Tauqeer Safdar
Lecturer
IT-Networking
Higher College of Technology (HCT)
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Introduction
Problem Formulation
Cognitive radio systems
Applications
Challenges
References
1
Current status: the frequency bands are statically assigned
to specific wireless operators/services
Problems: The static frequency allocation policy results in a low
utilization of the licensed frequency spectrum. For example, in most of
the time only 6% of the frequency spectrum is active [FCC/American
Foundation Broadband Forum, June 2003].
Current spectrum policy needs to be re-explored
Fixed Spectrum Assignment policy
spectrum white
spaces
Inefficient spectrum utilization
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Cognitive radio ad-hoc network (CRAHN):
◦ A new paradigm that provides the capability to
share or use the spectrum through Dynamic
Spectrum Access (DSA).
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The concept of dynamic spectrum access (DSA) has
been proposed by the Federal Communication
Committee (FCC) as a solution to the potential
spectrum scarcity and spectrum underutilizations
problems
Basic principle: secondary users can “borrow” spectrum from
primary users, but always respect primary users’ priority
Secondary Users
Zzzzzz
rights
Zzzzzz
Ideally, primary users do not perceive the existence of secondary
users
Zzzzzz
Primary Users
Hey, don’t waist
the spectrum
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To provide the user interference-aware routing so
that the end-to-end delay and packet collision can
be minimized and Average Data Rate is improved
under Dynamic Spectrum Access & Spectrum
Mobility environment of CRAHN.
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Analyze the impact of user interference on
QoS in CRAHN routing.
Implementation of channel selection through
the learning and decision mechanism on
Network layer for route calculation during
routing.
The channel information is accessed through
learning agent from MAC layer using the
spectrum mobility manager.
Minimize the end-to-end delay and user
interference in terms of packet collision.
Simulate the result using the CRCN based on
NS-2 simulator.
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Routing table
◦ the channel information such as, transmission
modulation, channel switching delay etc.
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rate,
Decision block
◦ path information and QoS performance
◦ QoS evaluation block influences the decision block by
measuring.
 how close the current performance of the routing
algorithm fares with the requirements specified by the
application layer.
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Learning Block
◦ tunes the working of the routing layer over time
◦ helps the decision block to make progressively better
channel and path switching decisions.
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CRCN simulator is a software based network
simulator for network-level simulations. [20]
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Based on open-source NS-2. [21]
Impact of transmission rate on packet delivery ratio
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Applications, Obstacles & Future Work
How is the military
planning on using
cognitive radio?
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Many of the same commercial
applications also apply to
military networks
◦ Opportunistic spectrum
utilization
◦ Improved link reliability
◦ Automated interoperability
◦ Cheaper radios
◦ Collaborative networks
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Military has much greater need
for advanced networking
techniques
◦ MANETs and infrastructure-less
networks
◦ Disruption tolerant
◦ Dynamic distribution of services
◦ Energy constrained devices
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Goal is to intelligently adapt
device, link, and network
parameters to help achieve
mission objectives
What does
cognitive radio
enable?
Cognitive Radio Technologies, 2007
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Interference avoidance
 QoS awareness
 Seamless communication
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Requires a cross layer design
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The overall end-to-end delay has been minimized
for CRAHN routing.
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Interference-Aware
routing
for
the
efficient
transmission in CRAHN is proposed in a cross layer
fashion of network architectural stack.
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Reinforcement learning is implemented on network
layer for proper interference handling by secondary
users.