The Dynamics of the Radiated Field Near a Mobile Phone Connected to a 4G or 5G Network

Deaconescu, D. B.; Buda, Andreea Maria; Vatamanu, David; Miclăuș, Simona

doi:10.48084/etasr.4670

Cited by 9 publications

(5 citation statements)

References 24 publications

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“…Joshi et al [29] and Lee et al [30] analyze 5G UE output power levels that are collected from measurements in commercial networks. Deaconescu et al [31] and Miclaus et al [32] collect EMF measurement from a 5G UE in an indoor controlled environment, with and without generating UL/DL traffic. Overall, such works indicate that the exposure from 5G smartphones is non-negligible, and that a huge variation in the exposure levels can be observed.…”

Section: Exposure Measurement From 5g Uementioning

confidence: 99%

Dominance of Smartphone Exposure in 5G Mobile Networks

Chiaraviglio

Lodovisi

Bartoletti

et al. 2024

IEEE Trans. on Mobile Comput.

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The deployment of 5G networks is sometimes questioned due to the impact of ElectroMagnetic Field (EMF) generated by Radio Base Station (RBS) on users. The goal of this work is to analyze such issue from a novel perspective, by comparing RBS EMF against exposure generated by 5G smartphones in commercial deployments. The measurement of exposure from 5G is hampered by several implementation aspects, such as dual connectivity between 4G and 5G, spectrum fragmentation, and carrier aggregation. To face such issues, we deploy a novel framework, called 5G-EA, tailored to the assessment of smartphone and RBS exposure through an innovative measurement algorithm, able to remotely control a programmable spectrum analyzer. Results, obtained in both outdoor and indoor locations, reveal that smartphone exposure (upon generation of uplink traffic) dominates over the RBS one. Moreover, Line-of-Sight locations experience a reduction of around one order of magnitude on the overall exposure compared to Non-Line-of-Sight ones. In addition, 5G exposure always represents a small share (up to 38%) compared to the total one radiated by the smartphone.

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Section: Exposure Measurement From 5g Uementioning

confidence: 99%

Dominance of Smartphone Exposure in 5G Mobile Networks

Chiaraviglio

Lodovisi

Bartoletti

et al. 2024

IEEE Trans. on Mobile Comput.

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“…The data are then analyzed to assess the time variability of the emissions. In a previous work of ours, we applied time series analysis to 4G and 5G signals using the Poincare plots method [57]. The temporal patterns and fluctuations of mobile phone emissions showed a more intensive dynamic in 5G than in 4G uplink signals, while short-term variability and long-term variability were different in the two networks.…”

Section: Performing Spectrograms Recordings and Signal Classificationmentioning

confidence: 99%

An Exposimetric Electromagnetic Comparison of Mobile Phone Emissions: 5G versus 4G Signals Analyses by Means of Statistics and Convolutional Neural Networks Classification

Miclaus,

Deaconescu,

Vatamanu

et al. 2023

Technologies

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To gain a deeper understanding of the hotly contested topic of the non-thermal biological effects of microwaves, new metrics and methodologies need to be adopted. The direction proposed in the current work, which includes peak exposure analysis and not just time-averaged analysis, aligns well with this objective. The proposed methodology is not intended to facilitate a comparison of the general characteristics between 4G and 5G mobile communication signals. Instead, its purpose is to provide a means for analyzing specific real-life exposure conditions that may vary based on multiple parameters. A differentiation based on amplitude-time features of the 4G versus 5G signals is followed, with the aim of describing the peculiarities of a user’s exposure when he runs four types of mobile applications on his mobile phone on either of the two mobile networks. To achieve the goals, we used signal and spectrum analyzers with adequate real-time analysis bandwidths and statistical descriptions provided by the amplitude probability density (APD) function, the complementary cumulative distribution function (CCDF), channel power measurements, and recorded spectrogram databases. We compared the exposimetric descriptors of emissions specific to file download, file upload, Internet video streaming, and video call usage in both 4G and 5G networks based on the specific modulation and coding schemes. The highest and lowest electric field strengths measured in the air at a 10 cm distance from the phone during emissions are indicated. The power distribution functions with the highest prevalence are highlighted and commented on. Afterwards, the capability of a convolutional neural network that belongs to the family of single-shot detectors is proven to recognize and classify the emissions with a very high degree of accuracy, enabling traceability of the dynamics of human exposure.

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“…It is important to define the breaks in the time-amplitude variations of the released signals by the devices, which are connected to the 4G and characterized by the LTE (Long Term Evolution), as well as 5G in terms of the NR (New Radio) work networks, which are close to the human body. In order to explain such exposure, some new metrics using the external physical parameters, the characteristic of Instantaneous Power Density (IPD) was introduced [28].…”

Section: The Perspective System For Measurement Of Human Exposure To ...mentioning

confidence: 99%

Evaluation of the Em Field Exposure in the Range of 4g Frequencies in The Laboratory Environment

Andriychuk,

Nazarovets

2023

CDS

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The aim of paper is to estimate the electromagnetic (EM) field radiation on the human body in the range of 4G operations. The analytical approach consists of application of concept of the equivalent cylindrical monopole antenna presenting grounded standing human. The analytical formulas, allowing to determine the EM field exposure are derived. The experimental setup, consisting of the spectrum analyzer USB-SA44B supplemented by the respective software, notebook for analysis of signals, transmitting-receiving antenna array designed of four microstrip antennas, the transmitting antenna operating in the frequencies 0.9 GHz, 1.8 GHz and 2.45 GHz, and signal generator SA6 are used for the measurements. The designed setup demonstrates the possibility to extract the spectral characteristics of radiation in the range of 4G operations that will used subsequently for the comparison with the modeling data. It is observed that the fixed strength of radiation depends on the sources of radiation. The perspective of design is evaluation of the SAR at the laboratory environment.

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The Dynamics of the Radiated Field Near a Mobile Phone Connected to a 4G or 5G Network

Cited by 9 publications

References 24 publications

Dominance of Smartphone Exposure in 5G Mobile Networks

Dominance of Smartphone Exposure in 5G Mobile Networks

An Exposimetric Electromagnetic Comparison of Mobile Phone Emissions: 5G versus 4G Signals Analyses by Means of Statistics and Convolutional Neural Networks Classification

Evaluation of the Em Field Exposure in the Range of 4g Frequencies in The Laboratory Environment

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