CN110445519A - Interference method and device between anti-group based on Signal to Interference plus Noise Ratio constraint - Google Patents
Interference method and device between anti-group based on Signal to Interference plus Noise Ratio constraint Download PDFInfo
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Abstract
It is a kind of based on Signal to Interference plus Noise Ratio constraint anti-group between interference method and device, which comprises building the extensive multiple-input and multiple-output frequency division duplex downlink system based on channel statistical；Approximation based on geographical location carries out user group division to user terminal；According to long-time statistical characteristic, first stage pre-coding matrix is formed by selected characteristic wave beam and Eigenvalues Decomposition；It is constrained based on the first stage pre-coding matrix and Signal to Interference plus Noise Ratio, forms second stage pre-coding matrix.Above-mentioned scheme can solve the problems, such as to interfere between interference and user group in group existing for user group, the total rate of lifting system when carrying out two stages Precoding Design.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to an inter-group interference resisting method and device based on signal-to-interference-and-noise ratio constraint.
Background
Massive Multiple Input Multiple Output (MIMO) is considered to be very likely to become one of the main transmission technologies of 5G systems, and has received intense attention in both academic and industrial fields. Most of the existing mobile communication systems adopt a Frequency-Division multiplexing (FDD) operating mode. In the frequency division duplex multiplexing mode, time-frequency resources required by uplink and downlink channel estimation are related to the number of base station antennas, and if a large-scale MIMO system works in the frequency division duplex multiplexing mode, the uplink and downlink resources far larger than those of the traditional MIMO system are required to realize channel estimation, so that a large amount of time-frequency resources are occupied, and the effective throughput of the system is reduced. Since coherent time-frequency resources of the system are limited, the number of users simultaneously served in each cell in the massive mimo system is limited, but the number of antennas of the base station is not limited.
In a large-scale mimo system, a linear data processing method is usually adopted, and the influence of channel fast fading and noise on the system performance is reduced as the number of antennas increases. Inter-cell pilot pollution becomes a major factor affecting the performance of large-scale mimo systems. Since the length of the pilot frequency is limited in the channel estimation of the fdd mimo system, users in different cells need to use the multiplexed or correlated pilot frequency sequence, which causes inter-cell interference of the pilot frequency signal and degrades the performance of the channel estimation, i.e. so-called "pilot pollution".
In view of the important role of frequency division duplex multiplexing in the current communication system, it is necessary to study how to apply the large-scale mimo technology to the fdd multiplexing system, and the most central problem is how to reduce the overhead of acquiring downlink CSI by the base station. The codebook-based limited feedback technology widely used in the conventional mimo system is only applicable to small-scale antenna arrays, and thus it is necessary to develop a new channel estimation scheme according to characteristics of large-scale mimo channels. A two-stage limited feedback precoding scheme is provided by combining JSDM (Joint Spatial Division and Multiplexing) and utilizing the Spatial correlation of channels, and the scheme is particularly suitable for large-scale MIMO channels and can greatly reduce the cost of channel estimation. When the joint space division multiplexing scheme is used for carrying out two-stage precoding design, the problems of intra-group interference and inter-user group interference of user terminal grouping exist, and the improvement of the total rate of the system is severely limited.
Disclosure of Invention
The technical problem solved by the invention is how to solve the problems of the intra-group interference and the inter-user-group interference existing in the user group when the two-stage precoding design is carried out, and the total rate of the system is improved.
In order to achieve the above object, the present invention provides an inter-group interference resisting method based on signal-to-interference-and-noise ratio constraints, the method comprising:
constructing a large-scale multi-input multi-output frequency division duplex downlink system based on channel statistics;
based on the similarity of the geographic position, dividing user groups of the user terminals;
according to the long-term statistical characteristics, a first-stage pre-coding matrix is formed by selecting eigen beams and decomposing eigenvalues;
and forming a second-stage precoding matrix based on the first-stage precoding matrix and the signal-to-interference-and-noise ratio constraint.
Optionally, the forming a first-stage precoding matrix by selecting eigen beams and eigenvalue decomposition according to the long-term statistical characteristics includes:
acquiring a channel covariance matrix of effective channel coherence time average of a user group;
performing eigenvalue decomposition on the channel covariance matrix to obtain an eigenvector and an eigenvalue of the channel covariance matrix;
and selecting a column vector which enables the value of a diagonal matrix formed by the eigenvalues to be maximum from the eigenvectors of the channel covariance matrix to form the first-stage precoding matrix.
Optionally, the first-stage precoding matrix is:
Bg＝Ug(Sg)；
wherein, BgRepresenting the first-stage precoding matrix, UgAn eigenvector, S, representing the channel covariance matrixgTo representAnd selecting a column vector which enables the value of a diagonal matrix formed by the characteristic values to be maximum from the characteristic vectors of the channel covariance matrix.
Optionally, the forming a second-stage precoding matrix based on the first-stage precoding matrix and the signal-to-interference-and-noise ratio constraint includes:
acquiring the information of the signal-to-interference-and-noise ratio of each user terminal;
introducing an interference coefficient for limiting the user terminals of the adjacent user groups into the constraint denominator of the signal-to-interference-and-noise ratio of each user terminal, and converting the problem of solving the maximum sum rate of the system under the minimum interference into the problem of solving the inter-group interference constraint problem;
and converting the non-convex solving inter-group interference constraint problem into a corresponding near-vision convex set problem by adopting a continuous convex approximation method and solving to obtain the second precoding matrix.
The embodiment of the invention also provides an inter-group interference resisting device based on the signal-to-interference-and-noise ratio constraint, which comprises:
the building unit is suitable for building a large-scale MIMO frequency division duplex downlink system based on channel statistics;
the dividing unit is suitable for dividing the user group of the user terminal based on the similarity of the geographic position;
the first pre-coding unit is suitable for forming a first-stage pre-coding matrix by selecting the eigen beams and decomposing the eigenvalues according to the long-term statistical characteristics;
and the second precoding unit is suitable for forming a second-stage precoding matrix based on the first-stage precoding matrix and the signal-to-interference-and-noise ratio constraint.
Optionally, the first-stage precoding unit is adapted to obtain a channel covariance matrix of an effective channel coherence time average of a user group; performing eigenvalue decomposition on the channel covariance matrix to obtain an eigenvector and an eigenvalue of the channel covariance matrix; and selecting a column vector which enables the value of a diagonal matrix formed by the eigenvalues to be maximum from the eigenvalues of the channel covariance matrix to form the first-stage pre-coding matrix.
Optionally, the first-stage precoding matrix constructed by the first-stage precoding unit is:
Bg＝Ug(Sg)；
wherein, BgRepresenting the first-stage precoding matrix, UgAn eigenvector, S, representing the channel covariance matrixgAnd the column vector which is selected from the eigenvectors of the channel covariance matrix and enables the value of a diagonal matrix formed by the eigenvalues to be maximum is shown.
Optionally, the second-stage precoding unit is adapted to obtain information of a signal-to-interference-and-noise ratio of each user equipment; introducing an interference coefficient for limiting the user terminals of the adjacent user groups into the constraint denominator of the signal-to-interference-and-noise ratio of each user terminal, and converting the maximum sum rate problem of the system under the minimum interference solving into the problem of solving the inter-group interference constraint; and converting the non-convex solving inter-group interference constraint problem into a corresponding near-vision convex set problem by adopting a continuous convex approximation method and solving to obtain the second precoding matrix.
Compared with the prior art, the invention has the beneficial effects that:
according to the scheme, a large-scale MIMO-FDD downlink system based on channel statistics is constructed, the user terminals are divided into user groups based on the similarity of geographic positions, the first-stage precoding matrix is formed by selecting eigen beams and eigenvalues according to long-term statistical characteristics and decomposing, and the second-stage precoding matrix is formed based on the first-stage precoding matrix and signal-to-interference-and-noise-ratio constraints, so that the intra-group interference and the inter-user-group interference existing in the user groups can be eliminated, and the total rate of the system is improved.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a schematic flowchart of an inter-group interference rejection method based on signal-to-interference-and-noise ratio constraints according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating experimental results of system performance simulation under different encoding methods;
fig. 3 is a schematic structural diagram illustrating an inter-group interference rejection apparatus based on a signal-to-interference-and-noise ratio constraint according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. The directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indication is changed accordingly.
As described in the background art, when a joint space division multiplexing scheme is used to perform two-stage precoding design in the prior art, the problems of intra-group interference and inter-user group interference of user terminal grouping exist, which severely limits the increase of the total rate of the system.
According to the technical scheme, a large-scale MIMO frequency division duplex downlink system based on channel statistics is constructed, user groups of user terminals are divided based on the similarity of geographic positions, according to long-term statistical characteristics, a first-stage precoding matrix is formed by selecting eigen beams and eigenvalues and decomposing the eigen beams and the eigenvalues, a second-stage precoding matrix is formed based on the first-stage precoding matrix and signal-to-interference-plus-noise ratio constraints, intra-group interference and inter-user group interference existing in the user groups can be eliminated, and the total rate of the system is improved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Fig. 1 is a schematic flowchart of an inter-group interference rejection method based on signal-to-interference-and-noise ratio constraints according to an embodiment of the present invention. Referring to fig. 1, a method for resisting inter-group interference based on signal-to-interference-and-noise ratio constraints may specifically include the following steps:
step S101: and constructing a large-scale MIMO frequency division duplex downlink system based on channel statistics.
In a specific implementation, the system comprises a single base station signal transmitting end with multiple antennas and a plurality of user terminals with single antennas. The sending end of the base station is provided with M antennas, and the base station simultaneously serves K single-antenna user terminals. To reduce the complexity of the analysis, in terms of transmit antenna correlation, a single loop model is used, the distance from the user terminal to the antenna is S, the azimuth angle is θ, the terminal is surrounded by a circular scatterer of radius r, and the Angular Spread (AS) Δ ≈ arctan (r/S).
Then, the downlink reception signal of the channel can be expressed as:
wherein Y represents a K-dimensional signal vector received by the Kth user terminal, x is an M-dimensional signal vector transmitted by the base station with M antennas, and z-CN (0, I)K) Is white Gaussian noise, hk～CN(0，RK) Is the M-dimensional channel vector for user terminal K.
Next, the user terminal channel vector { h } can be transformed using the Karhunen-Loeve expressionkExpressed as:
wherein, wk～CN(0，I)，RKIs a symmetric semi-positive definite channel covariance matrix, ΛKIs RKR x r dimensional diagonal composed of non-zero eigenvalues ofArray, UKIs RKThe high-order unitary matrix is formed by the eigenvectors corresponding to the nonzero eigenvalue.
The base station may represent the transmission signal as:
X＝Vd (4)
where d is the S-dimensional data symbol vector that needs to be sent to the user terminal.
Step S102: and based on the approximation of the geographic position, carrying out user group division on the user terminals.
In the implementation, it is assumed that the received power of plane waves from the base station antenna is uniformly distributed, and although the user terminals are uniformly distributed around the base station, they may often be interworked in geographical locations, so as to form a natural user cluster, and the base station considers the cluster when designing the transmission strategy.
Step S103: and according to the long-term statistical characteristics, a first-stage precoding matrix is formed by selecting the eigenbeams and decomposing the eigenvalues.
In the specific implementation, the K user terminals are divided into G user groups, KgIndicating the number of user terminals, u, in the user group ggRepresenting the number of user terminals, S, in a user group ggRepresenting a statistical beam, B, directed to each user in the group g of usersgFor all the statistical beams corresponding to the ues in the ue group g, there is B ═ B1 ... Bg]，wkIs KgAnd the second-stage precoding matrix of the Kth user terminal. The data transmitted to the Kth user terminal is dK，zkIs gaussian white noise. Therefore, the reception signal of the kth ue is:
in the above equation (5), the first term on the right side of the equationFor useful signals the user terminal expects to receive, item twoThe signal transmitted by the base station to other ues in the group is the interfering signal in the group relative to the kth ue in the group, and the third termFourth term z for inter-user group interferenceKIs gaussian white noise.
Therefore, the signal-to-interference-and-noise ratio of the kth user terminal can be expressed as:
then the sum rate of the system is:
wherein R represents the sum rate of the system, αKIndicating the weight determining the scheduling priority of user terminal K.
Assuming that the channel statistical characteristics of all the user terminals remain unchanged for a period of time, in this case, the channel covariance matrix may be decomposed by an Eigenvalue (EVD) to obtain its eigenvector and its corresponding eigenvalue, so as to construct the first-stage precoding matrix.
By usingRepresenting the superposition of all channel matrices in the user group g,
by usingA channel covariance matrix representing an effective channel coherence time average. Channel covariance matrix R averaged over effective channel coherence timegBy performing eigenvalue decomposition (EVD), one can obtain:
wherein,for the channel covariance matrix RgIs used to generate a matrix of feature vectors,for the channel covariance matrix RgThe feature vectors of (a) form a diagonal matrix with corresponding feature values.
In a specific implementation, U is now passedgSelected column vector SgSo that S isgCorresponding diagonal array LambdagThe eigenvalue of (d) is the maximum. Then, the first-stage precoding matrix can be obtained as:
Bg＝Ug(Sg) (9)
wherein, BgRepresenting the first-stage precoding matrix, UgAn eigenvector, S, representing the channel covariance matrixgAnd the column vector which is selected from the eigenvectors of the channel covariance matrix and enables the value of a diagonal matrix formed by the eigenvalues to be maximum is shown.
At the same time, a selected column vector S is obtainedgCombined new matrix Ug。
Step S104: and forming a second-stage precoding matrix based on the first-stage precoding matrix and the signal-to-interference-and-noise ratio constraint.
In a specific implementation, the main purpose of the second-stage precoding is to maximize the received power of the target ue, and at the same time minimize the interference to other ues in the same group and ues in other groups. But the limited number of transmit antennas M necessarily results in energy leakage to the adjacent groups due to the presence of statistical beam sidelobes. For this purpose, inter-group interference optimization is first performed to improve the system and speed.
To design a reduced-dimension pre-beamformer for each user group, the interference term of the constraint denominator of each user terminal in the above-mentioned SINR expression is expressed as
Wherein,in order to limit the interference coefficient of the adjacent user group f belonging to G, f is not equal to G to the user terminal, namely the interference coefficient is the second term corresponding to the right denominator of the equal sign of the formula (6).
By introducing a new variable ζf,kThen, specific groups are coordinated among user groupsThreshold values, the precoding matrix of the second stage can be designed for each user group. The problem is therefore solved by finding the maximum sum rate for the minimum interference case shown in equation (12)
The method is converted into an interclass interference constraint problem shown in an equation (13).
Because the above formula is a non-convex problem, a convergence solution cannot be solved, and therefore a continuous convex approximation technology is adopted, the non-convex problem is replaced by a near-vision convex subset problem, and iterative solution is carried out until convergence is achieved. The left equation of the above equation is convex, so some operating points are selectedA taylor approximation of a quadratic linear function is used nearby, and the following are provided:
solving the approximate convex equation using the above approximate equation is as follows:
wherein λ iskAndfor each user terminal in the system, a constraint coefficient, pgFor each power constraint factor, θ, of the user terminal groupg,kTo restrainThe interference coefficient at a fixed value. The Karush-Kuhn-Tucker conditional constraint variable is assumed to be lambdak,θg,k，ρgThe lagrange expression is classified as a constraint variable of the above-mentioned inequality
Respectively to gammak,βk,wkThe derivation is as follows:
the Karush-Kuhn-Tucker condition constraint is:
wherein by fixing lambdak> 0 andcan solve gammakAnd betakTo satisfy the IGI constraint, its bivariate θg,iSolving for the second-stage precoding w by iterative solving, substituting (15), (16), (17), (18)g。
Fig. 2 shows a schematic diagram of system performance simulation experiment results under different encoding methods. Wherein, the simulation experiment adopts a uniform linear antenna array, and the base station is provided with 64 uniform arrays to simultaneously serve 16 independent single-antenna user terminals. These user terminals are randomly distributed within the base station sector. These subscriber terminals are divided into 4 subscriber groups,and total power Psum20 dB. FromAs shown in the results of fig. 2, the total rate of the method provided by the present invention is similar to the total rate performance under an ideal condition, and the theoretical result is consistent with the simulation result.
The above detailed description is provided for the method for resisting inter-group interference based on the signal-to-interference-and-noise-ratio constraint in the embodiment of the present invention, and apparatuses corresponding to the above method will be described below.
Fig. 3 is a schematic structural diagram illustrating an inter-group interference rejection apparatus based on a signal-to-interference-and-noise ratio constraint according to an embodiment of the present invention. Referring to fig. 3, an inter-group interference rejection apparatus 30 based on the signal-to-interference-and-noise ratio constraint may include a constructing unit 301, a dividing unit 302, a first precoding unit 303, and a second precoding unit 304, where:
the constructing unit 301 is adapted to construct a large-scale mimo-ofdm downlink system based on channel statistics;
the dividing unit 302 is adapted to divide the user group of the user terminals based on the proximity of the geographic location;
the first precoding unit 303 is adapted to form a first-stage precoding matrix by selecting a eigen beam and decomposing an eigenvalue according to long-term statistical characteristics; in an embodiment of the present invention, the first-stage precoding unit 303 is adapted to obtain a channel covariance matrix of an effective channel coherence time average of a user group; performing eigenvalue decomposition on the channel covariance matrix to obtain an eigenvector and an eigenvalue of the channel covariance matrix; and selecting a column vector which enables the value of a diagonal matrix formed by the eigenvalues to be maximum from the eigenvectors of the channel covariance matrix to form the first-stage precoding matrix. Wherein the first-stage precoding matrix constructed by the first-stage precoding unit is: b isg＝Ug(Sg) (ii) a Wherein, BgRepresenting the first-stage precoding matrix, UgAn eigenvector, S, representing the channel covariance matrixgAnd the column vector which enables the value of a diagonal matrix formed by the eigenvalues to be maximum is selected from the eigenvectors of the channel covariance matrix.
The second precoding unit 304 is adapted to form a second-stage precoding matrix based on the first-stage precoding matrix and the signal-to-interference-and-noise ratio constraint.
In an embodiment of the present invention, the second-stage precoding unit 304 is adapted to obtain information of a signal to interference plus noise ratio of each ue; introducing an interference coefficient for limiting the user terminals of the adjacent user groups into the constraint denominator of the signal-to-interference-and-noise ratio of each user terminal, and converting the problem of solving the maximum sum rate of the system under the minimum interference into the problem of solving the inter-group interference constraint; and converting the non-convex solving inter-group interference constraint problem into a corresponding near-vision convex set problem by adopting a continuous convex approximation method and solving to obtain the second precoding matrix.
According to the scheme in the embodiment of the invention, a large-scale MIMO-FDD downlink system based on channel statistics is constructed, the user terminals are divided into user groups based on the similarity of geographic positions, a first-stage precoding matrix is formed by selecting eigen beams and eigenvalues according to long-term statistical characteristics and is decomposed based on the first-stage precoding matrix and signal-to-interference-and-noise ratio constraints, a second-stage precoding matrix is formed, the intra-group interference and the inter-user group interference existing in the user groups can be eliminated, and the total rate of the system is increased.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined by the appended claims, the description, and equivalents thereof.
Claims (8)
1. An inter-group interference resisting method based on signal-to-interference-and-noise ratio constraint is characterized by comprising the following steps:
constructing a large-scale multi-input multi-output frequency division duplex downlink system based on channel statistics;
based on the similarity of the geographic position, dividing user groups of the user terminals;
according to the long-term statistical characteristics, a first-stage pre-coding matrix is formed by selecting eigen beams and decomposing eigenvalues;
and forming a second-stage precoding matrix based on the first-stage precoding matrix and the signal-to-interference-and-noise ratio constraint.
2. The method of claim 1, wherein the forming a first-stage precoding matrix by selecting eigenbeams and eigenvalue decomposition according to long-term statistical characteristics comprises:
acquiring a channel covariance matrix of effective channel coherence time average of a user group;
performing eigenvalue decomposition on the channel covariance matrix to obtain an eigenvector and an eigenvalue of the channel covariance matrix;
and selecting a column vector which enables the value of a diagonal matrix formed by the eigenvalues to be maximum from the eigenvectors of the channel covariance matrix to form the first-stage precoding matrix.
3. The method of claim 2, wherein the first-stage precoding matrix is:
Bg＝Ug(Sg)；
wherein, BgRepresenting the first-stage precoding matrix, UgAn eigenvector, S, representing the channel covariance matrixgAnd representing a column vector which is selected from the eigenvectors of the channel covariance matrix and enables the value of a diagonal matrix formed by the eigenvalues to be maximum.
4. The method of any of claims 1-3, wherein forming a second-stage precoding matrix based on the first-stage precoding matrix and the SINR constraint comprises:
acquiring the information of the signal-to-interference-and-noise ratio of each user terminal;
introducing an interference coefficient for limiting the user terminals of the adjacent user groups into the constraint denominator of the signal-to-interference-and-noise ratio of each user terminal, and converting the problem of solving the maximum sum rate of the system under the minimum interference into the problem of solving the inter-group interference constraint;
and converting the non-convex solving inter-group interference constraint problem into a corresponding near-vision convex set problem by adopting a continuous convex approximation method and solving to obtain the second-stage precoding matrix.
5. An apparatus for resisting inter-group interference based on signal-to-interference-and-noise ratio (SINR) constraint, comprising:
the building unit is suitable for building a large-scale MIMO frequency division duplex downlink system based on channel statistics;
the dividing unit is suitable for dividing the user group of the user terminal based on the similarity of the geographic position;
the first pre-coding unit is suitable for forming a first-stage pre-coding matrix by selecting the eigen-beams and decomposing the eigen-values according to long-term statistical characteristics;
and the second precoding unit is suitable for forming a second-stage precoding matrix based on the first-stage precoding matrix and the signal-to-interference-and-noise ratio constraint.
6. The apparatus according to claim 5, wherein the first-stage precoding unit is adapted to obtain a channel covariance matrix of an effective channel coherence time average of a user group; performing eigenvalue decomposition on the channel covariance matrix to obtain an eigenvector and an eigenvalue of the channel covariance matrix; and selecting a column vector which enables the value of a diagonal matrix formed by the eigenvalues to be maximum from the eigenvectors of the channel covariance matrix to form the first-stage precoding matrix.
7. The apparatus according to claim 6, wherein the first-stage precoding matrix constructed by the first-stage precoding unit is:
Bg＝Ug(Sg)；
wherein, BgRepresenting the first-stage precoding matrix, UgAn eigenvector, S, representing the channel covariance matrixgAnd representing a column vector which is selected from the eigenvectors of the channel covariance matrix and enables the value of a diagonal matrix formed by the eigenvalues to be maximum.
8. The apparatus according to any of claims 5-7, wherein the second-stage pre-coding unit is adapted to obtain information of the sir of each ue; introducing an interference coefficient for limiting the user terminals of the adjacent user groups into the constraint denominator of the signal-to-interference-and-noise ratio of each user terminal, and converting the problem of solving the maximum sum rate of the system under the minimum interference into the problem of solving the inter-group interference constraint; and converting the non-convex solving inter-group interference constraint problem into a corresponding near-vision convex set problem by adopting a continuous convex approximation method and solving to obtain the second-stage precoding matrix.
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