Electromagnetic Simulation with 3D FEM for Design Automation in 5G Era

doi:10.12142/ZTECOM.202003007

ZTE Communications ›› 2020, Vol. 18 ›› Issue (3): 42-48.DOI: 10.12142/ZTECOM.202003007

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Electromagnetic Simulation with 3D FEM for Design Automation in 5G Era

BALEWSKI Lukasz¹, BARANOWSKI Michal², JASINSKI Maciej²(), LAMECKI Adam^1,², MROZOWSKI Michal²

^1.EM Invent, Gdansk 80-172, Poland
^2.Faculty of Electronics, Telecommunications, and Informatics, Gdansk University of Technology, Gdansk 80-233, Poland

Received:2020-06-02 Online:2020-09-25 Published:2020-11-03
About author:Lukasz BALEWSKI received his M.Sc. and Ph.D. (with honors) degrees in microwave engineering from Gdansk University of Technology (GUT), Poland in 2003 and 2008, respectively. He works with EM Invent, Poland. His research interests include CAD of microwave devices, filter design, and optimization techniques. He is the co-author of several software tools for microwave filter design.|Michal BARANOWSKI received the B.Sc. degree in electronics and telecommunications from Gdansk University of Technology, Poland in 2020. He is currently pursuing his M.Sc. degree at the Faculty of Electronics, Telecommunications and Informatics at Gdansk University of Technology. His research interests include computational electromagnetics and optimization techniques.|Maciej JASINSKI (maciej.jasinski@pg.edu.pl) received the M.Sc. degree in microwave engineering from Gdansk University of Technology, Poland in 2019, where he is currently a Ph.D. student. His main research interests include numerical electromagnetics, microwave filters and phasers. He was a recipient of a scholarship granted by Foundation for Polish Science.|Adam LAMECKI received the M.Sc., Ph.D. and D.Sc. degrees in electronics and electrical engineering from Gdansk University of Technology (GUT), Poland in 2002, 2007 and 2019, respectively. In 2006 he joined the Department of Microwave and Antenna Engineering, Faculty of Electronics, Telecommunications and Informatics at GUT, where he is an associate professor. His research interests include surrogate models and their application in the CAD of microwave components, computational electromagnetics, mainly focused on the finite element method, filter design and optimization techniques. He was a recipient of the Young Scientist Grant awarded by the Foundation for Polish Science, the Prime Minister of Poland Award for outstanding Ph.D. thesis, and the Scholarship for outstanding young researchers from the Polish Ministry of Science and Higher Education. He has been a principal investigator on several research projects funded by the Polish Ministry of Science and Higher Education, the Polish National Science Centre, and the Polish National Centre for Science and Development. He has co-authored over 35 papers in peer reviewed journals, including IEEE Transactions on Microwave Theory and Techniques, IEEE Microwave and Wireless Components Letters, and IEEE Antennas and Wireless Propagation Letters.|Michal MROZOWSKI received the M.Sc. and Ph.D. degrees, both with honors, from Gdansk University of Technology in 1983 and 1990, respectively. In 1986, he joined the Faculty of Electronics, Gdansk University of Technology, where he is now a full professor and the head of the Department of Microwave and Antenna Engineering. He is a member of Polish Academy of Sciences, Fellow of IEEE and Fellow of Electromagnetics Academy. He currently serves as an associate editor for the Proceedings of IEEE. He published more than 150 papers, mostly in IEEE journals. His current research interests include computational electromagnetics, the EDA of microwave devices, filter and sensor design, and optimization techniques.
Supported by:
the Electromagnetic Design of Flexible Sensors Project(POIR.04.04.00-00-1DC3/16-00);which is carried out within the Team-Tech Program of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund, Smart Growth Operational Program 2014–2020

Abstract

Abstract:

Electromagnetic simulation and electronic design automation (EDA) play an important role in the design of 5G antennas and radio chips. The simulation challenges include electromagnetic effects and long simulation time and this paper focuses on simulation software based on finite-element method (FEM). The state-of-the-art EDA software using novel computational techniques based on FEM can not only accelerate numerical analysis, but also enable optimization, sensitivity analysis and interactive design tuning based on rigorous electromagnetic model of a device. Several new techniques that help to mitigate the most challenging issues related to FEM based simulation are highlighted. In particular, methods for fast frequency sweep, mesh morphing and surrogate models for efficient optimization and manual design tuning are briefly described, and their efficiency is illustrated on examples involving a 5G multiple-input multiple-output (MIMO) antenna and filter. It is demonstrated that these new computational techniques enable significant reduction of time needed for design closure with the acceleration rates as large as tens or even over one hundred.

Key words: design by optimization, electronic design automation, fast frequency sweep, interactive design tuning, mesh morphing

BALEWSKI Lukasz, BARANOWSKI Michal, JASINSKI Maciej, LAMECKI Adam, MROZOWSKI Michal. Electromagnetic Simulation with 3D FEM for Design Automation in 5G Era[J]. ZTE Communications, 2020, 18(3): 42-48.

Figures/Tables 11

References 13

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Number of Tetrahedra	Matrix Size	Direct Sweep Time/s (201 freq. points)	Interpolating Sweep Time/s	Fast Frequency Sweep (MOR) Time/s
118 367	727 514	1 095	181	247
390 136	2 444 052	12 296	2 062	822
1 185 523	7 337 304	58 385.4	8 647	2 692

Number of Tetrahedra	Matrix Size	Direct Sweep Time/s (201 freq. points)	Interpolating Sweep Time/s	Fast Frequency Sweep (MOR) Time/s
118 367	727 514	1 095	181	247
390 136	2 444 052	12 296	2 062	822
1 185 523	7 337 304	58 385.4	8 647	2 692

Method	Good Starting Point		Bad Starting Point
Method	No. of Iterations	Total Runtime	No. of Iterations	Total Runtime
HFSS’s SNLP without mesh deformation^[3]	71	17.8 h	135	33.8 h
Quasi-Newton with mesh deformation^[3]	31	8.2 h	65	17.1 h
Quasi-Newton with Lagrangian method and mesh deformation^[3]	9	2.7 h	24	7.2 h
Quasi-Newton using InventSim FEM solver and mesh deformation	17	39 min 16 s	30	1.5 h
InventSim generalized Chebyshev filter optimizer with mesh deformation	9	11 min 13 s	14	18 min 43 s

Method	Good Starting Point		Bad Starting Point
Method	No. of Iterations	Total Runtime	No. of Iterations	Total Runtime
HFSS’s SNLP without mesh deformation^[3]	71	17.8 h	135	33.8 h
Quasi-Newton with mesh deformation^[3]	31	8.2 h	65	17.1 h
Quasi-Newton with Lagrangian method and mesh deformation^[3]	9	2.7 h	24	7.2 h
Quasi-Newton using InventSim FEM solver and mesh deformation	17	39 min 16 s	30	1.5 h
InventSim generalized Chebyshev filter optimizer with mesh deformation	9	11 min 13 s	14	18 min 43 s

Parameter	Description	Initial Value/mm	Final Value/mm
a	Cavity width, length	25.85	25.94
c	Cavity height	18.44	18.0
D	DR diameter	19.32	19.3
H	DR height	9.47	9.38
X	Distance of coax from cavity wall	4.2	4.18
L	Coax probe length	16.0	16.1
Lp	Tuning screw length	0.28	0.88

Electromagnetic Simulation with 3D FEM for Design Automation in 5G Era

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