Tuning Selection Impact on Kriging-Aided In-Building Path Loss Modeling

Diago-Mosquera, Melissa Eugenia; Aragón‐Zavala, Alejandro; Rodríguez-Corbo, Fidel Alejandro; Celaya-Echarri, Mikel; Shubair, Raed M.; Azpilicueta, Leyre

doi:10.1109/lawp.2021.3118673

Cited by 7 publications

(6 citation statements)

References 14 publications

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“…The principal novelty in the work here reported is the inclusion of Kriging as an effective tool to improve modeling accuracy for mmWave indoor propagation as it considers all the A singularities and site-associated features that are implicit in measured samples. To the best of our knowledge this has not been reported before despite the fact that its potential has been validated [19]- [21] in previous work. Therefore, this paper is focused on better understanding and modeling path loss considering long indoor corridors, the effect of corners and different receiver heights (i.e., 3D) validating the benefits of using Kriging to ensure accurate path loss predictions.…”

Section: Introductionmentioning

confidence: 70%

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Diago-Mosquera

Aragón‐Zavala

Rodríguez

2022

Antennas Wirel. Propag. Lett.

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Theoretical and empirical foundations of how radio waves behave in practical wireless channels need to be fully revisited for millimeter-wave (mmWave) frequencies so that fifthgeneration (5G) technologies may be successful. Kriging is an outstanding geostatistal interpolation technique that employs variography to understand the spatial variability of known samples at specific locations to predict unmeasured samples, based on the fact that there is an implied connection between the measured value and its location in space. The research we here report is aimed at validating the improvement in predictions when this tool is included for mmWave frequency path loss modeling in a long indoor corridor with break. In order to quantify the accuracy of the proposed methodology, it is compared with a wellestablished procedure described in the literature. Extensive pathloss measurements were collected through specialized narrowband sounders at 28 and 60 GHz. Spatially averaged power measurements using omnidirectional and directive antennas at different heights provided the empirical basis for the threedimensional (3D) Kriging-aided model. It was found that this method significantly improves the accuracy as it considers all the singularities and site-associated features that are implicit in measured samples. This is important to obtain a reliable path loss model for planning and deployment of mmWave wireless communication systems in indoor scenarios.

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Section: Introductionmentioning

confidence: 70%

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Diago-Mosquera

Aragón‐Zavala

Rodríguez

2022

Antennas Wirel. Propag. Lett.

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“…Prior to that, measures such as data cleaning, outlier detection, and missing value imputation were undertaken to ensure the validity of the results [ 25 ]. The normal distribution, semivariogram, and second-order trend analysis were conducted on the migraine-related BI data to provide evidence supporting the suitability of Ordinary Kriging interpolation [ 26 , 27 ].…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal distribution of migraine in China: analyses based on baidu index

Lin,

Zhu,

Qiu

et al. 2023

BMC Public Health

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Background In recent years, innovative approaches utilizing Internet data have emerged in the field of syndromic surveillance. These novel methods aim to aid in the early prediction of epidemics across various scenarios and diseases. It has been observed that these systems demonstrate remarkable accuracy in monitoring outbreaks even before they become apparent in the general population. Therefore, they serve as valuable complementary tools to augment existing methodologies. In this study, we aimed to investigate the spatiotemporal distribution of migraine in China by leveraging Baidu Index (BI) data. Methods Migraine-related BI data from January 2014 to December 2022 were leveraged, covering 301 city-level areas from 31 provincial-level regions by using the keyword “migraine (偏头痛)”. Prevalence data from the Global Burden of Disease study (GBD) were attracted to ensure the reliability of utilizing migraine-related BI data for research. Comprehensive analytical methods were then followed to investigate migraine’s spatiotemporal distribution. The Seasonal-Trend decomposition procedure based on Loess (STL) was used to identify the temporal distribution. Spatial distribution was explored using the Getis-Ord Gi* statistic, standard deviation ellipse analysis, Moran’s Index, and Ordinary Kriging. The top eight migraine-related search terms were analyzed through the Demand Graph feature in the Baidu Index platform to understand the public’s concerns related to migraine. Results A strong association was observed between migraine-related BI and the prevalence data of migraine from GBD with a Spearman correlation coefficient of 0.983 (P = 4.96 × 10− 5). The overall trend of migraine-related BI showed a gradual upward trend over the years with a sharp increase from 2017 to 2019. Seasonality was observed and the peak period occurred in spring nationwide. The middle-lower reaches of the Yangtze River were found to be hotspots, while the eastern coastal areas had the highest concentration of migraine-related BI, with a gradual decrease towards the west. The most common search term related to migraine was “How to treat migraine quickly and effectively (偏头痛怎么办最快最有效的方法)”. Conclusions This study reveals important findings on migraine distribution in China, underscoring the urgent need for effective prevention and management strategies.

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“…Based on the Kriging method, the shape sweep of the basis function reconstructs the air-gap magnetic flux distribution. The Kriging method has been used in the optimization of electromagnetic machines as a spatial interpolation method that began to be used in the field of mining geology [25]- [29]. This technique predicts values of continuous spatial fields with high accuracy using limited sample data in the problem domain.…”

Section: B Shape Sweeping Using Kriging Methodsmentioning

confidence: 99%

“…The introduced virtual air-gap section method provides a reduction in error by adjusting the magnetic flux distribution between a limited number of 2-D analysis planes. First, based on the Kriging method [25]- [29], the basis function interpolates the spatial field between neighboring 2-D analysis planes. Then, the magnetic flux distributions on the virtual air-gap section are reconstructed.…”

Section: Introductionmentioning

confidence: 99%

Novel Quasi-Three-Dimensional Modeling of Axial Flux In-Wheel Motor With Permanent Magnet Skew

Kim

Woo

2022

IEEE Access

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This paper presents a characteristic analysis of axial flux permanent magnet machines (AFPMMs) for in-wheel electric vehicles. Preferentially, a novel quasi-3-D model is developed for the fast and accurate design of AFPMMs. In electromagnetic field analysis, combined with field reconstruction method, the computation time of 2-D solutions is significantly reduced. With the use of time sweeping of the basis function, only the static finite element (FE) analysis is performed to calculate the air-gap flux distribution at the entire rotor position, whereas the conventional 2-D solutions require a transient FE analysis. In the shape sweeping process of the basis function, the virtual air-gap section method is introduced to take into account that the ratio of slot opening to slot pitch is different depending on the radius of analysis plane, which causes errors in the analysis results of the conventional quasi-3-D method. The virtual air-gap sections are obtained by interpolation of the spatial field between the mapped cylindrical planes. The proposed technique reduces the number of 2-D analysis planes required for high accuracy in the conventional quasi-3-D method, and it can also predict the air-gap magnetic flux distribution for skewed permanent magnets without additional FE analysis. Finally, using the magnetic fields calculated in the proposed method, the electromagnetic performances of the AFPMM are calculated, such as load torque, cogging torque, attraction force, and back-EMF. The analysis results were verified by comparison with the measurement results.INDEX TERMS Axial flux permanent magnet machine, in-wheel motor, magnetic field reconstruction, permanent magnet skew, quasi-3-D finite element analysis, virtual air-gap section method.

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Tuning Selection Impact on Kriging-Aided In-Building Path Loss Modeling

Cited by 7 publications

References 14 publications

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Spatiotemporal distribution of migraine in China: analyses based on baidu index

Novel Quasi-Three-Dimensional Modeling of Axial Flux In-Wheel Motor With Permanent Magnet Skew

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