Communication environment identification method and device based on ultra wide band, intelligent equipment and medium

Abstract

The invention relates to the technical field of ultra wide bands, in particular to a communication environment identification method and device based on an ultra wide band, intelligent equipment and a computer readable storage medium. The method comprises the following steps: performing channel estimation on a received ultra-wideband signal to determine a channel impulse response in a current communication environment; based on the channel impulse response, determining a channel time dispersion parameter at least comprising the following items: average excess time delay which is a weighted average of time delays of all multipath components in the channel, total receiving power which is the sum of the powers of all the multipath components in the channel, and total receiving power which is the sum of the powers of all the multipath components in the channel, the weighted average being the weighted average of the time delays of all the multipath components in the channel, and the weighted average being the weighted average of the time delays of all the multipath components in the channel; and a time interval between the maximum path and the first path, which is a delay inequality between the multipath component having the maximum power and the multipath component of the first arrival in the channel; and inputting the channel time dispersion parameter into the algorithm model, and identifying the type of the current communication environment by using the algorithm model.

Description

Technical Field

[0001] The present application relates to the field of ultra-wideband technology, and more specifically to an ultra-wideband-based communication environment identification method, 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. Background Art

[0002] At present, many application scenarios require the determination of the type of environment (such as indoors or outdoors) in which the device is located. Some existing technologies use smartphones to detect the number of surrounding base stations, and determine whether the phone is located indoors or outdoors based on the assumption that the number of base stations detected outdoors is greater than that detected indoors. Since modern system communication systems widely use microcell and micro-microcell technology for networking, the above assumption is not always valid. In addition, some existing technologies use information provided by multiple sensors (such as road signs, magnetic field strength, road texture, temperature, light intensity, odor, pollutant detection, etc.) to comprehensively determine the type of environment. Since 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 the prior art known to ordinary technicians in the 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 communication environment identification method 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; based on the channel impulse response, determining 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 a multipath component with maximum power in the channel and a multipath component that arrives first; 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 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 according to 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 according to 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 is provided with 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 also includes: an ultra-wideband transmitter for transmitting an ultra-wideband detection signal; and an ultra-wideband receiver for receiving a signal after the ultra-wideband detection signal is reflected by the current communication environment.

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

[0017] Compared with the prior art, the ultra-wideband-based communication environment identification scheme according to one or more embodiments of the present application introduces two channel time dispersion parameters, namely, the total received power and the time interval between the maximum path and the first path, so that the hidden features in the channel (that is, the current communication environment) experienced by the ultra-wideband signal transmission can be characterized from more dimensions. Among them, the total received power can reflect the overall strength of the signal, providing additional information about the signal propagation loss and the density of reflectors for environmental identification; and the time interval between the maximum path and the first path reflects the degree of temporal expansion of the signal energy in the channel. The addition of these two parameters can more comprehensively characterize the differences in channel characteristics of different communication environments, enhance the ability of the algorithm model to distinguish in complex environments, and thus improve the accuracy and robustness of communication environment identification (such as increasing the recognition rate to 97.1% under the application of 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 units are represented by the same reference numerals. In the accompanying drawings: Figure 1 is a schematic flow chart of a communication environment identification method 10 according to one or more embodiments of the present application; Figure 2 is a schematic block diagram of a communication environment identification device 20 according to one or more embodiments of the present application; Figure 3is a schematic block diagram of a smart device 30 according to one or more embodiments of the present application; and Figure 4 The diagram 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

[0019] 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, it is not intended to be bound by any express or implied theory presented in the aforementioned technical field, background technology or the following specific embodiments.

[0020] In the following detailed description of the embodiments, many specific details are set forth in order to provide a more thorough understanding of the disclosed technology. However, it is 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.

[0021] Terms such as “comprise” and “include” indicate that in addition to the units and steps directly and explicitly stated in the specification, the technical solution of the present application does not exclude the situation where there are other units and steps that are not directly or explicitly stated.

[0022] Hereinafter, various exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings.

[0023] Referring to the accompanying drawings, Figure 1 It is a schematic flow chart of a communication environment identification method 10 according to one or more embodiments of the present application.

[0024] 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.

[0025] It should be noted that the communication environment identification method 10 is implemented based on ultra-wideband (UWB) technology, so the device itself needs to have UWB communication capabilities (for example, equipped with a UWB transceiver), and / or have the ability to detect or process UWB signals. In an embodiment where the device itself has UWB communication capabilities, the communication environment identification method 10 also includes transmitting a UWB detection signal and receiving a signal after the UWB detection signal is reflected by the current communication environment.

[0026] Channel Impulse Response (CIR) is an important parameter for describing the characteristics of wireless channels. It can reflect the multipath effect, reflection, scattering, and attenuation experienced by the signal during propagation. By performing channel estimation on the received UWB signal and determining the CIR in the current communication environment, key channel characteristic information can be provided for subsequent environment identification. This process is the basis for achieving high-precision communication environment discrimination, because it can directly reflect the impact of the current environment on wireless signal propagation, thereby providing input data for subsequent algorithm models.

[0027] 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, multiple copies of the transmitted signal will be received at the receiving end at different times. These copies have different signal amplitudes, different phases, and arrive at the receiving end 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: in, is the CIR in the current communication environment, contains the multipath information of the current channel and can be expressed as: Here, is the Dirac function, N is the number of multipaths, is the gain factor (i.e., amplitude) of the nth arriving multipath component (referred to 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).

[0028] In practical applications, channel estimation can be achieved in many ways, for example, using a UWB chip that supports channel measurement to read the channel impulse response.

[0029] 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 a maximum path and a first path are determined.

[0030] 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 differences in the time dispersion characteristics of the channel. 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. Exemplarily, the channel time dispersion parameters are based on the channel impulse response. One or more of the following information in: the number of multipaths N, the amplitude of each multipath component , and delay .

[0031] 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 is used 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: 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: The time interval between the maximum path and the first path It is the time delay difference between the multipath component with the maximum power in the channel (referred to as the maximum path) and the first path, reflecting the degree of temporal expansion of the signal energy in the channel. For example, in an indoor environment with a significant multipath effect, since the signal undergoes multiple reflections and scattering, the time delay difference of signals from different paths reaching the receiver is large, so the time interval between the maximum path and the first path is usually large; while in an open outdoor environment, the signal is less reflected and scattered, the multipath effect is weaker, and the time interval between the maximum path and the first path is usually small. Therefore, the time interval between the maximum path and the first path can be used as an important basis for distinguishing different communication environments.

[0032] 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: The average delay without the first path is the average delay of the multipath components in the channel except the first multipath component. It is designed to exclude the influence of the direct path (usually the first path) to more accurately reflect the reflection and scattering characteristics in the channel. Specifically, the average delay without the first path is The calculation formula is as follows: The non-first-path RMS delay spread is the RMS value of the deviation between the delay of 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 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, so as to more accurately characterize the multipath characteristics of the channel. It is especially suitable for distinguishing between 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: 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. Usually, in a line-of-sight (LOS) environment, this value is usually smaller; in a non-line-of-sight (NLOS) environment, this value is usually larger. Specifically, the ratio of the amplitude of the maximum path to the amplitude of the first path is The calculation formula is as follows: The time interval between the first path and the second path , 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.

[0033] 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: 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: 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: in, Maximum multipath delay , which is the delay of the last arriving multipath component, reflects the longest path delay experienced by the signal during propagation.

[0034] Optionally, the channel time dispersion parameter also includes the number N of multipaths.

[0035] 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.

[0036] This process is the core of the entire communication environment identification method. By taking the channel time dispersion parameters as input features, the pre-trained algorithm model can distinguish different types of environments 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, time interval between the maximum path and the first path, etc.) can effectively reflect the multipath effect and propagation characteristics in the channel, and these characteristics vary significantly in different environments. Therefore, by analyzing and classifying these parameters through the algorithm model, high-precision environment identification can be achieved.

[0037] The algorithm model used in step 130 is a mathematical model or a machine learning model for identifying 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, a decision tree, a neural network, etc.). Exemplarily, the training process of the algorithm model 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, so that the algorithm model can learn the corresponding relationship between different channel time dispersion parameters and communication environment types.

[0038] Exemplarily, the types of current communication environments usually include indoors (there are usually a large number of reflectors and scatterers, such as walls, ceilings, furniture, etc., which lead to complex signal propagation paths and significant multipath effects), outdoors (the signal propagation path is relatively simple, with less reflection and scattering, and the multipath effect is not obvious), and may also include semi-open environments (environments with only ground and ceiling, such as charging stations, whose multipath effects are between indoor and outdoor environments). In order to more finely characterize the environment in which the device is located, the types of communication environments can also be divided in more detail: outdoor open spaces (no obvious reflectors and scatterers, the signal propagation path is the simplest), outdoor semi-open spaces (there are some reflectors and scatterers, but the number is small), light indoors (such as indoor spaces with open doors and windows, whose multipath effects are weaker), and deep indoors (such as indoor spaces without windows, whose multipath effects are the strongest).

[0039] Optionally, the type of the current communication environment identified in step 130 can provide reliable information support for subsequent applications. For example, in smart cars and smart home systems, the behavior and performance of the system can be optimized according to different environment types, thereby improving user experience and system operation efficiency. This information support based on environment type can achieve more intelligent and adaptive system control.

[0040] In a specific embodiment, a corresponding sunshine model may be determined according to the type of the current communication environment. The sunshine model indicates the distribution of sunshine intensity in different environments. For example, in an outdoor environment, the direct sunlight is relatively strong, and an outdoor sunshine model may be selected; in an indoor environment, the sunlight is blocked by buildings, and an indoor sunshine model may be selected. Afterwards, the control parameters of the air-conditioning system may be adjusted based on the selected sunshine model. For example, the cooling / heating power, air volume, and blowing direction of the air conditioner may be adjusted according to the intensity of sunshine to achieve the best in-vehicle temperature control effect.

[0041] In another specific embodiment, intelligent wiper control can also be performed based on the environmental recognition result. Specifically, if the current communication environment is indoors and the rain detector detects water droplets, it is determined that the vehicle may be in a car wash environment. At this time, in order to avoid misoperation, the wiper can be controlled not to start. If the current communication environment is outdoor, the working state of the wiper is adaptively controlled according to the amount of rain detected by the rain detector. For example, when the rain is small, the wiper is wiped intermittently; when the rain is heavy, the wiper is wiped at a high speed.

[0042] In order to verify the effectiveness of the communication environment identification method of 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 are as follows: Table 1 As shown in Table 1, under the same XGBoost model parameter configuration (100 trees, tree depth of 3), compared with the use of 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 improved from 96.1% to 97.1% using the combination of the three parameters 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 the total received power and the time interval between the maximum path and the first path, the solution of this application can reduce the number of parameters while obtaining a higher recognition accuracy. This phenomenon further proves that the more channel time dispersion parameters, the 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 the performance of model recognition. Reducing the number of parameters also helps reduce computational complexity, improves the model's operating efficiency, and is more suitable for resource-constrained embedded devices.

[0043] It is worth noting that in the field of machine learning, especially when the model recognition rate is already high, even a 1% improvement in accuracy is of great significance. This means that the model is more robust when dealing with complex scenarios or edge cases, which can reduce misjudgments and thus improve safety and reliability in applications that require extremely high accuracy (for example, autonomous driving, high-precision positioning, etc.).

[0044] In addition, as shown in Table 1, when the model input includes all 12 channel time dispersion parameters, the recognition accuracy is significantly improved to 99.5%. This further confirms that the channel time dispersion parameters proposed in this application can comprehensively characterize the hidden features of the communication environment, thereby greatly improving the accuracy of environment recognition.

[0045] Figure 2 2 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 above-mentioned communication environment identification method 10 to be executed. Exemplarily, the communication environment identification device 20 may be a part of an electronic control unit (ECU) of a vehicle system, or a control unit of an autonomous driving system.

[0046] Figure 3 FIG. 1 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 2The communication environment identification device 20 shown. The smart device 30 also 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. Exemplarily, the smart device 30 may include a driving device, a smart car, an electric car, a robot, and other devices.

[0047] In vehicle applications, vehicles are usually equipped with multiple UWB anchor stations to support high-precision channel estimation and positioning functions. In order to achieve communication environment identification, one or more pairs of UWB anchor stations can be selected to perform channel estimation separately. This flexible deployment method can adjust the measurement accuracy and coverage according to specific needs and application scenarios.

[0048] Figure 4 A schematic diagram of the deployment of a UWB anchor station 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 a UWB transmitter and a UWB receiver, respectively, which are installed on the outside of the B-pillar of the vehicle. This layout allows the two UWB anchor stations to be 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 station, the present application can adapt to a variety of different application scenarios, thereby providing more comprehensive and accurate data support for communication environment identification.

[0049] In addition, the present application can also be implemented as a computer-readable storage medium, in which a program for causing a computer to execute the above-mentioned communication environment identification method 10 is stored. Here, as a computer-readable storage medium, various 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, cassette tapes, etc.) can be used.

[0050] In the applicable situation, hardware, software or a combination of 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 subcomponents 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.

[0051] 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 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.

[0052] 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 implement and use the present application. However, those skilled in the art will appreciate that the above description and examples are provided only for ease of illustration and example. The description set forth is not intended to cover all aspects of the present application or to limit the present application to the precise form 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 items: 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 in the channel and the first arriving multipath component; 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 non-first-path average delay is the average delay of the multipath components other than the first arriving multipath component in the channel; and / or The non-first-path root mean square delay spread is the root mean square 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.

4. 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.

5. 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 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 multipath components is the average value of the delay differences between all adjacent multipath components in the channel.

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

7. 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 the sunshine intensity distribution under different environments; and According to the determined sunshine model, the control parameters of the air conditioning system are adjusted.

8. The method according to claim 1, wherein: The method further comprises: If the type of the current communication environment is indoor and the rain detector detects water droplets, the wiper is 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 rainfall detected by the rain detector.

9. 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 enables the method according to any one of claims 1 to 8 to be executed.

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

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

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium comprises instructions which, when executed, perform the method according to any one of claims 1-8.

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