CN103929384B - Blind frequency offset estimation method based on maximum likelihood two-dimension search - Google Patents
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Abstract
The invention discloses a blind frequency offset estimation method based on maximum likelihood two-dimension search. The method comprises the steps that a received signal matrix is obtained according to signal information received by a communication receiver; a frequency offset search list and a code parameter search list are initialized; frequency offset compensation signal matrixes are obtained according to a frequency offset search list compensation received signal matrix; according to the code parameter search list, the frequency offset-code parameter maximum likelihood function value of each frequency offset compensation signal matrix is calculated; the frequency offset corresponding to the maximum value in the frequency offset-code parameter maximum likelihood function values is judged. According to the blind frequency offset estimation method based on maximum likelihood two-dimension search, due to the fact that group merging processing is conducted on received signals, the result of the frequency offset-code parameter maximum likelihood function is independent of the data starting position, good estimation performance is provided for non-integrality data, and therefore the frequency offset estimation method has certain tolerance for synchronous errors.
Description
Technical Field
The invention belongs to the technical field of communication, relates to a multi-input multi-output space-time block coding MIMO-STBC technology, and further relates to a blind frequency offset estimation method based on maximum likelihood two-dimensional search. The method can be used for carrying out blind frequency offset estimation on the MIMO-STBC signal in a blind identification scene of the communication signal.
Background
The next generation wireless communication system will provide higher transmission rate and service quality, and in the background of tight spectrum resources, the MIMO-STBC technology can provide technical support for the realization of this goal. In a communication signal blind identification scene, blind estimation and identification are required to be carried out on a non-cooperative communication signal, and blind frequency offset estimation is one of key technologies of signal blind identification.
The existing MIMO-STBC frequency offset estimation algorithms are mainly classified into two types: a data-aided frequency offset estimation algorithm and a blind frequency offset estimation algorithm. The data-assisted frequency offset estimation algorithm comprises a training sequence-based algorithm and a pilot frequency-based algorithm, the complexity of the method is low, the estimation accuracy is high, but the frequency spectrum utilization rate is low due to the overhead of auxiliary data, and the method cannot be applied to the blind identification scene of communication signals. The blind frequency offset estimation algorithm comprises an algorithm based on a cyclic prefix, an algorithm based on a cyclostationary characteristic, a rotation invariant algorithm, a method based on a cost function, a method based on orthogonal space-time coding (OSTBC) and the like, and the method does not need extra auxiliary data overhead, and is high in frequency spectrum utilization rate but low in estimation precision.
Document 1[ Mody A N, stub G L. synchronization for MIMO OFDM systems [ C ]// Global communications Conference,2001.GLOBECOM'01.IEEE.IEEE,2001,1: 509-. The algorithm improves the performance of the algorithm under low signal-to-noise ratio by designing the orthogonal multiphase training sequence which can be directly modulated, and the algorithm complexity is low. The method has the disadvantages that the overhead of the training sequence causes the reduction of the frequency spectrum utilization rate, and the method cannot be applied to the blind identification scene of the communication signals.
Document 2[ Shahbazpanahi S, Gershman A B, Giannakis G B. Joint blue channel carrier frequency estimation in orthogonal space-time block coded MIMOssystems [ C ]// Signal Processing Advances in Wireless Communications,2005 IEEE 6th Workshop on. IEEE,2005:363-367] and document 3 Shahbazpanahi S, Gersman A B, Giannakis G B. Blind and semiconductor channel and carrier frequency-frequency estimation in orthogonal space-time block coded MIMO [ J. Signalprocessing, IEEE Processing, 56. TBC > the frequency offset estimation is performed based on the frequency offset estimation of the TBC coding and the frequency offset estimation is performed using the TBC coding algorithm, the TBC estimation of the frequency offset coding algorithm, TBC estimation algorithm is performed using the frequency offset coding algorithm of the TBC estimation of frequency offset coding algorithm, TBC estimation using the TBC estimation of the frequency offset coding algorithm, TBC estimation of frequency estimation of the TBC estimation of the frequency estimation of frequency offset coding algorithm, TBC estimation of frequency estimation of the TBC estimation of the frequency estimation of the TBC estimation of the frequency estimation of frequency of, but can not aim at the MIMO system of orthogonal and non-orthogonal space-time block coding to carry out effective frequency offset estimation, and the application range is limited.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a blind frequency offset estimation method based on maximum likelihood two-dimensional search for a MIMO-STBC system, which has higher frequency spectrum utilization rate and higher estimation precision compared with a data-assisted frequency offset estimation algorithm; compared with a blind frequency offset estimation algorithm based on an OSTBC code word structure, the method can be used for an MIMO system of OSTBC coding, and can also be suitable for an MIMO system of non-orthogonal space-time block coding and quasi-orthogonal space-time coding, namely the method is suitable for an MIMO-STBC system and has wider application range.
In order to achieve the purpose, the specific thought realized by the invention is as follows: and obtaining a received signal matrix according to the signal information received by the communication receiver. Initializing a frequency offset search list and a code parameter search list. And compensating the received signal matrix according to the frequency offset search list to obtain a frequency offset compensation signal matrix. And respectively calculating a frequency offset-code parameter maximum likelihood function value for each frequency offset compensation signal matrix according to the code parameter search list. And judging the frequency deviation corresponding to the maximum value in the frequency deviation-code parameter maximum likelihood function values.
The invention specifically realizes the following steps:
(1) a signal is received. The communication receiver receives the MIMO signal sent by the transmitting end through the receiving antenna to obtain a received signal matrix Y;
(2) and (5) initializing.
2a) Setting a frequency offset search list: setting a frequency offset searching step length according to the precision requirement of frequency offset estimation, setting a frequency offset searching range according to the frequency offset range of the system, obtaining a frequency offset searching list according to the frequency offset searching step length and the frequency offset searching range, and taking the first frequency offset in the list as the current frequency offset;
2b) setting a code parameter search list: according to the number of transmitting antennas, listing code parameters corresponding to all possible STBC, namely the packet length and the number of information symbols contained in each packet, and taking a first group of code parameters in the list as current code parameters;
(3) compensating the received signal matrix: and performing frequency offset compensation on the received signal matrix by using the current frequency offset to obtain a frequency offset compensation signal matrix.
(4) And carrying out pre-whitening processing on the frequency offset compensation signal matrix to obtain a pre-whitened signal matrix.
(5) Calculating a frequency offset-code parameter maximum likelihood function:
5a) connecting the real part and the imaginary part of the pre-whitened signal matrix in parallel, and performing grouping and combining treatment, namely connecting the column vectors of the received signals belonging to the same group in parallel according to the current code parameters and calculating the correlation matrix of the received signals;
5b) performing eigenvalue decomposition on the correlation matrix in the step 5a) to obtain an eigenvalue matrix;
5c) calculating a frequency offset-code parameter maximum likelihood function according to the current code parameter:
wherein N isrIs the number of receiving antennas, pkIs the eigenvalue matrix obtained in step 5a), where l is the packet length corresponding to the current code parameter, and n is the number of information symbols contained in each packet corresponding to the current code parameter.
(6) And recording the frequency offset-code parameter maximum likelihood function value corresponding to the current frequency offset and the current code parameter.
(7) And (4) judging whether the code parameter search list is traversed or not, if so, switching to the step (8), otherwise, updating the current code parameter according to the code parameter search list, and switching to the step (5).
(8) Judging whether the frequency offset search list is traversed or not, if so, switching to the step (9), otherwise, updating the current frequency offset according to the frequency offset search list, and switching to the step (4);
(9) and taking the frequency deviation corresponding to the maximum value of the frequency deviation-code parameter maximum likelihood function in the record set as the judgment frequency deviation.
Compared with the prior art, the invention has the following advantages:
1. the invention adopts the two-dimensional maximum likelihood search of the frequency offset-code parameter to the received signal, so that the estimation precision of the method is high.
2. Because the invention only uses the code word structure of STBC to estimate the frequency offset, no training sequence or pilot frequency is needed. The system can reduce the overhead of a training sequence or a pilot frequency, so the frequency spectrum utilization rate is higher;
3. because the frequency offset-code parameter maximum likelihood function of the system only depends on the grouping length and the grouping symbol number, the invention can be suitable for multiple conditions of orthogonality, non-orthogonality and quasi-orthogonality, and layered space-time block code LSTBC, and the like, and has wide application range;
because the invention adopts grouping combination processing to the received signal, the result of the frequency offset-code parameter maximum likelihood function does not depend on the initial position of the data, and has good estimation performance to non-integrity data, therefore, the method has certain tolerance to synchronous error;
drawings
FIG. 1 is a schematic diagram of a system model used in the present invention;
FIG. 2 is a flow chart of the present invention;
fig. 3 is a diagram of comparing the mean square error of frequency offset estimation of the present invention with the prior blind frequency offset estimation algorithm based on training sequence periodicity.
Detailed Description
The present invention will be described in detail with reference to specific examples.
Referring to fig. 1, the system model used in the present invention includes 1 transmitter and 1 receiver, wherein the number of antennas of the transmitter is NtThe number of antennas of the receiver is NrAnd N isr≥Nt(ii) a At the transmitter, the information sequence is space-time block coded (STBC), the serial data stream is converted into parallel data streams, and then N is passed respectivelytThe root antenna transmits. The transmitted signal reaches the receiver through a flat Rayleigh quasi-static channel, and the received signal is represented as Y ═ HX + B, wherein Y is a received signal matrix, H is a channel matrix with independent elements and obeying Gaussian distribution, X is a transmitted signal matrix, and B is a Gaussian white noise matrix.
The invention is described in further detail below with reference to fig. 2.
Step 1, a receiver receives an MIMO signal sent by a transmitting end through a receiving antenna to obtain a received signal matrix Y:
wherein,indicating the nth of the receiverrThe signal received by the root antenna in the first time slot is n or more than 1r≤Nr，NrL is more than or equal to 1 and less than or equal to L which is the number of time slots for receiving signals by the receiver.
And step 2, initializing.
2a) Setting a frequency offset search list: setting a frequency offset searching step length according to the precision requirement of frequency offset estimation, setting a frequency offset searching range according to the frequency offset range of the system, obtaining a frequency offset searching list according to the frequency offset searching step length and the frequency offset searching range, and taking the first frequency offset in the list as the current frequency offset f;
2b) setting a code parameter search list: according to the number of transmitting antennas, listing code parameters corresponding to all possible STBC, namely the packet length and the number of information symbols contained in each packet, and taking a first group of code parameters in the list as current code parameters (n, l);
and 3, compensating the received signal matrix.
Performing frequency offset compensation on the received signal matrix by using the current frequency offset to obtain a frequency offset compensation signal matrix
Wherein j is an imaginary unit, f is the current frequency offset, and L is the time slot number of the receiving signal of the receiver;
and 4, pre-whitening treatment.
4a) Calculating the correlation matrix of the frequency offset compensation signal matrix, and performing eigenvalue decomposition on the correlation matrix to obtain an eigenvector matrix U and an eigenvalue matrix Λ2：
Wherein λ is1≥λ2≥…λk，
4b) And calculating a whitening matrix W by using the eigenvector matrix U and the eigenvalue matrix:
wherein, (.)TRepresenting a transpose operation;
4c) and carrying out pre-whitening processing on the frequency offset compensation signal matrix by using the whitening matrix W to obtain a pre-whitened signal matrix.
And 5, calculating the frequency offset-code parameter maximum likelihood function.
5a) And (3) connecting the real part and the imaginary part of the pre-whitening signal matrix in parallel, and performing grouping and combining treatment, namely connecting column vectors of the received signals belonging to the same group in parallel according to code parameters, and calculating a correlation matrix of the column vectors.
5b) Performing eigenvalue decomposition on the correlation matrix in the step 5a) to obtain an eigenvalue matrix;
5c) calculating a frequency offset-code parameter maximum likelihood function according to the current code parameter:
wherein N isrIs the number of receiving antennas, pkIs the eigenvalue matrix obtained in step 5b), where l is the packet length corresponding to the current code parameter, and n is the number of information symbols contained in each packet corresponding to the current code parameter.
And 6, recording the current frequency offset and the frequency offset-code parameter maximum likelihood function value corresponding to the current code parameter.
And 7, judging whether the code parameter search list is traversed or not, if so, turning to a step 8, otherwise, updating the current code parameter according to the code parameter search list, and turning to a step 5.
And 8, judging whether the frequency offset search list is traversed or not, if so, turning to the step 9, otherwise, updating the current frequency offset according to the frequency offset search list, and turning to the step 4.
And 9, taking the frequency deviation corresponding to the maximum value of the frequency deviation-code parameter maximum likelihood function in the record set as the judgment frequency deviation.
The effects of the present invention will be described in detail with reference to fig. 3.
1. Simulation conditions
The simulation system is the number N of transmitting antennastReceiving antenna N4rMIMO-STBC system of 8. The length of the transmission signal frame is 96, and the data adopts QKSP modulation and adopts non-orthogonal space-time coding. The elements of the channel matrix H are independently and identically distributed and obey complex Gaussian distribution with the mean value of 0 and the variance of 1, the noise is white Gaussian noise, the mean value is 0, and the variance isDetermined by the normalized signal-to-noise ratio. The sample symbol length is 1000. The simulation signal-to-noise ratio range is 0-25 dB, Monte Carlo simulation is carried out every 5dB, and the Monte Carlo simulation frequency is 1000.
Each frame of signal in the simulation system 1 is composed of a training sequence and data, the training sequence is an orthogonal multiphase training sequence which can be directly modulated and is proposed in the literature [1], the length of the training sequence is 32, and the length of the data is 64. Each frame of signal in the simulation system 2 has no training sequence and only consists of data, and the data length is 96. The spectrum utilization of the simulation system 2 is higher than that of the simulation system 1.
2. Simulation content and simulation result
The system 1 and the system 2 are compared in simulation by using the training sequence design-based method proposed in the document 1 and the present invention, respectively, as shown in fig. 3. Wherein, the solid line marked by the circle represents that the simulation system 1 adopts the frequency deviation estimation normalized mean square error of the frequency deviation estimation algorithm designed based on the training sequence, and the solid line marked by the square represents that the simulation system 2 adopts the frequency deviation estimation normalized mean square error of the invention. It can be seen from the figure that the detection method of the present invention can perform effective frequency offset estimation on the non-orthogonal space-time coded MIMO signal, and the estimation accuracy is higher than that of the frequency offset estimation algorithm based on the training sequence.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.
Claims (5)
1. A blind frequency offset estimation method based on maximum likelihood two-dimensional search is characterized by comprising the following steps:
(1) receiving a signal; a communication receiving end receives the MIMO signal sent by a transmitting end through a receiving antenna to obtain a received signal matrix Y;
(2) initializing;
2a) setting a frequency offset search list: setting a frequency offset searching step length according to the precision requirement of frequency offset estimation, setting a frequency offset searching range according to the frequency offset range of the system, obtaining a frequency offset searching list according to the frequency offset searching step length and the frequency offset searching range, and taking the first frequency offset in the list as the current frequency offset;
2b) setting a code parameter search list: according to the number of transmitting antennas, code parameters corresponding to all possible space-time block coding (STBC), namely the block length and the number of information symbols contained in each block, are listed, and a first group of code parameters in the list are used as current code parameters;
(3) compensating the received signal matrix: performing frequency offset compensation on the received signal matrix Y by using the current frequency offset to obtain a frequency offset compensation signal matrix
(4) Compensating signal matrix for frequency deviationPerforming pre-whitening processing to obtain a pre-whitened signal matrix;
(5) calculating a frequency offset-code parameter maximum likelihood function:
5a) connecting the real part and the imaginary part of the pre-whitened signal matrix in parallel, and performing grouping and combining treatment, namely connecting the column vectors of the received signals belonging to the same group in parallel according to the current code parameters and calculating the correlation matrix of the received signals;
5b) performing eigenvalue decomposition on the correlation matrix in the step 5a) to obtain an eigenvalue matrix;
5c) calculating a frequency offset-code parameter maximum likelihood function according to the current code parameter:
wherein N isrIs the number of receiving antennas, L is the number of time slots in which the receiver receives the signal, pkThe eigenvalue matrix obtained in step 5a), wherein l is the packet length corresponding to the current code parameter, and n is the number of information symbols contained in each packet corresponding to the current code parameter;
(6) recording the current frequency offset and the frequency offset-code parameter maximum likelihood function value corresponding to the current code parameter;
(7) judging whether the code parameter search list is traversed or not, if so, turning to the step (8), otherwise, updating the current code parameter according to the code parameter search list, and turning to the step (5);
(8) judging whether the frequency offset search list is traversed or not, if so, switching to the step (9), otherwise, updating the current frequency offset according to the frequency offset search list, and switching to the step (4);
(9) and taking the frequency deviation corresponding to the maximum value of the frequency deviation-code parameter maximum likelihood function in the record set as the judgment frequency deviation.
2. The blind frequency offset estimation method according to claim 1, wherein the received signal matrix Y of step (2):
wherein,indicating the nth of the receiverrThe signal received by the root antenna in the first time slot is n or more than 1r≤Nr，NrL is more than or equal to 1 and less than or equal to L which is the number of time slots for receiving signals by the receiver.
3. The blind frequency offset estimation method according to claim 1, wherein the compensation of the received signal matrix in step (3) is performed by the following formula:
wherein j is an imaginary unit, f is the current frequency offset, and L is the time slot number of the receiving signal of the receiver.
4. The blind frequency offset estimation method according to claim 1, wherein the specific method in step 4) is:
4a) calculating frequency offsetCompensating the correlation matrix of the signal matrix, and performing eigenvalue decomposition on the correlation matrix to obtain an eigenvector matrix U and an eigenvalue matrix Λ2：
Wherein λ is1≥λ2≥…λk，
4b) And calculating a whitening matrix W by using the eigenvector matrix U and the eigenvalue matrix:
wherein, (.)TRepresenting a transpose operation;
4c) and carrying out pre-whitening processing on the frequency offset compensation signal matrix by using the whitening matrix W to obtain a pre-whitened signal matrix.
5. The blind frequency offset estimation method of claim 1 wherein said eigenvalue matrix is sorted in descending order of eigenvalue magnitude.
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