Channel modeling method, device, equipment, storage medium and program product

Abstract

The present disclosure provides a channel modeling method, device, equipment, storage medium and program product, which relate to the field of communication technology. The method includes: based on the first channel characteristic, calibrating the initial antenna parameters of the communication node to obtain the calibrated first antenna parameters; the first channel characteristic is determined by the communication node's detection data of the wireless channel; using the first antenna parameters to perform ray tracing to establish a channel model of the wireless channel. The method is applicable to the process of establishing a channel model, and is used to solve the problem that the channel model established by the ray tracing method is not accurate enough.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a channel modeling method, device, equipment, storage medium and program product. Background Art

[0002] As wireless communication systems become increasingly complex and sophisticated, wireless channel modeling technology has also changed from the traditional model method based on the average of a large amount of measurement data to a scenario-based modeling method based on a specific outer diameter, in order to provide a specific channel model that better matches the actual specific scenario.

[0003] For example, a ray tracing method is currently used in wireless channel modeling technology to establish a channel model. The ray tracing method is generally divided into two steps: scene construction and ray propagation. Scene construction first establishes a spatial scene model, including buildings and terrain. Ray propagation can emit rays according to certain rules and simulate the propagation and reflection paths of rays in the constructed spatial scene model based on the antenna parameters of the base station. Once the ray reaches the target receiver, the channel characteristics can be calculated to establish a channel model of the wireless channel.

[0004] However, the channel model established by the ray tracing method has errors and is not accurate enough. Summary of the invention

[0005] The present disclosure provides a channel modeling method, apparatus, device, storage medium and program product, which can calibrate antenna engineering parameters based on a first channel characteristic determined based on actual detection data of a wireless channel, thereby improving the accuracy of a channel model established by a ray tracing method.

[0006] In a first aspect, the present disclosure provides a channel modeling method, the method comprising:

[0007] Based on the first channel characteristics, calibrate the initial antenna working parameters of the communication node to obtain the calibrated first antenna working parameters; wherein the first channel characteristics are determined by the communication node based on the detection data of the wireless channel;

[0008] The first antenna engineering parameters are used to perform ray tracing and establish a channel model of the wireless channel.

[0009] It should be understood that in the process of establishing a channel model using the ray tracing method, the antenna parameters of the base station need to be used for ray tracing. However, due to factors such as errors during installation, it is difficult to obtain accurate antenna parameters of the on-site base station (i.e., the working parameters of the antenna, which are used to describe the working state of the antenna, and the antenna parameters may include, for example, the azimuth angle and downtilt angle, etc.) during ray tracing. Therefore, the channel model obtained by ray tracing has errors and is not accurate enough.

[0010] The channel modeling method provided by the present disclosure can calibrate the initial antenna parameters of the communication node based on the first channel characteristics to obtain the calibrated first antenna parameters, and the first channel characteristics are determined by the communication node based on the detection data of the wireless channel. That is, the present disclosure can calibrate the antenna parameters using the first channel characteristics determined by the actual detection data of the wireless channel. Ray tracing using the calibrated first antenna parameters can reduce errors and establish a more accurate channel model.

[0011] In a second aspect, the present disclosure provides a channel modeling device, the device comprising: a processing unit;

[0012] A processing unit is used to calibrate the initial antenna working parameters of the communication node based on the first channel characteristics to obtain the calibrated first antenna working parameters; wherein the first channel characteristics are determined by the communication node based on the detection data of the wireless channel; and use the first antenna working parameters to perform ray tracing to establish a channel model of the wireless channel.

[0013] In a third aspect, the present disclosure provides an electronic device, including: a processor and a memory;

[0014] The memory stores instructions executable by the processor;

[0015] When the processor is configured to execute the instructions, the electronic device implements the method as described in the first aspect above.

[0016] In a fourth aspect, the present disclosure provides a readable storage medium, including: software instructions;

[0017] When the software instructions are executed in the electronic device, the electronic device implements the method as described in the first aspect above.

[0018] In a fifth aspect, the present disclosure provides a computer program product, which includes computer instructions. When the computer instructions are executed in an electronic device, the electronic device implements the method described in the first aspect above.

[0019] The beneficial effects of the second to fifth aspects above can be referred to the first aspect and will not be elaborated on again. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the technical solution of the present invention and do not constitute a limitation on the technical solution of the present invention.

[0021] Figure 1 A schematic diagram of the composition of a channel modeling system provided by an embodiment of the present disclosure;

[0022] Figure 2A schematic diagram of a flow chart of a channel modeling method provided in an embodiment of the present disclosure;

[0023] Figure 3 A schematic diagram of the composition of a channel modeling device provided in an embodiment of the present disclosure;

[0024] Figure 4 A schematic diagram of another channel modeling device provided in an embodiment of the present disclosure;

[0025] Figure 5 A schematic diagram of the composition of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0027] Unless the context requires otherwise, throughout the specification and claims, the term "comprise" and other forms such as the third person singular form "comprises" and the present participle form "comprising" are to be interpreted as open, inclusive, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "example", "specific example" or "some examples" are intended to indicate that specific features, structures, materials or characteristics related to the embodiment or example are included in at least one embodiment or example of the present disclosure. The schematic representation of the above terms does not necessarily refer to the same embodiment or example. In addition, the specific features, structures, materials or characteristics may be included in any one or more embodiments or examples in any appropriate manner.

[0028] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present disclosure, unless otherwise specified, "plurality" means two or more.

[0029] In the embodiments of the present disclosure, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present disclosure should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0030] Additionally, the use of “based on” is meant to be open and inclusive, as a process, step, calculation, or other action “based on” one or more stated conditions or values ​​may, in practice, be based on additional conditions or values ​​beyond those stated.

[0031] As wireless communication systems become increasingly complex and sophisticated, wireless channel modeling technology has also changed from the traditional model method based on the average of a large amount of measurement data to a scenario-based modeling method based on a specific outer diameter, in order to provide a specific channel model that better matches the actual specific scenario.

[0032] For example, the current wireless channel modeling technology mainly provides the following three methods to establish a channel model:

[0033] 1. Ray tracing method.

[0034] The ray tracing method mainly evaluates the performance and characteristics of wireless channels by mathematically simulating the propagation and reflection paths of rays in space and performing simulations on computers. This method is widely used in the design and optimization of wireless communication systems and is generally divided into the following two steps:

[0035] 1.1) Scene construction: First, we build a spatial scene model, including buildings and terrain, which will affect the propagation and reflection of wireless signals. The ray tracing method simulates the transmission process of wireless signals in actual scenes by modeling these objects in three dimensions, determining their positions, shapes, and surface materials.

[0036] 1.2) Ray propagation. Next, the ray tracing method can emit rays according to certain rules, and simulate the propagation and reflection path of rays in the constructed space scene model according to the antenna parameters of the base station (that is, the working parameters of the antenna, which are used to describe the working status of the antenna. The antenna parameters may include, for example, the azimuth angle and downtilt angle, etc.), and then record all the points passed by the current ray propagation path, and calculate the reflection angle and reflection direction of the ray when encountering an object. Once the ray reaches the target receiver, the channel characteristics can be calculated to establish the channel model of the wireless channel.

[0037] The advantages of the ray tracing method are: simple, low cost, no need to deploy additional measurement equipment once the on-site digital map and pictures are obtained, and the channel model of the wireless channel can be established without a network. However, the channel model established by the ray tracing method has errors and is not accurate enough.

[0038] 2. Wireless channel detection method.

[0039] The wireless channel detection method is a method of deploying a special wireless channel detector and using multiple antennas and transmitting and receiving circuits to measure the propagation characteristics of signals in space (including channel response, channel loss, and transmission time delay, etc.). This method generally includes the following steps:

[0040] 2.1) Deployment of detectors: First, multiple Sounder detectors need to be deployed in the target area. These Sounder detectors need to be connected to each other through a wireless network to collect data.

[0041] 2.2) Collect data. Once deployed, each Sounder detector will automatically measure the wireless channel and upload the measurement data to the central server. These measurement data may include received signal strength indicator (RSSI) and round-trip time (RTT).

[0042] 2.3) Processing data, after storing the measured data on the central server, it is necessary to process and analyze the measured data, including denoising, channel parameter estimation, and propagation path analysis.

[0043] 2.4),Modeling,Finally, based on the analysis results, a channel model is established to predict future channel performance.

[0044] Wireless channel detection can be used to optimize wireless network design and improve network performance and efficiency. The advantage of this method is that it has high accuracy, but its disadvantage is that it requires the deployment of specialized equipment, which is expensive and takes a long time to measure.

[0045] 3. Wireless network online channel records.

[0046] This method uses wireless network equipment that has been deployed and running. During the communication process, base stations or terminals and other equipment will estimate the wireless channel for receiving data. Therefore, the estimated results will be recorded, and data processing and extraction will be performed to obtain the detection data of the wireless channel, from which the delay, power, horizontal and vertical arrival angles and other information of the wireless channel can be estimated.

[0047] The advantage of this method is that it does not require the deployment of expensive specialized equipment and can achieve relatively high accuracy. However, this method has high requirements for base station bandwidth, number of antennas and spacing, and the established channel model has errors and is not accurate enough.

[0048] Based on this, the embodiments of the present disclosure provide a channel modeling method, apparatus, equipment, storage medium and program product, which can calibrate antenna engineering parameters based on the first channel characteristics determined based on the actual detection data of the wireless channel, thereby improving the accuracy of the channel model established by the ray tracing method.

[0049] The following is an introduction with reference to the accompanying drawings.

[0050] Figure 1 The schematic diagram of the composition of the channel modeling system provided by the embodiment of the present disclosure. As shown in FIG1 , the system includes: at least one communication node 100 ( Figure 1 A base station is shown as an example in the figure) and a channel model modeling device 200.

[0051] The communication node 100 may be a node with a communication function in a wireless network. For example, the communication node 100 may be a base station in a wireless network.

[0052] In which, taking the communication node 100 as a base station as an example, the communication node 100 may be a base station (BS), a base transceiver station (BTS), a 3G base station (NodeB), a 4G base station (evolved NodeB, eNB), a 5G base station (next generation NodeB, gNB), etc. The embodiments of the present disclosure do not limit the specific type of the communication node 100.

[0053] The communication node 100 can be used to estimate the wireless channel, and process and extract the estimation result to obtain the detection data of the wireless channel.

[0054] In some embodiments, the communication node 100 may also be configured to record or store detection data of the wireless channel.

[0055] For example, the communication node 100 may have a built-in recording system or log function, and the communication node 100 may record or store the detection data of the wireless channel through the built-in recording system or log function.

[0056] In other embodiments, the communication node 100 may send the detection data of the wireless channel to other devices, and the other devices may record or store the detection data.

[0057] The channel modeling apparatus 200 may be an electronic device having a computing and processing function, such as a server or a computer.

[0058] Among them, the server can be a single server, or it can be a server cluster composed of multiple servers. In some implementations, the server cluster can also be a distributed cluster. Optionally, the server can also be implemented on a cloud platform. For example, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, and a multi-cloud, etc., or any combination thereof. The embodiments of the present disclosure are not limited to this.

[0059] The channel modeling device 200 can be used to calibrate the antenna parameters of the communication node 100 according to the detection data of the wireless channel obtained by the communication node 100, and then use the calibrated antenna parameters to perform ray tracing to establish a channel model of the wireless channel. The specific process can be referred to in the channel modeling method provided in the following method embodiment, which will not be repeated here.

[0060] In some embodiments, as described above, the detection data of the wireless channel may be stored in the communication node 100. In this case, the channel modeling apparatus 200 may obtain the detection data of the wireless channel from the communication node 100.

[0061] For example, the channel modeling apparatus 200 may request the communication node 100 to obtain the detection data of the wireless channel, or the communication node 100 may be configured to send the detection data of the wireless channel to the channel modeling apparatus 200 according to a preset period, etc. The embodiments of the present disclosure are not limited to this.

[0062] In other embodiments, as described above, the detection data of the wireless channel may be stored in other devices. In this case, the channel modeling apparatus 200 may obtain the detection data of the wireless channel from other devices.

[0063] It should be noted that the above description is based on the example that the communication node 100 and the channel model modeling device 200 are independent devices. Optionally, the communication node 100 and the channel model modeling device 200 can also be integrated into one. That is, the communication node 100 or its corresponding function, and the channel model modeling device 200 or its corresponding function can be integrated into one device. For example, a base station with a channel model modeling function. The embodiments of the present disclosure are not limited to this.

[0064] The execution subject of the channel model modeling method provided in the embodiment of the present disclosure is a channel model modeling device (such as the above-mentioned channel model modeling device 200). As mentioned above, the channel model modeling device can be an electronic device with computing and processing functions such as a server or a computer. Optionally, the channel model modeling device can also be a processor (such as a central processing unit (CPU)) in the aforementioned electronic device; or, the channel model modeling device can also be an application (application) with a channel model modeling function installed in the aforementioned electronic device; or, the channel model modeling device can also be a software system or platform in the aforementioned electronic device; or, the channel model modeling device can also be a functional module or functional unit in the aforementioned electronic device for executing the channel model modeling method. The embodiment of the present disclosure does not limit this.

[0065] For simplicity of description, the channel modeling method provided in the embodiments of the present disclosure is uniformly introduced below by taking the execution subject of the channel modeling method provided in the embodiments of the present disclosure as a channel modeling device as an example.

[0066] Figure 2 The following is a flow chart of the channel modeling method provided by the embodiment of the present disclosure. Figure 2 As shown, the method includes the following steps:

[0067] S101. Calibrate initial antenna working parameters of a communication node based on first channel characteristics to obtain calibrated first antenna working parameters.

[0068] The first channel feature is determined by the communication node based on the detection data of the wireless channel. The specific acquisition process of the communication node for the detection data of the wireless channel can refer to the above Figure 1 The channel modeling device 200 is described in detail and will not be described again. The first channel feature may be a set of multipath components, including path component features corresponding to each signal transmission path in the plurality of signal transmission paths. The initial antenna engineering parameters may include an azimuth angle and a downtilt angle (of the antenna).

[0069] For example, the first channel feature can be expressed as ,include The path component characteristics of the signal transmission paths, each signal transmission path (or the The path component characteristics corresponding to the signal transmission paths can be recorded as .in, Indicates that in the first channel feature, The power of the signal transmission path. Indicates that in the first channel feature, The delay of the signal transmission path. Indicates that in the first channel feature, The azimuth angle (or horizontal angle of arrival) of the signal transmission path. Indicates that in the first channel feature, The elevation angle (or vertical angle of arrival) of a signal transmission path.

[0070] As an example, the channel modeling device can use the initial antenna engineering parameters to perform ray tracing to obtain the second channel characteristics, and then calibrate the initial antenna engineering parameters based on the comparison between the first channel characteristics and the second channel characteristics. The specific process can be referred to in the following embodiments and will not be repeated here.

[0071] The second channel characteristic may also be a set of multipath components, including path component characteristics corresponding to each signal transmission path in multiple signal transmission paths.

[0072] For example, the second channel characteristic can be expressed as ,include The path component characteristics of the signal transmission paths, each signal transmission path (or the The path component characteristics corresponding to the signal transmission paths can be recorded as .in, Indicates that in the second channel feature, The power of the signal transmission path. Indicates that in the second channel feature, The delay of the signal transmission path. Indicates that in the second channel feature, The azimuth angle (or horizontal angle of arrival) of the signal transmission path. Indicates that in the second channel feature, The elevation angle (or vertical angle of arrival) of a signal transmission path.

[0073] S102: Perform ray tracing using the first antenna engineering parameters to establish a channel model of the wireless channel.

[0074] For example, the channel modeling device can obtain a three-dimensional (3D) map of the corresponding network area, input the coordinates of the transmitter and the receiver, use the first antenna engineering parameters as the antenna engineering parameters of the receiver, input the ray tracing model, and generate the channel model. The specific process of generating the channel model can refer to the relevant technology and will not be repeated here.

[0075] It should be understood that the process of establishing a channel model using the ray tracing method requires the use of the antenna parameters of the base station for ray tracing. However, due to factors such as errors during installation, it is difficult to obtain accurate antenna parameters (such as azimuth angle and downtilt angle) of the on-site base station during ray tracing. Therefore, the channel model obtained by ray tracing has errors and is not accurate enough.

[0076] In the channel modeling method provided by the embodiment of the present disclosure, the channel modeling device can calibrate the initial antenna parameters of the communication node based on the first channel characteristics to obtain the calibrated first antenna parameters, and the first channel characteristics are determined by the communication node's detection data of the wireless channel. That is, the present disclosure can calibrate the antenna parameters using the first channel characteristics determined by the actual detection data of the wireless channel. Ray tracing using the calibrated first antenna parameters can reduce errors and establish a more accurate channel model.

[0077] In some embodiments, before the above S101, the channel model building device may also obtain a first channel feature.

[0078] For example, taking the communication node as a 5G base station, the channel measurement module in the 5G base station can receive a sounding reference signal (SRS) through a receiver, and then use the least squares algorithm to obtain an estimated value H(t) of the current channel, and collect H(t) within 120 milliseconds. The channel modeling device can estimate the aforementioned H(t) through the estimation of signal parameters via rotational invariance techniques (ESPRIT) spectrum estimation algorithm to obtain the first channel feature.

[0079] For example, taking the communication node as a 4G base station, the channel measurement module in 4G can receive the SRS through the receiver, and then use the minimum mean square error (MMSE) algorithm to obtain the estimated value H(t) of the current channel, and collect H(t) within 240 milliseconds, and estimate the aforementioned H(t) through the ESPRIT spectrum estimation algorithm to obtain the first channel feature.

[0080] The specific process of the above S101 is introduced below.

[0081] In some possible embodiments, the channel modeling device may calibrate the initial antenna parameters in combination with the second channel characteristics. In this case, the above S101 may specifically include the following steps:

[0082] Step 1a: Determine the antenna engineering parameter deviation value based on the first channel characteristic and the second channel characteristic.

[0083] The second channel characteristics are determined after ray tracing based on the initial antenna engineering parameters.

[0084] As an example, the antenna engineering parameter deviation value may include an azimuth angle deviation value and a downtilt angle deviation value.

[0085] As an example, as described above, the first channel characteristic and the second channel characteristic may both include path component characteristics corresponding to each of the multiple signal transmission paths, and the azimuth deviation value may specifically be the average value of the deviations between the azimuths of the multiple signal transmission paths in the first channel characteristic and the azimuths in the second channel characteristic.

[0086] For example, the channel modeling device may specifically calculate the azimuth deviation value by the following formula:

[0087] Formula (1);

[0088] In formula (1), Indicates the azimuth deviation value. It can be understood that the above and The minimum value in .

[0089] As an example, the downtilt angle deviation value may be specifically an average value of deviations between the pitch angles of multiple signal transmission paths in the first channel characteristics and the pitch angles in the second channel characteristics.

[0090] For example, the channel modeling device may specifically calculate the downtilt angle deviation value by the following formula:

[0091] Formula (2);

[0092] In formula (2), Indicates the downtilt angle difference.

[0093] Step 2a: Based on the antenna engineering parameter deviation value, calibrate the initial antenna engineering parameters to obtain calibrated first antenna engineering parameters.

[0094] For example, as described above, the antenna engineering parameter deviation value may include an azimuth deviation value and a downtilt deviation value. In this case, the above step 2a may specifically include:

[0095] Step 2.1a, the channel model modeling device can use the azimuth deviation as the adjustment value of the azimuth angle in the initial antenna engineering parameters, and use the downtilt angle deviation value as the adjustment value of the downtilt angle in the initial antenna engineering parameters, calibrate the initial antenna engineering parameters, and obtain the calibrated first antenna engineering parameters.

[0096] For example, the azimuth angle in the initial antenna parameters is , the downward inclination angle is For example, the channel modeling device can add the azimuth angle to the azimuth angle deviation value, and add the downtilt angle to the downtilt angle deviation value, so as to obtain the calibrated first antenna engineering parameters. + , + .

[0097] In a possible implementation, the channel model building device may directly use the above adjustment values ​​to adjust the initial antenna engineering parameters.

[0098] In another possible implementation, the channel modeling device may calculate the calibration confidence and use the above adjustment value to make adjustments only when the calibration confidence is high. In this case, the above step 2.1a may specifically include:

[0099] Step 2.1.1a, determine the calibration confidence based on the deviation between the azimuth angles of multiple signal transmission paths in the first channel characteristics and the azimuth angles in the second channel characteristics, and the deviation between the elevation angles of multiple signal transmission paths in the first channel characteristics and the elevation angles in the second channel characteristics.

[0100] For example, the channel model modeling device can determine the calibration confidence based on the variance of the deviation between the azimuth angle of multiple signal transmission paths in the first channel characteristic and the azimuth angle in the second channel characteristic (for example, which can be called the first variance), and the variance of the deviation between the elevation angle of multiple signal transmission paths in the first channel characteristic and the elevation angle in the second channel characteristic (for example, which can be called the second variance).

[0101] As an example, the calibration confidence may include a first confidence and a second confidence. The channel modeling apparatus may specifically determine the first confidence according to the first variance, and determine the second confidence according to the second variance.

[0102] There is a negative correlation between the first variance and the first confidence level, and there is a negative correlation between the second variance and the second confidence level.

[0103] As another example, the channel modeling device may also perform a weighted summation on the first variance and the second variance to obtain a calibration confidence.

[0104] It should be noted that, the larger the first variance and the second variance are, the smaller the calibration confidence is, and the smaller the first variance and the second variance are, the larger the calibration confidence is.

[0105] Step 2.1.2a. When the calibration confidence is greater than the confidence threshold, the azimuth angle deviation value is used as the adjustment value of the azimuth angle in the initial antenna engineering parameters, and the downtilt angle deviation value is used as the adjustment value of the downtilt angle in the initial antenna engineering parameters. The initial antenna engineering parameters are calibrated to obtain the calibrated first antenna engineering parameters.

[0106] It should be understood that when the deviation between the azimuth angle in the first channel characteristic and the azimuth angle in the second channel characteristic, as well as the deviation between the elevation angle in the first channel characteristic and the elevation angle in the second channel characteristic are large, it indicates that the first channel characteristic and the second channel characteristic are greatly different, and the antenna engineering parameter deviation value determined at this time may also have a large error.

[0107] In the channel model modeling method provided by the embodiment of the present disclosure, the channel model modeling device can calculate the calibration confidence based on the deviation between the azimuth angle in the first channel feature and the azimuth angle in the second channel feature, and the deviation between the elevation angle in the first channel feature and the elevation angle in the second channel feature, and only when the calibration confidence is greater than the confidence threshold, the initial antenna engineering parameters are calibrated with the antenna engineering parameter deviation value, thereby avoiding the use of antenna engineering parameter deviation values ​​that may have large errors to calibrate the initial antenna engineering parameters, avoiding error propagation, and thus improving the accuracy of the calibrated first antenna engineering parameters.

[0108] In some other possible embodiments, before using the first channel characteristics to calibrate the initial antenna parameters, the channel model building device may also first calibrate the first channel characteristics. In this case, the above S101 may specifically include the following steps:

[0109] Step 1b, perform the first channel characteristic calibration step: use the second channel characteristic to calibrate the first channel characteristic to obtain the calibrated first channel characteristic.

[0110] The second channel characteristics are determined after ray tracing based on the initial antenna engineering parameters.

[0111] In a possible implementation, the above step 1b may specifically include the following steps:

[0112] Step 1.1b: Based on the path component characteristics corresponding to each signal transmission path in the first channel characteristics, determine the angle candidate domain corresponding to each signal transmission path.

[0113] The angle candidate domain includes a plurality of candidate angle features, and the candidate angle feature is an angle feature within a preset angle range, and the correlation parameter between the angle feature in the path component feature of the signal transmission path in the first channel feature is greater than the correlation threshold. For example, the preset angle range can be specifically: an azimuth angle interval of [-180°, 180°], and an elevation angle interval of [-90°, 90°].

[0114] As an example, taking any one first path among the multiple signal transmission paths as an example (that is, for any one first path among the multiple signal transmission paths), the above step 1.1b may specifically include the following steps:

[0115] Step 1.1.1b: Determine the spatial characteristic vector of the first path according to the angular characteristic of the first path in the first channel characteristic.

[0116] For example, the spatial feature vector can be specifically expressed as the following formula:

[0117] Formula (3);

[0118] In formula (3), Represents the spatial feature vector. Indicates the number of horizontal arrays in the communication node antenna array. Indicates the number of vertical arrays in the communication node antenna array. Indicates the array spacing in the horizontal direction. Indicates the array spacing in the vertical direction. represents the wavelength. The spatial characteristic vector includes × OK, go ahead In the line, The coefficient of the term is 0, The coefficient of the term increases from 0 to 1 row by row until it reaches . No. +1 line starts to 2 OK, The coefficient of the term increases from 0 to 1, then The coefficient of the term increases from 0 to 1 row by row until it reaches . 2nd +1 line starts to 3 OK, The coefficient of the term increases from 1 to 2, then The coefficient of the term increases from 0 to 1 row by row until it reaches And so on, until the last line The coefficient increases to , The coefficient increases to .

[0119] Step 1.1.2b: Scan within a preset angle range to obtain multiple initial angle features.

[0120] Step 1.1.3b: Based on multiple initial angle features, determine the spatial feature vector corresponding to each initial angle feature.

[0121] The spatial feature vector corresponding to each initial angle feature can be calculated by referring to the above formula (3), which will not be described in detail.

[0122] Step 1.1.4b, based on the spatial feature vector of the first path, the spatial feature vector corresponding to each initial angle feature, and the angle correlation function, determine the correlation parameter between each initial angle feature and the angle feature of the first path in the first channel feature.

[0123] For example, the channel modeling device may specifically calculate the correlation parameter according to the angle correlation function shown in the following formula (4):

[0124] Formula (4);

[0125] In formula (4), Represents the azimuth and elevation angles in one angular feature. Represents the azimuth and elevation angles from another angular feature. Represents the angle correlation function, which can also be understood as the above correlation parameter. Represents the dot product operation. Represents a norm operation.

[0126] Step 1.1.5b: Take the initial angle feature whose correlation parameter is greater than the correlation threshold as the candidate angle feature, and obtain the angle candidate domain corresponding to the first path.

[0127] Step 1.2b, select the target angle feature that is closest to the reference angle feature corresponding to each signal transmission path from the angle candidate domain corresponding to each signal transmission path, and calibrate the angle feature in the path component feature corresponding to each signal transmission path in the first channel feature.

[0128] The reference angle feature is an angle feature of a path component feature of a corresponding signal transmission path in the second channel feature.

[0129] Exemplarily, the channel modeling device may select the target angle feature to calibrate the first channel feature according to the following formula:

[0130] Formula (5);

[0131] In formula (5), the left side of the equal sign is It can be understood as the target angle feature, or the first target feature after calibration.

[0132] It should be understood that the method of modeling online channel records through wireless networks in related technologies usually involves scanning to determine the angle candidate domain, and then selecting angle features from the angle candidate domain to obtain the first channel feature. However, in the current commercial network, the horizontal antenna spacing and the vertical spacing used in the mainstream 5G frequency bands of 2.6GHz and 3.5GHz are greater than 0.5 half wavelengths, so there may be "false side lobes" in the angle candidate domain. The angle features selected from the angle candidate domain constitute the first channel feature, which may cause the first channel feature to have "false side lobes".

[0133] In the channel modeling method provided by the embodiment of the present disclosure, the channel modeling device can restore the angle candidate domain corresponding to each signal transmission path, and then select the angle feature corresponding to the path component feature in the second channel feature from the angle candidate domain to calibrate the first channel feature. Since the second channel feature is determined based on ray tracing simulation and does not have a "false side lobe", the target angle feature selected from the second channel feature also does not have a "false side lobe". Using the target angle feature to calibrate the first channel feature can eliminate the "false side lobe" in the first channel feature.

[0134] Step 2b, perform antenna engineering parameter calibration step: based on the calibrated first channel characteristics and second channel characteristics, calibrate the initial antenna engineering parameters to obtain the calibrated initial antenna engineering parameters.

[0135] The specific process of step 2b can refer to the above steps 1a to 2a, which will not be repeated here.

[0136] Step 3b: Obtain first antenna engineering parameters based on the calibrated initial antenna engineering parameters.

[0137] In a possible implementation, the channel model building device may directly use the calibrated initial antenna engineering parameters as the first antenna engineering parameters.

[0138] In another possible implementation, the channel modeling device may cyclically calibrate the first channel characteristic, the initial antenna parameters, and the second channel characteristic. In this case, after the above step 2b, the method may further include step 1c, and the above step 3b may specifically include steps 3.1b to 3.2b.

[0139] Step 1c, execute the second channel characteristic calibration step: use the calibrated initial antenna engineering parameters to perform ray tracing to obtain the calibrated second channel characteristics.

[0140] Step 3.1b, repeat the first channel characteristic calibration step (ie, the above step 1b), the antenna engineering parameter calibration step (ie, the above step 2b), and the second channel characteristic calibration step (ie, the above step 1c) until the iteration stop condition is met.

[0141] As an example, the iteration stop condition may include: the number of times the first channel characteristic calibration step, the antenna engineering parameter calibration step, and the second channel characteristic calibration step are executed reaches a number threshold.

[0142] The number threshold may be preset in the channel modeling device. For example, the number threshold may be set to 5 times, 10 times, 20 times, 50 times, or 100 times, etc. The embodiment of the present disclosure does not limit the specific value of the number threshold.

[0143] As another example, the iteration stop condition may include: an adjustment value when calibrating antenna engineering parameters is less than a preset threshold.

[0144] For example, as described above, the antenna engineering parameter deviation value may include an azimuth deviation value and a downtilt deviation value. When the azimuth deviation value and the downtilt deviation value are relatively small, it can be considered that the current antenna engineering parameter is relatively accurate, and the adjustment value to be adjusted is relatively small, so the iteration can be stopped. The preset threshold value can be preset in the channel model modeling device. For example, the preset threshold value can be set to 0.1°, or 0.2°, etc. The embodiments of the present disclosure do not limit the specific value of the preset threshold value.

[0145] As another example, the iteration stop condition may include: the number of times the first channel characteristic calibration step, the antenna engineering parameter calibration step, and the second channel characteristic calibration step are executed reaches a number threshold, and the adjustment value when calibrating the antenna engineering parameters is less than a preset threshold.

[0146] Step 3.2b, the antenna engineering parameters that meet the iteration stop condition are used as the first antenna engineering parameters.

[0147] In the channel modeling method provided by the embodiment of the present disclosure, the channel modeling device can also repeatedly perform the first channel characteristic calibration step, the antenna engineering parameter calibration step, and the second channel characteristic calibration step until the iteration stop condition is met, and then the antenna engineering parameters when the iteration stop condition is met are used as the first antenna engineering parameters. In this way, the first channel characteristic, the initial antenna engineering parameters, and the second channel characteristic can be calibrated cyclically and iteratively, thereby improving the accuracy of the calibrated first antenna engineering parameters and improving the accuracy of the channel model established based on the ray tracing of the first antenna engineering parameters.

[0148] In some embodiments, the correlation threshold in the above step 1.1.5b may be a preset value preset in the channel modeling device.

[0149] In some other embodiments, the correlation threshold in the above step 1.1.5b can also be dynamically calculated based on the maximum correlation parameter of the current initial angle feature. In this case, before the above step 1.1.5b, the method can also include the following steps:

[0150] Step 1d: Determine a maximum correlation parameter from correlation parameters between each initial angle characteristic and the angle characteristic of the first path in the first channel characteristic.

[0151] Exemplarily, the channel modeling device may determine the maximum correlation parameter according to the following formula:

[0152] Formula (6)

[0153] In formula (6), represents the maximum correlation parameter. Represents the azimuth and elevation angles in the initial angle feature.

[0154] Step 2d: Determine the correlation threshold value according to the difference between the maximum correlation parameter and the preset deviation threshold.

[0155] The preset deviation threshold may be preset in the channel modeling device. For example, the preset deviation threshold may be set to 0.1 or 0.2, etc. The embodiment of the present disclosure does not limit the specific value of the preset deviation threshold.

[0156] Exemplarily, taking the preset deviation threshold as 0.1 as an example, assuming that among the correlation parameters between each initial angle feature currently calculated and the angle feature of the first path in the first channel feature, the maximum correlation parameter is 0.8, the channel model modeling device can obtain the correlation threshold of 0.7 based on 0.8-0.1=0.7.

[0157] Exemplarily, as described above, the correlation threshold may be determined based on the difference between the maximum correlation parameter and the preset deviation threshold. In this case, the angle candidate domain in the above step 1.1.5b may be specifically expressed as the following formula:

[0158] Formula (7)

[0159] In formula (7), Indicates The angle candidate domain corresponding to the signal transmission path. Indicates the preset deviation threshold.

[0160] In some possible embodiments, as described above, the path component characteristics also include power and delay, and the channel modeling device can also match the path component characteristics in the first channel characteristics and the second channel characteristics in pairs according to power and delay, so as to determine the reference angle characteristics corresponding to each signal transmission path. In this case, before the above step 1.2b, the method can also include the following steps:

[0161] Step 1e: Match the path component features in the first channel features and the path component features in the second channel features according to the similarity between the powers and the similarity between the delays to obtain a plurality of matching pairs.

[0162] Each matching pair includes a path component feature in a first channel feature and a path component feature in a second channel feature.

[0163] For example, the channel modeling device can determine the similarity between the powers based on the ratio between the first difference and the first power. The first difference is the difference between the second power and the first power. The first power is the power in a path component feature in the first channel feature. The second power is the power in a path component feature in the second channel feature.

[0164] For another example, the channel modeling device can determine the similarity between the delays based on the ratio between the first difference and the first delay. The first difference is the difference between the second delay and the first delay. The first delay is the delay in a path component feature in the first channel feature. The second delay is the delay in a path component feature in the second channel feature.

[0165] As an example, the channel model modeling device can perform weighted summation on the similarity between the powers and the similarity between the delays to obtain the similarity between a path component feature in the first channel feature and a path component feature in the second channel feature, and select the two path component features with the greatest similarity to form a matching pair.

[0166] Step 2e: Determine the reference angle feature corresponding to each signal transmission path according to multiple matching pairs.

[0167] For example, taking the example that the signal transmission path 1 corresponds to the path component feature 1 in the first channel feature, the channel model modeling device can select a matching pair including the path component feature 1 from multiple matching pairs, and use the angle feature in the path component feature of the second channel feature in the matching pair as the reference angle feature corresponding to the signal transmission path 1.

[0168] It should be understood that the first channel characteristic and the second channel characteristic may include multiple path component characteristics, but the corresponding relationship between the path component characteristics in the two channel characteristics is not clear.

[0169] In the channel model modeling method provided by the embodiment of the present disclosure, before the channel model modeling device selects the target angle feature according to the reference angle feature in the second channel feature to calibrate the first channel feature, it can also match the path component features in the first channel feature and the second channel feature in pairs to establish multiple matching pairs, so as to facilitate the selection of the target angle feature according to the reference angle feature.

[0170] The above mainly introduces the solution provided by the embodiment of the present disclosure from the perspective of the method. In order to realize the above functions, each device, such as a cell switching device, includes a hardware structure and / or software module corresponding to the execution of each function in order to realize the above functions. It should be easy to realize that the technical goals in this field are combined with the algorithm steps of each example described in the embodiments disclosed in this article. The present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technical goals can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present disclosure.

[0171] In an exemplary embodiment, the present disclosure also provides a channel modeling device. Figure 3 A schematic diagram of a channel modeling device provided in an embodiment of the present disclosure. Figure 3 As shown, the channel modeling device 300 can be connected to the channel measurement module 400. The channel modeling device 300 includes: a channel measurement calibration module 301, an antenna engineering parameter calibration module 302, and a ray tracing module 303.

[0172] The channel measurement module 400 is responsible for performing channel measurement and estimation based on the received wireless signal in the wireless network, and generating channel characteristic 1 (that is, the first channel characteristic mentioned above). The wireless signal is a signal sent by a transmitter in the wireless network and received by a receiver, including a pilot or reference signal, which can be used for wireless channel characteristic estimation.

[0173] The ray tracing module 303 is responsible for generating channel characteristics 2 (i.e., the second channel characteristics mentioned above) based on the input 3D map and antenna engineering parameter data. The 3D map is a data file containing the terrain of the area where the network is located, as well as the height, location, and material of the buildings. The antenna engineering parameters include the horizontal azimuth angle of the base station antenna, the vertical downward tilt angle, and the number of arrays and the horizontal and vertical spacing of the receiver antenna array. When the module is run for the first time, the input antenna engineering parameters of the ray tracing module 303 come from the original antenna engineering parameters of the network management system; when subsequent iterative optimization is performed, the input antenna engineering parameters of the ray tracing module 303 come from the "calibrated antenna engineering parameters" generated by the antenna engineering parameter calibration module 302. Channel characteristics 2 include the power, delay, horizontal and vertical arrival angles of each path component of the channel.

[0174] The channel measurement calibration module 301 is used to calibrate the channel data 1 according to the input channel characteristics 2, eliminate the "false side lobes" caused by the non-ideal antenna array (the antenna array spacing is greater than half a wavelength, and there are interference and noise effects), and generate "calibrated channel characteristics 1".

[0175] The antenna engineering parameter calibration module 302 is used to compare the input calibrated channel characteristic 1 with the channel characteristic 2, estimate the error caused by the inaccurate antenna engineering parameters contained in the channel characteristic 2, and compensate for it to generate the calibrated antenna engineering parameters.

[0176] In an exemplary embodiment, Figure 4 A schematic diagram of another channel modeling device provided in an embodiment of the present disclosure. Figure 4 As shown, the channel modeling device 500 includes: a processing unit 501.

[0177] The processing unit 501 is used to calibrate the initial antenna working parameters of the communication node based on the first channel characteristics to obtain the calibrated first antenna working parameters; wherein the first channel characteristics are determined by the communication node based on the detection data of the wireless channel; and the first antenna working parameters are used to perform ray tracing to establish a channel model of the wireless channel.

[0178] In some possible embodiments, the processing unit 501 is specifically used to determine the antenna engineering parameter deviation value based on the first channel characteristics and the second channel characteristics; wherein the second channel characteristics are determined after ray tracing based on the initial antenna engineering parameters; and based on the antenna engineering parameter deviation value, the initial antenna engineering parameters are calibrated to obtain the calibrated first antenna engineering parameters.

[0179] In some other possible embodiments, the processing unit 501 is specifically used to use the azimuth angle deviation value as the adjustment value of the azimuth angle in the initial antenna engineering parameters, and use the downtilt angle deviation value as the adjustment value of the downtilt angle in the initial antenna engineering parameters, to calibrate the initial antenna engineering parameters, and obtain the calibrated first antenna engineering parameters.

[0180] In some other possible embodiments, the processing unit 501 is specifically used to determine the calibration confidence based on the deviation between the azimuth angle of the multiple signal transmission paths in the first channel characteristic and the azimuth angle in the second channel characteristic, and the deviation between the elevation angle of the multiple signal transmission paths in the first channel characteristic and the elevation angle in the second channel characteristic; when the calibration confidence is greater than the confidence threshold, the azimuth angle deviation value is used as the adjustment value of the azimuth angle in the initial antenna engineering parameters, and the downtilt angle deviation value is used as the adjustment value of the downtilt angle in the initial antenna engineering parameters, and the initial antenna engineering parameters are calibrated to obtain the calibrated first antenna engineering parameters.

[0181] In some other possible embodiments, the processing unit 501 is specifically used to determine the calibration confidence based on the variance of the deviation between the azimuth angles of the multiple signal transmission paths in the first channel characteristics and the azimuth angles in the second channel characteristics, and the variance of the deviation between the elevation angles of the multiple signal transmission paths in the first channel characteristics and the elevation angles in the second channel characteristics.

[0182] In some other possible embodiments, the processing unit 501 is specifically used to execute a first channel characteristic calibration step: calibrate the first channel characteristic using the second channel characteristic to obtain a calibrated first channel characteristic; wherein the second channel characteristic is determined after ray tracing based on the initial antenna engineering parameters; execute an antenna engineering parameter calibration step: calibrate the initial antenna engineering parameters based on the calibrated first channel characteristic and the second channel characteristic to obtain the calibrated initial antenna engineering parameters; obtain the first antenna engineering parameters based on the calibrated initial antenna engineering parameters.

[0183] In some other possible embodiments, the processing unit 501 is further configured to perform a second channel characteristic calibration step after performing the antenna engineering parameter calibration step: ray tracing is performed using the calibrated initial antenna engineering parameters to obtain the calibrated second channel characteristics. The processing unit 501 is specifically configured to repeatedly perform the first channel characteristic calibration step, the antenna engineering parameter calibration step, and the second channel characteristic calibration step until an iteration stop condition is met; the antenna engineering parameters when the iteration stop condition is met are used as the first antenna engineering parameters.

[0184] In some other possible embodiments, the processing unit 501 is specifically used to determine the angle candidate domain corresponding to each signal transmission path based on the path component characteristics corresponding to each signal transmission path in the first channel characteristic; wherein the angle candidate domain includes multiple candidate angle characteristics; the candidate angle characteristic is an angle characteristic within a preset angle range, and the correlation parameter between the angle characteristic in the path component characteristics of the signal transmission path in the first channel characteristic is greater than a correlation threshold; select the target angle characteristic that is most similar to the reference angle characteristic corresponding to the signal transmission path from the angle candidate domain corresponding to each signal transmission path, and calibrate the angle characteristic in the path component characteristics corresponding to each signal transmission path in the first channel characteristic; wherein the reference angle characteristic is the angle characteristic of the path component characteristic of the corresponding signal transmission path in the second channel characteristic.

[0185] In some other possible embodiments, the processing unit 501 is further used to match the path component characteristics in the first channel characteristics with the path component characteristics in the second channel characteristics according to the similarity between the powers and the similarity between the delays, to obtain multiple matching pairs; each matching pair includes a path component characteristic in the first channel characteristics and a path component characteristic in the second channel characteristics; and the reference angle characteristics corresponding to each signal transmission path are determined according to the multiple matching pairs.

[0186] In some other possible embodiments, the processing unit 501 is specifically used to determine, for any first path among multiple signal transmission paths, a spatial feature vector of the first path according to the angular feature of the first path in the first channel feature; scan within a preset angle range to obtain multiple initial angle features; determine, based on the multiple initial angle features, a spatial feature vector corresponding to each initial angle feature; determine a correlation parameter between each initial angle feature and the angular feature of the first path in the first channel feature according to the spatial feature vector of the first path, the spatial feature vector corresponding to each initial angle feature, and an angle correlation function; use the initial angle feature whose correlation parameter is greater than the correlation threshold as a candidate angle feature to obtain an angle candidate domain corresponding to the first path.

[0187] In some other possible embodiments, the processing unit 501 is further used to determine a maximum correlation parameter from correlation parameters between each initial angle feature and the angle feature of the first path in the first channel feature; and determine a correlation threshold based on the difference between the maximum correlation parameter and a preset deviation threshold.

[0188] In an exemplary embodiment, the present disclosure also provides an electronic device, and the above-mentioned channel modeling device can be applied to the electronic device. Figure 5 The following is a schematic diagram of the composition of an electronic device provided by an embodiment of the present disclosure. Figure 5As shown, the electronic device 60 includes: a processor 602, a communication interface 603, and a bus 604. As an example, the electronic device 60 may also include a memory 601.

[0189] The processor 602 may be a processor that implements or executes various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of the present disclosure. The processor 602 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of the present disclosure. The processor 602 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0190] The communication interface 603 is used to connect with other devices via a communication network, which may be Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0191] The memory 601 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0192] As a possible implementation, the memory 601 may exist independently of the processor 602, and the memory 601 may be connected to the processor 602 via a bus 604 for storing instructions or program codes. When the processor 602 calls and executes the instructions or program codes stored in the memory 601, the channel modeling method provided in the embodiment of the present disclosure can be implemented.

[0193] In another possible implementation, the memory 601 may also be integrated with the processor 602 .

[0194] The bus 604 may be an extended industry standard architecture (EISA) bus, etc. The bus 604 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0195] In an exemplary embodiment, the present disclosure also provides a readable storage medium including software instructions. When the software instructions are executed on an electronic device (eg, the electronic device 60 described above), the electronic device executes any one of the methods provided in the above embodiments.

[0196] In an exemplary embodiment, the present disclosure also provides a computer program product including computer instructions, which, when executed on an electronic device (eg, the electronic device 60 ), enables the electronic device to execute any one of the methods provided in the above embodiments.

[0197] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using a software program, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer-executable instructions. When the computer-executable instructions are loaded and executed on a computer, the process or function according to the embodiment of the present disclosure is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer-executable instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer-executable instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more servers that can be integrated with the medium. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), or an optical medium (e.g., a DVD), etc.

[0198] Although the present disclosure is described herein in conjunction with various embodiments, in the process of implementing the claimed disclosure, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in a claim. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0199] Although the present disclosure has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present disclosure. Accordingly, this specification and the drawings are merely exemplary illustrations of the present disclosure as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present disclosure. Obviously, those skilled in the art may make various modifications and variations to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

[0200] The above is only a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A channel modeling method, characterized in that: The method comprises: Determine an antenna engineering parameter deviation value based on a first channel characteristic and a second channel characteristic; wherein the first channel characteristic is determined by a communication node based on detection data of a wireless channel; and the second channel characteristic is determined after ray tracing based on an initial antenna engineering parameter of the communication node; Based on the antenna engineering parameter deviation value, calibrating the initial antenna engineering parameters to obtain the calibrated first antenna engineering parameters; Ray tracing is performed using the first antenna engineering parameters to establish a channel model of the wireless channel.

2. The method according to claim 1, characterized in that The antenna engineering parameter deviation value includes an azimuth angle deviation value and a downtilt angle deviation value.

3. The method according to claim 2, characterized in that The azimuth angle deviation value is an average value of deviations between the azimuth angles of multiple signal transmission paths in the first channel characteristics and the azimuth angles in the second channel characteristics.

4. The method according to claim 2, characterized in that: The downtilt angle deviation value is an average value of deviations between the pitch angles of multiple signal transmission paths in the first channel characteristics and the pitch angles in the second channel characteristics.

5. The method according to claim 2, characterized in that: The step of calibrating the initial antenna engineering parameters based on the antenna engineering parameter deviation value to obtain calibrated first antenna engineering parameters includes: The azimuth angle deviation value is used as the adjustment value of the azimuth angle in the initial antenna engineering parameters, and the downtilt angle deviation value is used as the adjustment value of the downtilt angle in the initial antenna engineering parameters. The initial antenna engineering parameters are calibrated to obtain the calibrated first antenna engineering parameters.

6. The method according to claim 5, characterized in that The method of using the azimuth angle deviation value as the adjustment value of the azimuth angle in the initial antenna engineering parameters, using the downtilt angle deviation value as the adjustment value of the downtilt angle in the initial antenna engineering parameters, and calibrating the initial antenna engineering parameters to obtain the calibrated first antenna engineering parameters includes: Determining calibration confidence based on deviations between azimuth angles of multiple signal transmission paths in the first channel characteristic and azimuth angles in the second channel characteristic, and deviations between elevation angles of multiple signal transmission paths in the first channel characteristic and elevation angles in the second channel characteristic; When the calibration confidence is greater than the confidence threshold, the azimuth angle deviation value is used as the adjustment value of the azimuth angle in the initial antenna engineering parameters, and the downtilt angle deviation value is used as the adjustment value of the downtilt angle in the initial antenna engineering parameters. The initial antenna engineering parameters are calibrated to obtain the calibrated first antenna engineering parameters.

7. The method according to claim 6, characterized in that The determining of calibration confidence based on deviations between azimuth angles of multiple signal transmission paths in the first channel characteristic and azimuth angles in the second channel characteristic, and deviations between elevation angles of multiple signal transmission paths in the first channel characteristic and elevation angles in the second channel characteristic, comprises: The calibration confidence is determined based on the variance of the deviations between the azimuth angles of the multiple signal transmission paths in the first channel characteristic and the azimuth angles in the second channel characteristic, and the variance of the deviations between the elevation angles of the multiple signal transmission paths in the first channel characteristic and the elevation angles in the second channel characteristic.

8. The method according to claim 1, characterized in that The step of calibrating the initial antenna working parameters of the communication node based on the first channel characteristics to obtain the calibrated first antenna working parameters includes: Performing a first channel characteristic calibration step: using a second channel characteristic, calibrating the first channel characteristic to obtain a calibrated first channel characteristic; wherein the second channel characteristic is determined by ray tracing based on initial antenna engineering parameters; Performing an antenna engineering parameter calibration step: calibrating the initial antenna engineering parameters based on the calibrated first channel characteristics and the second channel characteristics to obtain calibrated initial antenna engineering parameters; The first antenna engineering parameters are obtained based on the calibrated initial antenna engineering parameters.

9. The method according to claim 8, characterized in that After performing the antenna engineering parameter calibration step, the method further includes: Performing a second channel characteristic calibration step: performing ray tracing using the calibrated initial antenna engineering parameters to obtain a calibrated second channel characteristic; The obtaining the first antenna engineering parameters based on the calibrated initial antenna engineering parameters includes: Repeating the first channel characteristic calibration step, the antenna engineering parameter calibration step, and the second channel characteristic calibration step until an iteration stop condition is met; The antenna engineering parameters when the iteration stop condition is met are used as the first antenna engineering parameters.

10. The method according to claim 9, characterized in that The iteration stop condition includes: the number of times the first channel characteristic calibration step, the antenna engineering parameter calibration step, and the second channel characteristic calibration step are executed reaches a number threshold, and / or the adjustment value when calibrating the antenna engineering parameters is less than a preset threshold.

11. The method according to claim 8, characterized in that The first channel characteristic and the second channel characteristic each include a path component characteristic corresponding to each signal transmission path in a plurality of signal transmission paths, and the path component characteristic includes an angle characteristic; The angle characteristics include azimuth and elevation; The step of calibrating the first channel characteristic by using the second channel characteristic to obtain the calibrated first channel characteristic includes: Based on the path component characteristics corresponding to each signal transmission path in the first channel characteristics, determining the angle candidate domain corresponding to each signal transmission path; The angle candidate domain includes a plurality of candidate angle features; the candidate angle feature is an angle feature within a preset angle range, and the correlation parameter between the angle feature in the path component feature of the signal transmission path in the first channel feature is greater than a correlation threshold; Selecting a target angle feature that is closest to a reference angle feature corresponding to the signal transmission path from the angle candidate domain corresponding to each signal transmission path, and calibrating the angle feature in the path component feature corresponding to each signal transmission path in the first channel feature; The reference angle feature is an angle feature of a path component feature of a corresponding signal transmission path in the second channel feature.

12. The method according to claim 11, characterized in that The path component characteristics also include power and delay; the method also includes: According to the similarity between the powers and the similarity between the delays, path component features in the first channel features and path component features in the second channel features are matched to obtain a plurality of matching pairs; each matching pair includes a path component feature in the first channel features and a path component feature in the second channel features; A reference angle feature corresponding to each signal transmission path is determined according to the multiple matching pairs.

13. The method according to claim 11, characterized in that For any first path among the multiple signal transmission paths, determining the angle candidate domain corresponding to each signal transmission path based on the path component characteristics corresponding to each signal transmission path in the first channel characteristics includes: determining a spatial characteristic vector of the first path according to an angular characteristic of the first path in the first channel characteristic; Scanning within the preset angle range to obtain a plurality of initial angle features; Determine, according to the multiple initial angle features, a spatial feature vector corresponding to each initial angle feature; Determine, according to the spatial feature vector of the first path, the spatial feature vector corresponding to each initial angle feature, and the angle correlation function, a correlation parameter between each initial angle feature and the angle feature of the first path in the first channel feature; An initial angle feature whose correlation parameter is greater than the correlation threshold is used as a candidate angle feature to obtain an angle candidate domain corresponding to the first path.

14. The method according to claim 13, characterized in that The method further comprises: determining a maximum correlation parameter from correlation parameters between each initial angular characteristic and the angular characteristic of the first path in the first channel characteristic; The correlation threshold is determined according to the difference between the maximum correlation parameter and a preset deviation threshold.

15. A channel modeling device, characterized in that: include: Processing unit; The processing unit is used to determine the antenna engineering parameter deviation value based on the first channel characteristic and the second channel characteristic; wherein the first channel characteristic is determined by the communication node based on the detection data of the wireless channel; and the second channel characteristic is determined after ray tracing based on the initial antenna engineering parameters of the communication node; Based on the antenna engineering parameter deviation value, the initial antenna engineering parameters are calibrated to obtain calibrated first antenna engineering parameters; ray tracing is performed using the first antenna engineering parameters to establish a channel model of the wireless channel.

16. An electronic device, characterized in that: include: Processor and memory; The processor stores instructions executable by the memory; When the processor is configured to execute the instructions, the electronic device implements the method according to any one of claims 1 to 14.

17. A readable storage medium, characterized in that: include: Software instructions; When the software instructions are executed in an electronic device, the electronic device implements the method according to any one of claims 1 to 14.

18. A computer program product, characterized in that The computer program product comprises computer instructions, and when the computer instructions are executed in an electronic device, the electronic device implements the method according to any one of claims 1 to 14.

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