Challenges in modelling near field antenna-body interactions

At the end of the nineties, the FDTD simulation of a basic coaxial-MSL transition typically took about an hour; real-life problems were practically impossible to solve without supercomputing resources. Thanks to the tremendous performance boost in hardware and the advent of more efficient simulation technologies, computational power no longer limits to accurately simulate the most complex electromagnetic (EM) problems. As for near field antenna-body interactions, computations of detailed CAD-based radiating sources in the proximity of anatomical human models can be effectively carried out even with inexpensive commercial PCs. For cost and productivity reasons, replacing complex RF measurements by simulations is surely attractive. Then, what is the barrier to the 100%-numerical stage? Without pretending to deliver a comprehensive response to this question, this paper explains why defining an accurate model of a complex wireless device remains a major difficulty. Changing from the viewpoint of radiation performances evaluation to exposure assessment, the authors introduce a novel concept based on the combination of near-field vector measurement and simulation techniques which may offer an alternative to the 100%-numerical, with the advantage to get around source modelling difficulties under certain conditions.

[1]  Cynthia Furse,et al.  Computations of SAR distributions for two anatomically-based models of the human head using CAD files of commercial telephones and the parallelized FDTD code , 1997 .

[2]  Yahya Rahmat-Samii,et al.  EM interaction of handset antennas and a human in personal communications , 1995, Proc. IEEE.

[3]  Niels Kuster,et al.  Suitability of FDTD-based TCAD tools RF design of mobile phones , 2003 .

[4]  A. Lauer,et al.  Multi-PC FDTD: Solving large scale EM problems , 2010, 2010 IEEE MTT-S International Microwave Symposium.

[5]  C. Gabriel Compilation of the Dielectric Properties of Body Tissues at RF and Microwave Frequencies. , 1996 .

[6]  A new SAR assessment procedure for homogeneous and heterogeneous flat-phantoms based on near-field free-space measurements , 2007 .

[7]  A. Lauer,et al.  Solving large scale EM problems using FDTD analysis , 2011, Proceedings of the 5th European Conference on Antennas and Propagation (EUCAP).

[8]  M. Stuchly,et al.  A study of the handset antenna and human body interaction , 1996 .

[9]  Andrea Cozza,et al.  Influence of source - phantom multiple interactions on the field transmitted in a flat phantom , 2007, 2007 18th International Zurich Symposium on Electromagnetic Compatibility.

[10]  Uebayashi Shinji,et al.  The estimation of the maximum SAR with respect to various types of wireless device usage , 2004 .

[11]  A. Schiavoni,et al.  SAR generated by commercial cellular phones-phone modeling, head modeling, and measurements , 2000 .

[12]  Craig Scott,et al.  The spectral domain method in electromagnetics , 1989 .

[13]  N. Kuster,et al.  The dependence of electromagnetic energy absorption upon human head tissue composition in the frequency range of 300-3000 MHz , 2000 .

[14]  Osamu Fujiwara,et al.  Characteristics of the SAR distributions in a head exposed to electromagnetic fields radiated by a hand-held portable radio , 1996 .

[15]  Vikass Monebhurrun,et al.  An International Interlaboratory Comparison of Mobile Phone SAR Calculation With CAD-Based Models , 2010, IEEE Transactions on Electromagnetic Compatibility.

[16]  T. Samaras,et al.  The dependence of electromagnetic far-field absorption on body tissue composition in the frequency range from 300 MHz to 6 GHz , 2006, IEEE Transactions on Microwave Theory and Techniques.

[17]  O. Gandhi,et al.  Electromagnetic absorption in the human head and neck for mobile telephones at 835 and 1900 MHz , 1996 .