Christopher R. Anderson, canderso@usna.edu, 410-293-6185

Propagation Measurements and Modeling Techniques

for 3.5 GHz Radar-LTE Spectrum Sharing

NSMA 5/15/2019

Overview

Simulated and emulated

interference between SPN-43

and LTE systems.

Disclaimer: The opinions expressed in this presentation are those of the presenter only, and do not necessarily

reflect the views of the United States Naval Academy, Department of the Navy, Department of

Defense, National Telecommunications and Information Administration, Department of Commerce,

or United States Government.

Measured interference from the

SPN-43 to LTE sysetms.

Propagation measurements and

modeling for 3.5 GHz sharing.

For more information on these topics

1. C. R. Anderson and G. D. Durgin, "Propagation measurements and

modeling techniques for 3.5 GHz radar-LTE spectrum sharing," 2017

XXXIInd General Assembly and Scientific Symposium of the International Union

of Radio Science (URSI GASS), Montreal, QC, 2017, pp. 1-4.

2. J. H. Reed et al., "On the Co-Existence of TD-LTE and Radar Over 3.5

GHz Band: An Experimental Study," in IEEE Wireless Communications Letters,

vol. 5, no. 4, pp. 368-371, Aug. 2016.

3. R. J. Achatz, "Interference protection criteria simulation," 2018 IEEE Radar

Conference (RadarConf18), Oklahoma City, OK, 2018, pp. 0473-0477.

4. R. J. Achatz, B. Bedford, “Interference protection criteria simulation,” NTIA

Technical Report, expected June 2019.

3.5 GHz Spectrum sharing as currently

envisioned. A one-slide review.

Allow PAL and GAA access to the 3.5

GHz on a non-interference basis with

current incumbents.

Environmental Sensing Capability

(ESC) device used to detect the

presence of Navy Radars.

A Spectrum Access Server (SAS)

must be able to protect incumbents

from interference from PAL and

GAA users.

Ensure operation without degrading

performance ( “free-for-all” at 2.4

GHz).

Key: Reliable Propagation Model

PAL

GAA

ESC

SPN-43 Propagation Measurement Scenario

Radar located at Webster Field Annex in

St. Inigoes, MD.

Two buildings on either side (~2 stories)

and tall pedestal immediately behind.

Radar Height: 26 ft.

Antenna Uptilt: 3º.

July 10 & Oct. 30, 2014. Nominal weather

both days.

Limiter

Herotek

LS0140

Tektronix

SA2500

Bandpass

FilterLNA

Miteq

AFS3

Dipole

Antenna

Dipole mag-mounted on msmt. vehicle.

Amplifier and filter were required to

record weak observed signals (net gain

30.8 dB).

Measurement results and visualization

Compared Against

Log-Distance Path Loss (baseline)

Extended Hata

Irregular Terrain Model

TIREM

GIS - Attenuation Factor Model (new)

Refined attenuation factor model using St.

Mary’s County GIS data.

Elevation Contour Plot – 10m resolution Example Terrain Profile & Diffraction Loss

Model Inputs:

Digital Elevation Maps (30m)

Saturated exponential diffraction

NLCD 2011 Land Use Classifications

Endpoint clutter loss

Log-Distance Propagation

Empirically determined slope

Model Outputs:

Path Loss Exponent

Diffraction Map

Clutter Loss Map

Linear optimization to

determine model parameters.

Finding the attenuation factors.

If we use a least-squares formulation, then path loss for the kth link can be written as:

Given K total measurements, we can express this in matrix form:

is a K x I matrix, where I is the total number of attenuation factors in the model. Each

entry represents the number of each factor present for that link.

is a 1 x I matrix of the attenuation losses for the model, and is the unknown we are solving for.

Since is not usually easily invertible, we use the pseudoinverse to solve:

Using the technique presented in: G. D. Durgin, T. S. Rappaport, and H. Xu, “Measurements and models for radio path loss and penetration loss in and

around homes and trees at 5.85 GHz,” IEEE Transactions on Communications, Vol. 46, No. 11, Nov. 1998, pp. 1484-1496.

The result minimizes the mean square error of the system, not necessarily for any one

specific attenuation type. Will be differences when compared to individual link analyses.

( ) ( ) ( )00 10

1

10 logL

dDiff i id

i

PL d PL d n L =

= + + +

1 e

clear

crit

d

d

Diff dL A−

= −

With diffraction Loss:

The GIS Attenuation Factor based

propagation model.

Net Path Loss:

1 e

0.5

0.25

T

c

d

d

Diff T

T

c

L D

D dB

d m

− = −

=

=

Diffraction Loss

Clutter Loss: dB adjustment for RX Endpoint only.

Clutter Loss

( ) ( ) ( )00 10

1

10 logL

dDiff i id

i

PL d PL d n L =

= + + +

Note: Negative clutter loss does not imply a gain. It is simply less measured loss than

the baseline model predicted.

Numerical analysis of the accuracy of the

three major proposed propagation models.

Existing models are extremely poor at predicting RSS of our dataset.

However, they were not designed to meet the conditions of our scenario.

Log Distance anchor point at 80 meters at ground level.

eHata anchored at 1 km Avg. RSS, does not meet 30m TX height. Implemented

from NTIA TR-15-517, ported from Fortran.

ITM/TIREM from NRL Builder Implementation w/ theoretical antenna patterns.

GIS Model incorporates derived clutter losses.

( )0PL d

Comparison with model derived from ITS

3.5 GHz measurements in Denver and San Diego.

Base Propagation Model

Barren Rural Rural

Forest

Suburban Suburban

Forest

Urban Dense

Urban

µ

dB

µ

dB

µ

dB

µ

dB

µ

dB

µ

dB

µ

dB

ITM (Raw) N/A — — — — — —

ITM + Clutter N/A -1.7 — 11.9 — 5.2 4.5

Log Distance N/A -1.5 — 5.1 — 2.5 2.7

Free-Space + Diffraction N/A 17.2 — 21.2 — 19.3 20.4

Base Propagation Model

Mean Error RMSE PL Exp. ΔIDH

dB dB dB / m

ITM (Raw) -6.4 20.1 — —

ITM + Clutter 0.0 18.8 — —

Log Distance 4.5 13.6 2.53 0.094

Free-Space + Diffraction 3.2 12.9 2.0 0.079

ITS measurements result in an ~10 dB higher endpoint clutter loss than the

SPN-43 measurements.

Ldiff is ITU P.526 double knife-edge diffraction.

Investigating impact of radar pulse on LTE

Performance.

Site 1

Site 3,3A

Site 2

Setup 3 test links using a R&S EnB Emulator and handset.

Environments were clear, cluttered, and forested.

Distances were 1.2 – 4.0 km from the Radar.

-8.0 dBm UE transmit power to emulate femtocell links.

Swept LTE frequency to investigate effects of Radar pulse.

System Configuration

Site Distance

from Radar

(km)

Obstruction Radar Ant.

Elevation

(degrees)

Radar Power

Density

(dBm/cm2)

1 1.19 None +3 -17.1

2 3.98 Forest clutter +3 -84.6

3 1.26 Forest +3 -57.4

3A 1.26 Forest 0 -14.8

Downlink Uplink [1] Uplink [2,3] Uplink [3A]

Modulation 16 QAM QPSK QPSK QPSK

LTE Bandwidth (MHz) 10 10 10 10

# Res. Block 50 50 10 10

TX Power/Block (dBm/15 kHz) -42.8 -35.8 -29 -1

Total TX Power (dBm) -15.0 -8.0 -8.0 +20

RX Noise Floor (dBm) -126 -81 -81 -81

Results

Downlink BLER vs. Freq Offset

Downlink Throughput vs. Freq Offset

Uplink BLER vs. Freq Offset

Uplink Throughput vs. Freq Offset

Notes

Radar spectrum is asymmetric – causes asymmetric performance.

Site 2 and 3A are consistently the best performing, likely because of local geometry.

IPC emulation and simulations by NTIA/ITS.

Measurement setup and configuration.

Simulation of SPN-43 and LTE link operating simultaneously.

LTE configured in FDD mode, 10 MHz BW, 22.5 dB SNR, 50 Mbps.

SPN-43 operated such that and at baseline.

SPN-43 prf was set at exactly 1.0 kHz (pessimistic).

LTE was configured with 0 HARQ (vs. 8 in a nominal deployment).

Updated results in new NTIA Tech Report that more closely match a

nominal LTE configuration.

0.9dP =510faP −=

Throughput Performance and

comparison to our field test results.

Downlink

Throughput

vs. Freq Offset

Approximately the region where

our test was operating.

Of note: The ITS simulations (configured for worst-case) mostly agreed

with our measured results. The ITS lab measurements (interference to a

random RB) were more optimistic.

SPN-43 interference predictions.

For measured performance, 10

test targets were generated

along a radial for every

rotation. In 20 rotations, a

tester counts the number of

visible targets.

Stark contrast between the simulated Pd and Pfa and the measured Pd and Pfa.

Pd and Pfa were based on subjective judgment when a number of false alarms are

present on the screen.

Noticeable impact at -12 dB INR, 6 dB below the current -6 dB INR protection.

Observations

Field measurements, lab emulations, and simulations have demonstrated

the ability of LTE to co-exist with the SPN43.

The current “classic” models (e.g., very tall transmitter, very large area

coverage, path over land) are not a good match for small-cell 3.5 GHz

deployments.

The measured data we’ve analyzed thus far demonstrates a site-specific

nature to clutter losses along with a potentially high variability.

However, I would advocate against “dump everything into a deep learning

network and let it figure out the rest.” There’s still a need for a physics

foundation and knowledgeable propagation engineers.

Conclusions

Accurate, Reliable, Robust propagation models are vitally

important to the envisioned operation of spectrum sharing

systems.

A simple GIS-based Attenuation Factor model produced a 3-

20 dB improvement in RMSE vs. current models used in the

band.

IPC evaluation of LTE and SPN-43 under simulation,

emulation, and field measurements appear to agree – but

suggest careful selection of the IPC criteria.

Questions?

Backup Slides

Overview of the measurement system for a

new measurements-based model.

Signal Generator

Power Amplifier

Rubidium

Oscillator

Signal

Analyzer

GPS Receiver

& Signal monitor

Rubidium

Oscillator

RF

out

RF

outRF

In

Transmitting

Antenna

RF

In

Receiving

AntennaGPS

Antenna

RF In

TX Antenna installed on

18m extensible mast.

RX Antenna installed on

measurement vehicle,

3m above ground level.

CW Tone, 1755 or 3550 MHz

TX power: +47 dBm.

TX Gain: 7.7 dBi.

RX Gain: 2.2 dBi.

RX MDS: -120 dBm.

Max Distance: 18 km

Record raw I/Q samples as

time series.

Average over 1.0 sec to

eliminate small-scale fading.

Calibrated on NIST open-air

test site.

Antenna pattern effects are

extracted from measured RSS.

Detailed description of measurement system,

location, and procedures

Limiter

Herotek

LS0140

Tektronix

SA2500

Bandpass

FilterLNA

Miteq

AFS3

Dipole

Antenna

Simple dipole mag-mounted on roof of

measurement van.

Amplifier and filter were required to

record weak observed signals (net gain

30.8 dB).

Receiver in Amplitude vs. Time mode.

Each msmt. captured ~20 msec of data in

Max Hold mode with GPS coords.

Both stationary and moving (<55 MPH).

Raw data was postprocessed via Python

scripts, then loaded into Matlab for

analysis and visualization.

Antenna pattern translated to Matlab

from measured data.

SPN-43 Propagation Measurement Scenario

SPN-43 Operating Parameters

Tuning Range 3500 – 3650 MHz

Pulse Repetition Rate 889 (±20) µs

Pulse Width 0.9 (±0.15) µs

TX Power (Max) 850 (±150) kW

Bandwidth 1.3 (±0.3) MHz

Antenna Gain 32 dBi

Polarization Horizontal or Circular

Beamwitdth (3 dB) 3º

Rotation Rate 15 RPM (4 sec)

Radar located at Webster Field Annex in

St. Inigoes, MD.

Two buildings on either side (~2 stories)

and tall pedestal immediately behind.

Radar Height: 26 ft.

Antenna Uptilt: 3º.

July 10 & Oct. 30, 2014. Nominal weather

both days.

100m Digital Elevation Map (m) Terrain Blockage Distance (m)

Saturated exponential diffraction model using

digital elevation maps.

1 e

clear

crit

d

d

Diff dL A−

= −

Diff

d

clear

crit

L

A

d

d

Total Diffraction Loss (dB)

Total Diffraction loss (dB) [1.48 dB]

Clearance distance below terrain (m)

Critical distance (m) [2.0 m]

cleard

TX

Illustration of the matrix computation

Inte

rdeci

le H

eig

hts

Rura

l

Rura

l Fore

st

Suburb

an F

ore

st

Urb

an

Dense

Urb

an

Suburb

an

Solving minimizes the mean square error with respect to

the difference between measurements and models.

Can sometimes be instructive to illustrate which attenuation factors have the

biggest impact on the propagation loss.

Technique can be used for model tuning and optimization if attenuation loss

for a particular category is fixed a priori.

To understand clutter “gain”, consider first

Two-Ray Propagation.

Consider the following scenario with grazing angle conditions:20 t rh h

d

th

rh

d

The LOS and Reflected signal will combine destructively at the receiver.

Path Loss will follow the “Two-Ray Model” where:

Note 1: Essentially Log-Distance with n = 4.0.

( ) ( )1040log Other TermsPL d d= +

What might be causing negative clutter loss?

Hypothesis based on Two-Ray model.

Hypothesis 1: Direct path is blocked, but lateral wave propagates over the canopy. Results

provides enhancement relative to 2-Ray (n = 4) Propagation.

Hypothesis 2: Direct path is blocked by foliage/canopy, with no lateral wave. Propagation is only

through ground reflection; no destructive interference as in 2-Ray model.

First: What’s causing the RSS spread? A

closer look at the < 1 km distance.

Low height of Radar +

surrounding building/forest

leads to diffractive and

shadowing losses at

certain AoA/AoD.

Clear sight line to Radar

leads to very high RSS.

Result is a very high

spread of RSS inside the

first ~ 1.0 km radius.