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Understanding the Issues in Software Defined Cognitive Radio
Jeffrey H. ReedCharles W. BostianVirginia TechBradley Dept. of Electrical and Computer Engineering
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What You Will LearnBasic Concepts of Software Defined Radio (SDR)Basic Concepts of Cognitive Radio (CR) and its relationship to SDR.How Cognitive Radios are ImplementedAnalyzing Cognitive Radio Behavior and PerformanceRegulatory Issues in Cognitive Radio DeploymentCognitive Radio Applications in Interoperability and Spectrum AccessCurrent Research Issues
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Acknowledgements
Albrecht Johannes FehskeThomas RondeauBin LeJames NeelDavid Scaperoth
Kyouwoong KimDavid MaldonadoLizdabel MoralesYouping ZhaoJoseph Gaeddert
Students who contributed to this presentation:Software Defined Radio –Basic Concepts and Relationship to Cognitive Radio
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Software Defined Radio (SDR)
Termed coined by Mitola in 1992Radio’s physical layer behavior is primarily defined in softwareAccepts fully programmable traffic & control informationSupports broad range of frequencies, air interfaces, and application softwareChanges its initial configuration to satisfy user requirements
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Software Defined Radio Levels (1/2)
Highest Level of ReconfigurabilityCompletely flexible modulation format, protocols and user functionsFlexible bandwidths and center frequency, i.e., RF front end is also configurableAdapts to different network and air interfacesOpen architecture for expansion and modifications
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Software Defined Radio Levels (2/2)
Lowest Level of ReconfigurabilityRadio not easily changedPreset signal bandwidth and center frequencyFew and preset modulation formats, protocols, and user functions
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Advantages of SDRReduced content of expensive custom siliconReduce parts inventoryRide declining prices in computing componentsDSP can compensate for imperfections in RF components, allowing cheaper components to be usedOpen architecture allows multiple vendorsMaintainability enhanced
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Drawbacks of SDRPower consumption (at least for now)SecurityCostSoftware reliabilityKeeping up with higher data ratesFear of the unknownBoth subscriber and base units should be SDR for maximum benefit
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Applications for SDRMilitary
Full ConnectivitySensor NetworksBetter Performance
CommercialLower Cost – subscriber unitsLower Cost – base unitLower Cost – networkBetter performance
RegulatoryStretch expensive spectrumBuild in innovation mechanisms
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How is a Software Radio Different from Other Radios? - Application
SoftwareRadio
Dynamically support multiple variable systems, protocols and interfacesInterface with diverse systemsProvide a wide range of services with variable QoS
ConventionalRadio
Supports a fixed number of systemsReconfigurabilitydecided at the time of designMay support multiple services, but chosen at the time of design
CognitiveRadio
Can create new waveforms on its ownCan negotiate new interfacesAdjusts operations to meet the QoS required by the application for the signal environment
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How is a Software Radio Different from Other Radios?- Design
Software Radio
Conventional Radio +Software ArchitectureReconfigurabilityProvisions for easy upgrades
ConventionalRadio
Traditional RF DesignTraditional Baseband Design
Cognitive Radio
SDR + IntelligenceAwarenessLearning Observations
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How is a Software Radio Different from Other Radios? - Upgrade Cycle
Software Radio
Ideally software radios could be “future proof”Many different external upgrade mechanismsOver-the-Air (OTA)
Conventional Radio
Cannot be made “future proof”Typically radios are not upgradeable
Cognitive Radio
SDR upgrade mechanisms Internal upgradesCollaborative upgrades
Cognitive Radio Concepts
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Cognitive RadioTerm coined by Mitola in 1999Mitola’s definition:
Software radio that is aware of its environment and its capabilitiesAlters its physical layer behaviorCapable of following complex adaptation strategies
“A radio or system that senses, and is aware of, its operational environment and can dynamically and autonomously adjust its radio operating parameters accordingly”Learns from previous experiencesDeals with situations not planned at the initial time of design
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Adaptive radioscan adjust themselves to accommodate anticipated events
Fixed radiosare set by their operators
Cognitive radioscan sense their environment and learn how to adapt
Beyond adaptive radios, cognitive radios can handle unanticipated channels and events.
Cognitive radios require:• Sensing• Adaptation• Learning
Cognitive radios intelligently optimize their own performance in response to user requests and in conformity with FCC rules.
What is a Cognitive Radio?
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Cognitive radios are machines that sense their environment (the radio spectrum) and respond intelligently to it.
Like animals and people they
• seek their own kind (other radios with which they want to communicate)
• avoid or outwit enemies (interfering radios)
• find a place to live (usable spectrum)
• conform to the etiquette of their society (the Federal Communications Commission)
• make a living (deliver the services that their user wants)
• deal with entirely new situations and learn from experience
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1) Access to spectrum (finding an open frequency and using it)
Cognitive radios are a powerful tool for solving two major problems:
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2) Interoperability (talking to legacy radios using a variety of incompatible waveforms)
Cognitive radio platforms are a powerful tool for solving two major problems:
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Levels of Radio Functionality
Proposes and Negotiates New ProtocolsAdapts Protocols8Generates New GoalsAdapts Plans7
Autonomously Determines Structure of EnvironmentLearns Environment6
Settle on a Plan with Another RadioConducts Negotiations5
Analyze Situation (Level 2& 3) to Determine Goals (QoS, power), Follows Prescribed PlansCapable of Planning4
Knowledge of Radio and Network Components, Environment ModelsRadio Aware3
Knowledge of What the User is Trying to DoContext Awareness2
Chooses Waveform According to Goal. Requires Environment Awareness.Goal Driven1
A software radioPre-programmed0CommentsCapabilityLevel
Adapted From Table 4-1Mitola, “Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio,” PhD Dissertation Royal Institute of Technology, Sweden, May 2000.
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What is a cognitive radio?
An enhancement on the traditional software radioconcept wherein the radio is aware of its environment and its capabilities, is able to independently alter its physical layer behavior, and is capable of following complex adaptation strategies.
Adapted From Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications ”, IEEE Mobile Multimedia Conference, 1999, pp 3-10.
Urgent
Allocate ResourcesInitiate Processes
Negotiate Protocols
OrientInfer from Context
Select AlternateGoals
Plan
Normal
Immediate
LearnNew
StatesObserve
OutsideWorld
Decide
Act
User Driven(Buttons)Autonomous
Infer from Radio Model
StatesGenerate “Best”Waveform
Establish Priority
Parse Stimuli
Pre-process
Cognitive radio Cognition Cycle
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NormalUrgent
Level0 SDR1 Goal Driven2 Context Aware3 Radio Aware4 Planning5 Negotiating6 Learns Environment7 Adapts Plans8 Adapts Protocols
Allocate ResourcesInitiate Processes
OrientInfer from Context
Parse StimuliPre-process
Select AlternateGoals
Establish Priority
PlanNormal
Negotiate
Immediate
LearnNewStates
Negotiate Protocols
Generate AlternateGoals
Adapted From Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications ”, IEEE Mobile Multimedia Conference, 1999, pp 3-10.
Observe
OutsideWorld
Decide
Act
User Driven(Buttons) Autonomous Determine “Best”
Plan
Infer from Radio Model
States
Determine “Best”Known WaveformGenerate “Best”Waveform
Relationship between the Cognition Cycle and the Levels of Functionality
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FCC Motivation for Cognitive Radio
Currently the FCC is refarming licensed bands such as the TV BandsLong-term vision
Eliminate rigid, coarse spectrum allocationsSwitch to demand-based approach
Improve relative spectral efficiency
Need new protocols forSupporting long-term vision of the FCCInter-network interference avoidanceMaximizing utilization of available bandwidth
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Cognitive Radio AdvantagesAll of the benefits of software defined radioImproved link performance
Adapt away from bad channelsIncrease data rate on good channels
Improved spectrum utilizationFill in unused spectrumMove away from over occupied spectrum
New 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
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Cognitive Radio Drawbacks
All the software radio drawbacksSignificant research to realize
Information collection and modelingDecision processesLearning processesHardware support
Regulatory concernsLoss of controlFear of undesirable adaptations
Need some way to ensure that adaptations yield desirable networks
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Cognitive Radio & SDRSDR’s impact on the wireless world is difficult to predict
“But what…is it good for?”Engineer at the Advanced Computing Systems Division of IBM, 1968, commenting on the microchip
Some believe SDR is not necessary for cognitive radioCognition is a function of higher-layer application
Cognitive radio without SDR is limitedUnderlying radio should be highly adaptive
Wide QoS rangeBetter suited to deal with new standards
Resistance to obsolescenceBetter suited for cross-layer optimization
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Types of Software Defined Cognitive Radios
Policy-Based RadioReconfigurable RadioCognitive Radio
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Policy-based RadioA radio that is governed by a predetermined set of rules for choosing between different predefined waveformsThe definition and implementation of these rules can be:
during the manufacturing processduring configuration of a device by the user; during over-the-air provisioning; and/or by over-the-air control
Analogous to rules of what to order from a menu“I’ll have GSM today”
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Reconfigurable Radio
A radio whose hardware functionality can be changed under software controlReconfiguration control of such radios may involve any element of the communication networkAnalogous to rules of what to order from a menu and permit substitutions to the order
“I’ll have GSM today with the 802.11 FEC”
Technology Challenges in SDR
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Radio Architecture
RxTx
RF Signal Amplify
MixerFilter
AmplifyMixerFilter
IF Signal
Baseband Signal
Superhetrodyne
RF Signal Amplify
MixerFilter
AnalogTo DigitalConverter
IF Signal Digital
Signal Processing
Software Defined Radio
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Behind the Converters: The Software ArchitectureNature of Architecture Depends on Applications: Commercial vs. MilitaryBenefits of a Good Architecture
Clear way to implement systemReuse --- modularityQuality control and testingPortability – one radio to anotherUpgradabilityOutsourcing/managing developmentLanguage independenceMore potential for Over-the-Air ProgrammingStandardized interfaces
Middleware-based architectures are commonly used
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Implementing a SDR with the GNU Radio
USRP - Universal SoftwareRadio Peripheral
GNU Radio software- core s/w- user made s/w
Courtesy:http://www.gnu.org/software/gnuradio/doc/exploring-gnuradio.html
GNU Radio S/W available at www.gnuradio.org
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USRP 4 ADC’s: •12bits per second, 64MSps, •Analog Input BW over 200Mhz
4 DAC’s•14bits per second, 128MSps
Receive Channel RF Interface
Transmit Channel RF Interface
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Challenges in SDR DesignHardware
Significant effort in computing HWAdvance DSP DesignsFlexible RF and antennas Flexible ADCsTradeoff of performance and flexibility
SoftwareIntegration of components into single design flowTradeoff of performance and flexibility
Testing and validationFCC hardware/software certificationSmoothing of design cycle
Reduce overall time-to-market
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Technology Challenges of SDRTechnology in SDR partitioned into three basic pieces
HardwarePhysical devices on which processing is performed or interface to the “real world”
SoftwareGlue holding together system
NetworkFunctionality and ultimate value to the end-user
Advances needed in all three arenas
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HardwareSignificant effort to date in computing HW
Non-traditional computing platformsAdvanced DSP designsHigh data rate FEC remains problematic
Emphasis on computing HW alone can be myopic
Other critical areas that require significant further work
Flexible (or software controlled) RFFlexible ADCAntennas
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Flexible RFRF is one of the main limiting factors on system design
Places fundamental limits on the signal characteristics
BW, SNR, linearityTruly flexible SDR requires flexible RF
Difficult taskRF is fundamentally analog and requires different a different approach for the management of attributes
One method for achieving this is through the use of MEMS
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MEMS (Micro Electro Mechanical Systems) Designs for RF Front Ends
Tunable antenna with narrow fixed bandwidthPatch antenna connected by RF switches
E-tenna’s Reconfigurable Antenna
Idealized MEMs RF Front-end for a Software Radio
Use MEMS filter banks to create tunable RF filters
J.H. Reed, Software Radio: A Modern Approach to Radio Design, Prentice-Hall 2002. 40
ADC ChallengesADC is the bound between analog and digital worldSDR requires the tuning of ADC characteristics
Number of bitsSupport adequate SNR and dynamic range
Sampling ratePrevent over-sampling (waste power)
ADC technology trends are not necessarily compatible with these needs
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2BsP f= ⋅
B bitsfs sample rate
ADCs Getting Better Exponentially
Bin Le, Tom Rondeau, Jeff Reed, Charles Bostian, “Past, Present, and Future of ADCs,”IEEE Signal Processing Magazine, November 2005
1994 ~ 2004 a leap of Analog to Digital Converter (ADC) technologyRegression curve fit shows exponential increasing trendsTrends are quite different for different ADC structures
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ADC: Improving Even When Considering Power
2Bs
diss
fFP⋅
=
Power-to-sampling-speed ratio favors less number of comparatorsThe choice in selecting an ADC is tied to application requirement
Pdiss is power dissipation
Bin Le, Tom Rondeau, Jeff Reed, Charles Bostian, “Past, Present, and Future of ADCs,”IEEE Signal Processing Magazine, to be published, November, 2005
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Integration of Hardware
DSP share traits with GPPSimilar programming methodsSimilar computing concepts
Even though implementation may be wildly different
FPGA and CCM do not share these traits with GPP
Completely different programming paradigmPortability is an extremely difficult problem
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Software Operating EnvironmentStandardized structure for the management of HW and SW components
SCATechnology to date has been largely derived from existing PC paradigm
GPP-centric structureSCA 3.0 Hardware Supplement is an attempt to rectify this problem
Several challenges remainPower managementIntegration of HW into structure
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Software Architectures“The sheer ease with which we can produce a superficial image often leads to creative disaster.” Ansel Adams [1902-1984], American artist (photography)
Poor architectural design leads to significant inefficienciesArchitectures provide multiple benefits
Clear way to implement systemGenerally component-based
Software or hardware componentsStandardized interfaces
Standard technology interfaceCommon technology like middleware
Standard semantic -- APIArchitectures becoming more prominent
Software Communications Architecture (SCA)$14B to $27B for SCA radio work by DoDCluster 5 contract up to $1B for embedded & handheld prototypesMaintain awareness of activity: big money for SDR
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So How Do You Make a Software Radio?
You have some hardware
And you want to run some waveformsGSM, IS-95, or some other technology that the hardware is powerful enough to support
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What kind of software is needed? (1/4)
Something to manage hardwareConfigure associated devices
Set devices to known statei.e.: Make sure NCO is available and ready
Initialize coresMake sure programmable devices are ready
Set memory pointers in DSPSet FPGA to known state
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What kind of software is needed? (2/4)
Some standardized way of storing relevant information
More than just short-term memoryStore configuration filesStore last state of the machineStore user-defined attributes
IdentityPermissions
Store functional softwareShould be able to map any kind of storage device to this
Dynamic RAM, hard drive, FLASH, other
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What kind of software is needed? (3/4)
Some way of structuring the waveformsStandardized way of structuring “applications”so that the radio can “run” them
In a Windows machine, these are .exe filesIt has to be generic enough for it to fit well with machines other than GPPs
Needs to be able to interface with functional software
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What kind of software is needed? (4/4)
Something to actually “run” waveformsInstall functional software in appropriate coreGenerate a start event
Something to keep track of what is available and what can and cannot be installed
Ideally, this will bind the whole thing together
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Fundamental Composition of the SCAKeep track of HW in the system
Store working environment, bit images, properties, etc.
Boot up and maintain HW
Keep track of what’s there (installed)
Manage collection of resources to create waveform
Capabilities e.g.,Start and stop, test, describe
Connections between resources
Device Manager
FileSystem Manager
Devices
Domain Manager
Application Factory
Resources
Manage waveform operationApplication
Port
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Software Communications Architecture (SCA)
Processor-centric structure
Standardized interface for components
Seamless handling of HW and SW
Open-source implementations available
OSSIEC++ by MPRG
SCARIJava by Communications Research Centre
OS
CORBA
IDL
RedBlack
ManagementObjects
FileSystem
ConfigurationFiles
Software
HardwareHardware
Software
API
API
APIAPINon-CORBASoftware(Legacy)
CORBAAdapter
Non-CORBASoftware(Legacy)
CORBAAdapter
API
Trans.Security
SecurityBoundary
Non-secure Secure
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Is the SCA Suitable for Commercial Implementations?
MaybeNo
Current version is GPP-centric, hence heavyIrrelevant capabilities decrease its effectivenessFocus on waveform portability has limited appealStatic nature not well suited for cognitive radioNo provisions for power management
YesBasic architectural principles are soundSCA 3.0 is a first step in dealing with GPP-centric communications within the radioSignificant momentum ($$$ and time) within defense industryBeing adopted by several other nations’ defense establishments
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Summary of TrendsSDR need is driven by two principal factors
New applicationsCognitive radio, collaborative radio & advanced roaming
Increased number of protocols to supportPotential cost reductions
ADC is no longer the key bottleneckFlexible RF products starting to come to marketSoftware architecture critical
Additional technology supporting architectural approach availableReconfigurable hardware needed
General-purpose hardware approach is likely to be unable to keep up with wireless bandwidth growthComponent-based reconfigurable hardware architectures present powerful solutionMulti-core processors show promise
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SDR Market TodayMilitary
JTRS program created multi-billion dollar SDR marketDARPA neXt Generation (XG) Communications projectInternational derivatives of JTRS/SCA (EU, Canada, etc)
CommercialDigital RF processors (TI Bluetooth and GSM)Multi-standard base station implementations (Vanu)SDR handsets probably within 3 years as low power processors become available
RegulatoryRecent FCC directive to ensure code and RF compatibility
Cognitive Radio Implementation
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Radio Parameters“Knobs and Meters”
The VT Cognitive Engine
Simple Concept
Channel Statistics
Cognitive Engine
Radio RXRadio TX
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Radio TX
The VT Cognitive Engine
Simple Concept
Channel Statistics
Cognitive Engine
Radio RX
“Meters” “Old KnobsSettings”
“Old KnobsSettings”
Radio Parameters“Knobs and Meters”
“Optimized Solution”“New Settings” “New Settings”
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Knobs and Meters
CPU Frequency scalingComputational powerBattery Life
Other
Transmitter powerSpreading type and codeModulation typeModulation indexPulse shapingSymbol rateCarrier frequencyDynamic rangeEqualizationAntenna directivity
Bit error rateSINRReceived signal powerNoise powerInterference powerPower consumptionFading statisticsDoppler spreadDelay spreadAngle of Arrival
PHY
Source codingChannel coding rate and typeFrame size and typeInterleaving detailsChannel/slot/code allocationDuplexingMultiple accessEncryption
Frame error rateData rate
MAC
Knobs(writable parameters)
Meters(observable parameters)
Layer
Sample tabulation of knobs and meters by layer (adapted from Prof. Huseyin Arslan) 60
The VT Tiered Approach to CognitionModeling System
Take in surrounding radio environment and user/network requirements
Remember models and apply Case-based Decision Theory to determine best course of action to take
Use Genetic Algorithms to update and optimize the new radio parameters
Monitor feedback from radio to understand system performance
Penalize knowledge base for poor performance
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The Cognitive Engine“Intelligent agent” that manages cognition tasks in a Cognitive RadioIndependent entity that oversees cognitive operationsIdeal Characteristics:
Intelligence (Accurate decisions)Reliability (Consistent decisions)Awareness (Informed decisions)Adaptability (Situation dependent decisions)Efficiency (Low overhead decisions)Excellent QoS (Good decisions)
Tradeoffs exist between these characteristics62
Software Architecture - Theory
Radio Hardware
Awareness
Sensing and Modeling
AdaptingEvolution and Optimization
Learning
Building and retaining
Knowledge
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Software Architecture - Theory
EnvironmentObservationLink condition
User/policy
Radio hardware
ScenarioSynthesizing Case identified
Case-basedDecisionMaking
Case reportKnowledge Base
Reasoning
Apply experienceStrategy instruction
Link ConfigureOptimization
WSGAInitializationObjectivesConstraints
PerformanceEstimation
Bad trail overwrittenSuccess memorized
Radio Hardware
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Software Architecture – Limited Functionality
CE-Radio Interface
WMS
Security
Sele
ctor
API
Cognitive System Module
Cognitive System Controller
wavfrm
Policy
Sec
Knowledge BaseShort Term MemoryLong Term Memory
Decision Maker
CE
-use
r int
erfa
ce
Policy DomainUser preference
Local service facility
SecurityUser data security
System/Network security
Modeling System
Policy Model
Radio
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Software Architecture: Full Functionality
CE-Radio Interface
WMS
Security
Evolver
API
Resource Monitor
|(Simulated Meters) – (Actual Meters)|Simulated Meters
Actual Meters
Radio
Cognitive System Module
Cognitive System Controller
Chob
Uob
Reg
Knowledge BaseShort Term MemoryLong Term Memory
WSGA Parameter SetRegulatory Information
Initial ChromosomesWSGA Parameters
Objectives and weights
System Chromosome
}max{}max{
UUU
CHCHCH
USDUSD
•=•=
Decision Maker
User DomainUser preference
Local service facility
Policy DomainUser preference
Local service facility
SecurityUser data security
System/Network security
X86/UnixTerminal
Modeling System
User Model
Policy Model
RadioChannel Probe
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Some Approaches to Cognitive Engine
Genetic AlgorithmsMarkov ModelsNeural NetsExpert Systems Natural Language ProcessingFuzzy Logic
Open issue on what are the appropriate cognitive engine techniques
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GA’s and biological metaphor
The WSGA uses a genetic algorithm, which operates on chromosomes.
The genes of the chromosome represent the traits of the radio (frequency, modulation, bandwidth, coding, etc.).
The WSGA creatively analyzes the information from the CSM to create a new radio chromosome.
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Some Approaches to Signal Classification
Cyclic spectrum analysisStatistical characterization of signal parametersEigenstructure techniquesModel-based approachesVector space (I-Q plane) approaches
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Analyzing Performance in a Cognitive Radio
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Analyzing the Performance of a Network of Cognitive Radios
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Ways of Analyzing Performance
For the Cognitive RadioQOS, Detection of Primary Users (PU), SW Platform, QOS of PU, Position Location
For the network of Cognitive RadiosQuantifying the impact of the use of CR in a networkGame Theoretic Approach
See www.mprg.org/gametheory
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Cognitive Radio Performance Evaluation: QoS
ParametersData throughputLatencyVoice qualityVideo quality
These depend on link performance measures:
PHY Layer, e.g.:Bit error rate (BER)Signal to noise ratio (SIR)Signal to interference and noise ratio (SINR)Received signal strength
MAC, network-layer, e.g.:Frame error rate (FER)Packet error rateRouting table change rate
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Cognitive Radio Performance Evaluation: Detection of Primary Users
Probability of detection (PoD) as a function of:Number of observed symbolsSNRNumber of signals present (primary and secondary)Level of cooperation, e.g., number of devices (CRs) needed to achieve a given PoD (see next slide)
Probability of false alarmSame parameters as PoD
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Cognitive Radio Performance Evaluation: Underlying Software Radio Platform
Number of supported waveformsProcessing power (mips, flops, #gates)Waveform-code reusability and portability
Reusable: the same code can be used in principle in a different SDR platformPortable: instantaneous plug and play
Delay for loading unloading waveforms RF front-end:
Frequency range, Dynamic range, Sampling frequency, Sensitivity, Selectivity, Stability, Spurious response
Power consumptionSize, Weight, Cost
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Cognitive Radio Performance Evaluation: Position Location
Main performance measures for position location service:Precision and Availability
Different technologies provide different quality of position location services:
Assisted GPS (AGPS)performance degrades significantly when no clear view of sky (indoors, urban canyons)works best in rural areas (no shadowing)
Network based servicesaccuracy in general lower than AGPSworks best with many base stations present (populated areas)performance doesn't degrade indoors
Hybrid servicescombines advantages of both approachesAGPS whenever possible, if not available switch to network based service
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Cognitive Radio Performance Evaluation: Primary users' QoS
Time needed to vacate channel after primary user (re-) appearsNegative impacts:
Decreased SINR and Increased BER, FER, … results in:Decreased:
Data throughputLatencyVoice qualityVideo quality
IncreasedCall drop rate (cell phone networks)Handover failure (cell phone networks)
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Dynamic cognitive radios in a network
Dynamic benefitsImproved spectrum utilizationImprove QoS
Many decisions may have to be localized
Distributed behaviorAdaptations of one radio can impact adaptations of others
Interactive decisionsLocally optimal decisions may be globally undesirable
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Locally optimal decisions that lead to globally undesirable networksScenario: Distributed SINR maximizing power control in a single clusterFor each link, it is desirable to increase transmit power in response to increased interferenceSteady state of network is all nodes transmitting atmaximum power
Power
SINR
Need way to analyze networks with interactive decisions.Game theory can help.
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What is a game?A game is a model (mathematical representation) of an interactive decision process.Its purpose is to create a formal framework that captures the process’s relevant information in such a way that is suitable for analysis.Different situations indicate the use of different game models.Identification of the type of game played by the cognitive radios provides insights into performance
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1. Steady state characterization
2. Steady state optimality3. Convergence4. Stability5. Scalability a1
a2
NE1
NE2
NE3
a1
a2
NE1
NE2
NE3
a1
a2
NE1
NE2
NE3
a1
a2
NE1
NE2
NE3
a3
Steady State CharacterizationIs it possible to predict behavior in the system?How many different outcomes are possible?
OptimalityAre these outcomes desirable?Do these outcomes maximize the system target parameters?
ConvergenceHow do initial conditions impact the system steady state?What processes will lead to steady state conditions?How long does it take to reach the steady state?
StabilityHow does system variations impact the system?Do the steady states change?Is convergence affected?
ScalabilityAs the number of devices increases, How is the system impacted?Do previously optimal steady states remain optimal?
Key Issues in Implementation
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Cognitive Radio, Spectrum Policy, and Regulation
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An Analogy between a Cognitive Radio and a Car Driver
Cognitive Radio’s capabilities:Senses, and is aware of, its operational environment and its capabilitiesCan dynamically and autonomously adjust its radio operating parameters accordingly Learns from previous experiencesDeals with situations not planned at the initial time of design
Car Driver’s capabilities:Senses, and is aware of, its operational environment and its capabilitiesCan dynamically and autonomously adjust the driving operation accordinglyLearns from previous experiencesDeals with situations not planned at the initial time of learning to drive
They behave almost exactly
the same!!!
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“Rules of the Road” ➟“Rules of the Cognitive Radio”POLICY AWAREPrimary User has higher priority over Secondary users
Radio emission may be prohibited at certain location or for certain type of radio
LOCATION AWAREPrecautions for certain areas, such as hospital, airplane, gas station, etc, where RF emission is highly restricted
Parking Zone
*Source of some pictures in this section: “California Drivers Handbook 2005”; “Illinois Rules of the Road 2004”84
“Rules of the Road”-inspired CR Philosophy and EtiquetteInsights from “Traffic Model Analogy”
TRAFFIC Scheduling
Various traffic schedule methods and duplex methods for efficient and fair sharing of congested unlicensed spectrum
TDD vs. FDD ➟
Dynamic Uplink/Downlink transmission in TDD mode
Spectrum pooling is encouraged
Traffic Law ➟ Spectrum Regulations
Management by both Punishment and Encouragement
FDD mode operation with paired spectrum
$ fine
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A traffic model analogy – Common IssuesIt is critical that everyone drives sensibly or defensively
➟ Every CR should be aware of Hidden Node problems
Hidden Node Problem
A and C are unaware of their interference at B. Due to A, C and B cannot hear each other.
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Vehicle Following Distances: TWO-SECOND RULE:Use the two-second rule to determine a safe following distance.
Vehicle Following Distances for Car Drivers
➟ Time needed to vacate channel after primary user (re-) appears for Cognitive Radios
A traffic model analogy (cont.)
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A traffic model analogy (cont.)
SPEED LIMIT for car driver
➟ Interference Level Limit (e.g. Max. Allowed Interference Temperature)
for Cognitive Radio
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City Map for Car Drivers
➟ Radio Environment Map (REM) for Cognitive Radios
Learning from “Traffic model analogy”for the development of Cognitive Radio…
REMREM
Max. allowed Interference Level
Profile of primary users Profile of interference
Location (x, y, z), Type of radio environmentLocal Policy
Time (or duration)
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Learning from “Traffic model analogy” for the development of Cognitive Radio…(cont.)
Regular conformance check against
regulations
Language and Etiquette for CR for
Signaling and Negotiation
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Spectrum Policy ChallengesThe spectrum is already allocated
True spectrum scarcity on urban areas (ISM band)We need to deal with existing standardsThe standards are embedded in the hardware!
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Spectrum UtilizationSpectrum utilization is quite low in many bandsConcept:
Have radios (or networks) identify spectrum opportunities at run-timeTransparently (to legacy systems) fill in the gaps (time, frequency, space)
Considered BandsISMPublic SafetyTV (UHF)
Lichtenau (Germany), September 2001
dBµV
/m
From F. Jondral, “SPECTRUM POOLING - An Efficient Strategy for Radio Resource Sharing,” Blacksburg (VA), June 8, 2004.
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Spectrum Occupancy Study
Spectrum occupancy in each band averaged over six locations
(Riverbend Park, Great Falls, VA, Tysons Corner, VA, NSF Roof,
Arlington, VA, New York City, NRAO, Greenbank, WV,
SSC Roof, Vienna, VA)
Source: FCC NPRM 03-0322. http://hraunfoss.fcc.gov/edocs_public/attachmatch/FCC-03-322A1.pdf
Results from Shared Spectrum Co. and Univ. of Kansas
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Regulatory TrendsIn an effort to improve radio spectrum management and promote its more efficient use, the regulatory bodies are trying to adopt a new spectrum access model.This represents a paradigm shift from hardware-embedded policy implementation to dynamic software-based adaptation
Harder to keep tight control!
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Regulatory TrendsProceedings that are the Key Drivers:
Receiver StandardsET Docket No. 03-65 NOI
Interference Temperature ET Docket 03-237 NPRM/NOI
Cognitive RadioET Docket No. 03-108 NPRM
License-exempt Operation in the TV Broadcast BandsET Docket No. 04-186
Additional Spectrum for License-exempt devices below 900 MHz and in the 3 GHz Band
ET Docket No. 02-380
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Policy Engine ApproachPE needs to provide limiting operational parameters
Interpret policy automaticallyAct dynamically in response to the operating environment
PE needs to authenticate the policyIt will require an extremely efficient policy format
It must handle the complexity of current policy without presenting a significant load to the CE
The goal is to limit the search space before looking for a solution
Rely on CE to do the reasoning about spectrum sharing
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DARPA XG ProgramXG is trying to Develop the Technology and System Concepts to Dynamically Access Available Spectrum
ReactFormulate Best
Course of Action
ReactReactFormulate Best Formulate Best
Course of ActionCourse of Action
AdaptTransition
network to new emission plan
AdaptAdaptTransition Transition
network to new network to new emission plan emission plan
CharacterizeRapid waveform
determination
CharacterizeCharacterizeRapid waveform Rapid waveform
determinationdetermination
SenseReal time, Low-
power, wideband monitoring
SenseSenseReal time, LowReal time, Low--
power, wideband power, wideband monitoringmonitoring
AutonomousAutonomousDynamic Dynamic SpectrumSpectrumUtilizationUtilization
Source: DARPA XG Program
Goal: Demonstrate Factor of 10 Increase in Spectrum Access
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XG Program Aspects
The Primary Product XG Program is The Primary Product XG Program is Not a New Radio, but a , but a Set of Advanced Technologies for Dynamic Spectrum Accessfor Dynamic Spectrum Access
XG P
rodu
cts
XG P
rodu
cts
Temporal, Spectral, Temporal, Spectral, Dimensional, Energy Dimensional, Energy
CharacteristicsCharacteristics
Military & Civil Military & Civil Communications and Communications and Sensor ApplicationsSensor Applications
Transition to Transition to Military Use Military Use
MeasurementsMeasurementsMeasurements Policy-Based ControlsPolicyPolicy--Based ControlsBased Controls
XG BehaviorsXG BehaviorsXG Behaviors
Initial XG ImplementationInitial XG ImplementationInitial XG Implementation
Control of Features, Control of Features, Priorities, Allocations, Priorities, Allocations, Exclusions,…Exclusions,…
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The BIG Question: FCC Certification
At all costs, the FCC must avoid “an epidemic situation in the unlicensed area.”
FCC likes to operate from “established engineering practices.” The SDR and CR communities must defined these.
Open source radios are a particular problem because their operating parameters are not necessarily bounded.
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People seeking certification must explain how their software will respect parameter limits specified in FCC rules.
Submitted software must be accompanied by flow charts, code, and an explanation of how it works.
Software certification should not be more difficult to achieve than hardware certification.
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Bios/OS
Proposed Approach
Policy EnginePolicy Engine
Cognitive EngineCognitive Engine
ApplicationsApplications
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Example of a Possible Cognitive Radio Application
102
How can CR improve spectrum utilization?
Allocate the frequency usage in a network.Assist secondary markets with frequency use, implemented by mutual agreements.Negotiate frequency use between users.Provide automated frequency coordination.Enable unlicensed users when spectrum not in use.Overcome incompatibilities among existing communication services.
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How can CR improve network management efficiency?
Present practice characterizes service demand in a network statisticallyBy using cognitive radio, time-space characterization of demand is possibleCognitive Radio
Learns plans of the user to move and use wireless resourcesExpresses its plans to the network reducing uncertainty about future demand
The network can use its resources more efficiently
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How can a CR enhance service delivery?
Wireless communications in general and cognitive radio in particular have great potential to generate personal user information
For example: actual position, native language, habits, travel, etc.
Enhanced services can be provided using this informationCR interacts with the network on user’s behalf
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Note Daily Drive Home at 5:30(GPS Aided)Recall Brief Coverage Hole
1. Observe and Analyze Situation
2. Evaluate AlternativesDo NothingIncrease Coding GainIncrease Transmit PowerVertical HandoffDecrease Call Drop Threshold
4. Adapt Network
3. Signal Base StationRequest Decrease In Call Drop Threshold
CR in a Cellular System
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Example of Cognitive Radio in Cellular Environment
Cognitive radio is aware of areas with a bad signalCan learn the location of the bad signal
Has “insight”Radio takes action to compensate for loss of signal
Actions available:Power, bandwidth, coding, channel
Radio learns best course of action from situation
Good signal
Transition in signal
Bad signal
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Supplements Cellular SystemCellular systems are plagued with coverage gapsCognitive radio can enhance coverage around these gaps by:
Learning the areas of coverage gapsLearning the best PHY layer parameters Taking action prior to getting to the areaSharing this knowledge with other cell phones
Coverage gaps are found very rapidly
Alert cellular system of gap, so provider can remedy situation
Current Research Efforts in Cognitive Radio
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Universities Participating at DySPAN
Bar-Ilang Univ.Georgia TechMich. State Univ.Michigan TechMITNorthwestern Univ.Ohio Univ.Rutgers Univ.RWTH Aachen Univ.Stanford Univ.
Univ. of Calif. BerkeleyUniv. of CambridgeUniv. of Col.Univ. of MDUniv. of PittsburgUniv. of TorontoUniv. of WarwickUniversitaet KarlsruheUniversity of PiraeusVirginia Tech
DARPA
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DARPA neXt Generation Program: Motivation - Problems
Spectrum ScarcitySpectral resources are not fully exploitedOpportunities exist in space, time, frequencyCurrent static spectrum allocation prevents efficient spectrum utilization
Deployment difficultyDifferent policy regimes in different countriesDeployment of communication networks tediousOf particular interest in military applications
Unless otherwise stated, all the information in this description of the DARPA XG programis based on the XG Vision rfc, available online: http://www.darpa.mil/ato/programs/xg/ 112
DARPA neXt Generation Program: Research Goals1. Development of technologies that enable
spectrum agilitySensing and characterization of the (RF-) environmentIdentification of unused spectrum ("opportunities")Allocation and exploitation of opportunities
2. Development of standards for a software based policy regime to enable policy agility
Explained in more detail on the next slides
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DARPA neXt Generation Program: Concepts of Policy Agility (1)1. Decoupling of policies from implementation
Define abstract behaviors, e.g., "Channel can be vacated within t sec."Policies implement (dictate) behaviorsProtocols instantiate behaviors
2. TraceabilityAll behaviors must be traceable to policies:
Each operational mode a device is capable of is tied to a specific policy which allows it
3. Software basedSpectrum use policies have to be machine understandablePolicy constraints can be implemented "on-the-fly" via software downloads
114Transceiver
SystemStrategy
Reasoner
XG Operation
SelectOpportunities
PolicyReasoner
DevelopOptions Process
Request
Determine
Opportunities
Yes/No or Additional
Constraints
AccreditedPolicy
RF Info Acquisition
Sensing Loop
Policy Engine
RadioPlatform
Mes
sage
Flow
RF ResourceRequest
RF Transmit Plan
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115
DARPA neXt Generation Program: Concepts of Policy Agility
Machine understandable policies will enable software downloads "on-the-fly"
Figure drawn from XG Vision RFC116
XG AccomplishmentsCollected And Analyzed RF Environment For Many Scenarios
Used As Basis For Phase 2 Design EvaluationsDeveloped Low-Volume, High-Performance Sensor
Provides Needed Capability For Rapid Wideband SensingNext Phase To Explore Integration With JTRS C-1
Policy Language And Radio Interface DefinedPolicy Language RFC V1 Composed And ReleasedExtensible To Future “Cognitive” Technology
Three Feasible Designs For Interference Avoidance, Network Operation, And Rendezvous
Demonstrated Feasibility And Performance Of Adaptive Spectrum TechnologiesIn Midst Of Phase 3 Source SelectionWill Select At Least One Design For 2-year Prototype Development And Demonstration Effort
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XG Sensor
XG Sensor Focuses on Capabilities and Features Needed for JTRS C-1 Transition
Significantly smaller footprint (more than 3X volume reduction)
RF card is 2X2 inchesContinuous frequency coverage 30 MHz – 2.5 GHz (vs. 6 bands)
Only 1 filter for 30 MHz – 1 GHzLow power devices reduced power to 1 W average
XG Sensor Performance Necessary for XG Implementation Which Is Not Yet Available for Military Communications
XG Sensor Performance Necessary for XG Implementation Which Is XG Sensor Performance Necessary for XG Implementation Which Is Not Yet Available for Military CommunicationsNot Yet Available for Military Communications
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XG – Phase 2 Significant Findings
All Signals are Not Created EqualUnderstanding of Temporal Characteristics Is NecessaryNeed to Detect Below Noise FloorInterference Avoidance Policies Specific to Detected Signal
Degree of A Priori Knowledge of Signals Provides Significant Performance Enhancement
Difference in Detecting Known vs. Unknown Signals in Noise Affects How Aggressively XG Can Access SpectrumAllocation Tables Provide A Priori Knowledge of Expected Signal Types, Especially Fixed and Broadcast
Policy Reasoning Necessary for Range of Incumbent Signal ProtectionCommercial Services Are Sensitive to Effects of Interference at Many Levels, Including Reception Quality, BER, and Increase in Transmitter PowerMilitary Signals Are Inherently Hardened and Tolerant of InterferenceAgile Systems Can Even Move If Interference Occurs
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Phase 3 Development and Demonstration ActivitiesBuild XG Technologies in Prototype Radio
Integrate The Radio, Adaptation Algorithms, Sensor Components, Policy-based Controls, And Radio Software into SCA Traceable Prototype
Continue Developing Key Policy Control TechnologiesConduct Early Incremental Field Demos
Build Confidence in XG Capabilities Though A Series of DemosIncrease capability and environmental complexity at each demo
Implement Networks Of Spectrum-agile Radios Which Dynamically Adapt To Changing Spectrum Environments10x More Spectrum Without Interference To Non-XG RadiosDemonstrate And Validate The XG Prototype’s Capabilities In Representative Military And Urban RF Environments.
Transition to Military Program of Record In FY07
E2R
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E2R Research in Europe
E2R = End-to-End ReconfigurabilityEfficient, advanced & flexible end-user service provision
Tailoring of application and service provision to user preferences and profile
Efficient spectrum, radio and equipment resources utilization
Enabling technologies for flexible spectrum resources Multi-standard platforms
A single hardware platform shared dynamically amongst multiple applications
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E2R Participants 1/2Academic Partners
Eurecom: Institut EurecomI2RKCL:Centre for Telecommunications Research (CTR) - King's College LondonUoA: University of AthensTUD: Dresden UniversityUoKarlsruhe: University of Karlsruhe, Communications Engineering LabUPRC: University of Piraeus Research CenterUNIS: University of Surrey
Operator R&D PartnersDoCoMo: DoCoMo Communications Laboratories Europe GmbHFT: France Telecom R&DTILAB: Telecom Italia S.p.A.TID: Telefonica I+D
Source http://e2r.motlabs.com/
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E2R Participants 2/2Manufacturer Partners
MOTO: Motorola LabsACP: Advanced Circuit Pursuit AGASEL: Alcatel SELDICE: Danube Integrated Circuit EngineeringNokia: Nokia GmbHPMDL: Panasonic UKPEL: Panasonic European Laboratories GmbHSM: Siemens GermanySMC: Siemens Mobile Communications SpATHC: Thales CommunicationsTRL: Toshiba Research Europe LimitedMIL: Motorola Israel Ltd
Regulator partnersDiGITIPUPC: UPCRegTP
Berkeley Wireless Research Center
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Berkeley Wireless Research Center• Designing a cognitive radio to improve spectrum utilization• Radio searches for feasible region and optimal waveform for transmission
(environment sensing)• Avoiding of Interference with primary spectrum users by:
-Measuring spectrum usage in time, frequency, and space-Having statistical traffic models of primary spetrum users
• A cognitive radio test bed is currently being built
•From R.W. Brodersen, A. Wolisz, D. Cabric, S. M. Mishra, D. Willkomm "Corvus: A Cognitive Radio Aproach For Usage of Virtual Unlicensed Spectrum", July 29th 2004
• The six system functions are split between physical and data link layer
• Two control channels:- UCC for group management (group announcement)
- GCC used only by members of a certain group
Rutgers Winlab
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WINLAB Rutgers University
• Design of info-stations for emergency and disaster relief applications
• Use of customized commercially available hardware, e.g. 802.11 wireless
From: http://www.winlab.rutgers.edu/pub/docs/focus/Infostations.html
BenefitsIncreases the total information
available for rescue workersTailors the information with regard
to specific needs and available bandwidthCoordinates communication of
different rescue groups at one site
Virginia Tech’s CWT
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National Science Foundation Grant CNS-0519959 “An Enabling Technology for Wireless Networks – the VT Cognitive Engine”
National Institute of Justice Grant 2005-IJ-CX-K017 “A Prototype Public Safety Cognitive Radio for Universal Interoperability.”
Develop and test a prototype system for using cognitive techniques to allow WiFi-like unlicensed operation in unoccupied TV channels.
Investigate the behavior of networks containing both legacy radios and cognitive radios that can interoperate with them.
Build a prototype cognitive radio that can recognize and interoperate with three commonly used and mutually incompatible public safety waveform standards
Virginia Tech’s MPRG
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Some SDR and Cognitive Radio Research at VT
SCA core framework Open source effortRole of DSPsPower ManagementIntegration of testing into the frameworkRapid prototyping tools
Smart antennasSmart antenna API Networking performance Experimental MIMO systems
Cooperative radios Distributed MIMODistributed Applications
Cognitive radio networks Game theory analysis of cognitive networksLearning Techniques
Test Beds UWB SDRLow Power SCADistributed PCsPublic Safety Radio Demo
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CR Test-bed under development
AP (Data Collection Node)
AP (Data Collection Node)
AP (Data Collection Node)
InterferenceDetection,
Classification,Location
OSSIE Framework
ArbitraryWaveformGenerator
AP (Data Collection Node)
AP (Data Collection Node)
AP (Data Collection Node)
InterferenceDetection,
Classification,Location
OSSIE Framework
ArbitraryWaveformGenerator
NeighborWLANs
Ethernet
Actions
Cordless Phone Bluetooth
MWOL
Tektronix TDS694C:Digital Real-time Oscilloscope
Tektronix RSA3408A: Real-Time Spectrum Analyzer
Distributed MeasurementDistributed Measurement
Collaborative ProcessingCollaborative ProcessingObservations
Analysis and decision
REM online updating
TV station
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The Future of Cognitive Radio
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Public Safety - Interoperability
Focus on multi-agency interoperability since 9/11/2001Cognitive radio technology can improve interoperability by enabling devices to bridge communications between jurisdictions using different frequencies and modulation formats. Such interoperability is crucial to enabling public safety agencies to do their jobs.Example: National Public Safety Telecommunications Council (NPSTC) supported by U.S. DOJ’s AGILE Program
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IEEE 802.22
WRAN system based on 802.22 will make use of unused TV broadcast channelsInteroperable air interface for use in spectrum allocated to TV Broadcast ServiceAllows Point to Multi-point Wireless Regional Area Networks (WRANS)Supports a wide range of services
Data, voice and videoResidential, small and medium enterprisesSmall office/home office (SOHO) locations
136
IEEE Project 1900 (P1900)The IEEE P1900 Standards Group was established in The IEEE P1900 Standards Group was established in 1Q 2005 jointly by the IEEE 1Q 2005 jointly by the IEEE Communications Communications SocietySociety ((ComSocComSoc) and the IEEE ) and the IEEE Electromagnetic Electromagnetic Compatibility (EMC) Society.Compatibility (EMC) Society.The objective of this effort is to develop supporting The objective of this effort is to develop supporting standards related to new technologies and techniques standards related to new technologies and techniques being developed for next generation radio and being developed for next generation radio and advanced spectrum management.advanced spectrum management.
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IEEE P1900.1 Working GroupIEEE P1900.1 Working Group::Objective document:Objective document: ““Standard Terms, Standard Terms, Definitions and Concepts for Spectrum Definitions and Concepts for Spectrum Management, Policy Defined Radio, Adaptive Management, Policy Defined Radio, Adaptive Radio and Software Defined Radio.Radio and Software Defined Radio.””Purpose:Purpose: This document will facilitate the This document will facilitate the development of these technologies by development of these technologies by clarifying the terminology and how these clarifying the terminology and how these technologies relate to each other.technologies relate to each other.
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IEEE P1900.2 Working GroupIEEE P1900.2 Working Group::Objective document:Objective document: ““Recommended Recommended Practice for the Analysis of InPractice for the Analysis of In--Band and Band and Adjacent Band Interference and Coexistence Adjacent Band Interference and Coexistence Between Radio Systems.Between Radio Systems.””
Purpose:Purpose: TThis standard will provide his standard will provide guidance for the analysis of coexistence and guidance for the analysis of coexistence and interference between various radio services. interference between various radio services.
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IEEE P1900.3 Working GroupIEEE P1900.3 Working Group::Objective document:Objective document: ““Recommended Practice Recommended Practice for Conformance Evaluation of Software for Conformance Evaluation of Software Defined Radio (SDR) Software Modules.Defined Radio (SDR) Software Modules.””Purpose:Purpose: This recommended practice will This recommended practice will provide guidance for validity analysis of provide guidance for validity analysis of proposed SDR terminal software prior to proposed SDR terminal software prior to physical programming and activation of SDR physical programming and activation of SDR terminal components. terminal components.
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IEEE 802.11h802.11h helps WLANs share spectrumHow?
801.11h implements two methods to help spectrum sharing:
Dynamic Frequency Selection (DFS)Transmission Power Control (TPC)
DFS is used to select the appropriate spectrum for WLANTPC is used to manage WLAN networks and stations for reduction of interference, range control (setting borders for WLAN), and reduction of power consumption (e.g., beneficial in laptop use).
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IEEE 802.15.3a
Multiband OFDM for Personal Area NetworkWireless USB2.0 (480Mbps) at 5 meters distances
Cognitive Radio - Plausible Application to UWB Regulation
Very fast spectrum sculpting via OFDM technology with wide bandwidth 528MHz
QoS SupportQoS can be supported by controlling the number of sub-carriers
142
Hurdles in CRFCC Development Policies
The process and rules governing how frequencies and waveforms are selected and approved for use by cognitive equipment must be addressed.
Software FlexibilityInterface with policy updates
Real-life FunctionalityCR devices are smart enough to understand user request and surrounding environments
Network Availability for CRNetwork needs to announce their availability to CR
Flexible or Reconfigurable HardwareRequires a language and protocols for initial interfacing with software and validation for existing devices as policies change across time and spaceSoftware Architectures
More dynamic than SCA
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Predictions for Future Evolution
Time
SDR with high ASIC content
Re-programmable
for fixed number of systems
Factory reprogrammable
Increased use of
reconfigurable hardware
Limited reconfiguration
by userEarly cognition
Mid-level cognition
Cognitive radios
2005 2007 2010
Adaptive spectrum allocation
144
Just Remember This...
“The best way to predict the future is to invent it.”
Alan Kay, Author
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Jeffrey H. ReedWillis G. Worcester Professor of ECE and Deputy Director, Mobile and Portable Radio Research Group (MPRG)Authored book, Software Radio: A Modern Approach to Radio EngineeringIEEE Fellow for Software Radio, Communications Signal Processing and EducationIndustry Achievement Award from the SDR ForumHighly published. Co-authored – 2 books, edited – 7 books.Previous and Ongoing SDR projects from
DARPA, Texas Instruments, ONR, Mercury, Samsung, NSF, General Dynamics and Tektronix
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Jeffrey H. Reed
Contact Information:[email protected] and Computer EngineeringMPRG432 Durham HallBlacksburg, VA 24061(540) 231-2972
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Charles W. BostianAlumni Distinguished Professor of ECE and Director, Center for Wireless TelecommunicationsCo-author of John Wiley texts Solid State Radio Engineering and Satellite Communications.IEEE Fellow for contributions to and leadership in the understanding of satellite path radio wave propagation.Award winning teacherPrevious and Ongoing CR projects from National Science Foundation, National Institute of Justice
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Charles W. Bostian
Contact Information:[email protected] and Computer EngineeringVirginia Tech, Mail Code 0111 Blacksburg, VA 24061(540) 231-5096
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Backup Slides
150
Hardware Blocks
Software Modules
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Example: Simple AM Transmitter (1/2)Building Blocks
•All Blocks are each defined as objects
X
~Amp
m
FIR
“Amp” - Gain Stage
“m” - Message Signal
“mix” - Multiplication Stage
“LO” - Local Oscillator
“FIR” - Filter Stage
152
Example: Simple AM Transmitter (2/2)
Connecting Building Blocks
+ 1Amp µX
~
FIR mH/WInterface
•The arrow is an object that connects the flow graph
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Example SDR: GNU Radio
What is GNU Radio?GNU Radio is a set of S/W signal processing building blocks that allow users to create their own S/W radio
Why GNU Radio?Attempts to solve the complexity issues of both H/W and S/W of SDRModular (use with most any GPP)
S/W used on Windows, Linux, Mac
154
Multi-Objective OptimizationMultiple knobs are adjusted to tune multiple metersComplex problem to satisfy objectives like:
Bit error rateData rateBandwidthLatencyPowerBattery lifeMany more
Requires advanced algorithms for optimization and learning.Evolutionary Algorithms offer significant benefits for this problem
Stochastic search strategiesFlexible and powerful
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Spectrum Policy Language Design
SpectrumPolicy
PolicyAdministrator
(e.g. FCC, NTIA)
XG System
SpectrumOpportunities
Awareness via XG Protocols and Sensing
query
LanguageDesign
Knowledge
Core LanguageModel and
Representation
Policy LanguageDesigner
(e.g. BBN/XG Program)
Policy Editingand Verification
Tools
design
MachineReadable
Policy Instances
PolicyRepository
encode
publish
Actors and RolesActors and Roles
Source: BBN Technologies Solutions LLC
PolicyRepository
Area that needs Area that needs improvements!improvements!
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DARPA neXt Generation Program: Motivation – Proposed Solution
Complement static spectrum allocation with "Opportunistic spectrum access"
Primary usersLicensedPriority to use allocated spectrumGuaranteed QoS
Secondary usersNon-licensedCan allocate unused spectrum among themselvesHave to vacate bands if required by primaries
Unless otherwise stated, all the information in this description of the DARPA XG programis based on the XG Vision rfc, available online: http://www.darpa.mil/ato/programs/xg/
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DARPA neXt Generation Program: Concepts of Policy Agility (2)
Figure drawn from XG Vision RFC
Decoupling policies, behaviors, and protocols: Separating what needs to be done from how it is implemented
The framework's four key components158
DARPA neXt Generation Program: Promises1. Flexible radio operation due to spectrum agility2. Simplified user control of XG systems
System operation can be controlled in terms of behaviorNo need for technological details
3. Facilitated policy designConstraints can be tailored to national or institutional needs in terms of behaviorsNo need for technological details
4. Eased wireless device accreditationTraceability provides a means for an easy testing procedure of behaviors against policies
5. Broad and future proof standardWill be designed to be applicable to a broad range of radios Future proof design will enable extension of the standardFramework character: different technological solutions (protocols) can be accomodated to perform a particular task (sensing, identification, allocation)
