Cognitive Radio Communications for Dynamic Spectrum Access

1. Cognitive Radio Communications for Dynamic Spectrum Access Slides by: Alexander M. Wyglinski Research Assistant Professor ITTC The University of Kansas alexw@ittc.ku.edu This work was generously supported by the National Science Foundation (NSF), via grants ANI-0230786 and ANI-0335272, and both the Defense Advanced Research Projects Agency (DARPA) and the Department of the Interior National Business Center, via grant NBCHC050166 #161

2. Outline • Motivation • What are Cognitive Radios? • How are they “cognitive”? • Agile Transmission • Kansas University Agile Radio (KUAR) • Conclusion #162

3. Presentation Overview • Motivation • What are Cognitive Radios? • How are they “cognitive”? • Agile Transmission • Kansas University Agile Radio (KUAR) • Conclusion #163

4. Current Spectrum Allocation FCC frequency allocations for US radio spectrum #164

5. Increasing Demand • Rapid growth in the wireless communications sector, requiring more spectral bandwidth • Increasing number of users • Plethora of new wireless services being offered • Some applications are bandwidth-intensive • As a result of this demand, available spectrum under the legacy command-and-control regime is becoming increasingly scarce • Number of licensed transmissions are increasing within a finite allocated bandwidth • Unlicensed users constrained to a few overloaded bands #165

6. Increasing Demand 200 Million Subscribers! Source: CTIA #166

7. Increasing Demand 1.4 Trillion Minutes! Source: CTIA #167

8. Apparent Scarcity • Measurement studies have shown that in both the time and frequency domains that spectrum is underutilized Spectrum Holes Spectrum measurement across the 900 kHz –1 GHz band (Lawrence, KS, USA) #168

9. Potential Solution • Dynamic Spectrum Access (DSA) Fill with secondary users Spectrum measurement across the 900 kHz –1 GHz band (Lawrence, KS, USA) #169

10. But not in my spectrum! • Incumbent license holders are very concerned about co-existing transmissions from unlicensed users • Large-scale investments in developing communication infrastructure around spectrum • Maintain quality-of-service to its paying customers • Unlicensed users providing competing services (e.g., VoIP) but without the large-scale investment • Transmissions are a time-varying phenomena … a signal not interfering at one point in time may do so at another #1610

11. Example • Conclusion: Wireless equipment designed for DSA communications must be rapidly reconfigurable and spectrum-aware #1611

12. Presentation Overview • Motivation • What are Cognitive Radios? • How are they “cognitive”? • Agile Transmission • Kansas University Agile Radio (KUAR) • Conclusion #1612

13. Software-Defined Radios • Rapid evolution of microelectronics over the past several decades • Wireless transceivers are becoming more versatile, powerful, and portable • These advancements have given rise to Software-Defined Radio (SDR) technology • Baseband radio functions can be entirely implemented in digital logic and software #1613

14. Software-Defined Radios Radio functions performed in the software domain #1614

15. What is a Cognitive Radio? • “Cognitive radio is an intelligent wireless communication system that is aware of its surrounding environment (i.e., outside world), and uses the methodology of understanding-by-building to learn from the environment and adapt its internal states to statistical variations in the incoming RF stimuli by making corresponding changes in certain operating parameters (e.g., transmit-power, carrier-frequency, and modulation strategy) in real-time, with two primary objectives in mind: • highly reliable communications whenever and wherever needed; • efficient utilization of the radio spectrum.” S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications”, IEEE J-SAC, Feb. 2005. #1615

16. What is a Cognitive Radio? • An intelligent wireless communications system • Based on SDR technology • Reconfigurable • Agile Functionality • Aware of its environment • RF spectrum occupancy • Network traffic • Transmission quality • Learns from its environment and adapts to new scenarios based on previous experiences #1616

17. Presentation Overview • Motivation • What are Cognitive Radios? • How are they “cognitive”? • Agile Transmission • Kansas University Agile Radio (KUAR) • Conclusion #1617

18. Cognition Framework • Distinction between reconfigurability and adaptability • Reconfigurability • Involves choosing radio building blocks • Choice of blocks lasts for relatively long period of time • Requires “flashing” of programmable logic • Adaptability • Fine-tunes radio operating parameters • Parameter choices last for a short period of time • Does not require “flashing” of programmable logic #1618

19. Cognition Framework Basic schematic of the cognition component of a cognitive radio #1619

20. Reconfigurability • Given several desired radio requirements, determine best-possible choices for radio components #1620

21. Adaptation in Cognitive Radios Cognitive adaptation module possessing several knobs and dials #1621

22. AI-Based Adaptation • Genetic Algorithms (GA) • Biologically-inspired technique used typically for problems with large parameter spaces • Execution time becomes larger as number of operational and environmental parameters grows • Does not require much memory to run; requires long execution time • Expert Systems • Decisions determined offline and stored in radio memory • Decision making time is very fast • Interesting trade-off exists between rule base size and the efficiency of decision #1622

23. Example: GA Convergence Converges to an overall fitness score of 0.8 GA Convergence for a cognitive radio operating in emergency mode T. R. Newman et al., “Cognitive Engine Implementation for Wireless Multicarrier Transceivers”, To appear in the Wiley Wireless Communications and Mobile Computing Journal, 2007. #1623

24. Example: GA Solution Subcarrier channel attenuation, throughput, and transmit power levels T. R. Newman et al., “Cognitive Engine Implementation for Wireless Multicarrier Transceivers”, To appear in the Wiley Wireless Communications and Mobile Computing Journal, 2007. #1624

25. Presentation Overview • Motivation • What are Cognitive Radios? • How are they “cognitive”? • Agile Transmission • Kansas University Agile Radio (KUAR) • Conclusion #1625

26. Transmission Approaches for DSA • Transmission in licensed spectrum classified into three categories • Cooperative Approach • Primary and secondary users coordinate with each other regarding spectrum usage • Underlay Approach • Secondary signals transmitted at very low power spectral density; undetected by primary users • e.g., ultra wideband (UWB) • Overlay Systems • Secondary signals fill in the spectrum unoccupied by primary users #1626

27. NC-OFDM Transmission • Based on conventional orthogonal frequency division multiplexing (OFDM) • Uses spectrum sensing measurements to “turn off” potentially interfering subcarriers #1627

28. FFT-Pruning for NC-OFDM Pruning an FFT employed in an NC-OFDM Transceiver R. Rajbanshi et al., “An Efficient Implementation of NC-OFDM Transceivers for Cognitive Radios”, Proc. CrownCom, June. 2006. #1628

29. Example: FFT Execution Time Mean execution times for a 1024-point FFT R. Rajbanshi et al., “An Efficient Implementation of NC-OFDM Transceivers for Cognitive Radios”, Proc. CrownCom, June. 2006. #1629

30. Presentation Overview • Motivation • What are Cognitive Radios? • How are they “cognitive”? • Agile Transmission • Kansas University Agile Radio (KUAR) • Conclusion #1630

31. KUAR • Programmable, agile radio platform for networking (and other) research • Enabled by support from NSF and DARPA • Flexible foundation for experimental research • Agile platform for research at physical, link, MAC layers • Capability to sense and act across layers • Enables building new network architectures • Evolving into a cognitive radio platform • Provide sufficient computing resources for cognition experiments Front view of a KUAR unit #1631

32. KUAR Team • Principal Investigators • Gary J. Minden, Joseph B. Evans • Investigators • Arvin Agah, James Roberts, Alexander M. Wyglinski • Design Engineers • Leon Searl, Dan DePardo • Graduate Research Assistants • Rakesh Rajbanshi, Qi Chen, Tim Newman, Rory Petty, Ted Weidling, Brett Barker, Jordan Guffey, Dinesh Datla, Levi Pierce, Megan Lehnherr, Brian Cordill #1632

33. KUAR Schematic #1633

34. KUAR RF and Digital Boards • RF Board • Frequency Range: 5.25 – 5.85 GHz (includes UNII and ISM bands) • SW controls Tx Power, Rx Front-end attenuation and IF gain • 30 MHz Baseband Bandwidth • Digital Board • PC employing industry standard COMeXpress form-factor • Pentium-M @ 1.4GHz, 1 GB SDRAM, 6GB CF+ Disk • FPGA: Xilinx Virtex II Pro P30 • FPGA External Memory: 4 Mb SRAM • Dual ADC (14 bits parallel, 105 MSPS) • Dual DAC (16-bits parallel, 160/400 MSPS) #1634

35. KUAR Software/Firmware • PC runs Linux 2.6 kernel • Software measures radio power usage • Radio Net scripts automate multi-radio experiments • KUAR Radio Systems • BPSK with phase and timing recovery • Multi-carrier demo • KUAR VHDL components: • Energy Detector, Digital Sampler, Absolute Value, Clocks, Sin Generators, Control Processor, Bus Utilities, Delay, Register controls, etc… #1635

36. KUAR System Diagram System diagram of a KUAR unit (Version 3.0) #1636

37. KUAR Transmit Performance #1637

38. KUAR Receiver Eye Diagram #1638

39. Presentation Overview • Motivation • What are Cognitive Radios? • How are they “cognitive”? • Agile Transmission • Kansas University Agile Radio (KUAR) • Conclusion #1639

40. Conclusion • DSA approach to spectrum management is a reality • FCC Proposed Rule-Making with respect to TV bands • Cognitive Radios can help us realize DSA networks • Increased spectral efficiency • Enhanced transmission performance • Much work still required before deploying reliable DSA networks • Continue work on developing communication techniques that enable DSA #1640

41. References • S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications”, IEEE Journal on Selected Areas in Communications, Feb. 2005. • William Krenik and Anuj Batra, “Cognitive Radio Techniques from Wide Area Networks”, Proceedings of the 42nd Design Automation Conference, pages 409-412, 2005. • Upcoming May 2007 Issue of the IEEE Communications Magazine (Feature Topic on Cognitive Radios for Dynamic Spectrum Access) • KUAR Wiki: https://agileradio.ittc.ku.edu/ • DARPA XG Website: http://www.darpa.mil/ATO/programs/XG/index.htm • T. R. Newman et al., “Cognitive Engine Implementation for Wireless Multicarrier Transceivers”, To appear in the Wiley Wireless Communications and Mobile Computing Journal, 2007 • R. Rajbanshi et al., “An Efficient Implementation of NC-OFDM Transceivers for Cognitive Radios”, Proc. CrownCom, June. 2006. #1641

42. Additional Slides #1642

43. Current Spectrum Allocation • “Command-and-control” Approach • License holders maintain exclusive rights to their allocated spectrum • Purchased during a spectrum auction, e.g., 3G auctions • Allocated via government decree, e.g., military, television • Unlicensed devices not permitted to transmit in licensed bands • Allocated unlicensed bands (with transmit constraints) • Industrial, Scientific, Medical (ISM) bands • 900 MHz, 1.8 GHz, 2.4 GHz, 5.8 GHz • Unlicensed National Information Infrastructure (UNII) band • 5.15 GHz – 5.825 GHz #1643

44. Spectrum Sensing • Required by agile modulation process • Classification of spectrum into either signal or noise • Recursive One-Sided Hypothesis Testing (ROHT) recursively performs hypothesis test on the measurement data and classifies a portion of data as signal • Otsu’s algorithm segments data into 2 classes to achieve maximum separation between classes • Adaptive thresholding uses a sliding window approach that classifies blocks of data separately and then combine the classification results #1644

45. Channel Sounding • Need to identify spectrum worth transmitting across • Unoccupied spectrum may be severely attenuated • Simultaneously, sounding process cannot interfere with signals from primary users • Sounding a large bandwidth with several primary users requires the power spectral density to be low • Adapt current sounding techniques to DSA scenario • Swept Time Delay Cross-Correlator (STDCC) #1645

46. KUAR RF Board and Antennas • TX and RX Active Antennas • 5.250 - 5.850 GHz, -100 dBm min Rx, +25 dBm max Tx • Independent Tx and Rx antennas & frequencies • RF Board • Frequency Range: 5.25 – 5.85 GHz (includes UNII and ISM bands) • SW controls Tx Power, Rx Front-end attenuation and IF gain • Useful for fading channel experiments • Accommodates variety of experiments and test environments • Superheterodyne Hybrid direct conversion • IF range of 1.85 – 2.45 GHz controlled by SW • Quadrature Direct conversion between baseband and IF • 30 MHz Baseband Bandwidth • Microcontroller converts Digital Board I2C bus to RF device SPI bus, control/status lines #1646

47. KUAR Digital Board • PC in industry standard COMeXpress form-factor • Pentium-M @ 1.4GHz • 1 GB SDRAM • 6GB CF+ Disk • FPGA: Xilinx Virtex II Pro P30 • FPGA External Memory: 4 Mb SRAM • PC<->FPGA Buses: PCI Express / PCI / USB->Parallel • USB controller or PC software programs FPGA • Dual ADC (14 bits parallel, 105 MSPS) • Dual DAC (16-bits parallel, 160/400 MSPS) #1647

48. KUAR Software/Firmware • PC runs Linux 2.6 kernel • FPGA firmware registers addressable as PCI registers • Software measures radio power usage • Radio Net scripts automate multi-radio experiments • KUAR Radio Systems • BPSK with phase and timing recovery LFR-QPSK • Multi-carrier Demo • KUAR VHDL components: • Energy Detector, Digital Sampler, Absolute Value, Clocks, Sin Generators, Control Processor, Bus Utilities, Delay, Register controls, etc… • RF board configuration through RFControl API #1648