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Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of Electrical and Computer Engineering IEEE Vehicular Technology Society Distinguished Lecturer Worcester Polytechnic Institute Presentation outline Introduction The Information Age Wireless Innovation Laboratory Understanding, Securing, and Accessing Spectrum Concluding Remarks More Information
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Page 1: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D.

Associate Professor of Electrical and Computer Engineering

IEEE Vehicular Technology Society Distinguished Lecturer

Worcester Polytechnic Institute

Presentation outline

• Introduction

• The Information Age

• Wireless Innovation Laboratory

• Understanding, Securing, and Accessing Spectrum

• Concluding Remarks

• More Information

Page 2: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Introduction

Worcester Polytechnic Institute

Definition: Cognitive radio

A cognitive radio is a kind of two-way radio that automatically changes its transmission or reception parameters, in such a way that the entire wireless communication network - of which it is a node -communicates efficiently, while avoiding interference with licensed or unlicensed users.

A cognitive radio, as defined by the researchers at Virginia Polytechnic Institute and State University, is "a software defined radio with a cognitive engine brain".

http://en.wikipedia.org/wiki/Cognitive_radio

Page 3: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

So what is Cognitive Radio?

+ ?

Worcester Polytechnic Institute

Intelligence

Optim

izat

ion

Adaptation

Environmental Awareness

AgileFlexible

Spectrally Efficient

Learning

Cooperative

Op

po

rtu

nis

tic

Autonomous

Dynamic Spectrum Access

Cognitive radio means …

Page 4: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

The Information Age

Worcester Polytechnic Institute

Several Key Innovators

Marconi Shannon ShockleyBardeen Brittain

Wireless Transmission

Digital Communications

Transistors

Source: Wikipedia

Page 5: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Progress of Technology

Worcester Polytechnic Institute

Evolution of Wireless Systems“C

ognitiv

e Rad

io C

om

munic

atio

ns

and N

etw

ork

s: P

rinci

ple

s an

d P

ract

ice”

By

A.

M.

Wyg

linsk

i, M

. N

ekove

e, Y

. T.

Hou (

Els

evie

r, D

ecem

ber

2009)

Page 6: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Quick Survey

How many of you:─Own a cell phone?─Use a laptop with WiFi?─Use an ATM?─Fly on a plane?─Traveled in a car?

11

Worcester Polytechnic Institute

Increasing Demand262 Million Subscribers!

Source: CTIA

Page 7: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Increasing Demand

1.1 Trillion Minutes!

Source: CTIA

Worcester Polytechnic Institute

US Spectrum Scarcity!

So

urc

e:

NT

IA

Page 8: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Across the Pond in the UK!

So

urc

e:

Ro

ke M

an

or

Worcester Polytechnic Institute

Oh Canada!S

ou

rce:

Ind

ust

ry C

an

ad

a

Page 9: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

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

Worcester Polytechnic Institute

Potential Solution

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

• Dynamic Spectrum Access (DSA)

Fill with secondary

users

Page 10: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Enabling Transmission Agility

PROGRAMMABLE FIXED

Worcester Polytechnic Institute

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.

Page 11: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Mitola & Cognitive Radio

Mitola

Worcester Polytechnic Institute

Cognitive Radio: A Black Box Model

What you want

What you see

What you can do

What you can tune

Page 12: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Wireless Innovation Laboratory

Worcester Polytechnic Institute

• Associate Professor, WPI ECE

• Director, Wireless Innovation Laboratory─ 8 Ph.D. students, 5 M.S. students

• Distinguished Lecturer, IEEE Vehicular Technology Society (2012-2014)

• Technical Editor, IEEE Communications Magazine

• Editor, IEEE Transactions on Wireless Communications

• General Co-Chair, IEEE VTC 2015-Fall (Boston, MA, USA)

• ~35 journal publications, ~75 conference papers, 9 book chapters, 2 books

• Served or is serving as PI/co-PI for several federal and industrial grants

Who is Alex Wyglinski?

Page 13: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

~60 km

Where is WPI?

Worcester Polytechnic Institute

• Founded in 1865; 3rd oldest US polytechnic

─ Model for most engineering schools in US

─ Nationally ranked as 64th Best College in U.S. (2011 US News Rankings)

─ Voted one of the Top 10 Best U.S. Colleges for “Young Einsteins” by Unigo (together with MIT, CalTech, Princeton, Dartmouth, Stanford, Johns Hopkins, Case Western, Georgia Tech, and Cornell)

• 3800 students & 220 faculty─ ECE: 318 undegraduate, 250

graduate, 21 faculty

What is WPI?

Page 14: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

What is “Lehr und Kunst”?

• Project-based education at the core of “The WPI Plan”

• Many ECE students conduct their senior capstone design projects (called “Major Qualifying Projects”or MQPs) at off-campus locations:─ MIT Lincoln Laboratory─ MITRE (Bedford Campus)─ General Dynamics (Groton Campus)─ Silicon Valley─ Wall Street─ Etc …

Worcester Polytechnic Institute

Wireless Innovation Laboratory

• 2 USRP (Version 1) software-defined radio platforms

• 14 USRP (Version 2) software-defined radio platforms

• 15 USRP (Version N210) software-defined radio platforms

• 1 Agilent CSA N1996A 0-3 GHz spectrum analyzer (with battery packs)

• 1 Mini-discone antenna (100 – 1600 MHz, with 3’ tripod)

• 1 WG horn antenna (0.7 – 18.0 GHz, with tripod)

• 1 Xilinx Virtex 5 HW-V5-ML506-UNI-G Prototyping Board

• 25 complete licenses of MATLAB and Simulink with associated toolboxes and blocksets

• 2 OPNET licenses

Page 15: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

WI Lab External Sponsorship

Worcester Polytechnic Institute

SDR Activities at WPI

Photograph of a supervised laboratory session for ECE4305 “Software-Defined

Radio Systems and Analysis” during February 2011.

Screen capture of a functioning ECE4305 course design project in MATLAB showing four SDR units

forming an ad hoc wireless network.

http://www.sdr.wpi.edu/

Page 16: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Understanding Spectrum

Worcester Polytechnic Institute

Current state of the art

32

RFEye Spectrum Monitoring Solution

Page 17: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Probabilistic model

33

Worcester Polytechnic Institute

Random sampling concept

• Random sampling facilitates statistical characterization

• Random sampling designs ─ Systematic, SRS,

stratified, cluster,...

• Data grouping and sample allocation are crucial to effective characterization

• Benefits─ Dimensionality reduction,

summarization, estimator variance reduction, sampling bias reduction

34

Page 18: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Results

35

Securing Spectrum

36

Page 19: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

How is DSA currently managed?

37

Worcester Polytechnic Institute

Potential vulnerability

38

frequency

I’m a PU!

I’m a PU!

I’m a PU!

I’m a PU, too!

Get out of my way!

Page 20: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Existing techniques

• Energy Detection─ Possess a significant probability of missed detection

• Localization-based Detection─ Can only be employed for stationary primary transmitters

with known coordinates

• Analytical Model-based Detection─ Only works well for a specific network model

• Signature-based Detection─ Require special hardware or software

39

Worcester Polytechnic Institute

Our approach

40

Page 21: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Results

41

QPSK versus 8PSK

Worcester Polytechnic Institute

Results

42

Page 22: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Accessing Spectrum

43

Worcester Polytechnic Institute

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

Page 23: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

• 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 emptyempty

Worcester Polytechnic Institute

Leveraging the Electrospace

Several dimensions of the electrospace include space, time,

and frequency, although there do

exist others such as code, polarization,

and directional.

“Cognitiv

e Rad

io C

om

munic

atio

ns

and N

etw

ork

s: P

rinci

ple

s an

d P

ract

ice”

By

A.

M.

Wyg

linsk

i, M

. N

ekove

e, Y

. T.

Hou (

Els

evie

r, D

ecem

ber

2009)

Page 24: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

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

Worcester Polytechnic Institute

Spectral Opportunities!

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.

empty empty emptyempty

Page 25: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Underlay Solution

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.

underlay transmissions

Worcester Polytechnic Institute

Overlay Solution

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.

overlay transmissions

Page 26: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

Multicarrier-Based OSA

• 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

Worcester Polytechnic Institute

Multicarrier Overlay Solution

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.

multicarrier overlay transmissions

Page 27: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

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.

Worcester Polytechnic Institute

Spectrally Agile MulticarrierH

. Boguck

a, A

. M

. W

yglin

ski, S

. Pa

gadar

ai, A

. Klik

s. “

Spec

trally

Agile

Multic

arr

ier

Wav

eform

s fo

r O

pport

unis

tic

Wirel

ess

Acc

ess”

. IE

EE C

om

munic

atio

ns

Mag

azin

e, J

une

2011.

Page 28: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

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:

Worcester Polytechnic Institute

Sinc Pulses Have High OOB Levels!

-6 -4 -2 0 1 2 4 6-50

-45

-40

-35

-30

-25

-20

-15

-10

-5

0

5

Subcarrier Index

Nor

mal

ized

pow

er s

pect

rum

(in

dB

) OFDM carrier spacing

Interference power to the first adjacent

sub-band

−10 −5 0 5 10 15 20 25 30

0

0.5

1

Other

Transmissions

Other

Transmissions

Other

Transmissions

Subcarrier index

Nor

mal

ized

am

plitu

de

−10 −5 0 5 10 15 20 25 30

−60

−40

−20

0

Subcarrier index

Nor

mal

ized

pow

er in

dB

m

OtherTransmissions

OtherTransmissions

OtherTransmissions

OOB

OOB

Page 29: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

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

Worcester Polytechnic Institute

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.

Page 30: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

P. K

rysz

kiew

icz,

H.

Boguck

a, A

. M

. W

yglin

ski. "

Prote

ctio

n o

f Pr

imar

y U

sers

in D

ynam

ically

Vary

ing R

adio

Envi

ronm

ent:

Pr

actica

l Solu

tions

and C

halle

nges

." Acc

epte

d for

public

atio

n in

the

EU

RASIP

Journ

al o

n W

irel

ess

Com

munic

atio

ns

and

Net

work

ing

Dec

ember

23

2011

Results

Concluding Remarks

Page 31: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

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

Worcester Polytechnic Institute

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

Page 32: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

More Information

Worcester Polytechnic Institute

Contact info

Professor Alexander Wyglinski

Department of Electrical and Computer EngineeringWorcester Polytechnic Institute

Atwater Kent Laboratories, Room AK230

508-831-5061

[email protected]

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

Page 33: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

Worcester Polytechnic Institute

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

Worcester Polytechnic Institute

New SDR textbook

• January 2013 Publications Date (Artech House Publishers)

• 9 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

http://www.sdr.wpi.edu/

Page 34: Spectrally Agile Waveforms for Dynamic Spectrum Access · 2013-06-11 · Spectrally Agile Waveforms for Dynamic Spectrum Access Alexander M. Wyglinski, Ph.D. Associate Professor of

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