CN110519767A - A kind of NB-IoT coverage prediction method and device - Google Patents

Abstract

Embodiments of the present invention provide a NB-IoT coverage prediction method and device. The method includes obtaining a first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid; obtaining a coverage mapping model by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, The coverage mapping model includes at least the level difference between the NB-IoT network and the GSM900 network in each grid; according to the level difference of the coverage mapping model and the first level in the first coverage state, the NB-IoT The second coverage state under the network, the second coverage state includes the second level of each grid, the embodiment of the present invention establishes a coverage mapping model between the NB-IoT network and the GSM900 network, according to the grid of the GSM900 network Coverage status, so as to quickly, simply and accurately predict the grid coverage status in the NB-IoT network.

Description

A NB-IoT coverage prediction method and device

technical field

Embodiments of the present invention relate to the field of wireless communication technologies, and in particular, to a method and device for NB-IoT coverage prediction.

Background technique

With the rapid development of the Internet of Things business, China Mobile and China Unicom have launched narrowband network (Narrow Band Internet of Things, NB-IoT) network construction on a large scale. The current mobile NB-IoT network construction is mainly deployed through co-site deployment with the existing Global System for Mobile Communications (GSM900), and the network construction cost is low and the speed is fast.

The traditional LTE network coverage prediction mainly has the following methods: 1. Through road traversal tests, collect the network coverage of each location of the existing network; 2. Use the MR report reported by the users of the existing network to predict the coverage of each location of the network through geographicalization and other means ; NB-IoT is oriented to static IoT users, users do not have mobility, the protocol does not support handover, only supports reselection, reselection is relatively long in handover delay, and road traversal tests are prone to failure due to failure to reselect to the strongest in time Cells lead to inaccurate coverage prediction, and NB-IoT services are mostly smart meter reading, smart parking, etc., and the coverage scenarios are quite different from roads, so the applicability of road traversal tests is poor. The NB-IoT protocol does not support MR messages, and users cannot report MR reports. Therefore, NB-IoT terminals cannot report MRs to predict network coverage.

It is too complicated to predict the network coverage state by road traversal test for NB-IoT system, which requires a lot of manpower, and the obtained coverage prediction is not accurate.

Contents of the invention

Embodiments of the present invention provide a method and device for NB-IoT coverage prediction, which are used to solve the problem that the existing technology is too complicated, requires a lot of manpower, and the obtained coverage prediction is inaccurate.

In the first aspect, an embodiment of the present invention provides a NB-IoT coverage prediction method, including:

Obtaining a first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid;

The coverage mapping model is obtained by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, and the coverage mapping model includes at least the level difference between the NB-IoT network and the GSM900 network in each grid;

According to the level difference of the coverage mapping model and the first level in the first coverage state, the second coverage state under the NB-IoT network is obtained, and the second coverage state includes the second level of each grid .

In a second aspect, an embodiment of the present invention provides an apparatus for a NB-IoT coverage prediction method, including:

An acquisition module, configured to acquire a first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid;

A calculation module, configured to obtain a coverage mapping model by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, the coverage mapping model at least including the level difference between the NB-IoT network and the GSM900 network in each grid;

The mapping module is used to obtain a second coverage state under the NB-IoT network according to the level difference of the coverage mapping model and the first level in the first coverage state, and the second coverage state includes each grid of the second level.

In a third aspect, an embodiment of the present invention also provides an electronic device, including:

processor, memory, communication interface, and bus; where,

The processor, the memory, and the communication interface complete mutual communication through the bus;

The communication interface is used for information transmission between communication devices of the electronic device;

The memory stores program instructions executable by the processor, and the processor calls the program instructions to perform the following methods:

Obtaining a first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid;

The coverage mapping model is obtained by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, and the coverage mapping model includes at least the level difference between the NB-IoT network and the GSM900 network in each grid;

According to the level difference of the coverage mapping model and the first level in the first coverage state, the second coverage state under the NB-IoT network is obtained, and the second coverage state includes the second level of each grid .

In a fourth aspect, the embodiment of the present invention also provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following method is implemented:

Obtaining a first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid;

The coverage mapping model is obtained by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, and the coverage mapping model includes at least the level difference between the NB-IoT network and the GSM900 network in each grid;

According to the level difference of the coverage mapping model and the first level in the first coverage state, the second coverage state under the NB-IoT network is obtained, and the second coverage state includes the second level of each grid .

The NB-IoT coverage prediction method and device provided by the embodiments of the present invention can quickly, simply and accurately predict the NB-IoT network by establishing a coverage mapping model between the NB-IoT network and the GSM900 network, and according to the grid coverage status of the GSM900 network. - State of grid coverage in IoT networks.

Description of drawings

FIG. 1 is a flowchart of a method for NB-IoT coverage prediction according to an embodiment of the present invention;

FIG. 2 is a flowchart of another NB-IoT coverage prediction method according to an embodiment of the present invention;

Fig. 3 is a schematic structural diagram of the NB-IoT transmitting antenna, the GSM900 transmitting antenna and the terminal position according to the embodiment of the present invention;

FIG. 4 is a schematic structural diagram of a device for a NB-IoT coverage prediction method according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of another device used for a NB-IoT coverage prediction method according to an embodiment of the present invention;

FIG. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

FIG. 1 is a flow chart of the NB-IoT coverage prediction method according to an embodiment of the present invention. As shown in FIG. 1, the method includes:

Step S01. Obtain a first coverage state under the GSM900 network, the grid coverage state at least including the first level of each grid.

Since the NB-IoT network uses the 900M frequency band, the characteristics of the propagation model are basically the same as those of the GSM900 network, and the NB-IoT network is mainly deployed in a co-site with GSM900, and its path loss characteristics are also similar to those of GSM900; GSM900 measurement report (Measurement Report) Most of the data comes from indoor users. Therefore, the embodiment of the present invention establishes a coverage mapping model between the two networks, thereby obtaining the grid coverage state under the NB-IoT network based on GSM900, that is, the first coverage state.

Firstly, according to data such as GSM900 network MR files, site parameters, and base station configuration files, and relying on the main equipment manufacturer or third-party tools, the first coverage state is obtained through the MR positioning algorithm to realize the coverage grid level of the GSM900 network Geographical rendering. After the GSM900 network grid is geo-geographical, the GSM network is composed of multiple grids, and the obtained first coverage state at least includes the coverage level value of each GSM900 cell under each grid, that is, the first level.

Step S02: Obtain a coverage mapping model by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, the coverage mapping model at least including the level difference between the NB-IoT network and the GSM900 network in each grid.

Due to the difference in the performance and transmission environment of each device in the NB-IoT network and the GSM900 network, the transmission characteristics of the two networks are different. By comparing the transmission characteristics, the coverage mapping model can be obtained, for example, between base stations The difference in the transmission performance of the cell leads to different coverage capabilities of the cell, and the difference in the transmission environment will lead to different transmission losses, and the difference in the direction of the base station’s transmit antenna design will result in different gain attenuation values in each direction. Through the analysis of the two networks, the level difference between the two networks in each grid is obtained, and the distribution of the level difference of all the grids is combined to obtain the coverage mapping model between the two networks.

Step S03, according to the level difference of the coverage mapping model and the first level in the first coverage state, the second coverage state under the NB-IoT network is obtained, and the second coverage state includes the first coverage state of each grid. Two levels.

The second level of each grid under the NB-IoT network can be obtained by superimposing the first level in the first coverage state and the level difference in the coverage mapping model. Finally, the grid coverage state presented by coverage grid-level geography under the NB-IoT network is obtained, that is, the second coverage state.

The embodiment of the present invention establishes a coverage mapping model between the NB-IoT network and the GSM900 network, and according to the grid coverage status of the GSM900 network, quickly, simply and accurately predicts the grid coverage status in the NB-IoT network.

Figure 2 is a flow chart of another NB-IoT coverage prediction method according to an embodiment of the present invention, and Figure 3 is a schematic structural diagram of an NB-IoT transmitting antenna, a GSM900 transmitting antenna, and a terminal location according to an embodiment of the present invention, as shown in Figure 2 , the Described step S02 is specifically:

Step S021, by comparing the transmission performance of the base station between the NB-IoT network and the GSM900 network, the coverage capability difference between the NB-IoT network and the GSM900 network is obtained.

Due to the different business types handled by the NB-IoT network and the GSM900 network, although the base stations of the two networks are co-sited, the transmission performance will also vary according to the requirements of different business types, thus affecting the relationship between the two. coverage. NB-IoT services are generally not sensitive to delay, and the transmission reliability under poor channel conditions can be improved by introducing the coding method of repeated transmission, which can improve the coverage capability of NB-IoT. However, in terms of power spectral density, NB-IoT network has no advantage over GSM900 network: GSM900 network has no pilot channel, and all power is converted to level; while the Reference Signal Receiving Power (RSRP) of NB-IoT network ) comes from the average of the reference signal (Reference Signal, RS) power over the full bandwidth. The NB-IoT protocol specifies the power relationship between a resource element (Resource Element, RE) and RS under one port 1Port and two ports 2Port as shown in Table 1 below:

Table 1

Number of Ports Number of transmit channels NB power (W) RS power (W) 1 1T NB single channel power NB single channel power/12 2 2T 2*NB single channel power NB single channel power/6 2 4T 4*NB single channel power NB single channel power/6

Through the analysis of the above-mentioned NB-IoT network base station transmission performance, the coverage capability difference between it and the GSM900 network can be obtained.

Further, the step S021 is specifically:

The coverage difference ΔPower is obtained by the following formula,

ΔPower＝10×log ₁₀ (GSM _power )-10×log ₁₀ (NB _power /12),

The GSM _power is the transmission power of the GSM900 network base station, and the NB _power is the transmission power of the NB-IoT network base station.

The transmission power GSM _power of the GSM900 network base station and the transmission power NB _power of the NB-IoT network base station can be obtained through the pre-stored construction engineering data in the background, and then the coverage capability difference ΔPower between the two networks can be obtained through the above formula.

Step S022, by comparing the transmission loss between the base station and the terminal between the NB-IoT network and the GSM900 network, the transmission loss difference between the NB-IoT network and the GSM900 network is obtained.

Since the NB-IoT network is mostly used in Internet of Things services such as smart medical care and smart home, its corresponding terminals have the characteristics of low power consumption, low cost, and low mobility, and its application environment is quite different from that of terminals in GSM networks Therefore, it is necessary to give priority to the difference in transmission loss between the base station and the terminal in the two networks, so as to obtain the difference in transmission loss between the two networks.

Further, the transmission loss difference at least includes a penetration loss difference ΔPL and an over-the-air loss difference ΔOTA.

There are many factors that can affect the transmission loss, among which the most influential factors are the penetration loss that occurs when electromagnetic waves propagate between buildings, and the Over The Air (OTA) loss caused by the surrounding environment of the terminal.

The specific penetration loss is related to the specific building type, incident angle of radio waves and other factors. The penetration loss blocked by the partition wall is generally 5-20dB, while the loss in the basement may reach more than 30dB. Especially in urban scenarios, the penetration loss caused by tall buildings will obviously affect the coverage.

Through the test of GSM900 network terminals, multiple high-rise buildings, single-family high-rise buildings, middle-rise buildings, low-rise buildings and other scenes were selected for indoor sweeping tests, covering corridors, corridors and stairs, and the penetration loss was around 18dB. Compared with the GSM900 network, the terminals of the NB-IoT network are in deeper coverage scenarios, such as basements, garages, weak electric wells, elevators, etc. The average building penetration loss is about 28.7dB.

Therefore, compared with the GSM900 network, the penetration loss of the NB-IoT network is about 10dB more, so that the penetration loss difference ΔPL between the two networks is 10dB. Of course, the corresponding penetration loss difference may also be selected according to different application scenarios of different grids.

The over-the-air technology loss refers to the difference in loss generated by the terminal compared with the ideal radiation source during use, and is generally obtained through standard OTA testing. In a specific microwave anechoic chamber, the radiation power and receiving sensitivity of the mobile phone are tested. Different processes and antenna designs of terminals, as well as user habits will affect OTA loss.

Traditional GSM terminals mainly focus on the influence of the position between the terminal and the head of the human hand, and add 4-6dB of OTA loss to the human body loss, such as 3dB.

However, the environment of NB-IoT terminals is more complex. It may be in more complex environments such as electric meter boxes and water meter boxes, and the OTA loss is greater. After passing the multi-scenario OTA standard test, it is recommended that the OTA loss be around 12dB.

Compared with the GSM900 network, the OTA penetration loss difference ΔOTA of the NB-IoT network is about 6dB.

Step S023, by comparing the azimuth angle and downtilt angle of the transmitting antenna between the NB-IoT network and the GSM900 network, the antenna difference between the NB-IoT network and the GSM900 network is obtained.

Since the antenna has fixed coverage beams in the horizontal and vertical directions, each direction has a fixed gain, thereby forming a beam pattern of the antenna. Although the base station of the NB-IoT network is constructed in the way of co-site deployment with the existing GSM900 network, according to different coverage requirements, the azimuth and downtilt angle of the transmitting antenna of the NB-IoT network base station, that is, in the horizontal and vertical directions, respectively, are different from those of the GSM900 network. The transmitting antennas of the network base stations are not necessarily the same. These differences need to be considered in NB-IoT coverage prediction to obtain the antenna difference between NB-IoT and GSM900 networks.

Further, the step S023 is specifically:

By comparing the azimuth angle and downtilt angle of the transmitting antenna between the NB-IoT network and the GSM900 network, and according to a preset compensation algorithm, the antenna difference ΔAn between the NB-IoT network and the GSM900 network is obtained.

Through the pre-stored construction engineering data, the gain attenuation values of each transmitting antenna at each angle relative to the normal direction of the antenna in both horizontal and vertical directions can be obtained. Therefore, by comparing the differences in the azimuth and downtilt angles of the transmitting antennas of the live network GSM900 and the NB-IoT network, and querying the corresponding gain attenuation value according to the preset compensation algorithm, the antenna difference caused by the difference in azimuth angle and downtilt angle can be quantitatively calculated. Value ΔAn.

For example, as shown in Figure 3, NB-IoT antenna, GSM900 antenna, terminal position, wherein the terminal position is the position of the equivalent terminal in each grid after being processed by the MR positioning algorithm, so according to the formula of the compensation algorithm:

ΔAn=F(a-e,b-f)-F(c-e,d-f),

Where a, c, and e are the degrees of the NB-IoT transmitting antenna, the GSM900 transmitting antenna, and the terminal position in the vertical direction from the antenna normal, respectively, and b, d, and f are the NB-IoT transmitting antenna, the GSM900 transmitting antenna, and the terminal, respectively. The degree difference between the position and the antenna normal in the horizontal direction, and F() is to query the corresponding gain attenuation value according to the difference value of the degree.

Step S024. Obtain the coverage mapping model according to the coverage capability difference, transmission loss difference and antenna difference.

According to the coverage capability difference ΔPower between the NB-IoT network and the GSM900 network, the penetration loss difference ΔPL in the transmission loss difference, the over-the-air technology loss difference ΔOTA, and the antenna difference ΔAn, the two networks can be obtained The level difference of each grid is obtained to obtain the coverage mapping model.

In the embodiment of the present invention, the coverage mapping model between the NB-IoT network and the GSM900 network is established, wherein the coverage mapping model includes at least the coverage capability difference, the transmission loss difference and the antenna difference, and then according to the grid coverage status of the GSM900 network, thus Quickly, simply and accurately predict the grid coverage status in the NB-IoT network.

Based on the above embodiment, further, the step S03 is specifically:

The second level of each grid in the second coverage state under the NB-IoT network is obtained by the following formula:

Second level=first level-ΔPower-ΔPL-ΔOTA-ΔAn.

Based on the coverage capability difference ΔPower in the coverage mapping module, the penetration loss difference ΔPL in the transmission loss difference, the over-the-air technology loss difference ΔOTA, and the antenna difference ΔAn obtained based on the above embodiment, combined with each The first level of the grid, the second level of each grid can be obtained through the above formula. Through summarization, the second coverage state of the NB-IoT network offline can be obtained.

The embodiment of the present invention establishes a coverage mapping model between the NB-IoT network and the GSM900 network, and according to the grid coverage status of the GSM900 network, quickly, simply and accurately predicts the grid coverage status in the NB-IoT network.

FIG. 4 is a schematic structural diagram of a device for a NB-IoT coverage prediction method according to an embodiment of the present invention. As shown in FIG. 4 , the device includes: an acquisition module 10, a calculation module 11, and a mapping module 12, wherein,

The acquisition module 10 is used to acquire the first coverage state under the GSM900 network, the first coverage state includes at least the first level of each grid; the calculation module 11 is used to compare the NB-IoT network with The transmission characteristics of the GSM900 network obtain a coverage mapping model, the coverage mapping model at least includes the level difference between the NB-IoT network and the GSM900 network in each grid; the mapping module 12 is used to calculate the level according to the coverage mapping model The difference is summed with the first level in the first coverage state to obtain the second coverage state in the NB-IoT network, and the second coverage state includes the second level of each grid. specifically:

The acquisition module 10 obtains the first coverage status through the MR positioning algorithm based on data such as the GSM900 network MR files, site parameters, and base station configuration files, relying on the main equipment manufacturer or a third-party tool, so as to realize the grid-level geographic coverage of the GSM900 network. presented. After the GSM900 network grid is geographicalized, the GSM network is composed of multiple grids, and the obtained first coverage state at least includes the coverage level value of each GSM900 cell under each grid, that is, the first level. The obtaining module 10 sends the obtained first coverage state to the mapping module 12 .

The calculation module 11 obtains the coverage mapping model by comparing the transmission characteristics of the NB-IoT network and the GSM900 network. The difference in the transmission characteristics is caused by the performance of each device in the two networks and the difference in the transmission environment, for example, the transmission between base stations The difference in performance leads to different coverage capabilities of the cell, and the difference in the transmission environment will lead to different transmission losses, and the difference in the direction of the base station transmitting antenna design will result in different gain attenuation values in each direction, etc. The calculation module 11 obtains the level difference between the two networks in each grid by analyzing the two networks, and combines the level difference distributions of all the grids to obtain a coverage mapping model between the two networks. The calculation module 11 sends the coverage mapping model to the mapping module 12 .

The mapping module 12 superimposes the obtained first level in the first coverage state and the level difference in the coverage mapping model to obtain the second level of each grid under the NB-IoT network. level. Finally, the grid coverage state presented by coverage grid-level geography under the NB-IoT network is obtained, that is, the second coverage state.

The device provided by the embodiment of the present invention is used to execute the above method, and its function refers to the above method embodiment for details, and its specific method flow is not repeated here.

The embodiment of the present invention establishes a coverage mapping model between the NB-IoT network and the GSM900 network, and according to the grid coverage status of the GSM900 network, quickly, simply and accurately predicts the grid coverage status in the NB-IoT network.

FIG. 5 is a schematic structural diagram of another device used for the NB-IoT coverage prediction method according to an embodiment of the present invention. As shown in FIG. 5, the device includes: the acquisition module 10, the calculation module 11, and the mapping module 12. The first calculation unit 111, the second calculation unit 112, the third calculation unit 113, and the aggregation unit 114, wherein,

The first calculation unit 111 is used to obtain the coverage capability difference between the NB-IoT network and the GSM900 network by comparing the transmission performance of the base station between the NB-IoT network and the GSM900 network; the second calculation unit 112 is used to By comparing the transmission loss between the base station and the terminal between the NB-IoT network and the GSM900 network, the transmission loss difference between the NB-IoT and the GSM900 network is obtained; the third calculation unit 113 is used to compare the NB- The azimuth and downtilt angle of the transmitting antenna between the IoT network and the GSM900 network are used to obtain the antenna difference between the NB-IoT and the GSM900 network; the aggregation unit 114 is used to calculate the coverage difference, the transmission loss difference and the antenna difference Value to get the coverage map model. specifically:

The first calculation unit 111 can obtain the coverage capability difference between the two networks by analyzing the base station transmission performance of the NB-IoT network and the GSM900 network.

Further, the first calculation unit 111 is specifically configured to obtain the coverage capability difference ΔPower by the following formula,

ΔPower＝10×log ₁₀ (GSM _power )-10×log ₁₀ (NB _power /12),

The GSM _power is the transmission power of the GSM900 network base station, and the NB _power is the transmission power of the NB-IoT network base station.

The first calculation unit 111 can obtain the transmission power GSM _power of the GSM900 network base station and the transmission power NB _power of the NB-IoT network base station through the pre-stored construction engineering data, and then use the above formula to obtain the coverage capability difference between the two networks ΔPower , and sent to the aggregation unit 114.

The second calculation unit 112 obtains the transmission loss difference between the two networks by comparing the transmission loss difference between the base station and the terminal in the two networks.

Further, the transmission loss difference at least includes a penetration loss difference ΔPL and an over-the-air loss difference ΔOTA.

There are many factors that can affect the transmission loss, among which the most influential factors are the penetration loss that occurs when electromagnetic waves propagate between buildings, and the Over The Air (OTA) loss caused by the surrounding environment of the terminal.

The specific penetration loss is related to the specific building type, incident angle of radio waves and other factors. The penetration loss blocked by the partition wall is generally 5-20dB, while the loss in the basement may reach more than 30dB. Especially in urban scenarios, the penetration loss caused by tall buildings will obviously affect the coverage.

Through the test of GSM900 network terminals, multiple high-rise buildings, single-family high-rise buildings, middle-rise buildings, low-rise buildings and other scenes were selected for indoor sweeping tests, covering corridors, corridors and stairs, and the penetration loss was around 18dB. Compared with the GSM900 network, the terminals of the NB-IoT network are in deeper coverage scenarios, such as basements, garages, weak electric wells, elevators, etc. The average building penetration loss is about 28.7dB.

Therefore, compared with the GSM900 network, the penetration loss of the NB-IoT network is about 10dB more, so the second calculation unit 112 obtains the penetration loss difference ΔPL between the two networks as 10dB, and sends it to the aggregation unit 114 . Certainly, the second calculation unit 112 may also select a corresponding penetration loss difference according to different application scenarios of different grids.

The over-the-air technology loss refers to the difference in loss generated by the terminal compared with the ideal radiation source during use, and is generally obtained through standard OTA testing. In a specific microwave anechoic chamber, the radiation power and receiving sensitivity of the mobile phone are tested. Different processes and antenna designs of terminals, as well as user habits will affect OTA loss.

Traditional GSM terminals mainly focus on the influence of the position between the terminal and the head of the human hand, and add 4-6dB of OTA loss to the human body loss, such as 3dB.

However, the environment of NB-IoT terminals is more complex. It may be in more complex environments such as electric meter boxes and water meter boxes, and the OTA loss is greater. After passing the multi-scenario OTA standard test, it is recommended that the OTA loss be around 12dB.

Compared with the GSM900 network, the second calculation unit 112 obtains the over-the-air technology penetration loss difference ΔOTA of the NB-IoT network is about 6dB, and sends it to the aggregation unit 114 .

Since the antenna has fixed coverage beams in the horizontal and vertical directions, each direction has a fixed gain, thereby forming a beam pattern of the antenna. Although the base station of the NB-IoT network is constructed in the way of co-site deployment with the existing GSM900 network, according to different coverage requirements, the azimuth and downtilt angle of the transmitting antenna of the NB-IoT network base station, that is, in the horizontal and vertical directions, respectively, are different from those of the GSM900 network. The transmitting antennas of the network base stations are not necessarily the same, and the third calculation unit 113 needs to consider these differences when performing NB-IoT coverage prediction to obtain the antenna difference between NB-IoT and the GSM900 network, and send it to the aggregation unit 114.

Further, the third calculation unit 113 is specifically configured to obtain the NB-IoT and GSM900 network according to the difference between the azimuth angle and the downtilt angle of the transmitting antenna between the NB-IoT network and the GSM900 network, and a preset compensation algorithm. Antenna difference ΔAn between GSM900 networks.

The third calculation unit 113 can obtain the gain attenuation value of each transmitting antenna in each angle relative to the normal direction of the antenna in the horizontal and vertical directions through the pre-stored construction engineering data. Therefore, the third computing unit 113 queries the corresponding gain attenuation value according to the preset compensation algorithm by comparing the difference between the azimuth angle and the downtilt angle of the transmitting antenna of the live network GSM900 and the NB-IoT network, so as to quantitatively calculate the azimuth angle and the downtilt angle. The antenna difference ΔAn caused by the downtilt angle difference is sent to the aggregation unit 114 .

For example, as shown in Figure 3, NB-IoT antenna, GSM900 antenna, terminal position, wherein the terminal position is the position of the equivalent terminal in each grid after being processed by the MR positioning algorithm, so according to the formula of the compensation algorithm:

ΔAn=F(a-e,b-f)-F(c-e,d-f),

Where a, c, and e are the degrees of the NB-IoT transmitting antenna, the GSM900 transmitting antenna, and the terminal position in the vertical direction from the antenna normal, respectively, and b, d, and f are the NB-IoT transmitting antenna, the GSM900 transmitting antenna, and the terminal, respectively. The degree difference between the position and the antenna normal in the horizontal direction, and F() is to query the corresponding gain attenuation value according to the difference value of the degree.

According to the coverage capability difference ΔPower between the NB-IoT network and the GSM900 network, the penetration loss difference ΔPL in the transmission loss difference, the over-the-air technology loss difference ΔOTA, and the antenna difference ΔAn, the aggregation unit 114 can The level difference of the two networks in each grid is obtained, so as to obtain the coverage mapping model.

The device provided by the embodiment of the present invention is used to execute the above method, and its function refers to the above method embodiment for details, and its specific method flow is not repeated here.

The embodiment of the present invention establishes a coverage mapping model between the NB-IoT network and the GSM900 network, and according to the grid coverage status of the GSM900 network, quickly, simply and accurately predicts the grid coverage status in the NB-IoT network.

FIG. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. As shown in FIG. 6, the electronic device includes: a processor (processor) 601, a memory (memory) 602 and a bus 603;

Wherein, the processor 601 and the memory 602 complete mutual communication through the bus 603;

The processor 601 is used to call the program instructions in the memory 602 to execute the methods provided by the above method embodiments, for example, including: acquiring a first coverage status under the GSM900 network, the first coverage status includes at least The first level of each grid; the coverage mapping model is obtained by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, and the coverage mapping model includes at least the level of the NB-IoT network and the GSM900 network in each grid difference; according to the level difference of the coverage mapping model and the first level in the first coverage state, the second coverage state under the NB-IoT network is obtained, and the second coverage state includes the second coverage state of each grid level.

Furthermore, the embodiment of the present invention discloses a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, when the program instructions are executed by the computer During execution, the computer can execute the methods provided by the above method embodiments, for example, including: obtaining the first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid; by comparing The transmission characteristics of the NB-IoT network and the GSM900 network obtain a coverage mapping model, and the coverage mapping model includes at least the level difference between the NB-IoT network and the GSM900 network in each grid; according to the level difference of the coverage mapping model and The first level in the first coverage state obtains the second coverage state in the NB-IoT network, and the second coverage state includes the second level of each grid.

Furthermore, an embodiment of the present invention provides a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions cause the computer to execute the methods provided by the above-mentioned method embodiments. The method, for example, includes: obtaining the first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid; obtaining a coverage mapping model by comparing the transmission characteristics of the NB-IoT network and the GSM900 network , the coverage mapping model includes at least the level difference between the NB-IoT network and the GSM900 network in each grid; according to the level difference of the coverage mapping model and the first level in the first coverage state, NB- A second coverage state under the IoT network, the second coverage state includes a second level of each grid.

Those of ordinary skill in the art can understand that all or part of the steps for realizing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the It includes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other various media that can store program codes.

The above-described embodiments such as electronic equipment are only illustrative, and the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, It can be located in one place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative efforts.

Through the above description of the implementations, those skilled in the art can clearly understand that each implementation can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic discs, optical discs, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims (10)

1. A NB-IoT coverage prediction method, characterized in that, comprising: Obtaining a first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid; The coverage mapping model is obtained by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, and the coverage mapping model includes at least the level difference between the NB-IoT network and the GSM900 network in each grid; According to the level difference of the coverage mapping model and the first level in the first coverage state, the second coverage state under the NB-IoT network is obtained, and the second coverage state includes the second level of each grid . 2. The method according to claim 1, wherein the coverage mapping model is obtained by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, and the coverage mapping model at least includes the NB-IoT network and the GSM900 network The level difference of each grid, specifically: By comparing the transmission performance of the base station between the NB-IoT network and the GSM900 network, the coverage capability difference between the NB-IoT network and the GSM900 network is obtained; By comparing the transmission loss between the base station and the terminal between the NB-IoT network and the GSM900 network, the transmission loss difference between the NB-IoT and the GSM900 network is obtained; By comparing the azimuth and downtilt angle of the transmitting antenna between the NB-IoT network and the GSM900 network, the antenna difference between the NB-IoT and the GSM900 network is obtained; The coverage mapping model is obtained according to the coverage capability difference, the transmission loss difference and the antenna difference. 3. The method according to claim 2, wherein the transmission loss difference at least includes a penetration loss difference ΔPL and an over-the-air loss difference ΔOTA. 4. The method according to claim 2, wherein the antenna difference between the NB-IoT and the GSM900 network is obtained by comparing the azimuth and downtilt angle of the transmitting antenna between the NB-IoT network and the GSM900 network value, specifically: By comparing the azimuth angle and downtilt angle of the transmitting antenna between the NB-IoT network and the GSM900 network, and according to a preset compensation algorithm, the antenna difference ΔAn between the NB-IoT network and the GSM900 network is obtained. 5. The method according to claim 2, wherein the coverage capability difference between the NB-IoT and the GSM900 network is obtained by comparing the transmission performance of the base station between the NB-IoT network and the GSM900 network, specifically for: The coverage difference ΔPower is obtained by the following formula, ΔPower＝10×log ₁₀ (GSM _power )-10×log ₁₀ (NB _power /12), The GSM _power is the transmission power of the GSM900 network base station, and the NB _power is the transmission power of the NB-IoT network base station. 6. The method according to any one of claims 3-5, wherein, according to the level difference of the coverage mapping model and the first level in the first coverage state, the NB-IoT network is obtained The second coverage state, the second coverage state includes the second level of each grid, specifically: The second level of each grid in the second coverage state under the NB-IoT network is obtained by the following formula: Second level=first level-ΔPower-ΔPL-ΔOTA-ΔAn. 7. A device for NB-IoT coverage prediction method, characterized in that, comprising: An acquisition module, configured to acquire a first coverage state under the GSM900 network, the first coverage state at least including the first level of each grid; A calculation module, configured to obtain a coverage mapping model by comparing the transmission characteristics of the NB-IoT network and the GSM900 network, the coverage mapping model at least including the level difference between the NB-IoT network and the GSM900 network in each grid; The mapping module is used to obtain a second coverage state under the NB-IoT network according to the level difference of the coverage mapping model and the first level in the first coverage state, and the second coverage state includes each grid of the second level. 8. The device according to claim 7, wherein the calculation module specifically comprises: The first calculation unit is used to obtain the coverage capability difference between the NB-IoT and the GSM900 network by comparing the transmission performance of the base station between the NB-IoT network and the GSM900 network; The second calculation unit is used to obtain the transmission loss difference between the NB-IoT network and the GSM900 network by comparing the transmission loss between the base station and the terminal between the NB-IoT network and the GSM900 network; The third calculation unit is used to obtain the antenna difference between the NB-IoT network and the GSM900 network by comparing the azimuth angle and downtilt angle of the transmitting antenna between the NB-IoT network and the GSM900 network; An aggregation unit, configured to obtain the coverage mapping model according to the coverage capability difference, transmission loss difference and antenna difference. 9. An electronic device, characterized in that it includes a memory and a processor, and the processor and the memory complete mutual communication through a bus; the memory stores program instructions that can be executed by the processor, so The processor can execute the method according to any one of claims 1 to 6 by invoking the program instructions. 10. A computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.