5G Channel Modeling for mmW Systems Andreas F. Molisch Wireless - - PowerPoint PPT Presentation

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5G Channel Modeling for mmW Systems Andreas F. Molisch Wireless - - PowerPoint PPT Presentation

Dec 31, 2022 12 likes •307 views

5G Channel Modeling for mmW Systems Andreas F. Molisch Wireless Devices and Systems (WiDeS) Group University of Southern California (USC) 5G-<Molisch> Why hy mm-wave for cellul ular Many GHz of bandwidth available Cellular: 28,

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5G-<Molisch>

5G Channel Modeling for mmW Systems

Andreas F. Molisch

Wireless Devices and Systems (WiDeS) Group University of Southern California (USC)

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Why hy mm-wave for cellul ular

  • Many GHz of bandwidth available

– Cellular: 28, 38, 71-76, 81-86 – WLAN: 58-56

  • Short range due to high free-space pathloss
  • Natural fit for small-cell communications
  • History:

– Much activity in 1990s – Failure due to cost, not operating principles – Now CMOS available for mm-wave

  • System design requires understanding of channel
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Table of cont ntents nts

  • Motivation and basic propagation effects
  • Pathloss
  • Delay spread and angular spread
  • Modeling approaches
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Main n application n scena narios

  • Microcells
  • Macrocells
  • Backhaul
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Free space

  • Free-space pathloss:

– Mm-waves have high pathloss for constant-gain antennas – Mm-waves have low pathloss for constant-area antennas

  • Requires adaptive beamforming
  • Atmospheric attenuation

– No major concern at considered distances

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Penetrat ation loss

  • Outdoor walls:

– Attenuation up to 60 dB – Type of windows very important:

  • Energy saving

windows: >20 dB

  • Regular windows:

<5 dB

[Haneda et al. 2016]

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Body y shadowing

  • Body shadowing: much more pronounced than at cm-waves

– Body with device blocks radiation from large angular range

  • Bodies and cars blocking

LoS (and more)

  • >20 dB attenuation
  • Implications for system

design: – Connection might break – Or find alternative path (discontinuity in main beam direction)

[Haneda et al. 2016]

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Propagat agatio ion Effe fects

  • Diffuse scattering

– Significant when surface is rough compared to wavelength – Excepted to be much more significant at mm-wave frequencies at large distances (but: compare [Haneda et

  • al. 2014], [Sangodoyin et al. 2015])
  • Doppler spread

– Order of magnitude larger than at microwaves

  • Foliage:

– Stronger attenuation than at microwave

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Measurement methods (I)

  • SISO

– For pathloss and delay spread only – Usually horn antenna at one link end to get link budget – Results specific to used horn – Can measure dynamic effects

  • Rotating horn

– Takes long time to measure all combinations – Real-time measurements not feasible

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Measurement methods (II)

  • Vector Network Analyzer + Virtual Array

– No real-time measurements – Enables high-resolution evaluation (SAGE, RiMax) – Requires synchronization within inverse carrier frequency – Challenges from high frequencies:

  • Precision of virtual array location
  • Calibration of antennas
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Measurement methods (III)

  • Switched beam sounder USC/Samsung

– Real-time measurements – 60 dBm EIRP, 170 dB dynamic range without averaging – High phase stability suitable for high-resolution parameter extraction without cable connection

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[Bas et al. 2017; Arxiv; VTC]

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Table of cont ntents nts

  • Motivation and basic propagation effects
  • Pathloss
  • Delay spread and angular spread
  • Modeling approach
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Pathloss outdoor

  • Cellular access pathloss

coefficient – LOS: 1.7-2.7 – NLOS: 2.5-5

  • Backhaul pathloss

coefficient – LOS: 1.7-1.9 Similar pathloss coefficient as microwave, but higher offset

[Cho et al. 2015]

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Pathloss at large distanc ances

  • Larger pathloss variance at larger distances
  • Two-slope model can provide better fit

[Hur et al. 2016]

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Impact of street canyon

  • Cause for spreading of pathloss different

streets have different slopes

[Molisch et al. 2016]

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Street cany nyon

  • Very strong variations of path loss coefficients from

street to street

– For some streets pathloss curves are almost flat, for

  • thers almost vertical

– Euclidean distance might not be a good metric

  • Shadowing

– on a trajectory along a street has much smaller variance than the “standard deviation” of accumulated measurements from many streets and/or BSs – Shadowing within street is less sensitive to cutoff level

  • Applicability

– Applicable, but not necessary when we only want coverage probability (no interference, no spatial correlation) and the pdf of deviation from mean is known

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Table of cont ntents nts

  • Motivation and basic propagation effects
  • Pathloss
  • Delay spread and angular spread
  • Modeling approach
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Delay ay spread ad

  • Comparable to cm-wave
  • Sample result in suburban environment

[Bas et al. 2017 Globecom]

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Delay (us)

  • 175
  • 170
  • 165
  • 160
  • 155
  • 150
  • 145
  • 140
  • 135
  • 130
  • 125

PDP (dB)

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Number of MPCs

  • Unresolved question

– Delay resolution of mm-wave channels is high – But: outdoor channels usually measured with low angular resolution

  • MPCs occur in clusters

– Cluster number can be assessed more reliably

Daejon, Korea New York City [Cho et al. 2015] [Akdeniz et al. 2014]

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Angular ar spectra a at BS

Inter-cluster Intra-cluster

[Hur et al. 2015]

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Angular ar spectra a at MS

Inter-cluster Intra-cluster

[Hur et al. 2015]

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Table of cont ntents nts

  • Motivation and basic propagation effects
  • Pathloss
  • Delay spread and angular spread
  • Modeling approach
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Winner-typ ype

  • Winner used for LTE evaluations
  • MPCs in “clusters” all have same delay
  • Fixed number of MPCs per cluster
  • Angular spreads and delay spreads are

correlated

  • No Kronecker structure
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COST-typ ype models

  • Intra-cluster: stochastic
  • Inter-cluster: geometry-based stochastic
  • Allows inclusion of dynamic effects (longer

routes)

  • Twin-cluster
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Twin cluster model

BS MS „Twin-cluster“

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Semi-determi minis istic ic

[MiWEBA report D5.1] Combination of geometry and random components; similar to VDCA

  • f COST 259 [Steinbauer and Molisch 2000] and [Kunisch and Pamp 2003]
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Summa mmary

  • Mm-wave well suited for small cells
  • Higher free-space pathloss, but can be compensated

by directive antennas

  • Unreliable links

– Strong pathloss variations – Body shadowing

  • Angular spreads at MS, BS: comparable to microwave
  • Sparse propagation: fewer MPCs
  • Still challenges in measurement technology
  • Ray tracing: point cloud for good accuracy
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Questions ns?

Andreas F. Molisch

Ph.D., FIEEE, FAAAS, FIET, FNAI, MAASc. Head, Wireless Devices and Systems (WiDeS) Group Director, Communications Sciences Institute, Ming Hsieh Dpt. Of Electrical Engineering Viterbi School of Engineering University of Southern California (USC) Los Angeles, CA, USA

Email: molisch@usc.edu Website: wides.usc.edu

Contact information Thanks to: too many colleagues to list……

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Mahal halo

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