spectrum sensing and allocation techniques for cognitive radios

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Farrukh Javed F-05-020/07-UET - PHD-CASE-CP-40 Spectrum Sensing and Allocation Techniques for Cognitive Radios

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Spectrum Sensing and Allocation Techniques for Cognitive Radios. Farrukh Javed F-05-020/07-UET - PHD-CASE-CP-40. Sequence of Presentation. Section I – Cognitive Radios Introduction Next generation networks Cognitive radios Section II – Spectrum Sensing Transmitter detection - PowerPoint PPT Presentation

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Page 1: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Farrukh JavedF-05-020/07-UET - PHD-CASE-CP-40

Spectrum Sensing and Allocation Techniques for Cognitive Radios

Page 2: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Sequence of PresentationSection I – Cognitive Radios

IntroductionNext generation networksCognitive radios

Section II – Spectrum SensingTransmitter detectionCooperative detectionInterference based detectionSpectrum sensing challenges

Section III – Spectrum AllocationSpectrum analysisSpectrum decision

Section IV – Future of Cognitive RadiosConclusion

Page 3: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Cognitive Radios

Section – I

Page 4: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Motivation for Cognitive Radios

Spectrum Scarcity [1]

Farrukh Javed
-Spectrum is managed by FSA(Fixed Spectrum Access) techniques-Extensive utilisation has resulted in spectrum scarcity
Page 5: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Motivation for Cognitive Radios

Spectrum Utilisation [1]COGNITIVE RADIOS

Farrukh Javed
-The scarcity leads us to consider a re-consideration of spectrum allocation techniques-The FSA mgmt is convinient but resulted in under utilised spectrum-Some bands very congested and most not-Avg usage between 15 to 85 %
Page 6: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Motivation for Cognitive Radios

Measured Spectrum Occupancy Averaged over Six Locations

0.0% 25.0% 50.0% 75.0% 100.0%

PLM, Amateur, others: 30-54 MHzTV 2-6, RC: 54-88 MHz

Air traffic Control, Aero Nav: 108-138 MHzFixed Mobile, Amateur, others:138-174 MHz

TV 7-13: 174-216 MHzMaritime Mobile, Amateur, others: 216-225 MHz

Fixed Mobile, Aero, others: 225-406 MHzAmateur, Fixed, Mobile, Radiolocation, 406-470 MHz

TV 14-20: 470-512 MHzTV 21-36: 512-608 MHzTV 37-51: 608-698 MHzTV 52-69: 698-806 MHz

Cell phone and SMR: 806-902 MHzUnlicensed: 902-928 MHz

Paging, SMS, Fixed, BX Aux, and FMS: 928-906 MHzIFF, TACAN, GPS, others: 960-1240 MHz

Amateur: 1240-1300 MHzAero Radar, Military: 1300-1400 MHz

Space/Satellite, Fixed Mobile, Telemetry: 1400-1525 MHzMobile Satellite, GPS, Meteorologicial: 1525-1710 MHz

Fixed, Fixed Mobile: 1710-1850 MHzPCS, Asyn, Iso: 1850-1990 MHz

TV Aux: 1990-2110 MHzCommon Carriers, Private, MDS: 2110-2200 MHz

Space Operation, Fixed: 2200-2300 MHzAmateur, WCS, DARS: 2300-2360 MHz

Telemetry: 2360-2390 MHzU-PCS, ISM (Unlicensed): 2390-2500 MHz

ITFS, MMDS: 2500-2686 MHzSurveillance Radar: 2686-2900 MHz

Spectrum Occupancy

Spectrum Concentration [2] COGNITIVE RADIOS

Farrukh Javed
-Jean Piere Hubaux-Goes on to comment that 100 billion Euoros are spent to buy spectrum for 3rd Generation
Page 7: Spectrum Sensing and Allocation Techniques for Cognitive Radios

CognitionOxford English Dictionary definition of “cognition” as

“The action or faculty of knowing taken in its widest sense, including sensation, perception, conception, etc., as

distinguished from feeling and volition”Encyclopedia Encarta defines “cognition” as

“To acquire knowledge by use of reasoning, intuition or perception”

Encyclopedia of computer Sciences gives a three point computational view of “cognition” as

“1. Mental state and processes intervene between input stimuli and output responses

2. The mental state and processes are described by algorithms3. The mental states and processes lend themselves to

scientific investigations”

Page 8: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Cognitive Radio Joseph Mitola introduced the idea of Cognitive Radio in 2000 as

“Situation in which wireless nodes and related networks are sufficiently computationally intelligent about radio resources and related computer to computer communication to detect the user communication needs as a function of user context

and to provide the resources most required”Simon Haykin explains the concept in six key words

AwarenessIntelligentLearningAdaptabilityReliabilityEfficiency

An intelligent radio capable of adapting itself to best suit its surrounding radio environment

Farrukh Javed
-The CR utilises the flexibility of an SDR supplemented by the knowledge of prevailing radio environment through a sensing system. The transceiver should be able to sence the dictates of its prevailing spectrum conditions and change its transmission parameters accordingly
Page 9: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Operating Principal of CROverlay CRs utilise the concept of spectrum

holesUnderlay CRs use the concept of

interference temperature

Page 10: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Overlay Cognitive Radios

Frequency

Pow

er

Time

COGNITIVE RADIOS

Page 11: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Interference temperature TI is specified in Kelvin and is defined as

where PI (fc , B) is the average interference power in Watts centered at fc, covering bandwidth B measured in Hertz.

Boltzmann's constant k is 1.38 x 10-23

Any Un-licensed transmission must not violate the interference temperature limit at the licensed receivers. Mi is a fractional value between 0 and 1, representing a multiplicative attenuation due to fading and path loss between the unlicensed transmitter and the licensed receiver.

The TL is to be decided by regulatory authority such as FCC or PTA

Interference temperature model

Page 12: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Underlay Cognitive Radios

Interference Temperature Model [10]

SPECTRUM SENSING

Page 13: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Interference Temperature LevelInterference temperature is the maximum

RF interference acceptable at a receiving antenna

Page 14: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Basic Characteristics of Cognitive RadiosCognitive CapabilityRe-configurability

COGNITIVE RADIOS

Page 15: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Cognitive CapabilityCognitive CycleSpectrum SensingSpectrum Allocation

Spectrum AnalysisSpectrum Decision

Cognitive cycle [3]

Page 16: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Re - ConfigurabilityOperating FrequencyModulation SchemeTransmission PowerCommunication TechnologyDirectivity of Transmission

Page 17: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Next Generation NetworksIntroductionProtocol Layers and Cognitive Radio

Functionalities

xG Network Functionalities [3]COGNITIVE RADIOS

Farrukh Javed
-Explain the DSA or XG networks as hetrogenous networks which use cognitive radio as nodal pts-Works in parallel to primary networks and other xG-Aim is Optimum utilisation of spectrum -One network as suggested by Akyldiz is shown
Page 18: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum Sensing

Section – II

Page 19: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum Sensing Techniques

Spectrum Sensing

Transmitter DetectionMa

tched

Filter Detection

Energy Detection

Cyclo-

stationary Feature

Detection

Cooperative Detection

Interference Based

Detection

SPECTRUM SENSING

Page 20: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Transmitter DetectionIntroduction

TechniquesMatched Filter DetectionEnergy DetectionCyclo – Stationary Feature Detection

SPECTRUM SENSING

Page 21: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Matched Filter DetectionIntroductionOpportunities

Commonly UsedHigh Processing Gain

ChallengesMatched Filter BoundA priori knowledge of transmission is required

Tran

sm

itter D

ete

ctio

n

SPECTRUM SENSING

Page 22: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Energy DetectionIntroductionOpportunities

Easy implementationMulti path and fading channel studies carried

outChallenges

Critical selection of thresholdSusceptible to noise power variationsCommunication type identification not

possibleReduced flexibility

Tran

sm

itter D

ete

ctio

n

SPECTRUM SENSING

Page 23: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Cyclo – Stationary Feature DetectionIntroductionOpportunities

Robust against un-certain noise powersTransmitter information is not requiredNeural network application has been found

very feasibleChallenges

Computationally complexTransmission type identification is not

possibleReduced flexibility

Tran

sm

itter D

ete

ctio

n

SPECTRUM SENSING

Page 24: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Transmitter Detection Un – Certainties Receiver Un-certaintyShadowing Un-certainty

Tran

sm

itter D

ete

ctio

n

(a) Receiver Uncertainty (b) Shadowing Uncertainty [3]

SPECTRUM SENSING

Page 25: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Cooperative DetectionIntroduction

Centralised DetectionDistributed Detection

Cooperative Detection OpportunitiesNo receiver or shadowing un-certaintiesEffects of degrading factors mitigatedPrimary User’ interference reduced

Cooperative Detection ChallengesImplementation ComplexityConstrained ResourcesPrimary user un-certainty un-resolved

SPECTRUM SENSING

Page 26: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Interference Based Detection

Interference Temperature Model [10]

SPECTRUM SENSING

Page 27: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Opportunities and Challenges of Interference Based Detection Opportunities

Focus on primary receiver rather than primary transmitter

Frequency parameters of choice can be utilised

ChallengeReceiver temperature detectionDue to interference power constraints, the

underlay techniques can only be employed for short range communications

SPECTRUM SENSING

Page 28: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Few GeneralisedSpectrum Sensing ChallengesMulti user environmentInterference temperature measurementSpeed of detection etc.

SPECTRUM SENSING

Page 29: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum Allocation

Section – III

Page 30: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum Allocation

SPECTRUM ALLOCATION

Page 31: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum AnalysisChannel capacityPrimary user related informationxG user information

SPECTRUM ALLOCATION

Page 32: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Channel CapacityPath LossWireless Link LayerLink Layer DelayNoise Info

Sp

ectru

m A

naly

sis

Page 33: Spectrum Sensing and Allocation Techniques for Cognitive Radios

User Related Information(Primary and xG Users)InterferenceHolding TimeUser Transmission Parameters

Sp

ectru

m A

naly

sis

Page 34: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum Analysis Challenges and OpportunitiesChallenges

Heterogeneous Spectrum Sensing Non Cooperative Primary and xG usersVarying Transmission ParametersReal Time AnalysisDelays in Processing

Opportunities

Sp

ectru

m A

naly

sis

Page 35: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum DecisionSpectrum managementSpectrum mobility Spectrum sharingUser related info

SPECTRUM ALLOCATION

Page 36: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum ManagementDecision ModelMultiple Spectrum decisionReduced Transmission PowerCooperation with reconfigurationHeterogeneous Spectrum

SPECTRUM ALLOCATION

Page 37: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum MobilityIntroductionChallenges

LatencySuitable AlgorithmAppearance of a Primary UserVertical and Inter-Cell Handoff SchemeSuitable Threshold for HandoffSpectrum Mobility in Time DomainSpectrum Mobility in Space

OpportunitiesPrioritised White SpaceSoft and Hard Handoff

SPECTRUM ALLOCATION

Page 38: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Spectrum SharingArchitecture Based Classification

Centralised or DistributedChallenges and Opportunities

Access Behaviour ClassificationCooperative and Non-cooperative SharingChallenges and Opportunities

Access Technology ClassificationOverlay and Underlay TechniquesChallenges and Opportunities

Generalised Spectrum Sharing ChallengesCommon control ChannelDynamic radio rangeSpectrum Unit

SPECTRUM ALLOCATION

Page 39: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Future of Cognitive Radios

Section IV

Page 40: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Cognitive Radio AdvantagesAll of the benefits of software defined radioImproved link performanceAdapt away from bad channelsIncrease data rate on good channelsImproved spectrum utilizationFill in unused spectrumMove away from over occupied spectrumNew business propositionsHigh speed internet in rural areasHigh data rate application networks (e.g., Video-

conferencing)Significant interest from FCC, DoDPossible use in TV band refarming

Page 41: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Cognitive Radio DrawbacksAll the software radio drawbacksSignificant research to realizeInformation collection and modelingDecision processesLearning processesHardware supportRegulatory concernsLoss of controlFear of undesirable adaptationsNeed some way to ensure that adaptations

yield desirable networks

Page 42: Spectrum Sensing and Allocation Techniques for Cognitive Radios

How can CR improve spectrum utilization?Allocate the frequency usage in a networkAssist secondary markets with frequency

use, implemented by mutual agreementsNegotiate frequency use between usersProvide automated frequency coordinationEnable unlicensed users when spectrum

not in useOvercome incompatibilities among existing

communication services

Page 43: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Potential Applications of CRLeased networksMilitary usageEmergency situationsMesh networksLicensed user may enhance its

performanceImproving UWB transmission by avoiding

NBI

Page 44: Spectrum Sensing and Allocation Techniques for Cognitive Radios

Jeffery H Reed and Wills G Worcester

Page 45: Spectrum Sensing and Allocation Techniques for Cognitive Radios

ConclusionSpectrum Sensing and Allocation Techniques for Cognitive Radios