Timothy R. Newman, Ph.D. VT

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1 Timothy R. Newman, Ph.D. VT

2 Virginia Tech Wireless Umbrella Group MPRG, CWT, VTVT, WML, Antenna Group, Time Domain Lab, DSPRL Officially rolled out June 2006 Currently 32 tenure track faculty and more than 111 students Backlog in research growing University providing initial financial support Cognitive Networks targeted as strategic technical growth effort

3 Cognitive Radio Research Focus Areas Interoperability between legacy radio systems Focus on public safety systems (P25) Dynamic Spectrum Access Signal detection and classification Distributed spectrum sensing Cognitive Radio Networks Distributed computing Software Defined and Cognitive Radio Security Software Assurance DSA Security Analysis Distributed Cognitive Radio Network Trust

4 An Open Systems Approach for Rapid Prototyping Waveforms for SDR Faculty: J.H. Reed, W.H. Tranter, R.M. Buehrer, and C.B. Dietrich Funding: NSF, SAIC, Tektronix, TI, ONR, LTS Description: Work is ongoing in four major areas: Open Source SCA Core Framework (OSSIE) Rapid Prototyping Tools for SCA Components and Waveforms Component and Device Library Software Defined Radio Education

5 OSSIE s Goal: Support Education and Research OSSIE and Wireless Education: Software not emphasized in wireless education Grad. researchers learn SCA and SDR design Used in Virginia Tech and Naval Postgraduate School SDR classes NPS and VT developing free OSSIE lab modules OSSIE Enables SDR Research Baseline for studying architectures Power management Component deployment Testing OSSIE Enables other Wireless Research Cognitive Radio, e.g., VT s CoRTekS Collaborative radio Distributed processing over wireless links Propagation studies and MIMO

6 OSSIE Status OSSIE Open Source Core Framework Release available for download VMWare images available OSSIE Waveform Developer (OWD) Open Source Rapid Prototyping Tool Available for download Waveform Debugging Tool (ALF) Developed by SAIC Available for download OSSIE Labs Developed by NPS and Virginia Tech

7 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

8 Example Project: Morpheus Features Virginia Tech is Porting OSSIE to the Morpheus Radio (4) Xilinx XC4VLX60 s DAC ADC Stratix (2) DDS TI DaVinci (ARM+DSP) Flash & ROM

9 Distributed Computing for Collaborative Software Radio Faculty: Jeff Reed and Tim Newman Funding: ONR Description: Develop a distributed computing environment linked by wireless Show harvest energy trade offs Develop applications Collaborate Detection/classification Data Fusion Distributed MIMO

10 Cognitive Engine Software Architecture observe Adapt Learn and reason United States Patent 7,289,972 Cognitive Radio Engine Based on Genetic Algorithms in a Network

11 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.

12 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

13 The Cognitive Gateway

14 Proposed Solution A Cognitive Gateway (CG) to facilitate interoperability between incompatible radios (or systems) and provide an extended service coverage 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.

15 Cognitive Radio Network Testbed (VT CoRNET) Faculty: Jeffrey Reed, Tamal Bose,Timothy Newman Funding: VT ICTAS Description: 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. Hardware Side Physical Cognitive Radio Nodes CR #1 CR #3 CR #5 CR #2 CR #4 CR #6 HW/SW Interface Software Side Virtual Cognitive Radio Nodes Server Cluster

16 Cognitive Radio Network Security Faculty: Jeffrey Reed, Timothy Newman Funding: DoD Description: 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.

17 Distributed Spectrum Sensing for Cognitive Radio Systems Faculty: Claudio da Silva Description: 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, and evaluate the reliability and complexity of the spectrum sensing stage.

18 Efficient Jammers using a Cognitive Radio Network Faculty: Tamal Bose, Jeff Reed Funding: CAER Description: 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.

19 Modular Open Source Cognitive Radio Architecture Flexible CR development architecture 4 Categories of system components Cognitive Radio Shell Cognitive Engine Policy Engine Front 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.