Cognitive Radio Evolution from Agile Platforms to Omniscient Networks: the Road from Dreams to Prototypes

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Cognitive Radio Evolution from Agile Platforms to
Omniscient Networks the Road from Dreams to
Prototypes
Charles W. Bostian Virginia Tech bostian_at_vt.edu
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Acknowledgements
This project is supported by Award No.
2005-IJ-CX-K017 awarded by the National Institute
of Justice, Office of Justice Programs, US
Department of Justice. The opinions, findings,
and conclusions or recommendations expressed in
this publication/program/exhibition are those of
the author(s) and do not necessarily reflect the
views of the Department of Justice.
This material is based upon work supported by the
National Science Foundation under Grant No.
CNS-0519959. Any opinions, findings and
conclusions or recommendations expressed in this
material are those of the author(s) and do not
necessarily reflect the views of the National
Science Foundation (NSF).
Defense Advanced Research Projects
Agency Strategic Technology Office DARPA Order
AF89-00
This work is also supported by Air Force
Institute of Technology (AFIT). The views
expressed in this article are those of the author
and do not reflect the official policy or
position of the Air Force, Department of Defense
or the U.S. Government.
The views and conclusions contained in this
document are those of the authors and should not
be interpreted as representing the official
policies, either expressed or implied, of the
Defense Advanced Research Projects Agency or the
U.S. Government.
Center for Wireless Telecommunicationswww.cogniti
veradio.wireless.vt.edu
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Acknowledgment The VT Team
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An (old) radio guys vision of cognitive radio A
universal transceiver (all modes and all
frequencies) capable of discovering radios like
itself and working cooperatively to negotiate
frequencies, waveforms, and protocols to optimize
performance subject to user needs based on the
radios awareness of its environment and its past
experience.
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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.

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In developing this prototype, we have solved some
hard problems in rapid reconfiguration of a radio
platform and in signal recognition and
synchronization.
Find a signal of interest
Configure this in real time and operate it.
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Cognitive Engine SDR Cognitive Radio
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The relatively easier part realization of the
cognitive engine
General Implementations
A restricted implementation the VT Public Safety
Cognitive Radio
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FCC Worries Code correctness, insecure memory
accesses, tamper resistance. Off-line unit
testing and formal verification plus
light-weight yet effective anti-tampering methods
to ensure that any module replacement is
compliant. Ensures that any replacement of the
modules, including over-the-air updates is done
by trusted parties.
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The harder part building a universal radio
platform
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(No Transcript)
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The GPP Problem Latency and Inability to
Control Timing
OK for narrowband waveforms with simple timing
requirements. A real problem for wideband
waveforms and MACs requiring precise timing.
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The solution that we are developing now A hybrid
architecture containing fixed and reconfigurable
subsystems.

• Embedded GPP performs cognitive functions and
  determines radio configuration
• Reconfigurable FPGA and ASICs perform PHY and MAC
  layer operations
• Accelerators implement application layer functions

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System Overview of PSCR (hybrid implementation)?
FPGA
ADC/DAC
DSP
GPP
Analog RF
VTSDCSS
Spectrum Sweeper
Signal Classifier
Waveform Recognition
RF front-end
PGA
ADC
DDC
GUI Center Controller
Waveform Knowledge Base
Case-based Waveform Solution Maker
RX
Filter
Gain
Demod
RF front-end
PGA
ADC
DDC
configure
FEC Decoder
De-packet
Binary Data
MAC Layer Protocol
MAC Carrier Sense Algorithm
Packet
Binary Source
TX
FEC Encoder
RF front-end
PGA
DUC
Filter
Gain
Mod
DAC
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My student Ying Wang will demonstrate some of our
current spectrum, waveform identification, and
radio configuration technology as part of this
meeting. She and my student Qinqin Chen invented
the system we will demonstrate and many others in
our group contributed to the implementation.
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What is wrong with this picture?

• One radio platform cant do it all.
• Focuses on interactions of two nodes.
• Ignores network issues.
• Ignores applications that the radio will run.

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• The reality
• Multiple networks
• Multiple protocols
• Multiple applications
• Dynamic Spectrum Access

All this leads to the concept of an application
and network driven integrated architecture for a
cognitive node
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Architecture for An Application and Network
Driven Integrated Cognitive Node
Conceived by my student Feng Andrew Ge to capture
the overall cognitive radio efforts of our group.
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An important part of the implementation The
Universal Cognitive Gateway, dissertation topic
of my student Qinqin Chen
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Another application dissertation work of my
student Mark Silvius
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Dynamic Cellular Cognitive Radio (Ying Wang)
Basic Concept
700M Hz Application Scenario
Software Structure
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Contact Information Charles W. Bostian Alumni
Distinguished Prof. Virginia Tech bostian_at_vt.edu 5
40-231-5096 http//www.cognitiveradio.wireless.vt.
edu