CN102364885B - Frequency spectrum sensing method based on signal frequency spectrum envelope - Google Patents
Frequency spectrum sensing method based on signal frequency spectrum envelope Download PDFInfo
- Publication number
- CN102364885B CN102364885B CN201110305767.1A CN201110305767A CN102364885B CN 102364885 B CN102364885 B CN 102364885B CN 201110305767 A CN201110305767 A CN 201110305767A CN 102364885 B CN102364885 B CN 102364885B
- Authority
- CN
- China
- Prior art keywords
- msup
- mrow
- msub
- signal
- prime
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000001228 spectrum Methods 0.000 title claims abstract description 79
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000005070 sampling Methods 0.000 claims abstract description 17
- 238000004891 communication Methods 0.000 claims abstract description 13
- 238000006243 chemical reaction Methods 0.000 claims abstract description 8
- 230000001149 cognitive effect Effects 0.000 claims description 7
- 230000003595 spectral effect Effects 0.000 claims description 5
- 238000001514 detection method Methods 0.000 abstract description 21
- 239000011159 matrix material Substances 0.000 abstract description 8
- 230000007547 defect Effects 0.000 abstract description 2
- 230000019771 cognition Effects 0.000 abstract 2
- 125000004122 cyclic group Chemical group 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000005094 computer simulation Methods 0.000 description 1
- 238000013468 resource allocation Methods 0.000 description 1
Images
Landscapes
- Monitoring And Testing Of Transmission In General (AREA)
Abstract
The invention discloses a frequency spectrum sensing method based on signal frequency spectrum envelope. The frequency spectrum sensing method comprises the following steps of: firstly, receiving a time domain continuous radio frequency signal by using two receiving antennae; secondly, carrying out down conversion and time domain sampling processing on the time domain continuous radio frequency signal to obtain a time domain discrete base band signal; carrying out discrete Fourier transform on the time domain discrete base band signal to obtain a signal frequency spectrum; calculating a signal frequency spectrum enveloped crosscorrelation coefficient; and finally, judging whether a frequency band is occupied by other wireless communication services by comparing the signal frequency spectrum enveloped crosscorrelation coefficient with a decision threshold and realizing the frequency spectrum cognition. According to the frequency spectrum sensing method disclosed by the invention, the defects that the frequency spectrum cognition is failed when the time-domain correlation among a plurality of antenna receiving signals is lower or uncorrelated in a traditional covariance matrix detection method and a characteristic value detection method are overcome.
Description
Technical Field
The invention relates to a spectrum sensing technology in a cognitive radio system, in particular to a spectrum sensing method based on signal spectrum envelope.
Background
With the rapid growth of wireless communication services, the demand of people for spectrum resources is continuously increasing. However, the available physical spectrum resources that can be used for wireless communication services are limited, and the existing fixed spectrum resource allocation strategy causes low utilization rate of spectrum resources, which results in a situation of serious shortage of spectrum resources. The Cognitive Radio (CR) technology can effectively improve the utilization rate of spectrum resources, thereby alleviating the problem of spectrum resource shortage. The spectrum sensing is an important component in the cognitive radio technology, which can effectively prevent the interference of the wireless communication service adopting the cognitive radio technology to other wireless communication services in the same frequency band, and the performance of the spectrum sensing is directly related to the quality of the wireless communication service.
The existing spectrum sensing methods mainly comprise an energy detection method, a cyclic characteristic detection method, a covariance matrix detection method, an eigenvalue detection method and the like. The energy detection method requires that the noise power is accurately known, but the noise power cannot be accurately obtained in practice, and the performance of the energy detection method is rapidly reduced at the moment; the cyclic characteristic detection method needs prior knowledge of the cyclic characteristic frequency of the signal, and the cyclic characteristic frequency of the signal cannot be obtained in advance in practice; in the case of multiple antennas, the covariance matrix detection method and the eigenvalue detection method can use the time-domain correlation between the signals received by multiple antennas to realize spectrum sensing, but in practical applications, in order to obtain diversity gain, the time-domain correlation between the signals received by multiple antennas is low or even uncorrelated, and at this time, the covariance matrix detection method and the eigenvalue detection method may fail.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a spectrum sensing method based on signal spectrum envelope, which has good spectrum sensing performance and can effectively overcome the defect of poor spectrum sensing performance when the time domain correlation between signals received by multiple antennas is low or irrelevant.
The technical scheme adopted by the invention for solving the technical problems is as follows: a spectrum sensing method based on signal spectrum envelope is characterized by comprising the following steps:
suppose that the cognitive radio system employs two receptionsThe antennas receive radio frequency signals with continuous time domain, the radio frequency signals with continuous time domain received by the two receiving antennas are both expressed as a function of time t, and the radio frequency signals with continuous time domain received by the first receiving antenna are recorded as x1(t), recording the time-domain continuous radio frequency signal received by the second receiving antenna as x2(t)；
Secondly, respectively aiming at the radio frequency signals x of continuous time domain received by the first receiving antenna1(t) and a second receiving antenna receiving a continuous radio frequency signal x in the time domain2(t) performing down-conversion treatment on the obtained product, and then respectively comparing the obtained product with x1(t) and x2(t) performing time domain sampling for K times on the continuous time domain radio frequency signal obtained after the down-conversion treatment to obtain a time domain discrete baseband signal on the first receiving antenna and a time domain discrete baseband signal on the second receiving antenna, and representing the time domain discrete baseband signal on the first receiving antenna and the time domain discrete baseband signal on the second receiving antenna as functions of time domain sampling sequence numbers K which are respectively recorded as y1(k) And y2(k) Where K is 1, 2, …, K denotes the number of time-domain samples;
thirdly, respectively carrying out time domain discrete baseband signals y on the first receiving antenna1(k) And a time-domain discrete baseband signal y on a second receiving antenna2(k) Performing discrete Fourier transform to obtain signal spectrum on the first receiving antenna and signal spectrum on the second receiving antenna, representing the signal spectrum on the first receiving antenna and the signal spectrum on the second receiving antenna as functions of frequency domain sampling sequence numbers k', respectively denoted as w1(k') and w2(K '), wherein K ' is 1, 2, …, K ' represents the number of frequency domain samples;
fourthly, according to the signal frequency spectrum y on the first receiving antenna1(k') and the signal spectrum w on the second receiving antenna2(k') calculating a cross-correlation coefficient, denoted as r, <math>
<mrow>
<mi>r</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<msub>
<mi>w</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<msub>
<mi>μ</mi>
<mn>2</mn>
</msub>
</mrow>
<msqrt>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<msub>
<mi>K</mi>
<mo>′</mo>
</msub>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>)</mo>
</mrow>
</msqrt>
</mfrac>
<mo>,</mo>
</mrow>
</math> wherein, <math>
<mrow>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>,</mo>
</mrow>
</math> 
the symbol "|" is an absolute value symbol, | w1(k') l represents the signal spectrum w on the first receive antenna1(k') signal spectral envelope, | w2(k') l represents the signal spectrum w on the second receiving antenna2(k') a signal spectral envelope;
calculating judgment threshold according to frequency domain sampling times K', and recording as lambda, lambda being Q-1(1-Pf) Wherein P isfIndicating false alarm probability, Q-1(1-Pf) Is Q (1-P)f) The inverse function of (a) is,
u is an integral variable;
comparing the cross correlation coefficient r of the signal spectrum envelope with the size of a judgment threshold lambda, and if the cross correlation coefficient r of the signal spectrum envelope is larger than or equal to the judgment threshold lambda, judging that other wireless communication services are occupying the frequency band; and if the cross correlation coefficient r of the signal spectrum envelope is smaller than the judgment threshold lambda, judging that other wireless communication services do not occupy the frequency band.
Compared with the prior art, the method has the advantages that two receiving antennas are used for receiving the radio frequency signals with continuous time domains, then down-conversion and time-domain sampling processing are carried out on the radio frequency signals with continuous time domains to obtain baseband signals with discrete time domains, discrete Fourier transform is carried out on the baseband signals with discrete time domains to obtain signal frequency spectrums, then the cross correlation coefficient of signal frequency spectrum envelopes is calculated, finally, whether other wireless communication services occupy frequency bands or not is judged by comparing the cross correlation coefficient of the signal frequency spectrum envelopes with the size of a judgment threshold, and spectrum sensing is achieved.
Drawings
FIG. 1 is a block flow diagram of a spectrum sensing method of the present invention;
FIG. 2 is a diagram illustrating the comparison of the spectrum sensing performance of the covariance matrix detection method of the present invention with that of the prior art.
Detailed Description
The invention is described in further detail below with reference to the accompanying examples.
The invention provides a spectrum sensing method based on signal spectrum envelope, the flow chart of which is shown in figure 1, and the method mainly comprises the following steps:
firstly, supposing that the cognitive radio system adopts two receiving antennas to receive radio frequency signals with continuous time domains, the radio frequency signals with continuous time domains received by the two receiving antennas are both expressed as a function of time t, and the radio frequency signals with continuous time domains received by the first receiving antenna are recorded as x1(t), recording the time-domain continuous radio frequency signal received by the second receiving antenna as x2(t)。
Secondly, respectively aiming at the radio frequency signals x of continuous time domain received by the first receiving antenna1(t) and a second receiving antenna receiving a continuous radio frequency signal x in the time domain2(t) performing down-conversion treatment on the obtained product, and then respectively comparing the obtained product with x1(t) and x2(t) performing K time domain samples on the continuous time domain radio frequency signal obtained after down-conversion processing to obtain discrete time domain on the first receiving antennaThe baseband signal and the time-domain discrete baseband signal on the second receiving antenna are expressed as functions of time-domain sampling sequence numbers k which are respectively recorded as y1(k) And y2(k) Where K is 1, 2, …, K denotes the number of time-domain samples.
Thirdly, respectively carrying out time domain discrete baseband signals y on the first receiving antenna1(k) And a time-domain discrete baseband signal y on a second receiving antenna2(k) Performing discrete Fourier transform to obtain signal spectrum on the first receiving antenna and signal spectrum on the second receiving antenna, representing the signal spectrum on the first receiving antenna and the signal spectrum on the second receiving antenna as functions of frequency domain sampling sequence numbers k', respectively denoted as w1(k') and w2(K '), where K ' ═ 1, 2, …, K ' denotes the number of frequency domain samples. Here, the discrete fourier transform is performed on the time-domain discrete baseband signal, and the time-domain discrete baseband signal is substantially subjected to discrete frequency domain sampling.
Fourthly, according to the signal frequency spectrum w on the first receiving antenna1(k') and the signal spectrum w on the second receiving antenna2(k') calculating a cross-correlation coefficient, denoted as r, <math>
<mrow>
<mi>r</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<msub>
<mi>w</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<msub>
<mi>μ</mi>
<mn>2</mn>
</msub>
</mrow>
<msqrt>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<msub>
<mi>K</mi>
<mo>′</mo>
</msub>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>)</mo>
</mrow>
</msqrt>
</mfrac>
<mo>,</mo>
</mrow>
</math> wherein, <math>
<mrow>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>,</mo>
</mrow>
</math> 
the symbol "|" is absoluteValue symbol, | w1(k') l represents the signal spectrum w on the first receive antenna1(k') signal spectral envelope, | w2(k') l represents the signal spectrum w on the second receiving antenna2(k') envelope of the signal spectrum.
Calculating judgment threshold according to frequency domain sampling times K', and recording as lambda, lambda being Q-1(1-Pf) Wherein P isfIndicating false alarm probability, Q-1(1-Pf) Is Q (1-P)f) The inverse function of (a) is,u is an integral variable.
Comparing the cross correlation coefficient r of the signal spectrum envelope with the size of a judgment threshold lambda, and if the cross correlation coefficient r of the signal spectrum envelope is larger than or equal to the judgment threshold lambda, judging that other wireless communication services are occupying the frequency band; and if the cross correlation coefficient r of the signal spectrum envelope is smaller than the judgment threshold lambda, judging that other wireless communication services do not occupy the frequency band.
The feasibility and effectiveness of the spectrum sensing method of the present invention are further illustrated by computer simulation of actually measured digital television signals.
Assuming that the time-domain sampling frequency is 6MHz and the time-domain sampling time length is 1.3ms, that is, the time K of time-domain sampling is 7800, the false alarm probability P is setf0.1. Fig. 2 shows the detection probability of an actual measured digital television signal obtained by acquiring digital television signals at different locations using two antennas under different signal-to-noise ratios using the existing covariance matrix detection method and the method of the present invention. As can be seen from fig. 2, because the two antennas are far apart from each other, their receiving channels are independent from each other, which causes the received signals on the two antennas to be uncorrelated in the time domain, and thus the conventional covariance matrix detection method fails. As shown in fig. 2, the detection probability of the conventional covariance matrix detection method is around 0.1 regardless of the signal-to-noise ratio because the false alarm probability set in the simulation is 0.1.Because the signals received by the two antennas are from the same emission source, the spectrum envelopes of the received signals on the two antennas have correlation, and therefore, the method has higher detection performance under the condition of high enough signal-to-noise ratio. In this simulation, the detection probability can be higher than 0.95 when the signal-to-noise ratio is greater than-4 dB.
Claims (1)
1. A spectrum sensing method based on signal spectrum envelope is characterized by comprising the following steps:
firstly, supposing that the cognitive radio system adopts two receiving antennas to receive radio frequency signals with continuous time domains, the radio frequency signals with continuous time domains received by the two receiving antennas are both expressed as a function of time t, and the radio frequency signals with continuous time domains received by the first receiving antenna are recorded as x1(t), recording the time-domain continuous radio frequency signal received by the second receiving antenna as x2(t)；
Receiving to the first root respectivelyTime-domain continuous radio frequency signal x received by antenna1(t) and a second receiving antenna receiving a continuous radio frequency signal x in the time domain2(t) performing down-conversion treatment on the obtained product, and then respectively comparing the obtained product with x1(t) and x2(t) performing time domain sampling for K times on the continuous time domain radio frequency signal obtained after the down-conversion treatment to obtain a time domain discrete baseband signal on the first receiving antenna and a time domain discrete baseband signal on the second receiving antenna, and representing the time domain discrete baseband signal on the first receiving antenna and the time domain discrete baseband signal on the second receiving antenna as functions of time domain sampling sequence numbers K which are respectively recorded as y1(k) And y2(k) Where K is 1, 2, …, K denotes the number of time-domain samples;
thirdly, respectively carrying out time domain discrete baseband signals y on the first receiving antenna1(k) And a time-domain discrete baseband signal y on a second receiving antenna2(k) Performing discrete Fourier transform to obtain signal spectrum on the first receiving antenna and signal spectrum on the second receiving antenna, representing the signal spectrum on the first receiving antenna and the signal spectrum on the second receiving antenna as functions of frequency domain sampling sequence numbers k', respectively denoted as w1(k') and w2(K '), wherein K ' is 1, 2, …, K ' represents the number of frequency domain samples;
fourthly, according to the signal frequency spectrum w on the first receiving antenna1(k') and the signal spectrum w on the second receiving antenna2(k') calculating a cross-correlation coefficient, denoted as r, <math>
<mrow>
<mi>r</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<msub>
<mi>w</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<msub>
<mi>μ</mi>
<mn>2</mn>
</msub>
</mrow>
<msqrt>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<msub>
<mi>K</mi>
<mo>′</mo>
</msub>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<msub>
<mi>μ</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>)</mo>
</mrow>
</msqrt>
</mfrac>
<mo>,</mo>
</mrow>
</math> wherein, <math>
<mrow>
<msub>
<mi>μ</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</mfrac>
<munderover>
<mi>Σ</mi>
<mrow>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msup>
<mi>K</mi>
<mo>′</mo>
</msup>
</munderover>
<mo>|</mo>
<msub>
<mi>w</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msup>
<mi>k</mi>
<mo>′</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>,</mo>
</mrow>
</math> 
the symbol "|" is an absolute value symbol, | w1(k') l represents the signal spectrum w on the first receive antenna1(k') signal spectral envelope, | w2(k') l represents the signal spectrum w on the second receiving antenna2(k') a signal spectral envelope;
calculating judgment threshold according to frequency domain sampling times K', and recording as lambda, lambda being Q-1(1-Pf) Wherein P isfIndicating false alarm probability, Q-1(1-Pf) Is Q (1-P)f) The inverse function of (a) is,u is an integral variable;
comparing the cross correlation coefficient r of the signal spectrum envelope with the size of a judgment threshold lambda, and if the cross correlation coefficient r of the signal spectrum envelope is larger than or equal to the judgment threshold lambda, judging that other wireless communication services are occupying the frequency band; and if the cross correlation coefficient r of the signal spectrum envelope is smaller than the judgment threshold lambda, judging that other wireless communication services do not occupy the frequency band.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110305767.1A CN102364885B (en) | 2011-10-11 | 2011-10-11 | Frequency spectrum sensing method based on signal frequency spectrum envelope |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110305767.1A CN102364885B (en) | 2011-10-11 | 2011-10-11 | Frequency spectrum sensing method based on signal frequency spectrum envelope |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102364885A CN102364885A (en) | 2012-02-29 |
| CN102364885B true CN102364885B (en) | 2014-02-05 |
Family
ID=45691437
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201110305767.1A Expired - Fee Related CN102364885B (en) | 2011-10-11 | 2011-10-11 | Frequency spectrum sensing method based on signal frequency spectrum envelope |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102364885B (en) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140100822A1 (en) * | 2012-10-09 | 2014-04-10 | Tektronix, Inc. | Multi-signal covariance and correlation processing on a test and measurement instrument |
| CN103684636B (en) * | 2013-12-18 | 2015-08-19 | 同济大学 | A kind of frequency spectrum perception data processing method based on discrete Fourier transform |
| CN103746752B (en) * | 2013-12-18 | 2016-05-18 | 同济大学 | A kind of smart frequency spectrum cognitive method based on layering Di Li Cray process |
| CN103795477B (en) * | 2014-01-09 | 2016-03-09 | 南京邮电大学 | Based on the broader frequency spectrum compression sensing method of SVMs |
| CN104052556B (en) * | 2014-06-20 | 2017-02-15 | 中国电子科技集团公司第五十四研究所 | Cooperation detection method used for radio-frequency spectrum sensing and based on diversity combination |
| CN105429913B (en) * | 2015-11-11 | 2018-08-21 | 西安电子科技大学 | More level detections of feature based value and recognition methods |
| CN105813089B (en) * | 2016-05-05 | 2019-01-15 | 宁波大学 | A kind of matched filtering frequency spectrum sensing method fighting incorrect noise |
| CN108093410B (en) * | 2017-12-19 | 2020-04-28 | 温州大学瓯江学院 | High-efficiency spectrum resource sensing equipment |
| CN108471296B (en) * | 2018-03-07 | 2021-09-10 | 中国电子科技集团公司第三十研究所 | High-precision rapid automatic gain control system suitable for short-time burst transmission |
| CN109104257B (en) * | 2018-07-04 | 2020-08-21 | 北京邮电大学 | Wireless signal detection method and device |
| CN110649982B (en) * | 2019-08-29 | 2021-09-28 | 南京邮电大学 | Double-threshold energy detection method based on secondary user node selection |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101369424A (en) * | 2007-08-17 | 2009-02-18 | 株式会社东芝 | Character extraction device and method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SE0402649D0 (en) * | 2004-11-02 | 2004-11-02 | Coding Tech Ab | Advanced methods of creating orthogonal signals |
-
2011
- 2011-10-11 CN CN201110305767.1A patent/CN102364885B/en not_active Expired - Fee Related
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101369424A (en) * | 2007-08-17 | 2009-02-18 | 株式会社东芝 | Character extraction device and method |
Non-Patent Citations (2)
| Title |
|---|
| 王晓芳 等.认知无线电中一种改进的频谱感知算法.《通信技术》.2011, |
| 认知无线电中一种改进的频谱感知算法;王晓芳 等;《通信技术》;20110930;第7－11页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102364885A (en) | 2012-02-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102364885B (en) | Frequency spectrum sensing method based on signal frequency spectrum envelope | |
| US8688759B2 (en) | Efficient detection algorithm system for a broad class of signals using higher-order statistics in time as well as frequency domains | |
| US10623215B2 (en) | Process for tunnelized cyclostationary to achieve low-energy spectrum sensing | |
| JP2002508898A (en) | Selective diversity combinations | |
| CN103532649A (en) | Environment cognition technique and equipment applicable to aerospace information network | |
| CN102932047A (en) | Detection method for multitape spectrum of cognitive radio (CR) suitable for multiaerial system | |
| CN1638374A (en) | Receiving method and receiving apparatus with adaptive array signal processing | |
| CN105577598A (en) | Signal detection method and device of LTE uplink system under interference condition | |
| CN109738868B (en) | External radiation source radar non-stationary clutter suppression method based on channel identification | |
| CN103560991A (en) | Method of orthogonal frequency division multiplexing receiver for suppressing impulse interference of distance measure equipment | |
| JP5078931B2 (en) | Radio apparatus and radio wave arrival direction estimation method | |
| CN105634624B (en) | A kind of frequency domain cooperative frequency spectrum sensing method towards cognition wireless network | |
| CN111901058B (en) | Multi-antenna auxiliary broadband spectrum sensing method based on sub-nyquist sampling | |
| CN102035768A (en) | Method and device for measuring carrier to interference and noise ratio | |
| CN103546191A (en) | Method for detecting main synchronization sequence interference cancellation of full-domain coverage multi-beam S-LTE | |
| CN102142909B (en) | Ranging signal detection method and base station | |
| RU2470460C2 (en) | Methods and systems for hybrid mimo schemes in ofdm/a systems | |
| CN103595669B (en) | A kind of multiple antennas initial ranging method and device | |
| EP1838030A2 (en) | Uplink signal receiving method and apparatus using successive interference cancellation in wireless transmission system based on OFDMA | |
| CN105281854A (en) | Local maximum efficacy invariance test spectrum sensing method based on non-circular signal | |
| CN104506262A (en) | Self-adaptive DTMB (Digital Television Terrestrial Multimedia Broadcast) spectrum detection method on basis of PN ((Pseudo-noise) sequence auto-correlation | |
| CN101986572B (en) | Method and device for detecting random access signal in orthogonal frequency division multiplexing system | |
| US20220278801A1 (en) | Device and method for detecting interference between base stations in wireless communication system | |
| CN102300115A (en) | Method for rapidly identifying analog, digital television signal, apparatus thereof and communication receiver | |
| US10477587B2 (en) | Linear combination for RACH detection |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20140205 Termination date: 20161011 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |