WO2020177766A1 - 多径分离方法、装置和存储介质 - Google Patents

多径分离方法、装置和存储介质 Download PDF

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WO2020177766A1
WO2020177766A1 PCT/CN2020/078246 CN2020078246W WO2020177766A1 WO 2020177766 A1 WO2020177766 A1 WO 2020177766A1 CN 2020078246 W CN2020078246 W CN 2020078246W WO 2020177766 A1 WO2020177766 A1 WO 2020177766A1
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matrix
frequency domain
domain response
toplitz
multipath
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PCT/CN2020/078246
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English (en)
French (fr)
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陈诗军
王园园
陈大伟
毕程
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中兴通讯股份有限公司
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Priority to US17/436,959 priority Critical patent/US11843482B2/en
Priority to EP20767043.1A priority patent/EP3937443A4/en
Publication of WO2020177766A1 publication Critical patent/WO2020177766A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H04L25/0248—Eigen-space methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/022—Channel estimation of frequency response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2668—Details of algorithms
    • H04L27/2669—Details of algorithms characterised by the domain of operation
    • H04L27/2672—Frequency domain

Definitions

  • This application relates to the field of wireless communication networks, for example, to a method, device, and storage medium for multipath separation.
  • the positioning function has become a standard configuration of portable terminal equipment, but satellite positioning technology may not be able to complete positioning due to the inability to search for enough satellite signals in indoor or dense urban areas.
  • the coverage environment of cellular networks is better than satellite signals, and the technology of using cellular networks to assist positioning has been widely used.
  • the multi-path separation processing method uses the Multiple Signal Classification (MUSIC) algorithm.
  • MUSIC Multiple Signal Classification
  • the MUSIC algorithm has a high degree of multi-path recognition under ideal conditions.
  • the noise sensitivity problem of the MUSIC algorithm in a noisy environment, the MUSIC algorithm The deterioration of multi-path recognition is serious, and the multi-path cannot be separated.
  • the cellular networks are all Orthogonal Frequency Division Multiplexing (OFDM) systems. Because the OFDM system has zero frequency, it destroys the uniformity of the frequency domain signal distribution and affects the noise adaptation of the MUSIC algorithm for multipath separation. ability.
  • OFDM Orthogonal Frequency Division Multiplexing
  • the present application provides a multipath separation method, device, and storage medium, which can improve the noise adaptability of multipath separation.
  • the embodiment of the present application provides a multipath separation method, including:
  • the size of the Toplitz matrix corresponding to each frequency band is determined according to the number of subcarriers contained in each frequency band, and at least two The number of rows of the Toplitz matrix corresponding to different frequency bands is the same;
  • the delay is the delay of one path in the multipath.
  • the embodiment of the present application provides a multipath separation device, including:
  • the feature extraction module is configured to extract frequency domain response features of at least two received reference signals of different frequency bands
  • the matrix construction module is set to construct the Toplitz matrix corresponding to each frequency band according to the frequency domain response characteristics of the reference signal of each frequency band, and the size of the Toplitz matrix corresponding to each frequency band is based on the subcarriers contained in each frequency band The number is determined, and the number of rows of the Toplitz matrix corresponding to at least two different frequency bands is the same;
  • the matrix synthesis module is set to merge at least two Toplitz matrices corresponding to different frequency bands into a synthesized Toplitz matrix
  • the matrix decomposition module is set to perform singular value decomposition on the synthesized Toplitz matrix, and determine the signal space matrix and the noise space matrix according to the decomposed matrix;
  • the vector construction module is configured to construct multiple frequency domain response vectors according to the frequency domain response characteristics of multiple local signals with different time delays, and the local signals are the same as the reference signal;
  • the multipath separation module is set to inner product multiple frequency domain response vectors with the noise space matrix respectively, and after comparing the size of the inner product with a preset threshold, determine each of the multiple frequency domain response vectors that meet the preset threshold
  • the time delay corresponding to the frequency domain response vector is the time delay of one path in the multipath.
  • the embodiment of the present application provides a storage medium, and the storage medium stores a computer program.
  • the computer program is executed by a processor, any multipath separation method in the embodiments of the present application is implemented.
  • FIG. 1 is a flowchart of a multipath separation method according to an embodiment
  • FIG. 3 is a flowchart of another multipath separation method provided by an embodiment
  • FIG. 4 is a schematic structural diagram of a multipath separation device provided by an embodiment
  • Fig. 5 is a schematic structural diagram of a terminal provided by an embodiment.
  • the traditional positioning technology is satellite positioning technology, which uses the satellite positioning chip set in the terminal to receive the signals emitted by multiple positioning satellites and calculates to achieve positioning, such as the Global Positioning System (GPS) and the Global Satellite Navigation System ( Global Navigation Satellite System (GLONASS), Beidou satellite positioning system, etc., have been widely used in terminal equipment.
  • GPS Global Positioning System
  • GLONASS Global Satellite Navigation System
  • Beidou satellite positioning system etc.
  • the wireless signal in the cellular communication network will propagate in the space area due to many factors.
  • the wireless signal sent by the transmitting end may reach the receiving end through multiple paths, and the signals arriving at the receiving end through multiple paths have different times.
  • the signals received through multiple paths will affect each other and cause signal distortion. This is the multipath effect of electromagnetic waves. In order to solve the multipath effect, it is necessary to perform multipath separation processing on the received signal.
  • the MUSIC algorithm has a high degree of multipath recognition under ideal circumstances, and can identify multipaths with a delay interval much shorter than the sampling period.
  • the multipath recognition of the MUSIC algorithm deteriorates seriously, the path width becomes wider, and the multipath overlaps each other, which makes the multipath impossible to separate.
  • Cellular communication networks such as the 4th Generation (4G) and 5th Generation (5G) mobile communication systems, are both OFDM systems. Since the OFDM system has zero frequency, it destroys the frequency domain signal distribution. Due to the uniformity of the MUSIC algorithm, the full bandwidth cannot be fully utilized when the MUSIC algorithm is used for multipath separation, which affects the noise adaptability when the MUSIC algorithm is used for multipath separation.
  • a multipath separation method is provided to overcome the discontinuity problem caused by frequency domain resource segmentation caused by the 0 frequency in the OFDM system, thereby improving the noise adaptability of the multipath separation and the accuracy of the multipath separation .
  • Fig. 1 is a flowchart of a multipath separation method provided in an embodiment. As shown in Fig. 1, the method provided in this embodiment includes the following steps.
  • Step S1010 Extract frequency domain response characteristics of at least two received reference signals of different frequency bands.
  • Multipath separation is applied to the receiving end of the wireless signal.
  • the wireless signal may reach the receiving end through multiple paths.
  • the arrival time of signals received through multiple paths is different, which may affect the synthesis of wireless signals.
  • the transmitter and receiver of wireless signals need to send a variety of reference signals when transmitting wireless signals, such as sounding reference signal (Sounding Reference Signal, SRS), cell reference signal (Cell Reference Signal, CRS) ), demodulation reference signal (Demodulation Reference Sgnal, DMRS), positioning reference signal (Positioning Reference Signal, PRS), etc.
  • Various reference signals sent by the transmitting end exist in the receiving end, and the receiving end can obtain various parameters of the wireless channel by analyzing the received multiple reference signals to be applied to data reception.
  • the signal received by the receiving end will include reference signals received through multiple different paths, and the receiving end needs to analyze the received reference signals to achieve multipath separation.
  • the wireless communication system may also be multi-frequency, that is, in addition to the influence of frequency 0, it may also send reference signals through multiple different frequency bands, so the receiving end may receive two or more segments that are not in the frequency domain. Continuous reference signals, and these reference signals may be of the same frequency or of different frequencies.
  • the multipath separation of the wireless communication system it actually uses the relevant characteristics of multiple sub-carrier signals in the frequency band to analyze the received reference signal to achieve multipath separation, and if the received reference signal is in the frequency domain If it is not continuous, it will affect the processing capability of multipath separation. Therefore, the multipath separation method has a great impact on accuracy when it is applied to the OFDM system.
  • the embodiment of this application is an improvement to the situation where the received signal is discontinuous in the frequency domain. By combining multiple received reference signals of different frequency bands, the processing capability of multipath separation is improved. , To achieve the purpose of improving the accuracy of multipath separation.
  • the multipath separation method provided in the embodiments of the present application can be applied to OFDM systems, which are wireless communication systems in which the received signal is discontinuous in the frequency domain due to the presence of zero frequency, and can also be applied to other reasons that cause the received signal to be in the frequency domain.
  • OFDM systems which are wireless communication systems in which the received signal is discontinuous in the frequency domain due to the presence of zero frequency, and can also be applied to other reasons that cause the received signal to be in the frequency domain.
  • Discontinuous wireless communication systems such as multi-frequency wireless communication systems.
  • the frequency domain response characteristics are related characteristics that a signal changes with frequency changes, including but not limited to channel characteristics, power characteristics, and related characteristics.
  • the extracted frequency domain response characteristics actually include the frequency domain response characteristics of multiple subcarriers of the reference signal of each frequency band.
  • Step S1020 Construct a Toplitz matrix corresponding to each frequency band according to the frequency domain response characteristics of the reference signal of each frequency band, and the size of the Toplitz matrix corresponding to each frequency band is determined according to the number of subcarriers contained in each frequency band. And the number of rows of the Toplitz matrix corresponding to at least two segments of different frequency bands is the same.
  • the Toeplitz matrix is referred to as the T-type matrix, the main pair of the Toeplitz matrix The elements on the diagonal are equal, and the elements on the line parallel to the main diagonal are also equal. Multiple elements in the Toplitz matrix are symmetric about the subdiagonal line, that is, the Toplitz matrix is a sub-symmetric matrix.
  • the simple Toplitz matrix includes a forward displacement matrix and a backward displacement matrix.
  • the size of the Toplitz matrix corresponding to each frequency band is determined according to the number of sub-carriers contained in each frequency band.
  • the product of the number of rows and the number of columns of the Toplitz matrix corresponding to each frequency band is approximately equal to the number of sub-carriers contained in the frequency band. Quantity.
  • the number of rows of the Toplitz matrix corresponding to at least two different frequency bands is the same.
  • the Toplitz matrix corresponding to each frequency band is an M ⁇ N i matrix, where M is , N i is Column, i is the band identified, i ⁇ (1, ..., t ), t is the number of frequency bands, M, and N i is determined according to the number of subcarriers in frequency bands i.
  • the Toplitz matrix corresponding to frequency band i For example:
  • M is estimated in accordance with multi-path capability of a receiving terminal is determined, in general, M is smaller than N i. i ⁇ (1,...,t), t is the number of frequency bands.
  • step S1030 at least two sections of Toplitz matrices corresponding to different frequency bands are merged into a synthesized Toplitz matrix.
  • the MUSIC algorithm used is to process the frequency domain response characteristics corresponding to multiple frequency bands.
  • the MUSIC algorithm cannot make full use of the entire received signal.
  • the frequency domain response characteristics of the frequency band affect the noise adaptability of multipath separation.
  • the synthesized Toplitz matrix represents the frequency domain response characteristics of all frequency bands of the received signal, which is equivalent to increasing the bandwidth of the signal to be analyzed, then the synthesized Toplitz matrix is analyzed, A larger bandwidth can be used, thereby improving the noise adaptability of multipath separation.
  • T M ⁇ N represents the synthesized Toplitz matrix
  • the synthesized Toplitz matrix T M ⁇ N can be expressed as:
  • Step S1040 Perform singular value decomposition on the synthesized Toplitz matrix, and determine the signal space matrix and the noise space matrix according to the decomposed matrix.
  • the obtained synthesized Toplitz matrix represents the frequency domain response characteristics of the entire frequency band of the received reference signal, and the signal characteristics of the received reference signal can be obtained by analyzing the synthesized Toplitz matrix.
  • the processing method of analyzing the synthesized Toplitz matrix to obtain the signal characteristics of the received reference signal is a method using Singular Value Decomposition (SVD).
  • Singular value decomposition can represent a more complex matrix by the multiplication of several smaller and simpler sub-matrices, which describe important characteristics of the matrix.
  • U is an m ⁇ m matrix
  • ⁇ is an m ⁇ n matrix, all 0 except the elements on the main diagonal, each element on the main diagonal is called a singular value
  • V is a n ⁇ n matrix
  • V H is the conjugate matrix of V.
  • the columns of the matrix U form a set of orthogonal input or analysis basis vectors to M. These vectors are the feature vectors of MM*.
  • the columns of matrix V form a set of basis vectors for the orthogonal output of M. These vectors are the feature vectors of M*M.
  • the elements on the diagonal of the matrix ⁇ are singular values, which can be regarded as scalar expansion control between input and output. These are the singular values of M*M and MM*, and correspond to the column vectors of the matrix U and matrix V.
  • V H can be decomposed into a signal space matrix V1 and a noise space matrix V0 according to the size of the eigenvalue.
  • the signal space matrix V1 refers to the matrix composed of column vectors in V H corresponding to the eigenvalue modulus of the matrix ⁇ greater than or equal to the preset threshold
  • the noise space matrix V0 refers to the matrix ⁇ whose eigenvalue modulus is less than the preset
  • the eigenvalues of the threshold correspond to the matrix of column vectors in V H.
  • the modulus of the eigenvalue in the matrix ⁇ is determined according to the distribution of the eigenvalue.
  • Step S1050 Construct multiple frequency domain response vectors according to the frequency domain response characteristics of multiple local signals with different time delays, and the local signals are the same as the reference signal.
  • the signal space matrix and the noise space matrix are obtained, that is, the signal and noise characteristics of the space area are analyzed through the received reference signal. Since the reference signal received by the wireless signal receiving end has the original signal stored locally at the receiving end, the purpose of multipath separation is to determine the path in the space through which the reference signal sent by the transmitting end reaches the receiving end. The reference signal passes through different paths. The time for the path to reach the receiving end is different, that is, it has a different delay. Then, by setting different time delays for the original reference signals stored in the receiving end, and using the orthogonality between the reference signals with different time delays and the noise space vector, it is possible to judge whether the reference signals with different time delays are existing signals.
  • the frequency domain response characteristic of the signal finally obtains the frequency domain response vector corresponding to each delay signal, where the local signal is the same as the received reference signal.
  • the length of the frequency domain response vector corresponding to each time delay signal is the same as the length of the vector in the noise space.
  • the received reference signal is in multiple frequency bands
  • the same local reference signal as the received reference signal is also in multiple frequency bands.
  • the frequency domain response vector of is synthesized into a synthesized frequency domain response vector.
  • the decomposed matrix V H is an N ⁇ N matrix
  • Response vector Then the characteristic response vectors of multiple frequency bands are combined into a synthesized frequency domain response vector L ⁇ .
  • each frequency domain element of each L ⁇ is e jw ⁇ , where w is N-dimensional and has a linear relationship with the frequency domain feature corresponding to the reverse order of the first row of the synthesized Toplitz matrix.
  • Step S1060 Inner product the multiple frequency domain response vectors with the noise space matrix, and compare the size of the inner product with a preset threshold to determine each frequency domain response vector in the multiple frequency domain response vectors that meet the preset threshold The corresponding delay is the delay of one path in the multipath.
  • the frequency domain response vectors corresponding to the multiple time delay signals are respectively multiplied by the noise space matrix, and then the product result is compared with the preset threshold value, and finally each frequency domain response vector of the multiple frequency domain response vectors meeting the preset threshold value is determined.
  • the time delay corresponding to the domain response vector is the time delay of one path in the space, thereby realizing multipath separation. Since the noise space matrix is in the form of a matrix, multiplying the frequency domain response vector by the noise space matrix is actually the inner product of the frequency domain response vector and all vectors in the noise space vector, and then sum all the inner products, Get the product result.
  • the method of inner producting multiple frequency domain response vectors with the noise space matrix and determining the time delay may be, for example, summing the multiple frequency domain response vectors with the noise space matrix. After calculating the reciprocal, the time delay corresponding to each frequency domain response vector in the multiple frequency domain response vectors whose reciprocal is greater than the preset threshold is determined as the time delay of one path in the multipath.
  • the path with the time delay ⁇ is considered to be an actual path, that is, the signal with the time delay ⁇ is a signal existing in space, ⁇ Is the relative arrival time of the trail.
  • the preset threshold b is determined after calculating the value of p ⁇ corresponding to all time delays. After calculating the p ⁇ corresponding to all time delays, the maximum value of p ⁇ is multiplied by a coefficient ⁇ to obtain the preset threshold b, The coefficient ⁇ is determined by simulation results.
  • the multipath separation method provided in the embodiments of this application is not limited to use for positioning.
  • the multipath separation method provided in the embodiments of this application can be applied to various fields such as signal separation, signal detection, signal estimation, etc., as long as multipath exists in the spatial region. If the signal is transmitted through multiple discontinuous frequency bands, the multipath separation method provided in the embodiment of the present application can be used to perform multipath separation processing on the signal, thereby improving the accuracy of the multipath separation.
  • the multipath separation method extracts the frequency domain response characteristics of at least two received reference signals of different frequency bands, and constructs a Toplitz corresponding to each frequency band according to the frequency domain response characteristics of the reference signals of each frequency band Matrix, and then merge at least two sections of Toplitz matrix corresponding to different frequency bands into a synthesized Toplitz matrix, and perform singular value decomposition on the synthesized Toplitz matrix, and determine the signal space matrix and noise space according to the decomposed matrix Matrix, and then construct multiple frequency domain response vectors according to the frequency domain response characteristics of multiple local signals with different time delays that are the same as the received reference signal.
  • the delay corresponding to each of the multiple frequency domain response vectors that meet the preset threshold is the delay of one path in the multipath, thereby achieving multipath separation. Since the frequency domain response characteristics corresponding to signals of multiple different frequency bands are synthesized, the entire bandwidth of the received signal is fully utilized when the frequency domain response characteristics are processed, thereby improving the noise adaptability of the multipath separation processing. Therefore, the accuracy of multipath separation is improved.
  • the following takes the processing of multi-path separation on signals as an example to describe the multi-path separation method provided in the embodiments of the present application.
  • FIG. 2 is a flowchart of another multipath separation method provided by an embodiment.
  • the multipath separation method provided in this embodiment is used for multipathing positioning reference signals in a Long Term Evolution (LTE) system. Separate. As shown in Figure 2, the method provided in this embodiment includes the following steps.
  • LTE Long Term Evolution
  • Step S2010 extract the frequency domain response characteristics of the received positioning reference signal.
  • a single base station has a maximum of 200 subcarriers in the frequency domain on one symbol in the time domain.
  • the 200 subcarriers are divided into 100 subcarriers in the left frequency band and 100 subcarriers in the right frequency band.
  • the frequency domain response characteristic H 1 (w) corresponding to the 100 sub-carriers w belonging to the left frequency band and the frequency domain response characteristic H 2 (w) corresponding to the 100 sub-carriers w belonging to the right frequency band are obtained.
  • Step S2020 Construct a Toplitz matrix corresponding to each frequency band according to the frequency domain response characteristics of the positioning reference signal of each frequency band.
  • H 1 (w) and H 2 (w) need to be constructed as corresponding Toplitz matrices T 1 and T 2 respectively .
  • N 1 N 2
  • the matrices T 1 and T 2 have the characteristics that the elements on the main diagonal are equal, and the elements parallel to the main diagonal are also equal.
  • Step S2030 Combine the Toplitz matrices corresponding to the multiple frequency bands into a combined Toplitz matrix.
  • Step S2040 Perform singular value decomposition on the synthesized Toplitz matrix, and determine the signal space matrix and the noise space matrix according to the decomposed matrix.
  • Step S2050 Construct multiple frequency domain response vectors according to the frequency domain response characteristics of multiple local positioning reference signals with different time delays.
  • W n2 C 2 ⁇ [w2 1 w2 2 ...w2 N1 ]+b 2 n2 ⁇ N1+1,N1+2,...N ⁇ , where w2 is the first N1 frequency domain subcarriers corresponding to H 2 (w) position.
  • Step S2060 After inner producting the multiple frequency domain response vectors with the noise space matrix respectively, comparing the size of the inner product with a preset threshold, determine each frequency domain response of the multiple frequency domain response vectors that meet the preset threshold The delay corresponding to the vector is the delay of one path in the multipath.
  • the threshold value set P k, and P k is larger than the threshold value L k corresponding to a delay ⁇ k space is present in diameter.
  • the threshold value P k is calculated after all the delay values corresponding to P k is determined, in the calculation of all the delays corresponding P k, P k is the maximum value multiplied by a factor [alpha], to obtain the threshold value, the coefficient [alpha] by The simulation result is confirmed.
  • FIG. 3 is a flowchart of another multipath separation method provided by an embodiment.
  • the multipath separation method provided in this embodiment is used for multipath separation of a New Radio (NR) reference signal in 5G.
  • the method provided in this embodiment includes the following steps.
  • Step S3010 Extract the frequency domain response characteristics of the received NR reference signal.
  • the NR reference signal is affected by the 0 frequency and is divided into a left frequency band and a right frequency band.
  • the left frequency band and the right frequency band respectively include multiple subcarriers.
  • the left frequency band and the right frequency band are divided into two frequency bands, and frequency domain response characteristics (including but not limited to channel characteristics, power characteristics, correlation characteristics, etc.) of the subcarriers of the two frequency bands are extracted. Then the frequency domain response characteristic H 1 (w) corresponding to the subcarrier w of the left frequency band and the frequency domain response characteristic H 2 (w) corresponding to the subcarrier w of the right frequency band are obtained.
  • Step S3020 Construct a Toplitz matrix corresponding to each frequency band according to the frequency domain response characteristics of the NR reference signal of each frequency band.
  • H 1 (w) and H 2 (w) need to be constructed as corresponding Toplitz matrices T 1 and T 2 respectively .
  • the matrices T 1 and T 2 have the characteristics that the elements on the main diagonal are equal, and the elements parallel to the main diagonal are also equal.
  • Step S3030 Combine the Toplitz matrices corresponding to the multiple frequency bands into a synthesized Toplitz matrix.
  • Step S3040 Perform singular value decomposition on the synthesized Toplitz matrix, and determine the signal space matrix and the noise space matrix according to the decomposed matrix.
  • Step S3050 Construct multiple frequency domain response vectors according to the frequency domain response characteristics of multiple NR reference signals with different time delays.
  • W n2 C 2 ⁇ [w2 1 w2 2 ...w2 N1 ]+b 2 n2 ⁇ N1+1,N1+2,...N ⁇ , where w2 is the first N1 frequency domain subcarriers corresponding to H 2 (w) position.
  • Step S3060 After inner producting the multiple frequency domain response vectors with the noise space matrix, the size of the inner product is compared with a preset threshold, and then each frequency domain response vector of the multiple frequency domain response vectors meeting the preset threshold is determined The corresponding delay is the delay of one path in the multipath.
  • the threshold value set P k, and P k is larger than the threshold value L k corresponding to a delay ⁇ k space is present in diameter.
  • the threshold value P k is calculated after all the delay values corresponding to P k is determined, in the calculation of all the delays corresponding P k, P k is the maximum value multiplied by a factor [alpha], to obtain the threshold value, the coefficient [alpha] by The simulation result is confirmed.
  • Fig. 4 is a schematic structural diagram of a multi-path separation device provided by an embodiment.
  • the multi-path separation device provided in this embodiment includes: a feature extraction module 41 configured to extract at least two different segments received The frequency domain response characteristics of the reference signal of the frequency band; the matrix construction module 42 is set to construct the Toplitz matrix corresponding to each frequency band according to the frequency domain response characteristics of the reference signal of each frequency band, and the Toplitz matrix corresponding to each frequency band The size of is determined according to the number of subcarriers contained in each frequency band, and the number of rows of the Toplitz matrix corresponding to at least two sections of different frequency bands is the same; the matrix synthesis module 43 is set to set at least two sections of Toplitz matrix corresponding to different frequency bands The matrix decomposition module 44 is set to perform singular value decomposition on the synthesized Toplitz matrix, and the signal space matrix and the noise space matrix are determined according to the decomposed matrix; the vector construction module 45 is set to According to the frequency domain response characteristics of multiple local signals with different time delays,
  • the multipath separation device provided in this embodiment is used to implement the multipath separation method of the embodiment shown in FIG. 1.
  • the implementation principle and technical effect of the multipath separation device provided in this embodiment are similar, and will not be repeated here.
  • the matrix construction module 42 is configured to construct the Toplitz matrix corresponding to each frequency band according to the frequency domain response characteristics of the reference signal of each frequency band.
  • M is , N i is Column, i is the band identified, i ⁇ (1, ..., t ), t is the number of frequency bands, M, and N i is determined according to the number of subcarriers in frequency bands i.
  • M is determined according to the multipath estimation capability.
  • the matrix decomposition module 44 is configured to perform singular value decomposition on the synthesized Toplitz matrix T M ⁇ N
  • U is an M ⁇ M matrix
  • ⁇ is an M ⁇ N matrix
  • V H is an N ⁇ N matrix
  • the eigenvalue modulus of the matrix ⁇ is greater than or equal to the preset threshold and the corresponding eigenvalues are composed of multiple column vectors in V H
  • the matrix is used as a signal space matrix, and a matrix composed of multiple column vectors in V H corresponding to the eigenvalue modulus of the matrix ⁇ whose eigenvalue modulus is less than the preset threshold is used as the noise space matrix.
  • the multipath separation module 46 is configured to perform inner product summation of multiple frequency domain response vectors with the noise space matrix and calculate the reciprocal, and then the reciprocal is greater than the predetermined
  • the time delay corresponding to each frequency domain response vector in the multiple frequency domain response vectors of the threshold is determined as the time delay of one path in the multipath.
  • FIG. 5 is a schematic structural diagram of a terminal provided by an embodiment. As shown in FIG. 5, the terminal includes a processor 51 and a memory 52; the number of processors 51 in the terminal may be one or more.
  • the processor 51 is taken as an example; the processor 51 and the memory 52 in the terminal can be connected by a bus or in other ways. In FIG. 5, the connection by a bus is taken as an example.
  • the memory 52 can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the multipath separation method in the embodiments of FIGS.
  • the processor 51 implements various functional applications and data processing of the terminal by running the software programs, instructions, and modules stored in the memory 52, that is, implements the aforementioned multipath separation method.
  • the memory 52 may mainly include a program storage area and a data storage area.
  • the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created according to the use of the terminal.
  • the memory 52 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.
  • An embodiment of the present application also provides a storage medium containing computer-executable instructions.
  • the computer-executable instructions When executed by a computer processor, they are used to perform a multipath separation method.
  • the method includes: extracting received at least two different segments Frequency domain response characteristics of the reference signal of each frequency band; According to the frequency domain response characteristics of the reference signal of each frequency band, the Toplitz matrix corresponding to each frequency band is constructed. The size of the Toplitz matrix corresponding to each frequency band is based on each frequency band.
  • the number of sub-carriers included is determined, and the number of rows of the Toplitz matrices corresponding to at least two sections of different frequency bands is the same; at least two sections of Toplitz matrices corresponding to different frequency bands are merged into a synthesized Toplitz matrix;
  • the Pritz matrix performs singular value decomposition, and determines the signal space matrix and the noise space matrix according to the decomposed matrix; constructs multiple frequency domain response vectors according to the frequency domain response characteristics of multiple local signals with different delays, and the local signal is the same as the reference signal ; Perform inner product of multiple frequency domain response vectors with the noise space matrix, compare the size of the inner product with a preset threshold, and determine the corresponding frequency domain response vector in the multiple frequency domain response vectors that meet the preset threshold
  • the delay is the delay of one path in the multipath.
  • user terminal encompasses any suitable type of wireless user equipment, such as mobile phones, portable data processing devices, portable web browsers, or vehicle-mounted mobile stations.
  • the various embodiments of the present application can be implemented in hardware or dedicated circuits, software, logic or any combination thereof.
  • some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software that may be executed by a controller, microprocessor or other computing device, although the application is not limited thereto.
  • the embodiments of the present application may be implemented by executing computer program instructions by a data processor of a mobile device, for example, in a processor entity, or by hardware, or by a combination of software and hardware.
  • Computer program instructions can be assembly instructions, Industry Subversive Alliance (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, status setting data, or written in any combination of one or more programming languages Source code or object code.
  • ISA Industry Subversive Alliance
  • the block diagram of any logical flow in the drawings of the present application may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions.
  • the computer program can be stored on the memory.
  • the memory can be of any type suitable for the local technical environment and can be implemented by any suitable data storage technology, such as but not limited to read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), optical Memory devices and systems (Digital Video Disk (DVD) or Portable Compact Disc (CD)), etc.
  • Computer-readable media may include non-transitory storage media.
  • the data processor can be of any type suitable for the local technical environment, such as but not limited to general-purpose computers, special-purpose computers, microprocessors, digital signal processors (Digital Signal Processors, DSP), application specific integrated circuits (ASICs) ), programmable logic devices (Field Programmable Gate Array, FGPA), and processors based on multi-core processor architecture.

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Abstract

本申请提出一种多径分离方法、装置和存储介质，其中，多径分离方法包括：提取接收到的至少两段不同频段的参考信号的频域响应特征，并构造与每个频段对应的托普利兹矩阵，将至少两段不同频段对应的托普利兹矩阵合并，并对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵，根据不同时延的与接收到的参考信号相同的本地信号的频域响应特征构造多个频域响应向量，将多个频域响应向量分别与噪声空间矩阵进行内积后，将内积大小与预设阈值进行比较后确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。

Description

多径分离方法、装置和存储介质
本申请要求在2019年03月07日提交中国专利局、申请号为201910172473.2的中国专利申请的优先权，该申请的全部内容通过引用结合在本申请中。
技术领域
本申请涉及无线通信网络领域，例如涉及一种多径分离方法、装置和存储介质。
背景技术
定位功能已经成为便携式终端设备的标准配置，但卫星定位技术在室内或密集城区可能由于无法搜索到足够的卫星信号无法完成定位。蜂窝网络的覆盖环境优于卫星信号，利用蜂窝网络辅助进行定位的技术已经被广泛应用。
但是由于非视距(Non-Line of Sight，NLOS)、多径等因素，也会影响采用蜂窝网络定位的准确性。因此在采用蜂窝网络进行定位时需要进行多径分离处理。多径分离处理方法采用多信号分类(Multiple Signal Classification，MUSIC)算法，MUSIC算法在理想情况下，具有很高的多径识别度，但是由于MUSIC算法存在噪声敏感问题，在噪声环境下，MUSIC算法多径识别恶化严重，导致多径无法分离。
而蜂窝网络均为正交频分复用(Orthogonal Frequency Division Multiplexing，OFDM)系统，由于OFDM系统存在零频，破坏了频域信号分布的均匀性，影响了采用MUSIC算法进行多径分离的噪声适应能力。
发明内容
本申请提供一种多径分离方法、装置和存储介质，可以提高多径分离的噪声适应能力。
本申请实施例提供一种多径分离方法，包括：
提取接收到的至少两段不同频段的参考信号的频域响应特征；
根据每个频段的参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵，每个频段对应的托普利兹矩阵的大小根据每个频段中包含的子载波数量确定，且至少两段不同频段对应的托普利兹矩阵的行数相同；
将至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩 阵；
对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵；
根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，本地信号与参考信号相同；
将多个频域响应向量分别与噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
本申请实施例提供一种多径分离装置，包括：
特征提取模块，设置为提取接收到的至少两段不同频段的参考信号的频域响应特征；
矩阵构造模块，设置为根据每个频段的参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵，每个频段对应的托普利兹矩阵的大小根据每个频段中包含的子载波数量确定，且至少两段不同频段对应的托普利兹矩阵的行数相同；
矩阵合成模块，设置为将至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵；
矩阵分解模块，设置为对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵；
向量构造模块，设置为根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，本地信号与参考信号相同；
多径分离模块，设置为将多个频域响应向量分别与噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
本申请实施例提供了一种存储介质，存储介质存储有计算机程序，计算机程序被处理器执行时实现本申请实施例中的任意一种多径分离方法。
附图说明
图1为一实施例提供的一种多径分离方法的流程图；
图2为一实施例提供的另一种多径分离方法的流程图；
图3为一实施例提供的另一种多径分离方法的流程图；
图4为一实施例提供的一种多径分离装置的结构示意图；
图5为一实施例提供的一种终端的结构示意图。
具体实施方式
下文中将结合附图对本申请的实施例进行详细说明。需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互任意组合。
传统的定位技术为卫星定位技术，利用终端中设置的卫星定位芯片接收多个定位卫星发射的信号后进行计算，从而实现定位，例如全球定位系统(Global Positioning System，GPS)、全球卫星导航系统(Global Navigation Satellite System，GLONASS)、北斗卫星定位系统等，均已广泛应用于终端设备中。但在室内或密集城区等区域，由于卫星信号的衰减较大，将影响卫星定位的精度和速度，甚至可能由于无法搜索到足够数量的卫星信号导致无法实现定位。
而随着移动通信技术的发展，蜂窝网络的覆盖已经非常完善，因此出现了通过蜂窝通信网络辅助进行定位的定位技术。但是蜂窝通信网络中的无线信号在空间区域中进行传播也会由于多种因素，导致发射端发出的无线信号可能通过多条路径到达接收端，而通过多条路径到达接收端的信号具有不同的时延，在将通过多条路径接收到的信号进行合成的情况下，通过多条路径接收到的信号会相互影响而导致信号产生失真，这就是电磁波的多径效应。为了解决多径效应，就需要对接收信号进行多径分离处理。
传统的多径分离处理可以采用一些特定的算法，例如MUSIC算法，MUSIC算法在理想情况下具有很高的多径识别度，能够识别时延间隔远小于采样周期的多径。但是由于MUSIC算法存在噪声敏感问题，在噪声环境下，MUSIC算法多径识别恶化严重，径宽度变宽，多径相互重叠，导致多径无法分离。而蜂窝通信网络，例如第四代移动通信系统(4th Generation，4G)和第五代移动通信系统(5th Generation，5G)，均为OFDM系统，由于OFDM系统存在0频，破坏了频域信号分布的均匀性，导致采用MUSIC算法进行多径分离时无法充分利用全部带宽，从而影响了采用MUSIC算法进行多径分离时的噪声适应能力。
在本申请实施例中，提供一种多径分离方法，克服OFDM系统中0频导致的频域资源分段带来的不连续问题，从而提高多径分离的噪声适应能力，提高多径分离精度。
图1为一实施例提供的一种多径分离方法的流程图，如图1所示，本实施 例提供的方法包括如下步骤。
步骤S1010，提取接收到的至少两段不同频段的参考信号的频域响应特征。
多径分离应用于无线信号的接收端，在无线信号的发射端向接收端发送了无线信号后，由于环境空间中多种因素的影响，导致无线信号可能通过多条路径到达接收端，而对于接收端而言，通过多条路径接收到的信号到达时间不同，因此可能对无线信号的合成产生影响。那么对于接收端而言，就需要对多条路径的时延进行确定，从而将环境空间中的多条路径分离开，也就是进行多径分离。
在无线通信系统中，无线信号的发射端和接收端在进行无线信号的传输时，需要发送多种参考信号，例如探测参考信号(Sounding Reference Signal，SRS)、小区参考信号(Cell Reference Signal，CRS)、解调参考信号(DemodulationReference Sgnal，DMRS)、定位参考信号(Positioning Reference Signal，PRS)等。发射端发送的多种参考信号在接收端中均存在，接收端通过对接收到的多种参考信号进行分析，从而可以得到无线信道的多种参数，以应用于数据的接收。当空间区域中存在多径时，接收端接收到的信号将包含通过多个不同路径接收到的参考信号，接收端需要通过对接收到的参考信号进行分析，实现多径分离。而对于OFDM系统，由于0频的存在，导致信号在频域上并不是连续的，因此接收端将接收到两段在频域上不连续的参考信号，且这两段参考信号是同频的。另外，无线通信系统还可能是多频的，也就是除了0频的影响以外，还可能通过多个不同的频段发送参考信号，那么接收端可能接收到两段或两段以上在频域上不连续的参考信号，且这些参考信号可能是同频的也可能是异频的。
对于无线通信系统的多径分离而言，实际上是采用频段内多个子载波信号的相关特征，对接收到的参考信号进行分析后实现多径分离，而若接收到的参考信号在频域上是不连续的，那么将影响多径分离的处理能力，因此多径分离方法应用于OFDM系统时对精度的影响很大。本申请实施例就是针对这种接收到的信号在频域上是不连续的情况做出的改进，通过将接收到的多个不同频段的参考信号进行合并处理，从而提高多径分离的处理能力，达到提高多径分离精度的目的。本申请实施例提供的多径分离方法可以应用于OFDM系统这种由于存在0频而导致接收信号在频域上不连续的无线通信系统，也可以应用于由于其他原因而导致接收信号在频域上不连续的无线通信系统，例如多频的无线通信系统。
在接收到至少两段不同频段的参考信号后，需要对接收到的至少两段不同频段的参考信号进行处理，提取接收到的至少两段不同频段的参考信号的频域响应特征。本实施例中，频域响应特征为信号随频率变化而变化的相关特征， 包括但不限于信道特征、功率特征、相关特征等。对于每个频段而言，在频域上包括多个子载波，那么对于每个频段，所提取的频域响应特征实际上包括每个频段的参考信号的多个子载波的频域响应特征。
步骤S1020，根据每个频段的参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵，每个频段对应的托普利兹矩阵的大小根据每个频段中包含的子载波数量确定，且至少两段不同频段对应的托普利兹矩阵的行数相同。
在提取到每个频段的参考信号的频域响应特征后，就需要为每个频段构造对应的托普利兹(Toeplitz)矩阵，托普利兹矩阵简称为T型矩阵，托普利兹矩阵的主对角线上的元素相等，平行于主对角线的线上的元素也相等。托普利兹矩阵中的多个元素关于次对角线对称，即托普利兹型矩阵为次对称矩阵。简单的托普利兹形矩阵包括前向位移矩阵和后向位移矩阵。
每个频段对应的托普利兹矩阵的大小根据每个频段中包含的子载波数量确定，每个频段对应的托普利兹矩阵的行数与列数的乘积约等于该频段所包含的子载波的数量。并且，至少两段不同频段所对应的托普利兹矩阵的行数相同。例如，设接收到的参考信号包括i个频段，那么每个频段对应的托普利兹矩阵为M×N i矩阵，其中M为
Figure PCTCN2020078246-appb-000001
的行，N i为
Figure PCTCN2020078246-appb-000002
的列，i为频段标识，i∈(1,…,t)，t为频段数量，M与N i根据频段i中子载波的数量确定。那么对于频段i而言，频段i对应的托普利兹矩阵
Figure PCTCN2020078246-appb-000003
例如为：
Figure PCTCN2020078246-appb-000004
本实施例中，M根据接收端的多径估计能力确定，一般而言，M小于N i。i∈(1,…,t)，t为频段数量。
步骤S1030，将至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵。
传统的多径分离方法中，采用的MUSIC算法是针对多个频段所对应的频域响应特征进行分别的处理，但由于接收信号的多个频段是分离的，那么MUSIC算法无法充分利用接收信号整个频带的频域响应特征，从而影响了多径分离的 噪声适应能力。而在本申请实施例中，在得到至少两段不同频段对应的托普利兹矩阵之后，对至少两段不同频段对应的托普利兹矩阵进行合并，将多个频段分别对应的托普利兹矩阵合并为一个合成的托普利兹矩阵，那么合成的托普利兹矩阵就代表了接收信号所有频段的频域响应特征，相当于增加了待分析信号的带宽，那么对合成的托普利兹矩阵进行分析，就能够利用更大的带宽，从而提高多径分离的噪声适应能力。
由于至少两段不同频段对应的托普利兹矩阵的行数相同，因此对至少两段不同频段对应的托普利兹矩阵进行合并的方法即为
Figure PCTCN2020078246-appb-000005
其中T M×N表示合成的托普利兹矩阵，
Figure PCTCN2020078246-appb-000006
分别表示多个频段分别对应的托普利兹矩阵。那么，合成的托普利兹矩阵T M×N可以表示为：
Figure PCTCN2020078246-appb-000007
合成的托普利兹矩阵为M×N矩阵，其中N＝N 1+N 2+...+N t。
步骤S1040，对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵。
得到的合成的托普利兹矩阵表示了接收的参考信号整个频带的频域响应特征，对合成的托普利兹矩阵进行分析就能够得到接收的参考信号的信号特征。在一实施例中，对合成的托普利兹矩阵进行分析得到接收的参考信号的信号特征的处理方法为采用奇异值分解(Singular Value Decomposition，SVD)的方法。奇异值分解可以将一个比较复杂的矩阵用更小更简单的几个子矩阵的相乘来表示，这些子矩阵描述的是矩阵的重要的特性。
奇异值分解的原理如下：假设待分解矩阵A是一个m×n的矩阵，那么定义矩阵A的SVD为：
A＝UΣV H
其中U是一个m×m的矩阵，Σ是一个m×n的矩阵，除了主对角线上的元素以外全为0，主对角线上的每个元素都称为奇异值，V是一个n×n的矩阵，V H为V的共轭矩阵。U和V都是酉矩阵，即满足U TU＝I，V TV＝I。
经过奇异值分解的矩阵U的列组成一套对M的正交输入或分析的基向量。 这些向量是MM*的特征向量。矩阵V的列组成一套对M的正交输出的基向量。这些向量是M*M的特征向量。矩阵Σ对角线上的元素是奇异值，可视为是在输入与输出间进行的标量的膨胀控制。这些是M*M及MM*的奇异值，并与矩阵U和矩阵V的列向量相对应。再根据无线信号频域特征的意义，可以按照特征值的大小，将V H分解为信号空间矩阵V1和噪声空间矩阵V0。其中，信号空间矩阵V1指矩阵Σ中特征值模值大于或等于预设门限的特征值对应的V H中的列向量组成的矩阵，噪声空间矩阵V0指矩阵Σ中特征值模值小于预设门限的特征值对应的V H中的列向量组成的矩阵。矩阵Σ中的特征值模值，根据特征值的分布情况确定。
对于本实施例中得到的合成的托普利兹矩阵T M×N进行奇异值分解，即
Figure PCTCN2020078246-appb-000008
得到的矩阵U为M×M矩阵，Σ为M×N矩阵，V H为N×N矩阵。随后将矩阵Σ中特征值模值大于或等于预设门限的特征值对应的V H中多列向量组成的矩阵作为信号空间矩阵，将矩阵Σ中特征值模值小于预设门限的特征值对应的V H中多列向量组成的矩阵作为噪声空间矩阵。
步骤S1050，根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，本地信号与参考信号相同。
在对合成的托普利兹矩阵进行分析后，得到了信号空间矩阵和噪声空间矩阵，也就是通过接收的参考信号分析出了空间区域的信号及噪声的特征。而由于无线信号接收端接收到的参考信号在接收端本地都保存有原始信号，多径分离的目的就是确定发射端发送的参考信号经过哪些空间中的路径达到了接收端，其中参考信号通过不同路径到达接收端的时间是不同的，也就是具有不同的时延。那么就可以通过为接收端中存储的原始的参考信号设置不同的时延，并利用不同时延的参考信号与噪声空间向量的正交性，判断不同时延的参考信号是否是存在的信号。
在一实施例中，首先需要根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，也就是为本地信号设置多个不同的时延，并分别获取多个时延信号的频域响应特征，最终得到每个时延信号对应的频域响应向量，其中，本地信号与接收到的参考信号相同。每个时延信号对应的频域响应向量的长度，与噪声空间的向量长度相同。在构造不同时延信号对应的频域响应向量时，时延的取值是遍历多个时延的，多个时延的间隔根据系统处理能力决定。由于接收到的参考信号是多个频段的，那么与接收到的参考信号相同的本地参 考信号也是多个频段的，在生成多个频段分别对应的频域响应向量后，同样需要将多个频段的频域响应向量合成为一个合成的频域响应向量。
例如对于本实施例，由于分解后的矩阵V H为N×N矩阵，因此需要先针对多个频段的与接收到的参考信号相同的本地信号，构造长度为N的任意时延τ的频域响应向量
Figure PCTCN2020078246-appb-000009
然后把多个频段的特征响应向量合并为一个合成的频域响应向量L τ。
Figure PCTCN2020078246-appb-000010
其中，
Figure PCTCN2020078246-appb-000011
为第i个频段第j个子载波延迟为τ的频域响应。
Figure PCTCN2020078246-appb-000012
为第i个频段的频域响应向量。每个L τ的每个频域元素的特征为e jwτ，其中w为N维，且与合成的托普利兹矩阵的第一行的逆序所对应的频域特征有线性关系。
步骤S1060，将多个频域响应向量分别与噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
随后将多个时延信号对应的频域响应向量分别与噪声空间矩阵进行相乘，再将乘积结果与预设阈值进行比较，最终确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为空间中一个径的时延，从而实现多径分离。由于噪声空间矩阵为矩阵形式，因此将频域响应向量与噪声空间矩阵相乘，实际上是将频域响应向量与噪声空间向量中的所有向量分别求内积，然后将所有内积求和，得到乘积结果。
在本申请实施例中，对多个频域响应向量分别与噪声空间矩阵进行内积并确定时延的方法，例如可以是，将多个频域响应向量分别与噪声空间矩阵进行内积求和并求倒数后，将倒数大于预设阈值的多个频域响应向量中每个频域响应向量对应的时延确定为多径中一个径的时延。
即计算
Figure PCTCN2020078246-appb-000013
然后判断p τ是否大于预设阈值b，若p τ大于预设阈值b，则认定时延为τ的径是一个实际的径，也就是时延为τ的信号为空间中存在的信号，τ为该径的相对到达时间。其中预设阈值b在计算出所有时延对应的p τ的值后确定，在计算出所有时延对应的p τ后，将p τ的最大值乘以一个系数α，得到预设阈值b，该系数α通过仿真结果确定。
本申请实施例提供的多径分离方法不限于进行定位时使用，本申请实施例 提供的多径分离方法可以应用于信号分离、信号检测、信号估计等多种领域，只要是空间区域存在多径传输，且信号是通过多个不连续的频段发送的，就可以采用本申请实施例提供的多径分离方法对信号进行多径分离处理，从而提高多径分离的精度。
本实施例提供的多径分离方法，提取接收到的至少两段不同频段的参考信号的频域响应特征，根据每个频段的参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵，然后将至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵，并对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵，再根据多个不同时延的与接收到的参考信号相同的本地信号的频域响应特征构造多个频域响应向量，将多个频域响应向量分别与噪声空间矩阵进行内积后，将内积大小与预设阈值进行比较后确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延，从而实现多径分离，由于将多个不同频段的信号对应的频域响应特征进行了合成，使得在对频域响应特征进行处理时，充分利用了接收信号的整个带宽，从而提高了多径分离处理的噪声适应能力，因此提高了多径分离的精度。
下面以对信号进行多径分离的处理为例，对本申请实施例提供的多径分离方法进行说明。
图2为一实施例提供的另一种多径分离方法的流程图，本实施例提供的多径分离方法，用于对长期演进(Long Term Evolution，LTE)系统中的定位参考信号进行多径分离。如图2所示，本实施例提供的方法包括如下步骤。
步骤S2010，提取接收到的定位参考信号的频域响应特征。
根据第三代合作伙伴计划(3rd Generation Partnership Project，3GPP)LTE定位参考信号在频域的配置，单一基站在时域的一个符号上，频域最多有200个子载波，在本实施例中，以200个子载波均使用的情况为例，当然其他子载波数目也在本申请的保护范围之内。受到0频影响，200个子载波分为左频段100个子载波和右频段100个子载波。将左频段的100个子载波和右频段的100个子载波分为两个频段，分别提取左频段和右频段的子载波的频域响应特征(包括但不限于信道特征、功率特征、相关特征等)。那么将得到左频段所属的100个子载波w对应的频域响应特征H 1(w)和右频段所属的100个子载波w对应的频域响应特征H 2(w)。
步骤S2020，根据每个频段的定位参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵。
在本步骤中，需要将H 1(w)和H 2(w)分别构造为对应的托普利兹矩阵T 1和T 2。
Figure PCTCN2020078246-appb-000014
Figure PCTCN2020078246-appb-000015
其中，N 1＝N 2，矩阵T 1和T 2具有主对角线上的元素相等，平行于主对角线上的元素也相等的特征。
步骤S2030，将多个频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵。
也就是将矩阵T 1和T 2合并为M×N的矩阵T，T＝[T 2 T 1]，N＝2N 1＝2N 2。
步骤S2040，对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵。
即对合成的托普利兹矩阵T M×N进行奇异值分解，即
Figure PCTCN2020078246-appb-000016
得到的矩阵U为M×M矩阵，Σ为M×N矩阵，V H为N×N矩阵。随后将矩阵Σ中特征值模值大于或等于预设门限的特征值对应的V H中多列向量组成的矩阵作为信号空间矩阵，将矩阵Σ中特征值模值小于预设门限的特征值对应的V H中多列向量组成的矩阵作为噪声空间矩阵。
步骤S2050，根据多个不同时延的本地定位参考信号的频域响应特征构造多个频域响应向量。
在此，需要构造K个向量长度为N的不同时延τ k的本地定位参考信号的频域响应向量L k(w)，其中每个L k(w)k∈{1,2,...，K}的向量长度为N。
每个L k(w)的每个频域元素的特征为
Figure PCTCN2020078246-appb-000017
其中w为N维，且与合成的托普利兹矩阵T M×N的第一行的逆序所对应的频域特征有线性关系。即W n1＝C 1·[w1 1 w1 2…w1 N1]+b 1 n1∈{1,2,…N1}，其中w1为H 1(w)对应的前N1个频域子载波位置。W n2＝C 2·[w2 1 w2 2…w2 N1]+b 2 n2∈{N1+1,N1+2,…N}，其中w2为H 2(w)对应的前N1个频域子载波位置。
步骤S2060，将多个频域响应向量分别与噪声空间矩阵进行内积后，将内积大小与预设阈值进行比较后，确定满足预设阈值的多个频域响应向量中每个频 域响应向量对应的时延为多径中一个径的时延。
将L k(w)与V0的所有向量求内积，并将所求内积求和，再对和求倒数，
Figure PCTCN2020078246-appb-000018
根据设定的P k的阈值，大于阈值P k的L k所对应的τ k为一个空间中存在的径的时延。其中阈值P k在计算出所有时延对应的P k的值后确定，在计算出所有时延对应的P k后，将P k的最大值乘以一个系数α，得到阈值，该系数α通过仿真结果确定。
图3为一实施例提供的另一种多径分离方法的流程图，本实施例提供的多径分离方法，用于对5G中的新无线电(New Radio，NR)参考信号进行多径分离。如图3所示，本实施例提供的方法包括如下步骤。
步骤S3010，提取接收到的NR参考信号的频域响应特征。
根据3GPP定义的信号带宽，NR参考信号受到0频影响，分为左频段和右频段，左频段和右频段分别包括多个子载波。将左频段和右频段分为两个频段，分别提取两个频段的子载波的频域响应特征(包括但不限于信道特征、功率特征、相关特征等)。那么将得到左频段所属子载波w对应的频域响应特征H 1(w)和右频段所属子载波w对应的频域响应特征H 2(w)。
步骤S3020，根据每个频段的NR参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵。
在本步骤中，需要将H 1(w)和H 2(w)分别构造为对应的托普利兹矩阵T 1和T 2。
Figure PCTCN2020078246-appb-000019
Figure PCTCN2020078246-appb-000020
矩阵T 1和T 2具有主对角线上的元素相等，平行于主对角线上的元素也相等的特征。
步骤S3030，将多个频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵。
也就是将矩阵T 1和T 2合并为M×N的矩阵T，T＝[T 2 T 1]，N＝N 1+N 2。
步骤S3040，对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵。
即对合成的托普利兹矩阵T M×N进行奇异值分解，即
Figure PCTCN2020078246-appb-000021
得到的矩阵U为M×M矩阵，Σ为M×N矩阵，V H为N×N矩阵。随后将矩阵Σ中特征值模值大于或等于预设门限的特征值对应的V H中多列向量组成的矩阵作为信号空间矩阵，将矩阵Σ中特征值模值小于预设门限的特征值对应的V H中多列向量组成的矩阵作为噪声空间矩阵。
步骤S3050，根据多个不同时延的NR参考信号的频域响应特征构造多个频域响应向量。
在此，需要构造K个向量长度为N的不同时延τ k的NR参考信号的频域响应向量L k(w)，其中每个L k(w)k∈{1,2,...，K}的向量长度为N。
每个L k(w)的每个频域元素的特征为
Figure PCTCN2020078246-appb-000022
其中w为N维，且与合成的托普利兹矩阵T M×N的第一行的逆序所对应的频域特征有线性关系。即W n1＝C 1·[w1 1 w1 2…w1 N1]+b 1 n1∈{1,2,…N1}，其中w1为H 1(w)对应的前N1个频域子载波位置。W n2＝C 2·[w2 1 w2 2…w2 N1]+b 2 n2∈{N1+1,N1+2,…N}，其中w2为H 2(w)对应的前N1个频域子载波位置。
步骤S3060，将多个频域响应向量分别与噪声空间矩阵进行内积后，将内积大小与预设阈值进行比较后确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
将L k(w)与V0的所有向量求内积，并将所求内积求和，再对和求倒数，
Figure PCTCN2020078246-appb-000023
根据设定的P k的阈值，大于阈值P k的L k所对应的τ k为一个空间中存在的径的时延。其中阈值P k在计算出所有时延对应的P k的值后确定，在计算出所有时延对应的P k后，将P k的最大值乘以一个系数α，得到阈值，该系数α通过仿真结果确定。
图4为一实施例提供的一种多径分离装置的结构示意图，如图4所示，本实施例提供的多径分离装置包括：特征提取模块41，设置为提取接收到的至少 两段不同频段的参考信号的频域响应特征；矩阵构造模块42，设置为根据每个频段的参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵，每个频段对应的托普利兹矩阵的大小根据每个频段中包含的子载波数量确定，且至少两段不同频段对应的托普利兹矩阵的行数相同；矩阵合成模块43，设置为将至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵；矩阵分解模块44，设置为对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵；向量构造模块45，设置为根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，本地信号与参考信号相同；多径分离模块46，设置为将多个频域响应向量分别与噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
本实施例提供的多径分离装置用于实现图1所示实施例的多径分离方法，本实施例提供的多径分离装置实现原理和技术效果类似，此处不再赘述。
在一实施例中，在图4所示实施例中，矩阵构造模块42，是设置为根据每个频段的参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵
Figure PCTCN2020078246-appb-000024
其中M为
Figure PCTCN2020078246-appb-000025
的行，N i为
Figure PCTCN2020078246-appb-000026
的列，i为频段标识，i∈(1,…,t)，t为频段数量，M与N i根据频段i中子载波的数量确定。
在一实施例中，在图4所示实施例中，M根据多径估计能力确定。
在一实施例中，在图4所示实施例中，矩阵合成模块43，是设置为将至少两段不同频段对应的托普利兹矩阵
Figure PCTCN2020078246-appb-000027
合并为一个合成的托普利兹矩阵T M×N，
Figure PCTCN2020078246-appb-000028
N＝N 1+N 2+...+N t
在一实施例中，在图4所示实施例中，矩阵分解模块44，是设置为对合成的托普利兹矩阵T M×N进行奇异值分解
Figure PCTCN2020078246-appb-000029
其中U为M×M矩阵，Σ为M×N矩阵，V H为N×N矩阵；将矩阵Σ中特征值模值大于或等于预设门限的特征值对应的V H中多列向量组成的矩阵作为信号空间矩阵，将矩阵Σ中特征值模值小于预设门限的特征值对应的V H中多列向量组成的矩阵作为噪声空间矩阵。
在一实施例中，在图4所示实施例中，多径分离模块46，是设置为将多个频域响应向量分别与噪声空间矩阵进行内积求和并求倒数后，将倒数大于预设阈值的多个频域响应向量中每个频域响应向量对应的时延确定为多径中一个径的时延。
图5为一实施例提供的一种终端的结构示意图，如图5所示，该终端包括 处理器51和存储器52；终端中处理器51的数量可以是一个或多个，图5中以一个处理器51为例；终端中的处理器51和存储器52；可以通过总线或其他方式连接，图5中以通过总线连接为例。
存储器52作为一种计算机可读存储介质，可用于存储软件程序、计算机可执行程序以及模块，如本申请图1-图3实施例中的多径分离方法对应的程序指令/模块(例如，多径分离装置中的特征提取模块41、矩阵构造模块42、矩阵合成模块43、矩阵分解模块44、向量构造模块45、多径分离模块46)。处理器51通过运行存储在存储器52中的软件程序、指令以及模块，从而实现终端的各种功能应用以及数据处理，即实现上述的多径分离方法。
存储器52可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序；存储数据区可存储根据终端的使用所创建的数据等。此外，存储器52可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。
本申请实施例还提供一种包含计算机可执行指令的存储介质，计算机可执行指令在由计算机处理器执行时用于执行一种多径分离方法，该方法包括：提取接收到的至少两段不同频段的参考信号的频域响应特征；根据每个频段的参考信号的频域响应特征构造与每个频段对应的托普利兹矩阵，每个频段对应的托普利兹矩阵的大小根据每个频段中包含的子载波数量确定，且至少两段不同频段对应的托普利兹矩阵的行数相同；将至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵；对合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵；根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，本地信号与参考信号相同；将多个频域响应向量分别与噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
以上所述，仅为本申请的示例性实施例而已，并非用于限定本申请的保护范围。
本领域内的技术人员应明白，术语用户终端涵盖任何适合类型的无线用户设备，例如移动电话、便携数据处理装置、便携网络浏览器或车载移动台。
一般来说，本申请的多种实施例可以在硬件或专用电路、软件、逻辑或其任何组合中实现。例如，一些方面可以被实现在硬件中，而其它方面可以被实现在可以被控制器、微处理器或其它计算装置执行的固件或软件中，尽管本申请不限于此。
本申请的实施例可以通过移动装置的数据处理器执行计算机程序指令来实现，例如在处理器实体中，或者通过硬件，或者通过软件和硬件的组合。计算机程序指令可以是汇编指令、指令集架构(Industry Subversive Alliance，ISA)指令、机器指令、机器相关指令、微代码、固件指令、状态设置数据、或者以一种或多种编程语言的任意组合编写的源代码或目标代码。
本申请附图中的任何逻辑流程的框图可以表示程序步骤，或者可以表示相互连接的逻辑电路、模块和功能，或者可以表示程序步骤与逻辑电路、模块和功能的组合。计算机程序可以存储在存储器上。存储器可以具有任何适合于本地技术环境的类型并且可以使用任何适合的数据存储技术实现，例如但不限于只读存储器(Read-Only Memory，ROM)、随机访问存储器(Random Access Memory，RAM)、光存储器装置和系统(数码多功能光碟(Digital Video Disk，DVD)或便携式紧凑磁盘(Compact Disc，CD)光盘)等。计算机可读介质可以包括非瞬时性存储介质。数据处理器可以是任何适合于本地技术环境的类型，例如但不限于通用计算机、专用计算机、微处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、可编程逻辑器件(Field Programmable Gate Array，FGPA)以及基于多核处理器架构的处理器。

Claims (13)

  1. 一种多径分离方法，包括：
    提取接收到的至少两段不同频段的参考信号的频域响应特征；
    根据每个频段的参考信号的频域响应特征构造与所述每个频段对应的托普利兹矩阵，每个频段对应的托普利兹矩阵的大小根据所述每个频段中包含的子载波数量确定，且所述至少两段不同频段对应的托普利兹矩阵的行数相同；
    将所述至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵；
    对所述合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵；
    根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，所述本地信号与所述参考信号相同；
    将所述多个频域响应向量分别与所述噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足所述预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
  2. 根据权利要求1所述的方法，其中，所述根据每个频段的参考信号的频域响应特征构造与所述每个频段对应的托普利兹矩阵，包括：
    根据每个频段的参考信号的频域响应特征构造与所述每个频段对应的托普利兹矩阵
    Figure PCTCN2020078246-appb-100001
    其中M为所述
    Figure PCTCN2020078246-appb-100002
    的行，N i为所述
    Figure PCTCN2020078246-appb-100003
    的列，i为频段标识，所述i∈(1,…,t)，t为频段数量，所述M与所述N i根据频段i中子载波的数量确定。
  3. 根据权利要求2所述的方法，其中，所述M根据多径估计能力确定。
  4. 根据权利要求2或3所述的方法，其中，所述将所述至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵，包括：
    将所述至少两段不同频段对应的托普利兹矩阵
    Figure PCTCN2020078246-appb-100004
    合并为一个合成的托普利兹矩阵T M×N，
    Figure PCTCN2020078246-appb-100005
    N＝N 1+N 2+...+N t。
  5. 根据权利要求4所述的方法，其中，所述对所述合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵，包括：
    对所述合成的托普利兹矩阵T M×N通过
    Figure PCTCN2020078246-appb-100006
    进行奇异值分解，其中U为M×M的矩阵，Σ为M×N的矩阵，V H为N×N的矩阵；
    将矩阵Σ中特征值模值大于或等于预设门限的特征值对应的V H中多列向量组成的矩阵作为所述信号空间矩阵，将矩阵Σ中特征值模值小于所述预设门限 的特征值对应的V H中多列向量组成的矩阵作为所述噪声空间矩阵。
  6. 根据权利要求4所述的方法，其中，所述将所述多个频域响应向量分别与所述噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足所述预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延，包括：
    将所述多个频域响应向量分别与所述噪声空间矩阵进行内积求和并求倒数后，将倒数大于所述预设阈值的多个频域响应向量中每个频域响应向量对应的时延确定为多径中一个径的时延。
  7. 一种多径分离装置，包括：
    特征提取模块，设置为提取接收到的至少两段不同频段的参考信号的频域响应特征；
    矩阵构造模块，设置为根据每个频段的参考信号的频域响应特征构造与所述每个频段对应的托普利兹矩阵，每个频段对应的托普利兹矩阵的大小根据所述每个频段中包含的子载波数量确定，且所述至少两段不同频段对应的托普利兹矩阵的行数相同；
    矩阵合成模块，设置为将所述至少两段不同频段对应的托普利兹矩阵合并为一个合成的托普利兹矩阵；
    矩阵分解模块，设置为对所述合成的托普利兹矩阵进行奇异值分解，根据分解后的矩阵确定信号空间矩阵和噪声空间矩阵；
    向量构造模块，设置为根据多个不同时延的本地信号的频域响应特征构造多个频域响应向量，所述本地信号与所述参考信号相同；
    多径分离模块，设置为将所述多个频域响应向量分别与所述噪声空间矩阵进行内积，将内积大小与预设阈值进行比较后，确定满足所述预设阈值的多个频域响应向量中每个频域响应向量对应的时延为多径中一个径的时延。
  8. 根据权利要求7所述的装置，其中，所述矩阵构造模块，是设置为根据每个频段的参考信号的频域响应特征构造与所述每个频段对应的托普利兹矩阵
    Figure PCTCN2020078246-appb-100007
    其中M为所述
    Figure PCTCN2020078246-appb-100008
    的行，N i为所述
    Figure PCTCN2020078246-appb-100009
    的列，i为频段标识，所述i∈(1,…,t)，t为频段数量，所述M与所述N i根据频段i中子载波的数量确定。
  9. 根据权利要求8所述的装置，其中，所述M根据多径估计能力确定。
  10. 根据权利要求8或9所述的装置，其中，所述矩阵合成模块，是设置为将所述至少两段不同频段对应的托普利兹矩阵
    Figure PCTCN2020078246-appb-100010
    合并为一个合成的托普利兹矩阵T M×N，
    Figure PCTCN2020078246-appb-100011
    N＝N 1+N 2+...+N t。
  11. 根据权利要求10所述的装置，其中，所述矩阵分解模块，是设置为对所述合成的托普利兹矩阵T M×N通过
    Figure PCTCN2020078246-appb-100012
    进行奇异值分解，其中U为M×M的矩阵，Σ为M×N的矩阵，V H为N×N的矩阵；将矩阵Σ中特征值模值大于或等于预设门限的特征值对应的V H中多列向量组成的矩阵作为所述信号空间矩阵，将矩阵Σ中特征值模值小于所述预设门限的特征值对应的V H中多列向量组成的矩阵作为所述噪声空间矩阵。
  12. 根据权利要求10所述的装置，其中，所述多径分离模块，是设置为将所述多个频域响应向量分别与所述噪声空间矩阵进行内积求和并求倒数后，将倒数大于所述预设阈值的多个频域响应向量中每个频域响应向量对应的时延确定为多径中一个径的时延。
  13. 一种存储介质，所述存储介质存储有计算机程序，所述计算机程序被处理器执行时实现权利要求1-6中任一项所述的多径分离方法。
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