Download
cognitive radio research@winlab n.
Skip this Video
Loading SlideShow in 5 Seconds..
Cognitive Radio Research@WINLAB PowerPoint Presentation
Download Presentation
Cognitive Radio Research@WINLAB

Cognitive Radio Research@WINLAB

125 Vues Download Presentation
Télécharger la présentation

Cognitive Radio Research@WINLAB

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Cognitive Radio Research@WINLAB Narayan B. Mandayam WINLAB Rutgers University May 20, 2008 narayan@winlab.rutgers.edu www.winlab.rutgers.edu

  2. Cognitive Radio Research@WINLAB A Multidimensional Activity • Theory and Algorithms • Fundamental Limits • Information & Coding Theory • Cooperative Communications • Game Theory & Microeconomics • Spectrum Policy • Economics • Regulation • Legal • Business • Hardware/Software Platforms & Prototyping • Programmable agile radios • GNU platforms • Cognitive Radio Network Testbed

  3. How it all started -The Spectrum Debate & Cognitive Radio

  4. The Spectrum Debate Triumph of Technology vs. Triumph of Economics • Open Access (Commons) • [Noam, Benkler, Shepard, Reed …] • Triumph of Technology • Agile wideband radios will dynamically share a commons • Success of 802.11 vs 3G • Spectrum Property Rights • [Coase, Hazlett, Faulhaber+Farber] • Triumph of Economics • Owners can buy/sell/trade spectrum • Flexible use, flexible technology, flexible divisibility, transferability • A spectrum market will (by the force of economics) yield an efficient solution • What everyone agreed on (~ 10 years ago): • Spectrum use is inefficient • FCC licensing has yielded false scarcity

  5. Arguments against Triumph of Technology • Partially developed theory • Information theoretic relay channel • Information theoretic interference channel • Ad hoc network capacity, with/without mobility • Technology Panacea • Spread spectrum, UWB, MIMO, OFDM • Short range communications • Ad hoc multi-hop mesh networks • Infant technology • UWB, MIMO antenna arrays • Transmitter agility • Technology not separable from user assumptions • Capabilities of technology vary with cooperation

  6. Spectrum Management:In fairness to the FCC, Frequency allocation is complex… Source: FCC website

  7. Heavy Use Heavy Use Less than 6% Occupancy Atlanta Sparse Use Medium Use NewOrleans Time SanDiego Frequency Spectrum Management:Then again, poor utilization in most bands • FCC measurement shows that occupancy of approximately 700 MHz of spectrum 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

  8. The Spectrum Debate & Cognitive Radio • What everyone agrees on now:  • Spectrum use is inefficient • FCC licensing has yielded false scarcity • Possible middle ground? • Dynamic spectrum access • Short-term property rights • Spectrum use driven by both technology and market forces • Cognitive Radios with ability to incorporate market forces? • Microeconomics based approaches to spectrum sharing • “Dynamic Spectrum Access Models: Towards an Engineering Perspective in the Spectrum Debate” by Ileri & Mandayam, To appear in IEEE Communications Magazine 2007

  9. Dynamic Spectrum Access Models via Cognitive Radio • Develop engineering models for shaping spectrum policy • Three aspects we consider: • Dynamic Spectrum Access: Short term dedication of spectrum resources • Temporary Exclusive Usage: Parties do not suffer interference • Market Based Allocation: Supply and demand determines who gets how much bandwidth • We introduce two spectrum access models • D-Pass (Dynamic Property-Rights Spectrum Access) • D-CPass (Dynamic-Commons Property-Rights Spectrum Access)

  10. SPS W1 W2 Operator 2 Operator 1 Vectoral offers to users User N User 1 User 2 User 3 User 4 D-Pass Model (flavor of property rights) Allocation based charges, competition reminiscent of simultaneous ascending auctions

  11. D-CPass Model (flavor of open access) SPS Operator 1 Operator 2 Per user operator competition User 1 User 2 User N Usage based charges, competition reminiscent of English auctions

  12. MotivationforDynamic Spectrum and Cognitive Radio Techniques: • Static allocation of spectrum is inefficient • Slow, 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 computing • Interoperability between proliferating radio standards • Programmable radios that can form cooperating networks across multiple PHY’s

  13. Towards Cognitive Radio Networks Research 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 wins • Achievable rates via information theoretic relay and broadcast channels • “Global” awareness and coordination wins • Space, time and frequency awareness and coordination beyond local measurements • Efficient operation requires radios that can: • Cooperate • Collaborate • Discover • Self-Organize into hierarchical networks

  14. Selected Cognitive Radio Research @WINLAB

  15. Cognitive Radio - Theory & Algorithms Fundamental research and algorithms – based on foundations of: • Information and Coding Theory • Relay cooperation, User Cooperation, Coding techniques for cooperation, Collaborative MIMO techniques • Signal Processing • Collaborative signal processing, Signal design for spectrum sharing, Interference avoidance, Distributed sensing algorithms • Game Theory • Spectrum warfare, Microeconomics and pricing based schemes for spectrum sharing, negotiation and coexistence, Coalition formation, Incentive mechanisms for cooperation • MAC and Networking Algorithms • Discovery protocols, Etiquette protocols, Self-organization protocols, Multihop routing

  16. Information Theoretic Approaches • Various types of relay cooperation and user cooperation models • Cooperation – nodes share power and bandwidth to mutually enhance their transmissions • Can achieve spatial diversity – similar to multiple antennas • Fundamental limits are known in limited cases • Primary focus on achievable rates, outage and various cooperative coding schemes, e.g. • Decode-and-Forward • Compress-and-Forward • Amplify-and-Forward Relay Cooperation

  17. Information Theoretic Approaches • Various types of relay cooperation and user cooperation models • Cooperation – nodes share power and bandwidth to mutually enhance their transmissions • Can achieve spatial diversity – similar to multiple antennas • Fundamental limits are known in limited cases • Primary focus on achievable rates, outage and various cooperative coding schemes, e.g. • Decode-and-Forward • Compress-and-Forward • Amplify-and-Forward User Cooperation

  18. E.g. Relay Cooperation vs User Cooperation (Sankar-Kramer-Mandayam) • Sector of circle of radius 1 and destination at circle center. • Uniform node distribution. • Average rate and outage over 100 locations. • Path-loss exp.  = 4. • Transmit SNR for all users =P1. • Processing cost factor  Compare Outage Probability? How much better than TDMA? What is the effect of processing costs?

  19. Amplify-and-Forward Cooperation  = 0.01 • Relay and User Cooperation schemes gain over TDMA • Relay achieves gains relative to user-cooperation

  20. Amplify-and-Forward Cooperation  = 0.5, 1 • Even with  relay achieves gains relative user cooperation

  21. Game Theory Approaches • Negotiation strategies for mediation • Pricing and microeconomic strategies to promote cooperation in spectrum sharing • Reimbursing costs in cooperation – energy costs, delay costs • Domination strategies for situations of conflict • Spectrum warfare with agile waveforms and competition for spectrum • Coalition formation strategies for cooperation • Coalitional 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

  22. E.g. Inducing Forwarding through Reimbursement (Ileri-Mandayam) • 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 the • access point.

  23. 19 10 Aggregate bits/Joule Aggregate bits/Joule, no reimbursement. ACCESS POINT 18 10 Radio tower 5 m 17 10 POSITIONS OF USER 1 IN 16 HORIZONTAL 10 5 m 10 m GEOMETRY 15 10 USER 2 -5 m USER 1(NON- (POTENTIAL FORWARDER) FORWARDER) 14 10 - 0 1 2 3 4 5 6 7 E.g. Inducing Forwarding through Reimbursement Horizontal Trajectory user 2 distance • Incentives for forwarding works well when nodes tend to “cluster” • The aggregate bits/Joule in network is higher • Network revenue is also higher

  24. C C B B D’s agile radio waveform D’s agile radio waveform without coordination protocol without coordination protocol D D Coverage Coverage A’s agile radio waveform A’s agile radio waveform A cannot hear D A cannot hear D area of D area of D A A Y Y with coordination with coordination Coverage area of A Hidden Terminal Problem Hidden Terminal Problem Cognitive Radio: Reactive Schemes • Reactive (autonomous) methods used to avoid interference via: • Frequency agility: dynamic channel allocation by scanning • Power control: power control by interference detection and scanning • Time scheduling: MAC packet re-scheduling based on observed activity • Waveform agility: dynamism in signal space • Reactive schemes (without explicit coordination protocols) have limitations: Interference is a receiver property!

  25. B B PHY A End-to-end routed path From A to F Bootstrapped PHY & control link PHY C PHY B C Multi-mode radio PHY Ad-Hoc Discovery & Routing Capability D D Control (e.g. CSCC) E A A Functionality can be quite challenging! F Cognitive Approaches: Outlook • Cognitive radio networks require a large of amount of network (and channel) state information to enable efficient • Discovery • Self-organization • Cooperation Techniques

  26. Unlicensed band + simple coord protocols Ad-hoc, Multi-hop Collaboration Internet Server-based Spectrum Etiquette “cognitive radio” schemes Protocol Complexity (degree of coordination) Radio-level Spectrum Etiquette Protocol Unlicensed Band with DCA (e.g. 802.11x) Agile Wideband Radios Internet Spectrum Leasing “Open Access” + smart radios Reactive Rate/Power Control UWB, Spread Spectrum Static Assignment Hardware Complexity Cognitive Radio: Design Space • Broad range of technology & related policy options for spectrum

  27. Cognitive Radios need help too! • Infrastructure that can facilitate cognitive radio networks • Examples of coordination mechanisms: • Information aids • “Spectrum Coordination Channel” to enable spectrum sharing • Network architectures • “Spectrum Servers” to advise/mediate sharing

  28. CH#N CH#N-1 CH#N-2 CH#2 CH#1 CSCC CSCC RX range for X Ad-hoc net B Ad-hoc net A : : X Master Node CSCC RX range for Y Y Ad-hoc Piconet Frequency Cognitive Radio: Common Spectrum Coordination Channel (CSCC) (Jing-Raychaudhuri) • Common spectrum coordination channel (CSCC) can be used to coordinate radios with different PHY • Requires a standardized out-of-band etiquette channel & protocol • Periodic tx of radio parameters on CSCC, higher power to reach hidden nodes • Local contentions resolved via etiquette policies (independent of protocol) • Also supports ad-hoc multi-hop routing associations

  29. 802.11 & 16 Co-Existence Scenario

  30. 802.11 & 16 Co-Existence: Reactive vs. CSCC-based Power Control (Jing-Raychaudhuri) CSCC frequency adaptation when DSS-AP =200m and traffic load 2Mbps Single 802.11 Hot Spot Case Throughputs vs. DSS-APby using CSCC power adaptation and traffic load 2Mbps

  31. Cognitive Radio: Spectrum Policy Server • Internet-based 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 Internet Spectrum Policy Server www.spectrum.net AP1: type, loc, freq, pwr AP2: type, loc, freq, pwr BT MN: type, loc, freq, pwr Etiquette Protocol AP1 Access Point (AP2) WLAN operator A WLAN operator B Master Node Wide-area Cellular data service Ad-hoc Bluetooth Piconet

  32. What can a Spectrum Policy Server do? rate4 Spectrum Server • Spectrum Server facilitates co-existence of heterogeneous set of radios by advising them on several possible issues: rate1 rate2 rate3 • Mobility Management • Addressing • Authentication • Security • Content • Spectrum policy • Interference information • Scheduling and coexistence • Location specific services • Context

  33. (( )) Cross-layer scheduling of end-to-end flows AP Flow 1 Flow 2 • Wireless network • Physical links - achievable rates depend on the PHY layer transmission schemes, signal processing at receiver etc. • MAC – distributed/centralized schemes to avoid/control interference • Routing – decision made based on metric specified by application running on the network Overarching design principles for wireless networks employing a variety of physical layer strategies?

  34. 1 4 1 2 3 [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] 3 Scheduling with a Spectrum Server(Raman-Yates-Mandayam) Glk = link gain from Tx k to Rx l network with 4 links Transmission mode [1 0 1 0] Rate matrix C = The rate matrix C includes the achievable physical layer rates for a wide rate of physical layer transmission techniques • Spectrum server specifies • xi = fraction of time mode i is ON • Average rate in link l is rl = i cli xi

  35. . . . cM1 c11 x1 f1 cli cL1 fM xM x3 x1 f1 x1 x4 x2 f2 Universal cross-layer scheduling framework – centralized approach Utilities: Max throughput, max-min fairness, proportional fairness, energy efficiency Maximize User utilities such that: … 1 0 0 . . . . . . Physical layer rates Higher layer flow requirements 1 1 > … 1 0 PHY rates MAC schedule NETWORK routes TRANSPORT flows

  36. Hardware & Software Platforms

  37. WINLAB Cognitive Radio Requirements include: • ~Ghz spectrum scanning, • Etiquette policy processing • PHY layer adaptation (per pkt) • Ad-hoc network discovery • Multi-hop routing ~100 Mbps+ WINLAB’s “network centric” concept for cognitive radio prototype (..under development in collaboration with GA Tech & Lucent Bell Labs)

  38. Suburban Urban ORBIT Radio Grid 300 meters Office 20 meters 500 meters 30 meters Cognitive Radio Network Experiments Hardware/Software Platforms@WINLAB • ORBIT radio grid testbed currently supports ~10/USRP GNU radios, 100 low-cost spectrum sensors, WARP platforms, WINLAB Cognitive platforms and GNU/USRP2 • Cross-layer design and experimentation Current ORBIT sandbox with GNU radio 400-node Radio Grid Facility at WINLAB Tech Center Planned upgrade (2007-08) Programmable ORBIT radio node Radio Mapping Concept for ORBIT Emulator URSP2 CR board

  39. Wireless and the Future Internet ~750M servers/PC’s, >1B laptops, PDA’s, cell phones, sensors • “Wireless” is overtaking “Wired” as the primary mode of connectivity to the internet ~500M server/PC’s, ~100M laptops/PDA’s Wireless Edge Network INTERNET INTERNET Wireless Edge Network 2005 2010 • Wireless usage scenarios that will impact future internet design • Mobile data applications • Multihop Mesh networks • Sensor and vehicular networks

  40. Wireless/Mobile/Sensor Scenarios and the Future Internet • Some architectural and protocol implications for the future Internet... • Integrated support for dynamic end-user mobility • Wireless/mobile devices as routers (mesh networks, etc.) • Network topology changes more rapidly than in today’s wired Internet • Significant increase in network scale (10B sensors in 2020!) • New ad hoc network service concepts: sensors, P2P, P2M, M2M,… • Addressing architecture issues – name vs. routable address • Integrating geographic location into routing/addressing • Integrating cross-layer and cognitive radio protocol stacks • Data/content driven networking for sensors and mobile data • Pervasive network functionality vs. broadband streaming • Power efficiency considerations and computing constraints for sensors • Many new security considerations for wireless/mobile • Economic incentives, e.g. for forwarding and network formation

  41. NSF GENI Implementation Wireless Sub-Networks Overview Open API Wide-Area Networks Location Service 3 5 Emerging Technologies (cognitive radio) “Open” Internet Concepts for Cellular devices Other services GENI Infrastructure Advanced Technology Demonstrator (spectrum) 4 Sensor Networks 1 Ad-Hoc Mesh Network Embedded wireless, Real-world applications 2 NSF Radio Testbeds Broadband Services, Mobile Computing Protocol & Scaling Studies Emulation & Simulation

  42. Cognitive Radio in NSF’s GENI Project • Propose 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 proposals • Requires enhanced software interfaces for control of radio PHY, discovery and bootstrapping, adaptive network protocols …….. suitable for protocol virtualization • FCC experimental license for new cognitive radio band Cognitive Radio Network Node Cognitive Radio Client Spectrum Monitors Spectrum Server Cognitive Radio Network Node Connections to GENI Infrastructure • Research Focus: • New technology validation of cognitive radio • Protocols for adaptive PHY radio networks • Efficient spectrum sharing methods • Interference avoidance and spectrum etiquette • Dynamic spectrum measurement • Hardware platform performance studies Cognitive Radio Client

  43. CSCC Spectrum Etiquette Protocol • CSCC( Common Spectrum Coordination Channel)can enable mutual observation between neighboring radio devices by periodically broadcasting spectrum usage information Service channels Edge-of-band coordination channel

  44. CSCC: Proof-of-Concept Experiments WLAN-BT Scenario • Different devices with dual mode radios running CSCC • d=4 meters are kept constant • Priority-based etiquette policy

  45. CSCC Results: Throughput Traces • Observations: • WLAN session throughput can improve ~35% by CSCC coordination • BT session throughput can improve ~25% by CSCC coordination WLAN = high priority Bluetooth = high priority WLAN session with BT2 in initial position BT session with BT2 in initial position

  46. Cognitive Radio Networks: “CogNet” Architecture • New NSF FIND project called “CogNet” aimed at development of prototype cognitive radio stack within GNU framework • Joint effort between Rutgers, U Kansas, CMU and Blossom Inc

  47. Data Plane Global Control Plane Data Plane Control Plane Control Signalling Application Data Transport Boot - Disco Path strap very Establish Network ment MAC PHY 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 plane • Dynamically linked PHY, MAC, Network modules and parameters as specified by control plane protocol Naming & Addres sing Control MAC Control PHY

  48. Suburban Urban ORBIT Radio Grid 300 meters Office 20 meters 500 meters 30 meters Cognitive Radio Network Experiments Hardware/Software Platforms@WINLAB • ORBIT radio grid testbed currently supports ~10/USRP GNU radios, 100 low-cost spectrum sensors, WARP platforms, WINLAB Cognitive platforms and GNU/USRP2 • Each platform will include baseline CogNet stack Current ORBIT sandbox with GNU radio 400-node Radio Grid Facility at WINLAB Tech Center Planned upgrade (2007-08) Programmable ORBIT radio node Radio Mapping Concept for ORBIT Emulator URSP2 CR board

  49. 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 mobility • Wireless/mobile devices as routers (mesh networks, etc.) • Network topology changes more rapidly than in today’s wired Internet • Significant increase in network scale (10B sensors in 2020!) • New ad hoc network service concepts: sensors, P2P, P2M, M2M,… • Addressing architecture issues – name vs. routable address • Integrating geographic location into routing/addressing • Integrating cross-layer and cognitive radio protocol stacks • Data/content driven networking for sensors and mobile data • Pervasive network functionality vs. broadband streaming • Power efficiency considerations and computing constraints for sensors • Many new security considerations for wireless/mobile • Economic incentives, e.g. for forwarding and network formation