CN112272151A

CN112272151A - Channel estimation method and device

Info

Publication number: CN112272151A
Application number: CN202011175941.0A
Authority: CN
Inventors: 马静艳; 张忠皓; 冯毅; 李福昌; 高帅
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2020-10-28
Filing date: 2020-10-28
Publication date: 2021-01-26
Anticipated expiration: 2040-10-28
Also published as: CN112272151B

Abstract

The embodiment of the application provides a channel estimation method and a channel estimation device, relates to the technical field of communication, and solves the technical problem that the existing channel estimation method cannot accurately estimate a channel of a mixed forming architecture. The method comprises the following steps: the receiving end executes a first operation: determining first data received under the condition of adopting a current weighting vector; performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data; the receiving end updates the weighting vector and executes a first operation according to the updated weighting vector until determining N_aA second data; the base station is a receiving end or a transmitting end; the receiving end is according to N_aThe second data determines a data matrix between the transmitting end and the receiving end; and determining channel estimation between the transmitting end and the receiving end according to the data matrix. The channel estimation method is used for estimating the channel of the hybrid forming architecture.

Description

Channel estimation method and device

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a channel estimation method and apparatus.

Background

In the 5G technology, high frequency bands such as millimeter waves, submillimeter waves and the like are the current main research directions. The high frequency band means higher propagation loss. To compensate for the higher propagation loss, enhanced coverage is typically achieved with very large scale array antennas.

Based on the consideration of resource cost, the ultra-large scale array antenna usually adopts a digital-analog hybrid forming architecture. For a very large-scale array antenna with a digital-analog hybrid forming architecture, in the prior art, channel estimation between a base station and a terminal is completed by utilizing reciprocity of uplink and downlink channels (constructed by radio frequency modules of the base station and the terminal).

However, the radio frequency module of the terminal has non-ideal characteristics, and may have a certain influence on signals, thereby causing different signal fading of the uplink and downlink channels, i.e. affecting reciprocity of the uplink and downlink channels. Therefore, the existing channel estimation method has certain estimation error and is not accurate enough.

Disclosure of Invention

The application provides a channel estimation method and a channel estimation device, which solve the technical problem that the existing channel estimation method cannot accurately estimate a channel between a base station and a terminal.

In order to achieve the purpose, the technical scheme is as follows:

in a first aspect, a channel estimation method is provided, including: the receiving end executes a first operation: determining first data received under the condition of adopting a current weighting vector; performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data; the receiving end updates the weighting vector and executes a first operation according to the updated weighting vector until determining N_aA second data, N_aThe number of analog channels corresponding to the digital channels of the base station; the receiving end is according to N_aThe second data determines a data matrix between the transmitting end and the receiving end; and determining channel estimation between the transmitting end and the receiving end according to the data matrix.

From the above, the receiving end determines N by updating the weighting vector_aA second data according to N_aThe second data enables channel estimation between the transmitting end and the receiving end. Thus, all simulations will be passedThe data of the channel are all calculated, and the accuracy of the data used for channel estimation between the transmitting end and the receiving end is ensured.

Secondly, in the process that the receiving end executes the first operation, the second data is determined by performing dimension reduction and arrangement processing on the received first data. Because the data is subjected to the dimension reduction and arrangement processing, the storage resources required by the receiving end when receiving the data are reduced, and the operation speed is improved.

In summary, the channel estimation method provided by the present application not only ensures the working efficiency of the receiving end, but also ensures the accuracy of channel estimation between the transmitting end and the receiving end.

In a second aspect, a channel estimation apparatus is provided, including: an execution unit and a determination unit. An execution unit to execute a first operation: determining first data received under the condition of adopting a current weighting vector; performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data; a determining unit for updating the weighting vector and performing a first operation according to the updated weighting vector until N is determined_aA second data, N_aThe number of analog channels corresponding to the digital channels of the base station; the base station is the receiving end or the transmitting end; a determination unit for determining the N_aThe second data determines a data matrix between the transmitting end and the receiving end; and the determining unit is also used for determining channel estimation between the transmitting end and the receiving end according to the data matrix.

In a third aspect, a channel estimation apparatus is provided that includes a memory and a processor. The memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus. When the channel estimation device is operating, the processor executes computer-executable instructions stored in the memory to cause the channel estimation device to perform the channel estimation method of the first aspect.

The channel estimation apparatus may be a network device, or may be a part of an apparatus in the network device, such as a system on chip in the network device. The system on chip is configured to support the network device to implement the functions involved in the first aspect and any one of its possible implementations, for example, to receive, determine, and offload data and/or information involved in the above channel estimation method. The chip system includes a chip and may also include other discrete devices or circuit structures.

In a fourth aspect, a computer-readable storage medium is provided, the computer-readable storage medium comprising computer-executable instructions that, when executed on a computer, cause the computer to perform the channel estimation method of the first aspect.

In a fifth aspect, there is provided a computer program product comprising computer instructions which, when run on a computer, cause the computer to perform the channel estimation method as described in the first aspect above and its various possible implementations.

It should be noted that all or part of the above computer instructions may be stored on the first computer readable storage medium. The first computer readable storage medium may be packaged with or separately from a processor of the channel estimation apparatus, which is not limited in this application.

For the description of the second, third, fourth and fifth aspects of the present invention, reference may be made to the detailed description of the first aspect; in addition, for the beneficial effects described in the second aspect, the third aspect, the fourth aspect and the fifth aspect, reference may be made to beneficial effect analysis of the first aspect, and details are not repeated here.

In the present application, the names of the above-mentioned channel estimation devices do not limit the devices or functional modules themselves, and in practical implementations, these devices or functional modules may appear by other names. Insofar as the functions of the respective devices or functional blocks are similar to those of the present invention, they are within the scope of the claims of the present invention and their equivalents.

These and other aspects of the invention will be more readily apparent from the following description.

Drawings

Fig. 1 is a schematic structural diagram of a communication system according to an embodiment of the present application;

fig. 2 is a schematic hardware structure diagram of a channel estimation apparatus according to an embodiment of the present disclosure;

fig. 3 is a schematic hardware structure diagram of another channel estimation apparatus according to an embodiment of the present disclosure;

fig. 4 is a flowchart illustrating a channel estimation method according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of another communication system provided in the embodiment of the present application;

fig. 6 is a schematic flowchart of another channel estimation method according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a communication system according to an embodiment of the present application;

fig. 8 is a flowchart illustrating a channel estimation method according to an embodiment of the present application;

fig. 9 is a flowchart illustrating a channel estimation method according to an embodiment of the present application;

fig. 10 is a flowchart illustrating a channel estimation method according to an embodiment of the present application;

fig. 11 is a schematic structural diagram of a channel estimation device according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

For the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first" and "second" are used to distinguish the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first" and "second" are not used to limit the quantity and execution order.

As described in the background art, in the prior art, antennas on a base station mostly adopt a digital-analog hybrid forming architecture, and when estimating a channel established between the base station and a terminal, the existing channel estimation method estimates the channel based on reciprocity of uplink and downlink channels. Because the radio frequency module of the terminal has non-ideal characteristics, the reciprocity of uplink and downlink channels is influenced, and all the existing channel estimation methods have certain estimation errors and are not accurate enough.

In view of the foregoing problems, an embodiment of the present application provides a channel estimation method, where a receiving end determines N by updating a weighting vector_aA second data according to N_aThe second data enables channel estimation between the transmitting end and the receiving end. Therefore, the data passing through all the analog channels are calculated, and the accuracy of the data used for channel estimation between the transmitting end and the receiving end is ensured.

The channel estimation method provided by the embodiment of the application is suitable for a communication system. Fig. 1 shows a structure of the communication system. As shown in fig. 1, the communication system 10 includes: the base station 11 and the terminal 12, and the base station 11 and the terminal 12 realize communication through multiple antennas.

The base station 11 may be a base station that may include various forms, for example: macro base stations, micro base stations (also referred to as small stations), relay stations, access points, etc. The method specifically comprises the following steps: the base station may be an Access Point (AP) in a Wireless Local Area Network (WLAN), a Base Transceiver Station (BTS) in a global system for mobile communications (GSM) or Code Division Multiple Access (CDMA), a base station (nodeB) in a Wideband Code Division Multiple Access (WCDMA), an evolved node B (eNB or eNodeB) in a Long Term Evolution (LTE), or a relay station or access point, or a vehicle-mounted device, a wearable device, and a next generation node B (the next generation node B, NB) in a future 5G network or a Public Land Mobile Network (PLMN) in a future 5G network.

The terminal device 12 may be a portable electronic device, such as a cell phone, a wearable device with wireless communication capabilities (e.g., a smart watch), etc., that includes other functionality, such as personal digital assistant and/or music player functionality. Exemplary embodiments that may also be portable electronic devices include, but are not limited to, a mount

Or other operating system. The portable electronic device may also be other portable electronic devices such as laptop computers (laptop) with touch sensitive surfaces (e.g., touch panels), etc. It should also be understood that in other embodiments of the present invention, the terminal 12 may not be a portable electronic device, but may be a desktop computer having a touch-sensitive surface (e.g., a touch panel).

It should be noted that the communication system 10 shown in fig. 1 is only one implementation manner provided by the embodiment of the present application, and in practical applications, the base station 11 also communicates with other terminal devices, which is not limited in this application.

The base station 11 and the terminal 12 in fig. 1 comprise the elements comprised by the channel estimation device shown in fig. 2. The hardware configuration of base station 11 and terminal 12 in fig. 1 will be described below by taking the channel estimation apparatus shown in fig. 2 as an example.

Fig. 2 is a schematic diagram illustrating a hardware structure of a channel estimation apparatus according to an embodiment of the present application. As shown in fig. 2, the channel estimation apparatus includes a processor 21, a memory 22, a communication interface 23, and a bus 24. The processor 21, the memory 22 and the communication interface 23 may be connected by a bus 24.

The processor 21 is a control center of the channel estimation apparatus, and may be a single processor or a collective term for a plurality of processing elements. For example, the processor 21 may be a Central Processing Unit (CPU), other general-purpose processors, or the like. Wherein a general purpose processor may be a microprocessor or any conventional processor or the like.

For one embodiment, processor 21 may include one or more CPUs, such as CPU 0 and CPU 1 shown in FIG. 2.

The memory 22 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that may store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that may store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

In a possible implementation, the memory 22 may exist separately from the processor 21, and the memory 22 may be connected to the processor 21 via a bus 24 for storing instructions or program codes. The processor 21, when calling and executing instructions or program codes stored in the memory 22, can implement the channel estimation method provided by the embodiment of the present invention.

In another possible implementation, the memory 22 may also be integrated with the processor 21.

And a communication interface 23 for connecting with other devices through a communication network. The communication network may be an ethernet network, a radio access network, a Wireless Local Area Network (WLAN), or the like. The communication interface 23 may include a receiving unit for receiving data, and a transmitting unit for transmitting data.

The bus 24 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 2, but it is not intended that there be only one bus or one type of bus.

It should be noted that the structure shown in fig. 2 does not constitute a limitation to the channel estimation apparatus. The channel estimation apparatus may include more or fewer components than shown, or some components may be combined, or a different arrangement of components than shown in fig. 2.

Fig. 3 shows another hardware configuration of the channel estimation apparatus in the embodiment of the present application. As shown in fig. 3, the channel estimation apparatus may include a processor 31 and a communication interface 32. The processor 31 is coupled to a communication interface 32.

The function of the processor 31 may refer to the description of the processor 21 above. The processor 31 also has a memory function, and the function of the memory 22 can be referred to.

The communication interface 32 is used to provide data to the processor 31. The communication interface 32 may be an internal interface of the channel estimation device, or may be an external interface (corresponding to the communication interface 23) of the channel estimation device.

It is noted that the structure shown in fig. 2 (or fig. 3) does not constitute a limitation of the channel estimation device, which may include more or less components than those shown in fig. 2 (or fig. 3), or combine some components, or a different arrangement of components, in addition to those shown in fig. 2 (or fig. 3).

The following describes the channel estimation method provided in the embodiment of the present application in detail with reference to the communication system shown in fig. 1 and the channel estimation device shown in fig. 2 (or fig. 3).

Fig. 4 is a flowchart illustrating a channel estimation method according to an embodiment of the present application. As shown in fig. 4, the channel estimation method includes the following S401-S404.

S401, the receiving end executes a first operation: determining first data received under the condition of adopting a current weighting vector; and performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data.

The receiving end may be a base station or a terminal. And when the receiving end is a base station, the transmitting end is a terminal. When the receiving end is a terminal, the base station is a transmitting end. The preset rules comprise a conjugate transpose algorithm and a vectorization operator algorithm.

The weight vector includes a transmit weight vector and a receive weight vector. The weight vector may be constructed in advance by the transmitting end and stored. Similarly, the weighting vector may also be constructed and stored in advance by the receiving end.

It should be noted that, in the process of transmitting a signal at the transmitting end and receiving a signal at the receiving end, if the transmitting end has an analog channel, the transmitting end needs to transmit a signal using a transmission weight vector. Similarly, if there is an analog channel at the receiving end, the receiving end needs to receive the signal using the receiving weight vector.

In a possible implementation manner, if an analog channel exists at the transmitting end and an analog channel also exists at the receiving end, when the receiving end performs a first operation to determine received first data, the current weighting vector used by the receiving end includes a transmitting weighting vector and a receiving weighting vector.

S402, the receiving end updates the weighting vector and executes a first operation according to the updated weighting vector until determining N_aAnd second data.

Wherein N is_aThe number of analog channels corresponding to the digital channels of the base station.

It should be noted that the number of analog channels corresponding to each digital channel in the base station is the same.

In one possible implementation manner, the transmitting end is a base station, the receiving end is a terminal, an antenna of the base station includes a digital channel and an analog channel, and the terminal only has the digital channel. The terminal stores the transmission weighting vector in advance, and the number of the transmission weighting vectors is the number of the analog channels corresponding to one digital channel in the base station. The terminal sequentially switches all the transmission weight vectors and performs a first operation until it is determined that N is present_aAnd second data.

S403, the receiving end is according to N_aSecond data for determining the transmitting end and the receiving endAnd data matrix between the receiving ends.

A possible implementation way, the receiving end is according to N_aAnd determining a data matrix between the transmitting end and the receiving end by transposition operation of the second data.

S404, the receiving end determines channel estimation between the transmitting end and the receiving end according to the data matrix.

According to a possible implementation mode, a receiving end determines channel estimation between a base station and a terminal according to a data matrix, a weighting vector and the number of base station analog channels.

The embodiment of the application provides a channel estimation method, which comprises the following steps: the receiving end executes a first operation: determining first data received under the condition of adopting a current weighting vector; performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data; the receiving end updates the weighting vector and executes a first operation according to the updated weighting vector until determining N_aA second data, N_aThe number of analog channels corresponding to the digital channels of the base station; n is a radical of_aIs a positive integer; the receiving end is according to the N_aThe second data determines a data matrix between the transmitting end and the receiving end; and determining channel estimation between the transmitting end and the receiving end according to the data matrix.

From the above, the receiving end determines N by updating the weighting vector_aA second data according to N_aThe second data enables channel estimation between the transmitting end and the receiving end. Therefore, the data passing through all the analog channels are calculated, and the accuracy of the data used for channel estimation between the transmitting end and the receiving end is ensured.

Optionally, the channel estimation method provided in this embodiment of the present application may also be applied to the communication architecture shown in fig. 5, where fig. 5 is a specific structure of each device in the system in fig. 1.

As shown in FIG. 5, the base station includes a baseband data processing module, a digital-to-analog conversion module, and digital channels 1-N connecting the baseband data processing module and the digital-to-analog conversion module_dAnalog shaped module 1-N connected to digital channel_dEach analog shaped module comprises analog channels 1-N_a. The terminal includes digital channels 1-N_u，N_a、N_dAnd N_uAre all positive integers.

Based on the communication architecture shown in fig. 5, the base station and the terminal may pre-define the downlink channel matrix H_DLAnd an uplink channel matrix H_UL. To facilitate the derivation and explanation of the formula, define:

wherein

A downlink channel matrix representing Na analog channels corresponding to the m-th digital channel,

representing the uplink channel matrix of Na analog channels corresponding to the mth digital channel, wherein the dimensions of the uplink and downlink channel matrices are N_u×N_a，“[·]^H"denotes a conjugate transpose operation. For convenience of presentation, in describing the downlink channel estimation procedure, H_mTo represent

Illustrating uplink channel estimationWhen counting step, H_mTo represent

If the base station is a transmitting end and the terminal is a receiving end, the channel estimation method provided by the present application is as shown in embodiment 1 below.

Embodiment 1, estimation is carried out on a downlink channel.

Both the base station and the terminal may pre-construct the weighting vectors before implementing the method.

Specifically, the base station and the terminal construct the dimension N by traversing the wave beams_a X 1 of mutually orthogonal first set of weight vectors and dimension N_uA second set of mutually orthogonal weight vectors of x 1; the first set of weight vectors includes

Two sets of weight vectors include

For any m ≠ n,

||w_T,m||²＝||w_T,n||²＝N_a，m＝1，2，…，N_a，n＝1，2，…，N_a。

for any m ≠ n,

||w_R,m||²＝||w_R,n||²＝N_u；m＝1，2，…，N_u；n＝1，2，…，N_u；||·||²2, expressing 2 norm operation; the first set of weight vectors and the second set of weight vectors are weighted vectors.

Terminal determining transmission weighting matrix

The transmit weighting matrix satisfies

Since the transmission weighting matrix is a full rank matrix, then

Terminal determining receiving weighting matrix

The receiving weight matrix satisfies

Since the receiving weight matrix is a full rank matrix, then

Wherein, H represents the conjugate transpose,

represents N_a×N_aThe dimension-unit matrix is a matrix of the dimension units,

represents N_u×N_uA dimension unit matrix.

Before implementing the method, both the base station and the terminal can construct the downlink reference signal in advance.

Specifically, the base station and the terminal construct N_dThe downlink reference signals with equal power and mutual independence

And is

For any m ≠ n,

since the actual channel estimation is performed in the digital domain, the processed data is typically discrete data, and thus s_m(t)＝s_m＝[s_m1,s_m2,…,s_mK]。

Determining a downlink reference signal matrix S:

where t denotes the time, E denotes the mathematical expectation,

represents the reference signal power, defaults to 1 [ ·]^TRepresenting a transposition operation, K representing the length of the sequence of reference signals, reference signal s_mSignal sequences of a particular nature, such as ZC sequences, may be constructed for use in mapping to individual transmit channels in the frequency domain for channel amplitude and phase equalization and calibration.

Based on the communication system architecture shown in fig. 5, referring to fig. 6, a flowchart of another channel estimation method provided in the embodiment of the present application is shown, where the channel estimation method includes the following steps S501 to S506.

S501, the terminal determines first data received by the terminal according to a predefined downlink channel matrix, the number of digital channels of the base station, a current transmission weighting vector, a reference signal and downlink channel noise.

Specifically, the terminal determines the first data received by the terminal according to the following formula 7.

Wherein the content of the first and second substances,

representing the Kronecker product operation, N_DL,vWhich is indicative of the noise of the downlink channel,

represents N_d×N_dThe dimension-unit matrix is a matrix of the dimension units,

the general assumption is additive white Gaussian noise and is uncorrelated with the reference signal S, i.e. satisfies

Denotes the Nth_uThe noise corresponding to the digital channel of an individual user,

a conjugate transpose operation of the noise representing the digital channel of the nth user.

And S502, the terminal performs dimensionality reduction on the first data according to the conjugate transpose operation of the reference signal to obtain third data after dimensionality reduction.

Specifically, the terminal determines the third data according to formula 8, and formula 8 is obtained by multiplying S by formula 7 on the left and right sides simultaneously^HAnd (4) determining.

Wherein, Y_mRepresenting the transmit weight vector as w_T,mAnd then, the terminal receives the third data after the dimension reduction of the first data.

The step is used for carrying out dimensionality reduction processing on the data when the terminal receives the first data according to the current emission weighted vector, and the data dimensionality is N_uDecrease of xK to N_u×N_d. In general, K > N_dDue to the factThe step can reduce the storage resource and improve the operation speed.

And S503, the terminal rearranges the third data through vectorization operator operation and conjugate transpose operation to obtain second data.

Specifically, the terminal constructs a formula 9 based on the formula 1 and the formula 8, and rearranges the third data through the formula 9 to determine the second data.

Wherein vec (·) denotes a vectorization operator, vec (A)_M×N) Is used to arrange a matrix a of dimension M x N, stacked in columns, into a vector of dimension MN x 1.

Representing the conjugate transpose operation of the downlink channel matrix.

S504, the terminal updates the weighting vector and executes a first operation according to the updated weighting vector until the N is determined_aAnd second data.

Wherein the first operation is the above steps S501-S503.

In a possible implementation manner, the base station switches all the transmission weighting vectors to send reference signals in sequence, and the terminal receives and switches the transmission weighting vectors w based on the first operation_T,mLast N_aAnd second data.

S505, the terminal is according to N_aAnd determining a data matrix between the transmitting end and the receiving end by the second data.

A possible implementation manner, the terminal is according to N_aThe second data determines a data matrix by equation 11.

S506, the terminal determines channel estimation between the transmitting end and the receiving end according to the data matrix.

One possible implementation is to determine the channel estimation between the base station and the terminal according to the data matrix, the transmit weight vector, and the number of analog channels corresponding to the digital channels of the base station.

Specifically, the terminal determines the channel estimate based on equation 12 below.

Wherein the content of the first and second substances,

is estimated for the downlink channel of the communication system.

The terminal in the above embodiment 1 only includes a digital channel, and based on different terminals, another channel estimation method provided in the embodiments of the present application is as shown in the following embodiment 2.

Example 2: estimating for downlink channel

Referring to fig. 7, a base station is a transmitting end, and a terminal is a receiving end. The terminal comprises N_uAn analog channel, N_uEach analog channel corresponds to a digital channel. The base station is the same as in fig. 5 and is not described here again.

Before the embodiment is implemented, both the base station and the terminal may pre-construct the weighting vector and the downlink reference signal, which is not described herein with reference to embodiment 1.

Referring to fig. 8, a flowchart of another channel estimation method provided in the embodiment of the present application is shown, where the channel estimation method includes the following steps S601 to S608.

S601, the terminal executes a second operation: and determining first data received by the terminal according to the predefined downlink channel matrix, the number of digital channels of the base station, the current transmitting weight vector, the current receiving weight vector, the reference signal and the downlink channel noise.

Specifically, the terminal determines the first data based on the following equation 13.

Wherein m is 1,2, …, N_a，n＝1,2,…,N_u，n_m,nIs the noise of the first downlink channel, the noise of the first downlink channel is the noise in the channel formed by the mth analog channel of the base station and the nth model channel of the terminal, x_m,nWeighting vector for transmission as w_T,mThe received weight vector is

The first data received by the terminal. Referring to embodiment 1, the downlink channel noise is uncorrelated with the reference signal.

And S602, the terminal performs dimensionality reduction on the first data through conjugate transpose operation of the reference signal to obtain third data after dimensionality reduction.

Specifically, the terminal determines the third data by formula 14, and formula 14 is obtained by multiplying S by formula 13 on both sides^HAnd (4) determining.

Further, the terminal converts formula 14 into formula 15 according to formula 1.

Wherein, y_m,nExpressed as a transmit weight vector of w_T,mThe received weight vector is

And the third data after the dimensionality reduction of the first data received by the terminal.

The step is used for reducing the dimension of the received data from 1 xK to 1 xN_dThereby reducing the amount of data received at the receiving endThe required storage resource improves the operation speed.

S603, the terminal updates the receiving weight vector and executes a second operation according to the updated receiving weight vector until determining N_uAnd third data.

The steps S602 to S603 correspond to the second operation according to the embodiment of the present application.

In one possible implementation, the base station selects 1 transmit weight vector w_T,mTerminal sequential switching N_uReceiving the weighted vector to make the terminal determine N according to the second operation_uAnd third data.

S604, the terminal is according to N_uThe third data determines fourth data.

The fourth data is data determined by the terminal when the base station adopts the current transmitting weight vector and the terminal switches all receiving weight vectors.

Specifically, the terminal determines the fourth data according to equation 16.

And S605, the terminal rearranges the fourth data through the vectorization operator operation and the conjugate transpose operation to obtain second data.

Specifically, the second data is determined according to equation 17.

S606, the terminal updates the weighting vector and executes a first operation according to the updated weighting vector until determining N_aAnd second data.

The steps S601 to S605 correspond to the first operation according to the embodiment of the present application.

In a possible implementation mode, the base station switches all the transmission weighting vectors in sequence to send reference signals, and the terminal obtains N_aAnd second data.

S607, the terminal is according to N_aAnd determining a data matrix between the transmitting end and the receiving end by the second data.

A possible implementation manner, the terminal is according to N_aThe second data determines a data matrix by equation 18.

S608, the terminal determines channel estimation between the transmitting end and the receiving end according to the data matrix.

The detailed description is shown with reference to step S506, and is not repeated here.

Based on the communication architecture diagram illustrated in fig. 5, if the base station is a receiving end and the terminal is a transmitting end, the channel estimation method provided in the present application is as follows in embodiment 3.

Example 3: estimation is performed for the uplink channel.

Both the base station and the terminal may pre-construct the weighting vectors before implementing the method. This embodiment also requires the construction of a set of dimensions N_uX 1 mutually orthogonal weight vectors, and a set of dimensions N_aX 1, mutually orthogonal weight vectors. Thereby constructing a transmit weight matrix and a receive weight matrix from mutually orthogonal weight vectors.

The weighting vector constructed for the estimation of the uplink channel in this embodiment 3 may refer to the weighting vector constructed in embodiment 1, and in order to distinguish from embodiment 1, this embodiment 3 determines that the transmission weighting matrix is:

determining a receive weighting matrix as:

before implementing the method, both the base station and the terminal can construct the uplink reference signal in advance.

Specifically, the base station and the terminal construct N_dThe uplink reference signals with equal power and mutual independence

Uplink reference signal satisfies

For any m ≠ n,

since the channel estimation is actually performed in the digital domain, the processed data is generally discrete data, and s is therefore the channel estimation method_m(t)＝s_m＝[s_m1,s_m2,…,s_mK]. Determining an uplink reference signal matrix;

where t denotes the time, E denotes the mathematical expectation,

Based on the communication system architecture shown in fig. 5, referring to fig. 9, a flowchart of another channel estimation method provided in the embodiment of the present application is shown, where the channel estimation method includes the following steps S701 to S706.

S701, the base station determines first data received by the base station according to the predefined uplink channel matrix, the number of digital channels of the base station, the current receiving weight vector, the reference signal and the uplink channel noise.

Specifically, the base station determines the first data received by the terminal according to the following formula 21;

wherein N is_UL,vWhich is indicative of the noise of the uplink channel,

the uplink channel noise is generally assumed to be additive white gaussian noise and is uncorrelated with the reference signal S, i.e. satisfies

m＝1,2,…,N_u，n＝1,2,…,N_d。

S702, the base station performs dimensionality reduction on the first data according to the conjugate transpose operation of the reference signal to obtain third data after dimensionality reduction.

Specifically, the base station determines the third data according to the formula 22, and the formula 22 multiplies the left and right sides of the formula 21 by S at the same time^HAnd (4) determining.

Wherein, Y_mDenotes the received weight vector as w_T,mAnd then, the base station receives the third data after the dimension reduction of the first data.

And S703, the base station rearranges the third data through vectorization operator operation and conjugate transpose operation to obtain second data.

Specifically, the base station constructs a formula 23 according to the formula 2 and the formula 22, and rearranges the third data by using the formula 23 to determine the second data.

Wherein the content of the first and second substances,

representing the conjugate transpose operation of the uplink channel matrix.

S704, the base station updates the weighting vector and executes a first operation according to the updated weighting vector until determining N_aAnd second data.

The steps S701 to S703 correspond to a first operation according to the embodiment of the present application.

In one possible implementation, the base station switches all the receiving weight vectors to receive the reference signals in sequence, and the base station switches the transmitting weight vectors w based on the first operation receiving_T,mLast N_aAnd second data.

S705, the base station according to N_aAnd determining a data matrix between the transmitting end and the receiving end by the second data.

Optionally, the base station is according to N_aThe second data determines a data matrix by equation 25.

S706, the base station determines channel estimation between the transmitting end and the receiving end according to the data matrix.

One possible implementation is to determine the channel estimation between the base station and the terminal according to the data matrix, the receive weight vector, and the number of analog channels corresponding to 1 digital channel of the base station.

Specifically, the base station determines the channel estimate based on equation 26 below.

The terminal in the above embodiment 3 only includes a digital channel, and based on different terminals, another channel estimation method provided in the embodiments of the present application is as shown in the following embodiment 4.

Referring to fig. 6, a base station is a receiving end, and a terminal is a transmitting end.

Before the embodiment is implemented, both the base station and the terminal may pre-construct the weighting vector and the uplink reference signal, which is not described herein with reference to the above embodiment 3.

Referring to fig. 10 and fig. 6, a schematic flow chart of another channel estimation method provided in the embodiment of the present application is shown, where the channel estimation method includes the following steps S801 to S808.

S801, the base station executes a second operation: and determining first data received by the base station according to the predefined uplink channel matrix, the number of digital channels of the base station, the current transmitting weight vector, the current receiving weight vector, the reference signal and the uplink channel noise.

Specifically, the base station determines the first data based on the following equation 27.

Wherein m is 1,2, …, N_a，n＝1,2,…,N_uS is an uplink reference signal, and may be any one of the above uplink reference signal matrices, for example, s ═ s₁；n_m,nThe first uplink channel noise is the noise in the channel formed by the mth analog channel of the base station and the nth model channel of the terminal. x is the number of_m,nFor receiving a weight vector of w_T,mThe transmit weight vector is

The first data received by the terminal. The uplink channel noise is uncorrelated with the reference signal.

S802, the base station performs dimensionality reduction on the first data through conjugate transpose operation of the reference signal to obtain third data after dimensionality reduction.

Specifically, the base station determines the third data by formula 28, and formula 28 is multiplied by S simultaneously from the left and right sides of formula 27^HAnd (4) determining.

Further, the base station converts formula 28 into formula 29 according to formula 2.

Wherein, y_m,nExpressed as a received weight vector of w_T,mThe transmit weight vector is

And the third data after the dimensionality reduction of the first data is received by the time base station.

The step is used for carrying out dimensionality reduction processing on the received data, and the dimensionality of the data is N_dDecrease of xK to N_dX 1, thereby reducing the storage resource needed by the base station when receiving data and improving the operation speed.

S803, the base station updates the transmission weighting vector and executes a second operation according to the updated transmission weighting vector until determining N_uAnd third data.

The above steps S801 to S802 correspond to the second operation according to the embodiment of the present application.

In one possible implementation, the base station selects 1 receive weight vector w_T,mTerminal sequential switching N_uThe transmit weight vectors transmit reference signals such that the base station determines N according to the second operation_uAnd third data.

S804, the base station according to N_uThe third data determines fourth data.

The fourth data is data determined by the base station when the base station adopts the current receiving weighting vector and the terminal switches all the transmitting weighting vectors.

Specifically, the base station determines the fourth data according to equation 30.

And S805, the base station rearranges the fourth data through vectorization operator operation and conjugate transpose operation to obtain second data.

Specifically, the base station determines the second data according to equation 31.

S806, the base station updates the weighting vector and executes the first operation according to the updated weighting vector until determining N_aAnd second data.

In one possible implementation, the base station switches all the received weighted vectors in sequence to receive the reference signal and determines N_aAnd second data.

S807, the base station bases on N_aAnd determining a data matrix between the transmitting end and the receiving end by the second data.

In one possible implementation, the base station is based on N_aThe second data determines a data matrix by equation 32.

S808, the base station determines channel estimation between the transmitting end and the receiving end according to the data matrix.

The detailed description is shown with reference to step S706, and is not repeated here.

The scheme provided by the embodiment of the application is mainly introduced from the perspective of a method. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiment of the present application, the channel estimation apparatus may be divided into functional modules according to the method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. Optionally, the division of the modules in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

Fig. 11 is a schematic structural diagram of a channel estimation device 90 according to an embodiment of the present disclosure. The channel estimation device 90 is used to solve the technical problem that the prior art cannot accurately estimate the channel, for example, to perform the channel estimation method shown in fig. 4, 6, 8, 9 or 10. The channel estimation device 90 includes: an execution unit 901 and a determination unit 902.

An execution unit 901, configured to execute a first operation: determining first data received under the condition of adopting a current weighting vector; and performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data. For example, for performing S401 in fig. 4.

A determining unit 902, configured to update the weighting vector and perform a first operation according to the updated weighting vector until N is determined_aA second data, N_aThe number of analog channels corresponding to the digital channels of the base station; the base station is a receiving end or a transmitting end. For example, for performing S402 in fig. 4.

A determining unit 902, further configured to determine according to N_aAnd determining a data matrix between the transmitting end and the receiving end by the second data. For example, for performing S403 in fig. 4.

The determining unit 902 is further configured to determine a channel estimation between the transmitting end and the receiving end according to the data matrix. For example, for performing S404 in fig. 4.

Optionally, if the transmitting end is a base station, the base station includes a digital channel and an analog channel corresponding to each digital channel, the receiving end is a terminal, and the terminal includes a digital channel; the execution unit 901 is specifically configured to: determining first data received by a terminal according to a predefined downlink channel matrix, the number of digital channels of a base station, a current transmission weighting vector, a reference signal and downlink channel noise; performing dimensionality reduction on the first data through conjugate transpose operation of the reference signal to obtain third data subjected to dimensionality reduction; rearranging the third data through vectorization operator operation and conjugate transposition operation to obtain second data; wherein the weight vector comprises a transmit weight vector. The execution unit 901 is configured to execute S501-S503, for example, in conjunction with the communication architecture shown in fig. 5 and the channel estimation method shown in fig. 6.

Optionally, the execution unit 901 is specifically configured to: if the transmitting end is a base station, the base station comprises a digital channel and an analog channel corresponding to each digital channel, the receiving end is a terminal, and the terminal comprises an analog channel and a digital channel corresponding to the analog channel;

then a second operation is performed: determining first data received by a terminal according to a predefined downlink channel matrix, the number of digital channels of a base station, a current transmitting weight vector, a current receiving weight vector, a reference signal and downlink channel noise; performing dimensionality reduction on the first data through conjugate transpose operation of the reference signal to obtain third data subjected to dimensionality reduction; updating the received weighting vector and performing a second operation according to the updated received weighting vector until N is determined_uA third data; according to N_uDetermining fourth data by the third data, wherein the fourth data is the data determined by the terminal when the current transmitting weight vector is adopted by the base station and all receiving weight vectors are switched by the terminal; by vectorization operator operation and conjugate transpose operationAnd processing the fourth data to obtain rearranged second data. For example: in conjunction with the communication architecture shown in fig. 7 and the channel estimation method shown in fig. 8, the execution unit 901 is configured to execute S601-S605.

A determining unit 902, configured to update the transmission weighting vector after the executing unit 901 determines the second data from the fourth data, and execute the first operation according to the updated transmission weighting vector until N is determined_aA second data; wherein the weight vector comprises a transmit weight vector and a receive weight vector. For example, in conjunction with the communication architecture shown in fig. 7 and the channel estimation method shown in fig. 8, the determining unit 902 is configured to perform S606.

Optionally, if the receiving end is a base station, the base station includes a digital channel and an analog channel corresponding to each digital channel, the transmitting end is a terminal, and the terminal includes a digital channel; the execution unit 901 is specifically configured to: determining first data received by the base station according to the predefined uplink channel matrix, the number of digital channels of the base station, the current receiving weight vector, the reference signal and the uplink channel noise; performing dimensionality reduction on the first data through conjugate transpose operation of the reference signal to obtain third data subjected to dimensionality reduction; rearranging the third data through vectorization operator operation and conjugate transposition operation to obtain second data; wherein the weighting vector comprises a receive weighting vector. For example, optionally, in combination with the communication architecture shown in fig. 5 and the channel estimation method shown in fig. 9, the execution unit 901 is configured to execute S701-S703.

Optionally, the execution unit 901 is specifically configured to, if the receiving end is a base station, the base station includes a digital channel and an analog channel corresponding to each digital channel, the transmitting end is a terminal, and the terminal includes an analog channel and a digital channel corresponding to the analog channel; then a second operation is performed: determining first data received by the base station according to the predefined uplink channel matrix, the number of digital channels of the base station, the current transmitting weight vector, the current receiving weight vector, the reference signal and the uplink channel noise; performing dimensionality reduction on the first data through conjugate transpose operation of the reference signal to obtain third data subjected to dimensionality reduction; updating the transmit weight vector and based on the updateThe subsequent transmit weight vector performs a second operation until N is determined_uA third data; according to N_uDetermining fourth data by the third data, wherein the fourth data is data corresponding to the current receiving weighting vector; and rearranging the fourth data through vectorization operator operation and conjugate transposition operation to obtain second data. For example, in conjunction with the communication architecture shown in fig. 7 and the channel estimation method shown in fig. 10, the execution unit 901 is configured to execute S801-S805.

A determining unit 902, configured to update the receiving weight vector after the executing unit 901 determines the second data from the fourth data, and execute the first operation according to the updated receiving weight vector until N is determined_aA second data; wherein the weight vector comprises a transmit weight vector and a receive weight vector. For example, in conjunction with the communication architecture shown in fig. 7 and the channel estimation method shown in fig. 10, the determining unit 902 is configured to perform S806.

Optionally, the determining unit 902 is specifically configured to determine channel estimation between the base station and the terminal according to the data matrix, the weighting vector, and the number of analog channels corresponding to the digital channels of the base station. For example, in connection with fig. 4, the determining unit 902 is configured to perform S403-S404.

As an example, in connection with fig. 11, the determining unit 902 in the channel estimation apparatus implements the same function as the processor 21 in fig. 2.

Embodiments of the present application also provide a computer-readable storage medium, which includes computer-executable instructions. When the computer executes the instructions to run on the computer, the computer is caused to execute the steps executed by the channel estimation device in the channel estimation method provided by the above embodiment.

The embodiments of the present application further provide a computer program product, where the computer program product can be directly loaded into a memory and contains software codes, and the computer program product can be loaded into and executed by a computer to implement the steps performed by the channel estimation device in the channel estimation method provided in the foregoing embodiments.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented using a software program, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The processes or functions according to the embodiments of the present application are generated in whole or in part when the computer-executable instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). Computer-readable storage media can be any available media that can be accessed by a computer or can comprise one or more data storage devices, such as servers, data centers, and the like, that can be integrated with the media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules or units is only one logical function division, and there may be other division ways in actual implementation. For example, various elements or components may be combined or may be integrated into another device, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method of channel estimation, comprising:

the receiving end executes a first operation: determining first data received under the condition of adopting a current weighting vector; performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data;

the receiving end updates the weighting vector and executes the first operation according to the updated weighting vector until determining N_aA second data, N_aThe number of analog channels corresponding to the digital channels of the base station; the base station is the receiving end or the transmitting end; n is a radical of_aIs a positive integer;

the receiving end is according to the N_aSecond data, determining a data matrix between the transmitting end and the receiving end;

and the receiving end determines channel estimation between the transmitting end and the receiving end according to the data matrix.

2. The channel estimation method of claim 1, wherein the transmitting end is the base station, and the base station includes at least one digital channel and an analog channel corresponding to each digital channel; the receiving end is the terminal, and the terminal comprises at least one digital channel;

the determining first data received with a current weighting vector; performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data, wherein the process comprises the following steps:

determining the first data received by the terminal according to a predefined downlink channel matrix, the number of digital channels of the base station, a current transmission weighting vector, the reference signal and downlink channel noise;

performing dimensionality reduction on the first data through conjugate transpose operation of a reference signal to obtain third data subjected to dimensionality reduction;

rearranging the third data through vectorization operator operation and conjugate transpose operation to obtain the second data;

wherein the weight vector comprises the transmit weight vector.

3. The channel estimation method according to claim 1, wherein the transmitting end is the base station, and the base station includes at least one digital channel and an analog channel corresponding to each digital channel; the receiving end is a terminal, and the terminal comprises at least one analog channel and a digital channel corresponding to the analog channel; the current weighting vector comprises a current transmit weighting vector and a current receive weighting vector;

the terminal executes a second operation: determining the first data received by the terminal according to a predefined downlink channel matrix, the number of digital channels of the base station, the current transmitting weight vector, the current receiving weight vector, the reference signal and downlink channel noise; the terminal performs dimensionality reduction on the first data through conjugate transpose operation of a reference signal to obtain third data after dimensionality reduction;

the terminal updates the current receiving weighted vector and executes the second operation according to the updated receiving weighted vector until determining N_uA third data; n is a radical of_uSimulating the number of channels in the terminal; n is a radical of_uIs a positive integer;

the terminal is according to the N_uDetermining fourth data by the third data, wherein the fourth data is determined by the base station by adopting the current transmitting weight vector and the terminal when the terminal switches all receiving weight vectors;

the terminal processes the fourth data through vectorization operator operation and conjugate transpose operation to obtain rearranged second data;

the receiving end updates the weighting vectorAnd executing the first operation according to the updated weighting vector until determining N_aSecond data comprising:

the terminal updates the current transmission weighting vector and executes the first operation according to the updated transmission weighting vector until determining N_aAnd second data.

4. The channel estimation method according to claim 1, wherein the receiving end is the base station, and the base station includes at least one digital channel and an analog channel corresponding to each digital channel; the transmitting terminal is a terminal, and the terminal comprises at least one digital channel; the current weighting vector comprises a current receive weighting vector;

the base station determines the first data received by the base station according to a predefined uplink channel matrix, the number of digital channels of the base station, the current receiving weight vector, the reference signal and uplink channel noise;

the base station performs dimensionality reduction on the first data through conjugate transpose operation of a reference signal to obtain third data after dimensionality reduction;

and the base station rearranges the third data through vectorization operator operation and conjugate transpose operation to obtain the second data.

5. The channel estimation method according to claim 1, wherein the receiving end is the base station, and the base station includes at least one digital channel and an analog channel corresponding to each digital channel; the transmitting terminal is a terminal, and the terminal comprises at least one analog channel and a digital channel corresponding to the analog channel; the current weighting vector comprises a current transmit weighting vector and a current receive weighting vector;

the base station performs a second operation: determining the first data received by the base station according to a predefined uplink channel matrix, the number of digital channels of the base station, the current transmit weight vector, the current receive weight vector, the reference signal, and uplink channel noise;

the base station updates the current transmit weight vector and performs the second operation according to the updated transmit weight vector until N is determined_uA third data; n is a radical of_uSimulating the number of channels in the terminal; n is a radical of_uIs a positive integer;

the base station is according to the N_uDetermining fourth data by the third data, wherein the fourth data is determined by the base station when the current receiving weighting vector is adopted by the base station and all the transmitting weighting vectors are switched by the terminal;

the base station rearranges the fourth data through vectorization operator operation and conjugate transpose operation to obtain the second data;

the receiving end updates the weighting vector and executes the first operation according to the updated weighting vector until determining N_aSecond data comprising:

the base station updates the current receiving weight vector and executes the first operation according to the updated receiving weight vector until determining N_aAnd second data.

6. The channel estimation method according to any of claims 2-5, wherein the determining, by the receiving end, the channel estimation between the transmitting end and the receiving end according to the data matrix comprises:

and the receiving end determines channel estimation between the base station and the terminal according to the data matrix, the weighting vector and the number of analog channels corresponding to the digital channels of the base station.

7. A channel estimation device, comprising: an execution unit and a determination unit;

the execution unit is configured to execute a first operation: determining first data received under the condition of adopting a current weighting vector; performing dimension reduction and arrangement processing on the first data according to a preset rule to determine second data;

the determining unit is used for updating the weighting vector and executing the first operation according to the updated weighting vector until determining N_aA second data, N_aThe number of analog channels corresponding to the digital channels of the base station; the base station is the receiving end or the transmitting end; n is a radical of_aIs a positive integer;

the determining unit is further configured to determine N_aSecond data, determining a data matrix between the transmitting end and the receiving end;

the determining unit is further configured to determine channel estimation between the transmitting end and the receiving end according to the data matrix.

8. The channel estimation device according to claim 7, wherein the transmitting end is the base station, the base station includes at least one digital channel and an analog channel corresponding to each digital channel, the receiving end is the terminal, and the terminal includes at least one digital channel; the execution unit is specifically configured to:

rearranging the third data through vectorization operator operation and conjugate transpose operation to obtain the second data; wherein the weight vector comprises the transmit weight vector.

9. The channel estimation device according to claim 7,

the execution unit is specifically configured to: the transmitting end is the base station, the base station comprises at least one digital channel and an analog channel corresponding to each digital channel, the receiving end is a terminal, and the terminal comprises at least one analog channel and a digital channel corresponding to the analog channel; the current weighting vector comprises a current transmit weighting vector and a current receive weighting vector;

then a second operation is performed: determining the first data received by the terminal according to a predefined downlink channel matrix, the number of digital channels of the base station, the current transmitting weight vector, the current receiving weight vector, the reference signal and downlink channel noise; performing dimensionality reduction on the first data through conjugate transpose operation of a reference signal to obtain third data subjected to dimensionality reduction;

updating the current received weighting vector and executing the second operation according to the updated received weighting vector until determining N_uA third data; n is a radical of_uSimulating the number of channels in the terminal; n is a radical of_uIs a positive integer;

according to said N_uDetermining fourth data by the third data, wherein the fourth data is determined by the base station by adopting the current transmitting weight vector and the terminal when the terminal switches all receiving weight vectors;

processing the fourth data through vectorization operator operation and conjugate transposition operation to obtain rearranged second data;

the determining unit is configured to update the current transmission weighting vector after the executing unit determines the second data by the fourth data, and execute the first operation according to the updated transmission weighting vector until N is determined_aAnd second data.

10. The channel estimation device according to claim 7, wherein the receiving end is the base station, the base station includes at least one digital channel and an analog channel corresponding to each of the digital channels, the transmitting end is a terminal, and the terminal includes at least one digital channel; the execution unit is specifically configured to: the current weighting vector comprises a current receive weighting vector;

determining the first data received by the base station according to a predefined uplink channel matrix, the number of digital channels of the base station, the current reception weighting vector, the reference signal and uplink channel noise;

and rearranging the third data through vectorization operator operation and conjugate transpose operation to obtain the second data.

11. The channel estimation device according to claim 7,

the execution unit is specifically configured to enable the receiving end to be the base station, enable the base station to include at least one digital channel and an analog channel corresponding to each digital channel, enable the transmitting end to be a terminal, and enable the terminal to include at least one analog channel and a digital channel corresponding to the analog channel; the current weighting vector comprises a current transmit weighting vector and a current receive weighting vector;

then a second operation is performed: determining the first data received by the base station according to a predefined uplink channel matrix, the number of digital channels of the base station, the current transmit weight vector, the current receive weight vector, the reference signal, and uplink channel noise; performing dimensionality reduction on the first data through conjugate transpose operation of a reference signal to obtain third data subjected to dimensionality reduction;

updating the current transmit weight vector and performing the second operation based on the updated transmit weight vectorTo determine N_uA third data; n is a radical of_uSimulating the number of channels in the terminal; n is a radical of_uIs a positive integer;

according to said N_uDetermining fourth data by the third data, wherein the fourth data is determined by the base station when the current receiving weighting vector is adopted by the base station and all the transmitting weighting vectors are switched by the terminal;

rearranging the fourth data through vectorization operator operation and conjugate transpose operation to obtain the second data;

the determining unit is configured to update the current receiving weighting vector after the executing unit determines the second data by the fourth data, and execute the first operation according to the updated receiving weighting vector until N is determined_aAnd second data.

12. The channel estimation device according to any of claims 8 to 11, wherein the determining unit is specifically configured to:

and determining channel estimation between the base station and the terminal according to the data matrix, the weighting vector and the number of analog channels corresponding to the digital channels of the base station.