Sensory channel modeling method and device and storage medium

Abstract

The invention relates to a common sensing channel modeling method and device and a storage medium. The method comprises the following steps of: setting a random quantity adopted in the process of modeling a common sensing channel under a plurality of continuous transmission time intervals (TTI) as a fixed value; in a starting TTI, channel coefficients of a first echo cluster and a second echo cluster in the starting TTI are generated based on the fixed value, the first echo cluster represents an echo cluster corresponding to a motion sensing target, and the second echo cluster represents an echo cluster corresponding to an environment scatterer; and in a non-starting TTI, generating channel coefficients of the first echo cluster and the second echo cluster in the current TTI based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI. By adopting the method, the modeling efficiency of the sensing channel under the continuous time can be improved.

Description

[0001] This application claims priority to Chinese patent application No. 202410198816.3, filed on February 22, 2024, entitled “Synesthesia Channel Modeling Method, Device and Storage Medium,” the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present application relates to the field of communication technology, and in particular to a synaesthesia channel modeling method, device, and storage medium. Background Art

[0003] In the synaesthesia integrated channel modeling process, the channel coefficient of the perceived channel echo only represents the modeling value at the current moment. In the case of multiple consecutive TTIs (Transmission Time Intervals), each TTI needs to be modeled separately.

[0004] Traditional technologies require the entire perceptual channel modeling process to be performed once per TTI. Due to the influence of multiple random variables, this can easily lead to noticeable channel variations between adjacent TTIs, resulting in significant instantaneous changes in the perceptual environment. Furthermore, over long durations, the modeling process for large-scale and small-scale parameters, as well as channel coefficients, must be repeated for each TTI, making the calculation process repetitive and complex. Summary of the Invention

[0005] Based on this, it is necessary to provide a synaesthesia channel modeling method, device and storage medium to address the above technical problems, which can improve the modeling efficiency of the synaesthesia channel in continuous time.

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

[0007] The random amount used in the synaesthesia channel modeling process under multiple consecutive transmission time intervals TTI is set to a fixed value;

[0008] In the starting TTI, the channel coefficients of the first echo cluster and the second echo cluster in the starting TTI are generated based on fixed values. The first echo cluster represents the echo cluster corresponding to the motion perception target, and the second echo cluster represents the echo cluster corresponding to the environmental scatterer.

[0009] In a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI are generated based on a fixed value and a channel coefficient of the second echo cluster in a starting TTI.

[0010] In one embodiment, in a non-starting TTI, generating channel coefficients of the first echo cluster and the second echo cluster in the current TTI based on a fixed value and a channel coefficient of the second echo cluster in the starting TTI includes:

[0011] In a non-starting TTI, generating a channel coefficient of the first echo cluster in the current TTI based on a fixed value;

[0012] The channel coefficient of the second echo cluster in the starting TTI is determined as the channel coefficient of the second echo cluster in the current TTI.

[0013] In one embodiment, the random quantity includes at least an elevation angle, a horizontal angle, a cross-polarization power ratio, and an initialized random angle.

[0014] In one embodiment, the arrangement order of the first echo cluster and the second echo cluster in the start TTI is the same as the arrangement order of the first echo cluster and the second echo cluster in the non-start TTI.

[0015] In one embodiment, in a non-starting TTI, generating channel coefficients of the first echo cluster and the second echo cluster in the current TTI based on a fixed value and a channel coefficient of the second echo cluster in the starting TTI includes:

[0016] In a non-starting TTI, determining whether the number of TTIs in which the channel coefficients have been generated has reached a preset value;

[0017] In a case where the preset value is not reached, the channel coefficients of the first echo cluster and the second echo cluster in the current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

[0018] In a second aspect, the present application further provides a synaesthesia channel modeling device, comprising a memory, a transceiver, and a processor; the memory is configured to store a computer program; the transceiver is configured to transmit and receive data under the control of the processor; and the processor is configured to read the computer program in the memory and perform the following operations:

[0019] The random amount used in the synaesthesia channel modeling process under multiple consecutive transmission time intervals TTI is set to a fixed value;

[0020] In the starting TTI, the channel coefficients of the first echo cluster and the second echo cluster in the starting TTI are generated based on fixed values. The first echo cluster represents the echo cluster corresponding to the motion perception target, and the second echo cluster represents the echo cluster corresponding to the environmental scatterer.

[0021] In a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI are generated based on a fixed value and a channel coefficient of the second echo cluster in a starting TTI.

[0022] In one embodiment, in a non-starting TTI, generating channel coefficients of the first echo cluster and the second echo cluster in the current TTI based on a fixed value and a channel coefficient of the second echo cluster in the starting TTI specifically includes:

[0023] In a non-starting TTI, generating a channel coefficient of the first echo cluster in the current TTI based on a fixed value;

[0024] The channel coefficient of the second echo cluster in the starting TTI is determined as the channel coefficient of the second echo cluster in the current TTI.

[0025] In one embodiment, the random quantity includes at least an elevation angle, a horizontal angle, a cross-polarization power ratio, and an initialized random angle.

[0026] In one embodiment, the arrangement order of the first echo cluster and the second echo cluster in the start TTI is the same as the arrangement order of the first echo cluster and the second echo cluster in the non-start TTI.

[0027] In one embodiment, in a non-starting TTI, generating channel coefficients of the first echo cluster and the second echo cluster in the current TTI based on a fixed value and a channel coefficient of the second echo cluster in the starting TTI specifically includes:

[0028] In a non-starting TTI, determining whether the number of TTIs in which the channel coefficients have been generated has reached a preset value;

[0029] In a case where the preset value is not reached, the channel coefficients of the first echo cluster and the second echo cluster in the current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

[0030] In a third aspect, the present application further provides a synaesthesia channel modeling device, the device comprising:

[0031] A setting unit, configured to set a random amount used in the synaesthesia channel modeling process under a plurality of consecutive transmission time intervals TTI to a fixed value;

[0032] A first generating unit is configured to generate, in a starting TTI, channel coefficients of a first echo cluster and a second echo cluster in the starting TTI based on fixed values, where the first echo cluster represents an echo cluster corresponding to a motion sensing target, and the second echo cluster represents an echo cluster corresponding to an environmental scatterer;

[0033] The second generating unit is configured to generate, in a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI based on a fixed value and a channel coefficient of the second echo cluster in a starting TTI.

[0034] In one embodiment, the second generating unit is further configured to:

[0035] In a non-starting TTI, generating a channel coefficient of the first echo cluster in the current TTI based on a fixed value;

[0036] The channel coefficient of the second echo cluster in the starting TTI is determined as the channel coefficient of the second echo cluster in the current TTI.

[0037] In one embodiment, the random quantity includes at least an elevation angle, a horizontal angle, a cross-polarization power ratio, and an initialized random angle.

[0038] In one embodiment, the arrangement order of the first echo cluster and the second echo cluster in the start TTI is the same as the arrangement order of the first echo cluster and the second echo cluster in the non-start TTI.

[0039] In one embodiment, the second generating unit is further configured to:

[0040] In a non-starting TTI, determining whether the number of TTIs in which the channel coefficients have been generated has reached a preset value;

[0041] In a case where the preset value is not reached, the channel coefficients of the first echo cluster and the second echo cluster in the current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided in the first aspect or any one of the embodiments of the first aspect.

[0043] In a fifth aspect, the present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method provided in the first aspect or any one of the embodiments of the first aspect.

[0044] The aforementioned synaesthesia channel modeling method, apparatus, and storage medium set the random quantity used in the channel modeling process over multiple consecutive TTIs to a fixed value, thereby avoiding large instantaneous channel variations caused by large differences in random quantities over consecutive TTIs. Thus, after generating the channel coefficients for the echo cluster corresponding to the motion-sensing target and the echo cluster corresponding to the ambient scatterers at the starting TTI, the channel coefficients for the echo cluster corresponding to the ambient scatterers at non-starting TTIs can be generated based on the channel coefficients for the echo cluster corresponding to the ambient scatterers at the starting TTI. This reduces repeated modeling of the ambient scatterers, effectively simplifies the synaesthesia channel modeling process over continuous time, and improves modeling efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1A diagram showing an application environment of a synaesthesia channel modeling method in one embodiment;

[0047] Figure 2 Schematic diagram of a flow chart of a synaesthesia channel modeling method according to one embodiment;

[0048] Figure 3 Schematic diagram of a flow chart of a synaesthesia channel modeling method according to one embodiment;

[0049] Figure 4 Schematic diagram of a flow chart of a synaesthesia channel modeling method according to one embodiment;

[0050] Figure 5 is a structural block diagram of a synaesthesia channel modeling device in one embodiment;

[0051] Figure 6 FIG. 4 is a diagram showing the internal structure of a synaesthesia channel modeling device in one embodiment. DETAILED DESCRIPTION

[0052] In the embodiments of this application, the term "and / or" describes the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0053] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0054] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0055] Synaesthesia integration is the integration of communication and perception, fusing the two functions of communication and perception. Synaesthesia integration channels simultaneously possess both communication and perception functions. Synaesthesia integration can be simply referred to as synaesthesia, and synaesthesia integration channels can be simply referred to as synaesthesia channels.

[0056] Depending on whether the transmitter and receiver are the same device, the integrated interawareness network architecture can be divided into single-station sensing and dual-station sensing. Single-station sensing means that the same device can both send the sensing signal and receive the echo reflected from the sensing target and perform sensing calculations. Dual-station sensing means that one device sends the sensing signal and another device receives the echo reflected from the sensing target and performs sensing calculations.

[0057] The embodiments of the present application provide a method and apparatus for modeling a synaesthesia channel, which sets the random quantity used in the channel modeling process under multiple consecutive TTIs to a fixed value, and generates the channel coefficients of the echo cluster corresponding to the environmental scatterer in the non-starting TTI based on the channel coefficients of the echo cluster corresponding to the environmental scatterer in the starting TTI, thereby reducing the repeated modeling of the environmental scatterer, effectively simplifying the modeling process of the synaesthesia channel under continuous time, and improving modeling efficiency.

[0058] Among them, the method and the device are based on the same application concept. Since the principles of solving problems by the method and the device are similar, the implementation of the device and the method can refer to each other, and the repeated parts will not be repeated.

[0059] The synaesthesia channel modeling method provided in the embodiments of the present application can be applied to a single-station perception line of sight (LOS) echo mode, a single-station perception non-line of sight (NLOS) echo mode, a dual-station perception LOS echo mode, and a dual-station perception NLOS mode. In the embodiments of the present application, the synaesthesia channel modeling method is described using the single-station perception LOS echo mode as an example. The synaesthesia channel modeling method for other modes can refer to the synaesthesia channel modeling method for the single-station perception LOS echo mode, and will not be repeated here.

[0060] The synaesthesia channel modeling method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown in the figure, in the single-station sensing line-of-sight echo mode, the sensing transmitter and the sensing receiver are the same device, which is called the sensing transceiver. Figure 1 As shown, the sensing transceiver sends a sensing signal to the sensing target and receives an echo reflected by the sensing target. The sensing transceiver can be a terminal device or a network device. The sensing target can be an object such as a person, vehicle, animal, or building. The sensing target can be a moving object or a stationary object. The embodiments of the present application do not limit the sensing target.

[0061] The technical solutions provided in the embodiments of the present application can be applied to a variety of systems. For example, applicable systems may include Long Term Evolution (LTE) systems, LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, Long Term Evolution Advanced (LTE-A) systems, Universal Mobile Telecommunication System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) systems, 5G New Radio (NR) systems and their evolved communication systems. These various systems may include terminal devices and network devices. The systems may also include core network components, such as the Evolved Packet System (EPS) and the 5G System (5GS).

[0062] The terminal devices involved in the embodiments of the present application may be devices that provide voice and / or data connectivity to users, handheld devices with wireless connection capabilities, or other processing devices connected to wireless modems. In different systems, the names of terminal devices may also be different. For example, in a 5G system, the terminal device may be called User Equipment (UE). Wireless terminal devices may be USB storage devices, other personal computer memory devices, and dongles. They may also communicate with one or more core networks (CNs) via a radio access network (RAN). Wireless terminal devices may be mobile terminal devices, such as mobile phones (or "cellular" phones) and computers with mobile terminal devices. For example, they may be portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted mobile devices that exchange voice and / or data with a radio access network. For example, Personal Communication Service (PCS) phones, cordless phones, Session Initiated Protocol (SIP) phones, Wireless Local Loop (WLL) stations, Personal Digital Assistants (PDAs), personal computers, tablet computers, Machine-type Communication (MTC) terminal devices, etc. Wireless terminal devices may also be referred to as systems, subscriber units, subscriber stations, mobile stations, mobile stations, remote stations, access points, remote terminals, access terminals, user terminals, user agents, user devices, and wireless access points and routers / modems that meet the limitations of this definition, but are not limited in the embodiments of the present application.

[0063] The network device involved in the embodiments of the present application may be a base station, which may include multiple cells providing services to terminals. Depending on the specific application scenario, a base station may also be referred to as an access point, or may be a device in an access network that communicates with wireless terminal devices over the air interface through one or more sectors, or may be referred to by other names. The network device may be used to convert received air frames into and out of Internet Protocol (IP) packets, acting as a router between the wireless terminal device and the rest of the access network, which may include an Internet Protocol (IP) communication network. The network device may also coordinate the management of air interface attributes. For example, the network device involved in the embodiments of the present application may be an evolved Node B (eNB or e-NodeB) in a long-term evolution (LTE) system, a 5G base station (gNB) in a next-generation 5G network architecture, or a home evolved Node B (HeNB), a relay node, a femto base station, a pico base station, network testing equipment, etc., without limitation in the embodiments of the present application. In some network structures, network devices may include centralized unit (CU) nodes and distributed unit (DU) nodes. The centralized unit and the distributed unit may also be geographically separated.

[0064] The terminal device in the embodiment of the present application sends relevant information or similar descriptions to the network side device, which only indicates that the terminal device sends the relevant information in the form of a wireless signal, and its intended recipient is the network device. The network device can obtain the relevant information by receiving the wireless signal.

[0065] In an exemplary embodiment, Figure 2 As shown in the figure, a synaesthesia channel modeling method is provided, which is applied to Figure 1 The sensor receiving end in FIG is used as an example to illustrate. Figure 2 As shown, the method may include:

[0066] Step S201 : setting the random amount used in the synaesthesia channel modeling process in a plurality of consecutive TTIs to a fixed value.

[0067] The synaesthesia channel modeling process involves a large amount of random variables. If the random variables vary significantly across multiple consecutive TTIs, the channel coefficients can vary significantly over a short period of time. In this step, the random variables used in the synaesthesia channel modeling process over multiple consecutive TTIs are set to a fixed value. This ensures that the random variables generated over a short period of time remain consistent across consecutive TTIs, thereby significantly reducing the impact of the random variables on channel coefficient variations. In one example, the random variables used in the synaesthesia channel modeling process include at least the elevation angle, horizontal angle, cross-polarization power ratio, and an initialized random angle.

[0068] In one possible implementation, a random number seed can be fixed in the starting TTI so that the initial value of the random quantity generated each time is the same, thereby ensuring that the random quantity used in the synaesthesia channel modeling process remains a constant fixed value over multiple consecutive TTIs. In another possible implementation, each random quantity can be set to a constant fixed value in each TTI. It should be noted that the specific value of the fixed value is not limited in the embodiments of the present application.

[0069] Step S202: In a starting TTI, channel coefficients of the first echo cluster and the second echo cluster in the starting TTI are generated based on fixed values.

[0070] The sensing transmitter sends a sensing signal. Upon encountering a sensing target during propagation, the sensing signal reflects back to the sensing receiver. The reflected signal received by the sensing receiver is called an echo. A reflected signal may reach the sensing receiver via multiple different transmission paths. These reflected signals that reach the sensing receiver via different transmission paths are called an echo cluster. An echo cluster consists of multiple subpaths (i.e., transmission paths).

[0071] A perception target can represent any object. It can be categorized into moving perception targets and environmental scatterers. Moving perception targets refer to moving perception targets, such as pedestrians and moving cars. Environmental scatterers refer to stationary perception targets, such as buildings and roadside trees.

[0072] The first echo cluster may represent an echo cluster corresponding to a motion sensing target, i.e., an echo cluster reflected by the motion sensing target after the sensing signal reaches the motion sensing target. The second echo cluster may represent an echo cluster corresponding to an environmental scatterer, i.e., an echo cluster reflected by the environmental scatterer after the sensing signal reaches the environmental scatterer.

[0073] It should be noted that the number of echo clusters corresponding to each perception target may be one or more. That is, the number of first echo clusters may be one or more. The number of second echo clusters may also be one or more.

[0074] In this step, the sensing transceiver can generate signal coefficients for the first echo cluster at the starting TTI and channel coefficients for the second echo cluster at the starting TTI, with each random quantity set to a fixed value. Specifically, these coefficients include the channel coefficients for the echo clusters corresponding to each motion sensing target at the starting TTI and the channel coefficients for the echo clusters corresponding to each environmental scatterer at the starting TTI. In the starting TTI, the method for generating the channel coefficients for the first echo cluster is the same as the method for generating the channel coefficients for the second echo cluster.

[0075] In an example, the channel coefficient of any echo cluster (the first echo cluster or the second echo cluster) at the start TTI may be determined by using Formula 1.

[0076]

[0077] Formula 1

[0078] in, It represents the channel coefficient of an echo cluster at sampling time t in the single-station sensing LOS echo mode. Represents the sensing receiving antenna, Represents the sensing transmitting antenna. In the case of single-station sensing, the sensing receiving end and the sensing transmitting end are the same device, which can be called the sensing transceiver. M represents the number of subpaths in each echo cluster, and m represents the mth subpath in the echo cluster.

[0079] represents the pitch angle, represents the horizontal angle, the parameters with β subscript are the channel parameters from the sensing target to the sensing receiver, m represents the mth subpath in the echo cluster, represents the arrival zenith angle, represents the arrival azimuth. Therefore, It represents the pitch angle of the arrival zenith angle of the mth subpath from the perception target to the perception receiver. The horizontal angle representing the arrival azimuth of the mth subpath from the sensing target to the sensing receiver.

[0080] represents the directional pattern of the receiving antenna, represents the pitch angle, represents the horizontal angle. Therefore, Represents the directional pattern of the elevation angle of the receiving antenna, The directional pattern representing the horizontal angle of the receiving antenna, Indicates that the parameter is and The direction pattern of the receiving antenna’s elevation angle is perceived under the condition of Indicates that the parameter is and The azimuth pattern of the horizontal angle of the receiving antenna is perceived under the condition of . [] represents a matrix, and T represents the transpose of the matrix.

[0081] represents the random angle of initialization of the mth subpath, represents the pitch angle, represents the horizontal angle, 、 、 and Indicates the polarization antenna elevation angle of the mth subpath and horizontal angle Random initial phases under four combinations of . represents the cross-polarization power ratio of the mth subpath. exp represents the exponential function with e as the base, and j represents an imaginary number.

[0082] represents the pitch angle, represents the horizontal angle, the parameters with the α subscript are the channel parameters from the sensing transmitter to the sensing target, m represents the mth subpath in the echo cluster, ZOD represents the departure zenith angle, and AOD represents the departure azimuth angle. Therefore, represents the pitch angle of the mth subpath from the sensing transmitter to the sensing target, The horizontal angle representing the departure azimuth of the mth subpath from the sensing transmitter to the sensing target.

[0083] represents the directional pattern of the sensing transmitting antenna, represents the pitch angle, represents the horizontal angle. Therefore, Represents the directional pattern of the elevation angle of the transmitting antenna, The directional pattern representing the horizontal angle of the transmitting antenna, Indicates that the parameter is and In this case, the directional pattern of the receiving antenna’s elevation angle is perceived. Indicates that the parameter is and The directional pattern of the horizontal angle of the receiving antenna is perceived in this case.

[0084] represents the sending vector of the sensing transmitter, represents the receiving vector of the perceived target, represents the sending vector of the sensing target, Indicates the receiving vector of the sensing receiver. For single-station mode, . represents the position vector of the sensing transmitting antenna, Represents the position vector of the sensing receiving antenna. Indicates the wavelength of the perceived signal. Indicates the propagation speed of the perception signal.

[0085] In the embodiments of this application, 、 、 and is a fixed value.

[0086] When the sampling time t is in the starting TTI, the channel coefficient of any echo cluster in the starting TTI can be obtained by formula 1.

[0087] For motion sensing targets, the channel coefficients at different sampling times t remain continuous due to the Doppler effect of continuous motion; for environmental scatterers, the channel coefficients at different sampling times t are the same due to the absence of Doppler effect at stationary state.

[0088] Step S203 : In a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in the current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

[0089] Because the sensing transceiver sets the random variable to a fixed value, the random quantity remains consistent over a short period of time in consecutive TTIs, eliminating the impact of the random quantity on the channel coefficient. Furthermore, since the ambient scatterers remain stationary and there is no Doppler effect, the channel coefficients of the second echo cluster (i.e., the echo cluster corresponding to the ambient scatterers) remain the same in each TTI. Therefore, the sensing transceiver can reuse the channel coefficients of the second echo cluster in the starting TTI in non-starting TTIs. That is, the channel coefficients of the second echo cluster in the starting TTI are used as the channel coefficients of the second echo cluster in non-starting TTIs.

[0090] In this way, in the non-starting TTI, it is equivalent to sensing the channel coefficient of the echo cluster corresponding to the known environmental scatterer at the transceiver end in the current TTI, and the transceiver end regenerates the channel coefficient of the echo cluster corresponding to the motion sensing target in the current TTI, and the channel coefficients of the first echo cluster and the second echo cluster in the current TTI can be obtained.

[0091] In one possible implementation, step S203 may include: generating, in a non-starting TTI, a channel coefficient of the first echo cluster in the current TTI based on a fixed value, and determining the channel coefficient of the second echo cluster in the starting TTI as the channel coefficient of the second echo cluster in the current TTI. In this way, the channel coefficients of the first echo cluster and the second echo cluster in the non-starting TTI are obtained.

[0092] The generation method of the channel coefficient of the first echo cluster in the non-starting TTI can refer to the generation method of the channel coefficient of the first echo cluster in the starting TTI, and specifically refer to Formula 1. The difference between the two is the value of t, which will not be repeated here.

[0093] It can be seen that in the embodiment of the present application, the channel coefficients of the second echo cluster in the starting TTI can be reused as the channel coefficients of the second echo cluster in the non-starting TTI. In this way, there is no need to repeatedly generate the channel coefficients in the non-starting TTI, which saves resources and improves efficiency.

[0094] In an embodiment of the present application, the arrangement order of the first echo cluster and the second echo cluster in the starting TTI is the same as the arrangement order of the first echo cluster and the second echo cluster in the non-starting TTI. For example, assuming there are 10 echo clusters, and in the starting TTI, the first echo cluster is the second echo cluster and the fourth echo cluster, then in the non-starting TTI, the first echo cluster is also the second echo cluster and the fourth echo cluster. Therefore, the sensing transceiver can distinguish the first echo cluster and the second echo cluster of each TTI based on the arrangement order of the first echo cluster and the second echo cluster, thereby determining which echo clusters need to regenerate channel coefficients and which echo clusters can continue to use channel coefficients in the non-starting TTI.

[0095] In one example, for each TTI, the sensing transceiver can use a matrix to store the channel coefficients of each echo cluster in that TTI, where each element position in the matrix corresponds to an echo cluster. In different TTIs, the sensing transceiver can store the channel coefficients of the echo cluster corresponding to the same sensing target in the same element position of the matrix.

[0096] Assume there are Q echo clusters, where the first echo cluster is , , then the remaining QW echo clusters are the second echo clusters.

[0097] It can be understood that the method of generating the channel coefficient of each echo cluster in each non-starting TTI is the same, and will not be repeated here.

[0098] The aforementioned synaesthesia channel modeling method sets the random quantity used in the channel modeling process over multiple consecutive TTIs to a fixed value, thereby avoiding large instantaneous channel variations caused by large differences in the random quantity over consecutive TTIs. Thus, after generating the channel coefficients for the echo cluster corresponding to the motion-sensing target and the echo cluster corresponding to the ambient scatterer in the starting TTI, the channel coefficients for the echo cluster corresponding to the ambient scatterer in non-starting TTIs can be generated based on the channel coefficients for the echo cluster corresponding to the ambient scatterer in the starting TTI. This reduces repeated modeling of the ambient scatterer, effectively simplifies the synaesthesia channel modeling process over continuous time, and improves modeling efficiency.

[0099] In one possible implementation, step S203 may include: in a non-starting TTI, determining whether the number of TTIs for which channel coefficients have been generated reaches a preset value; if the preset value is not reached, generating the channel coefficients of the first echo cluster and the second echo cluster in the current TTI based on a fixed value and the channel coefficients of the second echo cluster in the starting TTI.

[0100] The preset value can be used to measure whether the number of TTIs meets the continuous modeling requirement. The preset value can be pre-set as needed. If the number of TTIs for which channel coefficients have been generated reaches the preset value, it indicates that the continuous modeling requirement has been met, and no further channel coefficient generation is required, and the process can be terminated. If the number of TTIs for which channel coefficients have been generated does not reach the preset value, it indicates that the continuous modeling requirement has not been met, and the next non-starting TTI is entered to generate channel coefficients for each echo cluster.

[0101] In an exemplary embodiment, Figure 3 As shown in the figure, a synaesthesia channel modeling method is provided, which is applied to Figure 1 The sensor receiving end in FIG is used as an example to illustrate. Figure 3 As shown, the method may include:

[0102] Step S301 : setting the random amount used in the synaesthesia channel modeling process in a plurality of consecutive TTIs to a fixed value.

[0103] Step S302 : In a starting TTI, channel coefficients of the first echo cluster and the second echo cluster in the starting TTI are generated based on fixed values.

[0104] Step S303: Save the channel coefficient of the second echo cluster at the starting TTI.

[0105] Step S304 , in a non-starting TTI, determine whether the number of TTIs in which channel coefficients have been generated reaches a preset value; if so, execute step S307 , otherwise execute steps S305 and S306 .

[0106] Step S305 : Generate channel coefficients of the first echo cluster in the current TTI based on fixed values.

[0107] Step S306: Determine the channel coefficient of the second echo cluster in the starting TTI as the channel coefficient of the second echo cluster in the current TTI.

[0108] Step S307, end the process.

[0109] The above steps may refer to steps S201 to S203 and will not be repeated here.

[0110] When the perceived target is in continuous motion at different moments, if the perceived moving target and environmental scatterers are modeled once at each TTI, on the one hand, the influence of different random factors in the two adjacent modelings cannot be avoided; on the other hand, the environmental scatterers that remain stationary are modeled repeatedly multiple times. The longer the time, the more repetitions are required.

[0111] The method of synaesthesia channel modeling proposed in this application is to fix the random amount in the case of continuous TTI modeling to ensure that the random amount of multiple modeling under the same conditions is fixed, which can avoid large instantaneous channel changes corresponding to large differences in random amounts under adjacent TTIs. On the other hand, it is assumed that the environmental scatterers remain stationary and modeling is only performed once at the starting TTI. Continuous modeling of motion perception targets can effectively avoid repeated modeling of environmental scatterers and effectively simplify the continuous time modeling process.

[0112] In a possible implementation, the method further includes: determining a large-scale parameter and a small-scale parameter.

[0113] Among them, large-scale parameters include delay spread (DS), angular spread (AS), shadow fading (SF) and K factor, and small-scale parameters include arrival angle and departure angle.

[0114] In the synaesthesia channel modeling, in addition to generating the channel coefficients of each echo cluster, the large-scale parameters and small-scale parameters are also determined. Therefore, in the embodiment of the present application, the large-scale parameters, small-scale parameters and the channel coefficients of each echo cluster can be determined in each TTI, thereby completing the synaesthesia channel modeling of each TTI. Figure 4 The process of modeling the synaesthesia channel is explained.

[0115] In an exemplary embodiment, Figure 4 As shown in , a synaesthesia channel modeling method is provided. Figure 4 As shown, the synaesthesia channel modeling process may include: entering the starting TTI; setting the scene, network layout and antenna parameters; calculating path loss; calculating large-scale parameters; generating cluster delay; generating cluster power; generating small-scale parameters; generating the perception channel of the environmental scatterer; cluster neutron path pairing; generating the cross-polarization power ratio; generating the initial random phase; generating the channel coefficient of each echo cluster in the current TTI; judging whether the number of TTIs for which the channel coefficient has been generated has reached a preset value; if so, ending the process; otherwise, entering the next TTI and resetting the scene, network layout and antenna parameters.

[0116] Among them, the method of generating the channel coefficient of each echo cluster in the current TTI in the starting TTI can refer to step S202, the method of generating the channel coefficient of each echo cluster in the current TTI in the non-starting TTI can refer to step S203, the step of generating random quantities such as the cross-polarization power ratio and the initial random phase can refer to step S201, and other steps can refer to related technologies.

[0117] The method for synaesthesia channel modeling proposed in this application distinguishes between motion-sensing targets and environmental scatterers under consecutive TTIs, and assumes that the environmental scatterers remain stationary for a short period of time, with only the position of the motion-sensing targets changing. Therefore, the motion-sensing targets and environmental scatterers are modeled simultaneously in the initial TTI, and only the dynamic perception targets are modeled in the remaining TTIs, thereby simplifying the complex process of synaesthesia channel modeling under multiple consecutive TTIs.

[0118] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0119] Based on the same inventive concept, embodiments of the present application further provide a synaesthesia channel modeling device for implementing the aforementioned synaesthesia channel modeling method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more synaesthesia channel modeling device embodiments provided below can be found in the above-described limitations of the synaesthesia channel modeling method and will not be further elaborated here.

[0120] In an exemplary embodiment, Figure 5 As shown, a synaesthesia channel modeling device is provided. The synaesthesia channel modeling device 500 may include: a setting unit 501, a first generating unit 502, and a second generating unit 503, wherein:

[0121] A setting unit 501 is configured to set a random amount used in the synaesthesia channel modeling process in a plurality of consecutive transmission time intervals TTI to a fixed value;

[0122] The first generating unit 502 is configured to generate, in a starting TTI, channel coefficients of a first echo cluster and a second echo cluster in the starting TTI based on fixed values, where the first echo cluster represents an echo cluster corresponding to a motion sensing target, and the second echo cluster represents an echo cluster corresponding to an environmental scatterer;

[0123] The second generating unit 503 is configured to generate, in a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI based on a fixed value and the channel coefficient of the second echo cluster in a starting TTI.

[0124] In one embodiment, the second generating unit 503 is further configured to:

[0125] In a non-starting TTI, generating a channel coefficient of the first echo cluster in the current TTI based on a fixed value;

[0126] The channel coefficient of the second echo cluster in the starting TTI is determined as the channel coefficient of the second echo cluster in the current TTI.

[0127] In one embodiment, the random quantity includes at least an elevation angle, a horizontal angle, a cross-polarization power ratio, and an initialized random angle.

[0128] In one embodiment, the arrangement order of the first echo cluster and the second echo cluster in the start TTI is the same as the arrangement order of the first echo cluster and the second echo cluster in the non-start TTI.

[0129] In one embodiment, the second generating unit 503 is further configured to:

[0130] In a non-starting TTI, determining whether the number of TTIs in which the channel coefficients have been generated has reached a preset value;

[0131] In a case where the preset value is not reached, the channel coefficients of the first echo cluster and the second echo cluster in the current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

[0132] It should be noted that the division of units in the embodiments of the present application is schematic and is merely a logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0133] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application.

[0134] It should be noted here that the above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0135] In an exemplary embodiment, a synaesthesia channel modeling device is provided. The synaesthesia channel modeling device may be a terminal device or a network device. The internal structure of the synaesthesia channel modeling device may be as follows: Figure 6 The synaesthesia channel modeling device includes a memory 1120 , a transceiver 1110 and a processor 1100 .

[0136] A transceiver is used to receive and send data under the control of the processor.

[0137] Among them, Figure 6 In the present invention, the bus architecture can include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processors and memories represented by memories. The bus architecture can also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be described further in this article. The bus interface provides an interface. The transceiver can be multiple components, that is, including a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, which includes a wireless channel, a wired channel, an optical cable, and other transmission media. The processor is responsible for managing the bus architecture and general processing, and the memory can store data used by the processor when performing operations.

[0138] The processor can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0139] The processor calls the program stored in the memory to execute any of the methods provided in the embodiments of the present application according to the obtained executable instructions. The processor and the memory can also be physically separated.

[0140] It should be noted here that the above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0141] In an exemplary embodiment, a synaesthesia channel modeling device is provided. The synaesthesia channel modeling device may be a terminal device or a network device, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of the above-mentioned method embodiments when executing the computer program.

[0142] In an exemplary embodiment, a processor-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0143] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0144] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROMs, EPROMs, EEPROMs, non-volatile memories (NANDFLASH), solid-state drives (SSDs)), etc.

[0145] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage and optical storage) containing computer-usable program code.

[0146] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by processor-executable instructions. These processor-executable instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0147] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the processor-readable memory produce an article of manufacture comprising an instruction device that implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0148] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A synaesthesia channel modeling method, characterized in that: The method comprises: The random amount used in the synaesthesia channel modeling process under multiple consecutive transmission time intervals TTI is set to a fixed value; In a starting TTI, generating channel coefficients of a first echo cluster and a second echo cluster in the starting TTI based on the fixed value, where the first echo cluster represents an echo cluster corresponding to a motion sensing target, and the second echo cluster represents an echo cluster corresponding to an environmental scatterer; In a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

2. The method according to claim 1, characterized in that The generating, in a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI includes: In the non-starting TTI, generating a channel coefficient of the first echo cluster in a current TTI based on the fixed value; The channel coefficient of the second echo cluster in the starting TTI is determined as the channel coefficient of the second echo cluster in the current TTI.

3. The method according to claim 1, characterized in that The random quantity includes at least an elevation angle, a horizontal angle, a cross-polarization power ratio, and an initialized random angle.

4. The method according to claim 1, wherein The arrangement order of the first echo cluster and the second echo cluster in the start TTI is the same as the arrangement order of the first echo cluster and the second echo cluster in the non-start TTI.

5. The method according to claim 1, wherein The generating, in a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI includes: In the non-starting TTI, determining whether the number of TTIs in which channel coefficients have been generated reaches a preset value; In a case where the preset value is not reached, the channel coefficients of the first echo cluster and the second echo cluster in the current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

6. A synaesthesia channel modeling device, characterized in that: Including memory, transceiver, processor; memory for storing computer programs; a transceiver, configured to transmit and receive data under the control of the processor; A processor is configured to read the computer program in the memory and perform the following operations: The random amount used in the synaesthesia channel modeling process under multiple consecutive transmission time intervals TTI is set to a fixed value; In a starting TTI, generating channel coefficients of a first echo cluster and a second echo cluster in the starting TTI based on the fixed value, where the first echo cluster represents an echo cluster corresponding to a motion sensing target, and the second echo cluster represents an echo cluster corresponding to an environmental scatterer; In a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

7. The device according to claim 6, characterized in that The generating, in a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI specifically includes: In the non-starting TTI, generating a channel coefficient of the first echo cluster in a current TTI based on the fixed value; The channel coefficient of the second echo cluster in the starting TTI is determined as the channel coefficient of the second echo cluster in the current TTI.

8. The device according to claim 6, characterized in that The random quantity includes at least an elevation angle, a horizontal angle, a cross-polarization power ratio, and an initialized random angle.

9. The device according to claim 6, characterized in that The arrangement order of the first echo cluster and the second echo cluster in the start TTI is the same as the arrangement order of the first echo cluster and the second echo cluster in the non-start TTI.

10. The device according to claim 6, characterized in that The generating, in a non-starting TTI, channel coefficients of the first echo cluster and the second echo cluster in a current TTI based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI specifically includes: In the non-starting TTI, determining whether the number of TTIs in which channel coefficients have been generated reaches a preset value; In a case where the preset value is not reached, the channel coefficients of the first echo cluster and the second echo cluster in the current TTI are generated based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

11. A synaesthesia channel modeling device, characterized in that: include: A setting unit, configured to set a random amount used in the synaesthesia channel modeling process under a plurality of consecutive transmission time intervals TTI to a fixed value; A first generating unit is configured to generate, in a starting TTI, channel coefficients of a first echo cluster and a second echo cluster in the starting TTI based on the fixed value, where the first echo cluster represents an echo cluster corresponding to a motion sensing target, and the second echo cluster represents an echo cluster corresponding to an environmental scatterer; The second generating unit is configured to generate, in a non-starting TTI, the channel coefficients of the first echo cluster and the second echo cluster in a current TTI based on the fixed value and the channel coefficient of the second echo cluster in the starting TTI.

12. A processor-readable storage medium, characterized in that: The processor-readable storage medium stores a program, and the program is used to enable the processor to execute the method according to any one of claims 1 to 5.

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