02 Simulation of 5G Antenna Design CST

Advanced Wireless Technologies by ROHDE&SCHWARZ

Simulation of 5G / MIMO Antennas Design Zeev Iluz

CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Agenda 1. 5G Motivation and Challenges 2. Antenna Array Simulation, MIMO post-processing 3. Mobile Device Antenna Array Example 4. Huawei MIMO Base Station Demonstrator


5G Motivation and Challenges Consumer device bandwidth requirements increasing at rapid rates Historical (4, 3G) bands below 3 GHz increasingly crowded Push for 28+ GHz frequency for 5G – subject to relatively high atmospheric attenuation - smaller wavelength more susceptible to multipath loss


5G Motivation and Challenges Efficiency is critical, Gain of 12 dBi for mobile device and 25 dBi targeted Gain cannot come at the expense of coverage – beam steered arrays ideal solution Diversity Gain can also be leveraged - MIMO High frequency and array topology pose simulation challenges (memory, system complexity)


Antenna Arrays Categories Large Arrays


Small Arrays

Small Arrays All elements need to be simulated.


Array Postprocessing  Use Combine Results and Correlation Coefficient result templates to achieve a desired beam shape.  Purely postprocessing, no further 3D simulations needed! How can I achieve a pattern like this?

All amplitudes = 1 CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Amplitudes = ????

Array Postprocessing Template Based Postprocessing as a “Simulation type”

Initial beam shape

Parameters for amplitude weights Desired beam shape


Achieved beam shape

Large Arrays  Can be approximated as an infinite array which requires the simulation of only a single element.  To include edge effects and other physical realities, the entire array needs to be modeled. CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

CST ARRAY WIZARD


CST Array Wizard – Sim Proj

Spacing X, Y = 100

Angle 60°


Drag&Drop your Unit Array Element


Set Elements Active/Passive/Empty


Finite Array Sim. Proj.


MIMO Antennas


Communication Networks Communication antennas need to cope with a complex environment All base-station antennas are placed near the horizontal plane  Mean Effective Gain (MEG)

Tilted reflecting planes change signal polarization  Cross Polarization Rate (XPR)

MIMO Antenna Systems for Advanced Communication Webinar

https://www.cst.com/Applications/Article/MIMO-Antenna-Advanced-Communication


Multi-path signal transmission may lead to destructive signal overlay, resulting in local deep dips (called Rayleigh-Fading)  Diversity/MIMO

Diversity / MIMO Antennas Simple Maximal Signal Diversity Gain

Multi-path signal transmission may lead to destructive signal overlay resulting in local deep dips (called Rayleigh-Fading) Antenna 1

Multiple antennas (antenna diversity) may overcome this problem


Antenna 2 „best of“ (diversity gain)

Diversity / MIMO Antennas Select from:    

Diversity Gain Envelope Correlation Coefficient Multiplexing Efficiency Mean Effective Gain

Load farfield of second antenna

Envelope Correlation from Farfield:


Envelope Corr. from S-Parameters:

Mobile Antenna Array  Element -> Array Design  Device level performance  System level performance


Antenna Magus


Mobile Antenna – Element Design

Magus Antenna Synthesis generates initial square patch design for 28 GHz operating frequency


Mobile Antenna – Element Performance Magus also provides performance estimation for initial design qualification Initial design is clearly ‘approximate’ – Microwave Studio can be used to optimize and modify


Results

Retuned for 28 GHz, at the expense of impedance match quality CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Finite Array Generation


Finite Array Performance


Best Achievable Pattern Envelope

Theta = 0 deg Phi = 0 deg

Theta = 15 deg Phi = 30 deg


Achievable Array Patterns

Theta=45 CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Theta=10

Theta=85

Installed Performance


System Assembly Modelling

System Assembly Modelling provides convenient layout assembly to bring in phone + other antenna models Several copies of array independently placed and parameterizable CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Layout Modelling After wiring system, switch to layout view and align antenna arrays


Layout Modelling

Lower hemispherical array needs to be flipped to aim ‘downward’ Rotate on axis for diversity


Simulation Task

In this case, all models will be solved together in 3D by MWS T solver CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Simulation Performance

3.5 Minutes simulation time per excitation on dual CPU workstation with nVIDIA Kepler 20 GPU (10% GPU capacity) 3.48 GB of system Memory utilized for initial Matrix Calculation CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Installed Performance - Coupling

Both arrays operating (boresight), pattern intact In band coupling to WIFI antenna, GPS coupling at 5G operating freq CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Installed Performance - Coupling


Installed Performance - Envelope

Relatively, low coupling to GPS at 28 GHz, but radiation angles towards GPS antenna are affected ‘Best Achievable Pattern’ envelope clearly shows performance degraded CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Cosite Interference / RF Interference Performance degradation when multiple RF systems are co-located in a common environment.


Mobile Phone Receiver Sensitivity WiFi Antenna

GPS Antenna

Clock

Tri-Band Cellular Antenna


Coupling Matrix Cellular-WiFi Coupling

Cellular-GPS Coupling WiFi-GPS Coupling


Transmitter / Receiver Definition Transmitter Defined by:  Excitation spectrum (signal)  Filter  Amplifier  Library


Receiver Defined by:  Sensitivity spectrum  Filter  Amplifier  Library

CST DS Interference Task


Violation Matrix


Effects of Hand Model ‘Top’ hemisphere array is largely unaffected ‘Bottom’ array highly dependent on finger proximity


MIMO Base Station Array Example

[1] Konstantinos Prionidis, “MIMO Configurable Array for Sector / Omni-Directional Coverage”, Department of Signals & Systems, Chalmers University of Technology, Gothenburg, Sweden 2014


Huawei MIMO Base Station Example -Novel antenna array concept study for small cell sizes (higher capacity and efficiency), 25% bandwidth at 2GHz -MIMO Diversity gain central to improved efficiency -2 logical ports; Polarization diversity utilized (Eh and Ev received) -12 physical ports (spatial diversity) -Unique 360°azimuth plane beam forming capabilities -Elevation up and down tilt beam steering capabillities CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Horizontal Element Horizontal (top) Vertical (bottom)

4 printed arc-dipoles, centrally fed Printed stack up and parasitic tuning elements used to obtain good compromise between size and bandwidth (~27%) CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Vertical Element

Vertical (top) Horizontal (bottom) ‘Small ground’ monopole Planar width increases bandwidth CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Obtained Return Loss

Broadband impedance matching obtained, while maintaining compact antenna configuration CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Array Design and Considerations

Both horizontal and vertical elements can produce one vertical polarized omni-directional OR one vertical polarized sector radiation pattern Spacing between horizontal elements a challenge, grating lobes for array Top and bottom ground plates introduce phased reflections to mitigate; acts as a small ground for vertical monopole elements CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Summary  5G Antenna Device design will require high efficiency devices at frequencies approaching mm wave  CST Array Simulation Workflows provide smooth design process for large and small finite arrays  Antenna Magus provides Antenna and Array synthesis for rapid design exploration  System level simulation increasingly important for antenna performance CST – COMPUTER SIMULATION TECHNOLOGY | www.cst.com

Advanced Wireless COMCAS 2015Technologies by ROHDE&SCHWARZ

Thank you


02 Simulation of 5G Antenna Design CST

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