CN114204967A

CN114204967A - Beam weight determination method, base station and readable medium

Info

Publication number: CN114204967A
Application number: CN202010910246.8A
Authority: CN
Inventors: 罗泽群; 张德坤; 刘巧艳
Original assignee: ZTE Corp
Current assignee: ZTE Corp
Priority date: 2020-09-02
Filing date: 2020-09-02
Publication date: 2022-03-18

Abstract

The present disclosure provides a method for determining a beam weight, including: determining a performance index function to be optimized according to key performance index KPI information reported by user terminals in at least one target cell respectively belonging to at least one base station, wherein the performance index function to be optimized represents the state of performance to be optimized of the whole target cell respectively belonging to at least one base station when the base station to which the target cell belongs configures different beam weight groups, wherein the current base station stores a plurality of beam weight groups, and each beam weight group comprises a plurality of beam weight values; and determining a target beam weight set of the base station to which the target cell belongs from the plurality of beam weight sets according to the performance index function to be optimized. The present disclosure also provides a base station, a computer readable medium.

Description

Beam weight determination method, base station and readable medium

Technical Field

The present disclosure relates to the field of communications technologies, and in particular, to a method for determining a beam weight, a base station, and a computer-readable medium.

Background

In a Multiple Input Multiple Output (MIMO) technology, dimensions of a spatial domain are introduced, so that User Equipment (UE) at different positions multiplex the same time-frequency resource, and utilization efficiency of cell spectrum resources is improved. The large-scale MIMO (massive MIMO) technology further increases the number of antennas at the base station side on the basis of MIMO, and can spatially multiplex more user terminals on the same time-frequency resource, so that the utilization efficiency of the frequency spectrum resource of a cell is further improved. MIMO and Massive MIMO technologies have become one of the core technologies of 5G communication.

In MIMO and Massive MIMO cells, a plurality of prefabricated narrow beams are used for covering the whole cell, so that the coverage area of the cell is improved; and space division multiplexing of user terminals in the cell can be realized through natural space isolation of different narrow beams. The existing coverage schemes of MIMO and Massive MIMO cells cannot ensure that the performance of the cells reaches the optimum.

Disclosure of Invention

The embodiment of the disclosure provides a method for determining a beam weight, a base station and a computer readable medium.

In a first aspect, an embodiment of the present disclosure provides a method for determining a beam weight, including:

determining a performance index function to be optimized according to key performance index KPI information reported by user terminals in at least one target cell respectively belonging to at least one base station, wherein the performance index function to be optimized represents the state of performance to be optimized of the whole target cell respectively belonging to at least one base station when the base station to which the target cell belongs configures different beam weight groups, wherein the current base station stores a plurality of beam weight groups, and each beam weight group comprises a plurality of beam weight values;

and determining a target beam weight set of the base station to which the target cell belongs from the plurality of beam weight sets according to the performance index function to be optimized.

In some embodiments, the step of determining the performance indicator function to be optimized according to key performance indicator KPI information reported by a user terminal in the target cell belonging to the current base station includes:

determining a weighting factor of each user terminal in the target cell belonging to the current base station according to KPI information reported by the user terminal in the target cell belonging to the current base station, wherein the weighting factor represents the communication requirement of the user terminal;

determining the performance index function component to be optimized of each user terminal in the target cell belonging to the current base station when the current base station configures different beam weight groups according to KPI information reported by each user terminal in the target cell belonging to the current base station;

and determining the performance index function to be optimized according to the weighting factor of each user terminal in the target cell belonging to the current base station and the component of the performance index function to be optimized of each user terminal in the target cell belonging to the current base station when the current base station configures different beam weight groups.

In some embodiments, in a case that the current base station stores the transmission power of the current base station in each direction when configuring different beam weight groups, the step of determining, according to KPI information reported by each user terminal in the target cell belonging to the current base station, a to-be-optimized performance indicator function component of each user terminal in the target cell belonging to the current base station when configuring different beam weight groups by the current base station includes:

and determining the performance index function component to be optimized of the user terminal when the current base station configures different beam weight groups according to the position information of the user terminal in the KPI information reported by the user terminal and the transmitting power of the current base station in each direction when the current base station configures different beam weight groups.

In some embodiments, the step of determining a target set of beam weight values for the current base station from the plurality of sets of beam weight values according to the performance indicator function to be optimized comprises:

judging whether the coverage enhancement direction of the target cell belonging to the current base station is intersected with the coverage enhancement direction of the cell of the adjacent base station of the current base station;

and when the coverage enhancement direction of the target cell belonging to the current base station does not intersect with the coverage enhancement direction of the cell of the adjacent base station, determining the corresponding beam weight group when the performance index function to be optimized takes the maximum value as the target beam weight group of the current base station.

In some embodiments, when there is an intersection between the coverage enhancing direction of the target cell belonging to the current base station and the coverage enhancing direction of the cell of the neighboring base station, the step of determining the target beam weight set of the current base station from the plurality of beam weight sets according to the performance indicator function to be optimized further includes:

judging whether the difference between the maximum value of the performance index function to be optimized of the target cell belonging to the current base station and the maximum value of the performance index function to be optimized of the cell of the adjacent base station exceeds a preset threshold value or not;

and when the difference between the maximum value of the performance index function to be optimized of the target cell belonging to the current base station and the maximum value of the performance index function to be optimized of the cell of the adjacent base station exceeds the preset threshold value, determining a corresponding beam weight group when the performance index function to be optimized of the target cell belonging to the current base station takes the maximum value as the target beam weight group of the current base station.

In some embodiments, when a difference between a maximum value of the performance indicator function to be optimized of the target cell belonging to the current base station and a maximum value of the performance indicator function to be optimized of the cell of the neighboring base station does not exceed the predetermined threshold, the step of determining the target beam weight group of the current base station from the plurality of beam weight groups according to the performance indicator function to be optimized further comprises:

determining a default beam weight value set as a target beam weight value set of the current base station, the default beam weight value set being one of a plurality of beam weight value sets stored by the current base station.

In some embodiments, before the step of determining the target beam weight set of the current base station from the plurality of beam weight sets according to the performance indicator function to be optimized, the determining method further includes:

determining a coverage enhancement direction of the target cell belonging to the current base station when the current base station configures a corresponding beam weight value group when the performance index function to be optimized takes the maximum value;

and sending the coverage enhancement direction information of the target cell belonging to the current base station and the maximum value of the performance index function to be optimized to the adjacent base station of the current base station.

In some embodiments, the performance indicator function to be optimized is expressed by the following formula:

wherein P (i) is a value of the performance indicator function to be optimized when the ith beam weight group is configured for the current base station, N is the number of the user terminals in the cell belonging to the current base station, and alpha_nWeighting factor, p, for the nth user terminal in the target cell_i,nAnd when the ith beam weight group is configured for the current base station, the performance index function component to be optimized of the nth user terminal in the target cell is configured, N is the serial number of the user terminal in the target cell, N and N are positive integers, and N is more than or equal to 1 and less than or equal to N.

In some embodiments, before the step of determining a performance indicator function to be optimized according to key performance indicator KPI information reported by a user equipment in the target cell belonging to the current base station, the determining method further includes:

judging whether the current base station meets the wave beam optimization condition or not according to KPI information reported by the user terminal in the target cell belonging to the current base station;

and when the current base station meets the beam optimization condition, executing the step of determining a performance index function to be optimized according to key performance index KPI information reported by the user terminal in the target cell belonging to the current base station.

In some embodiments, when the current base station satisfies the beam optimization condition, the determining method further includes:

and sending a notification message for beam optimization to base stations except the current base station to trigger the base stations except the current base station to perform beam optimization.

In some embodiments, the base station includes a plurality of target base stations, the target cells belong to the target base stations, respectively, and the step of determining the performance indicator function to be optimized according to key performance indicator KPI information reported by user terminals in the target cells belonging to the target base stations, respectively, includes:

determining a to-be-optimized performance indicator function component of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups according to KPI information of the user terminal in the target cell served by the target base station reported by a plurality of target base stations;

and determining the performance index function to be optimized according to the performance index function component to be optimized of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups and the weighting factor reported by each target base station of each user terminal in the target cell served by each target base station, wherein the weighting factor represents the communication requirement of the user terminal in the cell served by the target base station.

In some embodiments, the step of determining, according to KPI information of a user terminal in the target cell served by the target base station, which is reported by a plurality of target base stations, a to-be-optimized performance indicator function component of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups includes:

and determining the performance index function component to be optimized of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups according to the position information of the user terminal in the KPI information of the user terminal in the target cell served by the target base station reported by the target base stations and the transmitting power in each direction when the target base station configures different beam weight groups stored by the current base station.

In some embodiments, the step of determining the performance index function to be optimized according to the component of the performance index function to be optimized of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups and the weighting factor reported by each target base station of each user terminal in the serving cell served by each target base station includes:

weighting the to-be-optimized performance index function components of the user terminals in the target cells served by the target base stations through the weighting factors of the user terminals, and then summing the weighted components to serve as the to-be-optimized performance index function, wherein the to-be-optimized performance index function components of the user terminals in the target cells served by the same target base station correspond to the same beam weight group.

In some embodiments, determining a target set of beam weights for a plurality of the target base stations from the plurality of sets of beam weights according to the performance indicator function to be optimized comprises:

and when the performance index function to be optimized obtains a maximum value, determining the beam weight group corresponding to each target base station as a target beam weight group of each target base station respectively.

In some embodiments, the determining method further comprises:

and sending the target beam weight set information of each target base station to each target base station so as to enable each target base station to be switched to the respective target beam weight set.

In some embodiments, the step of determining a performance indicator function to be optimized according to key performance indicator KPI information reported by a user equipment in the target cell served by the target base station and reported by a plurality of target base stations includes:

and in response to a notification message for beam optimization sent by at least one target base station, determining a performance index function to be optimized according to key performance index KPI information reported by user terminals in the target cell served by the target base stations and reported by the target base stations.

In some embodiments, the performance to be optimized includes one or more of throughput, received power, signal to interference plus noise ratio.

In a second aspect, an embodiment of the present disclosure provides a base station, including:

one or more processors;

a storage device, on which one or more programs are stored, which, when executed by the one or more processors, cause the one or more processors to implement any one of the above methods for determining beam weight values;

one or more I/O interfaces connected between the processor and the memory and configured to enable information interaction between the processor and the memory.

In a third aspect, the present disclosure provides a computer-readable medium, on which a computer program is stored, where the computer program is executed by a processor to implement any one of the foregoing methods for determining a beam weight value.

In the embodiment of the disclosure, a plurality of beam weight value sets are prefabricated and stored in a base station in advance, each beam weight value set is respectively suitable for different coverage scenes, and when beam optimization is required, the beam weight value set which enables the whole network formed by cells respectively belonging to a plurality of base stations or the to-be-optimized performance of the cells belonging to the same base station to be optimal is determined as a target beam weight value set through a to-be-optimized performance index function; when the base station configures the target beam weight group to cover the MIMO or Massive MIMO cell, the coverage of the beam can be matched with the distribution of the user terminal or the service distribution, so that the performance to be optimized of the whole network formed by cells respectively belonging to a plurality of base stations or the cells belonging to the same base station can be optimized.

Drawings

Fig. 1 is a flowchart of a method for determining beam weights in an embodiment of the present disclosure;

fig. 2 is a flowchart of some steps in another method for determining beam weights in the embodiment of the present disclosure;

fig. 3 is a flowchart of a part of steps in a method for determining a beam weight according to another embodiment of the present disclosure;

fig. 4 is a flowchart of some steps in a method for determining a beam weight according to another embodiment of the present disclosure;

fig. 5 is a flowchart of some steps in a method for determining a beam weight according to another embodiment of the present disclosure;

fig. 6 is a flowchart of some steps in a method for determining a beam weight according to another embodiment of the present disclosure;

fig. 7 is a flowchart of some steps in a method for determining a beam weight according to another embodiment of the disclosure;

fig. 8 is a flowchart of some steps in a method for determining a beam weight according to another embodiment of the present disclosure;

fig. 9 is a flowchart of some steps in a method for determining a beam weight according to another embodiment of the disclosure;

fig. 10 is a flowchart of some steps in a method for determining beam weights according to another embodiment of the present disclosure;

fig. 11 is a flowchart of some steps in a method for determining beam weights according to another embodiment of the present disclosure;

fig. 12 is a flowchart of some steps in a method for determining beam weights according to another embodiment of the disclosure;

fig. 13 is a flowchart of some steps in a method for determining beam weights according to another embodiment of the present disclosure;

fig. 14 is a flow chart of a beamforming method in an embodiment of the disclosure;

fig. 15 is a block diagram of a base station in an embodiment of the disclosure;

FIG. 16 is a block diagram of a computer-readable medium in an embodiment of the disclosure.

Detailed Description

In order to make those skilled in the art better understand the technical solution of the present disclosure, the method for determining the beam weight value, the base station, and the computer readable medium provided in the present disclosure are described in detail below with reference to the accompanying drawings.

Example embodiments will be described more fully hereinafter with reference to the accompanying drawings, but which may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

The research of the inventor of the present disclosure finds that, in an area, the distribution of UEs in different MIMO or Massive MIMO cells is often different, and the communication demand of each UE is also different; furthermore, in the same cell, the distribution of UEs and the communication needs of UEs may change over time. Therefore, only one set of multi-beam is used for covering in an MIMO or Massive MIMO cell, which cannot meet the communication requirements of the UE at different times, and different cells are covered by only the same set of multi-beam, which is often not the best coverage scheme, and tends to interfere with the hot spot coverage area of the adjacent cell, causing the performance degradation of the adjacent cell.

In view of the above, in a first aspect, referring to fig. 1, an embodiment of the present disclosure provides a method for determining a beam weight, including:

in step S100, determining a performance indicator function to be optimized according to key performance indicator KPI information reported by a user terminal in at least one target cell respectively belonging to at least one base station, where the performance indicator function to be optimized represents a state of performance to be optimized of the whole target cell respectively belonging to at least one base station when the base station to which the target cell belongs configures different beam weight sets, where a current base station stores a plurality of beam weight sets, and each beam weight set includes a plurality of beam weights;

in step S200, a target beam weight set of the base station to which the target cell belongs is determined from the plurality of beam weight sets according to the performance index function to be optimized.

In the embodiment of the present disclosure, a plurality of beam weight sets are prefabricated in advance and stored in the base station, where one beam weight set refers to a set of multi-beam weights, and each beam weight set is suitable for different coverage scenarios. When beam optimization is needed, the beam weight set of the base station is adaptively switched through steps S100 to S200, so as to improve the performance of the cell and/or the whole network.

In the embodiment of the present disclosure, the performance to be optimized refers to characteristic quantities capable of characterizing performance of a single cell or an entire network, such as throughput, received power, Signal to Interference plus Noise Ratio (SINR), and the like, and this is not particularly limited in the embodiment of the present disclosure.

In the embodiment of the present disclosure, a performance index function to be optimized is defined, which is used to represent the state of performance to be optimized of the whole network formed by cells belonging to multiple base stations or the cells belonging to the same base station when corresponding to different sets of beam weight values. It should be noted that the performance index function to be optimized may be set according to the performance to be optimized of the cell or the entire network that needs to perform the beam optimization. For example, in order to optimize the throughput of the whole network formed by the cells respectively belonging to the plurality of base stations or the cell belonging to the same base station, the equivalent throughput of the whole network formed by the cells respectively belonging to the plurality of base stations or the cell belonging to the same base station is used as the performance index function to be optimized; in order to optimize the receiving power of the whole network formed by the cells respectively belonging to the plurality of base stations or the cell belonging to the same base station, the equivalent receiving power of the whole network formed by the cells respectively belonging to the plurality of base stations or the cell belonging to the same base station is used as the performance index function to be optimized; in order to optimize the signal to interference plus noise ratio of the whole network formed by the cells respectively belonging to the plurality of base stations or the cell belonging to the same base station, the equivalent signal to interference plus noise ratio of the whole network formed by the cells respectively belonging to the plurality of base stations or the cell belonging to the same base station is used as the performance index function to be optimized.

In the embodiment of the present disclosure, the Performance Indicator function to be optimized is determined according to Key Performance Indicator (KPI) information reported by the UE. In some embodiments, the UE distribution and the service distribution in the target cell are determined according to the KPI information reported by the UE, and the performance indicator function to be optimized is determined according to the UE distribution and the service distribution in the target cell. It should be noted that, in the embodiment of the present disclosure, UE distribution mainly refers to geographical location distribution of UEs, and may be a distribution of UEs in one cell, which is characterized by geographical locations of all UEs in one cell, or a distribution of UEs in one area, which is characterized by geographical locations of UEs in multiple cells in one area. The traffic distribution may coincide with the user terminal distribution, but may also not coincide with the user terminal distribution, since the communication needs of different UEs may be different.

In the embodiment of the present disclosure, the target set of beam weights is a set of beam weights that can match the coverage of a beam with the UE or traffic distribution, so as to optimize the performance to be optimized of a cell and/or the entire network. It should be noted that, in the embodiment of the present disclosure, beam optimization may be performed on cells belonging to the same base station, at this time, the target beam weight set in step S200 is a beam weight set when the performance to be optimized of the target cell belonging to the same base station is optimal; the beam optimization may also be performed with the goal that the performance of the whole network is optimal, and at this time, the target beam weight set in step S200 is a beam weight set that should be configured by the base station to which each target cell belongs when the performance index to be optimized of the whole network is optimal. It should be further noted that, in the embodiment of the present disclosure, the performance index function to be optimized may be calculated by each base station based on a distributed scheme, or may be calculated by a central base station based on a centralized scheme.

It should be further noted that, in the embodiment of the present disclosure, one base station may serve only one cell, or may serve multiple cells. The embodiment of the present disclosure is not particularly limited in this regard.

In the method for determining the beam weight provided by the embodiment of the disclosure, a plurality of beam weight groups are prefabricated in advance in a base station and stored, each beam weight group is respectively suitable for different coverage scenes, and when beam optimization is required, the beam weight groups which enable the whole network formed by cells respectively belonging to a plurality of base stations or the to-be-optimized performance of the cells belonging to the same base station to be optimal are determined as target beam weight groups through a to-be-optimized performance index function; when the base station configures the target beam weight group to cover the MIMO or Massive MIMO cell, the coverage of the beam can be matched with the distribution of the user terminal or the service distribution, so that the performance to be optimized of the whole network formed by cells respectively belonging to a plurality of base stations or the cells belonging to the same base station can be optimized.

As an optional implementation manner, the performance index functions to be optimized are calculated by each base station based on a distributed scheme, and beam optimization is performed. It should be noted that, in the implementation of the present disclosure, based on a distributed scheme, the performance indicator function to be optimized is a function with different sets of beam weights as arguments.

Accordingly, referring to fig. 2, in some embodiments, the base station is a current base station, and step S100 includes:

in step S111, determining a weighting factor of each user terminal in the target cell belonging to the current base station according to KPI information reported by the user terminal in the target cell belonging to the current base station, where the weighting factor represents a communication requirement of the user terminal;

in step S112, determining, according to KPI information reported by each user terminal in the target cell belonging to the current base station, a to-be-optimized performance indicator function component of each user terminal in the target cell when the current base station belonging to the current base station configures different beam weight groups;

in step S113, the performance index function to be optimized is determined according to the weighting factor of each user terminal in the target cell belonging to the current base station and the component of the performance index function to be optimized of each user terminal in the target cell belonging to the current base station when the current base station configures different beam weight groups, where the performance index function to be optimized represents the state of the performance to be optimized of the target cell belonging to the current base station when the current base station configures different beam weight groups.

It should be noted that the communication requirement of the UE includes, but is not limited to, the communication urgency of the UE. For example, in step S111, the UE has different weighting factors, which indicates that the UE has different communication urgency. The weighting factors of all UEs in the target cell can reflect the distribution of the communication demands of the UEs in the target cell, that is, the service distribution in the target cell is determined by determining the weighting factors of the UEs in the target cell in step S111.

It should be noted that, in step S112, the to-be-optimized performance indicator function component of the UE is used to represent the to-be-optimized performance indicator state of the UE when the base station configures different beam weight sets. When the base station configures different beam weight value sets, states of performance indicators to be optimized of the same UE in a cell may be different, for example, the received power of the UE may be different and the throughput of the UE may also be different under different beam weight value sets. In addition, the UE in different positions may have different states of performance index optimization under each set of beam weight values.

In the embodiment of the present disclosure, the transmission power or antenna gain of each beam weight group in each direction is pre-determined in the base station and stored in the base station. As an optional implementation manner, in the embodiment of the present disclosure, according to the transmission power or antenna gain of each beam weight group preset and stored in the base station in each direction, the KPI information reported by the UE is combined to determine the performance index function component to be optimized of each UE, for example, the relative reception power or the relative throughput of the UE when the base station configures different beam weight groups is determined according to the location information of the UE and the transmission power or antenna gain of each beam weight group in each direction.

Accordingly, referring to fig. 3, in some embodiments, when the current base station stores the transmission powers of the current base station in various directions when configuring different sets of beam weight values, step S112 includes:

in step S112a, according to the position information of the user terminal in the KPI information reported by the user terminal and the transmission power of the current base station in each direction when the current base station configures different beam weight groups, which is stored in the current base station, a to-be-optimized performance indicator function component of the user terminal when the current base station configures different beam weight groups is determined.

Accordingly, in some embodiments, the performance indicator function to be optimized is represented by equation (1):

wherein P (i) is the value of the performance index function to be optimized when the ith beam weight group is configured for the current base station, N is the number of user terminals in the target cell, and alpha_nIs the weighting factor, p, of the nth user terminal in the target cell_i,nAnd when the ith beam weight group is configured for the current base station, the performance index function component to be optimized of the nth user terminal in the target cell is configured, N is the serial number of the user terminal in the target cell, N and N are positive integers, and N is more than or equal to 1 and less than or equal to N.

As an optional implementation manner, when the performance index function to be optimized takes the maximum value, the performance to be optimized of the identified cell reaches the optimum, and the beam weight value group corresponding to the performance index function to be optimized when the performance index function to be optimized takes the maximum value is the target beam weight value group of the current base station.

Accordingly, referring to fig. 4, in some embodiments, step S200 comprises:

in step S201, the corresponding beam weight set when the performance index function to be optimized takes the maximum value is determined as the target beam weight set of the current base station.

As an optional implementation manner, when one cell in a region satisfies a beam optimization condition, each cell in the region performs beam optimization, and after each base station determines a respective target beam weight set, it is further determined whether the optimized coverage enhancement direction will interfere with an adjacent cell according to the coverage enhancement direction after configuring the target beam weight set, and the target beam weight set is switched to only when the optimized coverage enhancement direction will not interfere with the adjacent cell, so that the performance to be optimized of the entire network is optimized.

Accordingly, referring to fig. 5, in some embodiments, step S200 includes:

in step S211, it is determined whether there is an intersection between the coverage enhancing direction of the target cell belonging to the current base station and the coverage enhancing direction of the cell of the neighboring base station of the current base station;

in step S212, when there is no intersection between the coverage enhancing direction of the target cell belonging to the current base station and the coverage enhancing direction of the cell of the neighboring base station, the corresponding beam weight set when the performance index function to be optimized takes the maximum value is determined as the target beam weight set of the current base station.

Accordingly, referring to fig. 5, in some embodiments, when there is an intersection between the coverage enhancement direction of the target cell and the coverage enhancement direction of the cell of the neighboring base station, the step S200 further includes:

in step S213, it is determined whether a difference between a maximum value of the performance index function to be optimized of the target cell belonging to the current base station and a maximum value of the performance index function to be optimized of the cell of the neighboring base station exceeds a predetermined threshold;

in step S214, when a difference between a maximum value of the performance index function to be optimized of the target cell belonging to the current base station and a maximum value of the performance index function to be optimized of the cell of the neighboring base station exceeds the predetermined threshold, a corresponding beam weight group when the performance index function to be optimized of the target cell belonging to the current base station takes the maximum value is determined as the target beam weight group of the current base station.

It should be noted that, in step S211, the coverage enhancement direction of the cell of the neighboring base station is transmitted by the neighboring base station.

It should be further noted that, in step S214, "the difference between the maximum value of the performance index function to be optimized of the cell and the maximum value of the performance index function to be optimized of the cell of the neighboring base station exceeds the predetermined threshold value" means that the maximum value of the performance index function to be optimized of the cell is greater than the maximum value of the performance index function to be optimized of the cell of the neighboring base station, and the difference between the maximum value of the performance index function to be optimized of the cell and the maximum value of the performance index function to be optimized of the cell of the neighboring base station exceeds the predetermined threshold value.

In the embodiment of the present disclosure, when a plurality of beam weight value sets are prefabricated and stored in the base station, a default beam weight value set is further formulated for the base station, and when interference to an adjacent cell is generated after optimization, the default beam weight value set is switched to.

Accordingly, referring to fig. 5, in some embodiments, when the difference between the maximum value of the performance indicator function to be optimized of the target cell and the maximum value of the performance indicator function to be optimized of the cell of the neighboring base station does not exceed the predetermined threshold, step S200 further includes:

in step S215, a default beam weight value set, which is one of a plurality of beam weight value sets stored by the current base station, is determined as a target beam weight value set of the current base station.

In the embodiment of the present disclosure, the current base station determines, according to the received coverage enhancement direction of the neighboring base station sent by the neighboring base station and the maximum value of the performance index function to be optimized of the neighboring cell, whether there is an intersection between the coverage enhancement direction of the target cell and the neighboring base station in step S211, and determines, when there is an intersection, whether a difference between the maximum value of the performance index function to be optimized of the target cell and the maximum value of the performance index function to be optimized of the neighboring cell exceeds a predetermined threshold in step S213. It should be noted that, in the embodiment of the present disclosure, the current base station and the neighboring base station do not refer to a certain base station specifically, and both the current base station and the neighboring base station perform the determination method provided by the embodiment of the present disclosure to perform beam optimization. Therefore, in the embodiment of the present disclosure, after determining the beam weight value group corresponding to the maximum value of the performance index function to be optimized, the current base station sends the coverage enhancement direction information of the target cell and the maximum value of the performance index function to be optimized to the neighboring base station.

Accordingly, referring to fig. 6, in some embodiments, before step S200, the determining method further comprises:

in step S311, when the current base station configures the beam weight value group corresponding to the performance index function to be optimized taking the maximum value, the coverage enhancement direction of the target cell belonging to the current base station is determined;

in step S312, the coverage enhancement direction information of the target cell belonging to the current base station and the maximum value of the performance indicator function to be optimized are sent to the neighboring base station of the current base station.

As an alternative implementation, the base station performs beam optimization through steps S100 to S200 when the beam optimization condition is satisfied. In the embodiment of the present disclosure, the base station determines whether the beam optimization condition is satisfied according to the KPI information reported by the UE.

Accordingly, referring to fig. 7, in some embodiments, before step S100, the determining method further comprises:

in step S401, according to KPI information reported by the user terminal in the target cell belonging to the current base station, it is determined whether the current base station satisfies a beam optimization condition;

step S100 is executed when the current base station satisfies the beam optimization condition.

It should be noted that, the embodiment of the present disclosure does not specially limit the beam optimization condition. For example, when the UE distribution is not matched with the coverage of the cell by the current beam weight group, the base station is triggered to perform beam optimization; or when the service distribution in the cell is not matched with the coverage of the cell by the current beam weight group, triggering the base station to carry out beam optimization; or when the UE distribution and the service distribution are not matched with the coverage of the cell by the current beam weight group, triggering the base station to carry out beam optimization.

In the embodiment of the present disclosure, when one or more base stations satisfy the beam optimization condition, each base station performs beam optimization through steps S100 to S200 of the embodiment of the present disclosure, so that the performance to be optimized of the entire network is optimized. As an optional implementation manner, when a base station meets the beam optimization condition, the base station meeting the beam optimization condition notifies other base stations to perform beam optimization through inter-base station communication.

Accordingly, referring to fig. 7, in some embodiments, when the base station satisfies the beam optimization condition, the determining method further includes:

in step S402, a notification message for performing beam optimization is sent to a base station other than the current base station to trigger the base station other than the current base station to perform beam optimization.

In the embodiment of the present disclosure, the current base station performs beam optimization through steps S110 to S200 in response to the notification message for performing beam optimization transmitted by the current base station and the other base stations.

Accordingly, referring to fig. 8, in some embodiments, step S100 includes:

in step S101, in response to a notification message for performing beam optimization sent by a base station other than the current base station, a performance indicator function to be optimized is determined according to key performance indicator KPI information reported by a user terminal in a target cell belonging to at least one base station.

As an optional implementation manner, the performance index function to be optimized is calculated by the central base station in a distributed manner based on a centralized scheme, so as to obtain a target beam weight value set of each target base station. It should be noted that each target base station maintains the KPI information reported by the UE, and each target base station calculates a weighting factor for the UE accessing the target base station, and then reports the KPI information and the weighting factor reported by the UE to the central base station.

It should be noted that, in the embodiment of the present disclosure, the center base station may be a target base station designated as the center base station. The embodiment of the present disclosure is not particularly limited in this regard.

Accordingly, referring to fig. 9, in some embodiments, the base station includes a plurality of target base stations, a plurality of the cells are respectively attributed to the plurality of target base stations, and step S100 includes:

in step S121, determining, according to KPI information of user terminals in the target cell served by the target base station, which is reported by a plurality of target base stations, a to-be-optimized performance indicator function component of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups;

in step S122, a performance index function to be optimized is determined according to a component of a performance index function to be optimized of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups and a weighting factor reported by each target base station for each user terminal in the target cell served by each target base station, where the weighting factor represents a communication requirement of the user terminal in the cell served by the target base station, and the performance index function to be optimized represents a state of performance to be optimized of the whole cell served by a plurality of target base stations when the target base station configures different beam weight groups.

In the embodiment of the present disclosure, each base station in one area configures a respective beam weight value group, and the beam weight value groups configured by different base stations may be the same or different, which is not particularly limited in the embodiment of the present disclosure. In the embodiment of the present disclosure, based on a centralized scheme, the performance index function to be optimized is a function using different sets of beam weights and different base stations as arguments.

In the embodiment of the present disclosure, the transmission power or antenna gain of each target base station in each direction under each beam weight group is pre-determined in the central base station, and is stored in the central base station. As an optional implementation manner, in the embodiment of the present disclosure, according to the transmission power or antenna gain of each target base station in each direction under each beam weight group preset and stored in the central base station, the KPI information of the UE reported by each target base station is combined to determine the performance index function component to be optimized of each UE, for example, according to the location information of the UE and the transmission power or antenna gain of each beam weight group in each direction, the relative reception power or relative throughput of the UE when the base station configures different beam weight groups is determined.

Accordingly, referring to fig. 10, in some embodiments, step S121 includes:

in step S121a, according to the position information of the user terminal in the KPI information of the user terminal in the target cell served by the target base station reported by multiple target base stations and the transmission power in each direction when the target base station configures different beam weight groups stored in the current base station, determining the to-be-optimized performance index function component of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups.

In the embodiment of the disclosure, the centralized scheme aims to achieve the optimal performance of the whole network. And when the performance index function to be optimized obtains a maximum value, the performance of the whole network is optimal.

Accordingly, referring to fig. 11, in some embodiments, step S122 includes:

in step S122a, the performance index function components to be optimized of the user terminals in the target cell served by multiple target base stations are weighted by the weighting factors of the user terminals and then summed to serve as the performance index function to be optimized, where the performance index function components to be optimized of the user terminals in the target cell served by the same target base station correspond to the same set of beam weight values.

It should be noted that, when the number of the pre-formed beam weight sets is large, the number of the cells to be optimized is also large, and the maximum value of the performance index to be optimized cannot be directly obtained, as an optional implementation, a heuristic search algorithm is used to search and determine the target beam weight set of each base station.

In the embodiment of the present disclosure, after determining the target beam weight of each base station by calculating the maximum of the performance index to be optimized, the central base station sends the target beam weight information to each base station, so that each base station switches to its respective target beam weight set, thereby optimizing the overall network performance.

Accordingly, referring to fig. 12, in some embodiments, step S200 further comprises:

in step S221, when the performance indicator function to be optimized obtains a maximum value, the beam weight sets corresponding to the target base stations are respectively determined as the target beam weight set of each target base station.

In the embodiment of the present disclosure, when a single cell satisfies the beam optimization condition, or other cells in one area satisfy the beam optimization condition, the central base station performs steps S100 to S200 for beam optimization.

Accordingly, referring to fig. 13, in some embodiments, step S100 includes:

in step S102, in response to a notification message for performing beam optimization sent by at least one target base station, a performance indicator function to be optimized is determined according to key performance indicator KPI information reported by a user terminal in at least one target cell.

In order to make the technical solutions provided by the present invention more clearly understood by those skilled in the art, the technical solutions provided by the present invention are described in detail below by specific examples:

example one

And prefabricating a plurality of sets of beam weights suitable for different coverage scenes in advance, and storing the plurality of sets of prefabricated beam weights into an MIMO or Massive MIMO base station. Configuring a set of default beam weights for each base station, wherein the initial beam weight of each base station is the respective default beam weight;

calculating the relative receiving power of the broadcast beam synthesized by each beam in each set of beam weight in each direction in the coverage range of a single cell in advance, and storing the calculated relative receiving power in the MIMO or Massive MIMO base station in advance;

determining a performance index function to be optimized of a single cell of each cell, wherein the performance index function to be optimized is the sum of relative received power of each UE in the cell;

the MIMO or Massive MIMO base station maintains KPI information reported by each UE in a served cell, and calculates a weighting factor alpha for each UE according to part of information in the KPI information reported by the UE, wherein the weighting factor alpha is used for representing the communication urgency degree of different UEs;

when one or more base stations meet the beam optimization condition, each base station in the area calculates the optimal beam weight;

each base station independently calculates the optimized beam weight according to the performance index function to be optimized:

each base station calculates the relative received power of each UE in the cell under all beams, and then the total relative received power of all UEs in the cell under the ith set of beam weight is:

wherein, Power_iIs the total relative received power, of all UEs in the cell under the ith set of beam weights_i,nIs the relative received power of the nth UE under the ith set of beam weights, N is the number of UEs in the cell, alpha_nIs the weighting coefficient of the nth UE, N and N are positive integers, and N is more than or equal to 1 and less than or equal to N. The ith of single cell optimization^*The sleeve beam weight is:

i^*＝argmax{Power_i} (3)

wherein i^*Sequence number of optimal beam weights for a single cell, argmax { Power_iMean take Power_iThe value of the maximum time i.

Each base station judges the adjacent cell which will be subjected to strong interference of the cell according to the direction of coverage enhancement of each base station, and informs the adjacent cell of the information;

each base station judges whether the coverage enhancement directions of the cell served by the base station and all adjacent cells have intersection or not:

if the intersection exists, comparing target values calculated by the two cells according to the performance index function to be optimized, and if the difference between the target values is larger, switching the beam weight to the optimal weight by the cell with the larger target value, and returning the beam weight to the default beam weight by the cell with the smaller target value; when the target value has a small difference, the two cells return the beam weight to the default weight;

and if the coverage enhancement directions of the self cell and the adjacent cells do not have intersection, switching the beam weight to the respective optimal beam.

And finally, obtaining the optimized beam weight of each base station in the area.

Example two

calculating the relative receiving power of the broadcast beam synthesized by each beam in each set of beam weight in each direction in the coverage range of a single cell in advance, and storing the calculated relative receiving power in an MIMO or Massive MIMO base station in advance;

determining a performance index function to be optimized of multiple cells, wherein the target function is the equivalent throughput of the whole network;

the MIMO or Massive MIMO cell maintains KPI information reported by each UE in each cell, and calculates a weighting factor alpha for each UE according to part of information in the KPI information reported by the UE, wherein the weighting factor alpha is used for representing the communication urgency degree of different UEs;

the central base station carries out calculation of optimized beam weight in a centralized manner:

each base station in the area reports KPI information reported by UE in each cell to a central base station;

the central base station calculates the equivalent throughput of each UE under various weight schemes of each cell according to the KPI information reported by each UE, and sums the equivalent throughputs of all the UEs to obtain the equivalent throughput of the whole network as a performance index function to be optimized;

suppose that under the combination of the ith whole-network beam weight scheme, the UE_nEquivalent throughput of Thp_i,nThen, under the combination of the ith whole-network beam weight scheme, the equivalent throughput of the whole network is:

wherein, Thp_iFor the equivalent throughput of the entire net under the combination of the ith entire net beam weight schemes, Thp_i,nIs the equivalent throughput of the nth UE under the ith set of beam weight, N is the number of UEs in the cell, alpha_nIs the weighting coefficient of the nth UE, N and N are positive integers, and N is more than or equal to 1 and less than or equal to N.

Solving a maximum value for the performance index function to be optimized, wherein the corresponding weight scheme of each cell is the optimal weight scheme of each cell in the whole area. When there are a plurality of sets of pre-formed beam weights and there are many cells to be optimized, a closed-form solution may not be directly obtained, and at this time, a heuristic search algorithm may be used to search for the optimal weight.

In a second aspect, referring to fig. 14, an embodiment of the present disclosure provides a beamforming method, including:

in step S710, determining a target beam weight value set according to the method for determining beam weight values described in the first aspect of the embodiment of the present disclosure, where the target beam weight value set is one of a plurality of beam weight value sets stored by a current base station;

in step S720, a beamforming process is performed according to the target beam weight set.

In the beam weight forming method provided by the embodiment of the disclosure, a plurality of beam weight value sets are prefabricated and stored in a base station in advance, each beam weight value set is respectively suitable for different coverage scenes, and when beam optimization is required, the beam weight value set when the performance of a single cell or the whole network is optimal is determined as a target beam weight value set through a performance index function to be optimized; the base station configures the target beam weight set to carry out beam forming processing, thereby covering the MIMO or Massive MIMO cell, and enabling the coverage of the beam to be matched with the distribution of the user terminal or the service distribution, so that the performance of a single cell or the whole network is optimal.

In a third aspect, referring to fig. 15, an embodiment of the present disclosure provides a base station, including:

one or more processors 101;

a memory 102 on which one or more programs are stored, which, when executed by one or more processors, cause the one or more processors to implement the method for determining the beam weight or the method for beamforming;

one or more I/O interfaces 103 coupled between the processor and the memory and configured to enable information interaction between the processor and the memory.

The processor 101 is a device with data processing capability, and includes but is not limited to a Central Processing Unit (CPU) and the like; memory 102 is a device having data storage capabilities including, but not limited to, random access memory (RAM, more specifically SDRAM, DDR, etc.), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), FLASH memory (FLASH); an I/O interface (read/write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, which includes but is not limited to a data Bus (Bus) and the like.

In some embodiments, the processor 101, memory 102, and I/O interface 103 are interconnected via a bus 104, which in turn connects with other components of the computing device.

The method for determining the beam weight and the method for forming the beam have been described in detail above, and are not described herein again.

In a fourth aspect, referring to fig. 16, an embodiment of the present disclosure provides a computer readable medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the method for determining the beam weight value or the method for forming the beam.

It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.

Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted in a generic and descriptive sense only and not for purposes of limitation. In some instances, features, characteristics and/or elements described in connection with a particular embodiment may be used alone or in combination with features, characteristics and/or elements described in connection with other embodiments, unless expressly stated otherwise, as would be apparent to one skilled in the art. Accordingly, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the disclosure as set forth in the appended claims.

Claims

1. A method for determining beam weight value includes:

2. The method according to claim 1, wherein the target cell belongs to a current base station, and the step of determining the performance indicator function to be optimized according to key performance indicator KPI information reported by the user equipment in the target cell belonging to the current base station comprises:

3. The method according to claim 2, wherein, in the case that the current base station stores the transmission power of the current base station in each direction when configuring different beam weight groups, the step of determining the to-be-optimized performance indicator function component of each user terminal in the target cell belonging to the current base station when the current base station configures different beam weight groups according to the KPI information reported by each user terminal in the target cell belonging to the current base station comprises:

4. The determination method according to claim 2, wherein the step of determining the target beam weight set of the current base station from the plurality of beam weight sets according to the performance indicator function to be optimized comprises:

5. The determination method according to claim 4, wherein the step of determining the target set of beam weights for the current base station from the plurality of sets of beam weights according to the to-be-optimized performance indicator function when there is an intersection between the coverage enhancement direction of the target cell belonging to the current base station and the coverage enhancement direction of the cell of the neighboring base station further comprises:

6. The determination method according to claim 5, wherein the step of determining the target beam weight set of the current base station from the plurality of beam weight sets according to the performance indicator function to be optimized when a difference between a maximum value of the performance indicator function to be optimized of the target cell belonging to the current base station and a maximum value of the performance indicator function to be optimized of the cell of the neighboring base station does not exceed the predetermined threshold value further comprises:

7. The determination method according to any one of claims 2 to 6, wherein, before the step of determining the target beam weight set of the current base station from the plurality of beam weight sets according to the performance indicator function to be optimized, the determination method further comprises:

8. The determination method according to any one of claims 2 to 6, wherein the performance indicator function to be optimized is expressed by the following formula:

9. The method according to any one of claims 2 to 6, wherein before the step of determining the performance indicator function to be optimized according to Key Performance Indicator (KPI) information reported by the user equipment in the target cell belonging to the current base station, the method further comprises:

10. The determination method according to claim 9, wherein when the current base station satisfies the beam optimization condition, the determination method further comprises:

11. The method according to claim 1, wherein the base station includes a plurality of target base stations, the target cells are respectively attributed to the target base stations, and the step of determining the performance indicator function to be optimized according to key performance indicator KPI information reported by the user terminals in the target cells respectively attributed to the target base stations comprises:

12. The method according to claim 11, wherein the step of determining, according to KPI information of the ue in the target cell served by the target base station and reported by multiple target base stations, a component of the performance indicator function to be optimized for each ue in the target cell served by each target base station when the target base station configures different sets of beam weight values includes:

13. The method according to claim 11 or 12, wherein the step of determining the performance indicator function to be optimized according to the component of the performance indicator function to be optimized of each user terminal in the target cell served by each target base station when the target base station configures different beam weight groups and the weighting factor reported by each target base station for each user terminal in the serving cell served by each target base station includes:

14. The method according to claim 11 or 12, wherein determining a target set of beam weights for a plurality of the target base stations from the plurality of sets of beam weights according to the performance indicator function to be optimized comprises:

15. The determination method according to claim 11 or 12, wherein the determination method further comprises:

16. The method according to claim 11 or 12, wherein the step of determining the performance indicator function to be optimized according to key performance indicator KPI information reported by the user equipment in the target cell served by the target base station and reported by a plurality of target base stations comprises:

17. The determination method according to any of claims 1 to 6, 11, 12, wherein the performance to be optimized comprises one or more of throughput, received power, signal to interference plus noise ratio.

18. A base station, comprising:

one or more processors;

storage means having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement a method of determining beam weight values according to any one of claims 1 to 17;

19. A computer readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method of determining beam weight values according to any one of claims 1 to 17.