Method and apparatus for detecting presence of signal in wireless communication system based on CR technology
The present invention relates to a method of detecting the presence of a transmission signal of a transmitter in a reception signal in a wireless communication system based on CR technology. The method includes generating a frequency signal vector using a Fourier transform and a reception signal vector obtained by sampling the reception signal at a certain period, finding an eigenvalue and an eigenvector regarding a matrix, obtaining by approximating a covariance matrix of the frequency signal vector using a vectorized Fourier transform result of all channel impulse responses of the transmission signal linearly modulated, calculating a sufficient statistic on a basis of the frequency signal vector, the eigenvalue, and the eigenvector, finding a threshold which is a criterion for determining signal presence detection on a basis of a preset detection probability or a preset false alarm probability and the eigenvalue, and if the sufficient statistic is determined to be greater than the threshold, determining that the transmission signal exists.
1. A method of detecting a presence of a transmission signal, sent by a transmitter, in a reception signal in a wireless communication system based on Cognitive Radio (CR) technology, the method comprising:
generating a frequency signal vector using a Fourier transform and a reception signal vector obtained by sampling the reception signal at a certain period;
finding an eigenvalue and an eigenvector of a matrix obtained by approximating a covariance matrix of the frequency signal vector by using a vectorized Fourier transform result of a channel impulse response of a transmission signal;
calculating a sufficient statistic on a basis of the frequency signal vector, the eigenvalue, and the eigenvector;
finding a threshold which is a criterion for determining signal presence detection on a basis of a preset detection probability or a preset false alarm probability and the eigenvalue; and
if, as a result of the determination, the sufficient statistic is greater than the threshold, determining that the transmission signal exists.
2. The method of claim 1 , wherein the frequency signal vector is a product of a discrete Fourier transform matrix and a reception signal vector obtained by sampling the reception signal.
3. The method of claim 1 , wherein:
the eigenvector is proportional to the vectored Fourier transform result of all the channel impulse responses and a Kronecker product of a standard fundamental vector, and
the eigenvalue is proportional to a square of the vectored Fourier transform result of all the channel impulse responses and the Kronecker product of the standard fundamental vector.
4. The method of claim 1 , wherein:
the matrix obtained by approximating the covariance matrix of the frequency signal vector is a block matrix in which each element is a diagonal matrix, and
a diagonal component of each of the diagonal matrices is proportional to a dual Fourier transform result of an autocorrelation function of the reception signal.
5. The method of claim 1 , wherein the sufficient statistic
l
^
(
y
)
is
l
^
(
y
)
=
∑
k
=
1
K
λ
^
k
σ
N
2
(
σ
N
2
+
λ
^
k
)
v
^
k
ℋ
Wy
2
where {circumflex over (λ)} k a kth eigenvalue of the matrix obtained by approximating the covariance matrix of the frequency signal vector, {circumflex over (v)} k H a Hermitian transpose of the kth eigenvector of the matrix obtained by approximating the covariance matrix of the frequency signal vector, σ N 2 is a variance value of a noise component, and Wy is the frequency signal vector.
6. The method of claim 1 , wherein the threshold η is
η
=
∑
k
=
1
K
(
λ
^
k
σ
N
2
)
2
Q
-
1
(
P
D
)
+
∑
k
=
1
K
λ
^
k
σ
N
2
for a detection probability P D where {circumflex over (λ)} k is a kth eigenvalue of the matrix obtained by approximating the covariance matrix of the frequency signal vector, σ N 2 is a variance value of a noise component, Q −1 (x) is a reversed function of a function Q(x) , the function Q(x) is a probability that the function Q(x) can have a value greater than x in a standard normal distribution, and K is a period number in which a signal is received.
7. The method of claim 1 , wherein the threshold η is
η
=
∑
k
=
1
K
(
λ
^
k
σ
N
2
+
λ
^
k
)
2
Q
-
1
(
P
FA
)
+
∑
k
=
1
K
λ
^
k
σ
N
2
+
λ
^
k
for a false alarm probability P FA where {circumflex over (λ)} k a kth eigenvalue of the matrix obtained by approximating the covariance matrix of the frequency signal vector, σ N 2 is a variance value of a noise component, Q −1 (x) is a reversed function of a function Q(x) , the function Q(x) is a probability that the function Q(x) can have a value greater than x in a standard normal distribution, and K is a period number in which a signal is received.
8. An apparatus for detecting a presence of a transmission signal, sent by a transmitter, in a reception signal in a wireless communication system based on Cognitive Radio (CR) technology, the apparatus comprising:
a reception unit for receiving the reception signal through a channel;
a transform unit for generating a frequency signal vector using a Fourier transform and a reception signal vector obtained by sampling the reception signal at a certain interval;
a preliminary calculation unit for finding an eigenvalue and an eigenvector of a matrix obtained by approximating a covariance matrix of the frequency signal vector by using a vectored Fourier transform result of a channel impulse response of a transmission signal;
a calculation unit for calculating a sufficient statistic on a basis of the frequency signal vector, the eigenvalue, and the eigenvector;
finding a threshold which is a criterion for determining signal presence detection on a basis of a preset detection probability or a preset false alarm probability and the eigenvalue; and
a detection unit for, if, as a result of the determination, the sufficient statistic is greater than the threshold, determining that the transmission signal exists.
9. The apparatus of claim 8 , wherein the frequency signal vector is a product of a discrete Fourier transform matrix and a reception signal vector obtained by sampling the reception signal.
10. The apparatus of claim 8 , wherein:
the eigenvector is proportional to the vectored Fourier transform result of all the channel impulse responses and a Kronecker product of a standard fundamental vector, and
the eigenvalue is proportional to a square of the vectored Fourier transform result of all the channel impulse responses and the Kronecker product of the standard fundamental vector.
11. The apparatus of claim 8 , wherein:
the matrix obtained by approximating the covariance matrix of the frequency signal vector is a block matrix in which each element is a diagonal matrix, and
a diagonal component of each of the diagonal matrices is proportional to a dual Fourier transform result of an autocorrelation function of the reception signal.
12. The apparatus of claim 8 , wherein the sufficient statistic
l
^
(
y
)
is
l
^
(
y
)
=
∑
k
=
1
K
λ
^
k
σ
N
2
(
σ
N
2
+
λ
^
k
)
v
^
k
ℋ
Wy
2
where {circumflex over (λ)} k a kth eigenvalue of the matrix obtained by approximating the covariance matrix of the frequency signal vector, {circumflex over (v)} k H a Hermitian transpose of the kth eigenvector of the matrix obtained by approximating the covariance matrix of the frequency signal vector, σ N 2 is a variance value of a noise component, and Wy is the frequency signal vector.
13. The apparatus of claim 8 , wherein the threshold η is
η
=
∑
k
=
1
K
(
λ
^
k
σ
N
2
)
2
Q
-
1
(
P
D
)
+
∑
k
=
1
K
λ
^
k
σ
N
2
for a detection probability P D where {circumflex over (λ)} k is a kth eigenvalue of the matrix obtained by approximating the covariance matrix of the frequency signal vector, σ N 2 is a variance value of a noise component, Q −1 (x) is a reversed function of a function Q(x), the function Q(x) is a probability that the function Q(x) can have a value greater than x in a standard normal distribution, and K is a period number in which a signal is received.
14. The apparatus of claim 8 , wherein the threshold η is
η
=
∑
k
=
1
K
(
λ
^
k
σ
N
2
+
λ
^
k
)
2
Q
-
1
(
P
FA
)
+
∑
k
=
1
K
λ
^
k
σ
N
2
+
λ
^
k
for a false alarm probability P FA where {circumflex over (λ)} k a kth eigenvalue of the matrix obtained by approximating the covariance matrix of the frequency signal vector, σ N 2 is a variance value of a noise component, Q −1 (x) is a reversed function of a function Q(x), the function Q(x) is a probability that the function Q(x) can have a value greater than x in a standard normal distribution, and K is a period number in which a signal is received.