Proposed Model for Radio Wave Attenuation due to Rain (RWAR)

Singh, Hitesh; Kumar, Vivek; Saxena, Kumud; Bonev, Boncho; Prasad, Ramjee

doi:10.1007/s11277-020-07598-3

Cited by 20 publications

(8 citation statements)

References 21 publications

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“…The specific attenuation, γ (dB/km), expressed in terms of the rain rate, frequency, and polarization, can be easily estimated using the power-law relationship as shown in Equation (7): γ = aR b p (7) where R p denotes rainfall rate exceeded at p% of the time, a and b are the functions of frequency that depends on the polarization, which can be empirical values and can be obtained experimentally [21,63]. The ITU-R P.838-3 [44] includes a look-up table for values of a and b for frequencies ranging from 1 to 100 GHz in vertical and horizontal polarization.…”

Section: Frequency and Polarizationmentioning

confidence: 99%

A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction

et al. 2022

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Radio waves are attenuated by atmospheric phenomena such as snow, rain, dust, clouds, and ice, which absorb radio signals. Signal attenuation becomes more severe at extremely high frequencies, usually above 10 GHz. In typical equatorial and tropical locations, rain attenuation is more prevalent. Some established research works have attempted to provide state-of-the-art reviews on modeling and analysis of rain attenuation in the context of extremely high frequencies. However, the existing review works conducted over three decades (1990 to 2022), have not adequately provided comprehensive taxonomies for each method of rain attenuation modeling to expose the trends and possible future research directions. Also, taxonomies of the methods of model validation and regional developmental efforts on rain attenuation modeling have not been explicitly highlighted in the literature. To address these gaps, this paper conducted an extensive literature survey on rain attenuation modeling, methods of analyses, and model validation techniques, leveraging the ITU-R regional categorizations. Specifically, taxonomies in different rain attenuation modeling and analysis areas are extensively discussed. Key findings from the detailed survey have shown that many open research questions, challenges, and applications could open up new research frontiers, leading to novel findings in rain attenuation. Finally, this study is expected to be reference material for the design and analysis of rain attenuation.

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Section: Frequency and Polarizationmentioning

confidence: 99%

A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction

et al. 2022

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“…In predicting rainfall, one wishes to obtain the probability of rainfall, and rain rate. Rainfall can be predicted by partial measurement, by statistical models and a combination of these [7][8][9][10][11][12][13][14]. Empirical models for the probability of rain were developed based on experimental data, valid only in specific climates or frequency ranges.…”

Section: Rain Rate Statisticsmentioning

confidence: 99%

“…Given the average rain rate R, the attenuation can be found as a function of R. The symbol error probability can be found as a function of the attenuation. Attenuation as a function of rain rate has been widely calculated and measured [7][8][9][10][11][12][13][14], with the standard statistical method being the ITU-R recommendations [15][16][17], where we focus on outdoor long-distance communication as relevant to satellite-ground links. The challenge is that the symbol error probability is a non-linear function in terms of signal-to-noise ratio and attenuation, which is correlated with the rain rate.…”

Section: Introductionmentioning

confidence: 99%

Communication Systems Performance at mm and THz as a Function of Rain Rate Probability Density Function Model

Kupferman¹,

Arnon²

2022

Preprint

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6G is already being planned and will employ much higher frequencies, leading to a revolutionary era in communication between people as well as things. It is well known that weather, especially rain, can cause increased attenuation of signal transmission for higher frequencies. The standard methods for evaluating the effect of rain on symbol error rate are based on long-term averaging. These methods are an inaccurate, which results with an inefficient system design. This is critical regarding bandwidth scarcity and energy consumption and requires a more significant margin of effort to cope with the imprecision. Recently we have developed a new and more precise method for calculating communication system performance in case of rain, using the probability density function of rain rate. For high rain rate (above 10mm/hr), for a typical set of parameters, our method shows the symbol error rate in this range to be higher by orders of magnitude than that found by ITU standard methods. Our model also indicates that sensing and measuring the rain rate probability is important in order to provide the required bit error rate to the users. To the best knowledge of the authors, this novel analysis is unique. It can constitute a more effi-cient performance metric for the new era of 6G communication and prevent disruption due to incorrect system design. Keywords: atmospheric propagation, communication system performance, attenuation, com-munication

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“…This model [ 77 ] provides an easy calculation mechanism compared to the ITU-R model. The specific attenuation follows the ITU-R model for the frequency band of 1–100 GHz.…”

Section: Rain Attenuation Models: Terrestrial Linksmentioning

confidence: 99%

A Survey of Rain Attenuation Prediction Models for Terrestrial Links—Current Research Challenges and State-of-the-Art

Samad

Diba

Choi

2021

Sensors

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Millimeter-wave (30–300 GHz) frequency is a promising candidate for 5G and beyond wireless networks, but atmospheric elements limit radio links at this frequency band. Rainfall is the significant atmospheric element that causes attenuation in the propagated wave, which needs to estimate for the proper operation of fade mitigation technique (FMT). Many models have been proposed in the literature to estimate rain attenuation. Various models have a distinct set of input parameters along with separate estimation mechanisms. This survey has garnered multiple techniques that can generate input dataset for the rain attenuation models. This study extensively investigates the existing terrestrial rain attenuation models. There is no survey of terrestrial rain mitigation models to the best of our knowledge. In this article, the requirements of this survey are first discussed, with various dataset developing techniques. The terrestrial links models are classified, and subsequently, qualitative and quantitative analyses among these terrestrial rain attenuation models are tabulated. Also, a set of error performance evaluation techniques is introduced. Moreover, there is a discussion of open research problems and challenges, especially the exigency for developing a rain attenuation model for the short-ranged link in the E-band for 5G and beyond networks.

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Proposed Model for Radio Wave Attenuation due to Rain (RWAR)

Cited by 20 publications

References 21 publications

A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction

A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction

Communication Systems Performance at mm and THz as a Function of Rain Rate Probability Density Function Model

A Survey of Rain Attenuation Prediction Models for Terrestrial Links—Current Research Challenges and State-of-the-Art

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