CN113141229B - Interference suppression method and device - Google Patents

Interference suppression method and device Download PDF

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CN113141229B
CN113141229B CN202010067657.5A CN202010067657A CN113141229B CN 113141229 B CN113141229 B CN 113141229B CN 202010067657 A CN202010067657 A CN 202010067657A CN 113141229 B CN113141229 B CN 113141229B
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matrix
interference suppression
base station
channel correlation
vector
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CN113141229A (en
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肖晶成
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Datang Mobile Communications Equipment Co Ltd
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Datang Mobile Communications Equipment Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0023—Interference mitigation or co-ordination
    • H04J11/0026—Interference mitigation or co-ordination of multi-user interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes

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Abstract

The embodiment of the invention provides an interference suppression method and device, which are used for reducing the time consumption of an interference suppression process, wherein in the method, a base station acquires forming coefficient vectors of n paired terminal devices, determines a forming vector matrix according to the n forming coefficients, and calculates channel correlation matrices of the n terminal devices according to the forming vector matrix; the base station determines a channel correlation inverse matrix according to the channel correlation matrix; the base station carries out flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix, and then obtains an interference suppression matrix according to the forming vector matrix and the channel correlation inverse matrix adjustment matrix; and the base station carries out interference suppression processing on the n terminal devices according to the interference suppression matrix. The method places the flow power processing process of the interference suppression matrix behind the inverse matrix, thereby greatly reducing the calculation amount of the interference suppression processing process, reducing the time consumption of the system for executing the interference suppression and improving the performance of the system.

Description

Interference suppression method and device
Technical Field
The present application relates to the field of communications technologies, and in particular, to an interference suppression method and apparatus.
Background
At present, in a mobile communication system, as the number of terminal devices increases, the channel requirement for communication increases increasingly, and the problem of the limited spectrum resources becomes more and more prominent, and the beamforming technology is an important means for improving the reuse rate of the spectrum resources. The beamforming technology is to increase the strength of a target signal by weighting each antenna element in order to make the beam of an antenna point in a target direction as much as possible.
On the basis of a single terminal device beamforming technology, when a base station accesses a plurality of terminal devices, the base station needs to pair according to service processing among the terminal devices to ensure throughput in unit time. However, there are multiple terminal devices multiplexing the same time-frequency resource, and there is interference between the terminal devices. Therefore, when the multi-terminal equipment performs multi-input or multi-output, the interference suppression method can be adopted to avoid the interference generated among the multi-terminal equipment.
At present, a zero forcing algorithm is usually adopted by a base station to solve interference suppression generated when multiple terminal devices multiplex time-frequency resources. The method comprises the following steps: after a base station carries out channel estimation on accessed multi-terminal equipment, a forming coefficient of each terminal equipment is obtained, and a forming vector matrix is determined according to the obtained forming coefficients of the multi-terminal equipment; then the base station determines a channel correlation matrix of the multi-terminal equipment according to the forming vector matrix, and further determines an interference suppression matrix through an inverse matrix of the channel correlation matrix; and finally, the base station processes the interference suppression weight flow power and the antenna power according to the interference suppression matrix, thereby realizing interference suppression. The forming coefficient of each terminal device is the weight of each antenna array element corresponding to a downlink transmission beam used by a base station when the base station transmits to the terminal device; and the dimension of the shaped vector matrix is related to the number of the antennas of the base station and the total flow number of the paired terminal equipment.
Obviously, the amount of computation of the base station is proportional to the bandwidth of the terminal device, the number of antennas, and the square of the number of streams. However, as higher throughput is pursued. Because the existing communication system supports the ultra-large bandwidth, the base station uses the large-scale antenna technology, and the communication system supports resource multiplexing (for example, 16-stream signals) of multiple terminal devices, these result in a more complex calculation process of the interference suppression module of the base station and a larger calculation amount, thereby resulting in a more time-consuming whole interference suppression process.
Disclosure of Invention
The application provides an interference suppression optimization method and device, which are used for reducing time consumption of an interference suppression process.
The embodiment of the invention provides the following specific technical scheme:
in a first aspect, an embodiment of the present application provides an interference suppression method and an apparatus, where the method specifically includes the following steps:
a base station acquires forming coefficient vectors of n paired terminal devices, wherein the forming coefficient vector of each terminal device is a forming coefficient vector which is managed by the base station and corresponds to a downlink sending beam used for signal transmission with the terminal device, and n is an integer greater than 1;
the base station determines a forming vector matrix according to the n forming coefficients, and calculates channel correlation matrixes of the n terminal devices according to the forming vector matrix;
the base station determines a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is the inverse matrix of the channel correlation matrix;
the base station carries out flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix;
the base station adjusts a matrix according to the forming vector matrix and the channel correlation inverse matrix to obtain an interference suppression matrix;
and the base station carries out interference suppression processing on the n terminal devices according to the interference suppression matrix.
In a possible implementation manner, the determining, by the base station, a shaped vector matrix according to the n shaped coefficients includes: the base station makes the n shaped coefficients form the shaped vector matrix, wherein the shaped vector matrix conforms to the following formula: cn＝[w1,w2,...,wn]Wherein w isiA forming coefficient vector of the ith terminal equipment is represented, wherein i is an integer which is more than 1 and less than n; or
The base station makes the n shaped coefficients form a combined vector matrix, and performs 2-norm normalization processing on each column in the combined vector matrix to obtain the shaped vector matrix, wherein the shaped vector matrix conforms to the following formula: cn＝[w1',w2',...,wn']Wherein w isiIs' wiCarrying out 2 norm normalization processing to obtain the shaped vector matrix, wiAnd i is a forming coefficient vector of the ith terminal equipment, wherein i is an integer which is greater than 1 and less than n.
In one possible implementation, the channel correlation matrix conforms to the following equation:
Figure BDA0002376439320000031
wherein the content of the first and second substances,
Figure BDA0002376439320000032
is CnConjugate matrix of (2), CnIs the shaped vector matrix.
In one possible implementation, the channel correlation inverse matrix conforms to the following equation:
Figure BDA0002376439320000033
wherein R isnIs the channel correlation matrix.
In one possible implementation, the channelThe correlation inverse matrix adjustment matrix conforms to the following equation:
Figure BDA0002376439320000034
wherein R isinvIs the channel correlation inverse matrix.
In one possible implementation, the interference suppression matrix conforms to the following equation: vn＝Cn*Rinv,normWherein, CnIs said shaped vector matrix, Rinv,normAnd adjusting the matrix by the channel correlation inverse matrix.
In a possible implementation manner, the performing, by the base station, interference suppression processing on the n terminal devices according to the interference suppression matrix includes:
the base station determines a power adjustment factor of an antenna of the base station according to the interference suppression matrix;
according to the power adjustment factor of the antenna, antenna power adjustment processing is carried out on the interference suppression matrix to obtain an updated interference suppression matrix;
and the base station performs interference suppression processing on the n terminal devices by using the updated interference suppression matrix.
In one possible implementation, the power adjustment factor of the antenna conforms to the following formula: pant＝sum(|Vn|22), wherein VnIs the interference suppression matrix;
the updated interference suppression matrix conforms to the following equation:
Figure BDA0002376439320000035
in one possible implementation, the dimension of the shaped vector matrix is KaR×NlayerWherein, K isaRIs the number of antennas of the base station, NlayerThe total number of the streams of the n terminal devices.
In a second aspect, an embodiment of the present application provides a base station, including:
an obtaining unit, configured to obtain forming coefficient vectors of n paired terminal devices, where the forming coefficient vector of each terminal device is a forming coefficient vector managed by the base station and corresponding to a downlink transmission beam used for signal transmission with the terminal device, and n is an integer greater than 1;
the processing unit is used for determining a shaped vector matrix according to the n shaped coefficients and calculating channel correlation matrixes of the n terminal devices according to the shaped vector matrix; determining a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is an inverse matrix of the channel correlation matrix; performing flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix; adjusting a matrix according to the shaped vector matrix and the channel correlation inverse matrix to obtain an interference suppression matrix; and carrying out interference suppression processing on the n terminal devices according to the interference suppression matrix.
In a possible implementation manner, when determining the shaped vector matrix according to the n shaped coefficients, the processing unit is specifically configured to:
forming the n shaped coefficients into the shaped vector matrix, wherein the shaped vector matrix conforms to the following formula: cn＝[w1,w2,...,wn]Wherein w isiA forming coefficient vector of the ith terminal equipment is represented, wherein i is an integer which is more than 1 and less than n; or
Forming the n forming coefficients into a combined vector matrix, and performing 2-norm normalization processing on each column in the combined vector matrix to obtain the forming vector matrix, wherein the forming vector matrix conforms to the following formula: cn＝[w1',w2',...,wn']Wherein w isiIs' wiCarrying out 2 norm normalization processing to obtain the shaped vector matrix, wiAnd i is a forming coefficient vector of the ith terminal equipment, and is an integer which is greater than 1 and less than n.
In one possible implementation, the channel correlation matrix conforms to the following equation:
Figure BDA0002376439320000041
wherein the content of the first and second substances,
Figure BDA0002376439320000042
is CnOf the conjugate vector matrix, CnIs the shaped vector matrix.
In one possible implementation, the channel correlation inverse matrix conforms to the following equation:
Figure BDA0002376439320000043
Rnis the channel correlation matrix.
In one possible implementation, the channel correlation inverse matrix adjustment matrix conforms to the following equation:
Figure BDA0002376439320000051
Rinvis the channel correlation inverse matrix.
In one possible implementation, the interference suppression matrix conforms to the following equation: vn＝Cn*Rinv,normWherein, CnIs said shaped vector matrix, Rinv,normAnd adjusting the matrix by the channel correlation inverse matrix.
In a possible implementation manner, when performing interference suppression processing on the n terminal devices according to the interference suppression matrix, the processing unit is specifically configured to:
determining a power adjustment factor of an antenna of the base station according to the interference suppression matrix;
according to the power adjustment factor of the antenna, antenna power adjustment processing is carried out on the interference suppression matrix to obtain an updated interference suppression matrix;
and performing interference suppression processing on the n terminal devices by using the updated interference suppression matrix.
In one possible implementation, the power adjustment factor of the antenna conforms to the following formula: pant＝sum(|Vn|22), wherein VnIs the interference suppression matrix;
the updated interference suppression matrix conforms to the following equation:
Figure BDA0002376439320000052
in one possible implementation, the dimension of the shaped vector matrix is KaR×NlayerWherein, K isaRIs the number of antennas of the base station, NlayerThe total number of the streams of the n terminal devices.
In a third aspect, an embodiment of the present application provides a computer-readable storage medium, including: the computer-readable storage medium has stored thereon a computer program which, when run on an electronic device, causes the electronic device to perform any one of the possible implementations of any of the above aspects.
In a fourth aspect, embodiments of the present application provide a computer program comprising instructions that, when executed on a computer, cause the computer to perform any one of the possible implementations of any one of the above aspects.
In a fifth aspect, the present application provides a chip, where the chip is configured to read a computer program stored in a memory, and perform any one of the possible implementations of the foregoing aspects.
Through the above description, in the technical solution of the embodiment of the present application, a base station obtains forming coefficient vectors of n paired terminal devices, where the forming coefficient vector of each terminal device is a forming coefficient vector managed by the base station and corresponding to a downlink transmission beam used for signal transmission with the terminal device, and n is an integer greater than 1.
The base station determines a forming vector matrix according to the n forming coefficients, and calculates channel correlation matrixes of the n terminal devices according to the forming vector matrix; the base station determines a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is the inverse matrix of the channel correlation matrix; the base station carries out flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix, and then obtains an interference suppression matrix according to the forming vector matrix and the channel correlation inverse matrix adjustment matrix; and the base station carries out interference suppression processing on the n terminal devices according to the interference suppression matrix. The method places the flow power processing process of the interference suppression matrix behind the inverse matrix, thereby greatly reducing the calculation amount of the interference suppression processing process, further reducing the time consumption of the system for executing the interference suppression and improving the performance of the system.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic structural diagram of a communication device in an embodiment of the present invention;
FIG. 2 is a schematic diagram of a communication system according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating an interference suppression method according to the prior art;
fig. 4 is a flowchart illustrating an interference suppression method according to an embodiment of the present invention;
fig. 5 is a structural diagram of a base station provided in an embodiment of the present invention;
fig. 6 is a structural diagram of a base station provided in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the application provides an interference suppression optimization method, which is used for reducing the time consumption of interference suppression and improving the processing performance of a system. The method and the device are based on the same inventive concept, and because the principles of solving the problems of the method and the device are similar, the implementation of the device and the method can be mutually referred, and repeated parts are not repeated.
In the technical scheme of the embodiment of the application, a base station acquires forming coefficient vectors of n paired terminal devices, wherein the forming coefficient vector of each terminal device is a forming coefficient vector corresponding to a downlink sending beam managed by the base station and used for signal transmission with the terminal device, and n is an integer greater than 1; the base station determines a forming vector matrix according to the n forming coefficients, and calculates channel correlation matrixes of the n terminal devices according to the forming vector matrix; the base station determines a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is the inverse matrix of the channel correlation matrix; the base station carries out flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix, and then obtains an interference suppression matrix according to the forming vector matrix and the channel correlation inverse matrix adjustment matrix; and the base station carries out interference suppression processing on the n terminal devices according to the interference suppression matrix. The method places the flow power processing process of the interference suppression matrix behind the inverse matrix, thereby greatly reducing the calculation amount of the interference suppression processing process, reducing the time consumption of the system for executing the interference suppression and improving the performance of the system.
Some terms in the embodiments of the present application will be explained below to facilitate understanding by those skilled in the art.
1. A Base Station (BS), also referred to as a network device, is a device deployed in a radio access network to provide wireless communication functions.
Currently, some examples of base stations are: a gbb, an NR base station, an evolved Node B (eNB), a Transmission Reception Point (TRP), a Radio Network Controller (RNC), a Node B (NB), a Base Station Controller (BSC), a Base Transceiver Station (BTS), a home base station (e.g., home evolved Node B, or home Node B, HNB), or a Base Band Unit (BBU), etc.
In addition, in a network structure, the base station may include a Centralized Unit (CU) node and a Distributed Unit (DU) node. The structure separates the protocol layers of the eNB in a Long Term Evolution (LTE) system, the functions of part of the protocol layers are controlled in the CU in a centralized way, the functions of the rest part or all of the protocol layers are distributed in the DU, and the CU controls the DU in a centralized way.
2. A terminal device is a device that provides voice and/or data connectivity to a user. The terminal device may also be referred to as a User Equipment (UE), a Mobile Station (MS), a Mobile Terminal (MT), and so on.
For example, the terminal device may be a handheld device, a vehicle-mounted device, or the like having a wireless connection function. Currently, some examples of terminal devices are: a mobile phone (mobile phone), a tablet computer, a notebook computer, a palm top computer, a Mobile Internet Device (MID), a wearable device, a Virtual Reality (VR) device, an Augmented Reality (AR) device, a wireless terminal in industrial control (industrial control), a wireless terminal in self driving (self driving), a wireless terminal in remote surgery (remote medical supply), a wireless terminal in smart grid (smart grid), a wireless terminal in transportation safety (smart security), a wireless terminal in city (smart city), a wireless terminal in home (smart home), and the like.
3. "or", describing the association relationship of the associated object, for example, a or B, may mean: a is present alone, and B is present alone.
Embodiments of the present application will be described below with reference to the drawings.
Beamforming is a signal preprocessing technique based on an antenna array, and the beamforming generates a beam with directivity by adjusting a weighting coefficient of each array element in the antenna array, so as to obtain an obvious array gain. As shown in fig. 1, the communication device may obtain M beams in different directions through M groups of antenna array coefficients, in other words, one beam corresponds to one group of antenna array coefficients. The communication device may use either beam for signal transmission.
In the communication system shown in fig. 2, a base station performs beamforming to implement communication with a terminal device, however, on the basis of beamforming of a single terminal device, if multiple inputs and multiple outputs of multiple terminal devices occur, multiple terminal devices share the same time-frequency resource, which may cause interference between the terminal devices, and thus normal service transmission and processing cannot be efficiently performed.
In order to avoid interference among multiple terminal devices, a processing unit of the base station performs interference suppression, and performs equalization at a sending end of the base station in an interference suppression method, so that the weight of one terminal device is located at a 'null' position of the terminal device, and because of the complexity of an equalization algorithm, zero forcing equalization is used at present, and the algorithm meets the following formula:
Figure BDA0002376439320000091
wherein, VnRepresents a suppression matrix, CnA matrix of beamforming vectors representing n terminal devices,
Figure BDA0002376439320000092
is CnThe conjugate vector of (2).
The current implementation flow is shown in fig. 3 as follows:
1) a base station acquires forming coefficient vectors of n paired terminal devices: cn＝[w1,w2,...,wn](ii) a Matrix dimension KaR×Nlayer，KaRIs the number of antennas, NlayerThe total flow number of all paired terminal devices.
2) Calculating a channel correlation matrix:
Figure BDA0002376439320000093
3) calculating a channel correlation inverse matrix:
Figure BDA0002376439320000094
matrix dimension KaR×Nlayer。
4) Generating an interference suppression matrix of the terminal equipment: vn＝Cn*RinvDimension of matrix is KaR×Nlayer。
5) Interference rejection matrix stream power processing:
1. calculate the power adjustment factor for each stream:
Player＝sum(|Vn|2,1)
2. adjusting the flow power:
Figure BDA0002376439320000095
6) interference rejection matrix antenna power processing:
1. calculating a power adjustment factor for each antenna:
Pant＝sum(|Vn'|2,2)
2. antenna power adjustment:
Figure BDA0002376439320000101
wherein the fifth and sixth steps are to prevent the maximum transmission power of the device from being exceeded when the plurality of terminal devices are multiplexed.
However, in the current communication system, the key technologies adopted for pursuing higher throughput are: 1. the ultra-large bandwidth is, for example, the maximum bandwidth of a Frequency band (Frequency range 1, FR1) below 6GHz in 5G is 900MHz, and the maximum bandwidth of FR2 is 3250 MHz; 2. large-scale antenna technology, the number of antennas used by 5G is huge, and the antennas are usually 64, 128 and 256; 3. multi-user resource multiplexing, some communication systems support 16-stream signal peak speeds. These techniques pose significant challenges to the baseband digital processing unit of the base station. The interference suppression is a calculation intensive module in the baseband digital processing unit, and the calculation amount is proportional to the bandwidth and the number of antennas and proportional to the square of the number of streams, so that the processing overhead of interference suppression in the existing communication system is very large, the processing time consumption of interference suppression is reduced, and the performance of the 5G system can be effectively improved.
The existing interference suppression algorithm does not consider the mutual relation among data, the implementation steps are complex, the calculation redundancy is realized, and the calculation amount is large, so the calculation process of the interference suppression needs to be optimized from the algorithm perspective, the time consumption of the interference suppression is reduced, and the system performance is improved.
In order to solve the above problem, embodiments of the present application provide an interference suppression method. The method may be applied in a communication system as shown in fig. 2. The following describes a flow of an interference suppression method provided in an embodiment of the present application in detail with reference to fig. 4.
S401: the base station acquires forming coefficient vectors of N paired terminal devices, wherein the forming coefficient vector of each terminal device is a forming coefficient vector which is managed by the base station and corresponds to a downlink sending beam used for signal transmission with the terminal device, and N is an integer greater than 1.
In an embodiment, the base station composes the beamforming vector matrix according to the n beamforming coefficients, where the beamforming vector matrix conforms to the following formula: cn＝[w1,w2,...,wn]Wherein w isiAnd i is a forming coefficient vector of the ith terminal equipment, and is an integer which is greater than 1 and less than n.
In another embodiment, the base station combines the N beamforming coefficients into a combined vector matrix according to the N beamforming coefficients, and performs 2-norm normalization on each column in the combined vector matrix to obtain the beamforming vector matrix, where the beamforming vector matrix conforms to the following formula: cn＝[w1',w2',...,wn']Wherein w isiIs' wiCarrying out 2 norm normalization processing to obtain the shaped vector matrix, wiAnd i is a forming coefficient vector of the ith terminal equipment, wherein i is an integer which is greater than 1 and less than n.
S402: and the base station determines a forming vector matrix according to the n forming coefficients and calculates channel correlation matrixes of the n terminal devices according to the forming vector matrix.
In one embodiment, the channel correlation matrix conforms to the following equation:
Figure BDA0002376439320000111
wherein the content of the first and second substances,
Figure BDA0002376439320000112
is CnOf the conjugate vector matrix, CnIs the matrix of the shaped vectors.
Optionally, the channel correlation matrix of the n terminal devices is calculated as a channel correlation upper triangular matrix of the n terminal devices, and a diagonal line is not included.
For step S402, the channel-related upper triangular matrix of the n terminal devices is calculated, which does not include a diagonal, and the main reasons include: (1) due to the channel correlation matrix RnIs a Hermitian matrix, and can be inverted as long as the value of the upper triangle of the matrix is known; (2) the shaped vector matrix CnIs the result of 2-norm normalization, so RnIs 1 and therefore is not calculated.
S403: and the base station determines a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is the inverse matrix of the channel correlation matrix.
In one embodiment, the channel correlation inverse matrix conforms to the following equation:
Figure BDA0002376439320000113
Rnis the channel correlation matrix.
S404: and the base station carries out flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix.
In one embodiment of the method of the present invention,the channel correlation inverse matrix adjustment matrix conforms to the following formula:
Figure BDA0002376439320000121
Rinvis the channel correlation inverse matrix.
S405: and the base station adjusts the matrix according to the forming vector matrix and the channel correlation inverse matrix to obtain an interference suppression matrix.
In a first embodiment, the perturbation suppression matrix conforms to the following equation: vn＝Cn*Rinv,normWherein, CnIs said shaped vector matrix, Rinv,normAnd adjusting a matrix by the channel correlation inverse matrix.
S406: the base station carries out interference suppression processing on the n terminal devices according to the interference suppression matrix; the method comprises the following steps: and the base station adjusts the antenna power of the interference suppression matrix.
In one embodiment, the base station performs interference suppression processing on the n terminal devices according to the interference suppression matrix. The method comprises the following steps:
the base station determines a power adjustment factor of an antenna of the base station according to the interference suppression matrix;
the power adjustment factor of the antenna conforms to the following formula: pant＝sum(|Vn|22), wherein VnIs the interference suppression matrix.
According to the power adjustment factor of the antenna, antenna power adjustment processing is carried out on the interference suppression matrix to obtain an updated interference suppression matrix; the updated interference suppression matrix conforms to the following equation:
Figure BDA0002376439320000122
and the base station performs interference suppression processing on the N terminal devices by using the updated interference suppression matrix.
As can be seen from the above description, in a system with M antennas and N streams, compared with the existing solution at present, the interference suppression method proposed in the present application has the following improvements:
1. in step S402, the channel correlation matrix of the n terminal devices calculated by the base station is modified into a channel correlation upper triangular matrix of the n terminal devices, excluding diagonal lines. It is possible to reduce 4 × M × N (N +1)/2 multiplications and (4 × M-2) × N (N +1)/2 additions.
2. After the base station performs the flow power adjustment processing (step S404) on the channel correlation inverse matrix to the inverse matrix (step S403), the following derivation may be made for the reason:
Figure BDA0002376439320000131
it can be known that the interference rejection matrix V obtained after the over-current power processing in the existing schemen' and interference suppression matrix V obtained after stream power processing in the present applicationnAre equivalent. For a system with M antennas and N flows, the fifth step in the prior art is calculated by 4 × M × N multiplications and (N +1) × M additions, whereas the step S404 in the present embodiment is calculated by 2 × N multiplications, and thus the reduced calculation is 4 × M × N-2 × N multiplications and (N +1) × M additions.
Thus, the two improvements total 4 × M × N (N +1)/2+4 × M × N-2 × N multiplications, and (4 × M-2) × N (N +1)/2+ (N +1) × M additions.
For example: in 5G communication, 100M bandwidth (273PRB), 64 antennas, and 16 streams peak rate configuration, i.e., M is 64 and N is 16. Compared with the existing method, the interference suppression method provided by the application reduces 10483200 multiplications and 9727536 additions, and the processing time is reduced by about 5.6ms in total by assuming that the main frequency of a processor is 1.8GHz and executing 2 multiplications or additions per clock cycle.
In summary, the interference suppression method provided by the application makes full use of the characteristics between data, utilizes the context of matrix transformation, merges matrix operations, reduces unnecessary computation, and greatly reduces the computation amount in the interference suppression processing process, thereby reducing the time consumed by the system for performing interference suppression and improving the performance of the system.
Based on the same technical concept, the embodiment of the present application further provides a base station for implementing an interference suppression method, and the structure of the base station is as shown in fig. 5, and the base station includes an obtaining unit 501 and a processing unit 502. The base station apparatus may be applied to the communication system shown in fig. 2, and may implement one of the interference suppression methods shown in fig. 4 above. The functions of the various units in the apparatus 500 are described below.
An obtaining unit 501, configured to obtain forming coefficient vectors of n paired terminal devices, where a forming coefficient vector of each terminal device is a forming coefficient vector corresponding to a downlink transmission beam that is managed by the base station and used for signal transmission with the terminal device, and n is an integer greater than 1;
a processing unit 502, configured to determine a shaped vector matrix according to the n shaped coefficients, and calculate channel correlation matrices of the n terminal devices according to the shaped vector matrix;
determining a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is an inverse matrix of the channel correlation matrix; performing flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix; adjusting a matrix according to the shaped vector matrix and the channel correlation inverse matrix to obtain an interference suppression matrix; and carrying out interference suppression processing on the n terminal devices according to the interference suppression matrix.
In one embodiment, the processing unit 502 determines a matrix of shaped vectors according to the n shaped coefficients, and is configured to:
forming the n shaped coefficients into the shaped vector matrix, wherein the shaped vector matrix conforms to the following formula: cn＝[w1,w2,...,wn]Wherein w isiA forming coefficient vector of the ith terminal equipment is defined, wherein i is an integer which is more than 1 and less than n; or
Forming the n forming coefficients into a combined vector matrix, and performing 2-norm normalization processing on each column in the combined vector matrix to obtain the n forming coefficientsA shaped vector matrix, the shaped vector matrix conforming to the following formula: cn＝[w1',w2',...,wn']Wherein w isi' is wiCarrying out 2 norm normalization processing to obtain the shaped vector matrix, wiAnd i is a forming coefficient vector of the ith terminal equipment, and is an integer which is greater than 1 and less than n.
In one embodiment, the channel correlation matrix conforms to the following equation:
Figure BDA0002376439320000141
wherein the content of the first and second substances,
Figure BDA0002376439320000142
is CnOf the conjugate vector matrix, CnIs the shaped vector matrix.
In one embodiment, the channel correlation inverse matrix conforms to the following equation:
Figure BDA0002376439320000143
Rnis the channel correlation matrix.
In one embodiment, the channel correlation inverse matrix adjustment matrix conforms to the following equation:
Figure BDA0002376439320000144
Rinvis the channel correlation inverse matrix.
In one embodiment, the interference suppression matrix conforms to the following equation: vn＝Cn*Rinv,normWherein, CnFor said matrix of shaped vectors, Rinv,normAnd adjusting the matrix by the channel correlation inverse matrix.
In an embodiment, the processing unit 502, after performing interference suppression processing on the n terminal devices according to the interference suppression matrix, is configured to:
determining a power adjustment factor of an antenna of the base station according to the interference suppression matrix;
according to the power adjustment factor of the antenna, antenna power adjustment processing is carried out on the interference suppression matrix to obtain an updated interference suppression matrix;
and performing interference suppression processing on the n terminal devices by using the updated interference suppression matrix.
In one embodiment, the power adjustment factor of the antenna conforms to the following equation: pant＝sum(|Vn|22), wherein VnIs the interference suppression matrix;
the updated interference suppression matrix conforms to the following equation:
Figure BDA0002376439320000151
in one embodiment, the dimension of the matrix of shaped vectors is KaR×NlayerWherein, K isaRIs the number of antennas of the base station, NlayerThe total number of the streams of the n terminal devices.
Based on the same technical concept, the embodiment of the present application further provides a base station, which can implement the method for interference suppression as shown in fig. 3. Referring to fig. 6, the communication apparatus includes: a transceiver 601, a processor 602, and a memory 603. Wherein, the transceiver 601, the processor 602 and the memory 603 are connected to each other.
Optionally, the transceiver 601, the processor 602, and the memory 603 are connected to each other through a bus 604. The bus 604 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc.
The transceiver 601 is configured to receive and transmit data, so as to implement communication interaction with other devices.
The processor 602 is configured to implement an interference suppression method as shown in fig. 3.
The following description is provided by way of the functionality of each of the devices 500.
The transceiver 601 is configured to obtain forming coefficient vectors of n paired terminal devices, where the forming coefficient vector of each terminal device is a forming coefficient vector corresponding to a downlink transmission beam managed by the base station and used for signal transmission with the terminal device, and n is an integer greater than 1;
a processor 602, configured to determine a shaped vector matrix according to the n shaped coefficients, and calculate channel correlation matrices of the n terminal devices according to the shaped vector matrix;
determining a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is an inverse matrix of the channel correlation matrix; performing flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix; adjusting a matrix according to the forming vector matrix and the channel correlation inverse matrix to obtain an interference suppression matrix; and carrying out interference suppression processing on the n terminal devices according to the interference suppression matrix.
In one embodiment, the processor 602, upon determining a shaped vector matrix according to the n shaped coefficients, is configured to:
forming the n shaped coefficients into the shaped vector matrix, wherein the shaped vector matrix conforms to the following formula: cn＝[w1,w2,...,wn]Wherein w isiA forming coefficient vector of the ith terminal equipment is represented, wherein i is an integer which is more than 1 and less than n; or
Forming a combination vector matrix by the n forming coefficients, and performing 2-norm normalization processing on each column in the combination vector matrix to obtain the forming vector matrix, wherein the forming vector matrix conforms to the following formula: cn＝[w1',w2',...,wn']Wherein w isiIs' wiCarrying out 2 norm normalization processing to obtain the shaped vector matrix, wiAnd i is a forming coefficient vector of the ith terminal equipment, and is an integer which is greater than 1 and less than n.
In one embodiment, the channel correlation matrix conforms to the following equation:
Figure BDA0002376439320000161
wherein the content of the first and second substances,
Figure BDA0002376439320000162
is CnOf the conjugate vector matrix, CnIs the shaped vector matrix.
In one embodiment, the channel correlation inverse matrix conforms to the following equation:
Figure BDA0002376439320000163
Rnis the channel correlation matrix.
In one embodiment, the channel correlation inverse matrix adjustment matrix conforms to the following equation:
Figure BDA0002376439320000164
Rinvis the channel correlation inverse matrix.
In one embodiment, the interference suppression matrix conforms to the following equation: vn＝Cn*Rinv,normWherein, CnIs said shaped vector matrix, Rinv,normAnd adjusting the matrix by the channel correlation inverse matrix.
In an embodiment, the processor 602, performing interference suppression processing on the n terminal devices according to the interference suppression matrix, is configured to:
determining a power adjustment factor of an antenna of the base station according to the interference suppression matrix;
according to the power adjustment factor of the antenna, antenna power adjustment processing is carried out on the interference suppression matrix to obtain an updated interference suppression matrix;
and performing interference suppression processing on the n terminal devices by using the updated interference suppression matrix.
In one embodiment, the power adjustment factor of the antenna conforms to the following equation: pant＝sum(|Vn|22), wherein VnIs the interference suppression matrix;
the updated interference suppression matrix conforms to the following equation:
Figure BDA0002376439320000171
in one embodiment, the dimension of the matrix of shaped vectors is KaR×NlayerWherein, K isaRIs the number of antennas of the base station, NlayerThe total number of the streams of the n terminal devices.
Based on the above embodiments, the present application further provides a computer program, which when running on a computer, causes the computer to execute an interference suppression method provided in the embodiment shown in fig. 4.
Based on the above embodiments, the present application further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a computer, the computer causes the computer to execute an interference suppression method provided in the embodiment shown in fig. 4.
Based on the above embodiments, the embodiments of the present application further provide a chip, where the chip is used to read a computer program stored in a memory, and implement the interference suppression method provided by the embodiment shown in fig. 4.
Based on the foregoing embodiments, the present application provides a chip system, where the chip system includes a processor, and is configured to support a computer device to implement the functions related to the base station in the embodiment shown in fig. 4. In one possible design, the system-on-chip further includes a memory for storing programs and data necessary for the computer device. The chip system may be constituted by a chip, or may include a chip and other discrete devices.
To sum up, in the technical solution of the embodiment of the present application, a base station obtains forming coefficient vectors of n paired terminal devices, where the forming coefficient vector of each terminal device is a forming coefficient vector managed by the base station and corresponding to a downlink transmission beam used for signal transmission with the terminal device, and n is an integer greater than 1;
the base station determines a forming vector matrix according to the n forming coefficients, and calculates channel correlation matrixes of the n terminal devices according to the forming vector matrix; the base station determines a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is the inverse matrix of the channel correlation matrix; the base station carries out flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix, and then obtains an interference suppression matrix according to the forming vector matrix and the channel correlation inverse matrix adjustment matrix; and the base station carries out interference suppression processing on the n terminal devices according to the interference suppression matrix. The method places the flow power processing process of the interference suppression matrix behind the inverse matrix, thereby greatly reducing the calculation amount of the interference suppression processing process, reducing the time consumption of the system for executing the interference suppression and improving the performance of the system.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such 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 intended to include such modifications and variations as well.

Claims (20)

1. An interference suppression method, comprising:
a base station acquires forming coefficient vectors of n paired terminal devices, wherein the forming coefficient vector of each terminal device is a forming coefficient vector which is managed by the base station and corresponds to a downlink sending beam used for signal transmission with the terminal device, and n is an integer greater than 1;
the base station determines a forming vector matrix according to the forming coefficient vectors of the n terminal devices, and calculates channel correlation matrices of the n terminal devices according to the forming vector matrix;
the base station determines a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is the inverse matrix of the channel correlation matrix;
the base station carries out flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix;
the base station adjusts a matrix according to the shaped vector matrix and the channel correlation inverse matrix to obtain an interference suppression matrix;
and the base station carries out interference suppression processing on the n terminal devices according to the interference suppression matrix.
2. The method of claim 1, wherein the base station determines a shaped vector matrix according to the shaped coefficient vectors of the n terminal devices, comprising:
the base station makes the forming coefficient vectors of the n terminal devices form the forming vector matrix, wherein the forming vector matrix accords with the following formula: cn＝[w1,w2,...,wn]Wherein w isiA forming coefficient vector of the ith terminal equipment is defined, wherein i is an integer which is more than 1 and less than n; or
The base station makes the forming coefficient vectors of the n terminal devices form a combined vector matrix, and performs 2-norm normalization processing on each column in the combined vector matrix to obtain the forming vector matrix, wherein the forming vector matrix conforms to the following formula: cn＝[w1',w2',...,wn']Wherein w isiIs' wiCarrying out 2 norm normalization processing to obtain the shaped vector matrix, wiAnd i is a forming coefficient vector of the ith terminal equipment, and is an integer which is greater than 1 and less than n.
3. The method of claim 1, wherein the channel correlation matrix conforms to the following equation:
Figure FDA0003572953170000011
wherein the content of the first and second substances,
Figure FDA0003572953170000012
is CnConjugate matrix of CnIs the said forming directionA quantity matrix.
4. The method of claim 1, wherein the channel correlation inverse matrix conforms to the following equation:
Figure FDA0003572953170000021
wherein R isnIs the channel correlation matrix.
5. The method of claim 1, wherein the channel correlation inverse matrix adjustment matrix conforms to the following equation:
Figure FDA0003572953170000022
wherein R isinvIs the channel correlation inverse matrix.
6. The method of claim 1, wherein the interference suppression matrix conforms to the following equation: vn＝Cn*Rinv,normWherein, CnIs said shaped vector matrix, Rinv,normAnd adjusting a matrix for the channel correlation inverse matrix.
7. The method of claim 1, wherein the base station performs interference suppression processing on the n terminal devices according to the interference suppression matrix, and wherein the interference suppression processing comprises:
the base station determines a power adjustment factor of an antenna of the base station according to the interference suppression matrix;
according to the power adjustment factor of the antenna, antenna power adjustment processing is carried out on the interference suppression matrix to obtain an updated interference suppression matrix;
and the base station performs interference suppression processing on the n terminal devices by using the updated interference suppression matrix.
8. The method of claim 7, wherein the power adjustment factor for the antenna conforms to the following equation: pant＝sum(|Vn|22), wherein VnIs the interference suppression matrix;
the updated interference suppression matrix conforms to the following equation:
Figure FDA0003572953170000023
9. the method of any of claims 1-8, wherein the matrix of shaped vectors has a dimension of KaR×NlayerWherein, K isaRIs the number of antennas of the base station, NlayerThe total number of the streams of the n terminal devices.
10. A base station, comprising:
an obtaining unit, configured to obtain forming coefficient vectors of n paired terminal devices, where the forming coefficient vector of each terminal device is a forming coefficient vector managed by the base station and corresponding to a downlink transmission beam used for signal transmission with the terminal device, and n is an integer greater than 1;
the processing unit is used for determining a shaped vector matrix according to the shaped coefficient vectors of the n terminal devices and calculating the channel correlation matrix of the n terminal devices according to the shaped vector matrix; determining a channel correlation inverse matrix according to the channel correlation matrix, wherein the channel correlation inverse matrix is an inverse matrix of the channel correlation matrix; performing flow power adjustment processing on the channel correlation inverse matrix to obtain a channel correlation inverse matrix adjustment matrix; adjusting a matrix according to the forming vector matrix and the channel correlation inverse matrix to obtain an interference suppression matrix; and carrying out interference suppression processing on the n terminal devices according to the interference suppression matrix.
11. The base station of claim 10, wherein the processing unit, when determining the formed vector matrix according to the formed coefficient vectors of the n terminal devices, is specifically configured to:
will be describedForming the shaped vector matrix by the shaped coefficient vectors of the n terminal devices, wherein the shaped vector matrix conforms to the following formula: cn＝[w1,w2,...,wn]Wherein w isiA forming coefficient vector of the ith terminal equipment is represented, wherein i is an integer which is more than 1 and less than n; or
Forming a combined vector matrix by the forming coefficient vectors of the n terminal devices, and performing 2-norm normalization processing on each column in the combined vector matrix to obtain the forming vector matrix, wherein the forming vector matrix conforms to the following formula: cn＝[w1',w2',...,wn']Wherein w isiIs' wiCarrying out 2 norm normalization processing to obtain the shaped vector matrix, wiAnd i is a forming coefficient vector of the ith terminal equipment, wherein i is an integer which is greater than 1 and less than n.
12. The base station of claim 10, wherein the channel correlation matrix conforms to the following equation:
Figure FDA0003572953170000031
wherein the content of the first and second substances,
Figure FDA0003572953170000032
is CnOf the conjugate vector matrix, CnIs the matrix of the shaped vectors.
13. The base station of claim 10, wherein the channel correlation inverse matrix conforms to the following equation:
Figure FDA0003572953170000033
Rnis the channel correlation matrix.
14. The base station of claim 10, wherein the channel correlation inverse matrix adjustment matrix conforms to the following equation:
Figure FDA0003572953170000034
Rinvis the channel correlation inverse matrix.
15. The base station of claim 10, wherein the interference suppression matrix conforms to the following equation: vn＝Cn*Rinv,normWherein, CnIs said shaped vector matrix, Rinv,normAnd adjusting a matrix for the channel correlation inverse matrix.
16. The base station of claim 10, wherein the processing unit, when performing interference suppression processing on the n terminal devices according to the interference suppression matrix, is specifically configured to:
determining a power adjustment factor of an antenna of the base station according to the interference suppression matrix;
according to the power adjustment factor of the antenna, antenna power adjustment processing is carried out on the interference suppression matrix to obtain an updated interference suppression matrix;
and performing interference suppression processing on the n terminal devices by using the updated interference suppression matrix.
17. The base station of claim 16, wherein the power adjustment factor for the antenna conforms to the following equation: pant＝sum(|Vn|22), wherein VnIs the interference suppression matrix;
the updated interference suppression matrix conforms to the following equation:
Figure FDA0003572953170000041
18. the base station of any of claims 10-17, wherein the matrix of shaped vectors has a dimension KaR×NlayerWherein, K isaRIs the number of antennas of the base station, NlayerThe total number of the streams of the n terminal devices.
19. A computer-readable storage medium, in which a computer program is stored which, when run on an electronic device, causes the electronic device to perform the method according to any one of claims 1-9.
20. A chip for reading a computer program stored in a memory for performing the method according to any of claims 1-9.
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