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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal EECCIS SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Multitek Indonesia : Jurnal Ilmiah TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Pengabdian Masyarakat Borneo Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Elektrika Borneo JESCEE- Journal of Emerging Supply Chain, Clean Energy, and Process Engineering Jurnal INFOTEL
Syahfrizal Tahcfulloh
Universitas Borneo Tarakan
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Modeling and Optimization of 4G Pathloss using Swarm Intelligence Algorithm: Case Study and Python-Based Implementation Tri Noviyansyah; Syahfrizal Tahcfulloh
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 7, No 3 (2025): November (Special Issue)
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v7i3.3245

Abstract

Accurate pathloss (PL) modeling is critical for 4G-LTE network planning in complex urban environments like Central Tarakan, Indonesia. This study presents a Python-based, open-source implementation of Particle Swarm Optimization (PSO) to calibrate three conventional PL models, Okumura-Hata, SUI, and Ericsson 9999, using real drive-test data. Initial RMSE values exceeded 50 dB, revealing severe inaccuracies under heterogeneous terrain. PSO optimization dramatically improved accuracy: RMSE reduced to 5.98 dB (Okumura-Hata, 89.44% improvement), 9.83 dB (SUI, 84.03%), and 6.44 dB (Ericsson 9999, 91.32%). The optimized Okumura-Hata model achieved the highest reliability, with 88.89% of measurement points meeting the <8 dB threshold and the lowest standard deviation (1.71 dB). Ericsson 9999 attained the lowest minimum RMSE (0.06 dB), showcasing exceptional potential under favorable conditions. PSO converged rapidly within 50 iterations, and sensitivity analysis confirmed that standard parameters (ω = 0.5–0.7, c₁ = c₂ = 1.8–2.2) suffice for robust calibration, eliminating need for fine-tuning. Results demonstrate that real-world propagation deviates significantly from classical logarithmic assumptions, validating the necessity of data-driven, site-specific optimization. The fully open-source framework—built with NumPy, Pandas, and Matplotlib—offers a practical, scalable solution for intelligent radio planning in dynamic urban landscapes.
Co-Authors Abdul Muis Prasetia, Abdul Muis Antonius Antonius Ashar Ashar Budiman, Achmad Eka Riskayadi Huda, Abil Kristianto Pasepang Mado, Ismit Mizar Ahmad Maulana Muhammad Jeki Muttaqin Hardiwansyah Patria Julianto Petrick Petrick Sabaria, Sabaria Said, Fitriani Sapriansa Sapriansa Sartika, Linda Selviyani, Selviyani Sugeng Riyanto Sultan Mahdi Sumardi . Syamsiar, Syamsiar Tri Noviyansyah