Collaborative Sensing to Enhance Cognitive Radio Performance

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Collaborative Sensing To Enhance Cognitive

Radio Performance .

Presented by: Sara Elboutaybi.

Graduate Student, Computer science engineering

ENSEM Casablanca.

November 30th 2011

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Introduction to cognitive radio:

- The Need Of Cognitive Radio

- What Is Cognitive Radio

Motivation:

A Global view of collaborative Sensing

-Components of Collaborative Sensing

- The Dominating Factors Of Collaborative Sensing

Conclusion

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Outline:


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The Need of Cognitive Radio:

Introduction To Cognitive Radio:

The spectrum is scarce resource.

Multiple secondary access,

aggregate interference control and

agile modulation techniques

Actual measurements indicate

Underutilized bands.

Fig.1 USA frequency allocations and

Spectrum usage measurements.
http://e/Here%20u%20go/BiblioNet/Presentation_prep/illustration/frquency_use.PNGhttp://c/Users/Illusion/Desktop/2003-allochrt.pdf


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Introduction To Cognitive Radio:

transforming radio nodes

from blind executors of

predefined protocols toradio-domain-aware

intelligent agents that

search out ways to deliver

the services that the userwants even if that user

does not know how to

obtain them

J. Mitola III and G. Q. Maguire :

Fig2. Cognitive radio cycle

Decide

ActSense

Analyse

What Is Cognitive Radio


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Enabling cognitive radio via Sensing:c


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What Is Cognitive Radio:

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Awareness of an opportunity ?

Fig.3 Multi-dimensional radio spectrum space and transmission opportunities


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Motivation:

Exploit the spatial diversity.

Multipath fading

Shadowing

Receiver uncertainty

issues

..

Improving Performance of detection

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Fig.4 Receiver uncertainty and multipath/shadow

fading.


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FCC: Cognitive devices shouldbe able to sense both

television signals and wireless

microphones down to

114 dBm.:A cognitive device with a 114 dBm

sensitivity level will identify all DTT channels as

occupied.

BT Response to Ofcom Consultation on Digital

Dividend:

SNR walls

Relaxing sensivity requirements:

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Fig.5 Cooperation allows us to reduce the sensitivity of the CR device.

Motivation:


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How cooperative CR share the data?

A Global view of collaborative Sensing:

Fig.6 Classification of cooperative sensing: (a) centralized, (b)

distributed and ( c) relay-assisted. 9


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Components Of Collaborative Sensing

How can

cognitive

radios

cooperate?

Fig.7 Framework of centralized

cooperative sensing. 10

A Global view of collaborative Sensing:


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Components Of Collaborative Sensing:

Cooperation models:

How CRs cooperate to perform

spectrum sensing?Models

Parallel FusionModel

GameTheoretical

Model

Fig. 9 Game theoretical model.

Fig. 8 Parallel fusion model.

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Sensing techniques:

A quick Compraison:

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Accuracy

Complexity

Waveform-

based Sensing

Match

Filtering

Radio Identi

-fication

Cyclostationary

Energy

Detector



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Kullback-leibler distance: Motivation

In Akaiks paper we find:

Research results using AIC.

Fig. 10 Comparison with energy detection with

noise uncertainty .



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Exploiting model selection tools through distribution comparisonto detect vacant holes in the spectrum band.

The probability distribution of

the received signal.

The probability distribution

of noise.

Estimating the kullback-leibler divergence from the sampled

signal?

Kullback-leibler distance:



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-Probability of false detection.

- Probability of missed detection.

Hypothesis Testing

Fig. 11 Receiver Operating Characteristic

curve at SNR=-15db. [ ]



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HypothesisTesting

Binary

HypothesisTesting

Composite

Hypothesis

Testing

SequentialTesting

The distributions under

both hypotheses f(y|Hi) are completely

known?

Unknown parameters in the

PDFs ?

The number of required samples

for testing :fixed or variable?

Hypothesis Testing

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Control Channel and Reporting:

A channel to report local sensing data.

A point to point link from a cooperating CR to the fusion center.

A MAC scheme for all the CRs to access the control channel.

Reporting sensing data:

Control Channel

Bandwidth

Reliability

Security

Requirements

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Data Fusion

CombiningData

SoftCombining

Quantized

SoftCombining

HardCombining

Transmit the entire local sensing

samples or the complete local test.

Quantize the local sensing results andsend only the quantized data .

Make a local decision and transmit the one-bit

decision

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(1)

(2)

(3)

Combining local sensing data for hypothesis testingwhile considering the control channel bandwidth

requirements.

(2)

(1)

(3)



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UserSelection

Centralizedselection

Cluster-based

selection

User Selection

Correlated shadowing

Selecting a set of cooperating users satisfying

some conditions.

Grouping the cooperating users into clusters or

coalitions.

Malicious users..

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Knowledge

Base

Received Signal

Strength

Primary User

Activity & StatisticsPrimary User

Localization &

Tracking

Radio Environment

Map

Channel Gain Map

Power Spectral

Density Map

Knowledge Base:

All the knowledge of the RF environments.

To assist or even replace the cooperative sensing.

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Dominating factors of collaborative sensing:

Issues

Sensing Time& Delay.

ChannelImpairments

EnergyEfficiency

CooperationEfficiency

Mobility

Security

WidebandSensingStill other issues to

deal with !

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References:

I still have to right down myreferences,

Documents

Collaborative Sensing to Enhance Cognitive Radio Performance