Koilpillai / Mar 2009 / Cognitive Radio 1 IISc-DRDO Seminar on Cognitive Radio IITM Proprietary Information Electrical Engineering IIT Madras Cognitive

Koilpillai / Mar 2009 / Cognitive Radio 1 IISc-DRDO Seminar on Cognitive Radio IITM Proprietary Information

Electrical Engineering IIT Madras

Cognitive Radio - An Introduction

R. David KoilpillaiDepartment of Electrical Engineering

Indian Institute of Technology Madras

IISc-DRDO Workshop on Cognitive RadioBangalore – March 14, 2009



LTE-Adv

Evolution of Wireless …

Focus is on spectral efficiency – bits / sec / Hz

GSMGPRS WCDMA LTE

Rel. 7

Rel. 6Rel. 5

(HSDPA)

1xEV-DV

1xEV-DOcdmaOne cdma2000 UMB

IEEE802.16 d/e

IEEE802.16 m

MIMO-Wave2


Electrical Engineering IIT MadrasRadio Functionality Evolution

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


Electrical Engineering IIT MadrasSoftware Defined Radio (SDR)

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


Electrical Engineering IIT MadrasVanu SDR Architecture

Ref: www.vanu.com

Commercial product Multistandard

– GSM / GPRS / EDGE– Cdma / EV-DO

Flexibility Scaleability Cost-effectiveness


Electrical Engineering IIT MadrasVanu SDR Architecture

Ref: www.vanu.com


Electrical Engineering IIT 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 …



SDR Cognitive Radio


Electrical Engineering IIT 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



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


Electrical Engineering IIT MadrasCR Approach

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

Signal sensing (to detect Primary User’s 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


Electrical Engineering IIT MadrasToday’s 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 – Consider radically different paradigm

Secondary (unlicensed) users Opportunistic use of unused primary (licensed) band(s)


Electrical Engineering IIT 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

CPE’s 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 today’s 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


Electrical Engineering IIT 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


Electrical Engineering IIT 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


Electrical Engineering IIT 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



Cognitive Radio =

Sense + Learn + Adapt + Use



Spectrum Sensing


Electrical Engineering IIT 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


Electrical Engineering IIT 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 detectors – “Hybrid Detectors”


Electrical Engineering IIT MadrasSpectral Sensing

Binary hypothesis testing problem

Decision statistic (Energy detector)

When signal absent, Δ is Central Chi-Square Variable with N degrees of freedom

When signal present, non-Central Chi-Square Variable

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Electrical Engineering IIT MadrasEnergy Detector

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Electrical Engineering IIT 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


Electrical Engineering IIT 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


Electrical Engineering IIT 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 – Detection Sensitivity


Electrical Engineering IIT 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

Detection Sensitivity

– 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


Electrical Engineering IIT 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)

Detection Sensitivity

bs

p

PDLP

RLP

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

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Electrical Engineering IIT 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



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 IIT 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 making – not beneficial if SU SNRs are vastly different



Multicarrier Techniques in CR


Electrical Engineering IIT 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



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



Frequency

T

I

M

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Spectral Adaptation Waveforms

OFDM Carriers in Available Spectrum

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


Electrical Engineering IIT 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

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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 Engineering IIT 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



UWB-based CR


Electrical Engineering 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)

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Electrical Engineering 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 Engineering 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 Engineering 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 Engineering 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 issues that need to be addressed Potential countermeasures

– Authentication of the data and the sender – Robust data fusion methods



Information Theoretic Aspects - Capacity of CR Channel



Information Theoretic Aspects in CR

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

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



Electrical Engineering IIT MadrasInformation Theoretic Aspects in CR

Two links: – (X1 Y1 ) and (X2 Y2 )

X2 is a CR device

(X1 X2 ) exists

– X2 knows message of X1

– Genie aided X1does not know message of X2

– An asymmetric problem

An idealized situation Will provide an upper bound on rates achievable in practice An open problem Achievable region – combination of

– Han-Kobyashi interference region – Dirty paper coding – Relaying



Electrical Engineering IIT MadrasCapacity

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 than R2

Region 1 – Time sharing by X1 and X2

Region 2 – Interference region – both do not know other’s information Region 3 – Cognitive region Region 4 – MIMO region – Both X1 , X2 and Y1 , Y2 cooperate

– This is the region that gives maximum capacity



CR – A Practical Implementation


Electrical Engineering IIT MadrasCorDECT Rural WLL Deployment

CorDECT Base Station

CorDECT

CO xDSL/E1

Cor -DECTCPE

Village A

CorDECT Network

PSTN SS7/ R2MF V5.2

Access Center

Village B

Internet

Cor -DECTCPE

Fixed Wireless Link Up to 240 Kbps per village15 Km range (up to 25 km with repeater)

corDECT is deployed in > 15 countries


Electrical Engineering IIT MadrasGSM - CR Combination

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 PSTN PLMN VoIP

Fixed Wireless Link Up to 240kbps per village 15km range (more reach with Repeaters)

Access Center

GSMLite



CR Techniques for GSM band

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 Implementation – “intelligent hopping”

Prototype (under field trial):

Performance of Hybrid scheme


Electrical Engineering IIT MadrasSummary

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



My best wishes to

all participants of

IISc-DRDO Seminar on Cognitive Radio

Thank You !


Electrical Engineering IIT MadrasDavid Koilpillai Profile

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

Work Experience IIT Madras (2002 – present)

Professor, TeNeT Group, EE DepartmentCEWiT – 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

Documents

Koilpillai / Mar 2009 / Cognitive Radio 1 IISc-DRDO Seminar on Cognitive Radio IITM Proprietary Information Electrical Engineering IIT Madras Cognitive