Channel modeling method, device and equipment for near-field spatial non-stationary characteristic

Abstract

The invention provides a channel modeling method, device and equipment for near-field spatial non-stationary characteristics, and the method comprises the steps: determining the propagation distance of each scatterer cluster in a near-field propagation space according to the cluster time delay information of the scatterer clusters and the pre-configured distance information of the scatterer clusters; wherein the distance information comprises distance distribution information between the scatterer cluster and the signal transmitting end and / or the signal receiving end; generating space coordinate information of the scatterer cluster according to the arrival angle information, the departure angle information and the propagation distance of the scatterer cluster; determining near-field propagation channel parameters according to the space coordinate information; obtaining a non-stationary attenuation factor of the near-field propagation space according to the parameter information and the position information of the shielding object in the near-field propagation space; and on the basis of a standard channel model, according to the near-field propagation channel parameters and the non-stationary attenuation factors, constructing a channel model with near-field spatial non-stationary characteristics. The channel model constructed by the embodiment of the invention is high in accuracy, and the complexity of the calculation process is low.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular, to a channel modeling method, apparatus, and device for non-stationary characteristics of a near-field space. Background Art

[0002] With the deployment of the fifth-generation (5G) mobile communication system globally, the research on the sixth-generation (6G) mobile communication system has been fully launched. The number of antenna elements in a very large-scale multiple-input multiple-output (MIMO) system is huge (from dozens to thousands), and it can serve dozens of terminals within the same time-frequency resource block, with large capacity, high spectral and energy efficiency, meeting the higher requirements of the 6G system for performance indicators such as spectral efficiency and energy efficiency of the communication system.

[0003] As the frequency increases, the wavelength shortens, and a large number of antenna elements are configured at the base station, resulting in a significant increase in the antenna aperture. The large-scale MIMO channel will exhibit channel characteristics different from traditional channels, namely non-stationary characteristics of the near-field space. In the near-field region, the traditional plane-wave assumption fails, and the spherical-wave assumption needs to be adopted, that is, the equiphase surface of the electromagnetic wave is regarded as a sphere centered on the signal source to accurately calculate the channel coefficients. This method more accurately reflects the propagation characteristics of the signal and is crucial for optimizing the performance of the communication system. However, to obtain the channel coefficients of the signal under spherical-wave propagation, it is necessary to determine the positions of the scatterer clusters in the channel. Considering the spatial non-stationary characteristics under large-scale MIMO at the same time, different antenna elements have different propagation environments, and their visibility to different clusters is also different.

[0004] In the prior art, the positions of the scatterer clusters are often calculated through optimization algorithms, and the non-stationary characteristics of the space are determined through the visibility probability of the scatterer clusters. However, the above methods not only have a high computational complexity but also have low computational accuracy and compatibility rates. Summary of the Invention

[0005] The purpose of the present invention is to provide a channel modeling method, apparatus, and device for non-stationary characteristics of a near-field space, which are used to solve the problems in the prior art that under the condition of considering non-stationary characteristics in the near-field space, the computational complexity required for constructing a channel model is high and the accuracy of the generated model is low.

[0006] To solve the above technical problems, an embodiment of the present invention provides a channel modeling method for non-stationary characteristics of a near-field space, including:

[0007] In the near-field propagation space, determine the propagation distance of each scatterer cluster according to the cluster delay information of the scatterer cluster and the pre-configured distance information of the scatterer cluster; wherein, the distance information includes the distance distribution information between the scatterer cluster and the signal transmitter and / or the distance distribution information between the scatterer cluster and the signal receiver;

[0008] Generate the spatial coordinate information of the scatterer cluster according to the angle of arrival information, angle of departure information and the propagation distance of the scatterer cluster;

[0009] Determine the near-field propagation channel parameters according to the spatial coordinate information;

[0010] Obtain the non-stationary attenuation factor of the near-field propagation space according to the parameter information and position information of the obstacles in the near-field propagation space;

[0011] Based on the standard channel model, construct a channel model with non-stationary characteristics of the near-field space according to the near-field propagation channel parameters and the non-stationary attenuation factor.

[0012] Optionally, the method further includes:

[0013] Obtain the simulation distances between multiple scatterer clusters and the signal transmitter and / or the simulation distances between multiple scatterer clusters and the signal receiver by simulating the distribution of the scatterer clusters in different near-field scenarios;

[0014] Perform statistical analysis on the simulation distances and fit to generate a normal distribution model;

[0015] Obtain the distance information of the scatterer cluster according to the normal distribution model.

[0016] Optionally, determining the propagation distance of each scatterer cluster according to the cluster delay information of the scatterer cluster and the distance information of the scatterer cluster includes:

[0017] Randomly generate multiple first distances between the scatterer cluster and the signal transmitter and / or multiple first distances between the scatterer cluster and the signal receiver according to the pre-configured distance information of the scatterer cluster;

[0018] Match the cluster delay information with the first distance according to the magnitude correspondence between the cluster delay information of the scatterer cluster and the first distance, and determine the propagation distance of each scatterer cluster.

[0019] Optionally, the generating the spatial coordinate information of the scatterer cluster according to the angle of arrival information, angle of departure information and the propagation distance of the scatterer cluster includes:

[0020] Generate the spatial coordinate information of the first-hop scatterer cluster corresponding to the signal transmitter according to the departure angle information and the propagation distance of each of the scatterer clusters;

[0021] Generate the spatial coordinate information of the last-hop scatterer cluster corresponding to the signal receiver according to the arrival angle information and the propagation distance of each of the scatterer clusters.

[0022] Optionally, the parameter information of the obstacle includes one or more of the following:

[0023] The type of the obstacle;

[0024] The size information of the obstacle;

[0025] The movement mode information of the obstacle.

[0026] Optionally, obtaining the non-stationary attenuation factor of the near-field propagation space according to the parameter information and the position information of the obstacle in the near-field propagation space includes:

[0027] Obtain the projection distance information between the signal transmitter and the signal receiver and the obstacle respectively according to the parameter information and the position information of the obstacle in the near-field propagation space;

[0028] Establish the knife-edge diffraction model of the obstacle according to the projection distance information;

[0029] Obtain the non-stationary attenuation factor of the near-field propagation space according to the knife-edge diffraction model.

[0030] Optionally, obtaining the projection distance information between the signal transmitter and the signal receiver and the obstacle respectively according to the parameter information and the position information of the obstacle in the near-field propagation space includes:

[0031] Obtain the position schematic diagram among the obstacle, the signal transmitter and the signal receiver in the near-field propagation space according to the position information of the obstacle in the near-field propagation space; wherein, the position schematic diagram includes a side view projection schematic diagram and a top view projection schematic diagram;

[0032] Using the position schematic diagram, obtain the projection distance information between the signal transmitter and the edge of the first obstacle according to the parameter information of the first obstacle, wherein the first obstacle is the obstacle whose distance from the signal transmitter satisfies the first preset condition;

[0033] Using the position schematic diagram, according to the parameter information of the second obstacle, obtain the projection distance information between the signal receiving end and the edge of the second obstacle, where the second obstacle is the obstacle whose distance from the signal transmitting end satisfies a second preset condition.

[0034] An embodiment of the present invention further provides a channel modeling device for the non-stationary characteristics of the near-field space, including:

[0035] A first determination module, configured to determine the propagation distance of each scatterer cluster in the near-field propagation space according to the cluster delay information of the scatterer cluster and the pre-configured distance information of the scatterer cluster; where the distance information includes the distance distribution information between the scatterer cluster and the signal transmitting end and / or the distance distribution information between the scatterer cluster and the signal receiving end;

[0036] A first generation module, configured to generate the spatial coordinate information of the scatterer cluster according to the arrival angle information, departure angle information, and the propagation distance of the scatterer cluster;

[0037] A first calculation module, configured to determine the near-field propagation channel parameters according to the spatial coordinate information;

[0038] A second calculation module, configured to obtain the non-stationary attenuation factor of the near-field propagation space according to the parameter information and position information of the obstacle in the near-field propagation space;

[0039] A first construction module, configured to construct a channel model with non-stationary characteristics of the near-field space based on the standard channel model according to the near-field propagation channel parameters and the non-stationary attenuation factor.

[0040] An embodiment of the present invention further provides a network device, including: a processor, a memory, and a program stored on the memory and executable on the processor, where the program, when executed by the processor, implements the method for channel modeling of the non-stationary characteristics of the near-field space as described in any one of the above.

[0041] An embodiment of the present invention further provides a readable storage medium, including: a program stored on the readable storage medium, where the program, when executed by a processor, implements the steps of the method for channel modeling of the non-stationary characteristics of the near-field space as described in any one of the above.

[0042] An embodiment of the present invention further provides a computer program product, including computer instructions, where the computer instructions, when executed by a processor, implement the steps of the method for channel modeling of the non-stationary characteristics of the near-field space as described in any one of the above.

[0043] At least one of the above technical solutions of the present invention has the following beneficial effects:

[0044] In the above solution, in view of the near-field spatial non-stationary characteristics existing in the existing large-scale MIMO channels, a channel modeling method for near-field spatial non-stationary characteristics is proposed, which is divided into two parts: near-field propagation channel and spatial non-stationary characteristics for separate modeling. For the near-field propagation channel, first, according to the cluster delay information of the scatterer clusters and the pre-configured distance information of the scatterer clusters, the propagation distance of each scatterer cluster is determined; wherein, the distance information includes the pre-determined distance distribution information between the scatterer cluster and the signal transmitter and / or the pre-determined distance distribution information between the scatterer cluster and the signal receiver; then, according to the propagation distance, angle of arrival information and angle of departure information of the scatterer cluster, the spatial coordinate information of the scatterer cluster is obtained, and further the near-field propagation channel parameters are determined, reducing the computational complexity compared with the prior art. For the spatial non-stationary characteristics, according to the parameter information of the obstacles in the near-field propagation space, the non-stationary attenuation factor of the near-field propagation space is obtained; ensuring the spatial consistency between different scatterer clusters and different antenna elements, and improving the accuracy of the model. Finally, based on the existing 3rd Generation Partnership Project (3GPP) standard channel model (i.e., the standard channel model in this article), substituting the near-field propagation channel parameters and the non-stationary attenuation factor, a channel model with near-field spatial non-stationary characteristics is constructed, improving the versatility and usability of the present invention. Therefore, the method of using the embodiment of the present invention to construct a channel with near-field spatial non-stationary characteristics has a lower computational complexity, a higher accuracy of the built model, and better versatility and usability. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic flowchart of the channel modeling method for near-field spatial non-stationary characteristics according to an embodiment of the present invention;

[0046] Figure 2 It is a schematic diagram of the probability density function of the distance between all scatterer clusters and the base station of some users in the line-of-sight environment propagation in the indoor office scenario according to an embodiment of the present invention and its fitting result;

[0047] Figure 3 It is a schematic diagram of the probability density function of the distance between all scatterer clusters and the base station of some users in the non-line-of-sight environment propagation in the indoor office scenario according to an embodiment of the present invention and its fitting result;

[0048] Figure 4 It is a schematic diagram of the probability density function of the distance between all scatterer clusters and the base station of some users in the line-of-sight environment propagation in the urban macrocell scenario according to an embodiment of the present invention and its fitting result;

[0049] Figure 5Schematic diagram of the probability density function of the distances between all scatterer clusters of some users and the base station in non-line-of-sight environment propagation in urban macrocell scenario and its fitting result;

[0050] Figure 6 Full view of the obstacle in the embodiment of the present invention;

[0051] Figure 7 In the embodiment of the present invention Figure 6 Top view of the positional relationship between the scatterer cluster of the obstacle shown in the line-of-sight condition and the signal transmitter and signal receiver;

[0052] Figure 8 In the embodiment of the present invention Figure 6 One of the side views of the positional relationship between the scatterer cluster of the obstacle shown in the line-of-sight condition and the signal transmitter and signal receiver;

[0053] Figure 9 In the embodiment of the present invention Figure 6 Another side view of the positional relationship between the scatterer cluster of the obstacle shown in the line-of-sight condition and the signal transmitter and signal receiver;

[0054] Figure 10 In the embodiment of the present invention Figure 6 Top view of the positional relationship between the scatterer cluster of the obstacle shown in the non-line-of-sight condition and the signal transmitter and signal receiver;

[0055] Figure 11 In the embodiment of the present invention Figure 6 One of the side views of the positional relationship between the scatterer cluster of the obstacle shown in the non-line-of-sight condition and the signal transmitter and signal receiver;

[0056] Figure 12 In the embodiment of the present invention Figure 6 Another side view of the positional relationship between the scatterer cluster of the obstacle shown in the non-line-of-sight condition and the signal transmitter and signal receiver;

[0057] Figure 13 Schematic diagram of the positional relationship between the reference antenna unit and the obstacle in the embodiment of the present invention;

[0058] Figure 14 Schematic diagram of the structure of the channel modeling device for the near-field space non-stationary characteristic in the embodiment of the present invention. Detailed implementation manners

[0059] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0060] The embodiment of the present invention provides a channel modeling method for the non-stationary characteristics of the near-field space. Based on the construction method of the 3GPP standard channel model in the prior art, the acquisition of the near-field propagation channel parameters of the near-field space and the acquisition of the spatial non-stationary attenuation factor are added to generate a channel model with non-stationary characteristics of the near-field space. The construction method of the 3GPP standard channel model is well known to those skilled in the art, so the present invention will not elaborate on the construction method of the 3GPP standard channel model.

[0061] As Figure 1 shown, the embodiment of the present invention provides a channel modeling method for the non-stationary characteristics of the near-field space, including:

[0062] Step S101, in the near-field propagation space, determine the propagation distance of each scatterer cluster according to the cluster delay information of the scatterer cluster and the pre-configured distance information of the scatterer cluster; wherein, the distance information includes the distance distribution information between the scatterer cluster and the signal transmitter and / or the distance distribution information between the scatterer cluster and the signal receiver;

[0063] In step S101, in order to reduce the computational complexity, the distance distribution information between the scatterer cluster and the signal transmitter and / or the distance distribution information between the scatterer cluster and the signal receiver are pre-acquired, and then based on the construction method of the 3GPP standard channel model, the cluster delay information of the scatterer cluster is obtained. The present invention will not elaborate on this. After obtaining the cluster delay information, then according to the corresponding relationship between the cluster delay of the scatterer cluster and the propagation distance, that is, the larger the cluster delay, the farther the corresponding propagation distance, combined with the distance information of the scatterer cluster, determine the actual propagation distance of each scatterer cluster.

[0064] Among them, the embodiments of the present invention only focus on the distance distribution information between the scatterer cluster and the antenna array of the multi-antenna, and ignore the distance distribution information between the scatterer cluster and the single antenna. For example, the signal transmitter is a Base Station (BS), and the signal receiver is a User Terminal (UT); if both the BS and the UT are antenna arrays composed of multiple antennas, the distance information includes the distance distribution information between the scatterer cluster and the BS and the distance distribution information between the scatterer cluster and the UT. If the antenna of the BS is an antenna array composed of multiple antennas and the antenna of the UT is a single antenna, the distance information only includes the distance distribution information between the scatterer cluster and the BS.

[0065] Step S102: Generate the spatial coordinate information of the scatterer cluster according to the arrival angle information, departure angle information and the propagation distance of the scatterer cluster;

[0066] In step S102, the arrival angle information and departure angle information of the scatterer cluster are also obtained based on the construction method of the 3GPP standard channel model, which is not elaborated in the present invention. According to the angle information and propagation distance of the scatterer cluster, the three-dimensional coordinate information of the scatterer cluster, that is, the spatial coordinate information, is determined, and the calculation complexity is low.

[0067] Step S103: Determine the near-field propagation channel parameters according to the spatial coordinate information;

[0068] In step S103, according to the spatial coordinate information of the scatterer cluster, the distances between the scatterer cluster and different antenna elements of the signal receiver / signal transmitter can be calculated, and then according to the distances between the scatterer cluster and the antenna elements, the near-field propagation channel parameters are determined. The near-field propagation channel parameters include, but are not limited to, the delay parameter and phase parameter under the near-field spherical wave propagation.

[0069] Step S104: Obtain the non-stationary attenuation factor of the near-field propagation space according to the parameter information and position information of the obstacles in the near-field propagation space;

[0070] In step S104, based on the occlusion model in the standard channel model, according to the parameter information and position information of the obstacles arranged between the signal receiver and the signal transmitter in the near-field propagation space, the non-stationary attenuation factor caused by occlusion is obtained, ensuring the spatial consistency between different scatterer clusters and different antenna elements. It should be noted that, for the convenience of calculation, in the embodiments of the present invention, all the obstacles are simplified into rectangular screens of different sizes.

[0071] Step S105: Based on the standard channel model, construct a channel model with non-stationary characteristics of the near-field space according to the near-field propagation channel parameters and the non-stationary attenuation factor.

[0072] In step S105, based on the 3GPP standard channel model, the near-field propagation channel parameters and the non-stationary attenuation factor are substituted into the standard channel model to obtain the channel coefficients, and then a channel model with near-field spatial non-stationary characteristics is constructed.

[0073] In the embodiment of the present invention, aiming at the near-field spatial non-stationary characteristics existing in the existing large-scale MIMO channels, a channel modeling method with near-field spatial non-stationary characteristics is proposed. It is divided into two parts: near-field propagation channel and spatial non-stationary characteristics for separate modeling. For the near-field propagation channel, first, according to the cluster delay information of the scatterer clusters and the pre-configured distance information of the scatterer clusters, the propagation distance of each scatterer cluster is determined; wherein, the distance information includes the pre-determined distance distribution information between the scatterer cluster and the signal transmitter and / or the pre-determined distance distribution information between the scatterer cluster and the signal receiver; then, according to the propagation distance, the angle of arrival information and the angle of departure information of the scatterer cluster, the spatial coordinate information of the scatterer cluster is obtained, and then the near-field propagation channel parameters are determined, reducing the computational complexity compared with the prior art. For the spatial non-stationary characteristics, according to the parameter information of the obstacles in the near-field propagation space, the non-stationary attenuation factor of the near-field propagation space is obtained; ensuring the spatial consistency between different scatterer clusters and different antenna elements, and improving the accuracy of the model. Finally, based on the existing 3GPP standard channel model, substituting the near-field propagation channel parameters and the non-stationary attenuation factor, a channel model with near-field spatial non-stationary characteristics is constructed, improving the versatility and usability of the present invention. Therefore, the method of the embodiment of the present invention for constructing a channel with near-field spatial non-stationary characteristics has a lower computational complexity, a higher accuracy of the constructed model, and better versatility and usability.

[0074] Optionally, the method further includes:

[0075] By simulating the distribution of the scatterer clusters in different near-field scenarios, the simulated distances between multiple scatterer clusters and the signal transmitter and / or the simulated distances between multiple scatterer clusters and the signal receiver are obtained;

[0076] Statistically analyze the simulated distances and fit to generate a normal distribution model;

[0077] According to the normal distribution model, the distance information of the scatterer clusters is obtained.

[0078] In an embodiment of the present invention, a channel emulator is used to simulate a variety of near-field scenarios. Under different propagation conditions, the simulation distances between the scatterer clusters and the signal transmitter and / or between the scatterer clusters and the signal receiver are obtained respectively. Among them, the near-field scenarios include but are not limited to: Indoor office (INH) and Urban Macro (UMa), and the propagation conditions include but are not limited to: Line of sight (LOS) and Non line of sight (NLOS). Statistical analysis is performed on the simulation distance between the scatterer cluster and the signal transmitter. Since it well follows the log-normal distribution, a normal distribution model is generated by fitting. Similarly, for the simulation distance between the scatterer cluster and the signal receiver, since it well follows the log-normal distribution, a normal distribution model is generated by fitting. The distance information of the scatterer cluster can be directly obtained according to the normal distribution model.

[0079] The following uses a specific embodiment to illustrate the simulation process of obtaining the distance information of the scatterer cluster:

[0080] The channel emulator is used to perform multiple repeated simulations on a large number of randomly scattered users in the INH scenario and the UMa scenario. Among them, the signal transmitter is the Base Station (BS), and the signal receiver is the User Terminal (UT). It is assumed that the antenna array used by the BS is a Uniform planar array (UPA), and the UT uses a single antenna. Then, in this embodiment, the distance information between the scatterer cluster and the UT is ignored, and only the distance information between the scatterer cluster and the BS is considered. The simulation parameter configuration is shown in Table 1;

[0081]

[0082] Table 1;

[0083] Based on the above simulation parameter configuration, simulation is performed to obtain the simulation distance between the scatterer cluster and the BS, and statistical analysis is performed on it to generate a normal distribution model by fitting, as Figures 2 to 4 shown. It can be observed that the distance between the cluster and the BS well follows the log-normal distribution. Among them, Figure 2 a schematic diagram of the probability density function (PDF) and its fitting result of the distances between all scatterer clusters and the BS of some users under the LOS propagation in the INH scenario is provided, which follows a mean μ = 0.8773 and a standard deviation σ = 0.6047. Figure 3The PDF of the distances between all scatterer clusters of some users and the BS in NLOS propagation in the INH scenario and its fitting result diagram are provided, which follows a normal distribution with a mean μ = 0.9361 and a standard deviation σ = 0.4944. Figure 4 The PDF of the distances between all scatterer clusters of some users and the BS in LOS propagation in the UMa scenario and its fitting result diagram are provided, which follows a normal distribution with a mean μ = 0.8970 and a standard deviation σ = 0.3918. Figure 5 The PDF of the distances between all scatterer clusters of some users and the BS in NLOS propagation in the UMa scenario and its fitting result diagram are provided, which follows a normal distribution with a mean μ = 1.9173 and a standard deviation σ = 0.3979.

[0084] Optionally, according to the cluster delay information of the scatterer clusters and the distance information of the scatterer clusters, determine the propagation distance of each scatterer cluster, including:

[0085] Randomly generate a plurality of first distances between the scatterer clusters and the signal transmitter and / or a plurality of first distances between the scatterer clusters and the signal receiver according to the pre-configured distance information of the scatterer clusters;

[0086] Match the cluster delay information with the first distance according to the corresponding relationship between the cluster delay information of the scatterer clusters and the magnitude of the first distance, and determine the propagation distance of each scatterer cluster.

[0087] In the embodiments of the present invention, a method for obtaining the propagation distance of scatterer clusters is provided, which is simpler than the prior art and reduces the computational complexity. Specifically, in the embodiments of the present invention, based on the pre-configured distance information of the scatterer clusters, it can be known that the distances between the scatterer clusters and the signal transmitter and / or the signal receiver follow a lognormal distribution. According to the properties of the lognormal distribution, a plurality of first distances between the scatterer clusters and the signal transmitter and / or a plurality of first distances between the scatterer clusters and the signal receiver can be randomly generated. After obtaining the first distance, the first distance is matched with the cluster delay of the scatterer clusters. It is known that the greater the cluster delay of the scatterer clusters, the farther the propagation distance, that is, the farther the first distance corresponding to the scatterer clusters. Specifically, the cluster delays of the scatterer clusters are arranged in descending order, and the first distances corresponding to the scatterer clusters are also arranged in descending order, and then the cluster delays and the first distances are corresponded one by one, and the propagation distance of the corresponding scatterer clusters is determined according to the cluster delays. On the premise of ensuring the calculation accuracy, the computational complexity is greatly reduced.

[0088] For example: Still assuming that the antenna array used by the signal transmitting end BS is a UPA and the signal receiving end UT uses a single antenna, and this embodiment only considers the distance information between the scatterer cluster and the BS, then all the first distances between each user's scatterer clusters and the BS are randomly obtained from the lognormal distribution that the distance between the scatterer cluster and the BS follows, that is:

[0089] where d′ n is the first distance between the randomly generated scatterer cluster and the BS. X follows a lognormal distribution with a mean of μ and a variance of σ 2 , n is the serial number of the scatterer cluster, and n is an integer greater than or equal to 1.

[0090] Match according to the first distance and the cluster time delay to determine the propagation distance of the scatterer cluster:

[0091]

[0092] where d′ n is the first distance between the nth scatterer cluster and the BS, τ n is the time delay of the nth scatterer cluster, and d n is the propagation distance between the nth scatterer cluster and the BS.

[0093] Optionally, generating the spatial coordinate information of the scatterer cluster according to the arrival angle information, departure angle information and the propagation distance of the scatterer cluster includes:

[0094] Generating the spatial coordinate information of the first-hop scatterer cluster corresponding to the signal transmitting end according to the departure angle information of each scatterer cluster and the propagation distance;

[0095] Generating the spatial coordinate information of the last-hop scatterer cluster corresponding to the signal receiving end according to the arrival angle information of each scatterer cluster and the propagation distance.

[0096] In the embodiment of the present invention, the spatial coordinate information of the scatterer cluster is obtained through the angle information of the scatterer cluster. Among them, the departure angle information includes the vertical departure angle (Zenith angle of departure, ZOD) and the horizontal departure angle (Azimuth angle of departure, AOD), and the arrival angle information includes the vertical arrival angle (Zenith angle of arrival, ZOA) and the horizontal arrival angle (Azimuth angle of arrival, AOA).

[0097] Generate the spatial coordinate information of the first-hop scatterer cluster corresponding to the signal transmitter through the ZOD, AOD, and propagation distance of the scatterer cluster, and generate the spatial coordinate information of the last-hop scatterer cluster corresponding to the signal receiver through the ZOA, AOA, and propagation distance of the scatterer cluster, so as to obtain the spatial coordinate information of the scatterer cluster.

[0098] Through the ZOD, AOD, and propagation distance d of the scatterer cluster n , the formula for generating the spatial coordinate information of the first-hop scatterer cluster corresponding to the signal transmitter is as follows:

[0099]

[0100] Similarly, the spatial coordinate information of the last-hop scatterer cluster corresponding to the signal receiver can be obtained, and the formula is as follows:

[0101]

[0102] Optionally, the parameter information of the obstacle includes one or more of the following:

[0103] The type of the obstacle;

[0104] The size information of the obstacle;

[0105] The movement mode information of the obstacle.

[0106] In the embodiments of the present invention, the obstacle between the signal transmitter and the signal receiver is modeled according to the near-field space scenario, where the parameter information of the obstacle includes, but is not limited to, the type, size information, and movement mode information; wherein, for the convenience of calculation, all obstacles are simplified into rectangular screens, and the size information of the obstacle is represented by the height and width of the rectangular screen, and the movement mode information is used to determine whether the obstacle is in a moving state or a stationary state. Table 2 gives the parameter information of typical obstacles, which can be used as a reference for selecting obstacles during modeling, and allows different blocking scenarios to be constructed according to the needs of specific simulation studies.

[0107]

[0108] Table 2.

[0109] Optionally, obtaining the non-stationary attenuation factor of the near-field propagation space according to the parameter information and position information of the obstacle in the near-field propagation space includes:

[0110] Obtain the projection distance information between the signal transmitter and the signal receiver and the obstacle respectively according to the parameter information and position information of the obstacle in the near-field propagation space;

[0111] Establishing a blade diffraction model of the obstruction according to the projection distance information;

[0112] According to the knife-edge diffraction model, a non-stationary attenuation factor of the near-field propagation space is obtained.

[0113] In an embodiment of the present invention, the position information of the obstruction is determined based on the distances between the obstruction and the signal transmitting end and the signal receiving end respectively, and the distances between the obstruction and the signal transmitting end and the signal receiving end respectively are obtained by simulating multiple obstructions in different scenes. The acquisition method is similar to the method described in the above content of this article of simulating the distribution of scatterers in different scenes to obtain the distance information of the scatterer cluster, which will not be repeated here.

[0114] First, according to the location information and parameter information of the shielding object, the projection distance information between the signal transmitting end and the signal receiving end and the four edges of the shielding object is determined. Each shielding object is in the shape of a rectangular screen, and its dimensions are respectively: height h k and width k ,like Figures 6 to 12 As shown, the definition is the projection distance between the signal receiving end and the four edges of the corresponding obstruction, is the projection distance between the signal transmitting end and the four edges of the corresponding obstruction, where h1, h2, w1, and w2 are different edges of the obstruction. Specifically, under different propagation conditions, such as LOS and NLOS conditions, the determined projection distance is also different. Figure 6 is the full view of the occluder, and the coordinates of the center of the screen (x k ,y k ,z k ); Figure 7 for Figure 6 A top view of the positional relationship between the scatterer cluster and the signal transmitting end TX and the signal receiving end RX of the obstruction under LOS conditions shown; Figure 8 and Figure 9 Both Figure 6 A side view of the positional relationship between the scatterer cluster and the signal transmitting end TX and the signal receiving end RX of the obstruction under LOS conditions shown; Figure 10 for Figure 6 A top view of the positional relationship between the scatterer cluster and the signal transmitting end TX and the signal receiving end RX of the obstruction under NLOS conditions (the signal transmitting end TX is not marked in the figure); Figure 11 and Figure 12 Both Figure 6 The illustrated side view shows the positional relationship between the scatterer cluster and the signal transmitting end TX and the signal receiving end RX under NLOS conditions (the signal transmitting end TX is not marked in the figure).

[0115] Then, based on the projection distance information, i.e., and establish the knife-edge diffraction model of the obstacle under different propagation conditions (such as LOS and NLOS), and define which represent the knife-edge diffraction of the four sides of the rectangular screen of the obstacle respectively. The formulas are as follows:

[0116]

[0117] where λ is the wavelength. Since the rectangular screen should be perpendicular to each cluster, r is the direct distance between the signal transmitter and the signal receiver, and r′ is the projection distance of the distance between the obstacle and the signal receiver in the direction of the arrival angle of the NLOS cluster. In the above formulas, the method for determining the plus and minus signs is as follows:

[0118] If the scatterer cluster (terminating at the signal receiver or the signal transmitter) does not intersect the rectangular screen (obstacle) in the side view, then in the NLOS case and the shortest path is a negative sign (in the LOS case it is and ), and the other side takes a positive sign.

[0119] If the scatterer cluster (terminating at the signal receiver or the signal transmitter) does not intersect the rectangular screen (obstacle) in the top view, then in the NLOS case and the shortest path takes a negative sign (in the LOS case it is and ), and the other side takes a positive sign.

[0120] If the scatterer cluster intersects the rectangular screen (obstacle), then positive signs should be taken for both sides.

[0121] In addition, it should be noted that in the standard channel model, the obstacle needs to rotate around its center so that the arrival direction of the corresponding scatterer cluster is always perpendicular to the rectangular screen of the obstacle. However, for a large antenna array, the positions of the antenna elements cannot be exactly the same, especially considering near-field propagation. Even in the same scatterer cluster, the arrival directions of each antenna element pair may be different. Therefore, since the arrival directions of each antenna element pair are different, the rotation may need to change with the arrival direction of each antenna element pair. To simplify the model, a reference antenna element pair can be determined first. As Figure 13 shown, the gray point can be selected as the reference antenna pair.

[0122] For the reference antenna element pair, the occluder rectangular screen rotates around its center such that the direction of arrival of the corresponding cluster of scatterers is always perpendicular to the occluder rectangular screen. Then, under the same occlusion rotation of the reference antenna element pair, the occlusion conditions of other element pairs can be directly determined, and the occlusion attenuation can be calculated.

[0123] Finally, the spatially non-stationary attenuation factor caused by each occluder for each cluster of scatterers is modeled by the knife-edge diffraction model obtained in the previous step, and the expression is:

[0124]

[0125] L dB For the case of rectangular screens of multiple occluders, it is the sum of the losses of each occluder rectangular screen. The above model is consistent in time, frequency, and space, and is more suitable for arbitrarily specifying an occluder to simulate the spatially non-stationary characteristics caused by occlusion. Based on the occlusion model, according to the geometric relationship between the determined position of the occluder and the receiving antenna element of the signal receiving end and the transmitting antenna element of the signal transmitting end, the occlusion conditions and attenuation caused by occlusion are determined. At the same time, this method can not only model the spatially non-stationary characteristics caused by occlusion but also ensure the consistency between different clusters of scatterers and between antenna elements.

[0126] Optionally, the obtaining of the projection distance information between the signal transmitting end and the signal receiving end and the occluder respectively according to the parameter information and position information of the occluder in the near-field propagation space includes:

[0127] According to the position information of the occluder in the near-field propagation space, a position schematic diagram among the occluder, the signal transmitting end, and the signal receiving end in the near-field propagation space is obtained; wherein, the position schematic diagram includes a side view projection schematic diagram and a top view projection schematic diagram;

[0128] Using the position schematic diagram, according to the parameter information of the first occluder, the projection distance information between the signal transmitting end and the edge of the first occluder is obtained, wherein the first occluder is the occluder whose distance from the signal transmitting end satisfies a first preset condition;

[0129] Using the position schematic diagram, according to the parameter information of the second occluder, the projection distance information between the signal receiving end and the edge of the second occluder is obtained, wherein the second occluder is the occluder whose distance from the signal transmitting end satisfies a second preset condition.

[0130] In the embodiment of the present invention, as Figures 6 to 12As shown, according to the position information of the obstacles in the near-field propagation space, the position information of the signal transmitter and the signal receiver, a side view projection schematic diagram and a top view projection schematic diagram of the obstacles, the signal transmitter, and the signal receiver in the near-field propagation space are generated; in actual calculation, the occlusion effect weakens as the distance from the obstacle increases. To achieve the purpose, not all obstacles need to be considered. For the signal transmitter, only the occlusion situation of the first obstacles that meet the first preset condition needs to be considered. For the signal receiver, only the occlusion situation of the second obstacles that meet the second preset condition needs to be considered. For example: the signal transmitter is BS, and the signal receiver is UT. For the occlusion model on the BS side, only consider the occlusion situation of the K obstacles closest to BS or the obstacles closer to a specific UT. For the occlusion model on the UT side, only consider at most two of the closest hand-shaped obstacles or one head-shaped obstacle.

[0131] As Figure 14 shown, an embodiment of the present invention further provides a channel modeling device for non-stationary characteristics of the near-field space, including:

[0132] A first determination module 1401, configured to determine the propagation distance of each scatterer cluster in the near-field propagation space according to the cluster delay information of the scatterer clusters and the pre-configured distance information of the scatterer clusters; wherein, the distance information includes the distance distribution information between the scatterer clusters and the signal transmitter and / or the distance distribution information between the scatterer clusters and the signal receiver;

[0133] A first generation module 1402, configured to generate the spatial coordinate information of the scatterer clusters according to the arrival angle information, departure angle information, and the propagation distance of the scatterer clusters;

[0134] A first calculation module 1403, configured to determine the near-field propagation channel parameters according to the spatial coordinate information;

[0135] A second calculation module 1404, configured to obtain the non-stationary attenuation factor of the near-field propagation space according to the parameter information and position information of the obstacles in the near-field propagation space;

[0136] A first construction module 1405, configured to construct a channel model for non-stationary characteristics of the near-field space based on the standard channel model according to the near-field propagation channel parameters and the non-stationary attenuation factor.

[0137] Optionally, the device further includes:

[0138] A first simulation module, configured to obtain the simulation distances between multiple scatterer clusters and the signal transmitter and / or the simulation distances between multiple scatterer clusters and the signal receiver by simulating the distribution of the scatterer clusters in different near-field scenarios;

[0139] The first statistical module is used to statistically analyze the simulation distance and fit and generate a normal distribution model;

[0140] The first acquisition module is used to obtain the distance information of the scatterer cluster according to the normal distribution model.

[0141] Optionally, the first determination module 1401 includes:

[0142] The first generation unit is used to randomly generate a plurality of first distances between the scatterer clusters and the signal transmitter and / or a plurality of first distances between the scatterer clusters and the signal receiver according to the pre-configured distance information of the scatterer clusters;

[0143] The first matching unit is used to match the cluster delay information with the first distance according to the corresponding relationship between the cluster delay information of the scatterer cluster and the magnitude of the first distance, and determine the propagation distance of each scatterer cluster.

[0144] Optionally, the first generation module 1402 includes:

[0145] The second generation unit is used to generate the spatial coordinate information of the first-hop scatterer cluster corresponding to the signal transmitter according to the departure angle information of each scatterer cluster and the propagation distance;

[0146] The third generation unit is used to generate the spatial coordinate information of the last-hop scatterer cluster corresponding to the signal receiver according to the arrival angle information of each scatterer cluster and the propagation distance.

[0147] Optionally, the parameter information of the obstacle in the second calculation module 1404 includes one or more of the following:

[0148] The type of the obstacle;

[0149] The size information of the obstacle;

[0150] The movement mode information of the obstacle.

[0151] Optionally, the second calculation module 1404 includes:

[0152] The first calculation unit is used to obtain the projection distance information between the signal transmitter and the signal receiver and the obstacle respectively according to the parameter information and position information of the obstacle in the near-field propagation space;

[0153] The first establishment unit is used to establish the knife-edge diffraction model of the obstacle according to the projection distance information.

[0154] A second calculation unit, configured to obtain a non-stationary attenuation factor of the near-field propagation space according to the blade diffraction model.

[0155] Optionally, the first calculation unit includes:

[0156] A third generation unit, configured to obtain a position schematic diagram among the obstacle, the signal transmitter, and the signal receiver in the near-field propagation space according to the position information of the obstacle in the near-field propagation space; wherein, the position schematic diagram includes a side-view projection schematic diagram and a top-view projection schematic diagram;

[0157] A third calculation unit, configured to use the position schematic diagram to obtain projection distance information between the signal transmitter and the edge of the first obstacle according to the parameter information of the first obstacle, where the first obstacle is the obstacle whose distance from the signal transmitter satisfies a first preset condition;

[0158] A fourth calculation unit, configured to use the position schematic diagram to obtain projection distance information between the signal receiver and the edge of the second obstacle according to the parameter information of the second obstacle, where the second obstacle is the obstacle whose distance from the signal transmitter satisfies a second preset condition.

[0159] It should be noted that the embodiment of this device is a device corresponding to the embodiment of the above method. All implementation manners in the embodiment of the above method are applicable to the embodiment of this device and can achieve the same technical effect.

[0160] An embodiment of the present invention further provides a network device, including: a processor, a memory, and a program stored on the memory and executable on the processor. When the program is executed by the processor, it implements the channel modeling method for non-stationary characteristics of the near-field space as described in any one of the above, and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0161] An embodiment of the present invention further provides a readable storage medium, including: a program stored on the readable storage medium. When the program is executed by a processor, it implements the steps of the channel modeling method for non-stationary characteristics of the near-field space as described in any one of the above, and can achieve the same technical effect. To avoid repetition, it will not be elaborated here. Wherein, the readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0162] An embodiment of the present invention further provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the channel modeling method for non-stationary characteristics of the near-field space described in any one of the above, and can achieve the same technical effects. To avoid repetition, details are not described herein again.

[0163] It should be noted that, in this document, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

[0164] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A channel modeling method for near-field spatial non-stationary characteristics, characterized in that: include: In the near-field propagation space, the propagation distance of each scatterer cluster is determined according to the cluster delay information of the scatterer cluster and the pre-configured distance information of the scatterer cluster; wherein the distance information includes the distance distribution information between the scatterer cluster and the signal transmitting end and / or the distance distribution information between the scatterer cluster and the signal receiving end; Generate spatial coordinate information of the scatterer cluster according to the arrival angle information, departure angle information and the propagation distance of the scatterer cluster; Determining near-field propagation channel parameters according to the spatial coordinate information; Obtaining a non-stationary attenuation factor of the near-field propagation space according to parameter information and position information of the obstruction in the near-field propagation space; Based on the standard channel model, a channel model of near-field spatial non-stationary characteristics is constructed according to the near-field propagation channel parameters and the non-stationary attenuation factor.

2. The channel modeling method of near-field spatial non-stationary characteristics according to claim 1 is characterized in that: The method further comprises: By simulating the distribution of the scatterer clusters in different near-field scenarios, the simulated distances between the plurality of scatterer clusters and the signal transmitting end and / or the simulated distances between the plurality of scatterer clusters and the signal receiving end are obtained; Performing statistical analysis on the simulation distance and fitting to generate a normal distribution model; According to the normal distribution model, distance information of the scatterer cluster is obtained.

3. The channel modeling method of near-field spatial non-stationary characteristics according to claim 1 is characterized in that: Determining the propagation distance of each scatterer cluster according to the cluster delay information of the scatterer cluster and the pre-configured distance information of the scatterer cluster includes: Randomly generate first distances between a plurality of scatterer clusters and the signal transmitting end and / or first distances between a plurality of scatterer clusters and the signal receiving end according to preconfigured distance information of the scatterer clusters; According to the corresponding relationship between the cluster delay information of the scatterer cluster and the first distance, the cluster delay information is matched with the first distance to determine the propagation distance of each of the scatterer clusters.

4. The channel modeling method of near-field spatial non-stationary characteristics according to claim 1 is characterized in that: The generating the spatial coordinate information of the scatterer cluster according to the arrival angle information, the departure angle information and the propagation distance of the scatterer cluster comprises: Generate spatial coordinate information of a first-hop scatterer cluster corresponding to the signal transmitting end according to the departure angle information and the propagation distance of each scatterer cluster; The spatial coordinate information of the last-hop scatterer cluster corresponding to the signal receiving end is generated according to the arrival angle information and the propagation distance of each scatterer cluster.

5. The channel modeling method of near-field spatial non-stationary characteristics according to claim 1 is characterized in that: The parameter information of the obstruction includes one or more of the following: Type of occluder; The size information of the occluder; Movement pattern information of the occluder.

6. The channel modeling method of near-field spatial non-stationary characteristics according to claim 5 is characterized in that: The step of obtaining the non-stationary attenuation factor of the near-field propagation space according to the parameter information and position information of the obstruction in the near-field propagation space comprises: According to the parameter information and position information of the obstruction in the near-field propagation space, obtaining the projection distance information between the signal transmitting end and the signal receiving end and the obstruction respectively; Establishing a blade diffraction model of the obstruction according to the projection distance information; According to the knife-edge diffraction model, a non-stationary attenuation factor of the near-field propagation space is obtained.

7. The channel modeling method of near-field spatial non-stationary characteristics according to claim 6 is characterized in that: The obtaining, according to the parameter information and position information of the obstruction in the near-field propagation space, projection distance information between the signal transmitting end and the signal receiving end and the obstruction respectively includes: According to the position information of the obstruction in the near-field propagation space, a position schematic diagram between the obstruction in the near-field propagation space, the signal transmitting end, and the signal receiving end is obtained; wherein the position schematic diagram includes a side projection schematic diagram and a top projection schematic diagram; Using the position diagram, according to the parameter information of the first shielding object, obtaining the projection distance information between the signal transmitting end and the edge of the first shielding object, wherein the first shielding object is the shielding object whose distance from the signal transmitting end meets the first preset condition; Using the position diagram and according to the parameter information of the second obstruction, the projection distance information between the signal receiving end and the edge of the second obstruction is obtained, wherein the second obstruction is the obstruction whose distance from the signal transmitting end meets a second preset condition.

8. A channel modeling device for near-field spatial non-stationary characteristics, characterized in that: include: A first determination module is used to determine the propagation distance of each scatterer cluster in the near-field propagation space according to the cluster delay information of the scatterer cluster and the pre-configured distance information of the scatterer cluster; wherein the distance information includes the distance distribution information between the scatterer cluster and the signal transmitting end and / or the distance distribution information between the scatterer cluster and the signal receiving end; A first generating module, configured to generate spatial coordinate information of the scatterer cluster according to the arrival angle information, the departure angle information and the propagation distance of the scatterer cluster; A first calculation module, used to determine near-field propagation channel parameters according to the spatial coordinate information; A second calculation module, used for obtaining a non-stationary attenuation factor of the near-field propagation space according to parameter information and position information of the obstruction in the near-field propagation space; The first construction module is used to construct a channel model of near-field spatial non-stationary characteristics based on a standard channel model according to the near-field propagation channel parameters and the non-stationary attenuation factor.

9. A network device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the channel modeling method for near-field spatial non-stationary characteristics as described in any one of claims 1 to 7.

10. A readable storage medium, characterized in that: include: The readable storage medium stores a program, and when the program is executed by a processor, the steps of the channel modeling method of near-field spatial non-stationary characteristics as described in any one of claims 1 to 8 are implemented.

11. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps of the channel modeling method of near-field spatial non-stationary characteristics as described in any one of claims 1 to 8.

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