ANALISIS PATHLOSS JARINGAN 5G MIDDLE BAND 3,5GHZ DENGAN MODEL STANFORD UNIVERSITY INTERIM (SUI) DAN CLOSE-IN (CI)

Nazario Karangan

doi:10.23960/jitet.v13i3S1.8021

Authors

Nazario Karangan Universitas Hasanuddin

DOI:

https://doi.org/10.23960/jitet.v13i3S1.8021

Abstract Views: 34 File Views: 38

Keywords:

Pathloss, Close-In (CI), Stanford University Interim (SUI), Matlab, 5G, Power Receive

Abstract

The implementation of 5G networks in Indonesia continues to develop, with a primary focus on achieving equitable coverage through the construction of adequate infrastructure. This development is influenced by several technical parameters, such as gNodeB height, distance, and transmit power, all of which directly affect network performance, including the value of pathloss. Pathloss refers to the reduction in power or loss of energy during the transmission of information through radio waves, which is influenced by factors such as distance, frequency, and antenna height. By considering these aspects, the deployment of 5G networks is expected to provide optimal benefits for both operators and users, particularly in ensuring reliable services in urban areas. This study analyzes pathloss and received power at a frequency of 3.5 GHz (mid-band) with distance as the main parameter, using a comparison of 5G pathloss models for urban macro cells, namely the Stanford University Interim (SUI) model and the Close-In (CI) model. The modeling process was carried out through simulations using Matlab R2021a software. The results show that distance significantly affects both pathloss and received power in both models (SUI and CI). The greater the distance between the gNodeB and the receiver, the higher the pathloss value, under both Line of Sight (LOS) and Non-Line of Sight (NLOS) conditions. In the CI model under LOS conditions, the lowest pathloss value obtained was 101.48 dB, while the highest value in the SUI model was 140.45 dB. A similar pattern was observed under NLOS conditions, where the lowest pathloss value was recorded in the CI model at 125.63 dB, while the highest value was found in the SUI model at 150.45 dB.

Downloads

Download data is not yet available.

References

A. A. F., W. R. A., S. Ariyanti, D. Kusumawati, P. E. K., and A. Aziz, “Studi Lanjutan 5G Indonesia 2018 Spektrum Outlook dan Use Case untuk Layanan 5G Indonesia,” SDPPPI, 2018.

M. K. Adityo and I. Krisnadi, “Tinjauan Frekuensi 5G di Indonesia,” Universitas Telkom Bandung, pp. 1–4, 2018.

B. Alfaresi, M. V. Satya, and F. Ardianto, “Analisa model propagasi Okumura-Hata dan Cost-Hata pada komunikasi jaringan wireless 4G LTE,” Jurnal Ampere, vol. 5, no. 1, 2020.

D. Aryanta, “Analisis kinerja single user throughput 5G NR pada sel indoor dengan antena MIMO,” ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika, vol. 10, no. 3, pp. 500–513, 2022.

A. Bengawan, B. Taufik, and Muhardanus, “Analisa path loss radio jaringan 5G frekuensi high band 26 GHz dengan model 3GPP ETSI,” Jurnal Fokus Elektroda, vol. 5, no. 1, pp. 5–10, 2020.

S. Budiharjo and A. Ulfah, “Simulasi perhitungan pathloss area dengan metode Okumura-Hata dan Walfisch-Ikegami menggunakan MATLAB,” Jurnal ICT Penelitian dan Penerapan Teknologi, vol. 3, no. 4, 2012.

A. R. Darlis, T. Yunita, and J. Suryan, “Pengukuran model propagasi outdoor dan indoor sistem WiMAX 2.3 GHz di lingkungan kampus ITB,” Prosiding Seminar Radar Nasional, pp. 16–17, 2010.

A. Dwi, “Analisis prediksi path loss teknologi seluler 5G pada sel micro urban wilayah Kota Bandung,” ELKOMIKA, pp. 548–561, 2021.

M. Faqih, N. M. Ardiansyah, and U. K. Usman, “Analisis interferensi teknologi 5G terhadap sistem komunikasi satelit di pita frekuensi Extended-C (3.4–3.7 GHz),” e-Proceeding of Engineering, vol. 7, no. 3, 2020.

S. Sun, G. R. MacCartney, Jr., M. K. Samimi, and T. S. Rappaport, “Investigation of prediction accuracy, sensitivity, and parameter stability of large-scale propagation path loss models for 5G wireless communications,” IEEE Transactions on Vehicular Technology, vol. 65, no. 5, pp. 2843–2860, May 2016, doi: 10.1109/TVT.2016.2543139.

Iben, “Perbandingan pengukuran dan analisa okupansi spektrum menggunakan metode calculated threshold dan metode visual threshold di Balai Monitor Spektrum Frekuensi Radio Kelas II Batam,” Universitas Internasional Batam, 2018.

R. O. Manalu, “Perbandingan model empiris propagasi pathloss guna estimasi rugi-rugi lintasan antena radar di Perum LPPNPI Indonesia,” Politeknik Negeri Sriwijaya, 2017.

L. Mubarokah, O. Puspitorini, and N. A. Siswandari, “Pengukuran dan perhitungan pathloss eksponen untuk cluster residences, central business district (CBD), dan perkantoran di daerah urban,” 2014.

L. Mubarokah, O. Puspitorini, and N. A. Siswandari, “Pengukuran dan perhitungan pathloss eksponen untuk cluster residences, central business district (CBD), dan perkantoran di daerah urban,” Institut Teknologi Sepuluh Nopember, pp. 1–4, 2020.

O. Puspitorini, N. A. Siswandari, and A. Arifin, “Analisa pathloss exponent pada daerah urban dan suburban untuk mendukung pembangunan infrastruktur telekomunikasi dan informasi di Surabaya,” Prosiding SNaPP: Sains dan Teknologi, 2011.

T. S. Rappaport, Wireless Communications: Principles and Practice, 2nd ed. Upper Saddle River, NJ, USA: Prentice Hall, 2002.

M. P. Simarmata, S. Soim, and M. Fadhli, “Analisa link budget dengan perbandingan pemodelan propagasi pada komunikasi bergerak daerah urban,” Jurnal Elektro Telekomunikasi Terapan, 2018.

The MathWorks Inc., Getting Started with MATLAB® Version 7. The MathWorks Inc., 2005.

R. Kreher and K. Gaenger, LTE Signaling, Troubleshooting, and Optimization. 2010. [Online]. Available: https://doi.org/10.1002/9780470977729

N. K. A. P. Bakri, S. Dase, and U. Katu, “Analisis Kapasitas Shannon pada Jaringan LTE di Kota Makassar,” Prosiding Seminar Nasional Teknik Elektro dan Informatika (SNTEI), pp. 92–96, 2022.

A. F. S. Admaja, “Kajian Awal 5G Indonesia (5G Indonesia Early Preview),” Buletin Pos dan Telekomunikasi, vol. 13, no. 2, pp. 97–114, 2015.