Whale Optimization Algorithm Aided Markov Chain for Mobility Prediction
Sakarya University Journal of Computer and Information Sciences, cilt.9, sa.2 Special Issue, ss.563-575, 2026 (Scopus, TRDizin)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 9 Sayı: 2 Special Issue
- Basım Tarihi: 2026
- Dergi Adı: Sakarya University Journal of Computer and Information Sciences
- Derginin Tarandığı İndeksler: Scopus, Applied Science & Technology Source, Central & Eastern European Academic Source (CEEAS), Directory of Open Access Journals, TR DİZİN (ULAKBİM)
- Sayfa Sayıları: ss.563-575
- Anahtar Kelimeler: Handover, Markov Chain, Mobility Graph, Whale Optimization Algorithm
- İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet
Özet
Trajectory prediction remains a significant operation in mobile communications. In 5G and Beyond (B5G) networks, next-cell prediction for User Equipment (UE) becomes increasingly critical amid the exponential network complexity driven by unprecedented subscriber growth. Markov Chains are selected for their simplicity, interpretability, low computational demands, and proven effectiveness in modeling sequential mobility patterns, which makes them ideal for real-time predictions, despite the existence of more complex alternatives. Paralleling the growing interest in metaheuristic (MH) algorithms for parameter optimization, this paper employs the Whale Optimization Algorithm (WOA) to select the optimal Markov Chain order for each UE trajectory, thereby enhancing next-location prediction. Compared to the traditional fixed-order Markov Chain, the proposed method boosts average prediction accuracy by 20%.