CN104869610B - A kind of method that same group of access base station cluster is chosen for multiple mobile stations - Google Patents

Abstract

The invention discloses a kind of method that same group of access base station cluster is chosen for multiple mobile stations, including：Parameter setting step：Set for represent the base station number higher limit in the cluster of base station multiple mobile stations of transmission channel vector between all optional base stations of degree of rarefication parameter, the upper limit of emission power value of each in multiple mobile stations, each in multiple mobile stations in the service quality higher limit of each and service quality level value；Update step：More wheels are carried out according to the parameter value set in Parameter setting step to virtual the down beam shaping matrix and virtual noise power set of multiple mobile stations to update, the difference between the virtual noise power set that two-wheeled updates to obtain as of late is less than the first threshold value set in advance；And selecting step：Mobile station is linked into the base station cluster indicated by the virtual down beam shaping matrix obtained as nearest one wheel renewal.

Description

A Method of Selecting the Same Group to Access Base Station Cluster for Multiple Mobile Stations

technical field

The invention relates to the field of mobile communication, in particular to a method for selecting the same group of access base station clusters for multiple mobile stations.

Background technique

In a mobile communication network, a mobile station can access multiple base stations at the same time, that is, multiple base stations provide services for a mobile station at the same time. These base stations that simultaneously provide services for a mobile station form a base station cluster.

When the mobile station needs to access the base station, it needs to decide through a certain method to access the base station cluster composed of which base stations. The Chinese patent application with application number 201410547339.3 and publication number 104301968A discloses a method for selecting access base station clusters for mobile stations. The main technical problem that the method can solve is to select different access base station clusters for each mobile station under the condition of ensuring the service quality (signal-to-interference ratio) of each mobile station. The main technical scheme adopted by the method is to directly calculate the access control matrix on the uplink under the assumption that the transmission power of all mobile stations is fixed.

The main problems in the above-mentioned existing method are: firstly, in the actual situation, the transmission power of the mobile station cannot be fixed; secondly, this method does not consider the fairness of service obtained between the mobile stations, and the result of the processing may be some Mobile stations have better quality of service, while some mobile stations have poorer quality of service. In addition, each mobile station independently selects a cluster of base stations to access, which may eventually cause all base stations to be in working state, increasing the complexity of system management. When the number of base stations is large, a large amount of energy needs to be consumed to maintain the basic expenses of these base stations.

Contents of the invention

The purpose of the present invention is to provide a method for selecting the same group of access base station clusters for multiple mobile stations.

An embodiment of the present invention provides a method for selecting the same group of mobile stations to access the base station cluster, including: parameter setting step: setting the sparsity used to represent the upper limit of the number of base stations in the base station cluster parameter, the transmit power ceiling value for each of the plurality of mobile stations, the transmission channel vector between each of the plurality of mobile stations and all optional base stations, and the quality of service ceiling value for each of the plurality of mobile stations and the service Quality lower limit value; update step: perform multiple rounds of updating on the virtual downlink beamforming matrix and virtual noise power set of multiple mobile stations according to the parameter values set in the parameter setting step, until the virtual noise power obtained by the latest two rounds of updating The difference between the power sets is smaller than the preset first threshold value; and the selection step: accessing the mobile station to the base station cluster indicated by the virtual downlink beamforming matrix obtained from the latest round of update.

The method for selecting the same group of mobile stations to access the base station cluster provided by the present invention can maximize the minimum signal-to-interference ratio among multiple mobile stations, and can also adjust and limit the transmission power of each mobile station according to actual network requirements. Further improve network performance.

Description of drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiment. The drawings are only for the purpose of illustrating a preferred embodiment and are not to be considered as limiting the invention. Also throughout the drawings, the same reference numerals are used to designate the same components. Wherein in the drawings, letter marks after reference numerals indicate a plurality of identical components, and when referring to these components generally, the last letter marks thereof will be omitted. In the attached picture:

Fig. 1 is the flowchart of an embodiment of the method for selecting the same group to access base station clusters for multiple mobile stations of the present invention;

Fig. 2 is the flowchart of an embodiment of the update step in the method of the present invention;

Fig. 3 is a flowchart of an embodiment of step 201 in Fig. 2;

FIG. 4 is a flowchart of an embodiment of step 202 in FIG. 2;

FIG. 5 is a flow chart of another embodiment of the method for selecting the same group for multiple mobile stations to access the base station cluster of the present invention.

In the drawings, the same or similar reference numerals are used to refer to the same or similar elements.

Detailed ways

Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the implementations shown and described in the drawings are only exemplary, intended to explain the principle and spirit of the present invention, rather than limit the scope of the present invention.

Referring to FIG. 1 , FIG. 1 is a flowchart of an embodiment of a method 100 for selecting the same group of mobile stations to access a base station cluster according to the present invention. The method 100 may include steps 101 to 103 as follows.

In step 101, the sparsity parameter used to indicate the upper limit of the number of base stations in the base station cluster, the upper limit of transmit power of each of the multiple mobile stations, the upper limit of the transmission power of each of the multiple mobile stations and all optional A transmission channel vector between base stations and a quality of service upper limit value and a quality of service lower limit value for each of the plurality of mobile stations.

The size of the sparsity parameter α may reflect the number of base stations in the base station cluster. Assuming that there are M mobile stations in total, and there are K base stations that may be selected, the upper limit value of the transmission power of each mobile station can be expressed as P _m , The transmission channel vector between each mobile station and all optional base stations can be expressed as Its dimension is KT×1, where T is the number of antennas of each base station. The QoS lower limit and QoS upper limit of each mobile station can be represented by γ _L and γ _u respectively.

In one embodiment of the present invention, the initial value of the quality of service lower limit The initial value of the quality of service upper limit Among them, σ ² is the noise power.

In step 102, according to the parameter values set in step 101, the virtual downlink beamforming matrices and virtual noise power sets of multiple mobile stations are updated for multiple rounds, until the virtual noise power sets obtained by the latest two rounds of updates are equal to The difference is smaller than the preset first threshold value.

In this step, the uplink problem that needs to be calculated can be converted into a virtual downlink problem based on the fact that the maximum and minimum fairness problem of the uplink and downlink of a single user under the condition of limited transmission power has the characteristics of duality solve.

In an embodiment of the present invention, the virtual downlink beamforming matrix can be expressed as:

Among them, the dimension of the virtual downlink beamforming matrix W is KT×M, K is the total number of selectable base stations, T is the number of antennas of each base station, and M is the total number of mobile stations; the dimension of the column vector w _m is KT × 1, which represents the transmit beams of all base stations to mobile station m, the column vector w _m can be expressed as Among them, the dimension of the column vector w _k,m is T×1, which represents the transmission beam of the k-th base station to the mobile station m; the dimension of the row block matrix W _k is T×M, which represents the transmission beam of the k-th base station to all mobile stations The station's transmit beam.

The virtual noise power set can be expressed as Among them, θ _m is the virtual noise power of mobile station m.

Referring to FIG. 2 , FIG. 2 is a flowchart of an embodiment of the updating step 102 in the method of the present invention. In an embodiment of the present invention, step 102 may include the following sub-steps 201 to 202 .

In sub-step 201, keep the virtual noise power set unchanged, and update the virtual downlink beamforming matrix multiple times.

When substep 201 is executed for the first time, the value in the virtual noise power set can be the value set during initialization, and when the subsequent cycle executes substep 201, the value in the virtual noise power set can be the last execution of substep 202 The virtual noise power value calculated at .

In an embodiment of the present invention, referring to FIG. 3 , substep 201 may further include the following substeps 301 to 305 .

In sub-step 301, an intermediate quality of service value is obtained according to the upper limit value of the quality of service and the lower limit value of the quality of service.

In one embodiment of the present invention, the service quality intermediate value γ=(γ _L +γ _u )/2.

In sub-step 302, a virtual downlink beamforming matrix is calculated according to the service quality median value, the virtual noise power set and the transmission channel vector.

In one embodiment of the present invention, substep 302 may include the following substeps 302-1 to 302-6:

In sub-step 302-1, set and initialize:

The first auxiliary matrix U ^(l) = W = H;

The second auxiliary matrix D ^(l) = [H ^H U, t];

Lagrangian matrix multiplier factor Z ^(l) =rand(K*T, M) corresponding to constraint condition U=W;

Lagrangian matrix multiplier factor Λ ^(l) =rand(M,M+1) corresponding to constraint D=[H ^H U,t] condition, where H=[h ₁ , h ₂ ,..., h _M ], W is the virtual downlink beamforming matrix, and l represents the number of times sub-step 302-2 is repeatedly executed. It is a set of virtual noise power, T represents the transpose operation of matrix or vector, rand(m,n) represents an m×n-dimensional random matrix, and the value of each element in the random matrix can be between 0 and 1 A random number from a uniform distribution.

In sub-step 302-2, the first auxiliary matrix is updated according to the following formula:

in, Represents the vector consisting of the rightmost column of the matrix D ^(l) , Indicates that the matrix D ^(l) except the remainder of Represents the vector consisting of the rightmost column of the matrix Λ ^(l) , Indicates that the matrix Λ ^(l) except The remaining part; the parameter c can choose a number greater than zero.

If κ _U = 0, it can make Then the value of κ _U is zero; otherwise, the value of κ _U can be searched such that Among them, Tr(.) means to find the trace of the matrix.

In sub-step 302-3, the virtual downlink beamforming matrix W is updated, and the kth row block of the virtual downlink beamforming matrix can be updated by the following formula:

Among them, β _k is the weight of base station k being selected into the base station cluster, Z _k and U _k are the kth row block of matrix Z and U, respectively, and have the same dimension as W _k . Among them, || || _F represents the F norm.

In sub-step 302-4, the second auxiliary matrix D is updated by the following formula:

Among them, d _m,-m represents the remaining part after removing the element d _m,m in the mth row of the second auxiliary matrix D; y _m represents the mth row of the matrix [H ^H U ^(l+1) ,t] , y _{m, m} represent the elements of the mth row m column of the matrix [H ^H U ^(l+1) ,t], y _{m, -m} is the remaining part after removing y _{m , m} in y m; Λ _m represents The m-th row of matrix Λ, Λ _{m, m} represents the m-th row and m-column elements of matrix Λ, Λ _m,-m is the remaining part after Λ _{m, m is} removed from Λ m.

when When: μ _m = 0;

when Time:

when When , d _m =0, that is, the mth row of matrix D is all 0;

Among them, || || ₂ represents the 2-norm.

In sub-step 302-5, update Z ^(l+1) = Z ^(l) + c(U ^(l+1) -W ^(l+1) ) and Λ ^(l+1) = Λ ^(l) + c(D ^(l+1) -[H ^H U ^(l+1) ,t]).

In substep 302-6,

When ||U ^(l+1) -U ^(l) || _F +||W ^(l+1) -W ^(l) || _F +||D ^(l+1) -D ^(l) || When _F +||Z ^(l+1) -Z ^(l) || _F +||Λ ^(l+1) -Λ ^(l) || _F ≤ _{a 1} , end sub-step 302 and enter sub-step 303, Otherwise, return to substep 302-2. Wherein, a ₁ is a preset termination threshold.

It should be emphasized that the execution sequence between substep 302-2 and substep 302-5 can be adjusted arbitrarily, that is, any one of these three substeps can be executed first, and then any one of the remaining two substeps can be executed. Execute the last remaining one.

In sub-step 303, the QoS upper limit and QoS lower limit are adjusted according to the comparison result between the calculated virtual downlink beamforming matrix and the sparsity parameter.

In an embodiment of the present invention, the calculated virtual downlink beamforming matrix can be compared with the sparsity parameter by the following rules:

If the calculated virtual downlink beamforming matrix W satisfies Then let γ _L =γ, otherwise let γ _u =γ. That is: adjust the size of the lower limit value γ _L of the service quality to be equal to the middle value γ of the service quality, or adjust the size of the upper limit value γ _u of the service quality to be equal to the middle value γ of the service quality.

In sub-step 304, the intermediate value of the quality of service is updated according to the adjusted upper limit of the quality of service and the adjusted lower limit of the quality of service.

In an embodiment of the present invention, the formula in sub-step 301 may be used to update the intermediate value of the quality of service.

In sub-step 305, when the difference between the QoS intermediate values obtained by the latest two updates is smaller than the second preset threshold value, a virtual downlink beamforming matrix is output.

In one embodiment of the present invention, the following inequality can be used to determine whether the difference between the service quality intermediate values obtained by the latest two updates is smaller than the preset second threshold value:

|γ ^(t) -γ ^(t-1) |<δ ₂

Among them, δ2 represents the preset _second threshold value, γ ^(t) represents the intermediate value of the service quality obtained in the t-th round of update, and γ ^(t-1) represents the service quality intermediate value obtained in the t-1th round of update , |.| means seeking the absolute value.

In an embodiment of the present invention, when the difference between the service quality intermediate values obtained from the latest two updates is not less than the preset second threshold value, the process may return to sub-step 301 .

In sub-step 202, the virtual downlink beamforming matrix is kept unchanged, and the virtual noise power set is updated multiple times.

In an embodiment of the present invention, referring to FIG. 4 , substep 202 may include the following substeps 401 to 405 .

In sub-step 401, an intermediate quality of service value is obtained according to the upper limit value of the quality of service and the lower limit value of the quality of service.

In one embodiment of the present invention, the service quality intermediate value γ=(γ _L +γ _u )/2.

In sub-step 402, a virtual noise power set is calculated according to the service quality intermediate value, the virtual downlink beamforming matrix and the transmission channel vector.

In one embodiment of the present invention, the virtual noise power set can be calculated by the following formula:

in

θ _m is the mth element in the virtual noise power set, namely: the virtual noise power of the mth mobile station, γ is the median value of service quality, w _m is the mth column block of the virtual downlink beamforming matrix, h _m is the transmission channel vector of the mth mobile station, is the conjugate transpose of h _m , and M is the total number of multiple mobile stations.

In sub-step 403, the upper limit value of the quality of service and the lower limit value of the quality of service are adjusted according to the comparison result of the calculated virtual noise power set and the upper limit value of the transmission power.

In an embodiment of the present invention, the virtual noise power set can be compared with the transmit power upper limit by the following rules:

when , adjust the lower limit value of the service quality to be equal to the middle value of the service quality, otherwise, adjust the size of the upper limit value of the service quality to be equal to the middle value of the service quality;

Among them, θ _m is the mth element in the virtual noise power set, P _m is the transmit power upper limit of the mth mobile station, and M is the total number of multiple mobile stations.

In sub-step 404, the intermediate value of the quality of service is updated according to the adjusted upper limit value of the quality of service and the adjusted lower limit value of the quality of service.

In an embodiment of the present invention, the formula in sub-step 401 may be used to update the intermediate value of the quality of service.

In sub-step 405, when the difference between the QoS intermediate values obtained from the latest two updates is smaller than a preset third threshold value, a virtual noise power set is output.

In one embodiment of the present invention, the following inequality can be used to determine whether the difference between the service quality intermediate values obtained by the latest two updates is smaller than the preset third threshold value:

|γ ^(t) -γ ^(t-1) |<δ ₃

Among them, _δ3 represents the preset third threshold value, γ ^(t) represents the intermediate value of the service quality obtained in the t-th round of update, and γ ^(t-1) represents the service quality intermediate value obtained in the t-1th round of update , |.| means seeking the absolute value.

It should be noted that the above-mentioned sub-steps 201 to 202 can be executed repeatedly, and after each execution, it can be judged whether the difference between the virtual noise power sets obtained in the latest two rounds of updates is smaller than the preset first threshold value. Specifically, it can be judged whether the following inequalities hold:

Wherein, τ represents a preset first threshold value, Indicates the virtual noise power of the mth mobile station obtained from the nth round of update, Indicates the virtual noise power of the mth mobile station obtained from the n-1th round of update.

If the inequality is true, then output the virtual downlink beamforming matrix and end step 102; otherwise, repeat step 102, that is, repeat and execute substep 201 to substep 202 in a loop.

It should be emphasized that the execution order of sub-step 201 and sub-step 202 can be exchanged, that is, sub-step 201 can be executed first, and then sub-step 202 can be executed; or sub-step 202 can be executed first, and then sub-step 201 can be executed.

In step 103, the mobile station is connected to the base station cluster indicated by the virtual downlink beamforming matrix obtained in the latest round of update.

When the difference between the virtual noise power sets obtained in the latest two rounds of updates is smaller than the preset first threshold, step 102 will output the virtual downlink beamforming matrix obtained in the latest round of updates. In an embodiment of the present invention, the mobile station can be connected to the base station corresponding to the non-zero row block in the matrix.

So far, an embodiment 100 of the method for selecting the same group of access base station clusters for multiple mobile stations according to the present invention has been described. The method can select the same group of access base station clusters for multiple mobile stations, and can maximize the minimum signal-to-interference ratio.

Referring to FIG. 5 , FIG. 5 shows another embodiment 500 of the method for selecting the same group of access base station clusters for multiple mobile stations of the present invention. Embodiment 500 may include steps 501 to 504, wherein steps 501 to 503 are similar to steps 101 to 103 described above, and will not be repeated here.

In step 504, the uplink beamforming and transmit power of the mobile station are calculated under the condition that the limitation of the sparsity parameter is removed.

In one embodiment of the present invention, step 504 may include the following sub-steps 504-1 to 504-6.

In sub-step 504-1, calculate the uplink beamforming vector

in, Represents the uplink beamforming vector of mobile station m obtained when executing sub-step 504-1 for the ith time, σ ² is the noise power, I is the identity matrix, and M is the total number of mobile stations, Indicates the transmit power of the nth mobile station obtained when executing substep 504-3 for the i-1th time, Indicates the channel information between the nth mobile station and the selected base station providing access services for it, express The conjugate transpose of , (.) ^-1 means to invert the matrix.

In sub-step 504-2, the initial value of the signal-to-interference ratio is calculated:

In sub-step 504-3, the transmit power and signal-to-interference ratio of the mobile station are calculated:

For mobile station m, you can first pass the formula Calculate its transmit power Then the formula can be Adjust its transmit power.

Signal to Interference Ratio

in, Indicates the transmit power of mobile station m obtained when executing substep 504-3 for the jth time, Indicates the signal-to-interference ratio of mobile station m obtained when executing substep 504-3 for the jth time.

In substep 504-4, if Then enter sub-step 504-5, otherwise return to sub-step 504-3, where a ₂ is the preset termination threshold.

In substep 504-5, update Go to step 504-6.

In sub-step 504-6, if |γ ⁽ⁱ⁾ -γ ^(i-1) |<a ₃ , output the uplink beamforming and transmit power of the mobile station Otherwise, return to sub-step 504-1, where a ₃ is a preset termination threshold.

So far, another embodiment 500 of the method for selecting the same group of mobile stations to access the base station cluster of the present invention has been described. On the basis of embodiment 100, embodiment 500 can also adjust and limit the transmission power of each mobile station, and optimize the transmission power of each mobile station. Uplink beamforming of mobile stations.

Claims (8)

1. A method for selecting a same group of access base station clusters for a plurality of mobile stations is characterized by comprising the following steps:

parameter setting step: setting a sparsity parameter for indicating an upper limit value of the number of base stations in the base station cluster, an upper limit value of transmission power of each of the plurality of mobile stations, a transmission channel vector between each of the plurality of mobile stations and all optional base stations, and an upper limit value and a lower limit value of quality of service of each of the plurality of mobile stations;

an updating step: performing multiple rounds of updating on the virtual downlink beamforming matrixes and the virtual noise power sets of the mobile stations according to the parameter values set in the parameter setting step until the difference between the virtual noise power sets obtained by the last two rounds of updating is smaller than a preset first threshold value; and

selecting: and accessing the mobile station to a base station cluster indicated by the virtual downlink beamforming matrix obtained by the latest round of updating.

2. The method of claim 1, wherein the updating step further comprises:

keeping the virtual noise power set unchanged, and updating the virtual downlink beamforming matrix for multiple times; and

and keeping the virtual downlink beamforming matrix unchanged, and updating the virtual noise power set for multiple times.

3. The method of claim 2, wherein the step of updating the virtual downlink beamforming matrix a plurality of times while keeping the virtual noise power set unchanged further comprises:

obtaining a service quality intermediate value according to the service quality upper limit value and the service quality lower limit value;

calculating the virtual downlink beamforming matrix according to the service quality intermediate value, the virtual noise power set and the transmission channel vector;

adjusting the upper limit value and the lower limit value of the service quality according to the comparison result of the virtual downlink beamforming matrix and the sparsity parameter obtained through calculation;

updating the service quality intermediate value according to the adjusted service quality upper limit value and the adjusted service quality lower limit value; and

and when the difference of the service quality intermediate values obtained by the latest two updates is smaller than a preset second threshold value, outputting the virtual downlink beamforming matrix.

4. The method as claimed in claim 3, wherein the step of adjusting the upper limit value and the lower limit value of the quality of service according to the comparison result of the computed virtual downlink beamforming matrix and the sparsity parameter further comprises:

when in useIf not, adjusting the size of the service quality upper limit value to be equal to the service quality middle value;

wherein α is the sparsity parameter, w_kis the K-th line block in the virtual downlink beamforming matrix, K is the total number of the selectable base stations, β_kIs the weight chosen for the kth.

5. The method of claim 2, wherein the step of updating the virtual noise power set multiple times while keeping the virtual downlink beamforming matrix unchanged further comprises:

obtaining a service quality intermediate value according to the service quality upper limit value and the service quality lower limit value;

calculating the virtual noise power set according to the service quality intermediate value, the virtual downlink beamforming matrix and the transmission channel vector;

adjusting the upper limit value and the lower limit value of the service quality according to the comparison result of the virtual noise power set and the upper limit value of the transmitting power obtained by calculation;

updating the service quality intermediate value according to the adjusted service quality upper limit value and the adjusted service quality lower limit value; and

and when the difference of the service quality intermediate values obtained by the last two updates is smaller than a preset third threshold value, outputting the virtual noise power set.

6. The method of claim 5, wherein the step of calculating the virtual noise power set according to the QoS intermediate value, the virtual downlink beamforming matrix and the transmission channel vector further comprises:

according toCalculating the set of virtual noise powers;

wherein

θ_mFor the mth element in the virtual noise power set, γ is the quality of service median, w_mIs the m column block, h, of the virtual downlink beamforming matrix_mFor the transport channel vector of the mth mobile station,is h_mM is the total number of the mobile stations, w_nAnd H represents conjugate transpose for the nth column block of the virtual downlink beamforming matrix.

7. The method of claim 5, wherein the step of adjusting the upper and lower qos limits based on the comparison of the calculated virtual noise power set and the upper transmit power limit further comprises:

when in useIf not, adjusting the size of the service quality upper limit value to be equal to the service quality middle value;

wherein, theta_mFor the m-th element, P, in the virtual noise power set_mIs the upper limit value of the transmitting power of the mth mobile station, and M is the total number of the plurality of mobile stations.

8. The method of any of claims 1-7, further comprising:

and under the condition of removing the limitation of the sparsity parameter, calculating the uplink beam forming and the transmitting power of the mobile station.