Subscriber Growth Forecasting of LTE Network 1800 MHz FDD at Denpasar City using Monte Carlo Simulation

  Suci Rahmatia (1*), Azmi Azizah Azzahra (2), Muhammad Ismail (3), Dwi Astharini (4), Octarina Nur Samijayani (5)

(1) Universitas Al Azhar Indonesia - Indonesia
(2) Universitas Al Azhar Indonesia - Indonesia
(3) Universitas Al Azhar Indonesia
(4) Universitas Al Azhar Indonesia
(5) Universitas Al Azhar Indonesia
(*) Corresponding Author

Received: October 04, 2018; Revised: December 14, 2018
Accepted: December 31, 2018; Published: August 31, 2019

How to cite (IEEE): S. Rahmatia, A. A. Azzahra, M. Ismail, D. Astharini,  and O. N. Samijayani, "Subscriber Growth Forecasting of LTE Network 1800 MHz FDD at Denpasar City using Monte Carlo Simulation," Jurnal Elektronika dan Telekomunikasi, vol. 19, no. 1, pp. 1-6, Aug. 2019. doi: 10.14203/jet.v19.1-6


LTE is the 8th technology officially developed by the 3rd Generation Partnership Project (3GPP). The LTE technology is a solution that is used by engineers to resolve the problems of improving the quality of communications services. The LTE technology able to deliver up to 300 Mbps and 75 Mbps for downlink and uplink, respectively. This study aims to determine the maximum subscriber connected for LTE network technology with capacity planning at 1800 MHz Frequency Division Multiplexing for subscriber growth forecasting in 2025 at Denpasar city. The simulation used Atoll radio network planning software with the Monte Carlo method. Monte Carlo was used to investigating the increase in user throughput according to customer distribution, path loss, and services provided. This simulation is based on traffic data from traffic maps, lists of subscribers and user penetration and cellular services. Monte Carlo simulation shows the results in 2017 which 99.8% of users were successfully connected and only 0.2% of users were rejected. For forecasting in 2025, 99.3% of users are successfully connected, and only 0.7% of users are rejected.



LTE Network; Frequency Division Multiplexing; Capacity Planning; Monte Carlo Simulation

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