CN111082840A - Method and device for optimizing antenna broadcast beam - Google Patents
Method and device for optimizing antenna broadcast beam Download PDFInfo
- Publication number
- CN111082840A CN111082840A CN201911342705.0A CN201911342705A CN111082840A CN 111082840 A CN111082840 A CN 111082840A CN 201911342705 A CN201911342705 A CN 201911342705A CN 111082840 A CN111082840 A CN 111082840A
- Authority
- CN
- China
- Prior art keywords
- user distribution
- optimization
- user
- beam configuration
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0408—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas using two or more beams, i.e. beam diversity
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
Abstract
The embodiment of the invention provides an antenna broadcast beam optimization method and device, relates to the technical field of communication, and aims to optimize the beam configuration of an antenna broadcast beam according to future user distribution and improve user experience. The method comprises the following steps: predicting first user distribution, wherein the first user distribution is the user distribution of the target base station at the next moment of the current moment; inquiring and obtaining second user distribution and beam configuration of the second user distribution in a user distribution information base; the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; establishing a target optimization function according to the second user distribution and a preset rule; and adjusting the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration of the second user distribution. The embodiment of the application is applied to optimizing and adjusting the antenna broadcast beam.
Description
Technical Field
The embodiment of the invention relates to the technical field of communication, in particular to an antenna broadcast beam optimization method and device.
Background
The multiple antenna technology has been applied to various wireless communication systems as an effective means for improving the spectral efficiency and transmission reliability of the system. The more the number of antennas is, the more obvious the improvement of the spectrum efficiency and the reliability of the wireless communication system is. Therefore, the adoption of a multiple-input multiple-output (mu1tip1e-input mu1tip1e-output, MIMO) antenna provides an effective way for greatly improving the capacity of a wireless communication system. However, the introduction of large-scale antennas (massive MIMO) also increases the complexity of wireless communication systems. Further, the passive MIMO also faces the difficulties of diversity of coverage scenes, more complex parameter configuration, and the like in deployment, for example, due to the fact that the number of antennas is too large, the configuration parameters of corresponding antenna beams are also very large, and due to the fact that the beams of the antennas easily interfere with each other to cause power loss, the optimization of the configuration parameters of the antenna broadcast beams of the passive MIMO is more complex.
Currently, the method for optimizing the antenna broadcast beam is as follows: and the base station collects the historical network parameters of the users in the target area and determines the grids included in the target area. And then, the base station associates the acquired network parameters with the determined grids, compares the network data matched with the grids with the actual recorded data, and adjusts and optimizes the configuration parameters of the antenna broadcast beams according to the comparison result.
According to the method, the configuration parameters of the antenna broadcast wave beams are adjusted based on the historical network parameters of the users in the target area and the geogrid, and future user network data cannot be sensed, so that the adjustment performed when the user distribution corresponding to the antenna changes is not accurate any more and is not optimal according to the configuration parameters of the antenna broadcast wave beams adjusted by the historical network parameters of the users.
Disclosure of Invention
Embodiments of the present invention provide a method and an apparatus for optimizing an antenna broadcast beam, which can optimize a beam configuration of the antenna broadcast beam according to future user distribution, and improve user experience.
In a first aspect, the present application provides a method for optimizing an antenna broadcast beam, including the following steps: predicting first user distribution, wherein the first user distribution is the user distribution of the target base station at the next moment of the current moment; inquiring and obtaining second user distribution and beam configuration of the second user distribution in a user distribution information base; the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; the second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution; establishing a target optimization function according to the second user distribution and a preset rule; and adjusting the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration of the second user distribution.
In the scheme, first user distribution is predicted, wherein the first user distribution is the user distribution of the target base station at the next moment of the current moment; inquiring and obtaining second user distribution and beam configuration of the second user distribution in a user distribution information base; the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; the second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution; establishing a target optimization function according to the second user distribution and a preset rule; and adjusting the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration of the second user distribution. Therefore, firstly, the method predicts the user distribution of the target base station at the next moment of the current moment, and then adjusts the beam configuration of the antenna broadcast beam after establishing the target optimization function according to the user distribution. When the beam configuration of the antenna broadcast beam is adjusted, the predicted user distribution is used as a necessary parameter for adjustment, and adjustment optimization can be ensured after the future user distribution is considered when the beam configuration is adjusted. When the future user distribution changes, the adjustment of the future user distribution is considered, so that the accuracy of the beam optimization adjustment can be improved. Secondly, in the method and the device, the target optimization function is established according to the second user distribution, the target beam configuration of the antenna broadcast beam is adjusted according to the target optimization function and the beam configuration of the second user distribution, the beam configuration of the antenna broadcast beam can be correspondingly adjusted according to the user side requirement, and the user experience is improved.
In a second aspect, an apparatus for optimizing an antenna broadcast beam is provided, including: the prediction module is used for predicting the first user distribution, wherein the first user distribution is the user distribution of the target base station at the next moment of the current moment; the query module is used for querying and obtaining the second user distribution and the beam configuration of the second user distribution in the user distribution information base; the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; the second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution; the processing module is used for establishing a target optimization function according to the second user distribution and the preset rule inquired by the inquiry module; and the processing module is further used for adjusting the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration distributed by the second user.
In a third aspect, an antenna broadcast beam optimization apparatus is provided, which includes a processor, and when the antenna broadcast beam optimization apparatus is running, the processor executes a computer to execute instructions, so that the antenna broadcast beam optimization apparatus executes the antenna broadcast beam optimization method described above.
In a fourth aspect, there is provided a computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the method of optimizing an antenna broadcast beam as described above.
In a fifth aspect, a computer program product is provided, the computer program product comprising instruction code for performing the method of optimizing an antenna broadcast beam as described above.
It is to be understood that any one of the above-mentioned optimization apparatus, computer-readable storage medium or computer program product for antenna broadcast beam is used to execute the above-mentioned optimization method for antenna broadcast beam, and therefore, the beneficial effects achieved by the above-mentioned optimization method and the beneficial effects of the corresponding schemes in the following detailed description may be referred to and will not be described herein again.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a communication system for broadcasting beams by a base station antenna according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an antenna broadcast beam optimization apparatus according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating an antenna broadcast beam optimization method according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating a method for determining a target beam configuration according to a function value of a target optimization function according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an antenna broadcast beam optimization apparatus according to another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The multiple antenna technology has been applied to various wireless communication systems as an effective means for improving the spectral efficiency and transmission reliability of the system. The more the number of antennas is, the more obvious the improvement of the spectrum efficiency and the reliability of the wireless communication system is. Therefore, the adoption of a multiple-input multiple-output (mu1tip1e-input mu1tip1e-output, MIMO) antenna provides an effective way for greatly improving the capacity of a wireless communication system. However, the introduction of large-scale antennas (massive MIMO) also increases the complexity of wireless communication systems. Further, the passive MIMO also faces the difficulties of diversity of coverage scenes, more complex parameter configuration, and the like in deployment, for example, due to the fact that the number of antennas is too large, the configuration parameters of corresponding antenna beams are also very large, and due to the fact that the beams of the antennas easily interfere with each other to cause power loss, the optimization of the configuration parameters of the antenna broadcast beams of the passive MIMO is more complex.
The current broadcast beam optimization method is as follows: the base station collects the operation performance parameters, customer perception data, configuration parameters and engineering parameters of the antenna in the network. The base station associates the acquired data with the sectors and the relation among the sectors, stores the acquired data according to geogrids, and stores corresponding geographic parameters in advance in each geogrid. And the base station calculates the signal strength and the interference of the geogrid by using an electromagnetic wave transmission loss mathematical model and the configuration parameters and the engineering parameters of the antenna. And the base station determines the grid quality value of each geogrid according to the operation performance parameters in the network, the customer perception data, the configuration parameters and the engineering parameters of the antenna, the calculated signal strength and interference, the current and expected operation indexes of each sector, the current and expected network services and operation conditions and the current and past random faults of the equipment, and further acquires the area quality value of the geographic area consisting of the geogrids. The base station judges whether the acquired area quality value is smaller than the currently recorded area quality value, if so, the acquired area quality value is recorded, whether the area quality value is within a preset area quality value range is judged, if not, the acquired area quality value is abandoned, and the configuration parameters and the engineering parameters of the antenna are adjusted within the adjustable range of the configuration parameters and the engineering parameters. And if the base station determines that the area quality value is within the preset area quality value range, writing the current configuration parameters of the antenna into the electronic file according to the coding formats of different antenna manufacturers, and otherwise, adjusting the configuration parameters and the engineering parameters of the antenna within the adjustable ranges of the configuration parameters and the engineering parameters.
Therefore, firstly, the method is to adjust the configuration parameters of the antenna broadcast beams based on the historical network data and the geogrid of the current user distribution, so that the adjustment is no longer the optimal solution once the future user distribution changes; secondly, the method adjusts the configuration parameters of the antenna broadcast beam according to the network data of the grid of the target area, and cannot represent the network experience of the actual user.
In view of the foregoing problems, an embodiment of the present invention provides an antenna broadcast beam optimization method, where an antenna broadcast beam optimization apparatus predicts a first user distribution, where the first user distribution is a user distribution of a target base station at a time next to a current time. Then, the optimization device of the antenna broadcast beam is further used for querying and obtaining the second user distribution and the beam configuration of the second user distribution in the user distribution information base. The user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution. The second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution. And finally, the optimization device of the antenna broadcast wave beam establishes a target optimization function according to the second user distribution and the preset rule, and adjusts the target wave beam configuration of the antenna broadcast wave beam according to the target optimization function and the wave beam configuration of the second user distribution, so that the wave beam configuration of the antenna broadcast wave beam can be optimized according to the future user distribution, and the user experience is improved.
The embodiment of the application is suitable for a communication system of the broadcast beam of the base station antenna. For example, a massiveMIMO antenna communication system of a base station, or a MIMO antenna communication system.
Fig. 1 shows a structure of communication of a broadcast beam of a base station antenna provided in an embodiment of the present application. As shown in fig. 1, the communication system comprises a base station 11, an antenna broadcast beam 12, and at least one terminal 13. Wherein the base station 11 is capable of providing a communication service to each terminal 13 via an antenna broadcast beam 12.
Specifically, the base station 11 can obtain the network performance index of the user 13 in the process of providing the communication service for the terminal 13. For example, parameters such as Radio Resource Control (RRC) connection success rate, service call drop rate, average uplink and downlink service rate of an air interface, number of bytes of uplink and downlink service of the air interface, average utilization rate of Physical Resource Block (PRB) of uplink and downlink, and Circuit Switched Fallback (CSFB) establishment success rate.
The base station 11 may also provide good communication services for the terminal 13 by adjusting the antenna broadcast beam 12.
The optimization device for the antenna broadcast beam according to the embodiment of the present application may be the base station, or may be a chip system in the base station, which is not limited in the embodiment of the present application. Fig. 2 is a schematic composition diagram of an antenna broadcast beam optimization apparatus provided in the embodiment of the present application, where the antenna broadcast beam optimization apparatus may be used to implement the antenna broadcast beam optimization method provided in the embodiment of the present application.
As shown in fig. 2, the apparatus for optimizing an antenna broadcast beam includes a processor 202, and the processor 202 is configured to execute an application program code, so as to implement the method described in the embodiment of the present application.
The processor 202 may be a general-purpose Central Processing Unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more ics for controlling the execution of programs in accordance with the present disclosure.
As shown in fig. 2, the apparatus for optimizing an antenna broadcast beam may further include a memory 203. The memory 203 is used for storing application program codes for executing the scheme of the application, and the processor 202 controls the execution.
The memory 203 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these. The memory may be self-contained and coupled to the processor via a bus. The memory may also be integral to the processor.
As shown in fig. 2, the apparatus for optimizing an antenna broadcast beam may further include a communication interface 201, wherein the communication interface 201, the processor 202, and the memory 203 may be coupled to each other, for example, via a bus 204. The communication interface 201 is used for information interaction with other devices, for example, information interaction between the optimization apparatus supporting antenna broadcast beams and other devices, for example, data acquisition from other devices or data transmission to other devices.
The following describes a method for optimizing an antenna broadcast beam according to an embodiment of the present application, with reference to the communication system of a base station antenna broadcast beam shown in fig. 1 and the optimization apparatus of an antenna broadcast beam shown in fig. 2.
As shown in fig. 3, the present application provides a method for optimizing an antenna broadcast beam, including the following steps:
301. the optimization means of the antenna broadcast beam generates a user distribution information base.
The optimization device of the antenna broadcast beam firstly establishes and initializes a user distribution information base. Then, the optimization device for the antenna broadcast beam acquires a fourth user distribution of the target base station at a predetermined time in a historical time period and a second beam configuration corresponding to the fourth user distribution. And finally, the optimization device of the antenna broadcast beam stores the fourth user distribution and the second beam configuration of the target base station at a preset time in a historical time period to a user distribution information base. Specifically, the acquiring, by the antenna broadcast beam optimization apparatus, a fourth user distribution of the target base station at a predetermined time in a historical time period includes: firstly, the direction of arrival (direction of arrival) DOA of all users accessed by the target base station at a predetermined time in a historical time period is obtained through a target algorithm. The target algorithm is an algorithm capable of acquiring the DOA of the user of the target base station. Such as MUSIC algorithm, ESPRIT algorithm, etc. And then the optimization device of the antenna broadcast beam calculates the fourth user distribution accessed by the target base station at a preset moment in the historical time period through the DOA of the user accessed by the target base station. The second beam configuration includes parameters of the antenna broadcast beam such as horizontal lobe width, vertical lobe width, azimuth angle, downtilt angle, number of beam sweeps, and the like.
Further, in another optional scheme of the present application, the obtaining a fourth user distribution of the target base station at a predetermined time within a historical time period further includes: acquiring Reference Signal Receiving Power (RSRP) and Path Loss (PL) of all users accessed by a target base station at a preset time in a historical time period; and then, calculating the fourth user distribution accessed by the target base station at a preset time in the historical time period through DOA, RSRP and PL of the user accessed by the target base station.
Secondly, the optimization device of the antenna broadcast beam acquires the DOA of at least one user of the target base station at the current moment. And then, calculating a third user distribution of the target base station according to the DOA of the at least one user, where the method for calculating the third user distribution of the target base station according to the DOA of the at least one user refers to the method for calculating the fourth user distribution, and is not described herein again.
302. The optimizing means of the antenna broadcast beam predicts the first user distribution.
Alternatively, the method for predicting the first user distribution by the antenna broadcast beam optimization device may be to obtain a third user distribution of the target base station at the current time. Then, the optimization device of the antenna broadcast beam inputs the third user distribution into a preset prediction model to obtain the first user distribution.
The method for predicting the first user distribution by the antenna broadcast beam optimization device may also be to acquire historical user distribution in a preset time period and analyze the historical user distribution in the preset time period to determine a rule of the user distribution. Then, the optimization device of the antenna broadcast wave beam obtains the first user distribution according to the rule of the user distribution.
The preset prediction model is generated after the artificial intelligent time series prediction algorithm is input by historical user distribution. Specifically, the antenna broadcast beam optimization apparatus first obtains the historical user distribution of the target base station. The historical user distribution may be obtained from the user distribution information base established in step 301, or the historical user distribution may be recalculated. When the optimization apparatus for antenna broadcast beams obtains historical user distribution from the user distribution information base, in step 301, when storing the fourth user distribution and the second beam configuration of the target base station at a predetermined time within a historical time period in the user distribution information base, the method further includes storing the predetermined time in the user distribution information base. Then, the antenna broadcast beam optimization device takes the historical user distribution at the first moment as the input of an artificial intelligence time sequence prediction algorithm, takes the historical user distribution at the second moment as the output of the artificial intelligence time sequence prediction algorithm, and trains to obtain a preset prediction model. And the second moment is the next moment of the first moment. Specifically, the artificial intelligent time series prediction algorithm is an algorithm capable of learning the historical user distribution, such as a long-short term memory network (LSTM), a differential integrated moving average autoregressive model (ARIMA), and a Prophet.
303. And the optimization device of the antenna broadcast beam inquires and obtains the second user distribution and the beam configuration of the second user distribution in the user distribution information base.
The user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution. The second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution.
Specifically, if the optimization device of the antenna broadcast beam finds the user distribution same as the first user distribution in the user distribution information base, the user distribution same as the first user distribution is used as the second user distribution; and if the user distribution which is the same as the first user distribution is not found in the user distribution information base, taking the user distribution which is most similar to the first user distribution as the second user distribution.
304. And the optimization device of the antenna broadcast beam establishes a target optimization function according to the second user distribution and the preset rule.
305. And the optimization device of the antenna broadcast beam adjusts the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration distributed by the second user.
Specifically, referring to fig. 4, the present application provides a method for determining a target beam configuration according to a function value of a target optimization function, including the following steps:
401. and the optimization device of the antenna broadcast beam acquires the received signal strength, the signal-to-interference-and-noise ratio, the access delay and the access success rate of the users in the second user distribution.
Wherein, the received signal strength of the user is used to represent the signal quality condition, for example, it can be embodied by using RSRP of the user; the access success rate of the user is used to indicate the probability of success of the user accessing the base station, and may be embodied by using an RRC connection success rate, for example.
4011. And the optimization device of the antenna broadcast beam establishes a target optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access delay and the access success rate of the users in the second user distribution.
Specifically, in an optional scheme of the present application, after obtaining the received signal strength, the signal to interference plus noise ratio (SINR), the access delay, and the access success rate of the user in the second user distribution, normalization processing needs to be performed on the received signal strength, the SINR, the access delay, and the access success rate of the user.
Wherein the objective optimization function satisfies the formula
Wherein J represents an objective optimization function, u represents users in the second user distribution, Nu represents a total number of users in the second user distribution, RSRPuIndicating the received signal strength, SINR, of the useruRepresenting the signal-to-interference-and-noise ratio (delay) of the useru)-1Indicates the access delay of the user, success accessuIndicates the access success rate, W, of the user1Weights, W, representing the received signal strength of the users2Weights, W, representing the SINR of the users3Weights, W, representing access delays of users4Weight representing access success rate of user, wherein W1，W2，W3，W4Being preconfigured, e.g. W1，W2，W3，W4Is a default value, a value set by a manager according to experience, and the like, and W is more than or equal to 01≤1，0≤W2≤1，0≤W3≤1，0≤W4≤1。
4012. And the optimization device of the antenna broadcast beam calculates an actual function value Jreal of the target optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access delay and the access success rate of the users in the second user distribution.
Specifically, the optimization device of the antenna broadcast beam is based on a formula
Calculating actual function values of the objective optimization functions of the users in the second user distribution, wherein,
actual function values representing objective optimization functions of users in the second user distribution, u representing users in the second user distribution, Nu representing a total number of users in the second user distribution, RSRPuRepresenting received signal strength, SINR, of users in a second user distributionuRepresenting the SINR (Signal to interference plus noise ratio) of users in the second user distribution (relay)u)-1Representing the access delay, successful access, of users in the second user profileuRepresenting access of users in a second user distributionSuccess rate, W1Weights, W, representing received signal strengths of users in a second user distribution2Weights, W, representing the SINR of the users in the second user distribution3Weights, W, representing access delays of users in a second user distribution4A weight representing access success rate of users in a second user distribution, wherein W1，W2，W3，W4Being preconfigured, e.g. W1，W2，W3，W4Is a default value, a value set by a manager according to experience, and the like, and W is more than or equal to 01≤1，0≤W2≤1，0≤W3≤1，0≤W4≤1。
402. The optimization device of the antenna broadcast beam takes the beam configuration distributed by the second user as the initial value of the beam configuration optimization search, and the solution of the beam configuration optimization is searched in a distributed mode.
The solution of beam configuration optimization includes parameters of antenna broadcast beams such as horizontal lobe width, vertical lobe width, azimuth angle, downtilt angle, beam scanning number and the like.
Specifically, the optimization device for the antenna broadcast beam uses the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and searches a solution of beam configuration optimization in a distributed manner according to a predetermined motion rule. Wherein the predetermined motion rule satisfies a formula
Wherein, thetai(j +1) denotes a predetermined movement rule. And c (i) represents a search moving step size, which is preconfigured, for example, a default value, a value set by an administrator according to experience, and the like, wherein the smaller the search moving step size, the more accurate the searched solution for beam configuration optimization is. Δ (i) represents a random direction vector. Thetai(j) A predetermined motion rule representing the last search movement. i represents the number of times the solution for beam configuration optimization is searched. j denotes the number of search moves, which is preconfigured, e.g., a default value, a value set empirically by a manager, etc. Wherein, when the search moving times reaches the preset times, the search is stopped。
More specifically, the solution of the beam configuration optimization is searched in a distributed manner, that is, the solution of the beam configuration optimization is searched simultaneously in different directions at the same time by using a predetermined motion rule.
Further, in another optional scheme of the present application, the optimization apparatus for antenna broadcast beams uses the beam configuration distributed by the second user as an initial value for beam configuration optimization search, and searches a solution of beam configuration optimization in a distributed manner according to a predetermined motion rule. Wherein the predetermined motion rule satisfies a formula
Wherein, thetai(j +1, k, l) denotes a predetermined motion rule, C (i) denotes a search moving step, Δ (i) denotes a random direction vector, θi(j, k, l) represents a predetermined motion rule of the last search move, i represents the number of times the solution of the beam configuration optimization is searched, j represents the number of search moves, k represents the number of times of copying, and l represents the number of times of deletion. Wherein, the copying times and the deleting times are pre-configured. For example, a default value, a value set by an administrator based on experience, and the like. And stopping searching when the search moving times reach the preset times and the copying times and the deleting times reach the preset copying and deleting times.
403. The optimization device of the antenna broadcast beam calculates the solution of the optimization of the beam configuration of each distributed search and the prediction function value of the corresponding target optimization function.
Specifically, the antenna broadcast beam optimization device calculates the predicted received signal strength, the predicted signal to interference and noise ratio, the predicted access delay, and the predicted access success rate of the user in the second user distribution according to the beam configuration optimization solution obtained after distributed search in step 402, the second user distribution, and the antenna gain of the base station, and then calculates the predicted function value of the target optimization function according to the predicted received signal strength, the predicted signal to interference and noise ratio, the predicted access delay, and the predicted access success rate of the user in the second user distribution.
Further, in another optional scheme of the present application, after the optimization device for antenna broadcast beams calculates a prediction function value of the objective optimization function corresponding to a solution of each distributed searched beam configuration optimization, the prediction function value of the objective optimization function needs to be copied and deleted. The method specifically comprises the following steps: the optimization device of the antenna broadcast beam firstly sorts the prediction function values of the target optimization function according to a preset sorting rule. And then obtaining a beam configuration optimization solution corresponding to the prediction function value of the target optimization function before the preset ordering, namely copying the beam configuration optimization solution corresponding to the prediction function value of the target optimization function before the preset ordering, and deleting the beam configuration optimization solution corresponding to the prediction function value of the target optimization function after the preset ordering. And finally, continuing to perform distributed search according to the search direction of the solution of the beam configuration optimization corresponding to the prediction function value of the target optimization function before the preset sequencing.
404. The optimization device of the antenna broadcast beam obtains the maximum function value Jmax in the prediction function values of the target optimization function, obtains a solution of distributed search beam configuration optimization corresponding to the Jmax, and generates a first beam configuration.
4041. And if the optimization device of the antenna broadcast beam determines that Jmax is less than Jreal, the beam configuration distributed by the second user is used as the target beam configuration after the antenna broadcast beam is optimized.
4042. And if the optimization device of the antenna broadcast beam determines that Jreal is less than Jmax, setting a corresponding weight value for the first beam configuration, and adjusting the beam shape and the scanning sequence of the antenna broadcast beam to be used as the target beam configuration after the antenna broadcast beam is optimized.
The weight value is preconfigured, for example, the weight value is a default value, a value set by a manager according to experience, and the like.
Further, in another optional scheme of the present application, if the optimization device of the antenna broadcast beam determines that the first user distribution is the same as the second user distribution, the beam configuration of the second user distribution is used as the target beam configuration after the antenna broadcast beam is optimized.
And after the target beam configuration after the antenna broadcast beam optimization is obtained, adjusting the beam configuration of the base station according to the target beam configuration to complete the adjustment of the antenna broadcast beam of the base station.
In the scheme, first user distribution is predicted, wherein the first user distribution is the user distribution of the target base station at the next moment of the current moment; inquiring and obtaining second user distribution and beam configuration of the second user distribution in a user distribution information base; the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; the second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution; establishing a target optimization function according to the second user distribution and a preset rule; and adjusting the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration of the second user distribution. Therefore, firstly, the method predicts the user distribution of the target base station at the next moment of the current moment, and then adjusts the beam configuration of the antenna broadcast beam after establishing the target optimization function according to the user distribution. When the beam configuration of the antenna broadcast beam is adjusted, the predicted user distribution is used as a necessary parameter for adjustment, and adjustment optimization can be ensured after the future user distribution is considered when the beam configuration is adjusted. When the future user distribution changes, the adjustment of the future user distribution is considered, so that the accuracy of the beam optimization adjustment can be improved. Secondly, in the method and the device, the target optimization function is established according to the second user distribution, the target beam configuration of the antenna broadcast beam is adjusted according to the target optimization function and the beam configuration of the second user distribution, the beam configuration of the antenna broadcast beam can be correspondingly adjusted according to the user side requirement, and the user experience is improved.
In the embodiment of the present invention, the functional modules of the optimization apparatus for antenna broadcast beams may be divided according to the above method embodiment, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, the division of the modules in the embodiment of the present invention is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Referring to fig. 5, the present application provides an apparatus for optimizing an antenna broadcast beam, including:
a predicting module 51, configured to predict a first user distribution, where the first user distribution is a user distribution of a target base station at a next time of a current time; the prediction module 51 is configured to query and obtain a second user distribution and a beam configuration of the second user distribution in a user distribution information base; wherein, the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; the second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution; the processing module 53 is configured to establish an objective optimization function according to the second user distribution and a preset rule queried by the prediction module 51; the processing module 53 is further configured to adjust a target beam configuration of an antenna broadcast beam according to the target optimization function and the beam configuration of the second user profile.
Optionally, the prediction module 51 is specifically configured to obtain a third user distribution of the target base station at the current time; the prediction module 51 is specifically configured to input the third user distribution into a preset prediction model to obtain the first user distribution.
Optionally, the processing module 53 is specifically configured to obtain received signal strength, a signal-to-interference-and-noise ratio, an access delay, and an access success rate of the users in the second user distribution; the processing module 53 is specifically configured to establish an objective optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access delay, and the access success rate of the users in the second user distribution, where the objective optimization function satisfies a formula
Wherein the content of the first and second substances,
representing the objectAn optimization function, u representing users in the third user distribution, Nu representing a total number of users in the third user distribution, RSRPuIndicating the received signal strength, SINR, of said useruRepresenting the signal-to-interference-and-noise ratio (delay) of said useru)-1Representing the access delay of the user, success accessuIndicating the access success rate, W, of said user1Weight, W, representing the received signal strength of said user2Weight, W, representing the SINR of said user3Weight, W, representing the access delay of said user4A weight representing an access success rate of the user.
Optionally, the processing module 53 is specifically configured to calculate an actual function value Jreal of the objective optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access delay, and the access success rate of the users in the second user distribution; the processing module 53 is specifically configured to use the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and search a solution of beam configuration optimization in a distributed manner; the processing module 53 is specifically configured to calculate a solution of beam configuration optimization for each distributed search, and a prediction function value of the corresponding target optimization function; the processing module 53 is specifically configured to obtain a maximum function value Jmax in the prediction function values of the target optimization function, and obtain a solution of distributed search beam configuration optimization corresponding to the Jmax, to generate a first beam configuration; the processing module 53 is specifically configured to, if it is determined that Jmax is less than Jreal, use the beam configuration distributed by the second user as the target beam configuration after the antenna broadcast beam is optimized; the processing module 53 is specifically configured to set a corresponding weight for the first beam configuration and adjust the beam shape and the scanning order of the antenna broadcast beam to serve as the target beam configuration after the antenna broadcast beam is optimized if it is determined that Jreal is less than Jmax.
Optionally, the processing module 53 is specifically configured to use the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and search a solution of beam configuration optimization in a distributed manner according to a predetermined motion rule, where the predetermined motion rule satisfies a formula
Wherein, thetai(j +1) represents the predetermined motion rule, C (i) represents a search move step, Δ (i) represents a random direction vector, θi(j) A predetermined motion rule indicating the last search movement, i indicates the number of times the solution for the beam configuration optimization is searched, and j indicates the number of search movements.
Optionally, the processing module 53 is specifically configured to use the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and search a solution of beam configuration optimization in a distributed manner according to a predetermined motion rule, where the predetermined motion rule satisfies a formula
Wherein, thetai(j +1, k, l) represents the predetermined motion rule, C (i) represents a search move step, Δ (i) represents a random direction vector, θi(j, k, l) represents a predetermined motion rule of the last search move, i represents the number of times the solution of the beam configuration optimization is searched, j represents the number of search moves, k represents the number of copies, and l represents the number of deletions.
Optionally, the processing module 53 is further configured to sort the prediction function values of the target optimization function according to a predetermined sorting rule; the processing module 53 is further configured to obtain a solution of beam configuration optimization corresponding to a prediction function value of the target optimization function before the predetermined ordering; the processing module 53 is further configured to continue the distributed search according to the search direction of the solution of the beam configuration optimization corresponding to the prediction function value of the target optimization function before the predetermined ordering.
Optionally, the processing module 53 is further configured to, if it is determined that the first user distribution is the same as the second user distribution, use the beam configuration of the second user distribution as the target beam configuration after the antenna broadcast beam is optimized.
Optionally, the prediction module 51 is specifically configured to obtain a direction of arrival DOA of at least one user of the target base station at the current time; the predicting module 51 is specifically configured to calculate a third user distribution of the target base station according to the DOA of the at least one user.
Optionally, the optimizing apparatus further includes: an obtaining module 54, configured to obtain historical user distribution of the target base station; the obtaining module 54 is further configured to train to obtain the preset prediction model by taking the historical user distribution at the first time as an input of an artificial intelligence time series prediction algorithm and taking the historical user distribution at the second time as an output of the artificial intelligence time series prediction algorithm, where the second time is a next time of the first time.
The functions of the obtaining module 54, the predicting module 51, the querying module 52 and the processing module 53 are the same as those of the processor 202 in fig. 2.
Further, the present application also provides a computer-readable storage medium (or media) comprising instructions which, when executed, perform the operations of the method for optimizing an antenna broadcast beam in the above-described embodiments. Additionally, a computer program product is also provided, comprising the above-described computer-readable storage medium (or media).
All relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and the function thereof is not described herein again.
It should be understood that, in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Those of ordinary skill in the art would appreciate that the various illustrative modules, elements, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. For example, the device embodiments described above are merely illustrative, e.g., multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (23)
1. A method for optimizing an antenna broadcast beam,
predicting first user distribution, wherein the first user distribution is the user distribution of a target base station at the next moment of the current moment;
inquiring and obtaining second user distribution and beam configuration of the second user distribution in a user distribution information base; wherein, the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; the second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution;
establishing a target optimization function according to the second user distribution and a preset rule;
and adjusting the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration of the second user distribution.
2. The optimization method of claim 1, wherein predicting the first user distribution comprises:
acquiring third user distribution of the target base station at the current moment;
and inputting the third user distribution into a preset prediction model to obtain the first user distribution.
3. The optimization method according to claim 1, wherein the establishing an objective optimization function according to the second user distribution and a preset rule comprises:
acquiring the received signal strength, the signal-to-interference-and-noise ratio, the access delay and the access success rate of the users in the second user distribution;
establishing an objective optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access time delay and the access success rate of the users in the second user distribution, wherein the objective optimization function meets the formula
J represents the objective optimization function, u represents users in the third user distribution, Nu represents the total number of users in the third user distribution, RSRPuIndicating the received signal strength, SINR, of said useruRepresenting the signal-to-interference-and-noise ratio (delay) of said useru)-1Representing the access delay of the user, success accessuIndicating the access success rate, W, of said user1Weight, W, representing the received signal strength of said user2Weight, W, representing the SINR of said user3Weight, W, representing the access delay of said user4A weight representing an access success rate of the user.
4. The optimization method according to claim 3, wherein the adjusting the target beam configuration of the antenna broadcast beam according to the target optimization function and the beam configuration of the second user profile comprises:
calculating an actual function value Jreal of the objective optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access delay and the access success rate of the users in the second user distribution;
taking the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and searching a solution of beam configuration optimization in a distributed mode;
calculating a solution of each distributed searching beam configuration optimization, and a corresponding prediction function value of the target optimization function;
acquiring a maximum function value Jmax in the prediction function values of the target optimization function, and acquiring a solution of distributed search beam configuration optimization corresponding to the Jmax to generate a first beam configuration;
if Jmax is less than Jreal, the beam configuration distributed by the second user is used as the target beam configuration after the antenna broadcast beam is optimized;
and if Jreal < Jmax is determined, setting a corresponding weight value for the first beam configuration, and adjusting the beam shape and the scanning sequence of the antenna broadcast beam to be used as the target beam configuration after the antenna broadcast beam is optimized.
5. The optimization method according to claim 4, wherein the taking the beam configuration of the second user distribution as an initial value of a beam configuration optimization search, the distributed search for a solution of beam configuration optimization comprises:
taking the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and searching a solution of beam configuration optimization in a distributed manner according to a preset motion rule, wherein the preset motion rule meets a formula
θi(j +1) represents the predetermined motion rule, C (i) represents a search move step, Δ (i) represents a random direction vector, θi(j) A predetermined motion rule indicating the last search movement, i indicates the number of times the solution for the beam configuration optimization is searched, and j indicates the number of search movements.
6. The optimization method according to claim 4, wherein the taking the beam configuration of the second user distribution as an initial value of a beam configuration optimization search, the distributed search for a solution of beam configuration optimization comprises:
taking the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and searching a solution of beam configuration optimization in a distributed manner according to a preset motion rule, wherein the preset motion rule meets a formula
θi(j +1, k, l) represents the predetermined motion rule, C (i) represents a search move step, Δ (i) represents a random direction vector, θi(j, k, l) represents a predetermined motion rule of the last search move, i represents the number of times the solution of the beam configuration optimization is searched, j represents the number of search moves, k represents the number of copies, and l represents the number of deletions.
7. The optimization method of claim 6, wherein the calculating a solution of the beam configuration optimization for each distributed search further comprises, after the corresponding prediction function value of the objective optimization function:
sorting the prediction function values of the target optimization function according to a preset sorting rule;
obtaining a wave beam configuration optimization solution corresponding to a prediction function value of a target optimization function before the preset sequencing;
and continuing to perform distributed search according to the search direction of the solution of the beam configuration optimization corresponding to the prediction function value of the target optimization function before the preset sequencing.
8. The optimization method of claim 1, wherein if it is determined that the first user distribution is the same as the second user distribution, the optimization method further comprises:
and taking the beam configuration distributed by the second user as the target beam configuration after the antenna broadcasting beam is optimized.
9. The optimization method of claim 2, wherein the obtaining the third user distribution of the target base station at the current time comprises:
acquiring the DOA (direction of arrival) of at least one user of a target base station at the current moment;
and calculating the third user distribution of the target base station according to the DOA of the at least one user.
10. The optimization method of claim 2, further comprising:
acquiring historical user distribution of a target base station;
and training to obtain the preset prediction model by taking the historical user distribution at the first moment as the input of the artificial intelligence time series prediction algorithm and taking the historical user distribution at the second moment as the output of the artificial intelligence time series prediction algorithm, wherein the second moment is the next moment of the first moment.
11. An apparatus for optimizing an antenna broadcast beam, comprising:
the device comprises a prediction module, a prediction module and a processing module, wherein the prediction module is used for predicting first user distribution, and the first user distribution is the user distribution of a target base station at the next moment of the current moment;
the query module is used for querying and obtaining second user distribution and beam configuration of the second user distribution in a user distribution information base; wherein, the user distribution information base comprises at least one historical user distribution and the beam configuration of each historical user distribution in the at least one historical user distribution; the second user distribution is the historical user distribution with the highest similarity with the first user distribution in the at least one historical user distribution;
the processing module is used for establishing a target optimization function according to the second user distribution and the preset rule inquired by the inquiry module;
the processing module is further configured to adjust a target beam configuration of an antenna broadcast beam according to the target optimization function and the beam configuration of the second user distribution.
12. The optimization device of claim 11,
the prediction module is specifically used for acquiring the third user distribution of the target base station at the current moment;
the prediction module is specifically configured to input the third user distribution into a preset prediction model to obtain the first user distribution.
13. The apparatus for optimizing antenna broadcast beams according to claim 11,
the processing module is specifically configured to obtain the received signal strength, the signal-to-interference-and-noise ratio, the access delay, and the access success rate of the users in the second user distribution;
the processing module is specifically configured to establish an objective optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access delay, and the access success rate of the users in the second user distribution, where the objective optimization function satisfies a formula
14. The optimization device of claim 13,
the processing module is specifically configured to calculate an actual function value Jreal of the objective optimization function according to the received signal strength, the signal-to-interference-and-noise ratio, the access delay, and the access success rate of the users in the second user distribution;
the processing module is specifically configured to use the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and search a solution of beam configuration optimization in a distributed manner;
the processing module is specifically configured to calculate a solution of beam configuration optimization for each distributed search, and a prediction function value of the corresponding target optimization function;
the processing module is specifically configured to obtain a maximum function value Jmax in the prediction function values of the target optimization function, obtain a solution for optimizing the distributed search beam configuration corresponding to the Jmax, and generate a first beam configuration;
the processing module is specifically configured to, if it is determined that Jmax is less than Jreal, use the beam configuration distributed by the second user as a target beam configuration after antenna broadcast beam optimization;
the processing module is specifically configured to set a corresponding weight for the first beam configuration, and adjust a beam shape and a scanning sequence of the antenna broadcast beam to serve as the optimized target beam configuration of the antenna broadcast beam if it is determined that Jreal is less than Jmax.
15. The optimization device of claim 14,
the processing module is specifically configured to use the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and search a solution of beam configuration optimization in a distributed manner according to a predetermined motion rule, where the predetermined motion rule satisfies a formula
θi(j +1) represents the predetermined motion rule, C (i) represents a search move step, Δ (i) represents a random direction vector, θi(j) Indicating a predetermined motion rule of the last search movement, i indicatesThe number of times the solution of the beam configuration optimization is searched, j represents the number of search moves.
16. The optimization device of claim 14,
the processing module is specifically configured to use the beam configuration distributed by the second user as an initial value of beam configuration optimization search, and search a solution of beam configuration optimization in a distributed manner according to a predetermined motion rule, where the predetermined motion rule satisfies a formula
θi(j +1, k, l) represents the predetermined motion rule, C (i) represents a search move step, Δ (i) represents a random direction vector, θi(j, k, l) represents a predetermined motion rule of the last search move, i represents the number of times the solution of the beam configuration optimization is searched, j represents the number of search moves, k represents the number of copies, and l represents the number of deletions.
17. The optimization device of claim 16,
the processing module is further configured to sort the prediction function values of the target optimization function according to a predetermined sorting rule;
the processing module is further configured to obtain a solution of beam configuration optimization corresponding to a prediction function value of the target optimization function before the predetermined ordering;
the processing module is further configured to continue the distributed search according to the search direction of the solution of the beam configuration optimization corresponding to the prediction function value of the target optimization function before the predetermined ordering.
18. The optimization device of claim 11,
the processing module is further configured to, if it is determined that the first user distribution is the same as the second user distribution, use the beam configuration of the second user distribution as a target beam configuration after antenna broadcast beam optimization.
19. The optimization device of claim 12,
the prediction module is specifically configured to obtain a direction of arrival (DOA) of at least one user of the target base station at the current time;
the prediction module is specifically configured to calculate a third user distribution of the target base station according to the DOA of the at least one user.
20. The optimization device of claim 12, further comprising:
the acquisition module is used for acquiring historical user distribution of the target base station;
the acquisition module is further configured to train to obtain the preset prediction model by taking the historical user distribution at the first time as input of an artificial intelligence time series prediction algorithm and taking the historical user distribution at the second time as output of the artificial intelligence time series prediction algorithm, where the second time is a next time of the first time.
21. An antenna broadcast beam optimization apparatus, comprising a processor executing computer executable instructions to cause the antenna broadcast beam optimization apparatus to perform the antenna broadcast beam optimization method according to any one of claims 1 to 10 when the antenna broadcast beam optimization apparatus is in operation.
22. A computer-readable storage medium comprising instructions which, when run on a computer, cause the computer to perform a method of optimizing an antenna broadcast beam according to any one of claims 1-10.
23. A computer program product, characterized in that it comprises instruction code for performing a method of optimization of an antenna broadcast beam according to any one of claims 1-10.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911342705.0A CN111082840B (en) | 2019-12-23 | 2019-12-23 | Method and device for optimizing antenna broadcast beam |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911342705.0A CN111082840B (en) | 2019-12-23 | 2019-12-23 | Method and device for optimizing antenna broadcast beam |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111082840A true CN111082840A (en) | 2020-04-28 |
| CN111082840B CN111082840B (en) | 2021-06-18 |
Family
ID=70317079
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911342705.0A Active CN111082840B (en) | 2019-12-23 | 2019-12-23 | Method and device for optimizing antenna broadcast beam |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111082840B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114978253A (en) * | 2021-02-26 | 2022-08-30 | 中国电信股份有限公司 | Method, apparatus and storage medium for broadcast beam optimization |
| WO2023134650A1 (en) * | 2022-01-14 | 2023-07-20 | 维沃移动通信有限公司 | Information interaction method and apparatus, and communication device |
| WO2024031658A1 (en) * | 2022-08-12 | 2024-02-15 | Qualcomm Incorporated | Auxiliary reference signal for predictive model performance monitoring |
| WO2024067097A1 (en) * | 2022-09-29 | 2024-04-04 | 中兴通讯股份有限公司 | Model training method and apparatus, cell antenna adjustment method and apparatus, and electronic device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105375959A (en) * | 2015-10-14 | 2016-03-02 | 西安交通大学 | Distributed interference coordination method based on beam shape matching in 3D-MIMO system |
| US20170085329A1 (en) * | 2015-06-17 | 2017-03-23 | Hughes Network Systems, Llc | High speed, high terrestrial density global packet data mobile satellite system architectures |
| US20170195018A1 (en) * | 2016-01-04 | 2017-07-06 | Futurewei Technologies, Inc. | Radio frequency distribution network for a split beam user specific tilt antenna |
| CN109699037A (en) * | 2017-10-24 | 2019-04-30 | 中国移动通信有限公司研究院 | A kind of wave beam disconnection determines configuration method, determination method and device |
| CN109982350A (en) * | 2017-12-28 | 2019-07-05 | 中国移动通信集团山东有限公司 | A kind of MPS process self-adapting regulation method and device |
| CN110048755A (en) * | 2019-04-09 | 2019-07-23 | 深圳大学 | A kind of millimetre-wave attenuator method and communication system |
-
2019
- 2019-12-23 CN CN201911342705.0A patent/CN111082840B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170085329A1 (en) * | 2015-06-17 | 2017-03-23 | Hughes Network Systems, Llc | High speed, high terrestrial density global packet data mobile satellite system architectures |
| CN105375959A (en) * | 2015-10-14 | 2016-03-02 | 西安交通大学 | Distributed interference coordination method based on beam shape matching in 3D-MIMO system |
| US20170195018A1 (en) * | 2016-01-04 | 2017-07-06 | Futurewei Technologies, Inc. | Radio frequency distribution network for a split beam user specific tilt antenna |
| CN109699037A (en) * | 2017-10-24 | 2019-04-30 | 中国移动通信有限公司研究院 | A kind of wave beam disconnection determines configuration method, determination method and device |
| CN109982350A (en) * | 2017-12-28 | 2019-07-05 | 中国移动通信集团山东有限公司 | A kind of MPS process self-adapting regulation method and device |
| CN110048755A (en) * | 2019-04-09 | 2019-07-23 | 深圳大学 | A kind of millimetre-wave attenuator method and communication system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114978253A (en) * | 2021-02-26 | 2022-08-30 | 中国电信股份有限公司 | Method, apparatus and storage medium for broadcast beam optimization |
| WO2023134650A1 (en) * | 2022-01-14 | 2023-07-20 | 维沃移动通信有限公司 | Information interaction method and apparatus, and communication device |
| WO2024031658A1 (en) * | 2022-08-12 | 2024-02-15 | Qualcomm Incorporated | Auxiliary reference signal for predictive model performance monitoring |
| WO2024067097A1 (en) * | 2022-09-29 | 2024-04-04 | 中兴通讯股份有限公司 | Model training method and apparatus, cell antenna adjustment method and apparatus, and electronic device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111082840B (en) | 2021-06-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111082840B (en) | Method and device for optimizing antenna broadcast beam | |
| CN109379752B (en) | Massive MIMO optimization method, device, equipment and medium | |
| US7120431B1 (en) | System and method for adjusting antenna radiation in a wireless network | |
| CN103988526B (en) | Method for carrying out beam forming in self-organizing network (SON) | |
| US8897767B2 (en) | Parameter setting apparatus and parameter setting method | |
| CN112260731B (en) | Antenna weight optimization method based on ant colony algorithm | |
| US8150413B2 (en) | Radio network designing apparatus and method | |
| CN104584622A (en) | Method and system for cellular network load balance | |
| CN110401956A (en) | Coverage evaluating method and apparatus | |
| US9345032B2 (en) | Method and apparatus for determining network clusters for wireless backhaul networks | |
| CN110350965B (en) | Beam switching method and device and mobile terminal | |
| CN108064075B (en) | Method and apparatus for adjusting reference signal transmit power of one or more cells | |
| JP2002095040A (en) | Method and apparatus for design, adjustment or operation of wireless network by using pre-frequency- assignment optimization | |
| US7844698B2 (en) | Wireless network modification support system and radio network modification support method | |
| CN112385151A (en) | Beam forming method and device, base station and storage medium | |
| WO2021013367A1 (en) | Kpi-based tilt range selection | |
| CN112950243A (en) | 5G station address planning method and device, electronic equipment and storage medium | |
| CN107431937B (en) | Adaptive sector configuration for adaptive antenna system | |
| CN108271184B (en) | VoLTE service processing method and device | |
| CN108200655B (en) | Channel selection method and device | |
| KR20210057302A (en) | Server, method and computer program for calculating path loss | |
| CN112351449B (en) | Massive MIMO single-cell weight optimization method | |
| Tomforde et al. | Load-aware reconfiguration of LTE-antennas dynamic cell-phone network adaptation using organic network control | |
| CN116488747A (en) | Information interaction method and device and communication equipment | |
| CN107396325B (en) | Neighbor extraction system, method and related device of wireless access point |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |