Cognitive and Software Radio

1
Cognitive and Software Radio
2
Critical Research Issues in SDR and Cognitive
Radio

• Efficient and flexible SDR hardware
• Software architectures and waveform development
  tools
• Testing and security of software
• Sensing technologies
• Intelligence for Radios
• Intelligence for Networks

3
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
• 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

4
A Cognitive Radio Through Hardware Adaptation

• Faculty P. Athanas
• Funding Harris Corporation (Melbourne, FL)
• Description Hardware adaptation will be
  accomplished by sensing link statistics and
  multi-tasking radio management functions within
  the Harris Morpheus System-in-a-Package SDR.

The architecture of transmitter and receiver on
the Morpheussoftware defined radio
5
Cooperative Game Theory for Distributed Spectrum
Sharing

• Faculty Luiz A. DaSilva, Allen MacKenzie
• Description We utilize cooperative game theory
  to model situations where wireless nodes need to
  agree on a fair allocation of existing spectrum

Find out more J. Suris et al., Cooperative Game
Theory for Distributed Spectrum Sharing, under
review (available upon request), 2006.
6
Trustworthy Spectrum Sharing in Software Defined
Radio Networks

• Faculty J.-M. Park, T. Hou, J. Reed
• Funding NSF
• Description The emergence of Software Defined
  Radio (SDR) technology raises new security
  implications. In this project, we study security
  issues that pose the greatest threat when an
  adversary is able to install malicious software
  or modify already installed software on an SDR,
  with particular focus on threats that cannot be
  addressed using cryptographic techniques.

Read more R. Chen and J.-M. Park, Ensuring
trustworthy spectrum sensing in cognitive radio
networks, IEEE Workshop on Networking
Technologies for Software Defined Radio Networks
(held in conjunction with IEEE SECON 2006), Sep.
2006.
7
Game-theoretic Framework for Interference
Avoidance

• Faculty A. B. MacKenzie, R. M. Buehrer, J. H.
  Reed
• Funding ONR, ETRI
• Description We use game theory models to
  investigate and develop waveform adaptation
  schemes for interference avoidance in distributed
  and spectrum sharing networks.

Read more R. Menon, A. B. MacKenzie, R. M.
Buehrer and J.H. Reed, A game-theoretic
framework for interference avoidance in ad-hoc
networks, Globecom 2006.
8
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.

9
Application of Artificial Intelligence to the
Development of Cognitive Radio engine

• Faculty J. H. Reed
• Funding Army Research Office
• Description we have investigated the
  applicability of artificial intelligence
  algorithms to the development of cognitive radio
  engine.
• Identify the suitability of the AI techniques for
  the various cognitive radio tasks observing,
  orienting, deciding, and learning.

One of the key results is that a robust cognitive
engine relies on the combination of several
artificial intelligence algorithms ? Our team is
building a cognitive engine leveraging the
knowledge gathered through this research.
10
IEEE 802.22 WRAN Cognitive Engine and
Supporting Algorithms

• Faculty J. H. Reed
• Funding ETRI
• Description we are developing cognitive engine
  (CE) and supporting algorithms for IEEE 802.22
  WRAN system.
• The CE is capable of perceiving current radio
  environment, planning, learning, and acting
  according to its goals and current radio
  environment.

A typical radio environment for cognitive WRAN
system WRAN should be aware of all the local
radio activities surrounding the system so that
it can enable the coexistence of primary users
and secondary users.
11
IEEE 802.22 WRAN Cognitive Engine and
Supporting Algorithms
Detection Classification

• Cognitive engine
• Decide, learn, and plan
• Supporting algorithms
• Spectrum sensing detection and classification
  techniques
• REM-enabled cognition
• Waveform and power adaptation techniques

Adaptation Algorithm
Cognitive Engine
12
Application of Artificial Intelligence to the
Development of Cognitive Radio engine

• Faculty J. H. Reed
• Funding Army Research Office
• Description we have investigated the
  applicability of artificial intelligence
  algorithms to the development of cognitive radio
  engine.
• Identify the suitability of the AI techniques for
  the various cognitive radio tasks observing,
  orienting, deciding, and learning.

One of the key results is that a robust cognitive
engine relies on the combination of several
artificial intelligence algorithms ? Our team is
building a cognitive engine leveraging the
knowledge gathered through this research.
13
Cognitive Radio for Public Safety

• Faculty C. W. Bostian, M. Hsiao, A. B.
  MacKenzie
• Funding NIJ
• Description We are developing a public safety
  cognitive radio that is aware of the RF
  environment, identifying activity in public
  safety bands, and configures itself to needed
  combinations of waveform and network parameters.

Read more Thomas W. Rondeau, et. al. Cognitive
Radios in Public Safety and Spectrum Management
33rd Research Conference on Communications,
Information, and Internet Policy, 2005
14
Cognitive Engine

• Faculty C. W. Bostian, S. Ball, M. Hsiao, A.
  B. MacKenzie
• Funding NSF
• Description We are developing a cognitive
  engine, a software package that reads a software
  defined radios meters and turns its knobs
  intelligently adapting and learning from
  experience in order to achieve user goals within
  operational legal limits.

Read more T.W. Rondeau, B.Le, C.J. Rieser, and
C.W. Bostian, Cognitive Radios with Genetic
Algorithms Intelligent Control of Software
Defined Radios, Software Defined Radio Forum,
Phoenix, AZ, Nov. 15-18, 2004.
15
Cognitive Networks

• Faculty Luiz DaSilva, A. B. MacKenzie
• Funding NSF, DARPA (pending)
• Description we are developing cognitive
  networks, capable of perceiving current network
  conditions and then planning, learning, and
  acting according to end-to-end goals.

Read more R. Thomas et al., Cognitive networks
adaptation and learning to achieve end-to-end
performance objectives, IEEE Communications
Magazine, Dec. 2006
16
Unlicensed Wide Area Networks Using Cognitive
Radios and Available Resource Maps

• Faculty Claudio da Silva and Jeff Reed
• Funding Texas Instruments
• Description we are developing a new unlicensed
  wide area network (UWAN-ARM) based on cognitive
  radio and available resource maps that brings
  together the best attributes of licensed and
  unlicensed technologies into a new wireless
  paradigm.

17
Dynamic Spectrum Sharing

• Faculty R. M. Buehrer, J. H. Reed
• Funding ONR, ETRI
• Description We have developed a framework to
  investigate and identify desirable
  characteristics for dynamic spectrum sharing
  techniques. Desirability is with respect to
  impact on legacy system as well as capacity of SS
  network.

Read more R. Menon, R. M. Buehrer and J. H. ,
Outage probability based comparison of underlay
and overlay spectrum sharing techniques, IEEE
DySPAN 2005, pp. 101-109.
18
Application of Game Theory to the Analysis and
Design of MANETs

• Faculty J. Reed, R. Gilles, L. A. DaSilva, A. B.
  MacKenzie
• Funding ONR, NSF
• Description We are developing techniques for
  analyzing and designing MANET and cognitive radio
  algorithms in a network setting.

• More information at www.mprg.org/gametheory

19
Rapid Prototyping for SCA Development

• Faculty Cameron Patterson
• Description We are working with BAE, The
  Mathworks, and Zeligsoft to investigate a
  model-based design flow for SCA radios. Simulink
  and Component Enabler are used to build models
  that are linked with glue code and implemented in
  an SCA environment.