WO2022222896A1

WO2022222896A1 - Sending and receiving methods and apparatus, electronic device, and storage medium

Info

Publication number: WO2022222896A1
Application number: PCT/CN2022/087485
Authority: WO
Inventors: 李卫敏; 袁志锋; 马一华; 李志岗
Original assignee: 中兴通讯股份有限公司
Priority date: 2021-04-21
Filing date: 2022-04-18
Publication date: 2022-10-27
Also published as: CN115226240A

Abstract

Sending and receiving methods and apparatus, an electronic device, and a storage medium. The receiving method comprises: acquiring a merge vector W (110); and performing detection according to the merge vector W, and acquiring a detection result (120). The embodiments of the present application, by using a merge vector W to perform detection in a grant-free scenario, improve the accuracy of the detection of receiving signals, and improve data transmission performance.

Description

A sending and receiving method, apparatus, electronic device and storage medium

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on the Chinese patent application with the application number 202110432600.5 and the filing date on April 21, 2021, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is incorporated herein by reference.

technical field

The present application relates to the field of wireless communication, and in particular, to a sending and receiving method, apparatus, electronic device and storage medium.

Background technique

In Grant-free transmission, a terminal or User Equipment (UE) can send data autonomously without sending scheduling requests and waiting for dynamic scheduling. Compared with traditional transmission methods, scheduling-free transmission can reduce signaling overhead and transmission delay, and can reduce power consumption of terminals or UEs. A scheduling-free transmission method is contention-based scheduling-free transmission. For example, the UE randomly selects transmission resources (including time-frequency resources and pilots, etc.) for competing access and transmission. In this solution, since the time-frequency resources and pilots used by different UEs may be the same, collisions may occur. In the case of collision, the receiver performs channel estimation through pilots, and the obtained channel estimation value will be the sum of the channels of the multiple UEs that have collided. Another solution is that the UE randomly selects transmission resources and performs contention access and transmission in a data-only or pilot-free/pilot-free manner. In this scheme, there are no pilots available for the receiver to use for channel estimation, and the receiver needs to perform blind detection. In the above contention-based scheduling-free transmission scheme, it is difficult for the receiver to obtain accurate channel information of each UE, and cannot effectively combine received signals, resulting in inability to accurately detect received signals and affect transmission performance.

SUMMARY OF THE INVENTION

The main purpose of the embodiments of this application is to propose a sending and receiving method, apparatus, electronic device, and storage medium, which aim to implement better received signal detection and improve data transmission performance in a scheduling-free transmission scenario.

An embodiment of the present application provides a receiving method, which includes the following steps: acquiring a combined vector W; performing detection according to the combined vector W, and acquiring a detection result.

An embodiment of the present application further provides a sending method, the method includes the following steps: acquiring first data and P pilots; sending the first data and the P pilots; wherein P is greater than or equal to 0 The first data includes at least one of the following information: identification information, payload, information of the P pilots, sequence information, and transmission resource information, and the first data is detected according to the combining vector W.

An embodiment of the present application further provides a receiving apparatus, the apparatus includes: an acquisition module, configured to acquire a combined vector W; and a detection module, configured to perform detection according to the combined vector W, and acquire a detection result.

An embodiment of the present application further provides a sending apparatus, the apparatus includes: an obtaining module, configured to obtain first data and P pilot frequencies; a sending module, configured to send the first data and the P pilot frequencies; Wherein, P is an integer greater than or equal to 0, the first data includes at least one of the following information: identification information, payload, information of the P pilots, sequence information, transmission resource information, the first data The data is detected according to the merged vector W.

The embodiment of the present application further provides an electronic device, the electronic device includes: one or more processors; a memory for storing one or more programs, when the one or more programs are processed by the one or more programs The processor executes, so that the one or more processors implement the receiving method and/or the sending method according to any one of the embodiments of this application.

Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, implements the receiving method and/or the above-described method in any of the embodiments of the present application delivery method.

In the embodiment of the present application, by acquiring the combining vector W, performing detection according to the combining vector W, and acquiring the detection result, accurate detection of the received signal in the scheduling-free transmission scenario is realized, and data transmission performance is improved.

Description of drawings

1 is a flowchart of a receiving method provided by an embodiment of the present application;

2 is a flowchart of another receiving method provided by an embodiment of the present application;

3 is a flowchart of another receiving method provided by an embodiment of the present application;

4 is a flowchart of another receiving method provided by an embodiment of the present application;

5 is a flowchart of a sending method provided by an embodiment of the present application;

6 is a schematic structural diagram of a receiving apparatus provided by an embodiment of the present application;

FIG. 7 is a schematic structural diagram of a sending apparatus provided by an embodiment of the present application;

FIG. 8 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

In the following description, suffixes such as 'module', 'component' or 'unit' used to represent elements are used only to facilitate the description of the present application, and have no specific meaning per se. Thus, "module", "component" or "unit" may be used interchangeably.

FIG. 1 is a flowchart of a receiving method provided by an embodiment of the present application. The method may be executed by a receiving device, and the device may be implemented in hardware and/or software. Referring to FIG. 1 , an embodiment of the present application provides The receiving method specifically includes the following steps:

Step 110 , obtaining the combined vector W.

Step 120 , perform detection according to the combined vector W, and obtain a detection result.

Specifically, the received signal may be detected according to the combining vector W, and the detection result of the received signal may be obtained.

The embodiments of the present application can be applied to the situation of detecting received signals in a scheduling-free transmission scenario. By acquiring the combined vector W, performing detection according to the combined vector W, and acquiring the detection results, the accuracy of the received signals in the scheduling-free transmission scenario is achieved. Detection, improve data transmission performance.

In one embodiment, the combined vector W includes X vectors, each of which is composed of a specified N elements of a row vector or a column vector in the specified matrix, where X is an integer greater than or equal to 1, and N is An integer greater than 1, the specified matrix includes at least one of the following: a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix.

The specified N elements may be the first N elements, the consecutive N elements, or the N elements of the specified index, and the like. In one embodiment, the specified matrix may further include at least one of a sub-matrix of a discrete Fourier transform matrix and a sub-matrix of an inverse discrete Fourier transform matrix.

In one embodiment, the merged vector W includes a vector generated from a Kronecker product of a first set of vectors and a second set of vectors, wherein the first set of vectors includes at least one vector and each vector is composed of a a specified N1 elements of a row or column vector in a specified matrix, the second set of vectors contains at least one vector and each vector is composed of a specified N2 elements of a row or column vector in the second specified matrix composition, N1 is an integer greater than or equal to 1, N2 is an integer greater than or equal to 1, the first specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix, and the second specified matrix includes a discrete Fourier transform matrix. Fourier transform matrix or inverse discrete Fourier transform matrix.

Among them, the specified N1 elements can be the first N1 elements, the consecutive N1 elements, or the N1 elements of the specified index, etc. The specified N2 elements can be the first N2 elements, the consecutive N2 elements, or the N2 elements of the specified index Wait. In one embodiment, N1 is equal to one, alternatively, N2 is equal to one. It can be understood that the first specified matrix includes at least one of a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix, and the second specified matrix includes at least one of a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix. . The size of the first specified matrix and the second specified matrix may be the same or different. In one embodiment, the first specified matrix may further include at least one of a sub-matrix of a discrete Fourier transform matrix and a sub-matrix of an inverse discrete Fourier transform matrix, and the second specified matrix may further include a discrete Fourier transform matrix At least one of the submatrix of , and the submatrix of the inverse discrete Fourier transform matrix.

In one embodiment, the combined vector W includes:

or,

Among them, g is at least one value in the set [0,1,2,...,M-1], θ=2π/M, N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to The product of N and F, where F is an integer greater than or equal to 1, and j is an imaginary unit. In one embodiment, F may be an oversampling factor, and the size of the combined vector set may be controlled by setting the value of F. In one embodiment, the factors in the merging vector W

can be removed.

In one embodiment, the combined vector W includes:

or,

Wherein, g ₁ is at least one value in the set [0,1,2,...,M ₁ -1], θ ₁ =2π/M ₁ , N ₁ is an integer greater than or equal to 1, and M ₁ is greater than or equal to An integer of N ₁ , or, M ₁ is equal to the product of N ₁ and F ₁ , F ₁ is an integer greater than or equal to 1, and g ₂ is at least one of the set [0,1,2,...,M ₂ -1] value, θ ₂ =2π/M ₂ , N ₂ is an integer greater than or equal to 1, M ₂ is an integer greater than or equal to N ₂ , or, M ₂ is equal to the product of N ₂ and F ₂ , and F ₂ is greater than or equal to an integer of 1,

is the Kronecker product, and j is the imaginary unit. In one embodiment, N1 is equal to one, alternatively, N2 is equal to one. In one embodiment, F1 and F2 are each an oversampling factor. In one embodiment, the factors in the combined vector W

can be removed.

FIG. 2 is a flowchart of another receiving method provided by an embodiment of the present application. The embodiment of the present application is an embodiment based on the above-mentioned embodiment of the present application. Referring to FIG. 2 , the method provided by the embodiment of the present application specifically includes the following steps:

Step 210: Obtain a merged vector W from the merged vector set S.

Step 220: Perform detection according to the combined vector W to obtain a detection result.

In one embodiment, the combined vector set S includes:

a vector of the specified N elements for each row or column vector in the specified matrix; or,

A vector in a matrix generated from the Kronecker product of a first matrix and a second matrix, where the first matrix includes a vector of the specified N1 elements of each row or column vector in the first specified matrix , the second matrix includes a vector formed by the specified N2 elements of each row vector or column vector in the second specified matrix;

Wherein, N is an integer greater than 1, N1 is an integer greater than or equal to 1, N2 is an integer greater than or equal to 1, and the specified matrix includes at least one of a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix, The first specified matrix includes at least one of a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix, and the second specified matrix includes at least one of a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix. The size of the first specified matrix and the second specified matrix may be the same or different.

The specified N elements may be the first N elements, the consecutive N elements, or the N elements of the specified index, and the like. The specified N1 elements can be the first N1 elements, the consecutive N1 elements, or the N1 elements of the specified index, etc. The specified N2 elements can be the first N2 elements, the consecutive N2 elements, or the N2 elements of the specified index, etc.

In one embodiment, N1 is equal to one, alternatively, N2 is equal to one. In another embodiment, the specified matrix may further include at least one of a sub-matrix of a discrete Fourier transform matrix and a sub-matrix of an inverse discrete Fourier transform matrix, and the first specified matrix may further include a sub-matrix of the discrete Fourier transform matrix. At least one of a sub-matrix and a sub-matrix of an inverse discrete Fourier transform matrix, and the second specified matrix may also include at least one of a sub-matrix of a discrete Fourier transform matrix and a sub-matrix of an inverse discrete Fourier transform matrix.

In one embodiment, the combined vector set S includes:

or,

Among them, g=0,1,2,...,M-1, θ=2π/M, N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to the product of N and F, and F is Integer greater than or equal to 1, j is an imaginary unit. In one embodiment, F is the oversampling factor. In one embodiment, the factors in the combined vector set S are

can be removed.

In one embodiment, the combined vector set S includes:

or,

Wherein, g ₁ =0,1,2,...,M ₁ -1, θ ₁ =2π/M ₁ , N ₁ is an integer greater than or equal to 1, M ₁ is an integer greater than or equal to N ₁ , or, M ₁ is equal to the product of N ₁ and F ₁ , F ₁ is an integer greater than or equal to 1, g ₂ =0,1,2,...,M ₂ -1, θ ₂ =2π/M ₂ , N ₂ is greater than or equal to an integer of 1, M ₂ is an integer greater than or equal to N ₂ , or, M ₂ is equal to the product of N ₂ and F ₂ , and F ₂ is an integer greater than or equal to 1,

is the Kronecker product, and j is the imaginary unit. In one embodiment, N1 is equal to one, alternatively, N2 is equal to one. In one embodiment, F1 and F2 are each an oversampling factor. In one embodiment, the factors in the combined vector set S are

can be removed.

FIG. 3 is a flowchart of another receiving method provided by an embodiment of the present application. The embodiment of the present application is an embodiment based on the above-mentioned embodiment of the present application. Referring to FIG. 3 , the method provided by the embodiment of the present application specifically includes the following steps:

Step 310: Acquire the identified merged vector from the merged vector set S through merged vector identification, and use the identified merged vector as the merged vector W.

Step 320 , perform detection according to the combined vector W, and obtain a detection result.

Wherein, obtaining the identified merging vector from the merging vector set S through merging vector identification includes: determining the identification metric A _t of each merging vector S _t in the merging vector set S _; The value sorting of the identification metric A _t obtains the corresponding D merged vectors as the identified merged vectors;

Wherein, 1<=t<=T, T is the number of merged vectors in the merged vector set S, and D is an integer greater than or equal to 0.

In one embodiment, At = S _t ^H R ^-1 S _t _, where () ^H represents a conjugate transpose, () ^-1 represents an inversion operation, and R is the covariance matrix or correlation matrix of the received signal, Alternatively, R is the covariance matrix or correlation matrix of the signal, interference, and noise.

In one embodiment, an absolute value operation or a real part operation may also be performed on the identification metric, for example, A _t =abs(S _t ^H R ^-1 S _t ), or, A _t =real(S _t ^H R ^-1 S _t ), where abs() represents the operation of taking the absolute value, and real() represents the operation of taking the real part.

In an implementation manner, the combined vector set S is as described in the foregoing embodiment, and details are not repeated here.

In this embodiment of the present application, the values of the identification metrics A _t of each merged vector S _t may be sorted, and corresponding D merged vectors are selected from these merged vectors in the order from small to large or from large to small as the identification to the merged vector.

FIG. 4 is a flowchart of another receiving method provided by an embodiment of the present application. The embodiment of the present application is an embodiment based on the above-mentioned embodiment of the present application. Referring to FIG. 4 , the method provided by the embodiment of the present application specifically includes the following steps:

Step 410: Acquire a merged vector V, and obtain a merged vector W according to the merged vector V.

Step 420 , perform detection according to the combined vector W, and obtain a detection result.

Wherein, the combined vector V includes at least one vector.

In one embodiment, the obtaining of the combined vector V includes at least one of the following:

Obtain the identified merged vector from the merged vector set S by merging vector identification, and use the identified merged vector as the merged vector V;

Obtain a merged vector U, and obtain a merged vector V according to the merged vector U, wherein the merged vector U includes at least one vector;

The merged vector V is obtained from the merged vector set S according to a preset method.

In an implementation manner, the process of identifying the combined vector is as described in the foregoing embodiment, and details are not repeated here.

In one embodiment, a merged vector U is obtained, and a merged vector V is obtained according to the merged vector U, wherein the merged vector U may be obtained from the merged vector set S through the merged vector identification, or from the merged vector according to a preset method. Obtained from the vector set S, or obtained through iteration, for example, take the merged vector V obtained in the previous iteration as the merged vector U in this iteration, and then obtain the merged vector according to the merged vector U in this iteration V.

In one embodiment, the merged vector V is obtained from the merged vector set S according to a preset manner, wherein the preset manner includes a system preset rule or a system preset index and the like.

In one embodiment, the merged vector V is obtained, and the merged vector W is obtained according to the merged vector V, which can be obtained in an iterative manner. For example, the merged vector W obtained in the previous iteration is used as the merged vector V in this iteration, Then the merged vector W is obtained according to the merged vector V in this iteration.

In one embodiment, the merged vector W is obtained according to the merged vector V, including:

Obtain each merged vector S _t in the merged vector set S;

get the coefficient C _t ;

Obtain the updated merged vector V _t according to the merged vector V, the merged vector S _t and the coefficient C _t ;

Determine the identification metric B _t =V _t ^H R ^-1 V _{t of the merged vector V t} _;

According to the value sorting of the identification metric B _t of each merge vector V _t , the corresponding E merge vectors are obtained as the merge vector W;

Among them, 1<=t<=T, T is the number of merged vectors in the merged vector set S, E is an integer greater than or equal to 0, () ^H represents the conjugate transpose, () ^-1 represents the inversion operation, R is the covariance matrix or correlation matrix of the received signal, or R is the covariance matrix or correlation matrix of the signal, interference, and noise.

Specifically, in this embodiment, the values of the identification metrics B _t of the respective merge vectors V _t can be sorted, and corresponding E merge vectors are selected from these merge vectors in descending order or in descending order. as the merged vector W.

In one embodiment, an absolute value operation or a real part operation can also be performed on the identification metric, for example, B _t =abs(V _t ^H R ⁻¹ V _t ), or B _t =real(V _t ^H R ^{− 1} V _t ), where abs() represents the operation of taking the absolute value, and real() represents the operation of taking the real part.

In one embodiment, the obtained coefficient C _t includes at least one of the following:

Obtained from the first specified set of coefficients.

In one embodiment, acquiring a combined vector V, and acquiring a combined vector W according to the combined vector V, includes: the combined vector V includes K vectors V ₁ , V ₂ , . . . , V _K , and the combined vector W =(e ₁ *V ₁ +e ₂ *V ₂ +...+e _K *V _K )/f, where K is an integer greater than or equal to 1, e ₁ , e ₂ , ..., e _K are coefficients corresponding to V ₁ , V ₂ , . . . , V _K respectively, and f is an adjustment factor.

Wherein, the vectors V ₁ , V ₂ , . . . , V _K can be obtained according to a specified method, or obtained separately.

The coefficients e ₁ , e ₂ , . . . , e _K may be determined according to a specified method, for example, calculated according to a specified formula, or obtained from at least one coefficient set.

In one embodiment, e ₁ is equal to 1, and the combined vector W=(V ₁ +e ₂ *V ₂ +...+e _K *V _K )/q, where q is an adjustment factor.

In one embodiment, the combined vector V includes two vectors V ₁ , V ₂ , e ₁ is equal to 1, and e ₂ is equal to

Alternatively, _e2 is equal to

Alternatively, e ₂ is obtained from the second set of specified coefficients.

In one embodiment, the combined vector V includes three vectors V ₁ , V ₂ , and V ₃ , e ₁ is equal to 1, and e ₂ is equal to

Or _e2 is taken from the third specified set of coefficients, _e3 is equal to

Or e ₃ is obtained from the fourth set of specified coefficients.

In one embodiment, the first specified coefficient set, the second specified coefficient set, the third specified coefficient set, and the fourth specified coefficient set may be the same coefficient set.

In one embodiment, f and q are energy adjustment factors used to achieve energy adjustment or energy normalization.

In one embodiment, the embodiment of the present application further performs detection according to the combined vector V to obtain a detection result.

In one embodiment, on the basis of the above application embodiments, the detection according to the combined vector W includes at least one of the following:

Taking the product of the conjugate transpose WH of the combined vector ^W and the received signal as the combined signal;

The product of the combined vector W and the received signal is taken as a combined signal.

In this embodiment, when the received signal is detected, the combined signal may be obtained by multiplying the conjugate transpose ^WH of the combined vector W by the received signal, or the combined signal may be obtained by multiplying the combined vector W by the received signal.

For example, assuming that the received signal is y, the received signal y can be appropriately adjusted in dimension to ensure the dimensional matching between the received signal y and the combined vector W, or the conjugate transpose ^WH of the combined vector W, and then the combined signal z can be obtained = ^W Hy or z=Wy.

Obtain the product of the conjugate transpose ^WH of the combined vector W and the inverse matrix of the matrix R, and use the product of the product and the received signal as the combined signal;

Obtain the product of the combined vector W and the inverse matrix of the matrix R, and use the product of the product and the received signal as a combined signal;

The matrix R is a covariance matrix or a correlation matrix of a received signal, or a covariance matrix or a correlation matrix of a signal, interference, and noise.

In this embodiment, when the received signal is detected, the conjugate transpose ^WH of the combined vector W may be multiplied by the inverse matrix of the matrix R first, and then multiplied with the received signal to obtain the combined signal, or the combined signal may be The vector W is multiplied by the inverse of the matrix R and then multiplied by the received signal to obtain the combined signal. It can be understood that the product of the inverse matrix of the matrix R and the received signal can also be obtained first, and then the conjugate transpose ^WH of the combined vector W is multiplied by the product to obtain the combined signal, or the combined vector W and the received signal can be obtained. The above products are multiplied to obtain the combined signal.

For example, assuming that the received signal is y, the received signal y can be appropriately adjusted in dimension to ensure that the dimensions of each parameter match, and then the combined signal z=W ^H R ^-1 y or z=WR ^-1 y can be obtained.

In one embodiment, on the basis of the above application examples, it also includes:

The detection is performed according to the combined vector V, and the detection result is obtained. The process of detecting the received signal according to the combining vector V may be similar to the above-mentioned process of detecting the received signal based on the combining vector W, which will not be repeated here.

In one embodiment, based on the above application embodiments, the detection result includes at least one of the following information: payload, identification information, pilot information, sequence information, and transmission resource information.

In one embodiment, in order to solve the problem that the receiver cannot effectively detect and combine the received signals, the receiving method described below can be used to improve the performance and capacity of the scheduling-free transmission. The receiving method includes:

Get the merged vector W;

The detection is performed according to the combined vector W, and the detection result is obtained.

In one example, the combined vector W includes: X vectors, where X is an integer greater than or equal to 1;

Wherein, the X vectors are X vectors respectively formed by the specified N elements of the X row vectors or column vectors in the M-dimensional Inverse Discrete Fourier Transform (Inverse Discrete Fourier Transform, IDFT) matrix;

Or, the X vectors are X vectors respectively formed by the specified N elements of the X row vectors or column vectors in the M-dimensional Discrete Fourier Transform (Discrete Fourier Transform, DFT) matrix;

Wherein, the specified N elements include the first N elements, the consecutive N elements, or the N elements of the specified index;

Among them, N is an integer greater than 1, M is an integer greater than or equal to N, or M is equal to N times F, and F is an integer greater than or equal to 1, for example, F is an oversampling factor;

Among them, the X vectors formed by the specified N elements of the X row vectors or column vectors respectively include: the specified N elements of each row vector or column vector form a vector, then, X vectors can be formed in total.

In this example, the length of the merge vector W is N.

In one example, the combined vector W includes: a vector formed by the Kronecker product of X1 vectors and X2 vectors, where X1 is an integer greater than or equal to 1, and X2 is an integer greater than or equal to 1 integer;

Among them, the X1 vectors are X1 vectors respectively formed by the specified N1 elements of the X1 row vectors or column vectors in the M1-dimensional inverse discrete Fourier transform matrix, and the X2 vectors are the M2-dimensional inverse discrete Fourier transform matrix. X2 vectors formed by the specified N2 elements of the X2 row vectors or column vectors respectively;

Or, the X1 vectors are X1 vectors respectively formed by the specified N1 elements of the X1 row vectors or column vectors in the M1-dimensional discrete Fourier transform matrix, and the X2 vectors are X2 in the M2-dimensional discrete Fourier transform matrix X2 vectors formed by the specified N2 elements of a row vector or column vector respectively;

Among them, the specified N1 elements include the first N1 elements, the consecutive N1 elements, or the N1 elements of the specified index, and the specified N2 elements include the first N2 elements, the consecutive N2 elements, or the specified index. N2 elements;

Among them, N1 is an integer greater than or equal to 1, M1 is an integer greater than or equal to N1, or M1 is equal to N1 multiplied by F1, and F1 is an integer greater than or equal to 1; N2 is an integer greater than or equal to 1, and M2 is greater than or equal to 1 or an integer equal to N2, or M2 equals N2 times F2, where F2 is an integer greater than or equal to 1; for example, F1 and F2 are each an oversampling factor.

In this example, the combined vector W includes (X1 times X2) vectors of length (N1 times N2).

In one example, the merged vector W includes:

or,

where g is at least one value in the set [0,1,2,...,M-1], θ=2π/M, N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to N times F, where F is an integer greater than or equal to 1.

In this example, the length of the merge vector W is N.

In one example, the merged vector W includes:

or,

Wherein, g ₁ is at least one value in the set [0,1,2,...,M ₁ -1], θ ₁ =2π/M ₁ ; g ₂ is the set [0,1,2,... , M ₂ -1] at least one value, θ ₂ =2π/M ₂ ;

is the Kronecker product; N ₁ is an integer greater than or equal to 1, M ₁ is an integer greater than or equal to N ₁ , or M ₁ is equal to N ₁ multiplied by F ₁ , and F ₁ is greater than or equal to An integer of 1; N ₂ is an integer greater than or equal to 1, M ₂ is an integer greater than or equal to N ₂ , or M ₂ is equal to N ₂ multiplied by F ₂ , and F ₂ is an integer greater than or equal to 1.

In this example, the length of the merge vector W is (N1 times N2).

In an example, obtaining the merged vector W includes: obtaining the merged vector W from the merged vector set S;

Wherein, the combined vector set S includes one of the following:

A matrix composed of specified N rows (or specified N columns) of an M-dimensional inverse discrete Fourier transform matrix, and each column (or each row) in the matrix is a combined vector;

A matrix consisting of specified N rows (or specified N columns) of an M-dimensional discrete Fourier transform matrix, and each column (or each row) in the matrix is a combined vector;

The matrix formed by the Kronecker product of the matrix S1 and the matrix S2, each column (or each row) in the matrix is a merged vector; wherein, the matrix S1 is the specified N1 row of the M1-dimensional inverse discrete Fourier transform matrix ( Or specify a matrix composed of N1 columns), and matrix S2 is a matrix composed of specified N2 rows (or specified N2 columns) of an M2-dimensional inverse discrete Fourier transform matrix; or, matrix S1 is a specified M1-dimensional discrete Fourier transform matrix. A matrix composed of N1 rows (or specified N1 columns), and matrix S2 is a matrix composed of specified N2 rows (or specified N2 columns) of an M2-dimensional discrete Fourier transform matrix; each column (or each row) in matrix S1 is a Vector, each column (or each row) in matrix S2 is a vector;

Wherein, the specified N rows include the first N rows, the consecutive N rows, or the N rows of the specified index (the specified N columns include the first N columns, the consecutive N columns, or the N columns of the specified index);

Among them, the specified N1 rows include the first N1 rows, the consecutive N1 rows, or the N1 rows of the specified index, and the specified N2 rows include the first N2 rows, the consecutive N2 rows, or the N2 rows of the specified index (the specified N1 columns include the first N1 columns, the consecutive N1 rows column, or the N1 column of the specified index, the specified N2 column includes the first N2 column, the consecutive N2 column, or the N2 column of the specified index);

Among them, N is an integer greater than or equal to 1, M is an integer greater than or equal to N, or, M is equal to N times F, and F is an integer greater than or equal to 1; N1 is an integer greater than or equal to 1, and M1 is greater than or equal to An integer of N1, or, M1 is equal to N1 times F1, F1 is an integer greater than or equal to 1; N2 is an integer greater than or equal to 1, M2 is an integer greater than or equal to N2, or M2 is equal to N2 times F2, F2 is an integer greater than or equal to 1.

In this example, in the first two cases, the merged vector set S includes M merged vectors of length N, and in the third case, the merged vector set S includes (M1 times M2) lengths (N1 times N2) merged vector.

In this example, the combined vector set S may be preset or generated according to a specified rule; the matrix S1 and the matrix S2 may be preset or generated according to a specified rule.

Wherein, the combined vector set S includes:

or,

Among them, g=0,1,...,M-1, θ=2π/M; N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to N times F, and F is greater than or an integer equal to 1.

In this example, the merged vector set S includes M merged vectors of length N.

Wherein, the combined vector set S includes:

or,

Wherein, g ₁ =0,1,...,M ₁ -1, g ₂ =0,1,...,M ₂ -1, θ ₁ =2π/M ₁ , θ ₂ =2π/M ₂ ,

is the Kronecker product; N ₁ is an integer greater than or equal to 1, M ₁ is an integer greater than or equal to N ₁ , or M ₁ is equal to N ₁ F ₁ , and F ₁ is an integer greater than or equal to 1 ; N ₂ is an integer greater than or equal to 1, M ₂ is an integer greater than or equal to N ₂ , or M ₂ is equal to N ₂ F ₂ , and F ₂ is an integer greater than or equal to 1.

In this example, the set S of merged vectors contains (M1 times M2) merged vectors of length (N1 times N2).

In one example, N1=1 or N2=1 in the above example.

In an example, the method obtains the merged vector W by traversing each merged vector in the merged vector set S, and then performs detection according to the obtained merged vector W to obtain the detection result.

In an example, obtaining the merged vector W includes: obtaining the identified merged vector by identifying the merged vector, and using the identified merged vector as the merged vector W;

Wherein, obtaining the identified merged vector by identifying the merged vector includes: calculating the identification metric of each merged vector S _t in the merged vector set S

Obtain D merged vectors with smaller identification metrics as the identified merged vectors;

In this example, it is assumed that the number of combined vectors in the combined vector set S is T, 1<=t<=T, D is an integer greater than or equal to 0, R is the covariance matrix or correlation matrix of the received signal, or, R is the covariance matrix or correlation matrix of signal, interference and noise.

Wherein, R may be obtained according to the received signal, or may be obtained according to the channel estimation result, the interference and/or noise estimation result.

In this example, by performing combined vector identification, the receiver complexity can be significantly reduced.

In one example, the length of the combining vector is the same as the number of receive antennas of the receiver. For example, N is the number of receive antennas, or (N1 times N2) is the number of receive antennas, where N1 is the number of receive antennas in the horizontal dimension, and N2 is the number of receive antennas in the vertical dimension.

In one example, the length of the combining vector is the same as the number of receive antennas currently used by the receiver.

In one example, the length of the combining vector is the same as the length of the spreading sequence used by the transmitter.

In one example, the length of the combining vector is the same as the number of repetitions used by the transmitter.

In one example, the detection is performed according to the combined vector W, including one of the following:

The combined vector W is conjugated transposed, and then multiplied with the received signal to obtain the combined signal;

The combined signal is obtained by multiplying the combined vector W by the received signal.

The combined vector W is conjugated transposed, and multiplied by the inverse matrix of the matrix R, and then multiplied by the received signal to obtain the combined signal;

Multiply the combined vector W by the inverse of the matrix R, and then multiply it with the received signal to obtain the combined signal;

Wherein, R is the covariance matrix or correlation matrix of the received signal, or, R is the covariance matrix or correlation matrix of the signal, interference, and noise.

In an example, the method further includes: processing the combined signal to obtain a detection result; wherein the processing includes channel equalization or compensation, demodulation and decoding, and the like.

In an example, the method further includes: obtaining at least one of the following from the detection result: payload; identification information; pilot information; sequence information; transmission resource information.

Wherein, the receiver can determine which UE (terminal or user equipment or transmitter) it receives the data according to the acquired identification information.

The payload may include service data, specified messages, and the like. The receiver obtains the payload sent by the UE, and can complete the corresponding communication process.

The pilot information includes information about at least one pilot among the P pilots, and may also include information about the number P of pilots. The receiver can reconstruct the pilot symbols according to the acquired information of the pilot used by the UE, so as to perform interference cancellation on the pilot.

The sequence information includes the information of the sequence used by the UE transmitting end for processing, and may also include the information of the sequence set. The receiver can reconstruct the data symbols according to the acquired information of the sequence used by the UE, so as to perform interference cancellation on the data symbols.

The transmission resource information includes location information of at least one transmission resource used by the UE, may also include information on the quantity of transmission resources used by the UE, and may also include information on available transmission resources, such as the starting position or number of available transmission resources. According to the acquired information of the transmission resources used by the UE, the receiver can determine on which transmission resources the UE transmits, so as to further perform detection on these transmission resources.

In one example, the method further performs subsequent processing, including at least one of the following: symbol reconstruction, channel estimation update, interference cancellation, further detection, and the like. The symbol reconstruction may reconstruct the transmitted symbol according to the detection result, which is used for channel estimation and/or interference cancellation. Symbol reconstruction may include data symbol reconstruction, and may also include pilot symbol reconstruction. The channel estimation update includes using the reconstructed symbols to perform channel estimation based on the least squares algorithm, so as to obtain an updated channel estimation result. Further detection includes detection of other users, detection on other transmission resources, and iterative detection.

In the case of scheduling-free transmission, the receiver cannot effectively combine and detect the received signal. With the method described in this embodiment, the receiver performs detection according to the acquired combining vector W, which can effectively match the characteristics of the transmission channel, and also The interference generated by other user signals can be effectively suppressed, so that the received signals can be effectively combined and detected, the transmission performance of the scheduling-free UE can be improved, and the performance and capacity of the scheduling-free transmission can be improved.

The method described in this embodiment performs detection according to the acquired combining vector W, and realizes blind combining of received signals, which may also be called blind spatial combining or blind receive beamforming, thereby realizing blind detection of received signals.

The method described in this embodiment can be used for data-only or pilot-free/pilot-free transmission, pilot-based transmission, or pilot-free transmission. Schedule transmission.

The method described in this embodiment is suitable for scenarios such as multiple antennas, antenna arrays, correlated antenna arrays, and large-scale antenna arrays. By using the combination vector W, the characteristics of the multi-antenna channels can be matched, for example, the combination vector W can be used to reflect the correlation of the multi-antenna channels. Or reflect the phase difference of multi-antenna channels, in addition, it can also suppress the interference caused by other user signals, so as to achieve effective detection of received signals, improve the detection performance of received signals, and support a large number of users in these scenarios. Schedule access and transmission.

In one embodiment, an embodiment of the present application further provides a receiving method, applied to a receiver, the method includes:

get the merged vector V;

Obtain the merged vector W according to the merged vector V;

In one example, the merged vector V is similar to the merged vector W in the above example, and can be obtained in the same way.

In an example, obtaining the merged vector V includes: obtaining the merged vector V from the merged vector set S; wherein the merged vector set S is as described in the above example, and details are not repeated here.

In an example, obtaining the merged vector V includes: obtaining the identified merged vector through merge vector identification, and using the identified merged vector as the merged vector V; wherein, obtaining the identified merged vector through the merge vector identification is the same as that in the above example. The identification process of the merged vector is similar, and will not be repeated here.

In one example, obtaining the merged vector W according to the merged vector V includes: for each merged vector S _t in the merged vector set S, obtaining a coefficient C _t , and obtaining an update according to the merged vector V, the merged vector S _t and the coefficient C _t After the vector V _t , calculate the identification metric B _t =V _t ^H R ^-1 V _t , and then obtain E merged vectors with smaller identification metrics from the updated merged vector, as merged vectors W; among them, in this example Assuming that the number of merged vectors in the merged vector set S is T, 1<=t<=T, and E is an integer greater than or equal to 0. For example, E equals 1 or 2, or E equals D.

In one example, obtaining the coefficient C _t includes: according to

Calculate the coefficient C _t .

In one example, obtaining the coefficient C _t includes: according to

Calculate the coefficient C _t .

In one example, obtaining the coefficients C _t includes obtaining the coefficients C _t from a specified set of coefficients. For example, the coefficients C _t are obtained by iterating over the values in a specified set of coefficients.

In an example, the updated vector V _t is obtained according to the combined vector V, the combined vector S _t and the coefficient C _t , including: V _t =V+C _t S _t ; in addition, energy normalization may be performed, for example,

In one example, the merged vector V includes multiple vectors. The merged vector W can be obtained separately according to each merged vector V. For example, for each merged vector V, an updated vector is obtained, and the identification metric is calculated, and then E merged vectors with smaller identification metrics are obtained in the updated vector, As the merged vector W obtained from the current merged vector V. For example, the merged vector V includes D vectors, and E is equal to 1, then the obtained merged vector W also includes D vectors.

Alternatively, the merged vector W can be obtained as a whole according to all the merged vectors V. For example, for each merged vector V, all the updated vectors are obtained, and the identification metric is calculated, and then the identification metric E among all the updated vectors with the smaller identification metric is obtained. a merged vector as the obtained merged vector W. For example, E is equal to D.

In one example, the merged vector set S contains M vectors, then, for each merged vector V, M updated vectors can be obtained; or, the merged vector set S contains (M1 times M2) vectors, then , for each merged vector V, (M1 times M2) updated vectors can be obtained.

In an example, the combined vector V is acquired, and the combined vector W is acquired according to the combined vector V, which may be performed iteratively. For example, in the first execution, the merged vector V is obtained, and the merged vector W is obtained according to the merged vector V; in the second execution, the merged vector W obtained in the first execution is used as the new merged vector V, and then Obtain a new merged vector W according to the new merged vector V, and so on until the specified execution condition is satisfied. Wherein, the specified execution condition includes reaching the specified execution times or reaching the specified judgment threshold.

In an example, acquiring the combined vector V includes: acquiring the combined vector U, and acquiring the combined vector V according to the combined vector U.

Wherein, the process of obtaining the merged vector U is similar to the process of obtaining the merged vector V above, including: obtaining the merged vector U from the merged vector set S; The merged vector is taken as the merged vector U.

The process of obtaining the merged vector V according to the merged vector U is similar to the above process of obtaining the merged vector W according to the merged vector V.

This example can also be performed iteratively, similar to the description above.

In one example, the length of the combining vector V is the same as the number of receive antennas of the receiver, or the number of receive antennas currently used by the receiver, or the length of the spreading sequence used by the transmitter, or the same as the length of the spreading sequence used by the transmitter. the same number of repetitions.

In one example, the length of the merged vector W is the same as the length of the merged vector V.

Wherein, R is the covariance matrix or correlation matrix of the received signal, or R is the covariance matrix or correlation matrix of the signal, interference, and noise.

In one example, the method further performs subsequent processing, including at least one of the following: symbol reconstruction, channel estimation update, interference cancellation, further detection, and the like.

For the situation that the receiver cannot effectively combine and detect the received signal in the scheduling-free transmission, by using the method described in this embodiment, the receiver obtains the combined vector W according to the combined vector V, and performs detection according to the combined vector W. It can effectively match the characteristics of the transmission channel, and can also effectively suppress the interference caused by other user signals, so that the received signals can be effectively combined and detected, and the transmission performance of the scheduling-free UE can be improved, which in turn can improve the performance and capacity of the scheduling-free transmission. .

get the merged vector V;

Obtain the merged vector W according to the merged vector V;

The detection is performed according to the combined vector V and/or the combined vector W, and the detection result is obtained.

In one example, the process of obtaining the merged vector V is similar to the above example.

In one example, the process of obtaining the merged vector W according to the merged vector V is similar to the above-mentioned example.

In one example, the detection is performed according to the merged vector V and/or the merged vector W, including one of the following:

Detect according to the merged vector V;

Detect according to the merged vector W;

Detection is performed based on the merged vector V and the merged vector W.

In an example, the detection is performed according to the combined vector V and/or the combined vector W, including: a signal to noise ratio (Signal to Noise Ratio, SNR) or a signal to interference noise ratio (Signal to Interference Ratio) obtained when the detection is performed according to the combined vector V and Noise Ratio, SINR) is larger, the detection is performed according to the combined vector V.

In an example, the detection according to the combined vector V and/or the combined vector W includes: when the SNR or SINR obtained by the detection based on the combined vector W is relatively large, the detection is performed based on the combined vector W.

In one example, the detection according to the merged vector V and/or the merged vector W includes: performing detection only according to the obtained merged vector W.

In one example, the detection according to the combined vector V and/or the combined vector W includes: performing the detection according to the acquired combined vector V and the acquired combined vector W.

In one example, detection is performed according to the merged vector V, including one of the following:

Conjugate transpose the combined vector V, and then multiply it with the received signal to get the combined signal;

The combined signal is obtained by multiplying the combined vector V by the received signal.

The combined vector V is conjugated transposed, and multiplied by the inverse matrix of the matrix R, and then multiplied by the received signal to obtain the combined signal;

Multiply the combined vector V with the inverse of the matrix R, and then multiply it with the received signal to obtain the combined signal;

For the case where the receiver cannot effectively combine and detect the received signal in the scheduling-free transmission, with the method described in this embodiment, the receiver obtains the combining vector W according to the combining vector V, and according to the combining vector V and/or combining The detection of the vector W can realize the effective combination and detection of the received signals, and can improve the transmission performance of the scheduling-free UE, thereby improving the performance and capacity of the scheduling-free transmission.

The method described in this embodiment is suitable for scenarios such as multiple antennas, antenna arrays, correlated antenna arrays, large-scale antenna arrays, etc. In these scenarios, a large number of users can be supported for scheduling-free access and transmission.

FIG. 5 is a flowchart of a sending method provided by an embodiment of the present application. The method may be performed by a sending device, and the device may be implemented in hardware and/or software. Referring to FIG. 5 , the method provided by the embodiment of the present application The sending method specifically includes the following steps:

Step 510: Obtain first data and P pilots.

Step 520, sending the first data and P pilots;

Wherein, P is an integer greater than or equal to 0, and the first data includes at least one of the following information: identification information, payload, information of P pilots, sequence information, and transmission resource information, and the first data is performed according to the combining vector W detection.

In one embodiment, after the transmitter sends the first data and the P pilots, the receiver detects the first data, and the receiver detects the first data using a combination vector W, where the combination vector W includes at least one vector.

In one embodiment, the characteristics of the merged vector W are similar to those of the above-described embodiment.

In one embodiment, the merged vector W is obtained from the merged vector set S, wherein the characteristics of the merged vector set S are similar to the above-mentioned embodiments, and the acquisition process is similar to the above-mentioned embodiments.

In one embodiment, the merged vector W is obtained according to the merged vector V, and the merged vector V includes at least one vector, and the obtaining process is similar to the above-mentioned embodiment.

In this embodiment of the present application, by acquiring the first data and P pilot frequencies, and sending the first data and P pilot frequencies, the first data is detected by combining the vector W, which realizes signal transmission and effective signal transmission in a scheduling-free scenario. In receiving, the detection by combining the vector W can improve the accuracy of the received signal detection, thereby improving the data transmission performance.

In one embodiment, an embodiment of the present application provides a sending method, the method comprising:

obtaining P pilot frequencies and first data;

sending the P pilots and first data;

Wherein, P is an integer greater than or equal to 0, the first data includes at least one of the following information: identification information, payload, information of the P pilots, sequence information, transmission resource information, the The first data is detected according to the combined vector W.

In one example, P equals zero. This example can implement pure data transmission, or no pilot transmission, or no pilot transmission.

In one example, the method may enable schedule-free transmission.

In one example, the first data includes identification information. The identity information is used for the receiver to obtain the identity information of the UE (terminal or user equipment or transmitter), so as to determine which UE sends the data it receives.

In one example, the first data includes a payload. The payload may include business data, specified messages, and the like. The UE sends the payload to the receiver, thereby completing the corresponding communication process.

In one example, the first data includes information of P pilots. The information on the P pilots includes information on at least one pilot among the P pilots, and may also include information on the number P of pilots. The information of the P pilots is used for the receiver to obtain the information of the pilots used by the UE, so that the pilot symbols can be reconstructed so as to perform interference cancellation on the pilots.

In one example, the first data includes sequence information. The sequence information includes the information of the sequence used by the UE transmitting end for processing, and may also include the information of the sequence set. The sequence information is used for the receiver to obtain the information of the sequence used by the UE, so that the data symbols can be reconstructed so as to perform interference cancellation on the data symbols.

In one example, the first data includes transmission resource information. The transmission resource information includes location information of at least one transmission resource used by the UE, may also include information on the quantity of transmission resources used by the UE, and may also include information on available transmission resources, such as the starting position or number of available transmission resources. The transmission resource information is used for the receiver to obtain information of the transmission resources used by the UE, so as to determine which transmission resources the UE has performed transmission on, and perform subsequent detection on these transmission resources.

In an example, sending the P pilots and the first data includes at least one of the following:

mapping the P pilots and the first data to corresponding transmission resources, respectively, to generate a transmission signal, and then send it;

The P pilots are superimposed to obtain superimposed pilots, and the superimposed pilots and the first data are respectively mapped to corresponding transmission resources to generate a transmission signal, which is then sent.

In one example, the first data is detected according to a combined vector W, which includes at least one vector. Wherein, the characteristics of the merged vector W are similar to the above-mentioned embodiments; or, the merged vector W is obtained from the merged vector set S, wherein the characteristics of the merged vector set S are similar to the above-mentioned embodiments, and the acquisition process is similar to the above-mentioned embodiments; Alternatively, the merged vector W is obtained according to the merged vector V, and the merged vector V includes at least one vector, and the obtaining process is similar to the above-mentioned embodiment.

6 is a schematic structural diagram of a receiving apparatus provided by an embodiment of the present application, which can execute the receiving method provided by any embodiment of the present application, and has functional modules and beneficial effects corresponding to the execution method. The apparatus may be implemented by software and/or hardware, and specifically includes: an acquisition module 601 and a detection module 602 .

The obtaining module 601 is used to obtain the combined vector W.

The detection module 602 is configured to perform detection according to the combined vector W, and obtain a detection result.

In the embodiment of the present application, the acquisition module acquires the combined vector W, the detection module performs detection according to the combined vector W, and acquires the detection result, so as to realize the accurate detection of the received signal in the scheduling-free transmission scenario, and improve the data transmission performance.

In one embodiment, the combined vector W in the device includes X vectors, each of which is composed of a specified N elements of a row vector or a column vector in a specified matrix, where X is an integer greater than or equal to 1, N is an integer greater than 1, and the specified matrix includes at least one of the following: a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix.

In one embodiment, the combined vector W in the apparatus includes a vector generated by a Kronecker product of a first set of vectors and a second set of vectors, wherein the first set of vectors includes at least one vector and each vector Consists of a specified N1 elements of a row or column vector in the first specified matrix, the second set of vectors contains at least one vector and each vector is composed of a specified N2 of a row or column vector in the second specified matrix It consists of elements, N1 is an integer greater than or equal to 1, N2 is an integer greater than or equal to 1, the first specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix, and the second specified matrix Including discrete Fourier transform matrices or inverse discrete Fourier transform matrices.

In one embodiment, the combination vector W in the apparatus includes:

or,

Among them, g is at least one value in the set [0,1,2,...,M-1], θ=2π/M, N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to The product of N and F, where F is an integer greater than or equal to 1, and j is an imaginary unit.

In one embodiment, the combination vector W in the apparatus includes:

or,

is the Kronecker product, and j is the imaginary unit.

In one embodiment, the obtaining module 601 in the apparatus includes: a first obtaining unit, configured to obtain a merged vector W from a merged vector set S, wherein the merged vector set S includes:

Wherein, N is an integer greater than 1, N1 is an integer greater than or equal to 1, N2 is an integer greater than or equal to 1, the specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix, and the first A specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix, and the second specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix.

In one embodiment, the obtaining module 601 in the apparatus includes: a second obtaining unit, configured to obtain the merged vector W from the merged vector set S, wherein the merged vector set S includes:

or,

Among them, g=0,1,2,...,M-1, θ=2π/M, N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to the product of N and F, and F is Integer greater than or equal to 1, j is an imaginary unit.

In one embodiment, the obtaining module 601 in the apparatus includes: a third obtaining unit, configured to obtain the merged vector W from the merged vector set S, wherein the merged vector set S includes:

or,

is the Kronecker product, and j is the imaginary unit.

In one embodiment, the obtaining module 601 in the apparatus includes: a fourth obtaining unit, configured to obtain the identified merged vector from the merged vector set S by identifying the merged vector, and use the identified merged vector as the merged vector W; Wherein, the identified merged vector is obtained from the merged vector set S through merged vector identification, including:

Determine the identification metric A _t =S _t ^H R ^-1 S _t of each merging vector S _t in the merging vector set S;

Obtain corresponding D merged vectors as the identified merged vectors according to the value ordering of the identification metrics A _t of each merged vector S _t ;

Among them, 1<=t<=T, T is the number of merged vectors in the merged vector set S, D is an integer greater than or equal to 0, () ^H represents the conjugate transpose, () ^-1 represents the inversion operation, R is the covariance matrix or correlation matrix of the received signal, or R is the covariance matrix or correlation matrix of the signal, interference, and noise.

In one embodiment, the obtaining module 601 in the apparatus includes: a fifth obtaining unit, configured to obtain a merged vector V, and obtain a merged vector W according to the merged vector V, wherein the merged vector V includes at least one vector .

In one embodiment, the fifth obtaining unit is specifically used for at least one of the following:

In one embodiment, the fifth obtaining unit is further used for:

Obtain each merged vector S _t in the merged vector set S;

get the coefficient C _t ;

determining the identification metric B _t =V _t ^H R ^-1 V _{t of the merged vector V t} _;

Obtain corresponding E merging vectors as merging vectors W according to the value ordering of the identification metrics B _t of the respective merging vectors V _t ;

In one embodiment, the fifth obtaining unit is configured to obtain the coefficient C _t , including at least one of the following:

Get from the specified set of coefficients.

In one embodiment, the fifth obtaining unit is configured to obtain the merged vector V, and obtain the merged vector W according to the merged vector V, including: the merged vector V includes K vectors V ₁ , V ₂ , ..., V _K , the combined vector W=(e ₁ *V ₁ +e ₂ *V ₂ +...+e _K *V _K )/f, where K is an integer greater than or equal to 1, e ₁ , e ₂ , ..., e _K are coefficients corresponding to V ₁ , V ₂ , ..., V _K , respectively, and f is an adjustment factor.

In one embodiment, the detection module 602 in the device includes:

The first detection unit is configured to use the product of the conjugate transpose WH of the combined vector ^W and the received signal as a combined signal.

The second detection unit is configured to use the product of the combined vector W and the received signal as a combined signal.

In one embodiment, the detection module 602 in the device includes:

The third detection unit is configured to obtain the product of the conjugate transpose ^WH of the combined vector W and the inverse matrix of the matrix R, and use the product of the product and the received signal as the combined signal.

a fourth detection unit, configured to obtain the product of the combined vector W and the inverse matrix of the matrix R, and use the product of the product and the received signal as a combined signal;

In one embodiment, the apparatus further includes: a second detection module, configured to perform detection according to the combined vector V, and obtain a detection result.

In one embodiment, the detection result obtained by the apparatus includes at least one of the following information: payload, identity information, pilot frequency information, sequence information, and transmission resource information.

FIG. 7 is a schematic structural diagram of a sending apparatus provided by an embodiment of the present application, which can execute the sending method provided by any embodiment of the present application, and has functional modules and beneficial effects corresponding to the executing method. The apparatus may be implemented by software and/or hardware, and specifically includes: an obtaining module 701 and a sending module 702 .

The obtaining module 701 is used for obtaining first data and P pilots.

A sending module 702, configured to send the first data and the P pilots;

Wherein, P is an integer greater than or equal to 0, the first data includes at least one of the following information: identification information, payload, information of the P pilots, sequence information, transmission resource information, the first data The data is detected according to the merged vector W.

In this embodiment of the present application, the acquisition module acquires the first data and the P pilots, and the sending module transmits the first data and the P pilots, wherein the first data is detected by the combined vector W, which realizes the scheduling-free scenario. For signal transmission and effective reception, detection by combining the vector W can improve the accuracy of received signal detection, thereby improving data transmission performance.

8 is a schematic structural diagram of an electronic device provided by an embodiment of the present application, the electronic device includes a processor 50, a memory 51, an input device 52 and an output device 53; the number of processors 50 in the electronic device may be one or more 8, a processor 50 is taken as an example; the processor 50, the memory 51, the input device 52 and the output device 53 in the electronic device can be connected by a bus or other means, and the connection by a bus is taken as an example in FIG.

As a computer-readable storage medium, the memory 51 can be used to store software programs, computer-executable programs and modules, such as modules corresponding to the receiving device and/or the sending device in the embodiments of the present application (the acquisition module 601 and the detection module 602, and/or, acquiring module 701 and sending module 702). The processor 50 executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 51, ie, implements the above-mentioned receiving method and/or sending method.

The memory 51 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the electronic device, and the like. In addition, the memory 51 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, memory 51 may further include memory located remotely from processor 50, which may be connected to the electronic device through a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

The input device 52 may be used to receive input numerical or character information, and to generate key signal input related to user settings and function control of the electronic device. The output device 53 may include a display device such as a display screen.

Embodiments of the present application further provide a storage medium containing computer-executable instructions, where the computer-executable instructions are used to execute a receiving method when executed by a computer processor, and the method includes:

Get the merged vector W;

And/or, the computer-executable instructions, when executed by a computer processor, are used to perform a method of sending, the method comprising:

obtaining first data and P pilots;

sending the first data and the P pilots;

From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software and necessary general-purpose hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation manner . Based on this understanding, the technical solutions of the present application can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in a computer-readable storage medium, such as a floppy disk of a computer , read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including several instructions to make a computer device (which can be a personal computer , server, or network device, etc.) to execute the methods described in the various embodiments of this application.

It is worth noting that, in the embodiments of the above software device, the included units and modules are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, each function The specific names of the units are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present application.

Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, functional modules/units in the systems, and devices can be implemented as software, firmware, hardware, and appropriate combinations thereof.

In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be composed of several physical components Components execute cooperatively. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit . Such software may be distributed on computer-readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As known to those of ordinary skill in the art, the term computer storage media includes both volatile and nonvolatile implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules or other data flexible, removable and non-removable media. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridges, magnetic tape, magnetic disk storage or other magnetic storage devices, or may Any other medium used to store desired information and which can be accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and can include any information delivery media, as is well known to those of ordinary skill in the art .

Some embodiments of the present application have been described above with reference to the accompanying drawings, which are not intended to limit the scope of the right of the present application. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and essence of the present application shall fall within the scope of the right of the present application.

Claims

A method of receiving, comprising:

Get the merged vector W;

The detection is performed according to the combined vector W, and the detection result is obtained.
The method according to claim 1, wherein the merged vector W includes X vectors, each of which is composed of a specified N elements of a row vector or a column vector in a specified matrix, wherein X is greater than or equal to 1 is an integer of , N is an integer greater than 1, and the specified matrix includes at least one of the following: a discrete Fourier transform matrix and an inverse discrete Fourier transform matrix.
The method of claim 1, wherein the merged vector W comprises a vector generated from a Kronecker product of a first set of vectors and a second set of vectors, wherein the first set of vectors comprises at least one vector and Each vector consists of the specified N1 elements of a row or column vector in the first specified matrix, the second set of vectors contains at least one vector and each vector consists of a row or column vector in the second specified matrix The specified N2 elements of , N1 is an integer greater than or equal to 1, N2 is an integer greater than or equal to 1, the first specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix, the first Two specified matrices include discrete Fourier transform matrices or inverse discrete Fourier transform matrices.
The method of claim 1, wherein the combined vector W comprises:

or,

Among them, g is at least one value in the set [0,1,2,...,M-1], θ=2π/M, N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to The product of N and F, where F is an integer greater than or equal to 1, and j is an imaginary unit.
The method of claim 1, wherein the combined vector W comprises:

or,

Wherein, g 1 is at least one value in the set [0,1,2,...,M 1 -1], θ 1 =2π/M 1 , N 1 is an integer greater than or equal to 1, and M 1 is greater than or equal to An integer of N 1 , or, M 1 is equal to the product of N 1 and F 1 , F 1 is an integer greater than or equal to 1, and g 2 is at least one of the set [0,1,2,...,M 2 -1] value, θ 2 =2π/M 2 , N 2 is an integer greater than or equal to 1, M 2 is an integer greater than or equal to N 2 , or, M 2 is equal to the product of N 2 and F 2 , and F 2 is greater than or equal to an integer of 1,
is the Kronecker product, and j is the imaginary unit.
The method according to claim 1, wherein the obtaining the merged vector W comprises: obtaining the merged vector W from the merged vector set S, wherein the merged vector set S comprises:

a vector of the specified N elements for each row or column vector in the specified matrix; or,

A vector in a matrix generated from the Kronecker product of a first matrix and a second matrix, where the first matrix includes a vector of the specified N1 elements of each row or column vector in the first specified matrix , the second matrix includes a vector formed by the specified N2 elements of each row vector or column vector in the second specified matrix;

Wherein, N is an integer greater than 1, N1 is an integer greater than or equal to 1, N2 is an integer greater than or equal to 1, the specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix, and the first A specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix, and the second specified matrix includes a discrete Fourier transform matrix or an inverse discrete Fourier transform matrix.
The method according to claim 1, wherein the obtaining the merged vector W comprises: obtaining the merged vector W from the merged vector set S, wherein the merged vector set S comprises:

or,

Among them, g=0,1,2,...,M-1, θ=2π/M, N is an integer greater than 1, M is an integer greater than or equal to N, or, M is equal to the product of N and F, and F is Integer greater than or equal to 1, j is an imaginary unit.
The method according to claim 1, wherein the obtaining the merged vector W comprises: obtaining the merged vector W from the merged vector set S, wherein the merged vector set S comprises:

or,

Wherein, g 1 =0,1,2,...,M 1 -1, θ 1 =2π/M 1 , N 1 is an integer greater than or equal to 1, M 1 is an integer greater than or equal to N 1 , or, M 1 is equal to the product of N 1 and F 1 , F 1 is an integer greater than or equal to 1, g 2 =0,1,2,...,M 2 -1, θ 2 =2π/M 2 , N 2 is greater than or equal to an integer of 1, M 2 is an integer greater than or equal to N 2 , or, M 2 is equal to the product of N 2 and F 2 , and F 2 is an integer greater than or equal to 1,
is the Kronecker product, and j is the imaginary unit.
The method according to claim 1, wherein the obtaining the merged vector W comprises: acquiring the identified merged vector from the merged vector set S by identifying the merged vector, and using the identified merged vector as the merged vector W, wherein, Obtain the identified merged vector from the merged vector set S by identifying the merged vector, including:

Determine the identification metric for each merged vector S t in the merged vector set S

Obtain corresponding D merged vectors as the identified merged vectors according to the value ordering of the identification metrics A t of each merged vector S t ;

Among them, 1<=t<=T, T is the number of merged vectors in the merged vector set S, D is an integer greater than or equal to 0, () H represents the conjugate transpose, () -1 represents the inversion operation, R is the covariance matrix or correlation matrix of the received signal, or R is the covariance matrix or correlation matrix of the signal, interference, and noise.
The method according to claim 1, wherein the obtaining the merged vector W comprises: obtaining the merged vector V, and obtaining the merged vector W according to the merged vector V, wherein the merged vector V includes at least one vector.
The method according to claim 10, wherein the obtaining of the combined vector V comprises at least one of the following:

Obtain the identified merged vector from the merged vector set S by merging vector identification, and use the identified merged vector as the merged vector V;

Obtain a merged vector U, and obtain a merged vector V according to the merged vector U, wherein the merged vector U includes at least one vector;

The merged vector V is obtained from the merged vector set S according to a preset method.
The method according to claim 10, wherein the obtaining the merged vector W according to the merged vector V comprises:

Obtain each merged vector S t in the merged vector set S;

get the coefficient C t ;

Obtain the updated merged vector V t according to the merged vector V, the merged vector S t and the coefficient C t ;

determine the identification metric of the merged vector V t

Obtain corresponding E merging vectors as merging vectors W according to the value ordering of the identification metrics B t of the respective merging vectors V t ;

Among them, 1<=t<=T, T is the number of merged vectors in the merged vector set S, E is an integer greater than or equal to 0, () H represents the conjugate transpose, () -1 represents the inversion operation, R is the covariance matrix or correlation matrix of the received signal, or R is the covariance matrix or correlation matrix of the signal, interference, and noise.
The method according to claim 12, wherein the obtaining coefficient C t includes at least one of the following:

Get from the specified set of coefficients.
The method according to claim 10, wherein the obtaining a merged vector V, and obtaining the merged vector W according to the merged vector V, comprises: the merged vector V includes K vectors V 1 , V 2 , . .., V K , the combined vector W=(e 1 *V 1 +e 2 *V 2 +...+e K *V K )/f, where K is an integer greater than or equal to 1, e 1 , e 2 , ..., e K are coefficients corresponding to V 1 , V 2 , ..., V K respectively, and f is an adjustment factor.
The method according to claim 1, wherein the detecting according to the combined vector W comprises at least one of the following:

Taking the product of the conjugate transpose WH of the combined vector W and the received signal as the combined signal;

The product of the combined vector W and the received signal is taken as a combined signal.
The method according to claim 1, wherein the detecting according to the combined vector W comprises at least one of the following:

Obtain the product of the conjugate transpose WH of the combined vector W and the inverse matrix of the matrix R, and use the product of the product and the received signal as the combined signal;

Obtain the product of the combined vector W and the inverse matrix of the matrix R, and use the product of the product and the received signal as a combined signal;

The matrix R is a covariance matrix or a correlation matrix of a received signal, or a covariance matrix or a correlation matrix of a signal, interference, and noise.
The method of claim 10, further comprising:

The detection is performed according to the combined vector V, and the detection result is obtained.
The method according to claim 1, wherein the detection result includes at least one of the following information:

Payload, identification information, pilot information, sequence information, transmission resource information.
A method of sending, including:

obtaining first data and P pilots;

sending the first data and the P pilots;

Wherein, P is an integer greater than or equal to 0, the first data includes at least one of the following information: identification information, payload, information of the P pilots, sequence information, transmission resource information, the first data The data is detected according to the merged vector W.
A receiving device, comprising:

The acquisition module is used to acquire the merged vector W;

A detection module, configured to perform detection according to the combined vector W, and obtain a detection result.
A sending device, comprising:

an acquisition module for acquiring the first data and the P pilots;

a sending module, configured to send the first data and the P pilots;

Wherein, P is an integer greater than or equal to 0, the first data includes at least one of the following information: identification information, payload, information of the P pilots, sequence information, transmission resource information, the first data The data is detected according to the merged vector W.
An electronic device comprising:

one or more processors;

memory for storing one or more programs,

When the one or more programs are executed by the one or more processors, the one or more processors implement the receiving method according to any one of claims 1-18 and/or claim 19 the sending method described above.
A computer-readable storage medium on which a computer program is stored, wherein, when the computer program is executed by a processor, the receiving method according to any one of claims 1-18 and/or the method according to claim 19 is implemented delivery method.