Timothy R. Newman, Ph.D.Wireless @ VT

Wireless Umbrella GroupMPRG, CWT, VTVT, WML, Antenna Group, Time Domain Lab, DSPRL

Officially rolled‐out June 2006Currently 32 tenure‐track faculty and more than 111 students Backlog in research growingUniversity providing initial financial supportCognitive Networks targeted as strategic technical growth effort

Wireless @ Virginia Tech

Cognitive Radio Research Focus AreasInteroperability between legacy radio systems

Focus on public safety systems (P25)Dynamic Spectrum Access

Signal detection and classificationDistributed spectrum sensing

Cognitive Radio NetworksDistributed computing

Software‐Defined and Cognitive Radio SecuritySoftware AssuranceDSA Security AnalysisDistributed Cognitive Radio Network Trust

An Open Systems Approach for Rapid Prototyping  Waveforms for SDR

Faculty: J.H. Reed, W.H. Tranter, R.M. Buehrer, and C.B. DietrichFunding: NSF, SAIC, Tektronix, TI, ONR, LTSDescription: Work is ongoing in four major areas:

Open Source SCA Core Framework (OSSIE)Rapid Prototyping Tools for SCA Components and WaveformsComponent and Device LibrarySoftware Defined Radio Education

OSSIE’s Goal: Support Education and ResearchOSSIE and Wireless Education:

Software not emphasized in wireless educationGrad. researchers learn SCA and SDR designUsed in Virginia Tech and Naval Postgraduate School SDR classesNPS and VT developing free OSSIE lab modules

OSSIE Enables SDR ResearchBaseline for studying architecturesPower managementComponent deploymentTesting

OSSIE Enables other Wireless ResearchCognitive Radio, e.g., VT’s CoRTekS Collaborative radioDistributed processing over wireless linksPropagation studies and MIMO

OSSIE StatusOSSIE Open Source Core Framework

Release 0.7.1 available for downloadVMWare images available

OSSIE Waveform Developer (OWD) Open Source Rapid Prototyping ToolAvailable for download

Waveform Debugging Tool (ALF)Developed by SAICAvailable for download

OSSIE LabsDeveloped by NPS and Virginia Tech

Example Project:  Porting OSSIE to Morpheus Radio

Morpheus is an IR&D project at Harris, Inc (Melbourne, FL)

This highly agile and compact platform is suited for many adaptive applications

Example Project: Morpheus Features

TI DaVinci(ARM+DSP)

Flash & ROM

(4) Xilinx XC4VLX60’s

DAC

ADC

(2) DDS

Stratix

Virginia Tech is Porting OSSIE to the Morpheus Radio

Distributed Computing for Collaborative Software  Radio 

Faculty: Jeff Reed and Tim NewmanFunding: ONRDescription:

Develop a distributed computing environment linked by wirelessShow harvest energy trade‐offsDevelop applications

Collaborate Detection/classificationData FusionDistributed MIMO 

Cognitive Engine – Software Architecture

observe

Learn and reason

Adapt

United States Patent 7,289,972 Cognitive Radio Engine Based on 

Genetic Algorithms in a Network

Our First Application: The VT Public Safety  Cognitive Radio

• Recognize any P25 Phase 1 

waveforms

• Identify known networks

• Interoperate with legacy networks

• Provide a gateway between 

incompatible networks

•Serve as a repeater when necessary –

useful when infrastructure has been 

destroyed or does not exist.

Demonstrated Capabilities

•Scan Mode:

Shows the user what  waveforms / networks are present

•Talk Mode:

Allows the user to  interoperate with any selected 

network

•Gateway Mode:

Allows the user to  set up a link between any two 

incompatible networks

The Cognitive Gateway

Proposed SolutionA Cognitive Gateway (CG) to facilitate interoperability between incompatible radios (or systems) and provide an extended servicecoverage area

• CG Definition: CG is a special CR node that interconnects different systems.• CG Functions: CG is responsible for automatic communication link

establishments between incompatible systems upon communication initiators’ requests.

Cognitive Radio Network Testbed (VT‐CoRNET)

Faculty: Jeffrey Reed, Tamal Bose ,Timothy NewmanFunding: VT‐ICTASDescription: Develop a large scale hybrid cognitive radio network testbed.  48 physical nodes located in campus building interfaces with up to 1 million virtual nodes simulated on a large cluster located on campus.  This large scale simulation environment enables new and exciting research capabilities.  Physical nodes will make use of custom designed flexible (100 MHz – 4 GHz) RF daughterboard. 

Physical Cognitive Radio Nodes Virtual Cognitive Radio Nodes

HW/SWInterface

Hardware Side Software  Side

CR 

#3CR 

#4

CR 

#5CR 

#6

CR 

#1CR 

#2

Server Cluster

Cognitive Radio Network Security

Faculty: Jeffrey Reed, Timothy NewmanFunding: DoDDescription: Intelligence Community Postdoctoral fellowship aimed at identifying the security issues that cognitive radios bring and develop mitigation techniques for these security issues.First task is to evaluate 

DARPA xG cognitive radio 

network security.  Radios 

provided by Shared Spectrum 

Company.

Read more:  T. Clancy, N. Goergen, "Security in 

Cognitive Radio Networks: Threats and Mitigation," 

Third International Conference on Cognitive Radio 

Oriented Wireless Networks and Communications 

(CrownCom), May 2008. 

Distributed Spectrum Sensing for Cognitive Radio SystemsFaculty: Claudio da SilvaDescription: This project will establish detection limits of distributed spectrum sensing for cognitive radio systems. Specific research objectives are to: 

design signal processing methods at the node level,design data fusion techniques,design algorithms for the transmission of spectrum sensing information, andevaluate the reliability and complexity of the spectrum sensing stage.

Efficient Jammers using a Cognitive Radio NetworkFaculty: Tamal Bose, Jeff ReedFunding: CAERDescription: Develop an efficient jamming system using a Cognitive Jamming Network (CJN) based on cognitive radio technology. Use characteristics of the target signal to create a custom jamming waveform  Jamming is accomplished by using a network of collaborating jammers. This allows each jammer to operate at a lower power, thereby reducing the risk of self‐jamming.

Modular Open‐Source Cognitive Radio  Architecture

Flexible CR development architecture4 Categories of system components

Cognitive Radio ShellCognitive EnginePolicy EngineFront End

Socket interfaces provide language independence.Multiple CE capabilities for distributed CE workload.Initial reference implementation with a CBR engine implemented in C.Optional Policy engine provides additional functionality if desired.