1. IISc-DRDO Workshop on Cognitive Radio Bangalore – March 14, 2009
Cognitive Radio - An Introduction R. David Koilpillai Department of Electrical Engineering Indian Institute of Technology Madras
IISc-DRDO Workshop on Cognitive Radio
Bangalore – March 14, 2009

2. Evolution of Wireless …
LTE-Adv
GSM
GPRS
WCDMA
Rel. 5
(HSDPA)
LTE
1xEV-DV
UMB
cdmaOne
cdma2000
1xEV-DO
IEEE
d/e
IEEE m
MIMO-
Wave2
Focus is on spectral efficiency – bits / sec / Hz

3. Radio Functionality Evolution
Source: Prasad et al. IEEE Comm Magazine, April 2008

4. Software Defined Radio (SDR)
J. Mitola, “The software radio architecture” IEEE Communications Magazine, May 1995

5. Vanu SDR Architecture Commercial product Multistandard Flexibility
GSM / GPRS / EDGE
Cdma / EV-DO
Flexibility
Scaleability
Cost-effectiveness
Ref:

6. Vanu SDR Architecture
Ref:

7. SDR 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 …

8. SDR  Cognitive Radio

9. Cognitive 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

10. 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

11. CR 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

12. Today’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)

13. IEEE 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

14. Comparison 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 : The First Worldwide Wireless Standard based on Cognitive Radio,” IEEE, 2005

15. IEEE 802.22 Specifications Target specifications Air interface
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 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

16. IEEE 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

17. Cognitive Radio = Sense + Learn + Adapt + Use

18. Spectrum Sensing

19. Methods 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

20. Spectrum Sensing Optimum receiver Alternative – Energy Detector
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”

21. Spectral 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

22. Energy Detector
Decision statistic
If N large, invoke CLT

23. Spectral 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

24. Spectral Sensing Performance (2)
AWGN, Effect of sensing Period
Performance in fading
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

25. Spectrum 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

26. Regulatory 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

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

28. Uncertainties in Sensing
Channel Uncertainty
Due to fading / shadowing of PU signal
Noise Uncertainty
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
Ref: Ghasemi et al., IEEE Communications Mag, April 2008

29. 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)

30. Cooperative Sensing Decision making options Hard Decision
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

31. Multicarrier Techniques in CR

32. Multicarrier 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)
WRAN standard focus on TDD
OFDM based
Frequency
Code
Time

33. Multicarrier 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

34. OFDM Carriers in Available Spectrum
Frequency T I M E
Spectral Adaptation Waveforms
Ref: B. Fette, “SDR Technology Implementation for the Cognitive Radio,” General Dynamics

35. Performance of FFT Frequency response of “FFT filter”
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

36. Multicarrier 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

37. Performance of Filterbank
Ref: Boroujeny et al., IEEE Communications Mag, April 2008
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

38. UWB-based CR

39. UWB 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)

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

41. UWB-based CN An interesting possibility … Information exchange in CN
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

42. Cognitive 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

43. Security 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

44. Information Theoretic Aspects - Capacity of CR Channel

45. 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?

46. Information Theoretic Aspects in CR
Ref: Devroye et al., “Limits on Communications in a Cognitive Radio Channel,” IEEE Communications Mag, June, 2006
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

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

48. Capacity 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

49. CR – A Practical Implementation

50. CorDECT Rural WLL Deployment
CorDECT Network
Cor -
DECT
CPE
Fixed Wireless Link
Up to 240 Kbps per village
15 Km range
(up to 25 km with repeater)
PSTN
SS7/ R2MF
Village B
V5.2
This picture illustrates a typical rural deployment
The Access center is located at the district headquarters
This houses the CorDECT CO which interonnects this network to the PSTN and Internet
Mostly the Basestation is colocated with the Access Center,
However, depending on the deployment density, the basestations can be remotely located using E1 or xDSL interfaces.
The CorDECT CPE works as a fixed wireless terminal providing both voice and data connectivity to remote villages
The typical range is 15km, however it can be enhanced using cost effective repeater technology from Midas
CorDECT
CorDECT
Internet
Base
Station
xDSL/E1 CO
Cor -
DECT
CPE
Access Center
Village A
corDECT is deployed in > 15 countries

51. GSM - CR Combination
GSMLite

52. CR Techniques for GSM band
Goal: Adaptive freq selection for GSM BTS
Interference avoidance using CR
Prototype (under field trial):
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”
TeNeT group has developed Wireless Local Loop (WLL) product based on the DECT standard. This is a product called “corDECT” which is manufactured and sold by MIDAS, a company incubated under the auspices of TeNeT. It has clearly been demonstrated that corDECT is a cost-effective solution for wireless access. It is now being deployed in more than fifteen countries outside India, indicating that telecom products that are world-class and at the same time, are also cost-effective can be successfully developed in India.
TeNeT faculty play an active role in offering continuing education courses in Wireless to students and faculty from other engineering colleges and also to engineers working in industry.
Performance of Hybrid scheme

53. Summary 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 standard
A practical application – CR-based GSM basestation
Overall, CR is an exciting field

54. My best wishes to all participants of IISc-DRDO Seminar on Cognitive Radio Thank You !

55. David Koilpillai Profile
Education
B.Tech, IIT Madras, MS, PhD Caltech, USA
Work Experience
IIT Madras (2002 – present)
Professor, TeNeT Group, EE Department
CEWiT – Chief Scientist (Jan 2007 – July 2007
Co-Chair, IIT Hyderabad Task Force (June 2008 – present)
Ericsson Inc, USA ( )
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