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Cognitive Radio Research in the U.S.: Overview, Challengesand Directions
ARIB Frequency Resource Development Symposium, June 8, 2007
Narayan B. MandayamProfessor of ECE & Associate Director, WINLAB
Rutgers University
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Cognitive Radio Research A Multidimensional Activity
Spectrum PolicyEconomicsRegulationLegalBusiness
Theory and AlgorithmsFundamental LimitsInformation & Coding TheoryCooperative CommunicationsGame Theory & Microeconomics
Hardware/Software Platforms & Prototyping
Programmable agile radiosGNU platforms
Several Universities E.g. WINLAB-Rutgers, UC Berkeley, Virginia Tech, etc.
Govt Agencies E.g. FCC, DARPA, NSF, etc.
Industry – small and bigE.g. Blossom, Shared Spectrum, Vanu, Intel, Alcatel-Lucent, Philips, Qualcomm and a very many more
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How it all started -The Spectrum Debate & Cognitive Radio
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The Spectrum Debate Triumph of Technology vs. Triumph of Economics
Open Access (Commons)[Noam, Benkler, Shepard, Reed …]
Triumph of TechnologyAgile wideband radios will dynamically share a commonsSuccess of 802.11 vs 3G
Spectrum Property Rights[Coase, Hazlett, Faulhaber+Farber]
Triumph of EconomicsOwners can buy/sell/trade spectrumFlexible use, flexible technology, flexible divisibility, transferabilityA spectrum market will (by the force of economics) yield an efficient solution
What everyone agreed on (a few years ago):Spectrum use is inefficientFCC licensing has yielded false scarcity
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Source: FCC website
Spectrum Management: In fairness to the FCC, Frequency allocation is complex…
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Maximum Amplitudes
Frequency (MHz)
Am
plid
ue (d
Bm
)
Heavy Use
Sparse Use
Heavy Use
Medium Use
Less than 6% OccupancyLess than 6% Occupancy
FCC measurement shows that occupancy of approximately 700 MHz ofspectrum below 1 GHz is less than 6~10%~ 13% spectrum opportunities utilized in New York City during 2004 Political Convention to nominate U.S. Presidential Candidate
Spectrum Management: Then again, poor utilization in most bands
Atlanta
NewOrleans
SanDiego
Frequency
Time
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Arguments against Triumph of TechnologyPartially developed theory
Information theoretic relay channelInformation theoretic interference channelAd hoc network capacity, with/without mobility
Technology PanaceaSpread spectrum, UWB, MIMO, OFDMShort range communicationsAd hoc multi-hop mesh networks
Infant technologyUWB, MIMO antenna arraysTransmitter agility
Technology not separable from user assumptionsCapabilities of technology vary with cooperation
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Recent Research DevelopmentsResearch themes that have emerged from mobile ad hoc and/or
sensor networks research:Hierarchical Network Architecture wins
Capacity scaling, energy efficiency, increases lifetimes, facilitates discovery
Cooperation winsAchievable rates via information theoretic relay and broadcast channels
“Global” awareness and coordination winsSpace, time and frequency awareness and coordination beyond local measurements
Efficient operation requires radios that can:CooperateCollaborateDiscoverSelf-Organize into hierarchical networks
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The Spectrum Debate and Cognitive Radio
What everyone agrees on now:Spectrum use is inefficientFCC licensing has yielded false scarcity
Possible middle ground?Dynamic spectrum accessShort-term property rightsSpectrum use driven by both technology and market forces
Cognitive Radios with ability to incorporate market forces?Microeconomics based approaches to spectrum sharingPricing and negotiation based strategies
(e.g. Ileri & Mandayam, “Dynamic Spectrum Access Models- Towards an Engineering Perspective in the Spectrum Debate” in IEEE Communications Magazine January 2008)
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Dynamic Spectrum Management & Cognitive Radio
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Static allocation of spectrum is inefficientSlow, expensive process that cannot keep up with technology
Spectrum allocation rules that encourage innovation & efficiency
Free markets for spectrum, more unlicensed bands, new services, etc.Anecdotal evidence of WLAN spectrum congestion
Unlicensed systems need to scale and manage user “QoS”Density of wireless devices will continue to increase
~10x with home gadgets, ~100x with sensors/pervasive computingInteroperability between proliferating radio standards
Programmable radios that can form cooperating networks across multiple PHY’s
Motivation for Dynamic Spectrum and Cognitive Radio Techniques:
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Spectrum Management: Problem ScopeSpectrumAllocation
Rules(static)
INTERNET
BTS
AuctionServer
(dynamic)
SpectrumCoordination
Server(dynamic)
AP
Ad-hocsensor cluster(low-power, high density)
Short-rangeinfrastructure
mode network (e.g. WLAN)
Short-range ad-hoc net
Wide-area infrastructuremode network (e.g. 802.16)
Dense deployment of wireless devices, both wide-area and short-rangeProliferation of multiple radio technologies, e.g. 802.11a,b,g, UWB, 802.16, 4G, etc.How should spectrum allocation rules evolve to achieve high efficiency?Available options include:
Agile radios (interference avoidance)Dynamic centralized allocation methodsDistributed spectrum coordination (etiquette)Collaborative ad-hoc networks
Etiquettepolicy
SpectrumCoordination
protocols
Spectrum Coordinationprotocols
Dynamic frequencyprovisioning
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Broad range of technology & related policy options for spectrum
Need to determine performance (e.g. bps/Hz or bps/sq-m/Hz) of different technologies taking into account economic factors such as static efficiency, dynamic efficiency & innovation premium
Hardware Complexity
Protocol Complexity(degree of
coordination)
ReactiveRate/Power
Control
ReactiveRate/Power
Control
AgileWideband
Radios
AgileWideband
Radios
Unlicensed Band
with DCA (e.g. 802.11x)
Unlicensed Band
with DCA (e.g. 802.11x)
InternetServer-based
SpectrumEtiquette
InternetServer-based
SpectrumEtiquette
Ad-hoc,Multi-hop
Collaboration
Ad-hoc,Multi-hop
Collaboration
Radio-levelSpectrumEtiquetteProtocol
Radio-levelSpectrumEtiquetteProtocol
StaticAssignmentStatic
Assignment
InternetSpectrumLeasing
InternetSpectrumLeasing
“cognitive radio”schemes
UWB,Spread
Spectrum
UWB,Spread
Spectrum
“Open Access”+ smart radios
Unlicensed band +simple coord protocols
Cognitive Radio: Design Space
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Selected Cognitive Radio Research
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Cognitive Radio ResearchFundamental research and algorithms – based on foundations of:
Information and Coding TheoryRelay cooperation, User Cooperation, Coding techniques for cooperation, Collaborative MIMO techniques
Signal ProcessingCollaborative signal processing, Signal design for spectrum sharing, Interference avoidance, Distributed sensing algorithms
Game TheoryMicroeconomics and pricing based schemes for spectrum sharing, negotiation and coexistence, Incentive mechanisms for cooperation
MAC and Networking AlgorithmsDiscovery protocols, Etiquette protocols, Self-organization protocols, Multihop routing
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Information Theoretic ApproachesVarious types of relay cooperation and user cooperation models
Cooperation – nodes share power and bandwidth to mutually enhance their transmissionsCan achieve spatial diversity – similar to multiple antennas
Fundamental limits are known in limited casesPrimary focus on achievable rates, outage and various cooperative coding schemes, e.g.
Decode-and-ForwardCompress-and-ForwardAmplify-and-Forward
Relay Cooperation
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SN
Wired Backbone
SN
SN
SN
SN SN
SN
SN
SN
SN
SN
SN
SN SN
SN
SN
SN
SN
SNSN
SN
SN
SN
SN
SN
AP
AP
AP
SN
SN
SN
SN
SN
Information Theoretic ApproachesVarious types of relay cooperation and user cooperation models
Cooperation – nodes share power and bandwidth to mutually enhance their transmissionsCan achieve spatial diversity – similar to multiple antennas
Fundamental limits are known in limited casesPrimary focus on achievable rates, outage and various cooperative coding schemes, e.g.
Decode-and-ForwardCompress-and-ForwardAmplify-and-Forward
User Cooperation
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E.g. Relay Cooperation vs User Cooperation (Sankar-Kramer-Mandayam)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
x-coordinate
y-co
ordi
nate
User 1User 2DestinationRelay
Sector of circle of radius 1 and destination at circle center. Uniform node distribution.Average rate and outage over 100 locations.Path-loss exp. γ = 4. Transmit SNR for all users = P1.Processing cost factor η
Compare Outage Probability?
How much better than TDMA?
What is the effect of processing costs?
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Amplify-and-Forward Cooperation η = 0.01
Relay and User Cooperation schemes gain over TDMARelay achieves gains relative to user-cooperation
-10 -5 0 5 10
10-4
10-3
10-2
10-1
100
10-5
Transmit SNR P1 (dB)
Out
age
Pro
babi
lity
Pou
t
Sub-plot 1
-10 -5 0 5 10 15
10-4
10-3
10-2
10-1
100
10-5
Total (transmit+proc.) SNR Ptot (dB)
Out
age
Pro
babi
lity
Pou
t
Sub-plot 2
Coop. 2-hopRelay Pr=0.5P1Relay Pr=P1
TD-MAC
Coop. 2-hopRelay Pr=0.5P1Relay Pr=P1
TD-MAC
K = 2Rate R = .25
K = 2Rate R = .25η = .01
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Amplify-and-Forward Cooperation η = 0.5, 1
Even with η ↑ relay achieves gains relative user cooperation
-5 0 5 10 15
10-4
10-3
10-2
10-1
100
10-5
Total (transmit+proc.) SNR Ptot (dB)
Out
age
Pro
babi
lity
Pou
t
Sub-plot 1
-5 0 5 10 15
10-4
10-3
10-2
10-1
100
10-5
Total (transmit+proc.) SNR Ptot (dB)
Out
age
Pro
babi
lity
Pou
t
Sub-plot 2
Coop. 2-hopRelay Pr=0.5P1Relay Pr=P1
TD-MAC
Coop. 2-hopRelay Pr=0.5P1Relay Pr=P1
TD-MAC
K = 2Rate R = .25η = 1
K = 2Rate R = .25η = .5
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Game Theory ApproachesNegotiation strategies for mediation
Pricing and microeconomic strategies to promote cooperation in spectrum sharingReimbursing costs in cooperation – energy costs, delay costs
Domination strategies for situations of conflictSpectrum warfare with agile waveforms and competition for spectrum
Coalition formation strategies for cooperationCoalitional games for receiver and transmitter coalitions in spectrum sharing
Approaches result in algorithms that specify:• Power control • Rate control• Channel selection• Cooperation techniques• Route selection
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Each node•Enjoys its own data reaching the access point.•Pays for its outgoing throughput to adjacent devices.•Gets reimbursed for data it relays only if the data reaches theaccess point.
E.g. Inducing Forwarding through Reimbursement (Ileri-Mandayam)
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Horizontal Trajectory
Radio tower
5 m 10 m
-5 m
-
USER 2(POTENTIAL
FORWARDER)
USER 1(NON-FORWARDER)
ACCESS POINT
5 m POSITIONS OFUSER 1 IN
HORIZONTALGEOMETRY
• Incentives for forwarding works well when nodes tend to “cluster”
• The aggregate bits/Joule in network is higher
• Network revenue is also higher
0 1 2 3 4 5 6 710
14
1015
1016
1017
1018
1019
Aggregate bits/JouleAggregate bits/Joule, no reimbursement.
E.g. Inducing Forwarding through Reimbursement
user 2 distance
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Reactive (autonomous) methods used to avoid interference via:Frequency agility: dynamic channel allocation by scanningPower control: power control by interference detection and scanningTime scheduling: MAC packet re-scheduling based on observed activityWaveform agility: dynamism in signal space
A
D
C&D’s spectrum bandRange with Power Control
A
BB
C
DA&B’s spectrum band
Range without Power Control
Range without Power Control
Range with Power Control
PHY & MAC: Reactive Algorithms
Frequencyagility
Scheduling
D DC D
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Cognitive Radio: Limitations of Reactive Schemes
Reactive schemes (without explicit coordination protocols) suffer from certain limitations:
Near-far problems possible at the receiverInability to predict future behavior of other nodesOnly detects transmitters, not receivers, but interference is a receiver property
Coverage area of D
Y
A
B
C
D
A cannot hear DA’s agile radio waveform
D’s agile radio waveformwithout coordination protocol
with coordination
Hidden Terminal Problem
Coverage area of A
Coverage area of D
Y
A
B
C
D
A cannot hear DA’s agile radio waveform
D’s agile radio waveformwithout coordination protocol
with coordination
Hidden Terminal Problem
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Cognitive Approaches: OutlookFundamental research and algorithms – based on foundations
ofInformation and coding theory, Game theory, MAC, Networking, Signal processing
all point to the following:Cognitive radio networks require a large of amount of network (and channel) state information to enable efficient
DiscoverySelf-organization Cooperation Techniques
In addition to advances in cognitive radio technology, Network Architectures and Information Aids that
support these are required
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Cognitive Radios need help too!
Infrastructure that can facilitate cognitive radio networks
Coordination mechanisms for coexistence and cooperation
Information aids Spectrum Coordination Mechanisms
Network architectures “Spectrum Servers” to advise/mediate sharing
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Cognitive Radio: Common Spectrum Coordination Channel (CSCC) (Jing-Raychaudhuri)
Common spectrum coordination channel (CSCC) Common spectrum coordination channel (CSCC) can be used to coordinate radios with different PHY
Requires a standardized out-of-band etiquette channel & protocolPeriodic tx of radio parameters on CSCC, higher power to reach hidden
nodesLocal contentions resolved via etiquette policies (independent of
protocol)Also supports ad-hoc multi-hop routing associations
Frequency
CH#N
CH#N-1
CH#N-2
CH#2
CH#1
CSCC
::
Ad-hocnet B Ad-hoc
net A
Ad-hocPiconet
MasterNode
CSCCRX range
for X
CSCCRX range
for Y
Y
X
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CSCC Spectrum Etiquette ProtocolCSCC( Common Spectrum Coordination Channel) can enable mutual observation between neighboring radio devices by periodically broadcasting spectrum usage information
Edge-of-bandcoordination channel
Service channels
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CSCC: Proof-of-Concept Experiments
WLAN-BT Scenario
Different devices with dual mode radios running CSCCd=4 meters are kept constantPriority-based etiquette policy
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CSCC Results: Throughput Traces
0 20 40 60 80 100 120 140 160 180 200 220 240
3.4
3.6
3.8
4.0
4.2
4.4
4.6
4.8
WLA
N T
hrou
ghpu
t (M
bps)
Time (Seconds)
CSCC on CSCC off
WLAN session with BT2 in initial position
WLAN = high priority
0 50 100 150 200 250 30030
35
40
45
50
55
60
65
Blue
toot
h Th
roug
hput
(Kbp
s)
Time (Seconds)
CSCC on CSCC off
BT session with BT2 in initial position
Bluetooth = high priority
Observations:WLAN session throughput can improve ~35% by CSCC coordinationBT session throughput can improve ~25% by CSCC coordination
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802.11 & 16 Co-Existence Scenario
802.16a 802.11bTraffic Type UBR (Poisson arrival), UDP packet, 512 Bytes datagram
MAC protocol TDMA IEEE 802.11 BSS modeChannel Model AWGN, two ray ground propagation model, no fading
Default channel Channel 1 : centered at 2412GHz Channel 1 : centered at 2412GHzAvailable channels 4 (non-overlap) 12 (overlapping)
Bandwidth/channels 20 MHz / 4 non-overlapping chs 22MHz / 11 overlapping chs
Receiver Sensitivity -80dBm (@BER 10^-6) -82dBm (@BER 10^-5)Antenna Height BS 15m, SS 1.5m 1.5m
Tx Power/Max range 33dBm / 3.2Km 20dBm / 500m
Bit Rate 13Mbps 2MbpsRadio parameters OFDM (256-FFT, QPSK) DSSS (QPSK)Background Noise -174 dBm/Hz
Rx Noise Figure 9 dB 9 dB
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CSCC frequency adaptation when DSS-AP =200m and traffic load 2Mbps
AP1km
100m
802.11b Hotspot
802.16a Cell
BSSS
DSS-AP
802.16 DL 802.11 link0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Ave
rage
Lin
k Th
roug
hput
(Mbp
s)
802.16 DL and 802.11 link
No Coordination CSCC frequency adaptation
0 200 400 600 800 10000.0
0.2
0.4
0.6
0.8
1.0
1.2
Ave
rage
Lin
k Th
roug
hput
(Mbp
s)
Distance between 802.16 SS and 802.11 hotspot (meters)
802.16a DL 802.16a DL with CSCC 802.11 link 802.11 link with CSCC Average No Coordination Average with CSCC
Throughputs vs. DSS-AP by using CSCC power adaptation and traffic load 2Mbps
802.11 & 16 Co-Existence: Reactive vs. CSCC-based Power Control (Jing-Raychaudhuri)
Single 802.11 Hot Spot Case
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802.11 & 16 Co-Existence: Reactive vs. CSCC Power Control
0.2 0.4 0.6 0.8 1.070000
80000
90000
100000
110000
120000
130000
Aver
age
Net
wor
k Th
roug
hput
(bps
)
Clustering Index
No Coordination with CSCC with RTPC with TA
0.2 0.4 0.6 0.8 1.070000
80000
90000
100000
110000
120000
Ave
rage
Net
wor
k Th
roug
hput
(bps
)
Clustering Index
No Coordination with CSCC with RTPC with TA
802.16 SS nodes are (i) uniform or (ii) clustered in the cell.
clustering index CI = R11/R16
1km
Varying Max Cluster Radius
R16
Max Hotspot Radius R11
Region (i)
Region (ii)
802.16a BS802.16a SS802.11b AP802.11b Client
0.2 0.4 0.6 0.8 1.070000
80000
90000
100000
110000
120000
130000
Aver
age
Net
wor
k Th
roug
hput
(bps
)
Clustering Index
No Coordination with CSCC with RTPC with TA
CSCC power adaptation with clustered 802.16a SS in region (ii), with numbers of 802.16a SS :
802.11b nodes = 1:1
600 Kbps load
1 Mbps load
Multiple 802.11 Hot Spot Case
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Cognitive Radio: Spectrum Policy ServerInternetInternet--based Spectrum Policy Serverbased Spectrum Policy Server can help to coordinate wireless networks (a “Google for spectrum”)
Needs connection to Internet even under congested conditions (...low bit-rate OK)Some level of position determination needed (..coarse location OK?)Spectrum coordination achieved via etiquette protocol centralized at server
InternetInternet
Access Point(AP2)
AP1
WLANoperator A WLAN
operator B
Ad-hocBluetoothPiconet
Wide-areaCellular data
service
SpectrumPolicy Server
www.spectrum.netAP1: type, loc, freq, pwrAP2: type, loc, freq, pwrBT MN: type, loc, freq, pwr
MasterNode
EtiquetteProtocol
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What can a Spectrum Policy Server do?
Spectrum Server
rate4rate1
rate2 rate3
Spectrum Policy Server facilitates co-existence of heterogeneous set of radios by advising them on several possible issues
Spectrum etiquetteInterference informationLocation specific servicesMany more things ….
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Users share a common frequency bandOrthogonal signal dimensions = time slotsTime domain scheduling is used for channelization
Wireless network of L directed linksLinks employ ON-OFF transmission schedule in each time slot
Use constant transmission power in the ON stateLinks employ interference-adaptive modulation/coding
Link rate in each time slot depends on interference, receiver mitigation.Interference depends on the transmission mode
mode = subset of links that are ON simultaneously
Scheduling Variable Rate Links with a Spectrum Server (Raman-Yates-Mandayam)
1 4
3
2
1
3
tli = 1, if link l is in mode i= 0, otherwise.
[0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1] [0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1][0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1][0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1]
Transmission mode [1 0 1 0]
(one of 24 possible modes)
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network with 4 links
1 4
3
2
Transmission mode [1 0 1 0]
1
3
Rate matrix C =[6.6 0 0.01 0 0.56 0 0.01 0 2.05[ 0 6.6 0.06 0 0 1.86 0.06 0 0[ 0 0 0 6.6 1.0 1.86 0.83 0 0[ 0 0 0 0 0 0 0 6.65 0.32
0 0.01 0 0.49 0 0.01]0.97 0.06 0 0 0.77 0.06 ]0 0 0.04 0.04 0.04 0.04 ]0.05 0.04 0.40 0.19 0.05 0.04]
Glk = link gain fromTx k to Rx l
Spectrum Server Mode Matrix Rate Matrix
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Spectrum server specifies xi = fraction of time mode i is ON
Average rate in link l is rl = Σi cli xi
In vector form, r = Cx
Spectrum server specifies x to optimize an objective such as for example:
Maximum sum rate of the scheduleMaximize the common rate on the linksFair schedulingEfficient scheduling
Spectrum Server: Optimizing the Mode Schedule
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As common rmin increases, the sum rate decreasesRates of dominant mode links decreaseRates of disadvantaged links increase
Spectrum Server: Scheduling Results
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Spectrum Server: Fairness in Scheduling
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Hardware & Software Platforms
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Vanu Software Defined Radio
Vanu Inc. SDR programmable radio based on commodity processors. Supports multiple standards on handheld device.
Vanu Inc. Software Defined Radio Source: http://www.vanu.com/products.html
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GNU Hardware/Software Platform (Blossom)
GNU/USRP boards with GNU Software with API’s for flexible PHY and MAC are currently available for experimentationVarious RF front-ends (0-100MHz, 400MHz, 900MHz, 2.4GHZ) with data rates upto 64 MSamples/secAll DSP functions in software on general-purpose CPU
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WARP Platform (Rice University)
•Various RF front-ends (2.4GHZ, 5GHz) with baseband of up to 20 MHz•High data rates possible, Programmable PHY & Protocols, Extensible to MIMO•Backed by Xilinx, Nokia
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Cognitive Radio Networks & ProtocolsDiscovery strategies
Algorithms and protocols for frequency selection, coordination and cooperation
Multihop strategiesAlgorithms for self-organization and routing
AA
BB
D
C
D
E
F
Bootstrapped PHY &control link
End-to-end routed pathFrom A to F
PHY A
PHY BPHY C
Control(e.g. CSCC)
Multi-mode radio PHYAd-Hoc Discovery
& Routing Capability
E.g.
• Cognitive Radio scans for active nodes and executes discovery algorithm
• Control protocol for exchange of network information and routing tables
Functionality can be quitechallenging!
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WINLAB Cognitive RadioWINLAB’s “network centric” concept for
cognitive radio prototype (..under development in collaboration with GA Tech
& Lucent Bell Labs)
Requirements include:~Ghz spectrum scanning,Etiquette policy processingPHY layer adaptation (per pkt)Ad-hoc network discoveryMulti-hop routing ~100 Mbps+
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Cognitive Radio Networks: “CogNet”Architecture
New NSF FIND project called “CogNet” aimed at development of prototype cognitive radio stack within GNU frameworkJoint effort between Rutgers, U Kansas, CMU and Blossom Inc
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Cognitive Radio Networks: “CogNet”Protocol Stack
Global Control Plane (GCP)Common framework for spectrum allocation, PHY/MAC bootstrap, topology discovery and cross-layer routing
Data planeDynamically linked PHY, MAC, Network modules and parameters as specified by control plane protocol
Control PHYControl MAC
Boot-strap
Discovery
PHY
MACNetworkTransport
Application
Control Plane Data Plane
Global Control Plane
Data Plane
Control Signalling
Data Path
Establishment
Naming&
Addressing
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Cognitive Radio Network Experiments Hardware/Software Platforms@WINLAB
Urban
300 meters
500 meters
Suburban
20 meters
ORBIT Radio Grid
Office
30 meters
Radio Mapping Concept for ORBIT Emulator
400-node Radio Grid Facility at WINLAB Tech Center
ProgrammableORBIT radio node
URSP2CR board
Planned upgrade(2007-08)
Current ORBIT sandbox with GNU radio
ORBIT radio grid testbed currently supports ~10/USRP GNU radios, 100 low-cost spectrum sensors, WARP platforms, WINLAB Cognitive platforms and GNU/USRP2Each platform will include baseline CogNet stack
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Concluding Remarks
52
Wireless/Mobile/Sensor Scenarios and the Future Internet – NSF’s GENI Project
Some architectural and protocol implications for the future Internet...
Integrated support for dynamic end-user mobilityWireless/mobile devices as routers (mesh networks, etc.)Network topology changes more rapidly than in today’s wired InternetSignificant increase in network scale (10B sensors in 2020!)New ad hoc network service concepts: sensors, P2P, P2M, M2M,…Addressing architecture issues – name vs. routable addressIntegrating geographic location into routing/addressingIntegrating cross-layer and cognitive radio protocol stacksData/content driven networking for sensors and mobile data Pervasive network functionality vs. broadband streamingPower efficiency considerations and computing constraints for sensorsMany new security considerations for wireless/mobileEconomic incentives, e.g. for forwarding and network formation
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NSF GENI Implementation: Wireless Subnets – Overall Wireless Deployment PlanFive types of experimental wireless networks planned –necessary to support full range of protocol research and to enable new applications
1. Wireless emulation and simulation (repeatable protocol validations)2. Urban 802.11-based mesh/ad-hoc network (real-world networking experience with emerging short-range radios)3. Wide-area suburban network with both 3G/WiMax (wide area) and 802.11 radios4. Sensor networks (…application specific, specific system TBD via proposal process; may include environmental, vehicular, smart spaces, etc.)5. Cognitive radio network – advanced technology demonstrator (…adaptive, spectrum efficient networks using emerging CR platforms)…also some common network facilities such as location & dynamic binding services
Each network at a different geographic location – new spectrum allocation may be needed at some sites
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Advanced TechnologyDemonstrator (spectrum)
LocationService
NSF RadioTestbeds
Emulation &Simulation
Protocol &ScalingStudies
5 3
4
12
Other services
SensorNetworks
“Open” InternetConcepts forCellular devices
Embedded wireless,Real-world applicationsBroadband
Services,Mobile Computing
NSF GENI Implementation Wireless Sub-Networks Overview
Ad-HocMesh
Network
EmergingTechnologies
(cognitive radio)
GENIInfrastructure
Open APIWide-AreaNetworks
55
Cognitive Radio in NSF’s GENI ProjectPropose to build advanced technology demonstrator of cognitive radio networks for reliable wide-area services (over a ~50 Km**2 coverage area) with spectrum sharing, adaptive networking, etc.
Basic building block is a cognitive radio platform, to be selected from competing research projects now in progress and/or future proposalsRequires enhanced software interfaces for control of radio PHY, discovery and bootstrapping, adaptive network protocols …….. suitable for protocol virtualizationFCC experimental license for new cognitive radio band
Cognitive Radio Network Node
Cognitive Radio Client
Cognitive Radio Network Node
Cognitive Radio Client
Connections to GENIInfrastructure
Spectrum MonitorsSpectrum Server
Research Focus:1. New technology validation of cognitive
radio2. Protocols for adaptive PHY radio
networks3. Efficient spectrum sharing methods4. Interference avoidance and spectrum
etiquette5. Dynamic spectrum measurement6. Hardware platform performance studies
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Concluding RemarksFuture wireless networks need ~100-1000x increases in density and bit-rate of radios motivates better spectrum coordination methodsSpot shortages of spectrum will occur if present static allocation is continued significant improvement achieved with dynamic allocationCognitive radio technologies can be characterized in terms of the combination of hardware complexity & level of protocol coordinationPromising cognitive radio schemes include
Agile radio with interference avoidance
Spectrum etiquette protocols: spectrum server, CSCC..
Adaptive networks via ad-hoc collaboration
Early technical results now available for some of these methods, but very different complexity factors and market implications…
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Concluding RemarksFuture research areas in cognitive radio include:
New concepts and algorithms for agile radio and spectrum etiquette protocolsArchitecture and design of adaptive wireless networks based on cognitive radiosDetailed evaluation of large-scale cognitive radio systems using alternative methodsSpectrum measurement and field validation of proposed methodsCognitive radio hardware and software platforms
User-level field trials of emerging cognitive radios and related algorithms/protocols may also be useful to gain experience
Controlled testbed experiments comparing different co-existence methodsLarge-scale “spectrum server” trial for 802.11x coordinationExperimental deployments in proposed US FCC cognitive radio band
Success with cognitive radio technologies should lead to major improvements in spectrum efficiency, performance and interoperability