Alex Wyglinski - IEEE VTS UKRI - Cognitive radio - a panacea for RF spectrum scarcity

COGNITIVE RADIO:

A PANACEA FOR

RF SPECTRUM SCARCITY

Professor Alexander M. Wyglinski Worcester Polytechnic Institute

2

Cognitive Radio: A Panacea for RF Spectrum Scarcity

Presentation Outline

The Information Age

Wireless Spectrum Characterization

Spectrally Agile Waveform Design

Security Issues in Wireless Spectrum

Concluding Remarks

The Information Age

4


Several Key Innovators

Marconi Shannon Shockley Bardeen Brattain

Wireless

Transmission

Digital

Communications Transistors

Source: Wikipedia

5


Progress of Technology

6


Evolution of Wireless Systems

“Cog

nitive

Radio

Com

mun

ications

and

Net

work

s: P

rinc

iple

s and

Pra

ctic

e”

By A

. M

. W

yg

linsk

i, M

. N

eko

vee, Y

. T.

Hou

(Els

evi

er,

Dece

mb

er

20

09

)

7


Software-Defined Radio Anatomy

PROGRAMMABLE TUNABLE

8


Sample SDR Platforms

Universal Software Radio Peripheral 2 (USRP2) Unit. COSMIAC FPGA board currently being retrofitted for

better memory access, to add USB functionality and

to make the board SPA compatible.

9


Mitola & Cognitive Radio

Joseph Mitola III

10


Cognitive Radio: A Black Box Model

What you want

What you see

What you can do

What you

can tune

11


Flexible RF Front Ends Needed

88 MHz

5.8 GHz

Can I do this

with just one

RF front end?

12


RF MEMS Can Help!

A single RF front end

would not normally be

able to support a very

wide frequency range

of operations

Radio Frequency Micro-

Electro-Mechanical

Systems (RF MEMS) can

be used to “tune” the RF

front end to the

corresponding frequency Source: Wireless ICs and MEMS Laboratory,

McGill University

Close-Up of MEMS Tunable LC Filter.

Capacitor

Inductor

13


RF MEMS

RF MEMS can be used to implement:

Antennas (e.g., fractal antennas)

Filters (e.g., tunable RF bandpass filters)

Oscillators

Real-time operations very difficult to support

Time needed to physically change configurations on the

order of seconds

Compared to the rate at which data is transmitted, this is

considered to be ages!

Spectrum Characterization

15


Electromagnetic Spectrum

What do you think of when you hear the word

“spectrum”?

16


Electromagnetic Spectrum

Electromagnetic spectrum is the medium upon which wireless

communications is realized

Only portions of spectrum are suitable for mobile

communications

3-30 Hz

Extremely low frequency (ELF)

30-300 GHz

Extremely high frequency (EHF)

Not desirable: low bandwidth, long propagation range

Not desirable: short propagation range, line-of-sight communication

30-3000 MHz

Desirable: High bandwidth, reasonable propagation range

Radio Frequency range

17


How Do You Measure Spectrum?

“Cog

nitive

Radio

Com

mun

ications

and

Net

work

s: P

rinc

iple

s and

Pra

ctic

e”

By A

. M

. W

yg

linsk

i, M

. N

eko

vee, Y

. T.

Hou

(Els

evi

er,

Dece

mb

er

20

09

)

Radio Car – circa 1927 (photo courtesy of the Institute for Telecommunications Science (ITS),

NTIA, U.S. Dept. of Commerce)

18



WPI Wireless Innovation Laboratory NSF-sponsored Measurement Campaign – Summer 2008

19



SQUIRRELWeb online

spectrum measurement

portal

Queue-driven spectrum

observatory

Collects specific spectrum

measurements upon user

request

Available at: http://www.spectrum.wpi.edu

20



A map of the forty eight locations close to I-90 between Boston, MA

and West Stockbridge, MA over which the Toyota-sponsored

measurement campaign was conducted in June 2009.

21


How Much Spectrum Is There?

Spectrum occupancy characteristics in the four mid-size US cities visited during June 2008

NSF-sponsored measurement campaign.

22


From A Vehicular Perspective

Energy Spectral Density plots for the TV frequencies in the frequency range, 600 – 750 MHz over

550 time sweeps close on I-90 between Boston, MA and West Stockbridge, MA. The measurement

setup was located in a vehicle moving at an average velocity of 60 miles/hr.

S. Pa

ga

da

rai, A

. M

. W

yg

linsk

i, a

nd R

. V

uyyur

u. “

Cha

ract

eri

zation

of

Va

cant

UH

F TV

Cha

nnels

for

Vehi

cula

r D

yna

mic

Sp

ect

rum

Acc

ess

.” P

roce

ed

ing

s of

the

Firs

t IE

EE V

ehi

cula

r N

etw

ork

ing

Conf

ere

nce (To

kyo, Ja

pa

n), O

ctob

er

20

09

.

23


Total Available Bandwidth

The total available bandwidth for secondary usage at different locations along I-90. S. Pa

ga

da

rai, A

. M

. W

yg

linsk

i, a

nd R

. V

uyyur

u. “

Cha

ract

eri

zation

of

Va

cant

UH

F TV

Cha

nnels

for

Vehi

cula

r D

yna

mic

Sp

ect

rum

Acc

ess

.” P

roce

ed

ing

s of

the

Firs

t IE

EE V

ehi

cula

r N

etw

ork

ing

Conf

ere

nce (To

kyo, Ja

pa

n), O

ctob

er

20

09

.

24


Spectral Opportunity Analysis

Maximum contiguous bandwidth and the number of non-contiguous channel blocks at different

locations along I-90. S. Pa

ga

da

rai, A

. M

. W

yg

linsk

i, a

nd R

. V

uyyur

u. “

Cha

ract

eri

zation

of

Va

cant

UH

F TV

Cha

nnels

for

Vehi

cula

r D

yna

mic

Sp

ect

rum

Acc

ess

.” P

roce

ed

ing

s of

the

Firs

t IE

EE V

ehi

cula

r N

etw

ork

ing

Conf

ere

nce (To

kyo, Ja

pa

n), O

ctob

er

20

09

.

Spectrally Agile Waveforms

26


Opportunistic Spectrum Access

Opportunistic spectrum access (OSA) is a significant

paradigm shift in the way wireless spectrum is

accessed

Instead of PUs possessing exclusive access to licensed

spectrum, SUs can temporarily borrow unoccupied

frequency bands

SUs must respect the incumbent rights of the PUs with

respect to their licensed spectrum

OSA enables greater spectral efficiency and

facilitates greater user and bandwidth capacity

27


The utilization efficiency of “prime” wireless spectrum

has been shown to be poor

A snapshot of PSD from 88 MHz to 2686 MHz measured on July 11th 2008 in Worcester, MA (N42o16.36602, W71o48.46548)

OSA Motivation

A. M. Wyglinski, M. Nekovee, Y. T. Hou (Eds.). “Cognitive Radio Communications and Networks: Principles and Practice.” (Chapter 6) Academic Press, December 2009.

empty empty empty empty

28


Leveraging the Electrospace

Several dimensions of

the electrospace include

space, time, and

frequency, although

there do exist others

such as code,

polarization, and

directional.

“Cog

nitive

Radio

Com

mun

ications

and

Net

work

s: P

rinc

iple

s and

Pra

ctic

e”

By A

. M

. W

yg

linsk

i, M

. N

eko

vee, Y

. T.

Hou

(Els

evi

er,

Dece

mb

er

20

09

)

29


Several Possible Approaches

• Secondary transmission in licensed spectrum can be

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

30


Spectral Opportunities!



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31


Underlay Solution



underlay transmissions

32


Overlay Solution



overlay transmissions

33


Multicarrier Transmission Techniques for

Spectrally Opportunistic Communications

Multicarrier modulation is a variant of the

conventional frequency division multiplexing (FDM)

Orthogonal Frequency Division Multiplexing (OFDM)

an efficient form of multicarrier modulation

In order to utilize unused portions of licensed

spectrum, several subcarriers can be turned OFF to

avoid interfering with the primary signals

Each subcarrier experiences flat-fading and hence

high data-rates are possible if several unused bands

of secondary spectrum are available

34


Multicarrier Overlay Solution



multicarrier overlay transmissions

35


Spectral Agility In Action!

PU signal!

multicarrier overlay SU

transmission wraps around PU

As seen in this close-up of

the multicarrier overlay

transmission, subcarriers

located within the vicinity

of a PU can be

deactivated in order to

avoid interference with

that signal.

36


Spectrally Agile Multicarrier

H. Bog

ucka

, A

. M

. W

yg

linsk

i, S. Pa

ga

da

rai, A

. K

liks.

“Sp

ect

rally

Ag

ile M

ultica

rrie

r

Wa

vefo

rms

for

Op

port

unis

tic

Wir

ele

ss A

ccess

”. IEE

E C

om

mun

ica

tions

Ma

ga

zine

,

June

20

11

.

37


Major Issue: Out-of-band Emission

Out-of-band (OOB) interference problem with OFDM-based

cognitive radios

Power spectral density of the transmit signal over one

subcarrier:

Mean relative interference to a neighboring legacy system

subband:

38


Sinc Pulses Have High OOB Levels!

39


Several Solutions

Cancellation Carriers

Non-data bearing subcarriers whose phase and

amplitude values cancel OOB

Modulated Filter Banks

Attenuates OOB in stopband region

Combine cancellation carriers (CCs) with modulated

filter banks (MFBs) to attenuate OOB emissions

40


Cancellation Carriers

41


Filtering with CCs

42


Hardware Experimentation

Photograph of a spectrally agile wireless transceiver test-bed at Poznan University of Technology,

Poznan, Poland.

Photograph of a spectrally agile wireless transceiver test-bed at Worcester Polytechnic Institute,

Worcester, MA, USA.

43


Spectrally Agile Waveform Results

H. Bog

ucka

, A

. M

. W

yg

linsk

i, S. Pa

ga

da

rai, A

. K

liks.

“Sp

ect

rally

Ag

ile M

ultica

rrie

r

Wa

vefo

rms

for

Op

port

unis

tic

Wir

ele

ss A

ccess

”. IEE

E C

om

mun

ica

tions

Ma

ga

zine

,

June

20

11

.

44


Spectrally Agile Waveform Results

P. K

rysz

kiew

icz,

H. Bog

ucka

, A

. M

. W

yg

linsk

i. "P

rote

ctio

n of

Pri

ma

ry U

sers

in

Dyna

mic

ally

Va

ryin

g R

ad

io E

nvir

onm

ent

: Pra

ctic

al Solu

tions

and

Cha

lleng

es.

"

Acc

ep

ted

for

pub

lica

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in the

EU

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SIP

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Wir

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ss C

om

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Netw

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, D

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, 2

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1.

Security Issues

46


Motivation

Primary User Emulation (PUE) is a serious threat to

opportunistic spectrum access networks

Malicious secondary users can mimic spectral

characteristics of primary users to gain priority

access to wireless channels

Primary (licensed) users have the priority of using the

channel

All the secondary users have equal opportunity to use

the channel

47


An Example

frequency

I’m a

PU!

I’m a

PU!

I’m a

PU!

I’m a

PU, too!

Get out

of my

way!

48


Current Detection Techniques

Conventional techniques on their own are not

entirely up to the job!!

Simple energy detector

Significant probability of missed detection

Matched filter detector

Requires specialized hardware and software

Localization based detector

Can only be employed for stationary primary transmitters

with known coordinates

49


One Approach

Combine several techniques in order to detect the

presence of wireless signals as well as to classify

them:

Energy detection

Cyclostationary feature detection

Artificial neural network

Multilayer perceptron (MLP) employed

50


“Fingerprinting” Wireless Signals

Spectral coherence function of QPSK signal in an

AWGN channel at 10 dB SNR.

Spectral coherence function of 4FSK signal in an

AWGN channel at 10 dB SNR.

51


Simulation Results

The detection performance with and without the reliability check. The x-axis

represents SNR value, and the y-axis represents the percentage of correct detection.

Di Pu,

Yua

n Shi

, A

ndre

i Ily

ash

enk

o, A

lexa

nder

M. W

yg

linsk

i. "D

ete

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g P

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ary

Use

r Em

ula

tion

Atta

cks

in C

og

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s."

Pro

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the IEE

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), N

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.

52


Experimental Results

Proposed Approach

With Check 98.3%

Without Check 91.5%

The percentage of correct detection with the hardware implementation

Di Pu, Yuan Shi, Andrei Ilyashenko, Alexander M. Wyglinski. "Detecting Primary

User Emulation Attacks in Cognitive Radio Networks." Proceedings of the IEEE

Global Telecommunications Conference (Houston, TX, USA), November 2011.

53


Additional Enhancements

Action Recognition Techniques

Often employed in image and video processing

applications, action recognition can also be applied to

spectrum measurements

Consists of several parameters:

Feature Vector Construction

Covariance Descriptor of Feature Vectors

Log-covariance Descriptor of Feature Vectors

Concluding Remarks

55


These Are Interesting Times!

Numerous advances in cognitive radio, dynamic

spectrum access, and software-defined radio have

recently occurred

Secondary access of digital TV spectrum

Ratification of IEEE 802.22, IEEE 802.11af standards

Today’s wireless landscape is quickly changing due

to new capabilities of wireless transceiver devices

Largely due to smaller, faster processing devices

resulting from applications such as smart phones

56


Still Room For Improvement

There still exists a substantial amount of research

that is needed to make future wireless devices such

as cognitive radio more reliable

Ensuring minimal interference to other wireless

transmissions

Enabling real-time decision-making and transmission

operations

Making RF spectrum access more reliable for everyone

involved

More Information

58


Contact Info

Professor Alexander Wyglinski

Department of Electrical and Computer Engineering

Worcester Polytechnic Institute

Atwater Kent Laboratories, Room AK230

508-831-5061

[email protected]

http://www.wireless.wpi.edu/

59


Cognitive Radio Textbook

Available since December 2009 (Academic Press)

20 chapters

End-of-chapter problems (with solutions guide)

Presentation slides for most chapters

Covers physical and network layers, in addition to current platforms and standards

http://www.wireless.wpi.edu/?page_id=29

60


Software-Defined Radio Textbook

Anticipated publication: Q1

2013 (Artech House Publishers)

10 comprehensive chapters

Fundamentals in signals & systems,

probability, and digital

communications

“Hands on” approach to learning

digital communication concepts

using SDR and Simulink

End-of-chapter problems

Corresponding course lecture slides

61


References

Alexander M. Wyglinski, Maziar Nekovee, Y. Thomas Hou. Cognitive Radio Communications and Networks: Principles and

Practice, Academic Press, December 2009.

Pawel Kryszkiewicz, Hanna Bogucka, Alexander M. Wyglinski. "Protection of Primary Users in Dynamically Varying Radio

Environment: Practical Solutions and Challenges." Accepted for publication in the EURASIP Journal on Wireless Communications

and Networking, December 23, 2011.

Si Chen, Srikanth Pagadarai, Rama Vuyyuru, Alexander M. Wyglinski, Onur Altintas. “Feasibility Analysis of Vehicular Dynamic

Spectrum Access via Queueing Theory Model.” IEEE Communications Magazine, November 2011.

Srikanth Pagadarai, Adrian Kliks, Hanna Bogucka, Alexander M. Wyglinski. “Non-contiguous Multicarrier Waveforms in

Practical Opportunistic Wireless Systems.” IET Radar, Sonar, and Navigation Journal, vol. 5, no. 6, pp. 674-680, July 2011.

Hanna Bogucka, Alexander M. Wyglinski, Srikanth Pagadarai, Adrian Kliks. “Spectrally Agile Multicarrier Waveforms for

Opportunistic Wireless Access”. IEEE Communications Magazine, June 2011.

Srikanth Pagadarai, Alexander M. Wyglinski. “A Linear Mixed Effects Model of Wireless Spectrum Occupancy.” EURASIP

Journal on Wireless Communications and Networking, August 2010.

Zhou Yuan, Alexander M. Wyglinski. “On Sidelobe Suppression for Multicarrier-Based Cognitive Radio Transceivers.” IEEE

Transactions on Vehicular Technology, May 2010.

Chittabrata Ghosh, Srikanth Pagadarai, Dharma P. Agrawal, Alexander M. Wyglinski. “A Framework for Statistical Wireless

Spectrum Occupancy Modeling.” IEEE Transactions on Wireless Communications, Vol. 9, No. 1, Pages 38-44, January 2010.

Timothy Newman, Daniel DePardo, Alexander Wyglinski, Joseph B. Evans, Rakesh Rajbanshi, Victor R. Petty, Dinesh Datla,

Frederick Weidling, Paul Kolodzy, Michael Marcus, Gary J. Minden, James Roberts. “Measurements and Analysis of Secondary

User Device Effects on Digital Television Receivers.” EURASIP Journal on Advances in Signal Processing – Special Issue on

“Dynamic Spectrum Access for Wireless Networking”, August 2009.

62


References

Alexander M. Wyglinski. “Changing the Way Wireless Technology Accesses Electromagnetic Spectrum.” EEWeb Pulse

Magazine, Issue 14, 4 October 2011. [ONLINE]: http://www.eeweb.com/pulse/issue-14-2011

Si Chen, Rama Vuyyuru, Onur Altintas, Alexander M. Wyglinski. “Learning in Vehicular Dynamic Spectrum Access Networks:

Opportunities and Challenges.” Proceedings of the International Symposium on Intelligent Signal Processing and

Communication Systems, (Chiang Mai, Thailand), December 2011.

Di Pu, Yuan Shi, Andrei Ilyashenko, Alexander M. Wyglinski. "Detecting Primary User Emulation Attacks in Cognitive Radio

Networks." Proceedings of the IEEE Global Telecommunications Conference (Houston, TX, USA), November 2011.

Si Chen, Rama Vuyyuru, Onur Altintas, Alexander M. Wyglinski. “On Optimizing Vehicular Dynamic Spectrum Access Networks:

Automation and Learning in Mobile Wireless Environments.” Proceedings of the IEEE Vehicular Network Conference

(Amsterdam, The Netherlands), November 2011.

Tayyar Rzayev, Yuan Shi, Anastasios Vafeiadis, Srikanth Pagadarai, Alexander M. Wyglinski. “Implementation of a Vehicular

Networking Architecture Supporting Dynamic Spectrum Access.” Proceedings of the IEEE Vehicular Network Conference

(Amsterdam, The Netherlands), November 2011.

Onur Altintas, Mitsuhiro Nishibori, Takuro Oshida, Yutaka Ihara, Masahiro Saito, Chikara Yoshimura, Youhei Fujii, Kota Nishida,

Kazuya Tsukamoto, Masato Tsuru, Yuji Oie, Rama Vuyyuru, Abdulrahman Al Abbasi, Masaaki Ohtake, Mai Ohta, Takeo Fujii, Si

Chen, Srikanth Pagadarai, Alexander M. Wyglinski. "Demonstration of Vehicle to Vehicle Communications over TV White

Space." Proceedings of the 4th International Symposium on Wireless Vehicular Communications (San Franscisco, CA, USA),

September 2011.

Sean Rocke, Alexander M. Wyglinski. “Geo-Statistical Analysis of Wireless Spectrum Occupancy using Extreme Value Theory.”

Proceedings of the 2011 IEEE Pacific Rim Conference on Communications, Computers, and Signal Processing (Victoria, BC,

Canada), August 2011.

http://www.eeweb.com/pulse/issue-14-2011






63


References

Di Pu, Alexander M. Wyglinski. “Primary User Emulation Detection Using Frequency Domain Action Recognition.” Proceedings

of the 2011 IEEE Pacific Rim Conference on Communications, Computers, and Signal Processing (Victoria, BC, Canada), August

2011.

Si Chen, Alexander M. Wyglinski, Rama Vuyyuru, Onur Altintas. “Feasibility Analysis of Vehicular Dynamic Spectrum Access

Via Queueing Theory Model”. Proceedings of the IEEE Vehicular Networking Conference (Jersey City, NJ, USA), Dec. 2010.

Srikanth Pagadarai, Adrian Kliks, Hanna Bogucka, Alexander M. Wyglinski. “On Non-contiguous Multicarrier Waveforms for

Spectrally Opportunistic Cognitive Radio Systems”. Proceedings of the 5th International Waveform Diversity and Design

Conference (Niagara Falls, ON, Canada), August 2010.

Srikanth Pagadarai, Alexander M. Wyglinski, and Rama Vuyyuru. “Characterization of Vacant UHF TV Channels for Vehicular

Dynamic Spectrum Access.” Proceedings of the First IEEE Vehicular Networking Conference (Tokyo, Japan), October 2009.

Zhou Yuan, Srikanth Pagadarai, Alexander M. Wyglinski. “Feasibility of NC-OFDM Transmission in Dynamic Spectrum Access

Networks.” Proceedings of the 2009 Military Communications Conference (Boston, MA, USA), October 18, 2009.

Zhou Yuan and Alexander M. Wyglinski. “Cognitive Radio-Based OFDM Sidelobe Suppression Employing Modulated Filter

Banks and Cancellation Carriers.” Proceedings of the 2009 Military Communications Conference (Boston, MA, USA), October

18, 2009.

Chittabrata Ghosh, Srikanth Pagadarai, Dharma P. Agarwal, and Alexander M. Wyglinski. “Queuing Theory Representation

and Modeling of Spectrum Occupancy Employing Radio Frequency Measurements.” Proceedings of the IEEE Vehicular

Technology Conference (Anchorage, AK, USA), September 20, 2009.

Srikanth Pagadarai and Alexander M. Wyglinski. “A Quantitative Assessment of Wireless Spectrum Measurements for

Dynamic Spectrum Access.” Proceedings of the International Conference on Cognitive Radio Oriented Wireless Networks and

Communications (Hannover, Germany), June 22, 2009.

64


References

Zhou Yuan, Srikanth Pagadarai, and Alexander M. Wyglinski. “Sidelobe Suppression of OFDM Transmissions using Genetic

Algorithm Optimization.” Proceedings of the IEEE Military Communications Conference (San Diego, CA, USA), November 2008.

Srikanth Pagadarai and Alexander M. Wyglinski. “A Sub-optimal Sidelobe Suppression Technique for OFDM-based Cognitive

Radios.” Proceedings of the IEEE Military Communications Conference (San Diego, CA, USA), November 2008.

Srikanth Pagadarai and Alexander M. Wyglinski. “Novel Sidelobe Suppression Technique for OFDM-Based Cognitive Radio

Transmission.” Proceedings of the IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (Chicago, IL, USA),

October 2008.

Srikanth Pagadarai, Rakesh Rajbanshi, Alexander M. Wyglinski, and Gary J. Minden. “Sidelobe Suppression for OFDM-Based

Cognitive Radios Using Constellation Expansion.” Proceedings of the IEEE Wireless Communications and Networking

Conference (Las Vegas, NV, USA), April 2008.

Dinesh Datla, Alexander M. Wyglinski, and Gary J. Minden. “A Statistical Approach to Spectrum Measurement Processing.”

Proceedings of the 2007 Virginia Tech Symposium on Wireless Personal Communications (Blacksburg, VA, USA), June 2007.

Rakesh Rajbanshi, Victor R. Petty, Dinesh Datla, Frederick Weidling, Daniel DePardo, Paul J. Kolodzy, Michael. J. Marcus,

Alexander M. Wyglinski, Joseph B. Evans, Gary J. Minden, and James A. Roberts. “Feasibility Study of Dynamic Spectrum

Access in Underutilized Television Bands.” Proceedings of the Second IEEE Symposium on New Frontiers in Dynamic Spectrum

Access Networks (Dublin, Ireland), April 2007.

Rakesh Rajbanshi, Qi Chen, Alexander M. Wyglinski, Gary J. Minden, and Joseph B. Evans. “Quantitative Comparison of Agile

Modulation Techniques for Cognitive Radio Transceivers.” Proceedings of the IEEE Consumer Communications and Networking

Conference – Workshop on Cognitive Radio Networks (Las Vegas, NV, USA), January 2007.

Rakesh Rajbanshi, Qi Chen, Alexander M. Wyglinski, Joseph B. Evans, and Gary J. Minden. “Comparative Study of Frequency

Agile Data Transmission Schemes for Cognitive Radio Transceivers.” Proceedings of the First International Workshop on

Technology and Policy for Accessing Spectrum (Boston, MA, USA), July 2006.

Thank You!

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