CN115242282A - DMRS signal-based 5G NR DOA estimation method and estimation system - Google Patents
DMRS signal-based 5G NR DOA estimation method and estimation system Download PDFInfo
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Abstract
The invention discloses a DMRS signal-based 5G NR DOA estimation method, which comprises the following steps: receiving an uplink signal by adopting an MIMO technology, and carrying out synchronous processing on the uplink signal according to a 5G standard communication protocol to obtain a synchronous frame header position, wherein the synchronous frame header position comprises synchronous information; acquiring an uplink DMRS reference signal according to the synchronization information and the DMRS signal resource information configured by the upper layer; and according to the uplink DMRS reference signal, calculating the DOA by adopting a forward and backward space smoothing algorithm. The anti-coherence characteristic in single information source DOA estimation is improved, the estimation error is reduced, and the detection result is more accurate.
Description
Technical Field
The invention belongs to the technical field of 5G mobile communication and signal processing, and particularly relates to a DMRS (demodulation reference signal) -based 5G NR DOA estimation method and an estimation system.
Background
The multiple signal classification (MUSIC) algorithm divides a received signal into a signal subspace and a noise subspace, constructs a spatial spectrum by utilizing the orthogonality of the two subspaces, and obtains an arrival angle (DOA) estimation result by searching a spatial spectrum peak value. The forward and backward space smoothing MUSIC algorithm is an improved algorithm of the classic MUSIC algorithm, the anti-coherence characteristic is realized by reducing the dimensionality of a signal matrix and reducing the correlation coefficient of the signal, the matrix dimensionality reduction is advanced, and then the spectral peak search is carried out to estimate the arrival angle.
In a 5G NR (5G new air interface) scene, a target is always a single information source based on 5G NR DOA estimation of a DMRS signal, because a user uplink signal has multipath interference and is used as third-party receiving equipment, the signal-to-noise ratio of the acquired target signal is low, MIMO receiving is adopted, the small signal receiving performance is enhanced, and meanwhile, an improved forward-backward spatial smoothing MUSIC algorithm is adopted, so that the anti-coherence characteristic can be improved in the single information source DOA estimation. In 5G NR, the target user characteristic signal is difficult to obtain, and at the same time, there are multipath interference and signal interference from other users in the user uplink signal, which makes estimation based on the direction of arrival (DOA) of the user uplink characteristic signal difficult in 5G NR.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a DMRS signal-based 5G NR DOA estimation method and an estimation system, and aims to solve the problem that the conventional MUSIC algorithm in the prior art is difficult to estimate the direction of arrival (DOA) based on the user uplink characteristic signal in the 5G NR.
The invention is realized by adopting the following technical scheme:
a method for estimating 5G NR DOA based on DMRS signals comprises the following steps:
receiving an uplink signal by adopting an MIMO technology, and carrying out synchronous processing on the uplink signal according to a 5G standard communication protocol to obtain a synchronous frame header position, wherein the synchronous frame header position comprises synchronous information and parameter information;
acquiring an uplink DMRS reference signal according to the synchronization information and the DMRS signal resource information configured by the upper layer;
and according to the uplink reference signal DMRS, calculating the DOA by adopting a forward and backward spatial smoothing algorithm.
In order to optimize the technical scheme, the specific measures adopted further comprise:
further, according to the synchronization information and DMRS signal resource information configured in the upper layer, acquiring an uplink DMRS reference signal, specifically:
acquiring a synchronous position according to the synchronous information;
acquiring the position of the DMRS signal resource according to the DMRS signal resource information configured by the upper layer;
and acquiring the uplink DMRS signal according to the synchronization position and the DMRS signal resource position.
Further, according to the uplink reference signal DMRS, a forward and backward spatial smoothing algorithm is used to measure and calculate the direction of arrival DOA, specifically:
establishing a forward and backward space smoothing algorithm;
the direction of arrival DOA is estimated according to a forward and backward spatial smoothing algorithm.
Further, establishing the forward and backward spatial smoothing algorithm specifically comprises:
a forward spatial smoothing matrix is established and,
R x (i) ＝F i R x (F i ) H
x i ＝F i x
F i ＝[0 P×(i-1) I P 0 P×(L-i) ],i＝1,2,L,L
x i ＝[x i (t),x i+1 (t),L x P+i-1 (t)] T ,i＝1,2,L,L
L＝N-P+1
wherein: l denotes the number of mutually overlapping sub-arrays divided by N array elements, x i Representing the uplink signal received by the ith sub-array, x representing the uplink signals received by all sub-arrays, F i Denotes x i P denotes the number of elements of a single sub-array,
covariance matrix, R, representing the ith sub-array x,fss Representing a forward spatial smoothing matrix;
a backward spatial smoothing matrix is established and,
R x,b L-i+1 ＝G i R x * [G i ] H
G i ＝[0 P×(i-1) J P 0 P×(L-1) ],i＝1,2,L,L
x b i ＝[x N-i+1 (t),x N-i (t),L x N-i-P+2 (t)] T ,i＝1,2,L,L
wherein: r x,bss Representing a backward spatial smoothing matrix, R x,b L-i+1 Covariance matrix-to-space smoothing matrix, x, representing data received by backward smoothing L-i +1 th array element b Representing the upstream signals received in reverse by all sub-arrays,
indicating the upstream signal received by the reverse ith sub-array,
represents R x A conjugate matrix of (a);
establishing a forward and backward space smoothing matrix to obtain a forward and backward space smoothing algorithm,
wherein: r x，fbss Representing a forward and backward spatial smoothing matrix.
Further, estimating the direction of arrival DOA according to the forward and backward spatial smoothing algorithm, specifically:
the eigenvalue decomposition is carried out on the forward and backward space smoothing matrix,
R x，fbxx ＝U·Λ·U H
wherein: Λ represents a diagonal matrix;
estimating the number of the information sources by using the minimum eigenvalue repetition number G,
μ 1 ≥μ 2 ≥L≥μ N
M＝N-G
A＝M
wherein: mu.s N Representing the Nth eigenvalue arranged from large to small in the diagonal matrix, wherein M represents the number of eigenvalues of which the eigenvalues are larger than a set threshold value, and G represents the number of eigenvalues of which the eigenvalues are smaller than the set threshold value; a represents the estimated number of sources;
dividing the matrix U after the characteristic value decomposition into signal subspaces U according to the estimated information source quantity A s Sum noise subspace U W Signal subspace U s Composed of M eigenvectors corresponding to larger eigenvalues, noise subspace U W The characteristic vectors corresponding to G smaller characteristic values form the characteristic vector;
calculating the MUSIC spatial spectrum, searching the common peak value, calculating the incident angle, estimating the DOA according to the incident angle,
wherein: p (theta) represents an incident angle, a (theta) represents an incident direction matrix, a H (theta) represents a transformation matrix of the incident direction matrix,
representing a noise subspace U W The transformation matrix of (2).
A system for 5G NR DOA estimation based on DMRS signals, comprising,
the acquisition module acquires the uplink signal of the target user, performs synchronous processing and acquires synchronous information;
the analysis module is used for acquiring a target user uplink DMRS reference signal according to the synchronization information and the DMRS signal resource information configured by the upper layer;
the modeling module is used for establishing a forward and backward space smoothing algorithm model;
and the calculation module is used for estimating DOA according to the forward and backward space smoothing algorithm model.
The invention has the beneficial effects that:
compared with the prior art, the DMRS signal-based 5G NR DOA estimation method adopts the MIMO technology to receive the uplink signal of the target user and carry out synchronous processing, reduces the multipath interference existing in signal transmission, and enhances the receiving performance of small signals; the DOA of the target user is estimated by adopting a forward and backward space smoothing algorithm, and compared with the traditional MUSIC algorithm, the improved forward and backward space smoothing algorithm reduces the appearance of a plurality of spectral peaks, improves the anti-coherence characteristic in single information source DOA estimation, reduces the estimation error and has more accurate detection result.
Drawings
Fig. 1 is a flowchart of a method for estimating 5G NR DOA based on DMRS signals according to a first embodiment of the present invention.
Fig. 2 (a) is a graph of the comparison result of the DOA estimation error rate of the classical MUSIC algorithm and the forward and backward spatial smoothing algorithm in MATLAB simulation according to the first embodiment of the present invention.
Fig. 2 (b) is a comparison result graph of the DOA estimation mean square error in MATLAB simulation of the classical MUSIC algorithm and the forward and backward spatial smoothing algorithm provided by the first embodiment of the present invention.
Fig. 3 is a graph comparing the coherence characteristics of the classical MUSIC algorithm and the forward and backward spatial smoothing algorithm provided by the first embodiment of the present invention.
Fig. 4 (a) is a comparison graph of DOA estimation error rates in practical tests of the classical MUSIC algorithm and the forward and backward spatial smoothing algorithm provided by the first embodiment of the present invention.
Fig. 4 (b) is a diagram of comparing the mean square error of DOA estimation in practical tests by the classical MUSIC algorithm and the forward and backward spatial smoothing algorithm provided in the first embodiment of the present invention.
Fig. 5 is a block diagram of a module according to a second embodiment of the present invention.
Fig. 6 is a schematic structural diagram of a network-side server according to a third embodiment of the present invention.
Detailed Description
In order to clarify the technical solution and the working principle of the present invention, the present invention is further described in detail with reference to the following embodiments in conjunction with the accompanying drawings, it should be noted that, in the premise of not conflicting, any combination between the embodiments described below or between the technical features may form a new embodiment.
First embodiment
The invention provides a method for estimating 5G NR DOA based on DMRS signals, which comprises the following steps:
step S1: and receiving the uplink signal by adopting an MIMO technology, and carrying out synchronous processing on the uplink signal according to a 5G standard communication protocol to obtain a synchronous frame header position, wherein the synchronous frame header position comprises synchronous information.
Step S2: and acquiring an uplink DMRS reference signal according to the synchronization information and the DMRS signal resource information configured by the upper layer.
Acquiring a synchronous position according to the synchronous information;
acquiring the position of the DMRS signal resource according to the DMRS signal resource information configured by the upper layer;
and acquiring the uplink DMRS signal according to the synchronization position and the DMRS signal resource position.
And step S3: and according to the uplink DMRS reference signal, calculating the DOA by adopting a forward and backward spatial smoothing algorithm.
S31: establishing a forward and backward space smoothing algorithm;
s311: a forward spatial smoothing matrix is established and,
R x (i) ＝F i R x (F i ) H
x i ＝F i x
F i ＝[0 P×(i-1) I P 0 P×(L-i) ],i＝1,2,L,L
x i ＝[x i (t),x i+1 (t),L x P+i-1 (t)] T ,i＝1,2,L,L
L＝N-P+ 1
wherein: l denotes the number of mutually overlapping sub-arrays divided by N array elements, x i Representing the uplink signal received by the ith sub-array, x representing the uplink signals received by all sub-arrays, F i Denotes x i P denotes the number of elements of each sub-array,
covariance matrix, R, representing the ith sub-array x,fss Representing a forward spatial smoothing matrix.
S512: a backward spatial smoothing matrix is established and,
R x,b L-i+1 ＝G i R x * [G i ] H
G i ＝[0 P×(i-1) J P 0 P×(L-1) ],i＝1,2,L,L
x b i ＝[x N-i+1 (t),x N-i (t),L x N-i-P+2 (t)] T ,i＝1,2,L,L
wherein: r x,bss Representing a backward spatial smoothing matrix, R x,b L-i+1 Covariance matrix-to-space smoothing matrix, x, representing data received by backward smoothing L-i +1 th array element b Representing the upstream signals received in reverse by all sub-arrays,
indicating the upstream signal received by the reverse ith sub-array,
represents R x A conjugate matrix of (a);
s513: establishing a forward and backward space smoothing calculation matrix to obtain a forward and backward space smoothing algorithm,
wherein: r x，fbss Representing a forward and backward spatial smoothing matrix.
S52: and estimating the DOA according to a forward and backward space smoothing algorithm model.
S521: the eigenvalue decomposition is carried out on the forward and backward space smoothing calculation matrix,
R x，fbxx ＝U·Λ·U H
wherein: Λ represents a diagonal matrix;
s522: estimating the number of the information sources by using the minimum eigenvalue multiplicity G,
μ 1 ≥μ 2 ≥L≥μ N
M＝N-G
A＝M
wherein: mu.s N Representing the Nth eigenvalue arranged from large to small in the diagonal matrix, wherein M represents the number of eigenvalues of which the eigenvalues are larger than a set threshold value, and G represents the number of eigenvalues of which the eigenvalues are smaller than the set threshold value; a represents the estimated number of sources;
s523: dividing the matrix U after the characteristic value decomposition into signal subspaces U according to the estimated information source quantity A s Sum noise subspace U W Signal subspace U s Corresponding to M larger eigenvaluesFeature vector composition, noise subspace U W The characteristic vectors corresponding to G smaller characteristic values are formed;
s524: calculating the MUSIC space spectrum, searching the common peak value, calculating the incident angle, estimating the DOA according to the incident angle,
wherein: p (theta) represents an incident angle, a (theta) represents an incident direction matrix, a H (theta) represents a transformation matrix of the incident direction matrix,
representing a noise subspace U W The transformation matrix of (2).
Adopting MATLAB simulation to verify a forward and backward space smoothing algorithm:
and a single information source is adopted to transmit uplink signals, and multiple antennas are adopted to receive the uplink signals.
The source incidence angle is set to be-30 degrees, the signal-to-noise ratios are changed to be 0dB, 10dB and 20dB respectively, the position of the peak value of the spatial spectrum is searched to be the DOA value estimation result, the result shows that both algorithms can realize DOA estimation, the precision of the classic MUSIC algorithm is lost along with reduction of the signal-to-noise ratio, and the forward and backward spatial smoothing algorithm established by the scheme has higher precision, sharper spatial spectrum and better resolution than the classic MUSIC algorithm.
As shown in fig. 2, in an MATLAB simulation environment, an information source incidence angle is set to be-30 degrees, a signal-to-noise ratio is changed, an error rate and an estimated Mean Square Error (MSE) of a forward and backward spatial smoothing algorithm established by the classical MUSIC algorithm and the scheme are analyzed, and if an angle misjudgment is considered to occur when a difference between an estimated angle and an actual angle exceeds 15 degrees, a DOA estimation error rate is higher in the classical MUSIC algorithm at a low signal-to-noise ratio, and as the signal-to-noise ratio is reduced, the DOA estimation error is increased, and performance is greatly influenced; the forward and backward spatial smoothing algorithm can not generate angle estimation misjudgment, and has better estimation precision when the signal-to-noise ratio is lower.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
In actual test, 5G target terminal mobile phones are used for sending 5G signals, and a radio platform (SDR) is used for data acquisition and analysis.
In actual test, in non-line-of-sight transmission, under the environment of multipath interference, an included angle between a fixed target terminal and receiving equipment is set to be-30 degrees, and the algorithm function and the anti-coherence characteristic are tested under the condition that the receiving signal-to-noise ratio is 10 dB.
As shown in fig. 3, wherein 1 represents a classical MUSIC algorithm, and 2 represents a forward and backward spatial smoothing algorithm, when multipath interference exists, the classical MUSIC algorithm has a plurality of spectral peaks, the highest peak is the main meridian DOA estimation result, and the estimation deviation is large; the forward and backward space smoothing algorithm only has a single sharp spectral peak value, has obvious anti-coherence characteristics, and has smaller DOA estimation deviation and better performance.
In actual tests, during line-of-sight transmission, an included angle between a fixed 5G target terminal and receiving equipment is set to be-30 degrees, the distance between the target terminal and the receiving equipment is changed, DOA estimation Mean Square Error (MSE) of two algorithms is compared under different signal-to-noise ratios, meanwhile, the corresponding angle estimation error rate is counted, and the actual measurement performance of the algorithms is verified.
As shown in fig. 4, in a 5G NR scenario, both algorithms have an angle estimation error, and due to multipath interference and other user signal interference in practical application, the error rate and estimation error increase, and when the signal-to-noise ratio is low, the influence is larger, but the forward and backward spatial smoothing algorithm has a lower error rate and estimation error, and the actual measurement performance is obviously better than that of the classical MUSIC algorithm.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are within the scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
The second embodiment:
as shown in fig. 5, a second embodiment of the present invention provides a DMRS signal-based 5G NR DOA measurement system, including,
the acquisition module 201 acquires an uplink signal of a target user, performs synchronization processing, and acquires synchronization information;
the analysis module 202 is used for acquiring a target user uplink DMRS reference signal according to the synchronization information and the DMRS signal resource information configured by the upper layer;
the modeling module 203 is used for establishing a forward and backward space smoothing algorithm model;
the calculation module 204 estimates the DOA according to the forward and backward spatial smoothing algorithm model.
It should be understood that this embodiment is a system example corresponding to the first embodiment, and may be implemented in cooperation with the first embodiment. The related technical details mentioned in the first embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the first embodiment.
It should be noted that each module referred to in this embodiment is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, elements that are not so closely related to solving the technical problems proposed by the present invention are not introduced in the present embodiment, but this does not indicate that other elements are not present in the present embodiment.
The third embodiment:
as shown in fig. 6, a third embodiment of the present invention provides a network side server, including: at least one processor 301; and a memory 302 communicatively coupled to the at least one processor; wherein the memory 302 stores instructions executable by the at least one processor 301, the instructions being executable by the at least one processor 301 to enable the at least one processor 301 to perform one of the above-described 5G-oriented MIMO positioning and direction-finding methods.
The memory 301 and the processor 301 are coupled by a bus, which may comprise any number of interconnected buses and bridges that couple one or more of the various circuits of the processor 301 and the memory 301. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, etc., which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 301 is transmitted over a wireless medium through an antenna, which further receives the data and transmits the data to the processor 301.
The processor 301 is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. While memory 301 may be used to store data used by processor 301 in performing operations.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (6)
1. A method for estimating 5G NR DOA based on DMRS signals is characterized by comprising the following steps:
receiving an uplink signal by adopting an MIMO technology, and carrying out synchronous processing on the uplink signal according to a 5G standard communication protocol to obtain a synchronous frame header position, wherein the synchronous frame header position comprises synchronous information;
acquiring an uplink DMRS reference signal according to the synchronization information and the DMRS signal resource information configured by the upper layer;
and according to the uplink DMRS reference signal, calculating the DOA by adopting a forward and backward spatial smoothing algorithm.
2. The method for estimating 5G NR DOA based on DMRS according to claim 1, wherein the method for acquiring the uplink DMRS reference signal according to the synchronization information and the DMRS resource information configured by the upper layer comprises:
acquiring a synchronous position according to the synchronous information;
acquiring the position of the DMRS signal resource according to the DMRS signal resource information configured by the upper layer;
and acquiring the uplink DMRS signal according to the synchronization position and the DMRS signal resource position.
3. The method for estimating 5G NR DOA based on the DMRS signal according to claim 2, wherein the method for estimating the DOA is characterized in that a forward and backward spatial smoothing algorithm is used to measure and calculate the DOA according to the DMRS signal, and specifically comprises:
establishing a forward and backward space smoothing algorithm;
the direction of arrival DOA is estimated according to a forward and backward spatial smoothing algorithm.
4. The method for estimating 5G NR DOA based on a DMRS signal according to claim 3, wherein the forward and backward spatial smoothing algorithm is established specifically as follows:
a forward spatial smoothing matrix is established and,
R x (i) ＝F i R x (F i ) H
x i ＝F i x
F i ＝[0 P×(i-1) I P 0 P×(L-i) ],i＝1,2,L,L
x i ＝[x i (t),x i+1 (t),L x P+i-1 (t)] T ,i＝1,2,L,L
L＝N-P+1
wherein: l denotes the number of mutually overlapping sub-arrays divided by N array elements, x i Representing the uplink signal received by the ith sub-array, x representing the uplink signal received by all sub-arrays in the forward direction, F i Denotes x i P denotes the number of elements of a single sub-array,
covariance matrix, R, representing the ith sub-array x,fss Representing a forward spatial smoothing matrix;
a backward spatial smoothing matrix is established and,
R x,b L-i+1 ＝G i R x * [G i ] H
G i ＝[0 P×(i-1) J P 0 P×(L-1) ],i＝1,2,L,L
x b i ＝[x N-i+1 (t),x N-i (t),L x N-i-P+2 (t)] T ,i＝1,2,L,L
wherein: r x,bss Representing a backward spatial smoothing matrix, R x,b L-i+1 Covariance matrix-to-space smoothing matrix, x, representing data received by backward smoothing L-i +1 th array element b Representing the upstream signals received in reverse by all sub-arrays,
indicating the upstream signal received by the reverse ith sub-array,
represents R x A conjugate matrix of (a);
establishing a forward and backward space smoothing matrix to obtain a forward and backward space smoothing algorithm,
wherein: r x，fbss Representing a forward and backward spatial smoothing matrix.
5. The method for estimating 5G NR DOA based on a DMRS signal according to claim 4, wherein the estimating the DOA according to the forward and backward spatial smoothing algorithm comprises:
the eigenvalue decomposition is carried out on the forward and backward space smoothing matrix,
R x，fbxx ＝U·Λ·U H
wherein: Λ represents a diagonal matrix;
estimating the number of the information sources by using the minimum eigenvalue multiplicity G,
μ 1 ≥μ 2 ≥L≥μ N
M＝N-G
A＝M
wherein: mu.s N Representing the Nth eigenvalue arranged from large to small in the diagonal matrix, wherein M represents the number of eigenvalues of which the eigenvalues are larger than a set threshold value, and G represents the number of eigenvalues of which the eigenvalues are smaller than the set threshold value; a represents the estimated number of sources;
dividing the matrix U after the characteristic value decomposition into signal subspaces U according to the estimated information source quantity A s Sum noise subspace U W Signal subspace U s Composed of M eigenvectors corresponding to larger eigenvalues, noise subspace U W The characteristic vectors corresponding to G smaller characteristic values are formed;
calculating the MUSIC space spectrum, searching the common peak value, calculating the incident angle, estimating the DOA according to the incident angle,
wherein: p (theta) represents an incident angle, a (theta) represents an incident direction matrix, a H (theta) represents a transformation matrix of the incident direction matrix,
representing a noise subspace U W The transformation matrix of (2).
6. A DMRS signal-based 5G NR DOA estimation system, comprising: comprises the steps of (a) preparing a substrate,
the acquisition module acquires the uplink signal of the target user, performs synchronous processing and acquires synchronous information;
the analysis module is used for acquiring a target user uplink DMRS reference signal according to the synchronization information and the DMRS signal resource information configured by the upper layer;
the modeling module is used for establishing a forward and backward space smoothing algorithm model;
and the calculation module is used for estimating DOA according to the forward and backward space smoothing algorithm model.
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