Bilişsel Radyoda Sürüngen Arama Algoritması Kullanarak İşbirlikçi Spektrum Algılama

Yıl 2023, , 383 - 389, 27.10.2023

Burcu Ketenci , Necmi Taşpınar , Tareq M. Shami

https://doi.org/10.46387/bjesr.1349742

Öz

Kablosuz iletişim için giderek artan gereksinim ve spektrumun sınırlı doğası göz önüne alındığında, bilişsel radyo teknolojisi radyo frekansı spektrumunun kullanımının optimize edilmesinde çok önemli bir rol oynamaktadır. Spektrum algılama, bilişsel radyo ağının temel işlevidir. Bu makalede, yakın zamanda geliştirilen Sürüngen Arama Algoritması (RSA), bilişsel radyo sistemleri için işbirlikçi spektrum algılamada tespit yeteneklerini artırmak amacıyla kullanılmıştır. Yumuşak füzyon şeması yardımıyla ikincil kullanıcılara ağırlık atamaları gerçekleştirildi ve bu atamaların en yüksek tespit sonuçlarını vermesini sağlamak için Sürüngen Arama Algoritmasını kullanıldı. Sonuçlar diğer iki optimizasyon algoritması olan Parçacık Sürü Optimizasyonu (PSO) ve Aquila Optimizer (AO) ile karşılaştırılarak Sürüngen Arama Algoritmasının diğer algoritmalara göre daha iyi sonuçlar sağladığı görülmüştür.

Anahtar Kelimeler

Bilişsel Radyo, Sürüngen Arama Algoritması, Ağırlık Katsayıları Optimizasyonu, Algılama Performansı

Proje Numarası

FYL-2022-12479

Cooperative Spectrum Sensing Using Reptile Search Algorithm in Cognitive Radio

Öz

Given the growing requirement for wireless communication and the limited nature of the spectrum, cognitive radio technology plays a crucial role in optimizing the use of the radio frequency spectrum. Spectrum sensing is the core function of the cognitive radio network. In this paper, the recently developed Reptile Search Algorithm (RSA) is used to increase detection capabilities in cooperative spectrum sensing for cognitive radio systems. Weight assignments were made to secondary users with the help of soft fusion scheme and Reptile Search Algorithm was used to ensure that these assignments gave the highest detection results. The results were compared with the other two optimization algorithms, Particle Swarm Optimization (PSO) and Aquila Optimizer (AO), and it was seen that Reptile Search Algorithm provides better results than the other algorithms.

Anahtar Kelimeler

Cognitive Radio, Reptile Search Algorithm, Weight Coefficients Optimization, Detection Performance

Destekleyen Kurum

Erciyes University Scientific Research Projects Coordination Unit

Proje Numarası

FYL-2022-12479

Teşekkür

This work was supported by Erciyes University Scientific Research Projects Coordination Unit (Project No: FYL-2022-12479).

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