Excitation information determination method, electronic device and computer program product

Abstract

The invention provides an excitation information determination method, electronic equipment and a computer program product, and at least solves the technical problem that a preset excitation scheme cannot meet the excitation requirement of an array antenna in related technologies. Comprising the following steps: acquiring a first antenna pattern of an array antenna, the first antenna pattern being used for representing target signal intensity in each direction in a target space; target excitation data corresponding to the array antenna is determined based on the first antenna pattern, the target excitation data comprises excitation information, and the excitation information is used for indicating the signal strength and phase of a signal transmitted by an antenna unit in the array antenna.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a method for determining incentive information, an electronic device, and a computer program product. Background Art

[0002] Currently, the array antenna on the terminal sends a signal based on a preset excitation scheme corresponding to the target area so that the signal can cover the target area.

[0003] However, in the above method, the array antenna can only send signals based on one or several preset excitation schemes. When the excitation scheme required by the array antenna does not exist in the one or several preset excitation schemes, there is a problem that the preset excitation scheme cannot meet the excitation requirements of the array antenna, and the reliability of signal coverage cannot be guaranteed. Summary of the Invention

[0004] The embodiments of the present disclosure provide a method for determining excitation information, an electronic device, and a computer program product, which at least solve the technical problem in related technologies that the preset excitation scheme cannot meet the excitation requirements of the array antenna.

[0005] On the one hand, a method for determining excitation information is provided, including: obtaining a first antenna pattern, the first antenna pattern being used to characterize the target signal strength in various directions within the target space; based on the first antenna pattern of the array antenna, determining target excitation data corresponding to the array antenna, the target excitation data including excitation information, wherein the excitation information is used to indicate the signal strength and phase of the signal emitted by the antenna unit in the array antenna.

[0006] On the other hand, an excitation information determination device is provided, including: an acquisition module and a determination module; the acquisition module is used to obtain a first antenna pattern of the array antenna, the first antenna pattern is used to characterize the target signal strength in each direction within the target space; the determination module is used to determine the target excitation data corresponding to the array antenna based on the first antenna pattern, the target excitation data includes excitation information, wherein the excitation information is used to indicate the signal strength and phase of the signal emitted by the antenna unit in the array antenna.

[0007] On the other hand, an electronic device is provided, comprising: a memory and a processor; the memory and the processor are coupled; the memory is used to store a computer program; when the processor executes the computer program, it implements the signal transmission method described in any of the above embodiments, or implements the directional pattern generation model training method described in any of the above embodiments, or implements the excitation data generation model training method described in any of the above embodiments.

[0008] On the other hand, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the signal transmission method described in any of the above embodiments, or the directional pattern generation model training method described in any of the above embodiments, or the excitation data generation model training method described in any of the above embodiments are implemented.

[0009] On the other hand, a computer program product is provided, which includes computer program instructions, which, when executed by a processor, implement the signal transmission method described in any of the above embodiments, or implement the directional pattern generation model training method described in any of the above embodiments, or implement the excitation data generation model training method described in any of the above embodiments.

[0010] In an embodiment of the present disclosure, the electronic device obtains a first antenna pattern of the array antenna, where the first antenna pattern is used to characterize the target signal strength in various directions within the target space. Based on the first antenna pattern, target excitation data corresponding to the array antenna is determined, where the target excitation data includes excitation information, where each excitation information is used to indicate the signal strength and phase of a signal sent by an antenna unit on the array antenna. In this way, the electronic device can reliably generate excitation data based on the first antenna pattern of the array antenna, so that the antenna pattern corresponding to the signal transmitted by the array antenna is the first antenna pattern. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present disclosure, the following briefly introduces the drawings required for use in some embodiments of the present disclosure. Obviously, the drawings described below are only drawings of some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0012] Figure 1 A schematic diagram of a network architecture of an incentive information determination system provided in some embodiments of the present disclosure;

[0013] Figure 2 A flowchart of a method for determining incentive information provided in some embodiments of the present disclosure;

[0014] Figure 3 A flowchart of another method for determining incentive information provided in some embodiments of the present disclosure;

[0015] Figure 4 A flowchart of another method for determining incentive information provided in some embodiments of the present disclosure;

[0016] Figure 5 A flowchart of another method for determining incentive information provided in some embodiments of the present disclosure;

[0017] Figure 6 A schematic diagram of a coordinate system of an antenna pattern provided in some embodiments of the present disclosure;

[0018] Figure 7 A flowchart of another method for determining incentive information provided in some embodiments of the present disclosure;

[0019] Figure 8 A flowchart of another method for determining incentive information provided in some embodiments of the present disclosure;

[0020] Figure 9 A schematic diagram of a zoomed antenna pattern provided in some embodiments of the present disclosure;

[0021] Figure 10 A flowchart of another method for determining incentive information provided in some embodiments of the present disclosure;

[0022] Figure 11 A flowchart of a method for training a directional pattern generation model provided in some embodiments of the present disclosure;

[0023] Figure 12 A flowchart of another directional pattern generation model training method provided in some embodiments of the present disclosure;

[0024] Figure 13 A flowchart of another directional pattern generation model training method provided in some embodiments of the present disclosure;

[0025] Figure 14 A flowchart of a method for training a motivational data generation model provided in some embodiments of the present disclosure;

[0026] Figure 15 A flowchart of another method for training a model for generating incentive data provided in some embodiments of the present disclosure;

[0027] Figure 16 A flowchart of another method for training a model for generating incentive data provided in some embodiments of the present disclosure;

[0028] Figure 17 A schematic diagram of the internal structure of an array antenna provided in some embodiments of the present disclosure;

[0029] Figure 18 A schematic structural diagram of an incentive information determination device provided in some embodiments of the present disclosure;

[0030] Figure 19 A schematic structural diagram of an electronic device provided in some embodiments of the present disclosure. DETAILED DESCRIPTION

[0031] The following will clearly and completely describe the technical solutions of this disclosure in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this disclosure, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of this disclosure without making any creative efforts shall fall within the scope of protection of this disclosure.

[0032] It should be noted that in this disclosure, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described in this disclosure as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0033] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the quantity of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features.

[0034] In the description of this disclosure, unless otherwise specified, " / " means "or." For example, A / B can mean A or B. "And / or" in this document simply describes an association relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A exists alone, A and B exists simultaneously, and B exists alone. Furthermore, "at least one" means one or more, and "a plurality" means two or more.

[0035] Currently, array antennas can transmit signals using different excitation schemes based on preset excitation schemes to meet different signal coverage requirements. However, some signal coverage requirements do not have corresponding preset excitation schemes. In such cases, only configuring the preset excitation scheme for the array antenna results in fixed usage scenarios and lacks flexibility.

[0036] To solve the above problems, an embodiment of the present disclosure proposes a method for determining excitation information. The electronic device can reliably generate excitation data based on the first antenna pattern of the array antenna, so that the antenna pattern corresponding to the signal emitted by the array antenna is the first antenna pattern. Thus, the electronic device can generate an excitation scheme corresponding to the first antenna pattern, thereby increasing the real-time performance of the excitation scheme, that is, according to the signal coverage requirement corresponding to the first antenna pattern, the array antenna excitation scheme corresponding to the signal coverage requirement is determined in real time.

[0037] The embodiments of the present disclosure provide a method for determining incentive information, an electronic device, and a computer program product, which are applied to an incentive information determination system, such as Figure 1 As shown, it includes an electronic device 101 and a node 102.

[0038] The electronic device 101 is used to determine target excitation data corresponding to the array antenna based on the first antenna pattern of the array antenna. The electronic device 101 may include an array antenna, and the electronic device 101 transmits a signal based on the target excitation data through the array antenna.

[0039] The node 102 is configured to receive signals transmitted by the electronic device 101 and send signals to the electronic device 101 to implement data exchange between the electronic device 101 and the node 102 .

[0040] For example, in some embodiments, the electronic device 101 may be a mobile phone, tablet computer, desktop computer, laptop computer, handheld computer, notebook computer, ultra-mobile personal computer (UMPC), netbook computer, cellular phone, personal digital assistant (PDA), augmented reality (AR), or virtual reality (VR) device. The embodiments of the present disclosure do not impose any particular restrictions on the specific form of the electronic device. It may interact with the user through one or more methods such as a keyboard, touchpad, touch screen, remote control, voice interaction, or handwriting device.

[0041] In some embodiments, the above-mentioned node can be a base station, an evolved node base station (eNB), a next generation node base station (gNB), a new radio eNB, a macro base station, a micro base station, a high-frequency base station or a transmission and reception point (TRP), a non-3rd generation partnership project (3GPP) access network (such as WiFi) and / or a non-3GPP interworking function (N3IWF) and other devices.

[0042] like Figure 2 As shown, the method for determining incentive information provided by the embodiment of the present disclosure includes S101-S102.

[0043] S101. Obtain a first antenna pattern of an array antenna.

[0044] The first antenna pattern is used to represent the target signal strength in various directions within the target space.

[0045] It should be understood that the target space is a space at a preset distance from the array antenna, and the target signal strength is used to characterize the expected signal strength of the array antenna in a certain direction of the target space, that is, the first antenna pattern corresponds to the signal coverage requirement of the array antenna transmitting signal.

[0046] S102: Determine target excitation data corresponding to the array antenna based on the first antenna pattern.

[0047] The target excitation data includes excitation information, wherein the excitation information is used to indicate the signal strength and phase of the signal transmitted by the antenna unit in the array antenna; the first antenna pattern is used to characterize the target signal strength in various directions in space.

[0048] It should be understood that the target signal strength in each direction represented by the first antenna pattern is used to indicate the signal strength in each direction of the signal transmitted by the array antenna.

[0049] It can be understood that the target signal strength in each direction in the space represented by the first antenna pattern is the signal coverage requirement.

[0050] It can be understood that the target excitation data is used to indicate the signal strength and phase of the signal transmitted by each antenna unit in the array antenna, so that the signal strength distribution in each direction after the signals transmitted by each antenna unit in the array antenna are superimposed is the same as that represented by the first antenna pattern.

[0051] In the embodiment of the present disclosure, the electronic device can reliably generate excitation data based on the first antenna pattern of the array antenna, so that the antenna pattern corresponding to the signal transmitted by the array antenna is the first antenna pattern. Thus, the electronic device can generate an excitation scheme corresponding to the first antenna pattern. Compared with the method of transmitting signals based on a preset excitation scheme, the electronic device directly generates excitation information based on the first antenna pattern to obtain an excitation scheme corresponding to the first antenna pattern, and can promptly and quickly determine the excitation scheme of the array antenna that meets the signal coverage requirements.

[0052] Combine Figure 2 ,like Figure 3 As shown, the above-mentioned determination of target excitation data corresponding to the array antenna based on the first antenna pattern includes S102a-S102c.

[0053] S102a: Determine first excitation data based on the first antenna pattern.

[0054] It should be understood that the first excitation data includes first excitation information, and the first excitation information is used to indicate the signal strength and phase of the signal transmitted by the antenna unit.

[0055] Exemplarily, the first incentive information included in the first incentive data satisfies the following formula (1):

[0056] v=[Re(w1),…,Re(w n ),…,Re(w N ),Im(w1),…,Im(w n ),…,Im(w N )] (1)

[0057] Wherein, v is the first excitation data, Re(w1) is the real part of the first excitation information, Im(w1) is the imaginary part of the first excitation data, Re(w n ) is the real part of the nth first excitation information, Im(w n ) is the imaginary part of the nth first excitation information, Re(w N ) is the real part of the Nth first excitation information, Im(w N ) is the imaginary part of the Nth first excitation information, 1≤n≤N.

[0058] Combine Figure 3 ,like Figure 4 As shown, in one implementation, the electronic device determines first excitation data based on the first antenna pattern, including S102a.1.

[0059] S102a.1. Input the first antenna pattern into an excitation data generation model to obtain first excitation data.

[0060] The excitation data generation model is obtained based on the signal transmission data of the array antenna.

[0061] It should be understood that since the excitation data generation model is obtained based on the signal transmission data of the array antenna, that is, the excitation data generation model can map the relationship between the antenna pattern corresponding to the signal transmitted by the array antenna and the excitation data input to the array antenna, therefore, the first excitation data output by the excitation data generation model is the excitation data corresponding to the array antenna when the antenna pattern corresponding to the signal transmitted by the array antenna is the first antenna pattern.

[0062] It is understood that the signal transmission data of the array antenna may include antenna patterns of multiple array antennas and excitation data based on which the array antenna transmits a signal corresponding to each antenna pattern. The electronic device trains an initial excitation data generation model based on the signal transmission data to obtain the excitation data generation model. The excitation data generation model can predict the excitation data based on which the array antenna transmits a signal corresponding to the first antenna pattern.

[0063] In some embodiments, the above-mentioned incentive data generation model is obtained based on a neural network model framework.

[0064] S102b. Determine a first loss value based on the first excitation data.

[0065] Among them, the first loss value is the loss value between the second antenna pattern corresponding to the first excitation data and the first antenna pattern, and the second antenna pattern corresponding to the first excitation data is used to characterize the predicted signal strength in each direction in the target space after the array antenna transmits a signal based on the first excitation data.

[0066] It should be understood that the electronic device can predict the predicted signal strength in various directions within the target space after the array antenna transmits the signal based on the first excitation data, and determine the first loss value based on the predicted signal strength and the target signal strength in the first antenna pattern, thereby judging whether the first excitation data can meet the signal coverage requirements.

[0067] Combine Figure 3 ,like Figure 5 As shown, in an exemplary implementation, the electronic device determines the first loss value based on the first excitation data, including S102b.1-S102b.2.

[0068] S102b.1. Input the first excitation data into a directional pattern generation model to obtain a second antenna directional pattern corresponding to the first excitation data.

[0069] The pattern generation model is obtained based on the signal transmission data of the array antenna.

[0070] It should be understood that the signal transmission data of the array antenna includes the excitation data used for signal transmission and the corresponding antenna radiation pattern after the signal is transmitted based on the excitation data; the radiation pattern generation model can predict the corresponding antenna radiation pattern after an excitation data is input into the array antenna.

[0071] In one exemplary implementation, the signal transmission data of the array antenna may include multiple excitation data and antenna patterns corresponding to signals transmitted by the array antenna based on each excitation data. The electronic device trains an initial pattern generation model based on the signal transmission data of the array antenna to obtain the aforementioned pattern generation model. The pattern generation model can predict, based on the excitation data, the antenna pattern corresponding to signals transmitted by the array antenna based on the excitation data.

[0072] In some embodiments, the directional pattern generation model is obtained based on a neural network model framework.

[0073] It should be understood that the second antenna pattern corresponding to the first excitation data is a superposition of the respective patterns of each antenna unit on the array antenna.

[0074] Exemplarily, the superposition of the second antenna pattern corresponding to the first excitation data and the respective patterns of each antenna element in the array antenna satisfies the following formula (2):

[0075]

[0076] FF c is the second antenna pattern of the array, f n is the active unit pattern corresponding to the nth antenna array element, and the signal strength and phase of the nth antenna array element are I n and β n , N is a positive integer, 1≤n≤N.

[0077] like Figure 6 As shown, in some embodiments, the calculation of the second antenna pattern and the extraction of the active unit pattern are both performed in the same coordinate system, which is called the global coordinate system and is denoted as O g -x g y g z g When extracting the directional pattern of a single array element, the z-axis direction of the coordinate system is usually the radiation direction of the antenna, and this coordinate system is called the local coordinate system O p -x p y p z p .

[0078] S102b.2. Determine a first loss value based on the second antenna pattern and the first antenna pattern.

[0079] Exemplarily, the second antenna pattern corresponding to the first excitation data includes N directions, and the second antenna pattern corresponding to the first excitation data is expressed using the following formula (3):

[0080] FF c =[Re(F c(θ1)),…,Re(F c (θ N )),Im(F c (θ1)),…,Im(F c (θ N ))] (3)

[0081] Among them, FF c represents the second antenna pattern, F c (θ N ) indicates that in θ N The second antenna pattern information in the direction, Re(F c (θ N )) represents the real part of the second antenna pattern, Im(F c (θ N )) represents the imaginary part of the second antenna pattern.

[0082] The first antenna pattern is expressed using the following formula (4):

[0083] FF=[Re(F(θ1)),…,Re(F(θ N )),Im(F(θ1)),…,Im(F(θ N ))] (4)

[0084] Where FF represents the first antenna pattern, F(θ N ) indicates that in θ N The first antenna pattern information in the direction, Re(F(θ N )) represents the real part of the first antenna pattern, Im(F(θ N )) represents the imaginary part of the first antenna pattern.

[0085] The electronic device determines a first loss value based on the second antenna pattern and the first antenna pattern, satisfying the following formula (5):

[0086]

[0087] Among them, Loss represents the first loss value, Represents the square of the modulus value corresponding to the difference between the second antenna pattern and the first antenna pattern.

[0088] S102c: When the first loss value is less than or equal to the loss value threshold, determine the first stimulation data as the target stimulation data.

[0089] It should be understood that when the first loss value is less than or equal to the preset threshold, it means that the loss value between the second antenna pattern corresponding to the first excitation data and the first antenna pattern is small, and the signal transmitted by the array antenna based on the first excitation data can meet the signal coverage requirement corresponding to the first antenna pattern. At this time, the electronic device determines the first excitation data as the target excitation data, which can ensure the validity and reliability of the target excitation data.

[0090] Combine Figure 4 ,like Figure 7 As shown, in some instances, the above-mentioned method for determining incentive information also includes: S701-S704.

[0091] S701 : When the first loss value is greater than a loss value threshold, update the model parameters in the incentive data generation model based on the first loss value to obtain an updated incentive data generation model.

[0092] It should be understood that when the first loss value is greater than the loss value threshold, the antenna pattern corresponding to the signal transmitted by the array antenna based on the first excitation data cannot meet the signal coverage requirement corresponding to the first antenna pattern. At this time, the electronic device updates the model parameters in the excitation data generation model based on the first loss value to obtain an updated excitation data generation model.

[0093] It can be understood that by updating the excitation data generation model, the excitation data generation model can generate excitation data that better meets the signal coverage requirements of the first antenna pattern.

[0094] S702: Input the first antenna pattern into the updated excitation data generation model to obtain second excitation data.

[0095] It should be understood that the second excitation data includes second excitation information, and the second excitation information is used to indicate the signal strength and phase of the signal transmitted by the antenna unit in the array antenna.

[0096] S703: Determine a second loss value based on the second excitation data.

[0097] The second loss value is a loss value between the second antenna pattern corresponding to the second excitation data and the first antenna pattern.

[0098] S704: When the second loss value is less than or equal to the loss value threshold, determine the second stimulation data as the target stimulation data.

[0099] It should be understood that when the second loss value is less than or equal to the loss value threshold, it means that the antenna pattern corresponding to the signal transmitted by the array antenna based on the second excitation data can meet the signal coverage requirement corresponding to the first antenna pattern. At this time, the electronic device determines the second excitation data as the target excitation data, ensuring the reliability of the excitation scheme of the array antenna.

[0100] In an embodiment of the present disclosure, when the first loss value is greater than the loss value threshold, the antenna pattern corresponding to the signal transmitted by the array antenna based on the first excitation data cannot meet the signal coverage requirement corresponding to the first antenna pattern. At this time, the electronic device updates the model parameters in the excitation data generation model based on the first loss value to obtain an updated excitation data generation model. The electronic device inputs the first antenna pattern into the updated excitation data generation model to obtain second excitation data. The electronic device determines a second loss value based on the second excitation data. When the second loss value is less than or equal to the loss value threshold, it indicates that the antenna pattern corresponding to the signal transmitted by the array antenna based on the second excitation data can meet the signal coverage requirement corresponding to the first antenna pattern. At this time, the electronic device determines the second excitation data as the target excitation data, thereby ensuring the reliability of the excitation scheme of the array antenna, and further ensuring the effectiveness and reliability of communication between the electronic device and the node.

[0101] Combine Figure 3 ,like Figure 8 As shown, in some embodiments, the above-mentioned incentive information determination method further includes S801-S804.

[0102] S801. When the first loss value is greater than the loss value threshold, determine a third antenna pattern based on the first antenna pattern and the loss value threshold.

[0103] The loss value between the third antenna pattern and the first antenna pattern is less than or equal to a loss value threshold.

[0104] It should be understood that when the first loss value is greater than the loss value threshold, the antenna pattern corresponding to the signal transmitted by the array antenna based on the first excitation data cannot meet the signal coverage requirement corresponding to the first antenna pattern. At this time, the electronic device can also determine the third antenna pattern based on the first antenna pattern and the loss value threshold.

[0105] It can be understood that the loss value between the third antenna pattern and the first antenna pattern is less than or equal to the loss value threshold, that is, the excitation data generated by the third antenna pattern can also meet the signal coverage requirements corresponding to the first antenna pattern.

[0106] In an exemplary implementation, the third antenna pattern is the first antenna pattern after the signal strength in the main lobe area and the signal strength in the side lobe area are adjusted according to a preset ratio.

[0107] like Figure 9 As shown, an antenna pattern before scaling and an antenna pattern after scaling provided by an embodiment of the present disclosure are shown.

[0108] The horizontal axis represents the sine value of each direction in the antenna pattern. The angle corresponding to the sine value of each direction is the angle between the direction and the vertical direction of the array antenna. The main lobe area is [-1, -0.5] and [0.5, 1], the side lobe area is [-0.1, 0] and [0, 0.1], and the rest is the transition area.

[0109] In an exemplary implementation, the scaling of the first antenna pattern satisfies the following formulas (6) and (7):

[0110]

[0111]

[0112] Among them, F cn () represents the signal strength in one direction of the transformed antenna pattern, θ ML represents the direction of the main lobe area of ​​the transformed antenna pattern, θ SL Indicates the direction of the sidelobe area of ​​the transformed antenna pattern, Ω ML Indicates the value range of the main lobe area, Ω SL Indicates the value range of the sidelobe area, min() means taking the minimum value of the array in the brackets, max() means taking the maximum value of the array in the brackets, FF c Represents the first antenna pattern, | | represents the modulus value, FF cn Represents the transformed antenna pattern in complex form.

[0113] S802: Determine third excitation data based on the third antenna pattern.

[0114] It should be understood that the third excitation data includes third excitation information, and the third excitation information is used to indicate the signal strength and phase of the signal transmitted by the antenna unit in the array antenna.

[0115] S803: Determine a third loss value based on the third excitation data.

[0116] The third loss value is a loss value between the second antenna pattern corresponding to the third excitation data and the first antenna pattern.

[0117] S804: When the third loss value is less than or equal to the loss value threshold, determine the third stimulus data as the target stimulus data.

[0118] It should be understood that when the third loss value is less than or equal to the loss value threshold, it means that the antenna pattern corresponding to the signal transmitted by the array antenna based on the third excitation data can meet the signal coverage requirement corresponding to the first antenna pattern. At this time, the electronic device determines the third excitation data as the target excitation data, ensuring the reliability and effectiveness of the excitation data of the array antenna, thereby ensuring the reliability and effectiveness of the communication between the electronic device and the node.

[0119] In an embodiment of the present disclosure, the electronic device may include an array antenna, and control the array antenna to transmit a signal based on excitation information in target excitation data.

[0120] Exemplarily, the target excitation data includes at least one excitation information, the array antenna includes at least one antenna unit, and each antenna unit corresponds to one excitation information. In this way, each antenna unit in the array antenna transmits a signal based on the signal strength and phase indicated by the excitation information corresponding to the antenna unit. After the signals transmitted by each antenna unit are superimposed in space, the signal strength in each direction in space is the signal strength in each direction represented by the first antenna pattern. Since the first antenna pattern corresponds to the signal coverage requirement, when the signal strength in each direction in space meets the first antenna pattern, the signal coverage requirement is met, thereby ensuring the reliability and effectiveness of communication between the electronic device and the node.

[0121] Combine Figure 1 ,like Figure 10 As shown, in one implementation of the embodiment of the present disclosure, the above S102, based on the first antenna pattern, determines the target excitation data corresponding to the array antenna, including S102d-S102h:

[0122] S102d: Input the first antenna pattern into a first pattern generation model to obtain fourth excitation data.

[0123] The first pattern generation model is obtained based on signal transmission data of the array antenna.

[0124] S102e. Determine a fourth loss value based on the fourth excitation data.

[0125] The fourth loss value is a loss value between the second antenna pattern corresponding to the fourth excitation data and the first antenna pattern.

[0126] S102f. When the fourth loss value is greater than the loss value threshold, the second pattern generation model is updated based on the fourth loss value, and the first antenna pattern is input into the updated second pattern generation model to obtain fifth excitation data.

[0127] It should be understood that if the fourth loss value is greater than the loss value threshold, this indicates that after the array antenna transmits a signal based on the fourth excitation data, the signal strength in each direction in the target space cannot meet the target signal strength represented by the first antenna pattern. In this case, the electronic device updates the second pattern generation model based on the fourth loss value and inputs the first antenna pattern into the updated second pattern generation model to obtain fifth excitation data.

[0128] It is understandable that when the excitation data generated by the first pattern generation model does not meet the signal transmission requirements corresponding to the first antenna pattern, the model for generating the excitation data needs to be updated. Since the process of updating the model takes a long time, if the first pattern generation model is updated, it will result in the inability to generate new excitation data within the time period of updating the model. Therefore, when the fourth loss value is greater than the loss value threshold, the electronic device updates the second pattern generation model based on the fourth loss value. At this time, the electronic device can still generate new excitation data corresponding to the first antenna pattern based on the first antenna pattern. In this way, by running the two pattern generation models in parallel, the speed and efficiency of the electronic device in generating excitation data are guaranteed, and the pattern generation model is updated to generate excitation data that better meets the signal coverage requirements.

[0129] S102g. Determine a fifth loss value based on the fifth excitation data.

[0130] The fifth loss value is a loss value between the second antenna pattern corresponding to the fifth excitation data and the first antenna pattern.

[0131] S102h: When the fifth loss value is less than or equal to the loss value threshold, determine the fifth excitation data as the target excitation data and use the updated second directional pattern generation model as the first directional pattern generation model.

[0132] It should be understood that when the fifth loss value is less than or equal to the loss value threshold, it means that the array antenna transmits a signal based on the fifth excitation data that can meet the target signal strength in various directions in the target space represented by the first antenna pattern. At this time, the electronic device determines the fifth excitation data as the target excitation data.

[0133] It can be understood that the electronic device uses the updated second pattern generation model as the first pattern generation model, which can enable the first antenna pattern to generate excitation data that meets the signal strength in the target space represented by the first antenna pattern. Therefore, the next time when it is necessary to generate excitation data corresponding to the first antenna pattern similar to this time, the electronic device can directly obtain the target excitation data based on the first pattern generation model. In this way, the target excitation data can be obtained quickly and reliably by using the first pattern generation model and the second pattern generation model in parallel, thereby enabling the array antenna to transmit signals that can meet various signal coverage requirements, thereby ensuring the reliability and effectiveness of communication.

[0134] In an exemplary implementation, the first directional pattern generation model is an online encoder, and the second directional pattern generation model is an offline encoder.

[0135] like Figure 11 As shown, a directional pattern generation model training method provided by an embodiment of the present disclosure includes: S1101-S1104.

[0136] S1101. Determine a training set and a test set.

[0137] The training set and the test set each include a plurality of excitation data and an actual antenna pattern corresponding to each excitation data, wherein one excitation data includes excitation information, and the excitation information is used to indicate the signal strength and phase of different signals respectively.

[0138] S1102: Train the initial directional pattern generation model based on the training set to obtain a first directional pattern generation model.

[0139] S1103: Test the first directional pattern generation model based on the test set to obtain a fourth loss value.

[0140] The fourth loss value is a loss value between the directional pattern generated by the first directional pattern generation model based on the excitation data in the test set and the actual antenna directional pattern corresponding to the excitation data.

[0141] In some embodiments, the electronic device determines the fourth loss value, which satisfies the following formula (8):

[0142]

[0143] Among them, Loss represents the fourth loss value, Loss Fi It represents the loss value between the directional pattern corresponding to the i-th excitation data in the test set and the actual antenna directional pattern corresponding to the excitation data. S_num is the number of excitation data in the test set, which is a positive integer, 1≤i≤S_num.

[0144] Specifically, the loss value between the directional pattern corresponding to one excitation data and the directional pattern of the second antenna is determined to satisfy the following formulas (9), (10), (11) and (12):

[0145] Loss F =Loss MF +Loss SF +Loss TF (9)

[0146]

[0147]

[0148]

[0149] Among them, Loss F Is the fourth loss value, Loss MF is the main lobe area loss value, Loss SF is the sidelobe loss value, Loss TF is the transition zone loss value, FF norm (θ) is the signal strength in a certain direction of the directional diagram generated based on the excitation data in the test set, FF c (θ) is the directional map generated based on the stimulus data in the test set, Loss TLl Indicates the loss value of the left transition zone, Loss TLr Indicates the loss value of the right transition zone, N ML Indicates the number of sampling points in the main lobe area, N SL Indicates the number of sampling points in the sidelobe area, N TLl Indicates the number of sampling points in the left transition area, N TLr Indicates the number of sampling points in the right transition area, SLL indicates the upper limit of the signal strength in the sidelobe area, F smax Indicates the maximum value of the sidelobe signal strength, F mmax Indicates the maximum signal strength in the main lobe area.

[0150] S1104: When the fourth loss value is less than or equal to the loss value threshold, determine the first pattern generation model as the first antenna pattern generation model.

[0151] It should be understood that when the fourth loss value is less than or equal to the loss value threshold, it means that the loss value between the directional pattern generated by the first directional pattern generation model based on each excitation data in the test set and the actual antenna directional pattern corresponding to each excitation data is small, and the first directional pattern generation model can effectively generate the directional pattern corresponding to the excitation data based on the excitation data. At this time, the electronic device determines the first directional pattern generation model as the first antenna directional pattern generation model.

[0152] Combine Figure 11 ,like Figure 12 As shown, the electronic device trains the initial directional pattern generation model based on the training set to obtain a first directional pattern generation model, including S1102.1-S1102.3.

[0153] S1102.1. Input multiple excitation data in the training set into an initial pattern generation model to obtain antenna patterns corresponding to the multiple excitation data in the training set.

[0154] S1102.2. Determine a fifth loss value based on the antenna patterns corresponding to the multiple excitation data in the training set and the actual antenna patterns corresponding to the multiple excitation data in the training set.

[0155] The fifth loss value is a loss value between the antenna pattern generated by the initial pattern generation model based on the excitation data and the actual antenna pattern corresponding to the excitation data.

[0156] S1102.3. When the fifth loss value is less than or equal to the loss value threshold, the electronic device determines the initial directional pattern generation model as the first directional pattern generation model.

[0157] It should be understood that when the fifth loss value is less than or equal to the loss value threshold, it means that the initial directional pattern generation model can effectively generate the directional pattern corresponding to each excitation data in the training set. At this time, the electronic device determines the initial directional pattern generation model as the first directional pattern generation model.

[0158] Combine Figure 12 ,like Figure 13 As shown, the directional pattern generation model training method provided by the embodiment of the present disclosure also includes S1301-S1305.

[0159] S1301. When the fifth loss value is greater than the loss value threshold, determine the gradient of the model parameters in the initial directional pattern generation model based on the fifth loss value.

[0160] It should be understood that when the fifth loss value is greater than the loss value threshold, it means that the initial directional pattern generation model cannot reliably generate the directional pattern corresponding to each excitation data in the training set. At this time, the electronic device determines the gradient of the model parameters in the initial directional pattern generation model based on the fifth loss value.

[0161] S1302: Update model parameters based on the gradient to obtain an updated initial directional pattern generation model.

[0162] S1303: Input the multiple excitation data in the training set into the updated initial pattern generation model to obtain updated antenna patterns corresponding to the multiple excitation data in the training set.

[0163] S1304: Determine a sixth loss value based on the updated antenna patterns corresponding to the multiple excitation data in the training set and the actual antenna patterns corresponding to the multiple excitation data in the test set.

[0164] The sixth loss value is a loss value between an updated antenna pattern generated by the updated initial pattern generation model based on the excitation data and an actual antenna pattern corresponding to the excitation data.

[0165] S1305: When the sixth loss value is less than or equal to the loss value threshold, determine that the updated initial first antenna pattern generation model is the first pattern generation model.

[0166] It should be understood that when the sixth loss value is less than or equal to the loss value threshold, it means that the updated initial pattern generation model is able to generate the pattern of each excitation data in the training set. At this time, the electronic device determines that the updated initial first antenna pattern generation model is determined to be the first pattern generation model.

[0167] In the embodiment of the present disclosure, when the fifth loss value is greater than the loss value threshold, it means that the initial pattern generation model cannot reliably generate the pattern corresponding to each excitation data in the training set. At this time, the electronic device determines the gradient of the model parameters in the initial pattern generation model based on the fifth loss value, and updates the model parameters based on the gradient to obtain an updated initial pattern generation model. The electronic device inputs multiple excitation data in the training set into the updated initial pattern generation model to obtain updated antenna patterns corresponding to each of the multiple excitation data in the training set. The electronic device determines the sixth loss value based on the updated antenna patterns corresponding to each of the multiple excitation data in the training set and the actual antenna patterns corresponding to each of the multiple excitation data in the test set. When the sixth loss value is less than or equal to the loss value threshold, it means that the updated initial pattern generation model can generate the pattern for each excitation data in the training set. At this time, the electronic device determines that the updated initial first antenna pattern generation model is the first pattern generation model. In this way, the pattern generation model can be obtained accurately and reliably.

[0168] like Figure 14 As shown, a method for training an incentive data generation model provided by an embodiment of the present disclosure includes S1401-S1402.

[0169] S1401. Determine a data set.

[0170] The data set includes a plurality of first antenna patterns and actual excitation data corresponding to each of the plurality of first antenna patterns.

[0171] It should be understood that the data set is obtained through an array antenna, that is, the array antenna can obtain the multiple first antenna patterns based on actual excitation data corresponding to each of the multiple first antenna patterns.

[0172] S1402: Train the initial incentive data generation model based on the data set to obtain a target incentive data generation model.

[0173] In an embodiment of the present disclosure, the electronic device determines a data set, and the electronic device trains an initial excitation data generation model based on the data set to obtain a target excitation data generation model. In this way, the electronic device can effectively and reliably obtain the excitation data generation model, and then accurately and effectively generate excitation data corresponding to an antenna pattern on a target antenna array.

[0174] Combine Figure 14 ,like Figure 15 As shown, the initial incentive data generation model is trained based on the data set to obtain the target incentive data generation model, including S1402.1-S1402.3.

[0175] S1402.1. Input the multiple first antenna patterns in the data set into an initial excitation data generation model to obtain excitation data corresponding to each of the multiple first antenna patterns.

[0176] S1402.2. Determine a seventh loss value based on the excitation data corresponding to each of the plurality of first antenna patterns and the actual excitation data corresponding to each of the plurality of first antenna patterns.

[0177] The seventh loss value is a loss value between the excitation data corresponding to each of the plurality of first antenna patterns and the actual excitation data corresponding to each of the plurality of first antenna patterns.

[0178] S1402.3. When the seventh loss value is less than or equal to the loss value threshold, determine the initial excitation data generation model as the target excitation data generation model.

[0179] It should be understood that when the seventh loss value is less than or equal to the loss value threshold, it means that the initial excitation data generation model can reliably generate the excitation data corresponding to each of the multiple first antenna radiation patterns. At this time, the electronic device determines the initial excitation data generation model as the target excitation data generation model.

[0180] Combine Figure 15 ,like Figure 16 As shown, the incentive data generation model training method provided by the embodiment of the present disclosure also includes S1601-S1604.

[0181] S1601. When the seventh loss value is greater than the loss value threshold, update the model parameters of the initial excitation data generation model based on the seventh loss value to obtain an updated initial excitation data generation model.

[0182] It should be understood that when the seventh loss value is greater than the loss value threshold, it means that the initial excitation data generation model cannot reliably generate the excitation data corresponding to each of the multiple first antenna radiation patterns. At this time, the electronic device updates the model parameters of the initial excitation data generation model based on the seventh loss value to obtain an updated initial excitation data generation model.

[0183] S1602: Input the multiple first antenna patterns in the data set into the updated initial excitation data generation model to obtain updated excitation data corresponding to each of the multiple first antenna patterns.

[0184] S1603: Determine an eighth loss value based on the updated excitation data corresponding to each of the plurality of first antenna patterns and the actual excitation data corresponding to each of the plurality of first antenna patterns.

[0185] The eighth loss value is a loss value between the updated excitation data corresponding to each of the plurality of first antenna patterns and the actual excitation data corresponding to each of the plurality of first antenna patterns.

[0186] S1604: When the eighth loss value is less than or equal to the loss value threshold, determine the updated initial excitation data generation model as the target excitation data generation model.

[0187] It should be understood that when the eighth loss value is less than or equal to the loss value threshold, it means that the updated initial excitation data generation model can reliably generate the excitation data corresponding to each of the multiple first antenna radiation patterns. At this time, the electronic device determines the updated initial excitation data generation model as the target excitation data generation model. In this way, the target excitation data generation model can be reliably obtained, thereby ensuring the reliability and effectiveness of the excitation data generation.

[0188] like Figure 17 As shown, the array antenna in the embodiment of the present disclosure may include at least one link, and one link may include a phase shifter, a variable attenuator, and an antenna array element.

[0189] In which, when an electronic device transmits at least one signal through an array antenna, one link is used to transmit one signal, the phase shifter in the link is used to adjust the phase of the signal, the variable attenuator in the link is used to adjust the signal strength of the signal, and the antenna array element in the link is used to transmit the signal after the phase and signal strength are adjusted.

[0190] In some embodiments, each link of the above-mentioned array antenna also includes a radio frequency switch, and the radio frequency switch on each link is connected to the logic control unit. In this way, the electronic device can control the radio frequency switch by controlling the logic control unit, and control the on and off time of each radio frequency switch to achieve time modulation of the array antenna. At this time, the above-mentioned target excitation data also includes control information for each radio frequency switch. By controlling the radio frequency switch, the timing of the signal transmitted by each antenna unit of the array antenna can be controlled, and the time dimension (such as the pulse width or delay of the signal) can be added to the phase and amplitude of the signal. Control, more precise signal transmission can be achieved, thereby obtaining better signal strength coverage effect.

[0191] In some embodiments, the logic control unit may be a complex programmable logic device (CPLD).

[0192] It is understandable that, in order to realize the above functions, the incentive information determination device includes hardware structures and / or software modules corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the algorithm steps of each example described in the embodiments of the present disclosure, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present disclosure.

[0193] The embodiment of the present disclosure can divide the functional modules of the incentive information determination device according to the above-mentioned method embodiment. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one functional module. The above-mentioned integrated module can be implemented in the form of hardware or software. It should be noted that the division of modules in the embodiment of the present disclosure is schematic and is only a logical function division. There may be other division methods in actual implementation. The following is an example of dividing each functional module corresponding to each function.

[0194] Figure 18 This is a schematic diagram of the structure of an incentive information determination device provided by an embodiment of the present disclosure. The incentive information determination device can execute the incentive information determination method provided by the above method embodiment. Figure 18 As shown, the incentive information determination device 20 includes: an acquisition module 201 and a determination module 202.

[0195] The acquisition module 201 is configured to acquire a first antenna pattern of the array antenna, where the first antenna pattern is used to represent target signal strengths in various directions within the target space.

[0196] The determination module 202 is used to determine the target excitation data corresponding to the array antenna based on the first antenna radiation pattern of the array antenna, where the target excitation data includes excitation information, wherein the excitation information is used to indicate the signal strength and phase of the signal transmitted by the antenna unit in the array antenna.

[0197] It is understandable that, in order to realize the above functions, the directional pattern generation model training device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the algorithm steps of each example described in the embodiments of the present disclosure, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present disclosure.

[0198] The embodiment of the present disclosure can divide the functional modules of the directional pattern generation model training device according to the above-mentioned method embodiment. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one functional module. The above-mentioned integrated module can be implemented in the form of hardware or software. It should be noted that the division of modules in the embodiment of the present disclosure is schematic and is only a logical function division. There may be other division methods in actual implementation. The following is an example of dividing each functional module corresponding to each function.

[0199] In the case of implementing the functions of the above-mentioned integrated modules in the form of hardware, the embodiments of the present disclosure provide another possible structure of the electronic device involved in the above-mentioned embodiments. Figure 19 As shown, the electronic device 30 includes: a processor 302 and a bus 304. In an exemplary embodiment, the electronic device may further include a memory 301; in an exemplary embodiment, the electronic device may further include a communication interface 303.

[0200] Processor 302 may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of this disclosure. Processor 302 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of this disclosure. Processor 302 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, or a combination of a DSP and a microprocessor.

[0201] The communication interface 303 is used to connect to other devices via a communication network, such as Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0202] The memory 301 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0203] As a possible implementation, the memory 301 may exist independently of the processor 302, and the memory 301 may be connected to the processor 302 via a bus 304 for storing instructions or program codes. When the processor 302 calls and executes the instructions or program codes stored in the memory 301, it can implement the method for determining the excitation information provided in the embodiment of the present disclosure, or implement the method for training the directional pattern generation model provided in the embodiment of the present disclosure, or implement the method for training the excitation data generation model provided in the embodiment of the present disclosure.

[0204] In another possible implementation, the memory 301 may also be integrated with the processor 302 .

[0205] The bus 304 may be an extended industry standard architecture (EISA) bus, etc. The bus 304 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 19Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0206] Some embodiments of the present disclosure provide a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium), which stores computer program instructions. When the computer program instructions are executed on a computer, the computer executes the excitation information determination method as described in any of the above embodiments, or implements the directional pattern generation model training method provided by an embodiment of the present disclosure, or implements the excitation data generation model training method provided by an embodiment of the present disclosure.

[0207] Exemplarily, the above-mentioned computer-readable storage media may include, but are not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes, etc.), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memories (EPROMs), cards, sticks, or key drives, etc.). The various computer-readable storage media described in the present disclosure may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0208] An embodiment of the present disclosure provides a computer program product containing instructions. When the computer program product is run on a computer, the computer is caused to execute the method for determining the excitation information described in any of the above embodiments, or implement the directional pattern generation model training method provided by the embodiment of the present disclosure, or implement the excitation data generation model training method provided by the embodiment of the present disclosure.

[0209] The above is only a specific embodiment of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any changes or replacements within the technical scope disclosed in the present disclosure should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A method for determining incentive information, characterized in that: The method comprises: Acquire a first antenna pattern of the array antenna, where the first antenna pattern is used to represent target signal strength in various directions within the target space; Based on the first antenna pattern, target excitation data corresponding to the array antenna is determined, where the target excitation data includes excitation information, wherein the excitation information is used to indicate signal strength and phase of a signal transmitted by the array antenna.

2. The method for determining incentive information according to claim 1, wherein: The determining, based on the first antenna pattern, target excitation data corresponding to the array antenna includes: determining first excitation data based on the first antenna pattern; determining a first loss value based on the first excitation data, the first loss value being a loss value between a second antenna pattern corresponding to the first excitation data and the first antenna pattern, the second antenna pattern corresponding to the first excitation data being used to represent predicted signal strength in each direction within the target space after the array antenna transmits a signal based on the first excitation data; In a case where the first loss value is less than or equal to a loss value threshold, the first stimulation data is determined as the target stimulation data.

3. The method for determining incentive information according to claim 2, wherein: The determining a first loss value based on the first stimulus data includes: Inputting the first excitation data into a pattern generation model to obtain a second antenna pattern corresponding to the first excitation data, wherein the pattern generation model is obtained based on signal transmission data of the array antenna; The first loss value is determined based on the second antenna pattern and the first antenna pattern.

4. The method for determining incentive information according to claim 2, wherein: The determining first excitation data based on the first antenna pattern includes: The first antenna pattern is input into an excitation data generation model to obtain the first excitation data, where the excitation data generation model is obtained based on signal transmission data of the array antenna.

5. The method for determining incentive information according to claim 4, wherein: The method further comprises: When the first loss value is greater than the loss value threshold, updating the model parameters in the incentive data generation model based on the first loss value to obtain an updated incentive data generation model; Inputting the first antenna pattern into the updated excitation data generation model to obtain second excitation data; determining a second loss value based on the second excitation data, where the second loss value is a loss value between a second antenna pattern corresponding to the second excitation data and the first antenna pattern; In a case where the second loss value is less than or equal to the loss value threshold, the second stimulation data is determined as the target stimulation data.

6. The method for determining incentive information according to claim 2, wherein: The method further comprises: In a case where the first loss value is greater than a loss value threshold, determining a third antenna pattern based on the first antenna pattern and the loss value threshold, wherein a loss value between the third antenna pattern and the first antenna pattern is less than or equal to the loss value threshold; determining third excitation data based on the third antenna pattern; determining a third loss value based on the third excitation data, the third loss value being a loss value between the second antenna pattern corresponding to the third excitation data and the first antenna pattern; When the third loss value is less than or equal to the loss value threshold, the third excitation data is determined as the target excitation data.

7. The method for determining incentive information according to claim 6, wherein: The third antenna pattern is the first antenna pattern after the signal strength in the main lobe area and the signal strength in the side lobe area are adjusted according to a preset ratio.

8. The method for determining incentive information according to claim 1, wherein: The determining, based on the first antenna pattern, target excitation data corresponding to the array antenna includes: inputting the first antenna pattern into a first pattern generation model to obtain fourth excitation data, wherein the first pattern generation model is obtained based on signal transmission data of the array antenna; determining a fourth loss value based on the fourth excitation data, the fourth loss value being a loss value between the second antenna pattern corresponding to the fourth excitation data and the first antenna pattern; When the fourth loss value is greater than the loss value threshold, updating the second pattern generation model based on the four loss values, and inputting the first antenna pattern into the updated second pattern generation model to obtain fifth excitation data; determining a fifth loss value based on the fifth excitation data, the fifth loss value being a loss value between the second antenna pattern corresponding to the fifth excitation data and the first antenna pattern; In a case where the fifth loss value is less than or equal to the loss value threshold, the fifth excitation data is determined as the target excitation data and the updated second direction pattern generation model is used as the first direction pattern generation model.

9. An electronic device, characterized in that: include: memory and processor; Memory and processor coupling; The memory is used to store instructions executable by the processor; When the processor executes the instructions, the method according to any one of claims 1 to 8 is performed.

10. A computer program product, characterized in that The computer program product comprises computer program instructions, and when the computer program instructions are executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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