CN111669772B

CN111669772B - Network optimization method and device

Info

Publication number: CN111669772B
Application number: CN202010443830.7A
Authority: CN
Inventors: 杨艳; 朱常波; 冯毅; 张涛; 郭希蕊
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2020-05-22
Filing date: 2020-05-22
Publication date: 2022-04-08
Anticipated expiration: 2040-05-22
Also published as: CN111669772A

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 efficiency of UE (user equipment) in acquiring service data by optimizing a communication network of a target area by increasing the number of base stations of the target area under the condition that the existing base stations of the target area are not enough to meet the communication quality of the target area. The method comprises the following steps: the UE acquires a plurality of network test data groups, wherein one network test data group comprises SINR when the UE receives downlink data and downlink edge rate when the UE receives the downlink data; the UE determines N groups of downlink edge rate thresholds and N rate-SINR combined occupation ratios corresponding to the SINR thresholds according to the SINRs and the downlink edge rates in the multiple network test data groups; and the UE sends the N groups of downlink marginal rate threshold values and SINR threshold values and the N rate-SINR joint occupation ratios to network optimization equipment.

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

With the development of communication technology, the communication quality on a high-speed rail becomes more and more important, and the downlink rate when User Equipment (UE) performs service transmission on the high-speed rail is related to base station configuration along the high-speed rail, and the like.

Currently, a UE may acquire signal quality information of the UE corresponding to a plurality of sampling points on a certain high-speed rail, where the signal quality information of the UE corresponding to one sampling point includes Reference Signal Receiving Power (RSRP) when the UE receives downlink data, signal to interference plus noise ratio (SINR) when the UE receives downlink data, and downlink rate when the UE receives downlink data. The operation and maintenance personnel determine the signal coverage condition of the high-speed rail line according to the signal quality information corresponding to the plurality of sampling points acquired by the UE, for example, determine an average value of downlink rates when the UE corresponding to each of the plurality of sampling points receives downlink data as the downlink rate when the UE receives downlink data on the high-speed rail line, where the downlink rate when the UE receives downlink data may reflect the signal coverage condition of the high-speed rail line, for example, when the downlink rate is high, it indicates that the signal coverage condition of the high-speed rail line is good.

However, when the signal coverage condition of the high-speed rail cannot meet the network establishment requirement of the high-speed rail, for example, when the downlink rate when the UE receives the downlink data on the high-speed rail is lower than a preset downlink rate (specifically, the downlink rate when the UE receives the downlink data specified in the network establishment requirement), the communication quality of the UE on the high-speed rail may be affected, and the efficiency of the UE in performing service transmission may be reduced.

Disclosure of Invention

Embodiments of the present invention provide a network optimization method and apparatus, which can improve efficiency of a UE acquiring service data by increasing the number of base stations in a target area to optimize a communication network in the target area when an existing base station in the target area is not enough to meet communication quality of the target area.

In a first aspect, an embodiment of the present invention provides a network optimization method, including: the UE acquires a plurality of network test data groups, wherein one network test data group comprises SINR when the UE receives downlink data and downlink edge rate when the UE receives the downlink data; the UE determines N groups of downlink edge rate thresholds and N rate-SINR combined occupation ratios corresponding to the SINR thresholds according to the SINRs and the downlink edge rates in the multiple network test data groups, wherein N is a positive integer greater than or equal to 1; wherein, a rate-SINR combined ratio corresponding to a group of downlink edge rate thresholds and SINR thresholds is a ratio of the rate-SINR ratio to the SINR ratio, the rate-SINR ratio is a ratio of the downlink edge rate when the UE receives downlink data to be greater than or equal to the downlink edge rate threshold in the multiple network test data groups, and the SINR when the UE receives downlink data to be greater than or equal to the ratio of the number of network test data groups of the SINR threshold to the number of network test data groups acquired by the UE, the SINR ratio is a ratio of the number of network test data groups of the multiple network test data groups of the SINR when the UE receives downlink data to be greater than or equal to the SINR threshold to the number of network test data groups acquired by the UE; and the UE sends the N groups of downlink edge rate thresholds and SINR thresholds and the N rate-SINR joint occupation ratios to network optimization equipment, wherein the N groups of downlink edge rate thresholds and SINR thresholds and the N rate-SINR joint occupation ratios are used for determining the number of base stations to be increased in a target area.

In a second aspect, an embodiment of the present invention provides a network optimization method, including: the network optimization equipment receives N groups of downlink marginal rate threshold values and SINR threshold values sent by UE, and N rate-SINR joint occupation ratios corresponding to the N groups of downlink marginal rate threshold values and the SINR threshold values, wherein N is a positive integer greater than or equal to 1; wherein, a rate-SINR joint ratio corresponding to a group of downlink edge rate threshold and SINR threshold is the ratio of the rate-SINR ratio to the SINR ratio; the rate-SINR ratio is a ratio of a downlink marginal rate when the UE receives downlink data to a number of network test data groups acquired by the UE, where the downlink marginal rate is greater than or equal to the downlink marginal rate threshold, and the SINR when the UE receives downlink data is greater than or equal to the SINR threshold to the number of network test data groups acquired by the UE; the SINR ratio is a ratio of the number of network test data groups of which SINR is greater than or equal to the SINR threshold when the UE receives downlink data to the number of network test data groups acquired by the UE; the network optimization equipment acquires the downlink edge rate, SINR and the first rate-SINR combined ratio of a target area; the network optimization equipment takes the downlink edge rate as a target downlink edge rate threshold value, takes the SINR as a target SINR threshold value, and determines a second rate-SINR joint occupation ratio corresponding to the target downlink edge rate threshold value and the target SINR threshold value from the N rate-SINR joint occupation ratios; and the network optimization equipment determines the number of the base stations to be added in the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio.

In a third aspect, an embodiment of the present invention provides a UE, including: the device comprises an acquisition module, a determination module and a sending module; the obtaining module is configured to obtain multiple network test data sets, where one network test data set includes an SINR when the UE receives downlink data and a downlink edge rate when the UE receives downlink data; the determining module is configured to determine N groups of downlink edge rate thresholds and N rate-SINR joint occupation ratios corresponding to the SINR thresholds according to the SINR and the downlink edge rate in the multiple network test data groups, where N is a positive integer greater than or equal to 1; wherein, a rate-SINR combined ratio corresponding to a group of downlink edge rate thresholds and SINR thresholds is a ratio of the rate-SINR ratio to the SINR ratio, the rate-SINR ratio is a ratio of the downlink edge rate when the UE receives downlink data to be greater than or equal to the downlink edge rate threshold in the multiple network test data groups, and the SINR when the UE receives downlink data to be greater than or equal to the ratio of the number of network test data groups of the SINR threshold to the number of network test data groups acquired by the UE, the SINR ratio is a ratio of the number of network test data groups of the multiple network test data groups of the SINR when the UE receives downlink data to be greater than or equal to the SINR threshold to the number of network test data groups acquired by the UE; the sending module is configured to send the N sets of downlink edge rate threshold values and SINR threshold values and the N rate-SINR combined ratios to the network optimization device, where the N sets of downlink edge rate threshold values and SINR threshold values and the N rate-SINR combined ratios are used to determine the number of base stations to be added in the target area.

In a fourth aspect, an embodiment of the present invention provides a network optimization device, including: the device comprises a receiving module, an obtaining module and a determining module; the receiving module is used for receiving N groups of downlink edge rate thresholds and signals and SINR thresholds sent by UE, and N rate-SINR joint occupation ratios corresponding to the N groups of downlink edge rate thresholds and SINR thresholds, wherein N is a positive integer greater than or equal to 1; wherein, a rate-SINR joint ratio corresponding to a group of downlink edge rate threshold and SINR threshold is the ratio of the rate-SINR ratio to the SINR ratio; the rate-SINR ratio is a ratio of a downlink marginal rate when the UE receives downlink data to a number of network test data groups acquired by the UE, where the downlink marginal rate is greater than or equal to the downlink marginal rate threshold, and the SINR when the UE receives downlink data is greater than or equal to the SINR threshold to the number of network test data groups acquired by the UE; the SINR ratio is a ratio of the number of network test data groups of which SINR is greater than or equal to the SINR threshold when the UE receives downlink data to the number of network test data groups acquired by the UE; the acquisition module is used for acquiring the downlink edge rate, the SINR and the first rate-SINR combined ratio of the target area; the determining module is configured to determine, from the N rate-SINR joint occupancy ratios, a second rate-SINR joint occupancy ratio corresponding to the target downlink edge rate threshold and the target SINR threshold, using the downlink edge rate as a target downlink edge rate threshold and the SINR as a target SINR threshold; and determining the number of base stations to be added in the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio.

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

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

In a seventh aspect, an embodiment of the present invention provides a computer-readable storage medium, which includes instructions, when executed on a UE, to cause the UE to perform a network optimization method provided in the first aspect.

In an eighth aspect, an embodiment of the present invention provides a computer-readable storage medium, which includes instructions that, when executed on a network optimization device, cause the network optimization device to perform a network optimization method provided in the second aspect.

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

According to the network optimization method and device provided by the embodiment of the invention, UE (user equipment) acquires a plurality of network test data groups, wherein one network test data group comprises SINR (signal to interference plus noise ratio) when the UE receives downlink data and downlink marginal rate when the UE receives the downlink data; then UE determines N groups of downlink edge rate threshold values and N rate-SINR combined occupation ratios corresponding to the SINR threshold values according to the SINRs and the downlink edge rates in the multiple network test data groups; then the UE sends the N groups of downlink marginal rate threshold values and SINR threshold values and the N rate-SINR combined occupation ratios to network optimization equipment; thus, the network optimization device receives the N sets of downlink edge rate thresholds and SINR thresholds sent by the UE, and the N rate-SINR joint fractions; the network optimization device obtains a downlink edge rate, an SINR and a first rate-SINR joint proportion of a target area, the downlink edge rate of the target area is used as a target downlink edge rate threshold, the SINR of the target area is used as a target SINR threshold, and the network optimization device determines a second rate-SINR joint proportion corresponding to the target downlink edge rate threshold and the target SINR threshold from N rate-SINR joint proportions received by the network optimization device; and the network optimization equipment determines the number of base stations to be increased in the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio. In the embodiment of the invention, the UE determines N rate-SINR combined occupation ratios by obtaining a plurality of network test data and according to the SINR and the downlink marginal rate in a plurality of network test data groups; furthermore, the network optimization device may determine, based on the SINR threshold, the edge rate threshold, and the rate-SINR combined ratio determined by the UE, a downlink edge rate of the target area and a second rate-SINR combined ratio corresponding to the SINR, and then, in combination with a preset first rate-SINR combined ratio (the first rate-SINR combined ratio is a requirement index for network establishment, that is, the rate-SINR combined ratio that the target area needs to reach), may determine the number of base stations to be added to the target area. Therefore, under the condition that the existing base stations in the target area are not enough to meet the communication quality of the target area, the communication network of the target area is optimized by increasing the number of the base stations in the target area, and the efficiency of the UE in acquiring the service data can be 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 schematic network architecture of a communication system according to an embodiment of the present invention;

fig. 2 is a hardware schematic diagram of a mobile phone according to an embodiment of the present invention;

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

fig. 4 is a schematic diagram of a network optimization method according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a rectangular plane coordinate system according to an embodiment of the present invention;

fig. 6 is a graph of the rate-SINR ratio in accordance with an embodiment of the present invention;

fig. 7 is a first schematic structural diagram of a UE according to an embodiment of the present invention;

fig. 8 is a second schematic structural diagram of a UE according to an embodiment of the present invention;

fig. 9 is a first schematic structural diagram of a network optimization device according to an embodiment of the present invention;

fig. 10 is a schematic structural diagram of a network optimization device 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 rate-SINR joint proportion and the second rate-SINR joint proportion etc. are used to distinguish different rate-SINR joint proportions and not to describe a specific order of rate-SINR joint proportions.

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.

Some concepts related to a network optimization method and apparatus provided in the embodiments of the present invention are explained below.

Interpolation is an important method for approximation of discrete functions, and an interpolation method can be adopted to estimate approximate values at other points through the value conditions at a limited number of points. Commonly used interpolation methods include polynomial interpolation, spline interpolation, piecewise interpolation, triangular interpolation, and the like. In the embodiment of the invention, the network optimization equipment adopts an interpolation algorithm to determine M groups of downlink edge rate thresholds and SINR thresholds and M rates-SINR combined occupation ratios corresponding to the M groups of downlink edge rate thresholds and SINR thresholds through N groups of downlink edge rate thresholds and SINR thresholds and N rates-SINR combined occupation ratios.

Based on the problems existing in the background art, embodiments of the present invention provide a network optimization method and apparatus, where a UE obtains multiple network test data sets, where one network test data set includes an SINR when the UE receives downlink data and a downlink edge rate when the UE receives downlink data; then UE determines N groups of downlink edge rate threshold values and N rate-SINR combined occupation ratios corresponding to the SINR threshold values according to the SINRs and the downlink edge rates in the multiple network test data groups; then the UE sends the N groups of downlink marginal rate threshold values and SINR threshold values and the N rate-SINR combined occupation ratios to network optimization equipment; thus, the network optimization device receives the N sets of downlink edge rate thresholds and SINR thresholds sent by the UE, and the N rate-SINR joint fractions; the network optimization device obtains a downlink edge rate, an SINR and a first rate-SINR joint proportion of a target area, the downlink edge rate of the target area is used as a target downlink edge rate threshold, the SINR of the target area is used as a target SINR threshold, and the network optimization device determines a second rate-SINR joint proportion corresponding to the target downlink edge rate threshold and the target SINR threshold from N rate-SINR joint proportions received by the network optimization device; and the network optimization equipment determines the number of base stations to be increased in the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio. In the embodiment of the invention, the UE determines N rate-SINR combined occupation ratios by obtaining a plurality of network test data and according to the SINR and the downlink marginal rate in a plurality of network test data groups; furthermore, the network optimization device may determine, based on the SINR threshold, the edge rate threshold, and the rate-SINR combined ratio determined by the UE, a downlink edge rate of the target area and a second rate-SINR combined ratio corresponding to the SINR, and then, in combination with a preset first rate-SINR combined ratio (the first rate-SINR combined ratio is a requirement index for network establishment, that is, the rate-SINR combined ratio that the target area needs to reach), may determine the number of base stations to be added to the target area. Therefore, under the condition that the existing base stations in the target area are not enough to meet the communication quality of the target area, the communication network of the target area is optimized by increasing the number of the base stations in the target area, and the efficiency of the UE in acquiring the service data can be improved.

The network optimization method and apparatus provided by the embodiment of the present invention may be applied to a communication system, and fig. 1 is a schematic diagram of an architecture of a communication system provided by the embodiment of the present invention, where the communication system may include a UE 101 and a network optimization device 102, where the UE 101 is configured to obtain network test data, such as SINR and downlink edge rate when the UE 101 receives downlink data, the network optimization device 102 is configured to determine data of a base station to be added in a target area, and the UE 101 and the network optimization device 102 perform communication, such as when the UE 101 sends multiple rate-SINR combined ratios to the network optimization device 102. In general, in practical applications, the connections between the above-mentioned devices may be wireless connections, and fig. 1 is illustrated with solid lines for convenience of intuitively representing the connection relationships between the devices.

In this embodiment of the present invention, the UE illustrated in fig. 1 may be: a mobile phone, a tablet Computer, a notebook Computer, an Ultra-mobile Personal Computer (UMPC), a netbook, a Personal Digital Assistant (PDA), and the like.

Exemplarily, in the embodiment of the present invention, the UE shown in fig. 1 is taken as an example of a mobile phone, and a hardware structure of the UE provided in the embodiment of the present invention is exemplarily described. As shown in fig. 2, a mobile phone provided in an embodiment of the present invention includes: a processor 20, a Radio Frequency (RF) circuit 21, a power supply 22, a memory 23, an input unit 24, a display unit 25, and an audio circuit 26. Those skilled in the art will appreciate that the configuration of the handset shown in fig. 2 does not constitute a limitation of the handset, and may include more or fewer components than those shown in fig. 2, or may combine some of the components shown in fig. 2, or may be arranged differently than those shown in fig. 2.

The processor 20 is a control center of the mobile phone, connects various parts of the entire mobile phone by using various interfaces and lines, and performs various functions of the mobile phone and processes data by operating or executing software programs and/or modules stored in the memory 23 and calling data stored in the memory 23, thereby performing overall monitoring of the mobile phone. Alternatively, processor 20 may include one or more processing units. Alternatively, the processor 20 may integrate an application processor and a modem processor, wherein the application processor mainly handles operating systems, user interfaces, application programs, and the like; the modem processor handles primarily wireless communications. It will be appreciated that the modem processor described above may also be a processor separate from the processor 20.

The RF circuit 21 may be used to receive and transmit signals during the transmission and reception of information or during a call. For example, the downlink information of the base station is received and then processed by the processor 20; in addition, the uplink data is transmitted to the base station. Typically, the RF circuit includes, but is not limited to, an antenna, at least one Amplifier, a transceiver, a coupler, a Low Noise Amplifier (LNA), and a duplexer. In addition, the handset may also enable wireless communication with other devices in the network via the RF circuitry 21. The wireless Communication may use any Communication standard or protocol, including but not limited to Global System for Mobile Communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), LTE, email, and Short Messaging Service (SMS).

The power supply 22 may be used to power various components of the handset, and the power supply 22 may be a battery. Alternatively, the power supply may be logically connected to the processor 20 through a power management system, such that the power management system performs functions of managing charging, discharging, and power consumption.

The memory 23 may be used to store software programs and modules, and the processor 20 executes various functional applications and data processing of the mobile phone by operating the software programs and modules stored in the memory 23. The memory 23 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, image data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 23 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The input unit 24 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the cellular phone. Specifically, the input unit 24 may include a touch screen 241 and other input devices 242. The touch screen 241, also referred to as a touch panel, may collect touch operations of a user (e.g., operations of the user on or near the touch screen 241 using any suitable object or accessory such as a finger, a stylus, etc.) thereon or nearby, and drive the corresponding connection device according to a preset program. Alternatively, the touch screen 241 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 20, and can receive and execute commands sent by the processor 20. In addition, the touch screen 241 may be implemented in various types, such as resistive, capacitive, infrared, and surface acoustic wave. Other input devices 242 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, power switch keys, etc.), a trackball, a mouse, and a joystick.

The display unit 25 may be used to display information input by the user or information provided to the user and various menus of the mobile phone. The display unit 25 may include a display panel 251. Alternatively, the Display panel 251 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-emitting Diode (OLED), or the like. Further, the touch screen 241 may cover the display panel 251, and when the touch screen 241 detects a touch operation on or near the touch screen 241, the touch screen is transmitted to the processor 20 to determine the type of the touch event, and then the processor 20 provides a corresponding visual output on the display panel 251 according to the type of the touch event. Although in fig. 2 the touch screen 241 and the display panel 251 are shown as two separate components to implement the input and output functions of the mobile phone, in some embodiments, the touch screen 241 and the display panel 251 may be integrated to implement the input and output functions of the mobile phone.

Audio circuitry 26, a speaker 261, and a microphone 262 to provide an audio interface between the user and the handset. In one aspect, the audio circuit 26 may transmit the converted electrical signal of the received audio data to the speaker 261, and the converted electrical signal is converted into a sound signal by the speaker 261 and output. On the other hand, the microphone 262 converts the collected sound signals into electrical signals, which are received by the audio circuit 26 and converted into audio data, which are then output by the processor 20 to the RF circuit 21 for transmission to, for example, another cellular phone, or output by the processor 20 to the memory 23 for further processing.

Optionally, the handset as shown in fig. 2 may also include various sensors. Such as gyroscope sensors, hygrometer sensors, infrared sensors, magnetometer sensors, etc., and will not be described in detail herein.

Optionally, the mobile phone shown in fig. 2 may further include a Wireless fidelity (WiFi) module, a bluetooth module, and the like, which are not described herein again.

Fig. 3 is a schematic diagram of a hardware structure of a network optimization device according to an embodiment of the present invention. As shown in fig. 3, the network optimization device 30 includes a processor 301, a memory 302, a network interface 303, and the like.

The processor 301 is a core component of the network optimization device 30, and the processor 301 is configured to run an operating system of the network optimization device 30 and applications (including a system application and a third-party application) on the network optimization device 30, so as to implement the network optimization method performed by the network optimization device 30.

In this embodiment, the processor 301 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, a transistor logic device, a 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 the 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 301 of the network optimization device 30 includes one or more CPUs, which are single-core CPUs (single-CPUs) or multi-core CPUs (multi-CPUs).

The memory 302 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 302 holds the code for the operating system.

Optionally, the processor 301 implements the network optimization method in the embodiment of the present invention by reading the instructions stored in the memory 302, or the processor 301 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 301 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 303 is a wired interface, such as a Fiber Distributed Data Interface (FDDI) interface or a Gigabit Ethernet (GE) interface. Alternatively, the network interface 303 is a wireless interface. The network interface 303 is used for the network optimization device 30 to communicate with other devices.

The memory 302 is used for storing N sets of downlink edge rate threshold values and SINR threshold values, and N rate-SINR threshold values. Optionally, the memory 302 is also used for storing the current number of base stations in the target area, and the like. The at least one processor 301 further executes the method described in the embodiment of the present invention according to the N sets of downlink edge rate threshold and SINR threshold stored in the memory 302, N rate-SINR thresholds, the current number of base stations in the target area, and the like. For more details of the processor 301 to implement the above functions, reference is made to the following description of various method embodiments.

Optionally, the network optimization device 30 further includes a bus, and the processor 301 and the memory 302 are connected to each other through the bus 304, or are otherwise known to each other.

Optionally, the network optimization device 30 further includes an input/output interface 405, where the input/output interface 405 is configured to connect with an input device, and receive a network optimization request (e.g., a downlink edge rate, an SINR, and a first rate-SINR joint ratio of the target area) input by a 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 405 is also used to connect with an output device, which outputs the network optimization result (i.e., the number of base stations whose target area is to be increased) of the processor 301. 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 network optimization scene of a target area, and specifically, the communication network of the target area is optimized by increasing the number of base stations of the target area, so that the communication quality of the target area is optimized. In the embodiment of the invention, particularly in a high-speed rail scene, a networking basis can be provided for the construction of a high-speed rail base station, for example, how many high-speed rail base stations are constructed (or newly constructed) for a certain high-speed rail line or a certain section of high-speed rail line, and then the communication network of the high-speed rail line is optimized.

In conjunction with the communication system shown in fig. 1, the network optimization method provided by the embodiment of the present invention is fully described below from the perspective of interaction among devices in the communication system, so as to illustrate a process of optimizing the communication quality of a target area by a network optimization device.

As shown in fig. 4, the network optimization method provided in the embodiment of the present invention may include S101 to S107:

s101, the UE acquires a plurality of network test data sets.

Wherein, one network test data group includes SINR when the UE receives downlink data and downlink edge rate when the UE receives downlink data.

It should be understood that, when a network device (e.g., a base station) initiates a User Datagram Protocol (UDP) downlink service to a UE, that is, when the UE downloads service data from the network device, the UE may obtain (or collect) an SINR and a downlink edge rate when the service data is currently downloaded (that is, when the UE receives downlink data), where the downlink edge rate may be understood as a data download rate when the UE receives downlink data.

It is understood that the SINR and/or downlink edge rate obtained by the UE in different areas may be different. For example, in a high-speed rail scenario, in the same high-speed rail line, SINR and/or downlink edge rate corresponding to different inter-station distances may be different, and different inter-station distances may be understood as distances between adjacent base stations (specifically, high-speed rail base stations), heights of base stations of different base stations in the same high-speed rail line may also be different, and then SINR and/or downlink edge rate corresponding to heights of base stations of different base stations may also be different; similarly, different SINR and/or downlink edge rate may be used in different high-speed rail lines. Therefore, the SINR and/or downlink edge rate at which the UE receives downlink data is affected by the plurality of different high-speed rail configurations (e.g., different inter-site distances and/or different base station heights). In the embodiment of the invention, the UE can obtain SINR and downlink marginal rate corresponding to high-speed rail lines with various high-speed rail configurations, so that the test data or a plurality of obtained network test data groups meet various high-speed rail configuration conditions, and the reliability of the data is improved.

In an implementation manner of the embodiment of the present invention, the UE may determine the plurality of network test data groups from a plurality of data groups.

Specifically, the multiple network test data groups may be data groups of which the high-speed iron rate when the UE receives downlink data is greater than or equal to a rate threshold value among the multiple data groups.

It should be understood that, due to the characteristic of high-speed rail, i.e., fast driving speed, the UE may select a data set greater than or equal to the rate threshold from the plurality of data sets and determine the data set greater than or equal to the rate threshold as a plurality of network test data sets, i.e., preprocess the plurality of data sets to select data satisfying the condition. Illustratively, the velocity threshold may be 250km/h (kilometers per hour).

S102, the UE determines N groups of downlink edge rate thresholds and N rate-SINR combined occupation ratios corresponding to the SINR thresholds according to the SINRs and the downlink edge rates in the multiple network test data groups.

And one rate-SINR joint ratio corresponding to the set of downlink edge rate threshold and SINR threshold is the ratio of the rate-SINR ratio to the SINR ratio. The ratio of the rate to the SINR is a ratio of a number of network test data groups, of the plurality of network test data groups, to which the downlink marginal rate when the UE receives downlink data is greater than or equal to the downlink marginal rate threshold, and to which the SINR when the UE receives downlink data is greater than or equal to the SINR threshold, to a number of network test data groups acquired by the UE. The SINR ratio is a ratio of the number of network test data groups of which SINR is greater than or equal to the SINR threshold when the UE receives downlink data to the number of network test data groups acquired by the UE; n is a positive integer greater than or equal to 1.

Specifically, a rate-SINR combined ratio corresponding to the set of downlink edge rate threshold and SINR threshold satisfies:

wherein the content of the first and second substances,

represents the rate-SINR joint ratio, P (SINR ≧ sin r_a，s≥s_a) Represents the ratio of the speed to the SINR, P (SINR ≧ sin r)_a) Represents the SINR ratio, s_aRepresenting the downstream edge rate threshold, sin r_aRepresenting the SINR threshold.

It should be understood that after acquiring the N sets of downlink edge rate thresholds and SINR thresholds and the N rate-SINR joint occupancy, the UE determines the N rate-SINR joint occupancy based on the N sets of downlink edge rate thresholds and SINR thresholds (a set of downlink edge rate thresholds and SINR thresholds includes 1 downlink edge rate threshold and 1 SINR threshold).

As shown in table 1, an example of SINR and downlink edge rate in 10 network test data groups obtained for a UE is shown.

TABLE 1

Network test data set	SINR(dB)	Downstream edge rate (Mbit/s)
			Network test data set 1	5	5
Network test data set 2	5	10
			Network test data set 3	10	15
Network test data set 4	12.5	20
			Network test data set 5	12.5	20
Network test data set6	12.5	30
			Network test data set 7	15	30
Network test data set 8	15	50
			Network test data set 9	15	50
Network test data set 10	15	60

Assuming that N is 3, that is, the UE determines 3 rate-SINR joint ratios corresponding to 3 sets of downlink edge rate thresholds and SINR thresholds. Further assume that 3 rate-SINR joint odds (including rate-SINR joint odds 1, rate-SINR joint odds 2, and rate-SINR joint odds 3) corresponding to the 3 sets of downlink edge rate thresholds and SINR thresholds (including a first set of downlink edge rate thresholds and SINR thresholds, a second set of downlink edge rate thresholds and SINR thresholds, and a third set of downlink edge rate thresholds and SINR thresholds, where the first set of downlink edge rate thresholds and SINR thresholds correspond to rate-SINR joint odds 1, the second set of downlink edge rate thresholds and SINR thresholds correspond to rate-SINR joint odds 2, the third set of downlink edge rate thresholds and SINR thresholds correspond to rate-SINR joint odds), the downlink edge rate threshold in rate-SINR joint odds 1 is 10Mbit/s, and the SINR threshold is 5dB (decibels), the downlink edge rate threshold in the rate-SINR joint ratio 2 is 20Mbit/s, the SINR threshold is 10dB, the downlink edge rate threshold in the rate-SINR joint ratio 3 is 50Mbit/s, and the SINR threshold is 15 dB.

In combination with the above calculation formula of the rate-SINR joint ratio and table 1, it may be determined that, in the rate-SINR joint ratio 1 corresponding to the first group of downlink edge rate thresholds and SINR thresholds, the rate-SINR ratio corresponding to the first group of downlink edge rate thresholds and SINR thresholds is 0.9, and the SINR ratio corresponding to the first group of downlink edge rate thresholds and SINR thresholds is 1, so that the value of the rate-SINR joint ratio 1 may be determined to be 0.9, and in the same way, the process of determining the value of the rate-SINR joint ratio 2 (i.e., 0.875) and the value of the rate-SINR joint ratio 3 (i.e., 0.75) is the same as or similar to the manner of determining the rate-SINR joint ratio 1, which is not described herein again.

In an implementation manner of the embodiment of the present invention, the rate-SINR joint ratio may also be expressed by using an edge coverage ratio, for example, a larger edge coverage ratio (i.e., a larger value of the rate-SINR joint ratio) of the target area indicates better communication quality of the target area.

S103, the UE sends the N groups of downlink marginal rate threshold values and SINR threshold values and the N rate-SINR joint occupation ratios to the network optimization equipment.

S104, the network optimization equipment receives N groups of downlink edge thresholds and SINR thresholds sent by the UE, and N rates joint occupation ratios corresponding to the N groups of downlink edge rate thresholds and the SINR thresholds.

It should be understood that, after receiving the N sets of downlink edge rate thresholds and SINR thresholds and the N rate-SINR joint ratios, the network optimization device may determine the number of base stations to be added to the target area according to the N sets of downlink edge rate thresholds and SINR thresholds and the N rate-SINR joint ratios.

S105, the network optimization equipment acquires the downlink edge rate, the SINR and the first rate-SINR combined ratio of the target area.

It should be understood that the downlink edge rate is a target value of a rate that the operator desires to achieve in the target area, and may be understood as a data download rate that the UE in the target area should achieve when receiving downlink data, for example, the downlink edge rate of the target area is 50Mbit/s, and the data download rate when the UE in the target area receives downlink data should be greater than or equal to 50 Mbit/s. Similarly, the first rate-SINR joint proportion of the target region is a target value of the rate-SINR joint proportion that the operator expects the target region to reach.

Specifically, the SINR of the target area may be data actually measured by the UE, or may be obtained by importing a corresponding map (e.g., a three-dimensional (3D) map) into the network optimization device by using a simulation model (or software).

It should be understood that, since the network optimization device may obtain a plurality of SINRs in the target area, the network optimization device may determine one SINR from the plurality of SINRs, and further characterize the state of the SINR of the target area by using the SINR.

In an implementation manner of the embodiment of the present invention, a network optimization device obtains an SINR of a target area, which specifically includes steps 1 to 3:

step 1, the network optimization equipment acquires SINRs corresponding to a plurality of sampling points in a target area.

It should be understood that there may be multiple samples in the target region, and that different samples may correspond to different SINRs.

And step 2, the network optimization equipment determines a plurality of effective SINRs from SINRs corresponding to the plurality of sampling points by using a Cumulative Distribution Function (CDF).

It should be understood that, in order to improve the accuracy of the data, the CDF function may be used to select part of the valid data for network optimization. For example, assuming that the network optimization device obtains SINRs corresponding to 100 sampling points, at this time, the network optimization device may select 95 better SINRs from the SINRs corresponding to the 100 sampling points as effective SINRs, that is, delete 5 sampling points (5% of 100 sampling points) with the smallest SINR value.

And 3, determining the average value of the effective SINRs as the SINR of the target area by the network optimization equipment.

It should be noted that the execution order of S104 and S105 may not be limited by the embodiment of the present invention. For example, S104 may be performed first and then S105 may be performed, or S105 may be performed first and then S104 may be performed, or S104 and S105 may be performed simultaneously.

S106, the network optimization device takes the downlink edge rate of the target area as a target downlink edge rate threshold value, takes the SINR of the target area as a target SINR threshold value, and determines a second rate-SINR joint ratio corresponding to the target downlink edge rate threshold value and the target SINR threshold value from the N rate-SINR joint ratios.

With reference to the description of the foregoing embodiment, it should be understood that, the network optimization device determines, from the N sets of downlink edge rate thresholds and SINR thresholds, a set of downlink edge rate thresholds and SINR thresholds that are the same as the target downlink edge rate threshold and target SINR threshold, and further determines a rate-SINR joint proportion, that is, a second rate-SINR joint proportion, corresponding to the set of downlink edge rate thresholds and SINR thresholds.

Illustratively, in conjunction with the example in table 1 above, assuming that the downlink edge rate of the target region is 50Mbit/s (i.e., the target downlink edge rate threshold is 50Mbit/s), and the SINR of the target region is 15dB (i.e., the target SINR threshold is 15dB), the value of the second rate-SINR joint ratio is determined to be 0.75 (i.e., the rate-SINR joint ratio is 3).

In an implementation manner of the embodiment of the present invention, after the step S104, the method further includes:

the network optimization equipment interpolates N groups of downlink edge rate thresholds and SINR thresholds and N rate-SINR joint occupation ratios to obtain M groups of downlink edge rate thresholds and SINR thresholds and M rate-SINR joint occupation ratios corresponding to the M groups of downlink edge rate thresholds and the SINR thresholds, wherein M is larger than N.

It should be understood that the above-mentioned N sets of downlink edge rate thresholds and SINR thresholds, and the N rate-SINR joint fractions may have less data amount, i.e., the network optimization device may not be able to determine the second rate-SINR joint fraction corresponding to the target downlink edge rate threshold and the target SINR threshold from the N rate-SINR joint fractions, including that the network optimization device may not be able to query the target downlink edge rate threshold and the target SINR threshold from the N sets of downlink edge rate thresholds and SINR thresholds, and may not be able to query the second rate-SINR joint fraction from the N rate-SINR joint fractions. Thus, the network optimization device may obtain more downlink edge rate thresholds, SINR thresholds, and rate-SINR joint ratios (e.g., M groups of downlink edge rate thresholds and SINR thresholds, and M rate-SINR joint ratios) by using an interpolation method, and the network optimization device may determine the second rate-SINR joint ratio from the M rate-SINR joint ratios.

The following describes in detail the process of obtaining M groups of downlink edge rate thresholds and SINR thresholds and M rate-SINR joint ratios by the network optimization device, taking a triangle interpolation method as an example.

Firstly, the network optimization device determines 3 groups of downlink edge rate thresholds and SINR thresholds and 3 rate-SINR combined ratios from N groups of downlink edge rate thresholds and SINR thresholds and N rate-SINR combined ratios, and determines 3 coordinate points corresponding to the 3 groups of downlink edge rate thresholds and SINR thresholds as three vertexes of a triangle, wherein for a group of downlink edge rate thresholds and SINR thresholds, the SINR threshold is taken as an abscissa of one vertex, and the downlink edge rate threshold is taken as an ordinate of the one vertex.

Table 2 below is an example of 3 sets of downlink edge rate thresholds and SINR thresholds and 3 rate-SINR joint fractions.

TABLE 2

Coordinate point	SINR threshold	Downstream edge rate threshold	Rate-SINR joint ratio
				Point P1	SINR1	S1	Pr1
Point P2	SINR2	S2	Pr2
				Point P3	SINR3	S3	Pr3

With reference to table 2 and fig. 5, a rectangular plane coordinate system is shown, where the rectangular plane coordinate system includes a triangle P1P2P3 (i.e., the vertex coordinates of the triangle are a point P1, a point P2, and a point P3), a Y axis of the rectangular plane coordinate system is parallel to the P2P3 side of the triangle, an X axis is perpendicular to the Y axis and is located in a plane where the triangle is located, the X axis represents an SINR threshold, and the Y axis represents a downlink edge rate threshold.

Specifically, since the triangle shown in fig. 5 is a 2D graph, any point P (SINRn, Sn) of the triangle has two degrees of freedom, i.e., a degree of freedom u and a degree of freedom v, respectively, where u is greater than or equal to 0, v is greater than or equal to 0, and u + v is less than or equal to 1. Since the degree of freedom u and the degree of freedom v are used to represent the weight contribution of each vertex (i.e., the point P1, the point P2, and the point P3) to a specific region (e.g., the point P), and (1-u-v) is the third weight, the contribution of each vertex to the point P (SINRn, Sn) can be calculated by calculating the degree of freedom u and the degree of freedom v.

For any one point P, the following is satisfied:

P＝(1-u-v)*P1+u*P2+v*P3

where (1-u-v) represents the weight contribution of vertex P1 to point P, u represents the weight contribution of vertex P2 to point P, and v represents the contribution of vertex P3 to point P.

The values of u and v may be determined in conjunction with the coordinate values of point P1, point P2, point P3 (i.e., SINR threshold and downlink edge rate threshold in table 2 above) and the coordinate value of point P, where for any one point P, it also satisfies:

SINRn＝(1-u-v)*SINR1+u*SINR2+v*SINR3；

here, SINRn denotes an SINR threshold value of point P.

Sn＝(1-u-v)*S1+u*S2+v*S3；

Wherein Sn represents the downlink edge rate threshold of point P.

It is to be understood that the degrees of freedom u and/or the degrees of freedom v differ for different P points.

Then, a rate-SINR joint ratio corresponding to the point P may be determined according to the value of the degree of freedom u, the value of the degree of freedom v, and the rate-SINR joint ratios of the point P1, the point P2, and the point P3, where the rate-SINR joint ratio corresponding to the point P satisfies:

Prn＝(1-u-v)*Pr1+u*Pr2+v*Pr3

where Prn represents a rate-SINR joint ratio corresponding to point P.

The network optimization device can determine a three-dimensional coordinate point Q (SINRn, Sn, Prn) according to the rate-SINR joint ratio corresponding to each point P (SINRn, Sn), so as to complete one-time interpolation of N groups of downlink edge rate thresholds and SINR thresholds and N rate-SINR joint ratios.

For example, assuming that the coordinate value of the point P is (12,34), that is, the SINR threshold corresponding to the point P is 12dB, and the downlink edge rate threshold is 34Mbit/S, and assuming that the SINR thresholds and the downlink edge rate thresholds of the point P1, the point P2, and the point P3 are respectively the SINR threshold and the downlink edge rate threshold corresponding to the above-mentioned S102, the SINR threshold and the downlink edge rate threshold corresponding to the rate-SINR joint proportion 1, the SINR threshold and the downlink edge rate threshold corresponding to the rate-SINR joint proportion 2, and the SINR threshold and the downlink edge rate threshold corresponding to the rate-SINR joint proportion 2, the UE may determine that the degree of freedom u of the point P is 0.4 and the degree of freedom v is 0.5, and the point P corresponds to the three-dimensional coordinate point Q (12,34, 0.815), that is, that the value of the rate-SINR joint proportion corresponding to the point P is 0.815.

In the embodiment of the present invention, after the network optimization device performs multiple interpolations on N groups of downlink edge rate thresholds and SINR thresholds and N rate-SINR joint percentages to obtain M groups of downlink edge rate thresholds and SINR thresholds and M rate-SINR joint percentages, the M groups of downlink edge rate thresholds and SINR thresholds and the M rate-SINR joint percentages may be stored in a rate-SINR joint percentage height table, where table 3 below is an example of a rate-SINR joint percentage height table.

TABLE 3

As can be seen from Table 3, SINR_mDenotes the mth SINR threshold, S_mRepresents the mth downstream edge rate threshold P_mmIndicating the rate-SINR joint occupancy corresponding to the mth SINR threshold and the mth downlink edge rate threshold. Therefore, the network optimization equipment can determine the second combined ratio from the rate-SINR combined ratio and the like table, further determine the number of base stations to be increased in the target area, and can improve the efficiency of network optimization.

In one implementation manner of the embodiment of the present invention, the network optimization device may determine the color of the three-dimensional coordinate point Q (SINRn, Sn, Prn) according to the respective colors of the point P1, the point P2, and the point P3, and the degree of freedom u and the degree of freedom v of the three-dimensional coordinate point Q (SINRn, Sn, Prn).

Illustratively, in connection with the above example, assuming that the degree of freedom u of the three-dimensional coordinate point Q (SINRn, Sn, Prn) is 0.4, the degree of freedom v is 0.5, the color of the point P1 is red, the color of the point P2 is green, and the color of the point P3 is blue, as can be seen by a color editor in matrix laboratories (Matlab), the chromaticity of red is (0, 0, 255), the chromaticity of green is (0, 255, 0), and the chromaticity of blue is (255, 0, 0). Therefore, the chromaticity corresponding to the point P1 is (0, 0, 255), the chromaticity corresponding to the point P2 is (0, 255, 0), and the chromaticity corresponding to the point P3 is (255, 0, 0).

Then, in the chromaticity (a, b, c) corresponding to the three-dimensional coordinate point Q (SINRn, Sn, Prn), a is (1-u-v) × P1(a) + u × P2(a) + v × P3(a), b is (1-u-v) × P1(b) + u × P2(b) + v × P3(b), and c is (1-u-v) × P1(c) + u × P2(c) + v × P3 (c).

Wherein PN (a) represents the value of a in the chromaticity of the point PN, PN (b) represents the value of b in the chromaticity of the point PN, PN (c) represents the value of c in the chromaticity of the point PN, and N is a positive integer greater than or equal to 1.

Illustratively, when N is equal to 1, since the chromaticity of the point P1 is (0, 0, 255), a is 0, b is 0, and c is 255.

Thus, it can be determined that, in the chromaticity (a, b, c) corresponding to the three-dimensional coordinate point Q (SINRn, Sn, Prn), a is 127.5, b is 102, and c is 25.5, that is, the chromaticity (127.5, 102, 25.5) corresponding to the three-dimensional coordinate point Q (SINRn, Sn, Prn) is brought into the color editor in Matlab, whereby the color of the point P can be determined.

Note that the color corresponding to the point P (SINRn, Sn) is the same as the color of the three-dimensional coordinate point Q (SINRn, Sn, Prn), that is, the chromaticity corresponding to the point P (SINRn, Sn) is the same as the chromaticity corresponding to the three-dimensional coordinate point Q (SINRn, Sn, Prn).

In the embodiment of the present invention, after determining the color corresponding to each three-dimensional coordinate point Q (SINRn, Sn, Prn), the network optimization device may combine the coordinate values of each three-dimensional coordinate point Q (SINRn, Sn, Prn) to obtain a rate-SINR combined occupancy rate map as shown in fig. 6, it should be understood that the rate-SINR combined occupancy rate map is used to represent the relationship between an SINR threshold, a downlink edge rate threshold, and a rate-SINR combined occupancy rate, and the network optimization device may determine a second rate-SINR combined occupancy rate from the rate-SINR combined occupancy rate map, and further determine the number of base stations to be added in a target area, so as to improve the efficiency of network optimization.

S107, the network optimization device determines the number of base stations to be increased in the target area according to the first rate-SINR combined occupation ratio and the second rate-SINR combined occupation ratio.

In an implementation manner of the embodiment of the present invention, the step S107 specifically includes the steps of a to B:

step A, the network optimization equipment determines the station adding proportion of a target area according to the first rate-SINR combined occupation ratio and the second rate-SINR combined occupation ratio, and the station adding proportion of the target area meets the following requirements:

wherein, P_JZRepresenting the station-added proportion, P, of the target area₁Representing the first rate-SINR joint ratio, P₂Representing a second rate-SINR joint fraction.

Step B, the network optimization equipment determines the number of base stations to be increased in the target area according to the station adding proportion of the target area and the current number of the base stations in the target area, wherein the number of the base stations to be increased in the target area meets the following requirements:

N_JZ＝P_JZ×N_DQ；

N_JZindicates the number of base stations, P, to be added to the target area_JZRepresenting the station-added proportion of the target area, N_DQIndicating the current number of base stations in the target area.

Illustratively, assuming that the value of the first rate-SINR joint ratio is 0.9 and the value of the second rate-SINR joint ratio is 0.5, the network optimization device determines that the station adding ratio of the target area is 0.8. And assuming that the number of the current base stations in the target area is 10, the network optimization device determines that the number of the base stations to be added in the target area is 8, and further newly builds the 8 base stations to be added in the target area, so that the target area reaches the first rate-SINR combined ratio. In this way, the communication network of the target area can be optimized so that the target area achieves a better communication quality.

In the embodiment of the invention, UE (user equipment) acquires a plurality of network test data groups, wherein one network test data group comprises SINR (signal to interference plus noise ratio) when the UE receives downlink data and downlink edge rate when the UE receives the downlink data; then UE determines N groups of downlink edge rate threshold values and N rate-SINR combined occupation ratios corresponding to the SINR threshold values according to the SINRs and the downlink edge rates in the multiple network test data groups; then the UE sends the N groups of downlink marginal rate threshold values and SINR threshold values and the N rate-SINR combined occupation ratios to network optimization equipment; thus, the network optimization device receives the N sets of downlink edge rate thresholds and SINR thresholds sent by the UE, and the N rate-SINR joint fractions; the network optimization device obtains a downlink edge rate, an SINR and a first rate-SINR joint proportion of a target area, the downlink edge rate of the target area is used as a target downlink edge rate threshold, the SINR of the target area is used as a target SINR threshold, and the network optimization device determines a second rate-SINR joint proportion corresponding to the target downlink edge rate threshold and the target SINR threshold from N rate-SINR joint proportions received by the network optimization device; and the network optimization equipment determines the number of base stations to be increased in the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio. In the embodiment of the invention, the UE determines N rate-SINR combined occupation ratios by obtaining a plurality of network test data and according to the SINR and the downlink marginal rate in a plurality of network test data groups; furthermore, the network optimization device may determine, based on the SINR threshold, the edge rate threshold, and the rate-SINR combined ratio determined by the UE, a downlink edge rate of the target area and a second rate-SINR combined ratio corresponding to the SINR, and then, in combination with a preset first rate-SINR combined ratio (the first rate-SINR combined ratio is a requirement index for network establishment, that is, the rate-SINR combined ratio that the target area needs to reach), may determine the number of base stations to be added to the target area. Therefore, under the condition that the existing base stations in the target area are not enough to meet the communication quality of the target area, the communication network of the target area is optimized by increasing the number of the base stations in the target area, and the efficiency of the UE in acquiring the service data can be improved.

In an implementation manner of the embodiment of the present invention, the execution action of the network optimization device may also be executed by the UE, that is, the UE may complete the determination process of the N rate-SINR joint fractions, and may also complete the determination of the number of base stations to be added in the target area.

In another implementation manner of the embodiment of the present invention, the step S102 may also be executed by the network optimization device, that is, after the UE acquires the multiple network test data groups, the multiple network test data groups may be sent to the network optimization device, and the network optimization device determines the N rate-SINR combined ratios, thereby completing the process of determining the number of base stations to be added in the target area.

According to the method example, the functional modules of the UE and the network optimization device may be divided, for example, the functional modules may be divided corresponding to the functions, 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 the functional modules according to the respective functions, fig. 7 shows a possible structural diagram of the UE involved in the foregoing embodiment, as shown in fig. 7, the UE 40 may include: an acquisition module 401, a determination module 402 and a sending module 403.

An obtaining module 401, configured to obtain multiple network test data sets, where one network test data set includes an SINR when the UE receives downlink data and a downlink edge rate when the UE receives downlink data.

A determining module 402, configured to determine N groups of downlink edge rate thresholds and N rate-SINR joint ratios corresponding to the SINR thresholds according to the SINR and the downlink edge rate in the multiple network test data groups, where N is a positive integer greater than or equal to 1; the SINR ratio is a ratio of a rate-SINR ratio to an SINR ratio, where the rate-SINR ratio is a ratio of the rate-SINR ratio to an SINR ratio, the rate-SINR ratio is a ratio of the downlink marginal rate when the UE receives downlink data in the multiple network test data groups, and the SINR when the UE receives downlink data is greater than or equal to the ratio of the number of network test data groups of the SINR greater than or equal to the SINR threshold to the number of network test data groups acquired by the UE, and the SINR ratio is a ratio of the number of network test data groups of the multiple network test data groups of the SINR greater than or equal to the SINR threshold when the UE receives downlink data to the number of network test data groups acquired by the UE.

A sending module 403, configured to send the N sets of downlink edge rate threshold and SINR threshold, and the N rate-SINR combined ratios to a network optimization device, where the N sets of downlink edge rate threshold and SINR threshold, and the N rate-SINR combined ratios are used to determine the number of base stations to be added in a target area.

In case of using integrated units, fig. 8 shows a possible structural diagram of the UE involved in the above embodiments. As shown in fig. 8, the UE 50 may include: a processing module 501 and a communication module 502. The processing module 501 may be configured to control and manage actions of the UE 50, for example, the processing module 501 may be configured to support the UE 50 to execute S102 in the foregoing method embodiment. The communication module 502 may be configured to support communication between the UE 50 and other entities, for example, the communication module 502 may be configured to support the UE 50 to perform S103 in the above method embodiment. Optionally, as shown in fig. 8, the UE 50 may further include a storage module 503 for storing program codes and data of the UE 50.

The processing module 501 may be a processor or a controller. The communication module 502 may be a transceiver, a transceiving circuit or a communication interface, etc. The storage module 503 may be a memory.

When the processing module 501 is a processor, the communication module 502 is a transceiver, and the storage module 503 is a memory, the processor, the transceiver, and the memory may be connected by 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.

In the case of dividing each functional module by corresponding functions, fig. 9 shows a schematic structural diagram of a possible network optimization device in the foregoing embodiment, as shown in fig. 9, the network optimization device 60 may include: a receiving module 601, an obtaining module 602, and a determining module 603.

A receiving module 601, configured to receive N sets of downlink edge rate thresholds and signals and SINR thresholds sent by a UE, and N rate-SINR joint ratios corresponding to the N sets of downlink edge rate thresholds and SINR thresholds, where N is a positive integer greater than or equal to 1; wherein, a rate-SINR joint ratio corresponding to a group of downlink edge rate threshold and SINR threshold is the ratio of the rate-SINR ratio to the SINR ratio; the rate-SINR ratio is a ratio of a downlink marginal rate when the UE receives downlink data to a number of network test data groups acquired by the UE, where the downlink marginal rate is greater than or equal to the downlink marginal rate threshold, and the SINR when the UE receives downlink data is greater than or equal to the SINR threshold to the number of network test data groups acquired by the UE; the SINR ratio is a ratio of the number of network test data groups of which SINR is greater than or equal to the SINR threshold when the UE receives downlink data to the number of network test data groups acquired by the UE.

An obtaining module 602, configured to obtain a downlink edge rate, an SINR, and a first rate-SINR combined ratio of a target area.

A determining module 603, configured to determine, from the N rate-SINR joint fractions, a second rate-SINR joint fraction corresponding to the target downlink edge rate threshold and the target SINR threshold, using the downlink edge rate as a target downlink edge rate threshold and the SINR as a target SINR threshold; and determining the number of base stations to be added in the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio.

Optionally, the determining module 603 is specifically configured to determine the station adding ratio of the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio, where the station adding ratio of the target area satisfies:

wherein, P_JZIndicating the station-adding proportion, P, of the target area₁Represents the first rate-SINR joint ratio, P₂Represents the firstTwo rate-SINR joint ratio.

The determining module 603 is further specifically configured to determine, according to the station adding ratio of the target area and the current number of base stations in the target area, the number of base stations to be added in the target area, where the number of base stations to be added in the target area satisfies:

N_JZ＝P_JZ×N_DQ；

wherein N is_JZIndicates the number of base stations, P, to be added to the target area_JZIndicating the station-adding proportion of the target area, N_DQIndicating the current number of base stations in the target area.

Optionally, the obtaining module 602 is specifically configured to obtain SINRs corresponding to multiple sampling points in the target area;

the determining module 603 is further configured to determine, by using CDF, a plurality of effective SINRs from SINRs corresponding to the plurality of sampling points; then, the average of the effective SINRs is determined as the SINR of the target region.

Optionally, the determining module 603 is further configured to interpolate the N rate-SINR joint ratios to obtain M rate-SINR joint ratios, where M > N.

In the case of an integrated unit, fig. 10 shows a schematic diagram of a possible structure of the network optimization device involved in the above-described embodiment. As shown in fig. 10, the network optimization device 70 may include: a processing module 701 and a communication module 702. The processing module 701 may be configured to control and manage the actions of the network optimization device 70, for example, the processing module 701 may be configured to support the network optimization device 70 to execute S105, S106, and S107 in the above method embodiments. The communication module 702 may be configured to support the network optimization device 70 to communicate with other entities, for example, the communication module 702 may be configured to support the network optimization device 70 to execute S104 in the above method embodiment. Optionally, as shown in fig. 9, the network optimization device 70 may further include a storage module 703 for storing program codes and data of the network optimization device 70.

The processing module 701 may be a processor or a controller (for example, the processor 301 shown in fig. 3). The communication module 702 may be a transceiver, a transceiver circuit, or a communication interface (e.g., the communication interface 303 shown in fig. 3 described above). The storage module 703 may be a memory (e.g., may be the memory 302 described above with reference to fig. 3).

When the processing module 701 is a processor, the communication module 702 is a transceiver, and the storage module 703 is a memory, the processor, the transceiver, and the memory may be connected by a bus. The bus may be a PCI bus or an EISA bus, etc. 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:

user Equipment (UE) acquires a plurality of network test data groups, wherein one network test data group comprises a signal to interference plus noise ratio (SINR) when the UE receives downlink data and a downlink edge rate when the UE receives the downlink data;

the UE determines N groups of downlink edge rate thresholds and N rate-SINR combined occupation ratios corresponding to the SINR thresholds according to the SINRs and the downlink edge rates in the multiple network test data groups, wherein N is a positive integer greater than or equal to 1; a rate-SINR combined ratio corresponding to a group of downlink edge rate thresholds and SINR thresholds is a ratio of the rate-SINR ratio to the SINR ratio, where the rate-SINR ratio is a ratio of the downlink edge rate when the UE receives downlink data in the multiple network test data groups to the SINR ratio of the number of network test data groups obtained by the UE to the number of network test data groups obtained by the UE, and the SINR when the UE receives downlink data is greater than or equal to the SINR threshold to the number of network test data groups obtained by the UE, and the SINR ratio is a ratio of the number of network test data groups when the UE receives downlink data to the number of network test data groups obtained by the UE to the SINR when the UE receives downlink data in the multiple network test data groups;

and the UE sends the N groups of downlink edge rate thresholds, the SINR thresholds and the N rate-SINR joint occupation ratios to network optimization equipment, wherein the N groups of downlink edge rate thresholds, the SINR thresholds and the N rate-SINR joint occupation ratios are used for determining the number of base stations to be increased in a target area.

2. A method for network optimization, comprising:

the method comprises the steps that network optimization equipment receives N groups of downlink edge rate thresholds and signal-to-interference-plus-noise ratio (SINR) thresholds sent by User Equipment (UE), and N rate-SINR joint occupation ratios corresponding to the N groups of downlink edge rate thresholds and the SINR thresholds, wherein N is a positive integer greater than or equal to 1; wherein, a rate-SINR joint ratio corresponding to a group of downlink edge rate threshold and SINR threshold is the ratio of the rate-SINR ratio to the SINR ratio; the rate-SINR ratio is a ratio of a downlink marginal rate when the UE receives downlink data to a number of network test data groups acquired by the UE, where the downlink marginal rate is greater than or equal to the downlink marginal rate threshold, and the SINR when the UE receives downlink data is greater than or equal to the SINR threshold, to the number of network test data groups acquired by the UE; the SINR ratio is a ratio of the number of network test data groups, of which SINR is greater than or equal to the SINR threshold when the UE receives downlink data, to the number of network test data groups acquired by the UE;

the network optimization equipment acquires the downlink edge rate, the SINR and the first rate-SINR combined ratio of a target area;

the network optimization equipment takes the downlink edge rate as a target downlink edge rate threshold value, takes the SINR as a target SINR threshold value, and determines a second rate-SINR joint proportion corresponding to the target downlink edge rate threshold value and the target SINR threshold value from the N rate-SINR joint proportions;

and the network optimization equipment determines the number of the base stations to be increased in the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio.

3. The method according to claim 2, wherein the determining, by the network optimization device, the number of base stations to be added to the target area according to the first rate-SINR joint proportion and the second rate-SINR joint proportion specifically includes:

the network optimization equipment determines the station adding proportion of the target area according to the first rate-SINR joint proportion and the second rate-SINR joint proportion, and the station adding proportion of the target area meets the following requirements:

wherein, P_JZRepresenting the station-adding proportion, P, of the target area₁Representing the first rate-SINR joint ratio, P₂Representing the second rate-SINR joint fraction;

the network optimization equipment determines the number of base stations to be increased in the target area according to the station adding proportion of the target area and the current number of the base stations in the target area, wherein the number of the base stations to be increased in the target area meets the following requirements:

N_JZ＝P_JZ×N_DQ；

wherein N is_JZRepresenting the number of base stations, P, to be added to the target area_JZRepresenting the station-adding proportion, N, of the target area_DQRepresenting the current number of base stations of the target area.

4. The method according to claim 3, wherein the acquiring, by the network optimization device, the SINR of the target area specifically includes:

the network optimization equipment acquires SINRs corresponding to the multiple sampling points in the target area;

the network optimization equipment determines a plurality of effective SINRs from SINRs corresponding to the plurality of sampling points by adopting a Cumulative Distribution Function (CDF);

the network optimization device determines an average of the plurality of effective SINRs as the SINR of the target area.

5. The method according to any of claims 2-4, wherein after the network optimization device receives the N sets of downlink edge rate threshold and SINR threshold sent by the UE and the N rate-SINR joint ratios, the method further comprises:

and the network optimization equipment interpolates the N rate-SINR joint occupation ratios to obtain M rate-SINR joint occupation ratios, wherein M is larger than N.

6. A User Equipment (UE), comprising: the device comprises an acquisition module, a determination module and a sending module;

the acquiring module is configured to acquire a plurality of network test data groups, where one network test data group includes a signal to interference plus noise ratio SINR when the UE receives downlink data and a downlink edge rate when the UE receives downlink data;

the determining module is configured to determine N groups of downlink edge rate thresholds and N rate-SINR joint occupation ratios corresponding to the SINR thresholds according to the SINR and the downlink edge rate in the multiple network test data groups, where N is a positive integer greater than or equal to 1; a rate-SINR combined ratio corresponding to a group of downlink edge rate thresholds and SINR thresholds is a ratio of the rate-SINR ratio to the SINR ratio, where the rate-SINR ratio is a ratio of the downlink edge rate when the UE receives downlink data in the multiple network test data groups to the SINR ratio of the number of network test data groups obtained by the UE to the number of network test data groups obtained by the UE, and the SINR when the UE receives downlink data is greater than or equal to the SINR threshold to the number of network test data groups obtained by the UE, and the SINR ratio is a ratio of the number of network test data groups when the UE receives downlink data to the number of network test data groups obtained by the UE to the SINR when the UE receives downlink data in the multiple network test data groups;

the sending module is configured to send the N groups of downlink edge rate thresholds and SINR thresholds, and the N rate-SINR combined ratios to a network optimization device, where the N groups of downlink edge rate thresholds and SINR thresholds, and the N rate-SINR combined ratios are used to determine the number of base stations to be added in a target area.

7. A network optimization device, comprising: the device comprises a receiving module, an obtaining module and a determining module;

the receiving module is configured to receive N groups of downlink edge rate thresholds and signal-to-interference-plus-noise ratio SINR thresholds sent by user equipment UE, and N rate-SINR joint occupation ratios corresponding to the N groups of downlink edge rate thresholds and SINR thresholds, where N is a positive integer greater than or equal to 1; wherein, a rate-SINR joint ratio corresponding to a group of downlink edge rate threshold and SINR threshold is the ratio of the rate-SINR ratio to the SINR ratio; the rate-SINR ratio is a ratio of a downlink marginal rate when the UE receives downlink data to a number of network test data groups acquired by the UE, where the downlink marginal rate is greater than or equal to the downlink marginal rate threshold, and the SINR when the UE receives downlink data is greater than or equal to the SINR threshold, to the number of network test data groups acquired by the UE; the SINR ratio is a ratio of the number of network test data groups, of which SINR is greater than or equal to the SINR threshold when the UE receives downlink data, to the number of network test data groups acquired by the UE;

the acquisition module is used for acquiring the downlink edge rate, the SINR and the first rate-SINR combined ratio of the target area;

the determining module is configured to determine, from the N rate-SINR joint fractions, a second rate-SINR joint fraction corresponding to the target downlink edge rate threshold and the target SINR threshold, using the downlink edge rate as a target downlink edge rate threshold and the SINR as a target SINR threshold; and determining the number of base stations to be added to the target area according to the first rate-SINR joint ratio and the second rate-SINR joint ratio.

8. The network optimization device of claim 7,

the determining module is specifically configured to determine a station adding ratio of the target area according to the first rate-SINR joint proportion and the second rate-SINR joint proportion, where the station adding ratio of the target area satisfies:

the determining module is specifically further configured to determine the number of base stations to be added to the target area according to the station adding ratio of the target area and the current number of base stations in the target area, where the number of base stations to be added to the target area satisfies:

N_JZ＝P_JZ×N_DQ；

9. The network optimization device of claim 8,

the obtaining module is specifically configured to obtain SINRs corresponding to the multiple sampling points in the target area;

the determining module is specifically further configured to determine a plurality of effective SINRs from the SINRs corresponding to the plurality of sampling points by using a cumulative distribution function CDF; and determining an average value of the plurality of effective SINRs as the SINR of the target region.

10. The network optimization device of any one of claims 7 to 9,

the determining module is further configured to interpolate the N rate-SINR joint ratios to obtain M rate-SINR joint ratios, where M is greater than N.