viswanath
TRANSCRIPT
![Page 1: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/1.jpg)
Spectrum Sensing for Cognitive Radios
G Viswanath
Honeywell, Bangalore
![Page 2: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/2.jpg)
•Overview and introduction to Cognitive Radios
•Approaches for spectrum sensing
•Conclusions
Outline
![Page 3: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/3.jpg)
Motivation for Cognitive Radio
![Page 4: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/4.jpg)
Spectrum Utilization
Ref: M.A.McHenry, “NSF Spectrum Occupancy Measurements Project Summary,” August
2005
Ghasemi and Sousa, IEEE Communications Magazine, April 2008
Increasing demand for spectrum
Existing scenario
– Under-utilization of spectrum
Innovative approach to improve spectrum
utilization
– Cognitive Radio
![Page 5: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/5.jpg)
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- White spaces – primary user absent, and free of RF interferers
- Gray spaces – primary user absent but partially occupied by interferers
- Black spaces – primary user present
• Main functionality of Cognitive Radios- Ability to reliably identify unused frequency bands
- Sensing must be reliable and autonomous
• Radically different paradigm- Secondary (unlicensed) users - Opportunistic use of unused licensed bands
- Increased utilization of radio spectrum
![Page 6: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/6.jpg)
TV Bands
![Page 7: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/7.jpg)
![Page 8: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/8.jpg)
Unlicensed Bands
• Several co-existing radios networks interfere with each other
- 2.4GHZ band
Zigbee, Bluetooth and wireless LAN
• Co-existence approaches critical for capacity
• The network geometry and its structural fluctuations are critical parameters that influence the performance of random networks.
• The interference and the signal strength at a receiver critically also depends on the distribution of the interfering transmitters
• Studying wireless networks based on geometry is discussed in http://users.ece.utexas.edu/~jandrews/stochgeom/index.htm
We look at signal processing approaches for spectrum sensing here
![Page 9: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/9.jpg)
Spectrum Sensing
![Page 10: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/10.jpg)
Methods of spectrum sensing
![Page 11: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/11.jpg)
Aspects of Spectrum Sensing
![Page 12: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/12.jpg)
Regulatory constraints
![Page 13: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/13.jpg)
Spectrum Sensing Uncertainties
![Page 14: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/14.jpg)
Spectrum Sensing Uncertainties
![Page 15: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/15.jpg)
Detection Sensitivity
![Page 16: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/16.jpg)
Detection Sensitivity
![Page 17: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/17.jpg)
Spectrum Sensing - Approaches
![Page 18: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/18.jpg)
Spectrum Sensing
![Page 19: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/19.jpg)
Energy Detector
![Page 20: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/20.jpg)
Performance of Energy Detector
![Page 21: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/21.jpg)
Performance of Energy Detector (contd.)
![Page 22: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/22.jpg)
Correlation Detector
![Page 23: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/23.jpg)
Low Complexity Hybrid Detector for GSM
![Page 24: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/24.jpg)
Key Question
• Can we look at a spectrum sensing algorithm that does not depend on:
- Estimate of noise variance
- Prior knowledge of the signal
![Page 25: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/25.jpg)
Covariance Based Detector
Consider binary hypothesis testing problem again:
The transmitted signal is s(n) and the i.i.d white noise is
with variance )n(
2
Consider L consecutive samples of and define the following vectors
![Page 26: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/26.jpg)
Covariance Based Detector
• Consider the statistical covariance matrices of the signal and noise:
•The off diagonal elements of covariance matrix are zero if the signal is not
present.
• If the signal is present and the signal samples are correlated then covariance
matrix is not a diagonal matrix.
•Consider the following:
![Page 27: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/27.jpg)
Covariance Based Detector
• If there is no signal the ratio of T1 and T2 is ONE.
• If the signal is present the ratio is greater than one
• For a given probability of false alarm the threshold is set for the ratio T1 andT2
- The threshold is not related to noise power. Hence, robust to noise uncertainty
- The performance of the detector improves with the smoothing factor
- The performance of the detector also depends on number samples used for computing the sample autocorrelation
• Difficult to set the threshold based on probability of detection since signal is unknown
![Page 28: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/28.jpg)
Spectral Covariance Based Sensing
• Spectral covariance based sensing (SCS)
- Exploits correlation of the signal and noise in frequency domain
- Test statistics computed from partial spectrogram and compared with a threshold
- 3dB performance improvement over covariance based detector for DTV signal detection
![Page 29: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/29.jpg)
Key steps in the algorithm
• Down-convert the received signal to the base band
• Low pass filter and down-sample the received signal
• Compute the spectrogram of the signal
• Select the components near the DC terms for every dwell in the spectrogram
![Page 30: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/30.jpg)
Key steps in the algorithm
• The reduced spectrogram matrix:
- Selects the spectral feature of the desired signal
- Reduces noise power
- Computational reduces
• Calculate sample covariance matrix
• Compute the test statistic:
A threshold is obtained for T1 and T2 based on the probability of false
alarm.
![Page 31: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/31.jpg)
Improved SCS: Multi-band SCS System Model
![Page 32: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/32.jpg)
Performance of multi-band SCS
Performance of MB-SCS algorithm for DTV signals
![Page 33: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/33.jpg)
Performance with noise uncertainity
![Page 34: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/34.jpg)
Key conclusions
• Spectrum sensing using energy detection requires estimate of noise uncertainity
• Correlation based techniques require signal model
• Spectrum sensing algorithm using statistical covariance
- Without signal knowledge
- Without estimate of noise uncertainty
• Next steps
- Co-operative spectrum sensing
- Cross layer based approaches for sensing
![Page 35: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/35.jpg)
Thank You
![Page 36: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/36.jpg)
Backup Slides
![Page 37: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/37.jpg)
Software Defined Radios (SDR)
• Software Defined Radio (SDR)- A Software Defined Radio is a radio that is flexible
(programmable) to accommodate various physical layer formats and protocols
- A multiband, multimode radio with dynamic capability defined through software covering all layers of OSI protocol stack
Software Architecture
Reconfigurable
Generic Hardware
Flexible
Multiple Protocols
Upgradeable
Multiple Frequencies
Interoperable
![Page 38: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/38.jpg)
Radio Architecture
![Page 39: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/39.jpg)
Classification of SDRs
• Multi-band System
• Multi-standard System
• Multi-service system
• Multi-Channel System
![Page 40: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/40.jpg)
SDR Drivers: NCW (Military) Vs ATM (Commercial)
• NCW in Military environment
• 33 Waveforms
• Key Initiative : JTRS program w/ clusters & incremental waveforms
- Cluster 1: Ground vehicles, Helicopters
- Cluster 2 : Hand-held
- Cluster 3 & 4 : Airborne, marine & fixed (AMF)
- Cluster 5 : Manpack/handheld radios
• ATM in commercial Airspace(NAS in U.S)
• 26 Waveforms across CNS
• Key Initiative : CNS/ATM Systems
- 3 radio cores (C,N & S) common across 3 segments AT
BRH
GA
- Or A single CNS radio Core across 3
segments?
Network Centric Warfare(NCW) Air Traffic Management (ATM)
NCW mirrors ATM; Priorities for Military & commercial differ!
![Page 41: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/41.jpg)
Software Defined Radio to Cognitive Radio
• The FCC refers to a Software Defined Radio (SDR) as:
- “a transmitter in which the operating parameters … can be altered by making a change in software that controls the operation of the device without … changes in the hardware components that affect the radio frequency emissions.”
• The FCC view of cognitive radio:- “A cognitive radio (CR) is a radio that can change its transmitter parameters
based on interaction with the environment in which is operates.
![Page 42: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/42.jpg)
Definition: Cognition
• According to Encyclopedia of Computer Science:
- Mental states and processes intervene between input stimuli and output responses
- The mental states and processes are described by algorithms
- The mental states and processes lend themselves to scientific investigations
Please note this is from a computational perspective
![Page 43: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/43.jpg)
Why Cognitive Radios?
• Spectrum Utilization
- Presence of “Spectrum Holes”: band allocated to an user remains unused at a given time and geographical location
• Reliable communication
![Page 44: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/44.jpg)
Definition: Cognitive Radio
• An intelligent reconfigurable radio that is aware of its surrounding environment
• Adapts its internal states to statistical variations in the incoming RF signal by making corresponding changes in the certain parameters to provide:
- Reliable communication
- Improved spectrum utilization
![Page 45: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/45.jpg)
Cognitive Radio
• Responds to operators commands: “Turning the knobs”
• Also monitors its own performance continuously
![Page 46: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/46.jpg)
Cognitive Radios: Tasks
• Reconfigurability: achieved through Software Defined Radio
• Other Cognitive tasks achieved using:
- Signal processing
- Machine learning
• Starts with passive sensing of RF stimuli and culminates with an action
![Page 47: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/47.jpg)
Cognitive Radios: Tasks (contd.)
• Radio-scene analysis
- Estimation of “Interference Temperature”
Spectrum estimation techniques
- Detection of “Spectrum Holes”
Statistical techniques employed to detect
• Channel identification
- Estimation of channel state information
Blind and semi-blind approaches
- Prediction of channel capacity for use by the transmitter
• Co-operation
- Transmit power control and dynamic spectrum management
- Game theoretic approahes
• Dynamic Spectrum Sharing
![Page 48: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/48.jpg)
Radio Scene Analysis
• Time-frequency analysis
• Multi-taper spectral estimation
- Optimal
• Large number of sensor to obtain the spatial variation
• Adaptive beamforming
- At the transmitter power is preserved
- At the receiver leads to improved interference cancellation
![Page 49: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/49.jpg)
Transmit Power Control
• Optimal control theoretic based approach
• Game theoretic approach in the presence of competition
• Aims to:
- select the transmit power levels of n-unserviced users to jointly maximize their data-transmission rates, subject to the constraint of interference temperature
• Computationally feasible approach for a non-cooperative multi-user scenario:
- Maximize the performance of each unserviced transceiver subject to the constraint of interference temperature, irrespective what other transceivers do
![Page 50: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/50.jpg)
Dynamic Spectrum Management
• Builds on the
- Spectrum holes detected
- Output of transmit power control
• Selects:
- A modulation strategy that adapts to the time varying conditions of the radio environment
• In OFDM case:
- Number of bits per channel varied based on the SNR
- Bandwidth and carrier frequency dynamically modified depending on “Spectrum Holes”
![Page 51: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/51.jpg)
Illustration
![Page 52: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/52.jpg)
A possible test bed
![Page 53: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/53.jpg)
Consciousness in UWB networks
• Hybrid modeling for admission control
- A node leaves the network when there is no data to transmit, node failure or power exhaustion – discrete case
- Changes in the radio environment – Continuous case
![Page 54: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/54.jpg)
Consciousness in UWB networks (contd.)
• In the uplink situation the time varying set of parameters are obtained based on
- Waveform used for pulse shaping
- Power level at base station
- Noise level at base station
- MUI
- Number of active nodes
![Page 55: viswanath](https://reader034.vdocument.in/reader034/viewer/2022052409/5450caf5af7959ff088b4f59/html5/thumbnails/55.jpg)
Concluding Remarks
• All of the benefits of software defined radio
• Improved link performance
– Adapt away from bad channels
– Increase data rate on good channels
• Improved spectrum utilization
–Fill in unused spectrum
– Move away from over occupied spectrum
• New business propositions
–High speed internet in rural areas
–High data rate application networks (e.g., Video-conferencing)
• Significant interest from FCC, DoD
– Possible use in TV band reframing