CN103248441A - Method for sensing OFDM spectrum under conditions of time asynchronization and unknown cyclic prefix length - Google Patents
Method for sensing OFDM spectrum under conditions of time asynchronization and unknown cyclic prefix length Download PDFInfo
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Abstract
The invention discloses a method for sensing an OFDM (Orthogonal Frequency Division Multiplexing) spectrum under conditions of time asynchronization and unknown cyclic prefix length. The processing procedure of the method comprises the following steps: at first, sampling a receipt signal from a monitoring channel to obtain a sampled signal; then, computing an autocorrelation function of the sampled signal according to the sampled value in the sampled signal; next, computing test statistic according to an autocorrelation coefficient in the autocorrelation function of the sampled signal under the condition of time asynchronization; and at last, judging whether the monitoring channel is in the idle state or not according to the test statistic and the judgment threshold. The method has the advantages that the spectrum sensing can be carried out by directly using the sampled signal, without the need of time synchronization, so that the computation complexity is reduced effectively. When the cyclic prefix length of an OFDM signal is unknown, the method can still realize the spectrum sensing of the OFDM signal, and further improves the spectrum sensing performance of the OFDM signal.
Description
Technical field
The present invention relates to the frequency spectrum perception technology in a kind of cognitive radio system, especially relate to the OFDM frequency spectrum sensing method under the asynchronous and circulating prefix-length unknown situation of a kind of time.
Background technology
The support of a large amount of frequency spectrum resources of broadband wireless communications service needed.Existing static spectrum allocation may mode has caused the low-down result of frequency spectrum resource utilization rate, thereby has caused the phenomenon that frequency spectrum resource lacks.The proposition of cognitive radio provides a feasible thinking for improving the availability of frequency spectrum.For fear of existing wireless communication system is caused interference, cognitive radio system must be able to judge whether channel is in idle condition.Frequency spectrum perception can be used for judging whether channel is in idle condition, so frequency spectrum perception is one of key technology in the cognitive radio.
OFDM (Orthogonal frequency division multiplexing, OFDM) technology has characteristics such as availability of frequency spectrum height, and this technology is technology current and that future, wireless communication standard was widely adopted.Therefore the frequency spectrum perception (namely judge and whether have ofdm signal in the channel) to ofdm signal has very important significance.Existing frequency spectrum sensing method at ofdm signal mainly can be divided into frequency domain detection method and time domain detection method two classes.Wherein, the frequency domain detection method need be calculated the frequency spectrum of gathering signal, therefore has bigger amount of calculation; The utilization of time domain detection method is gathered the autocorrelation performance of Cyclic Prefix in the signal and is realized frequency spectrum perception.People such as Chaudhari have proposed to utilize the correlation properties of Cyclic Prefix in " in the Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios(cognitive radio based on autocorrelative ofdm signal distributed sequential detection method) " in 2009, realize frequency spectrum perception by calculating the auto-correlation function that receives signal, but this method is not considered the non-stationary property of auto-correlation function.At this problem, people such as Axell have proposed a kind of frequency spectrum sensing method based on the auto-correlation function of Cyclic Prefix newly in " the optimum and suboptimum frequency spectrum sensing method of the OFDM during the known and unknown noise variance of Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance() " in 2011, the method that people such as this method and Chaudhari propose is compared, has more excellent detection performance, but because this method needs asynchronous departure search of all possible time to received signal to realize time synchronized, so amount of calculation is bigger; On the other hand, this method needs the length of the Cyclic Prefix of known ofdm signal, and therefore when the length of the Cyclic Prefix of ofdm signal was unknown, the method for people such as Axell proposition will lose efficacy.
Summary of the invention
Technical problem to be solved by this invention provides the OFDM frequency spectrum sensing method under the asynchronous and circulating prefix-length unknown situation of a kind of time, its amount of calculation is little, and can further improve the frequency spectrum perception performance of ofdm signal under the length unknown condition of the Cyclic Prefix of ofdm signal.
The present invention solves the problems of the technologies described above the technical scheme that adopts: the OFDM frequency spectrum sensing method under the asynchronous and circulating prefix-length unknown situation of a kind of time, the processing procedure that it is characterized in that it is: at first, reception signal from supervisory channel is sampled, obtain sampled signal; Then, according to the sampled value in the sampled signal, the auto-correlation function of calculating sampling signal; Then, under the time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics; At last, according to the size of test statistics and decision threshold, judge whether supervisory channel is in idle condition.
It specifically may further comprise the steps:
1. utilize the sampling module in the cognitive radio system that the reception signal from supervisory channel is carried out M sampling, obtain the sampled signal that the sampled value by M sampled point constitutes, wherein, M is positive integer, and M〉N
d, N
dThe number of the subcarrier of expression ofdm signal;
2. according to the sampled value in the sampled signal, the auto-correlation function of calculating sampling signal is designated as ρ (t) with t auto-correlation coefficient in the auto-correlation function of sampled signal,
Wherein, the number of the auto-correlation coefficient in the auto-correlation function of sampled signal is M-N
d, t is positive integer, and 1≤t≤M-N
d, t sampled value in x (t) the expression sampled signal, x (N
d+ t) the N of expression in the sampled signal
d+ t sampled value, m is positive integer, and 1≤m≤M, m sampled value in x (m) the expression sampled signal;
3. under the time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics, be designated as T,
Wherein, symbol " " is the symbol that takes absolute value;
4. test statistics T and decision threshold λ are compared, if T, judges then that supervisory channel is in busy condition greater than λ, if T is less than or equal to λ, judge that then supervisory channel is in idle condition, wherein, λ=F
-1(P
f), P
fThe expression false alarm probability, span is 0＜P
f＜0.5, F
-1() is the inverse function of F (),
Compared with prior art, the invention has the advantages that:
1) the inventive method just can directly utilize sampled signal to carry out frequency spectrum perception synchronously when not required, has therefore reduced computation complexity effectively.
2) the inventive method still can realize the frequency spectrum perception to ofdm signal, and can further improve the frequency spectrum perception performance of ofdm signal when length the unknown of the Cyclic Prefix of ofdm signal.
Description of drawings
Fig. 1 is the FB(flow block) of frequency spectrum sensing method of the present invention;
Fig. 2 is under different state of signal-to-noise, and the frequency spectrum sensing method that people such as Axell propose and the detection probability of the inventive method be schematic diagram relatively.
Embodiment
Describe in further detail below in conjunction with the present invention of accompanying drawing embodiment.
OFDM frequency spectrum sensing method under the asynchronous and circulating prefix-length unknown situation of a kind of time that the present invention proposes, its FB(flow block) as shown in Figure 1, its main processing procedure is: at first, the reception signal from supervisory channel is sampled, obtain sampled signal; Then, according to the sampled value in the sampled signal, the auto-correlation function of calculating sampling signal; Then, under the time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics; At last, according to the size of test statistics and decision threshold, judge whether supervisory channel is in idle condition.
Ofdm signal frequency spectrum sensing method of the present invention, it specifically may further comprise the steps:
1. utilize the sampling module in the cognitive radio system that the reception signal from supervisory channel is carried out M sampling, obtain the sampled signal that the sampled value by M sampled point constitutes, wherein, M is positive integer, and M〉N
d, N
dThe number of the subcarrier of expression ofdm signal is as N
d=32 o'clock desirable M=432.
2. according to the sampled value in the sampled signal, the auto-correlation function of calculating sampling signal is designated as ρ (t) with t auto-correlation coefficient in the auto-correlation function of sampled signal,
Wherein, the number of the auto-correlation coefficient in the auto-correlation function of sampled signal is M-N
d, t is positive integer, and 1≤t≤M-N
d, t sampled value in x (t) the expression sampled signal, x (N
d+ t) the N of expression in the sampled signal
d+ t sampled value, m is positive integer, and 1≤m≤M, m sampled value in x (m) the expression sampled signal.
3. under the time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics, be designated as T,
Wherein, symbol " || " is the symbol that takes absolute value.
4. test statistics T and decision threshold λ are compared, if T, judges then that supervisory channel is in busy condition greater than λ, if T is less than or equal to λ, judge that then supervisory channel is in idle condition, wherein, λ=F
-1(P
f), P
fThe expression false alarm probability, span is 0＜P
f＜0.5, F
-1() is the inverse function of F (),
E is the nature radix, and e=2.71828..., y are variable.
By feasibility and the validity of following emulation to further specify frequency spectrum sensing method of the present invention.
The number of supposing the subcarrier of ofdm signal is N
d=32, the length of the Cyclic Prefix of ofdm signal is N
c=8, sampling number is M=432, and the value of establishing false alarm probability according to the requirement of IEEE802.22 standard is P
f=0.1.Fig. 2 provided signal to noise ratio from-when 20dB changes to 5dB, the method that people such as Axell propose and the comparison of the inventive method by the detection probability of 100000 Monte Carlo simulation acquisitions.Because the frequency spectrum sensing method that people such as Axell proposes needs the length of the Cyclic Prefix of known ofdm signal, so hypothesis N during the test statistics of the frequency spectrum sensing method that proposes people such as calculating Axell
c=8 is known, and suppose N when calculating the test statistics of the inventive method
c=8 the unknowns.As can be seen from Figure 2, in signal to noise ratio hour, the detection probability of the frequency spectrum sensing method that the detection probability of the inventive method proposes greater than people such as Axell, but all can't reach detection probability in the IEEE802.22 standard greater than 0.9 requirement; When signal to noise ratio during greater than 0.5dB, the detection probability of the inventive method is a bit larger tham the detection probability of the frequency spectrum sensing method that people such as Axell proposes, and the both has reached detection probability in the IEEE802.22 standard greater than 0.9 requirement.Analysis chart 2, though what the detection probability of the frequency spectrum sensing method that the detection probability of the inventive method proposes than people such as Axell was high is not a lot, but consider that frequency spectrum sensing method that people such as Axell proposes needs the length of Cyclic Prefix of ofdm signal known, and the inventive method does not need the length of Cyclic Prefix of ofdm signal known, and this is enough to illustrate feasibility and the validity of the inventive method.
Claims (2)
1. the OFDM frequency spectrum sensing method under the asynchronous and circulating prefix-length unknown situation of time is characterized in that its processing procedure is: at first, the reception signal from supervisory channel is sampled, obtain sampled signal; Then, according to the sampled value in the sampled signal, the auto-correlation function of calculating sampling signal; Then, under the time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics; At last, according to the size of test statistics and decision threshold, judge whether supervisory channel is in idle condition.
2. the OFDM frequency spectrum sensing method under the asynchronous and circulating prefix-length unknown situation of time according to claim 1 is characterized in that it specifically may further comprise the steps:
1. utilize the sampling module in the cognitive radio system that the reception signal from supervisory channel is carried out M sampling, obtain the sampled signal that the sampled value by M sampled point constitutes, wherein, M is positive integer, and M〉N
d, N
dThe number of the subcarrier of expression ofdm signal;
2. according to the sampled value in the sampled signal, the auto-correlation function of calculating sampling signal is designated as ρ (t) with t auto-correlation coefficient in the auto-correlation function of sampled signal,
Wherein, the number of the auto-correlation coefficient in the auto-correlation function of sampled signal is M-N
d, t is positive integer, and 1≤t≤M-N
d, t sampled value in x (t) the expression sampled signal, x (N
d+ t) the N of expression in the sampled signal
d+ t sampled value, m is positive integer, and 1≤m≤M, m sampled value in x (m) the expression sampled signal;
3. under the time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics, be designated as T,
Wherein, symbol " " is the symbol that takes absolute value;
4. test statistics T and decision threshold λ are compared, if T, judges then that supervisory channel is in busy condition greater than λ, if T is less than or equal to λ, judge that then supervisory channel is in idle condition, wherein, λ=F
-1(P
f), P
fThe expression false alarm probability, span is 0＜P
f＜0.5, F
-1() is the inverse function of F (),
E is the nature radix, and e=2.71828..., y are variable.
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Cited By (6)
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|---|---|---|---|---|
| CN103873163A (en) * | 2013-11-05 | 2014-06-18 | 南京航空航天大学 | Sparseness self-adaptation compression spectrum sensing method based on asymptotic step length |
| CN107222870A (en) * | 2017-06-21 | 2017-09-29 | 宁波大学 | For the ofdm signal frequency spectrum sensing method that the time is asynchronous and is not present under offset frequency situation |
| CN107465473A (en) * | 2017-06-21 | 2017-12-12 | 宁波大学 | For time synchronized and the ofdm signal frequency spectrum sensing method under offset frequency situation be present |
| CN108512793A (en) * | 2017-02-28 | 2018-09-07 | 畅想科技有限公司 | There is detection in ofdm signal |
| CN109600754A (en) * | 2018-12-24 | 2019-04-09 | 南京工业大学 | Sequential spectrum sensing method based on space-time correlation in WCSN (wideband coherent combining) |
| CN110856181A (en) * | 2019-11-20 | 2020-02-28 | 长江师范学院 | Distributed service matching sequential spectrum access decision method |
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| CN102404063A (en) * | 2011-12-26 | 2012-04-04 | 电子科技大学 | GLRT (General Likelihood Ratio Test) detection method based on oversampling |
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| CN103873163A (en) * | 2013-11-05 | 2014-06-18 | 南京航空航天大学 | Sparseness self-adaptation compression spectrum sensing method based on asymptotic step length |
| CN108512793A (en) * | 2017-02-28 | 2018-09-07 | 畅想科技有限公司 | There is detection in ofdm signal |
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| CN107222870B (en) * | 2017-06-21 | 2019-09-03 | 宁波大学 | Ofdm signal frequency spectrum sensing method asynchronous for the time and being not present under offset frequency situation |
| CN107465473B (en) * | 2017-06-21 | 2020-07-03 | 宁波大学 | OFDM signal spectrum sensing method under time synchronization and frequency offset condition |
| CN109600754A (en) * | 2018-12-24 | 2019-04-09 | 南京工业大学 | Sequential spectrum sensing method based on space-time correlation in WCSN (wideband coherent combining) |
| CN109600754B (en) * | 2018-12-24 | 2021-09-10 | 南京工业大学 | Sequential spectrum sensing method based on space-time correlation in WCSN (wideband coherent combining) |
| CN110856181A (en) * | 2019-11-20 | 2020-02-28 | 长江师范学院 | Distributed service matching sequential spectrum access decision method |
| CN110856181B (en) * | 2019-11-20 | 2021-07-20 | 长江师范学院 | Distributed service matching sequential spectrum access decision method |
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