{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T10:14:12Z","timestamp":1770286452778,"version":"3.49.0"},"reference-count":57,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T00:00:00Z","timestamp":1682035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Princess Nourah bint Abdulrahman University","award":["PNURSP2023R137"],"award-info":[{"award-number":["PNURSP2023R137"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The intelligent reflecting surface (IRS) is a cutting-edge technology for cost-effectively achieving future spectrum- and energy-efficient wireless communication. In particular, an IRS comprises many low-cost passive devices that can independently reflect the incident signal with a configurable phase shift to produce three-dimensional (3D) passive beamforming without transmitting Radio-Frequency (RF) chains. Thus, the IRS can be utilized to greatly improve wireless channel conditions and increase the dependability of communication systems. This article proposes a scheme for an IRS-equipped GEO satellite signal with proper channel modeling and system characterization. Gabor filter networks (GFNs) are jointly proposed for the extraction of distinct features and the classification of these features. Hybrid optimal functions are used to solve the estimated classification problem, and a simulation setup was designed along with proper channel modeling. The experimental results show that the proposed IRS-based methodology provides higher classification accuracy than the benchmark without the IRS methodology.<\/jats:p>","DOI":"10.3390\/s23084173","type":"journal-article","created":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T03:04:08Z","timestamp":1682305448000},"page":"4173","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Optimized Classification of Intelligent Reflecting Surface (IRS)-Enabled GEO Satellite Signals"],"prefix":"10.3390","volume":"23","author":[{"given":"Mamoona","family":"Jamil","sequence":"first","affiliation":[{"name":"School of Engineering & Applied Sciences, ISRA University, Islamabad 46000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6744-519X","authenticated-orcid":false,"given":"Mubashar","family":"Sarfraz","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, NUML, Islamabad 44000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sajjad A.","family":"Ghauri","sequence":"additional","affiliation":[{"name":"School of Engineering & Applied Sciences, ISRA University, Islamabad 46000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1351-898X","authenticated-orcid":false,"given":"Muhammad Asghar","family":"Khan","sequence":"additional","affiliation":[{"name":"Hamdard Institute of Engineering and Technology, Hamdard University, Islamabad 44000, Pakistan"},{"name":"Smart Systems Engineering Laboratory, College of Engineering, Prince Sultan University, Rafha Street, P.O. Box 66833, Riyadh 11586, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2105-7239","authenticated-orcid":false,"given":"Mohamed","family":"Marey","sequence":"additional","affiliation":[{"name":"Smart Systems Engineering Laboratory, College of Engineering, Prince Sultan University, Rafha Street, P.O. Box 66833, Riyadh 11586, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2129-7686","authenticated-orcid":false,"given":"Khaled Mohamad","family":"Almustafa","sequence":"additional","affiliation":[{"name":"Department of Information Systems, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hala","family":"Mostafa","sequence":"additional","affiliation":[{"name":"Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. 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