Pre-Launch Validation of 5G Site Prioritization Decisions Using PCA and Autoencoder Models
9th International Balkan Conference on Communications and Networking, Balkancom 2026, Ulcinj, Karadağ, 16 - 19 Haziran 2026, ss.103-108, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/balkancom71095.2026.11605033
- Basıldığı Şehir: Ulcinj
- Basıldığı Ülke: Karadağ
- Sayfa Sayıları: ss.103-108
- Anahtar Kelimeler: 5G planning, autoencoder, decision support, device readiness, fixed wireless access, planning validation, principal component analysis, site prioritization
- İstanbul Gelişim Üniversitesi Adresli: Evet
Özet
This paper presents a pre-launch validation framework for assessing whether 5G site-prioritization decisions prepared ahead of the planned April 1, 2026 opening in Türkiye are aligned with latent demand, load, device-readiness, fixed-wireless-access, and commercial-value patterns extracted from anonymized site-level observations. Rather than relying on a single ranking mechanism, the study compares two distinct unsupervised validation models with different inductive biases. The first is a PCA-based scoring method that transforms normalized feature families into a single interpretable priority score derived from the first principal component. The second is an autoencoder-based method that learns a nonlinear low-dimensional latent representation from standardized numerical and encoded planning-context features and identifies sites with extreme multidimensional profiles. Rather than replacing expert judgment, the proposed models are used as a decision-support layer to validate existing planning choices when post-launch 5G ground-truth data are not yet available. Experiments on anonymized operator data show substantial agreement with the existing planning list and consistently surface high-load, high-demand, and high-value sites. The findings further indicate that model-plan disagreements are often associated with strategic and operational constraints, highlighting the complementary roles of data-driven analytics and engineering judgment in early-stage 5G investment planning.