CN114339971A - Base station energy-saving control method and device, storage medium and electronic equipment - Google Patents
Base station energy-saving control method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The disclosure provides a base station energy-saving control method, a base station energy-saving control device, a storage medium and electronic equipment, relates to the technical field of communication, and aims to solve the problem that user experience cannot be guaranteed on the basis of saving energy for a base station in the related art. The related base station energy-saving control method comprises the following steps: acquiring train information, historical load information of a serving cell and an adjacent cell and measurement information of the serving cell and the adjacent cell in a target area; determining energy-saving control strategies of the base stations of the serving cell and the adjacent cell according to the train information, the historical load information and the measurement information, wherein the energy-saving control strategies are used for carrying out energy-saving control on the base stations; and issuing the energy-saving control strategy to a target base station, wherein the target base station is a base station which needs to perform energy-saving control in the service cell and the adjacent cell. The embodiment of the disclosure can realize the purpose of saving energy and reducing consumption of the base station.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a method and an apparatus for controlling energy saving of a base station, a storage medium, and an electronic device.
Background
Currently, with the increase of the scale of high-speed rail users and the increase of the energy consumption of the 5G (5th Generation Mobile Communication Technology, fifth Generation Mobile Communication Technology) base station itself, the effective reduction of the energy consumption of the high-speed rail private network base station is one of the currently important tasks of the operators.
The traditional high-iron base station energy-saving technology is usually realized by the cooperative scheduling of a public network and a private network, the radio frequency power of private network cells is raised temporarily when a train comes, the resource scheduling of the surrounding public network cells is limited, and the interference of the public network to the private network is reduced; and after the train leaves, reducing the radio frequency power of the private network cell to zero and sleeping the cell. The energy-saving mode has a single form and poor flexibility, the energy-saving purpose can be achieved only through the dormant base station, the energy-saving efficiency is low, and the public network user experience is influenced to a certain degree. Another way to save energy is by manually setting a threshold value, for example, setting a threshold of the number of connectable users that can be tolerated when the channel is turned off and activated. The parameter setting of the mode is conservative, and the mode cannot cope with changeable environments, so that the energy-saving effect is very limited.
Disclosure of Invention
The present disclosure provides a base station energy saving control method, apparatus, storage medium, and electronic device, which at least overcome, to some extent, a problem in the related art that user experience cannot be guaranteed on the basis of saving energy for a base station.
According to a first aspect of the present disclosure, there is provided a base station energy saving control method, including: acquiring train information, historical load information of a serving cell and an adjacent cell and measurement information of the serving cell and the adjacent cell in a target area; determining energy-saving control strategies of the base stations of the serving cell and the adjacent cell according to the train information, the historical load information and the measurement information, wherein the energy-saving control strategies are used for carrying out energy-saving control on the base stations; and issuing the energy-saving control strategy to a target base station, wherein the target base station is a base station which needs to perform energy-saving control in the service cell and the adjacent cell.
Optionally, determining the energy saving control strategies of the base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information includes: predicting the time of the train reaching the target area according to the train information; predicting the load of the base station according to the time of the train reaching the target area, the historical load information and the measurement information; and determining a target energy-saving control strategy of the base station according to the load of the base station and the time of the train reaching the target area.
Optionally, determining the energy saving control strategies of the base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information includes: clustering the energy-saving scenes of the base stations according to the historical load information and the measurement information to obtain clustering results; determining a historical energy-saving control strategy corresponding to a historical energy-saving scene similar to the current energy-saving scene of the base station; and determining the historical energy-saving control strategy as a target energy-saving control strategy of the base station, or determining the target energy-saving control strategy of the base station according to the historical energy-saving control strategy, the load of the base station and the time of the train reaching the target area.
Optionally, the measurement information at least includes one of: reference signal received power, RSRP, reference signal received quality, RSRQ, signal to interference plus noise ratio, SINR, quality of service, QoS, quality of experience, QoE, and uplink and downlink packet delay.
Optionally, the train information at least includes one of the following: train schedule, train movement direction, and train movement rate.
Optionally, the energy saving control strategy includes: the number of a target cell which needs to enter an energy-saving state and an energy-saving control strategy corresponding to the target cell, wherein the energy-saving control strategy corresponding to the target cell at least comprises one of the following strategies: subframe shutdown, symbol shutdown, channel shutdown, carrier shutdown, deep base station sleep, and device shutdown.
Optionally, the energy-saving control strategy corresponding to the target cell further includes: a recommended cell that takes over the cell entering the energy saving state and the energy saving state duration.
Optionally, the base station includes a central unit CU and a distribution unit DU, and issuing the energy-saving control policy to the target base station includes: and transmitting the energy-saving control strategy to the DU of the target base station.
According to the second aspect of the present disclosure, there is also provided a base station energy saving control apparatus, including: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring train information in a target area, historical load information of a serving cell and an adjacent cell and measurement information of the serving cell and the adjacent cell; a determining module, configured to determine energy saving control policies of base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information, where the energy saving control policies are used to perform energy saving control on the base stations; and the issuing module is used for issuing the energy-saving control strategy to a target base station, wherein the target base station is a base station which needs to perform energy-saving control in the service cell and the adjacent cell.
According to a third aspect of the present disclosure, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the base station energy saving control methods provided by the embodiments of the present disclosure through executing the executable instructions.
According to a fourth aspect of the present disclosure, there is also provided a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements any one of the base station energy saving control methods provided by the embodiments of the present disclosure.
According to the base station energy-saving control method, the base station energy-saving control device, the storage medium and the electronic equipment in the embodiments of the disclosure, the energy-saving control strategy of the base station of the serving cell and the adjacent cell can be determined according to the train information in the target area, the historical load information of the serving cell and the adjacent cell and the measurement information of the serving cell and the adjacent cell, and the energy-saving control strategy is issued to the corresponding base station, so that the purpose of saving energy and reducing consumption of the base station can be achieved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
Fig. 1 is a flowchart of a base station energy saving control method according to one or more embodiments of the present disclosure;
fig. 2 is a flowchart of determining an energy saving control strategy of base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information according to one or more embodiments of the present disclosure;
fig. 3 is a flowchart of determining an energy saving control strategy of base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information, according to one or more embodiments of the present disclosure;
fig. 4 is a schematic diagram of an AI network architecture in accordance with one or more embodiments of the present disclosure;
fig. 5 is a schematic diagram of an AI network architecture in accordance with one or more embodiments of the present disclosure;
fig. 6 is an AI energy saving diagram based on a high-speed rail private network separation architecture base station according to one or more embodiments of the present disclosure;
fig. 7 is a schematic structural diagram of a base station energy saving control apparatus according to one or more embodiments of the present disclosure; and
fig. 8 is a schematic structural diagram of an electronic device according to one or more embodiments of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
Fig. 1 is a flowchart of a base station energy saving control method according to one or more embodiments of the present disclosure, as shown in fig. 1, the method includes:
step S102: acquiring train information, historical load information of a serving cell and an adjacent cell and measurement information of the serving cell and the adjacent cell in a target area;
optionally, the target area may include a preset area range corresponding to a certain train stop of the train, the train information may include train information to pass through the target area, and the train information may be reported by a communication device of the train. Illustratively, the train may be a high-speed rail train. The measurement information of the serving cell and the neighbor cells may be measured by the terminal.
Step S104: determining energy-saving control strategies of the base stations of the serving cell and the adjacent cell according to the train information, the historical load information and the measurement information, wherein the energy-saving control strategies are used for carrying out energy-saving control on the base stations;
optionally, the time of the train reaching the target area can be determined according to the train information, the load of the base station can be estimated according to the historical load information of the serving cell and the adjacent cell and the measurement information of the serving cell and the adjacent cell, so that an energy-saving control strategy corresponding to the base station can be determined according to the time of the train reaching the target area and the estimated load of the base station, based on the energy-saving control strategy, the energy-saving control on the base station can be increased according to the time of the train reaching the target area when no train passes through, and the energy-saving control on the base station can be reduced or not performed according to the estimated load of the base station when the train is determined to reach the target area or is about to reach the target area, so that the purpose of saving the energy consumption of the base station is achieved.
Step S106: and issuing the energy-saving control strategy to a target base station, wherein the target base station is a base station which needs to perform energy-saving control in the service cell and the adjacent cell.
Optionally, the energy-saving control strategy may include energy-saving control strategies corresponding to cells that need to perform energy-saving control, and the energy-saving control strategies may be sent to base stations of related neighboring cells through the enabling base station or the network manager.
According to the base station energy-saving control method of the embodiment, the energy-saving control strategies of the base stations of the serving cell and the adjacent cell can be determined according to the train information in the target area, the historical load information of the serving cell and the adjacent cell and the measurement information of the serving cell and the adjacent cell, and the energy-saving control strategies are issued to the corresponding base stations, so that the purposes of saving energy and reducing consumption of the base stations can be achieved.
In one or more embodiments of the present disclosure, as shown in fig. 2, determining the energy saving control policy of the base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information may include:
step S1042: predicting the time of the train reaching the target area according to the train information;
optionally, train information may be collected in advance, model training may be performed on the train information, and the time of the train reaching the target area may be predicted according to the current train information by using the trained model.
Step S1044: predicting the load of the base station according to the time of the train reaching the target area, the historical load information and the measurement information;
optionally, historical load information of the serving cell and the neighboring cell may be collected in advance, model training is performed according to the historical load information of the serving cell and the neighboring cell in combination with the time of the train reaching the target area obtained in step S1042, and the trained model is used to predict the loads of the base stations of the serving cell and the neighboring cell according to the current measurement information of the serving cell and the neighboring cell. The energy-saving control strategy is determined based on model prediction, and the accuracy of a prediction result can be improved along with multiple times of model training, so that the energy-saving control is better and more accurate.
Alternatively, any of the models described above may be a neural network model.
Step S1046: and determining a target energy-saving control strategy of the base station according to the load of the base station and the time of the train reaching the target area.
Optionally, the target energy-saving control strategy needs to ensure that the base station implements energy-saving turn-off measures on the premise that the user experience can be guaranteed before the train reaches the base station. For example, for a certain base station a of a serving cell or an adjacent cell in a target area, a target energy-saving control strategy of the base station a is determined according to a predicted time for a train to reach the base station a and a predicted load of the base station a before the train reaches the base station a, so that the base station a implements the energy-saving control strategy on the premise of guaranteeing the requirement of a user on a network.
In one or more embodiments of the present disclosure, as shown in fig. 3, determining the energy saving control policy of the base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information may include:
step S1041: clustering the energy-saving scenes of the base stations according to the historical load information and the measurement information to obtain clustering results;
optionally, the historical load information of the serving cell and the neighboring cell may include information of a PDCP (Packet Data Convergence Protocol) Data capacity, a PRB (Physical Resource Block) utilization rate, and a Radio Resource Control (RRC) connection number, and correspondingly, the measurement information of the serving cell and the neighboring cell may also include information of the PDCP Data capacity, the PRB utilization rate, and the RRC connection number. Based on the method, the coverage state and tidal flow of the wireless network side can be analyzed based on the historical load information and the measurement information of the serving cell and the adjacent cells, and similar energy-saving scenes are clustered.
Step S1043: determining a historical energy-saving control strategy corresponding to a historical energy-saving scene similar to the current energy-saving scene of the base station;
the historical energy-saving scene similar to the current energy-saving scene may be any historical energy-saving scene in the historical energy-saving scenes belonging to the same cluster as the current energy-saving scene.
Step S1045: and determining the historical energy-saving control strategy as a target energy-saving control strategy of the base station, or determining the target energy-saving control strategy of the base station according to the historical energy-saving control strategy, the load of the base station and the time of the train reaching the target area.
Optionally, historical energy-saving scenes similar to the current energy-saving scenes of the serving cell and the neighboring cells may be determined by clustering, and in view of the similarity of the energy-saving scenes, for making an energy-saving control decision quickly, a historical energy-saving control strategy corresponding to the historical energy-saving scenes similar to the current energy-saving scenes may be used for reference, so as to be an embodiment mode, the historical energy-saving control strategy corresponding to the historical energy-saving scenes similar to the current energy-saving scenes may be directly used as the energy-saving control strategy of the current energy-saving scenes. Further, in order to improve the effectiveness of the energy-saving control strategy, the target energy-saving control strategy of the base station may be determined by combining the historical energy-saving control strategy, the predicted load of the base station and the time of the train reaching the target area, for example, the historical energy-saving control strategy may be adjusted by using the predicted load of the base station and the time of the train reaching the target area on the basis of the historical energy-saving control strategy, so as to obtain the target energy-saving control strategy.
In one or more embodiments of the present disclosure, the measurement information may include at least one of:
RSRP (Reference Signal Receiving Power), RSRQ (Reference Signal Receiving Quality), and SINR (Signal to Interference plus Noise Ratio), QoS (Quality of Service), QoE (Quality of Experience), and uplink and downlink packet delays.
In addition, the measurement information may further include at least one of the following information related to network performance:
virtual memory usage rate, disk usage rate, number of active terminals, number of terminals in RRC connected state, number of deactivated terminals, PRB usage rate, throughput of the predetermined IP, and data amount of the predetermined IP.
In one or more embodiments of the present disclosure, the train information may include at least one of:
train schedule, train movement direction, and train movement rate.
In one or more embodiments of the present disclosure, the energy saving control strategy may include:
the number of the target cell that needs to enter the energy saving state and the energy saving control strategy corresponding to the target cell may at least include one of the following:
subframe shutdown, symbol shutdown, channel shutdown, carrier shutdown, deep base station sleep, and device shutdown. Therefore, the energy-saving control method for the base station in the embodiment of the disclosure provides more types of energy-saving control strategies, so that the energy saving of the network can be realized more flexibly.
In one or more embodiments of the present disclosure, the energy-saving control policy corresponding to the target cell may further include:
a recommended cell that takes over the cell entering the energy saving state and the energy saving state duration. Wherein the recommended cell that takes over the cell entering the energy saving state may be used to continue processing the service of the cell entering the energy saving state. The duration of the energy saving state is also called an energy saving period, and refers to the duration of the cell that needs to maintain the energy saving state.
Optionally, the energy-saving control policy of the base station may further include at least one of the following:
adjusting the threshold corresponding to executing any one of the above shutdown operations, adjusting the energy saving state duration, and configuring the model parameters of any one of the above models. The threshold corresponding to the shutdown operation may include a threshold corresponding to a predicted load of the base station.
In one or more embodiments of the present disclosure, the base station may include a CU (Centralized Unit) and a DU (Distributed Unit), and issuing the energy saving control policy to the target base station may include:
and transmitting the energy-saving control strategy to the DU of the target base station.
Optionally, the base station energy saving control method according to one or more embodiments of the present disclosure may be executed by a CU, and based on this, the DU side may perform energy saving control on the base station based on an energy saving control policy issued by the CU, so as to save network energy consumption on the basis of ensuring user experience.
To implement the energy saving control strategy of the base stations of the serving cell and the neighboring cells determined according to the train information, the historical load information, and the measurement information, one or more embodiments of the present disclosure provide an AI (Artificial Intelligence) network architecture including a data acquisition module 412, a model training module 414, a model inference module 416, and an execution module 418, as shown in fig. 4.
The data acquisition module can collect data from devices such as terminals and network nodes according to different application scenes. The base station may report related data affecting the energy-saving control policy to the network management side, and may include basic information of the cell and the base station, such as cell ID, location, carrier, antenna downtilt, voltage, temperature, humidity, and disk usage. Performance related measurement information such as virtual memory usage, disk usage, number of active terminals, number of terminals in RRC connected state, number of deactivated terminals, PRB usage, throughput and data amount of a predetermined IP, etc. may also be included. In addition, at the cell level, terminal measurement information such as RSRP/RSRQ/SINR values of the serving cell and neighboring cells, and service performance related information such as QoS, QoE, and uplink and downlink packet delay may also be included.
The model training module obtains a training data set based on the data acquired by the data acquisition module, selects an ML (Machine Learning) model according to different application scenes, and trains the model. In order to be more beneficial to global optimization, model training can be completed on the network management side.
The model reasoning module generates reasoning data, and the reasoning data is derived into an energy-saving control strategy to carry out energy-saving indication on the base station. And the model reasoning module and the data acquisition module form a closed loop to realize the upgrading and feedback of model application, so that the reduction of energy consumption and the guarantee of network performance reach a balanced state.
The execution module is used for enabling the network manager or the base station to forward the output data to the relevant adjacent cell base station, so that the relevant adjacent cell base station generates corresponding action to achieve the aim of energy conservation. The output data may include the cell number recommended to enter the energy saving state and its energy saving control strategy, such as subframe shutdown, channel shutdown, carrier shutdown, deep base station sleep, and device shutdown. Other recommended cells that take over energy saving cell traffic and the time span of the energy saving state (i.e., the length of time the energy saving state needs to last) may also be included.
In one or more embodiments of the present disclosure, the base station may be a base station based on a CU/DU separation architecture of a high-speed rail private network, and in order to implement energy saving control for the base station, another AI network architecture is further provided, as shown in fig. 5, including: the energy-saving management system comprises a data acquisition module 512, an AI toolbox 514, an energy-saving decision module 516 and an energy-saving execution module 518, wherein the rest modules are all deployed on the CU side except the energy-saving execution module 518 which is deployed on the DU side. Based on this, the CU side can construct a model based on the historical data acquired by the data acquisition module 512, and continuously perform model training according to the introduction of real-time data, thereby intelligently realizing the recognition of an energy-saving scene, the prediction of a base station load, and the issuing of an energy-saving control strategy. The CU can issue the energy-saving control strategy to the DU through the F1 interface, and the DU can control the base station to execute the energy-saving control strategies such as turn-off and dormancy on the basis of the control of the CU, so that the network energy consumption is saved under the condition of ensuring the user experience. The functions of the modules are as follows:
the data acquisition module 512 is mainly responsible for acquiring and preparing data, where the acquired data includes a train schedule, a train moving direction, a moving speed, and load information (PDCP data capacity, PRB utilization, RRC connection number, etc.) of a serving cell and an adjacent cell.
The AI tool kit 514 is capable of performing model training procedures and model inference procedures, responsible for model training of the collected data information and making relevant predictions. The model reasoning process can cluster similar energy-saving scenes based on analysis of information such as wireless network side coverage state and tidal flow, so that an energy-saving decision module can make relevant decisions for specific energy-saving scenes quickly, for example, terminal services are not necessarily active although a train at night has a high attendance rate, and a base station can implement energy-saving strategies such as channel cut-off and carrier cut-off in the period. Aiming at the situation of high-speed rail, the AI toolbox can accurately predict the time of a train passing through a certain base station, base station load prediction is carried out according to historical load information, and before the train reaches the base station, the base station can implement energy-saving shutdown on the premise of guaranteeing user experience. The model reasoning process utilizes the trained ML model and combines the related data to make prediction, the process has a guiding function on issuing the energy-saving strategy, and the more accurate the prediction information is, the better the energy-saving decision of the prediction result obtained based on the prediction information is.
The energy saving decision module 516 makes decisions according to the prediction information result of the AI toolbox, which may include KPI (Key Performance Indicator) evaluation, adjustment of a threshold value, adjustment of an energy saving period, configuration of related parameters, and issuing of a base station energy saving policy, such as symbol turn-off, channel turn-off, carrier turn-off, deep sleep of a base station, and other energy saving policies.
The energy saving performing unit 518 performs an energy saving policy, such as sleeping the whole base station, or turning off a part of the base station module, a specific carrier or channel, etc.
Fig. 6 is a schematic diagram illustrating AI energy saving control of a high-speed private network separated architecture base station according to one or more embodiments of the present disclosure, where a CU shown in fig. 6 is connected to n DUs (for example, DUs 1-DUn shown in fig. 6) and can perform energy saving control on the n DUs. In the energy-saving control process, a CU data acquisition module acquires train schedule information, train moving direction and train moving speed, and sends historical load information and measurement information of a service cell and an adjacent cell to an AI toolbox. And the AI tool box performs scene recognition and load prediction through model training and model reasoning, so that the energy-saving decision module can make selection of an accurate energy-saving control strategy. For example, the energy saving control strategy may include: when a high-speed rail car does not pass through the base station, the CU controls the DU to carry out deep sleep on the base station; when the CU obtains the train information and determines that a train is about to pass through, traffic load prediction is performed on the cars (e.g., cars 1 to i shown in fig. 6) based on the train moving direction and train moving speed and historical traffic data of each car (which is an example of the above-described historical load information). Before a carriage is about to enter a certain base station cell, indicating the cells (1-n) in advance according to traffic prediction, and if the predicted load is large, determining that the base station does not implement any shutdown strategy in order to ensure QoS; and if the predicted load is small, performing symbol shutoff, channel shutoff or carrier shutoff and the like according to the calculated real-time changed threshold setting. Therefore, on the premise of ensuring the user experience of the high-speed rail, the waste of network resources is reduced, and the reduction of network energy consumption is realized to the greatest extent.
Fig. 7 is a schematic structural diagram of an apparatus for controlling base station energy saving according to one or more embodiments of the present disclosure, and as shown in fig. 7, the apparatus 710 includes:
an obtaining module 712, configured to obtain train information in a target area, historical load information of a serving cell and an adjacent cell, and measurement information of the serving cell and the adjacent cell;
a determining module 714, configured to determine energy saving control policies of base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information, where the energy saving control policies are used to perform energy saving control on the base stations;
an issuing module 716, configured to issue the energy saving control policy to a target base station, where the target base station is a base station that needs to perform energy saving control in the serving cell and an adjacent cell.
Optionally, the base station energy saving control apparatus according to one or more embodiments of the present disclosure may include any one of the modules in the AI network architectures shown in fig. 4 and fig. 5.
In one or more embodiments of the present disclosure, the determining module is specifically operable to:
predicting the time of the train reaching the target area according to the train information;
predicting the load of the base station according to the time of the train reaching the target area, the historical load information and the measurement information;
and determining a target energy-saving control strategy of the base station according to the load of the base station and the time of the train reaching the target area.
In one or more embodiments of the present disclosure, the determining module is specifically operable to:
clustering the energy-saving scenes of the base stations according to the historical load information and the measurement information to obtain clustering results;
determining a historical energy-saving control strategy corresponding to a historical energy-saving scene similar to the current energy-saving scene of the base station;
and determining the historical energy-saving control strategy as a target energy-saving control strategy of the base station, or determining the target energy-saving control strategy of the base station according to the historical energy-saving control strategy, the load of the base station and the time of the train reaching the target area.
In one or more embodiments of the present disclosure, the base station includes a central unit CU and a distribution unit DU, and the issuing module may be specifically configured to issue the energy saving control policy to the DU of the target base station.
One or more embodiments of the present disclosure also provide an electronic device including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the base station energy saving control methods provided by the embodiments of the present disclosure through executing the executable instructions.
One or more embodiments of the present disclosure also provide a computer-readable storage medium on which a computer program is stored, where the computer program is executed by a processor to implement any one of the base station energy saving control methods provided by the embodiments of the present disclosure.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 800 according to this embodiment of the invention is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is only an example and should not bring any limitations to the function and scope of use of the embodiments of the present invention.
As shown in fig. 8, electronic device 800 is in the form of a general purpose computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, and a bus 830 that couples the various system components including the memory unit 820 and the processing unit 810.
Wherein the storage unit stores program code that is executable by the processing unit 810 to cause the processing unit 810 to perform steps according to various exemplary embodiments of the present invention as described in the above section "exemplary methods" of the present specification. For example, the processing unit 810 may execute S102 shown in fig. 1, and acquire train information within the target area, historical load information of the serving cell and the neighboring cell, and measurement information of the serving cell and the neighboring cell; s104, determining energy-saving control strategies of the base stations of the service cell and the adjacent cell according to the train information, the historical load information and the measurement information, wherein the energy-saving control strategies are used for carrying out energy-saving control on the base stations; and S106, issuing the energy-saving control strategy to a target base station, wherein the target base station is a base station which needs to perform energy-saving control in the service cell and the adjacent cell.
The storage unit 820 may include readable media in the form of volatile memory units such as a random access memory unit (RAM)8201 and/or a cache memory unit 8202, and may further include a read only memory unit (ROM) 8203.
The storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 800 may also communicate with one or more external devices 900 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 800 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 850. Also, the electronic device 800 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 860. As shown, the network adapter 860 communicates with the other modules of the electronic device 800 via the bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary methods" of the present description, when said program product is run on the terminal device.
A program product for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (11)
1. A base station energy-saving control method is characterized by comprising the following steps:
acquiring train information, historical load information of a serving cell and an adjacent cell and measurement information of the serving cell and the adjacent cell in a target area;
determining energy-saving control strategies of the base stations of the serving cell and the adjacent cell according to the train information, the historical load information and the measurement information, wherein the energy-saving control strategies are used for carrying out energy-saving control on the base stations;
and issuing the energy-saving control strategy to a target base station, wherein the target base station is a base station which needs to perform energy-saving control in the service cell and the adjacent cell.
2. The method of claim 1, wherein determining the energy-saving control strategy for the base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information comprises:
predicting the time of the train reaching the target area according to the train information;
predicting the load of the base station according to the time of the train reaching the target area, the historical load information and the measurement information;
and determining a target energy-saving control strategy of the base station according to the load of the base station and the time of the train reaching the target area.
3. The method of claim 1, wherein determining the energy-saving control strategy for the base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information comprises:
clustering the energy-saving scenes of the base stations according to the historical load information and the measurement information to obtain clustering results;
determining a historical energy-saving control strategy corresponding to a historical energy-saving scene similar to the current energy-saving scene of the base station;
and determining the historical energy-saving control strategy as a target energy-saving control strategy of the base station, or determining the target energy-saving control strategy of the base station according to the historical energy-saving control strategy, the load of the base station and the time of the train reaching the target area.
4. The method of claim 1, wherein the measurement information comprises at least one of:
reference signal received power, RSRP, reference signal received quality, RSRQ, signal to interference plus noise ratio, SINR, quality of service, QoS, quality of experience, QoE, and uplink and downlink packet delay.
5. The method of claim 1, wherein the train information comprises at least one of:
train schedule, train movement direction, and train movement rate.
6. The method of claim 1, wherein the energy-saving control strategy comprises:
the number of a target cell which needs to enter an energy-saving state, and an energy-saving control strategy corresponding to the target cell, wherein the energy-saving control strategy corresponding to the target cell at least comprises one of the following:
subframe shutdown, symbol shutdown, channel shutdown, carrier shutdown, deep base station sleep, and device shutdown.
7. The method of claim 6, wherein the energy-saving control strategy corresponding to the target cell further comprises:
a recommended cell that takes over the cell entering the energy saving state and the energy saving state duration.
8. The method according to any one of claims 1 to 7, wherein the base station includes a Central Unit (CU) and a Distribution Unit (DU), and issuing the energy saving control policy to the target base station includes:
and transmitting the energy-saving control strategy to the DU of the target base station.
9. A base station energy saving control apparatus, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring train information in a target area, historical load information of a serving cell and an adjacent cell and measurement information of the serving cell and the adjacent cell;
a determining module, configured to determine energy saving control policies of base stations of the serving cell and the neighboring cell according to the train information, the historical load information, and the measurement information, where the energy saving control policies are used to perform energy saving control on the base stations;
and the issuing module is used for issuing the energy-saving control strategy to a target base station, wherein the target base station is a base station which needs to perform energy-saving control in the service cell and the adjacent cell.
10. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to execute the base station energy saving control method according to any one of claims 1 to 8 through executing the executable instruction.
11. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the base station energy saving control method according to any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115175288A (en) * | 2022-07-20 | 2022-10-11 | 中国联合网络通信集团有限公司 | Matching method, device and equipment of energy-saving strategy and storage medium |
| CN116095801A (en) * | 2023-04-13 | 2023-05-09 | 中国电信股份有限公司浙江分公司 | High-reliability energy-saving method and device for base station equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2015192252A (en) * | 2014-03-28 | 2015-11-02 | 日本電気株式会社 | Mobile communication system, communication controller, power saving control method, and program |
| CN112020125A (en) * | 2019-05-31 | 2020-12-01 | 中国移动通信集团重庆有限公司 | Base station power saving method and device based on high-speed rail pedestrian flow and computing equipment |
| CN113132945A (en) * | 2019-12-30 | 2021-07-16 | 中国移动通信集团辽宁有限公司 | Energy-saving scheduling method and system for railway private network base station cell |
| CN113543284A (en) * | 2020-04-17 | 2021-10-22 | 中兴通讯股份有限公司 | Energy saving method, base station, control unit and storage medium |
-
2021
- 2021-12-28 CN CN202111629544.0A patent/CN114339971A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2015192252A (en) * | 2014-03-28 | 2015-11-02 | 日本電気株式会社 | Mobile communication system, communication controller, power saving control method, and program |
| CN112020125A (en) * | 2019-05-31 | 2020-12-01 | 中国移动通信集团重庆有限公司 | Base station power saving method and device based on high-speed rail pedestrian flow and computing equipment |
| CN113132945A (en) * | 2019-12-30 | 2021-07-16 | 中国移动通信集团辽宁有限公司 | Energy-saving scheduling method and system for railway private network base station cell |
| CN113543284A (en) * | 2020-04-17 | 2021-10-22 | 中兴通讯股份有限公司 | Energy saving method, base station, control unit and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115175288A (en) * | 2022-07-20 | 2022-10-11 | 中国联合网络通信集团有限公司 | Matching method, device and equipment of energy-saving strategy and storage medium |
| CN116095801A (en) * | 2023-04-13 | 2023-05-09 | 中国电信股份有限公司浙江分公司 | High-reliability energy-saving method and device for base station equipment |
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