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

Transcription

1 White Sands Missile Range (WSMR) Radio Spectrum Enterprise Testbed: A Spectrum Allocation Solution Spectrum Management Academic Partnership (SMAP) Juan F. Gonzalez, B.S.E.E Graduate Research Associate jfgonzalez3@miners.utep.edu Virgilio Gonzalez, Ph.D. Principal Investigator vgonzalez3@utep.edu Pablo Rangel, M.S.E.E Doctoral Research Associate prangel2@miners.utep.edu

2 OUTLINE FCC (AWS-3 loss reason) UTEP Proposal Project Management & Systems Engineering Requirements Collection & Literature Review Characterization Testbed for Spectrum Mitigation Summary References

3 FCC SUMMARY Amendment of the Commission s Rules with Regard to Commercial Operations in the MHz, MHz, and MHz Bands [GN Docket No ] AWS-3: Advanced Wireless Services [ MHz, MHz, and MHz bands]. FCC made available 65 MHz of reserved spectrum for commercial use. DoD Proposal MHz band (25 MHz) of military spectrum will be removed from MHz band for commercial use. Current used of MHz band to be allocated into MHz band. (allocating 25 MHz into currently used 70 MHz) MHz band used on shared basis. DoD total estimated cost of new allocation: $3.5 billion.

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5 MHz

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7 UTEP Proposal Submitted by Virgilio Gonzalez and Pablo Rangel

8 Proposal Scope Optimization of the interaction of existing communications (ex. LTE and telemetry) through the radio spectrum. Open the path to ease the adoption of newer technologies (5G, IoT) through the WSMR radio spectrum ontology testbed. Evolution of legacy fixed to software defined systems opportunities to handle the spectrum. to create new The proposed research will emphasize the coordination aspect between the applications and users to access the common spectrum resource. The proposed work will be divided into the management of the communications spectrum solution and the definition of an ontology testbed.

9 Spectrum being acquired by communication/telephony companies. This is the current trend. Figure 1a. Wireless Core network evolution (Alcatel-Lucent 2009). Figure 1b. LTE Packet Core (Stallings 2014)

10 Background Topics: Legacy networks and systems Evolved architecture must consider the support and coexistence for some type 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 totally replaced overnight. Architectural model to be develop will consider the process to sustain and emulate legacy services through the new platform.

11 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.

12 Project Management & Systems Engineering

13 Project Personnel Organization Dr. Virgilio Gonzalez Principal Investigator Pavel Corral WSMR Project Manager Pablo Rangel Doctoral Research Associate Dr. Patrick Debroux ARL SLED Juan F. Gonzalez Graduate Research Associate

14 ConOps Revision: 12/15/2016 Data Communications Electromagnetic Spectrum Knowledge and Existing Solutions DoD Needs, Wants and Requirements Ontologies and Organized Knowledge Spectrum Applications New Technologies Impact EXTRACT Terrestrial P-P Wireless Communication Terrestrial P-MP Wireless Communication Satellite Radar Wired Communication Spectrum Basic Technology Fundamentals Bands Technology Application and Uses DCES_SME_KB Database SOLVE 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 T&E PROTOTYPE SME ANALYZE

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16 Functional Analysis Extract Analyze Allocate Organize Collect Prototype Solve Predict Test & evaluate

17 Requirements Collection & Literature Review

18 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 Objectives: 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 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) IoT

19 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).

20 Characterization Testbed for Spectrum Mitigation

21 Spectrum Robustness Analysis Experiment & Interference Importance Tx M 2 M 1 Rx Interference Source M 3 Noise Fig. 1. Basic experimental layout for the communication systems employed. The blocks represent a hardware component that does a specific task. What are you willing to loose/mitigate? Ex. Data, Video Streaming, Frames

22 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.

23 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 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.

24 References [1] Advanced Wireless Services (AWS). Washington, D.C.: Federal Communications Commission (FCC). (accessed January 5, 2017). [2] Auction 97 Advanced Wireless Services (AWS-3),. Federal Communications Commission. Washington, D.C.: (accessed December 3, 2016) [3] United States Frequency Allocation Chart. Washington, D.C.: National Telecommunications & Information Administration (NTIA). (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 [5] Nick Massa, Fiber Optic Telecommunication, Fundamentals of Photonics. University of Connecticut, Module 1.8, p

25 Bios Juan F. Gonzalez is a student at The University of Texas at El Paso (UTEP) pursuing a Master of Science in Electrical Engineering. He graduated from UTEP in May 2016 with a Bachelor of Science in Electrical Engineering. Currently employed as a Masters Research Assistant, his main objective is to classify signals in order to propose solutions for their coexistence. He has worked as an IT administrator, and in the patent division of the University. He is able to continue his education thanks to the scholarships and research assistantships 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 on Robotics, more specifically, in multi-agent systems; his interest is in collision avoidance for heterogeneous swarms 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 Electrical Engineering. 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 IEEE Robotics and Automation Society for the UTEP Chapter. Dr. Virgilio Gonzalez is a Clinical Associate Professor and Associate Chair at UTEP, from which he obtained a Ph.D. in Computer Engineering. He obtained his Master s in Manufacturing Systems, and his Bachelor s in Electronics and Communications Engineering from Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM) in Mexico City. He worked for AT&T-Alestra, as the Technology Planning Manager, and as Telecom 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 the project as the Principal Investigator.