Ss. Cyril and Methodius University in Skopje Faculty of Electrical Engineering and Information Technologies (FEEIT) Institute of Telecommunications (ITK)
Spectrum Sensing Framework for Cognitive Radio Networks
Prof. Liljana Gavrilovska
Outline • Introduction • Spectrum sensing methods • Cooperative spectrum sensing • Availability and opportunity detection • Spectrum measurements • Activities • Conclusion Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Introduction • Cognitive Radio (CR) - a radio that can change its transmitter parameters based on interaction with the environment in which it operates Spectrum underutilization
• Functions of the CR: o o o o
Spectrum Sensing Spectrum Management Spectrum Sharing Spectrum Mobility
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
What is Spectrum Sensing? • Spectrum sensing : – based on measurements performed on spectrum environment – detect the presence of the licensed users – determine which portions of the spectrum is available
• Spectrum sensing is an enabling technology for secondary spectrum access F. Akyildiz, W.-Y. Lee, M. C. Vuran and S. Mohanty, “NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey,” Computer Networks 50, 2006, pp. 2127 – 2159.
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Spectrum Sensing framework Spectrum Sensing
Decision making
Rasoning (computation)
Information acquisition
Signal Detection
Pd Pf
Availability detection
Opportunity detection
Decision
Spectrum access
Signal Detection – The process of assessing the presence (or absence) of a signal on the sensed spectrum band Spectrum Availability – A state when spectrum use by a SU impacts the service of PUs within acceptable limits Spectrum Opportunity – A spectrum availability extended to comply to the user and service requirements Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Outline • Introduction • Spectrum sensing methods • Cooperative spectrum sensing • Availability and opportunity detection • Spectrum measurements • Activities • Conclusion Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Spectrum sensing methods
Spectrum Sensing
Transmitter detection • Blind sensing •Signal specific sensing
Receiver detection • LO leakage power sensing
Cooperative sensing • Centralized • Distributed
• Cooperatibve vs. non-cooperative • Single-antenna vs. multi-antenna Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Blind Spectrum Sensing (1/2) • Does not require any knowledge of the received signal • Decision is based on received signal power samples • Encompass energy and eigenvalue detection
• Energy detection – Compares the received signal (Y[n]) power with a decision threshold
– The threshold is set according to noise power level
• Eigenvalue detection – Collects signal samples and calculates a covariance matrix
– Matrix eigenvalues consist information for proper threshold selection
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Blind Spectrum Sensing (2/2) • Energy detection Advantages:
Disadvantages:
o Implementation simplicity and low computational complexities o Optimum detection if the primary user signal is not known
o Relies on the knowledge of accurate noise power o The performance in shadowing and fading environments degrades clearly
• Eigenvalue detection Advantages:
Disadvantages:
o Overcomes the noise uncertainty problem o Performs better when detected signals are correlated
o Higher computational complexity o Underperforms when detecting uncorrelated signals
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Signal Specific Spectrum Sensing (1/4) • A priory knowledge for the transmitted
signal required • Higher complexity and computing power than energy detection methods • Do not require a priory knowledge of the noise power
Signal specific spectrum sensing method flow
Signal specific spectrum sensing methods: • • • •
Matched filter Cyclostationary detector Waveform – based sensing Radio identification – based sensing Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Signal Specific Spectrum Sensing (2/4) Matched filter - This method uses linear filter that maximizes received signal-to-noise ratio. Decision metric
Advantages: o Optimal detection o Short sensing time
Disadvantages: o Full knowledge of the transmitted signal o Large power consumption as various receiver algorithms need to be executed o Perfect synchronization requirements
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Signal Specific Spectrum Sensing (3/4) Cyclostationary detector – analysis based on cyclicautocorrelation function, power spectral density (PSD) or spectral correlation function (SCF). Cyclic autocorrelation decision metric Advantages: o Do not require full knowledge
Disadvantages: o Knowledge of
of the transmitted signal o Applicable for most of the transmitting signals used o Good performance at low SNR
specific transmitted signal parameters o High computational complexity
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Signal Specific Spectrum Sensing (4/4) Waveform - The receiver
Advantages:
Disadvantages:
correlates the received signal with a copy of itself in order to perform sensing.
o Short sensing time o Good at low SNR
o Required knowledge for longer sequences of the transmitted signal for better performance
Advantages: o Good
Disadvantages: o Complex
knowledge for the spectrum utilization
computations o Combination of different techniques
Radio identification the method combines multiple spectrum sensing techniques.
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Performance Evaluation • The most common parameters characterizing the performance of the sensing techniques are: Probability of Detection - Pd
where
Probability of False alarm - Pf ROC curve – the plot of Pd vs. Pf
• Other key evaluation parameters include: SNR Dependence
Sensing Duration
Hardware Complexity
Processing Complexity
PU waveform differentiation
A priori knowledge
Energy Efficiency Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Energy efficient aspects • Data transmission and spectrum sensing powers must be controlled for interference-free operation and prolonged lifespan of CR systems. • Achieving power saving through sensing methods: o Cooperative sensing – sequential detection techniques o Intelligent learning based techniques
• Achieving power saving through spectrum sharing methods: o Cooperative spectrum sharing o Multihop transmissions
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Comparison of spectrum sensing methods • Sensing methods in terms of sensing accuracy and complexity
T. Ycek and H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio applications,” IEEE Communications Surveys & Tutorials, vol. 11, no. 1, pp. 116–160, 2009.
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Challenges Spectrum sensing is subjected to a variety of hardware related challenges as well as wireless communications induced phenomena: Hardware limitations
Mobility (both PUs and SUs)
Hidden PU problem
Receiver detection
Spread Spectrum PUs detection
Sensing duration vs. reliability
Existence of multiple CRs
Compressed sensing
Security
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Outline • Introduction • Spectrum sensing methods • Cooperative spectrum sensing • Availability and opportunity detection • Spectrum measurements • Activities • Conclusion Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Cooperative spectrum sensing (1/1)
• • • •
•
The basic idea is to allow neighboring CRs to exchange sensing information through a dedicated control channel. The information from all nodes is combined to make a decision. Without cooperation, multipath fading and shadowing affects the sensitivity requirements for maintaining confidence The probability that all nodes see deep fade is indeed extremely low. => taking advantage of spatial diversity Cooperation is used to reduce drastic sensitivity requirements imposed by multipath fading and shadowing. – A small number of CRs (10-20) is enough to achieve sensitivity close to the nominal path loss * S.M. Mishra, A. Sahai, and R. W. Brodersen,“Cooperative sensing among Cognitive Radios”, IEEE ICC 2006.
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Cooperative spectrum sensing (1/2)
Cooperation between CRs can be used to: - mitigate multipath fading and shadowing effects - reduce the number of samples (i.e. reduce processing time)
Sensing Nodes Channel Behavior
D1
H1 or H0
D3
D2
Fusion Center Decision=f({Di,i=1~N})
D3
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Shadowing in cooperative sensing • There is usually a high degree of spatial correlation with lognormal shadowing • Empirical data suggests an exponential correlation function for shadowing effects :
R(d ) = e− ad
(*)
where d is the distance between 2 locations and a is constant depending on the environment. * M. Gudmundson,“A correlation model for shadow fading in mobile radio,” Electronic Letters, Nov. 1991
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Control channel bandwidth • Low BW control channel – Nodes exchange decisions or statistics (not data vectors)
• High BW control channel – Nodes can exchange entire data vectors and hence sophisticated decisions can be performed
In most papers, the cooperation regime envisioned is to use the first method, due to the small used BW, and the distributed decision making. Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Type of cooperative sensing techniques • Cooperative spectrum sensing techniques differ according to: – the type of information (metrics) that nodes exchange: • hard decisions (final decisions on presence/absence of PU) • soft decisions (e.g. energy values observed by the different CRs)
– the rule used for combining the decisions of all CRs:
- AND rule, OR rule, majority rule,… (hard) - maximum ratio combination, equal gain combination (soft)
– the topology of the CR network: - centralized cooperation - distributed cooperation Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Centralized and distributed cooperative spectrum sensing • In a centralized mode, – each node sends its decision to a fusion center (FC) (e.g. a CR base station) through control channels; – The FC makes the final decision about the occupancy of the band by “combining” all decisions made by CRs. • In a distributed mode, – the nodes exchange their decisions among themselves and each node performs its own fusion ; – The node takes into account both its own decision and the decisions from other nodes. Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Receiver Operating Characteristic in cooperative sensing • Different architectures imply in different performance in terms of ROC
Relation between PFA and PMD and tier influence
Relation between PFA and PMD and grid influence
Viktoria Fodor, Ioannis Glaropoulos, Loreto Pescosolido,” Detecting low-power primary signals via distributed sensing to support opportunistic spectrum access”, IEEE ICC 2009, 2009
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
A cooperative sensing scenario (USRP2 based)
Valentina Pavlovska, Daniel Denkovski, Vladimir Atanasovski and Liljana Gavrilovska, “RACCE: Novel Rendezvous Protocol for Asynchronous Cognitive Radios in Cooperative Environments,” accepted for presentation on PIMRC 2010
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Outline • Introduction • Spectrum sensing methods • Cooperative spectrum sensing • Availability and opportunity detection • Spectrum measurements • Activities • Conclusion Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Availability detection based on cooperative sensing
• Multiple CR users exchange sensing
information • Mutual control channel is used • Solution for the hidden terminal problem by introducing spatial diversity
Data Fusion: o Hard decision o Soft decision (summary statistics combination)
• Centralized scheme o All nodes send the sensing info to a common controller o The decision is reached at the controller
• Distributed scheme o Sensing info is completely cooperatively exchanged o Every CR user reaches a decision using the exchanged information Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Availability detection based on databases • An alternative approach to spectrum sensing are databases – Centralized – Distributed
• Databases store data of spectrum occupancy – Space (S) – Time (T) – Frequency (F)
• Detailed information for all PUs in the S/T/F domains
Spectrum sensing RF end for sensing Sensing technique
Databases Decision Entity
e.g. IEEE 802.22 uses a channel availability database (CAD) in order to determine which channel is available at the location at a certain time Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
ID Space Time Frequency
Outline • Introduction • Spectrum sensing methods • Cooperative spectrum sensing • Availability and opportunity detection • Spectrum measurements • Activities • Conclusion Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Sensing in practice (1/4) • Extensive measurement campaigns report spectrum is heavily underutilized • EU: Aachen, Barcelona, Ireland, … • USA: Chicago, New York, Maine, …
• Inspected bands (up to 10 GHz) are divided into sub-bands, each inspected separately – Hundreds of frequency points per sub-band – Thousands of samples per frequency point – Gigabytes of information per single piece of spectrum McHenry, M. A., Tenhula, P. A., McCloskey, D., Roberson, D. A., and Hood, C. S., “Chicago spectrum occupancy measurements& analysis and a long-term studies proposal,” in Proc. of Workshop onTechnology and Policy for Accessing Spectrum (TAPAS), Boston, USA, 2006.
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Sensing in practice (2/4) • Previous measurement campaigns Research institution
Year
Location
NTIA - National
1993-1997
San Diego, Denver, San Francisco, Los Angeles
2005-2007
Chicago, Dublin, Maine, New York, Virginia…
2008
Singapore
RWTH Aachen University 2009 UPC - Universitat 2009
Aachen Barcelona
Telecommunications and Information Administration
SSC - Shared Spectrum company
I2R - Institute for Infocomm Research
Politècnica de Catalunya Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Sensing in practice (3/4) • Measurement architecture
• Spectrum occupancy – most common used decision metric • Energy detection - most common used spectrum sensing method in practice o Noise estimation – key parameter for accurate spectrum occupancy decision Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Sensing in practice (4/4) Energy detected values
Duty cycle distribution
Detection of usable white holes
Duty cycle - fraction (percentage) of time at which primary signal exist
Further examination of collected data is needed for building accurate spectral maps, spectrum access algorithms, utilization models etc. Islam, M., Tan, G. L., Chin, F., Toh,B. E.,Liang, Y.-C., Wang, C., Lai,Y. Y., Qing, X., Oh, S. W., Koh,C. L., and Toh,W., 2008, “Spectrum survey in Singapore: Occupancy measurements and analyses,” in Proc.of International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Singapore, May. 2008.
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Spectrum sniffer (USRP2 based)
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Outline • Introduction • Spectrum sensing methods • Cooperative spectrum sensing • Availability and opportunity detection • Spectrum measurements • Activities • Conclusion Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Relevant EU Projects FARAMIR
Developing new spectrum sensing techniques (cooperative and non - cooperative) and prototyping
QUASAR
Plans for methodology for spectrum sensing techniques evaluation (theoretical, performances…)
SENDORA
Evaluation of spectrum sensing techniques, a performance evaluation framework and simulations
EUWB
Spectrum sensing methods in the UWB concept
E3
Overview and development of a few spectrum sensing techniques and some testing and prototyping
• Other EU projects in the cognitive radio area include: – ARAGORN, SACRA, PHYDYAS, QoSMOS, CoGEU…
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Standardization • IEEEstandards: – 802.22: secondary spectrum access in TV bands – 802.11af, a new WLAN standard for secondary access in TV bands • SCC41, 1900.1-1900.6: different aspects of cognitive radio domain – 1900.6: Definition of spectrum sensing interfaces and data structures for DSA • ETSI RRS: 4 WGs, cognitive radio standardization process • SDR Forum: CR Wgs • Ecma 392: part of CongNeA, spectrum sensing issues Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Outline • Introduction • Spectrum sensing methods • Cooperative spectrum sensing • Availability and opportunity detection • Spectrum measurements • Activities • Conclusion Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
Conclusion • Spectrum sensing and DSA is a extensively developing and challenging area in sense of research • The follow up standardization process try to harmonize the ongoing research activities • New spectrum regulation rules and new business models are inevitable future Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
About us . . . Research oriented group specializing in wireless and mobile networking WiNGroup = Wireless Networks Group
Special attention on: Reconfigurability in future heterogeneous wireless systems Interoperability of different wireless systems Cognitive radio and policing spectrum usage Cross-layer optimizations in wireless protocol stacks Resource management in future heterogeneous wireless systems Sensor networking and RFID User personalization aspects
Members
Prof. Liljana Gavrilovska, PhD
WINGroup Leader
Assist. Vladimir Atanasovski, MSc Assist. Pero Latkoski, MSc Valentin Rakovic, BSc Daniel Denkovski, BSc Ognen Ognenoski, BSc Aleksandra Mateska, BSc Valentina Pavlovska, BSc Bisera Jankuloska, BSc Mihajlo Pavloski, BSc Milan Zahariev, BSc
Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
WiNGroup Projects FP7 ARAGORN (STREP) FP7 QUASAR (STREP) FP7 FARAMIR (STREP) FP7 ProSense (SSA) NATO SfP RIWCoS More information http://wingroup.feit.ukim.edu.mk Parts of this work were funded by the EC through the FP7 projects ARAGORN (216856) and QUASAR (248303). The authors would like to thank everyone involved. Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
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Joint CTIF Workshop May 31 - June 1, 2010 ”Green Energy” with focus on ”Cognitive Networks and Spectrum Management”
