LEO UYDU AĞLARINDA BULANIK SİNİR AĞI TABANLI DEVİR ALGORİTMASININ PERFORMANS ANALİZİ

Öz

Alçak Dünya Yörüngesi (LEO) uydu ağları, 5G ve ötesi ile 6G haberleşme sistemleri için küresel kapsama sağlama potansiyeline sahiptir. Ancak bu teknolojiler beraberinde uyduların yüksek hızı nedeniyle uydular arasında yoğun devir (handover) zorunluluğunu da ortaya çıkarmaktadır. Geleneksel Alınan Sinyal Gücü Göstergesi (RSSI) tabanlı handover yaklaşımı, bu dinamik yapıda gereksiz handover durumlarına ve ping-pong etkisine yol açarak kullanıcıların Hizmet Kalitesini (QoS) düşürebilmektedir. Bu çalışmada, LEO uydu ağları için Bulanık Sinir Ağı tabanlı bir handover algoritması önerilmiştir. Starlink yörünge parametreleri ile gerçekleştirilen benzetimler aracılığıyla, önerilen Bulanık Sinir Ağı (FNN) modeli, RSSI ve Bulanık Mantık (FL) tabanlı handover yöntemleriyle karşılaştırılmıştır. Benzetim sonucu elde edilen bulgular göre, önerilen FNN tabanlı handover algoritması literatürde önerilen FL tabanlı yaklaşıma göre %51,7, geleneksel RSSI yöntemine göre ise %71,8 böoranında handover sayısını azalttığı tespit edilmiştir. Ayrıca, önerilen yaklaşım ağ kararlılığını artırmanın yanı sıra, ortalama veri hızını da 3269,7 Mbps seviyesine yükselterek handover-QoS ödünleşimi açısından dengeli bir performans sergilemiştir.

Anahtar Kelimeler

• LEO Uydu Ağları
• Handover Yönetimi
• FNN
• Ping-Pong

Fuzzy Neural Network based Handover Algorithms in LEO Satellite Networks

Öz

Low Earth Orbit (LEO) satellite networks have the potential to provide global coverage for 5G and beyond and 6G communication systems. However, these technologies also introduce the necessity of frequent handovers between satellites due to their high orbital velocity. In this dynamic structure, the conventional Received Signal Strength Indicator (RSSI)-based handover approach may lead to unnecessary handovers and the ping-pong effect, thereby reducing users’ Quality of Service (QoS). In this study, a Fuzzy Neural Network-based handover algorithm is proposed for LEO satellite networks. Through simulations conducted using Starlink orbital parameters, the proposed Fuzzy Neural Network (FNN) model was compared with RSSI- and Fuzzy Logic (FL)-based handover methods. According to the simulation findings, it was determined that the proposed FNN-based handover algorithm reduced the number of handovers by 51.7% compared to the FL-based approach proposed in the literature and by 71.8% compared to the conventional RSSI method. In addition, the proposed approach not only improved network stability but also exhibited a balanced performance in terms of the handover–QoS trade-off by increasing the average data rate to 3269.7 Mbps.

Anahtar Kelimeler

• LEO Satellite Networks
• Handover Management
• FNN
• Ping-Pong

Kaynakça

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