Cognitive Radio Technologies, 2008 1 Jeff Reed [email protected] [email protected] (540) 231 2972...
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Transcript of Cognitive Radio Technologies, 2008 1 Jeff Reed [email protected] [email protected] (540) 231 2972...
Cognitive Radio Technologies, 2008
1Cognitive RadioTechnologiesCCognitiveognitive RRadioadioTTechnologiesechnologies
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Jeff [email protected]@crtwireless.com(540) 231 2972
James [email protected](540) 230-6012www.crtwireless.com
CERDECFebruary 5, 2008
Cognitive Radio
Cognitive Radio Technologies, 2008
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Jeffrey H. Reed• Director, Wireless @ Virginia Tech• Willis G. Worcester Professor, Deputy
Director, Mobile and Portable Radio Research Group (MPRG)
• Authored book, Software Radio: A Modern Approach to Radio Engineering
• IEEE Fellow for Software Radio, Communications Signal Processing and Education
• Industry Achievement Award from the SDR Forum
• Highly published. Co-authored – 2 books, edited – 7 books.
• Previous and Ongoing CR projects from– ETRI, ONR, ARO, Tektronix
• Email: [email protected]
Cognitive Radio Technologies, 2008
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James Neel• President, Cognitive Radio Technologies,
LLC• PhD, Virginia Tech 2006• Textbook chapters on:
– Cognitive Network Analysis in – Data Converters in Software Radio: A
Modern Approach to Radio Engineering– SDR Case Studies in Software Radio: A
Modern Approach to Radio Engineering– UWB Simulation Methodologies in An
Introduction to Ultra Wideband Communication Systems
• SDR Forum Paper Awards for 2002, 2004 papers on analyzing/designing cognitive radio networks
• Email: [email protected]
Cognitive RadioTechnologiesCCognitiveognitive RRadioadioTTechnologiesechnologies
CRTCRTCRT
Cognitive Radio Technologies, 2008
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Presentation Overview
• (22) Introductory Material – Definitions, applications
• (76) Implementation Issues– Architectures, sensing, classification, decisions
• (39) Networking Issues– Problems and different approaches to mitigate those
problems
• (14) Ongoing Efforts– Commercial, University, Military
• (19) Conclusions
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What is a Cognitive Radio?
Concepts, Definitions
Cognitive Radio Technologies, 2008
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Cognitive Radio: Basic Idea• Software radios permit network or
user to control the operation of a software radio
• Cognitive radios enhance the control process by adding– Intelligent, autonomous control of the radio– An ability to sense the environment– Goal driven operation– Processes for learning about
environmental parameters– Awareness of its environment
• Signals• Channels
– Awareness of capabilities of the radio– An ability to negotiate waveforms with
other radios
Board package (RF, processors)
Board APIs
OS
Software ArchServices
Waveform Software
Co
ntr
ol
Pla
ne
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Definer
Adapts (Intelligently)
Autonom
ous
Can sense
Environm
ent
Transm
itter
Receiver
“Aw
are” Environm
ent
Goal D
riven
Learn the E
nvironment
“Aw
are” Capabilities
Negotiate W
aveforms
No interference
FCC Haykin IEEE 1900.1 IEEE USA ITU-R Mitola NTIA SDRF CRWG SDRF SIG VT CRWG
Cognitive Radio Capability Matrix
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Why So Many Definitions?• People want cognitive radio to be something
completely different– Wary of setting the hype bar too low– Cognitive radio evolves existing capabilities– Like software radio, benefit comes from the paradigm shift in
designing radios
• Focus lost on implementation– Wary of setting the hype bar too high– Cognitive is a very value-laden term in the AI community– Will the radio be conscious?
• Too much focus on applications– Core capability: radio adapts in response changing operating
conditions based on observations and/or experience – Conceptually, cognitive radio is a magic box
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OODA Loop: (continuously)• Observe outside world• Orient to infer meaning of
observations• Adjust waveform as
needed to achieve goal• Implement processes
needed to change waveform
Other processes: (as needed)
• Adjust goals (Plan)• Learn about the outside
world, needs of user,…
Urgent
Allocate ResourcesInitiate Processes
Negotiate Protocols
OrientInfer from Context
Select AlternateGoals
Plan
Normal
Immediate
LearnNew
States
Observe
OutsideWorld
Decide
Act
User Driven(Buttons)Autonomous
Infer from Radio Model
StatesGenerate “Best” Waveform
Establish Priority
Parse Stimuli
Pre-process
Cognition cycle
Conceptual Operation[Mitola_99]
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Typical Cognitive Radio Applications
What does cognitive radio enable?
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Measurements averaged over six locations:
1. Riverbend Park, Great Falls, VA,
2. Tysons Corner, VA, 3. NSF Roof, Arlington, VA, 4. New York City, NY 5. NRAO, Greenbank, WV,6. SSC Roof, Vienna, VA
~25% occupancy at peak
Modified from Figure 1 in Published August 15, 2005 M. McHenry in “NSF Spectrum Occupancy Measurements Project Summary”, Aug 15, 2005. Available online: http://www.sharedspectrum.com/?section=nsf_measurements
Bandwidth isn’t scarce, it’s underutilized
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RandomAccess
TDMAPrimary Signals
Opportunistic Signals
Conceptual example of opportunistic spectrum utilization
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• RF components are expensive• Cheaper analog implies more spurs and out-of-band
emissions• Processing is cheap and getting
cheaper • Cognitive radios will adapt
around spurs (just another interference source) or teach the radio to reduce the spurs
• Better radios results in still more available spectrum as the need arises.
• Likely able to exploit SDR
Cognitive radio permits the deployment of cheaper radios
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Improved Link Reliability• Cognitive radio is aware of
areas with a bad signal• Can learn the location of the
bad signal– Has “insight”
• Radio takes action to compensate for loss of signal– Actions available:
• Power, bandwidth, coding, channel, form an ad-hoc network
– Radio learns best course of action from situation
Good Transitional PoorSignal Quality
Can aid cellular system Inform system & other radios of identified gaps
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Automated Interoperability• Basic SDR idea
– Use a SDR as a gateway to translate between different radios
• Problems– Which devices are present?– Which links to support?– With SDR some network
administrator must answer these questions
• Basic CR idea– Let the cognitive radio observe
and learn from its environment in an automated fashion.
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Spectrum Trading• Underutilized spectrum
can be sold to support a high demand service– Currently done in Britain– Permitted in US among
public safety users• Currently has a very long
time scale (months)• Faster spectrum trading
could permit for significant increases in available bandwidth– How to recognize need and
availability of additional spectrum?
– Environment + context awareness + memory
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Collaborative Radio• A radio that leverages the
services of other radios to further its goals or the goals of the networks.
• Cognitive radio enables the collaboration process– Identify potential
collaborators– Implies observations
processes
• Classes of collaboration– Distributed processing– Distributed sensing
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Cooperative Antenna Arrays• Concept:
– Leverage other radios to effect an antenna array
• Applications:– Extended vehicular coverage– Backbone comm. for mesh
networks– Range extension with
cheaper devices
• Issues:– Timing, mobility– Coordination– Overhead
source
destination
Transmit Diversity
Cooperative MIMO
Source Cluster Relay cluster
First Hop Second Hop
Source Cluster Relay cluster
First Hop
Source Cluster Relay cluster
First Hop
Source Cluster Relay cluster
First Hop
Source Cluster Relay cluster
First Hop
Source Cluster Relay cluster
First Hop
Destination Cluster
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Other Opportunities for Collaborative Radio (1/3)
• Distributed processing– Exploit different
capabilities on different devices
• Maybe even for waveform processing
– Bring extra computational power to bear on critical problems
• Useful for most collaborative problems
• Collaborative sensing– Extend detection range by
including observations of other radios
• Hidden node mitigation
– Improve estimation statistics by incorporating more independent observations
– Immediate applicability in 802.22, likely useful in future adaptive standards
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Other Opportunities for Collaborative Radio (2/3)
• Improved localization– Application of
collaborative sensing– Security– Friend finders
• Reduced contention MACs– Collaborative
scheduling algorithms to reduce collisions
– Perhaps of most value to 802.11
• Some scheduling included in 802.11e
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Other Opportunities for Collaborative Radio (3/3)
• Distributed mapping– Gather information relevant to
specific locations from mobiles and arrange into useful maps
– Coverage maps• Collect and integrate signal
strength information from mobiles
• If holes are identified and fixed, should be a service differentiator
– Congestion maps• Density of mobiles should
correlate with traffic (as in automobile) congestion
• Customers may be willing to pay for real time traffic information
• Theft detection– Devices can learn which
other devices they tend to operate in proximity of and unexpected combinations could serve as a security flag (like flagging unexpected uses of credit cards)
– Examples:• Car components that expect
to see certain mobiles in the car
• Laptops that expect to operate with specific mobiles nearby
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Summary• Cognitive radio evolves the
software radio concept to permit intelligent autonomous adaptation of radio parameters– Significant variation in definitions
of “cognitive radio”– Question of how “cognitive” the
radio is• Numerous new applications
enabled– Opportunistic spectrum
utilization, collaborative radio, link reliability, advanced network structures
• Differing implementation approaches– Many applications
implementable with simple algorithms
– Greater flexibility achievable with a cognitive engine approach
• Many objectives will require development of a cognitive language
• In a network, adaptations of cognitive radios interact– Interaction can be mitigated with
policy, punishment, cost adjustments, centralization or potential games
• Commercial implementations starting to appear– 802.22, 802.11h,y, 802.16h– And may have been around for
a while (cordless phones with DFS)