Beam configuration method and apparatus, and computer device and readable storage medium

Abstract

The present application relates to a beam configuration method and apparatus, and a computer device and a computer-readable storage medium. The method comprises: acquiring a sensing period, a sensing range and a sensing performance requirement of a target scenario, wherein the sensing performance requirement comprises a sensing precision, a sensing resolution and a refresh rate; acquiring, from a data frame used by a base station to execute a communication and sensing function in the target scenario, sensing waveform information which is required when a sensing beam emitted by the base station executes a sensing function in the target scenario; on the basis of the sensing period, the sensing range and the sensing performance requirement, determining a beam scanning scheme of the sensing beam within the sensing period; and on the basis of the sensing waveform information and the beam scanning scheme, performing configuration on the sensing beam.

Description

Beam configuration method and device, computer device and readable storage medium

[0001] Related applications

[0002] The present application claims priority to the Chinese patent application No. 2024113857115, filed on September 30, 2024, entitled "Beam configuration method and device, computer device and readable storage medium", the contents of which are hereby incorporated by reference in their entirety. TECHNICAL FIELD

[0003] The present application relates to the field of communication technology, in particular to a beam configuration method, device, computer device and computer readable storage medium. BACKGROUND

[0004] The implementation of communication and perception integration design based on cellular network mainly refers to integrating and enhancing the communication and perception capabilities on the basis of the existing cellular mobile communication network, so that the base station and the terminal device can provide high-quality communication services and environmental perception functions at the same time.

[0005] In the traditional technology, when designing the integration of communication and perception, a separate design is often adopted, that is, communication and perception run as two independent entities, which can share some hardware components (such as antennas), but are usually independently optimized and designed in terms of signal processing, waveform design, frame structure, etc.

[0006] The traditional technology mainly focuses on independent optimization in respective fields when dealing with the integration design of communication and perception, and ignores the potential synergistic effect between the two, making it difficult for the traditional technology to meet the perception needs of different perception scenarios. SUMMARY

[0007] In a first aspect, the present application provides a beam configuration method applied to a base station, the method comprising:

[0008] obtaining the perception period, the perception range and the perception performance requirement of the target scene; the perception performance requirement includes the perception accuracy, the perception resolution and the refresh rate;

[0009] from the data frame used by the base station to perform communication and perception functions in the target scene, obtaining the perception waveform information required by the perception beam of the base station when performing the perception function in the target scene;

[0010] determining the beam scanning scheme of the perception beam in the perception period according to the perception period, the perception range and the perception performance requirement;

[0011] configuring the perception beam according to the perception waveform information and the beam scanning scheme.

[0012] In one of the embodiments, the target scene includes at least one sensing area; the data frame includes a communication symbol and a sensing symbol, and the sensing symbol is used to describe sensing waveform information corresponding to each sensing area;

[0013] The proportion between the number of communication symbols and the number of sensing symbols is determined by the first intelligent model according to the scene type of the target scene, the communication performance requirement and the sensing performance requirement of the target scene, and the communication and sensing resource allocation constraint of the base station in the target scene;

[0014] The sensing waveform information corresponding to each sensing area is determined by the first intelligent model according to the scene type of the target scene, the sensing range corresponding to the sensing area, and the waveform coverage capability of each candidate waveform;

[0015] The first intelligent model is further used to determine the time slot position of each sensing symbol in the data frame.

[0016] In one of the embodiments, the beam scanning scheme of the sensing beam in the sensing period is determined according to the sensing period, the sensing range and the sensing performance, including:

[0017] The beam period is allocated to the sensing beam corresponding to each sensing area; each beam period is located in the sensing period, and adjacent beam periods do not overlap with each other;

[0018] For each sensing area, the beam scanning scheme of the sensing beam used by the base station to perform the sensing function in the sensing area in the corresponding beam period is determined according to the sensing performance requirement and the sensing range corresponding to the sensing area.

[0019] In one of the embodiments, the sensing range includes a sensing distance range and a sensing angle range; the beam scanning scheme of the sensing beam in the sensing period is determined according to the sensing period, the sensing range and the sensing performance requirement, including:

[0020] The beam width parameter and the total number of beams corresponding to the sensing area are determined according to the sensing distance range and the sensing angle range of the sensing area;

[0021] The beam width parameter and the total number of beams are processed according to the sensing accuracy and the sensing resolution of the sensing area, to obtain the beam scanning scheme of the sensing beam used by the base station to perform the sensing function in the corresponding beam period for the sensing area; the beam scanning scheme satisfies the refresh rate.

[0022] In one of the embodiments, the beam width parameter and the total number of beams are processed according to the sensing accuracy and the sensing resolution of the sensing area, to obtain the beam scanning scheme of the sensing beam used by the base station to perform the sensing function in the corresponding beam period for the sensing area, including:

[0023] According to the perception accuracy and the perception resolution corresponding to the perception area, the beam period of the perception beam corresponding to the perception area is divided to obtain a plurality of same scanning periods;

[0024] According to the total number of beams, the scanning times corresponding to each scanning period are determined;

[0025] According to the scanning period and the scanning times corresponding to each scanning period, the beam scanning scheme of the perception beam used by the base station for performing the perception function in the perception area in the corresponding beam period is determined.

[0026] In one embodiment, according to the scanning period and the scanning times corresponding to each scanning period, the beam scanning scheme of the perception beam used by the base station for performing the perception function in the perception area in the corresponding beam period is determined, including:

[0027] For each scanning period, a plurality of same frame periods contained in the scanning period are determined, and according to the scanning times corresponding to the scanning period, the intra-frame scanning times and scanning intervals corresponding to each frame period are determined;

[0028] The intra-frame scanning times and scanning intervals of the frame period corresponding to each scanning period are determined as the beam scanning scheme of the perception beam used by the base station for performing the perception function in the perception area in the corresponding beam period.

[0029] In one embodiment, the perception angle range includes a horizontal visual angle range and a vertical visual angle range; the perception accuracy includes but is not limited to distance accuracy, speed accuracy, and angle accuracy; and the perception resolution includes distance resolution, speed resolution, or angle resolution.

[0030] In one embodiment, the allocation of the beam period to the perception beam corresponding to each perception area includes:

[0031] The scene information of the target scene, the area information of each perception area, and the beam information of the perception beam are input into the second intelligent model to obtain the beam period allocated to the perception beam corresponding to each perception area output by the second intelligent model.

[0032] In one embodiment, the first intelligent model includes a first sub-model, a second sub-model, and a third sub-model.

[0033] The ratio between the number of communication symbols and the number of sensing symbols is determined by the first sub-model according to the scene type of the target scene, the communication performance requirement of the target scene, the sensing performance requirement, and the communication and sensing resource allocation constraint of the base station in the target scene; wherein the training samples of the first sub-model include at least one of the following: scene label, scene feature, communication volume requirement, communication quality requirement, sensing range requirement, sensing accuracy requirement, spectrum resource limit, computing and storage resource limit, historical ratio record, and optimal ratio label;

[0034] The sensing waveform information corresponding to each sensing area is determined by the second sub-model according to the scene type of the target scene and the sensing range corresponding to the sensing area, and the waveform coverage capability of each candidate waveform; wherein the training samples of the second sub-model include at least one of the following: scene type label, sensing distance data, candidate waveform information, and sensing waveform information label;

[0035] The time slot position of each sensing symbol in the data frame is determined by the third sub-model according to the timing requirement of communication and sensing and the availability of resources.

[0036] In one embodiment, the second intelligent model includes a machine learning algorithm or a deep learning algorithm.

[0037] In one embodiment, the determination of the beam width parameter and the total number of beams corresponding to the sensing area according to the sensing distance range and the sensing angle range of the sensing area includes:

[0038] The total number of beams corresponding to the sensing area is determined based on the sensing distance range of the sensing area;

[0039] The beam width parameter corresponding to the sensing area is determined based on the total number of beams and the sensing angle range.

[0040] In one embodiment, the determination of the beam width parameter corresponding to the sensing area based on the total number of beams and the sensing angle range includes:

[0041] The ratio of the sensing angle range to the total number of beams is taken as the beam width parameter corresponding to the sensing area.

[0042] In a second aspect, the present application further provides a beam configuration device, comprising:

[0043] An acquisition module is configured to acquire the sensing period, sensing range and sensing performance requirement of a target scene; the sensing performance requirement includes sensing accuracy, sensing resolution and refresh rate;

[0044] a waveform determination module, configured to acquire, from a data frame used by the base station to perform a communication and a sensing function in the target scene, sensing waveform information required by a sensing beam of the base station to perform the sensing function in the target scene;

[0045] a scanning scheme determination module, configured to determine a beam scanning scheme of the sensing beam in the sensing period according to the sensing period, the sensing range and the sensing performance requirement;

[0046] a beam configuration module, configured to configure the sensing beam according to the sensing waveform information and the beam scanning scheme.

[0047] In a third aspect, the present application provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the beam configuration method in the first aspect when executing the computer program.

[0048] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the beam configuration method in the first aspect when executed by a processor.

[0049] In a fifth aspect, the present application provides a computer program product, comprising a computer program, and the computer program implements the steps of the beam configuration method in the first aspect when executed by a processor.

[0050] The details of one or more embodiments of the present application are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the application will be apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the accompanying drawings needed to be used in the description of the embodiments of the present application or the related art will be briefly introduced. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other related drawings can also be obtained without creative labor.

[0052] FIG. 1 is a flowchart of a beam configuration method in an embodiment;

[0053] FIG. 2 is a flowchart of a step of determining a beam scanning scheme of a sensing beam in a sensing period according to a sensing period, a sensing range and a sensing performance in an embodiment;

[0054] FIG. 3 is a schematic diagram of a beam scheme formed in a frame structure in an embodiment;

[0055] FIG. 4 is a flowchart illustrating a method for determining a beam scanning scheme of a sensing beam used by a base station to perform a sensing function in a sensing area according to a sensing performance requirement and a sensing range of the sensing area in an embodiment;

[0056] FIG. 5 is a flowchart illustrating a method for determining a beam scanning scheme of a sensing beam used by a base station to perform a sensing function in a sensing area in another embodiment;

[0057] FIG. 6 is a flowchart illustrating a method for determining a beam scanning scheme of a sensing beam used by a base station to perform a sensing function in a sensing area in an embodiment;

[0058] FIG. 7 is a block diagram illustrating a structure of a beam configuration apparatus in an embodiment;

[0059] FIG. 8 is a block diagram illustrating an internal structure of a computer device in an embodiment. DETAILED DESCRIPTION

[0060] To make the objects, technical solutions, and advantages of the present application clearer, the present application will be described in further detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are merely intended to explain the present application and should not be used to limit the present application.

[0061] In the context of the current dual demand for communication and sensing capabilities of multi-domain (airspace, ground, water) vehicles, the communication-sensing integrated technology is particularly important and widely concerned. This technology uses the information generated by the interaction between wireless signals and the environment during transmission, not only achieving data transmission, but also providing sensing capability of the surrounding environment. Through the widespread application of cellular networks, this technology can enhance the functionality of base station devices, achieve mutual assistance of sensing and communication, and thus improve the overall network performance and reduce operating costs.

[0062] To realize communication-sensing integration based on cellular networks, detailed design must be made according to the specific needs of different scenarios. This includes frame structure, waveform selection, beam scanning scheme, and other aspects. Among them:

[0063] (1) In the communication-sensing integrated (i.e., communication and sensing integrated) technology, the frame structure refers to the time or frequency unit structure used to organize and arrange data transmission in the communication and sensing process. The frame structure needs to reasonably divide the time resources to support the simultaneous performance of communication and sensing functions. This includes determining the time slots for communication data transmission and the time slots for sensing signal processing. The design of the frame structure also needs to consider how to optimize the use of communication and sensing resources. For example, in periods with low sensing demand, more time resources can be allocated to communication to improve the efficiency of data transmission. Conversely, in periods with heavy sensing tasks, the frame structure needs to be adjusted accordingly to meet the sensing demand.

[0064] (2) Different waveforms have different characteristics, such as bandwidth, time width, resolution, etc., which will affect the performance, such as communication rate, ranging accuracy, speed measurement capability, etc. Different application scenarios have different requirements for communication and perception performance. For example, in airspace traffic, aircraft such as unmanned aerial vehicles require high-speed data transmission and accurate positioning and speed measurement capability, which may require selecting a waveform with high bandwidth, low delay and good Doppler characteristics. In ground traffic, more attention can be paid to accurate perception and stable data transmission in close range, and the waveform selection will also be adjusted accordingly.

[0065] (3) The design of the beam scanning scheme needs to consider multiple factors such as scanning speed, scanning range, beam width parameter, beam gain, etc.

[0066] Among them, the scanning speed refers to the speed of the antenna scanning in different directions, which directly affects the response time and tracking ability. Faster scanning speed can shorten the response time to the target and improve the real-time tracking of the target. However, too fast scanning speed can also cause the antenna to be unable to fully focus the signal, affecting the quality of communication or perception. Therefore, when designing the beam scanning scheme, the scanning speed needs to be reasonably set according to the specific application scenario requirements to achieve a balance between response time and signal quality;

[0067] The scanning range refers to the angular region that the antenna beam can cover. A wider scanning range can expand the monitoring and communication range, but can also cause the beam gain to decrease, affecting the communication distance and quality. On the contrary, a narrower scanning range can improve the beam gain, but will limit the monitoring and communication range. Therefore, when designing the beam scanning scheme, the scanning range needs to be reasonably set according to the actual requirements of the application scenario to achieve the maximum monitoring and communication range while ensuring the communication quality;

[0068] The beam width parameter refers to the width of the beam in space, which directly affects the directivity and gain. A narrower beam width parameter can improve the directivity and gain, but will also reduce the coverage of the signal. When designing the beam scanning scheme, the beam width parameter needs to be reasonably set according to the specific application scenario requirements. For example, in an application scenario requiring high-precision positioning and tracking, a narrower beam width parameter can be selected to improve the positioning accuracy; while in an application scenario requiring extensive coverage, a wider beam width parameter needs to be selected to expand the coverage range.

[0069] Currently, the dynamically reconfigurable integrated communication and sensing scheme is under research, and no unified conclusion has been formed, which needs to be improved.

[0070] Based on this, in an exemplary embodiment, as shown in FIG. 1, the present embodiment provides a beam configuration method, which is applied to a base station as an example for illustration,

[0071] S101, obtain the perception period, perception range, and perception performance requirement of the target scene.

[0072] In the context of communication and perception integration, the target scene refers to specific environments or situations that require simultaneous implementation of communication and perception functions.

[0073] Specifically, the target scene can cover multiple fields such as airspace (such as unmanned aerial vehicle flight regulation), ground (such as Internet of Vehicles, smart home, climate environment monitoring), and water area, etc. Each scene has its unique characteristics and requirements, and a communication and perception integrated system needs to be designed to meet these requirements.

[0074] For example, in the context of unmanned aerial vehicles, communication and perception integration is mainly used for unmanned aerial vehicle regulation, path planning, and obstacle avoidance. Due to the high speed of unmanned aerial vehicles and the need for real-time regulation, the perception period should be as short as possible to ensure real-time tracking and regulation of unmanned aerial vehicles. The length of the specific perception period needs to be considered comprehensively according to the flight speed, flight altitude, and regulation requirements of the unmanned aerial vehicle. The perception range should cover all areas where the unmanned aerial vehicle may fly, including low, medium, and high altitudes. In addition, sensitive areas or no-fly zones that the unmanned aerial vehicle may enter also need to be considered to ensure effective perception and regulation in these areas.

[0075] The perception period refers to the time required for the base station to perform a complete perception. When determining the beam scanning scheme, the length of the perception period and its impact on system performance need to be considered.

[0076] The perception range refers to the spatial area of the target scene that the base station can perceive. When determining the beam scanning scheme, the size of the perception range and its impact on the beam scanning strategy need to be considered.

[0077] The perception performance requirement includes perception accuracy, perception resolution, and refresh rate.

[0078] It can be understood that the perception accuracy refers to the closeness between the data obtained by the sensor or perception system when measuring or perceiving the target object and the actual value. It includes but is not limited to the following aspects:

[0079] Distance accuracy: refers to the accuracy of the perception system when measuring the distance between the target and the perception device. For example, in the context of autonomous driving, the vehicle needs to accurately perceive the distance of the surrounding obstacles to ensure driving safety.

[0080] Speed accuracy: refers to the accuracy of the perception system when measuring the moving speed of the target object. In traffic monitoring, unmanned aerial vehicle tracking, and other scenarios, the requirement for speed accuracy is usually high.

[0081] Angle accuracy: refers to the accuracy of the perception system in measuring the direction or angle of a target object. In scenarios such as radar detection and target tracking, angle accuracy is crucial for determining the position and trajectory of the target object.

[0082] Further, the perception resolution refers to the ability of the sensor or perception system to distinguish or identify the smallest changes in the target object. It includes but is not limited to the following aspects:

[0083] Distance resolution: refers to the ability of the perception system to distinguish the smallest difference in distance between two target objects. In scenarios such as radar detection and sonar ranging, high distance resolution helps to more accurately identify the position of the target object.

[0084] Speed resolution: refers to the ability of the perception system to distinguish the smallest difference in speed between two target objects. In scenarios such as traffic monitoring and drone tracking, high speed resolution helps to more accurately determine the motion state of the target object.

[0085] Angle resolution: refers to the ability of the perception system to distinguish the smallest difference in direction or angle between two target objects. In scenarios such as radar detection and target tracking, high angle resolution helps to more accurately determine the position and trajectory of the target object.

[0086] Further, resolution is an important indicator of the ability of the perception system to capture details. It is usually related to the hardware design, signal processing algorithm and other factors of the perception system. In the communication and perception integrated system, in order to improve the perception resolution, more advanced sensor technology, optimization of signal processing algorithm, increase of measurement dimension (such as simultaneous measurement of distance, speed and angle) and other methods can be adopted. These methods help to improve the ability of the system to capture the details of the target object, so as to provide more rich and accurate perception information.

[0087] S102, from the data frame used by the base station to perform communication and perception functions in the target scene, obtain the perception waveform information required by the perception beam of the base station when performing perception functions in the target scene.

[0088] Among them, the data frame is the basic unit used to transmit communication data and perception data in the communication and perception integrated system. In the data frame, not only the information used for communication (such as user data, control information, etc.), but also the waveform data used for perception. These data are orderly organized in the data frame, so that the base station can efficiently send and receive.

[0089] In the data frame, the perception waveform information data is usually stored in specific fields or areas. These fields may include: waveform identification: used to uniquely identify the type or characteristics of the perception waveform information. Waveform parameters: such as frequency, amplitude, phase, etc., which define the specific shape and characteristics of the perception waveform information. Time stamp: records the time slot position of the perception beam of the waveform. Other auxiliary information: such as waveform processing algorithm, calibration data, etc., used to improve the perception accuracy and resolution.

[0090] Specifically, the perception waveform information required by the base station to perform the perception function of the perception beam in the target scene is obtained, including: first, the received data frame needs to be parsed to extract the perception waveform information data contained therein. This usually involves parsing and verifying the header, payload and check code of the data frame. After parsing the data frame, the required perception waveform information data is extracted according to the waveform identification and parameter fields. The extracted waveform parameters are used to reconstruct the perception waveform information through the corresponding algorithm or model.

[0091] S103, according to the perception period, the perception range and the perception performance requirement, the beam scanning scheme of the perception beam in the perception period is determined.

[0092] Among them, the beam scanning scheme refers to the strategy of how the base station scans and manages the perception beam in the perception period. It includes the number, layout, scanning parameters (such as scanning speed, frequency, angle, etc.) and scanning algorithm of the beam.

[0093] Optionally, the influence of the perception period, the perception range and the perception performance requirement on the beam scanning scheme is analyzed respectively, exemplarily:

[0094] If the perception period is longer, the target scene can be perceived more deeply in each period, improving the perception accuracy and resolution. But this may also lead to slower response speed to changes in the target scene. Short perception period: if the perception period is shorter, changes in the target scene can be captured faster, improving the response speed. But this may limit the time and resources available for perception in each period, affecting the perception accuracy and resolution.

[0095] If the perception range is larger, a more extensive beam scanning strategy needs to be adopted to cover the entire area. This may require increasing the number and scanning frequency of the beams to ensure full coverage of the target scene. If the perception range is smaller, a more concentrated beam scanning strategy can be used to focus on key areas. This helps to improve the perception accuracy and resolution, but may also limit the adaptability to changes in the target scene.

[0096] Sensing accuracy and resolution: To meet the high-precision and high-resolution sensing requirements, a more refined beam scanning scheme needs to be adopted. This may include using narrower beam widths, increasing the number of beams and scanning density, and other strategies.

[0097] Refresh rate: To meet the high refresh rate sensing requirements, the speed and frequency of beam scanning need to be accelerated. This may require optimization of beam scanning algorithms, improvement of hardware processing speed, and other strategies.

[0098] Determining the number and layout of beams: According to the requirements of sensing range and sensing accuracy, the number and layout of beams are determined. The number of beams should be sufficient to ensure comprehensive coverage of the target scene, while the layout of the beams should be reasonable to avoid mutual interference.

[0099] Setting beam scanning parameters: According to the requirements of sensing period and refresh rate, the parameters of beam scanning are set. This includes the scanning speed, scanning frequency, scanning angle, etc.

[0100] Optimizing beam scanning algorithms: To improve the efficiency and accuracy of beam scanning, the beam scanning algorithm can be optimized. For example, an adaptive beam scanning algorithm can be used to dynamically adjust the scanning strategy of the beam according to the changes of the target scene.

[0101] S104, according to the sensing waveform information and the beam scanning scheme, the sensing beam is configured.

[0102] Specifically, according to the requirements of the sensing waveform information, the key parameters of the sensing beam such as frequency, amplitude, phase, etc. are determined. These parameters should meet the performance requirements of accuracy, resolution and refresh rate of the sensing task. Consider the requirements of the beam scanning scheme for the sensing beam, such as the number, layout and scanning parameters of the beam. Ensure that the configuration of the sensing beam can support the effective implementation of the beam scanning scheme.

[0103] In the above beam configuration method, device, computer equipment and computer readable storage medium, the sensing period, sensing range and sensing performance requirements (including sensing accuracy, sensing resolution and refresh rate) of the target scene are obtained, and the scheme can ensure that the sensing system covers the entire target scene in the best way. This helps to reduce the sensing blind area and improve the comprehensiveness and accuracy of sensing. The sensing waveform information required by the sensing beam emitted by the base station in the target scene when performing sensing function is obtained from the data frame, which can ensure that the sensing beam matches the characteristics of the target scene. This helps to improve the penetration, anti-interference ability and echo quality of the sensing signal, thereby further improving the sensing accuracy and resolution.

[0104] Based on the sensing cycle, sensing range, and sensing performance requirements, a beam scanning scheme for the sensing beam is determined within the sensing cycle. This intelligent beam scanning strategy ensures a thorough and efficient scan of the target scene within a limited time, improving sensing efficiency and refresh rate. The sensing beam is configured based on the sensing waveform information and the beam scanning scheme. This flexible configuration allows the sensing system to dynamically adjust according to actual needs, adapting to sensing requirements under different scenarios and conditions. Simultaneously, it helps optimize the allocation and utilization of sensing resources, reducing the energy consumption and cost of the sensing system.

[0105] In an exemplary embodiment, the target scene includes at least one sensing area, and there is no overlap between the sensing areas; the data frame includes communication symbols and sensing symbols, the sensing symbols being used to describe the sensing waveform information corresponding to each sensing area.

[0106] Understandably, the target scenario is the object that the base station communicates with and senses, and it includes at least one sensing area. These sensing areas may be specific geographical regions, spatial ranges, or sets of objects, within which the base station needs to perform sensing tasks to obtain relevant information.

[0107] Furthermore, communication symbols are used to transmit user data, control information, and other communication content. The number and proportion of communication symbols affect the system's communication performance and resource utilization. Sensing symbols are used to describe the sensing waveform information corresponding to each sensing area. Sensing symbols contain key parameters of the sensing waveform information, such as frequency, amplitude, and phase, which are crucial for the base station to perform sensing tasks.

[0108] The ratio between the number of communication symbols and the number of sensing symbols is determined by the first intelligent model based on the target scenario type, the communication performance requirements and sensing performance requirements of the target scenario, and the resource allocation constraints of the base station in the target scenario.

[0109] Specifically, the first intelligent model includes a first sub-model. The ratio between the number of communication symbols and the number of sensing symbols is determined by the first sub-model in the first intelligent model based on the scenario type of the target scenario, the communication performance requirements of the target scenario, the sensing performance requirements, and the resource allocation constraints of the base station in the target scenario.

[0110] Understandably, the first sub-model needs to comprehensively consider the requirements of communication and sensing, as well as resource constraints, to find an optimal symbol ratio. This ratio should balance the performance of communication and sensing, ensuring that the system can efficiently transmit communication data while accurately performing sensing tasks.

[0111] The communication and perception resource allocation constraints of the base station in the target scenario refer to a series of measures and methods for reasonably allocating and utilizing various resources of the base station according to the communication and perception needs in a specific scenario, in order to optimize communication performance, improve network efficiency, and meet user needs. These resources include but are not limited to spectrum resources, power resources, antenna resources, and computing resources. The resource allocation constraints of the base station in the target scenario involve spectrum resources, power resources, and antenna resources, and the allocation of these resources directly affects the design of the data frame structure, specifically:

[0112] (1) The allocation of spectrum resources determines the frequency and bandwidth of data frame transmission. In the case of tight spectrum resources, the base station needs to design a more compact data frame structure to reduce transmission time and improve spectrum utilization. When the communication demand is high, the base station can allocate more spectrum resources to the communication symbol to increase the proportion of the communication symbol in the data frame, thereby ensuring smooth communication.

[0113] (2) The allocation of power resources affects the transmission distance and reception quality of data. In the case of long transmission distance or poor channel conditions, the base station needs to increase the transmission power to ensure reliable data transmission. At the same time, the base station can also adjust the power resources allocated to the perception symbol according to the perception needs to improve the accuracy and reliability of perception.

[0114] (3) The allocation of antenna resources can affect the directivity and spatial multiplexing rate of data transmission. Through reasonable antenna design, the base station can achieve more accurate spatial positioning, thereby improving the accuracy of perception. In multi-antenna, the base station can optimize the allocation of antenna resources through beamforming and other technologies to achieve better transmission effect and perception performance.

[0115] Specifically, the base station should dynamically adjust the proportion of communication symbols and perception symbols in the data frame according to real-time network conditions and user needs. The implementation of this strategy requires the base station to have an intelligent decision-making algorithm, which can be determined based on historical experience in different scenarios.

[0116] Correspondingly, the training samples of the first sub-model can include:

[0117] Scene label: Clearly identifies the classification information of different scene types, such as city, countryside, highway, and congested road section, etc. These labels are used to train the intelligent model to identify the communication and perception needs in different scenarios.

[0118] Scene features: Quantitative indicators that describe the characteristics of the scene, such as vehicle density, driving speed, road conditions, and weather conditions, etc. These features help the intelligent model understand the specific impact of the scene on communication and perception performance.

[0119] Traffic demand: represents the amount of information that needs to be exchanged between vehicles in a specific scenario, usually measured in data rate or packet number.

[0120] Communication quality requirement: such as bit error rate, delay time, etc., reflecting the reliability and real-time requirements of the communication system.

[0121] Perception range requirement: indicates the range of the surrounding environment that vehicles need to perceive in a specific scenario.

[0122] Perception accuracy requirement: such as object recognition accuracy, distance measurement accuracy, etc., reflecting the accuracy requirements of the perception system.

[0123] Spectrum resource limitation: indicates the total amount of spectrum resources available for communication and perception in a specific scenario.

[0124] Computing and storage resource limitation: indicates the amount of computing and storage resources available for processing communication and perception tasks at the base station or vehicle end in a specific scenario.

[0125] Historical proportion record: in similar scenarios in the past, the actual proportion of communication symbols and perception symbols in the data frame. These data can be used as a reference for intelligent model learning.

[0126] Optimal proportion label: in a specific scenario, the optimal proportion of communication symbols and perception symbols is verified by practice or calculated by theory. These labels are the goals of intelligent model learning.

[0127] Further, the perception waveform information corresponding to each perception area is determined by the first intelligent model according to the scene type of the target scene and the perception range corresponding to the perception area, and the waveform coverage ability of each candidate waveform.

[0128] Optionally, the first intelligent model includes a second sub-model, and the perception waveform information corresponding to each perception area is determined by the second sub-model in the first intelligent model according to the scene type of the target scene and the perception range corresponding to the perception area, and the waveform coverage ability of each candidate waveform.

[0129] It can be understood that different scene types (such as indoor, outdoor, urban, rural, etc.) have different requirements for perception waveform information. For example, indoor scenarios may require waveforms with better penetration ability and anti-interference, while outdoor scenarios may focus more on the propagation distance and coverage range of waveforms. Perception distance is one of the important factors in determining perception waveform information. Close-range perception may require waveforms with higher resolution and accuracy, while long-range perception focuses more on the propagation ability and anti-interference of waveforms. Different waveforms have different coverage abilities, including propagation distance, penetration ability, and anti-interference. The second sub-model needs to analyze the characteristics of each candidate waveform and select the most suitable waveform for the current perception task.

[0130] The second sub-model can employ advanced techniques such as deep learning, and through a large amount of training data and algorithm optimization, realize intelligent selection and configuration of perception waveform information. The composition of training samples should cover various possible scene types, perception distances, and candidate waveform combinations, and label the corresponding perception waveform information labels.

[0131] Specifically, it may include the following parts:

[0132] Scene type label: represents the classification information of different scene types, such as indoor, outdoor, urban, rural, etc.

[0133] Perception distance data: represents the specific numerical value or interval range of different perception distances.

[0134] Candidate waveform information: represents the characteristic parameters of different candidate waveforms, such as frequency, amplitude, phase, coverage ability, etc.

[0135] Perception waveform information label: represents the optimal perception waveform information selection under the given scene type and perception distance.

[0136] Further, the first intelligent model is also used to determine the time slot position of each perception symbol in the data frame.

[0137] Optionally, the first intelligent model further includes a third sub-model, and the third sub-model is also used to determine the time slot position of each perception symbol in the data frame.

[0138] It can be understood that the selection of time slot position is crucial for the performance and resource utilization of the system. Specifically: influences the coordination of communication and perception: the time slot position determines the arrangement order of communication symbols and perception symbols in the data frame, and further influences the execution time of communication and perception tasks. Unreasonable time slot arrangement may cause conflicts between communication and perception, reducing the overall performance of the system. Influences resource utilization: the selection of time slot position also determines the allocation method of system resources. If the time slot arrangement is unreasonable, it may cause waste or insufficient of resources, reducing the resource utilization of the system.

[0139] When determining the time slot position of each perception symbol in the data frame, the third sub-model needs to consider multiple factors. Specifically:

[0140] Timing requirements of communication and perception: the third sub-model needs to analyze the timing relationship of communication and perception tasks to ensure that they can be executed in the expected order and time interval. This helps to avoid conflicts between communication and perception, and improves the coordination and stability of the system.

[0141] Resource availability: The third sub-model also needs to consider the availability of system resources, including spectrum resources, computing resources, storage resources, etc. In the case of limited resources, the third sub-model needs to optimize the time slot arrangement to maximize the utilization of resources.

[0142] Application of intelligent algorithms: The third sub-model may use deep learning, reinforcement learning, and other intelligent algorithms to determine the time slot position. These algorithms can learn and optimize the time slot arrangement strategy according to historical data and real-time feedback to adapt to different application scenarios and needs.

[0143] For example, in the intelligent transportation scenario, the base station needs to meet the communication needs between vehicles and the road condition perception needs. The third sub-model can dynamically adjust the proportion of communication symbols and perception symbols in the data frame and the time slot position according to real-time traffic conditions and demand changes. For example, in the case of traffic congestion, the communication demand increases because vehicles need to exchange information more frequently to coordinate driving. At this time, the third sub-model can increase the proportion of communication symbols in the data frame and optimize the time slot arrangement to ensure smooth communication. In the case of complex road conditions, the perception demand increases because vehicles need to accurately perceive the surrounding environment to make correct driving decisions. At this time, the third sub-model can increase the proportion of perception symbols in the data frame and adjust the time slot position to improve the accuracy and reliability of perception.

[0144] In one embodiment, as shown in FIG. 2, according to the perception period, the perception range, and the perception performance, the beam scanning scheme of the perception beam in the perception period is determined, including:

[0145] S201, allocating a beam period for each perception beam corresponding to a perception area.

[0146] Each type of perception beam covers a different perception area, so in this embodiment, each perception area of the target scene corresponds to a type of perception beam.

[0147] For example, if one of the perception areas is an airspace or water area outside a 500-meter range, a full pulse wave is selected as the perception beam corresponding to the perception area; if the perception area is a ground area outside a 200-meter range, a full continuous wave is selected as the perception beam corresponding to the perception area.

[0148] Optionally, for each sensing region, it is evaluated which candidate waveforms are able to cover the region. This can be achieved by comparing the sensing range of the beam and the range of the sensing region. If the sensing range of the beam covers the sensing region completely or partially, the beam is considered as a potential candidate. After determining the candidate waveforms that are able to cover each sensing region, it is further needed to select the optimal sensing beam. This can be done according to various criteria, such as the intensity, directivity, signal-to-noise ratio, energy consumption, etc. of the beam. In some cases, it can be needed to select multiple beams to provide redundant coverage or to enhance the sensing effect.

[0149] wherein each beam period is located within the sensing period, and adjacent beam periods do not overlap with each other.

[0150] It can be understood that the beam period refers to the time required for a beam to be transmitted, received and complete a full scan.

[0151] For example, a sensing period T all may be 1 second, and the types of sensing beams can include pulse wave and continuous wave, the scanning period of the pulse wave T p may be 0.1 second, and the scanning period of the continuous wave T c may be 0.01 second.

[0152] wherein T p and T c may be determined according to the sensing performance requirements of the corresponding sensing beam in the target scene.

[0153] For example, the beam schemes formed by various sensing beams (Beam1, Beam2, Beam3, BeamN) in a frame structure can be as shown in Figure 3, beam scheme 1, beam scheme 2, beam scheme 3 and beam scheme 4.

[0154] In one implementation, historical experience can be used to manually divide the sensing beam period allocated to each sensing region.

[0155] In another implementation, allocating the beam period to the sensing beam corresponding to each sensing region includes: inputting the scene information of the target scene, the region information of each sensing region and the beam information of the sensing beam into a second intelligent model to obtain the beam period allocated to the sensing beam corresponding to each sensing region output by the second intelligent model.

[0156] wherein the construction process of the second intelligent model is: collecting and organizing the scene information of the target scene, which can include the size, shape, obstacle distribution, environmental characteristics, etc. of the scene. Determine the region information of each sensing region, such as the location, size, shape of each region and their relative position relationship in the scene. Obtain the beam information of the sensing beam, including the transmission angle, coverage range, power and other parameters of the beam.

[0157] A second intelligent model suitable for handling such problems is selected or constructed. This model should be able to receive scene information, region information, and beam information as input and output the assigned beam period for each perception region. Possible model choices include machine learning algorithms (such as decision trees, random forests, support vector machines, etc.) or deep learning algorithms (such as neural networks, convolutional neural networks, etc.).

[0158] If a model that needs training is used, the model needs to be trained using historical data or simulation data. The training data should contain similar scene information, region information, and beam information, as well as the corresponding beam period assignment results. Through training, the model should be able to learn how to assign reasonable beam periods to each perception region based on the input information.

[0159] The use process of the second intelligent model is as follows: the prepared scene information, region information, and beam information are input into the trained second intelligent model. The output from the model is the beam period assigned to the corresponding perception beam for each perception region.

[0160] Specifically, the second intelligent model first analyzes the characteristics of each perception region, including the size, shape, complexity of the perception range, and the expected perception target, etc. These characteristics will affect the selection and allocation of beam periods, as different regions may require different scanning times and precision.

[0161] Based on the characteristics of the perception region, the second intelligent model will calculate and optimize the beam period corresponding to each perception region. The beam period should ensure that each region is completely scanned once within the perception period, while avoiding overlap and conflict between adjacent beam periods.

[0162] The second intelligent model will allocate the corresponding perception beam for each perception region according to the optimized beam period. The characteristics of the beam, such as beam width, scanning angle, power, etc., will be considered during the allocation process to ensure that the beam can cover the entire perception region and meet the requirements of perception performance.

[0163] The second intelligent model also considers the resource limitations of the base station, such as spectrum resources, computing resources, storage resources, etc., to ensure that the allocation of beam periods and the use of perception beams do not exceed the carrying capacity of the base station. By optimizing resource allocation, the overall performance and resource utilization of the system can be improved.

[0164] S202, for each perception region, according to the perception performance requirements and the perception range of the perception region, determine the beam scanning scheme of the perception beam used by the base station in the perception region within the corresponding beam period to perform the perception function.

[0165] Optionally, for any sensing area, the beam scanning scheme of the sensing beam employed by the base station in the sensing area to perform the sensing function within the corresponding beam period can include: scanning mode selection, scanning path planning, scanning parameter setting; wherein the scanning parameter setting can include scanning speed, scanning angle, beam width and scanning times, etc.

[0166] Wherein the beam scanning scheme satisfies the refresh rate.

[0167] It can be understood that the refresh rate refers to the speed of scanning and updating the sensing area by the sensing. It determines how quickly changes in the sensing area can be captured. In order to ensure that the beam scanning scheme meets the refresh rate requirement, the base station needs to comprehensively adjust the scanning mode, scanning path, scanning parameters, etc. according to the characteristics of the sensing area, sensing performance requirements and resource conditions. For example, in the scenario requiring high refresh rate, continuous scanning mode can be selected, scanning path can be optimized to reduce scanning time, scanning speed can be increased or scanning times can be increased, etc.

[0168] In an exemplary embodiment, as shown in FIG. 4, the sensing range includes a sensing distance range and a sensing angle range; according to the sensing performance requirements and the sensing range corresponding to the sensing area, the beam scanning scheme of the sensing beam employed by the base station in the sensing area to perform the sensing function within the corresponding beam period is determined, including:

[0169] S401, according to the sensing distance range and the sensing angle range of the sensing area, determining the beam width parameter and the total number of beams corresponding to the sensing area.

[0170] Specifically, the sensing angle range refers to the coverage range of the geographical or spatial area that the base station needs to sense in terms of angle. The size of the sensing angle range will directly affect the selection of the beam width.

[0171] Beam width parameter: beam width refers to the coverage angle of the beam in the horizontal or vertical direction. A wider beam can cover a larger angle range, but may reduce the resolution of sensing; while a narrower beam can provide higher sensing resolution, but the angle range covered is limited.

[0172] Sensing distance range: this refers to the coverage range of the geographical or spatial area that the base station needs to sense in terms of distance. The size of the sensing distance range will directly affect the selection of the total number of beams.

[0173] Total number of beams: this refers to the number of beams configured by the base station to cover the entire sensing area. The total number of beams is related to multiple factors such as sensing distance range, beam width parameter and sensing performance requirements, etc.

[0174] In determining the beam width parameter, the base station needs to balance the requirements of the sensing angle range and the sensing resolution. If the sensing angle range is large, a wider beam may be selected to ensure comprehensive coverage; if the sensing performance requirement is high, a finer sensing resolution is required, and a narrower beam may be selected.

[0175] In this embodiment, the total number of beams Beam all is determined based on the sensing distance range. all Further, the beam width parameter Beam width is determined based on the total number of beams Beam and the sensing angle range.

[0176] For example, the total number of beams Beam all is equal to the sensing angle range divided by the beam width parameter Beam width .

[0177] Optionally, assuming that a full azimuth angle of 360 degrees needs to be covered, and the sensing accuracy requirement is high, the beam width parameter is selected as 5 degrees. According to the above steps, the total number of beams required can be calculated as: total number of beams = 360 degrees / 5 degrees = 72.

[0178] S402, according to the sensing accuracy and the sensing resolution of the sensing area, processing the beam width parameter and the total number of beams, to obtain a beam scanning scheme of the sensing beam used by the base station for performing the sensing function on the sensing area within a corresponding beam period.

[0179] Wherein, the beam scanning scheme satisfies the refresh rate.

[0180] It can be understood that for each type of sensing beam, after determining the beam width parameter and the total number of beams of the type of sensing beam, according to the sensing accuracy and the sensing resolution corresponding to the sensing area, the beam width parameter and the total number of beams are processed, the purpose is to further divide the scanning granularity of the type of sensing beam, and obtain a beam scanning scheme adapted to the sensing accuracy.

[0181] Specifically, as shown in FIG. 5, according to the sensing accuracy and the sensing resolution of the sensing area, processing the beam width parameter and the total number of beams, to obtain a beam scanning scheme of the sensing beam used by the base station for performing the sensing function on the sensing area within a corresponding beam period, including:

[0182] S501, according to the sensing accuracy and the sensing resolution corresponding to the sensing area, dividing the beam period of the sensing beam corresponding to the sensing area to obtain a plurality of same scanning periods.

[0183] Specifically, a division coefficient is determined according to the sensing accuracy and the sensing resolution corresponding to the sensing area, and the number of scans M of the beam in the scanning period is determined according to the division coefficient, and the scanning duration T of the single scan is determined r .

[0184] For example, the velocity measurement resolution ΔV in the sensing resolution is taken as the division coefficient for illustration:

[0185] When the velocity measurement resolution ΔV is used to determine the scanning period, the scanning period is determined by the following formula (1):

[0186] Wherein, λ is the signal wavelength, τ is the scanning period, τ is also recorded as T s ;

[0187] M is the number of scans of the beam in the scanning period, T r is the scanning duration of the single scan.

[0188] S502, according to the total number of beams, determine the number of scans corresponding to each scanning period.

[0189] Specifically, the number of scans M corresponding to each scanning period is equal to the total number of beams / T s ;

[0190] Wherein, the number of scans M corresponding to any scanning period is equal to Beam block ×Beamrepeat_out;

[0191] Wherein, Beam block is the number of beams of the sensing beam in the scanning period, and Beamrepeat_out is the scanning repetition number of the sensing beam in the scanning period.

[0192] As the example above, on the basis of positioning the scanning period of the sensing beam as T s , if the sensing beam is a pulse wave, the scanning period corresponding to the sensing beam is recorded as T s_p ; if the sensing beam is a pulse wave, the scanning period corresponding to the sensing beam is recorded as T s_c ;

[0193] Correspondingly, the number of scans M corresponding to any scanning period is equal to T s_p = T p ;

[0194] Correspondingly, the number of scans M corresponding to any scanning period is equal to T s_c = T c .

[0195] S503, determine, according to each scanning period and the scanning number corresponding to each scanning period, a beam scanning scheme of the sensing beam of the base station in the corresponding beam period, which is used for performing the sensing function in the sensing area.

[0196] In an implementation manner, each scanning period and the scanning number corresponding to each scanning period can be directly determined as the beam scanning scheme corresponding to the sensing area.

[0197] In another implementation manner, each scanning period and the scanning number corresponding to each scanning period can be further refined to obtain the beam scanning scheme corresponding to the sensing area.

[0198] In an exemplary embodiment, as shown in FIG. 6, according to each scanning period and the scanning number corresponding to each scanning period, a beam scanning scheme of the sensing beam of the base station in the corresponding beam period, which is used for performing the sensing function in the sensing area, comprises:

[0199] S601, for each scanning period, determine a plurality of same frame periods contained in the scanning period, and according to the scanning number corresponding to the scanning period, determine the intra-frame scanning number and the scanning interval corresponding to each frame period.

[0200] For example, one scanning period T s is divided into a plurality of same frame periods T frame ; for each frame period T frame , the intra-frame scanning number is Beam repeat_in , and one Beam repeat_in corresponds to the intra-frame scanning number N beam , and the beam interval is K beam .

[0201] It can be understood that, based on the secondary sensing accuracy, the more the number of continuous beam repetitions N beam in one frame period, the greater the single-direction beam gain, the stronger the long-distance coverage ability, and the more suitable for the target tracking scene. The higher the beam switching frequency in one frame period, the smaller the interval of different beams, and the more suitable for the low-speed scene.

[0202] For each frame period T frame , the intra-frame scanning number is Beam repeat_in ; correspondingly,

[0203] S602, determine, according to the intra-frame scanning number and the scanning interval of the frame period corresponding to each scanning period, the beam scanning scheme of the sensing beam of the base station in the corresponding beam period, which is used for performing the sensing function in the sensing area.

[0204] Furthermore, for the same scanning period, the number of intra-frame scans and the scan interval within that frame period can form various schemes, as shown in Figure 3, for example:

[0205] Beam scheme 1: Only one beam is included in one frame period, and the single beam is repeated 10 times.

[0206] Beam configuration 2: Contains only 2 beams within one frame period, and the number of repetitions per beam is half that of configuration 1 (N). beam / 2, the two beams scan continuously in chronological order.

[0207] Beamforming scheme 3: Contains multiple beams within a frame period; the single-beam scan time is N times the total time occupied by the sensing symbols. beam / N,N beam Each beam scans continuously in chronological order.

[0208] Beaming scheme 4: It also contains multiple beams within a frame period, but with different beam intervals. After beam 1 to beam scanning is completed, beam 1 to beam scanning begins again.

[0209] In one exemplary embodiment, this embodiment provides a beam configuration method, including:

[0210] Taking the millimeter-wave communication frame structure DDDSU as an example, with a subcarrier spacing of 120kHz, the corresponding period is 0.625ms, i.e., T frame = 0.0625ms.

[0211] The refresh rate of the target scene does not exceed T all =1s, taking the resource allocation constraint of the base station in the target scenario, which represents the proportion of sensing resources in the total resources corresponding to the data frame not exceeding 35%, as an example, it is found that 24 sensing symbols can be set in one data frame (DDDSU) period.

[0212] Depending on the specific application scenario and coverage requirements, for example, if the sensing area is in the airspace or water beyond 500m, full pulse wave coverage can be selected. If the sensing area is on the ground beyond 200m, full continuous wave coverage can be selected. The specific locations of the 24 sensing symbols and the 70 symbols can be at different D or S positions. These options form a candidate set, which is matched according to the specific scenario using an intelligent algorithm.

[0213] Taking full pulse wave coverage as an example, considering a sensing angle range of 60°, using Beam... all =120 sensing beams provide coverage. Further considering velocity resolution requirements, the duration T of the sensing signal is set. s =40ms. The entire coverage area is divided into 60 sub-regions. The number of sensing beams within the scanning cycle is set.block = 6, and repeats in the coverage sub-area with the same sensing beam sweeping scheme, and sets the number of repetitions Beamrepeat_out_p = 20.

[0214] One scanning period contains multiple communication frame periods T frame = 0.625 ms. For each frame period T frame , the sensing beam repeats the sweeping Beam repeat_in = 64 times;

[0215] For the pulsed wave

[0216] Beamrepeat_out_p x T s_p = 20 x 40 = 800 ms = T p .

[0217] Further, a sensing beam sweeping scheme in a frame period T frame = 0.625 ms is designed. For a low-speed scenario, a sensing beam arrangement scheme in a frame period is designed, and the number of sensing beam repetitions N beam and the sensing beam interval K beam in a frame period are set.

[0218] It should be understood that although each step in the flowchart involved in the above embodiments is shown in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in the flowchart involved in the above embodiments can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or steps or stages in other steps.

[0219] Based on the same inventive concept, the embodiments of the present application also provide a beam configuration device for implementing the above-mentioned beam configuration method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, and therefore the specific limitations in one or more beam configuration device embodiments provided below can refer to the limitations of the beam configuration method in the above text, which will not be repeated here.

[0220] In an exemplary embodiment, as shown in FIG. 7, a beam configuration device is provided, including an acquisition module 11, a beam configuration method module 12, a sensing data acquisition module 13, and a data transmission module 14, wherein:

[0221] The acquisition module 11 is configured to acquire a perception period, a perception range, and a perception performance requirement of a target scene; the perception performance requirement comprises a perception accuracy, a perception resolution, and a refresh rate;

[0222] The waveform determination module 12 is configured to acquire, from a data frame in which a base station performs a communication and a perception function in the target scene, perception waveform information required by a perception beam of the base station when performing the perception function in the target scene.

[0223] The scanning scheme determination module 13 is configured to determine a beam scanning scheme of the perception beam in the perception period according to the perception period, the perception range, and the perception performance requirement.

[0224] The beam configuration module 14 is configured to configure the perception beam according to the perception waveform information and the beam scanning scheme.

[0225] In one of the embodiments, the target scene comprises at least one perception region; the data frame comprises a communication symbol and a perception symbol, and the perception symbol is used to describe perception waveform information corresponding to each perception region.

[0226] The proportion between the number of the communication symbols and the number of the perception symbols is determined by the first intelligent model according to a scene type of the target scene, a communication performance requirement of the target scene, the perception performance requirement, and a communication and perception resource allocation constraint of the base station in the target scene.

[0227] The perception waveform information corresponding to each perception region is determined by the first intelligent model according to the scene type of the target scene, the perception range corresponding to each perception region, and a waveform coverage capability of each candidate waveform.

[0228] The first intelligent model is further configured to determine time slot positions of each perception symbol in the data frame.

[0229] In one of the embodiments, the scanning scheme determination module 13 is configured to:

[0230] allocate a beam period to the perception beam corresponding to each perception region; each beam period is located in the perception period, and adjacent beam periods do not overlap with each other.

[0231] For each perception region, a beam scanning scheme of the perception beam of the base station in the corresponding beam period when performing the perception function in the perception region is determined according to the perception performance requirement and the perception range corresponding to the perception region.

[0232] In one of the embodiments, the perception range comprises a perception distance range and a perception angle range; the scanning scheme determination module 13 is configured to:

[0233] determine a beam width parameter and a total number of beams corresponding to the perception area according to a perception distance range and a perception angle range of the perception area;

[0234] process the beam width parameter and the total number of beams according to a perception accuracy and a perception resolution of the perception area, to obtain a beam scanning scheme of a perception beam of the base station for performing the perception function on the perception area in a corresponding beam period;

[0235] The beam scanning scheme satisfies a refresh rate.

[0236] In one embodiment, the processing of the beam width parameter and the total number of beams according to the perception accuracy and the perception resolution of the perception area to obtain the beam scanning scheme of the perception beam of the base station for performing the perception function on the perception area in the corresponding beam period includes:

[0237] divide the beam period of the perception beam corresponding to the perception area according to the perception accuracy and the perception resolution of the perception area, to obtain a plurality of same scanning periods;

[0238] determine a scanning number corresponding to each scanning period according to the total number of beams;

[0239] determine the beam scanning scheme of the perception beam of the base station for performing the perception function on the perception area in the corresponding beam period according to each scanning period and the scanning number corresponding to each scanning period.

[0240] In one embodiment, the scanning scheme determination module 13 is configured to:

[0241] for each scanning period, determine a plurality of same frame periods contained in the scanning period, and determine a frame scanning number and a scanning interval corresponding to each frame period according to the scanning number corresponding to the scanning period;

[0242] determine the frame scanning number and the scanning interval of each frame period corresponding to each scanning period as the beam scanning scheme of the perception beam of the base station for performing the perception function on the perception area in the corresponding beam period.

[0243] In one embodiment, the perception angle range includes a horizontal visual angle range and a vertical visual angle range; the perception accuracy includes but is not limited to a distance accuracy, a speed accuracy, and an angle accuracy; and the perception resolution includes a distance resolution, a speed resolution, or an angle resolution.

[0244] In one embodiment, the scanning scheme determination module 13 is configured to:

[0245] allocate a beam period to each perception beam corresponding to each perception area, including:

[0246] The scene information of the target scene, the area information of each perception area, and the beam information of the perception beam are input into the second intelligent model to obtain the beam period allocated to the perception beam corresponding to each perception area output by the second intelligent model.

[0247] Each module in the beam configuration device can be realized by software, hardware, and combinations thereof, in whole or in part. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in a computer device in software form, so as to be called and executed by a processor to perform operations corresponding to each module.

[0248] In an exemplary embodiment, a computer device, which can be a server, is provided, and an internal structure diagram of the computer device can be as shown in FIG. 8. The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, the memory, and the input / output interface are connected through a bus, and the communication interface is connected to the bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores operations, a computer program, and a database. The internal memory provides an environment for running of the operations and the computer program in the non-volatile storage medium. The database of the computer device is configured to store data of the beam configuration method. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through a network connection. The computer program is executed by the processor to implement a beam configuration method.

[0249] Those skilled in the art can understand that the structure shown in FIG. 8 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. Specifically, the computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0250] In an exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the following steps:

[0251] Obtaining a perception period, a perception range, and a perception performance requirement of a target scene; the perception performance requirement includes a perception accuracy, a perception resolution, and a refresh rate;

[0252] Obtaining, from a data frame used by a base station to perform communication and perception functions in a target scene, perception waveform information required by a perception beam emitted by the base station when performing a perception function in the target scene;

[0253] determining a beam scanning scheme of the sensing beam in the sensing period according to the sensing period, the sensing range and the sensing performance requirement;

[0254] configuring the sensing beam according to the sensing waveform information and the beam scanning scheme.

[0255] In one embodiment, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the following steps:

[0256] obtaining a sensing period, a sensing range and a sensing performance requirement of a target scene; the sensing performance requirement includes sensing accuracy, sensing resolution and refresh rate;

[0257] obtaining sensing waveform information required by a sensing beam emitted by a base station when performing a sensing function in a target scene from a data frame adopted by the base station to perform a communication and sensing function in the target scene;

[0258] determining a beam scanning scheme of the sensing beam in the sensing period according to the sensing period, the sensing range and the sensing performance requirement;

[0259] configuring the sensing beam according to the sensing waveform information and the beam scanning scheme.

[0260] In one embodiment, a computer program product is provided, and the computer program product includes a computer program, and the computer program is executed by a processor to implement the following steps:

[0261] obtaining a sensing period, a sensing range and a sensing performance requirement of a target scene; the sensing performance requirement includes sensing accuracy, sensing resolution and refresh rate;

[0262] obtaining sensing waveform information required by a sensing beam emitted by a base station when performing a sensing function in a target scene from a data frame adopted by the base station to perform a communication and sensing function in the target scene;

[0263] determining a beam scanning scheme of the sensing beam in the sensing period according to the sensing period, the sensing range and the sensing performance requirement;

[0264] configuring the sensing beam according to the sensing waveform information and the beam scanning scheme.

[0265] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, the processes of the above-mentioned embodiment methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. The non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. The volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., and is not limited thereto. The processor involved in the embodiments provided in the present application can be a general processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a quantum computing-based beam configuration method logic device, an artificial intelligence (AI) processor, etc., and is not limited thereto.

[0266] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above-mentioned embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present application.

[0267] The above embodiments only express several implementation ways of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation to the patent scope of the application. It should be pointed out that for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, which all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for beam configuration, applied to a base station, the method comprising: obtaining a sensing period, a sensing range and a sensing performance requirement of a target scene; the sensing performance requirement comprising a sensing accuracy, a sensing resolution and a refresh rate; obtaining, from a data frame in which the base station performs a communication and a sensing function in the target scene, sensing waveform information required by a sensing beam of the base station when performing the sensing function in the target scene; determining a beam scanning scheme of the sensing beam in the sensing period according to the sensing period, the sensing range and the sensing performance requirement; and configuring the sensing beam according to the sensing waveform information and the beam scanning scheme. 2.The method of claim 1, wherein the target scene comprises at least one sensing area; the data frame comprises a communication symbol and a sensing symbol, the sensing symbol being used to describe sensing waveform information corresponding to each sensing area; a proportion between a number of the communication symbols and a number of the sensing symbols is determined by a first intelligent model according to a scene type of the target scene, a communication performance requirement of the target scene, the sensing performance requirement, and a communication and sensing resource allocation constraint of the base station in the target scene; wherein the sensing waveform information corresponding to each sensing area is determined by the first intelligent model according to the scene type of the target scene and a sensing range corresponding to the sensing area, and a waveform coverage capability of each candidate waveform; and wherein the first intelligent model is further used to determine time slot positions of each sensing symbol in the data frame. 3.The method of claim 2, wherein the determining the beam scanning scheme of the sensing beam in the sensing period according to the sensing period, the sensing range and the sensing performance requirement comprises: allocating a beam period to the sensing beam corresponding to each sensing area; wherein each beam period is located in the sensing period, and adjacent beam periods do not overlap with each other; and for each sensing area, determining a beam scanning scheme of the sensing beam of the base station in a corresponding beam period according to a sensing performance requirement and a sensing range corresponding to the sensing area. 4.The method of claim 3, wherein the sensing range comprises a sensing distance range and a sensing angle range; and the determining the beam scanning scheme of the sensing beam of the base station in the corresponding beam period according to the sensing performance requirement and the sensing range corresponding to the sensing area comprises: determining a beam width parameter and a total number of beams corresponding to the sensing area according to the sensing distance range and the sensing angle range of the sensing area; processing the beam width parameter and the total number of beams according to the sensing accuracy and the sensing resolution of the sensing area, to obtain the beam scanning scheme of the sensing beam of the base station in the corresponding beam period for performing the sensing function on the sensing area; and wherein the beam scanning scheme satisfies the refresh rate. ​ ​ ​ wherein ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ 5. The method of claim 4, wherein the processing the beam width parameter and the total number of beams according to the sensing accuracy and the sensing resolution of the sensing area to obtain the beam scanning scheme of the sensing beams of the base station in the corresponding beam period for performing the sensing function in the sensing area comprises: dividing the beam period of the sensing beams corresponding to the sensing area according to the sensing accuracy and the sensing resolution of the sensing area to obtain a plurality of same scanning periods; determining the number of scans corresponding to each scanning period according to the total number of beams; and determining the beam scanning scheme of the sensing beams of the base station in the corresponding beam period for performing the sensing function in the sensing area according to each scanning period and the number of scans corresponding to each scanning period.

6. The method of claim 5, wherein the determining the beam scanning scheme of the sensing beams of the base station in the corresponding beam period for performing the sensing function in the sensing area according to each scanning period and the number of scans corresponding to each scanning period comprises: determining a plurality of same frame periods contained in each scanning period, and determining the number of intra-frame scans and the scanning interval of each frame period according to the number of scans corresponding to the scanning period; and determining the number of intra-frame scans and the scanning interval of each frame period corresponding to each scanning period as the beam scanning scheme of the sensing beams of the base station in the corresponding beam period for performing the sensing function in the sensing area.

7. The method of claim 4, wherein the sensing angle range comprises a horizontal view angle range and a vertical view angle range; the sensing accuracy comprises, but is not limited to, distance accuracy, speed accuracy, and angle accuracy; and the sensing resolution comprises distance resolution, speed resolution, or angle resolution.

8. The method of claim 3, wherein the allocating the beam period to the sensing beams corresponding to each sensing area comprises: inputting scene information of the target scene, area information of each sensing area, and beam information of the sensing beams into a second intelligent model to obtain the beam period allocated to the sensing beams corresponding to each sensing area output by the second intelligent model.

9. The method of claim 2, wherein the first intelligent model comprises a first sub-model, a second sub-model, and a third sub-model; and the proportion between the number of communication symbols and the number of sensing symbols is determined by the first sub-model according to the scene type of the target scene, the communication performance requirement of the target scene, the sensing performance requirement, and the communication and sensing resource allocation constraint of the base station in the target scene; wherein the training sample of the first sub-model comprises at least one of the following: scene label, scene feature, communication volume requirement, communication quality requirement, sensing range requirement, sensing accuracy requirement, spectrum resource limitation, computing and storage resource limitation, historical proportion record, and optimal proportion label. ​ ​ ​ ​ ​ ​ ​ The perception waveform information corresponding to each perception area is determined by the second sub-model according to a scene type of the target scene, a perception range corresponding to the perception area, and a waveform coverage capability of each candidate waveform; wherein the training sample of the second sub-model includes at least one of the following: a scene type label, perception distance data, candidate waveform information, and a perception waveform information label; The time slot position of each perception symbol in the data frame is determined by the third sub-model according to the time sequence requirement of communication and perception and the availability of resources.

10. The method of claim 8, wherein the second intelligent model comprises a machine learning algorithm or a deep learning algorithm.

11. The method of claim 4, wherein the determining the beam width parameter and the total number of beams corresponding to the perception area according to the perception distance range and the perception angle range of the perception area comprises: determining the total number of beams corresponding to the perception area based on the perception distance range of the perception area; determining the beam width parameter corresponding to the perception area based on the total number of beams and the perception angle range.

12. The method of claim 11, wherein the determining the beam width parameter corresponding to the perception area based on the total number of beams and the perception angle range comprises: taking the ratio of the perception angle range to the total number of beams as the beam width parameter corresponding to the perception area.

13. A beam configuration apparatus, comprising: an acquisition module configured to acquire a perception period, a perception range, and a perception performance requirement of a target scene; the perception performance requirement comprises a perception accuracy, a perception resolution, and a refresh rate; a waveform determination module configured to acquire, from a data frame used by a base station to perform a communication and perception function in the target scene, perception waveform information required by a perception beam emitted by the base station to perform the perception function in the target scene; a scanning scheme determination module configured to determine a beam scanning scheme of the perception beam in the perception period according to the perception period, the perception range, and the perception performance requirement; a beam configuration module configured to configure the perception beam according to the perception waveform information and the beam scanning scheme.

14. A computer device, comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 12 when executing the computer program.

15. A computer readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method of any one of claims 1 to 12 when executed by a processor.

16. A computer program product comprising a computer program, wherein the computer program implements the steps of the method of any one of claims 1 to 12 when executed by a processor.

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