Slides - students

Cooperative spectrum sensing in
cognitive radio
Aminmohammad Roozgard
• Primary User (PU)
• Secondary User (SU)
• Cognitive Radio(CR)
• Probability of False alarm:P
– probability of a CR user declaring that a PU is
present when the spectrum is actually free
• Probability of detection: P
– probability of a CR user declaring that a PU is
present when the spectrum is indeed occupied by
the PU
• CR users should not cause harmful
interference to PUs by either switching to an
available band or limiting its interference with
PUs at an acceptable level
• CR users should efficiently identify and exploit
the spectrum holes for required throughput
and quality-of-service (QoS)
Sensing problems
• multipath fading
• Shadowing
• the receiver uncertainty problem
Why cooperation
• enhance the sensing performance by using
the spatial diversity in the observations of
spatially located CR users
(detection performance cannot be improved
by increasing the sensitivity, when the SNR of
PU signals is below a
certain level)
Gain vs Overhead
• Cooperation Gain
– performance improvement due to spatial diversity
• Cooperation Overhead
– any extra sensing time, delay, energy, and operations
devoted to cooperative sensing compared to the
individual (non-cooperative) spectrum sensing case
– any performance degradation in correlated shadowing
or the vulnerability to security attacks
Main questions
• How can cognitive radios cooperate?
(cooperation methods)
• How much can be gained from cooperation?
(cooperation gain)
• What is the overhead associated with
cooperation? (cooperation overhead)
Signal detection
Cooperation categories
a) Centralized
b) Distributed
c) Relay-assisted
• Sensing channel:
– selected licensed channel where a physical pointto-point link between the PU transmitter and each
cooperating CR user for observing the primary
• Reporting channel:
– For data reporting, all CR users are tuned to a
control channel where a physical point-to-point
link between each cooperating CR user and the FC
for sending the sensing results
Centralized Cooperation
the Fusion Center (FC) selects a
channel for sensing and instructs
all cooperating CR users to individually perform
local sensing
all cooperating CR users report their sensing
results via the control channel
the FC combines the received local sensing
information, determines the presence of PUs,
and diffuses the decision back to cooperating CR
Distributed Cooperation
• does not rely on a FC for making the cooperative
• CR users communicate among themselves and
converge to a unified decision on the presence or
absence of PUs
– by iterations
– based on a distributed algorithm, each CR user
sends its own sensing data to other users
combines its data with the received data
decides whether or not the PU is present
sends its decision
repeat until converge
Relay-assist cooperation
• both sensing channel and report channel are not
– a CR user observing a weak sensing channel and a
strong report channel
– a CR user with a strong sensing channel and a weak
report channel
• CRs can complement and
cooperate with each other to
improve the performance of
cooperative sensing
Cooperation steps
• Local sensing
• Reporting
• Data Fusion
Elements of cooperation
• Cooperation models:
how CRs cooperate for sensing
– parallel fusion network models
– game theoretical models
• Sensing techniques
taking observation samples
Elements of cooperation
• Hypothesis testing
a statistical test to
determine the presence
or absence of a PU.
– individually by each cooperating user
– performed by the fusion center
• Control channel and reporting concerns
how the sensing results can be efficiently and reliably
– bandwidth-limited
– fading-susceptible control channel
Elements of cooperation
• Data fusion:
process of combining the reported
shared sensing results
– signal combining techniques
– decision fusion rules
• User selection:
how to optimally select the cooperating CRs
– maximize the cooperative gain
– minimize the cooperation overhead
• Knowledge base
stores the information of sensing
– improve the detection performance
– a priori knowledge
– knowledge accumulated through the experience.
Cooperation models
• Parallel fusion model
– sensing
• Game theoretical models
– Cooperation
Sensing Technique
• Wide band
• Narrow band
• Coherent
– Using prior knowledge
• Non coherent
– No prior knowledge
Sensing Technique
• Energy detection
– Long sensing time
– depend on noise
– No distinguish between PU & SU
• Cyclostationary feature detection
– High computational complexity
– Long sensing time
• Compressed sensing
– Hardware
Hypothesis testing
• Binary hypothesis testing
– Likelihood ratio test (LRT)
– Bayes test
• Composite hypothesis testing
• Sequential testing
– Two thresholds
Control channel
• Bandwidth requirement
– Censoring
• reduces the unnecessary reporting and the usage of control
channel bandwidth
– Fixed bands
– Dynamic bands
• Reliability requirement
perfect error-free control channel
Gaussian noise
multipath fading
correlated shadowing
Data Fusion
• Soft combining
– complete local test statistics
– Best Result
– Methods:
• Equal gain combining (EGC)
• Maximal ratio combining (MRC)
• Quantized soft combining
– Only the quantized data for soft combining
• Hard combining
– users make a local decision and transmit the one bit decision
– Less channel bandwidth
– Methods:
• And
• Or
• Majority
User Selection
• independent CR users for cooperation can
improve the robustness of sensing results
• removing malicious users
• Methods:
– Centralized selection
– Cluster-based selection
Knowledge base
• Rules
– enhance the detection performance
• Accumulated knowledge
• Learned experience
– alleviate the burden of cooperative sensing
• retrieving the spectrum information
– list of PU-occupied channels from the database.
• Approaches
radio environment map (REM)
received signal strength (RSS) profiles
Channel gain map
power spectral density (PSD) map
gain and overhead
• sensing time and delay
Number of samples
Collision on report Channel
Relay data*
• channel impairments
– Multipath fading and shadowing
– Spatially correlated shadowing
• having a small number of CR users over a large distance may
be more effective than a large number of closely located
gain and overhead
• energy efficiency
Censoring Users
Optimal sensing time*
Optimal number of CRs*
• cooperation efficiency
– Sensing scheduling*
– Speed of converge*
• Mobility
– PU mobility*
– SU mobility
gain and overhead
• Security
– Data falsification
• Anomaly detection*
– Attacks
• PU emulation attack
• Control channel jamming
• Node capture attack*
• wideband sensing
– Multi-band cooperative sensing*
– Wideband cooperative sensing*
• Akyildiz, Ian F., Brandon F. Lo, and Ravikumar
Balakrishnan. "Cooperative spectrum sensing
in cognitive radio networks: A survey."
Physical Communication 4, no. 1 (2011): 4062.
• Movement

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