Application of Stochastic Dosimetry for assessing the Human RFEMF Exposure in a 5G indoor Scenario

In recent years the introduction of 5G networks is causing a drastically change of human exposure levels in the radio frequency range. The aim of this paper is on expanding the knowledge on this issue, assessing the exposure levels for a particular case of indoor 5G scenario, where the presence of an Access Point (AP) was simulated. Coupling the traditional deterministic computational method with an innovative stochastic approach, called Polynomial Chaos Kriging, allowed to evaluate the exposure variability of an user considering the 3D beamforming capability of the antenna. The exposure levels, expressed in terms of specific absorption rate (SAR) in specific tissues, showed low values compared to ICNIRP guidelines.

[1]  M. Parazzini,et al.  Influence of Low Frequency Near-Field Sources Position on the Assessment of Children Exposure Variability Using Stochastic Dosimetry , 2020, IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology.

[2]  Quirino Balzano,et al.  RF Energy Absorption by Biological Tissues in Close Proximity to Millimeter-Wave 5G Wireless Equipment , 2018, IEEE Access.

[3]  Joe Wiart,et al.  Stochastic Dosimetry for Radio-Frequency Exposure Assessment in Realistic Scenarios , 2018, Uncertainty Modeling for Engineering Applications.

[4]  Zhinong Ying,et al.  Exposure to RF EMF From Array Antennas in 5G Mobile Communication Equipment , 2016, IEEE Access.

[5]  Joe Wiart,et al.  A new surrogate modeling technique combining Kriging and polynomial chaos expansions - Application to uncertainty analysis in computational dosimetry , 2015, J. Comput. Phys..

[6]  Paolo Baracca,et al.  A Statistical Approach for RF Exposure Compliance Boundary Assessment in Massive MIMO Systems , 2018, WSA.

[7]  Piet Demeester,et al.  Hybrid Ray-Tracing/FDTD Method for Human Exposure Evaluation of a Massive MIMO Technology in an Industrial Indoor Environment , 2019, IEEE Access.

[8]  Zhong Fan,et al.  Emerging technologies and research challenges for 5G wireless networks , 2014, IEEE Wireless Communications.

[9]  Erik G. Larsson,et al.  Massive MIMO for next generation wireless systems , 2013, IEEE Communications Magazine.

[10]  G. Torfs,et al.  STATISTICAL APPROACH FOR HUMAN ELECTROMAGNETIC EXPOSURE ASSESSMENT IN FUTURE WIRELESS ATTO-CELL NETWORKS , 2018, Radiation protection dosimetry.

[11]  C Gabriel,et al.  The dielectric properties of biological tissues: I. Literature survey. , 1996, Physics in medicine and biology.

[12]  R. W. Lau,et al.  The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz. , 1996, Physics in medicine and biology.

[13]  I. Sobola,et al.  Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates , 2001 .

[14]  Laura Dossi,et al.  Stochastic Dosimetry Assessment of the Human RF-EMF Exposure to 3D Beamforming Antennas in indoor 5G Networks , 2021, Applied Sciences.

[15]  Lei Yang,et al.  Numerical evaluation of human exposure to 3.5-GHz electromagnetic field by considering the 3GPP-like channel features , 2019, Ann. des Télécommunications.

[16]  K R Foster,et al.  IEEE Committee on Man and Radiation—COMAR Technical Information Statement: Health and Safety Issues Concerning Exposure of the General Public to Electromagnetic Energy from 5G Wireless Communications Networks , 2020, Health physics.

[17]  Inkyu Lee,et al.  Three-Dimensional Beamforming: A new enabling technology for 5G wireless networks , 2014, IEEE Signal Processing Magazine.

[18]  I. Laakso,et al.  SAR variation study from 300 to 5000 MHz for 15 voxel models including different postures , 2010, Physics in medicine and biology.

[19]  G. Ziegelberger,et al.  International commission on non-ionizing radiation protection. , 2006, Progress in biophysics and molecular biology.

[20]  Stefano Marelli,et al.  UQLab: a framework for uncertainty quantification in MATLAB , 2014 .

[21]  W. Chin.  Emerging Technologies and Research Challenges for 5 G Wireless Networks , 2014 .

[22]  G. Blatman,et al.  Adaptive sparse polynomial chaos expansions for uncertainty propagation and sensitivity analysis , 2009 .

[23]  M. Parazzini,et al.  Human RF-EMF Exposure Assessment Due to Access Point in Incoming 5G Indoor Scenario , 2020, IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology.

[24]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[25]  J. Wiart,et al.  Polynomial-Chaos-based Kriging , 2015, 1502.03939.