Cognitive Radio Communications for Dynamic Spectrum Accessfrost/Access_Technologies_Course/... ·...

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Cognitive Radio Communications for Dynamic

Spectrum AccessSlides based on set provided by

Alexander M. WyglinskiResearch Assistant Professor

ITTCThe University of Kansas

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

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Outline

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

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Presentation Overview


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Current Spectrum Allocation

FCC frequency allocations for US radio spectrum

Command-and-control regulation

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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!

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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

White Space:just ambient noise

Black Space:occupied byhigh-power users

Grey Space:partially occupied

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Potential Solution

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

• Dynamic Spectrum Access (DSA)

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

– Consider all the adaptive mechanisms in:• HSDPA/HSUPA• EV-DO• IEEE 802.16

• Trust– Validation that cognitive radios provide real benefits– Confidence that cognitive radios will not interfere with legacy

users

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Example

• Conclusion: Wireless equipment designed for DSA communications must be rapidly reconfigurable and spectrum-aware

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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

• SDR’s are a prerequisite for Cognitive Radio

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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 onprevious experiences

• Access techniques are – Distributed, e.g., like in ad hoc networks.– Cooperative

• Shared resources– Interference temperature (interference at the receiver)– Spectrum holes

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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

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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

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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

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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 overall 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.

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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 off” 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.

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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

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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

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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, DineshDatla, Levi Pierce, Megan Lehnherr, Brian Cordill

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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

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KUAR Receiver Eye Diagram

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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

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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

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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

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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

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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)

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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

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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)

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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

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