CN107196721B - OFDM signal spectrum sensing method under time asynchronization and frequency offset condition - Google Patents

OFDM signal spectrum sensing method under time asynchronization and frequency offset condition Download PDF

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CN107196721B
CN107196721B CN201710472617.7A CN201710472617A CN107196721B CN 107196721 B CN107196721 B CN 107196721B CN 201710472617 A CN201710472617 A CN 201710472617A CN 107196721 B CN107196721 B CN 107196721B
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朱泽文
金明
余杰
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Ningbo University Science Park Development Co ltd
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Abstract

The invention discloses an OFDM signal frequency spectrum sensing method aiming at time asynchronization and frequency offset, which samples a received signal from a monitoring channel to obtain a sampled signal; then, estimating and obtaining noise power by utilizing autocorrelation of a cyclic prefix of an OFDM signal in a received signal under the conditions of time asynchronization and frequency offset according to sampling values of all sampling points in the sampled signal; calculating a covariance matrix of the sampling signal according to the sampling value of the sampling point in the sampling signal; then, calculating test statistic according to the noise power and the covariance matrix of the sampling signals; finally, whether an authorized user signal exists in the monitoring channel is judged by comparing the test statistic with the obtained judgment threshold so as to realize spectrum sensing; the method has the advantages that the spectrum sensing performance of the OFDM signal can be effectively improved, and the calculation complexity is low.

Description

OFDM signal spectrum sensing method under time asynchronization and frequency offset condition
Technical Field
The invention relates to a spectrum sensing method in a cognitive radio system, in particular to an OFDM signal spectrum sensing method aiming at time asynchronization and frequency offset condition based on noise power estimation.
Background
The cognitive radio system can sense the surrounding communication environment in real time, identify available idle channels, and then adaptively adjust system parameters of a cognitive radio network according to spectrum sensing results, so that the cognitive radio system has the capacity of intelligently identifying and changing spectrum use opportunities.
Orthogonal Frequency Division Multiplexing (OFDM) technology has the characteristic of high spectrum utilization rate, and is one of the technologies widely adopted by current and future wireless communication standards, so that the technology has a very important significance in researching spectrum sensing of OFDM signals (namely judging whether OFDM signals exist in a channel). Existing spectrum sensing methods for OFDM signals can be divided into frequency domain detection and time domain detection. The frequency domain detection needs to calculate the frequency spectrum of the sampling signal, so that the frequency domain detection has larger calculation amount; the time domain detection mainly utilizes the autocorrelation characteristic of the cyclic prefix in the OFDM signal to realize spectrum sensing, and the calculated amount is low. In 2009, Zeng et al proposed a Spectrum sensing method based on statistical covariance in cognitive radio, which can use correlation in OFDM signals to realize Spectrum sensing and has the characteristic of low calculated amount, but the method does not consider the specific situations of time asynchrony and frequency offset, so that the cyclic prefix autocorrelation characteristic of OFDM signals cannot be effectively used.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method for sensing the frequency spectrum of an OFDM signal under the condition of time asynchronization and frequency offset based on noise power estimation, which can effectively improve the frequency spectrum sensing performance of the OFDM signal and has low computational complexity.
The technical scheme adopted by the invention for solving the technical problems is as follows: a method for sensing OFDM signal frequency spectrum under the condition of time asynchronization and frequency offset is characterized in that the processing procedure is as follows: firstly, sampling a received signal from a monitoring channel to obtain a sampling signal; then, estimating and obtaining noise power by utilizing autocorrelation of a cyclic prefix of an OFDM signal in a received signal under the conditions of time asynchronization and frequency offset according to sampling values of all sampling points in the sampled signal; calculating a covariance matrix of the sampling signal according to the sampling value of the sampling point in the sampling signal; then, calculating test statistic according to the noise power and the covariance matrix of the sampling signals; and finally, judging whether an authorized user signal exists in the monitoring channel by comparing the test statistic with the obtained judgment threshold so as to realize spectrum sensing.
The OFDM signal spectrum sensing method specifically comprises the following steps:
sampling a received signal from a monitoring channel for M times by using a sampling module in a cognitive radio system to obtain a sampling signal formed by sampling values of M sampling points, wherein M is K × N, K represents the total number of OFDM symbols contained in the OFDM signal in the received signal, K is more than or equal to 1, N represents the total number of subcarriers in any one OFDM symbol in the OFDM signal in the received signal, and N is Nc+Nd，NcRepresenting the length of the cyclic prefix of an OFDM signal in a received signal, NdRepresenting the total number of sub-carriers of useful data within any one OFDM symbol in an OFDM signal in a received signal, Nd≥Nc>1, and is provided with NcAnd NdAre all even;
step two: according to the sampling values of all sampling points in the sampling signal, under the conditions of time asynchronization and frequency offset, estimating and obtaining noise power by utilizing autocorrelation of the cyclic prefix of the OFDM signal in the received signal, and marking as
Figure BDA0001327452390000021
Figure BDA0001327452390000022
Where ρ isηAn estimate value representing a correlation coefficient of the received signal,
Figure BDA0001327452390000023
an estimate value representing the power of the received signal;
step three: calculating a covariance matrix, denoted as R, of the sampled signal based on the sampled values of the sampled points in the sampled signalx，RxIs a L×L-dimensional matrix, and R isxThe element in the ith row and the q th column is marked as Rx(i,q)，
Figure BDA0001327452390000031
Wherein, L∈ [2, M-1 ]]I is 1-L, q is 1-L, x (p) represents the sampling value of the p-th sampling point in the sampling signal, x*(p-q + i) is conjugate of x (p-q + i), wherein x (p-q + i) represents a sampling value of a p-q + i sampling point in the sampling signal;
step four: according to
Figure BDA0001327452390000032
And RxThe test statistic, denoted as T,
Figure BDA0001327452390000033
step five: acquiring a judgment threshold, and recording as lambda; then comparing the test statistic T with the size of a decision threshold lambda, and if T is larger than lambda, judging that an authorized user signal exists in the monitoring channel; if T is less than or equal to lambda, it is judged that no authorized user signal exists in the monitoring channel, and the monitoring channel is in an idle state, so that spectrum sensing is realized.
In the second step, the first step is carried out,
Figure BDA0001327452390000034
wherein Re () is the operation function of the real part,
Figure BDA0001327452390000035
Figure BDA0001327452390000036
x (2n-1) represents the sample value of the 2n-1 th sample point in the sample signal, x*(2n-1+Nd) Is x (2N-1+ N)d) Conjugate of (2N-1+ N)d) Representing the 2N-1+ N th of the sampled signaldA sample value of a sample point, x (2n) represents a sample point of 2n in the sample signalSampling value, x*(2n+Nd) Is x (2N + N)d) Conjugate of (2N + N)d) Representing the 2N + N th of the sampled signaldThe sampled values of the sample points, j, are in the form of imaginary representations and the symbol "∠" is an angular representation.
In the second step, the first step is carried out,
Figure BDA0001327452390000037
wherein M is more than or equal to 1 and less than or equal to M, x (M) represents the sampling value of the mth sampling point in the sampling signal, and the symbol "|" is an absolute value symbol.
Compared with the prior art, the invention has the advantages that:
1) the method does not need to calculate the eigenvalue of the covariance matrix and the frequency spectrum of the sampling signal, so the method has the characteristics of low calculation complexity and simple operation.
2) The method of the invention divides the sampling signal into an odd part and an even part to calculate the correlation coefficient of the received signal under the condition of frequency deviation, thereby eliminating the influence of the frequency deviation on the accuracy of the estimated noise power and improving the spectrum sensing performance of the OFDM signal.
3) Compared with the traditional noise power estimator which is only effective in noise samples, the process of estimating the noise power of the method fully utilizes the autocorrelation of the cyclic prefix of the OFDM signal, so that the noise power in the current perception time slot can be accurately estimated.
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FIG. 1 is a block flow diagram of the method of the present invention;
FIG. 2 shows that when N isd＝90、NcA schematic diagram of comparison of ROC curves obtained by using the method of the present invention and the covariance method proposed by Zeng et al when the received signal-to-noise ratio is-10 db;
FIG. 3 shows that when N isd＝80、NcA schematic diagram comparing ROC curves obtained by the method of the present invention and the covariance method proposed by Zeng et al when the received snr is-10 db.
Detailed Description
The invention is described in further detail below with reference to the accompanying examples.
The invention provides an OFDM signal spectrum sensing method aiming at time asynchronization and frequency offset, the flow chart of which is shown in figure 1, and the processing procedure is as follows: firstly, sampling a received signal from a monitoring channel to obtain a sampling signal; then, estimating and obtaining noise power by utilizing autocorrelation of a cyclic prefix of an OFDM signal in a received signal under the conditions of time asynchronization and frequency offset according to sampling values of all sampling points in the sampled signal; calculating a covariance matrix of the sampling signal according to the sampling value of the sampling point in the sampling signal; then, calculating test statistic according to the noise power and the covariance matrix of the sampling signals; and finally, judging whether an authorized user signal (namely an OFDM signal) exists in the monitoring channel by comparing the test statistic with the obtained judgment threshold so as to realize spectrum sensing.
The invention relates to an OFDM signal frequency spectrum sensing method under the conditions of time asynchronism and frequency offset, which specifically comprises the following steps:
sampling a received signal from a monitoring channel for M times by using a sampling module in a cognitive radio system to obtain a sampling signal formed by sampling values of M sampling points, wherein M is K × N, K represents the total number of OFDM symbols contained in the OFDM signal in the received signal, K is more than or equal to 1, N represents the total number of subcarriers in any one OFDM symbol in the OFDM signal in the received signal, and N is Nc+Nd，NcRepresenting the length of the cyclic prefix of an OFDM signal in a received signal, NdRepresenting the total number of sub-carriers of useful data within any one OFDM symbol in an OFDM signal in a received signal, Nd≥Nc>1, and is provided with NcAnd NdAre all even numbers.
Step two: according to the sampling values of all sampling points in the sampling signal, under the conditions of time asynchronization and frequency offset, estimating and obtaining noise power by utilizing autocorrelation of the cyclic prefix of the OFDM signal in the received signal, and marking as
Figure BDA0001327452390000051
Figure BDA0001327452390000052
Where ρ η represents an estimated value of the correlation coefficient of the received signal,
Figure BDA0001327452390000053
an estimate representing the power of the received signal.
In this embodiment, in step two,
Figure BDA0001327452390000054
wherein Re () is the operation function of the real part,
Figure BDA0001327452390000055
Figure BDA0001327452390000056
x (2n-1) represents the sample value of the 2n-1 th sample point in the sample signal, x*(2n-1+Nd) Is x (2N-1+ N)d) Conjugate of (2N-1+ N)d) Representing the 2N-1+ N th of the sampled signaldA sample value of a sample point, x (2n) represents a sample value of a 2 n-th sample point in the sample signal, x*(2n+Nd) Is x (2N + N)d) Conjugate of (2N + N)d) Representing the 2N + N th of the sampled signaldThe sampled values of the sample points, j, are in the form of imaginary representations and the symbol "∠" is an angular representation.
In this embodiment, in step two,
Figure BDA0001327452390000057
wherein M is more than or equal to 1 and less than or equal to M, x (M) represents the sampling value of the mth sampling point in the sampling signal, and the symbol "|" is an absolute value symbol.
Step three: calculating a covariance matrix, denoted as R, of the sampled signal based on the sampled values of the sampled points in the sampled signalx，RxIs a L×L-dimensional matrix, and R isxThe element in the ith row and the q th column is marked as Rx(i,q)，
Figure BDA0001327452390000058
Wherein, L∈ [2, M-1 ]]If taking
Figure BDA0001327452390000059
1 ≦ i ≦ L, 1 ≦ q ≦ L, x (p) represents the sample value of the p-th sample point in the sample signal, x*And (p-q + i) is conjugate of x (p-q + i), and x (p-q + i) represents a sampling value of a p-q + i-th sampling point in the sampling signal.
Step four: according to
Figure BDA00013274523900000510
And RxThe test statistic, denoted as T,
Figure BDA00013274523900000511
step five: acquiring a judgment threshold by using the prior art and recording the judgment threshold as lambda; then comparing the test statistic T with the size of a decision threshold lambda, and if T is larger than lambda, judging that an authorized user signal exists in the monitoring channel; if T is less than or equal to lambda, it is judged that no authorized user signal exists in the monitoring channel, and the monitoring channel is in an idle state, so that spectrum sensing is realized.
The feasibility and effectiveness of the method of the present invention is further illustrated by the following simulations.
Assuming that the OFDM signal in the received signal from the monitoring channel is asynchronous in time and has frequency offset, the total number N of subcarriers in the effective data of any one OFDM symbol in the OFDM signal in the received signald90, the length N of the cyclic prefix of the OFDM signal in the received signalc10, the total number N of subcarriers in any one OFDM symbol in the OFDM signal in the received signal is Nc+NdWhen K is 100 and 10+90, the sampling signal is composed of sampling values of 1400 sampling points where M is K × N is 14 × 100, and L is 5.
FIG. 2 shows that when Nd＝90、NcAn ROC curve obtained by the method of the present invention and the covariance method proposed by Zeng et al, respectively, when the received snr is-10 db. FromAs can be seen in FIG. 2, the ROC curve obtained by the method of the present invention is much higher than the ROC curve obtained by the covariance method proposed by Zeng et al, which fully indicates that the spectrum sensing performance of the method of the present invention is superior to the covariance method proposed by Zeng et al.
Assuming that the OFDM signal in the received signal from the monitoring channel is asynchronous in time and has frequency offset, the total number N of subcarriers in the effective data of any one OFDM symbol in the OFDM signal in the received signald80, the length N of the cyclic prefix of the OFDM signal in the received signalc20, the total number N of subcarriers in any one OFDM symbol in the OFDM signal in the received signal is Nc+NdWhen K is 14, the sampling signal is composed of sampling values of 1400 sampling points where M is K × N is 14 × 100, and L is 5.
FIG. 3 shows that when Nd＝80、NcROC curves obtained by the method of the present invention and the covariance method proposed by Zeng et al were used when the received snr was-10 db. As can be seen from FIG. 3, the ROC curve obtained by the method of the present invention is much higher than that obtained by the covariance method proposed by Zeng et al, which fully indicates that the spectrum sensing performance of the method of the present invention is better than that of the covariance method proposed by Zeng et al.
In addition, the ROC curves shown in fig. 2 and 3 are called sensitivity curves, the abscissa is false alarm probability, and the ordinate is detection probability; the larger the area below the curve is, the better the detection performance of the spectrum sensing method corresponding to the curve is.

Claims (3)

1. A method for sensing OFDM signal frequency spectrum under the condition of time asynchronization and frequency offset is characterized in that the processing procedure is as follows: firstly, sampling a received signal from a monitoring channel to obtain a sampling signal; then, estimating and obtaining noise power by utilizing autocorrelation of a cyclic prefix of an OFDM signal in a received signal under the conditions of time asynchronization and frequency offset according to sampling values of all sampling points in the sampled signal; calculating a covariance matrix of the sampling signal according to the sampling value of the sampling point in the sampling signal; then, calculating test statistic according to the noise power and the covariance matrix of the sampling signals; finally, whether an authorized user signal exists in the monitoring channel is judged by comparing the test statistic with the obtained judgment threshold so as to realize spectrum sensing;
the OFDM signal spectrum sensing method under the conditions of time asynchronization and frequency offset is characterized by comprising the following steps:
sampling a received signal from a monitoring channel for M times by using a sampling module in a cognitive radio system to obtain a sampling signal formed by sampling values of M sampling points, wherein M is K × N, K represents the total number of OFDM symbols contained in the OFDM signal in the received signal, K is more than or equal to 1, N represents the total number of subcarriers in any one OFDM symbol in the OFDM signal in the received signal, and N is Nc+Nd，NcRepresenting the length of the cyclic prefix of an OFDM signal in a received signal, NdRepresenting the total number of sub-carriers of useful data within any one OFDM symbol in an OFDM signal in a received signal, Nd≥NcIs greater than 1 and is provided with NcAnd NdAre all even;
step two: according to the sampling values of all sampling points in the sampling signal, under the conditions of time asynchronization and frequency offset, estimating and obtaining noise power by utilizing autocorrelation of the cyclic prefix of the OFDM signal in the received signal, and marking as
Figure FDA0002357748400000011
Figure FDA0002357748400000012
Where ρ isηAn estimate value representing a correlation coefficient of the received signal,
Figure FDA0002357748400000013
an estimate value representing the power of the received signal;
step three: calculating a covariance matrix, denoted as R, of the sampled signal based on the sampled values of the sampled points in the sampled signalx，RxIs a L×L-dimensional matrix, and R isxThe element in the ith row and the q th column is marked as Rx(i,q)，
Figure FDA0002357748400000014
Wherein, L∈ [2, M-1 ]]I is 1-L, q is 1-L, x (p) represents the sampling value of the p-th sampling point in the sampling signal, x*(p-q + i) is conjugate of x (p-q + i), wherein x (p-q + i) represents a sampling value of a p-q + i sampling point in the sampling signal;
step four: according to
Figure FDA0002357748400000021
And RxThe test statistic, denoted as T,
Figure FDA0002357748400000022
step five: acquiring a judgment threshold, and recording as lambda; then comparing the test statistic T with the size of a decision threshold lambda, and if T is larger than lambda, judging that an authorized user signal exists in the monitoring channel; if T is less than or equal to lambda, it is judged that no authorized user signal exists in the monitoring channel, and the monitoring channel is in an idle state, so that spectrum sensing is realized.
2. The method for sensing the frequency spectrum of the OFDM signal with time asynchronization and frequency offset according to claim 1, wherein in the second step,
Figure FDA0002357748400000023
wherein Re () is the operation function of the real part,
Figure FDA0002357748400000024
Figure FDA0002357748400000025
x (2n-1) represents the sample value of the 2n-1 th sample point in the sample signal, x*(2n-1+Nd) Is x (2N-1+ N)d) Conjugate of (2N-1+ N)d) Watch (A)Indicating the 2N-1+ N in the sampled signaldA sample value of a sample point, x (2n) represents a sample value of a 2 n-th sample point in the sample signal, x*(2n+Nd) Is x (2N + N)d) Conjugate of (2N + N)d) Representing the 2N + N th of the sampled signaldThe sampled values of the sample points, j, are in the form of imaginary representations and the symbol "∠" is an angular representation.
3. The method for sensing the frequency spectrum of the OFDM signal with time asynchronization and frequency offset according to claim 1 or 2, wherein in the second step,
Figure FDA0002357748400000026
wherein M is more than or equal to 1 and less than or equal to M, x (M) represents the sampling value of the mth sampling point in the sampling signal, and the symbol "|" is an absolute value symbol.
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