CN103414506A - Multi-base-station channel feedback method with quantization error and calculation complexity compromise - Google Patents

Abstract

The invention discloses a multi-base-station channel feedback method with quantization error and calculation complexity compromise in the technical field of a multi-base-station cooperation system. Firstly, a user carries out quantization on the channel information of all base stations one by one and calculates quantization errors. Then the base station channel information with a minimum quantization error and the corresponding codeword are selected as a quantization result. In the condition that the existing quantization result is fixed, one by one quantization of the remaining base station information is carried out, and then the base station channel information with a minimum quantization error and the corresponding codeword are added to the existing quantization result. And so on, the quantization of all base channel information is completed, and finally a channel quantization codeword with multi-base-station cooperation is obtained and is sent to a base station. According to the method, the characteristic of a multi-base-station cooperation system is fully considered, compromise is carried out between system performance and calculation complexity, and the method is a limited feedback design method applicable to a multi-base-station system characteristic.

Description

Many BTS channel feedback method of a kind of quantization error and computation complexity compromise

Technical field

The invention belongs to multi-base station cooperative systems technology field, relate in particular to many BTS channel feedback method of a kind of quantization error and computation complexity compromise.

Background technology

In the multi-base station cooperative system, the antenna array unit of the different nodes in each community is connected to corresponding base station equipment by high-speed link, and adjacent base station interconnects by high-speed link, high-speed link can be special optic fibre, high-speed backbone network or high-speed radio repeated link etc.The node that is in diverse geographic location has cooperated and the communicating by letter of single or multiple mobile communication terminals on same running time-frequency resource, form the mimo channel strengthened, can fundamentally overcome the limitation of MIMO technology application in conventional cellular systems, can take full advantage of the Spatial Dimension Radio Resource in theory, significantly improve the availability of frequency spectrum and power utilization, and overcome " edge effect " of conventional cellular systems.

In wireless communication system, obtain desirable channel information very difficult.In actual FDD system, receiving terminal adopts training sequence to obtain channel information usually, and transmitting terminal adopts limited quantification feedback technique to obtain channel information usually.In limited quantification feedback, design in advance all known code books of a transmitting terminal and receiving terminal, receiving terminal according to certain criterion from code book, selecting a code word, and the sequence number of selected code word is sent to transmitting terminal by feedback channel, transmitting terminal is again from known code book, selecting the code word of corresponding sequence number, as channel information.

In the multi-base station cooperative system, when a plurality of node associatings and mobile communication terminal address, the channel of mimo channel for strengthening, base station end antenna number is antenna number sum on each cooperative node, significantly improve thus space diversity gain and spatial reuse gain, and the increase of channel matrix size also can cause implementing the increase of the complexity that quantizes to feed back.

Existing quantification feedback scheme for the multi-base station cooperative system, mainly adopted overall feedback scheme and difference feedback scheme.Overall feedback refers to that the user is considered as a channel matrix by the channel information of all base stations in many base station systems and quantizes feedback, and feedback refers to that the user quantizes respectively feedback for each base station respectively.The overall feedback scheme, because the dimension of each code book increases, has increased greatly and has quantized the complexity of calculating; In the difference feedback scheme, the low computation complexity of code book dimension is not high, but because there is error in the feedback for each base station, final error accumulation, systematic function is very poor.Therefore need to find the base station collaboration system characteristics that are applicable to, the feedback scheme that performance and computation complexity are applicable to.

Summary of the invention

For existing quantification feedback scheme, be not suitable with the problem of multi-base station cooperative system, the present invention proposes many BTS channel feedback method of a kind of quantization error and computation complexity compromise.

In the multi-base station cooperative system, there is S base station to participate in cooperation, N transmitting antenna of each base station configuration, be connected by high-speed backbone between base station, jointly forms an aerial array M, M equals the number of transmit antennas of s base station, and s base station is K user's service in whole S community.Now, can be expressed as for i user's reception signal,

$y_i=h_i{\hat{v}}_i{s}_i+\underset{\underset{j\≠i}{j=1}}{\overset{K}{\mathrm{\Σ}}}{h}_i{\hat{v}}_j{s}_j+n_i$

Wherein, s _iWith

Be respectively the transmission symbol of user i and the Limited Feedback channel precoding vector of user i, send symbol power and be constrained to P.N _iFor additive white Gaussian noise, average is 0, and variance is 1.H _iFor total channel vector of S base station and user i, h _i=[h _{I, 1}, h _{I, 2}..., h _i,s], h wherein _i,s, s=1,2 ..., S, mean the channel vector between s base station and user i; s _jWith

Be respectively the transmission symbol of user j and the Limited Feedback channel precoding vector of user j.Suppose that receiving terminal obtains ideal communication channel information, feedback channel desirable (namely there is no feedback error and delay), order Mean the user i feedback channel vector that transmitting terminal obtains, the broadcast channel quantization matrix of transmitting terminal acquisition is so

The ZF precoding vector is The respective column vector, use

Mean Limited Feedback channel precoding vector.Because the pre-coding matrix under Limited Feedback is orthogonal to the quantized value of channel vector, namely for all i ≠ j, have But not actual value, i.e. multi-user interference now

Usually non-vanishing.

Many BTS channel feedback method of a kind of quantization error and computation complexity compromise, is characterized in that, specifically comprises the following steps:

Step 1: the user quantizes one by one to the channel information of all base stations, and obtains quantization error;

Step 2: select the BTS channel information of quantization error minimum and corresponding code word, using the quantized result that obtains as final quantized channel vector

A part;

Step 3: under the existing quantized result fixing situation of step 2, remaining BTS channel information is quantized again one by one; Then select BTS channel information and the corresponding code word of quantization error minimum, join in existing quantized result;

Step 4: repeating step 3, until complete the quantification of all BTS channel information, finally obtain the channel quantitative code word of multi-base station cooperative, feed back to base station.

In step 1, the user quantizes one by one to the channel information of all base stations, and the process of obtaining quantization error is:

Step 101: the initialization quantization matrix is empty, even

Code book is

Collection of base stations be set as Ω=1,2 ..., S}; B is feedback bit number;

Step 102: user i quantizes to obtain to quantize vector one by one to the channel information of each base station respectively, that is, and and for s ∈ Ω,

$\begin{array}{c}{\hat{h}}_{i,s}=\arg \underset{j=1,...,2^B}{\max }\left|{\tilde{h}}_{i,s}{w}_j^H\right|\\ =\arg \underset{j=1,...,2^B}{\min }{\sin }^2(\∠({\tilde{h}}_{i,s},w_j))\end{array}$

Wherein,

Mean the quantification vector of user i to the channel information of base station s; Variate-value when argmax and argmin mean respectively to make target function get maximum and minimum value; () ^HMean conjugate transpose;

For the direction vector of user i to the channel of base station s, namely quantize object; w _jBe the M dimension code word in j user feedback code book, ‖ w _j‖=1, M equals the number of transmit antennas of s base station;

Step 103: calculate user i quantization error, for s ∈ Ω,

${\mathrm{\δ}}_{i,s}={\sin }^2(\∠({\hat{h}}_{i,s},{\tilde{h}}_{i,s}))$

Wherein, δ _i,sMean that user i carries out quantization error to the channel information of base station s,

Mean the angle between two vectors;

Mean

The quantification vector.

In step 2, select the BTS channel information of quantization error minimum and corresponding code word, using the quantized result that obtains as final quantized channel vector A part as the process of quantized result, be:

Step 201: select the quantification vector of quantization error minimum as quantized result, calculate simultaneously the base station numbering corresponding to quantification vector of quantization error minimum:

$s^{*}=\arg \underset{s\∈\mathrm{\Ω}}{\min }{\mathrm{\δ}}_{i,s}$

Wherein, s ^*Base station numbering corresponding to quantification vector that means the quantization error minimum;

Step 202: the quantification vector of the error minimum that step 201 is obtained is as final quantized channel

A part, namely

And by final quantized channel vector Corresponding quantification object is designated as

Step 203: the base station that the quantification vector of step 201 selection is corresponding is from removing collection of base stations, namely

Ω=Ω-{s ^*}。

In step 3, on the basis of the quantized result that step 2 obtains, remaining BTS channel information is quantized again one by one; Then select BTS channel information and the corresponding code word of quantization error minimum, the concrete steps that join in existing quantized result are:

Step 301: determine and quantize object: for all s ∈ Ω, the quantification object is:

${\tilde{h}}_{i,s}^{*}=[{\tilde{h}}_i,{\tilde{h}}_{i,s}]$

Step 302: user i, on the basis of the quantized result that step 2 obtains, quantizes to obtain to quantize vector one by one to the channel information that remains each base station, that is,

$\begin{array}{c}{\hat{h}}_{i,s}^{*}=\arg \underset{j=1,...,2^B}{\max }\left|{\tilde{h}}_{i,s}{[{\hat{h}}_i,w_j]}^H\right|\\ =\arg \underset{j=1,...,2^B}{\min }{\sin }^2(\∠\left({\tilde{h}}_{i,s}^{*}\right[{\hat{h}}_i,w_j\left]\right))\end{array}$

Step 303: calculate the quantization error of user i under existing quantized result fixing situation:

${\mathrm{\δ}}_{i,s}={\sin }^2(\∠({\hat{h}}_i,{\hat{h}}_{i,s}^{*}],{\tilde{h}}_{i,s}^{*}))$

Step 304: select the quantification vector of quantization error minimum as quantized result, and calculate the base station numbering that minimum quantification vector is corresponding:

$s^{*}=\arg \underset{s\∈\mathrm{\Ω}}{\min }{\mathrm{\δ}}_{i,s}$

Wherein, s ^*Mean the base station numbering that minimum quantification vector is corresponding;

Step 305: by the most final quantized channel of the quantized result of step

A part, namely ${\hat{h}}_i=[{\hat{h}}_i,{\hat{h}}_{i,s^{*}}^{*}];$ By final quantized channel

Corresponding quantification object is ${\tilde{h}}_i=[{\tilde{h}}_i,{\tilde{h}}_{i,s^{*}}^{*}];$

Step 306: the base station that the quantification vector of this step selection is corresponding is from removing collection of base stations, namely

Ω=Ω-{s ^*}。

The invention has the beneficial effects as follows:

Many BTS channel feedback method of a kind of quantization error 1) proposed and computation complexity compromise, taken into full account the characteristics of multi-base station cooperative system, and many base stations Limited Feedback is carried out step by step, compares and greatly reduce computation complexity with overall feedback.

Many BTS channel feedback method of a kind of quantization error 2) proposed and computation complexity compromise, in the substep quantizing process, each step is all carried out the comparison of quantization error, selection has the code word corresponding to BTS channel information of minimum quantization error, as quantized result, the accumulation of error in the time of can effectively avoiding feeding back respectively, compare and improved systematic function with feedback respectively.

Many BTS channel feedback method of a kind of quantization error 3) proposed and computation complexity compromise, compromise between systematic function and computation complexity, be a kind of Limited Feedback method for designing that adapts to many base station systems characteristics.

The accompanying drawing explanation

Fig. 1 is the system block diagram that the present invention is suitable for;

Fig. 2 is the inventive method and other method quantization error simulation result figure relatively;

Fig. 3 is the inventive method and other method entire system performance simulation result figure relatively.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.Should be emphasized that, following explanation is only exemplary, rather than in order to limit the scope of the invention and to apply.

As Fig. 1, it is the system block diagram that the present invention is suitable for.The MIMO descending multi-user system of multi-base station cooperative, in system, there is S base station to participate in cooperation, N transmitting antenna of each base station configuration, between base station, be connected by high-speed backbone, aerial array of common composition, K user's service in whole S communities, that is to say each mobile subscriber, can receive the signal from whole S base station.In this system, each user configures a reception antenna.In order to eliminate the interference between the user, need to select suitable precoding vector, if adopted the ZF linear predictive coding.Transmitting terminal need to be known channel information for this reason.In real system, transmitting terminal obtains channel information by the feedback of receiving terminal usually.Particularly, at first the user carries out channel estimating, then by corresponding feedback scheme, channel information is quantized, next by feedback channel, code book information is fed back to base station, base station is carried out channel reconstructing according to the code book information of feedback and actual feedback scheme at transmitting terminal, then according to the channel information of rebuilding, calculate precoding vector, transmitted signal was sued for peace after advancing corresponding pre-encode operation, then by aerial array, sent.

Suppose that receiving terminal obtains ideal communication channel information, feedback channel desirable (namely there is no feedback error and delay), order

Mean the user i feedback channel vector that transmitting terminal obtains, the broadcast channel quantization matrix of transmitting terminal acquisition is so

The ZF precoding vector is

The respective column vector, use

Mean Limited Feedback channel precoding vector.Because the pre-coding matrix under Limited Feedback is orthogonal to the quantized value of channel vector, namely for all i ≠ j, have

But not actual value, namely now multi-user interference is usually non-vanishing.Now, can be expressed as for i user's reception signal,

$y_i=h_i{\hat{v}}_i{s}_i+\underset{\underset{j\≠i}{j=1}}{\overset{K}{\mathrm{\Σ}}}{h}_i{\hat{v}}_j{s}_j+n_i$

Wherein, s _iWith Be respectively the transmission symbol of user i and the Limited Feedback channel precoding vector of user i, send symbol power and be constrained to P.N _iFor additive white Gaussian noise, average is 0, and variance is 1.H _iFor total channel vector of S base station and user i, h _i=[h _{I, 1}, h _{I, 2}..., h _i,s], h wherein _i,s, s=1,2 ..., S, mean the channel vector between s base station and user i; s _jWith

Be respectively the transmission symbol of user j and the Limited Feedback channel precoding vector of user j.

Many BTS channel feedback method of a kind of quantization error and computation complexity compromise, is characterized in that, specifically comprises the following steps:

Step 1: the user quantizes one by one to the channel information of all base stations, and the detailed process of obtaining quantization error is:

Step 101: the initialization quantization matrix is empty, even

Code book is

Collection of base stations be set as Ω=1,2 ..., S}; B is feedback bit number;

Step 102: user i quantizes to obtain to quantize vector one by one to the channel information of each base station respectively, that is, and and for s ∈ Ω,

$\begin{array}{c}{\hat{h}}_{i,s}=\arg \underset{j=1,...,2^B}{\max }\left|{\tilde{h}}_{i,s}{w}_j^H\right|\\ =\arg \underset{j=1,...,2^B}{\min }{\sin }^2(\∠({\tilde{h}}_{i,s},w_j))\end{array}$

Wherein, Mean the quantification vector of user i to the channel information of base station s; Variate-value when argmax and argmin mean respectively to make target function get maximum and minimum value; () ^HMean conjugate transpose;

For the direction vector of user i to the channel of base station s, namely quantize object; w _jBe the M dimension code word in j user feedback code book, ‖ w _j‖=1, M equals the number of transmit antennas of s base station;

Step 103: calculate user i quantization error, for s ∈ Ω,

${\mathrm{\δ}}_{i,s}={\sin }^2(\∠({\hat{h}}_{i,s},{\tilde{h}}_{i,s}))$

Wherein, δ _i,sMean that user i carries out quantization error to the channel information of base station s, Mean the angle between two vectors;

Mean

The quantification vector;

Step 2: select the BTS channel information of quantization error minimum and corresponding code word, using the quantized result that obtains as final quantized channel vector

A part; Detailed process is:

Step 201: select the quantification vector of quantization error minimum as quantized result, calculate simultaneously the base station numbering corresponding to quantification vector of quantization error minimum:

$s^{*}=\arg \underset{s\∈\mathrm{\Ω}}{\min }{\mathrm{\δ}}_{i,s}$

Wherein, s ^*Base station numbering corresponding to quantification vector that means the quantization error minimum;

Step 202: the quantification vector of the error minimum that step 201 is obtained is as final quantized channel

A part, namely

And by final quantized channel vector

Corresponding quantification object is designated as ${\tilde{h}}_i={\tilde{h}}_{i,s^{*}};$

Step 203: the base station that the quantification vector of step 201 selection is corresponding is from removing collection of base stations, namely

Ω=Ω-{s ^*}。

Step 3: under the existing quantized result fixing situation of step 2, remaining BTS channel information is quantized again one by one; Then select BTS channel information and the corresponding code word of quantization error minimum, join in existing quantized result, detailed process is:

Step 301: determine and quantize object: for all s ∈ Ω, the quantification object is:

${\tilde{h}}_{i,s}^{*}=[{\tilde{h}}_i,{\tilde{h}}_{i,s}]$

Step 302: user i, on the basis of the quantized result that step 2 obtains, quantizes to obtain to quantize vector one by one to the channel information that remains each base station, that is,

$\begin{array}{c}{\hat{h}}_{i,s}^{*}=\arg \underset{j=1,...,2^B}{\max }\left|{\tilde{h}}_{i,s}{[{\hat{h}}_i,w_j]}^H\right|\\ =\arg \underset{j=1,...,2^B}{\min }{\sin }^2(\∠\left({\tilde{h}}_{i,s}^{*}\right[{\hat{h}}_i,w_j\left]\right))\end{array}$

Step 303: calculate the quantization error of user i under existing quantized result fixing situation:

${\mathrm{\δ}}_{i,s}={\sin }^2(\∠\left({{[\hat{h}}_i,\hat{h}}_{i,s}^{*}\right],{\tilde{h}}_{i,s}^{*}))$

Step 304: select the quantification vector of quantization error minimum as quantized result, and calculate the base station numbering that minimum quantification vector is corresponding:

$s^{*}=\arg \underset{s\∈\mathrm{\Ω}}{\min }{\mathrm{\δ}}_{i,s}$

Wherein, s ^*Mean the base station numbering that minimum quantification vector is corresponding;

Step 305: by the most final quantized channel of the quantized result of step

A part, namely ${\hat{h}}_i=[{\hat{h}}_i,{\hat{h}}_{i,s^{*}}^{*}];$ By final quantized channel Corresponding quantification object is ${\tilde{h}}_i=[{\tilde{h}}_i,{\tilde{h}}_{i,s^{*}}^{*}];$

Step 306: the base station that the quantification vector of this step selection is corresponding is from removing collection of base stations, namely

Ω=Ω-{s ^*}。

Step 4: repeating step 3, until complete the quantification of all BTS channel information, finally obtain the channel quantitative code word of multi-base station cooperative, feed back to base station.

Fig. 2 is the inventive method and other method quantization error simulation result figure relatively.The base station number that participates in cooperation is 3,3 transmitting antennas of each base station configuration, and it is 4 that system is held number of users.As seen from Figure 2, the quantization error of the inventive method is between overall feedback with respectively between feedback.

Fig. 3 is the inventive method and other method entire system performance simulation result figure relatively.Fig. 3 is under three kinds of feedback schemes, and the base station number that participates in cooperation is 3,3 transmitting antennas of each base station configuration, it is 4 that system is held number of users, total feedback bit count B be respectively 3 and 6 o'clock system speed with the signal to noise ratio change curve.As seen from Figure 3, under difference feedback bit, the overall feedback best performance, feedback performance is the poorest respectively.And the feedback method performance that the present invention proposes is between overall feedback with respectively between feedback performance, and more near overall feedback.

Table 1 is the comparison sheet of the inventive method and other method computation complexity.In table, adopt flop to mean computation complexity.A flop is defined as a real floating number operation.Real add, a multiplication and division are calculated as a flop.As shown in Table 1, this invention computation complexity is between overall feedback and feedback is direct respectively, and more approaches feedback respectively.Because the present invention adopts the substep form, the matrix dimensionality that each one is calculated reduces greatly, so complexity reduces greatly than overall feedback.This scheme is obtaining good compromise aspect complexity and systematic function, be applicable to the system of multi-base station cooperative.

Table 1 calculation of complex kilsyth basalt

The above; only be the present invention's embodiment preferably, but protection scope of the present invention is not limited to this, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.

Claims (4)

1. many BTS channel feedback method of a quantization error and computation complexity compromise, in the multi-base station cooperative system, there is S base station to participate in cooperation, each base station configuration N transmitting antenna, between base station, be connected by high-speed backbone, aerial array M of common composition, M equals the number of transmit antennas of s base station; S base station is K user's service in whole S community; Now, can be expressed as for i user's reception signal,

$y_i=h_i{\hat{v}}_i{s}_i+\underset{\underset{j\≠i}{j=1}}{\overset{K}{\mathrm{\Σ}}}{h}_i{\hat{v}}_j{s}_j+n_i$

Wherein, s _iWith

Be respectively the transmission symbol of user i and the Limited Feedback channel precoding vector of user i, send symbol power and be constrained to P, n _iFor additive white Gaussian noise, average is 0, and variance is 1; h _iFor total channel vector of S base station and user i, h _i=[h _{I, 1}, h _{I, 2}..., h _i,s], h wherein _i,s, s=1,2 ..., S, mean the channel vector between s base station and user i; s _jWith

Be respectively the transmission symbol of user j and the Limited Feedback channel precoding vector of user j; It is characterized in that, specifically comprise the following steps:

Step 1: the user quantizes one by one to the channel information of all base stations, and obtains quantization error;

Step 2: select the BTS channel information of quantization error minimum and corresponding code word, using the quantized result that obtains as final quantized channel vector

A part;

Step 3: under the existing quantized result fixing situation of step 2, remaining BTS channel information is quantized again one by one; Then select BTS channel information and the corresponding code word of quantization error minimum, join in existing quantized result;

Step 4: repeating step 3, until complete the quantification of all BTS channel information, finally obtain the channel quantitative code word of multi-base station cooperative, feed back to base station.

2. method according to claim 1, is characterized in that, in described step 1, the user quantizes one by one to the channel information of all base stations, and the process of obtaining quantization error is:

Step 101: the initialization quantization matrix is empty, even

Code book is

Collection of base stations be set as Ω=1,2 ..., S}; B is feedback bit number;

Step 102: user i quantizes to obtain to quantize vector one by one to the channel information of each base station respectively, that is, and and for s ∈ Ω,

$\begin{array}{c}{\hat{h}}_{i,s}=\arg \underset{j=1,...,2^B}{\max }\left|{\tilde{h}}_{i,s}{w}_j^H\right|\\ =\arg \underset{j=1,...,2^B}{\min }{\sin }^2(\∠({\tilde{h}}_{i,s},w_j))\end{array}$

Wherein,

Mean the quantification vector of user i to the channel information of base station s; Variate-value when argmax and argmin mean respectively to make target function get maximum and minimum value; () ^HMean conjugate transpose;

For the direction vector of user i to the channel of base station s, namely quantize object; w _jBe the M dimension code word in j user feedback code book, ‖ w _j‖=1, M equals the number of transmit antennas of base station;

Step 103: calculate user i quantization error, for s ∈ Ω,

${\mathrm{\δ}}_{i,s}={\sin }^2(\∠({\hat{h}}_{i,s},{\tilde{h}}_{i,s}))$

Wherein, δ _i,sMean that user i carries out quantization error to the channel information of base station s,

Mean the angle between two vectors;

Mean The quantification vector.

3. method according to claim 1, is characterized in that, in described step 2, selects the BTS channel information of quantization error minimum and corresponding code word, using the quantized result that obtains as final quantized channel vector

A part as the process of quantized result, be:

Step 201: select the quantification vector of quantization error minimum as quantized result, calculate simultaneously the base station numbering corresponding to quantification vector of quantization error minimum:

$s^{*}=\arg \underset{s\∈\mathrm{\Ω}}{\min }{\mathrm{\δ}}_{i,s}$

Wherein, s ^*Base station numbering corresponding to quantification vector that means the quantization error minimum;

Step 202: the quantification vector of the error minimum that step 201 is obtained is as final quantized channel A part, namely

And by final quantized channel vector

Corresponding quantification object is designated as ${\tilde{h}}_i={\tilde{h}}_{{i,s}^{*}};$

Step 203: the base station that the quantification vector of step 201 selection is corresponding is from removing collection of base stations, namely

Ω=Ω-{s ^*}。

4. method according to claim 1, is characterized in that, in step 3, on the basis of the quantized result that step 2 obtains, remaining BTS channel information quantized respectively again; Then select BTS channel information and the corresponding code book of quantization error minimum, the concrete steps that join in existing quantized result are:

Step 301: determine and quantize object: for all s ∈ Ω, the quantification object is:

${\tilde{h}}_{i,s}^{*}=[{\tilde{h}}_i,{\tilde{h}}_{i,s}]$

Step 302: user i, on the basis of the quantized result that step 2 obtains, quantizes to obtain to quantize vector one by one to the channel information that remains each base station, that is,

$\begin{array}{c}{\hat{h}}_{i,s}^{*}=\arg \underset{j=1,...,2^B}{\max }\left|{\tilde{h}}_{i,s}{[{\hat{h}}_i,w_j]}^H\right|\\ =\arg \underset{j=1,...,2^B}{\min }{\sin }^2(\∠\left({\tilde{h}}_{i,s}^{*}\right[{\hat{h}}_i,w_j\left]\right))\end{array}$

Step 303: calculate the quantization error of user i under existing quantized result fixing situation:

${\mathrm{\δ}}_{i,s}={\sin }^2(\∠({[{\hat{h}}_i\widehat{,h}}_{i,s}^{*}],{\tilde{h}}_{i,s}^{*}))$

Step 304: select the quantification vector of quantization error minimum as quantized result, and calculate the base station numbering that minimum quantification vector is corresponding:

$s^{*}=\arg \underset{s\∈\mathrm{\Ω}}{\min }{\mathrm{\δ}}_{i,s}$

Wherein, s ^*Mean the base station numbering that minimum quantification vector is corresponding;

Step 305: by the most final quantized channel of the quantized result of step

A part, namely ${\hat{h}}_i=[{\hat{h}}_i,{\hat{h}}_{i,s^{*}}^{*}];$ By final quantized channel Corresponding quantification object is ${\tilde{h}}_i=[{\tilde{h}}_i,{\tilde{h}}_{i,s^{*}}^{*}];$

Step 306: the base station that the quantification vector of this step selection is corresponding is from removing collection of base stations, namely

Ω=Ω-{s ^*}。

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