CN107528673B - SM/AL space-time code identification method based on correlation spectrum peak value inspection - Google Patents
SM/AL space-time code identification method based on correlation spectrum peak value inspection Download PDFInfo
- Publication number
- CN107528673B CN107528673B CN201710886169.5A CN201710886169A CN107528673B CN 107528673 B CN107528673 B CN 107528673B CN 201710886169 A CN201710886169 A CN 201710886169A CN 107528673 B CN107528673 B CN 107528673B
- Authority
- CN
- China
- Prior art keywords
- correlation spectrum
- space
- signal
- value
- time code
- 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.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- 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
- H04L1/0618—Space-time coding
- H04L1/0631—Receiver arrangements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
- H04L1/0036—Systems modifying transmission characteristics according to link quality, e.g. power backoff arrangements specific to the receiver
- H04L1/0038—Blind format detection
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- Radio Transmission System (AREA)
Abstract
The invention provides an SM/AL space-time code identification method based on correlation spectrum peak value inspection, aiming at the problems of SM and AL space-time code identification in MIMO signals. Simulation results show that the space-time codes of the SM type and the AL type in the MIMO can be effectively identified under the condition of no signal prior information.
Description
Technical Field
The invention belongs to the field of signal identification and processing, and particularly relates to an SM/AL space-time code identification method based on correlation spectrum peak value detection.
Background
In 4G and future 5G communication systems, MIMO technology has been widely used. In an MIMO scene, the problem of signal identification and parameter estimation is considered to be a new trend, and the method has important application in the fields of cognitive radio, communication reconnaissance, spectrum monitoring and the like. In the analysis and processing of the MIMO signal, the identification of the space-time block code type is the sub-content, and a basis is provided for the modulation identification and parameter estimation of the subsequent signal. Currently, the space-time coding commonly used in MIMO communication is: space diversity (SM) and alamouti (al) space-time orthogonal block codes. The related recognition algorithms can be classified into a maximum likelihood method, a cyclostationary method, a high-order moment method, a distribution fitting test method and the like. The maximum likelihood method has the best performance, but needs prior information of signals and channels, has large calculated amount and is difficult to process in real time; the cyclostationary method does not need prior information of signals and channels; the high order moment method and the distribution fitting test method have poor performance at low signal-to-noise ratio. The invention provides a processing algorithm based on correlation spectrum peak value detection, and the method has simple calculation steps and still has better performance at low signal-to-noise ratio.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an SM/AL space-time code identification method based on correlation spectrum peak value inspection.
In order to achieve the purpose, the invention adopts the following technical scheme:
an SM/AL space-time code identification method based on correlation spectrum peak value inspection is characterized by comprising the following steps:
1) calculating the time delay correlation spectrum module value of the observation signal between two different receiving antennas;
2) taking the maximum value of the correlation spectrum modulus value as the identification statistic;
3) setting a threshold for identifying the MIMO space-time code;
4) and comparing the maximum value of the relevant spectral modulus with a threshold, and identifying two space-time coding types of SM and AL in the MIMO signal.
In order to optimize the technical scheme, the specific measures adopted further comprise:
in step 1):
in the MIMO transmission environment, L transmitting antennas and P receiving antennas are set, L is greater than 1, P is greater than 1, and the receiving signal vector of the receiving antenna is as follows: r (N) ═ h (N) s (N) + w (N), N ═ 0.., N-1, where h (N) is a rayleigh fading type channel matrix, w (N) is additive white gaussian noise, and the variance is white gaussian noise
s (N) is a signal vector, N is a signal sample length;
let the received signal of the ith antenna be ri(n) the received signal of the jth antenna is rj(n), if the delay is τ, the correlation spectrum module value is: c (k) ═ DFT [ ri(n)rj(n-τ)]I, k ≠ 0., N-1, where i ≠ j, the signals participating in the correlation spectrum calculation must come from different receiving antennas, τ > 1, and the received signal r is takeni(n) less than 0.5 times the number of sample dots.
In step 2):
the maximum value of the correlation spectrum modulus value u (k) is used as the identification statistic, and R ═ max { u (k) }.
In step 3):
and setting the corresponding threshold as th, and calculating by the following formula:
wherein, PfaIn order to set the probability of a false alarm,
is the variance of the correlation spectrum sequence.
In step 4):
when R is more than or equal to th, the code type is AL; when R < th, the code pattern is SM.
The invention has the beneficial effects that: the method takes the correlation spectrum among different receiving antennas as a basis, and provides an identification method based on the peak value characteristics of the correlation spectrum on the basis of analyzing the sequence statistic characteristics of the correlation spectrum.
Drawings
FIG. 1 is a flow chart of the identification method of the present invention.
Fig. 2 is a statistical histogram of the maximum of the correlation spectrum mode under different code pattern conditions.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings.
In the method, signals of two different receiving antennas are selected firstly, time delay correlation is carried out on the signals, then correlation spectrum module values of the signals are calculated, the maximum value of the correlation spectrum module values is set as statistic for identification and is compared with a specific threshold, if the maximum value of the correlation spectrum module values is larger than the threshold, the signals are identified as AL codes, otherwise, the signals are identified as SM codes.
Fig. 1 shows a SM/AL space-time code identification method based on correlation spectrum peak detection, which specifically includes the following steps.
First, calculate the correlation spectrum
Assuming that there are L transmitting antennas and P receiving antennas in the MIMO transmission environment, where L > 1 and P > 1, the received signal vector of the receiving antennas is:
r(n)＝H(n)s(n)+w(n)，n＝0，...，N-1
in the formula: h (n) is a Rayleigh fading type channel matrix, w (n) is an additive white Gaussian noise (variance of
) S (N) is a signal vector and N is a signal sample length.
Let the received signal of the ith antenna be ri(n) the received signal of the jth antenna is rj(n) the correlation spectrum modulus is:
U(k)＝|DFT[ri(n)ri(n-τ)]|，k＝0，...，N-1
in the formula, i is not equal to j, namely, the signals participating in the correlation spectrum calculation must come from different receiving antennas, tau is the delay amount, tau is more than 1, and the received signal r is takeni(n) less than 0.5 times the number of sample dots.
Determining recognition statistics
The maximum value of the correlation spectrum modulus value u (k) is used as the identification statistic, i.e., R ═ max { u (k) }.
Setting of three, threshold
And setting the corresponding threshold as th, and calculating by the following formula:
wherein P isfaIn order to set the probability of a false alarm,
is the variance of the correlation spectrum sequence. In practice, the amount of the liquid to be used,
by
Estimated to obtain in
Is the statistical average value of the correlation spectrum after 3-5 large spectral lines are removed.
Four, code pattern recognition
When R is more than or equal to th, the code type is AL; when R < th, the code pattern is SM.
Table 1 illustrates the average identification accuracy of the method, and assuming that there are 2 transmitting antennas and 2 receiving antennas in the MIMO transmission environment, the 1 st receiving antenna and the 2 nd receiving signal are delay-correlated, and the delay amount is 20 sample points. The channel is a Rayleigh fading type channel matrix, the additive noise is additive white Gaussian noise, the signal is divided into 2 time slots when being transmitted, the number of symbols of each time slot is 1024 points, and the signal adopts a QPSK modulation mode. The step length of the signal-to-noise ratio setting range is-3 dB to 12dB and is 3dB, and 1000 times of simulation is respectively carried out on two different code patterns at each signal-to-noise ratio.
From table 1, the correct recognition probability of the method under the above simulation conditions can be seen: when the signal-to-noise ratio is larger than-3 dB, the recognition accuracy of the two code patterns is more than 91%.
| SNR(dB) | -6 | -3 | 0 | 3 | 6 | 9 | 12 |
| Average recognition accuracy | 0.811 | 0.911 | 0.957 | 0.9765 | 0.9745 | 0.9795 | 0.9875 |
TABLE 1 Performance of SM/AL space-time code identification method based on correlation spectrum peak inspection under different signal-to-noise ratios
Fig. 2 shows a statistical histogram of the maximum value of the delay correlation spectrum mode of the two space-time coding systems SM and AL obtained by simulation. The signal-to-noise ratio is set to 0dB, 1000 times of simulation are respectively carried out on two different code patterns, and the conditions of other simulations are the same as those in reference table 1. It can be seen from the figure that, under different space-time code conditions, the statistical histograms of the maximum values of the correlation spectrum values have certain differences, which is the basic basis for the algorithm to identify.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (1)
1. An SM/AL space-time code identification method based on correlation spectrum peak value inspection is characterized by comprising the following steps:
1) calculating the time delay correlation spectrum module value of the observation signal between two different receiving antennas;
in the MIMO transmission environment, L transmitting antennas and P receiving antennas are set, L is greater than 1, P is greater than 1, and the receiving signal vector of the receiving antenna is as follows: r (N) ═ h (N) s (N) + w (N), N ═ 0.., N-1, where h (N) is a rayleigh fading type channel matrix, w (N) is additive white gaussian noise, and the variance is white gaussian noise
s (N) is a signal vector, N is a signal sample length;
let the received signal of the ith antenna be ri(n) the received signal of the jth antenna is rj(n), if the delay is τ, the correlation spectrum module value is: u (k) ═ DFT [ ri(n)rj(n-τ)]I, k ≠ 0., N-1, where i ≠ j, the signals participating in the correlation spectrum calculation must come from different receiving antennas, τ > 1, and the received signal r is takeni(n) less than 0.5 times the number of sample points;
2) taking the maximum value of the correlation spectrum modulus value as the identification statistic;
taking the maximum value of the correlation spectrum modulus value U (k) as an identification statistic, wherein R is max { U (k);
3) setting a threshold for identifying the MIMO space-time code;
and setting the corresponding threshold as th, and calculating by the following formula:
wherein, PfaIn order to set the probability of a false alarm,
is the variance of the sequence of the correlation spectrum,
by
Estimated to obtain in
The statistical average value of the correlation spectrum after 3-5 large spectral lines are removed;
4) comparing the maximum value of the correlation spectrum mode with a threshold, and identifying two space-time coding types of SM and AL in the MIMO signal;
when R is more than or equal to th, the code type is AL; when R < th, the code pattern is SM.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710886169.5A CN107528673B (en) | 2017-09-26 | 2017-09-26 | SM/AL space-time code identification method based on correlation spectrum peak value inspection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710886169.5A CN107528673B (en) | 2017-09-26 | 2017-09-26 | SM/AL space-time code identification method based on correlation spectrum peak value inspection |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107528673A CN107528673A (en) | 2017-12-29 |
| CN107528673B true CN107528673B (en) | 2021-01-26 |
Family
ID=60737536
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710886169.5A Active CN107528673B (en) | 2017-09-26 | 2017-09-26 | SM/AL space-time code identification method based on correlation spectrum peak value inspection |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107528673B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106357574A (en) * | 2016-09-26 | 2017-01-25 | 金陵科技学院 | BPSK (Binary Phase Shift Keying)/QPSK (Quadrature Phase Shift Keying) signal modulation blind identification method based on order statistic |
| CN106357369A (en) * | 2016-09-22 | 2017-01-25 | 金陵科技学院 | Method for identifying MIMO (multiple input multiple output) code types on basis of above-threshold features of correlation spectra |
| CN106411803A (en) * | 2016-09-22 | 2017-02-15 | 金陵科技学院 | Hybrid modulation signal blind-processing result check method based on order statistic characteristics |
| CN106443604A (en) * | 2016-09-22 | 2017-02-22 | 金陵科技学院 | Verification method for blind processing result of LFM/BPSK hybrid modulation signal |
-
2017
- 2017-09-26 CN CN201710886169.5A patent/CN107528673B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106357369A (en) * | 2016-09-22 | 2017-01-25 | 金陵科技学院 | Method for identifying MIMO (multiple input multiple output) code types on basis of above-threshold features of correlation spectra |
| CN106411803A (en) * | 2016-09-22 | 2017-02-15 | 金陵科技学院 | Hybrid modulation signal blind-processing result check method based on order statistic characteristics |
| CN106443604A (en) * | 2016-09-22 | 2017-02-22 | 金陵科技学院 | Verification method for blind processing result of LFM/BPSK hybrid modulation signal |
| CN106357574A (en) * | 2016-09-26 | 2017-01-25 | 金陵科技学院 | BPSK (Binary Phase Shift Keying)/QPSK (Quadrature Phase Shift Keying) signal modulation blind identification method based on order statistic |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107528673A (en) | 2017-12-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110099019B (en) | LoRa modulation signal detection method based on deep learning | |
| CN106357369B (en) | A kind of MIMO identification of code type method based on Correlated Spectroscopy superthreshold value tag | |
| CN106130942A (en) | A kind of wireless communication signals Modulation Identification based on Cyclic Spectrum and method for parameter estimation | |
| CN109951257B (en) | Method for constructing different distributed signal sequences in STBC-OFDM system | |
| CN107018110B (en) | Space-frequency coding blind identification method based on principal component sequence | |
| CN106357574A (en) | BPSK (Binary Phase Shift Keying)/QPSK (Quadrature Phase Shift Keying) signal modulation blind identification method based on order statistic | |
| CN106713190B (en) | MIMO transmitting antenna number blind estimation calculation method based on random matrix theory and characteristic threshold estimation | |
| CN106506427B (en) | A kind of STBC-OFDM Signal blind recognition method based on FOLP | |
| CN111027614B (en) | Noise enhanced radio frequency fingerprint identification method and device | |
| CN108881084B (en) | BPSK/QPSK signal identification method based on GP distribution | |
| CN107682119B (en) | MIMO space-time code identification method based on grouping extreme value model | |
| CN107707497B (en) | Communication signal identification method based on subtraction clustering and fuzzy clustering algorithm | |
| US11310083B2 (en) | Method and system for selecting important delay taps of channel impulse response | |
| CN107528674B (en) | SM/AL space-time code identification method based on Chebyshev inequality | |
| CN107528673B (en) | SM/AL space-time code identification method based on correlation spectrum peak value inspection | |
| CN106341360A (en) | Layered modulation identification method for multiple-input single-output time space group code system | |
| CN113556157B (en) | Method and system for estimating number of transmitting antennas of MIMO system under non-Gaussian interference | |
| CN102111228A (en) | Cognitive radio frequency spectrum sensing method based on circulation symmetry | |
| CN113014361B (en) | BPSK signal confidence test method based on graph | |
| CN108234083B (en) | Method for rapidly determining multi-antenna space-time block code identification threshold | |
| Choqueuse et al. | Blind detection of the number of communication signals under spatially correlated noise by ICA and KS tests | |
| CN116800575A (en) | MIMO-OFDM signal subcarrier blind modulation identification | |
| CN107483376A (en) | A kind of signal detecting method for MIMO ofdm systems | |
| CN103259631A (en) | Frequency spectrum blind detecting method based on characteristic functions in MIMO system | |
| CN107196720B (en) | OFDM signal frequency spectrum sensing method under condition of time synchronization and no frequency offset |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |