Performance Evaluation of Composite Fading Channels Using q-Weibull Distribution

Mukherjee, Tanmay; Pati, Bibudhendu; Senapati, Dilip

doi:10.1007/978-981-15-6584-7_31

Cited by 7 publications

(3 citation statements)

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“…The amplitude fluctuations as a result of shadowing is often modeled using the log-normal distribution with the fluctuation parameter satisfying the log distance path loss model [2,3,15]. The log-normal distribution is often averaged with several other distributions viz., the Rayleigh distribution, the Weibull distribution to contemplate the concurrent effects of fading and shadowing [23,18,27]. It is observed that the log-normal distribution has an ascendancy over other slow fading channel models viz., gamma distribution, inverse gaussian distribution [4,16] in capturing the long range fading signals.…”

Section: Introductionmentioning

confidence: 99%

“…It is observed that the log-normal distribution has an ascendancy over other slow fading channel models viz., gamma distribution, inverse gaussian distribution [4,16] in capturing the long range fading signals. However, the widely used conventional log-normal model fails to capture the extreme fluctuations due to its inability in distinguishing the tail behavior or outliers of the fading signals [23,27]. The outliers are the regions in the signal where the extreme fluctuations are observed due to various obstructions between the transmitter and the receiver, and this should be analyzed effectively for error free signal transmission and evaluation of performance measures.…”

Section: Introductionmentioning

confidence: 99%

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An adaptive q-Lognormal model towards the computation of average channel capacity in slow fading channels

Mukherjee

Senapati

2022

Telecommun Syst

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An adaptive q-Lognormal model towards the computation of average channel capacity in slow fading channels

Mukherjee

Senapati

2022

Telecommun Syst

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“…Thanks to its versatility and relative simplicity, the Weibull distribution is also widely used in material engineering for the analysis of different kinds of materials, including metals and their alloys [8,9], ceramics [20], plastic materials [21,22], and asphalt mixtures [23]. Nowadays, research in the area of composite materials is very extensive, in connection with statistical predictions and probability models based on the Weibull distribution [24][25][26]. However, there are only a few studies that deal with rubber materials.…”

Section: Introductionmentioning

confidence: 99%

Influence of Disinfectants on Airport Conveyor Belts

et al. 2021

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The coronavirus disease has influenced almost all of our everyday activities. Traveling and transportation have been influenced significantly and there is no doubt that air transportation has been restricted and therefore reduced considerably. It is predicted that the change back to pre-pandemic conditions will take several years, and so it is a reasonable assumption that disinfectants will be used more frequently for a long time. The presented article initially deals with the possible impacts of the pandemic on aircraft infrastructure—namely, on the influence of disinfectants on the rubber materials used, for example, in conveyor belts. The proposed methodology is based on the Weibull analysis for conveyor belt lifetime prediction regarding the impact of disinfectants. The Weibull distribution is a continuous probability distribution that can be applied as a theoretical model for statistical data processing. It was named after Weibull, who suggested shape, scale, and location parameters that made the distribution meaningful and useful. Currently, this distribution is applied in many areas, such as biology, economics, and hydrology. In engineering applications, it can be used for reliability and survival analysis. It is used mainly in cases where failure time is dependent on the operating hours, cycles, or age of the component. In the reliability area, it can be used, for example, to predict the lifetime or failure time of a component. To show the consequences of material changes due to the use of disinfectants, this article also presents a CAE (Computer Aided Engineering) analysis that was used for the evaluation of other hyperelastic material characteristics. This research is based on the results of experimental measurements, during which the influence of the types of disinfectant commonly used for the elimination of the coronavirus disease on airport conveyor belt rubber segments was tested. From the performed analysis, it was found that the influence of disinfectants on the material characteristics, including material hardness, elasticity, and static and dynamic loading, could be significant. Therefore, the probability of mechanical damage to the rubber part of the conveyor belt becomes higher, and time intervals for the maintenance or repair of airport conveyor belts should be considered.

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