White Sands Missile Range (WSMR) Radio Spectrum Enterprise Testbed: A Spectrum Allocation Solution

Spectrum Management Academic Partnership (SMAP)

Virgilio Gonzalez, Ph.D.Principal Investigatorvgonzalez3@utep.edu

Juan F. Gonzalez, B.S.E.EGraduate Research Associatejfgonzalez3@miners.utep.edu

Pablo Rangel, M.S.E.EDoctoral Research Associateprangel2@miners.utep.edu

OUTLINE

• FCC 14-31 (AWS-3 loss reason)

•UTEP Proposal

•Project Management & Systems Engineering

•Requirements Collection & Literature Review

•Characterization Testbed for Spectrum Mitigation

• Summary

•References

FCC 14-31 SUMMARY

• Amendment of the Commission’s Rules with Regard to Commercial Operations in the 1695-1710MHz, 1755-1780 MHz, and 2155-2180 MHz Bands [GN Docket No. 13-185]

• AWS-3: Advanced Wireless Services [1695-1710 MHz, 1755-1780 MHz, and 2155-2180 MHzbands].

• FCC made available 65 MHz of reserved spectrum for commercial use.

• DoD Proposal

• 1755-1780 MHz band (25 MHz) of military spectrum will be removed from 1755-1850 MHzband for commercial use.

• Current used of 1755-1780 MHz band to be allocated into 1780-1850 MHz band. (allocating 25MHz into currently used 70 MHz).

• 2055-2110 MHz band used on shared basis.

• DoD total estimated cost of new allocation: $3.5 billion.

1780-1850 MHz

UTEP ProposalSubmitted by Virgilio Gonzalez and Pablo Rangel

Proposal Scope

• Optimization of the interaction of existing communications (ex. LTE andtelemetry) through the radio spectrum.

• Open the path to ease the adoption of newer technologies (5G, IoT) throughthe WSMR radio spectrum ontology testbed.

• Evolution of legacy fixed to software defined systems to create newopportunities to handle the spectrum.

• The proposed research will emphasize the coordination aspect between theapplications and users to access the common spectrum resource.

• The proposed work will be divided into the management of thecommunications spectrum solution and the definition of an ontology testbed.

Figure 1a. Wireless Core network evolution (Alcatel-Lucent 2009). Figure 1b. LTE Packet Core (Stallings 2014)

Spectrum being acquired by communication/telephony companies. This is the current trend.

Background Topics: Legacy networks and systems

• Evolved architecture must consider the support and coexistence for sometype of legacy technologies already deployed for:

• Communications

• Radar

• Telemetry

• One major hurdle in technology change:

• The existing of assets that are already in service and cannot be totallyreplaced overnight.

• Architectural model to be develop will consider the process to sustain andemulate legacy services through the new platform.

Overview ARL/WSMR/UTEP work

1. Characterize spectrum environment is specific WSMR areas

2. Identify nuances to the WSMR spectrum

3. Proposed solutions based on AWS-3 Loss

4. Design solutions that satisfy client requirements

5. Develop spectrum characterization database and optimization modeling tools

6. Develop ontologies to describe the spectrum domain

• Emphasis is on the effects of LTE interference, Dynamic frequency management, tools for characterization and develop an ontology testbed for this.

Project Management & Systems Engineering

Project Personnel Organization

Dr. Virgilio Gonzalez

Principal Investigator

Pablo RangelDoctoral Research Associate

Juan F. Gonzalez

Graduate Research Associate

Pavel CorralWSMR Project Manager

Dr. Patrick Debroux

ARL SLED

ConOpsRevision: 12/15/2016

Spectrum Applications

Terrestrial P-MP Wireless

CommunicationSatellite Radar

Terrestrial P-P Wireless

Communication

Wired Communication

Spectrum Basic

Technology

Bands TechnologyApplication and

UsesFundamentals

· EMF

· Radio Physics

· Electromagnetic Spectrum allocation

· Signals, systems and Transforms

· Data Communications

· Antenna theory

· Analog communications

· Digital Communications

· Software Defined Radio

· Cognitive Radio

· Dynamic Spectrum Access

· Spectrum Analysis Basics

· AWS-3

· Standards

· Interoperability

· Cellular Communication

· Two-Way Trunked Radio

· Wireless connectivity

· Mobile Video Broadcasting

· IoT

· Data Files

· Telemetry

· Voice

· Video

· Real Time

· Near Real Time

· Store & Forward

· Use Cases

EXTRACT

DoD Needs, Wants and Requirements

Data Communications Electromagnetic Spectrum Knowledge and Existing Solutions

New Technologies Impact

Ontologies and Organized Knowledge

SME

DCES_SME_KB Database

ANALYZE

PROTOTYPE

SOLV

E

T&E

Functional Analysis

Organize

Extract

Allocate

Predict

CollectSolve

Analyze

Prototype

Test & evaluate

Requirements Collection & Literature Review

Key points

• Radio Spectrum • Fundamentals and Utilization• Allocation Surveys• Detection Techniques • Analysis and detection equipment survey• Allocation Solutions

• AWS-3 • Bands• Operations• Noise and other Nuances• Mitigation research

• Wireless Communications Techniques• Spread spectrum• Multiple Radio Access Protocols: CSMA• Multiple Division Techniques• Channel Allocation

• Current Wireless Technologies• Cellular• Radar• Wi Fi• Bluetooth• Radio• Ad Hoc and Sensor Networks• Satellite

• Wireless Technologies Updates and Advances• Dynamic Spectrum Access• Cognitive Radio• LTE• 5 G• Beamforming• Massive MIMO• Millimeter Wave• Free Space Propagation (optics)• IoTObjectives:

• Collect, catalog, organize and create guidelines

• UTEP is the Subject Matter Expert (SME) on Radio Spectrum since 2010

• Fully identify the state of the Radio Spectrum at WSMR and catalog solutions

Spectrum Database Ontologies

• Spectrum Basic Technology Ontology: it classifies the spectrum technologies by fundaments, frequency bands legislation and rules, difference among technologies, interference mitigation, and their general application and use.

• Frequency Bands Ontology: defines the spectrum utilization by their frequency (ELF, VF, VLF, LF, MF, HF, VHF, UHF, SHF and EHF).

• Spectrum Applications Ontology: it defines how the spectrum is classified based on data communications transmissions (Terrestrial Wireless Point-to-Point, Terrestrial Wireless Point-to-Multipoint, Satellite, Radar and Wired).

Characterization Testbed for Spectrum Mitigation

Fig. 1. Basic experimental layout for the communication systems employed. The blocks represent a hardware component that does a specific task.

Tx M2

Interference

Source M

3

Noise

Rx M1

Spectrum Robustness Analysis Experiment & Interference Importance

Ex. Data, Video Streaming, Frames…

What are you willing to loose/mitigate?

Scenarios

• Analysis of spectrum utilization within existing and future system communications: • Ex. does a video stream affects a signal?• Ex. how effective will be the mitigation solution?

• Analysis of spectrum interference done to existing systems due to LTE and vice versa.

Summary

The objective of this project is to automate and make more efficient use of the spectrum, our solution will be composed of three steps:

1. Ontology – a database containing all the theoretical information to back up our rules.

2. Spectrum characterization – this step is crucial for identifying the users and the use of the spectrum. Here is where all the data will be collected from the experiment.

3. Rules of interaction – these rules will be generated by the data collected from the previous step, and will be backed by the information contained in the database. These rules will ultimately aid in the efficient usage of the spectrum.

The spectrum band of concern is the 1780 – 1850 MHz band, with an emphasis on commercial LTE interference. The objective is for both uses to not interfere with each other, this to avoid any penalization by the FCC on each of the parties.

References

[1] 2015. Advanced Wireless Services (AWS). Washington, D.C.: Federal Communications Commission

(FCC). https://www.fcc.gov/general/advanced-wireless-services-aws (accessed January 5, 2017).

[2] 2014. “Auction 97 Advanced Wireless Services (AWS-3),”. Federal Communications Commission.

Washington, D.C.: http://wireless.fcc.gov/auctions/default.htm?job=auction_factsheet&id=97

(accessed December 3, 2016)

[3] 2016. United States Frequency Allocation Chart. Washington, D.C.: National Telecommunications

& Information Administration (NTIA). https://www.ntia.doc.gov/page/2011/united-states-frequency-

allocation-chart (accessed November 15, 2016).

[4] M. N. O. Sadiku, S.M. Musa, and Sudarshan R. Nelatury, “Free Space Optical Communications: An

Overview,” in European Scientific Journal, vol. XII., February 2016, ISSN 1857-7431.

[5] Nick Massa, “Fiber Optic Telecommunication,” Fundamentals of Photonics. University of

Connecticut, 2000. Module 1.8, p. 293-347.

Bios

• Juan F. Gonzalez is a student at The University of Texas at El Paso (UTEP) pursuing a Master of Science inElectrical Engineering. He graduated from UTEP in May 2016 with a Bachelor of Science in ElectricalEngineering. Currently employed as a Masters Research Assistant, his main objective is to classify signals inorder to propose solutions for their coexistence. He has worked as an IT administrator, and in the patentdivision of the University. He is able to continue his education thanks to the scholarships and researchassistantships awarded. Member of IEEE, IEEE-HKN, IEEE ComSoc, MAES, SHPE, and TSPE.

• Pablo Rangel is a doctoral student at UTEP, and is currently employed as a Research Assistant focused onRobotics, more specifically, in multi-agent systems; his interest is in collision avoidance for heterogeneousswarms of drones in an airway. He has also done research on Spectrum Dynamic Access and Cognitive Radio.He is a UTEP alumni from where he obtained both his Bachelor’s and Master’s degrees in ElectricalEngineering. He has been recognized by the graduate school for his research in Unmanned Aerial Vehicles(UAVs), and played a crucial role in the proposal of this project. He is the current president for the IEEERobotics and Automation Society for the UTEP Chapter.

• Dr. Virgilio Gonzalez is a Clinical Associate Professor and Associate Chair at UTEP, from which he obtained aPh.D. in Computer Engineering. He obtained his Master’s in Manufacturing Systems, and his Bachelor’s inElectronics and Communications Engineering from “Instituto Tecnológico y de Estudios Superiores deMonterrey (ITESM)” in Mexico City. He worked for AT&T-Alestra, as the Technology Planning Manager, and asTelecom Director of the ITESM-RZS in Mexico City. His research topics include: Robotics, Telecommunications,Fiber Optics, Systems Engineering and Operations, and Academic Advising. He is of vital importance to theproject as the Principal Investigator.