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

Presentation Outline
2

 The Information Age
 Wireless Spectrum Characterization
 Spectrally Agile Waveform Design
 Security Issues in Wireless Spectrum
 Concluding Remarks

Cognitive Radio: A Panacea for RF Spectrum Scarcity

Several Key Innovators
4

Marconi Shannon Bardeen Brattain Shockley

Wireless Digital Transistors
Transmission Communications
Source: Wikipedia


Progress of Technology
5


6

Evolution of Wireless Systems

“Cognitive Radio Communications and Networks: Principles and Practice”
By A. M. Wyglinski, M. Nekovee, Y. T. Hou (Elsevier, December 2009)

Software-Defined Radio Anatomy
7

PROGRAMMABLE TUNABLE


Sample SDR Platforms
8

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.


Mitola & Cognitive Radio
9

Joseph Mitola III


Cognitive Radio: A Black Box Model
10

What you want
What you see

What you can do

What you
can tune


Flexible RF Front Ends Needed
11

Can I do this
88 MHz

with just one
5.8 GHz

RF front end?


RF MEMS Can Help!
12

 A single RF front end
would not normally be
able to support a very Capacitor
wide frequency range Inductor

of operations
 Radio Frequency Micro-
Electro-Mechanical
Systems (RF MEMS) can
be used to “tune” the RF
Close-Up of MEMS Tunable LC Filter.
front end to the
corresponding frequency Source: Wireless ICs and MEMS Laboratory,
McGill University


RF MEMS
13

 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!


Electromagnetic Spectrum
15

 What do you think of when you hear the word
“spectrum”?


Electromagnetic Spectrum
16

 Electromagnetic spectrum is the medium upon which wireless
communications is realized
 Only portions of spectrum are suitable for mobile
communications
Radio Frequency range

3-30 Hz 30-3000 MHz 30-300 GHz
Extremely low Desirable: High bandwidth, Extremely high
frequency (ELF) reasonable propagation frequency (EHF)
range
Not desirable: low Not desirable: short
bandwidth, long propagation range, line-
propagation range of-sight communication


How Do You Measure Spectrum?
17

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.


How Much Spectrum Is There?
21

Spectrum occupancy characteristics in the four mid-size US cities visited during June 2008
NSF-sponsored measurement campaign.

From A Vehicular Perspective
22

UHF TV Channels for Vehicular Dynamic Spectrum Access.” Proceedings of the
S. Pagadarai, A. M. Wyglinski, and R. Vuyyuru. “Characterization of Vacant

First IEEE Vehicular Networking Conference (Tokyo, Japan), October 2009.
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.


23

Total Available Bandwidth

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


24

locations along I-90.
Spectral Opportunity Analysis

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


Opportunistic Spectrum Access
26

 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

OSA Motivation
27

 The utilization efficiency of “prime” wireless spectrum
has been shown to be poor

empty empty empty empty

A snapshot of PSD from 88 MHz to 2686 MHz measured on July 11th 2008 in Worcester, MA (N42o16.36602,
W71o48.46548)
A. M. Wyglinski, M. Nekovee, Y. T. Hou (Eds.). “Cognitive Radio Communications and Networks: Principles and Practice.” (Chapter 6) Academic Press, December 2009.


Leveraging the Electrospace
28

Several dimensions of
the electrospace include
space, time, and
frequency, although
there do exist others
such as code,
polarization, and
directional.


Several Possible Approaches
29

• 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


Spectral Opportunities!
30

empty empty empty empty

W71o48.46548)



Underlay Solution
31
underlay transmissions

W71o48.46548)



Overlay Solution
32
overlay transmissions

W71o48.46548)



Multicarrier Transmission Techniques for
Spectrally Opportunistic Communications
33

 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

Multicarrier Overlay Solution
34
multicarrier overlay transmissions

W71o48.46548)



Spectral Agility In Action!
35

PU signal!

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 multicarrier overlay SU
that signal. transmission wraps around PU


36

Spectrally Agile Multicarrier

H. Bogucka, A. M. Wyglinski, S. Pagadarai, A. Kliks. “Spectrally Agile Multicarrier
Waveforms for Opportunistic Wireless Access”. IEEE Communications Magazine,
June 2011.

Major Issue: Out-of-band Emission
37

 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:


Sinc Pulses Have High OOB Levels!
38


Several Solutions
39

 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


Cancellation Carriers
40


Filtering with CCs
41


Hardware Experimentation
42

Photograph of a spectrally agile wireless transceiver Photograph of a spectrally agile wireless transceiver
test-bed at Poznan University of Technology, test-bed at Worcester Polytechnic Institute,
Poznan, Poland. Worcester, MA, USA.


43

Spectrally Agile Waveform Results

H. Bogucka, A. M. Wyglinski, S. Pagadarai, A. Kliks. “Spectrally Agile Multicarrier
Waveforms for Opportunistic Wireless Access”. IEEE Communications Magazine,
June 2011.

44

Spectrally Agile Waveform Results

P. Kryszkiewicz, H. Bogucka, A. 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.

Motivation
46

 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


An Example
47

I’m a
PU, too!
Get out
I’m a of my I’m a I’m a
PU! way! PU! PU!

frequency


Current Detection Techniques
48

 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


One Approach
49

 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


“Fingerprinting” Wireless Signals
50

Spectral coherence function of QPSK signal in an Spectral coherence function of 4FSK signal in an
AWGN channel at 10 dB SNR. AWGN channel at 10 dB SNR.


Simulation Results
51

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

Global Telecommunications Conference (Houston, TX, USA), November 2011.
User Emulation Attacks in Cognitive Radio Networks." Proceedings of the IEEE
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.


Experimental Results
52

The percentage of correct detection with the hardware implementation

Proposed Approach
With Check 98.3%
Without Check 91.5%

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.


Additional Enhancements
53

 Action Recognition Techniques
 Often employed in image and video processing
applications, action recognition can also be applied to
spectrum measurements
 Consists of several parameters:
 FeatureVector Construction
 Covariance Descriptor of Feature Vectors
 Log-covariance Descriptor of Feature Vectors


These Are Interesting Times!
55

 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


Still Room For Improvement
56

 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


Contact Info
58

Professor Alexander Wyglinski
Department of Electrical and Computer Engineering
Worcester Polytechnic Institute
Atwater Kent Laboratories, Room AK230
508-831-5061
alexw@ece.wpi.edu
http://www.wireless.wpi.edu/


Cognitive Radio Textbook
59

 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

Software-Defined Radio Textbook
60

 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


References
61
 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.


References
62
 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.


References
63
 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.


References
64
 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.

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

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

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

Similar to Alex Wyglinski - IEEE VTS UKRI - Cognitive radio - a panacea for RF spectrum scarcity (20)

More from Keith Nolan

More from Keith Nolan (17)

Recently uploaded

Recently uploaded (20)

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