Outline Motivation Cognitive Radio Communications What are - - PDF document

Cognitive Radio Communications for Dynamic Spectrum Access

Yao Zheng

1

Outline

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

2

Presentation Overview

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

3

Current Spectrum Allocation

FCC frequency allocations for US radio spectrum

4

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

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Increasing Demand

Source: CTIA 200 Million Subscribers!

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Increasing Demand

Source:CTIA 1.4 Trillion Minutes!

7

Apparent Scarcity

• Measurement studies have shown that in both the time

and frequency domains that spectrum is underutilized

Spectrum measurement across the 900 kHz –1 GHz band (Lawrence, KS, USA) Spectrum Holes

8

Potential Solution

• Dynamic Spectrum Access (DSA)

Spectrum measurement across the 900 kHz –1 GHz band (Lawrence, KS, USA) Fill with secondary users

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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

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Example

• Conclusion: Wireless equipment designed for DSA communications

must be rapidly reconfigurable and spectrum-aware

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Presentation Overview

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

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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

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Software-Defined Radios

Radio functions performed in the software domain

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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.

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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

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Presentation Overview

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

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

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Cognition Framework

Basic schematic of the cognition component of a cognitive radio

19

Reconfigurability

• Given several desired radio requirements, determine best-possible

choices for radio components

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Adaptation in Cognitive Radios

Cognitive adaptation module possessing several knobs and dials

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

22

Example: GA Convergence

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. Converges to an

• verall

fitness score of 0.8

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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.

24

Presentation Overview

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

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

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NC-OFDM Transmission

• Based on conventional orthogonal frequency

division multiplexing (OFDM)

• Uses spectrum sensing measurements to “turn
• ff” potentially interfering subcarriers

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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.

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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.

29

Presentation Overview

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

30

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

31

KUAR Schematic

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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)

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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…

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KUAR System Diagram

System diagram of a KUAR unit (Version 3.0)

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KUAR Transmit Performance

#16 36

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KUAR Receiver Eye Diagram

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Presentation Overview

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

38

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

39

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.

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Additional Slides

41

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

42

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

43

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

44

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)

45

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

46

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)

47

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

48