Bandwidth allocation method, device and system for sensing calculation control closed loop

Abstract

The invention provides a sensing calculation control closed loop-oriented bandwidth allocation method, device and system. The method comprises the steps of determining a channel traversal capacity from each sensor to an unmanned aerial vehicle; based on the channel traversal capacity corresponding to each sensor, the data volume obtained by each sensor and the first data volume, determining a data allocation weight corresponding to each sensor; wherein the first data volume is the minimum data volume for the unmanned aerial vehicle to determine a correct control instruction, and the data distribution weight is used for indicating the ratio of the data volume allowed to be transmitted by each sensor to the first data volume; and determining the bandwidth allocated to each sensor based on the channel traversal capacity, the data allocation weight and the total bandwidth corresponding to each sensor. According to the method, the transmission delay of the sensor data is minimized under the condition that the correct execution of the unmanned operation task is ensured, and the availability of the sensing calculation control closed-loop system is effectively improved.

Description

Technical Field

[0001] This specification relates to the field of communications, and in particular, to a bandwidth allocation method, apparatus, and system for a sensing-communication-computing-control closed loop. Background Art

[0002] China has a vast territory and complex and diverse communication scenarios. In remote rural areas, disaster-stricken areas, and offshore regions, due to the damage of ground base stations or the difficulty of achieving dense deployment, the ground network is difficult to provide efficient communication services. During emergency rescue operations, it has become a development trend to build an emergency rescue communication network using residual ground base stations, unmanned aerial vehicles (UAVs), and satellites to support machine operations. To improve system performance, the system operates using sensing-communication-computing-control (SC 3 ), abbreviated as the sensing-communication-computing-control closed-loop network architecture. Among them, multiple sensors can sense the same target and transmit sensor data to the UAV. The UAV is equipped with a communication module and a mobile edge computing (MEC) module, which are responsible for receiving and analyzing sensor data, making decisions, and transmitting control instructions to on-site robots to perform controlled operations. SC 3 The closed-loop period is crucial for the correct execution of tasks, which also places higher requirements on the transmission delay of sensor data from the sensor to the UAV.

[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 can minimize the transmission delay of sensor data. Summary of the Invention

[0004] In view of this, this 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 this specification, there is provided a bandwidth allocation method for a sensing-communication-computing-control closed loop, which is executed by a UAV, and the method includes:

[0006] Determine the channel ergodic capacity from each sensor to the UAV;

[0007] Based on the channel ergodic capacity corresponding to each sensor, the amount of data obtained by each sensor, and a first amount of data, determine the data allocation weight corresponding to each sensor; 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;

[0008] Determine the bandwidth allocated to each sensor based on the channel ergodic capacity of each sensor to the UAV, the data allocation weight corresponding to each sensor, and the total bandwidth.

[0009] According to a second aspect of the embodiments of the present specification, a bandwidth allocation device for a sensing, transmitting, computing, and controlling closed loop is provided. The device is deployed on a UAV, and the device includes:

[0010] A first determination module, configured to determine the channel ergodic capacity of each sensor to the UAV;

[0011] A second determination module, configured to determine the data allocation weight corresponding to each sensor based on the channel ergodic 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;

[0012] A third determination module, configured to determine the bandwidth allocated to each sensor based on the channel ergodic capacity of each sensor to the UAV, the data allocation weight corresponding to each sensor, and the total bandwidth.

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

[0014] A UAV, on which the bandwidth allocation device for a sensing, transmitting, computing, and controlling closed loop described in the second aspect is deployed; wherein, a user communication module, a satellite communication module, and an edge computing module are further deployed on the UAV;

[0015] Multiple 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, on which computer instructions are stored, and when the instructions are executed by a processor, the steps of the method described in any item of the first aspect are implemented.

[0021] According to a fifth aspect of the embodiments of the present specification, a computer program product is provided, including computer programs / instructions, and when the computer programs / instructions are executed by a processor, the steps of the method described in any item of the first aspect are implemented.

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

[0023] In the embodiments of the present specification, based on the channel ergodic capacity of each sensor to the unmanned aerial vehicle (UAV), the amount of data obtained by each sensor, and the first data amount, the data allocation weight corresponding to each sensor can be determined. Furthermore, based on the channel ergodic capacity, data allocation weight, and total bandwidth corresponding to each sensor, the bandwidth allocated to each sensor can be determined, minimizing the upload delay of sensor data while ensuring the correct execution of the unmanned operation task, effectively improving the availability of the closed-loop system. 3 The availability of the closed-loop system.

[0024] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and cannot limit this specification. Brief Description of the Drawings

[0025] The drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with this specification, and are used together with the specification to explain the principles of this specification.

[0026] Figure 1 It is a schematic structural diagram of a sensing, transmitting, computing, and controlling closed-loop network provided by an exemplary embodiment.

[0027] Figure 2 It is a schematic flowchart of a bandwidth allocation method for a sensing, transmitting, computing, and controlling closed-loop provided by an exemplary embodiment.

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

[0029] Figure 4 It is a schematic structural diagram of a bandwidth allocation device for a sensing, transmitting, computing, and controlling closed-loop provided by an exemplary embodiment.

[0030] Figure 5 It is a schematic diagram of the architecture of a communication system provided by an exemplary embodiment.

[0031] Figure 6 It is a schematic structural diagram of a UAV provided by an exemplary embodiment. Detailed Embodiments

[0032] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this specification. On the contrary, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0033] In an embodiment of the present disclosure, a SC 3 schematic diagram of a closed-loop network architecture is provided. For example Figure 1 as shown. Among them, multiple sensors can sense the same target (i.e., the object to be sensed) and transmit the sensor data to the unmanned aerial vehicle (UAV). The UAV is equipped with a user communication module, a satellite communication module, and a mobile edge computing (MEC) module. Among them, the user communication module is responsible for receiving the sensor data and transmitting the control instructions to the robot. The MEC module can calculate the control instructions based on the received sensor data. The satellite communication module can transmit some data to the cloud server through the satellite. Among them, a SC 3 closed loop is formed among the robot, the target, the sensors, the UAV, the satellite, and the cloud server.

[0034] In the collaborative sensing scenario, multiple sensors transmit sensor data in parallel and compete for limited bandwidth resources; there is a correlation between the sensor data obtained by each sensor, and the correlation relationship is relatively complex. It is necessary to reasonably allocate the communication bandwidth to minimize the transmission delay of the sensor data.

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

[0036] Figure 2 is a schematic flowchart of a bandwidth allocation method for the sensing, communication, computing, and control closed loop provided by an exemplary embodiment. As Figure 2 shown, the method includes the following steps:

[0037] Step S201, determining the channel ergodic capacity from each sensor to the UAV.

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

[0039] In some embodiments, it is assumed that there are a total of K sensors, where K can be a positive integer greater than or equal to 2. The large-scale fading and small-scale fading of the k-th sensor to the UAV can be represented as l k and s k .

[0040] Among them, the large-scale fading l k refers to the fading caused by path loss and shadow effect during long-distance signal propagation.

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

[0042]

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

[0044] Among them, the small-scale fading s k refers to the rapid fluctuations caused by multipath effect and frequency-selective fading within a short period of time.

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

[0046] Among them, the channel ergodic capacity of the k-th sensor to the UAV can be R k , and based on the characteristic that |s k | obeys the Rayleigh distribution, R k is calculated according to Equation 2:

[0047]

[0048] Among them, p k is the transmission power of the k-th 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 . Among them, For x > 0, it represents the exponential integral.

[0049] Step S202: Determine the data allocation weight corresponding to each sensor based on the channel ergodic capacity corresponding to each sensor, the amount of data obtained by each sensor, and the first data volume.

[0050] In some embodiments, to facilitate calculating the data allocation weight corresponding to each sensor, after determining the channel ergodic capacity R corresponding to each sensor k re-number the sensors from small to large in the order of the channel ergodic capacity from large to small.

[0051] The re-numbered R k satisfies: R1 ≥ R2 ≥ … ≥ R K .

[0052] For example, the total number of sensors is 3. The channel ergodic 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 re-numbering the sensors from small to large in the order of the channel ergodic 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 re-numbering, the new sensor #1 has the largest R1, and the new sensor #3 has the smallest R3.

[0053] In some embodiments, among the re-numbered multiple sensors, determine the m sensors with the smallest numbers. Wherein, the m is less than or equal to the total number of the multiple sensors.

[0054] It can be understood that the purpose of selecting the m sensors with the smallest numbers is to enable the sensors with larger channel ergodic capacities to transmit all their data to be transmitted to the drone as much as possible, and enable the sensors with poorer channel ergodic capacities to transmit less data or even not transmit data.

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

[0056] In an example, the value of m is a fixed value, that is, a fixed value that enables the sum of the data volumes transmitted by the m sensors with the smallest numbers to be equal to the first data volume.

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

[0058] Among them, the first data volume D can be the minimum data volume for the drone to determine the correct control instruction. The control instruction can be used to control the robot to perform corresponding operations. That is, it is not necessary for all sensors to transmit the data volume to be transmitted to the drone. The drone only needs to obtain the data of the first data volume to determine the correct control instruction.

[0059] Among them, the total data volume obtained by all sensors should be greater than or equal to the first data volume, otherwise the system cannot work properly.

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

[0061]

[0062] Among them, K sensors use frequency division multiple access to avoid interference. The total bandwidth is B. Denote the bandwidth allocated to the k-th sensor as B k . Denote the time delay for the k-th sensor to transmit sensor data as T k , and the channel ergodic capacity to the drone is R k .

[0063] To obtain the optimal solution of (P1), first solve the optimal sensor data allocation vector q ∈ the set of real numbers Its k-th element q k can refer to the data allocation weight corresponding to the k-th sensor. Among them, the vector composed of the data allocation weights corresponding to all sensors is the sensor data allocation vector q. Among them, q k The expression of is shown in Formula 3:

[0064]

[0065] Among them, the data volume to be transmitted by the k-th sensor is D k .

[0066] Among them, m satisfies and

[0067] Among them, the number of the first type of sensors after renumbering is less than m, and its corresponding data allocation weight is determined based on the ratio of its own data volume D k occupying the first data volume D.

[0068] Among them, the number of the second type of sensors after renumbering is m, and its corresponding data allocation weight is the difference between 1 and the first sum value, where the first sum value is the sum value of the data allocation weights corresponding to all the first type of sensors.

[0069] Among them, the numbers of the third type of sensors after renumbering are greater than m and less than or equal to the total number K of sensors, and their corresponding data allocation weights are 0. That is, since the channel ergodic capacities of the third type of sensors are small, they may not transmit data to the UAV.

[0070] Step S203: Determine the bandwidth allocated to each sensor based on the channel ergodic capacity of each sensor to the UAV, the data allocation weight corresponding to each sensor, and the total bandwidth.

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

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

[0073] in 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] Furthermore, based on the product of the second value and the total bandwidth, the bandwidth B allocated to each sensor is determined k , as shown in Formula 4 for example.

[0075]

[0076] The k-th sensor can transmit D k data based on the allocated bandwidth B k , which is the optimal strategy of (P1). This strategy can ensure the minimum upload delay of sensor data when the UAV correctly calculates the control instruction. Furthermore, the UAV can control the robot to perform corresponding operations according to the determined correct control instruction.

[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 UAV only needs to exceed the threshold to obtain the correct control instruction. By transforming the original problem, the optimal sensor data allocation vector is obtained, and then the optimal sensor bandwidth allocation scheme is obtained by using the mapping relationship. This scheme can effectively reduce the upload delay of sensor data while ensuring the correct execution of the unmanned operation task compared with the two schemes of equal allocation and proportional allocation to the amount of sensor data. At the same time, the complexity of this scheme is not high and it can be solved efficiently.

[0078] The above process is further illustrated by the following examples.

[0079] Suppose, as Figure 1 shown, the SC of multi-sensor collaborative perception 3 The closed-loop network contains K sensors (numbered 1, 2,..., K), and the amount of sensor data of the k-th sensor is D k . To simplify the correlation between sensor data, we assume that the UAV can correctly calculate the control command by obtaining only the sensor data with an amount of D (this 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 k-th sensor to the UAV are l k and s k , respectively. Among them, the expression of l k is shown in Formula 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 k-th sensor and the UAV, respectively, c is the speed of light, and f is the carrier frequency.

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

[0084] The K sensors use frequency division multiple access to avoid interference. The total bandwidth is B, and the bandwidth allocated to the l-th sensor is denoted as B k . The transmission delay of the sensor data of the k-th sensor is denoted as T k , and the ergodic capacity of the channel to the UAV is R k .

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

[0086] First, calculate the ergodic capacity R k of the channel from the k-th sensor to the UAV according to the characteristic that |s k | obeys the Rayleigh distribution:

[0087]

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

[0089] Relabel the K sensors in descending order according to R k After relabeling, R k satisfies: R1 ≥ R2 ≥ … ≥ R K .

[0090] The optimization problem is as follows:

[0091]

[0092] To obtain the optimal solution of (P1), first solve the optimal sensor data allocation vector whose k-th element q k is expressed as shown in Equation 3:

[0093]

[0094] where m satisfies and

[0095] For the k-th sensor, the optimal allocated bandwidth B k is expressed as shown in Equation 4:

[0096]

[0097] The above bandwidth allocation method of the present disclosure can effectively reduce the transmission delay of sensor data compared with the two schemes of equal allocation (i.e., the same bandwidth is allocated to each sensor) and proportional allocation according to the sensor data volume (i.e., the more data volume the sensor obtains, the larger the allocated bandwidth). At the same time, the complexity of this scheme is not high and it can be solved efficiently.

[0098] This scheme is applied in the SC Figure 1 closed-loop network of multi-sensor collaborative perception as shown in 3 . The carrier frequency of the system is 2000 megahertz (MHz). 10 sensors are evenly distributed within a circle with a radius of 1000 m, and the unmanned aerial vehicle is fixed 100 meters above the center of the circle. The transmission power of each sensor is 20 decibel-milliwatts (dBm). The total data volume required by the unmanned aerial vehicle is 100 megabits (Mbits), and the total data volume obtained by the sensors is 640 Mbits. The data volume obtained by each sensor is randomly generated and fixed. Assume that after relabeling the sensors in descending order according to R k , the sensor data volumes of each sensor are 160, 115, 30, 28, 36, 74, 75, 23, 71, 28 (unit: Mbits). The channel parameters are taken as (η LoS , η NLoS, a, b) = (0.1, 21, 4.8800, 0.4290), and the noise power is -107 dBm.

[0099] Under the above simulation conditions, in this example, the total bandwidth ranges from 75 kHz to 150 kHz, and simulations are carried out point by point at intervals of 15 kHz to obtain the maximum transmission delay of sensor data under each total bandwidth. Then, the performance of this scheme is compared with two other schemes: equal distribution and distribution proportional to the amount of sensor data. The comparison results are as follows Figure 3 shown. The curve marked by the pentagram is the simulation result of the bandwidth allocation of the embodiment of the present disclosure. It can be seen that this scheme can effectively reduce the transmission delay of sensor data.

[0100] Figure 4 is a schematic structural diagram of a bandwidth allocation device for a sensing, transmission, computing, and control closed-loop provided by an exemplary embodiment. For example Figure 4 shown, this device can be deployed on a drone and includes:

[0101] A first determination module 401, configured to determine the channel ergodic capacity of each sensor to the drone;

[0102] A second determination module 402, configured to determine the data allocation weight corresponding to each sensor based on the channel ergodic 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 drone to determine the 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 determination module 403, configured to determine the bandwidth allocated to each sensor based on the channel ergodic capacity of each sensor to the drone, the data allocation weight corresponding to each sensor, and the total bandwidth.

[0104] Wherein, the actions performed by each module have been introduced in the foregoing embodiments and will not be elaborated here.

[0105] Figure 5 is a schematic architecture diagram of a communication system provided by an exemplary embodiment. For example Figure 5 shown, this system includes:

[0106] A drone 501, on which the aforementioned bandwidth allocation device for a sensing, transmission, computing, and control closed-loop is deployed. Wherein, a user communication module, a satellite communication module, and an edge computing module are also deployed on the drone 501;

[0107] Multiple sensors 502;

[0108] Robot 503; at least one target 504; satellite 505; cloud server 506.

[0109] Among them, the drone 501, multiple sensors 502, robot 503, target 504, satellite 505; cloud server 506 constitute an SC 3 Closed-loop network.

[0110] Among them, multiple sensors 502 can sense the target 504 to obtain sensed data. Multiple sensors 502 can transmit data to the drone 501 according to the allocated bandwidth. The drone 501 determines the correct control instruction based on the received data and issues it to the robot 503. The robot 503 performs corresponding operations on the target 504 based on the control instruction.

[0111] Of course, the drone 502 can communicate with the cloud server 506 through the satellite 505, including but not limited to writing the logs of the closed-loop network to the cloud server 506, transmitting some data to the cloud server for processing, receiving the control instruction of the cloud server 506 to determine the target 504 and transmitting it to the robot 503, etc.

[0112] In the above embodiments, the upload delay of sensor data can be minimized while ensuring the correct execution of the unmanned operation task, effectively improving the availability of the SC 3 Closed-loop system.

[0113] Figure 6 It is a schematic structural diagram of a drone provided by an exemplary embodiment. Please refer to Figure 6 , at the hardware level, the drone includes a processor 602, an internal bus 604, a network interface 606, a memory 808, and a non-volatile memory 610. Of course, it may also include other hardware required for other functions. One or more embodiments of this specification can be implemented in a software manner. The processor 602 reads the corresponding computer program from the non-volatile memory 610 into the memory 608 and then runs it. Of course, in addition to the software implementation manner, one or more embodiments of this specification do not exclude other implementation manners, such as logical devices or a combination of software and hardware, etc. That is to say, the execution subject of the following processing flow is not limited to each logical unit, and can also be hardware or logical devices. The foregoing vehicle control system can be deployed on the vehicle.

[0114] Based on the same concept as the above method, this specification also provides a computer-readable storage medium, on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method described in any of the above embodiments are implemented.

[0115] Based on the same concept as the above method, this specification also provides a computer program product, including computer programs / instructions, which when executed by a processor implement the steps of the method described in any of the above embodiments.

[0116] Those skilled in the art will readily conceive of other embodiments of this specification after considering the specification and practicing the invention claimed herein. This specification is intended to cover any variations, uses, or adaptations of this specification, which follow the general principles of this specification and include common general knowledge or conventional technical means in the technical field not claimed in this specification. The specification and examples are only to be considered as exemplary, and the true scope and spirit of this specification are pointed out by the following claims.

[0117] It should be understood that this specification is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of this specification is only limited by the appended claims.

[0118] The above are only the preferred embodiments of this specification, and are not intended to limit this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this specification shall be included within the scope of protection of this specification.

Claims

1. A bandwidth allocation method for a sensation transmission calculation and control closed loop, characterized in that, The method is executed by a drone, and the method includes: Determining the channel ergodic capacity of each sensor to the drone; Based on the channel ergodic capacity of each sensor to the drone, the amount of data obtained by each sensor, and a first amount of data, determining the data allocation weight corresponding to each sensor; wherein, the first amount of data is the minimum amount of data for the drone 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; Based on the channel ergodic capacity of each sensor to the drone, the data allocation weight corresponding to each sensor, and the total bandwidth, determining the bandwidth allocated to each sensor.

2. The method according to claim 1, characterized in that, Determining the channel ergodic capacity of each sensor to the drone includes: Determining the large-scale fading and small-scale fading of each sensor to the drone; Based on the large-scale fading and small-scale fading of each sensor to the drone, determining the channel ergodic capacity of each sensor to the drone.

3. The method according to claim 1, wherein The method further includes: Re-numbering each sensor from small to large in the order of the channel ergodic capacity from large to small; Among the multiple sensors after re-numbering, determining the m sensors with the smallest numbers; wherein, the m is less than or equal to the total number of the multiple sensors.

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

5. The method according to claim 3, characterized in that, The sum of the amounts of data transmitted by the m sensors is equal to the first amount of data.

6. The method according to claim 3, characterized in that Based on the channel ergodic capacity of each sensor to the drone, the amount of data obtained by each sensor, and the first amount of data, determining the data allocation weight corresponding to each sensor includes at least one of the following: Based on the ratio of the amount of data obtained by each first-type sensor to the first amount of data, determining the data allocation weight corresponding to each first-type sensor; wherein, the number of the first-type sensor after re-numbering is less than m; Determining the data allocation weight corresponding to the second-type sensor as the difference between 1 and the first sum value; wherein, the number of the second-type sensor after re-numbering is m, and the first sum value is the sum value of the data allocation weights corresponding to all first-type sensors; Determining the data allocation weight corresponding to the third-type sensor as 0; wherein, the number of the third-type sensor after re-numbering is greater than m.

7. The method according to claim 1, wherein Based on the channel ergodic capacity of each sensor to the drone, the data allocation weight corresponding to each sensor, and the total bandwidth, determining the bandwidth allocated to each sensor includes: Based on the quotient of the data allocation weight corresponding to each sensor and the channel ergodic capacity corresponding to each sensor, determining the first value corresponding to each sensor; Determining the second sum value; wherein, the second sum value is the sum value of the first values corresponding to each sensor; Based on the ratio of the first value corresponding to each sensor to the second sum value, determining the second value corresponding to each sensor; Based on the product of the second value and the total bandwidth, determining the bandwidth allocated to each sensor.

8. A bandwidth allocation device for a closed-loop sensing, transmission, computing, and control system, characterized in that The device is deployed on a drone, and the device includes: The first determination module is configured to determine the channel ergodic capacity of each sensor to the drone; The second determination module is configured to determine the data allocation weight corresponding to each sensor based on the channel ergodic capacity corresponding to each sensor, the data volume obtained by each sensor, and a first data volume, where the first data volume is the minimum data volume for the drone to determine a correct control instruction, and the data allocation weight is used to indicate the ratio of the data volume transmitted by each sensor to the first data volume; The third determination module is configured to determine the bandwidth allocated to each sensor based on the channel ergodic capacity of each sensor to the drone, the data allocation weight corresponding to each sensor, and the total bandwidth.

9. A communication system, characterized in that, The system includes: A drone on which the bandwidth allocation device for the sensing, transmission, computing, and control closed loop according to claim 8 is deployed; wherein, a user communication module, a satellite communication module, and an edge computing module are further deployed on the drone; Multiple sensors; At least one target; A robot; A satellite; A cloud server.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that, When the instruction is executed by a processor, the steps of the method according to any one of claims 1-7 are implemented.

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