PAPR reduction using Intelligent Optimization Algorithms - Alhalabi, Mahmoud;Taspinar, Necmi;Wadi, Mohammed
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In Intensity-Modulated Direct Detection Optical Orthogonal Frequency Division Multiplexing (IM/DD-OOFDM) communication systems, a lower Peak-to-Average Power Ratio (PAPR) is essential for improving system performance. In order to reduce the high PAPR, a Discrete Forest Optimization Algorithm (DFOA) is integrated with the classical Selective Mapping (SLM) method in IM/DD-OFDM system. This approach successfully optimizes the values of phase factors, minimizes the search numbers, and reduces computational complexity. To evaluate the impact of the DFOA-SLM method on PAPR reduction, the parameters…mehr

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Produktbeschreibung
In Intensity-Modulated Direct Detection Optical Orthogonal Frequency Division Multiplexing (IM/DD-OOFDM) communication systems, a lower Peak-to-Average Power Ratio (PAPR) is essential for improving system performance. In order to reduce the high PAPR, a Discrete Forest Optimization Algorithm (DFOA) is integrated with the classical Selective Mapping (SLM) method in IM/DD-OFDM system. This approach successfully optimizes the values of phase factors, minimizes the search numbers, and reduces computational complexity. To evaluate the impact of the DFOA-SLM method on PAPR reduction, the parameters of the DFOA-SLM method play a crucial role in decreasing the PAPR in an IM/DD optical OFDM system. The DFOA-SLM method demonstrates improved Bit Error Rate (BER) performance, power spectral density (PSD), and power saving performance compared to other PAPR reduction methods.
Autorenporträt
Mahmoud Alhalabi received received his Ph.D. from Erciyes University/Turkey in 2023. He is a post-doctoral researcher at Istanbul Sabahattin Zaim University from 2024 to 2025. His research interests include optical communications, OFDM, WDM-PONs, PAPR reduction methods, and applications of artificial intelligence techniques.