Tunnel-like road foliage path loss prediction for V2V communications for LoRa LPWAN 433 MHz and 920 MHz bands

Hakim, Galang P N and Habaebi, Mohamed Hadi and Alaydrus, Mudrik and Firdausi, Ahmad and Muwardi, Rachmat (2026) Tunnel-like road foliage path loss prediction for V2V communications for LoRa LPWAN 433 MHz and 920 MHz bands. Engineering Research Express, 8 (10). pp. 1-22. ISSN 2631-8695

PDF - Published Version Restricted to Repository staff only Download (3MB) | Request a copy

Abstract

An accurate path loss modeling is essential for reliable vehicle-to-vehicle (V2V) and infrastructureto- vehicle communication. However, many existing propagation models and machine learningbased approaches primarily focus on environmental and distance-related parameters, while neglecting the impact of radio configuration and mobility factors. This study proposes a new path loss model which integrates both wireless channel characteristics and machine-related parameters, including frequency, bandwidth, spreading factor, transmit power, vehicle speed, and distance. In addition, a real-world measurement campaign was conducted in a tunnel-like foliage environment, representing a challenging and underexplored propagation scenario. The proposed model is evaluated against conventional models and other machine learning approaches using root mean squared error (RMSE) and MAE metrics. The results show that the ANFIS model achieves superior performance, with the lowest error values of 5.677 (RMSE) and 4.187 (MAE) across both 433 MHz and 920 MHz frequency bands. These findings demonstrate that incorporating heterogeneous parameters with machine learning techniques significantly improves prediction accuracy and highlight the effectiveness of the proposed approach for complex V2V communication environments.

Item Type:	Article (Journal)
Uncontrolled Keywords:	vehicle-to-vehicle, path loss prediction, machine learning, tunnel-like foliage
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering
Depositing User:	Dr. Mohamed Hadi Habaebi
Date Deposited:	09 Jun 2026 09:21
Last Modified:	09 Jun 2026 09:21
Queue Number:	2026-05-Q3600
URI:	http://irep.iium.edu.my/id/eprint/129190

Actions (login required)

View Item