A digital twin channel modeling method

Abstract

The present invention provides a digital twin channel modeling method. The method includes: performing online measurement through a base station and a terminal to obtain channel measurement data; performing channel modeling and model optimization of a propagation environment based on the channel measurement data through the base station and the terminal; and realizing a digital twin channel model of a variety of environments based on the four twin elements of mapping, data, model, and synchronization according to the channel modeling and model optimization results, so as to realize the interactive mapping of physical channels and digital virtual channels. The present invention designs a novel digital twin channel modeling method, which can perform online distributed data acquisition and offline model optimization processing in different wireless communication environments (scenarios), so as to quickly obtain channel measurement data, and obtain the channel characteristics of the wireless channel, etc., so as to realize continuously optimized channel modeling.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular to a digital twin channel modeling method. Background Art

[0002] Studying the propagation characteristics of wireless channels and establishing channel models is the basis for building wireless communication systems.

[0003] At present, the wireless channel modeling methods in the prior art mainly include statistical channel modeling and deterministic channel modeling. Among them, the statistical channel modeling method mainly relies on the actual channel measurement data of the corresponding scene, has poor adaptability to different environmental characteristics, and many scenes have the problem of large amount of measured data and difficulty in data acquisition. Deterministic channel modeling is a mathematical modeling method that relies on simplification and assumptions of the environment and uses accurate electromagnetic calculations to describe the propagation characteristics of radio waves. However, there is an irreconcilable large deviation from the actual channel state, so the channel modeling is not accurate enough.

[0004] Therefore, the wireless channel modeling method in the prior art is inefficient and cannot meet the growing demand for communication services. Summary of the invention

[0005] An embodiment of the present invention provides a digital twin channel modeling method to effectively obtain the channel characteristics of a wireless channel.

[0006] In order to achieve the above object, the present invention adopts the following technical scheme.

[0007] A digital twin channel modeling method, characterized by comprising:

[0008] Perform online measurements through base stations and terminals to obtain channel measurement data;

[0009] Performing channel modeling and model optimization of the propagation environment based on the channel measurement data by the base station and the terminal;

[0010] According to the results of channel modeling and model optimization, the digital twin channel model of various environments is comprehensively realized based on the four twin elements of mapping, data, model and synchronization, realizing the interactive mapping of physical channels and digital virtual channels.

[0011] Preferably, the performing online measurement through the base station and the terminal to obtain channel measurement data includes:

[0012] Construct a channel measurement system including a cloud, a signal transmitter, a signal receiver, a data storage module and information input interfaces of each part. The signal transmitter transmits a channel detection signal. After the channel detection signal is propagated through the channel, online measurement of multiple working mode fusion or coordinated call is performed. The baseband data at the port of the signal receiver is converted by A / D to obtain channel measurement data. The channel measurement data includes power domain and delay domain feature data, completes environmental perception and measurement, and stores the channel measurement data in the data storage module.

[0013] The multiple working modes include wireless environment perception mode, wireless channel detection mode, communication mode, positioning mode and control mode. The wireless environment perception mode is to perceive the communication conditions, noise interference and overall system performance of the surrounding environment; the wireless channel detection mode is to measure and analyze the channel status and channel characteristics; the communication mode is a working mode in which the communication terminal selectively sends and receives signals after connecting to multiple base stations; the positioning mode is to determine the terminal position through the transmission and reception signal information of the signal transceiver, and transmit and share it to other terminals as needed, so as to obtain and share the terminal position information; the control mode is that the information processed by the local base station is integrated and transmitted to the cloud for centralized processing, so as to obtain a digital twin channel model for global information display and perform partial command control on the base station.

[0014] Preferably, the channel modeling and model optimization of the propagation environment based on the channel measurement data by the base station and the terminal includes:

[0015] The offline optimization unit includes a model generation and optimization module and a wireless environment map generation module. The model generation and optimization module generates a time-varying channel model of the corresponding scene based on the environmental perception and channel measurement data obtained by online measurement, as well as the propagation characteristics of the detection signal itself and the environmental interference information. The online measurement process continuously performs channel measurement and data acquisition, and updates the time-varying channel model. The wireless environment map generation module generates a wireless environment map of the environment based on the time-varying channel model. The wireless environment map includes: scene information with scene characteristics, network and system layer information containing network topology and system deployment, transmission channel information containing interference distribution and communication breakpoint locations, and transceiver information and feedback information of each radio frequency and reception.

[0016] Preferably, the digital twin channel model of various environments is comprehensively implemented based on the four twin elements of mapping, data, model, and synchronization according to the channel modeling and model optimization results to realize the interactive mapping of physical channels and digital virtual channels, including:

[0017] The channel modeling and model optimization results of the propagation environment comprehensively realize the digital twin channel model of various environments in mapping, data, model and synchronous twin elements. In the data part, the digital twin channel model obtains channel measurement data through online channel measurement and data acquisition functions, and updates the relevant model data in different scenarios by using the migration function in offline optimization; the twin channel data obtained in the model part is represented by offline optimized modeling and simulation to obtain the twin channel model; the wireless environment map generated in the mapping part reflects the relevant characteristics of the actual physical channel, realizing the mapping of physical channels and digital channels; in terms of synchronization, the channel characteristics of the wireless environment in the virtual world and the digital world are synchronized.

[0018] Preferably, the information interaction process of the channel measurement system includes:

[0019] The cloud sends out routine commands and provides initial terminal information and digital twin maps, activates target base stations that need to enter working status as needed, and the base station sends out a command to enter wireless environment perception mode. The terminal performs environmental perception and sends the measured environmental interference information to the base station. The base station issues a wireless channel detection mode command and transmits a detection signal. The terminal completes channel detection and generates a preliminary distributed channel model, and sends the result to the base station. The cloud sends out a command to enter positioning mode, and the base station performs terminal positioning operations and generates a wireless environment map at the same time. The cloud sends out a command to enter communication mode, and the base station uploads the terminal positioning information and the generated wireless environment map to the cloud. The cloud performs positioning accuracy detection. If it does not meet the performance requirements, the cloud sends out a command to enter control mode and transmits feedback information to the base station. The base station optimizes the detection signal according to the optimization instruction, and then repeats the above operation process to obtain a gradually optimized wireless channel model and an updated wireless environment map.

[0020] It can be seen from the technical solutions provided by the above-mentioned embodiments of the present invention that the present invention designs a novel digital twin channel modeling method, which can perform online distributed data acquisition and offline model optimization processing in different wireless communication environments (scenarios) to quickly acquire channel measurement data and obtain channel characteristics of the wireless channel, etc., to achieve continuously optimized channel modeling.

[0021] Additional aspects and advantages of the present invention will be given in part in the following description, which will become obvious from the following description, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0023] Figure 1 It is a schematic diagram of the implementation principle of a digital twin channel modeling method provided by an embodiment of the present invention.

[0024] Figure 2 It is a schematic diagram of four major elements constituting a digital twin channel model provided by an embodiment of the present invention.

[0025] Figure 3 It is an example of the implementation function of a device for digital twin channel modeling provided in an embodiment of the present invention.

[0026] Figure 4 It is an information interaction diagram for digital twin channel modeling provided by an embodiment of the present invention.

[0027] Figure 5 The invention provides a UWB channel detection signal generation, reception and detection result analysis.

[0028] Figure 6 This is a structural description of transmitting a UWB channel detection signal provided by an embodiment of the present invention.

[0029] Figure 7 It is a time domain waveform of sending and receiving a UWB channel detection signal provided by an embodiment of the present invention.

[0030] Figure 8 It is a power delay curve comparison (time domain analysis) of channel detection provided by an embodiment of the present invention.

[0031] Fig. 9 It is a power delay curve (frequency domain analysis) of channel detection provided by an embodiment of the present invention.

[0032] Fig.10 A two-path model measurement system is provided in an embodiment of the present invention.

[0033] Fig.11 It is a standard UWB signal frame structure-data unit format provided by an embodiment of the present invention.

[0034] Fig.12 This is a verification result of building a laboratory measurement system provided by an embodiment of the present invention.

[0035] Fig.13It is an example diagram of the composition of a digital twin channel model and the calling of multiple working modes provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0037] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or coupling. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0038] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0039] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0040] The embodiment of the present invention designs a digital twin channel modeling method, which adopts a combination of online measurement and offline optimization, calls the wireless environment perception mode to perceive environmental information, calls the wireless channel detection mode to obtain channel characteristics, calls the communication mode to perform selective communication connection between the base station, terminal and cloud, calls the positioning mode to perform positioning auxiliary enhancement through the detection signal transmission and reception process, obtains the terminal position, and transmits and shares it to other terminals as needed, quickly provides global indications for the terminal position, and calls the control mode to issue various control commands, etc. The information processed by the local base station is integrated and transmitted to the cloud for centralized data processing to obtain a digital twin channel model with global information display. Combined with the inspection feedback information of the system performance (including but not limited to) positioning accuracy, control commands or other indication commands can be sent to the base station to generate and send signals that are more suitable for the system performance, thereby obtaining better system performance.

[0041] Embodiment 1

[0042] The present invention proposes a digital twin channel modeling method, and its implementation principle schematic diagram is shown in Figure 1 As shown, the following working steps are included:

[0043] Step S1: Perform online measurement through the base station and the terminal to obtain channel measurement data;

[0044] Step S2: performing channel modeling and model optimization of the propagation environment based on the channel measurement data by the base station and the terminal;

[0045] Step S3: According to the channel modeling and model optimization results, a digital twin channel model for various environments is comprehensively implemented based on the four major twin elements of mapping, data, model, and synchronization, and the digital twin channel model is used to realize the interactive mapping of physical channels and digital virtual channels.

[0046] The above step S1 specifically includes: obtaining distributed channel measurement data through online measurement.

[0047] The entire system includes the cloud, a signal transmitting device (base station), a signal receiving device (terminal), a data storage module and information input interfaces of each part. As an example, the implementation form is a multi-mode fusion coordination call of the wireless environment perception mode, wireless channel detection mode, communication mode, positioning mode, control mode and other working modes it contains. Online measurement can perform tasks such as power domain measurement and delay domain measurement. The specific implementation is: the signal transmitting device transmits a channel detection signal, which reaches the signal receiving device after channel propagation, and finally obtains the power domain and delay domain characteristic data of the channel measurement through baseband data processing at the receiving device port, completes environmental perception and measurement, and obtains channel detection data. The channel detection data is transmitted to the offline optimization component for corresponding modeling simulation and model optimization, and some data is temporarily stored in the data storage module.

[0048] In the implementation mode, the wireless environment perception mode is to perceive the communication conditions, noise interference, overall system performance, etc. of the surrounding environment; the wireless channel detection mode is to measure and analyze the channel status and channel characteristics; the communication mode is a working mode in which the communication terminal selectively sends and receives signals after connecting to multiple base stations, which is a networking mode; the positioning mode is to determine the terminal position through the transmission and reception signal information of the signal transceiver, and transmit and share it to other terminals on demand, so as to obtain and share the terminal position information; the control mode is that the information processed by the local base station is integrated and transmitted to the cloud for centralized and refined processing, so as to obtain a digital twin channel model with global information display, and perform partial command control on the working process of the base station, etc.

[0049] The above step S2 specifically includes: offline optimization to perform channel modeling and model optimization.

[0050] The offline optimization in the digital twin channel modeling method includes a model generation and optimization module and a wireless environment map generation module. Offline optimization is based on the environmental perception and channel measurement data obtained by online measurement, including the propagation characteristics of the detection signal itself and the environmental interference information, and uses the model generation and optimization module to generate the time-varying channel model of the corresponding scene. Since the channel state may change dynamically, the online measurement function can continuously perform channel measurement and data acquisition, update the time-varying channel model, and generate a wireless environment map of the environment at the same time. The wireless environment map may include: scene information with scene characteristics, network / system layer information containing network topology and system deployment, transmission channel information containing interference distribution and communication breakpoint location, transceiver information with each radio frequency and receiving, and some feedback information that helps optimize signal or system performance. In addition, in view of the phenomenon that the characteristics of channel models are different in different scenarios, it is recommended to combine explainable artificial intelligence and transfer learning methods to make the channel model interpretable, establish the connection between the source scene and the target scene, and locally modify the model through data-scenario migration to optimize the model and reduce the computational complexity. In the later stage, the wireless environment map can be updated with the help of the digital twin channel model.

[0051] The above step S3 specifically includes: comprehensively realizing the digital twin channel model of various environments based on the four major twin elements of mapping, data, model, and synchronization.

[0052] In the present invention, the digital twin channel model is defined as: an interactively mappable channel model with physical channel entities and digital virtual channels, which includes four major elements: data, model, mapping and synchronization. Figure 2The figure shows the four major elements that constitute the digital twin channel model. In the data part, channel measurement data can be obtained through online measurement (perception) channel measurement and data acquisition functions. In different scenarios, the migration function in offline optimization is used to update the relevant model data; in the model part, the twin channel data obtained is modeled and simulated through offline optimization to obtain the representation form of the twin channel model; in the mapping part, the wireless environment map generated in step S2 can reflect the relevant characteristics of the actual physical channel and realize the mapping of physical channels and digital channels. The constructed digital twin channel model initially has channel characteristics and other analysis results after local rough processing in a variety of environments. The above parts ultimately achieve the synchronization of channel characteristics of the wireless environment of the virtual world and the digital world.

[0053] Example of implementation functionality for digital twin channel modeling

[0054] An example of the various functional components of the multi-mode fusion digital twin channel modeling in the embodiment of the present invention is as follows: Figure 3 As shown in Figure 2, the proposed online measurement and offline optimization are Figure 3 In the example, the online measurement functions performed by the signal transmitting device (base station) include wireless environment perception mode, wireless channel detection mode, communication mode, positioning mode and control mode, and the offline optimization performed by the signal transmitting device (base station) includes model generation and optimization and wireless environment map generation, while the online measurement functions performed by the signal receiving device (terminal) include wireless environment perception mode and wireless channel detection mode, and the offline optimization performed by the signal receiving device (terminal) includes model generation and optimization. Schematically, Figure 3 (a) with Figure 3 In (b), the application interfaces for inputting and obtaining the digital twin map and terminal location information are different. Figure 3 The device components with similar functional examples also belong to the invention scope of the embodiments of the present invention.

[0055] An information interaction process of a digital twin channel modeling provided by an embodiment of the present invention is as follows: Figure 4As shown, the specific description is as follows: the information interaction entity mainly includes the cloud, base station and terminal as the network management control center, and the commands involved include multiple mode control commands, such as (as an example but not limited to) entering the wireless environment perception mode command, entering the wireless channel detection mode command, entering the communication mode command, entering the positioning mode command and entering the control mode command and conventional commands for information acquisition. First, the cloud will issue conventional commands and provide initial terminal information and digital twin maps, and activate the target base station that needs to enter the working state on demand; then the base station issues a command to enter the wireless environment perception mode, the terminal performs environmental perception, and the obtained environmental interference and other information are sent to the base station; then the base station issues a wireless channel detection mode command and transmits a detection signal, the terminal completes the channel detection and generates a preliminary distributed channel model, and sends the obtained results to the base station; then the cloud issues a command to enter the positioning mode, the base station performs terminal positioning operations, and generates a wireless environment map at the same time; the cloud issues a command to enter the communication mode, the base station uploads the terminal positioning information and the generated wireless environment map to the cloud, and the cloud performs positioning accuracy detection. If it does not meet the performance requirements, the cloud issues a command to enter the control mode and transmits feedback information to the base station, and the base station optimizes the detection signal according to the optimization instruction. The above operation process is then repeated to obtain a gradually optimized wireless channel model and an updated wireless environment map.

[0056] The entire system of the proposed multi-mode fusion digital twin channel modeling method mainly includes: a mobile terminal (which may have ranging and positioning functions); an access point or base station (device) that supports the functions of the embodiments of the present invention; and a cloud with high-performance processing and computing capabilities.

[0057] Embodiment 2

[0058] Wireless channel sensing and detection simulation example description

[0059] In this example, some functions of wireless channel sensing and measurement are mainly used as examples. In this embodiment, ultra-wide band (UWB) signals are used as examples of channel detection signals, but the embodiments of the present invention are not limited to UWB signals. Figure 5 This is a block diagram of the designed UWB channel detection signal generation, reception and detection result analysis. The generated pulse signal is modulated by time-hopping pulse position modulation (TH-PPM) to obtain the UWB channel detection signal. The transmitted detection signal is transmitted through the wireless channel, through the RF unit and baseband unit, and reaches the processor to complete the signal reception and data processing process, thereby obtaining the channel impulse response. Finally, the relevant channel parameters can be generated and analyzed based on the obtained results (for example, multipath, delay domain characteristics, etc.).

[0060] UWB signals are generally in the form of Gaussian pulse waveforms, and their basic Gaussian pulse time domain expression is:

[0061]

[0062] where σ 2 is the variance of the Gaussian pulse signal, let α 2 =4πσ 2 is the shape factor of the Gaussian pulse, then

[0063] In carrier-free UWB communications, the transmitting and receiving antennas are often modeled as derivative operations. Therefore, the transmission can be the first-order derivative of a Gaussian pulse (i.e., a first-order Gaussian pulse), and the output waveform of the transmission is expressed as:

[0064]

[0065] In this example, the pulse modulation adopts the commonly used pulse position modulation (PPM), which performs pulse position modulation on the transmitted data information according to the modulation code. The modulation formula is:

[0066]

[0067] Where T f is the pulse period. In practical applications, in order to minimize the interference to existing communication systems or signals caused by the use of ultra-wideband signals, there are certain restrictions on the power spectrum density of ultra-wideband signals. However, the actual source sequence does not necessarily meet the conditions of random and equal probability distribution. The discrete peaks of the power spectrum density of the generated signal will inevitably violate this requirement. Therefore, it is necessary to spread the source sequence to achieve sequence scrambling, so that the spectrum line is smoother, so that the signal spectrum distribution meets the specifications. In this example, the commonly used time-hopping (TH) spread spectrum method is adopted. Time-hopping spread spectrum is generally not used alone, but is usually combined with pulse position modulation technology. The signal model (transmitted signal expression) of TH-PPM modulation is:

[0068]

[0069] Where T c is the chip period, d is the binary information data, and the subscript [j / N s ] represents the corresponding data bit, c j is the time-hopping spread spectrum sequence code, with a period of N s , δ is the PPM modulation pulse time shift.

[0070] Since the duration of UWB signals in the time domain is extremely short, the multipath components generated by reflections during the propagation of the signal will be delayed and attenuated, and will appear as a series of pulse components at the receiving end. According to the IEEE 802.15.4a standard, the ultra-wideband channel can be represented by a time-varying impulse response through the SV (Saleh-Valenzuela) model:

[0071]

[0072] Among them, α k,l is the coefficient of the kth multipath component (MPC) of the lth cluster, T l is the delay of the lth cluster, τ k,l is the additional delay of the kth MPC relative to the arrival time of the lth cluster, and the phase φ k,l Uniformly distributed in (0,2π).

[0073] The characteristics of UWB wireless channels can be described by the mean excess delay, the root mean square (RMS) delay spread, and the number of effective multipath components. The excess delay can reflect the concentration of multipath energy in the power delay curve. The RMS delay spread indicates the effective duration of the channel pulse response. If the time interval, i.e., the period, of the pulses transmitted by the channel transmitter is less than this value, there will be inter-symbol interference. The effective multipath components can reflect the multipath propagation of the environment under study. When analyzing the characteristics of multipath propagation, the multipath power delay curve within the observation time can be obtained first (assuming that the channel is stable within the observation time and the observation time is greater than the average pulse repetition period):

[0074]

[0075] The power delay distribution may be averaged in time or in space when the terminal moves. Then the average additional delay (the first moment of the power delay distribution) is expressed as:

[0076]

[0077] Then the RMS delay spread (the second-order moment of the power delay profile) is expressed as:

[0078]

[0079] The number of multipath components can be determined by the threshold of the multipath component strength, that is, the multipath components that meet the following conditions can be considered as valid multipath components:

[0080]

[0081] Among them, Smax_np is the strongest path power value in the power delay curve, S thr_mp The judgment threshold.

[0082] The simulation parameter settings are detailed in Table 1. Waveform reception analysis and channel detection analysis of UWB detection signals. The structure of the designed UWB channel detection signal is as follows: Figure 6 and Figure 7 As shown in (a), it includes two transmission symbols. The entire symbol duration is 100ns. Each symbol contains 25 code chips and 4 pulse waveforms. The system delay resolution of channel measurement is related to the measurement bandwidth (sweep bandwidth) and is 0.83ns (Δt = 1 / B f , B f is the measurement bandwidth). If the positioning performance of the system is studied, the distance resolution of the positioning system is 0.25m (Δr = Δtc, c is the speed of light). Since the sweep bandwidth is 1.2GHz and the sampling frequency of the time domain pulse signal is set to 100GSPS, the sweep interval is 12MHz, and the corresponding maximum detection capability (maximum multipath delay) is 83.3ns. For periodic sequence signals, when performing channel measurement, in order not to cause mixed superposition of reflected waves, the period of the transmitted detection signal sequence must be greater than the maximum multipath delay of the multipath channel experienced. Therefore, the parameters set in the simulation meet the requirements.

[0083] Table 1 Simulation parameter description

[0084]

[0085]

[0086] In the embodiment of the present invention, the theoretical delay resolution is 0.83ns. In order to facilitate the comparison of detection results of simulation analysis, a three-path channel model is set to be used. The set three-path delay and corresponding power are shown in Table 2.

[0087] Table 2 Comparison of channel detection results (PDP analysis)

[0088]

[0089] According to the relationship between the power delay curve and the channel impulse response, the channel impulse response amplitude of the corresponding path can be obtained, and the designed UWB detection signal is passed through the channel with the channel impulse response characteristics to complete the channel detection analysis process.

[0090] 1) Time domain analysis

[0091] The time domain measurement method can intuitively reflect the characteristics of UWB time domain signals, and the measurement results are relatively accurate. However, its calculation process is relatively complicated. In this part, the signal received by the terminal is filtered through the correlator operation (converting the pulse sequence into a baseband signal), the time domain windowing Kaiser, and the finite impulse response filter (Finite Impulse Response, FIR) to obtain the received signal waveform measured in the time domain, and then the received signal is deconvolved by the CLEAN algorithm to obtain the channel impulse response. It should be noted that when the environmental scatterers are simple and the multipath phenomenon is not serious, the windowing function and FIR filter steps can be omitted.

[0092] Theoretically, the received signal after the channel transmission can be obtained by convolving the transmitted signal with the channel impulse response. Assuming that the received signal after the channel is represented as y(t), it can be expressed as

[0093] y(t)=s TH―PPM (t)*h(t)+n(t) (10)

[0094] The signal y(t) is y′(t) after time domain windowing and FIR filter filtering. As an example, h(t) can be obtained by the CLEAN deconvolution method, but it is not excluded that h(t) can be obtained by deconvolution in other ways. By deconvolving the signal y′(t) through the CLEAN algorithm, the impulse response of the channel can be obtained. The CLEAN algorithm here can be briefly described as follows: the amplitude characteristic of the transmitted detection signal (wherein the template signal can also be obtained by cutting the strongest signal waveform from the received signal, for convenience, the amplitude of the transmitted signal waveform is used here) is used as the template signal s(t), and its autocorrelation function Rss(t) is first calculated and its absolute peak value and corresponding time position are obtained, and then the cross-correlation function Rsy(t) between the template signal s(t) and the detection received signal is extracted, and the absolute peak value and corresponding time position of Rsy(t) are obtained, and the peak value of Rsy(t) is divided by the peak value of Rss(t), and multiplied and iterated with the template signal corresponding to the time slice, and the amplitude and delay value corresponding to the impulse response are preliminarily obtained, and finally the time zero point of the impulse response at this time is set (wherein the time zero point is to set the first multipath time arriving in the extracted impulse response to zero, and the subsequent multipath time is based on the multipath time of the first path) to obtain the final actual channel impulse response.

[0095] After the transmitted UWB detection signal is transmitted through the wireless channel, the time domain waveform of the received signal is as follows: Figure 7As shown in (b), it can be seen from the figure that the UWB detection signal can be detected normally, the amplitude of the pulse signal is slightly attenuated, and due to the multipath effect, the UWB detection signal shows a delay expansion phenomenon after passing through the channel. The energy pulse signal has a certain dispersion in time, and the time delay between the corresponding single pulses is about 0.1ns. For the power delay spectrum analysis of channel detection, for the convenience of analysis, only the three-path situation is considered. When the interception threshold of multipath resolution is set to -30dB, the channel detection results are as follows: Figure 8 As shown in Table 2, compared with the pre-set parameter values, the time delays corresponding to the multipaths are basically consistent, which are 0ns, 0.83ns, and 1.67ns respectively, while the relative power has a slight error. The relative power error of the first path is about 0.05dB, the relative power error of the second path is about 0.05dB, and the relative power error of the third path is 0.04dB. The comparison results of the power delay spectrum analysis of channel detection are good.

[0096] 2) Frequency domain analysis

[0097] In this part, the frequency domain analysis is used to obtain the channel frequency domain response first, and then the time domain channel impulse response, so as to perform power delay spectrum analysis. In this frequency domain analysis process, no complicated deconvolution operation and other steps are required, which is convenient to implement. However, in actual channel measurement, there will be problems of inaccurate measurement over long distances.

[0098] Theoretically, the product of the frequency domain response of the transmitted signal and the frequency domain response of the channel is the frequency domain response of the received signal after the UWB detection signal is transmitted through the channel. Assuming that the received signal after the channel is represented as Y(f), it can be expressed as

[0099] Y(f)=S TH―PPM (f)H(f)+N(f) (10)

[0100] Among them, in the simulation, S TH―PPM (f) and Y(f) can perform discrete Fourier transform on the time domain waveform signal to obtain a one-sided power spectrum. Then, mathematical operations can be performed on the received signal to directly obtain the channel frequency domain response. Discrete Fourier transform can be performed on the channel frequency domain response to obtain the time domain channel impulse response and perform power delay spectrum analysis.

[0101] For the power delay spectrum analysis of channel detection, for the convenience of analysis, only the three-path situation is considered. When the interception threshold of multipath resolution is set to -30dB, the channel detection results are as follows Fig. 9As shown in Table 2, compared with the pre-set parameter values, there is only a 0.01ns error in the delay corresponding to the multipath, which are 0ns, 0.82ns, and 1.66ns respectively, while the relative power error is slightly larger than the result of time domain analysis, and the relative power error of the second path is about 0.87dB, and the relative power difference of the third path is 1.04dB. The power delay spectrum analysis comparison result of channel detection is better and easy to implement.

[0102] Wireless channel sensing and detection test and verification

[0103] As an example, a measurement system is built in a laboratory environment, and channel parameters are extracted from the acquired measurement data. Fig.10 As shown in FIG. 1 , it is a connection diagram of the constructed two-path model measurement system, in which the transmission signal is generated by a UWB signal simulator as a complete UWB signal in accordance with the IEEE 802.15.4a standard. The frame structure includes four main parts: synchronization frame (Synchronization field, SYNC), preamble (Start-of-Frame Delimiter field, SFD), data frame header (PHY header, PHR), and data load (PHY payload). See FIG. Fig.11 , the transmitter related parameters are shown in Table 3.

[0104] Table 3. UWB signal simulator transmission signal information

[0105] Transmit signal information illustrate frequency 3494.4MHz bandwidth 499.2MHz power -10dBm Frame length 150us Frame interval 80us Modulation BPSK PHY Protocol 802.15.4 Data Rate 6.81Mb / s

[0106] The UWB channel detection signal passes through the wired model channel of the two-way signal, and the data is collected by the data acquisition device with a sampling rate of 245.76MS / s*8 at the receiving end. After the measurement, the 8-way collected data is spliced ​​and intercepted, and the waveform of the recovered one frame of the received signal is as follows Fig.12 (a) As shown. Since the transmission lines of the two-path model (transmission line 1 is 0.5m, transmission line 2 is 3.5m) are filled with foamed polyethylene coaxial cable (signal transmission rate 0.81c~1c, where c is the speed of light), theoretically, the relative delay of a 3m distance difference is about 10ns~12.3ns. When the time domain analysis method is used for the collected data, the results are as follows Fig.12As shown in (b), the results of the power delay spectrum analysis are consistent with the results of the two-path model. In addition, the two paths differ by 11.6984ns in delay analysis, and the relative power differs by 1.05dB, which is in line with expectations. The noise floor is calculated using the natural noise floor theory formula to be -83.93dBm, and the noise factor NF is 3.0856dB (NF = 10lg (1 + T / T0), T0 is the absolute temperature (290K), and the room temperature T is 27 degrees Celsius, about 299.15K). The signal-to-noise ratio of the two-path model measurement result is calculated to be 67.97dB.

[0107] In order to improve the data processing method from the perspective of comprehensive performance such as accuracy, computational complexity and storage capacity, so as to better apply it in practice. Therefore, data interception was performed in different situations corresponding to the frame structure of the transmitted UWB channel detection signal, and then the time domain method was used for analysis. Various results are shown in Table 4. From the table results, the results of intercepting the preamble code (SFD) and the data frame header (PHR) data are basically consistent with the processing results of a complete frame signal. Therefore, considering the accuracy, computational complexity and storage of the comprehensive processing results, intercepting the data frame header (PHR) for channel parameter extraction is more in line with practical applications.

[0108] Table 4. Comprehensive performance analysis and comparison of data processing

[0109]

[0110] In summary, the embodiment of the present invention designs a digital twin channel modeling method, which can perform distributed online channel measurement. Through the call of multiple working modes, the signal transmitted by the signal transceiver can perform real-time environmental perception and channel measurement at the distributed signal transceiver (terminal), and the acquired multi-scenario data can efficiently perform digital twin wireless channel modeling of the scene. The present invention can be used in different application scenarios and can save a certain amount of manpower, material resources and financial resources.

[0111] Those skilled in the art can understand that the accompanying drawings are only schematic diagrams of an embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0112] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention or certain parts of the embodiments.

[0113] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0114] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A digital twin channel modeling method, characterized in that: include: Perform online measurements through base stations and terminals to obtain channel measurement data; Performing channel modeling and model optimization of the propagation environment based on the channel measurement data by the base station and the terminal; According to the channel modeling and model optimization results, a digital twin channel model for various environments is comprehensively implemented based on the four major twin elements of mapping, data, model, and synchronization, and the digital twin channel model is used to realize the interactive mapping of physical channels and digital virtual channels; The online measurement through the base station and the terminal to obtain the channel measurement data includes: Construct a channel measurement system including a cloud, a signal transmitter, a signal receiver, a data storage module and information input interfaces of each part. The signal transmitter transmits a channel detection signal. After the channel detection signal is propagated through the channel, online measurement of multiple working mode fusion or coordinated call is performed. The baseband data at the port of the signal receiver is converted by A / D to obtain channel measurement data. The channel measurement data includes power domain and delay domain feature data, completes environmental perception and measurement, and stores the channel measurement data in the data storage module. The multiple working modes include wireless environment perception mode, wireless channel detection mode, communication mode, positioning mode and control mode. The wireless environment perception mode is to perceive the communication conditions, noise interference and overall system performance of the surrounding environment; the wireless channel detection mode is to measure and analyze the channel status and channel characteristics; the communication mode is a working mode in which the communication terminal selectively sends and receives signals after connecting to multiple base stations; the positioning mode is to determine the terminal position through the transmission and reception signal information of the signal transceiver, and transmit and share it to other terminals as needed, so as to obtain and share the terminal position information; the control mode is to integrate the information processed by the local base station and transmit it to the cloud for centralized processing to obtain a digital twin channel model for global information display, and perform partial command control on the base station; The channel modeling and model optimization of the propagation environment based on the channel measurement data by the base station and the terminal includes: The offline optimization unit includes a model generation and optimization module and a wireless environment map generation module. The model generation and optimization module generates a time-varying channel model of the corresponding scene based on the environmental perception and channel measurement data obtained by online measurement, as well as the propagation characteristics of the detection signal itself and the environmental interference information. The online measurement process continuously performs channel measurement and data acquisition, and updates the time-varying channel model. The wireless environment map generation module generates a wireless environment map of the environment based on the time-varying channel model. The wireless environment map includes: scene information with scene characteristics, network and system layer information containing network topology and system deployment, transmission channel information containing interference distribution and communication breakpoint location, and information and feedback information of each radio frequency and receiving transceiver. The digital twin channel model of various environments is comprehensively realized based on the four twin elements of mapping, data, model, and synchronization according to the channel modeling and model optimization results, and the interactive mapping of physical channels and digital virtual channels is realized by using the digital twin channel model, including: The channel modeling and model optimization results of the propagation environment comprehensively realize the digital twin channel model of various environments in mapping, data, model and synchronous twin elements. In the data part, the digital twin channel model obtains channel measurement data through online channel measurement and data acquisition functions, and updates the relevant model data in different scenarios by using the migration function in offline optimization; the twin channel data obtained in the model part is represented by offline optimized modeling and simulation to obtain the twin channel model; the wireless environment map generated in the mapping part reflects the relevant characteristics of the actual physical channel, realizing the mapping of physical channels and digital channels; in terms of synchronization, the channel characteristics of the wireless environment in the virtual world and the digital world are synchronized.

2. The method according to claim 1, characterized in that The information interaction process of the channel measurement system includes: The cloud sends out routine commands and provides initial terminal information and digital twin maps, activates target base stations that need to enter working status as needed, and the base station sends out a command to enter wireless environment perception mode. The terminal performs environmental perception and sends the measured environmental interference information to the base station. The base station issues a wireless channel detection mode command and transmits a detection signal. The terminal completes channel detection and generates a preliminary distributed channel model, and sends the result to the base station. The cloud sends out a command to enter positioning mode, and the base station performs terminal positioning operations and generates a wireless environment map at the same time. The cloud sends out a command to enter communication mode, and the base station uploads the terminal positioning information and the generated wireless environment map to the cloud. The cloud performs positioning accuracy detection. If it does not meet the performance requirements, the cloud sends out a command to enter control mode and transmits feedback information to the base station. The base station optimizes the detection signal according to the optimization instruction, and then repeats the above operation process to obtain a gradually optimized wireless channel model and an updated wireless environment map.

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