SLM-based ABC and PSO implementation for PAPR reduction in FBMC/OQAM System

This research work compares two approaches, ABC-SLM and PSO-SLM, leveraging Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) optimization techniques to address the challenge of high Peak-to-Average Power Ratio (PAPR) in Filter Bank Multicarrier (FBMC) systems. High PAPR poses a significant hurdle in multi-carrier systems, impacting efficiency and performance. Traditionally, the Selective Mapping (SLM) technique has been employed to mitigate PAPR issues. However, conventional SLM methods may not fully exploit optimization opportunities. In this research, ABC and PSO optimizations are integrated into the SLM-based PAPR reduction scheme, acting as phase optimizers. When compared to the conventional SLM-based FBMC signal, both ABC-SLM and PSO-SLM exhibit substantial PAPR reduction. Simulation results show that original SLM alone achieves a PAPR of 5.19 dB. ABC-SLM achieves a PAPR of 5.16dB and ABC-PSO achieves 4.97 dB, at a complementary cumulative distribution function value of 10^-3, the FBMC signal incorporating ABC-SLM and PSO-SLM achieves a remarkable reduction in PAPR