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Dyspan Sdr Cr Tutorial 10 25 Rev02


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Dyspan Sdr Cr Tutorial 10 25 Rev02

  1. 1. Understanding the Issues in Software Defined Cognitive Radio Jeffrey H. Reed Charles W. Bostian Virginia Tech Bradley Dept. of Electrical and Computer Engineering
  2. 2. Comment Slide – Delete Before Submitting Following section presented by Reed
  3. 3. What You Will Learn <ul><li>Basic Concepts of Software Defined Radio (SDR) </li></ul><ul><li>Basic Concepts of Cognitive Radio (CR) and its relationship to SDR. </li></ul><ul><li>How Cognitive Radios are Implemented </li></ul><ul><li>Analyzing Cognitive Radio Behavior and Performance </li></ul><ul><li>Regulatory Issues in Cognitive Radio Deployment </li></ul><ul><li>Cognitive Radio Applications in Interoperability and Spectrum Access </li></ul><ul><li>Current Research Issues </li></ul>
  4. 4. Acknowledgements <ul><ul><li>Albrecht Johannes Fehske </li></ul></ul><ul><ul><li>Thomas Rondeau </li></ul></ul><ul><ul><li>Bin Le </li></ul></ul><ul><ul><li>James Neel </li></ul></ul><ul><ul><li>David Scaperoth </li></ul></ul><ul><ul><li>Kyouwoong Kim </li></ul></ul><ul><ul><li>David Maldonado </li></ul></ul><ul><ul><li>Lizdabel Morales </li></ul></ul><ul><ul><li>Youping Zhao </li></ul></ul><ul><ul><li>Joseph Gaeddert </li></ul></ul><ul><li>Students that contributed to this presentation: </li></ul>
  5. 5. Software Defined Radio – Basic Concepts and Relationship to Cognitive Radio
  6. 6. Comment Slide – Delete Before Submitting Following section presented by Reed
  7. 7. Software Defined Radio (SDR) <ul><li>Termed coined by Mitola in 1992 </li></ul><ul><li>Radio’s physical layer behavior is primarily defined in software </li></ul><ul><li>Accepts fully programmable traffic & control information </li></ul><ul><li>Supports broad range of frequencies, air interfaces, and application software </li></ul><ul><li>Changes its initial configuration to satisfy user requirements </li></ul>
  8. 8. Software Defined Radio Levels (1/2) <ul><li>Highest Level of Reconfigurablity </li></ul><ul><ul><li>Completely flexible modulation format, protocols and user functions </li></ul></ul><ul><ul><li>Flexible bandwidths and center frequency, i.e., RF front end is also configurable </li></ul></ul><ul><ul><li>Adapts to different network and air interfaces </li></ul></ul><ul><ul><li>Open architecture for expansion and modifications </li></ul></ul>
  9. 9. Software Defined Radio Levels (2/2) <ul><li>Lowest Level of Reconfigurability </li></ul><ul><ul><li>Radio not easily changed </li></ul></ul><ul><ul><li>Preset signal bandwidth and center frequency </li></ul></ul><ul><ul><li>Few and preset modulation formats, protocols, and user functions </li></ul></ul>
  10. 10. Advantages of SDR <ul><li>Reduced content of expensive custom silicon </li></ul><ul><li>Reduce parts inventory </li></ul><ul><li>Ride declining prices in computing components </li></ul><ul><li>DSP can compensate for imperfections in RF components, allowing cheaper components to be used </li></ul><ul><li>Open architecture allows multiple vendors </li></ul><ul><li>Maintainability enhanced </li></ul>
  11. 11. Drawbacks of SDR <ul><li>Power consumption (at least for now) </li></ul><ul><li>Security </li></ul><ul><li>Cost </li></ul><ul><li>Software reliability </li></ul><ul><li>Keeping up with higher data rates </li></ul><ul><li>Fear of the unknown </li></ul><ul><li>Both subscriber and base units should be SDR for maximum benefit </li></ul>
  12. 12. Applications for SDR <ul><li>Military </li></ul><ul><ul><li>Full Connectivity </li></ul></ul><ul><ul><li>Sensor Networks </li></ul></ul><ul><ul><li>Better Performance </li></ul></ul><ul><li>Commercial </li></ul><ul><ul><li>Lower Cost – subscriber units </li></ul></ul><ul><ul><li>Lower Cost – base unit </li></ul></ul><ul><ul><li>Lower Cost – network </li></ul></ul><ul><ul><li>Better performance </li></ul></ul><ul><li>Regulatory </li></ul><ul><ul><li>Stretch expensive spectrum </li></ul></ul><ul><ul><li>Build in innovation mechanisms </li></ul></ul>
  13. 13. How is a Software Radio Different from Other Radios? - Application <ul><li>Software Radio </li></ul><ul><li>Dynamically support multiple variable systems, protocols and interfaces </li></ul><ul><li>Interface with diverse systems </li></ul><ul><li>Provide a wide range of services with variable QoS </li></ul><ul><li>Conventional </li></ul><ul><li>Radio </li></ul><ul><li>Supports a fixed number of systems </li></ul><ul><li>Reconfigurability decided at the time of design </li></ul><ul><li>May support multiple services, but chosen at the time of design </li></ul><ul><li>Cognitive Radio </li></ul><ul><li>Can create new waveforms on its own </li></ul><ul><li>Can negotiate new interfaces </li></ul><ul><li>Adjusts operations to meet the QoS required by the application for the signal environment </li></ul>
  14. 14. How is a Software Radio Different from Other Radios?- Design <ul><li>Software Radio </li></ul><ul><li>Conventional Radio + </li></ul><ul><li>Software Architecture </li></ul><ul><li>Reconfigurability </li></ul><ul><li>Provisions for easy upgrades </li></ul><ul><li>Conventional </li></ul><ul><li>Radio </li></ul><ul><li>Traditional RF Design </li></ul><ul><li>Traditional Baseband Design </li></ul><ul><li>Cognitive Radio </li></ul><ul><li>SDR + </li></ul><ul><li>Intelligence </li></ul><ul><li>Awareness </li></ul><ul><li>Learning </li></ul><ul><li>Observations </li></ul>
  15. 15. How is a Software Radio Different from Other Radios? - Upgrade Cycle <ul><li>Software Radio </li></ul><ul><li>Ideally software radios could be “future proof” </li></ul><ul><li>Many different external upgrade mechanisms </li></ul><ul><ul><li>Over-the-Air (OTA) </li></ul></ul><ul><li>Conventional Radio </li></ul><ul><li>Cannot be made “future proof” </li></ul><ul><li>Typically radios are not upgradeable </li></ul><ul><li>Cognitive Radio </li></ul><ul><li>SDR upgrade mechanisms </li></ul><ul><li>Internal upgrades </li></ul><ul><li>Collaborative upgrades </li></ul>
  16. 16. Cognitive Radio Concepts
  17. 17. Comment Slide – Delete Before Submitting Following section presented by Bostian
  18. 18. Cognitive Radio <ul><li>Term coined by Mitola in 1999 </li></ul><ul><li>Mitola’s definition: </li></ul><ul><ul><li>Software radio that is aware of its environment and its capabilities </li></ul></ul><ul><ul><li>Alters its physical layer behavior </li></ul></ul><ul><ul><li>Capable of following complex adaptation strategies </li></ul></ul><ul><li>“ A radio or system that senses, and is aware of, its operational environment and can dynamically and autonomously adjust its radio operating parameters accordingly” </li></ul><ul><li>Learns from previous experiences </li></ul><ul><li>Deals with situations not planned at the initial time of design </li></ul>
  19. 19. What is a Cognitive Radio? Adaptive radios can adjust themselves to accommodate anticipated events Fixed radios are set by their operators Cognitive radios can sense their environment and learn how to adapt <ul><li>Beyond adaptive radios, cognitive radios can handle unanticipated channels and events. </li></ul><ul><li>Cognitive radios require: </li></ul><ul><ul><li>Sensing </li></ul></ul><ul><ul><li>Adaptation </li></ul></ul><ul><ul><li>Learning </li></ul></ul><ul><li>Cognitive radios intelligently optimize their own performance in response to user requests and in conformity with FCC rules. </li></ul>
  20. 20. <ul><li>Cognitive radios are machines that sense their environment (the radio spectrum) and respond intelligently to it. </li></ul><ul><li>Like animals and people they </li></ul><ul><li>seek their own kind (other radios with which they want to communicate) </li></ul><ul><li>avoid or outwit enemies (interfering radios) </li></ul><ul><li>find a place to live (usable spectrum) </li></ul><ul><li>conform to the etiquette of their society (the Federal Communications Commission) </li></ul><ul><li>make a living (deliver the services that their user wants) </li></ul><ul><li>deal with entirely new situations and learn from experience </li></ul>
  21. 21. 1) Access to spectrum (finding an open frequency and using it) Cognitive radios are a powerful tool for solving two major problems:
  22. 22. 2) Interoperability (talking to legacy radios using a variety of incompatible waveforms) Cognitive radios are a powerful tool for solving two major problems:
  23. 23. Levels of Radio Functionality Adapted From Table 4-1Mitola, “ Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio, ” PhD Dissertation Royal Institute of Technology, Sweden, May 2000. Level Capability Comments 0 Pre-programmed A software radio 1 Goal Driven Chooses Waveform According to Goal. Requires Environment Awareness. 2 Context Awareness Knowledge of What the User is Trying to Do 3 Radio Aware Knowledge of Radio and Network Components, Environment Models 4 Capable of Planning Analyze Situation (Level 2& 3) to Determine Goals (QoS, power), Follows Prescribed Plans 5 Conducts Negotiations Settle on a Plan with Another Radio 6 Learns Environment Autonomously Determines Structure of Environment 7 Adapts Plans Generates New Goals 8 Adapts Protocols Proposes and Negotiates New Protocols
  24. 24. What is a cognitive radio? <ul><li>An enhancement on the traditional software radio concept 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. </li></ul>Adapted From Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications ”, IEEE Mobile Multimedia Conference, 1999, pp 3-10. Urgent Allocate Resources Initiate Processes Negotiate Protocols Orient Infer from Context Select Alternate Goals Plan Normal Immediate Learn New States Observe Outside World Decide Act User Driven (Buttons) Autonomous Infer from Radio Model States Generate “Best” Waveform Establish Priority Parse Stimuli Pre-process Cognitive radio Cognition Cycle
  25. 25. <ul><li>Level </li></ul><ul><li>0 SDR </li></ul><ul><li>1 Goal Driven </li></ul><ul><li>2 Context Aware </li></ul><ul><li>3 Radio Aware </li></ul><ul><li>4 Planning </li></ul><ul><li>5 Negotiating </li></ul><ul><li>6 Learns Environment </li></ul><ul><li>7 Adapts Plans </li></ul><ul><li>8 Adapts Protocols </li></ul>Relationship between the Cognition Cycle and the Levels of Functionality Normal Urgent Select Alternate Goals Establish Priority Negotiate Immediate Negotiate Protocols Generate Alternate Goals Adapted From Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications ”, IEEE Mobile Multimedia Conference, 1999, pp 3-10. Determine “Best” Known Waveform Generate “Best” Waveform Allocate Resources Initiate Processes Orient Infer from Context Parse Stimuli Pre-process Plan Normal Learn New States Observe Outside World Decide Act User Driven (Buttons) Autonomous Determine “Best” Plan Infer from Radio Model States
  26. 26. FCC Motivation for Cognitive Radio <ul><li>Currently the FCC is refarming licensed bands such as the TV Bands </li></ul><ul><li>Long-term vision </li></ul><ul><ul><li>Eliminate rigid, coarse spectrum allocations </li></ul></ul><ul><ul><li>Switch to demand-based approach </li></ul></ul><ul><ul><ul><li>Improve relative spectral efficiency </li></ul></ul></ul><ul><li>Need new protocols for </li></ul><ul><ul><li>Supporting long-term vision of the FCC </li></ul></ul><ul><ul><li>Inter-network interference avoidance </li></ul></ul><ul><ul><li>Maximizing utilization of available bandwidth </li></ul></ul>
  27. 27. Cognitive Radio Advantages <ul><li>All the software radio benefits </li></ul><ul><li>Improved link performance </li></ul><ul><ul><li>Adapt away from bad channels </li></ul></ul><ul><ul><li>Increase data rate on good channels </li></ul></ul><ul><li>Improved spectrum utilization </li></ul><ul><ul><li>Fill in unused spectrum </li></ul></ul><ul><ul><li>Move away from over occupied spectrum </li></ul></ul><ul><li>New business propositions </li></ul><ul><ul><li>High speed internet in rural areas </li></ul></ul><ul><ul><li>High data rate application networks (e.g., Video-conferencing) </li></ul></ul><ul><li>Significant interest from FCC, DoD </li></ul><ul><ul><li>Possible use in TV band refarming </li></ul></ul>
  28. 28. Cognitive Radio Drawbacks <ul><li>All the software radio drawbacks </li></ul><ul><li>Significant research to realize </li></ul><ul><ul><li>Information collection and modeling </li></ul></ul><ul><ul><li>Decision processes </li></ul></ul><ul><ul><li>Learning processes </li></ul></ul><ul><ul><li>Hardware support </li></ul></ul><ul><li>Regulatory concerns </li></ul><ul><li>Loss of control </li></ul><ul><li>Fear of undesirable adaptations </li></ul><ul><ul><li>Need some way to ensure adaptations yield desirable networks </li></ul></ul>
  29. 29. Cognitive Radio & SDR <ul><li>SDR’s impact on the wireless world is difficult to predict </li></ul><ul><ul><li>“ But what…is it good for?” </li></ul></ul><ul><ul><ul><li>Engineer at the Advanced Computing Systems Division of IBM, 1968, commenting on the microchip </li></ul></ul></ul><ul><li>Some believe SDR is not necessary for cognitive radio </li></ul><ul><ul><li>Cognition is a function of higher-layer application </li></ul></ul><ul><li>Cognitive radio without SDR is limited </li></ul><ul><ul><li>Underlying radio should be highly adaptive </li></ul></ul><ul><ul><ul><li>Wide QoS range </li></ul></ul></ul><ul><ul><ul><li>Better suited to deal with new standards </li></ul></ul></ul><ul><ul><ul><ul><li>Resistance to obsolescence </li></ul></ul></ul></ul><ul><ul><ul><li>Better suited for cross-layer optimization </li></ul></ul></ul>
  30. 30. Types of Software Defined Cognitive Radios <ul><li>Policy-Based Radio </li></ul><ul><li>Reconfigurable Radio </li></ul><ul><li>Cognitive Radio </li></ul>
  31. 31. Policy-based Radio <ul><li>A radio that is governed by a predetermined set of rules for choosing between different predefined waveforms </li></ul><ul><li>The definition and implementation of these rules can be: </li></ul><ul><ul><li>during the manufacturing process </li></ul></ul><ul><ul><li>during configuration of a device by the user; </li></ul></ul><ul><ul><li>during over-the-air provisioning; and/or </li></ul></ul><ul><ul><li>by over-the-air control </li></ul></ul><ul><li>Analogous to rules of what to order from a menu </li></ul><ul><ul><li>“ I’ll have GSM today” </li></ul></ul>
  32. 32. Reconfigurable Radio <ul><li>A radio whose hardware functionality can be changed under software control </li></ul><ul><li>Reconfiguration control of such radios may involve any element of the communication network </li></ul><ul><li>Analogous to rules of what to order from a menu and permit substitutions to the order </li></ul><ul><ul><li>“ I’ll have GSM today with the 802.11 FEC” </li></ul></ul>
  33. 33. Technology Challenges in SDR
  34. 34. Comment Slide – Delete Before Submitting Following section presented by Reed Needs more work on example SDR architectures
  35. 35. Radio Architecture Rx Tx RF Signal Amplify Mixer Filter Amplify Mixer Filter IF Signal Baseband Signal Superhetrodyne RF Signal Amplify Mixer Filter Analog To Digital Converter IF Signal Digital Signal Processing Software Defined Radio
  36. 36. Behind the Converters: The Software Architecture <ul><li>Nature of Architecture Depends on Applications: Commercial vs. Military </li></ul><ul><li>Benefits of a Good Architecture </li></ul><ul><ul><li>Clear way to implement system </li></ul></ul><ul><ul><li>Reuse --- modularity </li></ul></ul><ul><ul><li>Quality control and testing </li></ul></ul><ul><ul><li>Portability – one radio to another </li></ul></ul><ul><ul><li>Upgradability </li></ul></ul><ul><ul><li>Outsourcing/managing development </li></ul></ul><ul><ul><li>Language independence </li></ul></ul><ul><ul><li>More potential for Over-the-Air Programming </li></ul></ul><ul><ul><li>Standardized interfaces </li></ul></ul><ul><li>Middleware-based architectures are commonly used </li></ul>
  37. 37. Example SDR: GNU Radio <ul><li>What is GNU Radio? </li></ul><ul><ul><li>GNU Radio is a set of S/W signal processing building blocks that allow users to create their own S/W radio </li></ul></ul><ul><li>Why GNU Radio? </li></ul><ul><ul><li>Attempts to solve the complexity issues of both H/W and S/W of SDR </li></ul></ul><ul><ul><li>Modular (use with most any GPP) </li></ul></ul><ul><ul><ul><li>S/W used on Windows, Linux, Mac </li></ul></ul></ul>
  38. 38. Implementing a SDR with the GNU Radio <ul><li>USRP - Universal Software </li></ul><ul><li>Radio Peripheral </li></ul>Courtesy of GNU Radio S/W available at GNU Radio software - core s/w - user made s/w
  39. 39. USRP <ul><li>4 ADC’s: </li></ul><ul><li>12bits per second, 64MSps, </li></ul><ul><li>Analog Input BW over 200Mhz </li></ul><ul><li>4 DAC’s </li></ul><ul><li>14bits per second, 128MSps </li></ul>Receive Channel RF Interface Transmit Channel RF Interface
  40. 40. Challenges in SDR Design <ul><li>Hardware </li></ul><ul><ul><li>Significant effort in computing HW </li></ul></ul><ul><ul><li>Advance DSP Designs </li></ul></ul><ul><ul><li>Flexible RF and antennas </li></ul></ul><ul><ul><li>Flexible ADCs </li></ul></ul><ul><ul><li>Tradeoff of performance and flexibility </li></ul></ul><ul><li>Software </li></ul><ul><ul><li>Integration of components into single design flow </li></ul></ul><ul><ul><li>Tradeoff of performance and flexibility </li></ul></ul><ul><li>Testing and validation </li></ul><ul><ul><li>FCC hardware/software certification </li></ul></ul><ul><ul><li>Smoothing of design cycle </li></ul></ul><ul><ul><ul><li>Reduce overall time-to-market </li></ul></ul></ul>
  41. 41. Technology Challenges of SDR <ul><li>Technology in SDR partitioned into three basic pieces </li></ul><ul><ul><li>Hardware </li></ul></ul><ul><ul><ul><li>Physical devices on which processing is performed or interface to the “real world” </li></ul></ul></ul><ul><ul><li>Software </li></ul></ul><ul><ul><ul><li>Glue holding together system </li></ul></ul></ul><ul><ul><li>Network </li></ul></ul><ul><ul><ul><li>Functionality and ultimate value to the end-user </li></ul></ul></ul><ul><li>Advances needed in all three arenas </li></ul>
  42. 42. Hardware <ul><li>Significant effort to date in computing HW </li></ul><ul><ul><li>Non-traditional computing platforms </li></ul></ul><ul><ul><li>Advanced DSP designs </li></ul></ul><ul><ul><li>High data rate FEC remains problematic </li></ul></ul><ul><li>Emphasis on computing HW alone can be myopic </li></ul><ul><ul><li>Other critical areas that require significant further work </li></ul></ul><ul><ul><ul><li>Flexible (or software controlled) RF </li></ul></ul></ul><ul><ul><ul><li>Flexible ADC </li></ul></ul></ul><ul><ul><ul><li>Antennas </li></ul></ul></ul>
  43. 43. Flexible RF <ul><li>RF is one of the main limiting factors on system design </li></ul><ul><ul><li>Places fundamental limits on the signal characteristics </li></ul></ul><ul><ul><ul><li>BW, SNR, linearity </li></ul></ul></ul><ul><ul><li>Truly flexible SDR requires flexible RF </li></ul></ul><ul><ul><ul><li>Difficult task </li></ul></ul></ul><ul><ul><ul><ul><li>RF is fundamentally analog and requires different a different approach for the management of attributes </li></ul></ul></ul></ul><ul><ul><ul><li>One method for achieving this is through the use of MEMS </li></ul></ul></ul>
  44. 44. MEMS (Micro Electro Mechanical Systems) Designs for RF Front Ends <ul><li>Tunable antenna with narrow fixed bandwidth </li></ul><ul><li>Patch antenna connected by RF switches </li></ul>E-tenna’s Reconfigurable Antenna Idealized MEMs RF Front-end for a Software Radio <ul><li>Use MEMS filter banks to create tunable RF filters </li></ul>J.H. Reed, Software Radio: A Modern Approach to Radio Design, Prentice-Hall 2002.
  45. 45. ADC Challenges <ul><li>ADC is the bound between analog and digital world </li></ul><ul><li>SDR requires the tuning of ADC characteristics </li></ul><ul><ul><li>Number of bits </li></ul></ul><ul><ul><ul><li>Support adequate SNR and dynamic range </li></ul></ul></ul><ul><ul><li>Sampling rate </li></ul></ul><ul><ul><ul><li>Prevent over-sampling (waste power) </li></ul></ul></ul><ul><li>ADC technology trends are not necessarily compatible with these needs </li></ul>
  46. 46. ADCs Getting Better Exponentially <ul><li>1994 ~ 2004 a leap of Analog to Digital Converter (ADC) technology </li></ul><ul><li>Regression curve fit shows exponential increasing trends </li></ul><ul><li>Trends are quite different for different ADC structures </li></ul>B bits f s sample rate Bin Lee, Tom Rondeau, Jeff Reed, Charles Bostian, “Past, Present, and Future of ADCs,” submitted to IEEE Signal Processing Magazine, August 2004
  47. 47. ADC: Improving Even When Considering Power <ul><li>Power-to-sampling-speed ratio favors less number of comparators </li></ul><ul><li>The choice in selecting an ADC is tied to application requirement </li></ul>P diss is power dissipation Bin Lee, Tom Rondeau, Jeff Reed, Charles Bostian, “Past, Present, and Future of ADCs,” submitted to IEEE Signal Processing Magazine, August 2004
  48. 48. Integration of Hardware <ul><li>DSP share traits with GPP </li></ul><ul><ul><li>Similar programming methods </li></ul></ul><ul><ul><li>Similar computing concepts </li></ul></ul><ul><ul><ul><li>Even though implementation may be wildly different </li></ul></ul></ul><ul><li>FPGA and CCM do not share these traits with GPP </li></ul><ul><ul><li>Completely different programming paradigm </li></ul></ul><ul><ul><li>Portability is an extremely difficult problem </li></ul></ul>
  49. 49. Software Operating Environment <ul><li>Standardized structure for the management of HW and SW components </li></ul><ul><ul><li>SCA </li></ul></ul><ul><li>Technology to date has been largely derived from existing PC paradigm </li></ul><ul><ul><li>GPP-centric structure </li></ul></ul><ul><ul><li>SCA 3.0 Hardware Supplement is an attempt to rectify this problem </li></ul></ul><ul><li>Several challenges remain </li></ul><ul><ul><li>Power management </li></ul></ul><ul><ul><li>Integration of HW into structure </li></ul></ul>
  50. 50. Software Architectures <ul><li>“ The sheer ease with which we can produce a superficial image often leads to creative disaster.” Ansel Adams [1902-1984], American artist (photography) </li></ul><ul><ul><li>Poor architectural design is leads to significant inefficiencies </li></ul></ul><ul><li>Architectures provide multiple benefits </li></ul><ul><ul><li>Clear way to implement system </li></ul></ul><ul><ul><ul><li>Generally component-based </li></ul></ul></ul><ul><ul><ul><ul><li>Software or hardware components </li></ul></ul></ul></ul><ul><ul><li>Standardized interfaces </li></ul></ul><ul><ul><ul><li>Standard technology interface </li></ul></ul></ul><ul><ul><ul><ul><li>Common technology like middleware </li></ul></ul></ul></ul><ul><ul><ul><li>Standard semantic -- API </li></ul></ul></ul><ul><ul><li>Architectures becoming more prominent </li></ul></ul><ul><ul><ul><li>Software Communications Architecture (SCA) </li></ul></ul></ul><ul><ul><ul><li>$14B to $27B for SCA radio work by DoD </li></ul></ul></ul><ul><ul><ul><li>Cluster 5 contract up to $1B for embedded & handheld prototypes </li></ul></ul></ul><ul><ul><ul><li>Maintain awareness of activity: big money for SDR </li></ul></ul></ul>
  51. 51. So How Do You Make a Software Radio? <ul><li>You have some hardware </li></ul><ul><li>And you want to run some waveforms </li></ul><ul><ul><li>GSM, IS-95, or some other technology that the hardware is powerful enough to support </li></ul></ul>
  52. 52. What kind of software is needed? (1/4) <ul><li>Something to manage hardware </li></ul><ul><ul><li>Configure associated devices </li></ul></ul><ul><ul><ul><li>Set devices to known state </li></ul></ul></ul><ul><ul><ul><ul><li>i.e.: Make sure NCO is available and ready </li></ul></ul></ul></ul><ul><ul><li>Initialize cores </li></ul></ul><ul><ul><ul><li>Make sure programmable devices are ready </li></ul></ul></ul><ul><ul><ul><ul><li>Set memory pointers in DSP </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Set FPGA to known state </li></ul></ul></ul></ul>
  53. 53. What kind of software is needed? (2/4) <ul><li>Some standardized way of storing relevant information </li></ul><ul><ul><li>More than just short-term memory </li></ul></ul><ul><ul><ul><li>Store configuration files </li></ul></ul></ul><ul><ul><ul><li>Store last state of the machine </li></ul></ul></ul><ul><ul><ul><li>Store user-defined attributes </li></ul></ul></ul><ul><ul><ul><ul><li>Identity </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Permissions </li></ul></ul></ul></ul><ul><ul><ul><li>Store functional software </li></ul></ul></ul><ul><ul><li>Should be able to map any kind of storage device to this </li></ul></ul><ul><ul><ul><li>Dynamic RAM, hard drive, FLASH, other </li></ul></ul></ul>
  54. 54. What kind of software is needed? (3/4) <ul><li>Some way of structuring the waveforms </li></ul><ul><ul><li>Standardized way of structuring “applications” so that the radio can “run” them </li></ul></ul><ul><ul><ul><li>In a Windows machine, these are .exe files </li></ul></ul></ul><ul><ul><li>It has to be generic enough for it to fit well with machines other than GPPs </li></ul></ul><ul><ul><ul><li>Needs to be able to interface with functional software </li></ul></ul></ul>
  55. 55. What kind of software is needed? (4/4) <ul><li>Something to actually “run” waveforms </li></ul><ul><ul><li>Install functional software in appropriate core </li></ul></ul><ul><ul><li>Generate a start event </li></ul></ul><ul><li>Something to keep track of what is available and what can and cannot be installed </li></ul><ul><ul><li>Ideally, this will bind the whole thing together </li></ul></ul>
  56. 56. Fundamental Composition of the SCA Keep 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 Resoruces Manage waveform operation Application Port
  57. 57. Software Communications Architecture (SCA) <ul><li>Processor-centric structure </li></ul><ul><ul><li>Standardized interface for components </li></ul></ul><ul><ul><ul><li>Seamless handling of HW and SW </li></ul></ul></ul><ul><li>Open-source implementations available </li></ul><ul><ul><li>OSSIE </li></ul></ul><ul><ul><ul><li>C++ by MPRG </li></ul></ul></ul><ul><ul><li>SCARI </li></ul></ul><ul><ul><ul><li>Java by Communications Research Centre </li></ul></ul></ul>Non-secure Secure
  58. 58. Is the SCA Suitable for Commercial Implementations? <ul><li>Maybe </li></ul><ul><ul><li>No </li></ul></ul><ul><ul><ul><li>Current version is GPP-centric, hence heavy </li></ul></ul></ul><ul><ul><ul><li>Irrelevant capabilities decrease its effectiveness </li></ul></ul></ul><ul><ul><ul><li>Focus on waveform portability has limited appeal </li></ul></ul></ul><ul><ul><ul><li>Static nature not well suited for cognitive radio </li></ul></ul></ul><ul><ul><ul><li>No provisions for power management </li></ul></ul></ul><ul><ul><li>Yes </li></ul></ul><ul><ul><ul><li>Basic architectural principles are sound </li></ul></ul></ul><ul><ul><ul><li>SCA 3.0 is a first step in dealing with GPP-centric communications within the radio </li></ul></ul></ul><ul><ul><ul><li>Significant momentum ($$$ and time) within defense industry </li></ul></ul></ul><ul><ul><ul><li>Being adopted by several other nations’ defense establishments </li></ul></ul></ul>
  59. 59. Summary of Trends <ul><li>SDR need is driven by two principal factors </li></ul><ul><ul><li>New applications </li></ul></ul><ul><ul><ul><li>Cognitive radio, collaborative radio & advanced roaming </li></ul></ul></ul><ul><ul><li>Increased number of protocols to support </li></ul></ul><ul><ul><li>Potential cost reductions </li></ul></ul><ul><li>ADC is no longer the key bottleneck </li></ul><ul><li>Flexible RF products starting to come to market </li></ul><ul><li>Software architecture critical </li></ul><ul><ul><li>Additional technology supporting architectural approach available </li></ul></ul><ul><li>Reconfigurable hardware needed </li></ul><ul><ul><li>General-purpose hardware approach is likely to be unable to keep up with wireless bandwidth growth </li></ul></ul><ul><ul><li>Component-based reconfigurable hardware architectures present powerful solution </li></ul></ul><ul><ul><li>Multi-core processors show promise </li></ul></ul>
  60. 60. SDR Market Today <ul><li>Military </li></ul><ul><ul><li>JTRS program created multi-billion dollar SDR market </li></ul></ul><ul><ul><li>DARPA neXt Generation (XG) Communications project </li></ul></ul><ul><ul><li>International derivatives of JTRS/SCA (EU, Canada, etc) </li></ul></ul><ul><li>Commercial </li></ul><ul><ul><li>Digital RF processors (TI Bluetooth and GSM) </li></ul></ul><ul><ul><li>Multi-standard basestation implementations (Vanu) </li></ul></ul><ul><ul><li>SDR handsets probably within 3 years as low power processors become available </li></ul></ul><ul><li>Regulatory </li></ul><ul><ul><li>Recent FCC directive to ensure code and RF compatibility </li></ul></ul>
  61. 61. Cognitive Radio Implementation
  62. 62. Comment Slide – Delete Before Submitting Following section presented by Bostian
  63. 63. Knobs and Meters Sample tabulation of knobs and meters by layer (adapted from Prof. Huseyin Arslan) Layer Meters (observable parameters) Knobs (writable parameters) MAC Frame error rate Data rate Source coding Channel coding rate and type Frame size and type Interleaving details Channel/slot/code allocation Duplexing Multiple access Encryption PHY Bit error rate SINR Received signal power Noise power Interference power Power consumption Fading statistics Doppler spread Delay spread Angle of Arrival Transmitter power Spreading type and code Modulation type Modulation index Pulse shaping Symbol rate Carrier frequency Dynamic range Equalization Antenna directivity Other Computational power Battery Life CPU Frequency scaling
  64. 64. The VT Cognitive Engine <ul><li>Simple Concept </li></ul>Radio Parameters “ Knobs and Meters” Channel Statistics Cognitive Engine Radio RX Radio TX
  65. 65. The VT Cognitive Engine <ul><li>Simple Concept </li></ul>Radio TX Channel Statistics Cognitive Engine Radio RX “ Meters” “ Old Knobs Settings” “ Old Knobs Settings” Radio Parameters “ Knobs and Meters” “ Optimized Solution” “ New Settings” “ New Settings”
  66. 66. The VT Tiered Approach to Cognition <ul><li>Modeling System </li></ul><ul><ul><li>Take in surrounding radio environment and user/network requirements </li></ul></ul><ul><li>Remember models and apply Case-based Decision Theory to determine best course of action to take </li></ul><ul><li>Use Genetic Algorithms to update and optimize the new radio parameters </li></ul><ul><li>Monitor feedback from radio to understand system performance </li></ul><ul><ul><li>Penalize knowledge base for poor performance </li></ul></ul>
  67. 67. The Cognitive Engine <ul><li>“ Intelligent agent” that manages cognition tasks in a Cognitive Radio </li></ul><ul><li>Independent entity that oversees cognitive operations </li></ul><ul><li>Ideal Characteristics: </li></ul><ul><ul><li>Intelligence (Accurate decisions) </li></ul></ul><ul><ul><li>Reliability (Consistent decisions) </li></ul></ul><ul><ul><li>Awareness (Informed decisions) </li></ul></ul><ul><ul><li>Adaptability (Situation dependent decisions) </li></ul></ul><ul><ul><li>Efficiency (Low overhead decisions) </li></ul></ul><ul><ul><li>Excellent QoS (Good decisions) </li></ul></ul><ul><li>Tradeoffs exist between these characteristics </li></ul>
  68. 68. Software Architecture - Theory
  69. 69. Software Architecture - Theory
  70. 70. Software Architecture – Limited Functionality
  71. 71. Software Architecture: Full Functionality
  72. 72. Some Approaches to Cognitive Engine <ul><li>Genetic Algorithms </li></ul><ul><li>Markov Models </li></ul><ul><li>Neural Nets </li></ul><ul><li>Expert Systems and Natural Language Processing </li></ul><ul><li>Fuzzy Logic </li></ul>Open issue on what are the appropriate cognitive engine techniques
  73. 73. 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.
  74. 74. Some Approaches to Signal Classification <ul><li>Cyclic Spectrum Analysis </li></ul><ul><li>Statistical characterization of signal parameters </li></ul><ul><li>Eigenstructure techniques </li></ul><ul><li>Model-based approaches </li></ul>
  75. 75. Analyzing Performance in a Cognitive Radio
  76. 76. Comment Slide – Delete Before Submitting Following section presented by Reed Needs more work on example SDR architectures
  77. 77. Analyzing the Performance of a Network of Cognitive Radios
  78. 78. Ways of Analyzing Performance <ul><li>For the Cognitive Radio </li></ul><ul><ul><li>QOS, Detection of Primary Users (PU), SW Platform, QOS of PU, Position Location </li></ul></ul><ul><li>For the network of Cognitive Radios </li></ul><ul><ul><li>Quantifying the impact of the use of CR in a network </li></ul></ul><ul><ul><li>Game Theoretic Approach </li></ul></ul><ul><ul><li>See </li></ul></ul>
  79. 79. Cognitive Radio Performance Evaluation: QoS <ul><li>Parameters </li></ul><ul><ul><li>Data throughput </li></ul></ul><ul><ul><li>Latency </li></ul></ul><ul><ul><li>Voice quality </li></ul></ul><ul><ul><li>Video quality </li></ul></ul><ul><li>These depend on link performance measures: </li></ul><ul><ul><li>PHY Layer, e.g.: </li></ul></ul><ul><ul><ul><li>Bit error rate (BER) </li></ul></ul></ul><ul><ul><ul><li>Signal to noise ratio (SIR) </li></ul></ul></ul><ul><ul><ul><li>Signal to interference and noise ratio (SINR) </li></ul></ul></ul><ul><ul><ul><li>Received signal strength </li></ul></ul></ul><ul><ul><li>MAC, network-layer, e.g.: </li></ul></ul><ul><ul><ul><li>Frame error rate (FER) </li></ul></ul></ul><ul><ul><ul><li>Packet error rate </li></ul></ul></ul><ul><ul><ul><li>Routing table change rate </li></ul></ul></ul>
  80. 80. Cognitive Radio Performance Evaluation: Detection of Primary Users <ul><li>Probability of detection (PoD) as a function of: </li></ul><ul><ul><li>number of observed symbols </li></ul></ul><ul><ul><li>SNR </li></ul></ul><ul><ul><li>Number of signals present (primary and secondary) </li></ul></ul><ul><ul><li>Level of cooperation, e.g., number of devices (CRs) needed to achieve a given PoD (see next slide) </li></ul></ul><ul><li>Probability of false alarm </li></ul><ul><ul><li>same parameters as PoD </li></ul></ul>
  81. 81. Cognitive Radio Performance Evaluation: Underlying Software Radio Platform <ul><li>Number of supported waveforms </li></ul><ul><li>Processing power (mips, flops, #gates) </li></ul><ul><li>Waveform-code reusability and portability </li></ul><ul><ul><li>Reusable: the same code can be used in principle in a different SDR platform </li></ul></ul><ul><ul><li>Portable: instantaneous plug and play </li></ul></ul><ul><li>Delay for loading unloading waveforms </li></ul><ul><li>RF front-end: </li></ul><ul><ul><li>Frequency range, Dynamic range, Sampling frequency, Sensitivity, Selectivity, Stability, Spurious response </li></ul></ul><ul><li>Power consumption </li></ul><ul><li>Size, Weight, Cost </li></ul>
  82. 82. Cognitive Radio Performance Evaluation: Position Location <ul><li>Main perfromance measures for position location service: </li></ul><ul><ul><li>Precision and Availability </li></ul></ul><ul><li>Different technologies provide different quality of position location services: </li></ul><ul><ul><li>Assisted GPS (AGPS) </li></ul></ul><ul><ul><ul><li>performance degrades significantly when no clear view of sky (indoors, urban canyons) </li></ul></ul></ul><ul><ul><ul><li>works best in rural areas (no shadowing) </li></ul></ul></ul><ul><ul><li>Network based services </li></ul></ul><ul><ul><ul><li>accuracy in general lower than AGPS </li></ul></ul></ul><ul><ul><ul><li>works best with many base stations present (populated areas) </li></ul></ul></ul><ul><ul><ul><li>performance doesn't degrade indoors </li></ul></ul></ul><ul><ul><li>Hybrid services </li></ul></ul><ul><ul><ul><li>Combines advantages of both approaches </li></ul></ul></ul><ul><ul><ul><li>AGPS whenever possible, if not available switch to network based service </li></ul></ul></ul>
  83. 83. Cognitive Radio Performance Evaluation: Primary users' QoS <ul><li>Time needed to vacate channel after primary user (re-) appears </li></ul><ul><li>Negative impacts: </li></ul><ul><ul><li>Increased SINR, BER, FER, … results in: </li></ul></ul><ul><ul><li>Decreased: </li></ul></ul><ul><ul><ul><li>Data throughput </li></ul></ul></ul><ul><ul><ul><li>Latency </li></ul></ul></ul><ul><ul><ul><li>Voice quality </li></ul></ul></ul><ul><ul><ul><li>Video quality </li></ul></ul></ul><ul><ul><li>Increased </li></ul></ul><ul><ul><ul><li>Call drop rate (cell phone networks) </li></ul></ul></ul><ul><ul><ul><li>Handover failure (cell phone networks) </li></ul></ul></ul>
  84. 84. Dynamic cognitive radios in a network <ul><li>Dynamic benefits </li></ul><ul><ul><li>Improved spectrum utilization </li></ul></ul><ul><ul><li>Improve QoS </li></ul></ul><ul><li>Many decisions may have to be localized </li></ul><ul><ul><li>Distributed behavior </li></ul></ul><ul><li>Adaptations of one radio can impact adaptations of others </li></ul><ul><ul><li>Interactive decisions </li></ul></ul><ul><ul><li>Locally optimal decisions may be globally undesirable </li></ul></ul>
  85. 85. Locally optimal decisions that lead to globally undesirable networks <ul><li>Scenario: Distributed SINR maximizing power control in a single cluster </li></ul><ul><li>For each link, it is desirable to increase transmit power in response to increased interference </li></ul><ul><li>Steady state of network is all nodes transmitting at maximum power </li></ul>Power SINR Need way to analyze networks with interactive decisions. Game theory can help.
  86. 86. What is a game? <ul><li>A game is a model (mathematical representation) of an interactive decision process. </li></ul><ul><li>Its purpose is to create a formal framework that captures the process’s relevant information in such a way that is suitable for analysis. </li></ul><ul><li>Different situations indicate the use of different game models. </li></ul><ul><li>Identification of the type of game played by the cognitive radios provides insights into performance </li></ul>
  87. 87. <ul><li>Steady state characterization </li></ul><ul><li>Steady state optimality </li></ul><ul><li>Convergence </li></ul><ul><li>Stability </li></ul><ul><li>Scalability </li></ul>Key Issues in Analysis Steady State Characterization Is it possible to predict behavior in the system? How many different outcomes are possible? Optimality Are these outcomes desirable? Do these outcomes maximize the system target parameters? Convergence How 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? Stability How does system variations impact the system? Do the steady states change? Is convergence affected? Scalability As the number of devices increases, How is the system impacted? Do previously optimal steady states remain optimal? a 1 a 2 NE1 NE2 NE3 a 1 a 2 NE1 NE2 NE3 a 1 a 2 NE1 NE2 NE3 a 1 a 2 NE1 NE2 NE3 a 3
  88. 88. Cognitive Radio, Spectrum Policy, and Regulation
  89. 89. Comment Slide – Delete Before Submitting Following section presented by Reed
  90. 90. An Analogy between a Cognitive Radio and a Car Driver <ul><li>Cognitive Radio’s capabilities: </li></ul><ul><li>Senses, and is aware of, its operational environment and its capabilities </li></ul><ul><li>Can dynamically and autonomously adjust its radio operating parameters accordingly </li></ul><ul><li>Learns from previous experiences </li></ul><ul><li>Deals with situations not planned at the initial time of design </li></ul><ul><li>Car Driver’s capabilities: </li></ul><ul><li>Senses, and is aware of, its operational environment and its capabilities </li></ul><ul><li>Can dynamically and autonomously adjust the driving operation accordingly </li></ul><ul><li>Learns from previous experiences </li></ul><ul><li>Deals with situations not planned at the initial time of learning to drive </li></ul>They behave almost exactly the same!!!
  91. 91. “ Rules of the Road” ➟ “Rules of the Cognitive Radio” POLICY AWARE Primary User has higher priority over Secondary users Radio emission may be prohibited at certain location or for certain type of radio LOCATION AWARE Precautions 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”
  92. 92. “ Rules of the Road”-inspired CR Philosophy and Etiquette Insights 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
  93. 93. A traffic model analogy – Common Issues It 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 cannot hear each other.
  94. 94. Vehicle Following Distances for Car Drivers ➟ Time needed to vacate channel after primary user (re-) appears for Cognitive Radios Vehicle Following Distances: TWO-SECOND RULE: Use the two-second rule to determine a safe following distance. A traffic model analogy (cont.)
  95. 95. A traffic model analogy (cont.) SPEED LIMIT for car driver ➟ Interference Level Limit (e.g. Max. Allowed Interference Temperature) for Cognitive Radio
  96. 96. City Map for Car Drivers ➟ Radio Environment Map (REM) for Cognitive Radios Learning from “Traffic model analogy” for the development of Cognitive Radio… REM Time (or duration) Location (x, y, z), Type of radio environment Local Policy Profile of primary users Profile of interference Max. allowed Interference Level
  97. 97. 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
  98. 98. Spectrum Policy Challenges <ul><li>The spectrum is already allocated </li></ul><ul><ul><li>True spectrum scarcity on urban areas (ISM band) </li></ul></ul><ul><li>We need to deal with existing standards </li></ul><ul><li>The standards are embedded in the hardware! </li></ul>
  99. 99. Spectrum Utilization <ul><li>Spectrum utilization is quite low in many bands </li></ul><ul><li>Concept: </li></ul><ul><ul><li>Have radios (or networks) identify spectrum opportunities at run-time </li></ul></ul><ul><ul><li>Transparently (to legacy systems) fill in the gaps (time, frequency, space) </li></ul></ul><ul><li>Considered Bands </li></ul><ul><ul><li>ISM </li></ul></ul><ul><ul><li>Public Safety </li></ul></ul><ul><ul><li>TV (UHF) </li></ul></ul>Lichtenau (Germany), September 2001 dB  V/m From F. Jondral, “ SPECTRUM POOLING - An Efficient Strategy for Radio Resource Sharing, ” Blacksburg (VA), June 8, 200 4.
  100. 100. 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. Results from Shared Spectrum Co. and Univ. of Kansas
  101. 101. Regulatory Trends <ul><li>In an effort to improve radio spectrum management and promote a more efficient use of it, the regulatory bodies are trying to adopt a new spectrum access model. </li></ul><ul><li>This represents a paradigm shift from hardware-embedded policy implementation to dynamic software-based adaptation </li></ul><ul><ul><li>Harder to keep tight control! </li></ul></ul>
  102. 102. Regulatory Trends <ul><li>Proceedings that are the Key Drivers: </li></ul><ul><li>Receiver Standards </li></ul><ul><ul><li>ET Docket No. 03-65 NOI </li></ul></ul><ul><li>Interference Temperature </li></ul><ul><ul><li>ET Docket 03-237 NPRM/NOI </li></ul></ul><ul><li>Cognitive Radio </li></ul><ul><ul><li>ET Docket No. 03-108 NPRM </li></ul></ul><ul><li>License-exempt Operation in the TV Broadcast Bands </li></ul><ul><ul><li>ET Docket No. 04-186 </li></ul></ul><ul><li>Additional Spectrum for License-exempt devices below 900 MHz and in the 3 GHz Band </li></ul><ul><ul><li>ET Docket No. 02-380 </li></ul></ul>
  103. 103. Policy Engine Approach <ul><li>PE needs to provide limiting operational parameters </li></ul><ul><ul><li>Interpret policy automatically </li></ul></ul><ul><ul><li>Act dynamically in response to the operating environment </li></ul></ul><ul><li>PE needs to authenticate the policy </li></ul><ul><li>It will require an extremely efficient policy format </li></ul><ul><ul><li>It must handle the complexity of current policy without presenting a significant load to the CE </li></ul></ul><ul><li>The goal is to limit the search space before looking for a solution </li></ul><ul><ul><li>Rely on CE to do the reasoning about spectrum sharing </li></ul></ul>
  104. 104. DARPA XG Program <ul><li>XG is trying to Develop the Technology and System Concepts to Dynamically Access Available Spectrum </li></ul>Source: DARPA XG Program
  105. 105. Spectrum Policy Language Design Actors and Roles Source: BBN Technologies Solutions LLC Area that needs improvements! Spectrum Policy Policy Administrator (e.g. FCC, NTIA) XG System Spectrum Opportunities Awareness via XG Protocols and Sensing query Language Design Knowledge Core Language Model and Representation Policy Language Designer (e.g. BBN/XG Program) Policy Editing and Verification Tools design Machine Readable Policy Instances Policy Repository encode publish Policy Repository
  106. 106. The BIG Question: FCC Certification <ul><li>At all costs, the FCC must avoid “an epidemic situation in the unlicensed area.” </li></ul><ul><li>FCC likes to operate from “established engineering practices.” The SDR and CR communities must defined these. </li></ul><ul><li>Open source radios are a particular problem because their operating parameters are not necessarily bounded. </li></ul>
  107. 107. <ul><li>People seeking certification must explain how their software will respect parameter limits specified in FCC rules. </li></ul><ul><li>Submitted software must be accompanied by flow charts, code, and an explanation of how it works. </li></ul><ul><li>Software certification should not be more difficult to achieve than hardware certification. </li></ul>
  108. 108. Proposed Approach Policy Engine Cognitive Engine Applications Bios/OS
  109. 109. Example of a Possible Cognitive Radio Application
  110. 110. Comment Slide – Delete Before Submitting Following section presented by Reed
  111. 111. How can CR improve Spectrum Utilization? <ul><li>Allocate the frequency usage in a network. </li></ul><ul><li>Assist secondary markets with frequency use, implemented by mutual agreements. </li></ul><ul><li>Negotiate frequency use between users. </li></ul><ul><li>Provide automated frequency coordination. </li></ul><ul><li>Enable unlicensed users when spectrum not in use. </li></ul><ul><li>Overcome incompatibilities among existing communication services. </li></ul>
  112. 112. How can CR improve Network Management Efficiency? <ul><li>Present Practice characterizes service demand in a network statistically </li></ul><ul><li>By using cognitive radio, time-space characterization of demand is possible </li></ul><ul><li>Cognitive Radio </li></ul><ul><ul><li>Learns plans of the user to move and use wireless resources </li></ul></ul><ul><ul><li>Expresses its plans to the network reducing uncertainty about future demand </li></ul></ul><ul><li>The network can use its resources more efficiently </li></ul>
  113. 113. How can a CR Enhance Service Delivery? <ul><li>Wireless Communications in general and cognitive radio in particular have great potential to generate personal user information </li></ul><ul><ul><li>For example: actual position, native language, habits, travel, etc. </li></ul></ul><ul><li>Enhanced services can be provided using this information </li></ul><ul><li>CR interacts with the network on user’s behalf </li></ul>
  114. 114. Note Daily Drive Home at 5:30 (GPS Aided) Recall Brief Coverage Hole 1. Observe and Analyze Situation 2. Evaluate Alternatives Do Nothing Increase Coding Gain Increase Transmit Power Vertical Handoff Decrease Call Drop Threshold 4. Adapt Network 3. Signal Base Station Request Decrease In Call Drop Threshold CR in a Cellular System
  115. 115. Example of Cognitive Radio in Cellular Environment <ul><li>Cognitive radio is aware of areas with a bad signal </li></ul><ul><li>Can learn the location of the bad signal </li></ul><ul><ul><li>Has “insight” </li></ul></ul><ul><li>Radio takes action to compensate for loss of signal </li></ul><ul><ul><li>Actions available: </li></ul></ul><ul><ul><ul><li>Power, bandwidth, coding, channel </li></ul></ul></ul><ul><ul><li>Radio learns best course of action from situation </li></ul></ul>
  116. 116. Supplements Cellular System <ul><li>Cellular systems are plagued with coverage gaps </li></ul><ul><li>Cognitive radio can enhance coverage around these gaps by: </li></ul><ul><ul><li>Learning the areas of coverage gaps </li></ul></ul><ul><ul><li>Learning the best PHY layer parameters </li></ul></ul><ul><ul><li>Taking action prior to getting to the area </li></ul></ul><ul><ul><li>Sharing this knowledge with other cell phones </li></ul></ul><ul><ul><ul><li>Coverage gaps are found very rapidly </li></ul></ul></ul><ul><ul><li>Alert cellular system of gap, so provider can remedy situation </li></ul></ul>
  117. 117. Current Research Efforts in Cognitive Radio
  118. 118. Comment Slide – Delete Before Submitting Following section presented by Reed
  119. 119. Universities Participating at Dyspan <ul><li>Bar-Ilang Univ. </li></ul><ul><li>Georgia Tech </li></ul><ul><li>Mich. State Univ. </li></ul><ul><li>Michigan Tech </li></ul><ul><li>MIT </li></ul><ul><li>Northwestern Univ. </li></ul><ul><li>Ohio Univ. </li></ul><ul><li>Rutgers Univ. </li></ul><ul><li>RWTH Aachen Univ. </li></ul><ul><li>Stanford Univ. </li></ul><ul><li>Univ. of Calif. Berkeley </li></ul><ul><li>Univ. of Cambridge </li></ul><ul><li>Univ. of Col. </li></ul><ul><li>Univ. of MD </li></ul><ul><li>Univ. of Pittsburg </li></ul><ul><li>Univ. of Toronto </li></ul><ul><li>Univ. of Warwick </li></ul><ul><li>Universitaet Karlsruhe </li></ul><ul><li>University of Piraeus </li></ul><ul><li>Virginia Tech </li></ul>
  120. 120. DARPA
  121. 121. DARPA neXt Generation Program - Motivation <ul><li>Problems: </li></ul><ul><ul><li>Spectrum Scarcity </li></ul></ul><ul><ul><ul><li>Spectral resources are not fully exploited </li></ul></ul></ul><ul><ul><ul><li>Opportunities exist in space, time, frequency </li></ul></ul></ul><ul><ul><ul><li>Current static spectrum allocation prevents efficient spectrum utilization </li></ul></ul></ul><ul><ul><li>Deployment difficulty </li></ul></ul><ul><ul><ul><li>Different policy regimes in different countries </li></ul></ul></ul><ul><ul><ul><li>Deployment of communication networks tedious </li></ul></ul></ul><ul><ul><ul><li>Of particular interest in military applications </li></ul></ul></ul><ul><li>Proposed solution: </li></ul><ul><ul><li>Complement static spectrum allocation with &quot;Opportunistic spectrum access&quot; </li></ul></ul><ul><ul><ul><li>Primary users </li></ul></ul></ul><ul><ul><ul><ul><li>Licensed </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Priority to use allocated spectrum </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Guaranteed QoS </li></ul></ul></ul></ul><ul><ul><ul><li>Secondary users </li></ul></ul></ul><ul><ul><ul><ul><li>Non-licensed </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Can allocate unused spectrum among themselves </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Have to vacate bands if required by primaries </li></ul></ul></ul></ul>Unless otherwise stated, all the information in this description of the DARPA XG program is based on the XG Vision rfc, available online:
  122. 122. DARPA neXt Generation Program: Research Goals <ul><li>Development of technologies that enable spectrum agility </li></ul><ul><ul><li>Sensing and characterization of the (RF-) environment </li></ul></ul><ul><ul><li>Identification of unused spectrum (&quot;opportunities&quot;) </li></ul></ul><ul><ul><li>Allocation and exploitation of opportunities </li></ul></ul><ul><li>Development of standards for a software based policy regime to enable policy agility </li></ul><ul><ul><li>explained in more detail on the next slides </li></ul></ul>
  123. 123. DARPA neXt Generation Program: Concepts of Policy Agility (1) <ul><li>Decoupling of policies from implementation </li></ul><ul><ul><li>Define abstract behaviors, e.g., &quot;Channel can be vacated within t sec.&quot; </li></ul></ul><ul><ul><li>Policies implement (dictate) behaviors </li></ul></ul><ul><ul><li>Protocols instantiate behaviors </li></ul></ul><ul><li>Traceability </li></ul><ul><ul><li>All behaviors must be traceable to policies: </li></ul></ul><ul><ul><ul><li>Each operational mode a device is capable of is tied to a specific policy which allows it </li></ul></ul></ul><ul><li>Software based </li></ul><ul><ul><li>Spectrum use policies have to be machine understandable </li></ul></ul><ul><ul><li>Policy constraints can be implemented &quot;on-the-fly&quot; via software downloads </li></ul></ul>
  124. 124. 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 components
  125. 125. DARPA neXt Generation Program: Concepts of Policy Agility (3) Machine understandable policies will enable software downloads &quot;on-the-fly&quot; Figure drawn from XG Vision RFC
  126. 126. DARPA neXt Generation Program: Promises <ul><li>Flexible radio operation due to spectrum agility </li></ul><ul><li>Simplified user control of XG systems </li></ul><ul><ul><li>System operation can be controlled in terms of behavior </li></ul></ul><ul><ul><li>No need for technological details </li></ul></ul><ul><li>Facilitated policy design </li></ul><ul><ul><li>Constraints can be tailored to national or institutional needs in terms of behaviors </li></ul></ul><ul><ul><li>No need for technological details </li></ul></ul><ul><li>Eased wireless device accreditation </li></ul><ul><ul><li>Traceability provides a means for an easy testing procedure of behaviors against policies </li></ul></ul><ul><li>Broad and future proof standard </li></ul><ul><ul><li>Will be designed to be applicable to a broad range of radios </li></ul></ul><ul><ul><li>Future proof design will enable extension of the standard </li></ul></ul><ul><ul><li>Framework character: different technological solutions (protocols) can be accomodated to perform a particular task (sensing, identification, allocation) </li></ul></ul>
  127. 127. E 2 R
  128. 128. E 2 R Research in Europe <ul><li>E 2 R = End-to-End Reconfigurability </li></ul><ul><ul><li>Efficient, advanced & flexible end-user service provision </li></ul></ul><ul><ul><ul><li>Tailoring of application and service provision to user preferences and profile </li></ul></ul></ul><ul><ul><li>Efficient spectrum, radio and equipment resources utilization </li></ul></ul><ul><ul><ul><li>Enabling technologies for flexible spectrum resources </li></ul></ul></ul><ul><ul><li>Multi-standard platforms </li></ul></ul><ul><ul><ul><li>A single hardware platform shared dynamically amongst multiple applications </li></ul></ul></ul>
  129. 129. E2R Participants 1/2 <ul><li>Academic Partners </li></ul><ul><li>Eurecom: Institut Eurecom </li></ul><ul><li>I2R </li></ul><ul><li>KCL:Centre for Telecommunications Research (CTR) - King's College London </li></ul><ul><li>UoA: University of Athens </li></ul><ul><li>TUD: Dresden University </li></ul><ul><li>UoKarlsruhe: University of Karlsruhe, Communications Engineering Lab </li></ul><ul><li>UPRC: University of Piraeus Research Center </li></ul><ul><li>UNIS: University of Surrey </li></ul><ul><li>Operator R&D Partners </li></ul><ul><li>DoCoMo: DoCoMo Communications Laboratories Europe GmbH </li></ul><ul><li>FT: France Telecom R&D </li></ul><ul><li>TILAB: Telecom Italia S.p.A. </li></ul><ul><li>TID: Telefonica I+D </li></ul><ul><ul><ul><ul><ul><li>Source </li></ul></ul></ul></ul></ul>
  130. 130. E2R Participants 2/2 <ul><li>Manufacturer Partners </li></ul><ul><li>MOTO: Motorola Labs </li></ul><ul><li>ACP: Advanced Circuit Pursuit AG </li></ul><ul><li>ASEL: Alcatel SEL </li></ul><ul><li>DICE: Danube Integrated Circuit Engineering </li></ul><ul><li>Nokia: Nokia GmbH </li></ul><ul><li>PMDL: Panasonic UK </li></ul><ul><li>PEL: Panasonic European Laboratories GmbH </li></ul><ul><li>SM: Siemens Germany </li></ul><ul><li>SMC: Siemens Mobile Communications SpA </li></ul><ul><li>THC: Thales Communications </li></ul><ul><li>TRL: Toshiba Research Europe Limited </li></ul><ul><li>MIL: Motorola Israel Ltd </li></ul><ul><li>Regulator partners </li></ul><ul><li>DiGITIP </li></ul><ul><li>UPC: UPC </li></ul><ul><li>RegTP </li></ul>
  131. 131. Berkeley Wireless Research Center
  132. 132. Berkeley Wireless Research Center <ul><li>Designing a cognitive radio to improve spectrum utilization </li></ul><ul><li>Radio searches for feasible region and optimal waveform for transmission (environment sensing) </li></ul><ul><li>Avoiding of Interference with primary spectrum users by: </li></ul><ul><ul><li>Measuring spectrum usage in time, frequency, and space </li></ul></ul><ul><ul><li>Having statistical traffic models of primary spetrum users </li></ul></ul><ul><li>A cognitive radio test bed is currently being built </li></ul><ul><li>From R.W. Brodersen, A. Wolisz, D. Cabric, S. M. Mishra, D. Willkomm &quot;Corvus: A Cognitive Radio Aproach For Usage of Virtual Unlicensed Spectrum&quot;, July 29th 2004 </li></ul><ul><li>The six system functions are split between physical and data link layer </li></ul><ul><li>Two control channels: </li></ul><ul><ul><li>UCC for group management (group announcement) </li></ul></ul><ul><ul><li>GCC used only by members of a certain group </li></ul></ul>
  133. 133. Rutgers Winlab
  134. 134. WINLAB Rutgers University <ul><li>Design of info-stations for emergency and disaster relief applications </li></ul><ul><li>Use of customized commercially available hardware, e.g. 802.11 wireless </li></ul>From: <ul><li>Benefits </li></ul><ul><li>Increases the total information available for rescue workers </li></ul><ul><li>tailors the information with regard to specific needs and available bandwidth </li></ul><ul><li>coordinates communication of different rescue groups at one site </li></ul>
  135. 135. Virginia Tech’s CWT
  136. 136. 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.” <ul><li>Develop and test a prototype system for using cognitive techniques to allow WiFi-like unlicensed operation in unoccupied TV channels. </li></ul><ul><li>Investigate the behavior of networks containing both legacy radios and cognitive radios that can interoperate with them. </li></ul><ul><li>Build a prototype cognitive radio that can recognize and interoperate with three commonly used and mutually incompatible public safety waveform standards </li></ul>
  137. 137. Virginia Tech’s MPRG
  138. 138. Some SDR and Cognitive Radio Research at VT <ul><li>SCA core framework </li></ul><ul><ul><li>Open source effort </li></ul></ul><ul><ul><li>Role of DSPs </li></ul></ul><ul><ul><li>Power Management </li></ul></ul><ul><ul><li>Integration of testing into the framework </li></ul></ul><ul><ul><li>Rapid prototyping tools </li></ul></ul><ul><li>Smart antennas </li></ul><ul><ul><li>Smart antenna API </li></ul></ul><ul><ul><li>Networking performance </li></ul></ul><ul><ul><li>Experimental MIMO systems </li></ul></ul><ul><li>Cooperative radios </li></ul><ul><ul><li>Distributed MIMO </li></ul></ul><ul><ul><li>Distributed Applications </li></ul></ul><ul><li>Cognitive radio networks </li></ul><ul><ul><li>Game theory analysis of cognitive networks </li></ul></ul><ul><ul><li>Learning Techniques </li></ul></ul><ul><li>Test Beds </li></ul><ul><ul><li>UWB SDR </li></ul></ul><ul><ul><li>Low Power SCA </li></ul></ul><ul><ul><li>Distributed PCs </li></ul></ul><ul><ul><li>Public Safety Radio Demo </li></ul></ul>Keep up to date at And
  139. 139. CR Test-bed under development Neighbor WLANs Ethernet Actions Cordless Phone Bluetooth MWOL Tektronix TDS694C: Digital Real-time Oscilloscope Tektronix RSA3408A: Real-Time Spectrum Analyzer Distributed Measurement Collaborative Processing Observations Analysis and decision REM online updating TV station
  140. 140. The Future of Cognitive Radio
  141. 141. Comment Slide – Delete Before Submitting Following section presented by Bostian
  142. 142. Public Safety - Interoperability <ul><li>Focus on multi-agency interoperability since 9/11/2001 </li></ul><ul><li>Cognitive radio technology can improve interoperability by enabling devices to bridge communications between jurisdictions using different frequencies and modulation formats. </li></ul><ul><li>Such interoperability is crucial to enabling public safety agencies to do their jobs. </li></ul><ul><li>Example: National Public Safety Telecommunications Council (NPSTC) supported by U.S. DOJ’s AGILE Program </li></ul>
  143. 143. IEEE 802.22 <ul><li>WRAN system based on 802.22 will make use of unused TV broadcast channels </li></ul><ul><li>Interoperable air interface for use in spectrum allocated to TV Broadcast Service </li></ul><ul><li>Allows Point to Multi-point Wireless Regional Area Networks (WRANS) </li></ul><ul><li>Supports a wide range of services </li></ul><ul><ul><li>Data, voice and video </li></ul></ul><ul><ul><li>Residential, Small and Medium Enterprises </li></ul></ul><ul><ul><li>Small Office/Home Office (SOHO) locations </li></ul></ul>
  144. 144. IEEE Project 1900 (P1900) <ul><li>The IEEE P1900 Standards Group was established in 1Q 2005 jointly by the IEEE Communications Society (ComSoc) and the IEEE Electromagnetic Compatibility (EMC) Society . </li></ul><ul><li>The objective of this effort is to develop supporting standards related to new technologies and techniques being developed for next generation radio and advanced spectrum management. </li></ul>
  145. 145. IEEE P1900.1 Working Group : <ul><li>Objective document: “Standard Terms, Definitions and Concepts for Spectrum Management, Policy Defined Radio, Adaptive Radio and Software Defined Radio.” </li></ul><ul><li>Purpose: This document will facilitate the development of these technologies by clarifying the terminology and how these technologies relate to each other. </li></ul>
  146. 146. IEEE P1900.2 Working Group : <ul><li>Objective document: “Recommended Practice for the Analysis of In-Band and Adjacent Band Interference and Coexistence Between Radio Systems.” </li></ul><ul><li>Purpose: T his standard will provide guidance for the analysis of coexistence and interference between various radio services. </li></ul>
  147. 147. IEEE P1900.3 Working Group : <ul><li>Objective document : “Recommended Practice for Conformance Evaluation of Software Defined Radio (SDR) Software Modules.” </li></ul><ul><li>Purpose : This recommended practice will provide guidance for validity analysis of proposed SDR terminal software prior to physical programming and activation of SDR terminal components. </li></ul>
  148. 148. IEEE 802.11h <ul><li>802.11h helps WLANs share spectrum </li></ul><ul><li>How? </li></ul><ul><ul><li>801.11h implements two methods to help spectrum sharing: </li></ul></ul><ul><ul><ul><li>Dynamic Frequency Selection (DFS) </li></ul></ul></ul><ul><ul><ul><li>Transmission Power Control (TPC) </li></ul></ul></ul><ul><ul><li>DFS is used to select the appropriate spectrum for WLAN </li></ul></ul><ul><ul><li>TPC is used to manage WLAN networks and stations for Reduction of interference , Range control (setting borders for WLAN) , and Reduction of power consumption (beneficial in laptop use e.g.) </li></ul></ul>
  149. 149. IEEE 802.15.3a <ul><li>Multiband OFDM for Personal Area Network </li></ul><ul><ul><li>Wireless USB2.0 (480Mbps) at 5 meters distances </li></ul></ul><ul><li>Cognitive Radio - Plausible Application to UWB Regulation </li></ul><ul><ul><li>Very fast spectrum sculpting via OFDM technology with wide bandwidth 528MHz </li></ul></ul><ul><li>QoS Support </li></ul><ul><ul><li>QoS can be supported by controlling the number of sub-carriers </li></ul></ul>
  150. 150. Hurdles in CR <ul><li>FCC Development Policies </li></ul><ul><ul><li>The process and rules governing how frequencies and waveforms are selected and approved for use by cognitive equipment must be addressed. </li></ul></ul><ul><li>Software Flexibility </li></ul><ul><ul><li>Interface with policy updates </li></ul></ul><ul><li>Real-life functionality </li></ul><ul><ul><li>CR devices are smart enough to understand user request and surrounding environments </li></ul></ul><ul><li>Network availability for CR </li></ul><ul><ul><li>Network needs to announce their availability to CR </li></ul></ul><ul><li>Flexible or Reconfigurable Hardware </li></ul><ul><li>Requires a language and protocols for initial interfacing with software and validation for existing devices as policies change across time and space </li></ul><ul><li>Software Architectures </li></ul><ul><ul><li>More dynamic than SCA </li></ul></ul>
  151. 151. 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 user Early cognition Mid-level cognition Cognitive radios 2005 2007 2010 Adaptive spectrum allocation
  152. 152. Just Remember This... <ul><li>“ The best way to predict the future is to invent it.” </li></ul><ul><li> </li></ul><ul><li>Alan Kay, Author </li></ul>
  153. 153. Jeffrey H. Reed <ul><li>Willis G. Worcester Professor of ECE and Deputy Director, Mobile and Portable Radio Research Group (MPRG) </li></ul><ul><li>Authored book, Software Radio: A Modern Approach to Radio Engineering </li></ul><ul><li>IEEE Fellow for Software Radio, Communications Signal Processing and Education </li></ul><ul><li>Industry Achievement Award from the SDR Forum </li></ul><ul><li>Highly published. Co-authored – 2 books, edited – 7 books. </li></ul><ul><li>Previous and Ongoing SDR projects from </li></ul><ul><ul><li>DARPA, Texas Instruments, ONR, Mercury, Samsung, NSF, General Dynamics and Tektronix </li></ul></ul>
  154. 154. Jeffrey H. Reed <ul><li>Contact Information: </li></ul><ul><li>[email_address] </li></ul><ul><li>Electrical and Computer Engineering MPRG 432 Durham Hall Blacksburg, VA 24061 (540) 231-2972 </li></ul>
  155. 155. Charles W. Bostian <ul><li>Alumni Distinguished Professor of ECE and Director, Center for Wireless Telecommunications </li></ul><ul><li>Co-author of John Wiley texts Solid State Radio Engineering and Satellite Communications. </li></ul><ul><li>IEEE Fellow for contributions to and leadership in the understanding of satellite path radio wave propagation. </li></ul><ul><li>Award winning teacher </li></ul><ul><li>Previous and Ongoing CR projects from National Science Foundation, National Institute of Justice </li></ul>
  156. 156. Charles W. Bostian <ul><li>Contact Information: </li></ul><ul><li>[email_address] </li></ul><ul><li>Electrical and Computer Engineering Virginia Tech, Mail Code 0111 Blacksburg, VA 24061-0111 (540) 231-5096 </li></ul>
  157. 157. Backup Slides
  158. 158. Hardware Blocks Software Modules
  159. 159. Example: Simple AM Transmitter (1/2) <ul><li>Building Blocks </li></ul><ul><ul><li>All Blocks are each defined as objects </li></ul></ul>“ Amp” - Gain Stage “ m” - Message Signal “ mix” - Multiplication Stage “ LO” - Local Oscillator “ FIR” - Filter Stage X ~ Amp m FIR
  160. 160. Example: Simple AM Transmitter (2/2) <ul><li>Connecting Building Blocks </li></ul>+ 1 Amp µ X ~ FIR m H/W Interface <ul><li>The arrow is an object that connects the flow graph </li></ul>