CN104869610A - Method of selecting same group of access base station cluster for plurality of mobile stations - Google Patents
Method of selecting same group of access base station cluster for plurality of mobile stations Download PDFInfo
- Publication number
- CN104869610A CN104869610A CN201510239789.0A CN201510239789A CN104869610A CN 104869610 A CN104869610 A CN 104869610A CN 201510239789 A CN201510239789 A CN 201510239789A CN 104869610 A CN104869610 A CN 104869610A
- Authority
- CN
- China
- Prior art keywords
- mrow
- limit value
- virtual
- service quality
- msubsup
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 37
- 239000011159 matrix material Substances 0.000 claims abstract description 58
- 230000005540 biological transmission Effects 0.000 claims abstract description 18
- 238000010586 diagram Methods 0.000 description 2
- 238000010295 mobile communication Methods 0.000 description 2
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W48/00—Access restriction; Network selection; Access point selection
- H04W48/08—Access restriction or access information delivery, e.g. discovery data delivery
Landscapes
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses a method of selecting the same group of access base station cluster for a plurality of mobile stations. The method comprises a parameter setting step: setting a sparseness parameter of a upper limit value of the number of base stations in a base station cluster, an emission power upper limit value of each of the plurality of mobile stations, a transmission channel vector between each of the plurality of mobile stations and a selectable base station, and a service quality upper limit value and a service quality lower limit value of each of the plurality of mobile stations; an updating step: according to the parameter values set in the parameter setting step, carrying out multiple rounds of updating on a virtual downlink beam-forming matrix and a virtual noise power set of the plurality of mobile stations until the difference of the virtual noise power sets obtained by the closest two rounds of updating is smaller than a preset first threshold; and a selecting step: accessing the mobile stations to the base station cluster indicated by the virtual downlink beam-forming matrix obtained in the latest round of updating.
Description
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 a plurality of mobile stations.
Background
In a mobile communication network, a mobile station can access a plurality of base stations simultaneously, namely: a mobile station is served simultaneously by a plurality of base stations. The base stations that serve a mobile station at the same time form a cluster of base stations.
When a mobile station needs to access a base station, a certain method is needed to determine which base stations form a base station cluster to which the mobile station is accessed. Chinese patent application No. 201410547339.3, publication No. 104301968a, discloses a method for selecting an access base station cluster for a mobile station. The method can mainly solve the technical problem that different access base station clusters are selected for each mobile station under the condition of ensuring the service quality (signal-to-interference ratio) of each mobile station. The method adopts the main technical scheme that the access control matrix is directly calculated on the uplink on the premise of assuming that the transmitting power of all the mobile stations is fixed and unchanged.
The main problems of the existing methods are as follows: firstly, in practical situations, the transmission power of the mobile stations cannot be fixed, secondly, the method does not consider the fairness of obtaining service among the mobile stations, and the processing result may be that the service quality of some mobile stations is better and the service quality of some mobile stations is worse. In addition, each mobile station independently selects a base station cluster to be accessed, which may result in that all base stations must be in an operating state finally, and the complexity of system management is increased. When the number of base stations is large, a large amount of energy is consumed to maintain the basic overhead of the base stations.
Disclosure of Invention
The invention aims to provide a method for selecting the same group of access base station clusters for a plurality of mobile stations.
One embodiment of the present invention provides a method for selecting a same group of access base station clusters for a plurality of mobile stations, comprising: parameter setting step: setting a sparsity parameter for representing an upper limit value of the number of base stations in a base station cluster, an upper limit value of transmission power of each of a plurality of mobile stations, a transmission channel vector between each of the plurality of mobile stations and all selectable base stations, and an upper limit value and a lower limit value of service quality 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 multiple 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 latest two rounds of updating is smaller than a preset first threshold value; and a selection step: and accessing the mobile station to a base station cluster indicated by the virtual downlink beamforming matrix obtained by the latest round of updating.
The method for selecting the same group of access base station clusters for the plurality of mobile stations can maximize the minimum signal-to-interference ratio in the plurality of mobile stations, can adjust and limit the sending power of each mobile station according to the actual network requirements, and further improves the network performance.
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 embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. Wherein like reference numerals are followed by like parts throughout the several views, the last letter designation thereof will be omitted when referring generally to these parts. In the drawings:
FIG. 1 is a flowchart of an embodiment of a method for selecting a same access base station cluster for a plurality of mobile stations according to the present invention;
FIG. 2 is a flow chart of one embodiment of the update step in the method of the present invention;
FIG. 3 is a flow diagram for one embodiment of step 201 in FIG. 2;
FIG. 4 is a flow diagram for one embodiment of step 202 in FIG. 2;
fig. 5 is a flowchart of another embodiment of a method for selecting a same access base station cluster for a plurality of mobile stations according to the present invention.
In the drawings, the same or similar reference numbers are used to refer to the same or similar elements.
Detailed Description
Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It is to be understood that the embodiments shown and described in the drawings are merely exemplary and are intended to illustrate the principles and spirit of the invention, not to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a flow chart of an embodiment of a method 100 for selecting the same set of access base station clusters for a plurality of mobile stations according to the present invention. The method 100 may comprise the following steps 101 to 103.
In step 101, a sparsity parameter indicating an upper limit value of the number of base stations in a base station cluster, an upper limit value of transmission power of each of a plurality of mobile stations, a transmission channel vector between each of the plurality of mobile stations and all of optional base stations, and an upper limit value of quality of service and a lower limit value of quality of service of each of the plurality of mobile stations are set.
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 and K base stations that may be selected, the upper limit of the transmission power of each mobile station may be represented as Pm,The transmission channel vector between each mobile station and all optional base stations can be expressed asThe dimension is ktx 1, where T is the number of antennas per base station. The lower limit value and the upper limit value of the service quality of each mobile station can be respectively gammaLAnd gammauTo indicate.
In one embodiment of the invention, the initial value of the lower limit value of the quality of serviceInitial value of upper limit value of service qualityWherein σ2Is the noise power.
In step 102, multiple rounds of updating are performed on the virtual downlink beamforming matrices and the virtual noise power sets of the multiple mobile stations according to the parameter values set in step 101 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.
In this step, the uplink problem that needs to be calculated originally can be converted into the virtual downlink problem to be solved based on the characteristic that the maximum and minimum fairness problem of the uplink and downlink of a single user under the condition of limited transmission power has duality.
In one embodiment of the present invention, the virtual downlink beamforming matrix may be represented as:
the dimension of the virtual downlink beamforming matrix W is KT multiplied by 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; column vector wmDimension of KT x 1, representing the transmit beams of all base stations to mobile station m, column vector wmCan be expressed as Wherein the column vector wk,mDimension (k) is T x 1, which represents the transmission beam of the kth base station to the mobile station m; row block matrix WkIs denoted by dimension T × M, which represents the transmission beam of the kth base station to all mobile stations.
The virtual noise power set may be expressed asWherein theta ismIs the virtual noise power of mobile station m.
Referring to fig. 2, fig. 2 is a flow chart of an embodiment of the update step 102 in the method of the present invention. In one embodiment of the invention, step 102 may include the following sub-steps 201 to 202.
In sub-step 201, the virtual downlink beamforming matrix is updated for multiple times while keeping the virtual noise power set unchanged.
When sub-step 201 is performed for the first time, the values in the virtual noise power set may be the values set at initialization, and when sub-step 201 is performed for the subsequent cycle, the values in the virtual noise power set may be the virtual noise power values calculated when sub-step 202 was performed for the last time.
In one embodiment of the present invention, referring to fig. 3, the substep 201 may further comprise substeps 301 to 305 as follows.
In sub-step 301, a qos intermediate value is obtained from the qos upper limit value and the qos lower limit value.
In one embodiment of the invention, the quality of service intermediate value γ ═ y (γ)L+γu)/2。
In sub-step 302, a virtual downlink beamforming matrix is calculated based on the qos intermediate value, the virtual noise power set, and the transmission channel vector.
In one embodiment of the present invention, sub-step 302 may comprise sub-steps 302-1 through 302-6 as follows:
in sub-step 302-1, the following are set and initialized:
first auxiliary matrix U(l)=W=H;
Second auxiliary matrix D(l)=[HHU,t];
Lagrangian matrix multiplier factor, corresponding to constraint U ═ W(l)=rand(K*T,M);
Corresponding to constraint D ═ HHU,t]Conditional Lagrange matrix multiplier factor Λ(l)Ran (M, M +1), whereinH=[h1,h2,...,hM]W is the virtual downlink beamforming matrix and l represents the number of times sub-step 302-2 is performed repeatedly.For the virtual noise power set, T represents a transpose operation of a matrix or vector, and rand (m, n) represents a random matrix of m × n dimensions, and the value of each element in the random matrix may be a random number evenly distributed between 0 and 1.
In sub-step 302-2, the first secondary matrix is updated according to the following formula:
wherein, is represented by a matrix D(l)The rightmost column of the vector,representation matrix D(l)Middle removing partThe remainder of (a);is represented by matrix Λ(l)The rightmost column of the vector,representation matrix Λ(l)Middle removing partThe remainder of (a); the parameter c may be chosen to be a number greater than zero.
If κUWhen equal to 0 can enableThen κUThe value of (d) is taken to be zero; otherwise, k can be searchedUA value of (a) such thatWherein, Tr (.) represents the trace of the matrix.
In sub-step 302-3, the virtual downlink beamforming matrix W is updated, and the k-th row block of the virtual downlink beamforming matrix W may be updated according to the following formula:
wherein, betakWeights, Z, selected for base station k to be inserted into the base station clusterkAnd UkThe k-th row block of matrices Z and U, respectively, and WkThe dimensions are the same. Wherein | | | purple hairFRepresenting the F norm.
In sub-step 302-4, the second auxiliary matrix D is updated by the following formula:
wherein d ism,-mRemoving elements D from the m-th row representing the second auxiliary matrix Dm,mThe remaining part of the process; y ismRepresentation matrix [ HHU(l+1),t]Row m, y ofm,mRepresentation matrix [ HHU(l+1),t]M row and m column elements of (1), ym,-mIs ymIn which y is removedm,mThe remaining part of the process; lambdamM-th row of the representation matrix Λ, Λm,mM rows and m columns of elements representing matrix Λ, Λm,-mIs ΛmRemoval of Λm,mThe remaining part of the process.
When in use <math>
<mrow>
<msqrt>
<msup>
<mi>γ</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
</msqrt>
<mrow>
<mo>(</mo>
<msubsup>
<mi>cy</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>Λ</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mo>≥</mo>
<msub>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msubsup>
<mi>cy</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>Λ</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>|</mo>
<mo>|</mo>
</mrow>
<mn>2</mn>
</msub>
</mrow>
</math> When it is mum=0;
When in use <math>
<mrow>
<msub>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msubsup>
<mi>cy</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>Λ</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mo>-</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>|</mo>
<mo>|</mo>
</mrow>
<mn>2</mn>
</msub>
<mo>></mo>
<mi>max</mi>
<mo>{</mo>
<msqrt>
<msup>
<mi>γ</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
</msqrt>
<mrow>
<mo>(</mo>
<msubsup>
<mi>cy</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>Λ</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mo>,</mo>
<mo>-</mo>
<msqrt>
<mi>γ</mi>
</msqrt>
<mrow>
<mo>(</mo>
<msubsup>
<mi>cy</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>Λ</mi>
<mrow>
<mi>m</mi>
<mo>,</mo>
<mi>m</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>l</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mo>}</mo>
</mrow>
</math> The method comprises the following steps:
when in useWhen d is greater thanm0, i.e. the mth row of matrix D is all 0;
wherein | | | purple hair2Representing a 2 norm.
In sub-step 302-5, update 1(l+1)=Ζ(l)+c(U(l+1)-W(l+1)) And Λ(l+1)=Λ(l)+c(D(l+1)-[HHU(l+1),t])。
In sub-step 302-6 of the method,
when | | | U(l+1)-U(l)||F+||W(l+1)-W(l)||F+||D(l+1)-D(l)||F+||Z(l+1)-Z(l)||F+||Λ(l+1)-Λ(l)||F≤a1Then substep 302 ends and substep 303 proceeds, otherwise, to substep 302-2. Wherein, a1Is a preset termination threshold.
It should be emphasized that the execution sequence between sub-step 302-2 to sub-step 302-5 can be arbitrarily adjusted, i.e.: any one of these three sub-steps may be performed first, followed by any one of the remaining two sub-steps, followed by the remaining last one.
In the substep 303, the upper limit value and the lower limit value of the service quality are adjusted according to the comparison result of the virtual downlink beamforming matrix and the sparsity parameter obtained by calculation.
In an embodiment of the present invention, the virtual downlink beamforming matrix obtained by calculation may be compared with the sparsity parameter according to the following rule:
if the virtual downlink beamforming matrix W obtained by calculation satisfiesLet gamma beLIf not, let gammauγ. Namely: lower limit value gamma of service qualityLIs adjusted to be equal to the quality of service middle value gamma, or the quality of service upper limit value gamma is adjusted to be equal to the quality of service middle value gammauIs adjusted to be equal to the quality of service median gamma.
In sub-step 304, the quality of service intermediate value is updated based on the adjusted quality of service upper limit value and the adjusted quality of service lower limit value.
In one embodiment of the invention, the formula in sub-step 301 may be used to update the quality of service intermediate value.
In the sub-step 305, when the difference between the two latest updated qos intermediate values is smaller than a preset second threshold, the virtual downlink beamforming matrix is output.
In an embodiment of the present invention, it may be determined whether the difference between the two latest updated qos median values is smaller than a preset second threshold by the following inequality:
|γ(t)-γ(t-1)|<2
wherein,2indicating a predetermined second threshold value, y(t)Represents the quality of service median, gamma, obtained from the t-th round of updating(t-1)The intermediate value of the service quality obtained by updating the t-1 th round is represented, and the absolute value is solved by the expression of |.
In an embodiment of the present invention, when the difference between the two latest updated qos median values is not less than the second threshold value, the process returns to substep 301.
In sub-step 202, the virtual downlink beamforming matrix is kept unchanged, and the virtual noise power set is updated for multiple times.
In one embodiment of the present invention, referring to fig. 4, sub-step 202 may comprise sub-steps 401 to 405 as follows.
In sub-step 401, a qos intermediate value is obtained according to the qos upper limit value and the qos lower limit value.
In one embodiment of the invention, the quality of service intermediate value γ ═ y (γ)L+γu)/2。
In sub-step 402, a virtual noise power set is calculated based on the qos intermediate value, the virtual downlink beamforming matrix and the transmission channel vector.
In one embodiment of the present invention, the virtual noise power set may be calculated by the following formula:
θmFor the mth element in the virtual noise power set, i.e.: the virtual noise power of the mth mobile station, gamma, is the quality of service median, wmFor the mth column block, h, of the virtual downlink beamforming matrixmFor the transport channel vector of the mth mobile station,is hmM is the total number of the plurality of mobile stations.
In sub-step 403, the upper and lower qos limits are adjusted according to the comparison result between the calculated virtual noise power set and the upper transmit power limit.
In one embodiment of the present invention, the virtual noise power set may be compared with the transmit power upper limit value by the following rule:
when in useIf not, adjusting the size of the service quality upper limit value to be equal to the service quality middle value;
wherein, thetamFor the m-th element, P, in the virtual noise power setmIs 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.
In sub-step 404, the quality of service intermediate value is updated based on the adjusted quality of service upper limit value and the adjusted quality of service lower limit value.
In one embodiment of the invention, the intermediate quality of service value may be updated with the formula in substep 401.
In sub-step 405, when the difference between the intermediate values of the quality of service obtained by the last two updates is smaller than a preset third threshold value, a virtual noise power set is output.
In an embodiment of the present invention, it may be determined whether the difference between the two latest updated qos median values is smaller than a preset third threshold value by the following inequality:
|γ(t)-γ(t-1)|<3
wherein,3indicating a predetermined third threshold value, gamma(t)Represents the quality of service median, gamma, obtained from the t-th round of updating(t-1)The intermediate value of the service quality obtained by updating the t-1 th round is represented, and the absolute value is solved by the expression of |.
It should be noted that, the above sub-steps 201 to 202 may be executed in multiple cycles, and after each execution, it may be determined whether a difference between virtual noise power sets obtained from the last two rounds of updates is smaller than a preset first threshold. Specifically, it can be determined whether the following inequality holds:
wherein tau represents a preset first threshold value,representing the virtual noise power of the mth mobile station obtained by the nth update,the virtual noise power of the mth mobile station obtained by the (n-1) th round of updating is shown.
If the inequality is true, outputting a virtual downlink beamforming matrix and ending the step 102, otherwise, repeatedly executing the step 102, that is: the loop is repeated to perform substeps 201 through 202.
It is emphasized that the order of execution of sub-step 201 and sub-step 202 may be interchanged, i.e.: substep 201 may be performed first, followed by substep 202; sub-step 202 may be performed first and then sub-step 201.
In step 103, the mobile station is accessed to the base station cluster indicated by the virtual downlink beamforming matrix obtained from the latest round of updating.
When the difference between the virtual noise power sets obtained by the last two rounds of updating is smaller than a preset first threshold value, step 102 will output the virtual downlink beamforming matrix obtained by the last round of updating. In one embodiment of the invention, the mobile station may be accessed to the base station corresponding to the non-zero row block in the matrix.
Thus, one embodiment 100 of a method for selecting a same set of access base station clusters for a plurality of mobile stations according to the present invention is described, which is capable of selecting a same set of access base station clusters for a plurality of mobile stations and maximizing a minimum signal-to-interference ratio among the plurality of mobile stations.
Referring to fig. 5, fig. 5 shows another embodiment 500 of the method for selecting the same set of access base station clusters for multiple mobile stations according to 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 are not described again here.
In step 504, the uplink beamforming and transmit power of the mobile station are calculated with the limitation of the sparsity parameter removed.
In one embodiment of the present invention, step 504 may include the following substeps 504-1 through 504-6.
In sub-step 504-1, an uplink beamforming vector is calculated
Wherein,represents the uplink beamforming vector, σ, of the mobile station m obtained when performing substep 504-1 the ith time2I is the identity matrix, M is the total number of mobile stations,indicating the transmit power of the nth mobile station obtained when substep 504-3 was performed the i-1 st time,indicating channel information between the nth mobile station and the selected base station for which access service is provided,to representIs a conjugate transpose of-1Representing an inversion matrix.
In sub-step 504-2, an 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 is calculated:
for the mobile station m, the formula can be firstly passedCalculating its transmitting powerCan then be represented byAdjusting its transmit power.
Signal to interference ratio <math>
<mrow>
<msubsup>
<mover>
<mi>SINR</mi>
<mo>‾</mo>
</mover>
<mi>m</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>=</mo>
<mfrac>
<mrow>
<msubsup>
<mi>p</mi>
<mi>m</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</msubsup>
<msubsup>
<mover>
<mi>w</mi>
<mo>^</mo>
</mover>
<mi>m</mi>
<mrow>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mi>H</mi>
</mrow>
</msubsup>
<msub>
<mover>
<mi>h</mi>
<mo>^</mo>
</mover>
<mi>m</mi>
</msub>
<msubsup>
<mover>
<mi>h</mi>
<mo>^</mo>
</mover>
<mi>m</mi>
<mi>H</mi>
</msubsup>
<msubsup>
<mover>
<mi>w</mi>
<mo>^</mo>
</mover>
<mi>m</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
</msubsup>
</mrow>
<mrow>
<msubsup>
<mover>
<mi>w</mi>
<mo>^</mo>
</mover>
<mi>m</mi>
<mrow>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mi>H</mi>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msup>
<mi>σ</mi>
<mn>2</mn>
</msup>
<mi>I</mi>
<mo>+</mo>
<msubsup>
<mi>Σ</mi>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</msubsup>
<msubsup>
<mi>p</mi>
<mi>n</mi>
<mrow>
<mo>(</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</msubsup>
<msub>
<mover>
<mi>h</mi>
<mo>^</mo>
</mover>
<mi>n</mi>
</msub>
<msubsup>
<mover>
<mi>h</mi>
<mo>^</mo>
</mover>
<mi>n</mi>
<mi>H</mi>
</msubsup>
<mo>)</mo>
</mrow>
<msubsup>
<mover>
<mi>w</mi>
<mo>^</mo>
</mover>
<mi>m</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
</msubsup>
</mrow>
</mfrac>
<mo>,</mo>
<mo>∀</mo>
<mi>m</mi>
</mrow>
</math>
Wherein,representing the transmit power of mobile station m obtained when substep 504-3 was performed the jth time,representing the signal-to-interference ratio of mobile station m obtained when substep 504-3 was performed the jth time.
In sub-step 504-4, ifThen go to substep 504-5, otherwise return to substep 504-3, where a2Is a preset termination threshold.
In sub-step 504-5, the update is performedStep 504-6 is entered.
In sub-step 504-6, if | γ(i)-γ(i-1)|<a3Then outputting the uplink beam forming and transmitting power of the mobile stationOtherwise, return to substep 504-1 wherein a3Is a preset termination threshold.
Thus, another embodiment 500 of the method for selecting the same group of access base station clusters for multiple mobile stations according to the present invention is described, and based on embodiment 100, embodiment 500 can also adjust and limit the transmit power of each mobile station, and optimize the uplink beamforming of each mobile station.
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, wkIs the K-th line block in the virtual downlink beamforming matrix, K is the total number of the selectable base stations, betakIs 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
θmFor the mth element in the virtual noise power set, γ is the quality of service median, wmIs the m column block, h, of the virtual downlink beamforming matrixmFor the transport channel vector of the mth mobile station,is hmM is the total number of the plurality of mobile stations.
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, thetamFor the m-th element, P, in the virtual noise power setmIs 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.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510239789.0A CN104869610B (en) | 2015-05-12 | 2015-05-12 | A kind of method that same group of access base station cluster is chosen for multiple mobile stations |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510239789.0A CN104869610B (en) | 2015-05-12 | 2015-05-12 | A kind of method that same group of access base station cluster is chosen for multiple mobile stations |
Publications (2)
Publication Number | Publication Date |
---|---|
CN104869610A true CN104869610A (en) | 2015-08-26 |
CN104869610B CN104869610B (en) | 2018-02-06 |
Family
ID=53915029
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201510239789.0A Expired - Fee Related CN104869610B (en) | 2015-05-12 | 2015-05-12 | A kind of method that same group of access base station cluster is chosen for multiple mobile stations |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN104869610B (en) |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101389115A (en) * | 2008-11-07 | 2009-03-18 | 北京工业大学 | Collaboration communication method for multi-cell base station dynamic clustering |
US7613145B2 (en) * | 2004-12-22 | 2009-11-03 | Alcatel Lucent | Method for fast resource scheduling in base station and the base station |
CN101877918A (en) * | 2009-04-30 | 2010-11-03 | 清华大学 | Equipment and method for dynamic clustering of base station in mobile communication |
CN102651888A (en) * | 2011-02-24 | 2012-08-29 | 中兴通讯股份有限公司 | Determining method and system for base station aggregation |
CN104301968A (en) * | 2014-10-16 | 2015-01-21 | 电子科技大学 | Method for selecting access base station cluster for mobile station |
CN104333885A (en) * | 2014-09-29 | 2015-02-04 | 电子科技大学 | Method for accessing mobile station to base station and device thereof |
-
2015
- 2015-05-12 CN CN201510239789.0A patent/CN104869610B/en not_active Expired - Fee Related
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7613145B2 (en) * | 2004-12-22 | 2009-11-03 | Alcatel Lucent | Method for fast resource scheduling in base station and the base station |
CN101389115A (en) * | 2008-11-07 | 2009-03-18 | 北京工业大学 | Collaboration communication method for multi-cell base station dynamic clustering |
CN101877918A (en) * | 2009-04-30 | 2010-11-03 | 清华大学 | Equipment and method for dynamic clustering of base station in mobile communication |
CN102651888A (en) * | 2011-02-24 | 2012-08-29 | 中兴通讯股份有限公司 | Determining method and system for base station aggregation |
CN104333885A (en) * | 2014-09-29 | 2015-02-04 | 电子科技大学 | Method for accessing mobile station to base station and device thereof |
CN104301968A (en) * | 2014-10-16 | 2015-01-21 | 电子科技大学 | Method for selecting access base station cluster for mobile station |
Also Published As
Publication number | Publication date |
---|---|
CN104869610B (en) | 2018-02-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN101569116B (en) | Method and apparatus to support SDMA transmission in OFDMA based network | |
KR101527110B1 (en) | Apparatus and method for power control in distributed multiple input multiple output wireless communication system | |
CN113411110B (en) | Millimeter wave communication beam training method based on deep reinforcement learning | |
US8718165B2 (en) | Method and apparatus for controlling multi-antenna transmission in a wireless communication network | |
DE202005022049U1 (en) | Frame format system and apparatus for exchanging MIMO channel measurements | |
US11246173B2 (en) | Systems and methods for multi-user pairing in wireless communication networks | |
CN111526592B (en) | Non-cooperative multi-agent power control method used in wireless interference channel | |
CN113490219B (en) | Dynamic resource allocation method for ultra-dense networking | |
Shen et al. | Design and implementation for deep learning based adjustable beamforming training for millimeter wave communication systems | |
CN113162666A (en) | Intelligent steel-oriented large-scale MIMO hybrid precoding method and device | |
CN107592675B (en) | A kind of 3D-MIMO multi-cell downlink adaptive transmission method | |
KR20220013906A (en) | Deep learning based beamforming method and apparatus for the same | |
CN109995496B (en) | Pilot frequency distribution method of large-scale antenna system | |
US11742901B2 (en) | Deep learning based beamforming method and apparatus | |
CN104301968B (en) | A kind of method that access base station cluster is chosen for mobile station | |
CN106972878A (en) | A kind of data processing method and device | |
WO2017185935A1 (en) | Message transmitting or receiving method and device, and base station | |
US12045721B2 (en) | Method and device for transmitting OFDM signal, and method and device for receiving OFDM signal | |
CN107872255B (en) | Pilot frequency scheduling method suitable for large-scale MIMO cellular mobile communication network | |
CN104869610B (en) | A kind of method that same group of access base station cluster is chosen for multiple mobile stations | |
CN114710187B (en) | Power distribution method for multi-cell large-scale MIMO intelligent communication under user number dynamic transformation scene | |
Kishimoto et al. | Reinforcement learning for joint channel/subframe selection of LTE in the unlicensed spectrum | |
KR20190090209A (en) | Method and apparatus for providing hybrid beamforming in large-scale antenna system | |
Wai et al. | Discrete sum rate maximization for MISO interference broadcast channels: Convex approximations and efficient algorithms | |
EP2039019B1 (en) | Method and system for robustly transmitting the minimum power in multi-user and multi-antenna communications systems with imperfect channel knowledge |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
EXSB | Decision made by sipo to initiate substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20180206 Termination date: 20210512 |
|
CF01 | Termination of patent right due to non-payment of annual fee |