{ "article_id": 619, "public_id": "07353a04-652e-417e-9d94-786d7e7bd148", "internal_identifier": null, "source_identifier": "5:269", "status": "published", "type": "research_article", "title": "Bilişsel Radyo Ağlarında Spektrum Algılama için Çevrimiçi Öğrenme Algoritmasına Dayalı Optimum Eşik Modeli", "title_secondary": null, "abstract": "Bilişsel radyo kullanılmayan ya da az kullanılan spektrum bantlarına dinamik olarak erişim olanağı sağlayan ve kullanıcılar arasında herhangi bir olumsuzluğa neden olmadan spektrum paylaşımını gerçekleştiren yazılım tabanlı bir teknolojidir. Kablosuz haberleşme ağlarında bilişsel radyonun başarımı spektrum boşluklarının doğru ve hızlı bir şekilde algılanmasına bağlıdır. Bu çalışmada, optimum eşik değerin belirlenmesi için katı bir eşik değer düzeni belirlenmemiştir. Bilişsel radyolarda spektrum algılama başarımını artırmak için yanlış algılama olasılığı minimize edilirken, algılama olasılığının maksimize edilmesi amaçlanmıştır. Bunun için algılama olasılığının performansını etkileyen birinci ve ikinci tip hatalar detaylı olarak incelenmiş ve kaskat eşik değer belirleme düzeni önerilmiştir. Yapılan çalışma üç aşamadan meydana gelmektedir. İlk aşamada IEEE 802.22 standardına göre yanlış alarm olasılığının 0.1’den küçük olması istenmektedir. Bu değer dikkate alınarak yanlış alarm olasılığına bağımlı bir eşik değer belirlenir. İkinci aşamada bu eşik değerin kullanılması sonucunda yapılan analize bağlı olarak kurulan ikili hipoteze göre birincil ve ikincil tip hataların toplamı optimize edilerek eşik\r\ndeğer ifadesi yeniden tanımlanır. Son aşamada ise çevrimiçi öğrenme algoritması sunulmuştur. Önerilen algoritma ile birincil ve ikincil tip istatistiksel hatalar analiz edilerek lisanslı kullanıcının varlığına ya da yokluğuna karar verebilmek için gerekli olan optimum eşik değer ifadesine ilişkin yeni matematiksel ifadeler türetilmiştir. Bu matematiksel ifadeler kullanılarak  önerilen algoritmanın farklı sönümlemeli kanallar üzerinde başarımı test edilmiştir. Simülasyon çalışmaları sonucunda optimum eşik değer seçimine bağlı olarak spektrum algılama performansında özellikle düşük SNR rejiminde önemli bir iyileşme olduğu görülmüştür.  ", "language": "tr", "english_title": "Optimal Threshold Model Based on Online Learning Algorithm for Spectrum Detection in Cognitive Radio Networks", "english_abstract": "Cognitive radio is a software-based technology that provides dynamic access to unused or underutilized spectrum bands and enables spectrum sharing among users without causing any negative consequences. In wireless communication networks, the performance of cognitive radio depends on the accurate and rapid detection of spectrum gaps. In this study, a strict threshold value system has not been established for determining the optimum threshold value. The aim is to maximize the detection probability while minimizing the false alarm probability to improve spectrum detection performance in cognitive radios. For this purpose, type 1 and type 2 errors affecting the performance of the detection probability have been examined in detail, and a cascaded threshold value determination system has been proposed. The study consists of three stages. In the first stage, according to the IEEE 802.22 standard, the false alarm probability is required to be less than 0.1. Considering this value, a threshold value dependent on the false alarm probability is determined. In the second stage, based on the analysis performed using this threshold value, the sum of primary and secondary type errors is optimized according to the binary hypothesis, and the threshold value expression is redefined. In the final stage, an online learning algorithm is presented. With the proposed algorithm, primary and secondary type statistical errors are analyzed, and new mathematical expressions are derived for the optimum threshold value expression necessary to determine the presence or absence of a licensed user. Using these mathematical expressions, the performance of the proposed algorithm is tested on different fading channels. As a result of the simulation studies, it was observed that there was a significant improvement in spectrum detection performance, especially in the low SNR regime, depending on the selection of the optimum threshold value.", "doi": null, "doi_url": null, "resource_url": "https://www.set-science.com/a/07353a04-652e-417e-9d94-786d7e7bd148", "pdf_url": "https://www.set-science.com/a/07353a04-652e-417e-9d94-786d7e7bd148/pdf", "og_image": "https://www.set-science.com/assets/img/og-card-v2.png", "authors": [ { "public_id": "78d96b5e-6a2c-4293-b050-abd8ad0a13ba", "given": "Kenan", "family": "Koçkaya", "full": "Kenan Koçkaya", "literal": null, "orcid": null, "orcid_url": null, "email": "kkockaya@cumhuriyet.edu.tr", "corresponding": true, "sequence": "first", "affiliations": [ { "name": "Cumhuriyet University", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] }, { "public_id": "ea1e0c06-1223-4063-86e2-0024978bbd02", "given": "İbrahim", "family": "Develi", "full": "İbrahim Develi", "literal": null, "orcid": null, "orcid_url": null, "email": "kkdockaya@cumhuriyet.edu.tr", "corresponding": false, "sequence": "additional", "affiliations": [ { "name": "Erciyes University", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] } ], "keywords": [], "translations": [ { "language": "en", "title": "Optimal Threshold Model Based on Online Learning Algorithm for Spectrum Detection in Cognitive Radio Networks", "abstract": "Cognitive radio is a software-based technology that provides dynamic access to unused or underutilized spectrum bands and enables spectrum sharing among users without causing any negative consequences. In wireless communication networks, the performance of cognitive radio depends on the accurate and rapid detection of spectrum gaps. In this study, a strict threshold value system has not been established for determining the optimum threshold value. The aim is to maximize the detection probability while minimizing the false alarm probability to improve spectrum detection performance in cognitive radios. For this purpose, type 1 and type 2 errors affecting the performance of the detection probability have been examined in detail, and a cascaded threshold value determination system has been proposed. The study consists of three stages. In the first stage, according to the IEEE 802.22 standard, the false alarm probability is required to be less than 0.1. Considering this value, a threshold value dependent on the false alarm probability is determined. In the second stage, based on the analysis performed using this threshold value, the sum of primary and secondary type errors is optimized according to the binary hypothesis, and the threshold value expression is redefined. In the final stage, an online learning algorithm is presented. With the proposed algorithm, primary and secondary type statistical errors are analyzed, and new mathematical expressions are derived for the optimum threshold value expression necessary to determine the presence or absence of a licensed user. Using these mathematical expressions, the performance of the proposed algorithm is tested on different fading channels. As a result of the simulation studies, it was observed that there was a significant improvement in spectrum detection performance, especially in the low SNR regime, depending on the selection of the optimum threshold value.", "keywords": [ "Spektrum algılama, Enerji Algılama, Eşik Değer, Makine Öğrenme Algoritmaları, Çevrimiçi Öğrenme Algoritması" ] } ], "subjects": [], "subject_names": [], "published_date": "2018-06-23", "published_year": "2018", "received_date": null, "accepted_date": null, "volume": "2", "issue": null, "page_first": "434", "page_last": "439", "article_number": null, "conference": { "short_name": "ISAS 2018", "full_title": "Ist International Symposium on Innovative Approaches in Scientific Studies", "name": "Ist International Symposium on Innovative Approaches in Scientific Studies", "acronym": "ISAS 2018", "location": "Kemer-Antalya, Türkiye", "start_date": "2018-04-11", "end_date": null, "public_id": "1d94fec9-c4fe-4034-9157-0b205eef4e56" }, "proceedings": { "title": "Ist International Symposium on Innovative Approaches in Scientific Studies", "series_title": "Setsci conference indexing system", "publisher": "SET Technology", "isbn": null, "eisbn": null, "issn": "2618-6446", "eissn": null, "doi": null, "doi_prefix": null, "slug": "setsci-volume-2-2018-legacy-5", "public_id": "03da7b1c-cb6e-4f3b-aee4-ac41ee60fd75", "url": "https://www.set-science.com/p/setsci-volume-2-2018-legacy-5" }, "license": { "name": "CC BY 4.0", "url": "https://creativecommons.org/licenses/by/4.0/", "code": "CC-BY-4.0", "open_access": true }, "copyright": { "holder": "SET Technology", "year": "2018" }, "funding_statement": null, "funders": [], "references": [ { "order": 1, "raw": "FCC, Federal Communications Commission Spectrum Policy Task Force, Report of the Spectrum Efficiency Working Group, (Teknik Rapor), USA, 2002.", "doi": null, "title": null, "authors": null, "source": null, "year": null, "volume": null, "pages": null }, { "order": 2, "raw": "Tuna, E. ve Karagöz, M. “Gelecek Nesil Ağlar İçin Spektrum Tahsisinde Yeni Bir Yaklaşım: Bilişsel Radyo”, International Journal of Engineering Research and Development, Vol. 4, No.1, pp. 25-31. 2012.", "doi": null, "title": null, "authors": null, "source": null, "year": null, "volume": null, "pages": null }, { "order": 3, "raw": "Mitola, J. ve Maguire, G. 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D.C.O. a. \"Energy Detection Based Spectrum Sensing for Sensing Error Minimization in Cognitive Radio Networks\", International Journal of Communication Networks and Information Security (IJCNIS), pp.1-5, 2009.", "doi": null, "title": null, "authors": null, "source": null, "year": null, "volume": null, "pages": null }, { "order": 17, "raw": "H. Urkowitz, \"Energy detection of unknown deterministic signals\",Proceedings of the IEEE, pp. 523-531, 1967.", "doi": null, "title": null, "authors": null, "source": null, "year": null, "volume": null, "pages": null }, { "order": 18, "raw": "Raman,D. Singh, N.P. “Improved Threshold Scheme for Energy Detection In Cognitive Radio Under Low SNR”. Association of Computer Electronics and Electrical Engineers, pp.251-256, 2013.", "doi": null, "title": null, "authors": null, "source": null, "year": null, "volume": null, "pages": null } ], "statements": { "acknowledgements": null, "conflict_of_interest": null, "data_availability": null, "ai_disclosure": null }, "credit": [], "history": { "published": "2018-06-23" } }