Edge information hub empowered non-terrestrial network communication, computing resource deployment method

Abstract

The application provides a non-ground network communication and computing resource deployment method based on edge information hub empowerment, traverses spectrum efficiency based on channel parameter calculation of communication between the edge information hub and the user end; solves an optimization problem with the target of minimizing the total communication bandwidth, the total communication rate and the total computing power resource deployment cost based on the traversed spectrum efficiency, and first obtains the optimal deployment of the total communication bandwidth; based on the optimal deployment of the total communication bandwidth, the optimization problem is converted into a sub-problem with the target of minimizing the total communication rate and the total computing power resource deployment cost and is solved, and then the optimal deployment of the total communication rate and the total computing power resource is obtained. Based on the compromise relationship of the total communication bandwidth, the total communication rate and the total computing power resource deployment of the edge information hub and the resource allocation relationship among users, multi-dimensional resource deployment optimal design is realized to minimize the total cost of communication and computing resources under the premise of meeting the data upload delay requirement, the utilization efficiency of communication and computing resources is improved, and efficient emergency response is realized.

Description

Technical Field

[0001] This application relates to the field of mobile communication technology, and in particular to methods for deploying non-terrestrial network communication and computing resources enabled by edge information hubs. Background Technology

[0002] Various natural and man-made disasters are among the main threats to life and property. To mitigate disaster losses, rapid situational awareness at the disaster site is crucial, requiring low-latency transmission of data collected by sensors in the disaster area back to the emergency command center for rapid emergency response. However, ground communication facilities are often damaged to some extent by disasters. Furthermore, a significant portion of disasters occur in remote areas (such as forest fires and landslides), where ground network coverage is already insufficient. Therefore, it is necessary to utilize satellites, drones, and other facilities to build non-terrestrial networks for data transmission. However, non-terrestrial network facilities are limited by factors such as size and power consumption, limiting their communication capabilities and potentially failing to meet the low-latency requirements of emergency rescue missions.

[0003] Mobile edge computing technology offers an effective solution to this problem. Specifically, sensor-collected data contains a large amount of redundant information. While data upload latency can be reduced by extracting key information and compressing data, sensors themselves are limited by size and power consumption, lacking the computational capabilities to process the data. Therefore, edge information hubs can be deployed at the network edge (such as on drone platforms), integrating communication, computing, and storage modules to achieve intelligent data processing at the edge, thereby reducing overall data upload latency.

[0004] However, the system design of such an edge information hub presents significant technical challenges: on the one hand, there is a complex trade-off between communication and computing resources, making it difficult to find the optimal deployment scheme for communication and computing resources to minimize total resource overhead; on the other hand, during the data upload process, there are complex data flow relationships between the various modules of the edge information hub, and these data flows occur simultaneously at the time level, resulting in a complex mapping relationship between data upload latency and resources, making it difficult to achieve efficient resource utilization while ensuring data upload latency requirements. Summary of the Invention

[0005] In view of this, this application provides a method for deploying non-terrestrial network communication and computing resources empowered by edge information hubs to solve the above-mentioned technical problems.

[0006] In a first aspect of this application, a method for deploying non-terrestrial network communication and computing resources enabled by an edge information hub is provided, wherein the edge information hub enables communication with user terminals and communication with relay devices, and the method includes:

[0007] Based on the channel parameters of the communication between the edge information hub and the user terminal, the traversal spectrum efficiency of the communication between the edge information hub and the user terminal is calculated.

[0008] Based on the traversal spectrum efficiency, an optimization problem is solved with the objective of minimizing the total resource deployment cost of the edge information hub, resulting in the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. The total resources of the edge information hub include the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power resources of the edge information hub. The constraints of the optimization problem include task latency constraints, the relationship between communication bandwidth and communication rate, and the relationship between computing power resource deployment.

[0009] Based on the optimal deployment of the total communication bandwidth, the optimization problem is transformed into a sub-problem aimed at minimizing the total communication rate and the deployment cost of the total computing power resources, and then solved to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources.

[0010] According to one embodiment of this application, calculating the ergodic spectrum efficiency of the communication between the edge information hub and the user terminal based on the channel parameters of the communication between the edge information hub and the user terminal includes:

[0011] For each user terminal, based on the channel parameters of the communication between the edge information hub and the user terminal, the large-scale channel fading of the communication between the edge information hub and the user terminal is calculated. The channel parameters include the distance between the user terminal and the mobile platform carrying the edge information hub, the pitch angle, the large-scale channel parameters, and the carrier frequency. The mobile platform includes a UAV.

[0012] Multiple small-scale channel fadings are generated, and for each small-scale channel fading, the instantaneous spectral efficiency corresponding to the small-scale channel fading is calculated based on the large-scale channel fading, the small-scale channel fading, and the transmit power of the user terminal.

[0013] The average of all the instantaneous spectral efficiencies is used to obtain the traversal spectral efficiency for communication with the user terminal.

[0014] According to one embodiment of this application, the total resource deployment cost of the edge information hub is a linear weighted sum of the total communication bandwidth, the total communication rate, and the total computing power resources.

[0015] According to one embodiment of this application, for each user terminal, the task latency constraint includes: the ratio of the amount of data that the user terminal needs to upload to the theoretical transmission rate is less than or equal to the set task latency, wherein the theoretical transmission rate is equal to the product of the communication bandwidth allocated to the user terminal and the traversal spectrum efficiency of the communication between the edge information hub and the user terminal;

[0016] The relationship between communication bandwidth and communication rate includes: the theoretical transmission rate is greater than or equal to the communication rate allocated to the user terminal, and less than or equal to the ratio of the communication rate allocated to the user terminal to the first ratio corresponding to the user terminal, wherein the first ratio is the ratio of the amount of data that the user terminal needs to upload after processing by the edge information hub to the original amount of data.

[0017] The computing resource deployment relationship is an equality constraint, wherein the computing resources allocated to the user terminal depend on the theoretical transmission rate, the communication rate allocated to the user terminal, the first proportion corresponding to the user terminal, and the computing density of the data uploaded by the user terminal.

[0018] According to one embodiment of this application, the method further includes:

[0019] For each user terminal, the computational efficiency of the edge information hub for the user terminal's uploaded data is determined based on the computational density of the data uploaded by the user terminal and the corresponding first ratio, wherein the first ratio is the ratio of the amount of data that the user terminal needs to upload after processing by the edge information hub to the original amount of data.

[0020] If the computational efficiency is greater than or equal to a specific threshold, the value of the binary variable corresponding to the user terminal is determined to be 1; otherwise, the value of the binary variable corresponding to the user terminal is determined to be 0. The specific threshold depends on the weight parameter corresponding to the total communication rate and the weight parameter corresponding to the total computing power resources.

[0021] According to one embodiment of this application, solving the sub-problem to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources includes:

[0022] For each user terminal, if the value of the binary variable corresponding to the user terminal is 0, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the amount of data that the user terminal needs to upload to the set task latency, and the optimal computing power resource allocated to the user terminal is determined to be 0.

[0023] If the value of the binary variable corresponding to the user terminal is 1, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the first ratio to the task latency, and the optimal computing power resources allocated to the user terminal are determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the computing density to the task latency.

[0024] Based on the optimal communication rate and optimal computing resources allocated to each user terminal, the optimal deployment of the total communication rate and the optimal deployment of the total computing resources are obtained respectively.

[0025] In a second aspect of this application, an edge information hub-enabled non-terrestrial network communication and computing resource deployment device is provided, wherein the edge information hub enables communication with user terminals and with relay devices, and the device includes:

[0026] The calculation unit is used to calculate the traversal spectrum efficiency of the communication between the edge information hub and the user terminal based on the channel parameters of the communication between the edge information hub and the user terminal.

[0027] The first deployment unit is used to solve an optimization problem based on the traversal spectrum efficiency, with the goal of minimizing the total resource deployment cost of the edge information hub, to obtain the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. The total resources of the edge information hub include the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power resources of the edge information hub. The constraints of the optimization problem include task latency constraints, the relationship between communication bandwidth and communication rate, and the relationship between computing power resource deployment.

[0028] The second deployment unit is used to convert the optimization problem into a sub-problem with the objective of minimizing the total communication rate and the total computing power resource deployment cost based on the optimal deployment of the total communication bandwidth, and solve the sub-problem to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources.

[0029] In a third aspect of this application, an electronic device is provided, including a processor and a memory, the memory storing machine-executable instructions executable by the processor, the processor executing the machine-executable instructions to implement the steps of the method proposed in the above embodiments.

[0030] In a fourth aspect of this application, a machine-readable storage medium is provided, wherein machine-executable instructions are stored therein, and when executed by a processor, the machine-executable instructions implement the steps of the method proposed in the above embodiments.

[0031] In a fifth aspect of this application, a computer program product is provided, including a computer program / instructions that, when executed by a processor, implement the steps of the method proposed in the above embodiments.

[0032] As can be seen from the above technical solutions, the edge information hub realizes communication with the user terminal and communication with the relay equipment respectively. Based on the channel parameters of the communication between the edge information hub and the user terminal, the ergodic spectrum efficiency of the communication between the edge information hub and the user terminal is calculated. First, based on the ergodic spectrum efficiency, an optimization problem is solved with the objective of minimizing the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay equipment, and the total computing power resource deployment cost of the edge information hub, thus obtaining the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. Then, based on the obtained optimal deployment of the total communication bandwidth, the optimization problem is transformed into a sub-problem with the objective of minimizing the total communication rate and the total computing power resource deployment cost, and solved, thus obtaining the optimal deployment of the total communication rate between the edge information hub and the relay equipment, and the optimal deployment of the total computing power resources of the edge information hub. This application, based on the trade-off relationship between the total communication bandwidth, total communication rate, and total computing power resource deployment of the edge information hub, as well as the resource allocation relationship among users, realizes a multi-dimensional optimal resource deployment design that minimizes the total overhead of communication and computing resources while meeting the data upload latency requirements, effectively improving the utilization efficiency of communication and computing resources and achieving efficient emergency response.

[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the non-terrestrial network and its data flow empowered by the edge information hub provided in the embodiments of this application;

[0035] Figure 2 This is a flowchart illustrating the method for deploying non-terrestrial network communication and computing resources empowered by an edge information hub, as provided in an embodiment of this application.

[0036] Figure 3 This is a schematic diagram illustrating the performance comparison results provided in the embodiments of this application;

[0037] Figure 4 This is a schematic diagram of the structure of the non-terrestrial network communication and computing resource deployment device empowered by the edge information hub provided in the embodiments of this application;

[0038] Figure 5 This is a schematic diagram of the hardware structure of an electronic device illustrated in an exemplary embodiment of this application. Detailed Implementation

[0039] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0040] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0041] To enable those skilled in the art to better understand the technical solutions provided in the embodiments of this application, and to make the above-mentioned objectives, features and advantages of the embodiments of this application more apparent and understandable, the technical solutions in the embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0042] Various natural and man-made disasters are among the main threats to life and property. To mitigate disaster losses, rapid situational awareness at the disaster site is crucial, requiring low-latency transmission of data collected by sensors in the disaster area back to the emergency command center for rapid emergency response. However, ground communication facilities are often damaged to some extent by disasters. Furthermore, a significant portion of disasters occur in remote areas (such as forest fires and landslides), where ground network coverage is already insufficient. Therefore, it is necessary to utilize satellites, drones, and other facilities to build non-terrestrial networks for data transmission. However, non-terrestrial network facilities are limited by factors such as size and power consumption, limiting their communication capabilities and potentially failing to meet the low-latency requirements of emergency rescue missions.

[0043] Mobile edge computing technology offers an effective solution to this problem. Specifically, sensor-collected data contains a large amount of redundant information. While data upload latency can be reduced by extracting key information and compressing data, sensors themselves are limited by size and power consumption, lacking the computational capabilities to process the data. Therefore, edge information hubs can be deployed at the network edge (such as on drone platforms), integrating communication, computing, and storage modules to achieve intelligent data processing at the edge, thereby reducing overall data upload latency.

[0044] like Figure 1 As shown, Figure 1 This is a schematic diagram of a non-terrestrial network and its data flow empowered by an edge information hub, provided in an embodiment of this application.

[0045] The off-terrestrial network enabled by the edge information hub includes the edge information hub, at least one user terminal (user terminal 1, 2, ..., U), and relay equipment. The edge information hub can be flexibly deployed on mobile platforms such as drones, and the relay equipment can be, for example,... Figure 1 The satellite shown.

[0046] An edge information hub can include a user communication module, a satellite communication module, a computing module, and a storage module. Sensing data from the user terminal can be uploaded to the edge information hub via communication with the user terminal and temporarily stored there. Some data can be processed in the edge information hub's computing module to reduce redundancy before being uploaded to the satellite via communication with the satellite, and finally transmitted to the cloud by the satellite. Figure 1 (Not shown in the image).

[0047] However, the system design of such an edge information hub presents significant technical challenges: on the one hand, there is a complex trade-off between communication and computing resources, making it difficult to find the optimal deployment scheme for communication and computing resources to minimize total resource overhead; on the other hand, during data upload, there are complex data flow relationships between the various modules of the edge information hub (such as...). Figure 1 As shown on the right), these data streams occur simultaneously in time, resulting in a complex mapping relationship between data upload latency and resources, making it difficult to achieve efficient resource utilization while ensuring data upload latency requirements.

[0048] In view of this, embodiments of this application disclose a method for deploying non-terrestrial network communication and computing resources empowered by edge information hubs, in order to solve the above-mentioned technical problems.

[0049] like Figure 2 As shown, Figure 2 This is a flowchart illustrating the method for deploying non-terrestrial network communication and computing resources empowered by an edge information hub, as provided in an embodiment of this application.

[0050] In the embodiments of this application, the edge information hub possesses communication resources and computing power resources. For example... Figure 1 As shown, the edge information hub may include a user communication module, a satellite communication module, and a computing module. The user communication module enables communication between the edge information hub and the user terminal, and the communication can adopt a frequency division multiple access method. The communication resources include the communication bandwidth deployed to enable communication between the edge information hub and the user terminal. The satellite communication module enables communication between the edge information hub and the satellite. The communication resources also include the communication rate deployed to enable communication between the edge information hub and the satellite. The computing module is used to process the sensing data uploaded by the user terminal to reduce redundant information. The computing resources include the computing resources deployed for the computing module.

[0051] The method for deploying off-terrestrial network communication and computing resources enabled by this edge information hub may include the following steps:

[0052] S201: Calculate the traversal spectrum efficiency of the communication between the edge information hub and the user terminal based on the channel parameters of the communication between the edge information hub and the user terminal.

[0053] For each user terminal, based on the given channel parameters for communication between the edge information hub and the user terminal, the ergodic spectral efficiency of the communication between the edge information hub and the user terminal is calculated. Here, ergodic spectral efficiency is the long-term average transmission rate per unit bandwidth, with units of bits per second per hertz (bps / Hz).

[0054] For example, for the u-th user terminal (denoted as user terminal u), the channel parameters for communication between a given edge information hub and user terminal u may include: the distance d between user terminal u and the mobile platform carrying the edge information hub. u and pitch angle θ u Large-scale channel parameters (η) LoS ,η NLoS (a, b) Carrier frequency f and speed of light c.

[0055] The edge information hub can be mounted on a mobile platform such as a drone, and is equivalent to the distance from the user terminal to the edge information hub. The distance between the user terminal and the edge information hub can be determined by the signal strength of multiple communication communications between the user terminal and the edge information hub, specifically the distance d between the user terminal and the drone. u and pitch angle θ u That is, the strength of each communication signal can determine a certain pitch angle θ. u The circular region below, the overlapping of multiple calculated circular regions can be used to obtain d. u and θ u .

[0056] Among them, the large-scale channel parameters (η) LoS ,η NLoS (a, b) can be read from local memory. Among them, large-scale channel parameters can be used to represent the law that the average power of the received signal decreases with increasing distance over a large range (e.g., hundreds or thousands of meters) of transmission and reception distance. Understandably, in scenarios where parameters such as the UAV platform's flight altitude and the edge information hub's transmission power are known, large-scale channel parameters can be obtained by looking up a table.

[0057] Among them, the carrier frequency f is a known quantity when the user terminal and the UAV communication module are known, and can be directly read and used from the local memory.

[0058] In some embodiments, the ergodic spectrum efficiency of the communication between the edge information hub and the user terminal is calculated based on the channel parameters of the communication between the edge information hub and the user terminal, including:

[0059] S2011: For each user terminal, calculate the large-scale channel fading of the communication between the edge information hub and the user terminal based on the channel parameters of the communication between the edge information hub and the user terminal.

[0060] For user terminal u, based on the given channel parameters of communication between the edge information hub and user terminal u, the large-scale channel fading of communication between the edge information hub and user terminal u is calculated as shown in Equation (1).

[0061]

[0062] In formula (1), l u For large-scale channel fading; a and b are large-scale channel environmental parameters, i.e., the environmental parameters of the town or the village, which are known quantities; η LoS η is the line-of-sight path loss exponent. NLoS θ is the non-line-of-sight path loss exponent; f is the carrier frequency, θ u Let d be the pitch angle. u The distance between the user terminal u and the drone.

[0063] S2012: Generate multiple small-scale channel fadings, and for each small-scale channel fading, calculate the instantaneous spectral efficiency corresponding to the small-scale channel fading based on the large-scale channel fading, the small-scale channel fading, and the transmit power of the user terminal.

[0064] Small-scale channels can be modeled using Rayleigh channels, following a mean of 0 and a variance of . The complex Gaussian distribution of the small-scale channel is used to generate multiple small-scale channel fadings s.

[0065] For each small-scale channel fading, the instantaneous spectral efficiency corresponding to the small-scale channel fading is calculated based on the large-scale channel fading, the small-scale channel fading, and the transmit power of the user terminal, as shown in formula (2).

[0066]

[0067] In formula (2), p represents the instantaneous spectral efficiency corresponding to the u-th small-scale channel fading. u Let u be the transmit power of the user terminal, which is a known parameter; s be the small-scale channel fading; l u For large-scale channel fading; σ 2 Let be the system noise power, and be a known parameter.

[0068] S2013: Average all the obtained instantaneous spectral efficiencies to obtain the ergodic spectral efficiency for communication with the user terminal. As shown in formula (3):

[0069]

[0070] In formula (3), r u E[] represents the ergodic spectrum efficiency of communication between the edge information hub and the user terminal u, and E[] represents the expectation, i.e. the mean, of the random variable within the brackets.

[0071] In the embodiments of this application, the ergodic spectrum efficiency of the communication between the edge information hub and the user terminal is calculated based on the channel parameters of the communication between the edge information hub and the user terminal, thereby providing data support for solving the optimization problem aimed at minimizing the total communication resources of the edge information hub (including the total communication bandwidth of the communication between the edge information hub and the user terminal and the total communication rate of the communication between the edge information hub and the relay device) and the total computing power resource deployment cost.

[0072] S202: Based on the traversal spectrum efficiency, solve the optimization problem with the objective of minimizing the total resource deployment cost of the edge information hub, and obtain the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. The total resources of the edge information hub include the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power resources of the edge information hub. The constraints of the optimization problem include task latency constraints, the relationship between communication bandwidth and communication rate, and the relationship between computing power resource deployment.

[0073] After calculating the ergodic spectrum efficiency of communication between the edge information hub and user terminal u as described in S201, the obtained ergodic spectrum efficiency of communication between the edge information hub and user terminal u is substituted into an optimization problem aimed at minimizing the total communication resources of the edge information hub (including the total communication bandwidth between the edge information hub and user terminal and the total communication rate between the edge information hub and relay devices) and the total computing power resource deployment cost. Under the condition of satisfying the various constraints in the optimization problem, the optimal communication bandwidth of communication between the edge information hub and user terminal u is solved. Then, based on the optimal communication bandwidth of all user terminals, the optimal deployment of the total communication bandwidth of communication between the edge information hub and user terminal is obtained.

[0074] Edge information hubs possess communication and computing resources. Communication resources include the communication bandwidth between the edge information hub and the user terminal; the total deployed communication bandwidth can be represented by B. total This indicates that communication resources include the communication rate of edge information hubs and relay equipment (such as satellites), and the total deployed communication rate can be expressed as... Furthermore, the total computing power resource deployment of the computing modules equipped in the edge information hub can be represented as F. total .

[0075] The optimization problem aims to minimize the deployment cost of the total resources of the edge information hub (including the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power of the edge information hub). The total resource deployment cost of this optimization problem can be represented by a linear weighted function of each resource. That is, the total resource deployment cost of this optimization problem is the linear weighted sum of the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power of the edge information hub, as shown in Equation (4).

[0076]

[0077] In formula (4), C represents the total resource deployment cost of the edge information hub; B total Total communication bandwidth for deployment; For the total communication rate deployed; F total The total computing power resources deployed; α1, α2 and α3 are B respectively. total , and F total The corresponding weight parameters.

[0078] The optimization problem aims to minimize the total resource deployment cost of the edge information hub. The constraints of this optimization problem include task latency constraints, the relationship between communication bandwidth and communication rate, and the relationship between computing resource deployment.

[0079] Among them, the task delay constraint is an inequality constraint. The task delay constraint can be specifically defined as: the ratio of the amount of data that user terminal u needs to upload to the theoretical transmission rate is less than or equal to the set task delay. The theoretical transmission rate is equal to the product of the communication bandwidth allocated to user terminal u and the ergonomic spectrum efficiency of communication between the edge information hub and user terminal u, as shown in formula (5).

[0080]

[0081] In formula (5), T req The set task delay; D u B represents the amount of data that the user client (u) needs to upload. u The communication bandwidth allocated to user terminal u; r u The traversal spectrum efficiency for communication between the edge information hub and the user terminal u is calculated according to the method described in S201. Wherein, B u r uThis represents the theoretical transmission rate of user terminal u under given communication bandwidth and channel conditions. The inequality constraint shown in formula (5) indicates that the data upload of each user terminal should be completed within the set task delay.

[0082] The relationship between communication bandwidth and communication rate is an inequality constraint. Specifically, the relationship between communication bandwidth and communication rate can be defined as follows: the theoretical transmission rate of user terminal u is greater than or equal to the communication rate allocated to user terminal u, and less than or equal to the ratio of the communication rate allocated to user terminal u to the first proportion corresponding to user terminal u. Here, the first proportion is the ratio of the amount of data that user terminal u needs to upload before and after processing by the edge information hub, that is, the ratio of the amount of data that user terminal u needs to upload after processing by the edge information hub to the original amount of data (i.e., the amount of data that user terminal u needs to upload). See formula (6) for details.

[0083]

[0084] In formula (6), B u The communication bandwidth allocated to user terminal u, r u For the traversal spectrum efficiency of communication between the edge information hub and the user terminal u, B u r u This represents the theoretical transmission rate of user terminal u under given communication bandwidth and channel conditions; The communication rate allocated to user terminal u; ζ u The first ratio corresponding to user terminal u is the ratio of the amount of data that user terminal u needs to upload after processing by the edge information hub to the original amount of data. The inequality constraint shown in formula (6) represents the relationship between the communication bandwidth and communication rate allocated to each user terminal in this optimization problem.

[0085] The computational resource deployment relationship is an equality constraint, where the computational resources allocated to user terminal u are jointly determined by the theoretical transmission rate of user terminal u, the communication rate allocated to user terminal u, the first proportion corresponding to user terminal u, and the computational density of the data uploaded by user terminal u. Specifically, as shown in formula (7).

[0086]

[0087] In formula (7), F u The computing resources allocated to user terminal u; B u The communication bandwidth allocated to user terminal u, r u For the traversal spectrum efficiency of communication between the edge information hub and the user terminal u, B u r u This represents the theoretical transmission rate of user terminal u under given communication bandwidth and channel conditions; The communication rate allocated to user terminal u; ζ uρ represents the first ratio corresponding to user u, which is the ratio of the amount of data that user u needs to upload after processing by the edge information hub to the original amount of data; u The computational density of data uploaded by user terminal u is the computing power required for the edge information hub to process a unit of data from user terminal u. The equation constraint shown in formula (7) quantifies the theoretical computing power resources that each user terminal can be allocated under a given communication bandwidth and communication rate.

[0088] Of course, the constraints included in this optimization problem may also include total resource constraints, non-negativity constraints, and scheduling ratio constraints.

[0089] The total resource constraints may include: the sum of communication bandwidth allocated to all user terminals is less than or equal to the total deployed communication bandwidth; the sum of communication rates allocated to all user terminals is less than or equal to the total deployed communication rates; and the sum of computing power resources allocated to all user terminals is less than or equal to the total deployed computing power resources.

[0090] Specifically, as shown in formula (8).

[0091]

[0092] The specific meanings of each parameter in formula (8) have been explained in detail above and will not be repeated here.

[0093] Nonnegativity constraints may include: the total communication bandwidth, total communication rate, and total computing power resources deployed are all greater than or equal to 0, and the communication bandwidth, communication rate, and computing power resources allocated to each user terminal are all greater than or equal to 0. Specifically, as shown in formula (9).

[0094]

[0095] The specific meanings of each parameter in formula (9) have been explained in detail above and will not be repeated here.

[0096] The amount of data that user u needs to upload is D. u It can be divided into direct data upload (ratio η) u ) and edge processing data (ratio 1-η) u It consists of two parts. The scheduling ratio constraint is shown in formula (10).

[0097] 0≤η u ≤1,u=1,...U Formula (10)

[0098] In formula (10), η u The proportion of data directly uploaded by user u to the total amount of data that user u needs to upload. Formula (10) indicates that the proportion of data directly uploaded by user u to the total amount of data that needs to be uploaded is limited to the interval [0,1].

[0099] S203: Based on the optimal deployment of the total communication bandwidth, the optimization problem is transformed into a sub-problem with the objective of minimizing the total communication rate and the deployment cost of the total computing power resources, and the sub-problem is solved to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources.

[0100] By substituting the optimal deployment of the total communication bandwidth between the edge information hub and user terminals, and the optimal communication bandwidth between the edge information hub and each user terminal, into the original optimization problem, one optimization dimension is eliminated. This transforms the optimization problem into a subproblem aimed at minimizing the total communication rate between the edge information hub and relay devices and the total computing power resource deployment cost of the edge information hub, with constraints updated synchronously. Under the condition of satisfying the constraints in the subproblem, the optimal communication rate allocated to user terminal u for the communication process between the edge information hub and relay devices (such as satellites), and the optimal computing power allocated to user terminal u for the computation process of the edge information hub, are solved. Furthermore, based on the optimal communication rate and optimal computing power of all user terminals, the optimal deployment of the total communication rate between the edge information hub and user terminals and the optimal deployment of the total computing power resources of the edge information hub are obtained, respectively.

[0101] In some embodiments, the method further includes:

[0102] S2031: For user terminal u, based on the computational density of the data uploaded by user terminal u and the corresponding first ratio, determine the computational efficiency of the edge information hub for the data uploaded by user terminal u, wherein the first ratio is the ratio of the amount of data to be uploaded by the user terminal after processing by the edge information hub to the original amount of data.

[0103] Specifically, ρ u This represents the computational density of data uploaded by user terminal u, which is the computing power required for the edge information hub to process a unit amount of data from user terminal u. u Let 1-ζ represent the first ratio corresponding to user u, that is, the ratio of the amount of data that the user needs to upload after processing by the edge information hub to the original amount of data. u This represents the percentage reduction in data volume after processing by the edge information hub, for example, ζ. u =0.6 means that the ratio of the amount of data that the user needs to upload after processing by the edge information hub to the original amount of data is 0.6. Assuming that the amount of data that the user needs to upload is 1 unit, then the amount of data that the user needs to upload after processing by the edge information hub is 0.6 units, which is reduced by 0.4 units. The ratio of the processed data to the original data (i.e., the amount of data that the user needs to upload) is 0.6.

[0104] Then the expression The physical meaning of "reduction" is the amount of data per cycle in edge computing, which can then be expressed as... The value serves as the computational efficiency of the edge information hub for data uploaded by the user terminal u.

[0105] S2032: If the computing performance is greater than or equal to a specific threshold, then the value of the binary variable corresponding to the user terminal is determined to be 1; otherwise, the value of the binary variable corresponding to the user terminal is determined to be 0, wherein the specific threshold depends on the weight parameter corresponding to the total communication rate and the weight parameter corresponding to the total computing power resources.

[0106] The specific threshold is determined by the weight parameters corresponding to the total communication rate between the edge information hub and the relay device, as well as the weight parameters corresponding to the total computing power resources of the edge information hub. For example, as shown in formula (4), α2 and α3 are the total communication rates deployed, respectively. And total computing power resources F total The corresponding weighting parameter can be the ratio of α3 to α2 as a specific threshold.

[0107] If the computational efficiency is greater than or equal to a specific threshold, then the value of the binary variable corresponding to user u is determined to be 1; otherwise, the value of the binary variable corresponding to user u is determined to be 0, as shown in formula (11).

[0108]

[0109] In formula (11), I u It is a binary variable, and its value is either 1 or 0; the expression The physical meaning is the reduction in data volume per cycle of edge computing, expressed as: The value represents the computational efficiency of the edge information hub for data uploaded by the user terminal u; the expression The value is a specific threshold.

[0110] In this embodiment, by introducing a binary variable determined by the computing performance of the edge information hub, the computational complexity can be reduced, laying the foundation for the subsequent implementation of a multi-dimensional resource deployment optimal design that minimizes total resource overhead while meeting the latency requirements of data upload tasks.

[0111] In some embodiments, after transforming the optimization problem into a sub-problem aimed at minimizing the total communication rate between the edge information hub and relay devices and the total computing power resource deployment cost of the edge information hub, solving the sub-problem yields the optimal deployment of the total communication rate between the edge information hub and relay devices, as well as the optimal deployment of the total computing power resources of the edge information hub. Solving the sub-problem to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources includes:

[0112] S2033: For each user terminal, if the value of the binary variable corresponding to the user terminal is 0, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the amount of data that the user terminal needs to upload to the set task latency, and the optimal computing power resource allocated to the user terminal is determined to be 0.

[0113] If the value of the binary variable corresponding to user terminal u is 0, it indicates that the computational efficiency of the edge information hub in processing user terminal u's data is too low, making it unsuitable for processing the data uploaded by user terminal u at the edge information hub. In this case, no computing resources are allocated to user terminal u, and the optimal communication rate of user terminal u is configured as the ratio of the total amount of data to be uploaded to the set task latency, thereby ensuring that the total communication and computation latency during the data upload process of user terminal u is within the task latency limit.

[0114] S2034: If the value of the binary variable corresponding to the user terminal is 1, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the first ratio to the task latency, and the optimal computing power resources allocated to the user terminal are determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the computing density to the task latency.

[0115] If the value of the binary variable corresponding to user terminal u is 1, it indicates that the edge information hub has high computational efficiency in processing user terminal u's data, which is within an acceptable range. Therefore, some of the data uploaded by user terminal u can be processed at the edge information hub. In this case, multiplying the total amount of data that user terminal u needs to upload by the computational density of the uploaded data and dividing by the set task latency yields the optimal computing power resources allocated to user terminal u. Furthermore, multiplying the total amount of data that user terminal u needs to upload by the first proportion corresponding to user terminal u and dividing by the set task latency yields the optimal communication rate allocated to user terminal u. This ensures that the total latency of communication and computation during user terminal u's data upload process is within the task latency limit.

[0116] S2035: Based on the optimal communication rate and optimal computing resources allocated to each user terminal, obtain the optimal deployment of the total communication rate between the edge information hub and the relay device, as well as the optimal deployment of the total computing resources of the edge information hub.

[0117] The optimal deployment of the total communication rate and the optimal computing resources allocated to all user terminals are summed to obtain the optimal deployment of the total communication rate between the edge information hub and the relay device, as well as the optimal deployment of the total computing resources of the edge information hub.

[0118] In this embodiment, by introducing a binary variable determined by the computing performance of the edge information hub, the computational complexity can be reduced, and the corresponding deployment strategy can be determined based on the value of the binary variable, thereby achieving a multi-dimensional optimal resource deployment design that minimizes the total resource overhead while meeting the latency requirements of data upload tasks.

[0119] In the embodiments of this application, the edge information hub implements communication with the user terminal and communication with the relay device respectively. Based on the channel parameters of the edge information hub's communication with the user terminal, the ergodic spectrum efficiency of the edge information hub's communication with the user terminal is calculated. First, based on the ergodic spectrum efficiency, an optimization problem is solved with the objective of minimizing the total communication bandwidth of the edge information hub's communication with the user terminal, the total communication rate of the edge information hub's communication with the relay device, and the total computing power resource deployment cost of the edge information hub, resulting in the optimal deployment of the total communication bandwidth of the edge information hub's communication with the user terminal. Then, based on the obtained optimal deployment of the total communication bandwidth, the optimization problem is transformed into a sub-problem with the objective of minimizing the total communication rate and the total computing power resource deployment cost of the edge information hub, and solved, resulting in the optimal deployment of the total communication rate of the edge information hub's communication with the relay device, and the optimal deployment of the edge information hub's total computing power resources. Based on the trade-off relationship between the total communication bandwidth, total communication rate, and total computing power resource deployment of the edge information hub, as well as the resource allocation relationship among users, this application achieves a multi-dimensional optimal resource deployment design that minimizes the total overhead of communication and computing resources while meeting the data upload latency requirements, effectively improving the utilization efficiency of communication and computing resources and achieving efficient emergency response.

[0120] In some embodiments, the optimization problem aimed at minimizing the total resource deployment cost of the edge information hub (including the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power of the edge information hub) can be expressed as Equation (12).

[0121]

[0122]

[0123] The specific meanings of each parameter in formula (12) have been explained in detail above and will not be repeated here.

[0124] In the expression shown in formula (12), the first row indicates that the total resource deployment cost of the edge information hub should be minimized. The meanings of the other rows have been explained in detail above and will not be repeated here.

[0125] For the communication between the edge information hub and the user terminal u, calculate the optimal communication bandwidth allocated to the user terminal u, as shown in formula (13).

[0126]

[0127] In formula (13), The optimal communication bandwidth allocated to user terminal u. The specific meanings of other parameters have been explained in detail above and will not be repeated here.

[0128] The optimal deployment of the total communication bandwidth between the edge information hub and the user terminals is obtained by summing the optimal communication bandwidth allocated to all user terminals, as shown in formula (14).

[0129]

[0130] In formula (14), The optimal deployment of total communication bandwidth for communication between the edge information hub and the user terminal is described above. The specific meanings of other parameters have been explained in detail above and will not be repeated here.

[0131] In this embodiment, as well as It can be proven to be the closed-form optimal solution to the optimization problem shown in Equation (12).

[0132] In this embodiment, the optimization problem aimed at minimizing the total resource deployment cost of the edge information hub is treated as a convex optimization problem. This avoids the problem of the optimization problem being difficult to solve due to complex piecewise functions. While ensuring the optimal communication bandwidth allocated to each user terminal and the optimal deployment of the total communication bandwidth are determined, the difficulty of solving the problem is reduced. Alternatively, in the context of emergency rescue scenarios, optimal results can be obtained within a limited time, improving the overall utilization efficiency of multi-dimensional resources, significantly reducing the total latency of sensing data upload, and facilitating timely decision-making by the decision center based on the uploaded data.

[0133] After obtaining the optimal communication bandwidth allocated to user u And the optimal deployment of total communication bandwidth between the edge information hub and the user terminal. Then, by substitution and Eliminating one optimization dimension from the optimization problem shown in Equation (12) transforms it into a subproblem as shown in Equation (15).

[0134]

[0135] The specific meanings of each parameter in formula (15) have been explained in detail above and will not be repeated here.

[0136] In the expression shown in formula (15), the first row indicates that the total communication rate between the edge information hub and satellite communication and the total computing power resource deployment cost of the edge information hub should be minimized. The meanings of the other rows have been explained in detail above and will not be repeated here.

[0137] For each user terminal, introduce a binary variable and calculate its value. For user terminal u, introduce a binary variable I. u And calculate its value, as shown in formula (11). In formula (11), I u For the user terminal u, there is a binary variable whose value is 1 or 0; the expression The physical meaning is the reduction in data volume per cycle of edge computing, expressed as: The value represents the computational efficiency of the edge information hub for data uploaded by the user terminal u; the expression The value is a specific threshold.

[0138] If the computational efficiency is greater than or equal to a certain threshold, i.e. Greater than or equal to Then determine the binary variable I corresponding to user u. u The value is 1; otherwise, i.e. Less than Then determine the binary variable I corresponding to user u. u The value of is 0.

[0139] Subsequently, for communication between the edge information hub and the satellite, the optimal communication rate allocated to the user terminal u can be calculated, denoted as . As shown in formula (16).

[0140]

[0141] Further summing the optimal communication rates allocated to all user terminals u yields the optimal deployment of the total communication rate between the edge information hub and satellite communication, denoted as . As shown in formula (17).

[0142]

[0143] Furthermore, the computation of the edge information hub can calculate the optimal computing resources allocated to user terminal u, denoted as... As shown in formula (18).

[0144]

[0145] Further summing the optimal computing resources allocated to all user terminals u yields the optimal deployment of total computing resources for the edge information hub, denoted as . As shown in formula (19).

[0146]

[0147] In this embodiment, as well as It can be proven to be the closed-form optimal solution to the subproblem shown in Equation (15).

[0148] In this embodiment, based on traversal spectrum efficiency, an optimization problem is solved to minimize the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power resource deployment cost of the edge information hub. This yields the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. Then, based on the optimal deployment of the total communication bandwidth, the optimization problem is transformed into sub-problems to minimize the total communication rate and the total computing power resource deployment cost, and these are solved to obtain the optimal deployment of the total communication rate between the edge information hub and the relay device, as well as the optimal deployment of the total computing power resources of the edge information hub. This application, based on the trade-offs between the total communication bandwidth, total communication rate, and total computing power resource deployment of the edge information hub, and the resource allocation relationship among users, achieves a multi-dimensional optimal resource deployment design that minimizes the total overhead of communication and computing resources while meeting data upload latency requirements. This effectively improves the utilization efficiency of communication and computing resources and enables efficient emergency response. Furthermore, this application, based on the closed-form solution of the optimization problem, can reduce computational complexity.

[0149] In some embodiments, to verify the performance of the edge information hub-enabled non-terrestrial network communication and computing resource deployment method provided in this application, the simulation parameters are set as follows:

[0150] Applications in, for example Figure 1 The non-terrestrial network empowered by the edge information hub shown has 5 terrestrial user terminals; the maximum data volume is considered to be {1, 5, 10, 50, 100} Mbits; the ratio of the data volume of each user terminal to the maximum data volume is randomly selected within the range of [0.1, 1]; the weighting parameters of the total resource deployment cost are [a1, a2, a3] = [1 (MHz)]. -1 3 (Mbits / s) -1 1×10 -3 (Mcycles / s) -1 For each maximum data volume parameter, 50 different system topologies are randomly generated, where the UAV position is [0,0,1000]m, and the user terminal positions are randomly selected within a circle with a height of 0, a center of origin, and a radius of 1000m; for the communication process between the edge information hub and the user terminal, the user terminal transmit power is 1W, the system noise power is -114dBm, and the large-scale channel parameter (η) is... LoS ,η NLoSGiven a, b) = [0.1, 21, 4.880, 0.429], carrier frequency 5.8 GHz, speed of light 3 × 10⁻⁶ 8 m / s, small-scale channel parameters The channel spectral efficiency was obtained by averaging the small-scale channel parameters 1000 times using the Monte Carlo method. For the calculation process of the edge information hub, the calculation density of each user terminal was randomly selected within the range of [1000, 5000] cycles / bit. The first ratio, i.e., the ratio of the amount of data that the user terminal needs to upload before and after processing by the edge information hub, was randomly selected within the range of [0.01, 0.1]. The overall time delay constraint of the task was 100s.

[0151] Under the above simulation conditions, this embodiment simulates the maximum data volume of the user terminal in the range of 1-100 Mbits, obtains the total resource deployment overhead for meeting the task latency requirements under each data volume, and compares the performance of the edge information hub-enabled non-terrestrial network communication and computing resource deployment method provided in this embodiment with existing solutions. The performance comparison results are as follows: Figure 3 As shown, the proposed solution is the non-terrestrial network communication and computing resource deployment method empowered by the edge information hub provided in this application embodiment. Comparative solution 1 is an existing deployment scheme that considers the sequential execution of communication and computing processes, and comparative solution 2 is a deployment scheme that considers the average allocation of resources based on comparative solution 1. It can be seen that the non-terrestrial network communication and computing resource deployment empowered by the edge information hub provided in this application embodiment can effectively reduce the total latency for users to complete data uploads and significantly improve system performance.

[0152] The above description describes the method provided in this application. The following description describes the apparatus provided in this application:

[0153] Please see Figure 4 This is a schematic diagram of the structure of the non-terrestrial network communication and computing resource deployment device that enables the edge information hub provided in this application embodiment.

[0154] like Figure 4 As shown, the device may include:

[0155] The calculation unit 410 is used to calculate the traversal spectrum efficiency of the communication between the edge information hub and the user terminal based on the channel parameters of the communication between the edge information hub and the user terminal.

[0156] The first deployment unit 420 is used to solve an optimization problem based on the traversal spectrum efficiency, with the goal of minimizing the total resource deployment cost of the edge information hub, to obtain the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. The total resources of the edge information hub include the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power resources of the edge information hub. The constraints of the optimization problem include task latency constraints, the relationship between communication bandwidth and communication rate, and the relationship between computing power resource deployment.

[0157] The second deployment unit 430 is used to convert the optimization problem into a sub-problem with the goal of minimizing the total communication rate and the total computing power resource deployment cost based on the optimal deployment of the total communication bandwidth, and solve the sub-problem to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources.

[0158] Optionally, the computing unit 410 is specifically used for:

[0159] For each user terminal, based on the channel parameters of the communication between the edge information hub and the user terminal, the large-scale channel fading of the communication between the edge information hub and the user terminal is calculated. The channel parameters include the distance between the user terminal and the mobile platform carrying the edge information hub, the pitch angle, the large-scale channel parameters, and the carrier frequency. The mobile platform includes a UAV.

[0160] Multiple small-scale channel fadings are generated, and for each small-scale channel fading, the instantaneous spectral efficiency corresponding to the small-scale channel fading is calculated based on the large-scale channel fading, the small-scale channel fading, and the transmit power of the user terminal.

[0161] The average of all the instantaneous spectral efficiencies is used to obtain the traversal spectral efficiency for communication with the user terminal.

[0162] Optionally, the total resource deployment cost of the edge information hub is a linear weighted sum of the total communication bandwidth, the total communication rate, and the total computing power resources.

[0163] Optionally, for each user terminal, the task latency constraint includes: the ratio of the amount of data that the user terminal needs to upload to the theoretical transmission rate is less than or equal to the set task latency, wherein the theoretical transmission rate is equal to the product of the communication bandwidth allocated to the user terminal and the traversal spectrum efficiency of the communication between the edge information hub and the user terminal.

[0164] The relationship between communication bandwidth and communication rate includes: the theoretical transmission rate is greater than or equal to the communication rate allocated to the user terminal, and less than or equal to the ratio of the communication rate allocated to the user terminal to the first ratio corresponding to the user terminal, wherein the first ratio is the ratio of the amount of data that the user terminal needs to upload after processing by the edge information hub to the original amount of data.

[0165] The computing resource deployment relationship is an equality constraint, wherein the computing resources allocated to the user terminal depend on the theoretical transmission rate, the communication rate allocated to the user terminal, the first proportion corresponding to the user terminal, and the computing density of the data uploaded by the user terminal.

[0166] Optionally, the second deployment unit 430 is further configured to:

[0167] For each user terminal, the computational efficiency of the edge information hub for the user terminal's uploaded data is determined based on the computational density of the data uploaded by the user terminal and the corresponding first ratio, wherein the first ratio is the ratio of the amount of data that the user terminal needs to upload after processing by the edge information hub to the original amount of data.

[0168] If the computational efficiency is greater than or equal to a specific threshold, the value of the binary variable corresponding to the user terminal is determined to be 1; otherwise, the value of the binary variable corresponding to the user terminal is determined to be 0. The specific threshold depends on the weight parameter corresponding to the total communication rate and the weight parameter corresponding to the total computing power resources.

[0169] Optionally, the second deployment unit 430 is specifically used for:

[0170] For each user terminal, if the value of the binary variable corresponding to the user terminal is 0, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the amount of data that the user terminal needs to upload to the set task latency, and the optimal computing power resource allocated to the user terminal is determined to be 0.

[0171] If the value of the binary variable corresponding to the user terminal is 1, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the first ratio to the task latency, and the optimal computing power resources allocated to the user terminal are determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the computing density to the task latency.

[0172] Based on the optimal communication rate and optimal computing resources allocated to each user terminal, the optimal deployment of the total communication rate and the optimal deployment of the total computing resources are obtained respectively.

[0173] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0174] This application also provides a hardware structure. See [link to relevant documentation]. Figure 5 , Figure 5 This is a structural diagram of an electronic device provided in an embodiment of this application. Figure 5 As shown, the hardware structure may include: a processor and a machine-readable storage medium, the machine-readable storage medium storing machine-executable instructions that can be executed by the processor; the processor is used to execute the machine-executable instructions to implement the method disclosed in the above example of this application.

[0175] Based on the same application concept as the above method, this application embodiment also provides a machine-readable storage medium storing a plurality of computer instructions, which, when executed by a processor, can implement the method disclosed in the above examples of this application.

[0176] For example, the aforementioned machine-readable storage medium can be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, etc. For instance, machine-readable storage media can be: RAM (Random Access Memory), volatile memory, non-volatile memory, flash memory, storage drives (such as hard disk drives), solid-state drives, any type of storage disk (such as optical discs, DVDs, etc.), or similar storage media, or combinations thereof.

[0177] It should be noted that, in this document, relational terms such as "objective" and "target" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0178] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for deploying non-terrestrial network communication and computing resources empowered by edge information hubs, characterized in that: The edge information hub enables communication with the user terminal and with the relay device, respectively, and the method includes: Based on the channel parameters of the communication between the edge information hub and the user terminal, the traversal spectrum efficiency of the communication between the edge information hub and the user terminal is calculated. Based on the traversal spectrum efficiency, an optimization problem is solved with the objective of minimizing the total resource deployment cost of the edge information hub, resulting in the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. The total resources of the edge information hub include the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power resources of the edge information hub. The constraints of the optimization problem include task latency constraints, the relationship between communication bandwidth and communication rate, and the relationship between computing power resource deployment. Based on the optimal deployment of the total communication bandwidth, the optimization problem is transformed into a sub-problem aimed at minimizing the total communication rate and the deployment cost of the total computing power resources, and then solved to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources. For each user terminal, the task latency constraint includes: the ratio of the amount of data that the user terminal needs to upload to the theoretical transmission rate is less than or equal to the set task latency, wherein the theoretical transmission rate is equal to the product of the communication bandwidth allocated to the user terminal and the traversal spectrum efficiency of the communication between the edge information hub and the user terminal. The relationship between communication bandwidth and communication rate includes: the theoretical transmission rate is greater than or equal to the communication rate allocated to the user terminal, and less than or equal to the ratio of the communication rate allocated to the user terminal to the first ratio corresponding to the user terminal, wherein the first ratio is the ratio of the amount of data that the user terminal needs to upload after processing by the edge information hub to the original amount of data. The computing resource deployment relationship is an equality constraint, wherein the computing resources allocated to the user terminal depend on the theoretical transmission rate, the communication rate allocated to the user terminal, the first proportion corresponding to the user terminal, and the computing density of the data uploaded by the user terminal.

2. The method according to claim 1, characterized in that, The calculation of the ergodic spectrum efficiency of the communication between the edge information hub and the user terminal based on the channel parameters of the communication between the edge information hub and the user terminal includes: For each user terminal, based on the channel parameters of the communication between the edge information hub and the user terminal, the large-scale channel fading of the communication between the edge information hub and the user terminal is calculated. The channel parameters include the distance between the user terminal and the mobile platform carrying the edge information hub, the pitch angle, the large-scale channel parameters, and the carrier frequency. The mobile platform includes a UAV. Multiple small-scale channel fadings are generated, and for each small-scale channel fading, the instantaneous spectral efficiency corresponding to the small-scale channel fading is calculated based on the large-scale channel fading, the small-scale channel fading, and the transmit power of the user terminal. The average of all the instantaneous spectral efficiencies is used to obtain the traversal spectral efficiency for communication with the user terminal.

3. The method according to claim 1, characterized in that, The total resource deployment cost of the edge information hub is a linear weighted sum of the total communication bandwidth, the total communication rate, and the total computing power resources.

4. The method according to claim 1, characterized in that, The method further includes: For each user terminal, the computational efficiency of the edge information hub for the user terminal's uploaded data is determined based on the computational density of the data uploaded by the user terminal and the corresponding first ratio, wherein the first ratio is the ratio of the amount of data that the user terminal needs to upload after processing by the edge information hub to the original amount of data. If the computational efficiency is greater than or equal to a specific threshold, the value of the binary variable corresponding to the user terminal is determined to be 1; otherwise, the value of the binary variable corresponding to the user terminal is determined to be 0. The specific threshold depends on the weight parameter corresponding to the total communication rate and the weight parameter corresponding to the total computing power resources.

5. The method according to claim 4, characterized in that, Solving the sub-problems to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources includes: For each user terminal, if the value of the binary variable corresponding to the user terminal is 0, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the amount of data that the user terminal needs to upload to the set task latency, and the optimal computing power resource allocated to the user terminal is determined to be 0. If the value of the binary variable corresponding to the user terminal is 1, then the optimal communication rate allocated to the user terminal is determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the first ratio to the task latency, and the optimal computing power resources allocated to the user terminal are determined to be the ratio of the product of the amount of data that the user terminal needs to upload and the computing density to the task latency. Based on the optimal communication rate and optimal computing resources allocated to each user terminal, the optimal deployment of the total communication rate and the optimal deployment of the total computing resources are obtained respectively.

6. A non-terrestrial network communication and computing resource deployment device empowered by an edge information hub, characterized in that, The edge information hub enables communication with the user terminal and with the relay equipment, respectively. The device includes: The calculation unit is used to calculate the traversal spectrum efficiency of the communication between the edge information hub and the user terminal based on the channel parameters of the communication between the edge information hub and the user terminal. The first deployment unit is used to solve an optimization problem based on the traversal spectrum efficiency, with the goal of minimizing the total resource deployment cost of the edge information hub, to obtain the optimal deployment of the total communication bandwidth between the edge information hub and the user terminal. The total resources of the edge information hub include the total communication bandwidth between the edge information hub and the user terminal, the total communication rate between the edge information hub and the relay device, and the total computing power resources of the edge information hub. The constraints of the optimization problem include task latency constraints, the relationship between communication bandwidth and communication rate, and the relationship between computing power resource deployment. For each user terminal, the task latency constraint includes: the ratio of the amount of data that the user terminal needs to upload to the theoretical transmission rate is less than or equal to the set task latency, wherein the theoretical transmission rate is equal to the product of the communication bandwidth allocated to the user terminal and the traversal spectrum efficiency of the communication between the edge information hub and the user terminal. The relationship between communication bandwidth and communication rate includes: the theoretical transmission rate is greater than or equal to the communication rate allocated to the user terminal, and less than or equal to the ratio of the communication rate allocated to the user terminal to the first ratio corresponding to the user terminal, wherein the first ratio is the ratio of the amount of data that the user terminal needs to upload after processing by the edge information hub to the original amount of data. The computing power resource deployment relationship is an equality constraint, wherein the computing power resources allocated to the user terminal depend on the theoretical transmission rate, the communication rate allocated to the user terminal, the first proportion corresponding to the user terminal, and the computing density of the data uploaded by the user terminal. The second deployment unit is used to convert the optimization problem into a sub-problem with the objective of minimizing the total communication rate and the total computing power resource deployment cost based on the optimal deployment of the total communication bandwidth, and solve the sub-problem to obtain the optimal deployment of the total communication rate and the optimal deployment of the total computing power resources.

7. An electronic device, characterized in that, It includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, the processor being used to execute the machine-executable instructions to implement the method as described in any one of claims 1-5.

8. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores machine-executable instructions, which, when executed by a processor, implement the method as described in any one of claims 1-5.

9. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-5.

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