Performance Evaluation of mmWave and Sub-TeraHertz Communication Propagation Path Loss Model Simulation Using NYUSIM
DOI:
https://doi.org/10.21512/commit.v19i2.13026Keywords:
mmWave, Sub-TeraHertz, Propagation Loss Model, New York University Channel Model Simulator (NYUSIM), Industrial ComplexAbstract
Wireless bandwidth becomes increasingly limited, prompting studies to explore frequency bands higher than 100 GHz to enable multi-gigabit communication services and low-latency applications. In this context, Sub-TeraHertz communication offers vast unused spectral resources, enabling unprecedented data rates that can power advanced applications such as ultra-highdefinition video streaming, holographic communication, and massive machine-type communications. Therefore, the research aims to review the performance of millimeter wave (mmWave) and Sub-TeraHertz signal propagation in a dense environment such as an industrial complex, addressing major challenges including high propagation losses, atmospheric absorption, and signal blockage. By using NS-3 to simulate different scenarios, both inside and outside the factory, the analysis aims to characterize the channel performance and provide insight into the potential of Sub-TeraHertz communication for industrial environments. Through comprehensive simulation using the Urban Micro (UMi) scenario, the analysis models the propagation loss from a dense environment with maximum blockages. In addition to the received signal as a function of transmitter–receiver distance, the results show that the number of blockages between the transmitter and receiver, the mobility of the receiver, the frequency band, and the spectrum bandwidth substantially affect the propagation loss of signal transmission in mmWave and Sub-Terahertz Bands. These findings highlight the importance of considering indoor–outdoor disparities, blockage effects, and environment-specific network design when deploying high-frequency communication systems. The research also provides a foundation for future research to explore mitigation techniques to enhance reliability and coverage in complex industrial deployments.
Plum Analytics
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