Novel geometric random channel model modeling method for communication perception integrated system

Abstract

The invention is applicable to the technical field of channel modeling, and provides a novel geometric random channel model modeling method for a communication and perception integrated system, which comprises the following steps: firstly, establishing a GBSM channel model framework and a scene for an ISAC scene, setting scene layout parameters, then respectively acquiring CIR and CTF of a communication channel and a perception channel from the established GBSM channel model, and establishing a GBSM channel model framework and scene layout parameters; the method comprises the following steps: establishing a GBSM channel model, deducing statistical characteristics of PSD and DS of a communication channel and a perception channel by using CIR and CTF, carrying out simulation analysis to obtain a simulation result of the GBSM channel model, constructing an RT channel model for an ISAC scene, arranging simulation parameters, respectively obtaining statistical characteristics of PSD and DS of the communication channel and the perception channel from the RT channel model, and carrying out simulation analysis to obtain a simulation result of the GBSM channel model. And performing simulation analysis to obtain a simulation result of the RT channel model, and finally comparing the simulation result of the GBSM channel model with the simulation result of the RT channel model to verify the accuracy. Therefore, through the modeling method, the applicability of the channel model in ISAC can be improved.

Description

Technical Field

[0001] This application belongs to the technical field of channel modeling, and particularly relates to a new geometric random channel model modeling method for communication-sensing integrated systems. Background Art

[0002] The sixth-generation (6G) mobile communication system is being steadily promoted. ISAC is considered a technology with broad prospects and has the potential to bring revolutionary changes to all walks of life. Fundamental research on wireless channels not only supports the design, deployment, optimization, and standardization of communication systems but also plays a crucial role in performance evaluation. In recent years, the research on ISAC has been continuously deepened. It is expected that the emergence of 6G ISAC will introduce new channel characteristics, making some of the existing communication channel models partially obsolete. Therefore, there is an urgent need to explore and create new channel models for 6G ISAC systems.

[0003] Traditional communication channels mainly focus on signal transmission, while sensing channels have multiple functions such as object positioning and target recognition in various applications. Therefore, the applicability of most existing channel models for ISAC systems needs to be improved. Summary of the Invention

[0004] The embodiments of this application provide a new geometric random channel model modeling method for communication-sensing integrated systems, which can solve the problem that the applicability of most existing channel models for ISAC systems needs to be improved.

[0005] In a first aspect, the embodiments of this application provide a new geometric random channel model modeling method for communication-sensing integrated systems, including: Step S1, establish a geometric random channel model GBSM channel model framework and scenario for the communication-sensing integrated ISAC scenario, and set scenario layout parameters; Step S2, respectively obtain the channel impulse response CIR and channel transfer function CTF of the communication channel and the sensing channel from the established GBSM channel model; Step S3, use the obtained CIR and CTF to derive the statistical characteristics of the delay power spectral density PSD and delay spread DS of the communication channel and the sensing channel, and conduct simulation analysis to obtain the simulation results of the GBSM channel model; Step S4, construct a ray tracing RT channel model for the ISAC scenario and arrange simulation parameters; Step S5, respectively obtain the statistical characteristics of the PSD and DS of the communication channel and the sensing channel from the constructed RT channel model, and conduct simulation analysis to obtain the simulation results of the RT channel model; Step S6, compare the simulation results of the GBSM channel model and the simulation results of the RT channel model to verify the accuracy.

[0006] In a possible implementation manner of the first aspect, the above Step S1 specifically includes:

[0007] Step S101: Set the wireless signal in the GBSM channel model to be reflected n times. In the nth reflection path, the propagation processes of the communication signal and the sensing signal can be described by the virtual path between the first and the last reflection clusters.

[0008] Step S102: The positions of the scatterers in both the communication channel and the sensing channel follow the ellipsoidal Gaussian scattering distribution, that is, the position coordinates of the scatterers centered on any cluster follow three independent Gaussian distributions in the x, y, and z directions. Based on the positions of the transmitter Tx, the receiver Rx, and the scatterers, obtain the time delay and angle of the rays in the cluster, and determine the statistical characteristics of the GBSM channel model according to the time delay and angle of the rays in the cluster.

[0009] Step S103: Set the scene layout parameters, where the scene layout parameters include the distance D from the pth Tx antenna element at the initial moment to ; the frequency band f c / D s being studied; the number of antenna array elements M c of Tx and the number of antenna array elements M T of the communication / sensing Rx R-c / M R-s ; the antenna spacing of Tx and the antenna spacing of the communication / sensing Rx the azimuth angle of the Tx antenna array and the azimuth angle of the communication / sensing Rx antenna array the elevation angle of the Tx antenna array and the elevation angle of the communication / sensing Rx antenna array the azimuth / elevation movement direction of Tx T the movement speed v R-c (t) of the sensing Rx and the movement speed v R-s (t) of the communication Rx; the first / last reflection cluster of the nth path in the communication channel and the first / last reflection cluster of the nth path in the sensing channel the movement speed

[0010] Optionally, in another possible implementation of the first aspect, step S2 specifically includes:

[0011] Step S201. For a communication channel, between the Tx antenna unit and the Rx antenna unit the sub-channels are composed of a LoS component and a NLoS component, which is expressed by the formula:

[0012]

[0013] where K(t) is the Rice coefficient at time t, and the LoS component of the channel and the NLoS component of the channel are respectively expressed as:

[0014]

[0015]

[0016] where N qp (t) is the number of clusters between and at time t; M n (t) is the number of rays in the nth cluster at time t; represents the vertical and horizontal polarization antenna patterns of the Tx when the carrier frequency is f c ; represents the vertical and horizontal polarization antenna patterns of the Rx when the carrier frequency is f c ; is the arrival elevation angle of the transmitted signal in the LOS component of the communication channel; is the departure elevation angle of the transmitted signal in the LOS component of the communication channel; is the arrival azimuth angle of the transmitted signal in the LOS component of the communication channel; is the departure azimuth angle of the transmitted signal in the LOS component of the communication channel; is the arrival elevation angle of in the NLOS component of the communication channel; is the departure elevation angle of in the NLOS component of the communication channel; is the arrival azimuth angle of in the NLOS component of the communication channel; is the departure azimuth angle of in the NLOS component of the communication channel; is the cross-polarization power ratio; μ is the co-polarization coefficient; and are random variables modeled as uniformly distributed on (0, 2π] in the initial stage; Denote the time delay corresponding to the LoS component at time t; is the time delay causing the phase change; is the time delay of the impulse function; and τ c,qp,mn (t) respectively represent the time-varying power and delay of the m-th ray on the n-th cluster between and in the NLoS component of the communication channel at time t; is the time delay causing the phase change; is the time delay of the impulse function;

[0017] For the sensing channel The formula is expressed as:

[0018]

[0019] is the elevation angle of arrival of in the NLOS component of the sensing channel; is the elevation angle of departure of in the NLOS component of the sensing channel; is the azimuth angle of arrival of in the NLOS component of the sensing channel; is the azimuth angle of departure of in the NLOS component of the sensing channel; and τ s,qp,mn (t) respectively represent the time-varying power and delay of the m-th ray on the n-th cluster between and in the NLoS component of the sensing channel at time t; is the phase change caused by the time delay τ - , is the time delay of the impulse function;

[0020] Step S202, perform Fourier transform on the CIR of the communication channel and the CIR of the sensing channel to obtain the of the communication channel and the

[0021] Optionally, in another possible implementation manner of the first aspect, the above step S3 specifically includes:

[0022] Step S301, the expression of the time autocorrelation function TACF of the communication channel is obtained according to the CTF of the communication channel, and the expression is:

[0023]

[0024] Among them, is the CTF of the communication channel obtained in step S202; E is to take the expectation; (·) * is to take the conjugate;

[0025] is the TACF of the LoS component of the communication channel, expressed as:

[0026]

[0027] is the TACF of the NLoS component of the communication channel, expressed as:

[0028]

[0029] Among them, f c -f represents the communication channel frequency; d qp (t) represents the distance between and in the LoS component at time t; λ represents the signal wavelength; represents the time-varying power of the m-th ray on the n-th cluster between and in the NLoS component of the channel at time t; Δt is the difference between two different times in the autocorrelation function; represents the distance between and in the NLoS component at time t;

[0030] The expression of the time autocorrelation function TACF of the sensing channel is obtained according to the CTF of the sensing channel, and the expression is:

[0031]

[0032] Among them, is the CTF of the sensing channel obtained in step S202, E is to take the expectation, (·) * is to take the conjugate;

[0033] is the TACF of the LoS component of the sensing channel, expressed as:

[0034]

[0035] is the TACF of the NLoS component of the sensing channel, expressed as:

[0036]

[0037] Among them, f s-f represents the communication channel frequency;

[0038] Step S302: In the frequency domain, the Doppler PSDS of the communication channel and the sensing channel qp (t, f; v) are obtained by Fourier transform according to the TACF of the channel respectively. The Doppler PSD represents the power distribution of the signal relative to the Doppler frequency:

[0039] S qp (t, f; v) = ∫R qp (t, f; Δt)e -j2πvΔt dΔt

[0040] where R qp (t, f; Δt) is the CTF of the channel;

[0041] Step S303: Define the delay spread DS as the square root of the second central moment of the PSD, and the expression is:

[0042]

[0043] where u τ,qp (t, f) is the average delay and the first moment of the PSD; S qp (t, f; τ) is the delay PSD of the channel. Substituting the PSDs of the communication channel and the sensing channel into the above formula respectively, the corresponding delay spreads can be obtained.

[0044] Step S304: Conduct simulation analysis based on the PSD and DS to obtain the simulation results of the GBSM channel model.

[0045] Optionally, in another possible implementation manner of the first aspect, the above step S4 specifically includes:

[0046] Step S401: The simulation of the RT channel in the ISAC scenario is divided into two cases: there is no LoS path between the communication and sensing transmitter TRx and the communication receiver CRx, indicating that the communication channel follows the NLoS propagation condition; the communication channel follows the LoS propagation condition;

[0047] The simulation is carried out at n different points of the model, labeled 1 - n from north to south, and the distance between adjacent points is m meters;

[0048] Step S402: Generate parameters, and respectively set whether the polarization directions of the TRx and CRx antennas are isotropic; configure the frequency and bandwidth of the transmitted signal; set the time interval for the Tx to uniformly transmit rays for tracking; set the maximum allowed reflection, transmission, and diffraction times in the light propagation path.

[0049] Optionally, in another possible implementation of the first aspect, the simulation results of the RT channel model include the RT simulation results of PSD and the RT simulation results of DS. The above step S5 specifically includes:

[0050] Step S501: Weight the delays of L multipaths with their corresponding powers respectively to obtain the RT simulation results of PSD:

[0051]

[0052] where P i is the power of the i-th multipath, τ i is the delay of the i-th multipath, and δ(τ - τ i ) is the impulse function at the moment when the delay is τ - τ i ;

[0053] Step S502: The RT simulation results of DS are:

[0054]

[0055] where is the power-weighted average delay.

[0056] A new geometric random channel model modeling method for a communication and sensing integrated system provided by this application first establishes a GBSM channel model framework and scenario for the ISAC scenario, sets the scenario layout parameters, then respectively obtains the CIR and CTF of the communication channel and the sensing channel from the established GBSM channel model, then uses the CIR and CTF to deduce the statistical characteristics of the PSD and DS of the communication channel and the sensing channel, conducts simulation analysis to obtain the simulation results of the GBSM channel model, then constructs an RT channel model for the ISAC scenario, arranges the simulation parameters, then respectively obtains the statistical characteristics of the PSD and DS of the communication channel and the sensing channel from the RT channel model, and conducts simulation analysis to obtain the simulation results of the RT channel model, and finally compares the simulation results of the GBSM channel model and the RT channel model to verify the accuracy. Thus, through the above modeling method, the applicability of the channel model in ISAC can be improved. Description of the Drawings

[0057] In order to more clearly illustrate the technical solutions in the embodiments of this application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0058] Figure 1Schematic flowchart of a novel geometric random channel model modeling method for a communication-sensing integrated system provided in an embodiment of the present application;

[0059] Figure 2 Schematic diagram of the geometric random channel model structure for a communication-sensing integrated scenario provided in an embodiment of the present application;

[0060] Figure 3 Scenario diagram of the RT channel model for the ISAC scenario provided in an embodiment of the present application;

[0061] Figure 4 TACF theoretical results and simulation results of the communication channel of the ISAC system at t = 0.5 s and t = 10 s provided in an embodiment of the present application;

[0062] Figure 5 TACF theoretical results and simulation results of the sensing channel of the ISAC system at t = 0.5 s and t = 10 s provided in an embodiment of the present application;

[0063] Figure 6 Comparison diagram of the GBSM and RT simulation results of the DS in the ISAC system provided in an embodiment of the present application. Detailed implementation manners

[0064] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0065] It should be understood that when used in the specification and appended claims of the present application, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0066] It should also be understood that the term " / and" as used in the specification and appended claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0067] As used in the specification and appended claims of this application, the term "if" may be construed as "when" or "once" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrases "if determined" or "if [the described condition or event] is detected" may be construed as meaning "once determined" or "in response to determining" or "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]" depending on the context.

[0068] In addition, in the description of the specification and appended claims of this application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be construed as indicating or implying relative importance.

[0069] Reference to "one embodiment" or "some embodiments" or the like described in the specification of this application means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0070] The following describes in detail a novel geometric random channel model modeling method for a communication and sensing integrated system provided by this application with reference to the accompanying drawings.

[0071] Figure 1 A flowchart showing a novel geometric random channel model modeling method for a communication and sensing integrated system provided by an embodiment of this application is shown.

[0072] As Figure 1 shown, the novel geometric random channel model modeling method for a communication and sensing integrated system includes the following steps:

[0073] Step S1: Establish a geometric random channel model GBSM channel model framework and scenario for the communication and sensing integrated ISAC scenario, and set scenario layout parameters;

[0074] Step S2: Respectively obtain the channel impulse response CIR and the channel transfer function CTF of the communication channel and the sensing channel from the established GBSM channel model;

[0075] Step S3: Derive the statistical characteristics of the delay power spectral density (PSD) and delay spread (DS) of the communication channel and the sensing channel using the obtained CIR and CTF, and perform simulation analysis to obtain the simulation results of the GBSM channel model;

[0076] Step S4: Construct a ray-tracing (RT) channel model for the ISAC scenario and arrange the simulation parameters;

[0077] Step S5: Obtain the statistical characteristics of the PSD and DS of the communication channel and the sensing channel respectively from the constructed RT channel model, and perform simulation analysis to obtain the simulation results of the RT channel model;

[0078] Step S6: Compare the simulation results of the GBSM channel model and the RT channel model to verify the accuracy.

[0079] Further, in a possible implementation manner of the embodiment of the present application, the above step S1 may include:

[0080] Step S101: Set the wireless signal in the GBSM channel model to be reflected n times. In the nth reflection path, the propagation processes of the communication signal and the sensing signal can be described by the virtual path between the first and the last reflection clusters;

[0081] Step S102: The positions of the scatterers in the communication channel and the sensing channel both follow the ellipsoidal Gaussian scattering distribution, that is, the position coordinates of the scatterers centered on any cluster follow three independent Gaussian distributions in the x, y, and z directions. According to the positions of the transmitter (Tx), the receiver (Rx), and the scatterers, obtain the delay and angle of the rays in the cluster, and determine the statistical characteristics of the GBSM channel model based on the delay and angle of the rays in the cluster;

[0082] Step S103: Set the scenario layout parameters, where the scenario layout parameters include the distance D from the pth Tx antenna unit to the qth communication / sensing Rx antenna array unit at the initial moment to ; the frequency band f under study c / D s ; the number M of antenna array units of Tx c and the number M of antenna array units of communication / sensing Rx T / M R-c / M R-s ; the antenna spacing of Tx and the antenna spacing of communication / sensing Rx the azimuth angle of the Tx antenna array and the azimuth angle of the communication / sensing Rx antenna array the elevation angle of the Tx antenna array Elevation angle of the communication / sensing Rx antenna array Azimuth / elevation movement direction of Tx Azimuth / elevation movement direction of communication Rx Azimuth / elevation movement direction of sensing Rx Moving speed v of Tx T 、Moving speed v of sensing Rx R-c (t) and moving speed v of communication Rx R-s (t); The first / last reflection cluster of the nth path of the communication channel And the first / last reflection cluster of the nth path of the sensing channel Moving speed in the communication / sensing channel And Moving speed in the communication / sensing channel

[0083] Furthermore, in a possible implementation manner of the embodiment of the present application, the above step S2 may include:

[0084] Step S201. For the communication channel, the Tx antenna unit And the Rx antenna unit The sub-channel between Is composed of the LoS component and the NLoS component, and is expressed by the formula:

[0085]

[0086] Wherein, K(t) is the Rice coefficient at time t, and the And the Of the NLoS component are respectively expressed as:

[0087]

[0088] Wherein, N qp (t) is the number of clusters between And At time t; M n (t) is the number of rays in the nth cluster at time t; Represents the vertical and horizontal polarization antenna patterns of Tx when the carrier frequency is f c ; Represents the vertical and horizontal polarization antenna patterns of Rx when the carrier frequency is f c ; Is the arrival elevation angle of the transmitted signal in the communication channel LOS component; Is the departure elevation angle of the transmitted signal in the communication channel LOS component; Is the arrival azimuth angle of the transmitted signal in the communication channel LOS component; is the departure azimuth angle of the transmitted signal in the LOS component of the communication channel; in the NLOS component of the communication channel is the arrival elevation angle; in the NLOS component of the communication channel is the departure elevation angle; in the NLOS component of the communication channel is the arrival azimuth angle; in the NLOS component of the communication channel is the departure azimuth angle; is the cross-polarization power ratio; μ is the co-polarization coefficient; and is a random variable modeled as uniformly distributed on (0, 2π] in the initial stage; represents the corresponding delay of the LoS component at time t; is the delay causing the phase change; is the delay is the impulse function; and τ c,qp,mn (t) respectively represent the time-varying power and delay of the m-th ray on the n-th cluster between and in the NLOS component of the communication channel at time t; is the delay causing the phase change; is the delay is the impulse function;

[0089] For the sensing channel the formula is expressed as:

[0090]

[0091] in the NLOS component of the sensing channel is the arrival elevation angle; in the NLOS component of the sensing channel is the departure elevation angle; in the NLOS component of the sensing channel is the arrival azimuth angle; in the NLOS component of the sensing channel is the departure azimuth angle; and τ s,qp,mn (t) respectively represent the time-varying power and delay of the m-th ray on the n-th cluster between and in the NLOS component of the sensing channel at time t; is the delay τ - The phase change brought about is the time delay of the impulse function;

[0092] Step S202: Perform Fourier transform on the CIR of the communication channel and the CIR of the sensing channel to obtain the of the communication channel

[0093] Furthermore, in a possible implementation manner of the embodiment of the present application, the above step S3 may include:

[0094] Step S301: The expression of the time autocorrelation function TACF of the communication channel is obtained according to the CTF of the communication channel, and the expression is:

[0095]

[0096] Wherein, is the CTF of the communication channel obtained in step S202; E is to take the expectation; (·) * is to take the conjugate;

[0097] is the TACF of the LoS component of the communication channel, expressed as:

[0098]

[0099] is the TACF of the NLoS component of the communication channel, expressed as:

[0100]

[0101] Wherein, f c -f represents the communication channel frequency; d qp (t) represents the and distance between in the LoS component at time t; λ represents the signal wavelength; represents the time-varying power of the mth ray on the nth cluster between and in the NLoS component of the channel at time t; Δt is the difference between two different times in the autocorrelation function; represents the and distance between in the NLoS component at time t;

[0102] The expression of the time autocorrelation function TACF of the sensing channel is obtained according to the CTF of the sensing channel, and the expression is:

[0103]

[0104] Among them, is the CTF of the sensed channel obtained in step S202, E represents taking the expectation, and (·) * is taking the conjugate;

[0105] is the TACF of the LoS component of the sensed channel, expressed as:

[0106]

[0107] is the TACF of the NLoS component of the sensed channel, expressed as:

[0108]

[0109] where f s -f represents the communication channel frequency;

[0110] Step S302, in the frequency domain, the Doppler PSDs qp (t, f; v) of the communication channel and the sensed channel are obtained by performing Fourier transforms according to the TACF of the channels respectively. The Doppler PSD represents the power distribution of the signal relative to the Doppler frequency:

[0111] S qp (t, f; v) = ∫R qp (t, f; Δt)e -j2πvΔt dΔt

[0112] where R qp (t, f; Δt) is the CTF of the channel;

[0113] Step S303, define the delay spread DS as the square root of the second-order central moment of the PSD, and the expression is:

[0114]

[0115] where u τ,qp (t, f) is the average delay and the first-order moment of the PSD; S qp (t, f; τ) is the delay PSD of the channel. Substituting the PSDs of the communication channel and the sensed channel into the above formula respectively can obtain the corresponding delay spreads.

[0116] Step S304, perform simulation analysis according to the PSD and DS to obtain the simulation results of the GBSM channel model.

[0117] Furthermore, in a possible implementation manner of the embodiment of the present application, the above step S4 may include:

[0118] Step S401: The simulation of the RT channel in the ISAC scenario is divided into two cases: there is no LoS path between the communication-aware transmitter TRx and the communication receiver CRx, indicating that the communication channel follows the NLoS propagation condition; the communication channel follows the LoS propagation condition.

[0119] The simulation is carried out at n different points of the model, labeled 1 - n from north to south, and the distance between adjacent points is m meters.

[0120] Step S402: Generate parameters, and respectively set whether the polarization directions of the TRx and CRx antennas are isotropic; configure the frequency and bandwidth of the transmitted signal; set the time interval for the Tx to uniformly emit rays for tracking; set the maximum allowed reflection, transmission, and diffraction times in the light propagation path.

[0121] Further, in a possible implementation manner of the embodiment of the present application, the above step S5 may include:

[0122] Step S501: Weight the time delays of L multipaths with their corresponding powers respectively to obtain the RT simulation result of the PSD:

[0123]

[0124] where P i is the power of the i-th multipath, τ i is the time delay of the i-th multipath, and δ(τ - τ i ) is the impulse function of the time delay at the moment of τ - τ i ;

[0125] Step S502: The RT simulation result of the DS is:

[0126]

[0127] where is the power-weighted average time delay.

[0128] The novel geometric random channel model modeling method for the communication and sensing integrated system provided by this application first establishes the GBSM channel model framework and scenario for the ISAC scenario, sets the scenario layout parameters, then obtains the CIR and CTF of the communication channel and the sensing channel respectively from the established GBSM channel model, then derives the statistical characteristics of the PSD and DS of the communication channel and the sensing channel using the CIR and CTF, conducts simulation analysis to obtain the simulation results of the GBSM channel model, then constructs the RT channel model for the ISAC scenario, arranges the simulation parameters, then obtains the statistical characteristics of the PSD and DS of the communication channel and the sensing channel respectively from the RT channel model, and conducts simulation analysis to obtain the simulation results of the RT channel model, and finally compares the simulation results of the GBSM channel model and the RT channel model to verify the accuracy. Thus, through the above modeling method, the applicability of the channel model in ISAC can be improved.

[0129] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of this application.

[0130] The above embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included in the protection scope of this application.

Claims

1. A new geometric random channel modeling method for communication perception integrated system, characterized in that: The channel modeling method comprises the following steps: Step S1, establishing a geometric random channel model GBSM channel model framework and scenario for the communication perception integrated ISAC scenario, and setting scenario layout parameters; Step S2, respectively obtaining the channel impulse response CIR and the channel transfer function CTF of the communication channel and the perception channel from the established GBSM channel model; Step S3, using the obtained CIR and CTF to derive the statistical characteristics of the delay power spectrum density PSD and the delay spread DS of the communication channel and the perception channel, and perform simulation analysis to obtain the simulation results of the GBSM channel model; Step S4: construct a ray tracing RT channel model for the ISAC scenario and arrange simulation parameters; Step S5, respectively obtaining statistical characteristics of PSD and DS of the communication channel and the perception channel from the constructed RT channel model, and performing simulation analysis to obtain simulation results of the RT channel model; Step S6: Compare the simulation results of the GBSM channel model with the simulation results of the RT channel model to verify their accuracy.

2. The method according to claim 1, characterized in that: The step S1 specifically includes the following steps: Step S101, setting the wireless signal in the GBSM channel model to reflect n times, in the nth reflection path, the propagation process of the communication signal and the perception signal can be described by a virtual path between the first and last reflection clusters; Step S102, the positions of scatterers in the communication channel and the sensing channel all follow the ellipsoidal Gaussian scattering distribution, that is, the position coordinates of the scatterer centered on any cluster in the x, y, and z directions follow three independent Gaussian distributions, and the time delay and angle of the ray in the cluster are obtained according to the position of the transmitter Tx, the receiver Rx, and the scatterer, and the statistical characteristics of the GBSM channel model are determined according to the time delay and angle of the ray in the cluster; Step S103: Set scene layout parameters, including the pth Tx antenna unit and the qth communication / sensing Rx antenna array unit Initial moment arrive The distance D c / D s ; Frequency band studied f c ; Number of antenna array elements of Tx M T and the number of antenna array elements M for communication / sensing Rx R-c / M R-s ;Tx antenna spacing and communication / sensing Rx antenna spacing Azimuth of the Tx antenna array and the azimuth of the communication / sensing Rx antenna array Tx antenna array elevation angle and the elevation angle of the communication / sensing Rx antenna array Tx azimuth / elevation moving direction Azimuth / elevation moving direction of communication Rx and sense the azimuth / elevation moving direction of Rx Tx's moving speed v T , perceive the moving speed v of Rx R-c (t) and the moving speed v of the communication Rx R-s (t); The first / last reflection cluster of the nth path of the communication channel and the first / last reflection cluster of the nth path of the sensing channel Speed ​​of movement in communication / sensing channels and Speed ​​of movement in communication / sensing channels 3. The method according to claim 2, characterized in that The step S2 specifically includes the following steps: Step S201: For a communication channel, the Tx antenna unit and Rx antenna unit Between sub-channels It consists of LoS component and NLoS component, and the formula is expressed as: Where K(t) is the Rice coefficient at time t, and the channel LoS component and NLoS components Respectively expressed as: Among them, N qp (t) is time t and The number of clusters between n (t) is the number of rays in the nth cluster at time t; Indicates that the carrier frequency is f c Vertical and horizontal polarization antenna patterns of Tx at 100 Hz; Indicates that the carrier frequency is f c Vertical and horizontal polarization antenna patterns of Rx when is the arrival elevation angle of the transmitted signal in the LOS component of the communication channel; is the departure elevation angle of the transmitted signal in the LOS component of the communication channel; is the arrival azimuth of the transmitted signal in the LOS component of the communication channel; is the departure azimuth of the transmitted signal in the LOS component of the communication channel; is the NLOS component of the communication channel The arrival pitch angle; is the NLOS component of the communication channel The departure pitch angle; is the NLOS component of the communication channel The arrival azimuth of is the NLOS component of the communication channel The departure azimuth of is the cross-polarization power ratio; μ is the co-polarization coefficient; as well as is modeled as a random variable uniformly distributed on (0,2π] in the initial stage; Indicates the corresponding delay of the LoS component at time t; Delay The phase change caused by Delay The impulse function of and τ c,qp,mn (t) represents the NLoS component of the communication channel at time t and The time-varying power and delay of the mth ray on the nth cluster between them; It is a delay The phase change caused by It is a delay The impulse function of For sensing channels The formula is: is the NLOS component of the sensing channel The arrival pitch angle; is the NLOS component of the sensing channel The departure pitch angle; is the NLOS component of the sensing channel The arrival azimuth of is the NLOS component of the sensing channel The departure azimuth of and τ s,qp,mn (t) represents the NLoS component of the perceived channel at time t. and The time-varying power and delay of the mth ray on the nth cluster between them; It is a delay The phase change caused by It is a delay The impulse function of Step S202: Perform Fourier transform on the CIR of the communication channel and the CIR of the perception channel to obtain the CIR of the communication channel. and sensing channels 4. The method according to claim 3, characterized in that The step S3 specifically comprises the following steps: Step S301: The expression of the time autocorrelation function TACF of the communication channel is obtained according to the CTF of the communication channel, and the expression is: in, is the CTF of the communication channel obtained in step S202; E is the expected value; (·) * To take conjugation; is the TACF of the LoS component of the communication channel, expressed as: is the TACF of the NLoS component of the communication channel, expressed as: Among them, f c -f indicates the communication channel frequency; d qp (t) represents the LoS component at time t and The distance between them; λ represents the signal wavelength; It is expressed as the NLoS component of the channel at time t and The time-varying power of the mth ray on the nth cluster; Δt is the difference between two different moments in the autocorrelation function; Expressed as the NLoS component at time t and The distance between The expression of the temporal autocorrelation function TACF of the perception channel is obtained based on the CTF of the perception channel, and the expression is: in, is the CTF of the perceived channel obtained in step S202, E is the expected value, (·) * To take conjugation; is the TACF of the LoS component of the perceived channel, expressed as: is the TACF of the NLoS component of the perceived channel and is expressed as: Among them, f s -f indicates the communication channel frequency; Step S302: In the frequency domain, the Doppler PSDS of the communication channel and the sensing channel qp (t, f; v) are obtained by Fourier transform according to the TACF of the channel, and the Doppler PSD represents the power distribution of the signal relative to the Doppler frequency: S qp (t,f;v)=∫R qp (t,f;Δt)e -j2πvΔt dΔt Among them, R qp (t,f;Δt) is the CTF of the channel; Step S303: define the delay spread DS as the square root of the second-order central moment of the PSD, expressed as: Among them, u τ,qp (t,f) is the first moment of the average delay and PSD; S qp (t,f; τ) is the delay PSD of the channel. Substituting the PSD of the communication channel and the perception channel into the above formula respectively can obtain the corresponding delay spread. Step S304: Perform simulation analysis based on the PSD and the DS to obtain a simulation result of a GBSM channel model.

5. The method according to claim 4, characterized in that The step S4 specifically comprises the following steps: Step S401, the simulation of the RT channel of the ISAC scenario is divided into two cases: there is no LoS ​​path between the communication sensing transmitter TRx and the communication receiving terminal CRx, indicating that the communication channel follows the NLoS propagation condition; the communication channel follows the LoS propagation condition; The simulation is performed at n different points of the model, which are labeled 1-n from north to south, and the spacing between adjacent points is m meters; Step S402, generate parameters, respectively set whether the polarization directions of the TRx and CRx antennas are isotropic; configure the frequency and bandwidth of the transmitted signal; set the time interval for Tx to uniformly transmit rays for tracking; set the maximum reflection, transmission and diffraction time allowed in the light propagation path.

6. The method according to claim 5, characterized in that The simulation results of the RT channel model include the RT simulation results of the PSD and the RT simulation results of the DS. The step S5 specifically includes the following steps: Step S501: weight the delays of L multipaths by their corresponding powers to obtain the RT simulation result of PSD: Among them, P i is the power of the i-th multipath, τ i is the delay of the i-th multipath, δ(τ-τ i ) is the time delay between τ and τ i The impulse function at this moment; Step S502, the RT simulation result of DS is: in, is the power-weighted average delay.

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