CN107682119A - A kind of MIMO space -time code recognition methods based on packet extreme value model - Google Patents
A kind of MIMO space -time code recognition methods based on packet extreme value model Download PDFInfo
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- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
- H04L1/06—Arrangements for detecting or preventing errors in the information received by diversity reception using space diversity
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- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
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Abstract
The present invention is directed to two kinds of space -time code identification problems of SM and STBC in MIMO transmission system, it is proposed that a kind of MIMO space -time code recognition methods based on packet extreme value model.It is related that the signal of any two different reception antennas is made into delay first, then calculate its Correlated Spectroscopy modulus value, application packet extreme value model, Correlated Spectroscopy modulus value sequence is suitably grouped and takes every group of maximum, obtain being grouped extreme value sequence and be normalized, find out the maximum of normalization packet extreme value sequence as identification feature amount；Corresponding thresholding is set, if identification feature amount is more than this threshold value, STBC patterns are identified as, conversely, being then identified as SM patterns.Simulation result shows, under conditions of the no signal prior information can to MIMO in two kinds of space -time code effectively identified.
Description
Technical field
The invention belongs to signal identification and process field, and in particular to a kind of MIMO space -time codes based on packet extreme value model
Recognition methods.
Background technology
Signal identification is the classical problem of the military affairs such as signal reconnaissance, cognitive radio and civil area, and reconfigurable
Indispensable sport technique segment in communication, its task generally comprise the estimation of transmitting antenna number, the identification of space -time code and modulation methods
The links such as formula identification.Under the conditions of non-cooperating, space -time code identification is typically the premise and base of modulation system and subsequent decoding link
Plinth.Existing method can be divided mainly into likelihood ratio identification and the class of feature recognition two, and the performance of likelihood ratio identification is optimal but needs letter
Number and channel prior information, and easily influenceed by model mismatch, complexity is also higher, and feature recognition method mainly includes circulation
Flat frequency detection method, Fourth-order moment sharp peaks characteristic method etc., the complexity of these methods is lower slightly, but the poor-performing in low noise ratio.
The present invention be based on extreme value theory (EVT) in packet extreme value model, using the Correlated Spectroscopy of any two reception antennas as
Foundation, specific characteristic quantity and thresholding being selected, complete the identification of two kinds of patterns of SM and STBC, the computation complexity of algorithm is low, and
Still there is preferable performance in low signal-to-noise ratio.Especially, this method can be overcome in cyclo-stationary frequency detecting because spectral line point be present
Split the shortcoming of the algorithm failure brought.
The content of the invention
The present invention's is directed to deficiency of the prior art, there is provided a kind of MIMO space -time codes identification based on packet extreme value model
Method.
To achieve the above object, the present invention uses following technical scheme：
1) the delay Correlated Spectroscopy modulus value of observation signal between different reception antennas is calculated；
2) Correlated Spectroscopy modulus value is suitably grouped, and takes the maximum of each packet, structure is grouped very big value sequence；
3) the normalized very big value sequence of packet is obtained based on extreme value theory EVT；
4) maximum of the normalized very big value sequence of packet is extracted, as identification feature amount；
5) thresholding of setting mimo space -time code identification；
6) identification feature amount is compared with thresholding, identifies two kinds of codings of SM and STBC in MIMO signal.
To optimize above-mentioned technical proposal, the concrete measure taken also includes：
In step 1)：
In setting mimo transmission environment, there are L transmitting antenna, P reception antenna, L ＞ 1, P ＞ 1, the reception of reception antenna
Signal vector is：R (n)=H (n) s (n)+w (n), n=0 ..., N-1, wherein, H (n) is Rayleigh fading type channel matrix, w
(n) it is additive white Gaussian noise, variance isS (n) is signal vector, and N is sample of signal length；
The reception signal for remembering i-th antenna is ri(n), the reception signal of jth root antenna is rj(n), amount of delay τ, then phase
Closing spectrum modulus value is：U (k)=| DFT [ri(n)rj(n- τ)] |, k=0 ..., N-1, wherein i ≠ j, the letter of participation Correlated Spectroscopy computing
Number must be from different reception antennas, τ ＞ 1.
In step 2)：
Correlated Spectroscopy modulus value U (k) is grouped, it is uniformly divided into K groups, and maximum γ is taken to each packetl, l
=0 ..., K-1, K packet maximum is formed and is grouped very big value sequence { γl, l=0 .., K-1.
In step 3)：
Based on EVT methods, very big value sequence { γ will be groupedlBe normalized, obtain normalization and be grouped very big value sequence
U ' (l)=[γl-aK]/bK, l=0 ..., K-1, wherein, normalization coefficient
σzFor the standard deviation of related spectral sequence.
In step 4)：
The maximum that selection normalization is grouped very big value sequence U ' (l) is designated as R as identification feature amountevt=max [U '
(l)]。
In step 5)：
The thresholding th of setting mimo space -time code identificationevt, thevt=-1n [- ln (1-Pfa)], in formula, PfaFor false-alarm probability.
In step 6)：
Work as Revt≥thevtWhen, then pattern is STBC；Otherwise, pattern SM.
The beneficial effects of the invention are as follows：It is used as by the maximum for extracting Correlated Spectroscopy normalization packet extreme value according to completion pair
The identification of two kinds of patterns of SM and STBC, it is only necessary to using the reception signal of any two reception antennas, without the prior information of signal,
Still there is preferable performance when compared with low signal-to-noise ratio, and method is easily achieved.
Brief description of the drawings
Fig. 1 is the recognition methods flow chart of the present invention.
Fig. 2 is the statistic histogram of Correlated Spectroscopy normalization packet extreme value sequence maximum under the conditions of different patterns.
Fig. 3 is the performance comparison figure of the present invention and cyclo-stationary frequency detecting method under identical simulated conditions.
Embodiment
In conjunction with the accompanying drawings, the present invention is further explained in detail.
In the recognition methods of the present invention, the signal of two different reception antennas is selected first, both are entered into line delay phase
Close, then calculate its Correlated Spectroscopy modulus value, Correlated Spectroscopy modulus value sequence is suitably grouped and takes maximum, obtain being grouped extreme value sequence
Arrange and be based on EVT methods and be normalized, find out the maximum of normalization packet extreme value sequence as identification feature amount, then set
Corresponding thresholding, if identification feature amount is more than this threshold value, STBC patterns are identified as, conversely, being then identified as SM patterns.
Fig. 1 shows the MIMO space -time code recognition methods based on packet extreme value model, specifically includes following steps.
First, Correlated Spectroscopy modulus value is calculated
Assuming that in MIMO transmission environment, there is a L transmitting antenna, P reception antenna, L ＞ 1, P ＞ 1, then reception antenna connect
Receiving signal vector is：
R (n)=H (n) s (n)+w (n), n=0 ..., N-1
In formula：H (n) is Rayleigh fading type channel matrix, and w (n) is that (variance is additive white Gaussian noise), s (n) is letter
Number vector, N is sample of signal length.
The reception signal for remembering i-th antenna is ri(n) reception signal for, remembering jth root antenna is rj(n), its Correlated Spectroscopy modulus value
For：
U (k)=| DFT [ri(n)rj(n- τ)] |, k=0 ..., N-1
Require i ≠ j in formula, that is, different reception antennas must be come from by participating in the signal of Correlated Spectroscopy computing, and τ is amount of delay, τ ＞
1。
2nd, structure is grouped very big value sequence
Correlated Spectroscopy modulus value U (k) is grouped, it is uniformly divided into K groups (general every group of number of samples is 5-15), and
Maximum γ is taken to each packetl, l=0 ..., K-1, K packet maximum is formed and is grouped very big value sequence { γl, l
=0 ..., K-1.
3rd, normalize
Based on EVT methods, very big value sequence { γ will be groupedlBe normalized, obtain normalized packet maximum sequence
Row：
U ' (l)=[γl-aK]/bK, l=0 ..., K-1
Wherein, normalization coefficientWherein σzFor the standard of related spectral sequence
Difference, in practice, σzByEstimation obtains, in formulaIt is that the statistics after the big spectral line of 3-5 roots is removed in Correlated Spectroscopy U (k)
Average value.
4th, identification feature amount is defined
The maximum that selection normalization is grouped very big value sequence U ' (l) is designated as R as identification feature amountevt=max [U '
(l)]。
5th, threshold sets
The thresholding th of setting mimo space -time code identificationevt, it is calculated by following formula：
thevt=-ln [- ln (1-Pfa)]
In formula, PfaFor false-alarm probability, typically take between 0.01-0.0001.
6th, identification of code type
Work as Revt≥thevtWhen, then pattern is STBC；Otherwise, pattern SM.
Table 1 illustrates the Mean accurate rate of recognition of this method, it is assumed that in MIMO transmission environment, there are 3 transmitting antennas, 4
Reception antenna, then the 1st reception antenna is related to the reception signal work delay of the 2nd, and amount of delay is 20 sample points.Channel is
Rayleigh fading type channel matrix, additional noise are additive white Gaussian noise, and signal is divided into 4 time slots, each time slot when launching
Symbol numbers are 1024 points, and the modulation system that signal uses is modulated for QPSK.Signal-to-noise ratio settings scope is -3dB to 12dB step-lengths
For 3dB, during every kind of signal to noise ratio, make 1000 emulation for two kinds of different patterns difference are each, false-alarm probability takes 0.0001.
Correct identification probability of this method under above simulated conditions as can be seen from Table 1：When signal to noise ratio is more than -3dB,
The recognition correct rate of two kinds of patterns is more than 91%.
| SNR(dB) | -6 | -3 | 0 | 3 | 6 | 9 | 12 |
| Mean accurate rate of recognition | 0.655 | 0.811 | 0.9075 | 0.933 | 0.9505 | 0.9555 | 0.9625 |
Performance of 1 recognition methods of the present invention of table under the conditions of different signal to noise ratio
Fig. 2 gives obtains SM and AL (STBC codes when i.e. dual-mode antenna is all 2, transmission time slot 2) two by emulation
The system normalization of kind Space Time Coding is grouped the statistic histogram of very big value sequence maximum.Signal-to-noise ratio settings 0dB, for two kinds not
It is identical with reference table 1 with 1000 emulation of each work of pattern difference, the condition of other emulation.As seen from the figure, different space -time code conditions
Under, there is certain difference in the statistic histogram that related spectrum normalization is grouped very big value sequence maximum, be the reality of this algorithm
Foundation is now provided.
Fig. 3 is shown under the simulated conditions that table 1 is set, the performance comparison of this method and cyclo-stationary frequency detecting method.
As seen from Figure 3, algorithm proposed by the present invention is slightly better than cyclo-stationary frequency detecting method.
The above is only the preferred embodiment of the present invention, protection scope of the present invention is not limited merely to above-described embodiment,
All technical schemes belonged under thinking of the present invention belong to protection scope of the present invention.It should be pointed out that for the art
For those of ordinary skill, some improvements and modifications without departing from the principles of the present invention, the protection of the present invention should be regarded as
Scope.
Claims (7)
1. a kind of MIMO space -time code recognition methods based on packet extreme value model, specifically includes following steps：
1) the delay Correlated Spectroscopy modulus value of observation signal between different reception antennas is calculated；
2) Correlated Spectroscopy modulus value is grouped, and takes the maximum of each packet, structure is grouped very big value sequence；
3) the normalized very big value sequence of packet is obtained based on extreme value theory EVT；
4) maximum of the normalized very big value sequence of packet is extracted, as identification feature amount；
5) thresholding of setting mimo space -time code identification；
6) identification feature amount is compared with thresholding, identifies two kinds of codings of SM and STBC in MIMO signal.
A kind of 2. MIMO space -time code recognition methods based on packet extreme value model as claimed in claim 1, it is characterised in that：
In step 1)：
In setting mimo transmission environment, there are L transmitting antenna, P reception antenna, L ＞ 1, P ＞ 1, the reception signal of reception antenna
Vector is：R (n)=H (n) s (n)+w (n), n=0 ..., N-1, wherein, H (n) is Rayleigh fading type channel matrix, and w (n) is
Additive white Gaussian noise, variance areS (n) is signal vector, and N is sample of signal length；
The reception signal for remembering i-th antenna is ri(n), the reception signal of jth root antenna is rj(n), amount of delay τ, then Correlated Spectroscopy
Modulus value is：U (k)=| DFT [ri(n)rj(n- τ)] |, k=0 ..., N-1, wherein i ≠ j, the signal for participating in Correlated Spectroscopy computing must
Must be from different reception antennas, τ ＞ 1.
A kind of 3. MIMO space -time code recognition methods based on packet extreme value model as claimed in claim 2, it is characterised in that：
In step 2)：
Correlated Spectroscopy modulus value U (k) is grouped, it is uniformly divided into K groups, and maximum γ is taken to each packetl, l=
0 ..., K-1, K packet maximum is formed and is grouped very big value sequence { γl, l=0 ..., K-1.
A kind of 4. MIMO space -time code recognition methods based on packet extreme value model as claimed in claim 3, it is characterised in that：
In step 3)：
Based on EVT methods, very big value sequence { γ will be groupedlBe normalized, obtain normalization and be grouped very big value sequence U ' (l)
=[γl-aK]/bK, l=0 .., K-1, wherein, normalization coefficientσzFor phase
Close the standard deviation of spectral sequence.
A kind of 5. MIMO space -time code recognition methods based on packet extreme value model as claimed in claim 4, it is characterised in that：
In step 4)：
The maximum that selection normalization is grouped very big value sequence U ' (l) is designated as R as identification feature amountevt=max [U ' (l)].
A kind of 6. MIMO space -time code recognition methods based on packet extreme value model as claimed in claim 5, it is characterised in that：
In step 5)：
The thresholding th of setting mimo space -time code identificationevt, thevt=-ln [- ln (1-Pfa)], in formula, PfaFor false-alarm probability.
A kind of 7. MIMO space -time code recognition methods based on packet extreme value model as claimed in claim 6, it is characterised in that：
In step 6)：
Work as Revt≥thevtWhen, then pattern is STBC；Otherwise, pattern SM.
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| CN112600594A (en) * | 2020-12-08 | 2021-04-02 | 中国人民解放军海军航空大学航空作战勤务学院 | Space frequency block code identification method, device, computer equipment and storage medium |
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