{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T10:53:29Z","timestamp":1782298409337,"version":"3.54.5"},"reference-count":25,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T00:00:00Z","timestamp":1700524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002383","name":"King Saud University","doi-asserted-by":"publisher","award":["RSP2023R260"],"award-info":[{"award-number":["RSP2023R260"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, a new peak average power and time reduction (PAPTR) based on the adaptive genetic algorithm (AGA) strategy is used in order to improve both the time reduction and PAPR value reduction for the SLM OFDM and the conventional genetic algorithm (GA) SLM-OFDM. The simulation results demonstrate that the recommended AGA technique reduces PAPR by about 3.87 dB in comparison to SLM-OFDM. Comparing the suggested AGA SLM-OFDM to the traditional GA SLM-OFDM using the same settings, a significant learning time reduction of roughly 95.56% is achieved. The PAPR of the proposed AGA SLM-OFDM is enhanced by around 3.87 dB in comparison to traditional OFDM. Also, the PAPR of the proposed AGA SLM-OFDM is roughly 0.12 dB worse than that of the conventional GA SLM-OFDM.<\/jats:p>","DOI":"10.3390\/s23239310","type":"journal-article","created":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T12:12:13Z","timestamp":1700568733000},"page":"9310","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Time Reduction for SLM OFDM PAPR Based on Adaptive Genetic Algorithm in 5G IoT Networks"],"prefix":"10.3390","volume":"23","author":[{"given":"Esam A. A.","family":"Hagras","sequence":"first","affiliation":[{"name":"Faculty of Engineering, Delta University for Science and Technology, Gamasa 35712, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sameh","family":"F. Desouky","sequence":"additional","affiliation":[{"name":"Independent Researcher, Ottawa, ON K1S 5B6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6168-4141","authenticated-orcid":false,"given":"Saad","family":"Aldosary","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Community College, King Saud University, Riyadh 11437, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5865-3686","authenticated-orcid":false,"given":"Haitham","family":"Khaled","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communications, School of Engineering, Edith Cowan University, Perth, WA 6027, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0278-3937","authenticated-orcid":false,"given":"Tarek M.","family":"Hassan","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Delta University for Science and Technology, Gamasa 35712, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1109\/MCOM.2017.1600940","article-title":"Network slicing based 5G and future mobile networks: Mobility, resource management, and challenges","volume":"55","author":"Zhang","year":"2017","journal-title":"IEEE Commun. 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