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Article Early Access 2025 · 0 atıf

Integrating WENSLO, Rough OPA, and ALWAS Methods for Strategic 5G Deployment: A Case Study from Turkey

Codur, Sadrettin, Erkayman, Burak, Alp, Saliha Sezgin, Ozenir, Omar, Yildiz, Gokhan, Gemalmaz, Ali, Dikel, Arsal, Akin, Hamza, Yilmaz, Yuksel, Turk, Yesim, Aktas, Semih, Pamucar, Dragan

Özet

By supporting transformative technologies such as the Internet of Things (IoT), Radio Frequency Identification (RFID), and blockchain, fifth-generation wireless technology (5G) has become a cornerstone of economic growth and digital transformation. These advancements position 5G at the forefront of mobile communications research, unlocking innovation across industries. However, deploying 5G networks poses challenges, particularly in prioritizing service points. While developed countries have established mature 5G networks, the transition process in developing countries like Turkey remains in its early stages. Limited resources, shifting demographics, and infrastructure constraints demand robust strategies for resource allocation and site prioritization. This study presents an integrated decision-making framework using Weights by ENvelope and SLOpe (WENSLO), Rough Ordinal Priority Approach (OPA), and Aczel-Alsina-Weighted Assessment (ALWAS) methods to prioritize service points in Istanbul for a telecommunications company operating in Turkey during its 5G migration process. While Rough OPA calculates criteria weights based on expert judgments, WENSLO reduces subjectivity in weight assignments by adopting a data-driven approach. Validation from four R&D experts and a Spearman correlation test (coefficient of 0.85) between proposed and expert rankings confirms the framework's robustness and effectiveness for strategic 5G deployment planning in resource-constrained environments.

Anahtar Kelimeler
Aczel-Alsina weighted assessment (ALWAS) Internet of Things (IOT) network planning ordinal priority approach (OPA) weights by envelope and slope (WENSLO) 5g technology
WoS Kategorileri
Computer Science, Artificial Intelligence Computer Science, Information Systems Computer Science, Interdisciplinary Applications Operations Research & Management Science
Künye
Dergi
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
Yıl
2025
ISSN
0219-6220
eISSN
1793-6845
DOI
10.1142/S021962202550110X
WoS UID
WOS:001576001300001
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