CN102970706B - The selection method of collaborative feedback collection and base station - Google Patents

Abstract

The invention discloses a cooperative feedback set selection method and an eNodeB, wherein, the eNodeB receives the reference signal quality parameter of each cell reported by the UE; The ratio of traffic volume respectively determines the decision threshold corresponding to each non-serving cell; The decision threshold corresponding to the serving cell is compared, and if the calculated difference is smaller than the decision threshold, the corresponding non-serving cell is put into the cooperative feedback set. The present invention dynamically adjusts the size of the judgment threshold according to the reference signal quality parameter and/or the ratio of the service volume of the serving cell to the traffic volume of each non-serving cell, thereby realizing the compromise between the feedback overhead and the cooperative transmission gain, and lowering the feedback overhead with a small feedback overhead. A larger cooperative transmission gain is obtained.

Description

Selection Method of Cooperative Feedback Set and Base Station

technical field

The present invention relates to wireless communication technology, in particular to a method for selecting a cooperative feedback set in a multi-base station cooperative transmission system and a base station for realizing the above method for selecting a cooperative feedback set.

Background technique

At present, multi-base station coordinated transmission (CoMP) technology has become one of the research hotspots in wireless communication systems in the near future. Through multiple base stations jointly scheduling users and sending signals, the inevitable interference signals between traditional cells can be converted into useful data, thereby Further improve spectrum utilization.

In a multi-base station coordinated transmission system, the base station eNodeB usually firstly configures a radio resource management (RRM) measurement set (measurement set) for the UE, wherein the RRM measurement set is a set composed of cells that need the UE to measure Reference Signal Received Power (RSRP) ; Then, the UE will select the cells that need to report RSRP to the eNodeB in the RRM measurement set according to the preset reporting conditions, and report the RSRP of these cells to the eNodeB; after receiving the report from the UE, the eNodeB will RSRP determines a CoMP feedback set (CoMP feedback set) and configures the determined CoMP feedback set to the UE. The CoMP feedback set is a set composed of cells that require the UE to feed back channel state information (CSI) to its serving cell; and then, The UE feeds back the CSI of the cells included in the coordinated feedback set to the eNodeB; finally, the eNodeB performs scheduling, precoding, signaling and data transmission according to the CSI fed back by the UE. Those skilled in the art can understand that the size of the cooperative feedback set can usually directly affect the size of the cooperative transmission gain. For example, the larger the cooperative feedback set (the more cells it contains), the greater the cooperative transmission gain that can be obtained; The smaller the feedback set (the fewer cells it includes), the smaller the cooperative transmission gain that can be obtained. In addition, the size of the collaborative feedback set will directly affect the size of the feedback overhead. For example, the larger the collaborative feedback set, the greater the feedback overhead; the smaller the collaborative feedback set, the smaller the feedback overhead. Therefore, how to determine the cooperative feedback set to balance the feedback overhead and the cooperative transmission gain is one of the key problems to be solved by the cooperative transmission technology.

Contents of the invention

In view of this, the present invention provides a method for selecting a cooperative feedback set in a multi-base station cooperative transmission system and a base station for implementing the cooperative transmission method, which can achieve a compromise between feedback overhead and cooperative transmission gain, with a small feedback overhead A larger cooperative transmission gain can be obtained.

A collaborative feedback set selection method provided by an embodiment of the present invention includes:

The eNodeB receives the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cell reported by the UE;

The eNodeB respectively determines the decision threshold corresponding to each non-serving cell according to the reference signal quality parameter of the serving cell or non-serving cell reported by the UE and/or the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell, wherein the decision threshold increasing with the increase of the reference signal quality parameter of the serving cell or the non-serving cell and/or said traffic volume ratio;

The eNodeB separately calculates the difference between the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cells, and compares the calculated difference with the decision thresholds corresponding to the non-serving cells, if calculated If the obtained difference is smaller than the decision threshold, the corresponding non-serving cell is put into the cooperative feedback set.

The above method further includes: the eNodeB selects the first m cells with the largest reference signal quality parameters from the coordinated feedback set as the cells in the final coordinated feedback set, where m is the maximum number of cells that can be included in the coordinated feedback set.

Wherein, the eNodeB respectively determines the decision threshold corresponding to each non-serving cell according to the reference signal quality parameter of the serving cell or the non-serving cell reported by the UE and/or the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell, including : The eNodeB determines a decision threshold according to the reference signal quality parameter of the serving cell reported by the UE, and uses the decision threshold as the decision threshold corresponding to each non-serving cell, wherein the decision threshold increases with the reference signal quality parameter of the serving cell And grow.

Determining a decision threshold by the eNodeB according to the reference signal quality parameter of the serving cell reported by the UE includes: establishing a corresponding relationship between the reference signal quality parameter and the decision threshold; and determining the decision threshold according to the reference signal quality parameter of the serving cell reported by the UE and the corresponding relationship Judgment threshold.

Wherein, the corresponding relationship is a functional relationship y=f(x), wherein x represents the reference signal quality parameter of the serving cell, y represents the decision threshold, and when x1>x2, it is guaranteed that y1-y2=f(x1)- f(x2)>0.

Or, the eNodeB respectively determines the decision threshold corresponding to each non-serving cell according to the reference signal quality parameters of the serving cell or each non-serving cell reported by the UE and/or the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell Including: the eNodeB respectively determines the decision thresholds corresponding to the non-serving cells according to the reference signal quality parameters of the non-serving cells, wherein the decision thresholds corresponding to the non-serving cells vary with the reference signal quality parameters of the non-serving cells grows with the increase of parameters.

Wherein, the eNodeB respectively determining the decision thresholds corresponding to the non-serving cells according to the reference signal quality parameters of the non-serving cells includes: establishing a corresponding relationship between the reference signal quality parameters and the decision thresholds; The reference signal quality parameters of the cell and the corresponding relationship determine the decision threshold corresponding to the non-serving cell.

The corresponding relationship is a functional relationship y=f(x), wherein, x represents a reference signal quality parameter of a certain non-serving cell, y represents the decision threshold corresponding to the non-serving cell, and when x1>x2, it is guaranteed that y1- y2=f(x1)-f(x2)>0.

Or, the eNodeB respectively determines the decision corresponding to each non-serving cell according to the reference signal quality parameters of the serving cell or each non-serving cell reported by the UE and/or the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell The threshold includes: the eNodeB separately calculates the ratio of the traffic volume of the serving cell to the traffic volume of the non-serving cells, and determines the decision threshold corresponding to the non-serving cells according to the traffic volume ratio, wherein the non-serving cells The decision threshold corresponding to the cell increases with the increase of the traffic ratio.

Wherein, determining the decision threshold corresponding to each non-serving cell according to the traffic ratio includes: establishing a corresponding relationship between the traffic ratio and the decision threshold; And the corresponding relationship determines the decision threshold corresponding to the non-serving cell.

Wherein, the corresponding relationship is a functional relationship y=f(x), wherein, x represents the ratio of the traffic volume of the serving cell to the traffic volume of a certain non-serving cell, and y represents the decision threshold corresponding to the non-serving cell, and at x1 When >x2, ensure that y1-y2=f(x1)-f(x2)>0.

Alternatively, the eNodeB determines the decision corresponding to each non-serving cell according to the reference signal quality parameters of the serving cell or each non-serving cell reported by the UE and/or the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell The threshold includes: the eNodeB separately calculates the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell, and determines the ratio of the traffic volume according to the reference signal quality parameters of the serving cell or each non-serving cell and the traffic volume ratio reported by the UE. The decision threshold corresponding to each non-serving cell, wherein the decision threshold increases with the increase of the reference signal quality parameter and traffic volume ratio of the serving cell or a non-serving cell.

Wherein, according to the reference signal quality parameters of the serving cell or each non-serving cell reported by the UE and the traffic volume ratio, respectively determining the decision threshold corresponding to each non-serving cell includes: establishing the reference signal quality parameter, the traffic volume ratio and the judgment threshold and determine the decision threshold corresponding to the non-serving cell according to the reference signal quality parameter of the serving cell or a certain non-serving cell, the ratio of the traffic volume of the serving cell to the traffic volume of a certain non-serving cell, and the corresponding relationship.

Wherein, the corresponding relationship is a functional relationship y=f(xa, xb), wherein xa represents the reference signal quality parameter of the serving cell or a certain non-serving cell reported by the UE; xb represents the reference signal quality parameter of the serving cell and a certain non-serving cell Traffic ratio; y represents the decision threshold corresponding to the non-serving cell, and when xa1≥xa2 and xb1≥xb2, it is guaranteed that y1-y2=f(xa1,xb1)-f(xa2,xb2)≥0.

The above corresponding relationship may also be recorded in a table.

The reference signal quality parameter includes: reference signal received power (RSRP) or reference signal received quality (RSRQ).

An eNodeB provided by an embodiment of the present invention includes:

A reference signal quality parameter receiving unit, configured to receive the reference signal quality parameter of the serving cell and the reference signal quality parameter of the non-serving cell reported by the UE of the user;

A decision threshold determination unit, configured to determine the corresponding decisions of the non-serving cells according to the ratio of the serving cell or the reference signal quality parameters of the non-serving cells and/or the service traffic to the traffic of each non-serving cell reported by the UE Threshold, wherein, the decision threshold increases with the increase of the reference signal quality parameter and/or traffic ratio of the serving cell or each non-serving cell;

A coordinated feedback set determination unit, configured to calculate the difference between the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cells, and compare the calculated difference with the judgment corresponding to the non-serving cells threshold, and if the calculated difference is less than the decision threshold, then put the corresponding non-serving cell into the cooperative feedback set.

The above eNodeB further includes:

The coordinated feedback set size limiting unit is configured to select the first m cells with the largest reference signal quality parameters from the coordinated feedback set as the cells in the final coordinated feedback set, where m is the maximum number of cells that can be included in the coordinated feedback set.

Wherein, the decision threshold determination unit includes: a first module, configured to determine the decision threshold corresponding to each non-serving cell according to the reference signal quality parameters of the serving cell or each non-serving cell reported by the UE, wherein the decision threshold varies with the service The growth of the reference signal quality parameter of the cell or each non-serving cell increases.

Alternatively, the decision threshold determination unit includes: a traffic volume ratio calculation module, configured to calculate the ratios of the traffic volume of the serving cell to the traffic volume of each non-serving cell; The decision threshold corresponding to the non-serving cell, wherein the decision threshold increases with the increase of the traffic ratio.

Or the decision threshold determination unit includes: a traffic volume ratio calculation module, which is used to calculate the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell; The reference signal quality parameters of the reference signal quality parameters and the traffic volume ratios respectively determine the decision thresholds corresponding to the non-serving cells, wherein the decision thresholds increase with the reference signal quality parameters and traffic volume ratios of the serving cell or each non-serving cell And grow.

Another collaborative feedback set selection method provided by an embodiment of the present invention includes:

The eNodeB receives the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cell reported by the UE;

The eNodeB separately calculates the difference between the reference signal quality parameter of the serving cell and the reference signal quality parameter of each non-serving cell, and serves as the difference of the reference signal quality parameter corresponding to each non-serving cell;

The eNodeB respectively compares the reference signal quality parameter difference corresponding to each non-serving cell with a preset first threshold, and compares the reference signal quality parameters of each non-serving cell with a preset second threshold, if a If the reference signal quality parameter difference corresponding to a non-serving cell is less than the first threshold or the reference signal quality parameter of a non-serving cell is greater than the preset second threshold, then the corresponding non-serving cell is put into the coordinated feedback set.

The above method further includes: counting the cumulative distribution function CDF of the reference signal quality parameter of the serving cell; setting a percentage setting value; and according to the CDF of the reference signal quality parameter of the serving cell, setting the second threshold as the reference signal quality parameter of the serving cell The reference signal quality parameter value at which the cumulative distribution of is equal to the percentage setting.

Another eNodeB provided by an embodiment of the present invention includes:

A reference signal quality parameter receiving unit, configured to receive the reference signal quality parameter of the serving cell and the reference signal quality parameter of the non-serving cell reported by the user terminal UE;

The reference signal quality parameter difference determination unit is used to calculate the difference between the reference signal quality parameter of the serving cell and the reference signal quality parameter of each non-serving cell, respectively, as the reference signal quality parameter difference corresponding to each non-serving cell;

The third coordinated feedback set determination unit is configured to compare the reference signal quality parameter difference corresponding to each non-serving cell with a preset first threshold, and respectively compare the reference signal quality parameters of each non-serving cell with the preset first threshold Two thresholds are compared, if the reference signal quality parameter difference corresponding to a certain non-serving cell is less than the first threshold or the reference signal quality parameter of a certain non-serving cell is greater than the preset second threshold, then the corresponding non-serving cell will be put into coordination feedback set.

The above-mentioned eNodeB further includes: a second threshold adjustment unit, configured to dynamically adjust the second threshold according to the cumulative distribution of the reference signal quality parameter of the serving cell.

In the present invention, according to an embodiment of the present invention, the eNodeB can dynamically adjust the size of the decision threshold according to its own RSRP and/or the ratio of its own traffic to the traffic of each cell. When the ratio of traffic volume to a certain cell’s service volume is large, a larger decision threshold is selected to make it easier for the cells around the eNodeB to perform cooperative transmission with the eNode, while the eNodeB’s own RSRP is small and/or its own traffic volume is different from the business volume of each cell. When the ratio of the quantity is small, a smaller decision threshold is selected, making it more difficult for the cells around the eNodeB to perform cooperative transmission with the eNode, so that a trade-off between feedback overhead and cooperative transmission gain can be achieved, and a larger feedback overhead can be obtained with a smaller feedback overhead. Synergistic transfer gain.

According to another embodiment of the present invention, the eNodeB determines whether to add the non-serving cell to the cooperative feedback set according to the size of the capacity gain that a certain non-serving cell can obtain when participating in coordinated transmission, which can ensure that only the capacity gain greater than the preset Cells with a capacity gain threshold can join the cooperative feedback set, so a better trade-off between cooperative transmission gain and feedback overhead can be achieved. Moreover, this method only needs to set a fixed capacity gain threshold, and does not need to adjust the capacity gain in different network scenarios, so it is very simple to implement.

In addition, according to yet another embodiment of the present invention, by setting two fixed thresholds, the eNodeB ensures that, on the one hand, when the difference between the reference signal quality parameters of a serving cell and a non-serving cell is small, the non-serving cell On the other hand, when the reference signal quality parameter of a non-serving cell is relatively large, the non-serving cell can also be added to the cooperative feedback set, so that the gain of cooperative transmission can be effectively increased, and the gain of cooperative transmission and Good tradeoff between feedback overhead.

Description of drawings

Figure 1a is a schematic diagram of a traditional heterogeneous network;

Figure 1b shows the relationship between the location of the UE and the RSRP measured by the UE in the heterogeneous network shown in Figure 1a;

Figure 2a is a schematic diagram of a homogeneous network with asymmetric traffic;

Figure 2b shows the relationship between the location of the UE and the RSRP measured by the UE in the homogeneous network shown in Figure 2a;

Fig. 3 is a flow chart of a collaborative feedback set selection method according to the present invention;

FIG. 4 is a schematic diagram of the internal structure of the eNodeB implementing a cooperative feedback set selection method according to the present invention;

FIG. 5 is a flow chart of the collaborative feedback set selection method described in Embodiment 1 of the present invention;

FIG. 6 is a schematic diagram of the internal structure of the eNodeB implementing the cooperative feedback set selection method described in Embodiment 1 of the present invention;

FIG. 7 is a flow chart of the collaborative feedback set selection method described in Embodiment 2 of the present invention;

FIG. 8 is a schematic diagram of the internal structure of the eNodeB implementing the cooperative feedback set selection method described in Embodiment 2 of the present invention;

FIG. 9 is a flow chart of the collaborative feedback set selection method according to Embodiment 3 of the present invention;

FIG. 10 is a schematic diagram of the internal structure of the eNodeB implementing the cooperative feedback set selection method described in Embodiment 3 of the present invention;

Fig. 11 is a flowchart of another cooperative feedback set selection method according to the present invention;

FIG. 12 is a schematic diagram of the internal structure of the eNodeB implementing another collaborative feedback set selection method according to the present invention;

Fig. 13 is a flow chart of another collaborative feedback set selection method according to the present invention;

FIG. 14 is a schematic diagram of an internal structure of an eNodeB implementing yet another cooperative feedback set selection method according to the present invention.

Detailed ways

In the existing multi-base station coordinated transmission system, when the eNodeB receives the RSRP of all the cells reported by the UE, the eNodeB first calculates the difference between the RSRP of the serving cell and the RSRP of each cell reported by the UE, and uses the calculated The difference is compared with a preset fixed threshold (for example, 3dB), and if the calculated difference is smaller than the fixed threshold, the cell corresponding to the difference is put into the candidate set; finally, select from the candidate set in turn The first m cells with the largest RSRP are used as cells in the coordination feedback set, where m is the maximum number of cells that can be included in the coordination feedback set.

Through research, it can be found that the above-mentioned method of determining candidate sets based on fixed thresholds and then determining cooperative feedback sets is only applicable to symmetric networks with symmetric RSRP and symmetric traffic (for example, homogeneous networks with the same base station transmission power and the same path loss factor) , however, it is not suitable for heterogeneous networks with asymmetric RSRP or homogeneous or heterogeneous networks with asymmetric services. For example, in a heterogeneous network as shown in FIG. 1a , cell A is a serving cell of a UE, and cell B is a micro cell within the coverage of cell A. The RSRPs of cell A and cell B measured by the UE are shown in Figure 1b. In FIG. 1b, the horizontal axis represents the position of the UE, and the vertical axis represents the received power of the UE. It can be seen from Figure 1a and Figure 1b that when the UE is located between cell A and cell B, the absolute values of the RSRPs of cell A and cell B are relatively _high . The difference between the reference signal received power RSRP B of cell _B is greater than a preset fixed threshold (for example, 3dB), at this time, adding cell B to the cooperative feedback set can still obtain a large cooperative transmission gain; and when the UE is located far away from cell A and the location of cell B (the right side in Figure 1a), the absolute values of the RSRPs of cell A and cell B are relatively low. At this time, even if the RSRP of cell _A and the RSRP The difference of RSRP _B is less than a preset fixed threshold (for example, 3dB), and the cooperative transmission gain that can be obtained by adding cell B to the cooperative feedback set is also very small. For another example, in the homogeneous network shown in Figure 2a, the traffic volume of cell A is relatively high, while the traffic volume of cell B is relatively low. The UE transmits data, and cell B will have a lot of idle resources to cooperate with cell A to transmit data for the UE in cell A. Therefore, at this time, it is not very appropriate to still use a fixed threshold (for example, 3dB) to determine the candidate set.

In order to solve the above problems, the present invention provides a selection method of multiple cooperative feedback sets and a base station implementing the cooperative transmission method, which can achieve a better compromise between feedback overhead and cooperative transmission gain, that is, obtain Larger cooperative transmission gain.

Fig. 3 shows the flow of a collaborative feedback set selection method provided by the present invention. As shown in Figure 3, it mainly includes:

Step 301: The eNodeB receives the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cell reported by the UE;

Step 302: The eNodeB respectively determines the decision threshold corresponding to each non-serving cell according to the reference signal quality parameters of the serving cell or each non-serving cell reported by the UE and/or the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell, Wherein, the decision threshold corresponding to each non-serving cell increases with the increase of the reference signal quality parameter of the serving cell or each non-serving cell and/or the above-mentioned traffic ratio;

Step 303: eNodeB respectively calculates the difference between the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cells, and compares the calculated differences with the decision thresholds corresponding to the non-serving cells , if the calculated difference is smaller than the decision threshold, put the corresponding non-serving cell into the cooperative feedback set.

The method may further include:

Step 304: The eNodeB selects the first m cells with the largest reference signal quality parameters from the coordinated feedback set as cells in the final coordinated feedback set, where m is the maximum number of cells that can be included in the coordinated feedback set.

In step 304, the eNodeB may sort the cells in the candidate set according to the size of the reference signal quality parameters, and then select the first m cells with the largest reference signal quality parameters as the cells in the cooperative feedback set.

After determining the coordinated feedback set, the eNodeB configures the determined coordinated feedback set to the UE, and after receiving the CSI of the cells included in the coordinated feedback set fed back by the UE, performs scheduling, precoding, signaling and communication based on the CSI fed back by the UE. data transmission.

Corresponding to the above method, the present invention also provides an eNodeB that implements the above method, as shown in Figure 4, the interior of the base station mainly includes:

The reference signal quality parameter receiving unit 401 is configured to receive the reference signal quality parameter of the serving cell and the reference signal quality parameter of the non-serving cell reported by the UE;

The decision threshold determining unit 402 is configured to respectively determine the ratio of the serving cell or the reference signal quality parameters of each non-serving cell and/or the service traffic to the traffic of each non-serving cell reported by the UE. Judgment threshold, wherein, the judgment threshold corresponding to each non-serving cell increases with the growth of the serving cell or reference signal quality parameters of each non-serving cell reported by the UE and/or the above-mentioned traffic ratio;

The coordinated feedback set determination unit 403 is configured to calculate the difference between the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cells, and compare the calculated differences with the corresponding values of the non-serving cells. The decision threshold is compared, and if the calculated difference is smaller than the decision threshold, the corresponding non-serving cell is put into the cooperative feedback set.

The eNodeB above may further include:

The coordinated feedback set size limiting unit is configured to select the first m cells with the largest reference signal quality parameters from the coordinated feedback set as the cells in the final coordinated feedback set, where m is the maximum number of cells that can be included in the coordinated feedback set.

In the present invention, the eNodeB can dynamically adjust the size of the decision threshold corresponding to each non-serving cell according to the reference signal quality parameters of each cell and/or the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell. When it is better and/or the ratio of the traffic volume of the serving cell to the traffic volume of a certain non-serving cell is large, a larger decision threshold is selected to make it easier for the non-serving cell to perform cooperative transmission with the eNode, thereby obtaining a higher probability of cooperative transmission gain, and select a smaller decision threshold when the reference signal quality of the serving cell is poor and/or the ratio of the traffic volume of the serving cell to the traffic volume of a certain non-serving cell is small, making it more difficult for the non-serving cell to perform cooperative transmission with the eNode , thereby reducing feedback overhead.

In the present invention, the reference signal quality parameter includes: reference signal received power (RSRP) or reference signal received quality (RSRQ).

The above method will be described in detail below in conjunction with specific embodiments. In the following examples, the reference signal quality parameter is RSRP as an example for illustration. It should be noted that, in practical applications, using RSRQ instead of RSRP as the reference signal quality parameter can also realize the technical solution of the present invention, and the illustration will not be repeated here.

Example 1:

The method for selecting a collaborative feedback set provided in this embodiment determines the above-mentioned judgment threshold according to the RSRP of the serving cell or the non-serving cell reported by the UE. The implementation process is shown in FIG. 5 and mainly includes:

Step 3011: The eNodeB receives the RSRP of the serving cell and the RSRP of each non-serving cell reported by the UE;

Step 3021: The eNodeB respectively determines the decision threshold corresponding to each non-serving cell according to the RSRP of the serving cell or each non-serving cell reported by the UE, wherein the above-mentioned decision threshold increases with the increase of the RSRP of each cell;

Specifically, in this step, the eNodeB may determine a decision threshold according to the RSRP of the serving cell reported by the UE, and use the decision threshold as the decision threshold corresponding to each non-serving cell, wherein the above decision threshold varies with the RSRP of the serving cell. growth and growth.

Alternatively, in this step, the eNodeB may respectively determine the decision thresholds corresponding to the non-serving cells according to the RSRPs of the non-serving cells reported by the UE, wherein the decision thresholds corresponding to the non-serving cells vary with the RSRPs of the non-serving cells. grow and grow;

Step 3031: The eNodeB separately calculates the difference between the RSRP of the serving cell and the RSRP of each non-serving cell, and compares the calculated difference with the decision threshold corresponding to each non-serving cell, if the calculated difference is smaller than the non-serving cell If the corresponding decision threshold is determined, then the corresponding non-serving cell is put into the coordinated transmission set.

As mentioned above, the above method may further include the above step 304 .

After determining the coordinated feedback set, the eNodeB configures the determined coordinated feedback set to the UE, and after receiving the CSI of the cells included in the coordinated feedback set fed back by the UE, performs scheduling, precoding, signaling and communication based on the CSI fed back by the UE. data transmission.

The method for the eNodeB to determine the decision threshold according to its own RSRP reported by the UE described in step 3021 will be described in detail below, the method includes:

First, establish the corresponding relationship between the RSRP of the serving cell or each non-serving cell and the decision threshold;

Then, the decision threshold is determined according to the RSRP of the serving cell reported by the UE and the corresponding relationship.

Wherein, the above-mentioned corresponding relationship may be a functional relationship, such as y=f(x), wherein, x represents the RSRP of the serving cell or each non-serving cell, y represents the decision threshold corresponding to each non-serving cell, and x1>x2 , it is guaranteed that y1-y2=f(x1)-f(x2)>0. Specifically, the above functional relationship can be Among them, k is a constant. Alternatively, the above corresponding relationship may be a table as shown in Table 1 below.

RSRP of the serving cell or a non-serving cell decision threshold -50dBm 15dB -75dBm 10dB … …

Table 1

Those skilled in the art can understand that it will be simpler to implement if the above table is selected.

Corresponding to the above method, the present invention also provides an eNodeB that implements the above method. As shown in FIG. Wherein, the decision threshold determination unit 402 includes: a first module 4021, which is used to determine the decision threshold corresponding to each non-serving cell according to the reference signal quality parameters (for example, RSRP) of the serving cell or each non-serving cell reported by the UE, wherein The decision threshold corresponding to each non-serving cell increases with the increase of the serving cell or the reference signal quality parameters of each non-serving cell reported by the UE. Other units, such as the reference signal quality parameter receiving unit 401 and the cooperative feedback set determining unit 403 have the same functions as the units with the same numbers in FIG. 4 , and will not be repeated here.

It can be seen from the selection method of the cooperative feedback set and the internal structure of the eNodeB that the eNodeB dynamically adjusts the size of the decision threshold according to the RSRP of the serving cell or each non-serving cell reported by the UE. When the RSRP of the cell is large, a larger decision threshold is selected to make it easier for the non-serving cell to perform cooperative transmission with the eNode, thereby improving the gain of cooperative transmission. When the RSRP of the serving cell or each non-serving cell is small, a smaller decision threshold is selected , making it more difficult for the non-serving cell to perform cooperative transmission with the eNode, thereby reducing the feedback overhead.

Example 2:

The method for selecting a collaborative feedback set provided in this embodiment determines the corresponding decision thresholds for each non-serving cell according to the ratio of the traffic volume of the serving cell to the traffic volume of the non-serving cell. The implementation process is shown in Figure 7, which mainly includes:

Step 3011: The eNodeB receives the RSRP of the serving cell and the RSRP of each non-serving cell reported by the UE;

Step 3022: The eNodeB separately calculates the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell, and determines the decision threshold corresponding to each non-serving cell according to the traffic volume ratio, wherein the above-mentioned judgment threshold increases with the traffic volume ratio and grow;

Step 3031: The eNodeB separately calculates the difference between the RSRP of the serving cell and the RSRP of each non-serving cell, and compares the calculated difference with the decision threshold corresponding to each non-serving cell, if the calculated difference is smaller than the decision threshold, Then put the corresponding non-serving cell into the cooperative feedback set.

The above method may further include the above step 304 .

After determining the coordinated feedback set, the eNodeB configures the determined coordinated feedback set to the UE, and after receiving the CSI of the cells included in the coordinated feedback set fed back by the UE, performs scheduling, precoding, signaling and communication based on the CSI fed back by the UE. data transmission.

The method for eNodeB determining the decision threshold corresponding to each non-serving cell according to the above-mentioned traffic volume ratio described in the above-mentioned step 3022 is described in detail below, and the method mainly includes:

First, establish the corresponding relationship between the traffic ratio and the decision threshold;

Then, the eNodeB respectively determines the decision threshold corresponding to each non-serving cell according to the calculated ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell and the corresponding relationship between the traffic volume ratio and the decision threshold.

Wherein, the above-mentioned corresponding relationship may be a functional relationship, such as y=f(x), wherein, x represents the ratio of the service volume of the serving cell to a certain non-serving cell, y represents the decision threshold corresponding to the non-serving cell, and in When x1>x2, it is guaranteed that y1-y2=f(x1)-f(x2)>0. Specifically, the above functional relationship can be Among them, k is a constant. Alternatively, the above correspondence relationship may be a table as shown in Table 2 below.

business volume ratio decision threshold 5 15dB 2 10dB … …

Table 2

Those skilled in the art can understand that if the above table manner is selected, the implementation will be simpler.

Corresponding to the above method, the present invention also provides an eNodeB implementing the above method. As shown in FIG. 8 , the base station mainly includes: a reference signal quality parameter receiving unit 401 , a decision threshold determining unit 402 and a cooperative feedback set determining unit 403 . Wherein, the judgment threshold determination unit 402 includes: a traffic volume ratio calculation module 4022, which is used to calculate the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell; a second module 4023, which is used to determine respectively according to the traffic volume ratio The decision threshold corresponding to each non-serving cell, wherein the decision threshold increases as the traffic ratio increases. Other units, such as the reference signal quality parameter receiving unit 401 and the cooperative feedback set determining unit 403 have the same functions as the units with the same numbers in FIG. 4 , and will not be repeated here.

It can be seen from the selection method of the cooperative feedback set and the internal structure of the eNodeB that the eNodeB dynamically adjusts the size of the decision threshold according to the ratio of the traffic volume of the serving cell to the traffic volume of the non-serving cell. When the ratio of the traffic volume of the cell is large, a larger decision threshold is selected to make it easier for the non-serving cell to perform cooperative transmission with the eNode, thereby obtaining a higher gain of cooperative transmission, while the traffic volume of the serving cell and the non-serving cell When the ratio is small, a small decision threshold is selected to make it more difficult for the non-serving cell to perform cooperative transmission with the eNode, thereby reducing feedback overhead.

Example 3:

This embodiment provides a method for selecting a collaborative feedback set, which determines the corresponding non-serving cell according to the RSRP of the serving cell or the RSRP of the non-serving cell reported by the UE, and the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell. The judgment threshold of , its implementation process is shown in Figure 9, mainly including:

Step 3011: The eNodeB receives the RSRP of the serving cell and the RSRP of each non-serving cell reported by the UE;

Step 3023: The eNodeB separately calculates the ratio of the service volume of the serving cell to the traffic volume of each non-serving cell, and determines the decision threshold corresponding to each non-serving cell according to the RSRP of the serving cell or the non-serving cell and the above-mentioned traffic ratio, wherein, the above The decision threshold increases with the increase of the RSRP of the serving cell and the traffic ratio;

Step 3031: The eNodeB separately calculates the difference between the RSRP of the serving cell and the RSRP of each non-serving cell, and compares the calculated difference with the decision threshold corresponding to each non-serving cell, if the calculated difference is smaller than the decision threshold , put the corresponding non-serving cell into the cooperative feedback set.

As mentioned above, the above method may further include the above step 304 .

After determining the coordinated feedback set, the eNodeB configures the determined coordinated feedback set to the UE, and after receiving the CSI of the cells included in the coordinated feedback set fed back by the UE, performs scheduling, precoding, signaling and communication based on the CSI fed back by the UE. data transmission.

The method for eNodeB determining the corresponding decision threshold of each non-serving cell according to the RSRP of the serving cell and the traffic volume ratio described in the above step 3023 will be described in detail below. The method mainly includes:

First, establish the corresponding relationship between RSRP, traffic ratio and decision threshold;

Then, the eNodeB determines the above decision threshold according to the RSRP of the serving cell or the non-serving cell, the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell, and the above correspondence.

Wherein, the above corresponding relationship may be a functional relationship, such as y=f(xa, xb), wherein, xa represents the RSRP of the serving cell or a certain non-serving cell; xb represents the traffic ratio between the serving cell and a certain non-serving cell Ratio; y represents the decision threshold corresponding to the non-serving cell, and when xa1≥xa2 and xb1≥xb2, it is guaranteed that y1-y2=f(xa1, xb1)-f(xa2, xb2)≥0. Alternatively, the above corresponding relationship may be a table as shown in Table 3 below.

table 3

Those skilled in the art can understand that if the above table manner is selected, the implementation will be simpler.

Corresponding to the above method, the present invention also provides an eNodeB that implements the above method. As shown in FIG. 10 , the base station mainly includes: a reference signal quality parameter receiving unit 401, a decision threshold determining unit 402, and a cooperative feedback set determining unit 403. Wherein, the decision threshold determination unit 402 includes: a traffic volume ratio calculation module 4022, which is used to calculate the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell; The reference signal quality parameters of the non-serving cells and the traffic ratios respectively determine the decision thresholds corresponding to the non-serving cells, wherein the decision thresholds follow the reference signal quality parameters of the serving cell or each non-serving cell reported by the UE As well as the growth of business volume ratio. Other units, such as the reference signal quality parameter receiving unit 401 and the cooperative feedback set determining unit 403 have the same functions as the units with the same numbers in FIG. 4 , and will not be repeated here.

It can be seen from the selection method of the collaborative feedback set and the internal structure of the eNodeB that the eNodeB dynamically adjusts the judgment threshold according to the RSRP of the serving cell or each non-serving cell and the ratio of the traffic volume of the serving cell to the traffic volume of each non-serving cell. Yes, when the RSRP of the serving cell or a non-serving cell is large and the ratio of the traffic volume of the serving cell to the traffic volume of a non-serving cell is large, a larger decision threshold is selected to make it easier for the non-serving cell to communicate with the eNode. Coordinated transmission, so as to obtain a higher gain of coordinated transmission, and select a smaller decision threshold when the RSRP of the serving cell or a non-serving cell is small and the ratio of the traffic volume of the serving cell to the traffic volume of a non-serving cell is small, It makes it more difficult for the non-serving cell to perform cooperative transmission with the eNode, thereby reducing the feedback overhead.

In addition to the above solution, the present invention also provides another collaborative feedback set selection method, the flow of which is shown in Figure 11, mainly including:

Step 301: The eNodeB receives the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cell reported by the UE;

Step 1101: The eNodeB separately calculates the capacity gain that each non-serving cell can obtain when participating in coordinated transmission according to the reference signal quality parameter of each cell reported by the UE;

This step may specifically include:

First, the eNodeB separately calculates the user capacity of each non-serving cell when it participates in coordinated transmission and the user capacity when it does not participate in coordinated transmission according to the reference signal quality parameter (for example, RSRP or RSRQ) of each cell reported by the UE;

Then, the eNodeB separately calculates the difference between the user capacity of each non-serving cell when it participates in coordinated transmission and the user capacity when it does not participate in coordinated transmission, and compares the difference between the user capacity and the user capacity when the non-serving cell does not participate in coordinated transmission The ratios of user capacities are respectively used as capacity gains corresponding to the non-serving cells.

Specifically, the user capacity of a certain non-serving cell when participating in coordinated transmission can be calculated by the following formula (1):

Among them, RSRP _S is the RSRP of the serving cell; RSRP _C is the RSRP of a non-serving cell; ICI is the inter-cell interference between the serving cell and the non-serving cell; N is noise.

Furthermore, if it is assumed that the joint multi-point processing (JP) cooperative transmission technology is adopted, the user capacity of each non-serving cell when participating in cooperative transmission can be calculated by the following formula (2):

Among them, RSRP _S is the RSRP of the serving cell; RSRP _C is the RSRP of a non-serving cell; ICI is the inter-cell interference between the serving cell and the non-serving cell; N is noise.

Assuming that the coordinated transmission technology of coordinated scheduling/coordinated beamforming (CS/CB) is adopted, the user capacity of each non-serving cell when participating in coordinated transmission can be calculated by the following formula (3):

Among them, RSRP _S is the RSRP of the serving cell; ICI is the inter-cell interference between the serving cell and the non-serving cell; N is noise.

The user capacity of a non-serving cell when not participating in coordinated transmission can be calculated by the following formula (4):

Among them, RSRP _S is the RSRP of the serving cell, RSRP _C is the RSRP of a non-serving cell; ICI is the inter-cell interference between the serving cell and the non-serving cell; N is noise.

Step 1102: the eNodeB respectively judges whether the capacity gain of each non-serving cell is greater than a preset capacity gain threshold (for example, 30%), and if so, puts the corresponding non-serving cell into the cooperative feedback set.

After the above process is performed, the above step 304 may be further performed to determine the final collaborative feedback set.

After determining the coordinated feedback set, the eNodeB configures the determined coordinated feedback set to the UE, and after receiving the CSI of the cells included in the coordinated feedback set fed back by the UE, performs scheduling, precoding, signaling and communication based on the CSI fed back by the UE. data transmission.

Corresponding to the above method, the present invention also provides an eNodeB for implementing the above method, as shown in FIG. 12 , the interior of the base station mainly includes:

The reference signal quality parameter receiving unit 401 is configured to receive the reference signal quality parameters of the serving cell and each non-serving cell reported by the user terminal UE;

The capacity gain determining unit 501 is configured to calculate the capacity gain that each non-serving cell can obtain when participating in coordinated transmission according to the reference signal quality parameters of the serving cell and each non-serving cell reported by the UE; and

The second cooperative feedback set determining unit 502 is configured to judge whether the capacity gain of each non-serving cell is greater than a preset capacity gain threshold, and if so, put the corresponding non-serving cell into the cooperative feedback set.

As mentioned above, the aforementioned reference signal quality parameters include RSRP or RSRQ.

From the selection method of the cooperative feedback set and the internal structure of the eNodeB, it can be seen that the eNodeB pre-estimates the capacity gain that a non-serving cell can obtain when participating in cooperative transmission, and determines whether to use the non-serving cell according to the size of the capacity gain. Adding a cooperative feedback set can ensure that only cells with a capacity gain greater than a preset capacity gain threshold can join the coordinated feedback set, so a better trade-off between cooperative transmission gain and feedback overhead can be achieved. Moreover, the above method only needs to set a fixed capacity gain threshold, and does not need to adjust the capacity gain in different network scenarios, so it is very simple to implement.

In addition to the above solution, the present invention also provides another collaborative feedback set selection method, the flow of which is shown in Figure 13, mainly including:

Step 301: The eNodeB receives the reference signal quality parameters of the serving cell and the reference signal quality parameters of the non-serving cell reported by the UE;

Step 1301: eNodeB respectively calculates the difference between the reference signal quality parameter of the serving cell and the reference signal quality parameter of each non-serving cell, and uses them as the difference of reference signal quality parameters corresponding to each non-serving cell;

Step 1302: The eNodeB compares the reference signal quality parameter difference corresponding to each non-serving cell with a preset first threshold (for example, 3dB), and compares the reference signal quality parameters of each non-serving cell with the preset first threshold respectively. Two thresholds are compared, if the reference signal quality parameter difference corresponding to a certain non-serving cell is less than the first threshold or the reference signal quality parameter of a certain non-serving cell is greater than the preset second threshold, then the corresponding non-serving cell will be put into coordination feedback set.

After the above process is performed, the above step 304 may be further performed to determine the final collaborative feedback set.

After determining the coordinated feedback set, the eNodeB configures the determined coordinated feedback set to the UE, and after receiving the CSI of the cells included in the coordinated feedback set fed back by the UE, performs scheduling, precoding, signaling and communication based on the CSI fed back by the UE. data transmission.

Furthermore, in the above method, the following method can also be used to dynamically adjust the above second threshold according to the cumulative distribution of the reference signal quality parameters of the serving cell, specifically including:

First, under a certain transmission power and cell radius, the statistics are the cumulative distribution function (CDF) of the reference signal quality parameters of the serving cell;

Then, set a percentage setpoint, for example, 5%;

Finally, according to the CDF of the reference signal quality parameter of the serving cell, the second threshold is set as the reference signal quality parameter value when the cumulative distribution of the reference signal quality parameter of the serving cell is equal to the percentage setting value.

Corresponding to the above method, the present invention also provides an eNodeB for implementing the above method, as shown in FIG. 14 , the interior of the base station mainly includes:

The reference signal quality parameter receiving unit 401 is configured to receive the reference signal quality parameter of the serving cell and the reference signal quality parameter of the non-serving cell reported by the user terminal UE;

The reference signal quality parameter difference determining unit 601 is used to calculate the difference between the reference signal quality parameter of the serving cell and the reference signal quality parameter of each non-serving cell, respectively, as the reference signal quality parameter difference corresponding to each non-serving cell;

The third coordinated feedback set determination unit 602 is configured to compare the reference signal quality parameter difference corresponding to each non-serving cell with a preset first threshold, and respectively compare the reference signal quality parameters of each non-serving cell with the preset For comparison with the second threshold, if the reference signal quality parameter difference corresponding to a certain non-serving cell is smaller than the first threshold or if the reference signal quality parameter of a certain non-serving cell is greater than the preset second threshold, then the corresponding non-serving cell will be put into Collaborative Feedback Set.

The above-mentioned eNodeB may further include: a second threshold adjusting unit 603, configured to dynamically adjust the second threshold according to the cumulative distribution of the reference signal quality parameter of the serving cell.

As mentioned above, the aforementioned reference signal quality parameters include RSRP or RSRQ.

It can be seen from the selection method of the cooperative feedback set and the internal structure of the eNodeB that the eNodeB sets two fixed thresholds to ensure that the difference between the reference signal quality parameters of the serving cell and a non-serving cell is small. Next, add the non-serving cell to the cooperative feedback set. On the other hand, when the reference signal quality parameter of a non-serving cell itself is large, the non-serving cell can also be added to the cooperative feedback set, so that the gain of cooperative transmission can be effectively increased. , to achieve a better trade-off between cooperative transmission gain and feedback overhead.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of the present invention. within the scope of protection.

Claims (24)

1. a kind of collaborative feedback collection selection method, which is characterized in that including：

Base station eNodeB receives the reference signal quality parameter of serving cell and the ginseng of non-service cell of user terminal UE reports Examine signal quality parameter；

ENodeB is according to the UE serving cells reported or the reference signal quality parameter of non-service cell and/or serving cell business Amount determines the corresponding decision threshold in each non-service cell respectively with the ratio of the portfolio of each non-service cell, wherein, it is described to sentence Certainly thresholding increases with the growth of the reference signal quality parameter and/or the portfolio ratio of serving cell or non-service cell It is long；

ENodeB calculates the reference signal quality parameter of serving cell and the reference signal quality of each non-service cell respectively The difference of parameter, and by the difference being calculated respectively decision threshold corresponding with each non-service cell compared with, such as The difference that fruit is calculated is less than decision threshold, then corresponding non-service cell is put into collaborative feedback collection.

2. according to the method described in claim 1, further comprise：

ENodeB from collaborative feedback concentration select before m reference signal quality parameter maximum cell as final collaborative feedback collection In cell, wherein, m can include the maximum number of cell for collaborative feedback collection.

3. according to the method described in claim 1, wherein, the eNodeB is according to the UE serving cells reported or non-service cell Reference signal quality parameter and/or serving cell portfolio and each non-service cell portfolio ratio determine respectively it is described The corresponding decision threshold in each non-service cell includes：ENodeB is true according to the reference signal quality parameter of the UE serving cells reported A fixed decision threshold, and using the decision threshold as the corresponding decision threshold in each non-service cell, wherein, the decision gate Limit increases with the growth of serving cell reference signal quality parameter.

4. according to the method described in claim 3, wherein, eNodeB joins according to the reference signal quality of the UE serving cells reported Number determines that a decision threshold includes：

Establish the correspondence of reference signal quality parameter and decision threshold；And

The decision threshold is determined according to the reference signal quality parameter of the UE serving cells reported and the correspondence.

5. according to the method described in claim 4, wherein, the correspondence is functional relation y=f (x), wherein, x represents clothes The reference signal quality parameter for cell of being engaged in, y represent decision threshold, and in x1>During x2, ensure y1-y2=f (x1)-f (x2)> 0。

6. according to the method described in claim 1, wherein, the eNodeB is small according to the UE serving cells reported or each non-serving The reference signal quality parameter and/or serving cell portfolio in area and the ratio of the portfolio of each non-service cell determine institute respectively Stating the corresponding decision threshold in each non-service cell includes：ENodeB is according to the reference signal quality parameter of each non-service cell Determine the corresponding decision threshold in each non-service cell respectively, wherein, the corresponding decision threshold in each non-service cell with It the growth of the reference signal quality parameter of each non-service cell and increases.

7. according to the method described in claim 6, wherein, eNodeB joins according to the reference signal quality of each non-service cell Number determines that the corresponding decision threshold in each non-service cell includes respectively：

Establish the correspondence of reference signal quality parameter and decision threshold；And

The non-clothes are determined according to the reference signal quality parameter of the UE a certain non-service cells reported and the correspondence The corresponding decision threshold of cell of being engaged in.

8. according to the method described in claim 7, wherein, the correspondence is functional relation y=f (x), wherein, x represents certain The reference signal quality parameter of one non-service cell, y represent the corresponding decision threshold in the non-service cell, and in x1>During x2, Ensure y1-y2=f (x1)-f (x2)>0.

9. according to the method described in claim 1, wherein, the eNodeB is small according to the UE serving cells reported or each non-serving The reference signal quality parameter and/or serving cell portfolio in area and the ratio of the portfolio of each non-service cell determine institute respectively Stating the corresponding decision threshold in each non-service cell includes：ENodeB calculates serving cell portfolio respectively and each non-serving is small The ratio of the portfolio in area, and the corresponding decision threshold in each non-service cell is determined according to the portfolio ratio respectively, Wherein, the corresponding decision threshold in each non-service cell increases with the growth of portfolio ratio.

10. according to the method described in claim 9, wherein, determine that each non-serving is small respectively according to the portfolio ratio The corresponding decision threshold in area includes：

Establish the correspondence of portfolio ratio and decision threshold；And

Determine that this is non-according to serving cell portfolio and the ratio of the portfolio of a certain non-service cell and the correspondence The corresponding decision threshold of serving cell.

11. according to the method described in claim 10, wherein, the correspondence is functional relation y=f (x), wherein, x is represented The ratio of the portfolio of serving cell and a certain non-service cell portfolio, y represent the corresponding decision threshold in the non-service cell, And in x1>During x2, ensure y1-y2=f (x1)-f (x2)>0.

12. according to the method described in claim 1, wherein, the eNodeB is according to the UE serving cells reported or each non-serving The reference signal quality parameter and/or serving cell portfolio and the ratio of the portfolio of each non-service cell of cell determine respectively The corresponding decision threshold in each non-service cell includes：ENodeB calculates serving cell portfolio and each non-serving respectively The ratio of the portfolio of cell, and according to UE report serving cell or each non-service cell reference signal quality parameter and The portfolio ratio determines the corresponding decision threshold in each non-service cell respectively, wherein, the decision threshold is with clothes Business cell or the reference signal quality parameter of each non-service cell and the growth of portfolio ratio and increase.

13. the method according to claim 11, wherein, according to the reference of the UE serving cells reported or each non-service cell Signal quality parameter and the portfolio ratio determine that the corresponding decision threshold in each non-service cell includes respectively：

Establish the correspondence of reference signal quality parameter, portfolio ratio and decision threshold；And

According to the reference signal quality parameter of serving cell or a certain non-service cell, serving cell portfolio and a certain non-serving The ratio of the portfolio of cell and the correspondence determine the corresponding decision threshold in the non-service cell.

14. according to the method for claim 13, wherein, the correspondence is functional relation y=f (xa, xb), wherein, Xa represents the serving cell of UE reports or the reference signal quality parameter of some non-service cell；Xb represents serving cell and some The portfolio ratio of non-service cell；Y represents the corresponding decision threshold in the non-service cell, and xa1 >=xa2 and xb1 >= During xb2, ensure y1-y2=f (xa1, xb1)-f (xa2, xb2) >=0.

15. according to the method described in claim 4,7,10 or 13, wherein, the correspondence record is in the table.

16. according to any one of claim 1 to 8 or 12 to 14 or the method, wherein, the reference signal quality parameter Including：Reference Signal Received Power RSRP or Reference Signal Received Quality RSRQ.

17. a kind of base station eNodeB, which is characterized in that including：

Reference signal quality parameter receiving unit (401), for receiving the reference signal matter of the serving cell of the UE of user reports Measure parameter and the reference signal quality parameter of non-service cell；

Decision threshold determination unit (402), for the serving cell or the reference signal matter of each non-service cell reported according to UE Amount parameter and/or service business amount determine that each non-service cell is corresponding respectively with the ratio of the portfolio of each non-service cell Decision threshold, wherein, the decision threshold with serving cell or each non-service cell reference signal quality parameter and/or The growth of portfolio ratio and increase；

Collaborative feedback collection determination unit (403), for calculate respectively the reference signal quality parameter of serving cell with it is described each non- The difference of the reference signal quality parameter of serving cell, and sentence the difference being calculated is corresponding with each non-service cell Certainly thresholding is compared, if the difference being calculated is less than decision threshold, corresponding non-service cell is put into collaborative feedback Collection.

18. eNodeB according to claim 17, further comprises：

Collaborative feedback collection size limiting unit (404), for from collaborative feedback concentrate selection before m reference signal quality parameter most The cell that big cell is concentrated as final collaborative feedback, wherein, m can include the maximum number of cell for collaborative feedback collection.

19. eNodeB according to claim 17, wherein, decision threshold determination unit (402) includes：

First module (4021), for the serving cell or the reference signal quality parameter point of each non-service cell reported according to UE Not Que Ding the corresponding decision threshold in each non-service cell, wherein, the decision threshold is with serving cell or each non-service cell Reference signal quality parameter growth and increase.

20. eNodeB according to claim 17, wherein, decision threshold determination unit (402) includes：

Portfolio ratio calculation module (4022), for calculating the portfolio of serving cell portfolio and each non-service cell respectively Ratio；

Second module (4023), for determining the corresponding decision gate in each non-service cell respectively according to the portfolio ratio Limit, wherein, the decision threshold increases with the growth of portfolio ratio.

21. eNodeB according to claim 17, wherein, decision threshold determination unit (402) includes：

Portfolio ratio calculation module (4022), for calculating the portfolio of serving cell portfolio and each non-service cell respectively Ratio；

3rd module (4024), for the serving cell reported according to UE or the reference signal quality parameter of each non-service cell with And the portfolio ratio determines the corresponding decision threshold in each non-service cell respectively, wherein, the decision threshold with The growth of the reference signal quality parameter and portfolio ratio of serving cell or each non-service cell and increase.

22. a kind of collaborative feedback collection selection method, which is characterized in that including：

Base station eNodeB receives the reference signal quality parameter of serving cell and the ginseng of non-service cell of user terminal UE reports Examine signal quality parameter；

ENodeB calculates the reference signal quality parameter of serving cell and the reference signal quality parameter of each non-service cell respectively Difference, respectively as the corresponding reference signal quality parameter difference in each non-service cell；And

ENodeB respectively by the corresponding reference signal quality parameter difference in each non-service cell and pre-set first thresholding into Row compares and respectively by the reference signal quality parameter of each non-service cell compared with preset second thresholding, If the corresponding reference signal quality parameter difference in some non-service cell is less than the first thresholding or some non-service cell with reference to letter Number mass parameter is more than pre-set second thresholding, then corresponding non-service cell is put into collaborative feedback collection；

The method is further included：

The Cumulative Distribution Function CDF of statistical fractals cell reference signals mass parameter；

One percentage setting value is set；And

According to the CDF of serving cell reference signal quality parameter, by the reference signal quality that the second threshold sets are serving cell The cumulative distribution of parameter is equal to the reference signal quality parameter value during percentage setting value.

23. a kind of base station eNodeB, which is characterized in that including：

Reference signal quality parameter receiving unit (401), for receiving the reference signal of the serving cell of user terminal UE reports Mass parameter and the reference signal quality parameter of non-service cell；

Reference signal quality parameter difference determination unit (601), for calculating the reference signal quality parameter of serving cell respectively With the difference of the reference signal quality parameter of each non-service cell, respectively as the corresponding reference signal quality in each non-service cell Parameter difference；

3rd collaborative feedback collection determination unit (602), for the corresponding reference signal quality parameter difference in each non-service cell with Pre-set first thresholding is compared and respectively by the reference signal quality parameter of each non-service cell with presetting The second thresholding be compared, if the corresponding reference signal quality parameter difference in some non-service cell be less than the first thresholding or certain A non-service cell reference signal quality parameter is more than pre-set second thresholding, then corresponding non-service cell is put into collaboration Feedback collection；

Further comprise, the second thresholding adjustment unit (603), for accumulative point of statistical fractals cell reference signals mass parameter Cloth function CDF；One percentage setting value is set；And the CDF according to serving cell reference signal quality parameter, by second Limit is set as the reference signal when cumulative distribution of the reference signal quality parameter of serving cell is equal to the percentage setting value Quality parameter value.

24. base station according to claim 23, the second thresholding adjustment unit (603), are further used for according to service The cumulative distribution dynamic of cell reference signals mass parameter adjusts second thresholding.