JP2009303224A - Apparatus and method for simultaneous transmission user selection - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus and method for simultaneous transmission user selection. <P>SOLUTION: This method is used for a multi-user MIMO mobile communication system and includes an initialization step, a projection step to be implemented iteratively, a selection step, a calculation step and an updating step. When the number of times of repetitions is twice or more, a projection target to be used for calculating a projection matrix in the projection step is each of row vectors in H matrices corresponding to users included in a user group R. H denotes a matrix constituted with channel responses of users as row vectors. R denotes the prescribed number of users selected, in order starting from the user having a largest projection value, from among users other than the users selected in the last repetition process. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a mobile communication system, and more particularly to a simultaneous transmission user selection apparatus and method in a MIMO (Multi-Input Multi-Output) communication system.

  Multi-antenna technology is a key technology in next-generation mobile communications. In a multi-user downlink broadcast channel, one base station communicates with a plurality of mobile stations simultaneously, so it is necessary for the base station to suppress multi-user interference by performing precoding based on channel information. There are a plurality of precoding methods such as a linear ZF (Zero-Forcing) method and a non-linear method. The channel information may be accurate information or non-accurate limited information, for example, information based on quantization information or statistics based on a code book.

  Assume that the number of base stations in the cell is 1, the number of mobile stations is K, the base station has M transmit antennas, each mobile station has one receive antenna, and K> M.

The base station transmits one data stream to each user, the total number of data stream transmissions is A, and A ≦ M. The A-dimensional transmission vector s = [s ₁ , s ₂ ,..., S _A ] is transmitted from the M antennas by the M × A precoding transmission matrix T. User k's channel is an M-dimensional vector h _k .

  Under the above assumption, the received signal of user k is expressed as follows.

ｎ_kは、ノイズ信号を示す。

n _k represents a noise signal.

Assuming that each user can accurately estimate their channel response h _{k and} that the base station knows all user channel information, the base station selects the most appropriate A users from the K users. Maximize frequency utilization efficiency.

  In a conventional multi-antenna MIMO wireless multi-user system, simultaneous transmission user selection algorithms include an exhaustive search algorithm, a Greedy algorithm, and an improved greedy algorithm based on semi-orthogonal projection.

  In the exhaustive search algorithm, it is necessary for the base station to select the set that maximizes the frequency use efficiency after calculating the frequency use efficiency of all user sets.

When the number K of mobile stations is relatively large, the calculation amount for exhaustive search is very large, the calculation complexity reaches O (K ^M ), and there is usually no way to receive the calculation amount.

  In order to reduce the amount of computation, a greedy algorithm is proposed and includes the following steps in user selection.

In the initialization step, i = 0, G ₀ is a null space, S ₀ = 0, and H = [h ₁ ^H h ₂ ^H ... H _k ^H ] ^H. All row vectors are marked as not processed.

に従ってＧ_i-1の補空間に投影する。 In the projection step, i = i + 1 and all row vectors not processed in the H matrix are

Is projected onto the complementary space of G _i-1 .

S _i-1 indicates the user selected in the previous step i-1.

となる。 In the selection step selects a row vector that maximizes the projection value from p _k, which processed the mark for the corresponding row vector. That is

It becomes.

In the calculation step, the frequency use efficiency of the user set S _i is calculated.

に従ってｇ_iとＧ_iを更新する。 In the update step,

Update g _i and G _i according to

  The process from the projection step to the update step is repeatedly executed, and the process is stopped when A = M or the frequency utilization efficiency is not improved any more by repeating A ≦ M times.

  In the above greedy algorithm, every time it is repeated, all the unselected users are selected and processed. Among the users not selected in the previous step, the channel of a certain user and the selected user are selected. Therefore, it is meaningless to be projected in the subsequent iterative process because the correlation with the channel is large and the probability of being selected in the subsequent iterative process is very low. Therefore, an improved greedy algorithm based on semi-orthogonal projection has been proposed to solve the above-mentioned problem of greedy algorithm. In the subsequent iterative process, projection users are limited and the amount of calculation is reduced. Details include the following steps.

In the initialization step, i = 0, G ₀ is a null space, S ₀ = 0, and H = [h ₁ ^H h ₂ ^H ... H _k ^H ] ^H. All row vectors are marked as not processed.

に従ってＧ_i-1の補空間に投影する。 In the projection step, i = i + 1, and the row vector corresponding to the users in the user set R _i in the H matrix is

Is projected onto the complementary space of G _i-1 .

R _i is the cosine value of the angle formed by the projection of the channel direction g _i-1 (the user selected in the i-1 step) among the users not selected before the i th step from the threshold α. Show all small users.

である。 That is,

It is.

S _i-1 indicates the user selected in the previous i-1 step.

となる。 In the selection step, the row vector that maximizes the projection value is selected from R _i and the corresponding row vector is marked as processed. That is,

It becomes.

In the calculation step, the frequency use efficiency of the user set S _i is calculated.

に従ってｇ_iとＧ_iとを更新する。 In the update step,

Update g _i and G _i according to the following.

  The process from the projection step to the update step is repeatedly executed, and the process is stopped when A = M or the frequency utilization efficiency is not improved any more by repeating A ≦ M times.

  In the projection step, the improved greedy algorithm based on semi-orthogonal projection selects and projects only a part of users, so that the amount of calculation is reduced.

  However, in the projection step of the improved greedy algorithm based on semi-orthogonal projection, it is necessary to select a user to be projected based on α, but it is difficult to specify α in advance, and due to α, Even if the number of projected users is reduced, the calculation amount of the algorithm remains relatively large.

  An object of the present invention is to provide a simultaneous transmission user selection apparatus and method for reducing the amount of calculation for selecting simultaneous transmission users in a MIMO (Multi-Input Multi-Output, Multi-input, Multi-output) communication system. is there.

  To achieve the above object, according to an embodiment of the present invention, there is provided a method for selecting a simultaneous transmission user used in a multi-user-MIMO mobile communication system, an initialization step, a repetitive projection step, a selection step, A calculation step and an update step are included.

  When the number of repetitions is 2 or more, the projection target used for calculating the projection matrix in the projection step is a row vector in the H matrix corresponding to the user included in the user set R.

  H is a matrix in which the channel response of each user is configured as a row vector. R is a user selected a predetermined number in order from the largest projection value among users other than the user selected in the previous iteration process.

  In the above method, the predetermined number decreases as the number of repetitions increases.

  The method includes the following steps.

In the initialization step, i = 0, G ₀ is a null space, S ₀ = 0, and H = [h ₁ ^H h ₂ ^H ... H _k ^H ] ^H.

に従ってＧ_i-1の補空間に投影する。 In the projection step, i = i + 1, and the row vector corresponding to the users in the user set R _i in the H matrix is

Is projected onto the complementary space of G _i-1 .

R _i is L _i−1 users selected in order from the largest projection value among users other than the user selected in the previous iteration process.

である。

It is.

S _i-1 indicates the user selected in the previous i-1 step.

に従って、投影値を最大とするユーザをＲ_iから選択して、前のステップで選択されたユーザグループＳ_i-1と統合する。 In the selection step,

Accordingly, the user who maximizes the projection value is selected from R _i and integrated with the user group S _i-1 selected in the previous step.

In the calculation step, the frequency use efficiency of the user set S _i is calculated.

に従ってｇ_iとＧ_iを更新する。 In the update step,

Update g _i and G _i according to

The projection step to the update step are repeatedly executed until the number of users included in the user set S _i becomes equal to the number of transmission antennas or the frequency utilization efficiency does not improve any more.

  In order to more effectively realize the above object, the embodiment of the present invention further provides a simultaneous transmission user selection device used in a multi-user-MIMO mobile communication system, and performs an operation repeatedly with an initialization module. A projection module, a selection module, a calculation module, and an update module are included.

  When the number of repetitions is 2 or more, the projection module projects a row vector in the H matrix corresponding to the user included in the user set R.

  H is a matrix in which the channel response of each user is configured as a row vector. R is a user selected a predetermined number in order from the largest projection value among users other than the user selected in the previous iteration process.

  In the apparatus, the predetermined number decreases as the number of repetitions increases.

  According to the embodiment of the present invention, the following effects can be obtained.

First, in the specific embodiment of the present invention, L _i−1 users who maximize the projection value in the previous iteration process are selected and projection is performed again, so that if L _i is larger than M−i + 1. In an improved greedy algorithm based on semi-orthogonal projection, the iterative process can proceed, and since the threshold is too small, it does not become a problem that the iterative process cannot proceed, so it has relatively good robustness. .

  Second, since the method according to the present invention comprehensively considers the channel gain of the user and the correlation between the users, the method according to the embodiment of the present invention is selected as compared with the improved greedy algorithm based on semi-orthogonal projection. The set of users is more reasonable.

  Third, the amount of computation is effectively reduced.

2 shows a flow of a method according to an embodiment of the present invention. The structure of the apparatus of the Example of this invention is shown. 2 shows a simulation of the present invention. 2 shows a simulation of the present invention. 2 shows a simulation of the present invention.

  In the apparatus and method for selecting simultaneously transmitting users in a multi-antenna MIMO wireless multi-user system according to an embodiment of the present invention, the selection waiting user set by the improved greedy algorithm based on semi-orthogonal projection is improved to reduce the amount of calculation.

  The method for selecting simultaneous transmission users in the multi-antenna MIMO wireless multi-user system of the embodiment of the present invention includes the following steps as shown in FIG.

In the initialization step, i = 0, G ₀ is a null space, S ₀ = 0, and H = [h ₁ ^H h ₂ ^H ... h _k ^H ] ^H. All row vectors are marked as not processed.

に従ってＧ_i-1の補空間に投影して、投影行列を取得する。 In the projection step, i = i + 1, and the row vector corresponding to the users in the user set R _i in the H matrix is

To project to a complementary space of G _i-1 to obtain a projection matrix.

R _i is L _i−1 users selected in order from the largest projection value among users other than the user selected in the previous iteration process. R _i is shown as follows.

である。

It is.

S _i-1 indicates the user selected in the previous i-1 step. | R _i | indicates the number of users included in R _i .

に従って、投影値を最大とするユーザをＲ_iから選択して、前のステップで選択されたユーザグループＳ_i-1と統合して新たなユーザ集合Ｓ_ｉを獲得し、対応する行ベクトルを処理済みとマークする。 In the selection step,

, The user who maximizes the projection value is selected from R _i and integrated with the user group S _i-1 selected in the previous step to obtain a new user set S _i , and the corresponding row vector is processed Mark as finished.

In the calculation step, the frequency use efficiency of the user set S _i is calculated.

に従ってｇ_iとＧ_iを更新する。 In the update step,

Update g _i and G _i according to

  The steps from the projection step to the update step are repeatedly executed, and A <= M times are repeated, and the process stops when A = M or the frequency utilization efficiency is not improved any more.

Hereinafter, an actual example will be described. Suppose that there are 12 users. In the initialization step, i = 0, G ₀ is a null space, S ₀ = 0, H = [h ₁ ^H h ₂ ^H h ₃ ^H h ₄ ^H h ₅ ^H h ₆ ^H h ₇ ^H h ₈ ^H h ₉ ^H h ₁₀ ^H h ₁₁ ^H h ₁₂ ^H ] ^H.

When i = 1, not all row vectors have been processed. The user set R ₁ includes all 12 users. At this time, all 12 row vectors in H are projected onto the complementary space of G ₀ to obtain p _k = h _k .

When the user who maximizes the projection value is selected from the user set R ₁ and the user who maximizes the projection value is user 1, S ₁ = [1].

After calculating the frequency utilization efficiency of S ₁ = [1], g _i and G _i are updated. That is, g ₁ = p ₁ and G ₁ = [g ₁ ^H ] ^H.

When i = 2, the set R ₂ is projected at a projection step of i = 1 among other users (ie, users 2, 3, 4,..., 12) other than user 1 in the first iteration process. Assuming that the number of users is 7 (assuming L ₂ = 7), and the seven users are users 2, 4, 5, 7, 8, 9, and 11, the users 2, 4 The row vectors of 5, 7, 8, 9 and 11 are projected onto the complementary space of G ₁ = [g ₁ ^H ] ^H to obtain p _k .

Then, a user who maximizes the projection value is selected from the user set R ₂ (that is, including users _{2, 4, 5,} 7, 8, 9, and 11), and the user who maximizes the projection value is user 4. , S ₂ = [1,4].

The frequency utilization efficiency of the user set S ₂ = [1, 4] is calculated and updated.

That is, g ₂ = p ₄ and G ₂ = [g ₁ ^H , g ₂ ^H ] ^H.

When i = 3, the set R ₃ is a projection step of i = 2 in the second iteration process among other users (ie, users 2, 5, 7, 8, 9, 11) than the user 4 , 4 users (assuming L ₃ = 4) having the maximum projection value, and assuming that these 4 users are users 2, 5, 7, and 11, users 2, 5, 7, And 11 are projected onto the complementary space of G ₂ = [g ₁ ^H , g ₂ ^H ] ^H to obtain p _k .

Then, if the user who maximizes the projection value is selected from the user set R ₃ (that is, includes users 2, 5, 7, and 11), and the user who maximizes the projection value is user 2, S ₃ = [ 1, 4, 2].

The frequency utilization efficiency of the user set S ₃ = [1, 4, 2] is calculated and updated.

That is, _{g 3 = p 2, G 3} = [g 1 H, g 2 H, g 3 H] H.

  The above steps are performed until the number of selected users becomes equal to the number of antennas of the base station, or the frequency usage efficiency of the user set in the current iteration does not improve further than the frequency usage efficiency of the user set in the previous iteration. Run repeatedly.

In a specific embodiment of the present invention, it is necessary to select a predetermined number of users that maximizes the projection value in the previous projection step, which should decrease as the iterative process proceeds. That is, L ₁ > L ₂ > L ₃ > L ₄ >.

  From the above description, according to the method of the embodiment of the present invention, the following effects can be obtained.

First, if L _i is larger than M−i + 1, the iterative process can proceed, and in the improved greedy algorithm based on semi-orthogonal projection, there is no problem that the iterative process cannot proceed because the parameter to be selected is too small. Therefore, it has relatively excellent robustness.

  Second, since the method according to the present invention comprehensively considers the channel gain of the user and the correlation between the users, the method according to the embodiment of the present invention is selected as compared with the improved greedy algorithm based on semi-orthogonal projection. The set of users is more reasonable.

  Third, the amount of computation is effectively reduced.

  The amount of multiplication of the greedy algorithm is as follows.

半直交投影に基づく改良した欲張りアルゴリズムの掛け算の計算量は、次となる。

The complexity of the improved greedy algorithm based on semi-orthogonal projection is

一方、本発明の実施例の方法の掛け算の計算量は、次となる。

On the other hand, the amount of calculation in the method of the embodiment of the present invention is as follows.

Ｍ＝４、Ｋ＝３０というシミュレーション条件の元で、α＝０．５のとき、シミュレーションした結果、｜Ｒ₂｜＝１８、｜Ｒ₃｜＝１４、｜Ｒ₄｜＝９となる。このとき、半直交投影に基づく改良した欲張りアルゴリズムの対応する掛け算の計算量は３２６７である。

Under the simulation conditions of M = 4 and K = 30, when α = 0.5, the simulation results are | R ₂ | = 18, | R ₃ | = 14, and | R ₄ | = 9. At this time, the corresponding amount of multiplication of the improved greedy algorithm based on semi-orthogonal projection is 3267.

In the method according to the embodiment of the present invention, when L ₂ = 10, L ₃ = 8, and L ₄ = 6, the amount of multiplication is 2179.

  As shown in FIG. 2, the simultaneous transmission user selection apparatus according to the embodiment of the present invention is used in a multi-antenna MIMO wireless multi-user system. The apparatus includes an initialization module, a projection module, a selection module, a calculation module, an update module, and an output module.

The initialization module is used to install i, G ₀ , S ₀ , and H and marks all row vectors as unprocessed.

に従ってＧ_i-1の補空間に投影して投影行列を取得する。 The projection module generates a row vector corresponding to a user in the user set R _i in the H matrix,

Then, the projection matrix is obtained by projecting onto the complementary space of G _i−1 .

R _i is L _i−1 users selected in order from the largest projection value among users other than the user selected in the previous iteration process.

である。

It is.

S _i-1 indicates the user selected in the previous i-1 step. | R _i | indicates the number of users included in R _i .

となり、対応する行ベクトルを処理済みとマークする。 The selection module selects the user with the highest projection value from R _i and integrates it with the user group S _i-1 selected in the previous step, ie

And the corresponding row vector is marked as processed.

The calculation module calculates the frequency use efficiency of the user set S _i .

に従ってｇ_iとＧ_iを更新する。 The update module

Update g _i and G _i according to

  The output module stops when the number of repetitions becomes equal to M or when the frequency utilization efficiency of the user set is no longer improved, and outputs the user set finally obtained by the calculation module.

  The first simulation condition is shown as follows.

Number of base station transmit antennas: 4
Number of receiving antennas on the terminal: 1
Number of data streams for each user: 1
Precoding method: ZF-DP (Zero Forcing-Drity-Paper) precoding technology Number of users: 60

  FIG. 3 shows the change of the system data rate according to the SNR of the method of the embodiment of the present invention, the Greedy algorithm, and the improved greedy algorithm based on semi-orthogonal projection under the first simulation condition. The curve with “*”, the curve with “◯”, and the curve with “Δ” correspond to the method, the greedy algorithm, and the improved greedy algorithm based on the semi-orthogonal projection, respectively. . According to FIG. 3, the method of the embodiment of the present invention basically matches the system data rate compared with the improved greedy algorithm based on semi-orthogonal projection.

On the other hand, assuming that the computational complexity of the greedy algorithm is 1 under the first simulation condition, as can be seen from the actual simulation, in the method of the embodiment of the present invention, L ₂ = 10, L ₃ = 8, L _{When 4} = 6, the relative computational complexity is 0.16, and in the improved greedy algorithm based on semi-orthogonal projection, when α = 0.5, the relative computational complexity is 0.45. Therefore, under the first simulation condition, the computational complexity of the method of the embodiment of the present invention is 35.55% (0.16 / 0.45) of the computational complexity of the improved greedy algorithm based on semi-orthogonal projection. ) And the amount of calculation is effectively reduced.

  The second simulation condition is shown as follows.

Number of base station transmit antennas: 4
Number of receiving antennas on the terminal: 1
Number of data streams for each user: 1
Precoding method: ZF-DP (Zero Forcing-Drity-Paper) precoding technology Number of users: 30

  FIG. 4 shows the change in SNR of the system data rate of the improved greedy algorithm based on the method, greedy algorithm, and semi-orthogonal projection of the embodiment of the present invention under the second simulation condition. The curves with “*”, the curves with “◯”, and the curves with “△” correspond to the method of the embodiment of the present invention, the greedy algorithm, and the improved greedy algorithm based on semi-orthogonal projection, respectively. . According to FIG. 4, the method of the embodiment of the present invention has a somewhat improved system data rate compared to the improved greedy algorithm based on semi-orthogonal projection.

Assuming that the computational complexity of the greedy algorithm is 1, relative computational complexity when L ₂ = 10, L ₃ = 8, and L ₄ = 6 in the method of the embodiment of the present invention, as can be seen from the actual simulation. Is 0.32, and when α = 0.5 in the improved greedy algorithm based on semi-orthogonal projection, the relative computational complexity is 0.49. Thus, under the second simulation condition, the computational complexity of the method of the embodiment of the present invention is 65.31% (0.32 / 0.49) of the computational complexity of the improved greedy algorithm based on semi-orthogonal projection. ) And the amount of calculation is effectively reduced.

  The third simulation condition is as follows.

Number of base station transmit antennas: 4
Number of receiving antennas on the terminal: 1
Number of data streams for each user: 1
Precoding method: ZF-DP (Zero Forcing-Drity-Paper) precoding technology Number of users: 30
SNR: 10 dB

  FIG. 5 illustrates the system data rate calculation complexity of the improved greedy algorithm based on the variation and the semi-orthogonal projection of the method according to the embodiment of the present invention under the third simulation condition. The change according to is shown. The abscissa is the computational complexity, and the ordinate indicates the system data rate. The upper curve corresponds to the method of the embodiment of the present invention, and the lower curve corresponds to an improved greedy algorithm based on semi-orthogonal projection. As can be seen from FIG. 5, in the method of the embodiment of the present invention, when the computational complexity is 0.15, the system data rate is close to 27 bps / HZ, and when the computational complexity is 0.2, the system data rate is When it is close to 28 bps / HZ and the computational complexity is 0.25, the system data rate reaches 28 bps / HZ, and even if the computational complexity is further improved, the system data rate is maintained at about 28 bps / HZ. On the other hand, in the improved greedy algorithm based on semi-orthogonal projection, when the computational complexity is 0.15, the system data rate is about 16.5 bps / HZ, and when the computational complexity is 0.25, the system data rate is Although it is about 23 bps / HZ, the system data rate basically keeps 28 bps / HZ after the computational complexity exceeds 0.4. Therefore, compared to an improved greedy algorithm based on semi-orthogonal projection, the method of the embodiment of the present invention achieves or approaches optimum performance even when the computational complexity is relatively small (eg 0.2). Thus, the amount of calculation selected by the user is reduced.

  The above is only a preferred implementation mode of the present invention. For general engineers in the field, some modifications and modifications can be considered without departing from the principle of the present invention. However, it will be understood that these modifications and modifications are also within the protection scope of the present invention.

Claims (5)

A method for selecting simultaneous transmission users used in a multi-user MIMO mobile communication system, including an initialization step, a repetitive projection step, a selection step, a calculation step, and an update step,
When the number of repetitions is 2 or more, the projection target used for calculating the projection matrix in the projection step is a row vector in the H matrix corresponding to the user included in the user set R,
H is a matrix in which the channel response of each user is configured as a row vector,
R is a simultaneous transmission user selection method characterized in that a predetermined number of users are selected in order from the largest projection value among users other than the user selected in the previous repetitive process. In the selection method of the simultaneous transmission user of Claim 1,
The method of selecting simultaneous transmission users, wherein the predetermined number decreases as the number of repetitions increases. In the simultaneous transmission user selection method according to claim 1 or 2,
In the initialization step, i = 0, G ₀ is a null space, S ₀ = 0, and H = [h ₁ ^H h ₂ ^H ... H _k ^H ] ^H ,
In the projection step, i = i + 1, and the row vector corresponding to the users in the user set R _i in the H matrix is

According to G _i-1
R _i is L _i−1 users selected in order from the largest projection value among the users other than the user selected in the previous iteration process,

And
S _i-1 indicates the user selected in the previous i-1 step,
In the selection step, the user who maximizes the projection value is selected from R _i and integrated with the user group S _i-1 selected in the previous step, ie

And
In the calculation step, the frequency utilization efficiency of the user set S _i is calculated,
In the update step,

Update g _i and G _i according to
Simultaneous transmission user selection characterized in that the projection step to the update step are repeatedly executed until the number of users included in the user set S _i becomes equal to the number of transmission antennas or the frequency utilization efficiency does not improve any more. Method. A simultaneous transmission user selection device used in a multi-user MIMO mobile communication system, including an initialization module, a projection module that repeatedly performs operations, a selection module, a calculation module, and an update module,
When the number of iterations is 2 or more, the projection module projects a row vector in the H matrix corresponding to the users included in the user set R;
H is a matrix in which the channel response of each user is configured as a row vector,
The simultaneous transmission user selection device, wherein R is a user selected in a predetermined order from the largest projection value among users other than the user selected in the previous repetitive process. The simultaneous transmission user selection device according to claim 4,
The apparatus for selecting simultaneous transmission users, wherein the predetermined number decreases as the number of repetitions increases.

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