Koilpillai Cognitive Radio Overview

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Koilpillai / Mar 2009 / Cognitive Radio 1

IISc-DRDO Seminar on Cognitive Radio IITM Proprietary Information

Electrical EngineeringIIT Madras

Cognitive Radio - An Introduction

R. David KoilpillaiDepartment of Electrical EngineeringIndian Institute of Technology Madras

IISc-DRDO Workshop on Cognitive Radio

BangaloreMarch 14, 2009


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LTE-Adv

Evolution of Wireless

Focus is on spectral efficiency bits / sec / Hz

GSMGPRS WCDMA LTE

Rel. 7

Rel. 6

Rel. 5(HSDPA)

1xEV-DV

1xEV-DOcdmaOne cdma2000

UMB

IEEE802.16 d/e

IEEE802.16 m

MIMO-Wave2
http://www.wimaxforum.org/


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Radio Functionality Evolution

Source: Prasad et al. IEEE Comm Magazine, April 2008


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Electrical EngineeringIIT MadrasSoftware Defined Radio (SDR)

J. Mitola, The software radio architecture IEEE Communications Magazine, May 1995


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Electrical EngineeringIIT MadrasVanu SDR Architecture

Ref: www.vanu.com

Commercial product

Multistandard GSM / GPRS / EDGE

Cdma / EV-DO

Flexibility

Scaleability

Cost-effectiveness


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Electrical EngineeringIIT MadrasVanu SDR Architecture

Ref: www.vanu.com


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Electrical EngineeringIIT MadrasSDR Summary

Many technical challenges have been solved

SDR now commercially viable and attractive Drivers for SDR

Advances in processors, DSPs, FPGAs,

High speed, high-resolution A/D,

Multi-standard support, MIMO capability,

Efficient software tools and structures

SDR: A flexible platform New technology development

Technology migration

Focus on basestations and not user equipment

Numerous national and international initiatives

Multiple SDR test beds Open-source material available

SDR Forum an active group

The next step in SDR Migration towards Cognitive Radio


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SDR Cognitive Radio


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Electrical EngineeringIIT MadrasCognitive Radio (CR)

Motivation for CR

Increasing demand for radio spectrum Broadband wireless demand is rapidly growing

Current approach to spectrum allocation Fixed allocation to licensed users

Existing scenario Under-utilization of spectrum

Spatial and temporal spectral holes exist

Innovative approach to improve spectrum utilization Cognitive Radio

Initiated by FCC regarding secondary usage of spectrum


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Utilization of Spectrum

Frequency range

30 MHz 2.9 GHz

Based on report by M.A. McHenry

Max. utilization ~ 25% TV channels

Average usage ~ 5.2 % New York City average ~ 13.1%

Significant # white spaces Even in cellular bands

Ref: M.A.McHenry, NSF Spectrum Occupancy

Measurements Project Summary, August 2005

Ghasemi and Sousa,

IEEE Communications Magazine,April 2008


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Electrical EngineeringIIT MadrasCR Approach

Main steps in CR approach Identify spectral bands not used by Primary User

Signal sensing (to detect Primary Users signal)

Estimation of Interference Temperature

Localised around user

Spectral hole

A spectral band assigned to primary user Currently unused at geographical location

Should be done reliably

Should be able to detect low level Primary User signals

Utilize spectrum as Secondary User

Increasing utilisation of radio spectrum

Without causing interference to Primary User Primary user always has priority


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Electrical EngineeringIIT MadrasTodays CR Scenario

CR: Opportunistic Unlicensed Access

To temporarily unused frequency bands (across the entire licensed radio spectrum)

A means to increase efficiency of spectrum usage

Stringent safeguards required

On-going licensed operations should not be compromised

Spectrum sensing based access

Unlicensed user transmits if licensed band is sensed to be free

Main functionality of Cognitive Radios

Ability to identify unused frequency bands

Sensing must be reliable and autonomous

Conclusion

A perceived spectrum scarcity - due to inefficient, fixed spectrum allocation

Considerradically different paradigm

Secondary (unlicensed) users

Opportunistic use of unused primary (licensed) band(s)


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Electrical EngineeringIIT MadrasIEEE 802.22

Project started by IEEE in Nov 2004

Charter: To develop a CR-based WRAN

PHY and MAC specifications Transmission in unused TV and guard bands (54 MHz 862 MHz)

Very favourable propagation characteristics

Channel BW 6 MHz (may be 7 MHz / 8 MHz in some countries)

Spectrum sensing for identifying white spaces Distributed sensing

FCC maintained server info about unused channels (by geographical location

Localised sensing

CPEs perform periodic measurements and send measurements to BTS

BTS makes decision to use the current channel or any other alternatives

Application scenarios

Wireless broadband in rural / remote areas

Performance comparable to todays DSL technology

Unlicensed devices lower cost and increased affordability Attractive for Wireless Internet Service Providers (WISP)

TV migration : moving from broadcast to cable and satellite

Broadcast TV channels available


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Electrical EngineeringIIT MadrasComparison of Networks

WRAN Aspects

Large coverage footprint

Up to 100 Km

Larger cells than cellular

Leverage two factors

Higher EIRP

Attractive propgn characteristics

Ideal for rural /remote services

Broadband wireless access

Unlicensed devices

Ref: Cordeiro et al., IEEE 802.22: The First Worldwide

Wireless Standard based on Cognitive Radio, IEEE, 2005


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Electrical EngineeringIIT MadrasIEEE 802.22 Specifications

Target specifications

Spectral efficiency 0.5 b/s/Hz 5 b/s/Hz

Average: 3 b/s/Hz 18 Mbps in 6 MHz Assuming 12 simultaneous users 1.5 Mbps (DL) and 384 Kbps (UL)

Range: 33 Km (extend to 100 Km)

CPE Tx power 4W EIRP @ CPE

Air interface

Requirements Flexibility and quick adaptibility

Link adaptation based on SINR

Adapt modulation and Coding option

Frequency agility

OFDM(A) based UL and DL

Transmit Power Control : 30 dB withsteps of 1 dB

Channel Bonding Utilizing more than one TV channel System can use larger BW to support higher throughput


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Electrical EngineeringIIT MadrasIEEE 802.22 MAC

Medium Access Control (MAC) Design tailored for Cognitive Radio Technology

Key aspect adaptability based on dynamic changes in environment

Spectrum sensing measurements

Two structures

Frame and Superframe

Superframe will have Superframe Control Header (SCH) and preamble

SCH sent by BS in every channel that is available

Two types of spectrum measurements

In-band measurements in channel currently being used Out-of-band measurements Other channels

Two types of sensing

Fast sensing - < 1 msec per channel

Performed by CPE and BS - For quick information gathering

Fine sensing up to 25 msec per channel

Verification / validation of measurements Deal with large propagation delay (roundtrip delay up to 300 microsec)

MAC deals with a number of issues not addressed in traditional systems


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Cognitive Radio =

Sense + Learn + Adapt + Use


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Spectrum Sensing


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Electrical EngineeringIIT MadrasMethods of Spectrum Sensing

Energy Detector Correlation-based detector

Cyclostationarity-based detector

Hybrid Detector

Performance of spectrum sensing

Sensing Criteria (Regulatory aspects)

Sensing Period

Detection Sensitivity


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Electrical EngineeringIIT MadrasSpectrum Sensing

Optimum receiver If structure of primary signal known

Optimum (in AWGN): Matched Filter (MF) followed by Threshold

Can be implemented for a few specific primary signals (selected bands)

Not practical for large # of primary users

Need for coherent detector for each transmitted signal

Alternative Energy Detector Measures energy of signal in primary band

Compare with properly set threshold

Declare presence of white spaces primary user absent Requires longer sensing time to achieve desired level of performanc e

Low computational complexity

Ease of implementation

ED - An attractive candidate for Cognitive Radio

Drawbacks of ED Cannot discriminate between sources of input energy (signal vs. noise)

Uncertainty of noise floor will degrade performance

Especially at low SNR

ED can be effectively combined with more robust detectorsHybrid Detectors


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Electrical EngineeringIIT MadrasSpectral Sensing

Binary hypothesis testing problem

Decision statistic (Energy detector)

When signal absent, is Central Chi-Square Variable with Ndegrees offreedom

When signal present, non-Central Chi-Square Variable

signaldtransmitte][ancewith variAWGNmean(zeronoise][

signaldtransmitte

signal)receivedofn windowobservatiosample(110

presenterPrimary Us][][][:

absenterPrimary Us][][:

2

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0

nynw

nx

N)(N-,,n

nwnxnyH

nwnyH

w

0

1

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0

2][

1

H

HandnyN

N

n


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Electrical EngineeringIIT MadrasEnergy Detector

Decision statistic

If N large, invoke CLT

0

1

1

0

2][1

H

HandnyN

N

n

N

PQThreshold

N

QP

HN

Normal

HN

Normal

fa

w

wx

wx

wxwx

ww

1

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22

22detection-missed

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22222

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for),(~

for,~


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Electrical EngineeringIIT MadrasSpectral Sensing Performance (1)

Performance of Energy Detector is validated against analytical performance

In AWGN, ED achieves good performance at very low SNRs ~ -8 dB Achieves low probability of false alarm

Evaluated for frequency selective fading channels also


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Electrical EngineeringIIT MadrasSpectral Sensing Performance (2)

Robustness of energy detector enhanced if longer sensing period is used

Performance in fading is poorer than in AWGN (as expected) Noise uncertainty causes major degradation in performance

Energy detector not suited as a stand-alone detector

Performance in fadingAWGN, Effect of sensing Period


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Electrical EngineeringIIT MadrasSpectrum Sensing Summary

Many methods available

Properties utilised: Energy, Correlation, Cyclostationarity

Computational complexity and estimation time are important factors

Searching over a vast frequency range

Focus on robustness (at low SNR) and reliability

Minimize probability of missed detection

To avoid interference to primary user Uncertainties regarding measurement

Noise and interference environment

Strong motivation for Hybrid Detectors

Sensing Criteria (Regulatory aspects)

Sensing Period



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Electrical EngineeringIIT MadrasRegulatory Constraints

Satisfactory protection of primary user from harmful interference

Essential for realization of opportunistic spectrum access

Regulatory constraints

Sensing Periodicity (Tp)

Period with which UL user must check for presence of primary user


Signal level at which the UL user must detect primary user reliably

Sensing Period (Tp)

Max. time (delay) UL user unaware of reappearance of primary user

Max. duration of harmful interference

Determines QoS degradation of primary user

Delay of primary user in accessing channel

Depends on type of primary user service delay sensitivity

Must be set by regulator for each licensed band

El t i l E i i


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Electrical EngineeringIIT MadrasDetection Sensitivity

Threshold to be satisfied even if PU Rx is at edge of coverage

Provided SU maintains distance D

SU (CR) must be able to detect PU at distance (R+D)


bsp

PDLP

RLP

n

p

P

RDLP min

Ref: Ghasemi et al., IEEE Communications Mag,

April 2008

ddL

R

PPP bsp

distanceatFading)and(ShadowinglossPath

receiverandrtransmittePUbetweendistanceMax

ceinterferennoisebackgroundandSU,PU,ofPower

)(

,,

El t i l E i i


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Electrical EngineeringIIT MadrasUncertainties in Sensing

Aggregate Interference Uncertainty

PU may experience harmful

interference

If multiple CR networks active

Requires more sensitive detectors

Detect PU at distance

Alternative system level coordination among CR devices

Cooperative sensing

RDD

Channel Uncertainty

Due to fading / shadowing of PU signal

Noise Uncertainty

Ref: Ghasemi et al., IEEE Communications Mag, April 2008

Electrical EngineeringCooperative Sensing


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Cooperative Sensing Sensing of primary user difficult with multipath fading and shadowing

Significant fluctuation of signal level (worst case is very severe)

Need to maintain sensing performance

CR requires higher detection sensitivity (lower )

Requirement becomes very stringent

To alleviate the problem Cooperative Sensing

Independent measurements at different locations / CRs

Exchange of sensing information among CR nodes

Diversity gain achieved (with respect to fading and shadowing) Improved probability of detecting PU

Without increasing sensitivity of each individual SU Rx

Introduces additional communications overhead

Requires functionality of Band Manager (Fusion Centre)

Collects information, makes decisions and shares information with all CR nodes

Shadowing is correlated over short distances

Cooperation to be done over larger distances (few nodes)

Different from conventional view of Mesh / Ad Hoc networks (many nodes in close proximity)

min

Electrical Engineering


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Electrical EngineeringIIT MadrasCooperative Sensing

Decision making options

Hard decision based Soft decision based

Hard Decision

Each SU makes indep decision

Reg presence of PU

One-bit decision

Band Manager gathers information

Shares decision with all CR nodes

Rule: If one of the SUs senses PU signal Primary User present

ROC Receiver Operating Characteristic to evaluate performance Observation

HD based decision makingnot beneficial if SU SNRs are vastly different



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Multicarrier Techniques in CR



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Electrical EngineeringIIT MadrasMulticarrier Techniques

Multicarrier techniques widely used in Cognitive Radio (PHY)

OFDM, Filterbank-based multicarrier, Multi-resolution filter banks

Spectrum sensing determine spectral holes

Spectrum usage communication

Transmit data w/o interfering with Primary user

In non-overlapping parts of spectrum

Multicarrier techniques efficient and effective

To maximize efficiency Sidelobes (frequency response) of the subcarriers must be minimized

CR transmission can be TDD or FDD

TDD has inherent advantages for CR

Tx and Rx in in same band knowledge of channel

Implicit sensing of channel during Rx period (Tx OFF)

802.22 WRAN standard focus on TDD

OFDM based

Frequency

Code

Time

Electrical EngineeringM lti i T h i


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Electrical EngineeringIIT MadrasMulticarrier Techniques

OFDM

Widely studied and well-understood (based on IFFT / FFT)

Used for spectral sensing

Underlying filter is the Rectangular window

Poor side-lobe suppression

Significant interference between sub-carriers

Not suitable for spectral sensing / transmission (non-contiguous bands)

Acceptable for contiguous bands

Approaches to consider

Muti-Taper Method (MTM) for spectral estimation

Filterbank Multi-Carrier

Filterbank-based approaches can overcome spectral leakage problems

Less used than OFDM


OFDM C i i A il bl S t


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Frequency

T

I

M

E

Spectral Adaptation Waveforms

OFDM Carriers in Available Spectrum

Ref: B. Fette, SDR Technology Implementation for the Cognitive Radio, General Dynamics



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g gIIT MadrasPerformance of FFT

Raised cosine filtering before FFT Reduces side-lobes

Improved freq selectivity At expense of lower time selectivity

Frequency response of FFT filter

Filtering at Rx end also possible Similar tradeoff as at Tx

Ref: Boroujeny et al., IEEE Communications Mag, April 2008

CP)(incl.periodsymbolOFDM

channel-suboffrequencyCentre

sinc)( 2

s

th

i

sii

T

if

TffKf

Electrical EngineeringM lti i T h i


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g gIIT MadrasMulticarrier Techniques

Multitaper Method (MTM)

Advanced, non-parametric spectral estimation method

A set of filters (Slepian 1978, Bell Labs)

Discrete Prolate Spheroidal Sequences

Optimal trade-off between time selectivity and frequency selectivity

Combine the output of a family of filters

Near-optimal performance in spectral sensing (Haykin, 2005)

Example: A set of 5 DPSS based filters and their responses Filterbank Method

Similar performance to MTM

Can be used for sensing and for transmission

Lower computational complexity than MTM

A rich area for further investigation for CR

Electrical EngineeringPerformance of Filterbank


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g gIIT MadrasPerformance of Filterbank

MTM five filters of length 2048 Three filters with attenuation more than -60 dB

Filterbank Multicarrier Length 6x256=1536, 256-channel filterbank Achieves comparable performance to MTM

Ref: Boroujeny et al., IEEE Communications Mag, April 2008



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IIT Madras

UWB-based CR



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IIT MadrasUWB Overview

Cognitive network an interconnection set of CR devices

Aware of radio channel characteristics

Interference temperature, spectrum availability, policies,

Devices sharing of information to facilitate CR functions

Suitable wireless technology facilitate collaboration between CR nodes

Ultra Wideband (UWB)

Bandwidth (BW) > 500 MHz or

Fractional BW

FCC permits unlicensed use of UWB (2002)

Proposed methods for UWB

OFDM-based UWB (UWB) (OFDM-UWB) Impulse radio based UWB (IR-UWB)

2.0

2

LH

LH

ff

ff



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IIT MadrasUWB Overview

UWB an underlay system

Co-exist with other licensed (primary) / UL users

In same temporal, spatial, and spectral domain

Signal embedded in noise floor secure transmission

UWB has multidimensional flexibility

Pulse shape, bandwidth (BW), data rate, power

UWB has inherent potential to meet CR requirements

IR-UWB multiple attractive features

High multipath resolution

Ranging and positioning

UWB unlicensed operation in 3.1-10.6 GHz

Tx power limit < -42 dBm/MHz Ensures that UWB does not affect licensed operations

Electrical EngineeringIIT M dUWB-based CN


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IIT MadrasUWB based CN

An interesting possibility

UWB as a complement to other CR technologies

For sharing information via UWB Locating other users

Information exchange in CN

CR nodes must have common understanding of spectrum to be used

Sharing of sensing information

Possible options

Common control channel for CR nodes to share information

A centralized controller that gathers info and decides spectrum availability

Allocates distinct bands to each CR user

Alternative: Low-power UWB signaling to share information

Leverage all the advantages of UWB

Low-throughput needed Low-complexity (OOK, with non-coherent detection)

Issue: range of UWB

Electrical EngineeringIIT M dCognitive Networks


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IIT MadrasCognitive Networks

Network of nodes with CR functionality

Cognitive networks is attractive for Dynamic Spectrum Access

Sharing via UWB is attractive Point-to-point model

Centralised model

Draw from research results in UWB-based sensor networks

Source: Arslan et al., Cognitive Wireless Communication Networks, Springer

Electrical EngineeringIIT MadrasSecurity in Distributed Sensing


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IIT MadrasSecurity in Distributed Sensing

Reliable spectrum sensing is key in CR networks

Shadowing and multipath fading challenges in sensing

Shadowing leads to hidden node problem Sensing challenges alleviated by Cooperative Sensing

Using multiple distributed CR nodes

Two major security issues

Incumbent emulation

Caused by a malicious secondary Gains priority over channel by emulating PU characteristics

Falsification of spectrum sensing data

False data to mislead band manager

Both are important issuesthat need to be addressed

Potential countermeasures Authentication of the data and the sender

Robust data fusion methods



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IIT Madras

Information Theoretic Aspects

- Capacity of CR Channel


Information Theoretic Aspects in CR


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IIT Madrasp

Current CR scenario

Device X1 transmits only when

channel is free

Device X2 transmits after X1

Or uses different freq band

X2 need not wait until X1 is done

Ref: Devroye et al., Limits on Communications in a

Cognitive Radio Channel, IEEE Communications Mag,

June, 2006

Is simultaneous transmission more efficient than time sharing?

What are the achievable rates at which two users (CR capable) could transmit

What are the achievable rates if two users do not have CR capability?


Information Theoretic Aspects in CR


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IIT Madras

Cognitive Radio Scenario Simplified model : Two transmitters (X1 and X2) and two receivers, (Y1 and Y2)

Goal: Define and evaluate channel capacity for CR channel Two links: (X1 Y1 ) and (X2 Y2 )

Evaluate max. rate at which information sent over both links

Capacity will be a two-dimensional graph (R1 , R2 ) Capacity regions max. set of all reliable rates that can be simultaneously achieved

Obtain inner (achievable region) bounds and outer bounds

Usually based on random coding (w/o explicitly constructing codes

Ref: Devroye et al., Limits on Communications in a

Cognitive Radio Channel, IEEE Communications

Mag, June, 2006

Electrical EngineeringIIT MadrasInformation Theoretic Aspects in CR


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IIT Madrasp

Two links:

(X1

Y1

) and (X2

Y2

)

X2 is a CR device

(X1 X2 ) exists

X2 knows message of X1 Genie aided

X1does notknow message of X2 An asymmetric problem

An idealized situation

Will provide an upper bound onrates achievable in practice

An open problem

Achievable region combination of

Han-Kobyashi interference region

Dirty paper coding Relaying

Ref: Devroye et al., Limits on Communications in a Cognitive Radio Channel, IEEE Communications Mag, June, 2006

Electrical EngineeringIIT MadrasCapacity


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IIT Madrasy Computing capacity regions uses three techniques

Han-Kobyashi interference region

Dirty paper coding

Relaying

Two links: (X1 Y1 ) and (X2 Y2 ) and X2 knows message of X1 Two possible actions of X2

Selfish Approach

Try to mitigate own interference Dirty Paper coding

Achieves region where R2 > R1 Selfless Approach

X2 acts a relay for X1 X2 does not transmit own information

Region where R1 is higher thanR2

Region 1 Time sharing by X1 and X2 Region 2 Interference regionboth do not know others information

Region 3 Cognitive region

Region 4 MIMO region Both X1 , X2 andY1 , Y2 cooperate This is the region that gives maximum capacity



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CR A Practical Implementation

Electrical EngineeringIIT MadrasCorDECT Rural WLL Deployment


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CorDECT Rural WLL Deployment

CorDECTBase

Station

CorDECTCOxDSL/E1

Cor -

DECT

CPE

Village A

CorDECT NetworkPSTN

SS7/ R2MFV5.2

Access Center

Village B

Internet

Cor -

DECT

CPE

Fixed Wireless Link

Up to 240 Kbps per vi l lage

15 Km range

(up to 25 km w ith repeater)

corDECT is deployed in > 15 countries

Electrical EngineeringIIT MadrasGSM - CR Combination


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Cor-DECT

CPE

GSM

BTS

GSM Hotspot

2 km radius

CorDECT

Base Stn

CorDECT

CO

Media&Signaling

Gateway

SoftSwitch

xDSL/E1

Cor-DECT

CPE

GSM

BTS

GSM Hotspot

2 km radius

Village A

Village B

CorDECT Network PSTNPLMNVoIP

Fixed Wireless Link

Up to 240kbps per vi l lage

15km range

(more reach with

Repeaters)

Access Center

GSMLite


CR Techniques for GSM band


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Goal: Adaptive freq selection for GSM BTS

Interference avoidance using CR

Description:

Support GSM Lite developed by Midas

Usage: rural areas, in-building, femtocells

Based on ADI Blackfin DSP

Challenges

Weak signal detection and monitoring

Listening to other GSM BTS

Hardware and Software Implementation

Approaches for detecting GSM signal

Cross Correlation Detector training sequence

Cyclostationarity-based

Sensitive to frequency error

Hybrid Detector (developed)

Combines different schemes

Implementationintelligent hopping

Prototype (under field trial):

Performance ofHybrid scheme

Electrical EngineeringIIT MadrasSummary


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A technical overview of Cognitive Radio

CR - A paradigm shift in wireless communications

Potential of significant increase in spectrum availability

Opportunistic access

Spectrum sensing

Understanding the various challenges

Technical and regulatory issues

Robust and computationally efficient approaches are needed

Cooperative sensing is attractive

Information theoretic aspects Capacity region for CR

IEEE 802.22 standard

A practical application CR-based GSM basestation

Overall, CR is an exciting field



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My best wishes to

all participants of

IISc-DRDO Seminar on Cognitive Radio

Thank You !

Electrical EngineeringIIT MadrasDavid Koilpillai Profile


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EducationB.Tech, IIT Madras, MS, PhD Caltech, USA

Work ExperienceIIT Madras (2002 present)

Professor, TeNeT Group, EE Department

CEWiT Chief Scientist (Jan 2007 July 2007Co-Chair, IIT Hyderabad Task Force (June 2008 present)Ericsson Inc, USA (1990-2002)

Director, Advanced Technologies, Research and Patents(R&D team of 75 engineers, annual budget US $20 Million)

Professional Areas of expertise: Cellular, wireless systems, DSP

32 Issued US patents

Publications: 11 Journal, 45 Conference Research Interests: DSP applications in Wireless

Ericsson Inventor of Year Award 1999

Fellow, Indian National Academy of Engineering

Koilpillai Cognitive Radio Overview

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