An empirical path loss model for wireless sensor network deployment in a dense tree environment

Abdulaziz Alsayyari; Ivica Kostanic; Carlos E. Otero; Abdallah Aldosary

doi:10.1109/SAS.2017.7894099

An empirical path loss model for wireless sensor network deployment in a dense tree environment

Abdulaziz Alsayyari, Ivica Kostanic, Carlos E. Otero, Abdallah Aldosary

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

34 Scopus citations

Abstract

This paper presents a model for predicting radio frequency (RF) propagation for Wireless Sensor Network (WSN) deployment in a dense tree environment. To create the model, data from a physical deployment are collected and an empirical path loss prediction model is derived from the actual measurements. Furthermore, the presented measurements and empirical path loss model are compared with measurements and models obtained from WSN deployments in other terrains, such as one characterized by long-grass and another by sparse-tree environments. The results from the comparison of these different terrains show significant differences in path loss and empirical models' parameters. In addition, the proposed model is compared with Free Space Path Loss (FSPL) and Two-Ray models to demonstrate the inaccuracy of these theoretical models in predicting path loss between wireless sensor nodes deployed in dense tree environment.

Original language	English
Title of host publication	SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509032020
DOIs	https://doi.org/10.1109/SAS.2017.7894099
State	Published - 6 Apr 2017
Externally published	Yes
Event	12th IEEE Sensors Applications Symposium, SAS 2017 - Glassboro, United States Duration: 13 Mar 2017 → 15 Mar 2017

Publication series

Name	SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings

Conference

Conference	12th IEEE Sensors Applications Symposium, SAS 2017
Country/Territory	United States
City	Glassboro
Period	13/03/17 → 15/03/17

Keywords

Channel Modeling
Path Loss Models
Radio Frequency Propagation Models
RF Propagation
Wireless Sensor Networks

Access to Document

10.1109/SAS.2017.7894099

Cite this

Alsayyari, A., Kostanic, I., Otero, C. E., & Aldosary, A. (2017). An empirical path loss model for wireless sensor network deployment in a dense tree environment. In SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings Article 7894099 (SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SAS.2017.7894099

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title = "An empirical path loss model for wireless sensor network deployment in a dense tree environment",

abstract = "This paper presents a model for predicting radio frequency (RF) propagation for Wireless Sensor Network (WSN) deployment in a dense tree environment. To create the model, data from a physical deployment are collected and an empirical path loss prediction model is derived from the actual measurements. Furthermore, the presented measurements and empirical path loss model are compared with measurements and models obtained from WSN deployments in other terrains, such as one characterized by long-grass and another by sparse-tree environments. The results from the comparison of these different terrains show significant differences in path loss and empirical models' parameters. In addition, the proposed model is compared with Free Space Path Loss (FSPL) and Two-Ray models to demonstrate the inaccuracy of these theoretical models in predicting path loss between wireless sensor nodes deployed in dense tree environment.",

keywords = "Channel Modeling, Path Loss Models, Radio Frequency Propagation Models, RF Propagation, Wireless Sensor Networks",

author = "Abdulaziz Alsayyari and Ivica Kostanic and Otero, \{Carlos E.\} and Abdallah Aldosary",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 12th IEEE Sensors Applications Symposium, SAS 2017 ; Conference date: 13-03-2017 Through 15-03-2017",

year = "2017",

month = apr,

day = "6",

doi = "10.1109/SAS.2017.7894099",

language = "English",

series = "SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings",

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Alsayyari, A, Kostanic, I, Otero, CE & Aldosary, A 2017, An empirical path loss model for wireless sensor network deployment in a dense tree environment. in SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings., 7894099, SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings, Institute of Electrical and Electronics Engineers Inc., 12th IEEE Sensors Applications Symposium, SAS 2017, Glassboro, United States, 13/03/17. https://doi.org/10.1109/SAS.2017.7894099

An empirical path loss model for wireless sensor network deployment in a dense tree environment. / Alsayyari, Abdulaziz; Kostanic, Ivica; Otero, Carlos E. et al.
SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. 7894099 (SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An empirical path loss model for wireless sensor network deployment in a dense tree environment

AU - Alsayyari, Abdulaziz

AU - Kostanic, Ivica

AU - Otero, Carlos E.

AU - Aldosary, Abdallah

PY - 2017/4/6

Y1 - 2017/4/6

N2 - This paper presents a model for predicting radio frequency (RF) propagation for Wireless Sensor Network (WSN) deployment in a dense tree environment. To create the model, data from a physical deployment are collected and an empirical path loss prediction model is derived from the actual measurements. Furthermore, the presented measurements and empirical path loss model are compared with measurements and models obtained from WSN deployments in other terrains, such as one characterized by long-grass and another by sparse-tree environments. The results from the comparison of these different terrains show significant differences in path loss and empirical models' parameters. In addition, the proposed model is compared with Free Space Path Loss (FSPL) and Two-Ray models to demonstrate the inaccuracy of these theoretical models in predicting path loss between wireless sensor nodes deployed in dense tree environment.

AB - This paper presents a model for predicting radio frequency (RF) propagation for Wireless Sensor Network (WSN) deployment in a dense tree environment. To create the model, data from a physical deployment are collected and an empirical path loss prediction model is derived from the actual measurements. Furthermore, the presented measurements and empirical path loss model are compared with measurements and models obtained from WSN deployments in other terrains, such as one characterized by long-grass and another by sparse-tree environments. The results from the comparison of these different terrains show significant differences in path loss and empirical models' parameters. In addition, the proposed model is compared with Free Space Path Loss (FSPL) and Two-Ray models to demonstrate the inaccuracy of these theoretical models in predicting path loss between wireless sensor nodes deployed in dense tree environment.

KW - Channel Modeling

KW - Path Loss Models

KW - Radio Frequency Propagation Models

KW - RF Propagation

KW - Wireless Sensor Networks

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Alsayyari A, Kostanic I, Otero CE, Aldosary A. An empirical path loss model for wireless sensor network deployment in a dense tree environment. In SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. 7894099. (SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings). doi: 10.1109/SAS.2017.7894099

An empirical path loss model for wireless sensor network deployment in a dense tree environment

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