CN119727812A - Antenna system precoding method, device, equipment, storage medium and product - Google Patents
Antenna system precoding method, device, equipment, storage medium and product Download PDFInfo
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Abstract
本发明公开了一种天线系统预编码方法、装置、设备、存储介质及产品，所述方法包括：获取初始上行信道矩阵、接入点侧校准系数矩阵与用户设备侧校准系数矩阵，根据接入点侧校准系数矩阵与用户设备侧校准系数矩阵确定校正补偿后的上行信道；确定校准系数误差统计特性参数，根据校准系数误差统计特性参数与校正补偿后的下行信道，并结合设定预编码算法，得到目标预编码矩阵。本发明公开的天线系统预编码方法，通过引入校准系数误差统计特性参数，消除校准系数误差的不确定性影响，使得即使在存在较大校准时延的情况下，本预编码方法也不会出现明显的性能下降。
The present invention discloses an antenna system precoding method, device, equipment, storage medium and product, the method comprising: obtaining an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix, determining a corrected and compensated uplink channel according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix; determining calibration coefficient error statistical characteristic parameters, and obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameters and the corrected and compensated downlink channel, and in combination with setting a precoding algorithm. The antenna system precoding method disclosed by the present invention eliminates the influence of uncertainty of the calibration coefficient error by introducing the calibration coefficient error statistical characteristic parameters, so that even in the presence of a large calibration delay, the precoding method will not show obvious performance degradation.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method, an apparatus, a device, a storage medium, and a product for precoding an antenna system.
Background
In a cellular-free large-scale antenna (CF-mMIMO) system, the access point AP is connected to a central processing unit CPU by wire, which needs to calculate a precoding matrix using downlink channel information. To avoid downlink channel feedback, it is generally assumed that the system operates in a TDD (Time-division Duplex) mode, and the downlink channel is obtained from the uplink channel by using reciprocity of the air interface uplink and downlink channels.
But the ideal channel reciprocity is limited to the air interface channel between the access point AP antenna to the user equipment UE antenna. In general, different radio frequency circuits are adopted for the transmitting chain and the receiving chain of the AP, which results in inconsistent gain coefficients of the uplink and downlink channels, so that the channels are no longer reciprocal. To restore reciprocity between the uplink and downlink channels, the gain difference between the uplink and downlink channels may be compensated for by a calibration scheme. However, due to distributed deployment, different APs often employ independent oscillators, and due to changes in the environment (e.g., temperature, humidity, etc.), phase drift between the independent oscillators exhibits time-varying characteristics, ultimately resulting in a gain difference between the upstream and downstream channels that also varies over time.
In the air interface calibration scheme, calibration reference signals are mutually transmitted between APs or between an AP and a UE. The AP or the UE estimates the uplink and downlink channels from the calibration reference signals and performs channel feedback. The final AP derives the gain difference between the upstream and downstream channels through channel feedback and channel estimation, which is called the calibration coefficient. Obviously, in the air interface calibration scheme, the calibration coefficient reflects the gain difference between the uplink and downlink channels corresponding to the transmission time of the calibration reference signal. In a practical system, there is a delay of several milliseconds at the time of transmitting the calibration reference signal and the time of transmitting the downlink data, which is called as a calibration delay. For low cost deployed APs, a calibration delay of several milliseconds is sufficient to cause a large error in the calibration coefficients. The conventional precoding method needs to use accurate downlink channel information to eliminate interference between multiple UEs. In this case, reciprocity of the uplink and downlink channels is difficult to be ensured, and the performance of precoding may be greatly affected.
Disclosure of Invention
The invention provides an antenna system precoding method, device, equipment, storage medium and product, which are used for overcoming the influence of calibration time delay on precoding performance.
According to an aspect of the present invention, there is provided an antenna system precoding method, including:
Acquiring an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix, and determining a corrected and compensated uplink channel according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix;
and determining a calibration coefficient error statistical characteristic parameter, and obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and combining a set precoding algorithm.
Further, the setting precoding algorithm includes a zero forcing precoding algorithm, and according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel, a target precoding matrix is obtained by combining the setting precoding algorithm, including:
Taking the product of the precoding matrix and the downlink channel matrix and the norm of the difference between the precoding matrix and the unit matrix as a first target norm, wherein the downlink channel matrix is related to the corrected and compensated uplink channel;
According to the zero-forcing precoding algorithm, taking the expectation of the first target norm about the calibration coefficient error statistical characteristic parameter as a first target expected function;
and determining a precoding matrix with the minimum value of the first target expected function as the target precoding matrix.
Further, after obtaining the target precoding matrix, the method further includes:
And determining a power constraint factor, and determining the product of the power constraint factor and the target precoding matrix as an actual precoding matrix.
Further, the power constraint factor is determined according to the maximum transmission signal power of the signal transmitting end and the initial transmission signal power of the signal transmitting end which is not precoded.
Further, the setting a precoding algorithm includes a wiener precoding algorithm, and according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel, a target precoding matrix is obtained by combining the setting precoding algorithm, including:
Taking the product of the received signal and the gain factor as a first product and taking the norm of the difference between the transmitted signal and the first product as a second target norm, wherein the received signal is related to the corrected and compensated uplink channel;
according to the wiener precoding algorithm, taking the second target norm as a second target expected function with respect to the calibration coefficient error statistical characteristic parameter, the sending signal and the expectation of the receiving end noise;
and determining a precoding matrix which enables the second target expected function to take a minimum value and meets a power constraint condition as the target precoding matrix.
Further, the set precoding algorithm includes a minimum mean square error precoding algorithm, and according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel, a target precoding matrix is obtained by combining the set precoding algorithm, including:
Taking the norm of the difference between the sending signal and the receiving signal as a third target norm, wherein the receiving signal is related to the corrected and compensated uplink channel;
According to the minimum mean square error precoding algorithm, taking the expectation of the third target norm about the calibration coefficient error statistical characteristic parameter, the sending signal and the noise of the receiving end as a third target expectation function;
And determining a precoding matrix which enables the third target expected function to take a minimum value and meets a power constraint condition as the target precoding matrix.
According to another aspect of the present invention, there is provided an antenna system precoding apparatus, including:
The uplink channel determining module after correction and compensation is used for acquiring an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix and determining an uplink channel after correction and compensation according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix;
The target precoding matrix determining module is used for determining the calibration coefficient error statistical characteristic parameter, and obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and combining a set precoding algorithm.
Optionally, the set precoding algorithm includes a zero forcing precoding algorithm, and the target precoding matrix determining module is further configured to:
Taking the product of the precoding matrix and the downlink channel matrix and the norm of the difference between the precoding matrix and the unit matrix as a first target norm, wherein the downlink channel matrix is related to the corrected and compensated uplink channel;
According to the zero-forcing precoding algorithm, taking the expectation of the first target norm about the calibration coefficient error statistical characteristic parameter as a first target expected function;
and determining a precoding matrix with the minimum value of the first target expected function as the target precoding matrix.
Optionally, the apparatus further includes an actual precoding matrix determining module configured to determine a power constraint factor, and determine a product of the power constraint factor and the target precoding matrix as an actual precoding matrix.
Optionally, the power constraint factor is determined according to the maximum transmission signal power of the signal transmitting end and the initial transmission signal power of the signal transmitting end which is not precoded.
Optionally, the set precoding algorithm includes a wiener precoding algorithm, and the target precoding matrix determining module is further configured to:
Taking the product of the received signal and the gain factor as a first product and taking the norm of the difference between the transmitted signal and the first product as a second target norm, wherein the received signal is related to the corrected and compensated uplink channel;
according to the wiener precoding algorithm, taking the second target norm as a second target expected function with respect to the calibration coefficient error statistical characteristic parameter, the sending signal and the expectation of the receiving end noise;
and determining a precoding matrix which enables the second target expected function to take a minimum value and meets a power constraint condition as the target precoding matrix.
Optionally, the set precoding algorithm includes a minimum mean square error precoding algorithm, and the target precoding matrix determining module is further configured to:
Taking the norm of the difference between the sending signal and the receiving signal as a third target norm, wherein the receiving signal is related to the corrected and compensated uplink channel;
According to the minimum mean square error precoding algorithm, taking the expectation of the third target norm about the calibration coefficient error statistical characteristic parameter, the sending signal and the noise of the receiving end as a third target expectation function;
And determining a precoding matrix which enables the third target expected function to take a minimum value and meets a power constraint condition as the target precoding matrix.
According to another aspect of the present invention, there is provided an electronic apparatus including:
At least one processor, and
A memory communicatively coupled to the at least one processor, wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the antenna system precoding method of any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the antenna system precoding method according to any one of the embodiments of the present invention when executed.
According to another aspect of the present invention, there is provided a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the antenna system precoding method according to any of the embodiments of the present invention.
The invention discloses an antenna system precoding method, which comprises the steps of firstly obtaining an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix, determining a corrected and compensated uplink channel according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix, then determining a calibration coefficient error statistical characteristic parameter, obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel, and combining with a set precoding algorithm. According to the antenna system precoding method disclosed by the invention, the uncertainty influence of the calibration coefficient error is eliminated by introducing the calibration coefficient error statistical characteristic parameter, so that the precoding method does not have obvious performance degradation even under the condition of larger calibration time delay.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an antenna system precoding method according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a cellular-free large-scale antenna system according to a first embodiment of the present invention;
Fig. 3 is a schematic structural diagram of an antenna system precoding device according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device implementing the antenna system precoding method according to the third embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of an antenna system precoding method according to an embodiment of the present invention, where the method may be performed by an antenna system precoding device, and the antenna system precoding device may be implemented in hardware and/or software, and the antenna system precoding device may be configured in an electronic device. As shown in fig. 1, the method includes:
s110, acquiring an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix, and determining a corrected and compensated uplink channel according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix.
In this embodiment, a non-cellular large-scale antenna (CF-mMIMO) is a wireless communication technology, and aims to eliminate inter-cell interference by deploying a large number of distributed small base stations and introducing a collaboration mechanism, and a network architecture centered on a user, so as to significantly improve network capacity and coverage. Fig. 2 is a schematic diagram of a non-cellular massive antenna system according to an embodiment of the present invention, where the non-cellular massive antenna system is composed of a Central Processing Unit (CPU), a plurality of Access Points (APs) and a plurality of User Equipments (UEs), and as shown in the drawing, the APs are connected to the CPU by wires, and signals are transmitted and received between the APs and the UEs by wireless channels.
And the numbers of antennas at the AP side and the UE side are respectively represented by M and K, the definitions c m,tx,ap and c m,rx,ap respectively represent the gain coefficient of a transmitting radio frequency circuit and the gain coefficient of a receiving radio frequency circuit of an mth antenna at the AP side, and the definitions c k,tx,ue and c k,rx,ue respectively represent the gain coefficient of the transmitting radio frequency circuit and the gain coefficient of the receiving radio frequency circuit of a kth antenna at the UE side. Then, the downlink channel h mk,d and the uplink channel h mk,u between the mth antenna on the AP side and the kth antenna on the UE side are respectively:
hmk,d＝ck,rx,ue·hmk·cm,tx,ap
hmk,u＝cm,rx,ap·hmk·ck,tx,ue
wherein h mk is an air interface channel between the m-th antenna on the AP side and the k-th antenna on the UE side. The above relationship is written in a matrix form, and there are:
defining a calibration matrix as:
defining a calibration vector as:
cap＝diag(Cap)
cue＝diag(Cue)
from the above relationship, the following equation can be obtained:
Wherein H u is an initial uplink channel matrix, C ap and C ue are an access point side (AP side) calibration coefficient matrix and a user equipment side (UE side) calibration coefficient matrix, respectively, and the corrected and compensated uplink channel can be determined according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix:
S120, determining the calibration coefficient error statistical characteristic parameter, and obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and combining with a set precoding algorithm.
Under ideal channel reciprocity, the CPU can calculate the downlink channel matrix under ideal conditions after obtaining the initial uplink channel matrix H u and the calibration coefficient matrices C ap and C ue at the AP side and the UE sideAnd performs precoding. However, due to changes in the environment (e.g., temperature, humidity, etc.), the phase drift between the independent oscillators exhibits time-varying characteristics. In general, the phase drift of the oscillator causes the phase of the real calibration coefficients to jitter around the estimated calibration coefficient phase, while the amplitude of the real calibration coefficients varies little. Thus, after considering the calibration delay, and the time-varying nature of the calibration coefficients, the relationship between the upstream and downstream channels can be modeled as follows:
Wherein, For correcting the compensated uplink channel, E ue and E ap are calibration coefficient error matrices of the UE side and the AP side, respectively, and the corresponding calibration coefficient error vectors are defined as follows:
eap＝diag(Eap)
eue＝diag(Eue)
Where θ m,ap, m=1,..m and θ k,ue, k=1,..k are subject to some independent co-distribution, e.g. a uniform distribution, or a gaussian cut-off distribution, etc., respectively, symmetrical about 0 °. Thus, it can be recorded that AndE ap and e ue are calibration coefficient error statistical characteristic parameters.
In this embodiment, after determining the calibration coefficient error statistical characteristic parameter, the calculation of the target precoding matrix may be performed according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel, and in combination with the set precoding algorithm.
Optionally, the method for obtaining the target precoding matrix by setting the precoding algorithm includes a zero forcing precoding algorithm, according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel, and combining the setting precoding algorithm includes that the product of the precoding matrix and the downlink channel matrix and the norm of the difference between the precoding matrix and the identity matrix are used as a first target norm, wherein the downlink channel matrix is related to the corrected and compensated uplink channel, according to the zero forcing precoding algorithm, the first target norm is used as a first target expected function with respect to the expectation of the calibration coefficient error statistical characteristic parameter, and the precoding matrix with the minimum value of the first target expected function is determined as the target precoding matrix.
Specifically, zero Forcing (ZF) is a linear precoding technique, whose core principle is to separate the transmitted data streams by beamforming so that a unit response is generated in the desired direction, and the response in the undesired direction is Zero. When using RZF for precoding, the target precoding matrix can be obtained by solving the following optimization problem:
wherein W is a precoding matrix, W RZF is an optimal solution of the precoding matrix W (i.e., a target precoding matrix), I is a unit matrix, Representing the expectation of the random variable x,As a first target norm,For the first target expectation function, the expectation of the first target norm with respect to the calibration coefficient error statistical characteristic parameters e ap and e ue is expressed. Due toTherefore, the downlink channel matrix H d and the corrected and compensated uplink channelAnd (5) correlation.
Target precoding matrix W RZF as a commandTaking the value of the precoding matrix W with the minimum value, and defining for solving W RZF Then there are:
where Δ is a quantity independent of W.
The conjugate gradient of J (W) with respect to W is:
according to the first order optimality condition, it is possible to:
wherein the method comprises the steps of Representing pseudo-inversion operations, and having
Wherein the "-. Is Hadamard product, and has
E=(1-|eap|2)·I+|eap|2·1M×M
Substitution is available
Wherein, Is thatIs used for the matrix of conjugates of (c),Is thatIs a transposed matrix of (a).
Based on the aboveThe uplink channel after correction and compensation can be obtained according to the error statistical characteristic parameter e ap、eue of the calibration coefficientA target precoding matrix W RZF is calculated.
Further, after the target precoding matrix is obtained, a power constraint factor may be determined, and a product of the power constraint factor and the target precoding matrix may be determined as an actual precoding matrix.
Preferably, the power constraint factor is determined according to the maximum transmission signal power of the signal transmitting terminal and the initial transmission signal power of the signal transmitting terminal which is not precoded.
Specifically, under the condition of considering the power constraint of the transmitting end at the AP side, let P max represent the maximum transmitting signal power of the signal transmitting end, letIndicating the initial transmission signal power of the signal transmitting end which is not pre-coded, there isWherein the method comprises the steps ofIs a downlink data symbol vector sent by the AP side and comprisesThe power constraint factor β RZF may be introduced in the W RZF expression:
The actual precoding matrix may be expressed as:
Optionally, the method for obtaining the target precoding matrix by combining the set precoding algorithm with the wiener precoding algorithm and according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel comprises taking the product of a received signal and a gain factor as a first product and taking the norm of the difference between a transmitted signal and the first product as a second target norm, wherein the received signal is related to the corrected and compensated uplink channel, taking the expected of the second target norm about the calibration coefficient error statistical characteristic parameter, the transmitted signal and the noise of the receiving end as a second target expected function according to the wiener precoding algorithm, and determining the precoding matrix which takes the second target expected function as a minimum value and meets the power constraint condition as the target precoding matrix.
In particular, wiener precoding (WIENER FILTER, WF) is a linear precoding technique whose basic principle is to design a filter by minimizing the mean square error between the received signal and the original signal. Assume that the downlink data symbol vector sent by the AP side isThe received data symbol vector received by the UE isWherein n is additive white Gaussian noise and hasAndWherein the method comprises the steps ofIndicating the initial transmit signal power at which the signal transmitting end is not precoded,Is the noise power. Let P max denote the maximum transmit signal power of the signal transmitter under the conditions of taking into account the automatic gain control at the UE side and the power constraint at the transmitter at the AP side
When using WF for precoding, the target precoding matrix can be obtained by solving the following optimization problem:
Where W RW is the optimal solution of the precoding matrix W (i.e., the target precoding matrix), beta -1 is the gain factor at the UE side, As a result of the first product of the products,For the second target norm,For the second target expectation function, the expectation of the second target norm with respect to the calibration coefficient error statistical characteristic parameters e ap and e ue, the transmission signal s, and the receiving-end noise n is expressed.Is a power constraint. W RW and beta RW are the ordersThe minimum precoding matrix W and the gain factor beta are taken as values.
According to the Lagrangian multiplier method, the following results can be obtained:
Wherein the "-. Is Hadamard product, and has
E=(1-|eap|2)·I+|eap|2·1M×M
Based on the expressionThe uplink channel after correction and compensation can be obtained according to the error statistical characteristic parameter e ap、eue of the calibration coefficientA target precoding matrix W RW is calculated.
Optionally, the method for obtaining the target precoding matrix by combining the set precoding algorithm with the minimum mean square error precoding algorithm and according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel includes taking a norm of a difference between a transmission signal and a reception signal as a third target norm, wherein the reception signal is related to the corrected and compensated uplink channel, taking a desire of the third target norm about the calibration coefficient error statistical characteristic parameter, the transmission signal and the noise of the receiving end as a third target desire function according to the minimum mean square error precoding algorithm, and determining the precoding matrix which takes the third target desire function as a minimum value and meets a power constraint condition as the target precoding matrix.
Specifically, minimum Mean Square Error precoding (MMSE) is a signal processing technique, which aims to minimize the Mean Square Error between a received signal and a desired signal, so as to obtain the best signal-to-noise ratio and bit Error rate performance. Assume that the downlink data symbol vector sent by the AP side isThe received data symbol vector received by the UE isWherein n is additive white Gaussian noise and hasAndWherein the method comprises the steps ofIndicating the initial transmit signal power at which the signal transmitting end is not precoded,Is the noise power. Let P max denote the maximum transmit signal power of the signal transmitter under the condition of considering the power constraint of the transmitter at the AP side
When MMSE is used for precoding, the target precoding matrix can be obtained by solving the following optimization problem:
Where W RMMSE is the optimal solution of the precoding matrix W (i.e., the target precoding matrix), For the third target norm,For the third target expectation function, the expectation of the third target norm with respect to the calibration coefficient error statistical characteristic parameters e ap and e ue, the transmission signal s, and the receiving-end noise n is expressed.Is a power constraint. W RMMSE is a command The value of the precoding matrix W with the minimum value is taken.
By introducing Lagrangian multiplier lambda not less than 0, can be obtained
Where W RMMSE is a function of λ. According to the relaxed complementation condition when
When W RMMSE is of the same form as W RZF without the power constraint factor beta RZF, i.e
Otherwise, the optimal solution for λ needs to be obtained by solving the following equation:
The above is equivalent to
Wherein, DΛd H isAnd Λ is a eigenvalue matrix. Let [ X ] mm denote the mth diagonal element of X, the above formula can be simplified to
Wherein, the left side of the above equation is monotonically decreased about λ, and λ can be searched by a dichotomy to determine the value of λ.
After determining the value of lambda, based on the expression The uplink channel after correction and compensation can be obtained according to the error statistical characteristic parameter e ap、eue of the calibration coefficientA target precoding matrix W RMMSE is calculated.
The invention discloses an antenna system precoding method, which comprises the steps of firstly obtaining an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix, determining a corrected and compensated uplink channel according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix, then determining a calibration coefficient error statistical characteristic parameter, obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel, and combining with a set precoding algorithm. According to the antenna system precoding method disclosed by the invention, the uncertainty influence of the calibration coefficient error is eliminated by introducing the calibration coefficient error statistical characteristic parameter, so that the precoding method does not have obvious performance degradation even under the condition of larger calibration time delay.
Example two
Fig. 3 is a schematic structural diagram of an antenna system precoding device according to a second embodiment of the present invention, and as shown in fig. 3, the device includes a corrected and compensated uplink channel determining module 310 and a target precoding matrix determining module 320.
The corrected and compensated uplink channel determining module 310 is configured to obtain an initial uplink channel matrix, an access point side calibration coefficient matrix, and a user equipment side calibration coefficient matrix, and determine a corrected and compensated uplink channel according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix.
The target precoding matrix determining module 320 is configured to determine a calibration coefficient error statistical characteristic parameter, and obtain a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and in combination with a set precoding algorithm.
Optionally, the set precoding algorithm includes a zero forcing precoding algorithm, and the target precoding matrix determining module 320 is further configured to:
The method comprises the steps of taking the product of a precoding matrix and a downlink channel matrix and the norm of the difference between the precoding matrix and a unit matrix as a first target norm, wherein the downlink channel matrix is related to an uplink channel after correction and compensation, taking the expectation of the first target norm about the calibration coefficient error statistical characteristic parameter as a first target expected function according to a zero-forcing precoding algorithm, and determining the precoding matrix with the minimum value of the first target expected function as a target precoding matrix.
Optionally, the apparatus further includes an actual precoding matrix determining module 330, configured to determine a power constraint factor, and determine a product of the power constraint factor and the target precoding matrix as the actual precoding matrix.
Optionally, the power constraint factor is determined according to the maximum transmission signal power of the signal transmitting end and the initial transmission signal power of the signal transmitting end which is not precoded.
Optionally, the set precoding algorithm includes a wiener precoding algorithm, and the target precoding matrix determining module 320 is further configured to:
The method comprises the steps of taking the product of a received signal and a gain factor as a first product, taking the norm of the difference between a transmitted signal and the first product as a second target norm, wherein the received signal is related to an uplink channel after correction and compensation, taking the second target norm as a second target expected function about the statistics characteristic parameters of calibration coefficient errors, the transmitted signal and the expectations of noise of a receiving end according to a wiener precoding algorithm, and determining a precoding matrix which takes the second target expected function as a minimum value and meets the power constraint condition as a target precoding matrix.
Optionally, the set precoding algorithm includes a minimum mean square error precoding algorithm, and the target precoding matrix determining module 320 is further configured to:
The method comprises the steps of taking a norm of a difference between a sending signal and a receiving signal as a third target norm, wherein the receiving signal is related to an uplink channel after correction and compensation, taking a statistic characteristic parameter of a third target norm about a calibration coefficient error, a sending signal and the expectation of receiving end noise as a third target expected function according to a minimum mean square error precoding algorithm, and determining a precoding matrix which enables the third target expected function to take a minimum value and meets a power constraint condition as a target precoding matrix.
The antenna system precoding device provided by the embodiment of the invention can execute the antenna system precoding method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example III
Fig. 4 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including an input unit 16, such as a keyboard, mouse, etc., an output unit 17, such as various types of displays, speakers, etc., a storage unit 18, such as a magnetic disk, optical disk, etc., and a communication unit 19, such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the antenna system precoding method.
In some embodiments, the antenna system precoding method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM13 and executed by processor 11, one or more of the steps of antenna system precoding described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the antenna system precoding method in any other suitable way (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be a special or general purpose programmable processor, operable to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user, for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a Local Area Network (LAN), a Wide Area Network (WAN), a blockchain network, and the Internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. An antenna system precoding method, comprising:
Acquiring an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix, and determining a corrected and compensated uplink channel according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix;
and determining a calibration coefficient error statistical characteristic parameter, and obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and combining a set precoding algorithm.
2. The method according to claim 1, wherein the setting the precoding algorithm includes a zero forcing precoding algorithm, and the obtaining the target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and in combination with the setting the precoding algorithm includes:
Taking the product of the precoding matrix and the downlink channel matrix and the norm of the difference between the precoding matrix and the unit matrix as a first target norm, wherein the downlink channel matrix is related to the corrected and compensated uplink channel;
According to the zero-forcing precoding algorithm, taking the expectation of the first target norm about the calibration coefficient error statistical characteristic parameter as a first target expected function;
and determining a precoding matrix with the minimum value of the first target expected function as the target precoding matrix.
3. The method of claim 2, further comprising, after obtaining the target precoding matrix:
And determining a power constraint factor, and determining the product of the power constraint factor and the target precoding matrix as an actual precoding matrix.
4. The method of claim 3 wherein the power constraint factor is determined based on a signal transmitter maximum transmit signal power and a signal transmitter initial transmit signal power that is not precoded.
5. The method according to claim 1, wherein the setting a precoding algorithm includes a wiener precoding algorithm, and the obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and in combination with the setting a precoding algorithm includes:
Taking the product of the received signal and the gain factor as a first product and taking the norm of the difference between the transmitted signal and the first product as a second target norm, wherein the received signal is related to the corrected and compensated uplink channel;
according to the wiener precoding algorithm, taking the second target norm as a second target expected function with respect to the calibration coefficient error statistical characteristic parameter, the sending signal and the expectation of the receiving end noise;
and determining a precoding matrix which enables the second target expected function to take a minimum value and meets a power constraint condition as the target precoding matrix.
6. The method of claim 1, wherein the setting a precoding algorithm includes a minimum mean square error precoding algorithm, and the obtaining the target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and in combination with the setting a precoding algorithm includes:
Taking the norm of the difference between the sending signal and the receiving signal as a third target norm, wherein the receiving signal is related to the corrected and compensated uplink channel;
According to the minimum mean square error precoding algorithm, taking the expectation of the third target norm about the calibration coefficient error statistical characteristic parameter, the sending signal and the noise of the receiving end as a third target expectation function;
And determining a precoding matrix which enables the third target expected function to take a minimum value and meets a power constraint condition as the target precoding matrix.
7. An antenna system precoding device, comprising:
The uplink channel determining module after correction and compensation is used for acquiring an initial uplink channel matrix, an access point side calibration coefficient matrix and a user equipment side calibration coefficient matrix and determining an uplink channel after correction and compensation according to the access point side calibration coefficient matrix and the user equipment side calibration coefficient matrix;
The target precoding matrix determining module is used for determining the calibration coefficient error statistical characteristic parameter, and obtaining a target precoding matrix according to the calibration coefficient error statistical characteristic parameter and the corrected and compensated uplink channel and combining a set precoding algorithm.
8. An electronic device, the electronic device comprising:
At least one processor, and
A memory communicatively coupled to the at least one processor, wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the antenna system precoding method of any one of claims 1-6.
9. A computer readable storage medium storing computer instructions for causing a processor to implement the antenna system precoding method of any one of claims 1-6 when executed.
10. A computer program product comprising computer program/instructions which, when executed by a processor, implement the steps of the antenna system precoding method of any of claims 1-6.
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