CN107196720B - OFDM signal frequency spectrum sensing method under condition of time synchronization and no frequency offset - Google Patents

OFDM signal frequency spectrum sensing method under condition of time synchronization and no frequency offset Download PDF

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CN107196720B
CN107196720B CN201710472605.4A CN201710472605A CN107196720B CN 107196720 B CN107196720 B CN 107196720B CN 201710472605 A CN201710472605 A CN 201710472605A CN 107196720 B CN107196720 B CN 107196720B
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童景文
金明
姚俊腾
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Ningbo University
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Abstract

The invention discloses an OFDM signal frequency spectrum sensing method aiming at time synchronization and under the condition of no frequency offset, which samples a received signal from a monitoring channel to obtain a sampled signal; then, according to the sampling values of all sampling points in the sampling signal, under the conditions of time synchronization and no frequency offset, estimating and obtaining the noise power by utilizing the autocorrelation of the cyclic prefix of the OFDM signal in the received 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 frequency spectrum sensing method under condition of time synchronization and no frequency offset
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 synchronization and without frequency offset based on noise power estimation.
Background
With the rapid development of various wireless communication services and emerging communication technologies (such as ZigBee technology, fast access module, LTE technology, ultra wideband network, etc.), the importance and scarcity of spectrum resources are increasingly prominent. A lot of research shows that the current shortage of spectrum resources is not caused by the physical shortage of frequency resources, but mainly caused by the low utilization rate of the spectrum due to the fixed spectrum allocation management mechanism. Cognitive radio is an attempt to essentially solve the problem of increasing shortage of wireless communication resources by improving spectrum utilization. The cognitive radio system can sense the surrounding communication environment in real time, recognize available idle channels and then adaptively adjust the system parameters of the cognitive radio network according to the spectrum sensing result, so that the cognitive radio system has the capacity of intelligently identifying and changing spectrum use opportunities. In order to prevent interference to the existing communication system, the cognitive radio system must be able to reliably and effectively identify the idle channel, and therefore spectrum sensing is one of the key technologies in cognitive radio.
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. A covariance matrix-based Spectrum sensing method proposed by Zeng et al in 2009 in spectral sensitive spectra for statistical radio on statistical covariance, which can achieve Spectrum sensing by using correlation in OFDM signals, has the characteristic of low calculation amount, but does not consider specific conditions of time synchronization and no frequency offset, so that the cyclic prefix autocorrelation characteristic of OFDM signals cannot be effectively utilized.
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 synchronization and no 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 synchronization and no frequency offset is characterized in that the processing process is as follows: firstly, sampling a received signal from a monitoring channel to obtain a sampling signal; then, according to the sampling values of all sampling points in the sampling signal, under the conditions of time synchronization and no frequency offset, estimating and obtaining the noise power by utilizing the autocorrelation of the cyclic prefix of the OFDM signal in the received 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 synchronization and no 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 BDA0001327453010000021
Figure BDA0001327453010000022
Where ρ isηAn estimate value representing a correlation coefficient of the received signal,
Figure BDA0001327453010000023
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 matrix of L × L dimension, and R isxThe element in the ith row and the jth column is marked as Rx(i,j)，
Figure BDA0001327453010000031
Wherein, L ∈ [2, M-1]，1≤i≤L，1≤j≤LX (p) denotes the sample value of the p-th sample point in the sample signal, x*(p-j + i) is conjugate of x (p-j + i), wherein x (p-j + i) represents a sampling value of a p-j + i sampling point in the sampling signal;
step four: according to
Figure BDA0001327453010000032
And RxThe test statistic, denoted as T,
Figure BDA0001327453010000033
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 BDA0001327453010000034
wherein K is more than or equal to 0 and less than or equal to K-1, N is more than or equal to 1 and less than or equal to NcX (N + k × N) represents the sample value of the N + k × N-th sample point in the sample signal, x (N + N)d+ k × N) is x (N + N)dConjugate of + k × N), x (N + N)d+ k × N) represents the N + N-th in the sampled signaldThe sample value of + k × N sample points.
In the second step, the first step is carried out,
Figure BDA0001327453010000035
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) under the condition of time synchronization, the method only needs to utilize the sample number with the same length as the cyclic prefix of the OFDM signal to calculate the correlation coefficient, namely only needs K × N when calculating the correlation coefficient of the received signalcThe information of individual sample values, and therefore the computational complexity of the test statistic can be reduced.
2) Compared with the traditional noise power estimator which is only effective in noise samples, the method for estimating the noise power fully utilizes the autocorrelation of the cyclic prefix of the OFDM signal, thereby accurately estimating the noise power in the current sensing time slot and effectively improving the spectrum sensing performance of the OFDM signal.
3) 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.
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FIG. 1 is a block flow diagram of the method of the present invention;
FIG. 2 is a schematic diagram showing ROC curves obtained by the covariance method of Zeng et al when N is 64 and the received SNR is-10 dB;
fig. 3 is a diagram showing a comparison of ROC curves obtained by the method of the present invention and the covariance method proposed by Zeng et al when N is 100 and 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 frequency spectrum sensing method aiming at time synchronization and without frequency offset, the flow chart of which is shown in figure 1, and the processing process is as follows: firstly, sampling a received signal from a monitoring channel to obtain a sampling signal; then, according to the sampling values of all sampling points in the sampling signal, under the conditions of time synchronization and no frequency offset, estimating and obtaining the noise power by utilizing the autocorrelation of the cyclic prefix of the OFDM signal in the received 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 method for sensing the frequency spectrum of the OFDM signal under the conditions of time synchronization and no frequency offset 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 synchronization and no 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 BDA0001327453010000041
Figure BDA0001327453010000042
Where ρ isηAn estimate value representing a correlation coefficient of the received signal,
Figure BDA0001327453010000043
an estimate representing the power of the received signal.
In this embodiment, in step two,
Figure BDA0001327453010000051
wherein K is more than or equal to 0 and less than or equal to K-1, N is more than or equal to 1 and less than or equal to NcX (N + k × N) represents the sample value of the N + k × N-th sample point in the sample signal, x (N + N)d+ k × N) is x (N + N)dConjugate of + k × N), x (N + N)d+ k × N) represents the N + N-th in the sampled signaldThe sample value of + k × N sample points.
In this embodiment, in step two,
Figure BDA0001327453010000052
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 matrix of L × L dimension, and R isxThe element in the ith row and the jth column is marked as Rx(i,j)，
Figure BDA0001327453010000053
Wherein, L ∈ [2, M-1]If taking
Figure BDA0001327453010000054
1 ≦ i ≦ L, 1 ≦ j ≦ L, x (p) represents the sample value of the p-th sample point in the sample signal, x*And (p-j + i) is conjugate of x (p-j + i), and x (p-j + i) represents a sampling value of a p-j + i th sampling point in the sampling signal.
Step four: according to
Figure BDA0001327453010000055
And RxThe test statistic, denoted as T,
Figure BDA0001327453010000056
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 OFDM signals in a received signal from a supervisory channel are time-synchronized and free of frequency offset, the received signalThe total number N of effective data subcarriers in any one OFDM symbol in the OFDM signald48, length N of cyclic prefix of OFDM signal in received signalc16, 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 896 sampling points, i.e., M is K × N is 14 × 64 is 8.
Figure 2 shows ROC curves obtained using the method of the present invention and the covariance method proposed by Zeng et al, respectively, when N is 64 and the received snr is-10 db. As can be seen from FIG. 2, 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.
Assuming that the OFDM signals in the received signals from the monitoring channel are time-synchronized and there is no frequency offset, the total number N of valid data subcarriers in any one OFDM symbol in the OFDM signals in the received signalsd80, 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 ROC curves obtained by using the covariance method of the present invention and Zeng et al when N is 100 and the received snr is still-10 db. As can be seen from FIG. 3, 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 method of the present invention has better spectrum sensing performance than 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 synchronization and no frequency offset is characterized in that the processing process is as follows: firstly, sampling a received signal from a monitoring channel to obtain a sampling signal; then, according to the sampling values of all sampling points in the sampling signal, under the conditions of time synchronization and no frequency offset, estimating and obtaining the noise power by utilizing the autocorrelation of the cyclic prefix of the OFDM signal in the received 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 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≥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 synchronization and no 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 FDA0002369780470000011
Figure FDA0002369780470000012
Where ρ isηAn estimate value representing a correlation coefficient of the received signal,
Figure FDA0002369780470000013
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 matrix of L × L dimension, and R isxThe element in the ith row and the jth column is marked as Rx(i,j)，
Figure FDA0002369780470000014
Wherein, L ∈ [2, M-1]I is 1. ltoreq. L, j is 1. ltoreq. L, x (p) represents the sampling value of the p-th sampling point in the sampling signal, x*(p-j + i) is conjugate of x (p-j + i), wherein x (p-j + i) represents a sampling value of a p-j + i sampling point in the sampling signal;
step four: according to
Figure FDA0002369780470000015
And RxThe test statistic, denoted as T,
Figure FDA0002369780470000016
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 synchronization and without frequency offset according to claim 1, wherein in said step two,
Figure FDA0002369780470000021
wherein K is more than or equal to 0 and less than or equal to K-1, N is more than or equal to 1 and less than or equal to NcX (N + k × N) represents the sample value of the N + k × N-th sample point in the sample signal, x*(n+Nd+ k × N) is x (N + N)dConjugate of + k × N), x (N + N)d+ k × N) represents the N + N-th in the sampled signaldThe sample value of + k × N sample points.
3. The method for sensing the frequency spectrum of the OFDM signal with time synchronization and without frequency offset according to claim 1 or 2, wherein in the second step,
Figure FDA0002369780470000022
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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