Timothy R. Newman, Ph.D. Wireless @ VT Wireless @ Virginia Tech - - PowerPoint PPT Presentation

Timothy R. Newman, Ph.D. Wireless @ VT

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

Wireless @ Virginia Tech

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

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

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

OSSIE Status

OSSIE Open Source Core Framework

• Release 0.7.1 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

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 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

Cognitive Engine – Software Architecture

• bserve

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 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.

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

• n 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/SW Interface

Hardware Side

Software Side

CR #3 CR #4 CR #5 CR #6 CR #1 CR #2

Server Cluster

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.

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.

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.

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.