An empirical path loss model for wireless sensor network deployment in a sand terrain environment

Alsayyari, Abdulaziz; Kostanic, Ivica; Otero, Carlos E.; Almeer, Mohammed; Rukieh, Kusay

doi:10.1109/wf-iot.2014.6803162

Cited by 40 publications

(33 citation statements)

References 15 publications

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“…The simplicity of implementation and its ability to cover all environment-related factors that affect the propagation of the radio wave throughout actual measurements [6] introduces empirical path losses models over theoretical path loss models. The accurate wave propagation model for wireless sensor network are expected to support in achieving suitable valuation with improving of wireless sensors networks performance all over the deployment planning process, minimizing the power consumption of network end nodes and to enhance the localization and target sensing tasks [7].…”

Section: Empirical Rf Models In Simulation Environmentmentioning

confidence: 99%

Investigation of Empirical Wave Propagation Models in Precision Agriculture

Sabri

Fouad

et al. 2018

MATEC Web of Conferences

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Wireless Sensor Networks have highly proved its contribution in precision agriculture. Communication channel modelling investigation is a highly demanded to achieve a successful communication system where a good wave propagation model is crucially needed. Precision agriculture degrades the traveling waves in various forms in addition to the effects of the large-scale path losses models. This paper reviews the most known theoretical large-scale path losses models such as free space (FSPL) and Plane earth (PE) models as well as the vegetation models represented by Weissberger, ITU-R, FITU-R and COS235 models. Indeed, this work illustrates the effects of many factors on the total path losses such as separation distance between transceivers, antenna heights and the depth of vegetation that presence in the path propagation. In conclusion, the total path loss is computed based on large-scale path losses and the vegetation losses in protected vegetation environment.

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Section: Empirical Rf Models In Simulation Environmentmentioning

confidence: 99%

Investigation of Empirical Wave Propagation Models in Precision Agriculture

Sabri

Fouad

et al. 2018

MATEC Web of Conferences

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“…In a related case, the authors in [23] present an empirical path loss model for wireless sensor network for sandy environment. They compare the model with that from sparse tree and long grass terrains.…”

Section: A Related Workmentioning

confidence: 99%

Empirical Path Loss Models for Wireless Sensor Network Deployments in Short and Tall Natural Grass Environments

Olasupo

Otero

Olasupo

et al. 2016

IEEE Trans. Antennas Propagat.

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Extensive research has not been done on propagation modeling for natural short-and tall-grass environments for the purpose of wireless sensor deployment. This study is essential for efficiently deploying wireless sensors in different applications such as tracking the grazing habits of cows on the grass or monitoring sporting activities. This study proposes empirical path loss models for wireless sensor deployments in grass environments. The proposed models are compared with theoretical models to demonstrate their inaccuracy in predicting path loss between sensor nodes deployed in natural grass environments. Results show that theoretical models deviate from the proposed models by 12 to 42%. Also, results of the proposed models are compared with experimental results obtained from similar natural grassy terrains at different locations resulting in similar outcomes. Finally, the results of the proposed models are compared with previous studies and other terrain models such as those in dense tree environments. These comparisons show that there is significant difference in path loss and empirical models' parameters. The proposed models, as well as the measured data, can be used for efficient planning and future deployments of wireless sensor networks in similar grass terrains.Index Terms-path loss model, RF propagation, short and tall natural grass, terrain, terrain factor, wireless sensor network, XBee radio.

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“…According to the authors, such high PLE is due to the absence of LOS communication between the sending and receiving nodes. The authors continue their work in characterizing signal propagation in different environments by providing RF measurements and empirical path loss models for sand terrain environment in [12]. Surprisingly, the PLE turned out to be 3.42, which is higher than the PLE obtained in the sparse tree environment.…”

Section: Introductionmentioning

confidence: 99%

“…This is because different grounds have different properties, which govern the reflection of an incident wave. Previous studies have shown the inaccuracy of FSPL and Two-Ray models in predicting path loss for WSN deployed outdoors, for example, see [11,12,13]. In addition, the works in [11], [12], and [13] reported differences in RSS readings of WSNs deployed in different outdoor environments.…”

Section: Introductionmentioning

confidence: 99%

An empirical path loss model for Wireless Sensor Network deployment in a concrete surface environment

Alsayyari

Kostanic

Otero

2015

2015 IEEE 16th Annual Wireless and Microwave Technology Conference (WAMICON)

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This paper presents a path loss model for predicting signal propagation of wireless sensor nodes deployed in concrete surface environments. To create the model, radio frequency (RF) measurements were collected through Wireless Sensor Network (WSN) deployment in such environment. From the actual measurements, the parameters of the log-normal shadowing model are fine-tuned to develop an accurate path loss model. In addition, the presented RF measurements and empirical path loss model are compared with measurements and models obtained from long-grass and sparse-tree environments, which were presented in a previous work. The results from the comparison of such different environments show significant differences in path loss and empirical models' parameters. Furthermore, the comparison between the proposed model and largely used path loss models such as free space path loss (FSPL) and Two-Ray demonstrate the inaccuracy of these models in predicting path loss between wireless sensor nodes deployed in concrete surface environments.

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An empirical path loss model for wireless sensor network deployment in a sand terrain environment

Cited by 40 publications

References 15 publications

Investigation of Empirical Wave Propagation Models in Precision Agriculture

Investigation of Empirical Wave Propagation Models in Precision Agriculture

Empirical Path Loss Models for Wireless Sensor Network Deployments in Short and Tall Natural Grass Environments

An empirical path loss model for Wireless Sensor Network deployment in a concrete surface environment

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