CN114189883A - Antenna weight value adjusting method and device and computer readable storage medium - Google Patents

Antenna weight value adjusting method and device and computer readable storage medium Download PDF

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CN114189883A
CN114189883A CN202010968441.6A CN202010968441A CN114189883A CN 114189883 A CN114189883 A CN 114189883A CN 202010968441 A CN202010968441 A CN 202010968441A CN 114189883 A CN114189883 A CN 114189883A
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antenna weight
rsrp
current
value
combination
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李家海
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ZTE Corp
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ZTE Corp
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/24—Cell structures
    • H04W16/28—Cell structures using beam steering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports

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Abstract

The invention provides an antenna weight value adjusting method, an antenna weight value adjusting device and a computer readable storage medium. The method for adjusting the antenna weight comprises the following steps: acquiring a plurality of MR data under the current scene type, wherein each MR data comprises first RSRP information corresponding to the current antenna weight combination and DOA information corresponding to the current antenna weight combination; traversing all MR data, and calculating according to the first RSRP information and the DOA information and aiming at each MR data to obtain second RSRP information which corresponds to each candidate antenna weight combination one by one; calculating to obtain evaluation information according to all the first RSRP information and all the second RSRP information; determining an optimal antenna weight combination from the current antenna weight combination and all candidate antenna weight combinations according to the evaluation information; and updating the current antenna weight combination into the optimal antenna weight combination. In the embodiment of the invention, the whole processing process does not need manual participation, so that the problem of untimely network optimization can be solved, and the efficiency of network optimization can be improved.

Description

Antenna weight value adjusting method and device and computer readable storage medium
Technical Field
The present invention relates to, but not limited to, the field of communications technologies, and in particular, to a method and an apparatus for adjusting antenna weights, and a computer-readable storage medium.
Background
In the current network architecture, in order to enable an LTE (Long Term Evolution) or 5G NR (5G New Radio, generation 5 New air interface) system to have optimal coverage and spectrum efficiency in a diversified scene, a large amount of human resources are often required to be invested for network optimization.
However, for more and more diversified coverage scenes, the traditional way of presetting the antenna weight cannot be used, and in order to cover as many scenes as possible, the number of antenna weight combinations needs to be additionally increased, so that one cell even has thousands of optional antenna weight combinations, and therefore, for LTE or 5G NR ultra-dense same-frequency networking, the complexity of the search space of the antenna weight can be exponentially increased, which causes that the network specification and network optimization means of the traditional artificial optimization network cannot timely respond to the change of users in the network, and thus, it is difficult to ensure that the area after artificial optimization has optimal coverage and frequency efficiency. Therefore, how to realize faster and more timely antenna weight adjustment to meet the requirement of network optimization is an urgent problem to be solved.
Disclosure of Invention
The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.
The embodiment of the invention provides an antenna weight value adjusting method, an antenna weight value adjusting device and a computer readable storage medium, which can improve the efficiency of network optimization.
In a first aspect, an embodiment of the present invention provides an antenna weight adjusting method, including:
acquiring a plurality Of Measurement Report (MR) data under a current scene type, wherein each MR data includes first Reference Signal Receiving Power (RSRP) information corresponding to a current antenna weight combination and Direction Of Arrival (DOA) information corresponding to the current antenna weight combination;
traversing all the MR data, and calculating to obtain second RSRP information corresponding to each candidate antenna weight combination one by one according to the first RSRP information and the DOA information aiming at each MR data;
calculating to obtain evaluation information corresponding to each antenna weight combination one by one according to all the first RSRP information and all the second RSRP information;
determining an optimal antenna weight combination from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information;
and updating the current antenna weight combination to the optimal antenna weight combination.
In a second aspect, an embodiment of the present invention further provides an apparatus for adjusting antenna weights, including: a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the antenna weight adjusting method according to the first aspect when executing the computer program.
In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, where computer-executable instructions are stored, where the computer-executable instructions are configured to execute the antenna weight adjusting method described above.
The embodiment of the invention comprises the following steps: acquiring a plurality of measurement report MR data under the current scene type, wherein each MR data comprises first Reference Signal Received Power (RSRP) information corresponding to the current antenna weight combination and direction of arrival (DOA) information corresponding to the current antenna weight combination; traversing all MR data, and calculating according to the first RSRP information and the DOA information and aiming at each MR data to obtain second RSRP information which corresponds to each candidate antenna weight combination one by one; calculating to obtain evaluation information corresponding to each antenna weight combination one by one according to all the first RSRP information and all the second RSRP information; determining an optimal antenna weight combination from the current antenna weight combination and all candidate antenna weight combinations according to all the evaluation information; and updating the current antenna weight combination into the optimal antenna weight combination. According to the scheme provided by the embodiment of the invention, after MR data under the current scene type is obtained, second RSRP information which is in one-to-one correspondence with each candidate antenna weight combination is obtained through calculation according to the first RSRP information and the DOA information in the MR data, evaluation information which is in one-to-one correspondence with each antenna weight combination is obtained through calculation according to all the first RSRP information and all the second RSRP information, then the optimal antenna weight combination is determined and updated from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information, and the whole processing process does not need manual participation, so that the problem that the traditional manual optimization network means cannot respond to the change of users in the network in time can be solved, and the efficiency of network optimization can be improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the example serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is a schematic diagram of a system architecture for performing an antenna weight adjustment method according to an embodiment of the present invention;
fig. 2 is a flowchart of an antenna weight adjustment method according to an embodiment of the present invention;
fig. 3 is a flowchart of calculating second RSRP information in an antenna weight adjustment method according to another embodiment of the present invention;
fig. 4 is a flowchart of calculating evaluation information in an antenna weight adjusting method according to another embodiment of the present invention;
fig. 5 is a flowchart of calculating evaluation information in an antenna weight adjusting method according to another embodiment of the present invention;
fig. 6 is a flowchart of calculating second RSRP information in an antenna weight adjustment method according to another embodiment of the present invention;
fig. 7 is a flowchart of calculating evaluation information in an antenna weight adjusting method according to another embodiment of the present invention;
fig. 8 is a flowchart of calculating evaluation information in an antenna weight adjusting method according to another embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that although functional blocks are partitioned in a schematic diagram of an apparatus and a logical order is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the partitioning of blocks in the apparatus or the order in the flowchart. The terms first, second and the like in the description and in the claims, and the drawings described above, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The invention provides an antenna weight value adjusting method, an antenna weight value adjusting device and a computer readable storage medium, wherein MR data under a current scene type are obtained, second RSRP information which corresponds to each candidate antenna weight value combination one by one is obtained through calculation according to first RSRP information and DOA information in the MR data, after the second RSRP information which corresponds to each candidate antenna weight value combination one by one is obtained through calculation, evaluation information which corresponds to each antenna weight value combination one by one is obtained through calculation according to all the first RSRP information and all the second RSRP information, an optimal antenna weight value combination is determined from the current antenna weight value combination and all the candidate antenna weight value combinations according to all the evaluation information, and then the current antenna weight value combination is updated to the optimal antenna weight value combination, so that the antenna weight value adjusting processing of a local area and a same-frequency adjacent area is completed. In the whole process of adjusting and processing the antenna weight, manual participation is not needed, the problem that the traditional manual network optimizing method cannot respond to the change of users in the network in time can be solved, and therefore the efficiency of network optimization can be improved.
The embodiments of the present invention will be further explained with reference to the drawings.
As shown in fig. 1, fig. 1 is a schematic diagram of a system architecture for performing an antenna weight adjustment method according to an embodiment of the present invention. In the example of fig. 1, the system architecture includes a local base station 100 and a plurality of neighboring base stations 200, where the local base station 100 and all neighboring base stations 200 cooperate with each other to provide signal coverage for a current area, in the current area, a signal coverage range of the local base station 100 forms a local area, and a signal coverage range of the neighboring base station 200 forms a neighboring area.
When a terminal is newly accessed or switched into any cell in a current area, a corresponding base station can issue an instruction of A3 co-frequency measurement and corresponding position information measurement to the terminal, and after the terminal receives the instruction, the terminal can send MR data to the base station sending the instruction, wherein the MR data comprises RSRP information and DOA information of the terminal in an access cell and RSRP information and DOA information of a co-frequency adjacent cell of the terminal in the access cell. The DOA information comprises horizontal position information and vertical position information of the terminal relative to the normal line of the antenna, and each RSRP information corresponds to one DOA information. Those skilled in the art can understand that the DOA information of the local cell can be measured according to the uplink reference signal or the channel information of the terminal, and the DOA information of the co-frequency neighboring cell can be measured by transmitting the uplink reference signal or the channel information of the terminal from the access cell to the co-frequency neighboring cell.
The system architecture and the application scenario described in the embodiment of the present invention are for more clearly illustrating the technical solution of the embodiment of the present invention, and do not form a limitation on the technical solution provided in the embodiment of the present invention, and it is known to those skilled in the art that the technical solution provided in the embodiment of the present invention is also applicable to similar technical problems with the evolution of the system architecture and the occurrence of new application scenarios.
Those skilled in the art will appreciate that the system architecture shown in FIG. 1 is not intended to limit embodiments of the present invention and may include more or less components than shown, or some components in combination, or a different arrangement of components.
In the system architecture shown in fig. 1, both the local base station and the neighboring base station may call the antenna weight adjustment program stored therein, so as to execute the antenna weight adjustment method.
Based on the system architecture, the invention provides various embodiments of the antenna weight value adjusting method.
As shown in fig. 2, fig. 2 is a flowchart of an antenna weight adjusting method according to an embodiment of the present invention, where the antenna weight adjusting method includes, but is not limited to, step S100, step S200, step S300, step S400, and step S500.
Step S100, a plurality of MR data under the current scene type are obtained, wherein each MR data comprises first RSRP information corresponding to the current antenna weight combination and DOA information corresponding to the current antenna weight combination.
In an embodiment, when the base station issues an instruction of a3 co-frequency measurement and corresponding position information measurement to the terminal, the terminals that receive the instruction all report MR data, that is, each terminal reports one MR data, so that the base station can acquire MR data of all terminals belonging thereto, and can perform adjustment processing of antenna weight according to the MR data in subsequent steps.
In an embodiment, the current scene type may have different instances, for example, the current scene type may be an aggregation scene, may be a weak coverage scene, may also be an overlapping coverage scene, and may also be a tidal effect scene, which is not particularly limited by the present embodiment, depending on the actual scene situation. In addition, as can be understood by those skilled in the art, the aggregation scene refers to a scene in which the number of online users is small or stable at ordinary times, and during a holiday or a competition day, the users are aggregated suddenly to cause that the number of online users is increased suddenly, but the duration is not long; the weak coverage scene is a scene that the coverage signal strength of a cell is weak under the current antenna weight configuration; the overlapping coverage scene is a scene that the signal intensity of the terminal in the local area and the signal intensity of the terminal in the same-frequency adjacent area have little difference under the current antenna weight configuration; the tidal effect scene is a scene that the number of online users is large in a certain time period, and the number of online users is small in another certain time period.
In an embodiment, the MR data reported by each terminal includes first RSRP information corresponding to the current antenna weight combination and DOA information corresponding to the current antenna weight combination. The first RSRP information may only include RSRP information of the terminal in the access cell, or may also include RSRP information of the terminal in the access cell and RSRP information of an intra-frequency neighboring cell of the terminal in the access cell, which may be determined according to an actual application situation, and this embodiment is not specifically limited to this. In addition, the DOA information may only include the DOA information of the terminal in the access cell, or may also include the DOA information of the terminal in the access cell and the DOA information of the terminal in the same-frequency neighboring cell of the access cell, which may be determined according to an actual application situation, and this embodiment is not specifically limited to this.
In an embodiment, the current antenna weight combination may be an antenna weight currently configured in the local area, or may include a combination of an antenna weight currently configured in the local area and an antenna weight currently configured in a neighboring area of the same frequency, which may be determined according to an actual application situation, and this embodiment is not specifically limited to this. To illustrate by a specific example, assuming that there are 3 same-frequency neighboring cells in the current cell, the current antenna weight combination can be represented as { W }1,W2,W3,W4In which W1The antenna weight, W, currently allocated to this region2The antenna weight, W, currently configured for the first co-frequency neighboring cell3Antenna weight, W, currently configured for a second co-frequency neighbor4And the antenna weight value currently configured for the third same-frequency adjacent cell.
Step S200, traversing all MR data, and calculating according to the first RSRP information and the DOA information and obtaining second RSRP information corresponding to each candidate antenna weight combination one by one aiming at each MR data.
In an embodiment, after the base station acquires the MR data from the terminal, since the first RSRP information and the DOA information in the MR data both correspond to the current antenna weight combination, the base station does not know RSRP information corresponding to other candidate antenna weight combinations, and therefore, the base station does not know which antenna weight combination has a better effect in the current scene type. In order to realize the self-adaptive adjustment of the antenna weight, the base station may traverse all the MR data under the current antenna weight combination, and for each MR data, calculate the second RSRP information corresponding to each candidate antenna weight combination one by one according to the first RSRP information and the DOA information, so that, after traversing all the MR data, the RSRP information corresponding to all the candidate antenna weight combinations can be obtained, and therefore, the base station can determine the optimal antenna weight combination according to the RSRP information in the subsequent steps.
In an embodiment, since the second RSRP information is calculated according to the first RSRP information and the DOA information, the second RSRP information and the first RSRP information correspond to each other, that is, the second RSRP information may only include RSRP information of the terminal in the access cell, or may include RSRP information of the terminal in the access cell and RSRP information of an intra-frequency neighboring cell of the terminal in the access cell, and only an antenna weight combination corresponding to the second RSRP information is a candidate antenna weight combination.
In an embodiment, the candidate antenna weight combination is opposite to the current antenna weight combination, and for each cell in the current area, the candidate antenna weight combination is a combination formed by other selectable antenna weights except the current antenna weight combination, and therefore, the candidate antenna weight combination may be an antenna weight of other selectable configurations of the current area, and may also include an antenna weight of other selectable configurations of the current area and an antenna weight of other selectable configurations of a neighboring area of the same frequency. To illustrate by a specific example, assuming that the local area has 2 same-frequency neighboring areas, and the antenna weights of the local area and the other optional configurations of the same-frequency neighboring areas are both 2, the combination of the candidate antenna weights is 2, and one of the candidate antenna weight combinations can be expressed as { W }11,W12,W13And another candidate antenna weight combination may be denoted as W21,W22,W23In which W11An antenna weight W of one of the optional configurations in the local area12An antenna weight W which is configured for one of the first same-frequency adjacent regions13An antenna weight W which can be configured for one of the second same-frequency adjacent regions21For another optional configuration of antenna weights, W, of this zone22For the first adjacent region with the same frequencyOf another alternative configuration of antenna weights, W23And the antenna weight value is configured for another optional configuration of the second same-frequency adjacent region.
And step S300, calculating to obtain evaluation information corresponding to each antenna weight combination one by one according to all the first RSRP information and all the second RSRP information.
In an embodiment, after the second RSRP information is obtained through calculation, evaluation information corresponding to each antenna weight combination (that is, including the current antenna weight combination and each candidate antenna weight combination) may be obtained through calculation according to all the first RSRP information and all the second RSRP information, so that the base station can determine an optimal antenna weight combination according to the evaluation information in subsequent steps.
In an embodiment, the evaluation information may have different instances according to different types of current scenes, and a specific instance of the evaluation information may be determined according to an actual application, which is not specifically limited in this embodiment. For example, in the case that the current scene type is an aggregation scene, the evaluation information may be a Signal to Interference plus Noise Ratio (SINR) average value; under the condition that the current scene type is a weak coverage scene, the evaluation information may include a weak coverage ratio value and an RSRP average value; under the condition that the current scene type is an overlapping coverage scene, the evaluation information may include an overlapping coverage proportion value and an SINR average value; in the case where the current scene type is a tidal effect scene, the evaluation information may be an RSRP average value.
And step S400, determining the optimal antenna weight combination from the current antenna weight combination and all candidate antenna weight combinations according to all the evaluation information.
In an embodiment, since the evaluation information corresponds to the antenna weight combinations one to one, an optimal antenna weight combination can be determined from the current antenna weight combination and all candidate antenna weight combinations according to all the evaluation information, so that the current antenna weight combination can be updated to the determined optimal antenna weight combination in the subsequent steps, and the adjustment of the antenna weight is realized.
In an embodiment, according to different examples of the evaluation information, an optimal antenna weight combination is determined from the current antenna weight combination and all candidate antenna weight combinations, and different implementations are possible. For example, when the evaluation information is the SINR average, determining the antenna weight combination corresponding to the largest SINR average as the optimal antenna weight combination; when the evaluation information is the RSRP average value, determining the antenna weight combination corresponding to the maximum RSRP average value as the optimal antenna weight combination; when the evaluation information comprises the weak coverage proportion value and the RSRP average value, determining the antenna weight combination corresponding to the minimum weak coverage proportion value as the optimal antenna weight combination, or determining the antenna weight combination corresponding to the maximum RSRP average value as the optimal antenna weight combination in the multiple antenna weight combinations under the condition that the antenna weight combinations corresponding to the minimum weak coverage proportion value are multiple; and when the evaluation information comprises the overlapping coverage proportion value and the SINR average value, determining the antenna weight combination corresponding to the minimum overlapping coverage proportion value as the optimal antenna weight combination, or determining the antenna weight combination corresponding to the maximum SINR average value as the optimal antenna weight combination in the multiple antenna weight combinations under the condition that the antenna weight combinations corresponding to the minimum overlapping coverage proportion value are multiple.
Step S500, the current antenna weight combination is updated to the optimal antenna weight combination.
In an embodiment, after the optimal antenna weight combination is determined, the optimal antenna weight of each cell is determined, at this time, the optimal antenna weight of each cell may be used to adjust the Channel State Information Reference Signal (CSI-RS) beam weight in a linkage manner, that is, the CSI-RS beam weight is adjusted to the antenna weight corresponding to the optimal antenna weight combination, then all the optimized antenna weights are spliced, and then the spliced antenna weights are issued to be effective, so as to adjust the antenna weight.
In an embodiment, after the optimized antenna weight is issued, in order to prevent the adjusted antenna weight from having a large influence on the Performance of the current region, Key Performance Indicator (KPI) evaluation may be performed on each cell, and if the KPI evaluation is passed, the weight is updated; if not, the weight retroversion can be carried out, and the optimal antenna weight combination is determined again. The time length for performing KPI evaluation may be configured as appropriate according to actual situations, and may be configured to be 1 minute or longer, for example.
In an embodiment, the KPIs to be evaluated may include a basic KPI and a performance KPI, where the basic KPI may include a Radio Resource Control (RRC) connection success rate, a handover success rate, a call drop rate, and the like; the performance KPI may include Spectral Efficiency (SE), average number of active users, and the like.
It is noted that the index statistics of KPI evaluation are performed after the antenna weights are validated until the configured duration is reached. After the KPIs are counted, KPI evaluation can be performed, if the KPI after antenna weight adjustment is within 5% of the fluctuation value of the KPI before antenna weight adjustment, it is considered as normal fluctuation, the current antenna weight is maintained as the adjusted antenna weight, and periodic KPI evaluation is performed until the fluctuation value of the KPI is greater than 5%, wherein the period duration and the period number for performing KPI evaluation can be properly configured according to the actual application, for example, 10-time period evaluation is performed, and the duration for each evaluation is 15 minutes. If the KPI after the antenna weight adjustment is greater than 5% with respect to the fluctuation value of the KPI before the antenna weight adjustment, it is considered that the performance is deteriorated, at this time, the current antenna weight is backed to the original configuration value, and the above steps S100 to S500 are executed again to execute the antenna weight adjustment method again until the fluctuation value of the KPI is within 5%.
In an embodiment, in the process of performing the periodic KPI evaluation, if the fluctuation value is maintained within 5%, it may further continuously monitor whether the total online user number in the current area reaches a preconfigured user number threshold, and if the total online user number in the current area reaches the preconfigured user number threshold, the current antenna weight may be backed to the original configuration value, and the above steps S100 to S500 are performed again to perform the antenna weight adjustment method again.
In an embodiment, by using the antenna weight adjusting method including the above steps S100, S200, S300, S400, and S500, after acquiring multiple MR data under a current scene type, second RSRP information corresponding to each candidate antenna weight combination is calculated according to first RSRP information and DOA information in the MR data, evaluation information corresponding to each antenna weight combination is calculated according to all the first RSRP information and all the second RSRP information, an optimal antenna weight combination is determined from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information, and then the current antenna weight combination is updated to the optimal antenna weight combination, thereby completing adjustment processing of the antenna weights of the current region and the neighboring regions of the same frequency without manual participation in the whole antenna weight adjusting process, therefore, the problem that the traditional manual network optimization method cannot respond to the change of users in the network in time can be solved, and the efficiency of network optimization can be improved.
In addition, in an embodiment, when the current scene type is an aggregation scene or an overlapping coverage scene, the current antenna weight combination may include a current antenna weight of the current cell and current antenna weights of the same-frequency neighboring cells; the first RSRP information may include a first RSRP measurement value corresponding to the current antenna weight of the current cell and a second RSRP measurement value corresponding to the current antenna weight of each co-frequency neighboring cell one to one; the DOA information can comprise a first DOA measurement value corresponding to the current antenna weight of the cell and a second DOA measurement value corresponding to the current antenna weight of each same-frequency neighboring cell one by one; the candidate antenna weight combination can comprise a candidate antenna weight of the cell and a candidate antenna weight of each same-frequency neighboring cell; the second RSRP information may include a third RSRP predicted value corresponding to the candidate antenna weight of the current cell and fourth RSRP measured values corresponding to the candidate antenna weights of the same-frequency neighboring cells one to one. In this case, referring to fig. 3, the calculating of the second RSRP information corresponding to each candidate antenna weight combination one to one according to the first RSRP information and the DOA information in step S200 may include, but is not limited to, the following steps:
step S210, calculating according to the first RSRP measurement value and the first DOA measurement value to obtain a third RSRP prediction value;
and step S220, calculating to obtain a fourth RSRP predicted value according to the second RSRP measured value and the second DOA measured value.
In one embodiment, after the base station receives the MR data reported by the terminal, the base station can only obtain the first RSRP measurement value corresponding to the current antenna weight of the local area and the second RSRP measurement values corresponding to the current antenna weights of the same-frequency neighboring areas one by one, and the base station does not know the RSRP value corresponding to the candidate antenna weight of the local area and the RSRP value corresponding to the candidate antenna weight of each same-frequency neighboring area, therefore, the base station can calculate a third RSRP predicted value corresponding to the candidate antenna weight value of the local area through the first RSRP measured value and the first DOA measured value, and calculating to obtain fourth RSRP predicted values corresponding to the candidate antenna weights of the same-frequency neighboring cells one by one through the second RSRP measured value and the second DOA measured value, therefore, the base station can conveniently determine the optimal antenna weight combination according to the first RSRP measured value, the second RSRP measured value, all the third RSRP predicted values and all the fourth RSRP predicted values in the subsequent steps.
In an embodiment, the third RSRP prediction value may be calculated according to the following formula:
Figure BDA0002683189400000071
wherein, RSRPLocal area candidateAs a third RSRP predicted value, RSRPCurrent in this areaIs a first RSRP measurement value that is,
Figure BDA0002683189400000072
and obtaining a power difference value according to the first DOA measured value and a first preset three-dimensional wave beam power table corresponding to the current antenna weight value of the local area.
It should be noted that the base station may pre-store a first preset three-dimensional beam power table corresponding to the current antenna weight of the cell, where the first preset three-dimensional beam power table includes power values corresponding to the antenna weight and the DOA value. Therefore, after the base station obtains the first RSRP measurement value and the first DOA measurement value in the MR data, it may first find the first preset three-dimensional beam power table, then determine the first position corresponding to the first DOA measurement value in the first preset three-dimensional beam power table, then determine the second position corresponding to the current antenna weight of the local area and the third position corresponding to the candidate antenna weight currently desired to be obtained by the local area at the first position in the first preset three-dimensional beam power table, at this time, according to the second position, it may determine the power value corresponding to the current antenna weight of the local area in the first preset three-dimensional beam power table, according to the third position, it may determine the power value corresponding to the candidate antenna weight currently desired to be obtained by the local area in the first preset three-dimensional beam power table, so, according to the difference value of the two power values, can obtain
Figure BDA0002683189400000073
In an embodiment, the fourth RSRP prediction value may be calculated according to the following formula:
Figure BDA0002683189400000074
wherein, RSRPNeighbor candidatesAs a fourth RSRP predicted value, RSRPNeighbor currentIs the second RSRP measurement value and,
Figure BDA0002683189400000075
and obtaining a power difference value according to the second DOA measured value and a second preset three-dimensional wave beam power table corresponding to the current antenna weight of the same-frequency adjacent region.
It should be noted that the base station may pre-store a second preset three-dimensional beam power table corresponding to the current antenna weight of the same-frequency neighboring cell, where the second preset three-dimensional beam power table includes power values corresponding to the antenna weight and the DOA value. Therefore, after the base station acquires the second RSRP measurement value and the second DOA measurement value in the MR data, the second preset three-dimensional beam power table may be found first, and then the second preset three-dimensional beam power table may be found in the second preset three-dimensional beam power tableSetting a third position corresponding to a third DOA measurement value in a three-dimensional wave beam power table, then respectively determining a fifth position corresponding to the current antenna weight of the same-frequency adjacent region and a sixth position corresponding to the current candidate antenna weight which is desired to be solved in the same-frequency adjacent region at the fourth position in a second preset three-dimensional wave beam power table, at the moment, determining a power value corresponding to the current antenna weight of the same-frequency adjacent region in the second preset three-dimensional wave beam power table according to the fifth position, and determining a power value corresponding to the current candidate antenna weight which is desired to be solved in the same-frequency adjacent region in the second preset three-dimensional wave beam power table according to the sixth position, so that the difference value of the two power values can be obtained
Figure BDA0002683189400000076
In addition, in an embodiment, in the case that the current scene type is an aggregation scene, the evaluation information may include a first evaluation index corresponding to the current antenna weight combination and a second evaluation index corresponding to each candidate antenna weight combination one to one. In this case, referring to fig. 4, the step S300 of calculating, according to all the first RSRP information and all the second RSRP information, evaluation information corresponding to each antenna weight combination one to one may include, but is not limited to, the following steps:
step S311, traversing all MR data, and calculating to obtain a first statistical value corresponding to the current antenna weight combination according to the first RSRP measurement value and all the second RSRP measurement values aiming at each MR data;
step S312, obtaining a first evaluation index according to all the first statistical values;
step 313, traversing all MR data for each candidate antenna weight combination, calculating to obtain a second statistical value corresponding to the current candidate antenna weight combination according to the third RSRP predictive value and all fourth RSRP predictive values for each MR data, and obtaining a second evaluation index corresponding to the current candidate antenna weight combination according to all second statistical values after traversing all MR data.
In an embodiment, the first statistical value and the second statistical value may both be SINR values, and both may be obtained by using the following formulas:
Figure BDA0002683189400000081
wherein, the SINRiFor the SINR value corresponding to the ith MR data, the SINR for the current antenna weight combinationiI.e. the first statistic, for the candidate antenna weight combination, the SINRiThe second statistical value is obtained; RSRPThis districtFor the RSRP value of the ith MR data under the antenna weight of the region, for the current antenna weight combination, the RSRPThis districtNamely the first RSRP measurement value, and for the candidate antenna weight combination, the RSRPThis districtThe third RSRP predicted value is obtained; RSRPNeighbor summationFor the RSRP value of the ith MR data under the antenna weight of the same-frequency adjacent region, for the current antenna weight combination, the RSRPNeighbor summationI.e. the sum of all second RSRP measurements, RSRP for the candidate antenna weight combinationNeighbor summationThe sum of all the fourth RSRP measurement values is obtained; w is aNoise(s)Is Gaussian white noise power, wNoise(s)May be typically-105 dBm.
In an embodiment, when both the first statistical value and the second statistical value are SINR values, both the first evaluation index and the second evaluation index may be SINR average values. After the first statistical value corresponding to each MR data is calculated according to the above formula, all the first statistical values may be averaged to obtain a first evaluation index; for each candidate antenna weight combination, after the second statistical value corresponding to each MR data is calculated according to the above formula, all the second statistical values may be averaged, thereby obtaining a second evaluation index corresponding to the current candidate antenna weight combination. After the evaluation indexes corresponding to each antenna weight combination are obtained, the optimal antenna weight combination can be determined according to the evaluation indexes in the subsequent steps.
In an embodiment, in the case that the current scene type is an aggregation scene, before step S100, the following steps may be further included, but not limited to:
step 1, monitoring the number of online users of all cells in a current area, and executing step 2 when the number of online users of one cell reaches a preset first user number threshold value, otherwise, continuing to monitor;
step 2, starting a timing monitor to prevent the current task for identifying the scene type from being in the current state and being incapable of being restarted;
step 3, monitoring whether the sum of the online user numbers of all the cells in the current area reaches a preset second user number threshold value, if so, executing step 5; if not, executing the step 4;
step 4, judging whether the timing monitor reaches a preset time threshold, if so, stopping the current task, and executing the step 1; if not, executing the step 5;
step 5, monitoring whether the sum of the online user number in the current area is stable, and if so, executing step 100; if not, executing the step 6;
step 6, judging whether the timing monitor reaches a preset time threshold, if so, stopping the current task, and executing the step 1; if not, go to step S100.
In an embodiment, whether the sum of the online user numbers in the current area monitored in step 5 is stable or not can be determined by the following steps:
counting the number of online users by taking a preset and configurable time length as a statistical granularity, and when the fluctuation rate of the continuous 3-time statistical value is less than 5%, determining that the sum of the number of online users in the current area is stable, otherwise, determining that the sum of the number of online users in the current area is not stable, and continuously monitoring the change of the number of online users in the current area. Wherein, the fluctuation ratio can be calculated by the following method:
firstly, calculating the average value of the number of RRC connections for 3 times;
then, finding out the maximum value and the minimum value of the number of RRC connections for 3 times;
then, the fluctuation rate is calculated from the average value, the maximum value and the minimum value.
To illustrate by a specific example, assuming that the number of RRC connections for 3 consecutive times is RRC0, RRC1, and RRC2, respectively, the average value is: RRCavr ═ (RRC0+ RRC1+ RRC 2)/3; the maximum value is: maxrcc ═ max (RRC0/RRC1/RRC 2); the minimum value is: min (RRC0/RRC1/RRC 2); therefore, the fluctuation ratio can be calculated by the formula (maxRRC-minRRC)/RRCavr.
In addition, in an embodiment, in the case that the current scene type is an aggregation scene, step S400 may include, but is not limited to, the following steps:
and determining the antenna weight combination corresponding to the largest antenna weight combination in the first evaluation index and all the second evaluation indexes as the optimal antenna weight combination.
In an embodiment, since the first evaluation index and the second evaluation index are both SINR average values, and the larger the SINR average value is, the better the effect of the corresponding antenna weight combination is, therefore, after the first evaluation index corresponding to the current antenna weight combination and the second evaluation indexes corresponding to the candidate antenna weight combinations one-to-one are obtained through calculation, it may be determined that the antenna weight combination corresponding to the largest one of the first evaluation index and all the second evaluation indexes is the optimal antenna weight combination.
It is noted that, since the number of configurable candidate antenna weights per cell is very large (typically greater than 1000), the number of candidate antenna weight combinations for N cells is at least 1000NSuch a large number of combinations is impossible to determine the optimal antenna weight combination through traversal. In order to improve the efficiency of determining the optimal antenna weight combination, the processing time for determining the optimal antenna weight combination may be optimized by using a particle swarm algorithm in this embodiment. For example, any one of the first evaluation index and all the second evaluation indexes is used as an output result of the particle swarm optimization, 100 iterations are performed, and the largest one of the first evaluation index and all the second evaluation indexes is found out, at this time, the antenna weight combination corresponding to the evaluation index with the largest value can be regarded as the optimal antenna weight combination.
In addition, in an embodiment, when the current scene type is an overlapping coverage scene, the evaluation information may include third evaluation indexes corresponding to the respective candidate weight combinations one to one and fourth evaluation indexes corresponding to the respective candidate weight combinations one to one. In this case, referring to fig. 5, the step S300 of calculating, according to all the first RSRP information and all the second RSRP information, evaluation information corresponding to each antenna weight combination one to one may include, but is not limited to, the following steps:
step S314, determining a candidate weight set from the current antenna weight combination and all candidate antenna weight combinations according to the first RSRP measurement value, all second RSRP measurement values, all third RSRP prediction values, all fourth RSRP prediction values and the first RSRP threshold value, wherein the candidate weight set comprises a plurality of candidate weight combinations, and the candidate weight combinations comprise candidate weights of the cell and candidate weights of all same-frequency neighboring cells;
step S315, traversing all MR data according to each weight combination to be selected, calculating to obtain a third statistical value corresponding to the current weight combination to be selected according to the RSRP value corresponding to the weight combination to be selected of the current weight combination to be selected and the RSRP value corresponding to the weight combination to be selected of each same-frequency neighboring cell in the current weight combination to be selected, and calculating to obtain a third evaluation index corresponding to the current weight combination to be selected according to all the third statistical values corresponding to the current weight combination to be selected after traversing all the MR data;
step S316, aiming at each weight combination to be selected, acquiring the number of all RSRP values which meet the overlapping coverage condition and correspond to the weight to be selected of the current region in the weight combination to be selected, and calculating to obtain a fourth evaluation index corresponding to the current weight combination to be selected according to the number of the overlapping coverage condition and the number of all RSRP values which correspond to the weight to be selected of the current region in the weight combination to be selected, wherein the third evaluation index corresponds to the fourth evaluation index one by one.
In an embodiment, after the MR data from the terminal is obtained, it may be determined which cells belong to the cells with overlapping coverage, and then, based on the antenna weights of the cells with overlapping coverage, the evaluation information corresponding to each antenna weight combination is calculated. Whether the current cell belongs to the cell with the overlapped coverage can be judged in the following modes: and traversing all the MR data, and if the MR data meeting the overlapping coverage condition exists and the proportion of the MR data meeting the overlapping coverage condition to all the MR data exceeds 5%, determining that the current cell belongs to the cell with the overlapping coverage. Wherein, the overlapping coverage condition is as follows: the difference between the first RSRP measurement value and the largest of all the second RSRP measurement values is less than 6 dB. It should be noted that, the optimization adjustment of the antenna weight may be performed only for cells belonging to the overlapping coverage, and the optimization adjustment of the antenna weight may not be performed for cells not belonging to the overlapping coverage.
In an embodiment, in step S314, according to the first RSRP measurement value, all the second RSRP measurement values, the third RSRP prediction value, all the fourth RSRP prediction values, and the first RSRP threshold, the to-be-selected weight set is determined from the current antenna weight combination and all the candidate antenna weight combinations, which may specifically be:
and finding out all RSRP values which are greater than or equal to the first RSRP threshold value from the first RSRP measurement value, all second RSRP measurement values, all third RSRP predicted values and all fourth RSRP predicted values, wherein the antenna weight values corresponding to the RSRP values which are greater than or equal to the first RSRP threshold value are the weight value set to be selected.
It should be noted that the first RSRP threshold may have different embodiments, for example, the first RSRP threshold may be a preset threshold, or may be an average RSRP value calculated according to RSRP values corresponding to the current antenna weight and all candidate antenna weights, which is not limited in this embodiment. And when the first RSRP threshold is an RSRP average value calculated according to the current antenna weight and RSRP values corresponding to all the candidate antenna weights, each cell corresponds to one first RSRP threshold, that is, for each cell, an average value calculation is performed by using the current antenna weight of the cell and the RSRP values corresponding to all the candidate antenna weights of the cell to obtain the first RSRP threshold corresponding to the cell. In addition, after all the first RSRP thresholds are obtained through calculation, for each cell, the RSRP values corresponding to all the antenna weights are compared with the first RSRP thresholds, so that the antenna weights corresponding to the RSRP values which are greater than or equal to the first RSRP thresholds and correspond to the cell are found out, and therefore, after all the cells are traversed, a candidate weight set can be obtained.
In an embodiment, the third statistical value may be an SINR value, and may be obtained by using the following formula:
Figure BDA0002683189400000101
wherein, the SINRiIs the SINR value corresponding to the ith MR data, i.e. the third statistical value; RSRPThis districtThe value of RSRP of the ith MR data under the current weight to be selected of the current region under the current weight to be selected combination; RSRPNeighbor summationThe sum of the RSRP values of the ith MR data under the current weight to be selected of the same-frequency adjacent cells under the current weight to be selected combination; w is aNoise(s)Is Gaussian white noise power, wNoise(s)May be typically-105 dBm.
In an embodiment, when the third statistic is an SINR value, the third evaluation index may be an SINR average value. For each weight combination to be selected, after a third statistical value corresponding to each MR data is calculated according to the above formula, all the third statistical values may be averaged, thereby obtaining a third evaluation index corresponding to the current weight combination to be selected.
In an embodiment, the fourth evaluation index may be an overlap coverage ratio value, and may be obtained by using the following formula:
Figure BDA0002683189400000111
wherein, OverCoverRatioThis districtThe weak coverage proportion value under the weight value to be selected of the area under the current weight value combination to be selected is the fourth evaluation index corresponding to the weight value to be selected of the area under the current weight value combination to be selected; pAndis selected as the current candidateThe number of the RSRP values corresponding to the to-be-selected weight values of the region in the weight combination, which meet the overlapping coverage condition; pGeneral assemblyThe number of all RSRP values corresponding to the weight values to be selected of the current weight value combination to be selected in the current region.
In an embodiment, after the third evaluation index and the fourth evaluation index corresponding to all the weight combinations to be selected are obtained, the third evaluation index and the fourth evaluation index can be used to determine the optimal antenna weight combination in the subsequent steps.
In addition, in an embodiment, in the case that the current scene type is the overlapping coverage scene, the step S400 may include, but is not limited to, the following steps:
and determining the antenna weight combination corresponding to the smallest numerical value in all the fourth evaluation indexes as the optimal antenna weight combination.
In an embodiment, since the fourth evaluation index is an overlap coverage ratio value, and the smaller the overlap coverage ratio value is, the better the effect of the corresponding antenna weight combination is, therefore, after the fourth evaluation indexes corresponding to all the candidate weight combinations are obtained by calculation, it may be determined that the antenna weight combination corresponding to the smallest value among all the fourth evaluation indexes is the optimal antenna weight combination.
It is noted that, since the number of configurable candidate antenna weights per cell is very large (typically greater than 1000), the number of candidate antenna weight combinations for N cells is at least 1000NSuch a large number of combinations is impossible to determine the optimal antenna weight combination through traversal. In order to improve the efficiency of determining the optimal antenna weight combination, the processing time for determining the optimal antenna weight combination may be optimized by using a particle swarm algorithm in this embodiment. For example, any one of all the fourth evaluation indexes is used as an output result of the particle swarm optimization, 100 iterations are performed, and the smallest antenna weight combination among all the fourth evaluation indexes is found out, at this time, the antenna weight combination corresponding to the fourth evaluation index with the smallest value can be regarded as the optimal antenna weight combination.
In addition, in an embodiment, in the case that the current scene type is the overlapping coverage scene, the step S400 may further include, but is not limited to, the following steps:
and when the number of the fourth evaluation indexes with the minimum value in all the fourth evaluation indexes is more than two, determining that the antenna weight combination corresponding to the one with the maximum value in all the third evaluation indexes corresponding to the fourth evaluation index with the minimum value is the optimal antenna weight combination.
It should be noted that the steps in this embodiment and the step of determining that the antenna weight combination corresponding to the smallest value among all the fourth evaluation indexes is the optimal antenna weight combination in the above embodiments belong to parallel technical solutions.
In an embodiment, since the fourth evaluation index is an overlap coverage ratio value, the third evaluation index is an SINR average value, and the smaller the overlap coverage ratio value is, or the larger the SINR average value is, the better the effect of the corresponding antenna weight combination is, therefore, when there is a case that the number of the fourth evaluation indexes with the smallest value among all the fourth evaluation indexes is two or more, it may be determined that the antenna weight combination corresponding to the one with the largest value among all the third evaluation indexes corresponding to the fourth evaluation index with the smallest value is the optimal antenna weight combination.
It should be noted that, in this embodiment, the particle swarm optimization may also be used to optimize and determine the processing time of the largest one of all the third evaluation indexes corresponding to the fourth evaluation index with the smallest value, and when the particle swarm optimization is used to determine the largest one of all the third evaluation indexes corresponding to the fourth evaluation index with the smallest value, the antenna weight combination corresponding to the third evaluation index with the largest value may be regarded as the optimal antenna weight combination.
In addition, in an embodiment, in the case that the current scene type is a weak coverage scene or a tidal effect scene, the current antenna weight combination includes the current antenna weight of the local region; the first RSRP information comprises a first RSRP measurement value corresponding to the current antenna weight of the cell; the DOA information comprises a first DOA measured value corresponding to the current antenna weight value of the region; the candidate antenna weight combination comprises the candidate antenna weight of the local area; the second RSRP information includes a third RSRP predicted value corresponding to the candidate antenna weight of the local region. In this case, referring to fig. 6, the calculating of the second RSRP information corresponding to each candidate antenna weight combination one to one according to the first RSRP information and the DOA information in step S200 may include, but is not limited to, the following steps:
and step S230, calculating to obtain a third RSRP predicted value according to the first RSRP measured value and the first DOA measured value.
In an embodiment, after the base station receives the MR data reported by the terminal, the base station can only obtain the first RSRP measurement value corresponding to the current antenna weight of the local area, and the base station does not know the RSRP value corresponding to the candidate antenna weight of the local area.
In an embodiment, the third RSRP prediction value may be calculated according to the following formula:
Figure BDA0002683189400000121
wherein, RSRPLocal area candidateAs a third RSRP predicted value, RSRPCurrent in this areaIs a first RSRP measurement value that is,
Figure BDA0002683189400000122
and obtaining a power difference value according to the first DOA measured value and a first preset three-dimensional wave beam power table corresponding to the current antenna weight value of the local area.
It should be noted that the base station may pre-store a first preset three-dimensional beam power table corresponding to the current antenna weight in the cell, where the first preset three-dimensional beam power table includes power values corresponding to the antenna weight and the DOA value. Therefore, after the base station acquires the first RSRP measurement value and the first DOA measurement value in the MR data, the first preset three-dimensional beam power table may be found first, and thenThen, a first position corresponding to a first DOA measurement value is determined in the first preset three-dimensional wave beam power table, then, a second position corresponding to the current antenna weight of the local area and a third position corresponding to the candidate antenna weight which is desired to be obtained currently of the local area are respectively determined at the first position in the first preset three-dimensional wave beam power table, at the moment, a power value corresponding to the current antenna weight of the local area can be determined in the first preset three-dimensional wave beam power table according to the second position, a power value corresponding to the candidate antenna weight which is desired to be obtained currently of the local area can be determined in the first preset three-dimensional wave beam power table according to the third position, and therefore, the power value corresponding to the candidate antenna weight which is desired to be obtained currently of the local area can be obtained according to the difference value of the two power values
Figure BDA0002683189400000123
In addition, in an embodiment, when the current scene type is a weak coverage scene, the evaluation information may include a fifth evaluation index corresponding to the current antenna weight of the local area, a sixth evaluation index corresponding to the current antenna weight of the local area, a seventh evaluation index corresponding to the candidate antenna weights of the local areas one by one, and an eighth evaluation index corresponding to the candidate antenna weights of the local areas one by one. In this case, referring to fig. 7, the step S300 of calculating, according to all the first RSRP information and all the second RSRP information, evaluation information corresponding to each antenna weight combination one to one may include, but is not limited to, the following steps:
step S321, acquiring the number of first RSRP measurement values with the numerical values smaller than a preset weak coverage threshold value in all the first RSRP measurement values, and calculating to obtain a fifth evaluation index according to the number of the first RSRP measurement values with the numerical values smaller than the preset weak coverage threshold value and the number of all the first RSRP measurement values;
step S322, acquiring the sum of all the first RSRP measurement values, and calculating to obtain a sixth evaluation index according to the sum of all the first RSRP measurement values and the number of all the first RSRP measurement values, wherein the fifth evaluation index corresponds to the sixth evaluation index;
step S323, aiming at the candidate antenna weight of each local area, obtaining the number of third RSRP predicted values with the numerical value smaller than a preset weak coverage threshold value in all third RSRP predicted values corresponding to the candidate antenna weight of the current local area, and calculating to obtain a seventh evaluation index corresponding to the candidate antenna weight of the current local area according to the number of the third RSRP predicted values with the numerical value smaller than the preset weak coverage threshold value and the number of all third RSRP predicted values corresponding to the candidate antenna weight of the current local area;
step S324, for the candidate antenna weight of each local area, obtaining a sum of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area, and calculating an eighth evaluation index corresponding to the current candidate antenna weight of the local area according to the sum and the number of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area, where the seventh evaluation index corresponds to the eighth evaluation index one to one.
In an embodiment, after the MR data from the terminal is obtained, which cells belong to the cells with weak coverage may be determined first, and then, based on the antenna weights of the cells with weak coverage, evaluation information corresponding to each antenna weight combination one to one is calculated. Whether the current cell belongs to the cell with weak coverage can be judged in the following modes: and traversing all the MR data under the current antenna weight combination, and if the first RSRP measurement value is smaller than a preset weak coverage threshold value and the proportion of the MR data with the SINR value smaller than 5dB in all the MR data exceeds 5%, determining that the current cell belongs to a cell with weak coverage. It should be noted that, the optimization adjustment of the antenna weight may be performed only for the cell belonging to the weak coverage, and the optimization adjustment of the antenna weight may not be performed for the cell not belonging to the weak coverage.
In an embodiment, the fifth evaluation index may be a weak coverage ratio value, and may be obtained by using the following formula:
Figure BDA0002683189400000131
wherein PoorcoverratioAt presentCurrent antenna weight of this regionA lower weak coverage ratio value; qAndthe number of the first RSRP measurement values which are smaller than a preset weak coverage threshold value in all the first RSRP measurement values is counted; qGeneral assemblyThe number of all first RSRP measurements.
In an embodiment, the sixth evaluation index may be an RSRP average value, and therefore, the sixth evaluation index may be calculated by obtaining a sum of all the first RSRP measurement values and then according to the sum of all the first RSRP measurement values and the number of all the first RSRP measurement values.
In an embodiment, the seventh evaluation indicator may be a weak coverage ratio value, and the candidate antenna weight for each local area may be obtained by using the following formula:
Figure BDA0002683189400000132
wherein PoorcoverratioCandidatesThe weak coverage ratio value under the current candidate antenna weight of the local area is a seventh evaluation index corresponding to the current candidate antenna weight of the local area; l isAndthe number of the third RSRP predicted values with the numerical value smaller than the preset weak coverage threshold value in all the third RSRP predicted values corresponding to the current candidate antenna weight of the current region is set; l isGeneral assemblyAnd the number of all third RSRP predicted values corresponding to the current candidate antenna weight of the current region is obtained.
In an embodiment, the eighth evaluation index may be an average RSRP value, and for the candidate antenna weight of each local area, the eighth evaluation index may be obtained by obtaining a sum of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area, and then calculating according to the sum and the number of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area.
In an embodiment, after a fifth evaluation index corresponding to the current antenna weight of the local area, a sixth evaluation index corresponding to the current antenna weight of the local area, a seventh evaluation index corresponding to the candidate antenna weights of each local area one to one, and an eighth evaluation index corresponding to the candidate antenna weights of each local area one to one are obtained, an optimal antenna weight combination can be determined in the subsequent steps by using the fifth evaluation index, the sixth evaluation index, the seventh evaluation index, and the eighth evaluation index.
In addition, in an embodiment, in the case that the current scene type is a weak coverage scene, the step S400 may include, but is not limited to, the following steps:
and determining the antenna weight combination corresponding to the fifth evaluation index and the smallest antenna weight combination as the optimal antenna weight combination.
In an embodiment, since the fifth evaluation index and the seventh evaluation index are weak coverage ratio values, and the smaller the weak coverage ratio value is, the better the effect of the corresponding antenna weight combination is, therefore, after the fifth evaluation index corresponding to the current antenna weight of the local area and the seventh evaluation index corresponding to the candidate antenna weights of each local area one by one are obtained through calculation, it may be determined that the antenna weight combination corresponding to the smallest value of the fifth evaluation index and all the seventh evaluation indexes is the optimal antenna weight combination.
It is noted that, since the number of configurable candidate antenna weights per cell is very large (typically greater than 1000), the number of candidate antenna weight combinations for N cells is at least 1000NSuch a large number of combinations is impossible to determine the optimal antenna weight combination through traversal. In order to improve the efficiency of determining the optimal antenna weight combination, the processing time for determining the optimal antenna weight combination may be optimized by using a particle swarm algorithm in this embodiment. For example, any one of the fifth evaluation index and all the seventh evaluation indexes is used as an output result of the particle swarm optimization, 100 iterations are performed, and the smallest antenna weight combination among the fifth evaluation index and all the seventh evaluation indexes is found out.
In addition, in an embodiment, in the case that the current scene type is a weak coverage scene, the step S400 may further include, but is not limited to, the following steps:
and when more than two numerical values in the fifth evaluation index and all the seventh evaluation indexes are equal, determining that the antenna weight combination corresponding to the largest numerical value in the sixth evaluation index and all the eighth evaluation indexes is the optimal antenna weight combination.
It should be noted that the steps in this embodiment and the step of determining that the antenna weight combination corresponding to the smallest value among the fifth evaluation index and all the seventh evaluation indexes in the above embodiments is the optimal antenna weight combination belong to parallel technical solutions.
In an embodiment, since the fifth evaluation index and the seventh evaluation index are weak coverage ratio values, the sixth evaluation index and the eighth evaluation index are RSRP average values, and the smaller the weak coverage ratio value is, or the larger the RSRP average value is, the better the effect of the corresponding antenna weight combination is, therefore, when there is a case where two or more values are equal in the fifth evaluation index and all the seventh evaluation indexes, it may be determined that the antenna weight combination corresponding to the one with the largest value in the sixth evaluation index and all the eighth evaluation indexes is the optimal antenna weight combination.
It should be noted that, in this embodiment, a particle swarm optimization may also be used to optimize and determine the processing time of the largest one of the sixth evaluation index and all the eighth evaluation indexes, and when the largest one of the sixth evaluation index and all the eighth evaluation indexes is determined by using the particle swarm optimization, the antenna weight combination corresponding to the evaluation index with the largest value may be regarded as the optimal antenna weight combination.
In addition, in an embodiment, in the case that the current scene type is a tidal effect scene, the evaluation information may include a ninth evaluation index corresponding to the current antenna weight of the local zone and tenth evaluation indexes corresponding to the candidate antenna weights of the respective local zones one to one. In this case, referring to fig. 8, the step S300 of calculating, according to all the first RSRP information and all the second RSRP information, evaluation information corresponding to each antenna weight combination one to one may include, but is not limited to, the following steps:
step S325, acquiring the sum of all the first RSRP measurement values, and calculating to obtain a ninth evaluation index according to the sum of all the first RSRP measurement values and the number of all the first RSRP measurement values;
step S326, for the candidate antenna weight of each local area, obtaining a sum of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area, and according to the sum and the number of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area, calculating to obtain a tenth evaluation index corresponding to the current candidate antenna weight of the local area.
In an embodiment, after the MR data from the terminal is acquired, which cells belong to the cells in the tidal effect scenario may be determined, and then, based on the antenna weights of the cells belonging to the tidal effect scenario, evaluation information corresponding to each antenna weight combination one to one is calculated. Wherein, whether the current cell belongs to the cell of the tidal effect scene can be judged by the following modes: under the current antenna weight combination, the number of online users or the traffic at busy hours (for example, from 7 a.m. to 23 a.m.) in a preset time period (for example, one week or one month) is obtained, then the average value of the number of online users or the traffic at busy hours and the fluctuation rate at busy hours are calculated, and when the fluctuation rate at busy hours is more than 5%, the current cell is considered to belong to the cell in the tidal effect scene.
In one embodiment, the busy hour fluctuation rate can be obtained by the following formula:
busy hour fluctuation rate abs (number of busy hour on-line users-average number of busy hour on-line users)/average number of busy hour on-line users)
Wherein abs () is a function that takes the absolute value.
It should be noted that both the preset time period and the duration of the busy hour can be appropriately selected according to actual situations, which is not specifically limited in this embodiment.
In one embodiment, for a cell determined to belong to a tidal effect scenario, the antenna weight adjustment method may be selected to be performed during a time period when the busy hour fluctuation rate is greater than 5%. In addition, when a plurality of continuous time periods with the fluctuation rate of busy hour being more than 5% exist in the cell belonging to the tidal effect scene, the plurality of continuous time periods can be combined into one time period to carry out the unified adjustment of the antenna weight; and for the discontinuous condition of the time period with the fluctuation rate of busy hour more than 5%, the adjustment of the antenna weight value can be carried out in each time period separately.
In an embodiment, the ninth evaluation index may be an RSRP average value, and therefore, the ninth evaluation index may be calculated by obtaining a sum of all the first RSRP measurement values and then according to the sum of all the first RSRP measurement values and the number of all the first RSRP measurement values.
In an embodiment, the tenth evaluation index may be an average RSRP value, and for the candidate antenna weight of each local area, the tenth evaluation index may be calculated by obtaining a sum of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area, and then according to the sum and the number of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area.
In an embodiment, after the ninth evaluation index corresponding to the current antenna weight of the local area and the tenth evaluation index corresponding to the candidate antenna weights of each local area one by one are obtained, the ninth evaluation index and the tenth evaluation index may be used to determine an optimal antenna weight combination in subsequent steps.
Additionally, in an embodiment, in the case that the current scene type is a tidal effect scene, step S400 may include, but is not limited to, the following steps:
and determining the antenna weight combination corresponding to the largest antenna weight combination in the ninth evaluation index and all the tenth evaluation indexes as the optimal antenna weight combination.
In an embodiment, since the ninth evaluation index and the tenth evaluation index are both RSRP average values, and the larger the RSRP average value is, the better the effect of the corresponding antenna weight combination is, therefore, after the ninth evaluation index corresponding to the current antenna weight of the local area and the tenth evaluation index corresponding to the candidate antenna weights of each local area one by one are obtained through calculation, it may be determined that the antenna weight combination corresponding to the largest one of the ninth evaluation index and all the tenth evaluation indexes is the optimal antenna weight combination.
It is noted that, since the number of configurable candidate antenna weights per cell is very large (typically greater than 1000), the number of candidate antenna weight combinations for N cells is at least 1000NSuch a large number of combinations is impossible to determine the optimal antenna weight combination through traversal. In order to improve the efficiency of determining the optimal antenna weight combination, the processing time for determining the optimal antenna weight combination may be optimized by using a particle swarm algorithm in this embodiment. For example, any one of the ninth evaluation index and all the tenth evaluation indexes is used as an output result of the particle swarm optimization, 100 iterations are performed, and the largest one of the ninth evaluation index and all the tenth evaluation indexes is found out, at this time, the antenna weight combination corresponding to the evaluation index with the largest value can be regarded as the optimal antenna weight combination.
In addition, an embodiment of the present invention further provides an antenna weight adjusting apparatus, where the antenna weight adjusting apparatus includes: a memory, a processor, and a computer program stored on the memory and executable on the processor.
The processor and memory may be connected by a bus or other means.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
It should be noted that the antenna weight adjusting apparatus in this embodiment may be applied to the local base station or the neighboring base station in the embodiment shown in fig. 1, and the antenna weight adjusting apparatus in this embodiment can form a part of the system architecture in the embodiment shown in fig. 1, and these embodiments all belong to the same inventive concept, so these embodiments have the same implementation principle and technical effect, and are not described in detail here.
The non-transitory software program and instructions required for implementing the antenna weight adjustment method of the above embodiment are stored in the memory, and when being executed by the processor, the antenna weight adjustment method of the above embodiment is executed, for example, the method steps S100 to S500 in fig. 2, the method steps S210 to S220 in fig. 3, the method steps S311 to S313 in fig. 4, the method steps S314 to S416 in fig. 5, the method step S230 in fig. 6, the method steps S321 to S324 in fig. 7, and the method steps S325 to S326 in fig. 8, which are described above, are executed.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions, which are executed by a processor or a controller, for example, by a processor in the above-mentioned apparatus embodiment, and can enable the processor to execute the antenna weight adjusting method in the above-mentioned embodiment, for example, execute the above-mentioned method steps S100 to S500 in fig. 2, method steps S210 to S220 in fig. 3, method steps S311 to S313 in fig. 4, method steps S314 to S416 in fig. 5, method step S230 in fig. 6, method steps S321 to S324 in fig. 7, and method steps S325 to S326 in fig. 8.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. 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 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.
While the preferred embodiments of the present invention have been described in detail, it will be understood by those skilled in the art that the foregoing and various other changes, omissions and deviations in the form and detail thereof may be made without departing from the scope of this invention.

Claims (15)

1. An antenna weight value adjusting method comprises the following steps:
acquiring a plurality of measurement report MR data under a current scene type, wherein each MR data comprises first Reference Signal Received Power (RSRP) information corresponding to a current antenna weight combination and direction of arrival (DOA) information corresponding to the current antenna weight combination;
traversing all the MR data, and calculating to obtain second RSRP information corresponding to each candidate antenna weight combination one by one according to the first RSRP information and the DOA information aiming at each MR data;
calculating to obtain evaluation information corresponding to each antenna weight combination one by one according to all the first RSRP information and all the second RSRP information;
determining an optimal antenna weight combination from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information;
and updating the current antenna weight combination to the optimal antenna weight combination.
2. The method according to claim 1, wherein, when the current scene type is an aggregation scene or an overlapping coverage scene, the current antenna weight combination comprises a current antenna weight of the local region and current antenna weights of each same-frequency neighboring region; the first RSRP information comprises a first RSRP measurement value corresponding to the current antenna weight of the local area and second RSRP measurement values corresponding to the current antenna weights of the same-frequency adjacent areas one by one; the DOA information comprises a first DOA measurement value corresponding to the current antenna weight of the local region and second DOA measurement values corresponding to the current antenna weights of the same-frequency adjacent regions one by one; the candidate antenna weight combination comprises a candidate antenna weight of the cell and a candidate antenna weight of each same-frequency adjacent cell; the second RSRP information comprises a third RSRP predicted value corresponding to the candidate antenna weight of the local area and fourth RSRP measured values corresponding to the candidate antenna weights of the same-frequency adjacent areas one by one;
the calculating according to the first RSRP information and the DOA information to obtain second RSRP information corresponding to each candidate antenna weight combination one to one includes:
calculating to obtain a third RSRP predicted value according to the first RSRP measured value and the first DOA measured value;
and calculating to obtain the fourth RSRP predicted value according to the second RSRP measured value and the second DOA measured value.
3. The method according to claim 2, wherein in a case that a current scene type is an aggregation scene, the evaluation information includes a first evaluation index corresponding to the current antenna weight combination and a second evaluation index corresponding to each of the candidate antenna weight combinations one to one;
the calculating to obtain evaluation information corresponding to each antenna weight combination one to one according to all the first RSRP information and all the second RSRP information includes:
traversing all the MR data, and calculating to obtain a first statistical value corresponding to the current antenna weight combination according to the first RSRP measurement value and all the second RSRP measurement values aiming at each MR data;
obtaining the first evaluation index according to all the first statistical values;
and traversing all the MR data aiming at each candidate antenna weight combination, calculating to obtain a second statistical value corresponding to the current candidate antenna weight combination according to the third RSRP predicted value and all the fourth RSRP predicted values aiming at each MR data, and obtaining a second evaluation index corresponding to the current candidate antenna weight combination according to all the second statistical values after traversing all the MR data.
4. The method according to claim 3, wherein the determining an optimal antenna weight combination from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information comprises:
and determining the antenna weight combination corresponding to the largest antenna weight combination in the first evaluation index and all the second evaluation indexes as an optimal antenna weight combination.
5. The method according to claim 2, wherein in a case that the current scene type is an overlapping coverage scene, the evaluation information includes third evaluation indexes corresponding to the respective weight combinations to be selected one by one and fourth evaluation indexes corresponding to the respective weight combinations to be selected one by one;
the calculating to obtain evaluation information corresponding to each antenna weight combination one to one according to all the first RSRP information and all the second RSRP information includes:
determining a candidate weight set from the current antenna weight combination and all candidate antenna weight combinations according to the first RSRP measurement value, all the second RSRP measurement values, all the third RSRP prediction values, all the fourth RSRP prediction values and a first RSRP threshold, wherein the candidate weight set comprises a plurality of the candidate weight combinations, and the candidate weight combinations comprise the candidate weight of the local area and the candidate weight of each same-frequency neighboring area;
traversing all the MR data aiming at each weight combination to be selected, calculating to obtain a third statistical value corresponding to the current weight combination to be selected according to the RSRP value corresponding to the weight combination to be selected of the local region in the current weight combination to be selected and the RSRP value corresponding to the weight combination to be selected of each same-frequency neighboring region in the current weight combination to be selected, and calculating to obtain a third evaluation index corresponding to the current weight combination to be selected according to all the third statistical values corresponding to the current weight combination to be selected after traversing all the MR data;
and for each weight combination to be selected, obtaining the number of all RSRP values which meet overlapping coverage conditions and correspond to the weight to be selected of the current region in the weight combination to be selected, and calculating to obtain the fourth evaluation index corresponding to the current weight combination to be selected according to the number of all RSRP values which meet overlapping coverage conditions and correspond to the weight to be selected of the current region in the weight combination to be selected, wherein the third evaluation index corresponds to the fourth evaluation index one to one.
6. The method according to claim 5, wherein the determining an optimal antenna weight combination from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information comprises:
determining the antenna weight combination corresponding to the smallest numerical value in all the fourth evaluation indexes as an optimal antenna weight combination;
or,
and when the number of the fourth evaluation indexes with the minimum value in all the fourth evaluation indexes is more than two, determining that the antenna weight combination corresponding to the one with the maximum value in all the third evaluation indexes corresponding to the fourth evaluation index with the minimum value is the optimal antenna weight combination.
7. The method of claim 1, wherein the current antenna weight combination comprises a current antenna weight of the local zone in case the current scene type is a weak coverage scene or a tidal effect scene; the first RSRP information comprises a first RSRP measurement value corresponding to the current antenna weight of the local area; the DOA information comprises a first DOA measurement value corresponding to the current antenna weight of the local area; the candidate antenna weight combination comprises the candidate antenna weight of the local area; the second RSRP information comprises a third RSRP predicted value corresponding to the candidate antenna weight of the local area;
the calculating according to the first RSRP information and the DOA information to obtain second RSRP information corresponding to each candidate antenna weight combination one to one includes:
and calculating to obtain the third RSRP predicted value according to the first RSRP measured value and the first DOA measured value.
8. The method according to claim 7, wherein in a case that a current scene type is a weak coverage scene, the evaluation information includes a fifth evaluation index corresponding to a current antenna weight of the local zone, a sixth evaluation index corresponding to the current antenna weight of the local zone, a seventh evaluation index corresponding to a candidate antenna weight of each local zone, and an eighth evaluation index corresponding to the candidate antenna weight of each local zone;
the calculating to obtain evaluation information corresponding to each antenna weight combination one to one according to all the first RSRP information and all the second RSRP information includes:
acquiring the number of first RSRP measurement values of which the values are smaller than a preset weak coverage threshold value in all the first RSRP measurement values, and calculating to obtain a fifth evaluation index according to the number of the first RSRP measurement values of which the values are smaller than the preset weak coverage threshold value and the number of all the first RSRP measurement values;
acquiring the sum of all the first RSRP measurement values, and calculating to obtain a sixth evaluation index according to the sum of all the first RSRP measurement values and the number of all the first RSRP measurement values, wherein the fifth evaluation index corresponds to the sixth evaluation index;
for the candidate antenna weight of each local area, acquiring the number of third RSRP predicted values with the numerical value smaller than a preset weak coverage threshold value in all third RSRP predicted values corresponding to the current candidate antenna weight of the local area, and calculating to obtain a seventh evaluation index corresponding to the current candidate antenna weight of the local area according to the number of the third RSRP predicted values with the numerical value smaller than the preset weak coverage threshold value and the number of all third RSRP predicted values corresponding to the current candidate antenna weight of the local area;
and for the candidate antenna weight of each local area, obtaining the sum of all the third RSRP predicted values corresponding to the current candidate antenna weight of the local area, and calculating to obtain the eighth evaluation index corresponding to the current candidate antenna weight of the local area according to the sum and the number of all the third RSRP predicted values corresponding to the current candidate antenna weight of the local area, wherein the seventh evaluation index corresponds to the eighth evaluation index one to one.
9. The method according to claim 8, wherein the determining an optimal antenna weight combination from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information comprises:
determining the antenna weight combination corresponding to the fifth evaluation index and the smallest numerical value among all the seventh evaluation indexes as an optimal antenna weight combination;
or,
and when more than two numerical values are equal in the fifth evaluation index and all the seventh evaluation indexes, determining that the antenna weight combination corresponding to the largest numerical value in the sixth evaluation index and all the eighth evaluation indexes is the optimal antenna weight combination.
10. The method according to claim 7, wherein in the case that the current scene type is a tidal effect scene, the evaluation information includes a ninth evaluation index corresponding to the current antenna weight of the local zone and a tenth evaluation index corresponding to the candidate antenna weight of each local zone in a one-to-one manner;
the calculating to obtain evaluation information corresponding to each antenna weight combination one to one according to all the first RSRP information and all the second RSRP information includes:
acquiring the sum of all the first RSRP measurement values, and calculating to obtain the ninth evaluation index according to the sum of all the first RSRP measurement values and the number of all the first RSRP measurement values;
and for the candidate antenna weight of each local area, obtaining the sum of all the third RSRP predicted values corresponding to the current candidate antenna weight of the local area, and calculating to obtain the tenth evaluation index corresponding to the current candidate antenna weight of the local area according to the sum and the number of all the third RSRP predicted values corresponding to the current candidate antenna weight of the local area.
11. The method according to claim 10, wherein the determining an optimal antenna weight combination from the current antenna weight combination and all the candidate antenna weight combinations according to all the evaluation information comprises:
and determining the antenna weight combination corresponding to the largest antenna weight combination in the ninth evaluation index and all the tenth evaluation indexes as an optimal antenna weight combination.
12. A method as claimed in claim 2 or 7, wherein said calculating a third RSRP prediction value from said first RSRP measurement value and said first DOA measurement value comprises:
calculating to obtain the third RSRP predicted value according to the following formula:
Figure FDA0002683189390000041
wherein, RSRPLocal area candidateFor the third RSRP predicted value, RSRPCurrent in this areaFor the first RSRP measurement value to be,
Figure FDA0002683189390000042
obtaining a power difference value according to the first DOA measurement value and a first preset three-dimensional wave beam power table corresponding to the current antenna weight value of the local area, wherein the first preset three-dimensional wave beam power table comprises power values corresponding to the antenna weight value and the DOA value.
13. The method of claim 2, wherein said calculating the fourth RSRP prediction value from the second RSRP measurement value and the second DOA measurement value comprises:
calculating the fourth RSRP predicted value according to the following formula:
Figure FDA0002683189390000043
wherein, RSRPNeighbor candidatesFor the fourth RSRP predicted value, RSRPNeighbor currentFor the second RSRP measurement value to be,
Figure FDA0002683189390000044
obtaining a power difference value according to the second DOA measured value and a second preset three-dimensional wave beam power table corresponding to the current antenna weight of the same-frequency adjacent cell, wherein the second preset three-dimensional wave beam power table is used for obtaining the power difference valueAnd setting the three-dimensional beam power table to comprise power values corresponding to the antenna weight values and the DOA values.
14. An antenna weight adjusting device, comprising: memory, processor and computer program stored on the memory and executable on the processor, wherein the processor implements the antenna weight adjusting method according to any one of claims 1 to 13 when executing the computer program.
15. A computer-readable storage medium storing computer-executable instructions for performing the antenna weight adjustment method according to any one of claims 1 to 13.
CN202010968441.6A 2020-09-15 2020-09-15 Antenna weight value adjusting method and device and computer readable storage medium Pending CN114189883A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023226868A1 (en) * 2022-05-25 2023-11-30 中兴通讯股份有限公司 Antenna direction adjustment method and apparatus, base station, electronic device, and storage medium

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023226868A1 (en) * 2022-05-25 2023-11-30 中兴通讯股份有限公司 Antenna direction adjustment method and apparatus, base station, electronic device, and storage medium

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