Network equipment and data sending method

Abstract

The invention provides network equipment and a data sending method. The network equipment comprises a BBU (Base Band Unit), an RRU (Radio Remote Unit), an analog demixing network module and an antenna which are connected in sequence, the BBU is used for determining a first beamforming weight matrix corresponding to any group of k antennas, and performing linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix; based on the second beam forming weight matrix, obtaining k paths of data respectively mapped to k antennas, and performing aliasing processing on the k paths of data to obtain k paths of aliasing data; the RRU is used for outputting k paths of aliasing data to the analog unmixing network module through k transmitting channels respectively; and the analog unmixing network module is used for carrying out unmixing processing on the aliasing data output by the k transmitting channels to obtain transmitting data corresponding to the k antennas, and outputting the transmitting data to the corresponding antennas for transmitting. And maximization of channel gain and link performance can be realized.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a network device and a data transmission method. Background Art

[0002] The digital beamforming weights calculated by the non-codebook beamforming algorithm are usually not amplitude-normalized, that is, each transmit channel cannot radiate at full power, resulting in power waste. In order to maximize the use of the radiation power capacity of the transmit channel, the usual practice is to directly normalize the total power of the digital beamforming weights in the full bandwidth, that is, to pull the power of each transmit channel back to the state of full power radiation. However, this power normalization method will destroy the beam pointing accuracy of the beamforming weights, and the matching degree between the weights and the channels will also be damaged to a certain extent. Summary of the invention

[0003] In view of the problems existing in the prior art, the present application provides a network device and a data sending method.

[0004] In a first aspect, the present application provides a network device, including:

[0005] The baseband processing unit BBU, the radio remote unit RRU, the analog demixing network module and the antenna are connected in sequence;

[0006] The BBU is used to: determine a first beamforming weight matrix corresponding to any group of k antennas, and perform linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix; obtain k-channel data mapped to the k antennas respectively based on the second beamforming weight matrix, perform aliasing processing on the k-channel data to obtain k-channel aliased data; output the k-channel aliased data to the RRU; wherein k is an integer greater than or equal to 2;

[0007] The RRU is used to: output k-channel aliased data to the analog demixing network module through k transmission channels respectively;

[0008] The analog demixing network module is used to: demix the aliased data output by the k transmission channels to obtain the transmission data corresponding to the k antennas, and output the transmission data to the corresponding antennas for transmission.

[0009] In some embodiments, determining a first beamforming weight matrix corresponding to any group of k antennas includes:

[0010] In the case where the first beamforming weight matrix is ​​set to satisfy a first weight distribution condition, determining the first beamforming weight matrix based on a beamforming algorithm;

[0011] The first weight distribution condition is that in the first beamforming weight matrix, the amplitudes of k beamforming weight vectors corresponding to k antennas are equal to each other, and k is an even number.

[0012] In some embodiments, performing aliasing processing on k-channel data includes:

[0013] The k-channel data are aliased based on the spatial precoding matrix, and the spatial precoding matrix satisfies:

[0014]

[0015] In the formula, F s represents the spatial precoding matrix, A is a non-zero matrix, O is a zero matrix, and both A and O are matrices with k / 2 rows and k / 2 columns.

[0016] In some embodiments, performing aliasing processing on k-channel data based on a spatial precoding matrix includes:

[0017] Aliasing is performed on k-way data based on the following formula:

[0018]

[0019] In the formula, Data represents the data obtained after aliasing processing, x1, x2, x k Respectively represent the first data path, the second data path, and the kth data path among the k data paths;

[0020] Any two data x in k data a and x b They correspond to two beamforming weight vectors with equal amplitudes, where a=1, 2, ..., k / 2, b=(k / 2)+1, (k / 2)+2, ..., k, and a+b=k+1.

[0021] In some embodiments, when k is equal to 8,

[0022]

[0023] In some embodiments, performing linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix includes:

[0024] The first beamforming weight matrix is ​​multiplied by the amplification coefficient α to obtain a second beamforming weight matrix; wherein the amplification coefficient α is determined based on the first beamforming weight matrix and the value of k, and the value of the amplification coefficient α is greater than 1.

[0025] In some embodiments, the amplification factor α is determined by the following formula:

[0026]

[0027] Where L represents the number of columns of the first beamforming weight matrix, w 1,l 、w 2,l 、w k / 2,l represent the element of the 1st row and the 1st column of the first beamforming weight matrix, the element of the 2nd row and the 1st column of the first beamforming weight matrix, and the element of the k / 2th row and the 1st column of the first beamforming weight matrix respectively;

[0028] In the first beamforming weight matrix, the amplitudes of the elements in the mth row and the nth row corresponding to the same column are equal, m=1, 2, ..., k / 2, n=(k / 2)+1, (k / 2)+2, ..., k, and m+n=k+1.

[0029] In some embodiments, the analog unmixing network module includes 2 analog unmixing network units, each analog unmixing network unit includes k / 2 3dB bridges;

[0030] In each analog demixing network unit, each input end of the k / 4 first 3dB bridges is respectively connected to the output end of a transmitting channel, each output end of the k / 4 second 3dB bridges is respectively connected to an antenna, and the two output ends of each first 3dB bridge are connected to two different second 3dB bridges.

[0031] In a second aspect, an embodiment of the present application further provides a data sending method, which is applied to the network device of the first aspect, and the method includes:

[0032] The BBU determines a first beamforming weight matrix corresponding to any group of k antennas, and performs linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix;

[0033] The BBU obtains k-channel data respectively mapped to the k antennas based on the second beamforming weight matrix, performs aliasing processing on the k-channel data to obtain k-channel aliased data, and outputs the k-channel aliased data to the RRU;

[0034] The RRU outputs k channels of aliased data to the analog demixing network module through k transmission channels respectively;

[0035] The analog demixing network module performs demixing processing on the aliased data output by the k transmission channels to obtain the transmission data corresponding to the k antennas, and outputs the transmission data to the corresponding antennas for transmission.

[0036] In a third aspect, an embodiment of the present application further provides a network device, including a memory, a transceiver, and a processor;

[0037] A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of a processor; and a processor for reading the computer program in the memory and executing the data transmission method of the second aspect.

[0038] The network device and data transmission method provided in the embodiments of the present application linearly amplify the beamforming weights through the BBU and then perform aliasing processing on the data mapped to each antenna, and then output the aliased data to the RRU, and perform demixing processing on the aliased data through the analog demixing network module to obtain the corresponding transmission data on each antenna, thereby achieving the maintenance of the non-codebook beamforming weights while ensuring that the total radiated power of each channel can be fully utilized, thereby ensuring both the maximum output power and the accuracy of the beamforming weights, and maximizing the channel gain and link performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the following is a brief introduction to the drawings required for use in the embodiments or the related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 A schematic diagram of the structure of a network device provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of the input-output relationship of a 3dB bridge provided in an embodiment of the present application;

[0042] Figure 3 An example diagram of an analog demixing network module based on a 3dB bridge provided in an embodiment of the present application;

[0043] Figure 4 A flowchart of a data transmission method provided in an embodiment of the present application;

[0044] Figure 5 A schematic diagram of the structure of a network device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In the embodiments of the present application, the term "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0046] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0047] In the embodiments of the present application, the terms "first", "second", etc. are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first" and "second" are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0048] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] The application of massive antennas in fifth-generation (5G) mobile communications has greatly improved the freedom of base station radiation beams. The weights obtained by non-codebook beamforming can maximize the matching of the data sent by the base station and the channel, thereby obtaining the best channel gain. However, the digital beamforming weights calculated by the non-codebook beamforming algorithm are usually not amplitude-normalized, that is, each transmission channel cannot radiate at full power, resulting in power waste. The common power normalization method saves some power, but sacrifices the accuracy of non-codebook beamforming, which ultimately affects the beamforming performance.

[0050] In response to the above problems, the embodiments of the present application provide a solution. By linearly amplifying the signal power of the transmitting channel and then sharing the power among the channels, the non-codebook beamforming weights can be maintained unchanged while ensuring that the total radiation power of each channel can be maximized, thereby ensuring both the maximum output power and the accuracy of the shaping weights, thereby maximizing the channel gain and link performance.

[0051] Figure 1 A schematic diagram of the structure of a network device provided in an embodiment of the present application, such as Figure 1 As shown, the network equipment includes:

[0052] The BBU 110 , the RRU 120 , the analog demixing network module 130 , and the antenna 140 are connected in sequence;

[0053] The BBU 110 is used to: determine a first beamforming weight matrix corresponding to any group of k antennas 140, and perform linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix; obtain k-channel data mapped to the k antennas 140 respectively based on the second beamforming weight matrix, perform aliasing processing on the k-channel data to obtain k-channel aliased data; output the k-channel aliased data to the RRU; wherein k is an integer greater than or equal to 2;

[0054] The RRU 120 is used to: output k-channel aliased data to the analog demixing network module 130 through k transmission channels respectively;

[0055] The analog demixing network module 130 is used to perform demixing processing on the aliased data output by the k transmission channels to obtain the transmission data corresponding to the k antennas 140 , and output the transmission data to the corresponding antennas 140 for transmission.

[0056] Specifically, in the network device, the output end of the baseband processing unit (Building Base band Unit, BBU) is connected one-to-one with the input end of the transmission channel in the remote radio unit (Remote Radio Unit, RRU), the output end of the transmission channel in the RRU is connected one-to-one with the input end of the analog demixing network module, and each output end of the analog demixing network module is connected to an antenna.

[0057] When sending downlink data, the BBU can first determine the first beamforming weight matrix corresponding to any group of k antennas, and perform linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix; then, based on the second beamforming weight matrix, obtain k-path data mapped to the k antennas respectively, perform aliasing processing on the k-path data, and obtain k-path aliased data.

[0058] Among them, any group of k antennas can be any group of multiple preset groups of antennas.

[0059] Common 5G large-scale antennas are one or more rows of 8 columns of dual-polarized antennas. For example, a 16TR (16 receive and 16 transmit) base station has one row of 8 columns of dual polarization, a 32TR base station has two rows of 8 columns of dual polarization, and a 64TR base station has four rows of 8 columns of dual polarization. Typically, the accuracy of beamforming in the horizontal direction plays a more important role in the performance of non-codebook beamforming, and it is more valuable to achieve power sharing between channels in the horizontal direction. In addition, power sharing in the horizontal direction also simplifies the complexity of the power sharing system and avoids designing a very complex network that shares all the channel powers of the base station together. Therefore, in some embodiments, multiple antennas in the same row and the same polarization direction in the horizontal direction can be grouped together, and antennas in other polarization directions and other rows can also be grouped in the same way.

[0060] The first beamforming weight matrix may be a beamforming weight matrix obtained by using a beamforming algorithm, and the second beamforming weight matrix is ​​a beamforming weight matrix obtained by linearly amplifying the first beamforming weight matrix. Since the digital beamforming weights directly calculated by using the beamforming algorithm are not output at full power, the linear amplification of the first beamforming weight matrix is ​​performed here to amplify the signal power of each transmission channel, so as to achieve the purpose of full power output of each transmission channel.

[0061] The k-path data mapped to the k antennas refers to the data on the k antennas after the port-level data stream is weighted by the second beamforming weight matrix during the downlink data transmission process. The data mapped to each antenna may also be referred to as antenna-level data or antenna data, which will not be described in detail later. The weighting of the data stream by the second beamforming weight matrix and the mapping process of the port-level data stream to the antenna-level data may adopt the existing technical solutions, and the detailed process will not be given here.

[0062] After obtaining k data paths mapped to k antennas, the BBU can perform aliasing on the k data paths to obtain k aliased data paths. The aliasing process refers to mixing and reorganizing the k data paths. Each aliased data path is obtained by mixing and reorganizing multiple data paths, thereby ensuring that after the k aliased data paths are output to the k transmission channels of the RRU, multiple aliased data paths are sent on each transmission channel to achieve power sharing between channels.

[0063] In the embodiment of the present application, the aliasing process for k-channel data is to enable the transmission power to be shared between the transmission channels, and should not affect the data transmitted from the final antenna, that is, the data transmitted from each antenna should not contain the data originally mapped to other antennas. Therefore, after the RRU outputs the k-channel aliased data to the analog demixing network module through k transmission channels respectively, the analog demixing network module needs to perform demixing process on the aliased data output by the k transmission channels to obtain the corresponding transmission data on each antenna. For example, assuming that the data mapped to a certain antenna c is x c After the BBU performs aliasing processing on the data at each antenna level, the analog demixing network module needs to demix the aliasing data output by the RRU's transmit channel to obtain the corresponding transmission data on each antenna, where the corresponding transmission data on antenna c should still be x c .

[0064] The present application does not limit the method of demixing the aliased data, as long as the corresponding transmission data on each antenna can be separated, the demixing of the aliased data can be achieved by hardware and / or software.

[0065] The network device provided in the embodiment of the present application linearly amplifies the beamforming weights through the BBU and then performs aliasing processing on the data mapped to each antenna, and then outputs the aliased data to the RRU, and demixes the aliased data through the analog demixing network module to obtain the corresponding transmission data on each antenna, thereby achieving the maintenance of the non-codebook beamforming weights while ensuring that the total radiated power of each channel can be fully utilized, thereby ensuring both the maximum output power and the accuracy of the beamforming weights, and maximizing the channel gain and link performance.

[0066] In some embodiments, determining a first beamforming weight matrix corresponding to any group of k antennas includes:

[0067] In the case where the first beamforming weight matrix is ​​set to satisfy a first weight distribution condition, determining the first beamforming weight matrix based on a beamforming algorithm;

[0068] The first weight distribution condition is that in the first beamforming weight matrix, the amplitudes of k beamforming weight vectors corresponding to k antennas are equal to each other, and k is an even number.

[0069] Specifically, in order to reduce the complexity of system implementation, the embodiment of the present application proposes that the first weight distribution condition can be set as a constraint condition when calculating the beamforming weight matrix, so that in the calculated first beamforming weight matrix, the amplitudes of the k beamforming weight vectors corresponding to the k antennas are equal to each other. Therefore, the effect of power sharing of all transmission channels can be achieved by only realizing power sharing of half of the transmission channels respectively, which greatly reduces the complexity of system implementation. Among them, the beamforming algorithm used is not limited in this application, for example, it can be a commonly used genetic algorithm or other commonly used beamforming algorithms.

[0070] The following is a brief introduction to this idea. From the beamforming theory, we know that any beamforming weight W can be realized by a weighted combination of a set of grid of beam (GOB) weights, and the GOB vector naturally has the characteristics of phase symmetric distribution. Taking 8 antennas as an example, the GOB vector G can be expressed as follows:

[0071]

[0072] In the formula, e represents a natural constant (its value is approximately 2.718281828459045), i represents an imaginary unit (i 2 =-1), θ represents the angle value, this concept is consistent throughout the text and will not be repeated later.

[0073] The beamforming weights realized by the weighted combination of a set of GOB vectors are It also has the characteristics of amplitude symmetry, namely:

[0074]

[0075] Satisfies: |w1|=|w8|, |w2|=|w7|, |w3|=|w6|, |w4|=|w5|. In this application, this kind of amplitude symmetry feature can be used As the beamforming weight W, it can reduce the complexity of system implementation.

[0076] In order to obtain weights with the above characteristics, corresponding weight distribution conditions may be set when performing non-codebook beamforming weight calculations, and then weight optimization calculations may be performed.

[0077] In some embodiments, performing linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix includes:

[0078] The first beamforming weight matrix is ​​multiplied by the amplification coefficient α to obtain a second beamforming weight matrix; wherein the amplification coefficient α is determined based on the first beamforming weight matrix and the value of k, and the value of the amplification coefficient α is greater than 1.

[0079] Specifically, the first beamforming weight matrix W calculated by the non-codebook beamforming algorithm is usually lossy weights after element maximum normalization. For example, assuming that the dimension of W is 8×L, where L is the total number of transmitted streams, the weight W of a stream l is l Among the 8 weight elements, only two have a modulus of 1 after element maximum normalization, for example, |w 4,l |=|w 5,l |=1, at this time, only channel 4 (w 4,l corresponding channel) and channel 5 (w 5,l The corresponding channel) can reach full power output, and the power of other channels is lossy, that is, |w 1,l |=|w 8,l |<1,|w 2,l |=|w 7,l |<1,|w 3,l |=|w 6,l |<1.

[0080] Therefore, in order to ensure that the total radiation power of each channel can be maximized, the first beamforming weight matrix can be linearly amplified to obtain the second beamforming weight matrix, and then the second beamforming weight matrix is ​​used to obtain k-channel data mapped to k antennas respectively.

[0081] The first beamforming weight matrix is ​​linearly amplified by multiplying the first beamforming weight matrix by an amplification factor α greater than 1, that is, each element in the first beamforming weight matrix is ​​multiplied by the amplification factor α, and the modulus amplification of the weight matrix also realizes power amplification. The amplification factor α is related to the first beamforming weight matrix obtained by the non-codebook beamforming algorithm and the value of k, and the appropriate amplification factor α can be determined according to the first beamforming weight matrix and the value of k.

[0082] In some embodiments, the amplification factor α may be determined by the following formula:

[0083]

[0084] Where L represents the number of columns of the first beamforming weight matrix, w 1,l 、w 2,l 、w k / 2,l represent the element of the 1st row and the 1st column of the first beamforming weight matrix, the element of the 2nd row and the 1st column of the first beamforming weight matrix, and the element of the k / 2th row and the 1st column of the first beamforming weight matrix respectively;

[0085] In the first beamforming weight matrix, the amplitudes of the elements in the mth row and the nth row corresponding to the same column are equal, m=1, 2, ..., k / 2, n=(k / 2)+1, (k / 2)+2, ..., k, and m+n=k+1.

[0086] For example, assuming k = 8, the first beamforming weight matrix Satisfies: |w1|=|w8|, |w2|=|w7|, |w3|=|w6|, |w4|=|w5|.

[0087] The power amplification process is as follows:

[0088]

[0089] In the formula, The second beamforming weight matrix is ​​represented by performing modular amplification on the weight W through the above power amplification process, so that the total radiation power of the 8 transmission channels = 8. Because the amplification coefficient α here is a real number, it is a linear amplification of the vector, so the beamforming weight remains unchanged in space.

[0090] In some embodiments, performing aliasing processing on k-channel data includes:

[0091] The k-channel data are aliased based on the spatial precoding matrix, and the spatial precoding matrix satisfies:

[0092]

[0093] In the formula, F s represents the spatial precoding matrix, A is a non-zero matrix, O is a zero matrix, and both A and O are matrices with k / 2 rows and k / 2 columns.

[0094] Specifically, after obtaining k-channel data mapped to k antennas respectively using a beamforming weight matrix with a symmetrical weight distribution feature, it is possible to This form of spatial precoding matrix is ​​used to perform aliasing processing on k-channel data. Its characteristic is that it can achieve the effect of power sharing of all transmission channels by mixing and reorganizing k / 2-channel data respectively.

[0095] In some embodiments, performing aliasing processing on k-channel data based on a spatial precoding matrix includes:

[0096] Aliasing is performed on k-way data based on the following formula:

[0097]

[0098] In the formula, Data represents the data obtained after aliasing processing, x1, x2, x k They respectively represent the 1st data channel, the 2nd data channel, and the kth data channel among the k data channels.

[0099] Among them, any two data x in k data a and x b Corresponding to two beamforming weight vectors with equal amplitudes, a=1, 2, ..., k / 2, b=(k / 2)+1, (k / 2)+2, ..., k, and a+b=k+1.

[0100] For example, assuming k = 8, the second beamforming weight matrix And meet based on The data streams are weighted to obtain the time domain transmission data x1, x2, x3, x4, x5, x6, x7, and x8 at the 8-way antenna level, where x1 and x8 correspond to and x2 and x7 correspond to and x3 and x6 correspond to and x4 and x5 correspond to and

[0101] In some embodiments, when k is equal to 8,

[0102]

[0103] Taking the 8-channel antenna-level time-domain transmitted data x1, x2, x3, x4, x5, x6, x7, and x8 as an example, the aliasing processing of these 8 channels of data is as follows:

[0104]

[0105] After digital aliasing, each of the first four rows contains x1 to x4, and each of the last four rows contains x5 to x8, thereby achieving power sharing. After weighting, each element of Data is aliased data sent at full power.

[0106] In some embodiments, the analog unmixing network module includes 2 analog unmixing network units, each analog unmixing network unit includes k / 2 3dB bridges;

[0107] In each analog demixing network unit, each input end of the k / 4 first 3dB bridges is respectively connected to the output end of a transmitting channel, each output end of the k / 4 second 3dB bridges is respectively connected to an antenna, and the two output ends of each first 3dB bridge are connected to two different second 3dB bridges.

[0108] Specifically, the analog demixing network module can be implemented by using a 3dB bridge. Figure 2 This is a schematic diagram of the input-output relationship of a 3dB bridge provided in an embodiment of the present application, in which I1 and I2 represent the input of the 3dB bridge, and O1 and O2 represent the output of the 3dB bridge.

[0109] Since the aliased data is obtained by mixing and reorganizing k / 2 paths of data respectively, the corresponding analog unmixing network module can be simplified, which can include 2 analog unmixing network units, each analog unmixing network unit is used to process a set of aliased data (aliased data obtained by mixing and reorganizing k / 2 paths of data).

[0110] Figure 3 An example diagram of an analog demixing network module based on a 3dB bridge provided in an embodiment of the present application is shown in FIG. Figure 3As shown, the analog unmixing network module can be used for analog unmixing of 8 transmission channels, which includes 2 analog unmixing network units, and each analog unmixing network unit includes 4 3dB bridges. For the 1 analog unmixing network unit on the left part, the input ends of the 2 first 3dB bridges (IN1, IN2, IN3, IN4 in the figure) are connected to the output ends of the 4 transmission channels, and the output ends of the 2 second 3dB bridges (OUT1, OUT2, OUT3, OUT4 in the figure) are connected to the antenna, and the data x1, x2, x3, x4 are output respectively. For the 1 analog unmixing network unit on the right part, the input ends of the 2 first 3dB bridges (IN5, IN6, IN7, IN8 in the figure) are connected to the output ends of the 4 transmission channels, and the output ends of the 2 second 3dB bridges (OUT5, OUT6, OUT7, OUT8 in the figure) are connected to the antenna, and the data x5, x6, x7, x8 are output respectively. As shown Figure 3 As shown, the two output ends of each first 3dB bridge are connected to two different second 3dB bridges, which means that each output end of the first 3dB bridge is connected to one second 3dB bridge.

[0111] Figure 3 The analog demixing network module shown in the figure only uses two layers of 3dB bridges. The left and right analog demixing network units respectively realize the orthogonal separation of the first 4 data channels and the last 4 data channels. If the first weight distribution condition of the beamforming weight matrix is ​​not constrained, more layers of bridges are required, and the process of aliasing and demixing all 8 data channels is much more complicated. Figure 3 The solution shown can enable all eight transmit channels to radiate at full power through simple power sharing of four data channels.

[0112] It should be noted that the specific structure of the analog demixing network module corresponds to the aliased data obtained in the BBU, so as to correctly separate the corresponding transmitted data on each antenna. The specific setting and connection method of the 3dB bridge can be flexibly changed, and no specific restrictions are made in the embodiments of the present application.

[0113] Figure 4 The flowchart of the data transmission method provided in the embodiment of the present application is as follows. The method can be applied to the network devices provided in the above embodiments, such as Figure 4 As shown, the method comprises the following steps:

[0114] Step 400: The BBU determines a first beamforming weight matrix corresponding to any group of k antennas, and performs linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix.

[0115] Step 401: The BBU obtains k data paths mapped to k antennas respectively based on the second beamforming weight matrix, performs aliasing processing on the k data paths to obtain k aliased data paths, and outputs the k aliased data paths to the RRU.

[0116] Step 402: The RRU outputs k channels of aliased data to the analog demixing network module through k transmission channels respectively.

[0117] Step 403: The analog demixing network module performs demixing processing on the aliased data output by the k transmission channels to obtain transmission data corresponding to the k antennas, and outputs the transmission data to the corresponding antennas for transmission.

[0118] Specifically, when sending downlink data, the BBU can first obtain the first beamforming weight matrix corresponding to any group of k antennas based on the beamforming algorithm, and perform linear amplification processing on the first beamforming weight matrix to obtain the second beamforming weight matrix; then use the second beamforming weight matrix to weight the data stream and map the data stream of each port to each antenna to obtain k-channel data mapped to the k antennas respectively; then perform aliasing processing on the k-channel data to obtain k-channel aliased data. The specific implementation method of the above process can be found in the above embodiment, which will not be repeated here.

[0119] After k-channel aliased data are output to the RRU, the RRU can output the k-channel aliased data to the analog demixing network module through k transmission channels respectively. Then the analog demixing network module demixes the aliased data output by the k transmission channels to obtain the corresponding transmission data on each antenna and output it to the corresponding antenna for transmission, thereby achieving the two requirements of ensuring the maximum output power and the accuracy of the shaping weights at the same time.

[0120] The data sending method provided in the embodiment of the present application linearly amplifies the beamforming weights through the BBU and then performs aliasing processing on the data mapped to each antenna, and then outputs the aliased data to the RRU, and demixes the aliased data through the analog demixing network module to obtain the corresponding transmission data on each antenna, thereby achieving the maintenance of the non-codebook beamforming weights while ensuring that the total radiated power of each channel can be fully utilized, thereby ensuring both the maximum output power and the accuracy of the beamforming weights, and maximizing the channel gain and link performance.

[0121] The methods and devices provided in the various embodiments of the present application are based on the same application concept. Since the methods and devices solve problems based on similar principles, the implementation of the devices and methods can refer to each other, and the repeated parts will not be repeated.

[0122] In some embodiments, determining a first beamforming weight matrix corresponding to any group of k antennas includes:

[0123] In the case where the first beamforming weight matrix is ​​set to satisfy a first weight distribution condition, determining the first beamforming weight matrix based on a beamforming algorithm;

[0124] The first weight distribution condition is that in the first beamforming weight matrix, the amplitudes of k beamforming weight vectors corresponding to k antennas are equal to each other, and k is an even number.

[0125] In some embodiments, performing aliasing processing on k-channel data includes:

[0126] The k-channel data are aliased based on the spatial precoding matrix, and the spatial precoding matrix satisfies:

[0127]

[0128] In the formula, F s represents the spatial precoding matrix, A is a non-zero matrix, O is a zero matrix, and both A and O are matrices with k / 2 rows and k / 2 columns.

[0129] In some embodiments, performing aliasing processing on k-channel data based on a spatial precoding matrix includes:

[0130] Aliasing is performed on k-way data based on the following formula:

[0131]

[0132] In the formula, Data represents the data obtained after aliasing processing, x1, x2, x k Respectively represent the first data path, the second data path, and the kth data path among the k data paths;

[0133] Any two data x in k data a and x b They correspond to two beamforming weight vectors with equal amplitudes, where a=1, 2, ..., k / 2, b=(k / 2)+1, (k / 2)+2, ..., k, and a+b=k+1.

[0134] In some embodiments, when k is equal to 8,

[0135]

[0136] In some embodiments, performing linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix includes:

[0137] The first beamforming weight matrix is ​​multiplied by the amplification coefficient α to obtain a second beamforming weight matrix; wherein the amplification coefficient α is determined based on the first beamforming weight matrix and the value of k, and the value of the amplification coefficient α is greater than 1.

[0138] In some embodiments, the amplification factor α is determined by the following formula:

[0139]

[0140] Where L represents the number of columns of the first beamforming weight matrix, w 1,l 、w 2,l 、w k / 2,l represent the element of the 1st row and the 1st column of the first beamforming weight matrix, the element of the 2nd row and the 1st column of the first beamforming weight matrix, and the element of the k / 2th row and the 1st column of the first beamforming weight matrix respectively;

[0141] In the first beamforming weight matrix, the amplitudes of the elements in the mth row and the nth row corresponding to the same column are equal, m=1, 2, ..., k / 2, n=(k / 2)+1, (k / 2)+2, ..., k, and m+n=k+1.

[0142] In some embodiments, the analog unmixing network module includes 2 analog unmixing network units, each analog unmixing network unit includes k / 2 3dB bridges;

[0143] In each analog demixing network unit, each input end of the k / 4 first 3dB bridges is respectively connected to the output end of a transmitting channel, each output end of the k / 4 second 3dB bridges is respectively connected to an antenna, and the two output ends of each first 3dB bridge are connected to two different second 3dB bridges.

[0144] Figure 5 A schematic diagram of the structure of a network device provided in an embodiment of the present application, such as Figure 5 As shown, the network device includes a memory 520, a transceiver 510 and a processor 500; wherein the processor 500 and the memory 520 may also be arranged physically separately.

[0145] The memory 520 is used to store computer programs; the transceiver 510 is used to send and receive data under the control of the processor 500.

[0146] Specifically, the transceiver 510 is used to receive and send data under the control of the processor 500 .

[0147] Among them, Figure 5In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 500 and memory represented by memory 520. The bus architecture may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described in this application. The bus interface provides an interface. The transceiver 510 may be a plurality of components, namely, a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, which may include a wireless channel, a wired channel, an optical cable, and other transmission media.

[0148] The processor 500 is responsible for managing the bus architecture and general processing, and the memory 520 can store data used by the processor 500 when performing operations.

[0149] The processor 500 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or a complex programmable logic device (CPLD). The processor may also adopt a multi-core architecture.

[0150] The processor 500 calls the computer program stored in the memory 520 to execute any of the methods provided in the embodiments of the present application according to the obtained executable instructions, for example: the BBU determines a first beamforming weight matrix corresponding to any group of k antennas, and performs linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix; the BBU obtains k-path data mapped to the k antennas respectively based on the second beamforming weight matrix, performs aliasing processing on the k-path data to obtain k-path aliased data, and outputs the k-path aliased data to the RRU; the RRU outputs the k-path aliased data to the analog demixing network module through k transmission channels respectively; the analog demixing network module performs demixing processing on the aliasing data output by the k transmission channels to obtain the transmission data corresponding to the k antennas, and outputs the transmission data to the corresponding antennas for transmission.

[0151] In some embodiments, determining a first beamforming weight matrix corresponding to any group of k antennas includes:

[0152] In the case where the first beamforming weight matrix is ​​set to satisfy a first weight distribution condition, determining the first beamforming weight matrix based on a beamforming algorithm;

[0153] The first weight distribution condition is that in the first beamforming weight matrix, the amplitudes of k beamforming weight vectors corresponding to k antennas are equal to each other, and k is an even number.

[0154] In some embodiments, performing aliasing processing on k-channel data includes:

[0155] The k-channel data are aliased based on the spatial precoding matrix, and the spatial precoding matrix satisfies:

[0156]

[0157] In the formula, F s represents the spatial precoding matrix, A is a non-zero matrix, O is a zero matrix, and both A and O are matrices with k / 2 rows and k / 2 columns.

[0158] In some embodiments, performing aliasing processing on k-channel data based on a spatial precoding matrix includes:

[0159] Aliasing is performed on k-way data based on the following formula:

[0160]

[0161] In the formula, Data represents the data obtained after aliasing processing, x1, x2, x k Respectively represent the first data path, the second data path, and the kth data path among the k data paths;

[0162] Any two data x in k data a and x b They correspond to two beamforming weight vectors with equal amplitudes, where a=1, 2, ..., k / 2, b=(k / 2)+1, (k / 2)+2, ..., k, and a+b=k+1.

[0163] In some embodiments, when k is equal to 8,

[0164]

[0165] In some embodiments, performing linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix includes:

[0166] The first beamforming weight matrix is ​​multiplied by the amplification coefficient α to obtain a second beamforming weight matrix; wherein the amplification coefficient α is determined based on the first beamforming weight matrix and the value of k, and the value of the amplification coefficient α is greater than 1.

[0167] In some embodiments, the amplification factor α is determined by the following formula:

[0168]

[0169] Where L represents the number of columns of the first beamforming weight matrix, w 1,l 、w 2,l 、w k / 2,l represent the element of the 1st row and the 1st column of the first beamforming weight matrix, the element of the 2nd row and the 1st column of the first beamforming weight matrix, and the element of the k / 2th row and the 1st column of the first beamforming weight matrix respectively;

[0170] In the first beamforming weight matrix, the amplitudes of the elements in the mth row and the nth row corresponding to the same column are equal, m=1, 2, ..., k / 2, n=(k / 2)+1, (k / 2)+2, ..., k, and m+n=k+1.

[0171] In some embodiments, the analog unmixing network module includes 2 analog unmixing network units, each analog unmixing network unit includes k / 2 3dB bridges;

[0172] In each analog demixing network unit, each input end of the k / 4 first 3dB bridges is respectively connected to the output end of a transmitting channel, each output end of the k / 4 second 3dB bridges is respectively connected to an antenna, and the two output ends of each first 3dB bridge are connected to two different second 3dB bridges.

[0173] The methods and devices provided in the various embodiments of the present application are based on the same application concept. Since the methods and devices solve problems based on similar principles, the implementation of the devices and methods can refer to each other, and the repeated parts will not be repeated.

[0174] It should be noted that the division of modules (or units) in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module (or unit) in each embodiment of the present application may be integrated in a processing unit, or each module (or unit) may exist physically separately, or two or more modules (or units) may be integrated in one unit. The above-mentioned integrated modules (or units) may be implemented in the form of hardware or in the form of software functional modules (or units).

[0175] If the integrated module (or unit) is implemented in the form of a software function module (or unit) and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or 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 to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program code.

[0176] It should be noted here that the above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0177] The technical solution provided in the embodiment of the present application can be applicable to a variety of systems, especially 5G systems. For example, the applicable system can be a global system of mobile communication (GSM) system, a code division multiple access (CDMA) system, a wideband code division multiple access (WCDMA) general packet radio service (GPRS) system, a long term evolution (LTE) system, a LTE frequency division duplex (FDD) system, a LTE time division duplex (TDD) system, an advanced long term evolution (LTE-A) system, a universal mobile telecommunication system (UMTS), a world-wide interoperability for microwave access (WiMAX) system, a 5G new air interface (NR) system, etc. These various systems include terminal equipment and network equipment. The system may also include a core network part, such as an evolved packet system (EPS), a 5G system (5GS), etc.

[0178] The network device involved in the embodiment of the present application may be a base station, which may include multiple cells providing services for the terminal. Depending on the specific application scenario, the base station may also be called an access point, or may be a device in the access network that communicates with the wireless terminal device through one or more sectors on the air interface, or other names. The network device may be used to interchange received air frames with Internet Protocol (IP) packets, and serve as a router between the wireless terminal device and the rest of the access network, wherein the rest of the access network may include an Internet Protocol (IP) communication network. The network device may also coordinate the attribute management of the air interface. For example, the network device involved in the embodiments of the present application may be a network device (Base Transceiver Station, BTS) in the Global System for Mobile communications (Global System for Mobile communications, GSM) or Code Division Multiple Access (Code Division Multiple Access, CDMA), or a network device (NodeB) in Wide-band Code Division Multiple Access (WCDMA), or an evolutionary network device (evolutional Node B, eNB or e-NodeB) in the long term evolution (long term evolution, LTE) system, a 5G base station (gNB) in the 5G network architecture (next generation system), or a home evolved Node B (Home evolved Node B, HeNB), a relay node, a home base station (femto), a pico base station (pico), etc., which is not limited in the embodiments of the present application. In some network structures, the network device may include a centralized unit (CU) node and a distributed unit (DU) node, and the centralized unit and the distributed unit may also be arranged geographically separately.

[0179] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0180] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer executable instructions. These computer executable instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0181] These processor executable instructions may also be stored in a processor readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the processor readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0182] These processor-executable instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0183] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A network device, characterized in that: include: The baseband processing unit BBU, the radio remote unit RRU, the analog demixing network module and the antenna are connected in sequence; The BBU is used to: determine a first beamforming weight matrix corresponding to any group of k antennas, and perform linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix; based on the second beamforming weight matrix, obtain k-channel data respectively mapped to the k antennas, perform aliasing processing on the k-channel data to obtain k-channel aliased data; output the k-channel aliased data to the RRU; wherein k is an integer greater than or equal to 2; The RRU is used to: output the k-channel aliased data to the analog demixing network module through k transmission channels respectively; The analog demixing network module is used to: perform demixing processing on the aliased data output by the k transmission channels to obtain the transmission data corresponding to the k antennas, and output the transmission data to the corresponding antennas for transmission.

2. The network device according to claim 1, characterized in that: The determining of a first beamforming weight matrix corresponding to any group of k antennas includes: In the case where the first beamforming weight matrix is ​​set to satisfy a first weight distribution condition, determining the first beamforming weight matrix based on a beamforming algorithm; The first weight distribution condition is: in the first beamforming weight matrix, the amplitudes of the k beamforming weight vectors corresponding to the k antennas are equal to each other, and k is an even number.

3. The network device according to claim 2, characterized in that: The aliasing process is performed on the k-channel data, comprising: The k-channel data are subjected to aliasing processing based on a spatial precoding matrix, wherein the spatial precoding matrix satisfies: In the formula, F s represents the spatial precoding matrix, A is a non-zero matrix, O is a zero matrix, and both A and O are matrices with k / 2 rows and k / 2 columns.

4. The network device according to claim 3, characterized in that: The performing aliasing processing on the k-channel data based on the spatial precoding matrix includes: The k-channel data are aliased based on the following formula: In the formula, Data represents the data obtained after aliasing processing, x1, x2, x k Respectively represent the first data path, the second data path, and the kth data path among the k data paths; Any two data x in the k data a and x b They correspond to two beamforming weight vectors with equal amplitudes, where a=1, 2, ..., k / 2, b=(k / 2)+1, (k / 2)+2, ..., k, and a+b=k+1.

5. The network device according to claim 4, characterized in that: When k is equal to 8, 6. The network device according to any one of claims 2 to 5, characterized in that: The linearly amplifying the first beamforming weight matrix to obtain a second beamforming weight matrix includes: The first beamforming weight matrix is ​​multiplied by a magnification coefficient α to obtain a second beamforming weight matrix; wherein the magnification coefficient α is determined based on the first beamforming weight matrix and the value of k, and the value of the magnification coefficient α is greater than 1.

7. The network device according to claim 6, characterized in that: The amplification factor α is determined by the following formula: Where L represents the number of columns of the first beamforming weight matrix, w 1,l 、w 2,l 、w k / 2,l represent the element of the 1st row and 1st column of the first beamforming weight matrix, the element of the 2nd row and 1st column of the first beamforming weight matrix, and the element of the k / 2th row and 1st column of the first beamforming weight matrix respectively; In the first beamforming weight matrix, the amplitudes of elements in the same column corresponding to the mth row and the nth row are equal, m=1, 2, ..., k / 2, n=(k / 2)+1, (k / 2)+2, ..., k, and m+n=k+1.

8. The network device according to any one of claims 2 to 5 or 7, characterized in that: The analog unmixing network module includes two analog unmixing network units, each of which includes k / 2 3dB bridges; In each of the analog demixing network units, each input end of the k / 4 first 3dB bridges is respectively connected to the output end of one of the transmitting channels, each output end of the k / 4 second 3dB bridges is respectively connected to one of the antennas, and the two output ends of each of the first 3dB bridges are connected to two different second 3dB bridges.

9. A data transmission method, characterized in that: Applied to the network device according to any one of claims 1 to 8, the method comprising: The BBU determines a first beamforming weight matrix corresponding to any group of k antennas, and performs linear amplification processing on the first beamforming weight matrix to obtain a second beamforming weight matrix; The BBU obtains, based on the second beamforming weight matrix, k data paths respectively mapped to the k antennas, performs aliasing processing on the k data paths to obtain k aliased data paths, and outputs the k aliased data paths to the RRU; The RRU outputs the k-channel aliased data to the analog demixing network module through k transmission channels respectively; The analog demixing network module performs demixing processing on the aliased data output by the k transmission channels to obtain transmission data corresponding to the k antennas, and outputs the transmission data to the corresponding antennas for transmission.

10. A network device, characterized in that: Including memory, transceiver, processor; Memory for storing computer programs; a transceiver, for transmitting and receiving data under the control of the processor; A processor, configured to read the computer program in the memory and execute the data sending method according to claim 9.

Images