Terminal positioning method and device, electronic equipment and storage medium

Abstract

The invention discloses a terminal positioning method and device, electronic equipment and a storage medium, and belongs to the technical field of communication, in the method, a relation between fingerprint information and positioning information of each test terminal in a base station coverage range is learned in advance to obtain a positioning model, then the fingerprint information of each terminal is obtained every a preset time period, and the positioning model is obtained; and inputting the fingerprint information of each terminal into a positioning model to obtain positioning information of each terminal, the fingerprint information of each terminal including CQI information and MAC layer resource scheduling information. The CQI information and the MAC layer resource scheduling information are naturally generated in the communication process, and a protocol does not need to be changed for obtaining the CQI information and the MAC layer resource scheduling information. And the terminal does not need to send the positioning reference information before positioning, so that batch terminal positioning can be realized on the premise that the terminal is non-inductive, and air interface resources can be saved. And the terminal is positioned by combining multiple dimensions of the CQI information of the physical layer and the resource scheduling information of the MAC layer, so that accurate positioning can be realized more easily.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a terminal positioning method, device, electronic device and storage medium. Background Art

[0002] The fifth-generation mobile communication network has spawned a large number of new application scenarios, and base stations obtaining accurate terminal location information is a basic functional requirement in most application scenarios.

[0003] In related technologies, the terminal is located using channel state information (CSI) as fingerprint information. However, since CSI is a set of physical layer information, it is generally not available to the wireless network card and base station of the terminal without additional operations to modify the protocol layer. In addition, when locating the terminal, the terminal must first send a positioning reference signal to the base station, and sending a positioning reference signal requires air interface resources, so to a certain extent, it will also waste the air interface resources of the base station.

[0004] It can be seen that the terminal positioning method in the related art has the problem that the protocol layer needs to be modified and air interface resources are wasted. Summary of the invention

[0005] The embodiments of the present application provide a terminal positioning method, device, electronic device and storage medium, which are used to solve the problem that the terminal positioning method in the related art needs to modify the protocol layer and waste air interface resources.

[0006] In a first aspect, an embodiment of the present application provides a terminal positioning method, including:

[0007] At every preset time period, fingerprint information of each terminal is obtained, where the fingerprint information of each terminal includes channel quality indication information and medium access control MAC layer resource scheduling information;

[0008] The fingerprint information of each terminal is input into the positioning model to obtain the positioning information of each terminal. The positioning model is obtained by learning in advance the relationship between the fingerprint information and the positioning information of each test terminal within the coverage range of the corresponding base station.

[0009] In some embodiments, the MAC layer resource scheduling information of each terminal includes any combination of the following information:

[0010] The assigned beam number, time slot, frequency band, and power level,

[0011] Scheduling time,

[0012] Time advance,

[0013] Correct transmission of confirmation characters,

[0014] Terminal identification,

[0015] The base station number of the base station.

[0016] In some embodiments, before inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the method further includes:

[0017] The collection time of target information that meets preset conditions in the MAC layer resource scheduling information of each terminal is extended, and the preset conditions include that the degree of information change at consecutive scheduling moments is greater than a first preset value, and the degree of information correlation at consecutive scheduling moments is greater than a second preset value.

[0018] In some embodiments, the collection time of target information that meets preset conditions in the MAC layer resource scheduling information of each terminal is extended, including:

[0019] Obtain target information of each terminal at N historical scheduling moments, where N is a preset integer;

[0020] The target information of the N historical scheduling moments is integrated into the target information of the terminal at the scheduling moment.

[0021] In some embodiments, after inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the method further includes:

[0022] Determine the distribution of terminals within the coverage area of ​​the base station based on the positioning information of each terminal;

[0023] Based on the terminal distribution, the air interface scheduling resources of the base station are optimized.

[0024] In a second aspect, an embodiment of the present application provides a terminal positioning device, including:

[0025] An acquisition module, used to acquire fingerprint information of each terminal at every preset time period, where the fingerprint information of each terminal includes channel quality indication information and media access control MAC layer resource scheduling information;

[0026] The positioning module is used to input the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal. The positioning model is obtained by learning the relationship between the fingerprint information and the positioning information of each test terminal within the coverage range of the corresponding base station in advance.

[0027] In some embodiments, the MAC layer resource scheduling information of each terminal includes any combination of the following information:

[0028] The assigned beam number, time slot, frequency band, and power level,

[0029] Scheduling time,

[0030] Time advance,

[0031] Correct transmission of confirmation characters,

[0032] Terminal identification,

[0033] The base station number of the base station.

[0034] In some embodiments, a pre-processing module is further included for:

[0035] Before inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the collection time of the target information that meets the preset conditions in the MAC layer resource scheduling information of each terminal is extended, and the preset conditions include that the degree of information change at continuous scheduling moments is greater than a first preset value, and the degree of information correlation at continuous scheduling moments is greater than a second preset value.

[0036] In some embodiments, the preprocessing module is specifically used to:

[0037] Obtain target information of each terminal at N historical scheduling moments, where N is a preset integer;

[0038] The target information of the N historical scheduling moments is integrated into the target information of the terminal at the scheduling moment.

[0039] In some embodiments, an optimization module is further included for:

[0040] After inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the distribution of the terminals within the coverage area of ​​the base station is determined based on the positioning information of each terminal;

[0041] Based on the terminal distribution, the air interface scheduling resources of the base station are optimized.

[0042] In a third aspect, an embodiment of the present application provides an electronic device, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein:

[0043] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute any of the above-mentioned terminal positioning methods.

[0044] In a fourth aspect, an embodiment of the present application provides a storage medium. When a computer program in the storage medium is executed by a processor of an electronic device, the electronic device can execute any of the above-mentioned terminal positioning methods.

[0045] In the embodiment of the present application, the relationship between the fingerprint information and the positioning information of each test terminal within the coverage of the base station is learned in advance to obtain a positioning model. After that, the fingerprint information of each terminal is obtained at every preset time period, and the fingerprint information of each terminal is input into the positioning model to obtain the positioning information of each terminal, wherein the fingerprint information of each terminal includes channel quality indication (CQI) information and medium access control (MAC) layer resource scheduling information. Since CQI is a channel quality indication flag, it can be reported together with the terminal measurement, and it is not necessary to change the protocol layer to obtain it, and the MAC layer resource scheduling information is naturally generated during the communication establishment process, and does not require additional signaling to control the generation, and can also be directly obtained. Before positioning, there is no need for the terminal to send positioning reference information first, and batch positioning of terminals can be achieved under the premise of terminal insensitivity, and the air interface resources required for sending positioning reference information can also be saved. In addition, the terminal is positioned in multiple dimensions by combining the CQI information of the physical layer and the MAC layer resource scheduling information, which is also easier to achieve accurate positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0047] Figure 1 A schematic diagram of a terminal positioning process provided in an embodiment of the present application;

[0048] Figure 2 A schematic diagram of the deployment of an LMF network element entity provided in an embodiment of the present application;

[0049] Figure 3 A flowchart of a terminal positioning method provided in an embodiment of the present application;

[0050] Figure 4 A schematic diagram of the structure of a terminal positioning device provided in an embodiment of the present application;

[0051] Figure 5 A schematic diagram of the hardware structure of an electronic device for implementing a terminal positioning method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to solve the problem that the terminal positioning method in the related art needs to modify the protocol layer and waste air interface resources, the embodiments of the present application provide a terminal positioning method, device, electronic device and storage medium.

[0053] The preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application. In addition, the embodiments and features in the embodiments of the present application may be combined with each other if there is no conflict.

[0054] The embodiment of the present application proposes a solution for realizing outdoor sensorless batch positioning of terminals by combining physical layer information and MAC layer information. Figure 1 , which is a schematic diagram of a terminal positioning process provided in an embodiment of the present application. In a multi-user cellular mobile communication scenario, first, the fingerprint information and positioning information of the test terminal that can be directly obtained by the base station side during the communication process are collected, and the fingerprint information of the test terminal is preprocessed to construct a fingerprint database that can be used for deep learning. Then, a deep neural network model is designed to train the fingerprint database offline to obtain a positioning model. Finally, the positioning model is used to locate the terminal online in real time.

[0055] The above process is described in detail below.

[0056] The first step is to collect fingerprint information and positioning information of the test terminal from the cellular mobile communication scenario, and use the fingerprint information and positioning information to build a fingerprint database.

[0057] 1. Extract the fingerprint information and positioning information of the test terminal that can be collected by the base station side within a period of time as the original data.

[0058] Generally, some terminals can be selected as test terminals, and the staff can take these test terminals to the set positioning positions to obtain fingerprint information. This manual method can obtain accurate fingerprint information and positioning information of the test terminals, but due to the large coverage of the base station, it is difficult to obtain fingerprint information at all positioning positions manually, and only a small part of accurate positioning positions and fingerprint information can be obtained. In order to locate the terminal at any position within the coverage of the base station, the positioning model can be used to learn the relationship between this small part of accurate fingerprint information and positioning information, and then the positioning model can be used to locate the terminal within the coverage of the base station.

[0059] Here, the fingerprint information collected for each test terminal includes CQI information and MAC layer resource scheduling information, which is equivalent to combining the physical layer CQI information and the scheduling information of the base station for resource scheduling at the MAC layer as the terminal's fingerprint information. This information is naturally generated during the communication process, and there is no need to change the protocol or any additional processing on the terminal side. In addition, combining the two layers of information as fingerprint information can more completely reflect the terminal's location information, which is conducive to accelerating the convergence speed of the neural network and improving positioning accuracy.

[0060] In practical applications, the richer the MAC layer resource scheduling information is, the more conducive it is to achieve accurate positioning. In some embodiments, the MAC layer resource scheduling information may include resource allocation result information and resource scheduling process information. The resource allocation result information may be recorded as RAR (the most important MAC layer resource scheduling information is RAR, and each terminal has a unique RAR, and RAR is unique), including the allocated beam number, time slot, frequency band, power size, etc. The resource scheduling process information may include the time T when the base station performs scheduling, the time advance (Time Advance, TA), the correct transmission confirmation character (Acknowledge character, ACK), the International Mobile Subscriber Identity (International Mobile Subscriber Identity, IMSI) reflecting the terminal identity, and the base station number information reflecting the base station identity.

[0061] When the MAC layer resource scheduling information includes the above information, the fingerprint information of any test terminal obtained by the base station side can be expressed as: d = (T, CQI, TA, RAR, ACK, IMSI, eNB_Id), and the positioning information corresponding to the fingerprint information is the label of d.

[0062] Where T is the scheduling time;

[0063] CQI is a vector, which can be expressed as c = (c1, c2, ..., c n ), reflecting the quality of the channel of the test terminal on n channels, c1, c2, …, c n The value range of is between 0 and 15;

[0064] TA is the time advance;

[0065] RAR can be expressed as (r beam ,r slot ,r fre ,p), and Indicates the use of m beams by the test terminal. When any beam is used, the value is 1, and when it is not used, the value is 0. Indicates the occupancy of k time slots by the test terminal. When any time slot is occupied, the value is 1, and when it is not occupied, the value is 0; Indicates the occupancy of j frequency bands by the test terminal. When any frequency band is occupied, the value is 1, and when it is not occupied, the value is 0. p indicates the power value allocated to the test terminal.

[0066] ACK is a character that confirms the correct transmission. The value is 1 when it is correct and 0 when it is wrong.

[0067] IMSI is the terminal identification;

[0068] eNB_Id is the base station number.

[0069] It should be noted that the fingerprint information and positioning information reported by the test terminal once form one piece of original data. A test terminal can report fingerprint information and positioning information multiple times within a period of time, so multiple pieces of original data can be obtained for the same test terminal.

[0070] 2. Perform data preprocessing on the fingerprint information in the original data, remove the strong correlation between some information, and construct a fingerprint database suitable for training and prediction through the neural network model.

[0071] Generally, a fingerprint information contains multiple information, and the scheduling time of the base station is at the millisecond level, that is, there will be a fingerprint information every several milliseconds. This may cause some information in the fingerprint information to change greatly at continuous scheduling moments but have strong correlation. If this information is directly used for model training, it will increase the model training time and it will be difficult to get a good training effect. For this reason, the collection time of this information can be extended to reduce its correlation between continuous scheduling moments and improve the accuracy of this information.

[0072] The following will analyze whether each type of fingerprint information needs to have its collection time extended.

[0073] 1) RAR: allocated beam number, time slot, frequency band, and power size.

[0074] Generally, the RAR changes at consecutive scheduling moments are relatively large (i.e., the degree of change is greater than the first preset value), and the correlation is also relatively high (i.e., the degree of correlation is greater than the second preset value). In order to cope with the strong correlation between RARs caused by the short scheduling moment, the RAR collection time can be extended.

[0075] 2) Scheduling time T.

[0076] The scheduling time T increases naturally with the number of scheduling times and is only used to mark the time corresponding to the fingerprint data, without the need to extend the collection time.

[0077] 3) Time advance TA.

[0078] Generally, TA remains basically unchanged within three consecutive scheduling times, and there is no problem of huge changes. Therefore, there is no need to extend the collection time.

[0079] 4) Correctly transmit the confirmation character ACK.

[0080] Generally, the ACKs at consecutive scheduling moments vary greatly (i.e., the degree of variation is greater than the first preset value) but the correlation is also relatively high (i.e., the degree of correlation is greater than the second preset value). In order to cope with the strong correlation between ACKs caused by the short scheduling moment, the ACK collection time can be extended.

[0081] 5)Terminal identification.

[0082] It will not change with the scheduling time and there is no need to extend the collection time.

[0083] 6) Base station number.

[0084] It will not change with the scheduling time and there is no need to extend the collection time.

[0085] From the above analysis, it can be known that the information that needs to be processed by extending the collection time includes RAR and ACK. The following introduces the method of extending the collection time.

[0086] It is assumed that the base station has 3 time slots, 3 frequency bands, and 3 beam numbers, and that the acquisition time is extended by using the data of the test terminal at 2 historical scheduling moments before the T scheduling moment.

[0087] Further assume that the RAR and ACK of the test terminal at the scheduling time T are:

[0088]

[0089] The RAR and ACK at the T-1 scheduling time are:

[0090]

[0091] The RAR and ACK at the T-2 scheduling time are:

[0092]

[0093] Assuming that the data of the three scheduling times are fused according to the maximum probability generation rule (i.e., if 1 appears the most times among the three scheduling times, then it is 1, and if 0 appears the most times, then it is 0), then the RAR and ACK at the T scheduling time after fusion are:

[0094]

[0095] It should be noted that the two historical scheduling moments here are only examples. In actual applications, the number N of historical scheduling moments can be adjusted according to the training effect of the positioning model.

[0096] After preprocessing the fingerprint data in all the original data according to the above process, a fingerprint database suitable for model training is obtained.

[0097] The second step is to design a deep neural network model to perform offline training on the fingerprint database to obtain a positioning model.

[0098] First, the fingerprint database is divided into a training set and a validation set in a ratio of 8:2.

[0099] Then, a deep neural network model is designed for regression prediction of terminal location. The specific process is as follows:

[0100] Model pre-training stage: You can build network models with different structures of 1, 2, 3, 4, and 5 fully connected layers, with 128, 256, 512, 1024, and 2048 neurons in each layer. Then, input the training set into each network model for training, and select the network model with the appropriate structure according to the training effect. The number of iterations in this stage can be 20,000 times, the learning rate can be 0.001, and the batch size can be 4. After pre-training, analyze the complexity and convergence of network models with different structures, and determine the selected structure is a network model with 4 fully connected layers and 1024 neurons.

[0101] Model verification phase: After determining the structure of the network model, input the training set into the network model of the corresponding structure, analyze the network convergence by adjusting hyperparameters such as learning rate and batch size, and save the network model after every 1,000 iterations during the training process, and use the verification set to verify the training effect of the network model. In order to judge the convergence performance of the network model, the terminal positioning error function can be set to quantitatively analyze the positioning accuracy of the network model. Adjust the hyperparameters of the network model by analyzing the training loss function curve of the network model and the accuracy curve of the verification network model. Finally, test the network model with the smallest average positioning error in the actual environment. The network model that meets the test standards is the trained positioning model.

[0102] Step 3: Use the positioning model to locate the terminal online in real time.

[0103] In a cellular mobile communication network, a location management function (LMF) network element entity of a terminal positioning calculation function can be established to be responsible for batch positioning of terminals, such as Figure 2 As shown, the LMF network element entity can be deployed on each base station (of course, it can also be deployed on other feasible communication equipment). In actual applications, the trained positioning model is loaded into each LMF network element entity, and then the LMF network element collects the fingerprint information of each terminal on the corresponding base station side, pre-processes each fingerprint information according to the above pre-processing method, and inputs it into the loaded positioning model. The output is the positioning information of each terminal, thereby realizing batch positioning of the terminal without the terminal being aware of it.

[0104] In actual applications, after determining the positioning information of each terminal accessed by the base station, the terminal distribution within the coverage of the base station can be analyzed based on the positioning information of each terminal, and then the air interface scheduling resources of the base station can be optimized based on the terminal distribution.

[0105] Generally, during the access process between the terminal and the base station, the terminal sends the estimated result of the channel state quality information between the terminal and the base station in the form of CQI through the transmission control channel to the base station, and the base station configures resource blocks for the service channels between the two accordingly. If the base station knows the distribution of terminals under the coverage range, it can roughly know the service request density of the terminals under its coverage range, and then optimize the air interface scheduling resources by reasonably configuring each user resource block. Among them, the reasonable configuration of each user resource block includes reducing the frequency band resource reuse rate of users in hot spots, improving the time slot ratio, adjusting the beam number aligned with the terminal in real time according to the terminal position, adjusting the base station's transmission power for users with the same frequency multiplexing, etc. In this way, the same-frequency interference between users can be avoided or suppressed, and the user's signal-to-noise ratio (Signal Interference Plus Noise Radio, SINR) can be improved, thereby increasing the channel capacity.

[0106] In the embodiment of the present application, the collected raw data of physical layer information and MAC layer scheduling information about multi-terminal positioning are processed to construct a fingerprint database, and the designed deep neural network model is trained offline and fine-tuned online according to the fingerprint database to obtain a positioning model. In the case of no terminal perception, the positioning model is used to achieve batch positioning of terminals. In addition, the terminal positions located in batches can also be used to optimize the air interface scheduling resources of the base station, helping the base station to reasonably avoid or suppress interference during the resource scheduling process.

[0107] The terminal positioning proposed in this application is described below with reference to specific embodiments.

[0108] Figure 3 A flowchart of a terminal positioning method provided in an embodiment of the present application, the method includes the following steps.

[0109] In step 301, fingerprint information of each terminal is obtained every preset time period, and the fingerprint information of each terminal includes CQI information and MAC layer resource scheduling information.

[0110] In some embodiments, fingerprint information of each terminal can be obtained from a base station, and the base station can be a ground base station or an air base station (ie, a satellite). Under the premise of no conflict, the solution of the embodiments of the present application is applicable to both types of base stations.

[0111] Here, fingerprint information required for terminal positioning is actively obtained at preset time periods, and the terminal does not need to send positioning reference information first. This not only allows batch positioning of terminals without the terminals being aware of it, but also saves air interface resources of the base station (sending positioning reference information requires air interface resources).

[0112] In addition, the fingerprint information of each terminal includes both the CQI information of the physical layer and the resource scheduling information of the MAC layer, which is equivalent to combining the information of the physical layer and the MAC layer as the fingerprint information of the terminal. The CQI information and the MAC layer resource scheduling information are naturally generated during the communication process. The wireless modification protocol does not require any additional processing on the terminal side, and the acquisition of fingerprint information is relatively simple. There is no need to send a positioning reference signal before positioning, so batch positioning of terminals can be achieved without the terminal being aware of it, and air interface resources can be saved. The combination of the two layers of information helps the fingerprint information to more completely characterize the terminal's position, and also helps to accelerate the convergence speed of the neural network and improve positioning accuracy.

[0113] In some embodiments, the MAC layer resource scheduling information of each terminal includes any combination of the following information:

[0114] RAR: assigned beam number, time slot, frequency band, power size,

[0115] Scheduling time T,

[0116] Time advance TA,

[0117] Correct transmission confirmation character ACK,

[0118] Terminal identification IMSI,

[0119] The base station number eNB_Id of the base station to which each terminal accesses.

[0120] In step 302, the collection time of the target information that meets the preset conditions in the MAC layer resource scheduling information of each terminal is extended.

[0121] Among them, the preset conditions include that the degree of information change at continuous scheduling moments is greater than a first preset value, and the degree of information correlation at continuous scheduling moments is greater than a second preset value. Among them, the values ​​of the first preset value and the second preset value can be determined by technical personnel based on experience or experiments, and will not be repeated here.

[0122] In practical applications, the fingerprint information of a terminal may contain multiple types of information, and the scheduling time of the base station is at the millisecond level, that is, there will be fingerprint information of a terminal every several milliseconds. This may result in some information in the fingerprint information having large changes at consecutive scheduling moments but strong correlation. In order to reduce the difficulty of data processing of the subsequent positioning model, the collection time of this information can be extended to reduce the correlation of this information between consecutive scheduling moments.

[0123] For example, the target information for which the collection time needs to be extended in the fingerprint information of a terminal includes: RAR: the allocated beam number, time slot, frequency band, power size, and ACK.

[0124] In specific implementation, when the collection time of the target information of each terminal is extended, the target information of this terminal at N historical scheduling moments can be obtained, and then the target information of the N historical scheduling moments is fused into the target information of the terminal at the scheduling moment T, where N is a preset integer, and these N historical scheduling moments are scheduling moments adjacent to the scheduling moment T, so as to ensure the accuracy and rationality of the fusion processing.

[0125] The following is a detailed introduction to the method of extending the collection time.

[0126] It is assumed that the base station has 3 time slots, 3 frequency bands, and 3 beam numbers, and that the collection time is extended by using the data of the terminal at 2 historical scheduling moments before the T scheduling moment.

[0127] Further assume that the RAR and ACK of the terminal at the scheduling time T are:

[0128]

[0129] The RAR and ACK at the T-1 scheduling time are:

[0130]

[0131] The RAR and ACK at the T-2 scheduling time are:

[0132]

[0133] Then, if the data of the three scheduling times are fused according to the maximum probability generation rule (i.e., if 1 appears the most times in the three scheduling times, then it is 1, and if 0 appears the most times in the three scheduling times, then it is 0), then the RAR and ACK at the T scheduling time after fusion are:

[0134]

[0135] In this way, the correlation between target information within continuous scheduling moments can be reduced by extending the acquisition time, making the target information more accurate, thereby improving the accuracy of the final positioning.

[0136] In step 303, the fingerprint information of each terminal is input into the positioning model to obtain the positioning information of each terminal. The positioning model is obtained by learning in advance the relationship between the fingerprint information and the positioning information of each test terminal within the coverage of the corresponding base station.

[0137] The corresponding base station refers to the base station to which each terminal accesses, that is, the base station that provides communication services for each terminal.

[0138] In actual applications, the fingerprint information of each terminal is input into the positioning model in sequence to obtain the positioning information of the corresponding terminal. The training process of the positioning model has been introduced in detail above and will not be repeated here.

[0139] In step 304, based on the positioning information of each terminal, the distribution of terminals within the coverage of the base station is determined.

[0140] In step 305, based on the terminal distribution, the air interface scheduling resources of the base station are optimized.

[0141] Generally, during the access process between the terminal and the base station, the terminal sends the estimated result of the channel state quality information between the terminal and the base station in the form of CQI through the transmission control channel to the base station, and the base station configures resource blocks for the service channels between the two accordingly. If the base station knows the distribution of terminals under the coverage range, it can roughly know the service request density of the terminals under its coverage range, and then optimize the air interface scheduling resources by reasonably configuring each user resource block. Among them, the reasonable configuration of each user resource block includes reducing the frequency band resource reuse rate of users in hot spots, improving the time slot ratio, adjusting the beam number aligned with the terminal in real time according to the terminal position, adjusting the base station's transmission power for users with the same frequency multiplexing, etc. In this way, the same-frequency interference between users can be avoided or suppressed, the SINR of users can be improved, and the channel capacity can be increased.

[0142] In the embodiment of the present application, the combination of MAC layer resource scheduling information and physical layer CQI information is used as position fingerprint positioning information, and the terminal does not need to send a positioning reference signal specifically, so batch terminal positioning is achieved without the terminal being aware of it. In addition, the terminal positions located in batches can also be used to help the base station avoid or suppress interference in the subsequent MAC layer resource scheduling process, thereby better allocating resources to the terminal and improving the throughput of the communication system.

[0143] Based on the same technical concept, the embodiment of the present application also provides a terminal positioning device. The principle of solving the problem by the terminal positioning device is similar to that of the above-mentioned terminal positioning method. Therefore, the implementation of the terminal positioning device can refer to the implementation of the terminal positioning method, and the repeated parts will not be repeated.

[0144] Figure 4 A schematic diagram of the structure of a terminal positioning device provided in an embodiment of the present application includes an acquisition module 401 and a positioning module 402.

[0145] The acquisition module 401 is used to acquire fingerprint information of each terminal at every preset time period, where the fingerprint information of each terminal includes channel quality indication information and medium access control MAC layer resource scheduling information;

[0146] The positioning module 402 is used to input the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal. The positioning model is obtained by learning the relationship between the fingerprint information and the positioning information of each test terminal within the coverage of the corresponding base station in advance.

[0147] In some embodiments, the MAC layer resource scheduling information of each terminal includes any combination of the following information:

[0148] The assigned beam number, time slot, frequency band, and power level,

[0149] Scheduling time,

[0150] Time advance,

[0151] Correct transmission of confirmation characters,

[0152] Terminal identification,

[0153] The base station number of the base station.

[0154] In some embodiments, a pre-processing module 403 is further included for:

[0155] Before inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the collection time of the target information that meets the preset conditions in the MAC layer resource scheduling information of each terminal is extended, and the preset conditions include that the degree of information change at continuous scheduling moments is greater than a first preset value, and the degree of information correlation at continuous scheduling moments is greater than a second preset value.

[0156] In some embodiments, the preprocessing module 403 is specifically used to:

[0157] Obtain target information of each terminal at N historical scheduling moments, where N is a preset integer;

[0158] The target information of the N historical scheduling moments is integrated into the target information of the terminal at the scheduling moment.

[0159] In some embodiments, an optimization module 404 is further included for:

[0160] After inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the distribution of the terminals within the coverage area of ​​the base station is determined based on the positioning information of each terminal;

[0161] Based on the terminal distribution, the air interface scheduling resources of the base station are optimized.

[0162] The division of modules in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, the functional modules in the embodiments of the present application may be integrated in a processor, or may exist physically separately, or two or more modules may be integrated in one module. The coupling between the modules may be achieved through some interfaces, which are usually electrical communication interfaces, but it is not excluded that they may be mechanical interfaces or other forms of interfaces. Therefore, the modules described as separate components may or may not be physically separated, and may be located in one place or distributed to different locations of the same or different devices. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0163] After introducing the terminal positioning method and device according to the exemplary embodiment of the present application, next, an electronic device according to another exemplary embodiment of the present application is introduced.

[0164] Refer to the following Figure 5 The electronic device 130 implemented according to this embodiment of the present application is described. Figure 5 The electronic device 130 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0165] like Figure 5 As shown, the electronic device 130 is in the form of a general electronic device. The components of the electronic device 130 may include but are not limited to: the at least one processor 131, the at least one memory 132, and a bus 133 connecting different system components (including the memory 132 and the processor 131).

[0166] Bus 133 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a processor, or a local bus using any of a variety of bus architectures.

[0167] The memory 132 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 1321 and / or a cache memory 1322 , and may further include a read-only memory (ROM) 1323 .

[0168] The memory 132 may also include a program / utility 1325 having a set (at least one) of program modules 1324, such program modules 1324 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0169] The electronic device 130 may also communicate with one or more external devices 134 (e.g., keyboards, pointing devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 130, and / or communicate with any device that enables the electronic device 130 to communicate with one or more other electronic devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 135. Furthermore, the electronic device 130 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 136. As shown, the network adapter 136 communicates with other modules for the electronic device 130 via a bus 133. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 130, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0170] In an exemplary embodiment, a storage medium is also provided, and when a computer program in the storage medium is executed by a processor of an electronic device, the electronic device can perform the above-mentioned terminal positioning method. Optionally, the storage medium can be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0171] In an exemplary embodiment, the electronic device of the present application may include at least one processor and a memory communicatively connected to the at least one processor, wherein the memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor may execute the steps of any terminal positioning method provided in the embodiments of the present application.

[0172] In an exemplary embodiment, a computer program product is also provided. When the computer program product is executed by an electronic device, the electronic device can implement any exemplary method provided in the present application.

[0173] Furthermore, the computer program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a compact disk read only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0174] The program product for terminal positioning in the embodiment of the present application may adopt a CD-ROM and include program code, and may be run on a computing device. However, the program product of the present application is not limited thereto, and in this document, a readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus, or device.

[0175] The readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, wherein the readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0176] The program code contained on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, radio frequency (RF), etc., or any suitable combination of the foregoing.

[0177] Program code for performing the operations of the present application may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device via any type of network such as a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0178] It should be noted that, although several units or subunits of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided into multiple units to be embodied.

[0179] In addition, although the operations of the method of the present application are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0180] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0181] The present application is described with reference to the flowcharts and / or block diagrams of the methods, apparatus (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0182] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0183] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0184] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0185] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application also includes these modifications and variations.

Claims

1. A terminal positioning method, characterized in that: include: At every preset time period, fingerprint information of each terminal is obtained, where the fingerprint information of each terminal includes channel quality indication information and medium access control MAC layer resource scheduling information; The fingerprint information of each terminal is input into the positioning model to obtain the positioning information of each terminal. The positioning model is obtained by learning in advance the relationship between the fingerprint information and the positioning information of each test terminal within the coverage range of the corresponding base station.

2. The method according to claim 1, characterized in that The MAC layer resource scheduling information of each terminal includes any combination of the following information: The assigned beam number, time slot, frequency band, and power level, Scheduling time, Time advance, Correct transmission of confirmation characters, Terminal identification, The base station number of the base station.

3. The method according to claim 1 or 2, characterized in that Before inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the following steps are also included: The collection time of target information that meets preset conditions in the MAC layer resource scheduling information of each terminal is extended, and the preset conditions include that the degree of information change at consecutive scheduling moments is greater than a first preset value, and the degree of information correlation at consecutive scheduling moments is greater than a second preset value.

4. The method according to claim 3, characterized in that The collection time of target information that meets preset conditions in the MAC layer resource scheduling information of each terminal is extended, including: Obtain target information of each terminal at N historical scheduling moments, where N is a preset integer; The target information of the N historical scheduling moments is integrated into the target information of the terminal at the scheduling moment.

5. The method according to claim 1, characterized in that After the fingerprint information of each terminal is input into the positioning model to obtain the positioning information of each terminal, the following steps are also included: Determine the distribution of terminals within the coverage area of ​​the base station based on the positioning information of each terminal; Based on the terminal distribution, the air interface scheduling resources of the base station are optimized.

6. A terminal positioning device, characterized in that: include: An acquisition module, used to acquire fingerprint information of each terminal at every preset time period, where the fingerprint information of each terminal includes channel quality indication information and media access control MAC layer resource scheduling information; The positioning module is used to input the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal. The positioning model is obtained by learning the relationship between the fingerprint information and the positioning information of each test terminal within the coverage range of the corresponding base station in advance.

7. The device according to claim 6, characterized in that The MAC layer resource scheduling information of each terminal includes any combination of the following information: The assigned beam number, time slot, frequency band, and power level, Scheduling time, Time advance, Correct transmission of confirmation characters, Terminal identification, The base station number of the base station.

8. The device according to claim 6 or 7, characterized in that Also includes preprocessing modules for: Before inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the collection time of the target information that meets the preset conditions in the MAC layer resource scheduling information of each terminal is extended, and the preset conditions include that the degree of information change at continuous scheduling moments is greater than a first preset value, and the degree of information correlation at continuous scheduling moments is greater than a second preset value.

9. The device according to claim 8, characterized in that The preprocessing module is specifically used for: Obtain target information of each terminal at N historical scheduling moments, where N is a preset integer; The target information of the N historical scheduling moments is integrated into the target information of the terminal at the scheduling moment.

10. The device according to claim 6, characterized in that Also includes optimization modules for: After inputting the fingerprint information of each terminal into the positioning model to obtain the positioning information of each terminal, the distribution of the terminals within the coverage area of ​​the base station is determined based on the positioning information of each terminal; Based on the terminal distribution, the air interface scheduling resources of the base station are optimized.

11. An electronic device, characterized in that: include: at least one processor, and a memory communicatively connected to the at least one processor, wherein: The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the method according to any one of claims 1 to 5.

12. A storage medium, characterized in that: When the computer program in the storage medium is executed by a processor of an electronic device, the electronic device can execute the method according to any one of claims 1 to 5.

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