Antenna beam adjusting method and device, computer program product and electronic equipment

Abstract

The invention discloses an antenna beam adjustment method and device, a computer program product and electronic equipment. The method comprises the steps that first parameter information and first attitude information of a first antenna to be adjusted are acquired, the first parameter information at least comprises a first beam width, and the first attitude information at least comprises a first pitch angle and a first beam angle; analyzing the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain first predicted received signal strength of the first antenna; and performing iterative adjustment on the first beam width according to the first predicted received signal strength, so that a deviation error between the first predicted received signal strength and the expected received signal strength approaches zero. The technical problem that the receiving and transmitting performance of the antenna is poor due to the fact that the antenna beam cannot be intelligently adjusted in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of wireless communication technologies, and in particular, to an antenna beam adjustment method and apparatus, a computer program product, and an electronic device. Background Art

[0002] As a core component in a wireless communication system, the performance of an antenna is directly related to the transmission efficiency and quality of signals. In a traditional wireless communication environment, the adjustment of antenna gain is a key strategy for optimizing signal transceiver performance. By increasing the antenna gain, the coverage range and penetration power of signals can be effectively enhanced, especially in urban or terrestrial communication scenarios. However, in specific long-distance communication scenarios, especially in environments such as sea area coverage, this adjustment strategy faces severe challenges.

[0003] In scenarios such as sea area coverage, in order to overcome signal attenuation caused by long-distance communication, high-gain antennas are usually required. However, although high-gain antennas can significantly improve signal strength, their beams are relatively narrow, which means that the directivity of the antennas is stronger and the accuracy requirements for beam pointing are extremely high. At the same time, due to the dynamics and unpredictability of mobile terminals such as ships, it is difficult for the beams of high-gain antennas to continuously align with communication targets, resulting in a decline in signal quality and unstable communication links. Therefore, the above scheme sacrifices the beam width while increasing the antenna gain, reducing the coverage ability for dynamic targets and signal reception performance.

[0004] In response to the above problems, no effective solutions have been proposed yet. Summary of the Invention

[0005] Embodiments of this application provide an antenna beam adjustment method and apparatus, a computer program product, and an electronic device to at least solve the technical problem that in related technologies, the antenna beam cannot be intelligently adjusted, resulting in poor transceiver performance of the antenna.

[0006] According to one aspect of the embodiments of this application, an antenna beam adjustment method is provided, including: obtaining first parameter information and first attitude information of a first antenna to be adjusted, where the first parameter information at least includes: a first beam width, and the first attitude information at least includes: a first pitch angle, a first beam angle; analyzing the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain a first predicted received signal strength of the first antenna; and iteratively adjusting the first beam width according to the first predicted received signal strength so that the deviation error between the first predicted received signal strength and the expected received signal strength approaches zero.

[0007] Optionally, before analyzing the first parameter information and the first attitude information by using the pre-trained received signal strength prediction model to obtain the first predicted received signal strength of the first antenna, the method further includes: adjusting the first beam angle of the first antenna according to the first pitch angle and the first parameter information, so that the main beam direction of the first antenna meets the preset direction requirement.

[0008] Optionally, the first parameter information further includes: physical parameters of the antenna array, and the physical parameters of the antenna array include at least one of the following: the number of antenna elements, the spacing between antenna elements, and the array form. Wherein, adjusting the first beam angle of the first antenna according to the first pitch angle and the first parameter information includes: determining the angle deviation between the first pitch angle and the preset direction requirement, and determining whether the angle deviation exceeds a preset deviation threshold; in the case where the angle deviation exceeds the deviation threshold, based on the angle deviation and the physical parameters of the antenna array, using a preset beamforming algorithm to determine the amplitude-phase weight values of each antenna element in the first antenna, where the amplitude-phase weight values include: the weight value corresponding to the amplitude, the weight value corresponding to the phase; based on the amplitude-phase weight values of each antenna element in the first antenna, adjusting the amplitude and phase of each antenna element, so that the main beam direction of the first antenna meets the preset direction requirement.

[0009] Optionally, the training process of the received signal strength prediction model includes: obtaining multiple groups of training sample data, where each group of training sample data includes: the second parameter information and the second attitude information of the second antenna, and the second true received signal strength of the second antenna; constructing a neural network model; for each group of training sample data, inputting the second parameter information and the second attitude information of the second antenna in the training sample data into the neural network model to obtain the second predicted received signal strength output by the neural network model; constructing an objective loss function of the neural network model according to the second true received signal strength and the second predicted received signal strength in multiple groups of training sample data, and by optimizing the objective loss function until the model parameters converge, obtaining the trained received signal strength prediction model.

[0010] Optionally, obtaining multiple groups of training sample data includes: determining the second parameter information of each of multiple second antennas, where the second parameter information further includes at least one of the following: operating frequency, environmental information; for each second antenna, using an attitude sensor to collect the second pitch angle and the initial beam angle of the second antenna, and adjusting the initial beam angle according to the second pitch angle and the second parameter information to obtain the second beam angle; using a signal testing device to collect the second true received signal strength of the second antenna; forming multiple groups of training sample data from the second parameter information and the second attitude information of multiple second antennas, and the second true received signal strength of each second antenna.

[0011] Optionally, iteratively adjust the first beam width according to the first predicted received signal strength, including: The first step: Determine whether the first predicted received signal strength is equal to the expected received signal strength. Among them, when the first predicted received signal strength is equal to the expected received signal strength, execute the second step, otherwise execute the third step to the fifth step; The second step: Set the first antenna according to the first attitude information and the first parameter information; The third step: Subtract the first predicted received signal strength from the received signal strength threshold to obtain a deviation error; The fourth step: Adjust the first beam width according to the deviation error to obtain updated first parameter information; The fifth step: Analyze the updated first parameter information and the first attitude information by using the received signal strength prediction model to obtain the new first predicted received signal strength of the first antenna, and continue to return to execute the first step.

[0012] Optionally, adjust the first beam width according to the deviation error, including: When the deviation error is greater than zero, increase the first beam width; When the deviation error is not greater than zero, decrease the first beam width.

[0013] According to another aspect of the embodiments of the present application, there is also provided an antenna beam adjustment device, including: An acquisition module, configured to acquire the first parameter information and the first attitude information of the first antenna to be adjusted, where the first parameter information at least includes: the first beam width, and the first attitude information at least includes: the first pitch angle, the first beam angle; A prediction module, configured to analyze the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain the first predicted received signal strength of the first antenna; A first adjustment module, configured to iteratively adjust the first beam width according to the first predicted received signal strength, so that the deviation error between the first predicted received signal strength and the expected received signal strength approaches zero.

[0014] According to another aspect of the embodiments of the present application, there is also provided a computer program product, including: a computer program, where when the computer program is executed by a processor, it implements the above-mentioned antenna beam adjustment method.

[0015] According to another aspect of the embodiments of the present application, there is also provided an electronic device, including: a memory and a processor, where a computer program is stored in the memory, and the processor is configured to execute the above-mentioned antenna beam adjustment method through the computer program.

[0016] In the embodiments of the present application, by introducing an intelligent beam control mechanism, it aims to achieve efficient and stable communication of high-gain antennas in a dynamic environment. Specifically, the first parameter information and the first attitude information of the first antenna to be adjusted are obtained, analyzed in combination with the signal strength prediction model, and the first beam width in the first parameter information is iteratively adjusted according to the obtained first predicted received signal strength. During this adjustment process, the steps of prediction, comparison, and adjustment are continuously repeated until the deviation error between the first predicted received signal strength and the expected received signal strength is reduced to within the preset deviation error range, ensuring the accuracy of the antenna beam adjustment of the first antenna. Therefore, this innovative mechanism not only maintains the advantages of high-gain antennas in long-distance coverage scenarios but also overcomes the beam pointing problem in dynamic target communication, achieving the purpose of maintaining the stability of the communication link and improving the signal quality in a dynamic environment, thereby solving the technical problem that the related technology cannot intelligently adjust the antenna beam, resulting in poor transceiver performance of the antenna. Description of the Drawings

[0017] The drawings described herein are used to provide a further understanding of the present application and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0018] Figure 1 is a schematic flowchart of an optional antenna beam adjustment method according to an embodiment of the present application;

[0019] Figure 2 is a schematic principle diagram of an optional antenna beam adjustment according to an embodiment of the present application;

[0020] Figure 3 is a schematic structural diagram of an optional antenna beam adjustment device according to an embodiment of the present application;

[0021] Figure 4 is a schematic structural diagram of an optional electronic device according to an embodiment of the present application. Detailed Embodiments

[0022] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0023] It should be noted that the terms "first", "second", etc. in the description, claims and drawings of this application are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of this application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0024] To better understand the embodiments of this application, the following is a translation and explanation of some nouns or terms that appear during the description of the embodiments of this application:

[0025] Antenna (Aerial): It is a transducer that transforms the guided wave propagating on the transmission line into an electromagnetic wave propagating in an unbounded medium (usually free space), or vice versa.

[0026] Attitude information: It is the angle between the radiation direction of the antenna and the horizontal direction.

[0027] Antenna beam: In the antenna pattern, the radiation lobe that contains the required maximum radiation direction, which can also be called the main lobe of the antenna.

[0028] Beam Width: The angle between two half-power points of the beam. It is related to the antenna gain. Generally, the larger the antenna gain, the narrower the beam. Generally, the beam width is divided into horizontal beam width and vertical beam width, where: in the horizontal direction, on both sides of the maximum radiation direction, the angle between the two directions where the radiation power drops by 3 dB is the horizontal beam width; in the vertical direction, on both sides of the maximum radiation direction, the angle between the two directions where the radiation power drops by 3 dB is the vertical beam width.

[0029] Antenna element: It is a component on the antenna that has the functions of guiding and amplifying electromagnetic waves, making the electromagnetic signal received by the antenna stronger.

[0030] Beam Forming: Or beam shaping, spatial filtering. It is a technology that adjusts the amplitude and phase of multi-antenna signals to generate an interference effect, so that the finally radiated signal is concentrated in a certain direction for propagation or reception. Its basic principle is to adjust the signal phase and amplitude of each antenna unit so that the signals interfere constructively (signal enhancement) in a certain direction and interfere destructively (signal attenuation) in other directions.

[0031] Received Signal Strength (RSS): It is an important indicator used by the wireless transmission layer to judge the link quality. It is usually expressed in dBm (decibel milliwatt), which is the ratio of the received signal power to the reference power of 1 milliwatt. When factors such as interference and line loss are not considered, the calculation formula for the received signal strength is: Received Signal Strength = Radio Frequency Transmit Power + Transmitter Antenna Gain - Path Loss - Obstacle Attenuation + Receiver Antenna Gain.

[0032] Embodiment 1

[0033] According to an embodiment of the present application, an antenna beam adjustment method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0034] Figure 1 It is a flowchart diagram of an antenna beam adjustment method provided according to an embodiment of the present application. As Figure 1 shown, the method includes the following steps S102 - S106, including:

[0035] Step S102, obtain the first parameter information and the first attitude information of the first antenna to be adjusted.

[0036] In the technical solution provided in the above step S102, the above first parameter information and the first attitude information refer to collecting key data and physical attitude states of the antenna under the current operating state. Among them, the above first parameter information refers to the technical characteristics when the antenna is working. Specifically in the present application, it at least includes the first beam width. This indicator measures the width of the antenna beam covered in space. The narrower the beam width, the higher the antenna gain, but the smaller the coverage range; conversely, the wider the beam width, the larger the coverage range, but the lower the gain. And the first attitude information refers to the physical attitude state of the antenna, which at least includes the first pitch angle and the first beam angle. The first pitch angle reflects the tilt angle of the antenna in the vertical direction, and the first beam angle describes the pointing of the antenna beam in space.

[0037] Step S104, analyze the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain the first predicted received signal strength of the first antenna.

[0038] In the technical solution provided in the above step S104, the controller analyzes the signal propagation environment and antenna configuration of the first antenna by using a pre-trained received signal strength prediction model based on the obtained first antenna parameter information (such as the first beam width) and the first attitude information (such as the first pitch angle and the first beam angle), so as to predict the expected received signal strength under the first antenna configuration.

[0039] Step S106: Iteratively adjust the first beam width according to the first predicted received signal strength, so that the deviation error between the first predicted received signal strength and the expected received signal strength approaches zero.

[0040] In the technical solution provided in the above step S106, the controller continuously compares the difference between the first predicted received signal strength output by the received signal strength prediction model and the set expected received signal strength, that is, the deviation error. If the deviation error does not approach zero, it indicates that the current first beam width configuration fails to achieve the ideal signal reception effect, which may be caused by antenna attitude changes or other environmental factors. At this time, the controller will automatically adjust the first beam width of the first antenna based on the error information in order to improve the received signal strength.

[0041] Based on the solution defined in the above steps S102 to S106, it can be learned that in the embodiment of the present application, the first parameter information and the first attitude information of the first antenna to be adjusted are obtained, analyzed in combination with the signal strength prediction model, and the first beam width in the first parameter information is iteratively adjusted according to the obtained first predicted received signal strength. In this adjustment process, the steps of prediction, comparison, and adjustment are continuously repeated until the deviation error between the first predicted received signal strength and the expected received signal strength is reduced to within the preset deviation error range, ensuring the accuracy of the antenna beam adjustment of the first antenna, so as to achieve the purpose of maintaining the stability of the communication link and improving the signal quality in a dynamic environment.

[0042] Next, Figure 2 The antenna beam adjustment diagram shown below, combined with the specific implementation process, will illustrate each step of the antenna beam adjustment method.

[0043] Optionally, in the technical solution provided in the above step S102, the first attitude information may further include: yaw angle, roll angle, etc., and these angle information can be collected by an attitude sensor. In addition, the above first parameter information may further include: antenna array physical parameters (at least including the number of antenna elements, the antenna element spacing, and the array form), antenna operating frequency, etc., and these information are all set during antenna design, and these parameters can be obtained from the antenna specification sheet.

[0044] It should be noted that the change in the beam angle of the antenna will affect the propagation range of the antenna signal in the vertical direction. Especially in scenarios of long-distance communication or high-speed movement, if the beam tilt angle is not adjusted in time, it may lead to service interruption or unstable connection. In addition, due to different communication environments having different angle requirements for the antenna beam angle. For example, in open sea areas, it is usually required that the antenna has a larger tilt angle to overcome the influence of the sea level curvature; while in mountainous areas or urban environments with dense high-rise buildings, it is usually required that the antenna has a smaller tilt angle to avoid signal occlusion by obstacles.

[0045] Therefore, in the embodiment of the present application, after the controller obtains the first attitude information and the first parameter information of the first antenna to be adjusted, it can adjust the first beam angle of the first antenna according to the first pitch angle and the first parameter information, so that the main beam direction of the first antenna meets the preset direction requirements.

[0046] Optionally, the above method can be implemented through the following steps:

[0047] Step 1: Determine the angle deviation between the first pitch angle and the preset direction requirements, and judge whether the angle deviation exceeds the preset deviation threshold.

[0048] Step 2: When the angle deviation exceeds the deviation threshold, it indicates that the current first attitude of the first antenna is inconsistent with the expected direction, and this inconsistency may lead to poor antenna signal reception or transmission effects. At this time, the controller can determine the amplitude-phase weight values of each antenna oscillator in the first antenna based on the angle deviation and the physical parameters of the antenna array, using a preset beamforming algorithm.

[0049] Among them, the amplitude-phase weight values include: the weight value corresponding to the amplitude (which determines the intensity of the oscillator signal), and the weight value corresponding to the phase (which affects the phase difference between signals). In addition, the beamforming algorithms used above can include but are not limited to: beamforming algorithms based on machine learning (such as using neural networks to predict and determine the optimal amplitude-phase weight value combination), beamforming methods based on adaptively changing the weight vector (such as recursive least squares method, least mean square algorithm, etc.), particle swarm optimization algorithm, etc. In the embodiment of the present application, beamforming algorithms based on machine learning are preferably used to adapt to more complex environmental changes and improve the efficiency and accuracy of beamforming.

[0050] Step 3: Based on the amplitude-phase weight values of each antenna oscillator in the first antenna, adjust the amplitude and phase of each antenna oscillator. By changing the amplitude-phase weight values of each antenna oscillator in the first antenna, the antenna array forms a new beam direction, so that the main beam of the antenna can be aligned with the preset direction requirements. Thus, when the antenna attitude changes, the antenna beam direction can be automatically adjusted so that its beam can still be accurately aligned with the communication target to maintain high-quality signal transmission.

[0051] As an alternative implementation, in the technical solution provided in step S104 above, the training process of the above received signal strength prediction model may include:

[0052] Step S1, obtain multiple sets of training sample data.

[0053] Among them, each set of training sample data includes: the second parameter information and the second attitude information of the second antenna, as well as the second true received signal strength of the second antenna.

[0054] Optionally, in the technical solution provided in step S1 above, it can be implemented through the following steps, including:

[0055] Step S11, determine the second parameter information of each of the multiple second antennas. Among them, the second parameter information further includes but is not limited to: antenna operating frequency, antenna array physical parameters, antenna gain data, etc.

[0056] Step S12, for each second antenna, use an attitude sensor to collect the second pitch angle and the initial beam angle of the second antenna, and adjust and correct the initial beam angle according to the second pitch angle and the second parameter information to obtain a new second beam angle; use a signal testing device to collect the second true received signal strength of the second antenna;

[0057] Step S113, form multiple sets of training sample data from the second parameter information and the second attitude information of the multiple second antennas, and the second true received signal strength of each second antenna.

[0058] Step S2, construct a neural network model.

[0059] Among them, the model architecture of this neural network model can be a convolutional neural network, a deep neural network, a support vector machine, or an ensemble learning model combined with multiple learners.

[0060] Step S3, for each set of training sample data, input the second parameter information and the second attitude information of the second antenna in the training sample data into the neural network model to obtain the second predicted received signal strength output by the neural network model.

[0061] Step S4, construct an objective loss function of the neural network model based on the second true received signal strength and the second predicted received signal strength in multiple sets of training sample data, and optimize the objective loss function until the model parameters converge to obtain the trained received signal strength prediction model.

[0062] Through the above steps S1 - S4, a trained received signal strength prediction model can be obtained. Furthermore, the controller can call the trained received signal strength prediction model to analyze the first parameter information and the first attitude information to obtain the first predicted received signal strength of the first antenna.

[0063] As an alternative implementation, in the technical solution provided in the above step S106, the controller can implement the intelligent optimization of the antenna beam width according to the following iterative control process, including:

[0064] The first step: Determine whether the first predicted received signal strength is equal to the expected received signal strength. This step is a preliminary evaluation of the current antenna configuration. The expected received signal strength is usually a target value preset according to system requirements, representing the signal reception level in the ideal state. Among them, when the first predicted received signal strength is equal to the expected received signal strength, the second step is executed; otherwise, the third step to the fifth step are executed.

[0065] The second step: When the first predicted received signal strength is equal to the expected received signal strength, it indicates that the controller believes that the current first attitude information and first parameter information (including the first beam width) have met the predetermined signal quality requirements. At this time, the controller can set the first antenna according to the first attitude information and the first parameter information.

[0066] The third step: When the first predicted received signal strength is not equal to the expected received signal strength, the controller can determine the deviation error between the first predicted received signal strength and the received signal strength threshold. Among them, the received signal strength threshold is the minimum requirement for communication quality. Therefore, the deviation error helps the controller quantify the gap between the first predicted received signal strength and the received signal strength threshold.

[0067] The fourth step: Adjust the first beam width according to the deviation error in order to improve the signal reception situation and obtain the updated first parameter information.

[0068] In the technical solution provided in the above fourth step, the first beam width can be adjusted according to the following rules, including:

[0069] When the deviation error is greater than zero, increase the first beam width. Specifically, the controller can adjust the phase relationship of each antenna oscillator in the first antenna to reduce its phase difference. In this way, the signals emitted by the antenna array interfere within a wider angular range, thus forming a wider beam to cover a larger area and increase the probability of capturing signals. While adjusting the phase, the amplitude weight can also be adjusted accordingly to ensure that the beam energy distribution is more uniform, avoid coverage blind spots caused by over - concentration of the main beam energy, and thus improve the signal reception in remote or blocked environments.

[0070] When the deviation error is not greater than zero, reduce the first beam width. Specifically, the controller can increase the phase difference between the antenna elements, so that the signal is concentrated in a specific direction, forming a narrow and deep beam, improving the directivity gain and avoiding energy dispersion. While adjusting the phase, the amplitude weights can also be adjusted to ensure the concentration of energy in the main beam direction and control the energy attenuation in the non-main beam direction, thereby improving the signal quality and anti-interference ability.

[0071] Step 5: Use the received signal strength prediction model to analyze the updated first parameter information (including the adjusted new beam width) and the first attitude information to obtain the new first predicted received signal strength of the first antenna. This step verifies the effect of the beam adjustment and provides a new starting point for subsequent iterations. Subsequently, the controller continues to return to execute Step 1.

[0072] The controller iterates through the above loop until the deviation error between the first predicted received signal strength and the expected received signal strength is controlled within the preset error range, thereby achieving the dynamic optimization of the antenna beam width and ensuring the stability of signal reception and the quality of the communication link.

[0073] Through the above steps, it is not difficult to see that the antenna beam adjustment method provided by the embodiments of the present application has the following technical advantages compared with the existing solutions:

[0074] (1) In the embodiments of the present application, an attitude sensor is used to monitor the antenna attitude in real time and automatically adjust the beam direction. Compared with traditional mechanical adjustment or multi-channel comparison adjustment based on measurement, the embodiments of the present application can respond to changes in the antenna attitude in a short time, without additional hardware modification or increasing the receiving channels, greatly improving the real-time performance and flexibility of the system.

[0075] (2) In the embodiments of the present application, by comparing the predicted received signal strength with the actual received signal strength, the problem that the antenna beam adjustment direction is inaccurate due to the large cumulative error of the attitude sensor, resulting in the antenna being unable to accurately cover the communication target, is timely discovered and corrected. And through an intelligent closed-loop iterative process, the beam width is dynamically adjusted. Even when the attitude measurement is not completely accurate, the signal reception quality can be ensured, improving the overall stability and reliability of the system.

[0076] Embodiment 2

[0077] According to the embodiments of the present application, there is also provided an antenna beam adjustment device for implementing the antenna beam adjustment method in Embodiment 1, as Figure 3 shown. The antenna beam adjustment device at least includes: an acquisition module 32, a prediction module 34, and a first adjustment module 36, where:

[0078] An acquisition module 32, configured to acquire first parameter information and first attitude information of a first antenna to be adjusted.

[0079] Wherein, the first parameter information at least includes: a first beam width, and the first attitude information at least includes: a first pitch angle, a first beam angle.

[0080] A prediction module 34, configured to analyze the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain a first predicted received signal strength of the first antenna.

[0081] A first adjustment module 36, configured to iteratively adjust the first beam width according to the first predicted received signal strength, so that the deviation error between the first predicted received signal strength and the expected received signal strength approaches zero.

[0082] The functions of the modules of the antenna beam adjustment device will be described below in combination with a specific implementation process.

[0083] Optionally, the first attitude information acquired by the acquisition module 32 may further include: a yaw angle, a roll angle, etc., and these angle information can be acquired by an attitude sensor; and the first parameter information acquired by the acquisition module 32 may further include: antenna array physical parameters (at least including the number of antenna elements, the antenna element spacing, the array form), the antenna operating frequency, etc., and these information are all set during antenna design, and these parameters can be obtained from the antenna specification.

[0084] It should be noted that the change of the beam angle of the antenna will affect the propagation range of the antenna signal in the vertical direction. Especially in scenarios such as long-distance communication or high-speed movement, if the beam inclination angle is not adjusted in time, service interruption or link instability may occur. In addition, due to different communication environments having different angle requirements for the antenna beam angle, for example, in the open sea, it is usually required that the antenna has a larger inclination angle to overcome the influence of the sea level curvature; while in mountainous areas or urban environments with dense high-rise buildings, it is usually required that the antenna has a smaller inclination angle to avoid signal occlusion by obstacles.

[0085] Therefore, in the embodiment of the present application, the antenna beam adjustment device provided in the embodiment of the present application further includes a second adjustment module, and the second adjustment module can adjust the first beam angle of the first antenna according to the first pitch angle and the first parameter information, so that the main beam direction of the first antenna meets the preset direction requirement.

[0086] Optionally, the second adjustment module can adjust the first beam angle according to the following method, including:

[0087] The first step: Determine the angle deviation between the first pitch angle and the preset direction requirement, and determine whether the angle deviation exceeds a preset deviation threshold.

[0088] Step 2: When the angular deviation exceeds the deviation threshold, it indicates that the current first attitude of the first antenna is inconsistent with the desired direction, and this inconsistency may lead to poor antenna signal reception or transmission. At this time, the controller can determine the amplitude-phase weight values of each antenna oscillator in the first antenna based on the angular deviation and the physical parameters of the antenna array, using a preset beamforming algorithm. Among them, the amplitude-phase weight values include: the weight value corresponding to the amplitude (which determines the intensity of the oscillator signal) and the weight value corresponding to the phase (which affects the phase difference between signals).

[0089] Step 3: Based on the amplitude-phase weight values of each antenna oscillator in the first antenna, adjust the amplitude and phase of each antenna oscillator. By changing the amplitude-phase weight values of each antenna oscillator in the first antenna, the antenna array forms a new beam direction, enabling the main beam of the antenna to be aligned with the preset direction requirement. Thus, when the antenna attitude changes, the antenna beam direction can be automatically adjusted so that its beam can still be accurately aligned with the communication target to maintain high-quality signal transmission.

[0090] In addition, the antenna beam adjustment device provided in the embodiment of the present application further includes a model training module, and this model training module is used to train a received signal strength prediction model.

[0091] Optionally, the model training module can train the received signal strength prediction model according to the following method, including:

[0092] Step S1, obtain multiple groups of training sample data.

[0093] Among them, each group of training sample data includes: the second parameter information and the second attitude information of the second antenna, as well as the second true received signal strength of the second antenna.

[0094] Optionally, in the technical solution provided in the above step S1, it can be implemented through the following steps, including:

[0095] Step S11, determine the second parameter information of each of the multiple second antennas. Among them, the second parameter information further includes but is not limited to: antenna operating frequency, antenna array physical parameters, antenna gain data, etc.

[0096] Step S12, for each second antenna, use an attitude sensor to collect the second pitch angle and the initial beam angle of the second antenna, and adjust and correct the initial beam angle according to the second pitch angle and the second parameter information to obtain a new second beam angle; use a signal testing device to collect the second true received signal strength of the second antenna.

[0097] Step S113: Multiple groups of training sample data are composed of the second parameter information and second attitude information of multiple second antennas, and the second true received signal strength of each second antenna.

[0098] Step S2: Construct a neural network model.

[0099] Among them, the model architecture of the neural network model can be a convolutional neural network, a deep neural network, a support vector machine, or an ensemble learning model combined with multiple learners.

[0100] Step S3: For each group of training sample data, input the second parameter information and second attitude information of the second antenna in the training sample data into the neural network model to obtain the second predicted received signal strength output by the neural network model.

[0101] Step S4: Construct an objective loss function of the neural network model based on the second true received signal strength and the second predicted received signal strength in multiple groups of training sample data, and optimize the objective loss function until the model parameters converge to obtain a trained received signal strength prediction model.

[0102] Through the above steps, the model training module can obtain a trained received signal strength prediction model. Furthermore, the prediction module 34 can call the trained received signal strength prediction model to analyze the first parameter information and first attitude information to obtain the first predicted received signal strength of the first antenna.

[0103] As an optional implementation manner, the first adjustment module 36 can achieve intelligent optimization of the antenna beam width according to the following iterative control process, including:

[0104] The first step: Determine whether the first predicted received signal strength is equal to the expected received signal strength. This step is a preliminary evaluation of the current antenna configuration. The expected received signal strength is usually a target value preset according to system requirements, representing the signal reception level in the ideal state. Among them, when the first predicted received signal strength is equal to the expected received signal strength, execute the second step, otherwise execute the third step to the fifth step.

[0105] The second step: When the first predicted received signal strength is equal to the expected received signal strength, it means that the first adjustment module 36 believes that the current first attitude information and first parameter information (including the first beam width) have met the predetermined signal quality requirements. At this time, the first adjustment module 36 can set the first antenna according to the first attitude information and first parameter information.

[0106] Step 3: In the case where the first predicted received signal strength is not equal to the expected received signal strength, it indicates that the first adjustment module 36 can determine the deviation error between the first predicted received signal strength and the received signal strength threshold. Here, the received signal strength threshold is the minimum requirement for communication quality. Therefore, the deviation error is used by the auxiliary controller to quantify the gap between the first predicted received signal strength and the received signal strength threshold.

[0107] Step 4: Adjust the first beam width according to the deviation error, with the aim of improving the signal reception condition, and obtain the updated first parameter information.

[0108] In the technical solution provided in the above Step 4, the first adjustment module 36 can adjust the first beam width according to the following rules, including:

[0109] In the case where the deviation error is greater than zero, the first adjustment module 36 can increase the first beam width. Specifically, the first adjustment module 36 can adjust the phase relationship of each antenna element within the first antenna to reduce the phase difference. In this way, the signals emitted by the antenna array interfere within a wider angular range, thus forming a wider beam to cover a larger area and increase the probability of capturing signals. While adjusting the phase, the amplitude weights can also be adjusted accordingly to ensure a more uniform beam energy distribution, avoid coverage blind spots caused by over-concentration of the main beam energy, and thus improve the signal reception in remote or blocked environments.

[0110] In the case where the deviation error is not greater than zero, the first adjustment module 36 can reduce the first beam width. Specifically, the first adjustment module 36 can increase the phase difference between the antenna elements, making the signals concentrate in a specific direction to form a narrow and deep beam, improving the directional gain and avoiding energy dispersion. While adjusting the phase, the amplitude weights can also be adjusted to ensure the concentration of energy in the main beam direction and control the energy attenuation in the non-main beam directions, thereby improving the signal quality and anti-interference ability.

[0111] Step 5: The first adjustment module 36 analyzes the updated first parameter information (including the adjusted new beam width) and the first attitude information using the received signal strength prediction model to obtain the new first predicted received signal strength of the first antenna. This step verifies the effect of the beam adjustment and provides a new starting point for subsequent iterations. Subsequently, the first adjustment module 36 continues to return to execute Step 1.

[0112] The first adjustment module 36 realizes the dynamic optimization of the antenna beam width by iterating until the deviation error between the first predicted received signal strength and the expected received signal strength is controlled within the preset error range, ensuring the stability of signal reception and the quality of the communication link.

[0113] It should be noted that each module in the antenna beam adjustment device in the embodiments of the present application corresponds one by one to each implementation step of the antenna beam adjustment method in Embodiment 1. Since a detailed description has been given in Embodiment 1, some details not shown in this embodiment can be referred to Embodiment 1 and will not be elaborated here.

[0114] Embodiment 3

[0115] According to an embodiment of the present application, there is also provided a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the antenna beam adjustment method in Embodiment 1.

[0116] According to an embodiment of the present application, there is also provided a non-volatile storage medium, which includes a stored computer program. When the device where the non-volatile storage medium is located runs the computer program, it executes the antenna beam adjustment method in Embodiment 1.

[0117] According to an embodiment of the present application, there is also provided a processor, which is used to run a computer program. When the computer program runs, it executes the antenna beam adjustment method in Embodiment 1.

[0118] According to an embodiment of the present application, there is also provided an electronic device, which includes: a memory and a processor. Among them, a computer program is stored in the memory, and the processor is configured to execute the antenna beam adjustment method in Embodiment 1 through the computer program.

[0119] Specifically, when the computer program runs, it executes the following steps: obtaining first parameter information and first attitude information of a first antenna to be adjusted. Among them, the first parameter information at least includes: a first beam width, and the first attitude information at least includes: a first pitch angle, a first beam angle; analyzing the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain a first predicted received signal strength of the first antenna; iteratively adjusting the first beam width according to the first predicted received signal strength so that the deviation error between the first predicted received signal strength and the expected received signal strength approaches zero.

[0120] As an optional implementation manner, the above electronic device may exist in the form of a mobile terminal, a computer terminal, or a similar computing device. Figure 4 Shows a hardware structure block diagram of an electronic device for implementing the antenna beam adjustment method. As Figure 4As shown, the electronic device 40 may include one or more processors 402 (shown as 402a, 402b, ……, 402n in the figure) (the processor 402 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 404 for storing data, and a transmission device 406 for communication functions. In addition, it may further include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply, and / or a camera. Those of ordinary skill in the art can understand that Figure 4 the structure shown is only schematic and does not limit the structure of the above-mentioned electronic device. For example, the electronic device 40 may further include more or fewer components than Figure 4 shown in, or have a different configuration from Figure 4 that shown.

[0121] It should be noted that the above one or more processors 402 and / or other data processing circuits are generally referred to as "data processing circuits" herein. The data processing circuit may be embodied in software, hardware, firmware, or any combination thereof, in whole or in part. In addition, the data processing circuit may be a single independent processing module, or be incorporated in whole or in part into any one of other elements in the electronic device 40. As involved in the embodiments of the present application, the data processing circuit is a kind of processor control (such as the selection of a variable resistance terminal path connected to an interface).

[0122] The memory 404 may be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the antenna beam adjustment method in the embodiments of the present application. The processor 402 executes various functional applications and data processing by running the software programs and modules stored in the memory 404, that is, implements the vulnerability detection method of the above application program. The memory 404 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 404 may further include a memory remotely set relative to the processor 402, and these remote memories may be connected to the electronic device 40 through a network. Examples of the above network include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0123] The transmission device 406 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wireless network provided by the communication provider of the electronic device 40. In one example, the transmission device 406 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 406 can be a Radio Frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0124] The display can be, for example, a touch-screen liquid crystal display (LCD), which enables the user to interact with the user interface of the electronic device 40.

[0125] The above-mentioned serial numbers of the embodiments are only for description and do not represent the advantages or disadvantages of the embodiments.

[0126] In the above embodiments of the present application, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0127] In several embodiments provided in the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of units or modules can be in an electrical or other form.

[0128] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0129] In addition, the functional units in the various embodiments of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0130] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs.

[0131] The above are only the preferred embodiments of this application. It should be noted that for those of ordinary skill in the art of this technology, without departing from the principle of this application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. An antenna beam adjustment method, characterized in that, Including: Obtain the first parameter information and the first attitude information of the first antenna to be adjusted. Among them, the first parameter information at least includes: the first beam width, and the first attitude information at least includes: the first pitch angle, the first beam angle; Analyze the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain the first predicted received signal strength of the first antenna; Iteratively adjust the first beam width according to the first predicted received signal strength, so that the deviation error between the first predicted received signal strength and the expected received signal strength approaches zero.

2. The method according to claim 1, characterized in that, Before analyzing the first parameter information and the first attitude information by using a pre-trained received signal strength prediction model to obtain the first predicted received signal strength of the first antenna, the method further includes: Adjust the first beam angle of the first antenna according to the first pitch angle and the first parameter information, so that the main beam direction of the first antenna meets the preset direction requirement.

3. The method according to claim 2, wherein The first parameter information further includes: antenna array physical parameters, and the antenna array physical parameters include at least one of the following: the number of antenna elements, the antenna element spacing, the array form. Among them, adjusting the first beam angle of the first antenna according to the first pitch angle and the first parameter information includes: Determine the angle deviation between the first pitch angle and the preset direction requirement, and judge whether the angle deviation exceeds a preset deviation threshold; In the case that the angle deviation exceeds the deviation threshold, based on the angle deviation and the antenna array physical parameters, use a preset beamforming algorithm to determine the amplitude-phase weight values of each antenna element in the first antenna. Among them, the amplitude-phase weight values include: the weight value corresponding to the amplitude, the weight value corresponding to the phase; Based on the amplitude-phase weight values of each antenna element in the first antenna, adjust the amplitude and phase of each antenna element so that the main beam direction of the first antenna meets the preset direction requirement.

4. The method according to claim 1, characterized in that, The training process of the received signal strength prediction model includes: Obtain multiple groups of training sample data. Among them, each group of training sample data includes: the second parameter information and the second attitude information of the second antenna, and the second true received signal strength of the second antenna; Construct a neural network model; For each group of training sample data, input the second parameter information and the second attitude information of the second antenna in the training sample data into the neural network model to obtain the second predicted received signal strength output by the neural network model; Construct the target loss function of the neural network model according to the second true received signal strength and the second predicted received signal strength in multiple groups of training sample data, and optimize the target loss function until the model parameters converge to obtain the trained received signal strength prediction model.

5. The method according to claim 4, characterized in that, Obtain multiple groups of training sample data, including: Determine the second parameter information of each of the multiple second antennas. Among them, the second parameter information further includes at least one of the following: the operating frequency, the environmental information where it is located; For each of the second antennas, a posture sensor is used to collect the second pitch angle and the initial beam angle of the second antenna, and the initial beam angle is adjusted according to the second pitch angle and the second parameter information to obtain a second beam angle; a signal testing device is used to collect the second actual received signal strength of the second antenna; The multiple groups of training sample data are composed of the second parameter information and the second posture information of the multiple second antennas, and the second actual received signal strength of each second antenna.

6. The method according to claim 1, characterized in that, The iterative adjustment of the first beam width according to the first predicted received signal strength includes: The first step: Determine whether the first predicted received signal strength is equal to the expected received signal strength. Among them, when the first predicted received signal strength is equal to the expected received signal strength, execute the second step, otherwise execute the third step to the fifth step; The second step: Set the first antenna according to the first posture information and the first parameter information; The third step: Subtract the first predicted received signal strength from the received signal strength threshold to obtain a deviation error; The fourth step: Adjust the first beam width according to the deviation error to obtain the updated first parameter information; The fifth step: Use the received signal strength prediction model to analyze the updated first parameter information and the first posture information to obtain the new first predicted received signal strength of the first antenna, and continue to return to execute the first step.

7. The method according to claim 6, characterized in that, Adjusting the first beam width according to the deviation error includes: When the deviation error is greater than zero, increase the first beam width; When the deviation error is not greater than zero, decrease the first beam width.

8. An antenna beam adjustment device, characterized in that, Includes: An acquisition module, configured to acquire the first parameter information and the first posture information of the first antenna to be adjusted, where the first parameter information at least includes: the first beam width, and the first posture information at least includes: the first pitch angle, the first beam angle; A prediction module, configured to use a pre-trained received signal strength prediction model to analyze the first parameter information and the first posture information to obtain the first predicted received signal strength of the first antenna; A first adjustment module, configured to iteratively adjust the first beam width according to the first predicted received signal strength, so that the deviation error between the first predicted received signal strength and the expected received signal strength approaches zero.

9. A computer program product, characterized in that, Includes: A computer program, where when the computer program is executed by a processor, it implements the antenna beam adjustment method according to any one of claims 1 to 7.

10. An electronic device, characterized in that, Includes: A memory and a processor, where a computer program is stored in the memory, and the processor is configured to execute the antenna beam adjustment method according to any one of claims 1 to 7 through the computer program.

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