CN113923789B - LTE carrier scheduling device and method - Google Patents
LTE carrier scheduling device and method Download PDFInfo
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- CN113923789B CN113923789B CN202010663785.6A CN202010663785A CN113923789B CN 113923789 B CN113923789 B CN 113923789B CN 202010663785 A CN202010663785 A CN 202010663785A CN 113923789 B CN113923789 B CN 113923789B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/535—Allocation or scheduling criteria for wireless resources based on resource usage policies
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/20—Control channels or signalling for resource management
- H04W72/21—Control channels or signalling for resource management in the uplink direction of a wireless link, i.e. towards the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/20—Control channels or signalling for resource management
- H04W72/23—Control channels or signalling for resource management in the downlink direction of a wireless link, i.e. towards a terminal
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses an LTE carrier scheduling device and a method, wherein the device is arranged between X2 interfaces of a base station and comprises the following steps: the receiving module is suitable for receiving the cell state information in the sampling period reported by the base station through the X2 interface; the calculating module is suitable for calculating the average congestion degree of the cell in the sampling period according to the cell state information; the verification module is suitable for calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and carrying out robust function verification on the cell state fluctuation data to obtain the number of the initial scheduling cells; the decision module is suitable for comparing the number of the initial dispatching cells with the number of the dispatching cells, and determining the number of the target dispatching cells according to a comparison result; and the feedback module is suitable for issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction. The device can timely and accurately make the scheduling strategy under the condition of cell state change, and is more energy-saving and efficient.
Description
Technical Field
The invention relates to the technical field of wireless networks, in particular to an LTE carrier scheduling device and method.
Background
With the continuous development of mobile networks, the continuous updating and upgrading of user terminals and the promotion of operators for reducing the cost, the current change of LTE network load presents more and more obvious complications, but the current network resources are limited, and the full capacity expansion of each station cannot be realized, so that the change of the cell state is required to be adapted through the scheduling of carrier resources, the value of each scheduling resource is fully exerted on the premise of ensuring the user experience,
the strategy of LTE carrier scheduling in the prior art includes the following 3 steps: 1. selection of a scheduling cell: the existing auxiliary carriers or the carriers co-covered by the multi-frequency points of the existing network are brought into the category of the dispatching cells in batches so as to be used for follow-up dispatching; 2. determination of a scheduling strategy: manually performing statistical analysis on recent load changes of sites which are incorporated into a scheduling cell, and manually making selection judgment on scheduling time; 3. execution of the scheduling policy: and implementing the scheduling strategy for the corresponding scheduling cell at the corresponding time node according to the scheduling strategy made by people. Namely, firstly determining the category of the dispatching cell, then manually counting and analyzing the change condition of the recent load, manually judging the dispatching time according to the change condition of the load, and finally implementing corresponding dispatching at the corresponding time node according to the dispatching strategy by the cell which is included in the dispatching category.
However, the inventors have found that there are at least the following disadvantages in the prior art in the practice of the present invention: 1. accuracy aspect: the decision of the current scheduling strategy is made based on the statistical analysis of the recent load change condition of the cell by manual operation, and the manual operation inevitably causes errors to influence the accuracy of the scheduling strategy; 2. timeliness aspect: the scheduling time length of the current scheduling strategy is generally in a unit of day, and is rarely changed once the scheduling time length is determined, but the load of the network is changed greatly every moment, when the load change is not obvious, the scheduling time length is required to be prolonged, otherwise, the scheduling period is required to be shortened to adapt to the load change more quickly, so that the current scheduling strategy is slightly insufficient in the aspect of coping with the time of the cell load change; 3. energy conservation aspect: the current scheduling strategy is that once a certain site is executed with a scheduling instruction, all scheduling cells under the site are scheduled in batches, but sometimes the cell state fluctuation is not large, the change of cell load can be met only by scheduling a small number of cells, and the batch scheduling can cause the waste of resources.
Disclosure of Invention
The present invention has been made in view of the above-mentioned problems, and it is an object of the present invention to provide an LTE carrier scheduling apparatus and method that overcomes or at least partially solves the above-mentioned problems.
According to one aspect of the present invention, there is provided an LTE carrier scheduling apparatus, the apparatus being installed between X2 interfaces of a base station, comprising:
the receiving module is suitable for receiving the cell state information in the sampling period reported by the base station through the X2 interface;
the calculating module is suitable for calculating the average congestion degree of the cell in the sampling period according to the cell state information;
the verification module is suitable for calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and carrying out robust function verification on the cell state fluctuation data to obtain the number of the initial scheduling cells;
the decision module is suitable for comparing the number of the initial dispatching cells with the number of the dispatching cells, and determining the number of the target dispatching cells according to a comparison result;
and the feedback module is suitable for issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction.
Optionally, the apparatus further comprises:
and the first updating module is suitable for updating the duration of the sampling period according to the number of the target scheduling cells.
Optionally, the first update module is further adapted to:
if the number of the target scheduling cells is zero, the duration of the sampling period is prolonged according to a period extension rule;
and if the number of the target scheduling cells is not zero, shortening the duration of the sampling period according to the period shortening rule.
Optionally, the cell status information includes: the method comprises the steps of activating state cell number, activating state dispatching group cell number, total dispatching group cell number, cell uplink and downlink air interface total flow data, cell synchronous state user number, cell uplink PRB utilization rate data and cell downlink PRB utilization rate data.
Optionally, the decision module is further adapted to:
if the number of the initial scheduling cells is smaller than or equal to 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells;
if the number of the initial scheduling cells is larger than 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the difference value between the total scheduling group cell number and the active scheduling group cell number.
Optionally, the apparatus further comprises:
and the second updating module is suitable for updating the historical average congestion degree of the cell according to the average congestion degree of the cell in the sampling period.
According to another aspect of the present invention, there is provided an LTE carrier scheduling method, including:
receiving cell state information in a sampling period reported by a base station through an X2 interface;
calculating the average congestion degree of the cell in the sampling period according to the cell state information;
calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and performing robust function verification on the cell state fluctuation data to obtain the number of initially scheduled cells;
comparing the initial dispatching cell number with the dispatching cell number, and determining the target dispatching cell number according to the comparison result;
and issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction.
Optionally, the method further comprises:
and updating the time length of the sampling period according to the number of the target scheduling cells.
Optionally, updating the duration of the sampling period according to the number of target scheduling cells further includes:
if the number of the target scheduling cells is zero, the duration of the sampling period is prolonged according to a period extension rule;
and if the number of the target scheduling cells is not zero, shortening the duration of the sampling period according to the period shortening rule.
Optionally, the cell status information includes: the method comprises the steps of activating state cell number, activating state dispatching group cell number, total dispatching group cell number, cell uplink and downlink air interface total flow data, cell synchronous state user number, cell uplink PRB utilization rate data and cell downlink PRB utilization rate data.
Optionally, comparing the initial scheduling cell number with the schedulable cell number, and determining the target scheduling cell number according to the comparison result further includes:
if the number of the initial scheduling cells is smaller than or equal to 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells;
if the number of the initial scheduling cells is larger than 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the difference value between the total scheduling group cell number and the active scheduling group cell number.
Optionally, the method further comprises:
and updating the historical average congestion degree of the cell according to the average congestion degree of the cell in the sampling period.
According to yet another aspect of the present invention, there is provided a computing device comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction, where the executable instruction causes the processor to execute an operation corresponding to the LTE carrier scheduling method.
According to still another aspect of the present invention, there is provided a computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the above-described LTE carrier scheduling method.
According to the LTE carrier scheduling device and the method of the invention, the device is arranged between X2 interfaces of a base station and comprises the following steps: the receiving module is suitable for receiving the cell state information in the sampling period reported by the base station through the X2 interface; the calculating module is suitable for calculating the average congestion degree of the cell in the sampling period according to the cell state information; the verification module is suitable for calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and carrying out robust function verification on the cell state fluctuation data to obtain the number of the initial scheduling cells; the decision module is suitable for comparing the number of the initial dispatching cells with the number of the dispatching cells, and determining the number of the target dispatching cells according to a comparison result; and the feedback module is suitable for issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction. The device can timely and accurately make a scheduling strategy under the condition of cell state change, can accurately control each carrier resource, and is more energy-saving and efficient.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
fig. 1 shows a schematic structural diagram of an LTE carrier scheduling apparatus according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an LTE carrier scheduling apparatus according to another embodiment of the present invention;
fig. 3 shows an interactive flow chart of LTE carrier scheduling in an embodiment of the invention;
fig. 4 is a schematic flow chart of an LTE carrier scheduling method according to another embodiment of the present invention;
fig. 5 is a schematic flow chart of an algorithm of LTE carrier scheduling according to another embodiment of the present invention;
FIG. 6 illustrates a schematic diagram of a computing device provided by an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Fig. 1 shows a schematic structural diagram of an LTE carrier scheduling apparatus according to an embodiment of the present invention, where the apparatus is installed between X2 interfaces of a base station (Evolved Node B, enodebs). As shown in fig. 1, the apparatus comprises the following modules: the device comprises a receiving module 11, a calculating module 12, a checking module 13, a decision module 14 and a feedback module 15.
The receiving module 11 is adapted to receive cell status information in a sampling period reported by the base station through the X2 interface.
The base station periodically collects the cell state information under the base station, and reports the cell state information to the LTE carrier scheduling device through the X2 interface, and a receiving module in the device receives the cell state information uploaded by the base station.
The cell state information is state information of all active cells under the station, and comprises the number of active cells, the number of active scheduling group cells, the number of total scheduling group cells, the total flow data of uplink and downlink air interfaces of the cells, the number of synchronous state users of the cells, the utilization rate of uplink PRB of the cells and the utilization rate of downlink PRB of the cells.
The calculating module 12 is adapted to calculate the average congestion degree of the cell in the sampling period based on the cell status information.
Firstly, calculating the congestion degree of a single cell under a base station according to cell state information acquired by the base station, and then calculating the average congestion degree of the cell.
And the verification module 13 is suitable for calculating cell state fluctuation data according to the average cell congestion degree and the average cell history congestion degree in the sampling period, and carrying out robust function verification on the cell state fluctuation data to obtain the number of the initial scheduling cells.
The calibration coefficient of the robust function may be set by the user, so as to represent the sensitivity of the cell state fluctuation under the site, for example, the calibration coefficient may be appropriately increased in the area with larger fluctuation in the urban area, and the calibration coefficient may be appropriately reduced in the suburban area.
Comparing the average congestion degree of the cells in the sampling period with the historical average congestion degree of the cells, calculating the cell state fluctuation data in the sampling period, and then carrying out robust function verification on the cell state fluctuation to preliminarily obtain the number of the cells to be scheduled at this time, namely the number of the cells to be scheduled initially.
The decision module 14 is adapted to compare the initial number of cells to the number of cells that can be scheduled, and to determine the number of cells to be scheduled according to the comparison result.
And comparing the primarily obtained dispatching cell number with the dispatching cell number under the current station, and finally deciding the final dispatching cell number in the sampling period, namely the target dispatching cell number.
And the feedback module 15 is suitable for issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a corresponding scheduling instruction.
And feeding back a scheduling decision to the base station according to the decided scheduling cell number, and implementing a scheduling instruction by the base station according to the fed back scheduling decision so as to activate the scheduling cell.
Fig. 3 shows an interaction flow chart of LTE carrier scheduling in the embodiment of the present invention, and as shown in fig. 3, the interaction process mainly includes: (1) the eNODEB periodically detects cell state information; (2) the eNODEB reports cell state information to the device; (3) the LTE carrier scheduling device calculates and makes scheduling decisions and transmits the scheduling decisions to the eNODEB; (4) the enodebs make a schedule based on the received decisions.
It can be seen that, in this embodiment, through the LTE carrier scheduling apparatus installed between the X2 interfaces of the base station, the average congestion degree of the cells in the sampling period is calculated according to the cell state information in the sampling period reported by the base station, and then the average congestion degree of the cells in the sampling period is compared with the average congestion degree of the cell history under the present station, so as to obtain the cell state fluctuation in the sampling period, and the number of the cells to be scheduled is primarily determined through the verification of the robust function, and finally the final scheduling information is determined through the comparison with the current number of the cells capable of being scheduled. The device can timely and accurately make a scheduling strategy under the condition of cell state change, can accurately control each carrier resource according to the verification of cell robustness, is not activated by traditional batch scheduling, is more energy-saving and efficient, and can ensure the accuracy, timeliness and energy-saving performance of site cell scheduling.
Fig. 2 shows a schematic structural diagram of an LTE carrier scheduling apparatus according to another embodiment of the present invention, as shown in fig. 2, where the apparatus includes the following modules: the device comprises a receiving module 21, a calculating module 22, a checking module 23, a decision module 24, a feedback module 25, a first updating module 26 and a second updating module 27.
The receiving module 21 is adapted to receive the cell state information in the sampling period reported by the base station through the X2 interface.
The base station periodically collects the cell state information under the base station, and reports the cell state information to the LTE carrier scheduling device through the X2 interface, and a receiving module in the device receives the cell state information uploaded by the base station. Wherein the cell status information includes: number of active cells n, number of active schedule group cells m, number of total schedule group cells w, and
cell uplink and downlink air interface total flow data G= { G i I=1, …, n }, cell synchronization state user number u= { U i I=1, …, n }, cell uplink PRB utilization data P Upper part ＝{P Upper i I=1, …, n }, and cell downlink PRB utilization data P Lower part(s) ＝{P Lower i |i＝1,…,n}。
The calculating module 22 is adapted to calculate the average congestion level of the cell in the sampling period based on the cell status information.
Specifically, the calculation module calculates the average congestion level of the cell by performing the following steps:
step 1, calculating the congestion degree omega of a single cell under the eNODEB according to the cell state information acquired by the eNODEB i ；
Step 2, calculating the average congestion degree of the cells in the sampling periodWhere x represents the x-th sampling period.
And the verification module 23 is adapted to calculate cell state fluctuation data according to the average cell congestion degree and the average cell history congestion degree in the sampling period, and perform robust function verification on the cell state fluctuation data to obtain the number of the initial scheduling cells.
Wherein the cell state fluctuation data p x Average congestion degree for a cellAverage congestion level with cell historyIs equal to the difference of the cell history average congestion degree +.>The specific calculation formula is as follows:
then, for the cell state fluctuation data p x Performing robust function verification to preliminarily obtain the number of cells to be scheduled at this time
Wherein y= { y i I=1, …, w } is a robust verification coefficient that can be set by the user by himself, to characterize the sensitivity of the cell fluctuation state under the site.
The decision module 24 is adapted to compare the initial number of cells to the number of cells that can be scheduled, and to determine the number of cells to be scheduled according to the comparison result.
The number of scheduling cells to be preliminarily obtainedComparing with the number of cells which can be scheduled under the current station, and determining the final number phi of the scheduled cells according to the comparison result x 。
Specifically, if the number of the initial scheduling cells is less than or equal to 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells; if the number of the initial scheduling cells is larger than 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the difference value between the total scheduling group cell number and the active scheduling group cell number. The formula is as follows:
if it isThen->
If it isThen->
The feedback module 25 is adapted to feed back a scheduling decision to the base station according to the decided number of scheduling cells, and the base station implements a scheduling instruction according to the fed back scheduling decision to activate the scheduling cells.
For example, if phi x -1, then 1 scheduling cell is activated, if Φ x =2, then exciteThere are 2 inactive scheduling cells.
The first updating module 26 is adapted to update the duration of the sampling period according to the number of target scheduling cells, and by updating the dynamic sampling period, the state change of the cells can be better adapted.
Specifically, if the number of the target scheduling cells is zero, the duration of the sampling period is prolonged according to a period extension rule, if the number of the finally determined cells to be scheduled is zero, which indicates that the current robustness of the cells is better, in order to save air interface resources, the sampling period can be extended, and the next scheduling is performed according to the data acquired by the extended sampling period. An alternative calculation formula is as follows:
next sampling period=min { current sampling period+15 min, 60 min }
If the number of the target scheduling cells is not zero, the duration of the sampling period is shortened according to a period shortening rule, if the number of the finally determined cells needing to be scheduled is zero, the current robustness of the cells is poor, the sampling period is required to be shortened in order to adapt to the state change of the cells more rapidly, and data is acquired according to the prolonged sampling period for scheduling processing in the next sampling. An alternative calculation formula is as follows:
next sampling period=max { current sampling period- |Φ ] x 15 min, 15 min }
Therefore, the device of the embodiment can better adapt to the state change of the cell by updating the dynamic sampling period.
The second updating module 27 is adapted to update the cell history average congestion level according to the cell average congestion level in the sampling period. And according to the average congestion degree of the cell in the sampling period, the average congestion degree of the cell is included in the historical congestion degree of the cell, the current historical average congestion degree of the cell is updated, and the updated historical average congestion degree of the cell is used as a reference when scheduling processing is carried out in the next sampling period.
Therefore, by collecting the cell state information, the device calculates the cell congestion degree of all the dispatching stations by itself and is used for checking the robust function, and the whole process is automatically executed and completed by the device, so that the manual participation is avoided, and the dispatching accuracy is improved. Secondly, comparing the average congestion degree in the cell period with the historical congestion degree to obtain fluctuation in the cell period, introducing a robust function to check, judging the number of cells to be scheduled, and improving the accuracy and energy conservation of an algorithm compared with the traditional batch scheduling; in addition, the device evaluates the current robustness of the cell according to the result of the robustness function verification, and increases or decreases the sampling period accordingly, so that the device is better and more rapidly adapted to the change of the cell state, and the timeliness of scheduling is improved.
Fig. 4 is a flow chart illustrating an LTE carrier scheduling method according to another embodiment of the present invention, as shown in fig. 4, the method includes the following steps:
step S410, receiving the cell state information in the sampling period reported by the base station through the X2 interface.
The base station periodically collects the cell state information under the base station, and reports the cell state information to the LTE carrier scheduling device through the X2 interface, and a receiving module in the device receives the cell state information uploaded by the base station.
Wherein the cell status information includes: the method comprises the steps of activating state cell number, activating state dispatching group cell number, total dispatching group cell number, cell uplink and downlink air interface total flow data, cell synchronous state user number, cell uplink PRB utilization rate data and cell downlink PRB utilization rate data.
Step S420, calculating the average congestion degree of the cell in the sampling period according to the cell state information.
Specifically, firstly, calculating the congestion degree of a single cell under a base station according to cell state information acquired by the base station, and then calculating the average congestion degree of the cell. Specific embodiments may be referred to the descriptions in the foregoing embodiments, and are not described herein in detail.
And step S430, calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and performing robust function verification on the cell state fluctuation data to obtain the number of the initial scheduling cells.
The calibration coefficient of the robust function may be set by the user, so as to represent the sensitivity of the cell state fluctuation under the site, for example, the calibration coefficient may be appropriately increased in the area with large urban fluctuation, and the calibration coefficient may be appropriately reduced in the suburb.
Comparing the average congestion degree of the cells in the sampling period with the historical average congestion degree of the cells, calculating the cell state fluctuation data in the sampling period, and then carrying out robust function verification on the cell state fluctuation to preliminarily obtain the number of the cells to be scheduled.
Specifically, if the number of the initial scheduling cells is less than or equal to 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells; if the number of the initial scheduling cells is larger than 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the difference value between the total scheduling group cell number and the active scheduling group cell number.
Step S440, the initial dispatching district number is compared with the dispatching district number, and the target dispatching district number is determined according to the comparison result.
And comparing the primarily obtained dispatching cell number with the dispatching cell number under the current station, and finally deciding the final dispatching cell number in the sampling period. Specific embodiments may be referred to the descriptions in the above embodiments, and are not described herein.
Step S450, the scheduling decision is issued to the base station according to the number of the target scheduling cells, so that the base station can implement the scheduling instruction.
And feeding back a scheduling decision to the base station according to the decided scheduling cell number, and implementing a scheduling instruction by the base station according to the fed back scheduling decision so as to activate the scheduling cell.
In an alternative manner, the method further comprises: and updating the time length of the sampling period according to the number of the target scheduling cells.
Specifically, if the number of the target scheduling cells is zero, the duration of the sampling period is prolonged according to a period extension rule, if the number of the finally determined cells to be scheduled is zero, which indicates that the current robustness of the cells is better, in order to save air interface resources, the sampling period can be extended, and data is acquired according to the extended sampling period for scheduling processing in the next sampling.
If the number of the target scheduling cells is not zero, the duration of the sampling period is shortened according to a period shortening rule, if the number of the finally determined cells needing to be scheduled is zero, the current robustness of the cells is poor, the sampling period is required to be shortened in order to adapt to the state change of the cells more rapidly, and data is acquired according to the prolonged sampling period for scheduling processing in the next sampling.
In an alternative manner, the method further comprises: and updating the historical average congestion degree of the cell according to the average congestion degree of the cell in the sampling period. And according to the average congestion degree of the cell in the sampling period, the average congestion degree of the cell is included in the historical congestion degree of the cell, the current historical average congestion degree of the cell is updated, and the updated historical average congestion degree of the cell is used as a reference for scheduling processing in the next sampling period.
Therefore, the method of the embodiment calculates the average congestion degree of the cells in the sampling period by collecting the state information of the cells in the sampling period, compares the average congestion degree with the historical average congestion degree of the cells to obtain the fluctuation in the sampling period of the cells, obtains the initial dispatching cell number through the verification of the robust function, and then determines the final dispatching information according to the comparison of the current dispatching cell number. By the method, the scheduling strategy can be timely and accurately made under the condition of cell state change, each carrier resource can be accurately controlled according to the verification of cell robustness, the traditional batch scheduling is not activated, the energy is saved, the efficiency is improved, and the scheduling timeliness is ensured by dynamically updating the sampling period.
Fig. 5 shows a schematic flow chart of an algorithm for LTE carrier scheduling according to another embodiment of the present invention, and fig. 5 shows a complete scheduling algorithm flow, as shown in fig. 5, where the algorithm flow specifically includes the following steps:
in step S501, the base station performs the x-th sampling to collect the cell state information under the base station, where the initial x=1, and the initial sampling period is set to 15 minutes.
Step S502, a base station reports the acquired information to a device;
step S503, the device calculates the average congestion degree omega of the cells in the sampling period Period x ；
Step S504, comparing the average congestion degree in the sampling period with the historical congestion degree to obtain the fluctuation P in the sampling period of the cell x ；
Step S505, checking the current fluctuation improved robust function to preliminarily obtain the number of the scheduling cells
Step S506, judgingWhether less than or equal to 0; if yes, go to step S507; if not, go to step S508.
Step S507, calculating the final dispatching cell number, wherein the calculation formula is as follows:
step S508, calculating the final quantity of the dispatching cells, wherein the calculation formula is as follows:
step S509, updating the historical average congestion degree Ω of the cell History of ＝(Ω History of ×x+Ω Period x )/(x+1)
Step S510, updating the sampling number x=x+1;
step S511-step S513 are algorithm flows for updating the sampling period, specifically:
step S511, judgingWhether or not to equal 0; if yes, go to step S512; if not, step S513 is performed.
Step S512, ifEqual to 0, the next sampling period = min { current sampling period +15 minutes, 60 minutes }.
Step S513, ifNot equal to 0, the next sampling period = max { current sampling period- |Φ } is updated x 15 min, 15 min }
In step S514, the apparatus issues a scheduling instruction to the base station.
Step S515, the present scheduling algorithm ends.
The LTE carrier scheduling method provided in this embodiment may be executed according to a period, and in the above, the flow of the LTE carrier scheduling algorithm in one sampling period is described.
The embodiment of the invention provides a non-volatile computer storage medium, which stores at least one executable instruction, and the computer executable instruction can execute the LTE carrier scheduling method in any of the method embodiments.
The executable instructions may be particularly useful for causing a processor to:
receiving cell state information in a sampling period reported by a base station through an X2 interface;
calculating the average congestion degree of the cell in the sampling period according to the cell state information;
calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and performing robust function verification on the cell state fluctuation data to obtain the number of initially scheduled cells;
comparing the initial dispatching cell number with the dispatching cell number, and determining the target dispatching cell number according to the comparison result;
and issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction.
In one alternative, the executable instructions cause the processor to:
and updating the time length of the sampling period according to the number of the target scheduling cells.
In one alternative, the executable instructions cause the processor to:
if the number of the target scheduling cells is zero, the duration of the sampling period is prolonged according to a period extension rule;
and if the number of the target scheduling cells is not zero, shortening the duration of the sampling period according to the period shortening rule.
In an alternative way, the cell state information includes: the method comprises the steps of activating state cell number, activating state dispatching group cell number, total dispatching group cell number, cell uplink and downlink air interface total flow data, cell synchronous state user number, cell uplink PRB utilization rate data and cell downlink PRB utilization rate data.
In one alternative, the executable instructions cause the processor to: if the number of the initial scheduling cells is smaller than or equal to 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells;
if the number of the initial scheduling cells is larger than 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the difference value between the total scheduling group cell number and the active scheduling group cell number.
In one alternative, the executable instructions cause the processor to: and updating the historical average congestion degree of the cell according to the average congestion degree of the cell in the sampling period.
By the method, the scheduling strategy can be timely and accurately made under the condition of cell state change, each carrier resource can be accurately controlled according to the verification of cell robustness, and the method is not activated by traditional batch scheduling, so that the method is more energy-saving and efficient, and the accuracy, timeliness and energy-saving performance of site cell scheduling can be ensured.
FIG. 6 illustrates a schematic diagram of an embodiment of a computing device of the present invention, and the embodiments of the present invention are not limited to a particular implementation of the computing device.
As shown in fig. 6, the computing device may include: a processor 602, a communication interface (Communications Interface), a memory 606, and a communication bus 608.
Wherein: processor 602, communication interface 604, and memory 606 perform communication with each other via communication bus 608. Communication interface 604 is used to communicate with network elements of other devices, such as clients or other servers. The processor 602 is configured to execute the program 610, and may specifically perform relevant steps in the embodiment of the LTE carrier scheduling method for a computing device.
In particular, program 610 may include program code including computer-operating instructions.
The processor 602 may be a central processing unit CPU or a specific integrated circuit ASIC (Application Specific Integrated Circuit) or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included by the computing device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
A memory 606 for storing a program 610. The memory 606 may comprise high-speed RAM memory or may further comprise non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 610 may be specifically operable to cause the processor 602 to:
receiving cell state information in a sampling period reported by a base station through an X2 interface;
calculating the average congestion degree of the cell in the sampling period according to the cell state information;
calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and performing robust function verification on the cell state fluctuation data to obtain the number of initially scheduled cells;
comparing the initial dispatching cell number with the dispatching cell number, and determining the target dispatching cell number according to the comparison result;
and issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction.
In an alternative, the program 610 causes the processor 602 to:
and updating the time length of the sampling period according to the number of the target scheduling cells.
In an alternative, the program 610 causes the processor 602 to:
if the number of the target scheduling cells is zero, the duration of the sampling period is prolonged according to a period extension rule;
and if the number of the target scheduling cells is not zero, shortening the duration of the sampling period according to the period shortening rule.
In an alternative way, the cell state information includes: the method comprises the steps of activating state cell number, activating state dispatching group cell number, total dispatching group cell number, cell uplink and downlink air interface total flow data, cell synchronous state user number, cell uplink PRB utilization rate data and cell downlink PRB utilization rate data.
In an alternative, the program 610 causes the processor 602 to:
if the number of the initial scheduling cells is smaller than or equal to 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells;
if the number of the initial scheduling cells is larger than 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the difference value between the total scheduling group cell number and the active scheduling group cell number.
In an alternative, the program 610 causes the processor 602 to:
and updating the historical average congestion degree of the cell according to the average congestion degree of the cell in the sampling period.
By the method, the scheduling strategy can be timely and accurately made under the condition of cell state change, each carrier resource can be accurately controlled according to the verification of cell robustness, and the method is not activated by traditional batch scheduling, so that the method is more energy-saving and efficient, and the accuracy, timeliness and energy-saving performance of site cell scheduling can be ensured.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components according to embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.
Claims (8)
1. An LTE carrier scheduling apparatus, the apparatus being installed between X2 interfaces of a base station, comprising:
the receiving module is suitable for receiving the cell state information in the sampling period reported by the base station through the X2 interface;
wherein the cell status information includes: the method comprises the steps of activating state cell number, activating state dispatching group cell number, total dispatching group cell number, cell uplink and downlink air interface total flow data, cell synchronous state user number, cell uplink PRB utilization data and cell downlink PRB utilization data;
the calculating module is suitable for calculating the average congestion degree of the cell in the sampling period according to the cell state information;
the verification module is suitable for calculating cell state fluctuation data according to the average cell congestion degree and the average cell history congestion degree in the sampling period, and carrying out robust function verification on the cell state fluctuation data to obtain the number of initially scheduled cells;
the decision module is suitable for determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells if the number of the initial scheduling cells is smaller than or equal to 0; if the initial scheduling cell number is greater than 0, determining that the target scheduling cell number is the maximum value between the initial scheduling cell number and the difference value between the total scheduling group cell number and the active scheduling group cell number;
and the feedback module is suitable for issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction.
2. The apparatus of claim 1, wherein the apparatus further comprises:
and the first updating module is suitable for updating the duration of the sampling period according to the number of the target scheduling cells.
3. The apparatus of claim 2, wherein the first update module is further adapted to:
if the number of the target scheduling cells is zero, prolonging the duration of the sampling period according to a period prolonging rule;
and if the number of the target scheduling cells is not zero, shortening the duration of the sampling period according to a period shortening rule.
4. A device according to any one of claims 1-3, wherein the device further comprises:
and the second updating module is suitable for updating the historical average congestion degree of the cell according to the average congestion degree of the cell in the sampling period.
5. An LTE carrier scheduling method, comprising:
receiving cell state information in a sampling period reported by a base station through an X2 interface; wherein the cell status information includes: the method comprises the steps of activating state cell number, activating state dispatching group cell number, total dispatching group cell number, cell uplink and downlink air interface total flow data, cell synchronous state user number, cell uplink PRB utilization data and cell downlink PRB utilization data;
calculating the average congestion degree of the cell in the sampling period according to the cell state information;
calculating cell state fluctuation data according to the average cell congestion degree and the historical average cell congestion degree in the sampling period, and performing robust function verification on the cell state fluctuation data to obtain the number of initially scheduled cells;
if the number of the initial scheduling cells is smaller than or equal to 0, determining that the number of the target scheduling cells is the maximum value between the number of the initial scheduling cells and the negative value of the number of the active scheduling group cells; if the initial scheduling cell number is greater than 0, determining that the target scheduling cell number is the maximum value between the initial scheduling cell number and the difference value between the total scheduling group cell number and the active scheduling group cell number;
and issuing a scheduling decision to the base station according to the number of the target scheduling cells so as to enable the base station to implement a scheduling instruction.
6. The method of claim 5, wherein the method further comprises:
and updating the time length of the sampling period according to the number of the target scheduling cells.
7. A computing device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction, where the executable instruction causes the processor to perform the operations corresponding to the LTE carrier scheduling method according to claim 5 or 6.
8. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the LTE carrier scheduling method of claim 5 or 6.
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