Bandwidth allocation method, device and system for sense-transmission algorithmic control closed loop

Abstract

The specification provides a bandwidth allocation method, device and system for a sense-transmitting calculation and control closed loop, the method comprising: determining the channel traversal capacity of each sensor to the unmanned aerial vehicle; determining the data allocation weight corresponding to each sensor based on the channel traversal capacity corresponding to each sensor, the data amount obtained by each sensor and the first data amount; wherein the first data amount is the minimum data amount for the unmanned aerial vehicle to determine the correct control instruction, and the data allocation weight is used to indicate the ratio of the data amount allowed to be transmitted by each sensor to the first data amount; and determining the bandwidth allocated to each sensor based on the channel traversal capacity corresponding to each sensor, the data allocation weight and the total bandwidth. The disclosure minimizes the transmission delay of sensor data while ensuring the correct execution of unmanned operation tasks, effectively improving the availability of the sense-transmitting calculation and control closed loop system.

Description

TECHNICAL FIELD

[0001] The present specification relates to the field of communication, and in particular, to a bandwidth allocation method, device and system for a sensing-communication-computing-control closed loop. BACKGROUND

[0002] China is vast in territory, and the communication scene is complex and diverse. In remote rural areas, post-disaster areas and offshore areas, due to the destruction of ground base stations or the difficulty of intensive deployment, the ground network is difficult to provide efficient communication services. In the process of emergency rescue, it has become a development trend to use ground residual base stations, unmanned aerial vehicles and satellites and other facilities to build emergency rescue communication networks to support machine operation. In order to improve system performance, the system runs in a sensing-communication-computing-control (SC 3 ) network architecture, which is referred to as a sensing-communication-computing-control closed loop network architecture. A plurality of sensors can sense the same target, and transmit sensor data to an unmanned aerial vehicle. The unmanned aerial vehicle is equipped with a communication module and a mobile edge computing (MEC) module, which is responsible for receiving and analyzing sensor data, making decisions, and transmitting control instructions to on-site robots to perform controlled operations. The SC 3 The closed loop cycle is crucial for the correct execution of the task, which also puts higher requirements on the transmission delay of sensor data from the sensor to the unmanned aerial vehicle.

[0003] However, there is a lack of a task-oriented bandwidth allocation scheme that takes into account both sensor data redundancy and channel conditions and minimizes the transmission delay of sensor data. SUMMARY

[0004] Therefore, the present specification provides a bandwidth allocation method, device and system for a sensing-communication-computing-control closed loop.

[0005] According to a first aspect of an embodiment of the present specification, a bandwidth allocation method for a sensing-communication-computing-control closed loop is provided, the method is executed by an unmanned aerial vehicle, and the method comprises:

[0006] determining the channel traversal capacity of each sensor to the unmanned aerial vehicle;

[0007] determining a data allocation weight corresponding to each sensor based on the channel traversal capacity corresponding to each sensor, the amount of data obtained by each sensor, and a first data amount, wherein the first data amount is the minimum data amount for the unmanned aerial vehicle to determine a correct control instruction, and the data allocation weight is used to indicate the ratio of the amount of data transmitted by each sensor to the first data amount;

[0008] determine a bandwidth allocated to each sensor based on the channel traversal capacity of each sensor to the UAV, the data distribution weight corresponding to each sensor, and a total bandwidth.

[0009] According to a second aspect of the embodiments of the present specification, a bandwidth allocation device for a sensor-algorithm-control closed loop is provided, the device is deployed on a UAV, and the device comprises:

[0010] a first determining module configured to determine a channel traversal capacity of each sensor to the UAV;

[0011] a second determining module configured to determine a data distribution weight corresponding to each sensor based on the channel traversal capacity of each sensor, an amount of data obtained by each sensor, and a first amount of data; wherein the first amount of data is a minimum amount of data for the UAV to determine a correct control instruction, and the data distribution weight is used to indicate a ratio of an amount of data transmitted by each sensor to the first amount of data;

[0012] a third determining module configured to determine a bandwidth allocated to each sensor based on the channel traversal capacity of each sensor to the UAV, the data distribution weight corresponding to each sensor, and a total bandwidth.

[0013] According to a third aspect of the embodiments of the present specification, a communication system is provided, the system comprises:

[0014] a UAV, wherein the bandwidth allocation device for a sensor-algorithm-control closed loop according to the second aspect is deployed on the UAV; and wherein a user communication module, a satellite communication module, and an edge computing module are also deployed on the UAV;

[0015] a plurality of sensors;

[0016] at least one target;

[0017] a robot;

[0018] a satellite;

[0019] a cloud server.

[0020] According to a fourth aspect of the embodiments of the present specification, a computer readable storage medium is provided, and the computer readable storage medium stores computer instructions, and the computer instructions are executed by a processor to implement the steps of the method according to any one of the first aspect.

[0021] According to a fifth aspect of the embodiments of the present specification, a computer program product is provided, and the computer program product comprises computer program / instructions, and the computer program / instructions are executed by a processor to implement the steps of the method according to any one of the first aspect.

[0022] The technical solutions provided by the embodiments of the present specification can have the following beneficial effects:

[0023] In the embodiments of the present specification, the data distribution weight corresponding to each sensor can be determined based on the channel traversal capacity of each sensor to the unmanned aerial vehicle, the data amount obtained by each sensor, and the first data amount, and then the bandwidth allocated to each sensor can be determined based on the channel traversal capacity corresponding to each sensor, the data distribution weight, and the total bandwidth, so as to minimize the uploading delay of sensor data in the case of ensuring the correct execution of unmanned operation tasks, effectively improving the SC 3 Availability of a closed loop system.

[0024] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present specification. BRIEF DESCRIPTION OF DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present specification and serve to explain the principles of the present specification together with the specification.

[0026] Figure 1 FIG. 1 is a structural schematic diagram of a sensory calculation control closed loop network provided by an exemplary embodiment.

[0027] Figure 2 FIG. 2 is a flow schematic diagram of a bandwidth allocation method for a sensory calculation control closed loop provided by an exemplary embodiment.

[0028] Figure 3 FIG. 3 is a simulation result schematic diagram of various bandwidth allocation methods provided by an exemplary embodiment.

[0029] Figure 4 FIG. 4 is a structural schematic diagram of a bandwidth allocation device for a sensory calculation control closed loop provided by an exemplary embodiment.

[0030] Figure 5 FIG. 5 is an architectural schematic diagram of a communication system provided by an exemplary embodiment.

[0031] Figure 6 FIG. 6 is a structural schematic diagram of an unmanned aerial vehicle provided by an exemplary embodiment. DETAILED DESCRIPTION

[0032] The exemplary embodiments will be described in detail herein with reference to the accompanying drawings. The following description, with reference to the accompanying drawings, relates to specific embodiments so as to fully enable those skilled in the art to make and use the present specification. However, claims are not limited to the specific embodiments described herein, but include all embodiments that would normally occur to those skilled in the art. The present specification can have other various modifications, and can have various embodiments. Specific embodiments are provided in the drawings and detailed description to fully convey the scope of the present specification to those skilled in the art.

[0033] In the embodiments of the present disclosure, an SC 3 A schematic diagram of a closed-loop network architecture is shown, for example Figure 1 The same target (i.e. the object to be perceived) can be perceived by multiple sensors, and the sensor data is transmitted to the UAV. The UAV is equipped with a user communication module, a satellite communication module and a mobile edge computing (MEC) module, wherein the user communication module is responsible for receiving sensor data and transmitting control instructions to the robot, the MEC module can calculate the control instructions based on the received sensor data, and the satellite communication module can transmit part of the data to the cloud server through the satellite. Among them, the robot, the target, the sensor, the UAV, the satellite and the cloud server form an SC 3 closed loop.

[0034] In the cooperative perception scenario, multiple sensors transmit sensor data in parallel, competing for limited bandwidth resources. There is a correlation between the sensor data obtained by each sensor, and the correlation relationship is complex. It is necessary to reasonably allocate communication bandwidth to minimize the transmission delay of sensor data.

[0035] Researchers have explored various methods to optimize the process of unmanned aerial vehicle-assisted sensor data collection, such as clustering of sensors, unmanned aerial vehicle path planning, and communication resource allocation. Among them, joint perception and data collection, and efficient multiple access are two promising research directions. Currently, research in the field of sensor data processing, fusion and analysis mainly focuses on data itself, and less attention is paid to its integration or coupling with communication. However, in the SC 3 closed loop, the perception, communication, computation and control processes are tightly coupled, and the joint design of perception and communication is necessary for minimizing the transmission delay of sensor data. Considering that there will be differences between different sensors and UAVs, in order to jointly consider perception redundancy and channel conditions, minimize the transmission delay of sensor data while ensuring that the unmanned operation task can be executed correctly, in the embodiments of the present disclosure, the following bandwidth allocation method, device and system for the perception, transmission, computation and control closed loop are provided.

[0036] Figure 2 A flowchart of a bandwidth allocation method for a perception, transmission, computation and control closed loop provided by an exemplary embodiment is shown. As Figure 2 shown, the method comprises the following steps:

[0037] Step S201, determine the channel traversal capacity of each sensor to the UAV.

[0038] In some embodiments, the large-scale fading and the small-scale fading of each sensor to the UAV can be determined first, and then the channel ergodic capacity of each sensor to the UAV can be determined based on the large-scale fading and the small-scale fading of each sensor to the UAV.

[0039] In some embodiments, assuming there are K sensors in total, K can be a positive integer greater than or equal to 2, and the large-scale fading and the small-scale fading of the kth sensor to the UAV can be represented as l k and s k , respectively.

[0040] wherein the large-scale fading l k refers to fading of a signal caused by path loss and shadowing effect during long-distance propagation.

[0041] Exemplarily, the large-scale fading l k can be calculated based on Formula 1:

[0042]

[0043] wherein (η LoS , η NLoS , a, b) are constants related to the transmission environment, d k and θ k represent the distance and the elevation angle between the kth sensor and the UAV, respectively, c is the speed of light, and f is the carrier frequency.

[0044] wherein the small-scale fading s k refers to rapid fluctuation of a signal caused by multipath effect and frequency-selective fading in a short time.

[0045] Exemplarily, the small-scale fading s k obeys a standard complex Gaussian distribution (i.e., Rayleigh fading) that is independent and identically distributed.

[0046] wherein the channel ergodic capacity of the kth sensor to the UAV can be R k , and R k can be calculated based on Formula 2 according to the characteristic that |s k | obeys Rayleigh distribution:

[0047]

[0048] wherein p k is the transmission power of the kth sensor, the system noise is additive white Gaussian noise with variance σ 2 , and h k is equal to the product of the large-scale fading l k and the small-scale fading s k . Wherein, For x > 0, denotes the exponential integral.

[0049] In step S202, based on the channel traversal capacity corresponding to each sensor, the data amount obtained by each sensor, and the first data amount, a data distribution weight corresponding to each sensor is determined.

[0050] In some embodiments, in order to facilitate the calculation of the data distribution weight corresponding to each sensor, after the channel traversal capacity R k Then, the each sensor is renumbered from small to large in the order of the channel traversal capacity from large to small.

[0051] After renumbering, R k Satisfies: R1≥R2≥…≥R K .

[0052] For example, the total number of sensors is 3, and the channel traversal capacities corresponding to sensor #1, sensor #2, and sensor #3 are R1, R2, and R3, respectively, where R3 is the largest and R2 is the smallest. After renumbering the each sensor from small to large in the order of the channel traversal capacity from large to small, the original sensor #3 is numbered 1, the original sensor #1 is numbered 2, and the original sensor #2 is numbered 3. After renumbering, the new sensor #1 corresponds to the largest R1, and the new sensor #3 corresponds to the smallest R3.

[0053] In some embodiments, among the renumbered sensors, the smallest numbered m sensors can be determined. Wherein, the m is less than or equal to the total number of sensors.

[0054] It can be understood that the purpose of selecting the smallest numbered m sensors is to enable sensors with larger channel traversal capacities to transmit as much data as possible to the UAV, and to enable sensors with poor channel traversal capacities to transmit as little data as possible, or even not to transmit data.

[0055] In one example, the data amount obtained by the m sensors is greater than or equal to the first data amount D.

[0056] In one example, the value of m is a constant value, i.e., a constant value that enables the sum of the data amounts transmitted by the smallest numbered m sensors to be equal to the first data amount.

[0057] Wherein, if the total data amount obtained by all sensors is equal to the first data amount, at this time m is equal to the total number of sensors.

[0058] The first data amount D can be a minimum data amount for the UAV to determine a correct control instruction. The control instruction can be used to control the robot to perform a corresponding operation. That is, all sensors do not need to transmit the data amount to be transmitted to the UAV, and the UAV only needs to obtain the first data amount of data to determine the correct control instruction.

[0059] The total data amount obtained by all sensors should be greater than or equal to the first data amount, otherwise the system cannot work normally.

[0060] In some embodiments, the optimization problem can be expressed as:

[0061]

[0062] The K sensors use frequency division multiple access to avoid interference, the total bandwidth is B, and the bandwidth allocated to the kth sensor is B k . The time delay of the kth sensor for transmitting sensor data is T k , and the channel traversal capacity to the UAV is R k .

[0063] To obtain the optimal solution of (P1), first solve the optimal sensor data allocation vector q∈real number set The kth element of q k may refer to the data allocation weight corresponding to the kth sensor, wherein the vector composed of the data allocation weights corresponding to all sensors is the sensor data allocation vector q. The expression of q k is shown in formula 3:

[0064]

[0065] The data amount to be transmitted by the kth sensor is D k .

[0066] Where m satisfies and

[0067] The first type of sensor after renumbering has a number less than m, and the corresponding data allocation weight is determined based on the ratio of the data amount D k to be transmitted by itself to the first data amount D.

[0068] The second type of sensor after renumbering has a number of m, and the corresponding data allocation weight is the difference between 1 and the first sum, wherein the first sum is the sum of the data allocation weights corresponding to all first type sensors.

[0069] The third type of sensor has a number greater than m and less than or equal to the total number of sensors K after renumbering, and the corresponding data allocation weight is 0, that is, the third type of sensor can not transmit data to the unmanned aerial vehicle because the channel traversal capacity is small.

[0070] In step S203, the bandwidth allocated to each sensor is determined based on the channel traversal capacity of each sensor to the unmanned aerial vehicle, the data allocation weight corresponding to each sensor, and the total bandwidth.

[0071] In some embodiments, the data allocation weight q k corresponding to each sensor can be used to determine the first value corresponding to each sensor, that is, the first value = q k / R k . k .

[0072] Further, the sum of the first values corresponding to each sensor can be calculated, that is, the second sum value.

[0073] Further, the second value corresponding to each sensor can be determined based on the ratio of the first value corresponding to each sensor to the second sum value, that is,

[0074] Further, the bandwidth allocated to each sensor B k can be determined based on the product of the second value and the total bandwidth, for example, as shown in formula 4.

[0075]

[0076] The kth sensor can transmit data D k based on the allocated bandwidth B k , which is the optimal strategy of (P1). This strategy can ensure that the upload delay of sensor data is minimized under the condition that the unmanned aerial vehicle correctly calculates the control command. Further, the unmanned aerial vehicle can control the robot to perform the corresponding operation according to the correct control command determined.

[0077] In the above embodiments, the correlation between the sensor data obtained by different sensors is simplified, and it is assumed that the amount of data required by the unmanned aerial vehicle only needs to exceed a threshold value to obtain a correct control command. By transforming the original problem, an optimal sensor data allocation vector is obtained, and an optimal sensor bandwidth allocation scheme is obtained using the mapping relationship. This scheme can effectively reduce the upload delay of sensor data while ensuring that the unmanned operation task can be correctly executed, compared with the two schemes of equal allocation and proportional allocation with the amount of sensor data. At the same time, the complexity of this scheme is not high, and it can be efficiently solved.

[0078] The above process is further illustrated as follows.

[0079] Suppose the multi-sensor cooperative perception SC Figure 1 is shown in the following figure. 3 The closed-loop network contains K sensors (numbered 1, 2, …, K), and the amount of sensor data of the kth sensor is D k . To simplify the correlation between sensor data, we assume that the UAV only needs to obtain sensor data with an amount of D to correctly calculate the control command (which requires ). At the same time, it is assumed that the UAV is stationary during the transmission of sensor data.

[0080] The large-scale and small-scale fading of the kth sensor to the UAV are l k and s k , respectively. The expression of l k is shown in Equation 1:

[0081]

[0082] where (η LoS , η NLoS , a, b) are constants related to the transmission environment, d k and θ k represent the distance and elevation angle between the kth sensor and the UAV, respectively, c is the speed of light, and f is the carrier frequency.

[0083] s k obeys a standard complex Gaussian distribution (i.e., Rayleigh fading) independently and identically. The transmission power of the kth sensor is p k , and the system noise is an additive white Gaussian noise with a variance of σ 2 .

[0084] The K sensors use frequency division multiple access to avoid interference, and the total bandwidth is B. Let B k denote the bandwidth allocated to the lth sensor. Let T k denote the time delay of the kth sensor in transmitting sensor data, and R k denote the traversal capacity of the channel to the UAV.

[0085] In the embodiments of the present disclosure, the bandwidth allocation method is as follows:

[0086] First, according to the characteristic that |s k | obeys Rayleigh distribution, the traversal capacity R k of the channel from the kth sensor to the UAV is calculated as follows:

[0087]

[0088] where For x>0, it represents the exponential integral.

[0089] Arrange the K sensors according to R k Relabel in descending order, and the R after the label. k Satisfying: R1≥R2≥…≥R K .

[0090] The optimization issues are as follows:

[0091]

[0092] To obtain the optimal solution for (P1), we first need to find the optimal sensor data allocation vector. Its k-th element q k The expression is shown in Formula 3:

[0093]

[0094] Where m satisfies and

[0095] For the k-th sensor, the optimal allocated bandwidth B k The expression is shown in Formula 4:

[0096]

[0097] The bandwidth allocation method described above can effectively reduce the transmission latency of sensor data compared to two other schemes: equal allocation (i.e., each sensor is allocated the same bandwidth) and allocation proportional to the amount of sensor data (i.e., the more data a sensor acquires, the larger the allocated bandwidth). Furthermore, this scheme has low complexity and can be solved efficiently.

[0098] This solution is applied in, for example Figure 1 The multi-sensor collaborative sensing SC shown 3 In the closed-loop network, the system's carrier frequency is 2000 MHz. Ten sensors are evenly distributed within a circle with a radius of 1000 m, and the UAV is fixed 100 meters above the center of the circle. Each sensor has a transmit power of 20 dBm. The UAV requires a total of 100 Mbits of data, and the sensors acquire a total of 640 Mbits of data. The amount of data that each sensor can acquire is randomly generated and fixed. Assume that the sensors follow R... k After relabeling in descending order, the sensor data volumes for each sensor are 160, 115, 30, 28, 36, 74, 75, 23, 71, and 28 (unit: Mbits). The channel parameters are taken as (η). LoS ,η NLoSa, b) = (0.1, 21, 4.8800, 0.4290), and the noise power is -107 dBm.

[0099] Under the simulation conditions described above, the present example simulates each total bandwidth in the range of 75 kHz to 150 kHz with an interval of 15 kHz, obtains the maximum transmission delay of sensor data under each total bandwidth, and compares the performance of the present scheme with that of the equal allocation and the allocation proportional to the amount of sensor data. The comparison results are shown in FIG. 5, for example. Figure 3 As shown in FIG. 5, the curve marked by the five-pointed star is the simulation result of the bandwidth allocation of the embodiment of the present disclosure, and it can be seen that the present scheme can effectively reduce the transmission delay of sensor data.

[0100] Figure 4 FIG. 1 is a schematic structural diagram of a bandwidth allocation device for a sensor-data-driven algorithm-control closed loop provided by an example embodiment. As shown in FIG. 1, the device can be deployed on a UAV, and includes: Figure 4

[0101] A first determining module 401 is configured to determine the channel traversal capacity of each sensor to the UAV;

[0102] A second determining module 402 is configured to determine a data allocation weight corresponding to each sensor based on the channel traversal capacity corresponding to each sensor, the amount of data obtained by each sensor, and a first amount of data, wherein the first amount of data is the minimum amount of data for the UAV to determine a correct control instruction, and the data allocation weight is used to indicate the ratio of the amount of data transmitted by each sensor to the first amount of data;

[0103] A third determining module 403 is configured to determine the bandwidth allocated to each sensor based on the channel traversal capacity of each sensor to the UAV, the data allocation weight corresponding to each sensor, and the total bandwidth.

[0104] The actions performed by each module have been described in the foregoing embodiments, and will not be described here again.

[0105] Figure 5 FIG. 6 is a schematic architecture diagram of a communication system provided by an example embodiment. As shown in FIG. 6, the system includes: Figure 5

[0106] A UAV 501, on which the aforementioned bandwidth allocation device for a sensor-data-driven algorithm-control closed loop is deployed; wherein the UAV 501 further has a user communication module, a satellite communication module, and an edge computing module deployed thereon;

[0107] A plurality of sensors 502;

[0108] ​​The robot 503; at least one target 504; a satellite 505; a cloud server 506.

[0109] The unmanned aerial vehicle 501, the plurality of sensors 502, the robot 503, the target 504, the satellite 505, and the cloud server 506 form an SC 3 closed loop network.

[0110] The plurality of sensors 502 can perceive the target 504 and obtain perception data, and the plurality of sensors 502 can transmit the data to the unmanned aerial vehicle 501 according to the allocated bandwidth. The unmanned aerial vehicle 501 determines the correct control instruction based on the received data and issues the control instruction to the robot 503. The robot 503 executes the corresponding operation on the target 504 based on the control instruction.

[0111] Of course, the unmanned aerial vehicle 502 can communicate with the cloud server 506 through the satellite 505, including but not limited to writing logs of the closed loop network to the cloud server 506, transmitting part of the data to the cloud server for processing, receiving control instructions from the cloud server 506 to determine the target 504 and transmit the target 504 to the robot 503, etc.

[0112] In the above embodiments, the uploading time delay of the sensor data can be minimized while ensuring that the unmanned operation task is correctly executed, and the availability of the SC 3 closed loop system is effectively improved.

[0113] Figure 6 is a schematic structural diagram of an unmanned aerial vehicle provided by an example embodiment. Please refer to Figure 6 At the hardware level, the unmanned aerial vehicle includes a processor 602, an internal bus 604, a network interface 606, a memory 608, and a non-volatile memory 610, and can also include other hardware required for functions. One or more embodiments of the present specification can be implemented in a software manner, in which the processor 602 reads the corresponding computer program from the non-volatile memory 610 into the memory 608 and then runs. Of course, in addition to the software implementation, one or more embodiments of the present specification do not exclude other implementation manners, such as logic devices or a combination of software and hardware, etc. That is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or a logic device. The vehicle can be deployed with the aforementioned vehicle management and control system.

[0114] Based on the same idea as the above method, the present specification also provides a computer readable storage medium having computer instructions stored thereon, which instructions are executed by a processor to implement the steps of the method according to any one of the above embodiments.

[0115] Based on the same idea as the above method, the specification also provides a computer program product comprising computer programs / instructions which, when executed by a processor, implement the steps of the method according to any of the above embodiments.

[0116] Other embodiments of this specification will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of this specification being indicated by the following claims.

[0117] It should be understood that the specification is not intended to be limited to the exact details that have been described in the foregoing, and that modifications and variations can be made within the purview of the above described principles without departing from the scope of the application. The scope of the application is limited only by the claims that follow.

[0118] The above description is intended to be illustrative and not restrictive. Many other modifications within the scope of the application will be apparent to those of skill in the art upon reviewing the above description. The scope of the application should, therefore, be determined not with reference to the above description, but instead with reference to the appended claims, along with their full scope of equivalents.

Claims

1. A bandwidth allocation method for a sensing-control closed loop, characterized in that, The method is performed by a drone, and the method includes: Determine the channel traversal capacity from each sensor to the UAV; Based on the channel traversal capacity from each sensor to the UAV, the amount of data obtained by each sensor, and the first amount of data, a data allocation weight is determined for each sensor; wherein, the first amount of data is the minimum amount of data required for the UAV to determine the correct control command, and the data allocation weight is used to indicate the ratio of the amount of data transmitted by each sensor to the first amount of data. The bandwidth allocated to each sensor is determined based on the channel traversal capacity from each sensor to the UAV, the data allocation weight corresponding to each sensor, and the total bandwidth. The method further includes: Each sensor is renumbered in ascending order according to the channel traversal capacity, from largest to smallest. Among a plurality of renumbered sensors, determine the m sensors with the smallest numbers; wherein m is less than or equal to the total number of the plurality of sensors; Based on the channel traversal capacity from each sensor to the UAV, the amount of data obtained by each sensor, and the first data amount, the data allocation weight corresponding to each sensor is determined, including at least one of the following: Based on the ratio of the amount of data obtained by each type of sensor to the total amount of data, a data allocation weight is determined for each type of sensor; wherein, the number of the first type of sensor after renumbering is less than m; The difference between the data allocation weight of the second type of sensor and the first sum is determined; wherein, after renumbering, the number of the second type of sensor is m, and the first sum is the sum of the data allocation weights of all the first type of sensors; The data allocation weight corresponding to the third type of sensor is determined to be 0; wherein, after renumbering, the number of the third type of sensor is greater than m.

2. The method according to claim 1, characterized in that, Determining the channel traversal capacity from each sensor to the UAV includes: Determine the large-scale and small-scale fading from each sensor to the UAV; Based on the large-scale and small-scale fading from each sensor to the UAV, the channel traversal capacity from each sensor to the UAV is determined.

3. The method according to claim 1, characterized in that, When the total amount of data obtained by all sensors is equal to the first amount of data, m is equal to the total number of the plurality of sensors.

4. The method according to claim 1, characterized in that, The sum of the data transmitted by the m sensors is equal to the first data amount.

5. The method according to claim 1, characterized in that, Based on the channel traversal capacity from each sensor to the UAV, the data allocation weight corresponding to each sensor, and the total bandwidth, the bandwidth allocated to each sensor is determined, including: Based on the quotient of the data allocation weight corresponding to each sensor and the channel traversal capacity corresponding to each sensor, the first value corresponding to each sensor is determined; Determine a second sum value; wherein the second sum value is the sum of the first values ​​corresponding to each sensor; The second value corresponding to each sensor is determined based on the ratio of the first value corresponding to each sensor to the second sum value. The bandwidth allocated to each sensor is determined based on the product of the second value and the total bandwidth.

6. A bandwidth allocation device for a closed-loop sensing and control system, characterized in that, The device is deployed on a drone, and the device includes: The first determining module is used to determine the channel traversal capacity from each sensor to the UAV; The second determining module is used to determine the data allocation weight corresponding to each sensor based on the channel traversal capacity corresponding to each sensor, the amount of data obtained by each sensor, and the first data amount; wherein, the first data amount is the minimum amount of data for the UAV to determine the correct control command, and the data allocation weight is used to indicate the ratio of the amount of data transmitted by each sensor to the first data amount. The third determining module is used to determine the bandwidth allocated to each sensor based on the channel traversal capacity from each sensor to the UAV, the data allocation weight corresponding to each sensor, and the total bandwidth. The device is also configured to: Each sensor is renumbered in ascending order according to the channel traversal capacity, from largest to smallest. Among a plurality of renumbered sensors, determine the m sensors with the smallest numbers; wherein m is less than or equal to the total number of the plurality of sensors; The second determining module is also configured to be at least one of the following: Based on the ratio of the amount of data obtained by each type of sensor to the total amount of data, a data allocation weight is determined for each type of sensor; wherein, the number of the first type of sensor after renumbering is less than m; The difference between the data allocation weight of the second type of sensor and the first sum is determined; wherein, after renumbering, the number of the second type of sensor is m, and the first sum is the sum of the data allocation weights of all the first type of sensors; The data allocation weight corresponding to the third type of sensor is determined to be 0; wherein, after renumbering, the number of the third type of sensor is greater than m.

7. A communication system, characterized in that, The system includes: The drone is equipped with the bandwidth allocation device for the sensing, transmission, computing and control closed loop as described in claim 6; wherein the drone is also equipped with a user communication module, a satellite communication module and an edge computing module. Multiple sensors; At least one objective; robot; satellite; Cloud server.

8. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by the processor, this instruction implements the steps of the method as described in any one of claims 1-5.

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