CN108966242B - Coverage estimation method and device for NB-IoT - Google Patents
Coverage estimation method and device for NB-IoTDownload PDFInfo
- Publication number
- CN108966242B CN108966242BCN201810671101.XACN201810671101ACN108966242BCN 108966242 BCN108966242 BCN 108966242BCN 201810671101 ACN201810671101 ACN 201810671101ACN 108966242 BCN108966242 BCN 108966242B
- Authority
- CN
- China
- Prior art keywords
- coverage index
- coverage
- difference
- things
- network
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034methodMethods0.000titleclaimsabstractdescription60
- 238000012360testing methodMethods0.000claimsabstractdescription186
- 238000009826distributionMethods0.000claimsabstractdescription142
- 238000005070samplingMethods0.000claimsabstractdescription107
- 238000010295mobile communicationMethods0.000claimsdescription4
- 230000007774longtermEffects0.000claimsdescription3
- 230000008569processEffects0.000description13
- 238000005259measurementMethods0.000description10
- 238000004590computer programMethods0.000description9
- 230000005540biological transmissionEffects0.000description7
- 238000010586diagramMethods0.000description7
- 238000004458analytical methodMethods0.000description4
- 230000001413cellular effectEffects0.000description4
- 238000004891communicationMethods0.000description4
- 238000005516engineering processMethods0.000description4
- 238000004364calculation methodMethods0.000description3
- 230000006870functionEffects0.000description3
- 238000010276constructionMethods0.000description2
- 230000006855networkingEffects0.000description2
- 238000012545processingMethods0.000description2
- 230000004044responseEffects0.000description2
- 230000011664signalingEffects0.000description2
- 238000004088simulationMethods0.000description2
- 230000008878couplingEffects0.000description1
- 238000010168coupling processMethods0.000description1
- 238000005859coupling reactionMethods0.000description1
- 238000001514detection methodMethods0.000description1
- 238000005315distribution functionMethods0.000description1
- 230000000694effectsEffects0.000description1
- 238000007726management methodMethods0.000description1
- 238000012986modificationMethods0.000description1
- 230000004048modificationEffects0.000description1
- 238000004806packaging method and processMethods0.000description1
- 230000035515penetrationEffects0.000description1
- 230000005855radiationEffects0.000description1
- 238000009877renderingMethods0.000description1
- 230000035945sensitivityEffects0.000description1
- 238000006467substitution reactionMethods0.000description1
- 238000012546transferMethods0.000description1
Images
Classifications
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/22—Traffic simulation tools or models
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
Description
Technical Field
The invention relates to a wireless communication technology, in particular to a coverage estimation method and device for a narrowband Internet of things.
Background
The internet of things technology is a main technical means for realizing mass connection and all-thing interconnection globally, and becomes an important component in all-thing interconnection networks. The Narrow-Band Internet of Things (NB-IoT network) is an important branch of the Internet of everything. The NB-IoT is constructed in the cellular network, only consumes about 180KHz of bandwidth, and can be directly superposed and constructed in a GSM network, a UMTS network or an LTE network so as to reduce the deployment cost and realize smooth upgrading. In the process of establishing and deploying the internet of things, the network coverage of the newly-built internet of things needs to be estimated and adjusted so as to ensure that the perfectly-deployed NB-IoT network coverage index can reach an expected index. However, the NB-IoT network is greatly simplified in the existing LTE technology, and in order to save terminal power consumption, the NB-IoT network does not support measurement reporting, so that the NB-IoT network background coverage index cannot be intuitively obtained through terminal automatic dotting.
The existing coverage estimation method of the NB-IoT network mainly adopts a simulation estimation method based on a propagation model. And for different sampling points, acquiring the receiving power in the drive test data of each sampling point, and correcting the receiving power according to the propagation model, thereby estimating the network planning condition of the whole area.
However, sampling points of drive test data are usually limited to trunk roads, unpredictable errors are brought to the propagation model by various application environments, the simulation coverage estimation method depends too much on the accuracy of parameters of the propagation model, fast iteration is difficult to reflect real environment coverage close to reality, and the existing coverage estimation method of the NB-IoT network is not high in accuracy.
Disclosure of Invention
The invention provides a coverage estimation method and device of a narrowband Internet of things, and provides accuracy of coverage estimation of the narrowband Internet of things.
According to a first aspect of the present invention, a coverage estimation method for a narrowband internet of things is provided, including:
acquiring a current network drive test coverage index and an Internet of things drive test coverage index corresponding to at least one sampling point, wherein the current network drive test coverage index is a drive test coverage index obtained at the sampling point by a test terminal accessed to a current network, the Internet of things drive test coverage index is a drive test coverage index obtained at the sampling point by a test terminal accessed to a narrow-band Internet of things, the narrow-band Internet of things is a co-station network superposed with the current network, and the narrow-band Internet of things and the current network transmit test signals in the same network frequency band;
obtaining a first coverage index difference according to the current network drive test coverage index and the internet of things drive test coverage index corresponding to each sampling point, wherein the first coverage index difference indicates the difference between the current network actual coverage index distribution and the narrow-band internet of things actual coverage index distribution;
and obtaining estimated coverage index distribution of the narrowband Internet of things according to the first coverage index difference and the existing network background coverage index distribution, wherein the existing network background coverage index distribution indicates the existing network background coverage indexes at each coverage position of the existing network.
According to a second aspect of the present invention, there is provided a coverage estimation apparatus for a narrowband internet of things, including:
the system comprises a drive test coverage index acquisition module, a drive test coverage index acquisition module and a drive test coverage index acquisition module, wherein the drive test coverage index acquisition module is used for acquiring a current network drive test coverage index and an Internet of things drive test coverage index corresponding to at least one sampling point, the current network drive test coverage index is a drive test coverage index acquired by a test terminal accessed to a current network at the sampling point, the Internet of things drive test coverage index is a drive test coverage index acquired by a test terminal accessed to a narrow-band Internet of things at the sampling point, the narrow-band Internet of things is a co-station network superposed with the current network, and the narrow-band Internet of things and the current network transmit test signals in the same network frequency band;
a first coverage index difference obtaining module, configured to obtain a first coverage index difference according to the existing network drive test coverage index and the internet of things drive test coverage index corresponding to each sampling point, where the first coverage index difference indicates a difference between an actual coverage index distribution of the existing network and an actual coverage index distribution of the narrowband internet of things;
and the estimation module is used for obtaining the estimated coverage index distribution of the narrowband Internet of things according to the first coverage index difference and the current network background coverage index distribution, wherein the current network background coverage index distribution indicates the current network background coverage indexes at each coverage position of the current network.
According to a third aspect of the present invention, there is provided a coverage estimation apparatus for a narrowband internet of things, including: memory, a processor and a computer program, wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of the first aspect of the invention and its various possible designs.
According to a fourth aspect of the present invention, there is provided a readable storage medium having stored therein a computer program for implementing the method of the first aspect of the present invention and its various possible designs when executed.
The invention provides a coverage estimation method and a coverage estimation device of a narrow-band Internet of things, which mainly comprises the steps of obtaining a current network drive test coverage index and an Internet of things drive test coverage index corresponding to at least one sampling point, wherein the current network drive test coverage index is a drive test coverage index obtained by a test terminal accessed to a current network at the sampling point, the Internet of things drive test coverage index is a drive test coverage index obtained by the test terminal accessed to the narrow-band Internet of things at the sampling point, the narrow-band Internet of things is a co-station network superposed with the current network, and the narrow-band Internet of things and the current network send test signals in the same network frequency band, so that the physical and logical co-station co-antenna of the narrow-station Internet of things and the current network is realized; then obtaining a first coverage index difference according to the current network drive test coverage index and the internet of things drive test coverage index corresponding to each sampling point, wherein the first coverage index difference indicates the difference between the current network actual coverage index distribution and the narrow-band internet of things actual coverage index distribution; according to the first coverage index difference and the existing network background coverage index distribution, the estimated coverage index distribution of the narrow-band Internet of things is obtained, the existing network background coverage index distribution indicates the existing network background coverage indexes at all coverage positions of the existing network, the coverage estimation of the narrow-band Internet of things is realized by the existing network with the same physical and logic settings, the selection requirement of sampling points in the drive test is reduced, and the accuracy of the coverage estimation of the narrow-band Internet of things is improved.
Drawings
Fig. 1 is a schematic diagram of an application scenario provided in an embodiment of the present invention;
fig. 2 is a schematic flow chart of a coverage estimation method of a narrowband internet of things according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of another coverage estimation method for a narrowband internet of things according to an embodiment of the present invention;
fig. 4 is a schematic flowchart of a coverage estimation method for a narrowband internet of things according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a coverage estimation apparatus for a narrowband internet of things according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of another coverage estimation device for a narrowband internet of things according to an embodiment of the present invention;
fig. 7 is a schematic hardware structure diagram of a coverage estimation apparatus for a narrowband internet of things according to an embodiment of the present invention.
Detailed Description
In order to make the objects, 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 with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
It should be understood that, in the various embodiments of the present application, the size of the serial number of each process does 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 to the implementation process of the embodiments of the present application.
It should be understood that, in this application, "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in this application, "plurality" means two or more. It should be understood that in the present application, "B corresponding to a", "a corresponds to B", or "B corresponds to a" means that B is associated with a, from which B can be determined. Determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.
It should be understood that in the present application, "if" may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection".
It should be understood that in the present application, a co-sited network built by superposition means that 2 or more than 2 networks physically use the same set of base station equipment. Specifically, the superposition construction of the narrowband internet of things and the existing network refers to adding a board card in a baseband processing Unit (BBU) of the existing network, and using the same Remote Radio Unit (RRU) and a transmitting antenna to realize physical co-station and co-antenna.
It should be understood that in the present application, the present network refers to a deployed network, an existing network.
It should be understood that in the present application, the Narrow-Band Internet of Things (NB-IoT network for short) is an important branch of the Internet of everything. The NB-IoT is constructed in a cellular network, only consumes about 180KHz of bandwidth, and can be directly deployed in a GSM network, a UMTS network or an LTE network so as to reduce the deployment cost and realize smooth upgrading. The NB-IoT network supports cellular data connectivity for low power devices over a wide area network, also known as a Low Power Wide Area Network (LPWAN). NB-IoT supports efficient connectivity for devices with long standby time and high requirements for network connectivity. It is said that NB-IoT device battery life can be increased to at least 10 years while still providing very comprehensive indoor cellular data connection coverage. The NB-IoT is greatly simplified in the existing LTE technology, has no mobility management, does not support switching and only supports reselection. "164 dB MCL (path loss) and 20dB coverage gain compared to GPRS" are the biggest technical features of NB-IOT networks, but to save terminal power consumption, NB-IOT does not support measurement report mr (measurement report), and therefore, it is not intuitive and all-around method for terminal to automatically click on to evaluate NB-IOT coverage.
It should be understood that in the present application, the Path loss, or propagation loss, specifically, the loss caused by the propagation of the electric wave in space, is caused by the radiation spread of the transmitted power and the propagation characteristics of the channel, and reflects the variation of the mean value of the received signal power in the macroscopic range.
It should be understood that in the present application, Measurement Report (MR) is one of the main bases for evaluating the quality of wireless environment. MR refers to information transmitted once every 480ms (470 ms on signaling channel) on traffic channel, and for Global System for Mobile Communication (GSM) System, MR is the main means for network side to obtain terminal wireless information, and mainly includes two parts: uplink signal information and downlink signal information. Wherein: the downlink signal information is measured and collected by a network terminal and reported to the network through a Measurement Report signaling of a Um port; uplink signal information is measured and collected by a BTS at a network side, and the BTS summarizes uplink and downlink measurement information and reports the information to the BSC through the MR. The downlink measurement report of the MR should include: the level intensity and quality of the service cell, the current transmitting power of the mobile phone, the DTX use condition, the strongest signal intensity and BSIC of six adjacent cells and the like. The MR uplink measurement information should include: the uplink level intensity and quality of the mobile phone, the current transmitting power of the BTS, the DTX use condition and the TA value. One of the main functions of MR is to perform coverage assessment analysis: the blind area of network coverage is presented by the distribution rendering of the uplink and downlink signal intensity, which is not only objective and accurate, but also can save a large amount of time and resources and effectively and timely find out the problem of network coverage.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present invention. The narrow-band Internet of things is constructed on the existing network in an overlapping mode, and the base station equipment 1 is used by the narrow-band Internet of things and the existing network together, so that the narrow-band Internet of things can transmit network signals through the RRU and the antenna of the existing network. In this embodiment, coverage estimation of the narrowband internet of things may be performed by using an individual device 5, and the device 5 may obtain data of the base station and data of each test terminal. For example, the device 5 may be connected to communicate with the base station 1 and the test terminals (2, 3) of the two networks, respectively, to obtain data from the base station 1 and the test terminals (2, 3). For example, the device 5 may be connected to and communicate with the base station 1, the test terminals (2, 3) of the two networks may be connected to and communicate with the base station 1, and the device 5 may acquire data of the base station 1 and the test terminals (2, 3) from the base station 1. Data acquisition should be performed before the device 5 performs coverage estimation. A plurality of sampling points 4 (only one is shown in fig. 1) may be set on, for example, a street, a drive test is performed at eachsampling point 4 using a test terminal (2, 3) accessing two networks, thetest terminal 2 accesses an existing network, and the test terminal 3 accesses a narrowband internet of things. And obtaining the drive test coverage indexes of the two networks at the same sampling point from the test terminals (2 and 3) of the two networks, and obtaining the drive test coverage index difference of the two networks at the sampling point. And obtaining the overall distribution difference of the coverage indexes of the two networks according to the drive test coverage index difference of the two networks on the plurality of sampling points. For example, the coverage index adopted in fig. 1 is used as the received power, and for example, the received power of the narrowband internet of things is lower than that of the existing network by a certain difference on the whole. The coverage index distribution of the background of the existing network can be obtained from the data stored in the background, the coverage index distribution of the background of the existing network can include the coverage indexes of all coverage positions of the existing network, and then the estimated coverage index distribution of the narrow-band internet of things is obtained according to the coverage index distribution of the background of the existing network and the determined difference value.
Referring to fig. 2, which is a schematic flow chart of a coverage estimation method of a narrowband internet of things provided in an embodiment of the present invention, an execution subject of the embodiment may be a coverage estimation device of the narrowband internet of things, and the device may be a server host or a terminal device, or may be a computer software module embedded in the server host or the terminal device. The method shown in fig. 2 mainly includes steps S101 to S103, and specifically includes the following steps:
s101, obtaining a current network test coverage index and an Internet of things drive test coverage index corresponding to at least one sampling point.
The network comprises a sampling point, a current network drive test coverage index, an Internet of things drive test coverage index, a narrow-band Internet of things and a common-station network, wherein the current network drive test coverage index is a test terminal for accessing a current network the drive test coverage index obtained by the sampling point, the Internet of things drive test coverage index is a test terminal for accessing a narrow-band Internet of things, the drive test coverage index obtained by the sampling point, the narrow-band Internet of things is a common-station network constructed by overlapping the current network, and the narrow-band Internet of things and the current network send test signals in the same network frequency band. The superposition construction means that the BBU adds the board card in the existing network, and uses the same RRU and the same transmitting antenna to realize the physical co-station and co-antenna. In this embodiment, a 900MHz network frequency band is taken as an example, the 900MHz narrowband internet of things and a 900MHz current network share an RRU, and a radio frequency mixed mode is adopted for networking, and both the use frequency bands are the same and are 900MHz frequency bands.
Before acquiring the current network drive test coverage index and the internet of things drive test coverage index, parameter consistency setting needs to be performed on the network and the terminal corresponding to the network respectively, so that the terminal can access the network corresponding to the terminal and successfully receive the test signal of the network from the corresponding network. For example, a scrambling switch of the narrowband internet of things is set to be turned on, a scrambling switch of the narrowband internet of things terminal is also set to be turned on, and reselection parameters and access parameters of the narrowband internet of things terminal are set to be matched with the narrowband internet of things. In a specific embodiment, 2 terminals can be adopted, wherein 1 terminal is accessed to 1 network, and then the drive test coverage indexes of the two networks are respectively sampled through the 2 terminals at a sampling point; or 1 terminal which can be accessed to 2 networks simultaneously can be adopted, 1 terminal is accessed to 2 networks, and then the 1 terminal is used for sampling the drive test coverage indexes of the two networks at a sampling point. The test signal may be understood as a signal of a single frequency, such as a reference signal or a pilot signal, and is used for estimating the network coverage index.
For the existing network and the superposed narrowband internet of things, because the transmitting base stations of the two networks and the receiving positions of the terminals are the same, and the path loss of the narrowband internet of things and the existing network can be considered to be the same, the coverage indexes of the two networks corresponding to the coverage positions have relatively stable difference. And next, according to the coverage index difference of the two networks on the sampling point, the coverage index difference of the whole distribution of the two networks is obtained.
S102, obtaining a first coverage index difference according to the current network test coverage index and the Internet of things drive test coverage index corresponding to each sampling point.
Specifically, the first coverage index difference indicates a difference between the actual coverage index distribution of the existing network and the actual coverage index distribution of the narrowband internet of things. The narrow-band Internet of things and the existing network are superposed and built co-station networks, the narrow-band Internet of things and the existing network use the same frequency band to send test signals in the coverage index estimation process, and the coverage indexes of the two networks at each coverage position have the same path loss, so that the difference of the narrow-band Internet of things relative to the existing network at each coverage position is the same. Based on the method, the first coverage index difference of the two networks at all coverage positions can be obtained according to the current network drive test coverage index and the internet of things drive test coverage index of the sampling point. The first coverage indicator difference may be understood as a determined difference, or a table or function characterizing the difference.
In a specific implementation with a certain difference as the first coverage indicator difference, the coverage indicator difference is the same for both networks at each coverage location. The process of obtaining the first coverage index difference may specifically be: firstly, determining the difference between the current network drive test coverage index corresponding to each sampling point and the internet of things drive test coverage index as a first difference value corresponding to each sampling point. And then determining the average value of the first difference values corresponding to the at least one sampling point as the first coverage index difference.
S103, obtaining estimated coverage index distribution of the narrowband Internet of things according to the first coverage index difference and the current network background coverage index distribution.
Wherein the existing network background coverage index distribution indicates existing network background coverage indexes at each coverage position of the existing network. The existing network background coverage index distribution can be data pre-stored in a medium inside or outside the device and is used for representing the coverage indexes of the existing network at each coverage position. The distribution of the coverage indexes of the background of the existing network can be understood as a distribution table of the coverage indexes of the existing network, and can also be understood as a distribution function of the coverage indexes of the existing network.
In one implementation, coverage estimation of the narrowband internet of things can be performed without considering the difference between the background data and the real data of the existing network. The existing network background coverage index distribution can be directly used as the existing network actual coverage index distribution, and then the estimated coverage index distribution of the narrow-band internet of things is obtained according to the first coverage index difference on the basis of the existing network background coverage index distribution.
In another implementation, coverage estimation of the narrowband internet of things can be performed by considering the difference between the background data and the real data of the existing network. The method comprises the steps of firstly obtaining a current network drive test coverage index according to drive test data, obtaining a second coverage index difference between the current network drive test coverage index and a current network background coverage index, and then obtaining more accurate estimated coverage index distribution of the narrow-band internet of things according to the first coverage index difference and the second coverage index difference on the basis of current network background coverage index distribution.
The embodiment provides a coverage estimation method of a narrowband internet of things, which mainly includes acquiring a current network drive test coverage index and an internet of things drive test coverage index corresponding to at least one sampling point, wherein the current network drive test coverage index is a drive test coverage index obtained by a test terminal accessing a current network at the sampling point, the internet of things drive test coverage index is a drive test coverage index obtained by the test terminal accessing the narrowband internet of things at the sampling point, the narrowband internet of things is a co-station network superposed with the current network, and the narrowband internet of things and the current network send test signals in the same network frequency band, so that the physical and logical co-station co-antenna of the narrowband internet of things and the current network is realized; then obtaining a first coverage index difference according to the current network drive test coverage index and the internet of things drive test coverage index corresponding to each sampling point, wherein the first coverage index difference indicates the difference between the current network actual coverage index distribution and the narrow-band internet of things actual coverage index distribution; according to the first coverage index difference and the existing network background coverage index distribution, the estimated coverage index distribution of the narrow-band Internet of things is obtained, the existing network background coverage index distribution indicates the existing network background coverage indexes at all coverage positions of the existing network, the coverage estimation of the narrow-band Internet of things is realized by the existing network with the same physical and logic settings, the selection requirement of sampling points in the drive test is reduced, and the accuracy of the coverage estimation of the narrow-band Internet of things is improved.
Fig. 3 is a schematic flow chart of another coverage estimation method for a narrowband internet of things according to an embodiment of the present invention, and fig. 4 is a schematic flow chart of another coverage estimation method for a narrowband internet of things according to an embodiment of the present invention, and on the basis of the foregoing embodiments, two implementation manners of step S103 in fig. 2 are respectively described below with reference to fig. 3 and 4 and a specific embodiment.
The following is a specific description of a case that, in step S103 in fig. 2, coverage estimation of the narrowband internet of things is performed in consideration of a difference between current network background data and real data, with reference to the method flow shown in fig. 3, where the method shown in fig. 3 mainly includes steps S201 to S205, and specifically, the following steps are performed:
s201, obtaining a current network test coverage index and an Internet of things drive test coverage index corresponding to at least one sampling point.
S202, obtaining a first coverage index difference according to the current network test coverage index and the Internet of things drive test coverage index corresponding to each sampling point.
Specifically, the difference between the current network test coverage index and the internet of things coverage index corresponding to each sampling point may be determined as a first difference value corresponding to each sampling point. And then determining the average value of the first difference values corresponding to the at least one sampling point as the first coverage index difference. For example, the current network drive test coverage index may be the current network drive test received power, and the internet of things drive test coverage index may be the internet of things drive test received power. Then, subtracting the internet of things drive test receiving power of the sampling point from the current internet of things drive test receiving power of the sampling point to obtain a first difference value of the sampling point. For setting 50 sampling points, the 50 first difference values corresponding to the 50 sampling points are averaged. And determining the average value of the 50 first difference values as a first coverage index difference reflecting the difference between the actual coverage index distribution of the current network and the actual coverage index distribution of the narrow-band Internet of things.
The implementation of S201-S202 in this embodiment refers to the specific description of S101-S102 shown in fig. 2, and is not described herein again.
And S203, acquiring a target current network background coverage index corresponding to the at least one sampling point from the pre-stored current network background coverage index distribution.
Specifically, the current network may be a universal mobile telecommunications system UMTS network, or a long term evolution LTE network, or a global system for mobile communications GSM network. For example, if the existing network is a UMTS network, the background coverage indicator distribution of the existing network can be obtained according to a Measurement Report (MR) pre-stored in the UMTS network. The existing network background coverage index distribution indicates the coverage indexes of all coverage positions of the UMTS network, so that the target existing network background coverage index corresponding to the at least one sampling point can be obtained from the existing network background coverage index distribution.
And S204, acquiring a second coverage index difference according to the target current network background coverage index and the current network drive test coverage index corresponding to each sampling point.
Wherein the second coverage metric difference indicates a difference between the existing network actual coverage metric distribution and the existing network background coverage metric distribution. Specifically, the difference between the target current network background coverage index corresponding to each sampling point and the current network drive test coverage index is determined as a second difference value corresponding to each sampling point. And then determining the average value of the second difference values corresponding to the at least one sampling point as the second coverage index difference. If the current network test coverage index is the current network test received power, the target current network background coverage index is also the target current network background received power, and here, the second difference value corresponding to each sampling point can also be understood as: and subtracting the current network path measurement received power from the current target network background received power corresponding to each sampling point to obtain a difference value.
S205, obtaining the estimated coverage index distribution of the narrowband Internet of things according to the second coverage index difference, the first coverage index difference and the current network background coverage index distribution.
Specifically, first, the sum of the second coverage index difference and the first coverage index difference is determined as a third difference value. And then, determining the difference between the current network background coverage index of each coverage position in the current network background coverage index distribution and the third difference value as the estimated coverage index of the narrow-band internet of things corresponding to each coverage position. And finally, determining the distribution of the estimated coverage indexes of the narrowband Internet of things according to the estimated coverage indexes of the narrowband Internet of things corresponding to the coverage positions.
According to the embodiment, the second coverage index difference is introduced through the difference between the target current network background coverage index and the current network drive test coverage index, and the coverage condition recorded by the current network background and the actual coverage condition are subjected to difference analysis, so that the accuracy of the narrow-band Internet of things coverage estimation is improved.
The following is a specific description of a case of performing coverage estimation of the narrowband internet of things without considering a difference between current network background data and real data in step S103 in fig. 2 with reference to the method flow shown in fig. 4, where the method shown in fig. 4 mainly includes steps S301 to S305, and specifically, the following steps are performed:
s301, obtaining the current network test coverage index and the Internet of things test coverage index corresponding to at least one sampling point.
S302, determining the difference between the current network test coverage index corresponding to each sampling point and the Internet of things drive test coverage index as a first difference value corresponding to each sampling point.
S303, determining an average value of the first difference values corresponding to the at least one sampling point as the first coverage index difference.
The specific implementation of S301 to S303 in this embodiment is described in detail with reference to S101 to S102 in fig. 2 or S201 to S202 in fig. 3, and is not described herein again.
S304, determining the difference between the current network background coverage index of each coverage position in the current network background coverage index distribution and the first coverage index as the estimated coverage index of the narrow-band Internet of things corresponding to each coverage position.
Specifically, the difference between the current network background coverage index distribution and the current network actual coverage index distribution is small, and especially, the current network background coverage index distribution obtained according to the latest MR update is substantially consistent with the current network actual coverage index distribution, so the difference between the current network background coverage index distribution and the current network actual coverage index distribution can be disregarded in this embodiment. In this embodiment, the existing network background coverage index of each coverage location is directly used as the actual existing network coverage index of each coverage location. Therefore, a difference value obtained by subtracting the difference of the first coverage indexes from the current network background coverage indexes of each coverage position is used as an estimated coverage index of the narrow-band Internet of things corresponding to each coverage position. The calculation process of the second coverage index difference is omitted, the estimation process is simplified, and the efficiency of the coverage estimation of the narrow-band Internet of things is improved.
S305, determining the distribution of the estimated coverage indexes of the narrowband Internet of things according to the estimated coverage indexes of the narrowband Internet of things corresponding to the coverage positions.
The estimated coverage index distribution of the narrowband Internet of things indicates the coverage index of each coverage position of the narrowband Internet of things.
In the embodiment, the existing network background coverage index of each coverage position is directly used as the actual existing network coverage index of each coverage position, so that the calculation process of the difference of the second coverage indexes is omitted, the estimation process is simplified, and the efficiency of the coverage estimation of the narrow-band internet of things is improved.
On the basis of the above embodiments, the current network includes a universal mobile telecommunications system UMTS network, or a long term evolution LTE network, or a global system for mobile communications GSM network.
On the basis of the above embodiment, the coverage index of the existing network test is the received power of the existing network test, and correspondingly, the coverage index distribution of the existing network background is the background received power distribution of the existing network. The road test coverage index of the internet of things is the road test receiving power of the internet of things, and correspondingly, the estimated coverage index distribution of the narrowband internet of things is the estimated receiving power distribution of the narrowband internet of things.
The calculation of the first coverage index difference is exemplified below.
Specifically, taking the 900MHz frequency band as an example, the existing network of the 900MHz frequency band (this embodiment is abbreviated as U900) and the narrowband internet of things of the 900MHz frequency band (this embodiment is abbreviated as N900) share the RRU, and a radio frequency mixed mode is adopted for networking, where the frequency bands used by the two are the same, and the coverage condition of the narrowband internet of things is estimated by using the MR of the existing network sharing the station. Because the two networks have different application scenes, different systems, different terminal types and the like, the mobility of the terminals is different, and various influence factors in the propagation loss model and the received field strength model need to be considered during estimation.
For the propagation loss model, the electromagnetic wave free space propagation path loss model is: los ═ 32.44+20lg d (Km) +20lg f (MHz), where Los is the propagation loss in dB; d is distance in Km; f is the operating frequency in MHz. When f is 900MHz, Los is 91.48+20lgd (km).
For the receiving field strength model, it may specifically be: the RSS is Pt + Gr + Gt-Lc-Los, wherein the RSS is the intensity of the received signal; pt is the emission power; gr is the receiving antenna gain; gt is the transmitting antenna gain; lc is attenuation of the cable and the cable head; los is the free space loss.
The analysis shows that:
(1) n900 and U900 have the same frequency band and the same path loss. The actual path loss is affected by factors such as atmosphere, shadowing, and penetration loss, and they are considered equivalent.
(2) The test signal configurations of N900 and U900 are different in the transmission power affecting the received field strength, which can be understood as the received power. The power of a test signal (which may be understood as a pilot signal) of U900 is configured to be 33dbm ═ 2W, a wideband system, and the pilot power is a full frequency band; the test signal (which may be understood as a reference signal) power of N900 is configured as 32.2 dbm-1.66W, narrowband system, power per RE symbol.
(3) The terminal receiving sensitivity is related to the chip, the receiving antenna gain, the antenna packaging mode and the like.
Based on the above analysis it can be assumed that: receive power-transmit power-path loss. Since the N900 and the U900 share one set of antenna feed system, and the frequency bands are the same, the coupling loss is the same, and therefore, the following relationship exists for the same coverage position: n received power-U received power-N transmit power-U transmit power-N path loss-U path loss. Since the two networks have the same path loss, the relationship can be directly equivalent to: the N received power is U received power + N transmit power-U transmit power, where N received power is the received power of the narrowband internet of things, and may be, for example, the received power RSRP of the downlink reference signal; the U received power is the received power of the existing network, and may be, for example, received signal code power RSCP; the N transmission power is transmission power of the narrowband internet of things, and may be reference signal RS transmission power, for example; the U transmission power is the transmission power of the existing network, and may be the primary common control channel PCPICH transmission power, for example. Therefore, U900RSCP coverage can be obtained through U900MR, and the N900 actual coverage index condition is evaluated according to the coverage condition. If the PCPICH transmitting power of the U900 is consistent with the transmitting power of the N900RS, the RSCP of the U900 and the RSRP of the N900 are respectively tested at the same place, so that the difference between the receiving capacities of the terminal signals of the existing network and the narrowband Internet of things can be obtained, and the difference needs to be added in the final narrowband Internet of things coverage index estimation.
Referring to fig. 5, a schematic structural diagram of a coverage estimation device for a narrowband internet of things provided in an embodiment of the present invention mainly includes: a drive test coverageindex obtaining module 51, a first coverage indexdifference obtaining module 52 and anestimating module 53. The method comprises the following specific steps:
a drive test coverageindex obtaining module 51, configured to obtain a current network drive test coverage index and an internet of things drive test coverage index corresponding to at least one sampling point, where the current network drive test coverage index is a drive test coverage index obtained at the sampling point by a test terminal accessing a current network, the internet of things drive test coverage index is a drive test coverage index obtained at the sampling point by a test terminal accessing a narrowband internet of things, the narrowband internet of things is a co-located network superposed with the current network, and the narrowband internet of things and the current network send test signals in the same network frequency band;
a first coverage indexdifference obtaining module 52, configured to obtain a first coverage index difference according to the current network drive test coverage index and the internet of things drive test coverage index corresponding to each sampling point, where the first coverage index difference indicates a difference between actual coverage index distribution of the current network and actual coverage index distribution of the narrowband internet of things;
the estimatingmodule 53 is configured to obtain estimated coverage index distribution of the narrowband internet of things according to the first coverage index difference and existing network background coverage index distribution, where the existing network background coverage index distribution indicates existing network background coverage indexes at each coverage position of the existing network.
The coverage estimation apparatus of the narrowband internet of things in the embodiment shown in fig. 5 can be correspondingly used to execute the steps in the method embodiment shown in fig. 2, and the implementation principle and the technical effect are similar, which are not described herein again.
Referring to fig. 6, it is a schematic structural diagram of another coverage estimation apparatus for a narrowband internet of things provided in the embodiment of the present invention, and further includes: a second coverage indexdifference obtaining module 54, configured to obtain a target current network background coverage index corresponding to the at least one sampling point from pre-stored current network background coverage index distributions before obtaining an estimated coverage index distribution of the narrowband internet of things according to the first coverage index difference and current network background coverage index distributions; and obtaining a second coverage index difference according to the target current network background coverage index and the current network drive test coverage index corresponding to each sampling point, wherein the second coverage index difference indicates the difference between the current network actual coverage index distribution and the current network background coverage index distribution.
Accordingly, theestimation module 53 is configured to: and obtaining estimated coverage index distribution of the narrowband Internet of things according to the second coverage index difference, the first coverage index difference and the current network background coverage index distribution, wherein the current network background coverage index distribution indicates the current network background coverage indexes at each coverage position of the current network.
On the basis of the foregoing embodiment, the second coverage indexdifference obtaining module 54 is configured to:
before obtaining the estimated coverage index distribution of the narrowband internet of things according to the first coverage index difference and the current network background coverage index distribution, obtaining a target current network background coverage index corresponding to the at least one sampling point from the pre-stored current network background coverage index distribution; determining the difference between the target current network background coverage index corresponding to each sampling point and the current network drive test coverage index as a second difference value corresponding to each sampling point; and determining the average value of the second difference values corresponding to the at least one sampling point as the second coverage index difference.
On the basis of the foregoing embodiment, the first coverage indexdifference obtaining module 52 is configured to:
determining the difference between the current network drive test coverage index corresponding to each sampling point and the internet of things drive test coverage index as a first difference value corresponding to each sampling point; determining an average value of the first difference values corresponding to the at least one sampling point as the first coverage index difference, wherein the first coverage index difference indicates a difference between the actual coverage index distribution of the existing network and the actual coverage index distribution of the narrowband internet of things.
On the basis of the above embodiment, theestimation module 53 is configured to:
determining a sum of the second coverage indicator difference and the first coverage indicator difference as a third difference; determining the difference between the current network background coverage index of each coverage position in the current network background coverage index distribution and the third difference as an estimated coverage index of the narrow-band internet of things corresponding to each coverage position, wherein the current network background coverage index distribution indicates the current network background coverage index at each coverage position of the current network; and determining the distribution of the estimated coverage indexes of the narrowband Internet of things according to the estimated coverage indexes of the narrowband Internet of things corresponding to the coverage positions.
On the basis of the foregoing embodiment, the first coverage indexdifference obtaining module 52 is configured to:
determining the difference between the current network drive test coverage index corresponding to each sampling point and the internet of things drive test coverage index as a first difference value corresponding to each sampling point; determining an average value of the first difference values corresponding to the at least one sampling point as the first coverage index difference, wherein the first coverage index difference indicates a difference between the actual coverage index distribution of the existing network and the actual coverage index distribution of the narrowband internet of things.
On the basis of the above embodiment, theestimation module 53 is configured to:
determining the difference between the current network background coverage index of each coverage position in the current network background coverage index distribution and the first coverage index as an estimated coverage index of the narrow-band internet of things corresponding to each coverage position, wherein the current network background coverage index distribution indicates the current network background coverage index of each coverage position of the current network; and determining the distribution of the estimated coverage indexes of the narrowband Internet of things according to the estimated coverage indexes of the narrowband Internet of things corresponding to the coverage positions.
Referring to fig. 7, it is a schematic diagram of a hardware structure of a coverage estimation apparatus of a narrowband internet of things provided in an embodiment of the present invention, where the apparatus includes: aprocessor 91,memory 92 and computer programs; wherein
Amemory 92 for storing the computer program, which may also be a flash memory (flash). The computer program is, for example, an application program, a functional module, or the like that implements the above method.
Aprocessor 91 for executing the computer program stored in the memory to implement the steps performed by the apparatus in the above method. Reference may be made in particular to the description relating to the preceding method embodiment.
Alternatively, thememory 92 may be separate or integrated with theprocessor 91.
When thememory 92 is a device independent of theprocessor 91, the apparatus may further include:
abus 93 for connecting thememory 92 and theprocessor 91.
The present invention also provides a readable storage medium, in which a computer program is stored, which when executed is used to implement the methods provided by the various embodiments described above.
The readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, a readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and the readable storage medium may reside in an Application Specific Integrated Circuits (ASIC). Additionally, the ASIC may reside in user equipment. Of course, the processor and the readable storage medium may also reside as discrete components in a communication device.
The present invention also provides a program product comprising execution instructions stored in a readable storage medium. The at least one processor of the device may read the execution instructions from the readable storage medium, and the execution of the execution instructions by the at least one processor causes the device to implement the methods provided by the various embodiments described above.
In the above embodiments of the apparatus, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present application may be embodied directly in a hardware processor, or in a combination of the hardware and software modules in the processor.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (12)
Translated fromChinesePriority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810671101.XACN108966242B (en) | 2018-06-26 | 2018-06-26 | Coverage estimation method and device for NB-IoT |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810671101.XACN108966242B (en) | 2018-06-26 | 2018-06-26 | Coverage estimation method and device for NB-IoT |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108966242A CN108966242A (en) | 2018-12-07 |
| CN108966242Btrue CN108966242B (en) | 2021-10-22 |
Family
ID=64486765
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810671101.XAActiveCN108966242B (en) | 2018-06-26 | 2018-06-26 | Coverage estimation method and device for NB-IoT |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108966242B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108471627B (en)* | 2018-06-28 | 2021-02-23 | 中国联合网络通信集团有限公司 | Network quality determination method and device |
| CN111328121B (en)* | 2018-12-17 | 2022-06-14 | 中国移动通信集团北京有限公司 | A road test method and device |
| CN111385038B (en)* | 2018-12-27 | 2022-06-10 | 中国移动通信集团山西有限公司 | NB-IoT coverage evaluation method, device, equipment and medium |
| CN111818550B (en)* | 2019-04-11 | 2022-09-27 | 中国移动通信集团四川有限公司 | Method, device and device for predicting network coverage |
| CN111988785B (en)* | 2019-05-21 | 2022-04-05 | 大唐移动通信设备有限公司 | 5G network coverage processing method and device |
| CN110233684B (en)* | 2019-07-04 | 2021-09-07 | 中国联合网络通信集团有限公司 | Signal-to-noise ratio evaluation method, apparatus, equipment and storage medium |
| CN113625031B (en)* | 2021-08-23 | 2023-06-16 | 中国联合网络通信集团有限公司 | Intelligent ammeter terminal, MR data reporting system and method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1845631A (en)* | 2005-04-06 | 2006-10-11 | 华为技术有限公司 | Realization Method of Network Planning in Wireless Communication System |
| CN101060689A (en)* | 2007-05-17 | 2007-10-24 | 华为技术有限公司 | A method and equipment for planning the communication system network |
| CN102065432A (en)* | 2009-11-13 | 2011-05-18 | 中国移动通信集团黑龙江有限公司 | Transmission model-based network coverage correcting method and system |
| CN102883338A (en)* | 2011-07-11 | 2013-01-16 | 同济大学 | Correction method for propagation model in TD-LTE system |
| CN103347261A (en)* | 2013-07-01 | 2013-10-09 | 广东省电信规划设计院有限公司 | Networking method and device for determining deployment of LTE network based on CDMA network data |
| CN103533554A (en)* | 2013-10-21 | 2014-01-22 | 上海邮电设计咨询研究院有限公司 | Method for predicting coverage of 4G LTE (Long-Term Evolution) network based on 3G path measurement data |
| WO2014183782A1 (en)* | 2013-05-14 | 2014-11-20 | Nokia Solutions And Networks Oy | Method and network device for cell anomaly detection |
- 2018
- 2018-06-26CNCN201810671101.XApatent/CN108966242B/enactiveActive
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1845631A (en)* | 2005-04-06 | 2006-10-11 | 华为技术有限公司 | Realization Method of Network Planning in Wireless Communication System |
| CN101060689A (en)* | 2007-05-17 | 2007-10-24 | 华为技术有限公司 | A method and equipment for planning the communication system network |
| CN102065432A (en)* | 2009-11-13 | 2011-05-18 | 中国移动通信集团黑龙江有限公司 | Transmission model-based network coverage correcting method and system |
| CN102883338A (en)* | 2011-07-11 | 2013-01-16 | 同济大学 | Correction method for propagation model in TD-LTE system |
| WO2014183782A1 (en)* | 2013-05-14 | 2014-11-20 | Nokia Solutions And Networks Oy | Method and network device for cell anomaly detection |
| CN103347261A (en)* | 2013-07-01 | 2013-10-09 | 广东省电信规划设计院有限公司 | Networking method and device for determining deployment of LTE network based on CDMA network data |
| CN103533554A (en)* | 2013-10-21 | 2014-01-22 | 上海邮电设计咨询研究院有限公司 | Method for predicting coverage of 4G LTE (Long-Term Evolution) network based on 3G path measurement data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108966242A (en) | 2018-12-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108966242B (en) | Coverage estimation method and device for NB-IoT | |
| US11239926B2 (en) | Measurement method, terminal, device, and access network device | |
| CN102457890B (en) | A kind of method and system realizing drive test | |
| CN107896380B (en) | Network switching control method and device | |
| US20210195456A1 (en) | Method and device for wireless communication | |
| EP3596976A1 (en) | Altitude position state based mobile communications | |
| JP7220945B2 (en) | Automatic optimization of serving base station cell parameters | |
| CN114268982B (en) | Vehicle-mounted mobile communication terminal test system | |
| CN112135291A (en) | State detection method and device | |
| CN110933741A (en) | User equipment positioning method and device | |
| CN105493543B (en) | Information processing device, wireless communication system, and terminal position estimation method | |
| CN111447654A (en) | Switching method and system of track traffic equal-line type networking terminal between different-frequency cells | |
| CN106998563A (en) | A kind of room subsystem method for early warning and device based on network performance | |
| EP2733973B1 (en) | Subscriber terminal identification | |
| CN116349277A (en) | Method and apparatus for designing a radio access network | |
| CN111615136A (en) | Test method and system for determining signal coverage area of electronic fence equipment | |
| CN110649981A (en) | MOD3 interference processing method and equipment | |
| CN107949026A (en) | Network switching control method and device | |
| CN114040426B (en) | Network optimization method, abnormal cell push method, device, terminal and server | |
| Karimi et al. | Measurement based mobility emulation platform for next generation wireless networks | |
| JP7534030B2 (en) | Method and apparatus for using unlicensed spectrum | |
| KR20240129042A (en) | Information transmission method, radio frequency device and control device | |
| CN101330699A (en) | Device and method for testing base station | |
| WO2019185143A1 (en) | Method and apparatus for characterizing a radio frequency environment in a telecommunications network | |
| CN110519767A (en) | A kind of NB-IoT coverage prediction method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |