Literature DB >> 20808028

The influence of the reflective environment on the absorption of a human male exposed to representative base station antennas from 300 MHz to 5 GHz.

G Vermeeren1, M C Gosselin, S Kühn, V Kellerman, A Hadjem, A Gati, W Joseph, J Wiart, F Meyer, N Kuster, L Martens.   

Abstract

The environment is an important parameter when evaluating the exposure to radio-frequency electromagnetic fields. This study investigates numerically the variation on the whole-body and peak spatially averaged-specific absorption rate (SAR) in the heterogeneous virtual family male placed in front of a base station antenna in a reflective environment. The SAR values in a reflective environment are also compared to the values obtained when no environment is present (free space). The virtual family male has been placed at four distances (30 cm, 1 m, 3 m and 10 m) in front of six base station antennas (operating at 300 MHz, 450 MHz, 900 MHz, 2.1 GHz, 3.5 GHz and 5.0 GHz, respectively) and in three reflective environments (a perfectly conducting wall, a perfectly conducting ground and a perfectly conducting ground + wall). A total of 72 configurations are examined. The absorption in the heterogeneous body model is determined using the 3D electromagnetic (EM) finite-difference time-domain (FDTD) solver Semcad-X. For the larger simulations, requirements in terms of computer resources are reduced by using a generalized Huygens' box approach. It has been observed that the ratio of the SAR in the virtual family male in a reflective environment and the SAR in the virtual family male in the free-space environment ranged from -8.7 dB up to 8.0 dB. A worst-case reflective environment could not be determined. ICNIRP reference levels not always showed to be compliant with the basic restrictions.

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Year:  2010        PMID: 20808028     DOI: 10.1088/0031-9155/55/18/018

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  1 in total

1.  A Smartphone Camera-Based Indoor Positioning Algorithm of Crowded Scenarios with the Assistance of Deep CNN.

Authors:  Jichao Jiao; Fei Li; Zhongliang Deng; Wenjing Ma
Journal:  Sensors (Basel)       Date:  2017-03-28       Impact factor: 3.576

  1 in total

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