CN116405350A - A channel estimation method and device for a very massive MIMO communication system - Google Patents

Abstract

The invention provides a channel estimation method and a device of a super-large-scale MIMO communication system, wherein an antenna array of a base station of the system is uniformly divided into a plurality of sub-antenna arrays; the method specifically comprises the following steps: designing a combining matrix corresponding to the antenna array by adopting a space-time coding mode, and acting the combining matrix on a phase shifter of a base station; controlling a user terminal to send a pilot signal to a base station so that the base station obtains a corresponding receiving signal; extracting a received signal corresponding to each sub-antenna array based on the received signal; estimating a subchannel corresponding to each sub-antenna array on a link from the user terminal to the base station by using a received signal corresponding to each sub-antenna array; and merging the sub-channels to obtain the channel from the user terminal to the base station. The invention provides a design method of a combining matrix under a mixed pre-coding framework and an estimation method of a space non-stationary channel based on the combining matrix, so that the accuracy of channel estimation is improved.

Description

A channel estimation method and device for ultra-large-scale MIMO communication system

Technical Field

The present invention relates to the technical field of wireless mobile communications, and in particular to a channel estimation method and device for a very large-scale MIMO communication system.

Background Art

In order to meet the growing business needs, the extremely high bandwidth mobile communication technology provided by high frequency bands such as millimeter wave (30GHz-300GHz, adopted by 5G standard) and terahertz (0.1THz-10THz) has become an important technical means for future mobile communication networks. However, in the millimeter wave and terahertz bands with rich spectrum resources, there is serious path loss in wireless propagation. Taking the terahertz signal in the 0.16 THz band as an example, its propagation process will experience severe path loss of up to 80 dB/km. Massive multiple-input multi-output (MIMO) technology is recognized as one of the key technologies to overcome this challenge. Massive MIMO technology forms directional beams with extremely high array gain by configuring ultra-large-scale antenna arrays (such as 256 antennas), which can compensate for the path loss in high frequency bands and improve the spectrum efficiency of the system. Since its proposal, massive MIMO technology has become a research hotspot in academia and industry, and has been officially adopted as the physical layer technology of 5G in the latest 3GPP R15 standard. In future communications, the size of antennas will be further increased, becoming ultra-large-scale MIMO communication systems equipped with thousands of antennas. While being able to form higher gains, the substantial increase in the number of antennas also brings new challenges to communications.

Thanks to the high path attenuation of high-frequency signals, the number of multipaths is usually small in high-frequency communication systems. By converting the received signal from the spatial domain to the angle domain or from the spatial domain to the angle-distance domain through Fourier transform, the specific parameters of each path can be extracted, which greatly facilitates channel estimation. However, due to the huge aperture of ultra-large-scale MIMO, spatial non-stationarity is prevalent in ultra-large-scale MIMO communication systems, that is, different parts of the antenna see different scatterers or users. In traditional channel estimation methods, the assumption of spatial stationarity is implicit, so for the entire array, the parameters of different paths can only be described by angle or angle-distance. In spatial non-stationary systems, the parameters of different paths also need to be added with the corresponding antenna units, which introduces new complexity to channel estimation. This also means that if traditional channel estimation methods are directly used for spatial non-stationary channels, the accuracy of channel estimation will be greatly reduced. (Reference Z. Yuan, J. Zhang, Y. Ji, G. F. Pedersen, and W. Fan, “Spatial non-stationary near-field channel modeling and validation for massive MIMO systems,” IEEE Trans. Antennas Propag., vol. 71, no. 1, pp. 921–933, 2023.)

At present, some studies have been conducted on spatial non-stationary channel estimation, but all of them are based on the full digital precoding framework, which means that the base station can easily extract the received signals of each subarray for processing. However, such methods cannot be used in the hybrid precoding framework of ultra-large-scale MIMO systems, because for the full digital precoding framework, each antenna is connected to an RF chain, and each RF chain obtains the received signal of the corresponding antenna; while for the hybrid precoding framework, the received signal of the RF chain is a mixture of the received signals of each antenna after being acted on by the merging matrix, and cannot be extracted; there is an incompatibility problem between the two. Therefore, it is urgent to provide a non-stationary channel estimation method under the hybrid precoding framework.

Summary of the invention

To solve the above problems, the present invention provides a channel estimation method and device for a very large-scale MIMO communication system, which improves the accuracy of channel estimation by designing a merging matrix under a hybrid precoding framework and an estimation method for a spatial non-stationary channel based on the merging matrix.

In a first aspect, the present invention provides a channel estimation method for a very large-scale MIMO communication system, wherein an antenna array of a base station in the very large-scale MIMO communication system is evenly divided into a plurality of sub-antenna arrays; the method comprises:

A merging matrix corresponding to the antenna array is designed by using a space-time coding method, and the merging matrix is applied to a phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots;

Controlling the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal;

Based on the received signal, extracting the received signal corresponding to each of the sub-antenna arrays;

Using a received signal corresponding to each of the sub-antenna arrays, estimating a sub-channel corresponding to each of the sub-antenna arrays on a link from the user terminal to the base station;

The sub-channels are combined to obtain a channel from the user terminal to the base station.

According to the channel estimation method for a very large-scale MIMO communication system provided by the present invention, the design of a merging matrix corresponding to the antenna array by adopting a space-time coding method includes:

Based on the preset conditions, design the space-time coding matrix;

Generate the merging matrix according to the space-time coding matrix and the merging matrix corresponding to each of the sub-antenna arrays;

The pre-conditions at least include the following requirements:

，

为所述子天线阵列的数目；The number of rows and columns of the space-time coding matrix is

,

is the number of the sub-antenna arrays;

The space-time coding matrix is a full-rank square matrix;

The columns of the space-time coding matrix are mutually orthogonal;

The precision required for phase shifting of elements in the space-time coding matrix is less than a preset precision threshold.

阶Hadamard矩阵。According to the channel estimation method for a very large-scale MIMO communication system provided by the present invention, the space-time coding matrix is

Hadamard matrix of order.

According to the channel estimation method for a very large-scale MIMO communication system provided by the present invention, generating the merging matrix according to the space-time coding matrix and the merging matrix corresponding to each of the sub-antenna arrays includes:

Generate a combination matrix based on the merging matrix corresponding to each of the sub-antenna arrays;

的全1矩阵，得到第一矩阵；Multiply each element in the space-time coding matrix by

The full-1 matrix is obtained to obtain the first matrix;

Multiply the first matrix by the combined matrix to obtain the merged matrix;

，所述合并矩阵的表达式为

，

为第

个所述子天线阵列对应的合并矩阵，

为第

个时隙所述天线阵列对应的合并矩阵，

。Wherein, the expression of the combination matrix is:

, the expression of the merge matrix is

,

For the

The merging matrix corresponding to the sub-antenna arrays,

For the

The merging matrix corresponding to the antenna array in the time slot is:

.

According to the channel estimation method for a very large-scale MIMO communication system provided by the present invention, the received signal corresponding to each of the sub-antenna arrays is determined by the following formula:

；

;

为所述子天线阵列的数目，

为所述空时编码矩阵，

为第

个时隙所述基站在第

个子载波上的接收信号，

为第

个时隙所述基站在第

个子载波上的接收信号中与所述第

个所述子天线阵列对应的部分。in,

is the number of the sub-antenna arrays,

is the space-time coding matrix,

For the

The base station is in the

The received signal on the subcarriers is

For the

The base station is in the

The received signal on the subcarrier is

The part corresponding to the sub-antenna array.

According to the channel estimation method for a very large-scale MIMO communication system provided by the present invention, the sub-channel corresponding to each of the sub-antenna arrays on the link of the base station is estimated by using the received signal corresponding to each of the sub-antenna arrays, including:

The subchannel corresponding to each of the sub-antenna arrays on the link of the base station is estimated by using the pilot signal, a merging matrix corresponding to each of the sub-antenna arrays, and a received signal corresponding to each of the sub-antenna arrays.

According to the channel estimation method for a very large-scale MIMO communication system provided by the present invention, the channel from the user terminal to each of the sub-antenna arrays is estimated by using estimation algorithms including but not limited to OMP and AMP.

In a second aspect, the present invention provides a channel estimation device for a very large-scale MIMO communication system, wherein an antenna array of a base station in the very large-scale MIMO communication system is evenly divided into a plurality of sub-antenna arrays; the device comprises:

A design module is used to design a merging matrix corresponding to the antenna array by using a space-time coding method, and apply the merging matrix to the phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots;

A pilot signal transceiver module, used to control the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal;

An extraction module, configured to extract a received signal corresponding to each of the sub-antenna arrays based on the received signal;

A subchannel estimation module, used to estimate the subchannel corresponding to each of the subantenna arrays on the link from the user terminal to the base station by using the received signal corresponding to each of the subantenna arrays;

The channel estimation module is used to combine the sub-channels to obtain a channel from the user terminal to the base station.

In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the channel estimation method for the ultra-large-scale MIMO communication system as described in the first aspect is implemented.

In a fourth aspect, the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the channel estimation method for the ultra-large-scale MIMO communication system as described in the first aspect.

The present invention provides a channel estimation method and device for a very large-scale MIMO communication system. First, a space-time coding method is used to design a merging matrix corresponding to the antenna array; wherein the antenna array of the base station in the very large-scale MIMO communication system is evenly divided into a plurality of sub-antenna arrays, and the merging matrix makes overall changes to the merging matrix corresponding to each of the sub-antenna arrays in different time slots; secondly, the user terminal is controlled to send a pilot signal to the base station so that the base station obtains a corresponding received signal; then, based on the received signal, the received signal corresponding to each of the sub-antenna arrays is extracted; then, the received signal corresponding to each of the sub-antenna arrays is used to estimate the sub-channel corresponding to each of the sub-antenna arrays on the link from the user terminal to the base station; finally, the sub-channels are merged to obtain the channel from the user terminal to the base station. The present invention adopts the space-time coding idea to design a base station-side merging matrix under a hybrid precoding framework, and designs an estimation method for a spatial non-stationary channel based on the base station-side merging matrix, thereby improving the accuracy of channel estimation.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

FIG1 is a schematic diagram of the structure of a very large-scale MIMO communication system provided by the present invention;

2 is a schematic flow chart of a channel estimation method for a very large-scale MIMO communication system provided by the present invention;

3 is a schematic diagram of simulation effects of the estimation accuracy of the conventional channel estimation-far field, the conventional channel estimation-near field and the method of the present invention provided by the present invention;

FIG4 is a schematic diagram of the structure of a channel estimation device for a very large-scale MIMO communication system provided by the present invention;

FIG5 is a schematic diagram of the structure of an electronic device provided by the present invention;

Reference numerals:

510: processor; 520: communication interface; 530: memory; 540: communication bus.

DETAILED DESCRIPTION

In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

A channel estimation method and apparatus for a very large-scale MIMO communication system of the present invention will be described below in conjunction with FIG. 1 to FIG. 5 .

个天线，

根射频链，用户单天线。系统宽带为

，采用正交频分复用（orthogonalfrequency division multiplexing, OFDM）技术来实现上行传输，其中包含

个子载波，其中心频率表示为

，第

个子载波上的频率可以表示为：

，基站天线间隔设置为中心频率对应载波波长的一半。超大规模MIMO通信系统建模为：FIG1 provides a schematic diagram of the structure of a very large-scale MIMO communication system. As shown in FIG1 , it is assumed that the base station includes

Antennas,

RF chain, single user antenna. System bandwidth is

, using orthogonal frequency division multiplexing (OFDM) technology to achieve uplink transmission, including

subcarriers, whose center frequencies are expressed as

,

The frequency on the subcarrier can be expressed as:

, the base station antenna spacing is set to half the carrier wavelength corresponding to the center frequency. The ultra-large-scale MIMO communication system is modeled as:

；

;

为第

个子载波上的用户接收信号，

为用户终端在第

个子载波上发送的导频信号，

为加性高斯白噪声，

为基站侧合并矩阵（用于移相器），

为第

个子载波从用户终端到基站的信道。In the above formula,

For the

The user receives the signal on the subcarriers.

For user terminals

The pilot signal sent on subcarriers,

is additive white Gaussian noise,

is the base station side merging matrix (for phase shifter),

For the

The channel from the user terminal to the base station has subcarriers.

可以表示为：in,

It can be expressed as:

；

;

为天线阵列中包含的天线总数，

为信道

中包含的路径总数，

和

分别为信道

中第

条路径的角度和距离，

表示信道

中第

条路径的路径增益，

为第

个子载波对应的波数，表达式为

，

为第

个子载波对应的频率，

为光速，

为超大规模MIMO通信系统中天线阵列的导引矢量，

为非平稳现象带来的可视区域向量。In the above formula,

is the total number of antennas in the antenna array,

For Channel

The total number of paths contained in

and

Channel

Middle

The angle and distance of the path,

Indicates channel

Middle

The path gain of the path,

For the

The wave number corresponding to the subcarrier is expressed as

,

For the

The frequency corresponding to the subcarrier is

is the speed of light,

is the steering vector of the antenna array in the ultra-large-scale MIMO communication system,

The visible area vector caused by non-stationary phenomena.

表示为：here,

It is expressed as:

；

;

中的第

个元素的表达式为：

The

The expression for each element is:

；

;

为中心频率子载波对应的波数，

为第

根天线的标号，

为相邻两根天线的间距，

表示第

根天线到用户的距离，

表示信道

中第

条路径的可视区域。in,

is the wave number corresponding to the center frequency subcarrier,

For the

The number of the antenna.

is the distance between two adjacent antennas,

Indicates

The distance from the antenna to the user,

Indicates channel

Middle

The visible area of the path.

信道估计影响），以致传统信道估计方法如果直接用于空间非平稳信道，信道估计精度会大幅降低。但是如果考虑空间非平稳现象，受超大规模天线阵列的影响，信道估计将会变得极度复杂。考虑到在非平稳信道中，某条路径的可视区域通常是连续的一部分子阵面，所以为了进一步简化系统模型，本发明将天线阵列分成若干个子天线阵列来处理，记子天线阵列数为

，

表示按子阵区分的可视区域，所以，可视区域向量可以进一步表示为：In the traditional channel estimation method, the assumption of spatial stationarity is implicit (i.e., the

Channel estimation is affected by the spatial non-stationary channel, so if the traditional channel estimation method is directly used for the spatial non-stationary channel, the channel estimation accuracy will be greatly reduced. However, if the spatial non-stationary phenomenon is taken into account, the channel estimation will become extremely complicated due to the influence of the ultra-large-scale antenna array. Considering that in a non-stationary channel, the visible area of a certain path is usually a continuous part of the sub-array surface, so in order to further simplify the system model, the present invention divides the antenna array into several sub-antenna arrays for processing, and the number of sub-antenna arrays is recorded as

,

Represents the visible area divided by sub-matrix, so the visible area vector can be further expressed as:

；

;

In this case, the non-stationary channel estimation problem from the user terminal to the base station under the hybrid precoding framework will be transformed into the estimation problem of the non-stationary sub-channel corresponding to each sub-antenna array on the link from the user terminal to the base station under the hybrid precoding framework. In view of this, the present invention provides a channel estimation method for a very large-scale MIMO communication system, as shown in FIG2 , in which the antenna array of the base station in the very large-scale MIMO communication system is evenly divided into a plurality of sub-antenna arrays; the method comprises:

S11: designing a merging matrix corresponding to the antenna array by using a space-time coding method, and applying the merging matrix to a phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots;

It can be understood that the phase shifter is used to apply a phase shift of 0 to 360 degrees to the antenna reception signal, that is, to merge the elements corresponding to the matrix A.

S12: Control the user terminal to send a pilot signal to the base station, so that the base station obtains a corresponding received signal;

S13: extracting a received signal corresponding to each of the sub-antenna arrays based on the received signal;

S14: using the received signal corresponding to each of the sub-antenna arrays, estimating the sub-channel corresponding to each of the sub-antenna arrays on the link from the user terminal to the base station;

S15: Merge the sub-channels to obtain a channel from the user terminal to the base station.

The present invention provides a channel estimation method for a very large-scale MIMO communication system, which adopts the space-time coding idea to design a base station-side merging matrix under a hybrid precoding framework, and designs an estimation method for a spatial non-stationary channel based on the base station-side merging matrix, thereby improving the accuracy of channel estimation.

Specifically, the S11 includes:

S11.1: Based on the preset conditions, design the space-time coding matrix;

S11.2: Generate the merging matrix according to the space-time coding matrix and the merging matrix corresponding to each of the sub-antenna arrays;

The pre-conditions at least include the following requirements:

，

为所述子天线阵列的数目；The number of rows and columns of the space-time coding matrix is

,

is the number of the sub-antenna arrays;

The space-time coding matrix is a full-rank square matrix;

The columns of the space-time coding matrix are mutually orthogonal;

The precision required for phase shifting of elements in the space-time coding matrix is less than a preset precision threshold.

阶Hadamard矩阵。Optionally, the space-time coding matrix is

Hadamard matrix of order.

Furthermore, the S11.2 includes:

S11.2.1: Generate a combined matrix based on the merging matrix corresponding to each of the sub-antenna arrays;

的全1矩阵，得到第一矩阵；S11.2.2: Multiply each element of the space-time coding matrix by

The full-1 matrix is obtained to obtain the first matrix;

S11.2.3: Multiply the first matrix by the combined matrix to obtain the merged matrix;

，所述合并矩阵的表达式为

，

为第

个所述子天线阵列对应的合并矩阵，

为第

个时隙所述天线阵列对应的合并矩阵，

。Wherein, the expression of the combination matrix is:

, the expression of the merge matrix is

,

For the

The merging matrix corresponding to the sub-antenna arrays,

For the

The merging matrix corresponding to the antenna array in the time slot is:

.

The present invention changes the practice of randomly generating the merging matrix of each time slot in the traditional channel estimation process, and instead changes the merging matrix on the base station side by sub-array grouping in different time slots in a space-time coding manner. Take the simple case of dividing the base station antenna array into two sub-antenna arrays as an example for explanation:

个时隙，两个子天线阵列对应的合并矩阵分别为

和

，天线阵列对应的合并矩阵

为

，此时基站接收信号可以表示为：For

time slots, the merging matrices corresponding to the two sub-antenna arrays are

and

, the merging matrix corresponding to the antenna array

for

, at this time the base station receiving signal can be expressed as:

；

;

和

被解耦。It can be seen that the channels corresponding to the two sub-antenna arrays

and

Decoupled.

个时隙，按子阵分组对合并矩阵

做整体改变得到

，即两个子天线阵列对应的合并矩阵分别为

和

，天线阵列对应的合并矩阵

为

，此时接收信号则可以表示为：For

time slots, group the merged matrices by sub-array

Make overall changes to get

, that is, the merging matrices corresponding to the two sub-antenna arrays are

and

, the merging matrix corresponding to the antenna array

for

, then the received signal can be expressed as:

；

;

By combining the two received signals, the received signals corresponding to the two sub-antenna arrays can be extracted:

；

;

，基站侧依据已知导频

，合并矩阵

和接收信号

即可恢复信道

。因此在得到两个子天线阵列对应的接收信号时，即可估计出

和

。According to the ultra-large-scale MIMO communication system, during the channel estimation process, the user terminal transmits a known pilot signal.

, the base station side uses the known pilot

, merge matrix

and receive signals

You can restore the channel

Therefore, when the received signals corresponding to the two sub-antenna arrays are obtained, it can be estimated that

and

.

Therefore, we can extend this idea to the case where the array is divided into any number of sub-antenna arrays. In the case where the array is divided into two sub-antenna arrays, the merge matrix design process can be abstracted as follows:

；

;

为设计的空时编码矩阵，利用其对原始合并矩阵

进行分组整体变换，即可获得对应的各时隙合并矩阵。in,

The space-time coding matrix is designed, and the original merging matrix is used

By performing overall transformation of the groups, the corresponding merging matrix of each time slot can be obtained.

，其需要满足如下三个条件：For the space-time coding matrix

, which needs to meet the following three conditions:

1) It needs to be a full-rank square matrix so that the received signal corresponding to each sub-antenna array can be obtained by inversion;

2) The columns need to be orthogonal to each other to eliminate the influence of noise;

3) The required accuracy of element phase shifting should be as small as possible to meet the needs of the actual system.

阶Hadamard矩阵作为空时编码矩阵

。In order to meet these three requirements, the present invention selects

Hadamard matrix of order φ as space-time coding matrix

.

阶Hadamard矩阵为

，其中

，则各阶Hadamard矩阵可以由如下表达式得到：The Hadamard matrix is a matrix composed of 1 and -1, which can be obtained by recursion.

The Hadamard matrix of order is

,in

, then the Hadamard matrices of each order can be obtained by the following expressions:

；

;

个子天线阵列的情况，相应的合并矩阵可以由下式生成：For the base station antenna array, it is divided into

In the case of a sub-antenna array, the corresponding merging matrix can be generated by the following formula:

；

;

由下式生成in

Generated by the following formula

；

;

即为上述第一矩阵。here,

This is the first matrix mentioned above.

Specifically, the received signal corresponding to each of the sub-antenna arrays in S13 is determined by the following formula:

；

;

为所述子天线阵列的数目，

为所述空时编码矩阵，

为第

个时隙所述基站在第

个子载波上的接收信号，

为第

个时隙所述基站在第

个子载波上的接收信号中与所述第个所述子天线阵列对应的部分。in,

is the number of the sub-antenna arrays,

is the space-time coding matrix,

For the

The base station is in the

The received signal on the subcarriers is

For the

The base station is in the

The part of the received signal on the subcarrier corresponding to the th subantenna array.

For the above case where the antenna arrays are divided into two sub-antennas, the operation on the received signal can be abstracted as follows:

；

;

，即可提取对应子天线阵列的接收信号，方便后续进一步处理。It can be seen that by designing the space-time coding matrix

, the received signal of the corresponding sub-antenna array can be extracted to facilitate subsequent further processing.

Correspondingly, when divided into any number of sub-antenna arrays, the operation of receiving signals can be abstracted as follows:

；

;

In this way, the received signal corresponding to each sub-antenna array can be obtained, so as to estimate the channel corresponding to each sub-antenna array respectively.

，合并后可以得到完整信道

。Specifically, in S14-S15, after obtaining the received signal corresponding to each sub-antenna array, the channel of each sub-antenna array can be estimated by using an existing compressed sensing-based algorithm, including but not limited to an orthogonal matching pursuit algorithm (OMP), an approximate message passing algorithm (AMP), etc. After estimating the channel of each sub-antenna array, the estimated sub-channel is obtained as

, after merging, we can get the complete channel

.

The proposed scheme is simulated and verified, considering that the number of base station antennas is 512, the number of subcarriers is 256, the number of users is 4, the number of RF chains is 4, the center frequency is 100 GHz, the bandwidth is 100 MHz, the number of subarrays is 4, and the number of multipaths is 3. FIG3 illustrates a schematic diagram of the simulation effect of the estimation accuracy of the traditional channel estimation-far field, the traditional channel estimation-near field, and the method of the present invention. FIG3 shows the mean absolute error after the NMSE is not normalized. It can be seen that the proposed method can improve the channel estimation accuracy by about 8 dB compared with the traditional channel estimation method.

That is, the channel estimation method proposed in the present invention can effectively identify the spatial non-stationary phenomenon in ultra-large-scale MIMO systems, and can achieve significant improvement in channel estimation accuracy compared to traditional solutions.

In the second aspect, the channel estimation device of the ultra-large-scale MIMO communication system provided by the present invention is described. The channel estimation device of the ultra-large-scale MIMO communication system described below and the channel estimation method of the ultra-large-scale MIMO communication system described above can be referred to each other. FIG4 illustrates a schematic structural diagram of the channel estimation device of the ultra-large-scale MIMO communication system. As shown in FIG4, the device includes:

A design module 21 is used to design a merging matrix corresponding to the antenna array by using a space-time coding method, and apply the merging matrix to the phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots;

A pilot signal transceiver module 22, used to control the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal;

An extraction module 23, configured to extract a received signal corresponding to each of the sub-antenna arrays based on the received signal;

The subchannel estimation module 24 is used to estimate the subchannel corresponding to each of the subantenna arrays on the link from the user terminal to the base station by using the received signal corresponding to each of the subantenna arrays; the channel estimation module 25 is used to merge the subchannels to obtain the channel from the user terminal to the base station.

The present invention provides a channel estimation device for a very large-scale MIMO communication system, adopts the space-time coding idea to design a base station-side merging matrix under a hybrid precoding framework, and designs an estimation method for a spatial non-stationary channel based on the base station-side merging matrix, thereby improving the accuracy of channel estimation.

Based on the above embodiments, as an optional embodiment, the design module includes:

A first design unit, configured to design a space-time coding matrix based on a preset condition;

A generating unit, configured to generate the merging matrix according to the space-time coding matrix and a merging matrix corresponding to each of the sub-antenna arrays;

The pre-conditions at least include the following requirements:

，

为所述子天线阵列的数目；The number of rows and columns of the space-time coding matrix is

,

is the number of the sub-antenna arrays;

The space-time coding matrix is a full-rank square matrix;

The columns of the space-time coding matrix are mutually orthogonal;

The precision required for phase shifting of elements in the space-time coding matrix is less than a preset precision threshold.

阶Hadamard矩阵。Based on the above embodiments, as an optional embodiment, the space-time coding matrix is

Hadamard matrix of order.

Based on the above embodiments, as an optional embodiment, the generating unit includes:

A first generating subunit, configured to generate a combined matrix based on a merging matrix corresponding to each of the sub-antenna arrays;

的全1矩阵，得到第一矩阵；The second generating subunit is used to multiply each element in the space-time coding matrix by

The full-1 matrix is obtained to obtain the first matrix;

A third generating subunit is used for dot multiplication of the first matrix and the combined matrix to obtain the merged matrix;

，所述合并矩阵的表达式为

，

为第

个所述子天线阵列对应的合并矩阵，

为第

个时隙所述天线阵列对应的合并矩阵，

。Wherein, the expression of the combination matrix is:

, the expression of the merge matrix is

,

For the

The merging matrix corresponding to the sub-antenna arrays,

For the

The merging matrix corresponding to the antenna array in the time slot is:

.

Based on the above embodiments, as an optional embodiment, the received signal corresponding to each of the sub-antenna arrays is determined by the following formula:

；

;

为所述子天线阵列的数目，

为所述空时编码矩阵，

为第

个时隙所述基站在第

个子载波上的接收信号，

为第

个时隙所述基站在第

个子载波上的接收信号中与所述第

个所述子天线阵列对应的部分。in,

is the number of the sub-antenna arrays,

is the space-time coding matrix,

For the

The base station is in the

The received signal on the subcarriers is

For the

The base station is in the

The received signal on the subcarrier is

The part corresponding to the sub-antenna array.

Based on the above embodiments, as an optional embodiment, the subchannel estimation module is used to:

The subchannel corresponding to each of the sub-antenna arrays on the link of the base station is estimated by using the pilot signal, the merging matrix corresponding to each of the sub-antenna arrays, and the received signal corresponding to each of the sub-antenna arrays.

Based on the above embodiments, as an optional embodiment, the estimating of the channel from the user terminal to each of the sub-antenna arrays is implemented by using an estimation algorithm including but not limited to OMP and AMP.

In the third aspect, FIG5 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG5, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute a channel estimation method for a very large-scale MIMO communication system, the method comprising: designing a merging matrix corresponding to the antenna array in a space-time coding manner, and applying the merging matrix to the phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots; controlling the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal; extracting a received signal corresponding to each of the sub-antenna arrays based on the received signal; estimating a channel from the user terminal to each of the sub-antenna arrays using the received signal corresponding to each of the sub-antenna arrays; merging the channel from the user terminal to each of the sub-antenna arrays to obtain a channel from the user terminal to the base station.

In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

In a fourth aspect, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the channel estimation method of the ultra-large-scale MIMO communication system provided by the above methods, the method comprising: designing a merging matrix corresponding to the antenna array using a space-time coding method, and applying the merging matrix to the phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots; controlling the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal; based on the received signal, extracting the received signal corresponding to each of the sub-antenna arrays; using the received signal corresponding to each of the sub-antenna arrays, estimating the channel from the user terminal to each of the sub-antenna arrays; merging the channel from the user terminal to each of the sub-antenna arrays to obtain the channel from the user terminal to the base station.

In a fifth aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the channel estimation method of the ultra-large-scale MIMO communication system provided by the above-mentioned methods, the method comprising: designing a merging matrix corresponding to the antenna array in a space-time coding manner, and applying the merging matrix to the phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots; controlling the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal; based on the received signal, extracting the received signal corresponding to each of the sub-antenna arrays; using the received signal corresponding to each of the sub-antenna arrays, estimating the channel from the user terminal to each of the sub-antenna arrays; merging the channel from the user terminal to each of the sub-antenna arrays to obtain the channel from the user terminal to the base station.

The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on this understanding, the above technical solution can be essentially or in other words, the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A channel estimation method for a very large-scale MIMO communication system, characterized in that an antenna array of a base station in the very large-scale MIMO communication system is evenly divided into a plurality of sub-antenna arrays; the method comprising: A merging matrix corresponding to the antenna array is designed by using a space-time coding method, and the merging matrix is applied to the phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots; Controlling the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal; Based on the received signal, extracting the received signal corresponding to each of the sub-antenna arrays; Using a received signal corresponding to each of the sub-antenna arrays, estimating a sub-channel corresponding to each of the sub-antenna arrays on a link from the user terminal to the base station; The sub-channels are combined to obtain a channel from the user terminal to the base station. 2. The channel estimation method for a very large-scale MIMO communication system according to claim 1, wherein the step of designing a merging matrix corresponding to the antenna array by adopting a space-time coding method comprises: Based on the preset conditions, design the space-time coding matrix; Generate the merging matrix according to the space-time coding matrix and the merging matrix corresponding to each of the sub-antenna arrays; The pre-conditions at least include the following requirements: The number of rows and columns of the space-time coding matrix is

,

is the number of the sub-antenna arrays; The space-time coding matrix is a full-rank square matrix; The columns of the space-time coding matrix are mutually orthogonal; The precision required for phase shifting of elements in the space-time coding matrix is less than a preset precision threshold. 3. The channel estimation method for a very large-scale MIMO communication system according to claim 2, wherein the space-time coding matrix is

Hadamard matrix of order. 4. The channel estimation method for a very large-scale MIMO communication system according to claim 2 or 3, characterized in that generating the merging matrix according to the space-time coding matrix and the merging matrix corresponding to each of the sub-antenna arrays comprises: Generate a combination matrix based on the merging matrix corresponding to each of the sub-antenna arrays; Multiply each element in the space-time coding matrix by

The full-1 matrix is obtained to obtain the first matrix; Multiply the first matrix by the combined matrix to obtain the merged matrix; Wherein, the expression of the combination matrix is:

, the expression of the merge matrix is

,

For the

The merging matrix corresponding to the sub-antenna arrays,

For the

The merging matrix corresponding to the antenna array in the time slot is:

. 5. The channel estimation method for a very large-scale MIMO communication system according to claim 4, wherein the received signal corresponding to each of the sub-antenna arrays is determined by the following formula:

; in,

is the number of the sub-antenna arrays,

is the space-time coding matrix,

For the

The base station is in the

The received signal on the subcarriers is

For the

The base station is in the

The received signal on the subcarrier is

The part corresponding to the sub-antenna array. 6. The channel estimation method of the ultra-large-scale MIMO communication system according to claim 1, characterized in that the estimating the sub-channel corresponding to each of the sub-antenna arrays on the link of the base station by using the received signal corresponding to each of the sub-antenna arrays comprises: The subchannel corresponding to each of the sub-antenna arrays on the link of the base station is estimated by using the pilot signal, the merging matrix corresponding to each of the sub-antenna arrays, and the received signal corresponding to each of the sub-antenna arrays. 7. The channel estimation method for a very large-scale MIMO communication system according to claim 6 is characterized in that the estimating of the channel from the user terminal to each of the sub-antenna arrays is implemented using an estimation algorithm including but not limited to OMP and AMP. 8. A channel estimation device for a very large-scale MIMO communication system, characterized in that the antenna array of a base station in the very large-scale MIMO communication system is evenly divided into a plurality of sub-antenna arrays; the device comprises: A design module is used to design a merging matrix corresponding to the antenna array by using a space-time coding method, and apply the merging matrix to the phase shifter of the base station; wherein the merging matrix makes an overall change to the merging matrix corresponding to each of the sub-antenna arrays in different time slots; A pilot signal transceiver module, used to control the user terminal to send a pilot signal to the base station so that the base station obtains a corresponding received signal; An extraction module, configured to extract a received signal corresponding to each of the sub-antenna arrays based on the received signal; A subchannel estimation module, used to estimate the subchannel corresponding to each of the subantenna arrays on the link from the user terminal to the base station by using the received signal corresponding to each of the subantenna arrays; The channel estimation module is used to combine the sub-channels to obtain a channel from the user terminal to the base station. 9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the channel estimation method for the ultra-large-scale MIMO communication system as claimed in any one of claims 1 to 7 is implemented. 10. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the channel estimation method for a very large-scale MIMO communication system as claimed in any one of claims 1 to 7 is implemented.

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