A Radio Propagation Model for Mixed Paths in Amazon Environments for the UHF Band

Eras, Leslye Estefania Castro; Silva, Diego K. N. da; Barros, Fabrício José Brito; Correia, Luıs M.; Cavalcante, Gervásio P. S.

doi:10.1155/2018/2850830

Cited by 10 publications

(6 citation statements)

References 25 publications

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Section: A Problem Formulation and Backgroundmentioning

confidence: 99%

“…The authors of [10] and [1] analyzed an outdoor mixed path tropical Amazon region and developed a propagation model for Digital TV (DTV) services in the UHF band. The model in [10] was based on Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD). In contrast, [1] proposed an empirical propagation model based on Machine Learning (ML) approaches suitable to non-homogeneous paths and various climates.…”

Section: A Problem Formulation and Backgroundmentioning

confidence: 99%

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Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

et al. 2022

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The Internet of Things (IoT) has rapidly expanded for a wide range of applications towards a smart future world by connecting everything. As a result, new challenges emerge in meeting the requirements of IoT applications while retaining optimal performance. These challenges may include power consumption, quality of service, localization, security, and accurate modeling and characterization of wireless channel propagation. Among these challenges, the latter is critical to establishing point-to-point wireless communication between the sensors. Channel modeling also varies depending on the features of the surrounding area, which have a direct impact on the propagation of wireless signals. This presents a difficult task for network planners to efficiently design and deploy IoT applications without understanding the appropriate channel model to analyze coverage and predict optimal deployment configurations. As a result, this challenge has attracted considerable interest in academic and industrial communities in recent years. Therefore, this review presents an overview of current breakthroughs in wireless IoT technologies. The challenges in such applications are then briefly reviewed, focusing on wireless channel propagation modeling and characterization. Finally, the study gives a generalized form of commonly used channel models and a summary of recent channel modeling developments for wireless IoT technology. The outcome of this review is expected to provide a new understanding of the propagation behavior of present and future wireless IoT technologies, allowing network engineers to undertake correct planning and deployment in any environment. Additionally, the study may serve as a guideline for future channel modeling and characterization studies.

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Section: A Problem Formulation and Backgroundmentioning

confidence: 99%

Section: A Problem Formulation and Backgroundmentioning

confidence: 99%

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

et al. 2022

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“…This concept is significant in gaining insight into the performance of the system. [18][19][20][21] While path loss in free-space depends on only the frequency and distance, it is dependent on various electromagnetic parameters such as scattering, multipath fading, diffraction, refraction, and reflection in environments such as vegetative areas. The path loss can simply be shown in Equation (1).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A new empirical propagation model depending on volumetric density in citrus orchards for wireless sensor network applications at sub‐6 GHz frequency region

Doğan¹

2021

Int J RF Microw Comput Aided Eng

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The accuracy of the path loss models directly affects the performance of the wireless sensor networks (WSN) and the efficiency of coverage planning. In this article, as a novelty, new empirical path loss models with foliage depth are proposed at two different 5G frequencies (3.5 and 4.2 GHz) based on volumetric density rate (v) of the trees in citrus orchards for WSN. In order to generate/verify empirical models, measurements are performed at different locations with similar environment characteristics. First, the measurements are compared with commonly used empirical models such as LITU-R, FITU-R, Cost 235, and log-normal, and they are found to be compatible with these models. Second, empirical path loss model is generated based on these measurements. Accordingly, for 3.5 and 4.2 GHz, the coefficient of determination (R 2 ) values are 0.966 and 0.965, respectively. Thirdly, based on the proposed model, it is determined that increasing the v value by 30% increased path loss by 20 dB. Finally, the performance of the proposed models is compared with four different empiric models for calculated v as 0.571. Additionally, the 3.08 and 3.46 root mean square error values of the proposed models are considerably better than those of other models.

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“…Theoretical formulations explaining propagation behaviors in non-line-of-sight (NLOS) measurements, which depend on various attenuation parameters, are very complicated to understand [10,[18][19][20][21][22]. For this purpose, models based on empirical formulation generated from the measurement results at different frequencies are quite common.…”

Section: Fundamentals Of Foliage Path Loss Modelsmentioning

confidence: 99%

A new path loss model based on the volumetric occupancy rate for the pine forests at 5G frequency band

Genç

2020

Int. J. Microw. Wireless Technol.

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In this paper, a new empirical path loss model based on frequency, distance, and volumetric occupancy rate is generated at the 3.5 and 4.2 GHz in the scope of 5G frequency bands. This study aims to determine the effect of the volumetric occupancy rate on path loss depending on the foliage density of the trees in the pine forest area. Using 4.2 GHz and the effect of the volumetric occupancy rate contributes to the literature in terms of novelty. Both the reference measurements to generate a model and verification measurements to verify the proposed models are conducted in three different regions of the forest area with double ridged horn antennas. These regions of the artificial forest area consist of regularly sorted and identical pine trees. Root mean square error (RMSE) and R-squared values are calculated to evaluate the performance of the proposed model. For 3.5 and 4.2 GHz, while the RMSEs are 3.983 and 3.883, the values of R-squared are 0.967 and 0.963, respectively. Additionally, the results are compared with four path loss models which are commonly used in the forest area. The proposed one has the best performance among the other models with values 3.98 and 3.88 dB for 3.5 and 4.2 GHz.

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A Radio Propagation Model for Mixed Paths in Amazon Environments for the UHF Band

Cited by 10 publications

References 25 publications

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

A new empirical propagation model depending on volumetric density in citrus orchards for wireless sensor network applications at sub‐6 GHz frequency region

A new path loss model based on the volumetric occupancy rate for the pine forests at 5G frequency band

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