21-07-2011, 02:09 PM
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Spectrum sensing based on energy detection
Today’s topic
Background of energy detection
Energy detection of unknown deterministic signal
Energy detection of unknown signal over fading channels
Background of energy detection
Energy detection of unknown deterministic signal
The detection of a deterministic signal in white Gaussian noise reduces to the consideration of the sum of the squares of statistically independent Gaussian variates.
Lowpass processes
Bandpass processes
Introduce a method of computing the detection and false alarm probabilities.
Moderate values of TW
Large values of TW
Lowpass processes
Signal: deterministic (little know about form)
the spectral region is known
Gaussian
Noise: Gaussian and additive with zero mean.
flat band-limited power density spectrum.
bandwidth W
Lowpass processes
Lowpass processes
also signal energy can be written as:
Bandpass processes
If the noise is a bandpass random process, each sample function may be expressed in the form:
Energy detection of unknown deterministic signal
The detection of a deterministic signal in white Gaussian noise reduces to the consideration of the sum of the squares of statistically independent Gaussian variates.
Lowpass processes
Bandpass processes
Introduce a method of computing the detection and false alarm probabilities.
Moderate values of TW
Large values of TW
Computation of detection and false alarm probability
The probability of false alarm :
Computation of detection and false alarm probability
If 2TW≥250, we use Gaussian approximations to the probability density functions of the test statistic
DISCUSSION OF RELATED WORK
Marcum
Kaplan
Energy detection of unknown signal over fading channels
First
obtain closed-form expressions for the probability of detection over Rayleigh, Nakagami and Rician fading channels.
Second
quantify the improvement in the
probability of detection when equal gain combining (EGC), selection combining (SC), and switch and stay combining (SSC) diversity schemes are used.
and over AWGN channels
Over fading channel with no diversity
Over fading channel with no diversity
with diversity reception
Diversity paths are IID and are subject to Rayleigh fading
with diversity reception
Conclusions
The detection of a deterministic signal in white Gaussian noise reduces to the consideration of the sum of the squares of statistically independent Gaussian variates.
Introduce a method of computing the detection and false alarm probabilities
obtain closed-form expressions for the probability of detection over Rayleigh, Nakagami and Rician fading channels.
quantify the improvement in the
probability of detection when equal gain combining (EGC), selection combining (SC), and switch and stay combining (SSC) diversity schemes are used
Spectrum sensing based on energy detection
Today’s topic
Background of energy detection
Energy detection of unknown deterministic signal
Energy detection of unknown signal over fading channels
Background of energy detection
Energy detection of unknown deterministic signal
The detection of a deterministic signal in white Gaussian noise reduces to the consideration of the sum of the squares of statistically independent Gaussian variates.
Lowpass processes
Bandpass processes
Introduce a method of computing the detection and false alarm probabilities.
Moderate values of TW
Large values of TW
Lowpass processes
Signal: deterministic (little know about form)
the spectral region is known
Gaussian
Noise: Gaussian and additive with zero mean.
flat band-limited power density spectrum.
bandwidth W
Lowpass processes
Lowpass processes
also signal energy can be written as:
Bandpass processes
If the noise is a bandpass random process, each sample function may be expressed in the form:
Energy detection of unknown deterministic signal
The detection of a deterministic signal in white Gaussian noise reduces to the consideration of the sum of the squares of statistically independent Gaussian variates.
Lowpass processes
Bandpass processes
Introduce a method of computing the detection and false alarm probabilities.
Moderate values of TW
Large values of TW
Computation of detection and false alarm probability
The probability of false alarm :
Computation of detection and false alarm probability
If 2TW≥250, we use Gaussian approximations to the probability density functions of the test statistic
DISCUSSION OF RELATED WORK
Marcum
Kaplan
Energy detection of unknown signal over fading channels
First
obtain closed-form expressions for the probability of detection over Rayleigh, Nakagami and Rician fading channels.
Second
quantify the improvement in the
probability of detection when equal gain combining (EGC), selection combining (SC), and switch and stay combining (SSC) diversity schemes are used.
and over AWGN channels
Over fading channel with no diversity
Over fading channel with no diversity
with diversity reception
Diversity paths are IID and are subject to Rayleigh fading
with diversity reception
Conclusions
The detection of a deterministic signal in white Gaussian noise reduces to the consideration of the sum of the squares of statistically independent Gaussian variates.
Introduce a method of computing the detection and false alarm probabilities
obtain closed-form expressions for the probability of detection over Rayleigh, Nakagami and Rician fading channels.
quantify the improvement in the
probability of detection when equal gain combining (EGC), selection combining (SC), and switch and stay combining (SSC) diversity schemes are used