Propagation Measurements and Modeling Techniques for 3.5 GHz Radar-LTE Spectrum Sharing

NSMA 5/15/2019 Christopher R. Anderson, [email protected], 410-293-6185 Overview

Propagation measurements and modeling for 3.5 GHz sharing.

Measured interference from the SPN-43 to LTE sysetms.

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. 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 PAL current incumbents.

Environmental Sensing Capability (ESC) device used to detect the presence of Navy Radars. ESC A Spectrum Access Server (SAS) must be able to protect incumbents from interference from PAL and GAA GAA users.

Ensure operation without degrading performance ( “free-for-all” at 2.4 GHz).

Key: Reliable Propagation Model SPN-43 Propagation Measurement Scenario

Tektronix SA2500

Dipole Bandpass Antenna Limiter LNA Filter Herotek Miteq LS0140 AFS3 Dipole mag-mounted on msmt. vehicle.

Amplifier and filter were required to record weak observed signals (net gain 30.8 dB).

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. 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: Model Outputs: Digital Elevation Maps (30m) Path Loss Exponent Saturated exponential diffraction Diffraction Map NLCD 2011 Land Use Classifications Clutter Loss Map Endpoint clutter loss Log-Distance Propagation Linear optimization to Empirically determined slope 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: L PL d= PL d +10 n log d + L +  ( ) ( 0) 10 ( d0 ) Diff i i i=1 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.

d − clear LA=−1e dcrit With diffraction Loss: Diff d   Since is not usually easily invertible, we use the pseudoinverse to solve:

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.

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 GIS Attenuation Factor based propagation model. L Net Path Loss: PL d= PL d +10 n log d + L +  ( ) ( 0) 10 ( d0 ) Diff i i i=1

Diffraction Loss Clutter Loss

d Clutter Loss: dB adjustment for RX Endpoint only. − T LD=−1e dc Diff T  

DT = 0.5 dB dmc = 0.25

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.

Log Distance anchor point PL ( d 0 ) 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.

Existing models are extremely poor at predicting RSS of our dataset. However, they were not designed to meet the conditions of our scenario. Comparison with model derived from ITS 3.5 GHz measurements in Denver and San Diego.

Barren Rural Rural Suburban Suburban Urban Dense Forest Forest Urban Base Propagation Model µ µ µ µ µ µ µ dB dB dB dB dB dB 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

Mean Error RMSE PL Exp. ΔIDH Base Propagation Model 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

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

ITS measurements result in an ~10 dB higher endpoint clutter loss than the SPN-43 measurements. Investigating impact of radar pulse on LTE Performance. 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.

Site 1

Site 3,3A

Site 2 System Configuration

Site Distance Obstruction Radar Ant. Radar Power from Radar Elevation Density (km) (degrees) (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 Uplink BLER vs. Freq Offset

Downlink Throughput 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. −5 SPN-43 operated such that P d = 0.9 and P fa = 10 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. 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. CW Tone, 1755 or 3550 MHz

TX power: +47 dBm. Receiving Antenna GPS TX Gain: 7.7 dBi. Transmitting Antenna Antenna RX Gain: 2.2 dBi. GPS Receiver Rubidium & Signal monitor RX MDS: -120 dBm. Oscillator RF In Max Distance: 18 km Power Amplifier RF Rubidium RF out Oscillator In Record raw I/Q samples as time series. Signal Analyzer Average over 1.0 sec to RF RF eliminate small-scale fading. Signal Generator out In Calibrated on NIST open-air test site. TX Antenna installed on RX Antenna installed on 18m extensible mast. measurement vehicle, Antenna pattern effects are 3m above ground level. extracted from measured RSS. Detailed description of measurement system, location, and procedures

Simple dipole mag-mounted on roof of measurement van. Tektronix SA2500 Amplifier and filter were required to Dipole Bandpass Antenna Limiter LNA record weak observed signals (net gain Filter Herotek Miteq LS0140 AFS3 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. Saturated exponential diffraction model using digital elevation maps. 100m Digital Elevation Map (m) Terrain Blockage Distance (m)

TX

dclear

d LDiff Total Diffraction Loss (dB) − clear dcrit Ad Total Diffraction loss (dB) [1.48 dB] LADiff=− d 1e d Clearance distance below terrain (m) clear dcrit Critical distance (m) [2.0 m]

Illustration of the matrix computation

Rural Forest Rural Interdecile Heights Interdecile Rural Suburban Forest Suburban Urban UrbanDense

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. 20hh Consider the following scenario with grazing angle conditions: d  tr 

ht

hr d The LOS and Reflected signal will combine destructively at the receiver. Path Loss will follow the “Two-Ray Model” where:

PL( d) =+40log10 ( d ) Other Terms

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

Clear sight line to Radar leads to very high RSS.

Low height of Radar + surrounding building/forest leads to diffractive and shadowing losses at certain AoA/AoD.

Result is a very high spread of RSS inside the first ~ 1.0 km radius.