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

mailto:[email protected]



http://www.crtwireless.com/


2

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]


3

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

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4

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


5

What is a Cognitive Radio?

Concepts, Definitions


6

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


7

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


8

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


9

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]


10

Typical Cognitive Radio Applications

What does cognitive radio enable?


11

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


12

RandomAccess

TDMAPrimary Signals

Opportunistic Signals

Conceptual example of opportunistic spectrum utilization


13

• 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


14

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


15

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.


16

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


17

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


18

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


First Hop


First Hop


First Hop


First Hop


First Hop

Destination Cluster


19

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


20


• 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


21


• 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


22

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)

cognitive radio technologies, 2008 1 jeff reed [email protected] [email protected] (540) 231 2972...

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