Enhancing Nano-Optoelectronic Orthogonal Frequency Division Multiplexing Passive Optical Networks (OFDM-PONs) via SLM-DFOA: A Low-Complexity PAPR Reduction Approach

Abstract

High peak-to-average power ratio (PAPR) remains a critical challenge in orthogonal frequency division multiplexing passive optical networks, particularly in nano-optoelectronic applications where laser nonlinearities and power efficiency are paramount. Conventional PAPR reduction techniques like selective mapping (SLM) and partial transmit sequence (PTS) suffer from high computational complexity, limiting their practicality in high-speed optical communication systems. This paper introduces a novel SLM-based discrete forest optimization algorithm (SLM-DFOA) that significantly reduces PAPR while maintaining low computational overhead. We present a comprehensive simulation of a 40 Gb/s OFDM-PON transmitted over 50 km of single-mode fiber, modeled using OptiSystem and MATLAB. The proposed SLM-DFOA method achieves a remarkable 5.4 dB reduction in PAPR, lowering it from 10.5 dB to 5.1 dB at a complementary cumulative distribution function (CCDF) of 10-3, alonwith a 6.1 dB improvement in bit error rate (BER) compared to the original OFDM signal. The algorithm demonstrates superior computational efficiency, offering an 86.59% complexity reduction over PTS with discrete invasive weed optimization (PTS-DIWO) and 53.13% over genetic algorithm-based SLM (SLM-GA). Through detailed parameter analysis, we identify optimal DFOA configurations, including an area limit of 5 and local seeding changes (LSC) of 2, which ensure robust performance under nano-optoelectronic hardware constraints. With a power-saving efficiency of 51.4%, the SLM-DFOA technique emerges as a promising solution for energy-efficient, high-speed optical communication systems, including 5G fronthaul, visible light communication (VLC), and future nano-photonic networks.