Towards Outdoor Electromagnetic Field Exposure Mapping Generation Using Conditional GANs

Mallik, Mohammed; Tesfay, Angesom Ataklity; Allaert, Benjamin; López, Esteban Egea; Pardo, Jose-Maria Molina-Garcia; Kassi, Rédha; Wiart, Joe; Gaillot, Davy P.; Clavier, Laurent

doi:10.20944/preprints202211.0040.v1

2022

DOI: 10.20944/preprints202211.0040.v1

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Towards Outdoor Electromagnetic Field Exposure Mapping Generation Using Conditional GANs

Mohammed Mallik¹,

Angesom Ataklity Tesfay²,

Benjamin Allaert³

et al.

Abstract: With the ongoing fifth-generation cellular network (5G) deployment, electromagnetic field exposure has become a critical concern. However, measurements are scarce, and accurate electromagnetic field reconstruction in a geographic region remains challenging. This work proposes a conditional Generative Adversarial Network to address this issue. The main objective is to reconstruct the electromagnetic field exposure map accurately according to the environment’s topology from a few sensors located in an … Show more

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Cited by 3 publications

References 29 publications

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SDR-Based Portable System for Evaluating Exposure to Ambient Electromagnetic Fields

Tuta,

Panait-Radu,

Ardelean

et al. 2023

Electronics

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This paper discusses the need to accurately determine the population’s exposure to low-intensity radio-frequency electromagnetic fields (RF-EMF) from modern technologies like mobile networks, Wi-Fi, and IoT and proposes a practical solution for this assessment. There is no scientific consensus on the biological effects, mostly due to challenges in conducting accurate biological experiments. Recent research suggests that real-life exposure sources trigger stronger biological responses than laboratory-generated RF-EMF. However, there is a lack of research comparing the effects of these sources. This paper introduces a portable system for assessing and monitoring EMF exposure in urban areas. Employing a Software-Defined Radio (SDR) platform to ensure adaptability, the system incorporates two measurement configurations. The initial version concentrates on determining the average power within a 20 MHz Wi-Fi channel, whereas the subsequent configuration augments its functionality by introducing a frequency sweep. This sweep broadens the scrutinized bandwidth, thereby enriching the captured data content through the storage of spectrum sweeps corresponding to each average power value. These data can be used to create EMF profile maps based on individuals’ geographical coordinates. Compared to current limited-performance commercial exposimeters, the proposed system offers expanded capabilities by broadening the frequency bandwidth, georeferencing measurements, and storing data in an SQL database. Compared to high-performance commercial exposimeters, the major advantage of the system is its ability to detect short-term fluctuations in signal spectra and store the corresponding data for subsequent analysis.

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SDR-Based Portable System for Evaluating Exposure to Ambient Electromagnetic Fields

Tuta,

Panait-Radu,

Ardelean

et al. 2023

Electronics

View full text Add to dashboard Cite

show abstract

Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping

Ivanov,

Tonchev,

Poulkov

et al. 2023

Sensors

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The increasing densification and diversification of modern and upcoming wireless networks have become an important motivation for the development of agile spectrum sharing. Radio environment maps (REMs) are a basic tool for spectrum utilisation characterisation and adaptive resource allocation, but they need to be estimated through accurate interpolation methods. This work evaluated the performance of two established algorithms for spatial three-dimensional (3D) data collected in two real-world scenarios: indoors, through a mechanical measuring system, and outdoors, through an unmanned aerial vehicle (UAV) for measurement collection. The investigation was undertaken for the complete dataset on two-dimensional (2D) planes of different altitudes and for a subset of limited samples (representing the regions of interest or RoIs), which were combined together to describe the spatial 3D environment. A minimum error of −9.5 dB was achieved for a sampling ratio of 21%. The methods’ performance and the input data were analysed through the resulting Kriging error standard deviation (STD) and the STD of the distances between the measurement and the estimated points. Based on the results, several challenges for the interpolation performance and the analysis of the spatial RoIs are described. They facilitate the future development of 3D spectrum occupancy characterisation in indoor and UAV-based scenarios.

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Enhancement Methods of Hydropower Unit Monitoring Data Quality Based on the Hierarchical Density-Based Spatial Clustering of Applications with a Noise–Wasserstein Slim Generative Adversarial Imputation Network with a Gradient Penalty

Zhang,

Guo,

Yuan

et al. 2023

Sensors

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In order to solve low-quality problems such as data anomalies and missing data in the condition monitoring data of hydropower units, this paper proposes a monitoring data quality enhancement method based on HDBSCAN-WSGAIN-GP, which improves the quality and usability of the condition monitoring data of hydropower units by combining the advantages of density clustering and a generative adversarial network. First, the monitoring data are grouped according to the density level by the HDBSCAN clustering method in combination with the working conditions, and the anomalies in this dataset are detected, recognized adaptively and cleaned. Further combining the superiority of the WSGAIN-GP model in data filling, the missing values in the cleaned data are automatically generated by the unsupervised learning of the features and the distribution of real monitoring data. The validation analysis is carried out by the online monitoring dataset of the actual operating units, and the comparison experiments show that the clustering contour coefficient (SCI) of the HDBSCAN-based anomaly detection model reaches 0.4935, which is higher than that of the other comparative models, indicating that the proposed model has superiority in distinguishing between the valid samples and anomalous samples. The probability density distribution of the data filling model based on WSGAIN-GP is similar to that of the measured data, and the KL dispersion, JS dispersion and Hellinger’s distance of the distribution between the filled data and the original data are close to 0. Compared with the filling methods such as SGAIN, GAIN, KNN, etc., the effect of data filling with different missing rates is verified, and the RMSE error of data filling with WSGAIN-GP is lower than that of other comparative models. The WSGAIN-GP method has the lowest RMSE error under different missing rates, which proves that the proposed filling model has good accuracy and generalization, and the research results in this paper provide a high-quality data basis for the subsequent trend prediction and state warning.

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Towards Outdoor Electromagnetic Field Exposure Mapping Generation Using Conditional GANs

Cited by 3 publications

References 29 publications

SDR-Based Portable System for Evaluating Exposure to Ambient Electromagnetic Fields

SDR-Based Portable System for Evaluating Exposure to Ambient Electromagnetic Fields

Limited Sampling Spatial Interpolation Evaluation for 3D Radio Environment Mapping

Enhancement Methods of Hydropower Unit Monitoring Data Quality Based on the Hierarchical Density-Based Spatial Clustering of Applications with a Noise–Wasserstein Slim Generative Adversarial Imputation Network with a Gradient Penalty

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