOA-SLM) is proposed. Simulation results demonstrate that the proposed scheme significantly outperforms conventional reduction techniques; specifically, at a Complementary Cumulative Distribution Function (CCDF) of 10−2 and a fixed computational budget of 256 evaluations, the HWOA-SLM achieves a PAPR reduction gain of 3.9 dB relative to the original OFDM signal. Furthermore, in terms of algorithmic efficiency, it outperforms standard Genetic Algorithm (GA) and WOA-based SLM techniques by approximately 0.4 dB under identical computational budgets. Parametric analysis further confirms that increasing population size and iteration numbers consistently improves convergence, thereby minimizing non-linear distortions and enhancing signal integrity. Moreover, the technique exhibits superior Bit Error Rate (BER) performance, delivering Optical Signal-to-Noise Ratio (OSNR) gains of 0.63 dB, 1.31 dB, and 2.0 dB over standard WOA-SLM, GA-SLM, and conventional SLM, respectively. Conclusively, the HWOA-SLM offers a favorable trade-off between computational complexity and reduction efficiency, validating its potential for reliable, high-speed optical communication networks.