CN111885629B

CN111885629B - Network optimization method and device

Info

Publication number: CN111885629B
Application number: CN202010796679.5A
Authority: CN
Inventors: 曹艳霞; 李福昌; 钟志刚; 张忠皓
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2020-08-10
Filing date: 2020-08-10
Publication date: 2022-05-03
Anticipated expiration: 2040-08-10
Also published as: CN111885629A

Abstract

The embodiment of the invention provides a network optimization method and device, relates to the technical field of communication, and aims to improve the reasonability of determining the type of a target cell and further improve the reasonability of network optimization. The method comprises the following steps: the method comprises the steps that network optimization equipment obtains flow characteristic information of a plurality of time intervals corresponding to a target cell, wherein the flow characteristic information of one time interval comprises the flow of the target cell during data transmission in the time interval, the number of CCEs occupied in a PDCCH corresponding to the time interval and the available number of CCEs in the PDCCH corresponding to the time interval; the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; and the network optimization equipment performs network optimization on the target cell according to the type of the target cell.

Description

Network optimization method and device

Technical Field

The embodiment of the invention relates to the technical field of communication, in particular to a network optimization method and device.

Background

At present, when network optimization is performed, the type of a certain cell may be determined according to downlink traffic corresponding to the cell, and different network optimization modes may be allocated to different types of cells. Specifically, when the downlink traffic corresponding to a cell is greater than or equal to a traffic threshold, the cell is determined to be a high-flow service cell; otherwise, determining the cell as a low-flow service cell. The high flow service cell and the low flow service cell can respectively correspond to different network optimization modes.

However, the method for determining the type of the cell only according to the downlink traffic corresponding to the cell may not be reasonable, that is, the influence of other factors on the type or characteristics of the cell is not considered, so that some other types of cells may not be determined (or distinguished), that is, the case that the type of the cell is determined unreasonably may exist, and the rationality of network optimization may be influenced.

Disclosure of Invention

The embodiment of the invention provides a network optimization method and device, which can improve the reasonability of determining the type of a target cell and further improve the reasonability of network optimization.

In a first aspect, an embodiment of the present invention provides a network optimization method, including: the method includes the steps that a network optimization device obtains traffic characteristic information of a plurality of time intervals corresponding to a target cell, wherein the traffic characteristic information of one time interval includes traffic of the target cell during data transmission in the time interval, the number of occupied Control Channel Elements (CCEs) in a Physical Downlink Control Channel (PDCCH) corresponding to the time interval, and the available number of the CCEs in the PDCCH corresponding to the time interval; the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; the busy hour flow of the target cell is used for representing the flow characteristic when the target cell carries out data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree when the target cell carries out data transmission; and the network optimization equipment performs network optimization on the target cell according to the type of the target cell.

In a second aspect, an embodiment of the present invention provides a network optimization apparatus, including: the system comprises an acquisition module, a determination module and a network optimization module; the acquiring module is configured to acquire traffic characteristic information of multiple time intervals corresponding to a target cell, where the traffic characteristic information of a time interval includes traffic of the target cell during data transmission in the time interval, the number of CCEs occupied in a PDCCH corresponding to the time interval, and the available number of CCEs in the PDCCH corresponding to the time interval; the determining module is used for determining the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; the busy hour flow of the target cell is used for representing the flow characteristic when the target cell carries out data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree when the target cell carries out data transmission; the network optimization module is used for carrying out network optimization on the target cell according to the type of the target cell.

In a third aspect, an embodiment of the present invention provides another network optimization apparatus, including: a processor, a memory, a bus, and a communication interface; the memory is used for storing computer-executable instructions, the processor is connected with the memory through a bus, and when the network optimization device runs, the processor executes the computer-executable instructions stored in the memory, so that the network optimization device executes the network optimization method provided by the first aspect.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which includes a computer program, when it runs on a computer, the computer is caused to execute a network optimization method provided in the first aspect.

In a fifth aspect, an embodiment of the present invention provides a computer program product containing instructions, which, when run on a computer, causes the computer to execute the network optimization method of the first aspect and any one of the implementations thereof.

In the network optimization method and apparatus provided in the embodiments of the present invention, a network optimization device obtains traffic characteristic information of multiple time intervals corresponding to a target cell, where the traffic characteristic information of a time interval includes a traffic of the target cell during data transmission in the time interval, an occupied number of CCEs in a PDCCH corresponding to the time interval, and an available number of CCEs in the PDCCH corresponding to the time interval; then, the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; and then the network optimization equipment performs network optimization on the target cell according to the type of the target cell. In the embodiment of the invention, the type of the target cell is determined based on the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell, the busy hour flow of the target cell is used for representing the flow characteristic of the target cell during data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree of the target cell during data transmission. The network optimization equipment can determine the type of the target cell based on more factors or conditions, and further determine the network optimization mode of the target cell according to more cell types, so that the rationality of determining the type of the target cell can be improved, and the rationality of network optimization is further improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.

Fig. 1 is a hardware schematic diagram of a server according to an embodiment of the present invention;

fig. 2 is a first schematic diagram illustrating a network optimization method according to an embodiment of the present invention;

fig. 3 is a second schematic diagram of a network optimization method according to an embodiment of the present invention;

fig. 4 is a schematic diagram illustrating a type of a target cell determined based on a two-dimensional space according to an embodiment of the present invention;

fig. 5 is a first schematic structural diagram of a network optimization apparatus according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a network optimization apparatus according to an embodiment of the present invention.

Detailed Description

The network optimization method and apparatus provided by the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

The terms "first" and "second" etc. in the description and drawings of the present application are used to distinguish different objects and not to describe a specific order of objects, e.g. the first PDCCH load-level difference threshold and the second PDCCH load-level difference threshold etc. are used to distinguish different PDCCH load-level difference thresholds and not to describe a specific order of PDCCH load-level difference thresholds.

Furthermore, the terms "including" and "having," and any variations thereof, as referred to in the description of the present application, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements but may alternatively include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "e.g.," an embodiment of the present invention is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

The term "and/or" as used herein includes the use of either or both of the two methods.

In the description of the present application, the meaning of "a plurality" means two or more unless otherwise specified.

The following explains some concepts related to a network optimization method and device provided by the embodiments of the present invention.

The PDCCH may carry scheduling information and other control information, and specifically may include a transmission format, resource allocation, uplink scheduling grant, power control, and the like. In order to more efficiently configure the video resources of PDCCH and other downlink control channels, Long Term Evolution (LTE) defines two dedicated control channel resource units: RE groups (REGs) and CCEs, one CCE consists of 9 REGs. Herein, REG is used to support resource allocation of a control channel with a small data rate, such as a Physical Control Format Indication Channel (PCFICH) and a physical hybrid automatic repeat request indication channel (PHICH), and CCE is used to support resource allocation of a PDCCH with a large data amount. In the embodiment of the present invention, the network optimization device may determine the PDCCH load rate corresponding to a time interval according to the available number of CCEs in the PDCCH corresponding to the time interval and the available number of CCEs in the PDCCH corresponding to the time interval.

Based on the problems existing in the background art, embodiments of the present invention provide a method and an apparatus for network optimization, where a network optimization device obtains traffic characteristic information of multiple time intervals corresponding to a target cell, where the traffic characteristic information of a time interval includes traffic of the target cell during data transmission in the time interval, the number of CCEs occupied in a PDCCH corresponding to the time interval, and the available number of CCEs in the PDCCH corresponding to the time interval; then, the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; and then the network optimization equipment performs network optimization on the target cell according to the type of the target cell. In the embodiment of the invention, the type of the target cell is determined based on the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell, the busy hour flow of the target cell is used for representing the flow characteristic of the target cell during data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree of the target cell during data transmission. The network optimization equipment can determine the type of the target cell based on more factors or conditions, and further determine the network optimization mode of the target cell according to more cell types, so that the rationality of determining the type of the target cell can be improved, and the rationality of network optimization is further improved.

An embodiment of the present invention provides a network optimization device, where the network optimization device may be a server, and fig. 1 is a schematic diagram of a hardware structure of the server in the network optimization method provided in the embodiment of the present invention. As shown in fig. 1, the server 10 includes a processor 101, a memory 102, a network interface 103, and the like.

The processor 101 is a core component of the server 10, and the processor 101 is configured to run an operating system of the server 10 and application programs (including a system application program and a third-party application program) on the server 10, so as to implement the network optimization method performed by the server 10.

In an embodiment of the present invention, the processor 101 may be a Central Processing Unit (CPU), a microprocessor, a Digital Signal Processor (DSP), an application-specific integrated circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, transistor logic, hardware component, or any combination thereof, which is capable of implementing or executing various exemplary logic blocks, modules, and circuits described in connection with the disclosure of an embodiment of the present invention; a processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, a DSP and a microprocessor, or the like.

Optionally, the processor 101 of the server 10 includes one or more CPUs, which are single-core CPUs (single-CPUs) or multi-core CPUs (multi-CPUs).

The memory 102 includes, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical memory, or the like. The memory 102 holds the code of the operating system.

Optionally, the processor 101 reads the instructions stored in the memory 102 to implement the network optimization method in the embodiment of the present invention, or the processor 101 implements the network optimization method provided in the embodiment of the present invention by using the instructions stored inside. In the case that the processor 101 implements the network optimization method provided by the embodiment of the present invention by reading the execution saved in the memory, the memory stores instructions for implementing the network optimization method provided by the embodiment of the present invention.

The network interface 103 is a wired interface, such as a Fiber Distributed Data Interface (FDDI) interface or a Gigabit Ethernet (GE) interface. Alternatively, the network interface 103 is a wireless interface. The network interface 103 is used for the server 10 to communicate with other devices.

The memory 102 is used for storing the traffic of the target cell during a time interval for data transmission. Optionally, the memory 102 is further configured to store the number of occupied CCEs in the PDCCH corresponding to the time interval, the available number of CCEs in the PDCCH corresponding to the time interval, and the like. The at least one processor 101 further executes the method described in the embodiment of the present invention according to the traffic of the target cell during data transmission in a time interval, the occupied number of CCEs in the PDCCH corresponding to the time interval, and the available number of CCEs in the PDCCH corresponding to the time interval, which are stored in the memory 102. For more details of the above functions implemented by the processor 101, reference is made to the following description of various method embodiments.

Optionally, the server 10 further includes a bus, and the processor 101 and the memory 102 are connected to each other through the bus 104, or in other manners.

Optionally, the server 10 further includes an input/output interface 105, where the input/output interface 105 is configured to connect with an input device, and receive traffic characteristic information of a plurality of time intervals corresponding to the target cell, which is input by the user through the input device. Input devices include, but are not limited to, a keyboard, a touch screen, a microphone, and the like. The input/output interface 105 is further configured to connect with an output device, and output a network optimization result of the processor 101 (i.e., determine a network optimization mode corresponding to the target cell). Output devices include, but are not limited to, a display, a printer, and the like.

The network optimization method and device provided by the embodiment of the invention are applied to a scene that a certain cell (namely, a target cell) needs to be subjected to network optimization, and after network optimization equipment acquires certain information of the target cell, namely, flow characteristic information of a plurality of time intervals corresponding to the target cell, the type of the target cell can be determined according to specific contents in the flow characteristic information, and then the network optimization is carried out on the target cell based on the type of the target cell.

As shown in fig. 2, the network optimization method provided by the embodiment of the present invention may include S101 to S103.

S101, the network optimization equipment acquires traffic characteristic information of a plurality of time intervals corresponding to the target cell.

The traffic characteristic information of a time interval includes traffic of a target cell during data transmission in the time interval, the number of CCEs occupied in the PDCCH corresponding to the time interval, and the available number of CCEs in the PDCCH corresponding to the time interval.

It should be understood that the network optimization device may obtain the traffic characteristic information from the network management device. Specifically, the gateway device may obtain traffic characteristic information of a plurality of time intervals corresponding to the target cell, and send the traffic characteristic information corresponding to the plurality of time intervals to the network optimization device. In an implementation manner, assuming that the multiple time intervals respectively correspond to multiple first time intervals, the network management device may further obtain traffic characteristic information of the target cell in multiple second time intervals, and send the traffic characteristics of the multiple second time intervals to the network optimization device, and the network optimization device integrates and determines the traffic characteristic information of the multiple first time intervals, where a time length corresponding to one first time interval is greater than a time length corresponding to one second time interval.

It can be understood that the occupied number of CCEs in a PDCCH corresponding to a time interval is the used number of CCEs in the PDCCH corresponding to the time interval of the target cell. Similarly, the available number of CCEs in the PDCCH corresponding to a time interval is the total number of CCEs in the PDCCH corresponding to the time interval that can be used by the target cell.

It should be noted that, the flow rate of the target cell during data transmission in a time interval may be a Media Access Control (MAC) layer flow or a downlink MAC layer flow rate of the target cell corresponding to the time interval, may also be a sum of an uplink MAC layer flow rate and a downlink MAC layer flow rate of the target cell corresponding to the time interval, and may also be a Packet Data Convergence Protocol (PDCP) layer flow rate corresponding to the time interval of the target cell.

Optionally, the one time interval (or the first time interval) may be 1 hour or 30 minutes, and the time length corresponding to the time interval is not specifically limited in the embodiment of the present invention.

S102, the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell.

The busy hour flow of the target cell is used to represent a flow characteristic when the target cell performs data transmission, and specifically, the larger the busy hour flow of the target cell is, the larger the flow when the target cell performs data transmission is. The PDCCH load difference value of the target cell is used to characterize the frequency of the target cell during data transmission, and specifically, the larger the PDCCH load difference value of the target cell is, the higher the frequency of the target cell during data transmission is.

It should be understood that after the network optimization device obtains the traffic characteristic information of the multiple time intervals corresponding to the target cell, the busy-time traffic of the target cell may be determined based on the traffic of the target cell when data transmission is respectively performed in the multiple time intervals, and the PDCCH load factor difference of the target cell may be determined based on the number of CCEs occupied in the PDCCH corresponding to each of the multiple time intervals and the possible number of CCEs in the PDCCH corresponding to each of the multiple time intervals. And then, determining the type of the target cell based on the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell.

S103, network optimization equipment carries out network optimization on the target cell according to the type of the target cell.

It should be understood that different types of cells may correspond to different network optimization approaches. For example, physical resources may be added to a cell having a large traffic volume when data transmission is performed.

In the network optimization method provided by the embodiment of the invention, network optimization equipment acquires flow characteristic information of a plurality of time intervals corresponding to a target cell, wherein the flow characteristic information of one time interval comprises the flow of the target cell during data transmission in the time interval, the number of CCEs occupied in a PDCCH corresponding to the time interval and the available number of CCEs in the PDCCH corresponding to the time interval; then, the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; and then the network optimization equipment performs network optimization on the target cell according to the type of the target cell. In the embodiment of the invention, the type of the target cell is determined based on the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell, the busy hour flow of the target cell is used for representing the flow characteristic of the target cell during data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree of the target cell during data transmission. The network optimization equipment can determine the type of the target cell based on more factors or conditions, and further determine the network optimization mode of the target cell according to more cell types, so that the rationality of determining the type of the target cell can be improved, and the rationality of network optimization is further improved.

As shown in fig. 3, in one implementation manner, the network optimization method provided by the embodiment of the present invention includes S201 to S208.

S201, the network optimization equipment acquires traffic characteristic information of a plurality of time intervals corresponding to the target cell.

It should be understood that the explanation of S201 may refer to the description in S101 above, and is not repeated here.

S202, the network optimization equipment determines M time intervals, wherein the flow is greater than or equal to the flow threshold value when data transmission is carried out, from the multiple time intervals.

Wherein M is an integer greater than or equal to 1.

It should be understood that the traffic during data transmission in a time interval is used to indicate the data transmission condition of the target cell in the time interval, i.e. to reflect the size of the data traffic generated by the target cell in the time interval. In the embodiment of the present invention, the network optimization device may reflect the data transmission condition of the target cell based on the flow rate when the data transmission is performed in the M time intervals.

For example, table 1 below shows an example of traffic when data transmission is performed in each of 8 time intervals corresponding to the target cell.

TABLE 1

Assuming that the traffic threshold is 10GB/hour, the network optimization device determines that M is 3, and the M time intervals are time interval 4, time interval 5, and time interval 6.

S203, the network optimization equipment determines the average value of the flow when data transmission is carried out in the M time intervals as the busy hour flow of the target cell.

In an implementation manner of the embodiment of the present invention, the network optimization device may also determine, in the M time intervals, a maximum value of traffic during transmission as busy-hour traffic of the target cell.

In connection with the above example in S202, the network optimization device determines that the busy hour traffic of the target cell is 12 GB/hour.

S204, the network optimization equipment determines the PDCCH load rates corresponding to the multiple time intervals according to the available number of CCEs in the PDCCHs corresponding to the multiple time intervals and the available number of CCEs in the PDCCHs corresponding to the multiple time intervals.

The PDCCH load rate corresponding to a time interval is the ratio of the number of occupied CCEs in the PDCCH corresponding to the time interval to the available number of CCEs in the PDCCH corresponding to the time interval.

It should be understood that the PDCCH loading rate corresponding to a time interval is used to indicate the channel quality of the target cell corresponding to the time interval. Specifically, a user (or User Equipment (UE)) in the target cell sends a channel Sounding Reference Signal (SRS) to a network device (e.g., a base station), and the base station may detect a channel of the UE based on the SRS, that is, detect channel quality of the UE. If the channel quality of the UE is good (or the downlink channel environment is good), the base station may only need to allocate one CCE to the UE; if the channel quality of the UE is poor (or the downlink channel environment is poor), the base station may need to allocate more CCEs to the UE. Thus, it can be determined that, if the PDCCH load rate corresponding to a time interval (i.e. the PDCCH load rate corresponding to the target cell in the time interval) is greater, it indicates that the channel quality of the target cell in the time interval is poor; if the PDCCH load factor corresponding to the time interval is small, it indicates that the channel quality of the target cell in the time interval is good.

S205, the network optimization device determines N time intervals with the PDCCH load rate being greater than or equal to the PDCCH load rate threshold value from the multiple time intervals.

Wherein N is an integer greater than or equal to 1.

Exemplarily, the following table 2 is an example of PDCCH load ratios corresponding to each of 8 time intervals corresponding to the target cell determined by the network optimization device based on S204.

TABLE 2

Assuming that the PDCCH load factor threshold is 0.6, the network optimization device determines that N is 3, and the N time intervals are time interval 1, time interval 2, and time interval 3.

S206, the network optimization equipment determines the difference value of the target PDCCH load rate of the target cell and the busy hour PDCCH load rate of the target cell as the PDCCH load rate difference value of the target cell.

The target PDCCH load rate of the target cell is the average value of the PDCCH load rates corresponding to the N time intervals, and the busy hour PDCCH load rate of the target cell is the average value of the PDCCH load rates corresponding to the M time intervals.

In conjunction with the above description of the embodiments, it should be understood that the PDCCH load rate difference of the target cell is used to characterize how frequently the target cell performs data transmission. The larger the difference value of the load rate of the PDCCH of the target cell is, the more frequent the data transmission of the target cell is (i.e. the more frequent the data transmission is); otherwise, the frequency degree of data transmission of the target cell is low.

With reference to the examples in table 1 and table 2, the network optimization device determines that the target PDCCH load rate (i.e., the average of PDCCH load rates corresponding to time interval 1, time interval 2, and time interval 3) of the target cell is 0.7, and the busy PDCCH load rate (i.e., the average of PDCCH load rates corresponding to time interval 4, time interval 5, and time interval 6) of the target cell is 0.3, that is, the network optimization device determines that the PDCCH load rate difference of the target cell is 0.4.

In an implementation manner of the embodiment of the present invention, the network optimization device may also determine, in the N time intervals, a maximum value of the PDCCH load ratios as the target PDCCH load ratio. Similarly, the maximum value of the PDCCH loading rate in the M time intervals may also be determined as the busy PDCCH loading rate of the target cell.

S207, the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell.

In conjunction with the above description of the embodiments, it should be understood that the busy hour traffic of the target cell is used to characterize traffic characteristics when the target cell performs data transmission, and the PDCCH load rate difference value of the target cell is used to characterize how frequently the target cell performs data transmission.

In an implementation manner of the embodiment of the present invention, the target cell is one of the following 4 types of cells: a hybrid cell, a high flow cell, a small packet cell, or a low flow cell.

It should be understood that a hybrid cell is used to indicate that the cell includes the characteristics of a high flow cell and also the characteristics of a small cell. The high-flow cell is characterized in that the flow rate is large when data transmission is carried out; the packet cell is characterized in that the frequency of data transmission is high, that is, a data transmission task performed in the packet cell is a packet service, which is a service requiring continuous and frequent data transmission and reception, such as instant messaging services like WeChat and QQ. In addition, the low flow cell is characterized by a small flow rate when data transmission is performed.

Specifically, the above S207 may be implemented by step 1 to step 4.

Step 1, when the network optimization equipment determines that the busy hour flow of a target cell is greater than or equal to a busy hour flow threshold and the PDCCH load rate difference of the target cell is greater than or equal to a first PDCCH load rate difference threshold, the network optimization equipment determines that the target cell is a mixed cell.

With reference to the above description of the embodiments, it should be understood that if the busy hour traffic of the target cell is greater than or equal to the busy hour traffic threshold, it indicates that the traffic of the target cell during data transmission is larger, that is, the target cell has the characteristics of the high-flow cell. And if the PDCCH load factor difference of the target cell is greater than or equal to the first PDCCH load factor difference threshold, it indicates that the frequency of data transmission by the target cell is high, that is, the target cell also has the characteristics of a cell. Thus, the network optimization device determines the target cell as a hybrid cell.

And 2, under the condition that the network optimization equipment determines that the busy hour flow of the target cell is greater than or equal to a busy hour flow threshold and the PDCCH load rate difference of the target cell is less than a first PDCCH load rate difference threshold, the network optimization equipment determines that the target cell is a high-flow cell.

It can be appreciated that a busy hour traffic of the target cell greater than or equal to the busy hour traffic threshold indicates that the traffic of the target cell during data transmission is large, i.e. the target cell has the characteristics of a high-flow cell. However, the PDCCH load rate difference of the target cell being smaller than the first PDCCH load rate difference threshold indicates that the frequency of data transmission by the target cell is low, and the target cell does not have the characteristics of a cell. The network equipment determines that the target cell is a high-flow cell.

And 3, the network optimization equipment determines that the target cell is a small cell under the condition that the busy hour flow of the target cell is smaller than a busy hour flow threshold and the PDCCH load rate difference of the target cell is larger than or equal to a second PDCCH load rate difference threshold.

And the second PDCCH load rate difference threshold is larger than the first PDCCH load rate difference threshold.

It should be understood that the busy hour traffic of the target cell being less than the busy hour traffic threshold indicates that the traffic of the target cell during data transmission is less, i.e. the target cell has the characteristics of a low-flow cell. However, the PDCCH load rate difference of the target cell being greater than or equal to the second PDCCH load rate difference threshold indicates that the frequency of data interaction is high in the target cell, and the target cell has the characteristics of a cell. Thus, the network device determines the target cell as a small cell.

And 4, under the condition that the network optimization equipment determines that the busy hour flow of the target cell is smaller than a busy hour flow threshold and the PDCCH load rate difference of the target cell is smaller than a second PDCCH load rate difference threshold, the network optimization equipment determines that the target cell is a low-flow cell.

It will be appreciated that a target cell having a busy hour traffic less than the busy hour traffic threshold indicates that the target cell has less traffic for data transmission, i.e., the target cell does not have the characteristics of a high flow cell (or has the characteristics of a low flow cell). And the PDCCH load rate difference value of the target cell is smaller than the second PDCCH load rate difference threshold value, which indicates that the frequency degree of data transmission of the target cell is low, and the target cell does not have the characteristics of a cell. When the target cell has neither the characteristics of the high-flow cell nor the characteristics of the packet cell, the network optimization device determines that the target cell is a low-flow cell.

Illustratively, in conjunction with the examples in S203 and S206, it is assumed that the busy hour traffic threshold is 10GB/hour, the first PDCCH load rate difference threshold is 0.3, and the second PDCCH load rate difference threshold is 0.6. The network optimization device determines the target cell to be a hybrid cell.

In an implementation manner of the embodiment of the present invention, the process of determining the type of the target cell by the network optimization device based on the busy hour traffic of the target cell and the PDCCH load rate difference of the target cell may be exemplified by a two-dimensional space as shown in fig. 4.

Wherein S represents the busy hour traffic of the target cell, S₁Represents a busy hour traffic threshold, Δ η represents a PDCCH load rate of a target cell, Δ η₁Represents a first PDCCH load difference threshold, Δ η₂Represents a second PDCCH load-rate difference threshold. Specifically, when a data point corresponding to the target cell (namely, a coordinate point corresponding to the busy hour flow of the target cell is used as an abscissa and the PDCCH load rate difference value of the target cell is used as an ordinate) is located in the first space, determining that the target cell is a mixed cell; when the data point corresponding to the target cell is located in the second space, determining the target cell as a high-flow cell; when the data point corresponding to the target cell is located in the space III, determining the target cell as a small cell; and when the data points corresponding to the target cell are located in the space four, determining that the target cell is a low-flow cell.

In an implementation manner, the network optimization device may further determine whether the target cell is a high-flow cell or a low-flow cell based on the busy hour traffic of the target cell, and then determine whether the target cell is a hybrid cell or a packet cell based on a PDCCH load rate difference of the target cell. Specifically, the method can be realized through steps A to D.

Step A, under the condition that the busy hour flow of the target cell is larger than or equal to a busy hour flow threshold value, the network optimization equipment determines that the target cell is a high-flow cell.

And step B, under the condition that the busy hour flow of the target cell is smaller than the busy hour flow threshold, the network optimization equipment determines that the target cell is a low-flow cell.

And step C, under the condition that the target cell is a high-flow cell and the PDCCH load rate difference value of the target cell is greater than or equal to the first PDCCH load rate difference value threshold, the network equipment determines that the target cell is a mixed cell.

And D, under the condition that the target cell is a low-flow cell and the PDCCH load rate difference value of the target cell is greater than or equal to the second PDCCH load rate difference value threshold value, the network equipment determines that the target cell is a small cell.

In the embodiment of the present invention, the network optimization device may determine the type of the target cell based on the busy hour traffic of the target cell and the PDCCH load rate difference of the target cell (that is, determine the target cell as one of the 4 types of cells), or may determine the target cell as a mixed cell or a packet cell based on the PDCCH load rate difference of the target cell after determining the target cell as a high-flow cell or a low-flow cell based on the busy hour traffic of the target cell.

And S208, the network optimization equipment performs network optimization on the target cell according to the type of the target cell.

In an implementation manner of the embodiment of the present invention, when the network optimization device determines that the target cell is a hybrid cell or a high-flow cell, the network optimization device may determine whether downlink resource expansion needs to be performed on the target cell according to the busy-hour traffic of the downlink MAC layer of the target cell.

Specifically, when the traffic of the target cell in the busy downlink MAC layer is smaller than the traffic threshold in the busy downlink MAC layer, the network optimization device determines that the target cell does not need to expand the capacity of downlink resources, that is, does not need to add physical resources, including adding frequency points, a base station, and the like, to the target cell.

Optionally, the network optimization device may configure different downlink MAC layer busy hour traffic thresholds for the hybrid cell and the high-flow cell, respectively. For example, the hybrid cell corresponds to a first downlink MAC layer busy traffic threshold, the high-flow cell corresponds to a second downlink MAC layer busy traffic threshold, and the first downlink MAC layer busy traffic threshold is smaller than the second downlink MAC layer busy traffic threshold.

When the traffic of the target cell in the busy hour of the downlink MAC layer is greater than or equal to the threshold of the traffic of the busy hour of the downlink MAC layer, the network optimization device determines whether the number of data streams of the transport layer corresponding to the target cell (i.e., the number of data streams transmitted by the target cell on the same video resource) is greater than or equal to the threshold of the number of data streams.

Under the condition that the network optimization equipment determines that the number of the data streams of the transmission layer corresponding to the target cell is greater than or equal to the threshold value of the number of the data streams, the network optimization equipment determines that the target cell needs to perform downlink resource capacity expansion and data stream number capacity expansion, namely, physical resources are added for the target cell and the number of the data streams is added for the target cell.

And under the condition that the network optimization equipment determines that the number of the data streams of the transmission layer corresponding to the target cell is smaller than the threshold value of the number of the data streams, the network equipment determines whether the target cell has an optimization space from an equipment manufacturer. If the target cell has an optimization space, configuring a pairing algorithm for the target cell, namely establishing pairing among a plurality of users for the users in the target cell and matching with multi-stream data of the same user; and if the target cell has no optimization space, performing downlink resource expansion on the target cell, namely adding frequency points, base stations and the like for the target cell.

In another implementation manner of the embodiment of the present invention, when the network optimization device determines that the target cell is a small cell, the network optimization device may determine whether network optimization needs to be performed on the target cell according to the number of Radio Resource Control (RRC) busy connection users of the target cell.

Specifically, when the number of users connected in an RRC busy hour of the target cell is smaller than the threshold number of users connected in an RRC busy hour, the network optimization determines that the target cell does not need network optimization (or capacity expansion).

And when the number of the users connected in the RRC busy hour of the target cell is larger than or equal to the threshold value of the number of the users connected in the RRC busy hour, the network optimization equipment determines to increase the RRC lisscience (authorization) for the target cell.

It should be understood that the number of users connected in the RRC busy hour of the target cell is used to indicate the number of users that the target cell can serve together, and the more RRC lists of the target cell, the more users that the target cell can intervene in.

In one implementation, in a case where the network optimization device determines that the target cell is a low-flow cell, the network optimization device determines that network optimization is not required for the target cell.

The embodiment of the present invention may perform division of function modules on the network optimization device and the like according to the method example, for example, each function module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, the division of the modules in the embodiment of the present invention is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

In the case of dividing each functional module by corresponding functions, fig. 5 shows a schematic structural diagram of a possible network optimization device according to the foregoing embodiment, and as shown in fig. 5, the network optimization device 20 may include: an acquisition module 201, a determination module 202 and a network optimization module 203.

An obtaining module 201, configured to obtain traffic characteristic information of multiple time intervals corresponding to a target cell, where the traffic characteristic information of a time interval includes a traffic of the target cell during data transmission in the time interval, an occupied number of CCEs in a PDCCH corresponding to the time interval, and an available number of CCEs in the PDCCH corresponding to the time interval.

A determining module 202, configured to determine a type of the target cell according to a busy hour traffic of the target cell and a PDCCH load rate difference of the target cell; the busy hour flow of the target cell is used for representing the flow characteristic when the target cell performs data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree when the target cell performs data transmission.

And the network optimization module 203 is configured to perform network optimization on the target cell according to the type of the target cell.

Optionally, the determining module 202 is specifically configured to determine PDCCH load ratios corresponding to the multiple time intervals according to the number of occupied CCEs in the PDCCH corresponding to each of the multiple time intervals and the available number of CCEs in the PDCCH corresponding to each of the multiple time intervals, where the PDCCH load ratio corresponding to one time interval is a ratio of the number of occupied CCEs in the PDCCH corresponding to the time interval to the available number of CCEs in the PDCCH corresponding to the time interval; determining N time intervals with the PDCCH load rate being greater than or equal to the PDCCH load rate threshold value from the plurality of time intervals, wherein N is an integer greater than or equal to 1; determining the difference value of the target PDCCH load rate of the target cell and the busy hour PDCCH load rate of the target cell as the PDCCH load rate difference value of the target cell; the target PDCCH load rate of the target cell is an average value of PDCCH load rates corresponding to the N time intervals, and the busy PDCCH load rate of the target cell is an average value of PDCCH load rates corresponding to the M time intervals.

Optionally, the determining module 202 is further specifically configured to determine, from the multiple time intervals, M time intervals in which the traffic during data transmission is greater than or equal to a traffic threshold, where M is an integer greater than or equal to 1; and determining the average value of the flow when the M time intervals carry out data transmission as the busy-time flow of the target cell.

Optionally, the target cell is one of the following 4 types of cells: a hybrid cell, a high flow cell, a small packet cell, or a low flow cell;

the determining module 202 is further specifically configured to determine that the target cell is the hybrid cell when the determining module determines that the busy hour traffic of the target cell is greater than or equal to the busy hour traffic threshold and the PDCCH load rate difference of the target cell is greater than or equal to the first PDCCH load rate difference threshold.

The determining module 202 is further specifically configured to determine that the target cell is the high-flow cell when the determining module determines that the busy hour traffic of the target cell is greater than or equal to the busy hour traffic threshold and the PDCCH load rate difference of the target cell is smaller than the first PDCCH load rate difference threshold.

The determining module 202 is further specifically configured to determine that the target cell is the small cell if the determining module determines that the busy hour traffic of the target cell is smaller than the busy hour traffic threshold and the PDCCH load rate difference of the target cell is greater than or equal to a second PDCCH load rate difference threshold, where the second PDCCH load rate difference threshold is greater than the first PDCCH load rate difference threshold.

The determining module 202 is further specifically configured to determine that the target cell is the low-flow cell when the determining module determines that the busy hour traffic of the target cell is smaller than the busy hour traffic threshold and the PDCCH load rate difference of the target cell is smaller than the second PDCCH load rate difference threshold.

Fig. 6 shows a schematic diagram of a possible structure of the network optimization device according to the above-described embodiment, in the case of an integrated unit. As shown in fig. 6, the network optimization device 30 may include: a processing module 301 and a communication module 302. The processing module 301 may be configured to control and manage the actions of the network optimization device 30, for example, the processing module 301 may be configured to support the network optimization device 30 to execute S102 and S103 in the above method embodiments. The communication module 302 may be configured to support the network optimization device 30 to communicate with other entities, for example, the communication module 302 may be configured to support the network optimization device 30 to execute S101 in the above method embodiment. Optionally, as shown in fig. 6, the network optimization device 30 may further include a storage module 303 for storing program codes and data of the network optimization device 30.

The processing module 301 may be a processor or a controller (e.g., the processor 101 shown in fig. 1). The communication module 302 may be a transceiver, a transceiver circuit, or a communication interface, etc. (e.g., may be the network interface 103 shown in fig. 1 described above). The storage module 103 may be a memory (e.g., may be the memory 102 described above in fig. 1).

When the processing module 301 is a processor, the communication module 302 is a transceiver, and the storage module 303 is a memory, the processor, the transceiver, and the memory may be connected via a bus. The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc.

It should be understood that, in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented using a software program, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the invention are all or partially effected when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optics, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or can comprise one or more data storage devices, such as a server, a data center, etc., that can be integrated with the medium. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for network optimization, comprising:

the method comprises the steps that network optimization equipment obtains flow characteristic information of a plurality of time intervals corresponding to a target cell, wherein the flow characteristic information of one time interval comprises the flow of the target cell during data transmission in the time interval, the number of occupied CCEs (control channel elements) in a Physical Downlink Control Channel (PDCCH) corresponding to the time interval and the available number of CCEs in the PDCCH corresponding to the time interval;

the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; the busy hour flow of the target cell is used for representing the flow characteristic when the target cell performs data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree when the target cell performs data transmission;

the network optimization equipment performs network optimization on the target cell according to the type of the target cell;

the determining, by the network optimization device, the PDCCH load factor difference of the target cell includes:

the network optimization equipment determines PDCCH load rates corresponding to the time intervals according to the number of CCEs occupied in the PDCCHs corresponding to the time intervals and the available number of the CCEs in the PDCCHs corresponding to the time intervals, wherein the PDCCH load rate corresponding to one time interval is the ratio of the number of the CCEs occupied in the PDCCHs corresponding to the time interval to the available number of the CCEs in the PDCCHs corresponding to the time interval;

the network optimization equipment determines N time intervals with the PDCCH load rate being greater than or equal to a PDCCH load rate threshold value from the plurality of time intervals, wherein N is an integer greater than or equal to 1;

the network optimization equipment determines the difference value of the target PDCCH load rate of the target cell and the busy hour PDCCH load rate of the target cell as the PDCCH load rate difference value of the target cell; the target PDCCH load rate of the target cell is the average value of the PDCCH load rates corresponding to the N time intervals, the busy hour PDCCH load rate of the target cell is the average value of the PDCCH load rates corresponding to the M time intervals, and M is an integer greater than or equal to 1.

2. The method of claim 1, wherein the network optimization device determining busy hour traffic of the target cell comprises:

the network optimization equipment determines the M time intervals with the flow greater than or equal to a flow threshold value when data transmission is carried out from the multiple time intervals, wherein M is an integer greater than or equal to 1;

and the network optimization equipment determines the average value of the flow when the data transmission is carried out in the M time intervals as the busy hour flow of the target cell.

3. The method of claim 2, wherein the target cell is one of the following 4 types of cells: a hybrid cell, a high flow cell, a small packet cell, or a low flow cell;

the network optimization equipment determines the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell, and the determination comprises the following steps:

when the network optimization equipment determines that the busy hour flow of the target cell is greater than or equal to a busy hour flow threshold and the PDCCH load rate difference of the target cell is greater than or equal to a first PDCCH load rate difference threshold, the network optimization equipment determines that the target cell is the mixed cell;

when the network optimization equipment determines that the busy hour traffic of the target cell is greater than or equal to the busy hour traffic threshold and the PDCCH load rate difference of the target cell is less than the first PDCCH load rate difference threshold, the network optimization equipment determines that the target cell is the high-flow cell;

when the network optimization equipment determines that the busy hour flow of the target cell is smaller than the busy hour flow threshold and the PDCCH load rate difference of the target cell is greater than or equal to a second PDCCH load rate difference threshold, the network optimization equipment determines that the target cell is the small cell, and the second PDCCH load rate difference threshold is greater than the first PDCCH load rate difference threshold;

and under the condition that the network optimization equipment determines that the busy hour flow of the target cell is smaller than the busy hour flow threshold and the PDCCH load rate difference of the target cell is smaller than the second PDCCH load rate difference threshold, the network optimization equipment determines that the target cell is the low-flow cell.

4. The network optimization device is characterized by comprising an acquisition module, a determination module and a network optimization module;

the acquiring module is configured to acquire traffic characteristic information of multiple time intervals corresponding to a target cell, where the traffic characteristic information of a time interval includes traffic of the target cell during data transmission in the time interval, an occupied number of Control Channel Elements (CCEs) in a Physical Downlink Control Channel (PDCCH) corresponding to the time interval, and an available number of CCEs in the PDCCH corresponding to the time interval;

the determining module is used for determining the type of the target cell according to the busy hour flow of the target cell and the PDCCH load rate difference value of the target cell; the busy hour flow of the target cell is used for representing the flow characteristic when the target cell performs data transmission, and the PDCCH load rate difference value of the target cell is used for representing the frequency degree when the target cell performs data transmission;

the network optimization module is used for carrying out network optimization on the target cell according to the type of the target cell;

the determining module is specifically configured to determine PDCCH load ratios corresponding to the multiple time intervals according to the number of occupied CCEs in the PDCCH corresponding to each of the multiple time intervals and the available number of CCEs in the PDCCH corresponding to each of the multiple time intervals, where the PDCCH load ratio corresponding to one time interval is a ratio of the number of occupied CCEs in the PDCCH corresponding to the time interval to the available number of CCEs in the PDCCH corresponding to the time interval; determining N time intervals with the PDCCH load rate being greater than or equal to a PDCCH load rate threshold value from the plurality of time intervals, wherein N is an integer greater than or equal to 1; determining the difference value of the target PDCCH load rate of the target cell and the busy hour PDCCH load rate of the target cell as the PDCCH load rate difference value of the target cell; the target PDCCH load rate of the target cell is the average value of the PDCCH load rates corresponding to the N time intervals, the busy hour PDCCH load rate of the target cell is the average value of the PDCCH load rates corresponding to the M time intervals, and M is an integer greater than or equal to 1.

5. The network optimization device of claim 4,

the determining module is specifically further configured to determine, from the multiple time intervals, the M time intervals in which a traffic during data transmission is greater than or equal to a traffic threshold, where M is an integer greater than or equal to 1; and determining the average value of the flow when the M time intervals carry out data transmission as the busy hour flow of the target cell.

6. The network optimization device of claim 5, wherein the target cell is one of the following 4 types of cells: a hybrid cell, a high flow cell, a small packet cell, or a low flow cell;

the determining module is specifically further configured to determine that the target cell is the hybrid cell when the determining module determines that the busy hour traffic of the target cell is greater than or equal to a busy hour traffic threshold and the PDCCH load rate difference of the target cell is greater than or equal to a first PDCCH load rate difference threshold;

the determining module is specifically further configured to determine that the target cell is the high-flow cell when the determining module determines that the busy hour traffic of the target cell is greater than or equal to the busy hour traffic threshold and the PDCCH load rate difference of the target cell is smaller than the first PDCCH load rate difference threshold;

the determining module is further specifically configured to determine that the target cell is the small cell if the determining module determines that the busy hour traffic of the target cell is smaller than the busy hour traffic threshold and the PDCCH load rate difference of the target cell is greater than or equal to a second PDCCH load rate difference threshold, where the second PDCCH load rate difference threshold is greater than the first PDCCH load rate difference threshold;

the determining module is further specifically configured to determine that the target cell is the low-flow cell when the determining module determines that the busy hour traffic of the target cell is smaller than the busy hour traffic threshold and the PDCCH load rate difference of the target cell is smaller than the second PDCCH load rate difference threshold.

7. A network optimization device, the network optimization device comprising: a processor, a memory, a bus, and a communication interface; the memory is used for storing computer-executable instructions, and when the network optimization device runs, the processor executes the computer-executable instructions stored in the memory, so that the network optimization device executes the network optimization method according to any one of claims 1 to 3.

8. A computer-readable storage medium, in which a computer program is stored which, when run on a computer, causes the computer to perform the network optimization method according to any one of claims 1 to 3.