Cognitive Engine Development for IEEE 802.22

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Cognitive Engine Development for IEEE 802.22

• Lizdabel Morales
• April 16th, 2007
• lizdabel_at_vt.edu

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Presentation Outline

• Introduction
• IEEE 802.22
• Cognitive Radio
• CE Development Approach
• Simulation and Results
• Future Work

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What is a cognitive radio?
Cognitive radio
Cognition cycle

• An enhancement on the traditional software radio
  concept wherein the radio is aware of its
  environment and its capabilities, is able to
  independently alter its physical layer behavior,
  and is capable of following complex adaptation
  strategies.

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Cognitive Radio is a promising tool for

• Access to spectrum
• finding an open frequency and using it
• Interoperability
• talking to legacy radios using a variety of
  incompatible waveforms

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Motivation for using cognition in IEEE 802.22
Systems

• Using previous experience to predict
• Channel reputation
• Incumbent detection
• Other patterns
• Protect incumbent users by being aware of the
  environment
• Co-existence and self co-existence
• Spectrum utilization improvements
• Future proofing for other CR technologies

It is not known whether a CR network can offer
satisfactory performance despite the injection of
many new incumbent handling mechanisms
Cordeiro, et. al. 2005
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MPRGs Development of an IEEE 802.22 Cognitive
Engine

• Objective was to create a Cognitive Engine for
  IEEE 802.22 systems
• Phases I and II completed
• Main Accomplishments
• Development of a solid and generic architecture
  for the IEEE 802.22 CE
• Development of a flexible framework that allows
  for future design, development and testing of
  more sophisticated modules

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WRAN Considered Scenario

• System Description
• Single WRAN BS
• CPEs with different application requests
• Incumbent users TV only and Part 74 devices
• Events that trigger change in the system
• New CPE service request in the WRAN
• Incumbent detected in TV channel

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Cognitive Engine Architecture
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Cognitive Engine Modules

• Sensing Module provides radio environment
  sensing results
• REM provides a snapshot of the radio scenario
  through time
• Main Controller decides which algorithm to use
• Case and Knowledge Reasoner provides coarse
  solution, starting point for the Multi-objective
  Optimizer
• Multi-objective Optimizer further refines the
  solution obtained by the CBR

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Utility function Performance metrics

• Utility function used in CE should reflect the
  performance metrics of cognitive WRAN systems,
  and weight of each performance metrics may vary
  with radio scenarios
• U1 QoS satisfaction of each (uplink and
  downlink) connection for adding new CPE
  connections
• U2 Incumbent PU protection (fast adaptation and
  evacuation) more important for relocating CPEs
  in case PU reappears
• U3 Spectral efficiency more important for
  multi-cell or large number of CPEs
• U4 Power efficiency and interference
  temperature reduction more important for mobile
  UE and large-scale cognitive networks

U w1U1 w2U2 w3U3 w4U4
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Testing scenarios for WRAN BS CE Performance
evaluation
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REM-CKL vs. GA
CKL runs much faster than GA, especially under
complicated situations.
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802.22 Specification
Current framework picks up after incumbent user
is detected
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Questions