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7/27/2019 Koilpillai Cognitive Radio Overview
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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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Electrical EngineeringIIT Madras
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/7/27/2019 Koilpillai Cognitive Radio Overview
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Electrical EngineeringIIT Madras
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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Electrical EngineeringIIT Madras
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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Electrical EngineeringIIT Madras
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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Electrical EngineeringIIT Madras
Cognitive Radio =
Sense + Learn + Adapt + Use
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Electrical EngineeringIIT Madras
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
1
0
nynw
nx
N)(N-,,n
nwnxnyH
nwnyH
w
0
1
1
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
2
22
22detection-missed
1
22222
0
22
2
1
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
Detection Sensitivity
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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
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
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)
Detection Sensitivity
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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Electrical EngineeringIIT Madras
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
Electrical Engineering
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Electrical EngineeringIIT Madras
Multicarrier Techniques in CR
Electrical Engineering
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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
Electrical Engineering
OFDM C i i A il bl S t
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Electrical EngineeringIIT Madras
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
Electrical Engineering
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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
Electrical Engineering
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IIT Madras
UWB-based CR
Electrical Engineering
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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
Electrical Engineering
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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
Electrical EngineeringIIT Madras
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IIT Madras
Information Theoretic Aspects
- Capacity of CR Channel
Electrical EngineeringIIT Madras
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?
Electrical EngineeringIIT Madras
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
Electrical EngineeringIIT Madras
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