Cognitive Radio Communications for Dynamic Spectrum Access. Outline

Transcription

1 Cognitive Radio Communications for Dynamic Spectrum Access Slides based on set provided by Alexander M. Wyglinski Research Assistant Professor ITTC The University of Kansas This work was generously supported by the National Science Foundation (NSF), via grants ANI and ANI , and both the Defense Advanced Research Projects Agency (DARPA) and the Department of the Interior National Business Center, via grant NBCHC #16 1 Outline Motivation What are Cognitive Radios? How are they cognitive? Agile Transmission Kansas University Agile Radio (KUAR) Conclusion #16 2

2 Presentation Overview Motivation What are Cognitive Radios? How are they cognitive? Agile Transmission Kansas University Agile Radio (KUAR) Conclusion #16 3 Current Spectrum Allocation Command-and-control regulation FCC frequency allocations for US radio spectrum #16 4

3 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 #16 5 Increasing Demand 200 Million Subscribers! Source: CTIA #16 6

4 Increasing Demand 1.4 Trillion Minutes! Source: CTIA #16 7 Apparent Scarcity Measurement studies have shown that in both the time and frequency domains that spectrum is underutilized White Space: just ambient noise Spectrum Holes Black Space: occupied by high-power users Grey Space: partially occupied Spectrum measurement across the 900 khz 1 GHz band (Lawrence, KS, USA) #16 8

5 Potential Solution Dynamic Spectrum Access (DSA) Fill with secondary users Spectrum measurement across the 900 khz 1 GHz band (Lawrence, KS, USA) #16 9 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 Consider all the adaptive mechanisms in: HSDPA/HSUPA EV-DO IEEE Trust Validation that cognitive radios provide real benefits Confidence that cognitive radios will not interfere with legacy users #16 10

6 Example Conclusion: Wireless equipment designed for DSA communications must be rapidly reconfigurable and spectrum-aware #16 11 Presentation Overview Motivation What are Cognitive Radios? How are they cognitive? Agile Transmission Kansas University Agile Radio (KUAR) Conclusion #16 12

7 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 SDR s are a prerequisite for Cognitive Radio #16 13 Software-Defined Radios Radio functions performed in the software domain #16 14

8 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 realtime, 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 #16 15 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 Access techniques are Distributed, e.g., like in ad hoc networks. Cooperative Shared resources Interference temperature (interference at the receiver) Spectrum holes #16 16

9 Presentation Overview Motivation What are Cognitive Radios? How are they cognitive? Agile Transmission Kansas University Agile Radio (KUAR) Conclusion #16 17 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 #16 18

10 Cognition Framework Basic schematic of the cognition component of a cognitive radio #16 19 Reconfigurability Given several desired radio requirements, determine bestpossible choices for radio components #16 20

11 Adaptation in Cognitive Radios Cognitive adaptation module possessing several knobs and dials #16 21 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 #16 22

12 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, #16 23 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, #16 24

13 Presentation Overview Motivation What are Cognitive Radios? How are they cognitive? Agile Transmission Kansas University Agile Radio (KUAR) Conclusion #16 25 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 #16 26

14 NC-OFDM Transmission Based on conventional orthogonal frequency division multiplexing (OFDM) Uses spectrum sensing measurements to turn off potentially interfering subcarriers #16 27 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 #16 28

15 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 #16 29 Required functions for Cognitive Radios Radio scene analysis Spectral estimation, Finding the white spaces/spectral holes Determining the channel conditions Interference temperature Worst case RF environment in a specific band at a specific location for the receiver to operate satisfactorily Transmit power control Dynamic spectrum management, what to do with the finding white spaces/spectral holes Possibility of emergent behavior #16 30

16 Presentation Overview Motivation What are Cognitive Radios? How are they cognitive? Agile Transmission Kansas University Agile Radio (KUAR) Conclusion #16 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 #16 32

17 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 #16 33 KUAR Schematic #16 34

18 KUAR RF and Digital Boards RF Board Frequency Range: 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 formfactor 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) #16 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 #16 36

19 KUAR System Diagram System diagram of a KUAR unit (Version 3.0) #16 37 KUAR Transmit Performance #16 38

20 KUAR Receiver Eye Diagram #16 39 Presentation Overview Motivation What are Cognitive Radios? How are they cognitive? Agile Transmission Kansas University Agile Radio (KUAR) Conclusion #16 40

21 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 #16 41 References S. Haykin, Cognitive Radio: Brain-Empowered Wireless Communications, IEEE Journal on Selected Areas in Communications, Feb William Krenik and Anuj Batra, Cognitive Radio Techniques from Wide Area Networks, Proceedings of the 42 nd Design Automation Conference, pages , Upcoming May 2007 Issue of the IEEE Communications Magazine (Feature Topic on Cognitive Radios for Dynamic Spectrum Access) KUAR Wiki: DARPA XG Website: 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 #16 42

22 Additional Slides #16 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 GHz #16 44

23 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 #16 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) #16 46

24 KUAR RF Board and Antennas TX and RX Active Antennas GHz, -100 dbm min Rx, +25 dbm max Tx Independent Tx and Rx antennas & frequencies RF Board Frequency Range: 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 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 #16 47 KUAR Digital Board PC in industry standard COMeXpress form-factor 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) #16 48

25 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 #16 49