Atmospheric Attenuation due to Humidity

Tamošiūnaitė, M.; Tamošiūnas, S.; Zilinskas, Mindaugas; Tamosiuniene, M.

doi:10.5772/21430

Cited by 13 publications

(10 citation statements)

References 28 publications

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“…In contrast, others have confirmed that humidity (in its various forms) does impact negatively on very weak reception, especially at higher frequencies and high daytime noise floors. Tamošiunaite et al in [14] have surveyed other atmospheric physicists findings and through experimental results corroborate that moisture and different weather conditions do cause EM signal fading.…”

Section: Introductionmentioning

confidence: 85%

Parameter Optimization of a Temperature and Relative Humidity Based Transmission Power Control Scheme for Wireless Sensor Networks

Ortega-Corral

Palafox

García-Macías

et al. 2015

International Journal of Distributed Sensor Networks

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We present refinements of a novel transmission power control (TPC) algorithm based on temperature and relative humidity (TRH). Previously, we deployed a prototype TRH TPC algorithm on wireless sensor nodes operating in real harsh environmental conditions and reported promising results. Since then, we have made enhancements of the TRH TPC model, which we will show here. Furthermore, in order to develop an understanding of the nonlinear behavior that we observed from this TRH TPC scheme, we developed a simulation platform that uses real radio frequency (RF) signal and interference samples and actual T and RH sensor data acquired simultaneously. Afterwards, we logged results of repeated experiments and determined the algorithms operating ranges and behaviors, varying its main parameters, such as (1) its gain factor, (2) the average time period to recalculate power level updates, and (3) proper received signal threshold selection. We then summarize optimal parameter ranges from the analytical results that reflect where this TRH TPC technique works best. And finally, we report results of the TRH TPC algorithm running on long range WSN systems deployed in harsh environmental conditions, corroborating behaviors observed through simulation.

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Section: Introductionmentioning

confidence: 85%

Parameter Optimization of a Temperature and Relative Humidity Based Transmission Power Control Scheme for Wireless Sensor Networks

Ortega-Corral

Palafox

García-Macías

et al. 2015

International Journal of Distributed Sensor Networks

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“…For the first days of measurements, the integration time of the rain gauge was 30 min. It is known that high rain amounts are likely to be lost when this period is too large (Tamošiunaite et al ., 2011). For this reason, integration time of the rainfall was set to a minimum of τ = 5 min.…”

Section: Methodsmentioning

confidence: 99%

A rain estimation model based on microwave signal attenuation measurements in the city of Ioannina, Greece

Christofilakis

Tatsis

Lolis

et al. 2020

Meteorological Applications

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Rain monitoring through signal attenuation has been a significant concern for the scientific community over the last decade. The lowest L‐, S‐ and C‐bands in the microwave spectrum are full of potential for environmental monitoring devices. It has not been extensively proven whether signal attenuation can be used for rain estimation throughout the microwave spectrum in the region of 1–6 GHz. The study derives a power‐law rain estimation model by validating the one year data for the amount of rain and signal attenuation at the lowest limit of the S‐band. This is achieved by a prototype accurate experimental set‐up in a laboratory environment at the campus of the University of Ioannina, northwest Greece. A comparison with global rain attenuation models as well as measurements near this frequency band are also presented and discussed.

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“…In this chapter, the atmospheric effects on propagation are briefly overviewed in terms of the THz communications. A more detailed description of the atmospheric effects is provided in [16].…”

Section: Propagation Modeling (Atmospheric Attenuation)mentioning

confidence: 99%

“…To trace such downpours, "one-minute" rain rate values, R (1 min) (in mm/h), are required. Since data with such accuracy are rarely collected, the "one-minute" rain rate values (integration time is 1 min) can be estimated from various models [16]. However, those models are also based on averaged data; therefore, in territories of varying climate conditions, it is suggested to specify the conversion formula in accordance with the peculiarities of the climate.…”

Section: Rainfallmentioning

confidence: 99%

See 1 more Smart Citation

Atmospheric Attenuation of the Terahertz Wireless Networks

Tamošiūnaitė¹,

Tamošiūnas²,

Zilinskas³

et al. 2018

Broadband Communications Networks - Recent Advances and Lessons From Practice

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The increase of data traffic, a demand for high-speed reliable mobile networks and congested frequency bands raised both technological and regulatory challenges. Therefore, the fifth-generation mobile network (5G) is being developed. Recently, researchers have focused on a very promising terahertz (THz) band (frequencies from 100 GHz to 30 THz), which will allow fast transmission of huge amounts of data. However, transmission distance is limited due to atmospheric attenuation, as THz waves undergo significant absorption by water vapor and oxygen molecules in the atmosphere. Moreover, THz waves are very vulnerable by precipitation. Furthermore, the path of the propagating waves changes due to variations of the atmospheric refractive index. Nevertheless, the THz networks could be perfect candidates for fiber-to-THz bridges in difficult-to-access areas. The aim of this chapter is to present the possibilities and challenges of the THz networks from a point of view of atmospheric attenuation. The results show that simulations of the atmospheric attenuation using real-time data are a powerful tool that should complement technological basis, as it will help to foresee possible failures, extend transmission distance and improve reliability of the THz and other high-frequency broadband wireless networks.

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Atmospheric Attenuation due to Humidity

Cited by 13 publications

References 28 publications

Parameter Optimization of a Temperature and Relative Humidity Based Transmission Power Control Scheme for Wireless Sensor Networks

Parameter Optimization of a Temperature and Relative Humidity Based Transmission Power Control Scheme for Wireless Sensor Networks

A rain estimation model based on microwave signal attenuation measurements in the city of Ioannina, Greece

Atmospheric Attenuation of the Terahertz Wireless Networks

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