Communication environment identification method and device based on ultra-wideband, intelligent device and medium

Abstract

The present application relates to the field of ultra-wideband technology, and more specifically to a method and apparatus for identifying a communication environment based on ultra-wideband, an intelligent device, and a computer-readable storage medium. The method comprises: performing channel estimation on a received ultra-wideband signal to determine a channel impulse response under a current communication environment; determining, based on the channel impulse response, a channel time dispersion parameter including at least the following items: an average excess delay, which is a weighted average of the delays of all multipath components in the channel, wherein the power of each multipath component serves as a corresponding weight, a total received power, which is the sum of the powers of all multipath components in the channel, and a time interval between a maximum path and a first path, which is the delay difference between the multipath component with the maximum power in the channel and the first arriving multipath component; inputting the channel time dispersion parameter into an algorithm model, and using the algorithm model to identify the type of the current communication environment.

Description

Technical Field

[0001] The present application relates to the field of ultra-wideband technology, and more specifically to a communication environment identification method based on ultra-wideband, a communication environment identification device implementing the method, an intelligent device equipped with the device, and a computer-readable storage medium capable of implementing the method. Background Art

[0002] Many current application scenarios require determining the type of environment a device is in (e.g., indoors or outdoors). Some existing technologies use smartphones to detect the number of nearby base stations and determine whether the phone is indoors or outdoors based on the assumption that more base stations are detected outdoors than indoors. However, since modern communication systems widely utilize micro-cell and pico-micro-cell technologies for networking, this assumption is not always true. Furthermore, some existing technologies use information provided by multiple sensors (e.g., road signs, magnetic field strength, road texture, temperature, light intensity, odor, and pollutant detection) to comprehensively determine the type of environment. Because this method requires the use of technologies such as visual recognition, the system is complex and costly.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute prior art known to ordinary technicians in this field. Summary of the Invention

[0004] In order to solve or at least alleviate one or more of the above problems, the present application provides a communication environment identification method based on ultra-wideband, a communication environment identification device for implementing the method, an intelligent device equipped with the device, and a computer-readable storage medium capable of implementing the method, which further improves the accuracy of communication environment identification by constructing channel time dispersion parameters.

[0005] According to a first aspect of the present application, a method for identifying a communication environment based on ultra-wideband is provided, comprising the following steps: performing channel estimation on a received ultra-wideband signal to determine a channel impulse response under a current communication environment; determining, based on the channel impulse response, a channel time dispersion parameter including at least the following items: an average excess delay, which is a weighted average of the delays of all multipath components in the channel, wherein the power of each multipath component serves as a corresponding weight, a total received power, which is the sum of the powers of all multipath components in the channel, and a time interval between a maximum path and a first path, which is the delay difference between the multipath component with the maximum power in the channel and the first arriving multipath component; inputting the channel time dispersion parameter into an algorithm model, and using the algorithm model to identify the type of the current communication environment.

[0006] As an alternative or supplement to the above solution, the communication environment identification method according to an embodiment of the present application further includes: transmitting an ultra-wideband detection signal; and receiving a signal after the ultra-wideband detection signal is reflected by the current communication environment.

[0007] As an alternative or supplement to the above scheme, in a communication environment identification method according to an embodiment of the present application, the channel time dispersion parameter also includes: an average delay without a first path, which is the average value of the delays of multipath components other than the first arriving multipath component in the channel; and / or a root mean square delay spread without a first path, which is the root mean square value of the deviation between the delays of multipath components other than the first arriving multipath component and the average delay without a first path.

[0008] As an alternative or supplement to the above scheme, in a communication environment identification method according to an embodiment of the present application, the channel time dispersion parameter also includes: the ratio of the amplitude of the maximum path to the amplitude of the first path, which is the absolute value of the ratio of the amplitude of the multipath component with the maximum power in the channel to the amplitude of the first arriving multipath component.

[0009] As an alternative or supplement to the above scheme, in a communication environment identification method according to an embodiment of the present application, the channel time dispersion parameter also includes one or more of the following: the time interval between the first path and the second path, which is the delay difference between the second arriving multipath component and the first arriving multipath component in the channel; the interval between the two latest arriving multipaths, which is the delay difference between the last arriving multipath component and the second to last arriving multipath component in the channel; and the average interval between adjacent multipaths, which is the average value of the delay differences between all adjacent multipath components in the channel.

[0010] As an alternative or supplement to the above solution, in a communication environment identification method according to an embodiment of the present application, the type of the current communication environment includes indoor, outdoor, and semi-open environment.

[0011] As an alternative or supplement to the above scheme, the communication environment identification method according to an embodiment of the present application also includes: determining a corresponding sunlight model based on the type of the current communication environment, the sunlight model indicating the sunlight intensity distribution under different environments; and adjusting the control parameters of the air-conditioning system based on the determined sunlight model.

[0012] As an alternative or supplement to the above scheme, the communication environment identification method according to an embodiment of the present application also includes: if the type of the current communication environment is indoor and the rain detector detects water droplets, the wiper is not started; and / or if the type of the current communication environment is outdoor, the working state of the wiper is controlled according to the amount of rain detected by the rain detector.

[0013] According to the second aspect of the present application, a communication environment identification device is provided, comprising: a memory; a processor; and a computer program stored on the memory and executable on the processor, wherein the execution of the computer program enables any one of the communication environment identification methods described in the first aspect of the present application to be executed.

[0014] According to a third aspect of the present application, a smart device is provided, which includes the communication environment identification device according to the second aspect of the present application.

[0015] As an alternative or supplement to the above solution, the smart device according to an embodiment of the present application further includes: an ultra-wideband transmitter for transmitting an ultra-wideband detection signal; and an ultra-wideband receiver for receiving a signal of the ultra-wideband detection signal after being reflected by the current communication environment.

[0016] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes instructions, and the instructions, when run, execute any one of the communication environment identification methods according to the first aspect of the present invention.

[0017] Compared to existing technologies, the ultra-wideband (UWB)-based communication environment identification scheme according to one or more embodiments of the present application introduces two channel time dispersion parameters: total received power (TRP) and the time interval between the maximum path and the first path. This allows for a more comprehensive characterization of the hidden characteristics of the channel (i.e., the current communication environment) traversed by the UWB signal transmission. TRP reflects the overall signal strength, providing additional information about signal propagation loss and reflector density for environment identification; while the time interval between the maximum path and the first path reflects the temporal spread of the signal energy in the channel. The inclusion of these two parameters more comprehensively characterizes the differences in channel characteristics across different communication environments, enhancing the algorithm model's ability to distinguish complex environments, and thus improving the accuracy and robustness of communication environment identification (for example, the recognition rate was increased to 97.1% using the XGBoost algorithm model). BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or other aspects and advantages of the present application will become clearer and easier to understand through the following description of various aspects in conjunction with the accompanying drawings, in which the same or similar elements are represented by the same reference numerals. In the drawings:

[0019] Figure 1 is a schematic flow chart of a communication environment identification method 10 according to one or more embodiments of the present application;

[0020] Figure 2 is a schematic block diagram of a communication environment identification device 20 according to one or more embodiments of the present application;

[0021] Figure 3 is a schematic block diagram of a smart device 30 according to one or more embodiments of the present application; and

[0022] Figure 4 FIG. 1 is a schematic diagram of deploying a UWB anchor station on a vehicle according to one or more embodiments of the present application. DETAILED DESCRIPTION

[0023] The description of the following specific embodiments is merely exemplary in nature and is not intended to limit the disclosed technology or the application and use of the disclosed technology. In addition, there is no intention to be bound by any express or implied theory presented in the foregoing technical field, background technology or the following specific embodiments.

[0024] In the following detailed description of the embodiments, numerous specific details are set forth to provide a more thorough understanding of the disclosed technology. However, it will be apparent to one of ordinary skill in the art that the disclosed technology can be practiced without these specific details. In other instances, well-known features are not described in detail to avoid unnecessarily complicating the description.

[0025] Terms such as “comprise” and “include” indicate that in addition to the units and steps directly and clearly stated in the specification, the technical solution of the present application does not exclude the situation where it has other units and steps that are not directly or clearly stated.

[0026] Hereinafter, various exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings.

[0027] Referring to the accompanying drawings, Figure 1 1 is a schematic flow chart of a communication environment identification method 10 according to one or more embodiments of the present application.

[0028] like Figure 1 As shown, in step 110, channel estimation is performed on the received UWB signal to determine the channel impulse response under the current communication environment.

[0029] It should be noted that the communication environment identification method 10 is implemented based on ultra-wideband (UWB) technology, and therefore requires the device to have UWB communication capabilities (e.g., be equipped with a UWB transceiver) and / or the ability to detect or process UWB signals. In embodiments where the device itself has UWB communication capabilities, the communication environment identification method 10 also includes transmitting a UWB probe signal and receiving a signal after the UWB probe signal is reflected by the current communication environment.

[0030] The Channel Impulse Response (CIR) is a key parameter that describes wireless channel characteristics. It reflects the multipath effects, reflections, scattering, and attenuation experienced by signals during propagation. By performing channel estimation on received UWB signals and determining the CIR in the current communication environment, we can provide key channel characteristic information for subsequent environmental identification. This process is fundamental to achieving high-precision communication environment identification because it directly reflects the impact of the current environment on wireless signal propagation, providing input data for subsequent algorithm models.

[0031] Specifically, in step 110, channel estimation refers to the process of estimating the CIR using the received UWB signal after being reflected by the current communication environment. According to the theory of wireless communication systems, the propagation characteristics of radio waves in space are characterized by the impulse response of the wireless channel. This theory regards the wireless channel as a linear time-varying filter. Corresponding to the signal sent by the transmitter, the receiver will receive multiple copies of the transmitted signal at different times. These copies have different signal amplitudes, different phases, and arrive at the receiver at different times. Multiple copies of the transmitted signal are received because there are a certain number of signal reflectors, scatterers, and diffractors in the radio wave propagation environment. If the signal sent by the transmitter is , in a multipath propagation environment and without considering noise, the received ultra-wideband signal It can be expressed as:

[0032]

[0033] in, is the CIR in the current communication environment, contains the multipath information of the current channel and can be expressed as:

[0034]

[0035] Here, is the Dirac function, N is the number of multipaths, is the gain factor (i.e., amplitude) of the nth arriving multipath component (abbreviated as the nth path), is the arrival delay of the nth path relative to the first arriving multipath component (referred to as the first path for short).

[0036] In practical applications, channel estimation can be achieved in a variety of ways, such as using a UWB chip that supports channel measurement to read the channel impulse response.

[0037] In step 120, based on the channel impulse response, channel time dispersion parameters including at least average excess delay, total received power, and a time interval between the maximum path and the first path are determined.

[0038] Channel time dispersion refers to the time dispersion phenomenon caused by the multipath effect during the transmission of wireless signals. Different communication environments have different strengths of multipath effects, resulting in different channel time dispersion characteristics. Therefore, by extracting and analyzing the channel time dispersion parameters, different types of communication environments can be effectively identified. In the context of this application, the channel time dispersion parameters refer to parameters that can reflect the channel time dispersion characteristics. For example, the channel time dispersion parameters are based on the channel impulse response. One or more of the following information is obtained: the number of multipath N, the amplitude of each multipath component , and delay .

[0039] Specifically, the average excess delay is the weighted average of the delays of all multipath components in the channel, where the power of each multipath component serves as the weight. It reflects the average delay of the signal propagating in the channel. The larger the average excess delay, the more obvious the multipath effect of the channel. Specifically, the average excess delay is The calculation formula is as follows:

[0040]

[0041] The total received power is the sum of the powers of all multipath components in the channel, reflecting the overall strength of the received signal, which can provide additional information about signal propagation loss and reflector density. The higher the total received power, the stronger the signal. Specifically, the total received power The calculation formula is as follows:

[0042]

[0043] The time interval between the maximum diameter and the first diameter The delay difference between the multipath component with the highest power in the channel (referred to as the maximum path) and the first path reflects the temporal spread of the signal energy in the channel. For example, in an indoor environment with significant multipath effects, the signal delays along different paths reaching the receiver vary significantly due to multiple reflections and scattering. Therefore, the time interval between the maximum path and the first path is typically larger. In contrast, in an open outdoor environment, where signal reflections and scattering are less frequent and multipath effects are weaker, the time interval between the maximum path and the first path is typically smaller. Therefore, the time interval between the maximum path and the first path can serve as an important basis for distinguishing different communication environments.

[0044] In some embodiments according to the present application, in addition to the above 、 、 In addition, the channel time dispersion parameters may also include one or more of the following:

[0045] The average delay without the first path is the average delay of the multipath components in the channel except the first arriving multipath component. It is designed to exclude the influence of the direct path (usually the first path) and thus more accurately reflect the reflection and scattering characteristics of the channel. Specifically, the average delay without the first path is the average delay of the multipath components in the channel except the first arriving multipath component. The calculation formula is as follows:

[0046]

[0047] The non-first-path RMS delay spread is the RMS value of the deviation between the delay of the multipath components other than the first arriving multipath component and the non-first-path average delay. It is used to measure the delay spread of the multipath components other than the first path in the channel. This parameter can effectively eliminate the interference of the direct path or the strongest path, thereby more accurately characterizing the multipath characteristics of the channel. It is especially suitable for distinguishing indoor and outdoor environments, because indoor environments usually have more reflection and scattering paths, resulting in larger delay spread. Specifically, the non-first-path RMS delay spread The calculation formula is as follows:

[0048]

[0049] The ratio of the maximum path to the first path, which is the amplitude of the multipath component with the maximum power in the channel ( ) and the amplitude of the first arriving multipath component ( ). It reflects the strength comparison between the strongest signal and the first path signal. Generally, in line-of-sight (LOS) environments, this value is usually smaller; in non-line-of-sight (NLOS) environments, this value is usually larger. Specifically, the ratio of the amplitude of the maximum path to the first path is The calculation formula is as follows:

[0050]

[0051] The time interval between the first and second paths , which is the delay difference between the second multipath component arriving in the channel and the first multipath component arriving, and is used to reflect the degree of separation between the two earliest arriving paths in the channel.

[0052] The interval between the two latest arriving multipaths is the time delay difference between the last arriving multipath component and the second to last arriving multipath component in the channel. It can reflect the time interval of the last stage of signal propagation and is helpful in identifying the long-distance propagation environment. Specifically, the interval between the two latest arriving multipaths is The calculation formula is as follows:

[0053]

[0054] The average interval between adjacent multipaths is the average value of the delay difference between all adjacent multipath components in the channel, which can reflect the density of multipath components on the time axis. Specifically, the average interval between adjacent multipaths is The calculation formula is as follows:

[0055]

[0056] The mean square delay spread is the square root of the difference between the weighted average of the squares of the delays of all multipath components in the channel and the square of the average excess delay. The calculation formula is as follows:

[0057]

[0058] in,

[0059] Maximum multipath delay , that is, the delay of the last arriving multipath component, reflects the longest path delay experienced by the signal during propagation.

[0060] Optionally, the channel time dispersion parameter also includes the multipath number N.

[0061] In step 130, the channel time dispersion parameter is input into the algorithm model, and the algorithm model is used to identify the type of the current communication environment.

[0062] This process is the core of the entire communication environment identification method. By using channel time dispersion parameters as input features, the pre-trained algorithm model can distinguish different environment types based on the differences in these features. The channel time dispersion parameters defined in this application (including but not limited to: average excess delay, total received power, and the time interval between the maximum path and the first path) can effectively reflect the multipath effect and propagation characteristics of the channel, which vary significantly across different environments. Therefore, by analyzing and classifying these parameters through the algorithm model, high-precision environment identification can be achieved.

[0063] The algorithm model used in step 130 is a mathematical model or machine learning model used to identify the type of communication environment. It can be a threshold-based classification model or a more complex machine learning model (such as a support vector machine, decision tree, or neural network). Exemplarily, the algorithm model training process is as follows: First, a large number of channel time dispersion parameter samples under different communication environments are collected, and each sample is labeled to indicate the corresponding communication environment type. Then, these samples are input into the algorithm model for training, allowing the algorithm model to learn the corresponding relationship between different channel time dispersion parameters and communication environment types.

[0064] For example, current communication environments typically include indoor environments (where there are often a large number of reflectors and scatterers, such as walls, ceilings, and furniture, resulting in a complex signal propagation path and significant multipath effects), outdoor environments (where the signal propagation path is relatively simple, with fewer reflections and scattering, and the multipath effect is not significant), and semi-open environments (environments with only ground and ceilings, such as charging stations, where the multipath effect is between indoor and outdoor environments). To more accurately characterize the environment in which the device is located, the communication environment types can be further divided into: outdoor open spaces (where there are no obvious reflectors and scatterers, and the signal propagation path is the simplest), outdoor semi-open spaces (where there are some reflectors and scatterers, but in smaller numbers), light indoor spaces (such as indoor spaces with open doors and windows, where the multipath effect is weaker), and deep indoor spaces (such as indoor spaces without windows, where the multipath effect is strongest).

[0065] Optionally, the type of current communication environment identified in step 130 can provide reliable information support for subsequent applications. For example, in smart cars and smart home systems, system behavior and performance can be optimized based on different environment types, thereby improving user experience and system operational efficiency. This type of environment-based information support enables more intelligent and adaptive system control.

[0066] In one specific embodiment, a corresponding sunlight model can be determined based on the type of the current communication environment. The sunlight model indicates the distribution of sunlight intensity in different environments. For example, in an outdoor environment with strong direct sunlight, an outdoor sunlight model can be selected; in an indoor environment with sunlight blocked by buildings, an indoor sunlight model can be selected. The control parameters of the air conditioning system can then be adjusted based on the selected sunlight model. For example, the cooling / heating power, air volume, and air direction of the air conditioner can be adjusted based on the sunlight intensity to achieve optimal in-vehicle temperature control.

[0067] In another specific embodiment, intelligent wiper control can also be performed based on environmental recognition results. Specifically, if the current communication environment is indoors and the rain detector detects water droplets, it is determined that the vehicle is likely in a car wash environment. To avoid malfunction, the wipers can be disabled. If the current communication environment is outdoor, the wiper operation is adaptively controlled based on the amount of rain detected by the rain detector. For example, intermittent wiping is performed when the rain is light, and high-speed wiping is performed when the rain is heavy.

[0068] To verify the effectiveness of the communication environment identification method proposed in this application, Table 1 shows the impact of different channel time dispersion parameter combinations on the accuracy of model identification (for indoor and outdoor environments) when using the XGBoost algorithm model. The specific data is as follows:

[0069]

[0070] Table 1

[0071] As shown in Table 1, under the same XGBoost model parameter configuration (100 trees, tree depth 3), compared to using the four channel time dispersion parameters of average excess delay, mean square delay spread, maximum multipath delay, and number of multipaths, the model recognition accuracy is actually improved from 96.1% to 97.1% using the three-parameter combination of average excess delay, total received power, and the time interval between the maximum path and the first path proposed in this application. This result shows that by introducing total received power and the time interval between the maximum path and the first path, the solution of this application can achieve higher recognition accuracy while reducing the number of parameters. This phenomenon further proves that more channel time dispersion parameters are not necessarily better. Compared with the combination of the four parameters of average excess delay, mean square delay spread, maximum multipath delay, and number of multipaths, the combination of average excess delay, total received power, and the time interval between the maximum path and the first path can provide more effective and discriminative environmental information, thereby improving model recognition performance. Reducing the number of parameters also helps reduce computational complexity, improves model efficiency, and is more suitable for resource-constrained embedded devices.

[0072] It's worth noting that in the field of machine learning, even a 1% improvement in accuracy is significant, especially when the model's recognition rate is already high. This means the model is more robust when handling complex scenarios or edge cases, reducing false positives and improving safety and reliability in applications requiring extremely high accuracy, such as autonomous driving and high-precision positioning.

[0073] Furthermore, as shown in Table 1, when the model input includes all 12 channel time dispersion parameters, the recognition accuracy significantly increases to 99.5%. This further confirms that the channel time dispersion parameters proposed in this application can comprehensively characterize the hidden characteristics of the communication environment, thereby significantly improving the accuracy of environment recognition.

[0074] Figure 2 This is a schematic block diagram of a communication environment identification device 20 according to one or more embodiments of the present application. The communication environment identification device 20 includes a memory 210, a processor 220, and a computer program 230 stored in the memory 210 and executable on the processor 220. The execution of the computer program 230 enables the aforementioned communication environment identification method 10 to be executed. For example, the communication environment identification device 20 may be part of an electronic control unit (ECU) of a vehicle system or a control unit of an autonomous driving system.

[0075] Figure 3 FIG. 3 is a schematic block diagram of a smart device 30 according to one or more embodiments of the present application. The smart device 30 has the following features: Figure 2 The communication environment identification apparatus 20 is shown. The smart device 30 further includes a UWB transmitter 310 for transmitting a UWB detection signal, and a UWB receiver 320 for receiving a signal after the UWB detection signal is reflected by the current communication environment. For example, the smart device 30 may include a driving device, a smart car, an electric car, a robot, or other devices.

[0076] In vehicular applications, multiple UWB anchor stations are typically deployed to support high-precision channel estimation and positioning. To identify the communication environment, one or more pairs of UWB anchor stations can be selected for channel estimation. This flexible deployment approach allows for tailoring measurement accuracy and coverage to specific needs and application scenarios.

[0077] Figure 4 A schematic diagram of the deployment of UWB anchor stations on a vehicle according to one or more embodiments of the present application is shown. The two UWB anchor stations marked with hexagons in the figure correspond to the UWB transmitter and the UWB receiver, respectively, which are installed on the outside of the B-pillar of the vehicle. This layout makes the two UWB anchor stations completely blocked by the vehicle body, thereby simulating NLOS propagation conditions. However, in other application scenarios, the deployment method between UWB anchor stations may be different. For example, there may be a LOS path between the anchor stations, that is, there is no obstruction between the two communication nodes. By flexibly selecting the deployment method of the UWB anchor stations, the present application can adapt to a variety of different application scenarios, thereby providing more comprehensive and accurate data support for communication environment identification.

[0078] In addition, the present application may also be implemented as a computer-readable storage medium having stored therein a program for causing a computer to execute the communication environment identification method 10 described above. Computer-readable storage media may include various types of computer-readable storage media, such as disks (e.g., magnetic disks, optical disks, etc.), cards (e.g., memory cards, optical cards, etc.), semiconductor memories (e.g., ROMs, non-volatile memories, etc.), and tapes (e.g., magnetic tapes, cassettes, etc.).

[0079] In the applicable situation, the combination of hardware, software or hardware and software can be used to realize the various embodiments provided by the application. Moreover, in the applicable situation, without departing from the scope of the application, the various hardware components and / or software components set forth herein can be combined into a composite component comprising software, hardware and / or both. In the applicable situation, without departing from the scope of the application, the various hardware components and / or software components set forth herein can be divided into a subcomponent comprising software, hardware or both. In addition, in the applicable situation, it is contemplated that the software component can be implemented as a hardware component, and vice versa.

[0080] Software according to the present application (such as program code and / or data) can be stored on one or more computer-readable storage media. It is also contemplated that the software identified herein can be implemented using one or more general-purpose or special-purpose computers and / or computer systems, networked and / or otherwise. Where applicable, the order of the various steps described herein can be changed, combined into composite steps, and / or divided into sub-steps to provide the features described herein.

[0081] The embodiments and examples set forth herein are provided to best illustrate embodiments according to the present application and its specific applications, and thereby enable those skilled in the art to make and use the present application. However, those skilled in the art will appreciate that the above description and examples are provided for ease of illustration and example only. The descriptions set forth are not intended to be exhaustive of all aspects of the present application or to limit the present application to the precise forms disclosed.

Claims

1. A communication environment identification method based on ultra-wideband, characterized in that: The following steps are involved: Perform channel estimation on the received ultra-wideband signal to determine the channel impulse response under the current communication environment; Based on the channel impulse response, determining a channel time dispersion parameter including at least the following: The average excess delay is the weighted average of the delays of all multipath components in the channel, where the power of each multipath component is used as the corresponding weight. The total received power, which is the sum of the powers of all multipath components in the channel, and The time interval between the maximum path and the first path is the time delay difference between the multipath component with the maximum power and the first arriving multipath component in the channel; The average delay without the first path is the average delay of the multipath components in the channel except the first arriving multipath component; and / or The non-first-path RMS delay spread is the RMS value of the deviation between the delays of the multipath components other than the first arriving multipath component in the channel and the non-first-path average delay; The channel time dispersion parameter is input into an algorithm model, and the algorithm model is used to identify the type of the current communication environment.

2. The method according to claim 1, wherein Also includes: transmitting an ultra-wideband detection signal; as well as A signal of the ultra-wideband detection signal reflected by the current communication environment is received.

3. The method according to claim 1, wherein The channel time dispersion parameters also include: The ratio of the amplitude of the maximum path to the first path is the absolute value of the ratio of the amplitude of the multipath component with the maximum power in the channel to the amplitude of the first arriving multipath component.

4. The method according to claim 1, wherein The channel time dispersion parameters also include one or more of the following: The time interval between the first path and the second path is the time delay difference between the second arriving multipath component and the first arriving multipath component in the channel; The interval between the two latest arriving multipaths is the time delay difference between the last arriving multipath component and the second to last arriving multipath component in the channel; as well as The average interval between adjacent multipaths is the average value of the delay differences between all adjacent multipath components in the channel.

5. The method according to claim 1, wherein The types of the current communication environment include indoor, outdoor, and semi-open environments.

6. The method according to claim 1, wherein The method further comprises: Determining a corresponding sunshine model according to the type of the current communication environment, the sunshine model indicating sunshine intensity distribution under different environments; and Adjust the control parameters of the air conditioning system according to the determined sunlight model.

7. The method according to claim 1, wherein The method further comprises: If the current communication environment is indoor and the rain detector detects water droplets, the wipers are not activated; and / or If the type of the current communication environment is outdoor, the working state of the wiper is controlled according to the amount of rain detected by the rain detector.

8. A communication environment identification device, comprising: a memory; a processor; and a computer program stored in the memory and executable on the processor, wherein the execution of the computer program causes the method according to any one of claims 1 to 7 to be executed.

9. A smart device, characterized in that: A communication environment recognition device according to claim 8 is provided.

10. The smart device according to claim 9, wherein: The smart device further includes: an ultra-wideband transmitter for transmitting an ultra-wideband detection signal; and The ultra-wideband receiver is used to receive the ultra-wideband detection signal after being reflected by the current communication environment.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium comprises instructions that, when executed, perform the method according to any one of claims 1-7.

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