Communication Technology Metrology for 5G Innovation

Nada Golmie

Chief, Wireless Networks Division 
Communication Technology Laboratory 

Established in 2014

Through development of appropriate measurements and standards:

• Enable robust, mission-critical, interoperable public safety communications

• Enable effective and efficient spectrum use and sharing

• Enable advanced communications technologies

• Identify next generation wireless technology measurement 

challenges, and develop appropriate measurement science to 

support innovation. 

• Strengthen spectrum sharing, coexistence, and channel propagation 

and modeling expertise.

• Develop measurements to support future generation wireless: 

massive-MIMO, millimeter wave, ultra-dense networks.

• Support the development of future generation wireless standards 

and pre-standards activities.

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Advanced Communications: “5G” Program

Technical Thrusts

• Millimeter wave metrology

• Ultra-dense networks

• Massive MIMO

Drivers

• Exponential increase in demand for wireless data 

transmission – massive increases in:

• capacity >1,000x

• connectivity (billions of users and machines)

• Top administration priority

• Widely recognized need to develop greater resource 

efficiencies – including temporal, spectral, coding, and spatial

• Integrated-circuit technology provides components, antennas at millimeter wave frequencies

The White House

Office of the Press Secretary

For Immediate Release 

June 14, 2013 

Presidential Memorandum -- Expanding 

America's Leadership in Wireless 

Innovation

MEMORANDUM FOR THE HEADS OF EXECUTIVE 

DEPARTMENTS AND AGENCIES

SUBJECT: Expanding America's Leadership in Wireless 

Innovation

A combination of American entrepreneurship and 

innovation, private investment, and smart policy has 

positioned the United States as the global leader in 

wireless broadband technologies. 
Millimeter Wave Metrology

• 5th year of NIST Innovation in Measurement 

Science program: “Traceability to Enable Giga- bit-per-Second Mobile Wireless.” 

• Channel sounders for 83.5, 28, and 60 GHz

• Development of channel propagation models

• Contributions to SDOs (e.g. IEEE 802.11ay)

• Calibrations, uncertainties for millimeter wave wideband 

vector sources and receivers: new IEEE Best Practices 

document.

• Over-the-air test of highly integrated millimeter wave 

devices

• Nonlinear network analysis of amplifiers, circuit 

components

Distance 

and angle 

and Doppler

1% uncertainty?

1.6% EVM at 45 GHz
Unique Channel Sounders

83.5 GHz channel measurements in NIST lab

x [m]

1 2 3 4 5 6 7

y [m] 0

1

2

3

4

5

6

0 20 40 60 80 100 120 140 0

100

200

300

400

500

600

700

800

Point #

Velocity (mm/s)

 

0 0.05 0.1 0.15

-130

-120

-110

-100

-90

-80

-70

-60

-50

-40

Time (usec)

PDP Amplitude (dB)

 , 

LOS On-Axis

NLOS On-Axis

LOS On-Axis Elev 45

NLOS On-Axis Elev 45

Receive array location

TX

Receive array velocity

Power delay profile: one location

• Fast: electronic switching and direct digitization of 

16 scalar feed horn receive antennas 

• Mobile: Robotic, laser-guided navigation system

• Centimeter accuracy (indoor), 

• GPS equipped (outdoor)

• Directional: 45°Angle of arrival resolution over 

upper hemisphere
Channel Modeling Capabilities

Small-scale fading and Doppler-frequency shift

• Fading distribution (Rayleigh, Rician, etc.) and Doppler-frequency shift 

computed for each path

• Coherence time computed from Doppler-frequency spread over all paths

• Example confirms that the direct path and the wall-reflected path have 

opposite Doppler shift 

Large-scale path loss and shadowing

• The path loss for each path can be computed 

separately

• Example shows path loss exponent of direct LOS path is 

~2.0

Tx-Rx Separation [m]

1.5 2 2.5 3 3.5 4 4.5 5 5.5 6

Path Loss [dB]

50

60

70

80

90

100

110

120

LOS

NLOS

n

L O S

= 2.0304, L O S

= 1.7737

n

N L O S

= -0.2595, N L O S

= 2.3091

Free Space Loss

Multidimensional power profiles

• Each path indexed according to delay, azimuth, and elevation

• Enables parameterizing Saleh-Valenzuela-type models 

• RMS-delay/angle spread and coherence bandwidth 

• Example shown is power vs. azimuth and delay
Response to Industry Need

Key Causes for Action:

• Industry needs accurate millimeter wave channel models ASAP 

for standardization and to optimize hardware design for a 

variety of different usage scenarios and environments.

• Individual research organizations do not have the scale, visibility 

or resources to characterize millimeter wave propagation across 

a sufficiently broad spectrum.

• Need for increased partnership and communication between 

Industry and Academia.

• Lack of understanding of current millimeter wave research 

efforts and need for improved coordination.
NIST/CTL Establishes 5G Millimeter 

Wave Channel Model Alliance

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• NIST convened Alliance’s first meeting in July 2015, in 

Boulder, to define charter, organizational structure, and 

develop plans for working group activities. 
Organizational Expectations

Transparency:

• The Alliance openly publishes its mission, research 

activities, data, and work products

• Participation is open to the public

Flexibility:

• No formal membership, fees, binding contracts or 

legal agreements

• Participation is entirely voluntary 

Open Data Sharing:

• Participants are encouraged to share non-sensitive 

information with fellow working group members

• Success of the Alliance depends on efficient, 

coordinated exchange of measurement and modeling 

data and methodologies

Member Discretion:

• Participants are not forced to share data is considered 

intellectual property under copyright

Connection to Other Efforts:

• Alliance research is not tied to a single wireless 

system, device, or organization: 

• Broad scope provides in-depth, extensible 

understanding of millimeter wave propagation 

mechanisms

• Aggregation of data from multiple sounders: more 

comprehensive view, more predictive models

Developing Consensus:

• Group is not used to provide consensus advice or 

recommendations to NIST or SDOs

Opportunity for Partnership:

• Alliance to leverage industry conferences to 

publicize work, solicit additional input, and host 

meetings
Less than a year later...

10

• Established user community

5G Alliance Wiki Link:

https://sites.google.com/a/corneralliance.com/5gmmwave-channel-model-alliance-wiki/home

• Alliance organizing two workshops co-located 

with IEEE VTC, September 2016 in Montreal 

Canada, and IEEE Globecom, December 2016 

Washington DC.

• Repository of data measurements and models 

coming online soon

• NIST to host through web services
Short-Term Milestones

• Select a limited number of usage scenarios:

• Frequencies

• Environments

• Parameters and metrics

• Conduct measurements in canonical 

environments for hardware verification

• Develop modeling framework

• Conduct parallel measurement campaigns

• Produce initial models based on data from 

multiple channel sounders

• Submit to standards groups

• Publish in the open literature
NIST’s Contributions

• Contribute measurement data and models

• Support and coordinate working groups

• Establish methods for joint use of data

• Develop efficient data reduction techniques

• Aggregate data from different channel sounders into sophisticated new 

models

• Facilitate open communication

• Run meetings and virtual collaboration platform

• Publish data, methodologies, papers and models
Cost of NIST Support Role

• Burden on NIST technical staff

• Involvement in Alliance activities represents 30~40% of total labor dedicated 

to project

• Time spent on organization and coordination is time away from lab 

experiments and results

• Service contract to assist in working group facilitation/coordination

• Monthly fees and service contract to host online data repository 
Going Forward – Long Term

• Establish common methods for hardware calibration and 

measurement with uncertainties:

• IEEE Guidance / Best Practice Document

• Improved accuracy of channel models:

• Spatial multiplexing and/or massive MIMO

• Mobility & dynamic environments

• Device-to-device models

• Methods to predict system performance

• Refine models selected by standards bodies, if necessary

• Refine models for hardware deployment