Wireless resource allocation method and device, and base station equipment readable storage medium

Abstract

The invention relates to a wireless resource allocation method and device, base station equipment and a computer readable storage medium. The method comprises the following steps: acquiring terminal information and communication service information of each terminal in a target cell configured by base station equipment; the target cell represents a cell used for covering a ground area and a low-altitude area; inputting the terminal information and the communication service information into a pre-trained first allocation model to obtain BWP allocation information of the target cell, and allocating a first BWP to each terminal according to the BWP allocation information; determining a target terminal from the terminals according to the communication quality information of the terminals after the first BWP is allocated; and inputting the communication quality information and the communication service information of the target terminal into a pre-trained second allocation model to obtain BWP adjustment information of the target terminal, and allocating a second BWP to the target terminal according to the BWP adjustment information. By adopting the method, the problem of wireless resource allocation under dual-carrier sharing AAU deployment can be solved, so that the accuracy degree of wireless resource allocation is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a wireless resource allocation method, apparatus, base station equipment, computer-readable storage medium, and computer program product. Background Art

[0002] With the development of communication technology, a low-altitude communication technology has emerged. This technology can use platforms such as drones and balloons flying at low altitudes for data transmission and communication. Low-altitude communication has advantages such as low latency, high flexibility and easy deployment, which can solve communication problems in areas with insufficient coverage of existing communication networks.

[0003] In traditional technology, in order to maintain the stability of low-altitude communications, dual-carrier shared AAU deployment is usually used to implement base station deployment, thereby achieving air and ground coverage of the communication network.

[0004] However, since drone users mainly use uplink services and ground users mainly use downlink services, the service demands of air and ground users are quite different, and the service demands between different low-altitude services and ground services are quite different, there is usually a problem of wireless resource allocation. Therefore, the current low-altitude communication technology deployed through dual-carrier shared AAU cannot accurately allocate wireless resources. Summary of the invention

[0005] Based on this, it is necessary to provide a wireless resource allocation method, apparatus, base station equipment, computer-readable storage medium and computer program product that can improve the accuracy of wireless resource allocation in response to the above technical problems.

[0006] In a first aspect, the present application provides a wireless resource allocation method, which is applied to a base station device, including:

[0007] Acquire terminal information and communication service information of each terminal in a target cell configured by the base station device; the target cell represents a cell used to cover a ground area and a low-altitude area;

[0008] Inputting the terminal information and the communication service information into a pre-trained first allocation model to obtain BWP allocation information of the target cell, and allocating a first BWP to each terminal according to the BWP allocation information;

[0009] determining a target terminal from among the terminals according to the communication quality information of the terminals after the first BWP is allocated;

[0010] The communication quality information and communication service information of the target terminal are input into a pre-trained second allocation model to obtain BWP adjustment information of the target terminal, and a second BWP is allocated to the target terminal according to the BWP adjustment information.

[0011] In one of the embodiments, before inputting the terminal information and communication service information into the pre-trained first allocation model, it also includes: obtaining first sample terminal information and first sample communication service information of the first sample terminal in the sample cell, and obtaining target BWP allocation information for the sample cell; inputting the first sample terminal information and the first sample communication service information into the first allocation model to be trained to obtain the first predicted BWP allocation information of the sample cell; training the first allocation model to be trained according to the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain the pre-trained first allocation model.

[0012] In one of the embodiments, the obtaining of the target BWP allocation information for the sample cell includes: obtaining candidate BWP allocation information of the sample cell; allocating a third BWP to each of the first sample terminals according to the candidate BWP allocation information, and obtaining comprehensive communication quality information corresponding to the candidate BWP allocation information; based on the comprehensive communication quality information corresponding to each of the candidate BWP allocation information, obtaining the target BWP allocation information for the sample cell from each of the candidate BWP allocation information.

[0013] In one embodiment, the training of the first allocation model to be trained based on the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain the pre-trained first allocation model includes: training the first allocation model to be trained based on the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain the first allocation model to be updated; obtaining the second sample terminal information and the second sample communication service information of the second sample terminal in the sample cell, inputting the second sample terminal information and the second sample communication service information into the first allocation model to be updated to obtain the second predicted BWP allocation information of the sample cell; allocating a fourth BWP to each of the second sample terminals according to the second predicted BWP allocation information to obtain the comprehensive communication quality information corresponding to the second predicted BWP allocation information; and updating the first allocation model to be updated using the comprehensive communication quality information corresponding to the second predicted BWP allocation information to obtain the pre-trained first allocation model.

[0014] In one of the embodiments, before inputting the communication quality information and communication service information of the target terminal into the pre-trained second allocation model, it also includes: obtaining the communication service information of a third sample terminal and the first communication quality information of the third sample terminal; inputting the communication service information of the third sample terminal and the first communication quality information into the second allocation model to be trained, and obtaining the BWP adjustment action information of the third sample terminal through the second allocation model; obtaining the second communication quality information of the third sample terminal after performing the BWP adjustment action according to the BWP adjustment action information of the third sample terminal, and obtaining the reward information of the second allocation model based on the first communication quality information and the second communication quality information; and training the second allocation model to be trained using the reward information to obtain the pre-trained second allocation model.

[0015] In one embodiment, the using the reward information to train the second allocation model to be trained to obtain the pre-trained second allocation model includes: using the reward information to train the second allocation model to be trained to obtain the second allocation model to be evaluated; obtaining communication service information of a fourth sample terminal and third communication quality information of the fourth sample terminal; inputting the communication service information of the fourth sample terminal and the third communication quality information of the fourth sample terminal into the second allocation model to be evaluated to obtain the BWP adjustment action of the fourth sample terminal; obtaining the fourth communication quality information of the fourth sample terminal after performing the BWP adjustment action according to the BWP adjustment action information of the fourth sample terminal, and obtaining a model evaluation result of the second allocation model to be evaluated based on the fourth communication quality information; when the model evaluation result meets a preset evaluation condition, using the second allocation model to be evaluated as the pre-trained second allocation model.

[0016] In one of the embodiments, the terminal information includes the terminal type and terminal location of each of the terminals, and the communication service information includes the service priority and service required bandwidth of each of the terminals; obtaining the terminal information and communication service information of each terminal in the target cell includes: obtaining the terminal type, terminal location and communication service type information of each terminal; and obtaining the service priority and service required bandwidth of each terminal based on the communication service type information.

[0017] In a second aspect, the present application further provides a wireless resource allocation device, which is applied to a base station device, including:

[0018] A terminal information acquisition module, used to acquire terminal information and communication service information of each terminal in a target cell configured by the base station device; the target cell represents a cell used to cover a ground area and a low-altitude area;

[0019] A first BWP allocation module, configured to input the terminal information and the communication service information into a pre-trained first allocation model, obtain BWP allocation information of the target cell, and allocate a first BWP to each terminal according to the BWP allocation information;

[0020] A target terminal acquisition module, configured to determine a target terminal from the terminals according to the communication quality information of the terminals after the first BWP is allocated;

[0021] The second BWP allocation module is used to input the communication quality information and communication service information of the target terminal into a pre-trained second allocation model to obtain the BWP adjustment information of the target terminal, and allocate a second BWP to the target terminal according to the BWP adjustment information.

[0022] In a third aspect, the present application further provides a base station device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described in any one of the embodiments of the first aspect when executing the computer program.

[0023] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of the embodiments of the first aspect.

[0024] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method described in any one of the embodiments of the first aspect.

[0025] The above-mentioned wireless resource allocation method, device, base station equipment, computer-readable storage medium and computer program product obtain terminal information and communication service information of each terminal in the target cell configured by the base station equipment; the target cell represents a cell used to cover the ground area and the low-altitude area; the terminal information and communication service information are input into a pre-trained first allocation model to obtain the BWP allocation information of the target cell, and the first BWP is allocated to each terminal according to the BWP allocation information; according to the communication quality information of each terminal after the first BWP is allocated, the target terminal is determined from each terminal; the communication quality information and communication service information of the target terminal are input into a pre-trained second allocation model to obtain the BWP adjustment information of the target terminal, and the second BWP is allocated to the target terminal according to the BWP adjustment information. The present application obtains terminal information and communication service information of each terminal in a target cell configured to cover a ground area and a low-altitude area through a base station device, and then inputs the terminal information and communication service information into a pre-trained first allocation model to obtain BWP allocation information for the target cell, thereby allocating a first BWP to each terminal in the target cell according to the BWP allocation information, and then the target terminal that needs to adjust the BWP allocation again can be determined based on the communication quality information of each terminal after the first BWP is allocated, so that the communication quality information and communication service information of the target terminal are input into a pre-trained second allocation model to obtain the BWP adjustment information of the target terminal, thereby allocating a second BWP to the target terminal. In this way, the allocation of wireless resources BWP is achieved from the target cell as a whole and a single target terminal, and the target cell can cover the ground area and the low-altitude area, solving the problem of wireless resource allocation under dual-carrier shared AAU deployment, thereby improving the accuracy of wireless resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 An application environment diagram of a wireless resource allocation method in an embodiment;

[0028] Figure 2 A schematic diagram of a flow chart of a wireless resource allocation method in an embodiment;

[0029] Figure 3 A schematic diagram of a process for training a first allocation model in one embodiment;

[0030] Figure 4A schematic diagram of a process of updating a first allocation model in one embodiment;

[0031] Figure 5 A schematic diagram of a process for training a second allocation model in one embodiment;

[0032] Figure 6 A schematic diagram of a process for evaluating a second allocation model in one embodiment;

[0033] Figure 7 A schematic diagram of carrier coverage of an air-to-ground coverage base station and a ground coverage base station in one embodiment;

[0034] Figure 8 A schematic diagram of selecting bandwidth resources according to business requirements in one embodiment;

[0035] Fig. 9 A schematic diagram of BWP allocation for an air cell and a ground cell in one embodiment;

[0036] Fig.10 A schematic diagram of a flow chart of a method for dynamic resource allocation of an air-ground integrated base station network in one embodiment;

[0037] Fig.11 is a structural block diagram of a wireless resource allocation device in an embodiment;

[0038] Fig.12 FIG. 4 is an internal structure diagram of a base station device in an embodiment. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0040] The wireless resource allocation method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the base station device 101 communicates with the terminal device 102 in the low-altitude area and the terminal device 103 in the ground area through wireless signals. Specifically, the base station device 101 can obtain the terminal information and communication service information of each terminal in the target cell configured by the base station device, that is, the terminal device 102 in the low-altitude area and the terminal device 103 in the ground area, and then the terminal information and communication service information can be input into the pre-trained first allocation model to obtain the BWP allocation information of the target cell, so as to allocate the first BWP to each terminal, that is, to allocate the first BWP to each terminal device 102 and the terminal device 103. Afterwards, the target terminal can be screened out according to the communication quality information of each terminal after the first BWP is allocated, and then the communication quality information and communication service information of the target terminal are input into the pre-trained second allocation model to obtain the BWP adjustment information for the target terminal, so as to achieve the allocation of the second BWP to the target terminal. The base station device 101 may be an air-to-ground coverage base station, the terminal device 102 may be a communication device such as an unmanned aerial vehicle operating in a cell in a low-altitude area, and the terminal device 103 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices, portable wearable devices, and other devices that communicate in ground areas.

[0041] In one embodiment, Figure 2 As shown, a wireless resource allocation method is provided, which is applied to Figure 1 The base station device 101 in the example is used as an example to illustrate, including the following steps:

[0042] Step S201, obtaining terminal information and communication service information of each terminal in a target cell configured by the base station device 101; the target cell refers to a cell used to cover a ground area and a low-altitude area.

[0043] Among them, the target cell refers to the cell configured by the base station device 101, which may be composed of two parts, a ground cell for covering the ground area, and an air cell for covering the low-altitude area. In this embodiment, the base station device 101 may be an air-to-ground coverage base station, and the base station may be deployed with two carrier signals, namely a first carrier and a second carrier, wherein the first carrier is deployed on the ground, and the second carrier simultaneously realizes ground and air coverage, that is, part of the SSB beam of the second carrier covers the air, and part of the SSB beam covers the ground. The second carrier is configured into multiple different cells, covering the low altitude and the ground respectively. The initial BWP of each cell is staggered in the frequency domain, and the dedicated BWP is dynamically allocated as needed.

[0044] The terminal information refers to the terminal information of each terminal in the target cell configured by the base station device 101, such as the location of each terminal and the current BWP, etc. The communication service information is the information used by each terminal to describe the communication service, such as the service type that can enable the communication service, etc.

[0045] Specifically, after the terminal accesses the target cell configured by the base station device, for example, after accessing the ground cell or the air cell in the air-to-ground coverage base station, its terminal information and communication service information can be sent to the base station device 101, and the base station device 101 can obtain the terminal information and communication service information of each terminal in the target cell in real time.

[0046] Step S202: Input the terminal information and the communication service information into a pre-trained first allocation model to obtain the BWP allocation information of the target cell, and allocate a first BWP to each terminal according to the BWP allocation information.

[0047] The first allocation model is a neural network model used to perform overall BWP configuration for each terminal device in the target cell, and the BWP allocation information of the target cell corresponds to the BWP allocation plan information of the target cell, which may record the first BWP to be allocated to each terminal in the target cell. Specifically, the base station device 101 may input the obtained terminal information and communication service information into the pre-trained first allocation model, and the first allocation model outputs the BWP allocation information of the target cell, thereby allocating the first BWP to each terminal in the target cell according to the BWP allocation information.

[0048] For example, the target cell includes terminal 1, terminal 2 and terminal 3, and the BWP includes BWP1, BWP2 and BWP3 for the ground cell, and also includes BWP4, BWP5 and BWP6 for the air cell. The base station device 101 can input the terminal information and the communication service information into the pre-trained first allocation model to obtain the BWP allocation information of the target cell, which can be terminal 1 allocated to BWP1, terminal 2 allocated to BWP3, and terminal 3 allocated to BWP5. Then, the first BWP can be allocated to each terminal in the target cell according to the above allocation information.

[0049] Step S203: determining a target terminal from among the terminals according to the communication quality information of the terminals after the first BWP is allocated.

[0050] The communication quality information can be used to characterize the communication quality of each terminal in the target cell after the first BWP is allocated, which can be network throughput, user experience, energy efficiency, etc., and the target terminal refers to the terminal device whose BWP needs to be further adjusted. After the first BWP allocation is completed through the first allocation model, since the BWP allocation information is based on the overall allocation information of the target cell, its allocation goal is usually to reduce the overall optimal wireless network quality of the target cell. In this case, there may be a situation where the wireless network communication quality of some terminals is poor. Therefore, the base station device 101 can also further determine the terminal device whose BWP needs to be adjusted as the target terminal based on the communication quality information fed back by each terminal after the first BWP is allocated.

[0051] Step S204: input the communication quality information and communication service information of the target terminal into the pre-trained second allocation model to obtain BWP adjustment information of the target terminal, and allocate a second BWP to the target terminal according to the BWP adjustment information.

[0052] The second allocation model is a neural network model used to configure the BWP of a single terminal device, which is mainly used to optimize the wireless resource configuration of a single terminal device. The BWP adjustment information of the target terminal refers to the adjustment information used to adjust the BWP of the target terminal. Specifically, after determining the target terminal, the base station device 101 can also input the communication quality information and communication service information of the target terminal into the pre-trained second allocation model, and the BWP adjustment information of the target terminal is obtained by the output of the second allocation model, so that the base station device 101 can allocate a second BWP to the target terminal according to the BWP adjustment information.

[0053] In the above-mentioned wireless resource allocation method, the terminal information and communication service information of each terminal in the target cell configured by the base station device 101 are obtained; the target cell represents a cell used to cover the ground area and the low-altitude area; the terminal information and the communication service information are input into a pre-trained first allocation model to obtain the BWP allocation information of the target cell, and the first BWP is allocated to each terminal according to the BWP allocation information; based on the communication quality information of each terminal after the first BWP is allocated, the target terminal is determined from each terminal; the communication quality information and the communication service information of the target terminal are input into a pre-trained second allocation model to obtain the BWP adjustment information of the target terminal, and the second BWP is allocated to the target terminal according to the BWP adjustment information. The present application obtains terminal information and communication service information of each terminal in a target cell configured to cover a ground area and a low-altitude area through a base station device 101, and then inputs the terminal information and communication service information into a pre-trained first allocation model to obtain BWP allocation information for the target cell, thereby allocating a first BWP to each terminal in the target cell according to the BWP allocation information, and then the target terminal that needs to adjust the BWP allocation again can be determined based on the communication quality information of each terminal after the first BWP is allocated, thereby inputting the communication quality information and communication service information of the target terminal into a pre-trained second allocation model to obtain the BWP adjustment information of the target terminal, thereby allocating a second BWP to the target terminal. In this way, the allocation of wireless resources BWP is achieved from the target cell as a whole and from a single target terminal, and the target cell can cover the ground area and the low-altitude area, solving the problem of wireless resource allocation under dual-carrier shared AAU deployment, thereby improving the accuracy of wireless resource allocation.

[0054] In one embodiment, Figure 3 As shown, before step S202, the following may also be included:

[0055] Step S301: obtaining first sample terminal information and first sample communication service information of a first sample terminal in a sample cell, and obtaining target BWP allocation information for the sample cell.

[0056] Among them, the sample cell refers to the cell sample used for training the first allocation model. Similar to the target cell, the sample cell may also include a ground cell for covering the ground area and an air cell for covering the low-altitude area. The first sample terminal refers to the terminal used in the sample cell for training the first allocation model. The terminal may be a terminal within the coverage of the sample cell. The first sample terminal information refers to the terminal information corresponding to the first sample terminal, and the first sample communication service information refers to the communication service information corresponding to the first sample terminal.

[0057] The target BWP allocation information of the sample cell refers to the BWP allocation information with the best overall communication performance of the sample cell. Specifically, the terminal device 101 can also collect the first sample terminal information and the first sample communication service information of the first sample terminal in the sample cell, and at the same time obtain the BWP allocation information with the best overall communication performance of the sample cell as the target BWP allocation information of the sample cell.

[0058] Step S302: input first sample terminal information and first sample communication service information into a first allocation model to be trained to obtain first predicted BWP allocation information of a sample cell.

[0059] The first predicted BWP allocation information is the BWP allocation information for the first sample terminal in the sample cell obtained by the output of the first allocation model. The first allocation model to be trained refers to the first allocation model that needs to complete the training of the neural network model. Specifically, the base station device 101 can input the first sample terminal information and the first sample communication service information into the first allocation model to be trained, thereby outputting the first predicted BWP allocation information of the sample cell through the first allocation model to be trained.

[0060] Step S303: training the first allocation model to be trained according to the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain a pre-trained first allocation model.

[0061] After obtaining the first predicted BWP allocation information, the difference between the first predicted BWP allocation information and the target BWP allocation information can be obtained. For example, a loss function can be set to obtain a loss value between the first predicted BWP allocation information and the target BWP allocation information to represent the difference. The difference can then be used to complete the training of the first allocation model. For example, the model parameters can be continuously optimized through a back propagation algorithm to minimize the loss function to obtain a pre-trained first allocation model.

[0062] In this embodiment, the training of the first allocation model can also be implemented through a deep learning algorithm. By obtaining the first sample terminal information, the first sample communication service information, and the target BWP allocation information of the sample cell of the first sample terminal in the sample cell, the first allocation model can be completed using the above information. The above method can improve the accuracy of the predicted BWP allocation information for the entire cell output by the first allocation model.

[0063] Furthermore, step S201 may further include: obtaining candidate BWP allocation information of the sample cell; allocating a third BWP to each first sample terminal according to the candidate BWP allocation information, and obtaining comprehensive communication quality information corresponding to the candidate BWP allocation information; based on the comprehensive communication quality information corresponding to each candidate BWP allocation information, obtaining target BWP allocation information for the sample cell from each candidate BWP allocation information.

[0064] Among them, the candidate BWP allocation information may refer to a plurality of selectable BWP allocation information of the sample cell, for example, it may be a plurality of BWP allocation information generated by an optimization algorithm, and the comprehensive communication quality information corresponding to the candidate BWP allocation information refers to the overall communication quality information of the sample cell after the third BWP is allocated to the first sample terminal using the candidate BWP allocation information, for example, it may be obtained based on the communication quality information of each first sample terminal after the third BWP is allocated to the first sample terminal.

[0065] Specifically, before obtaining the target BWP allocation information of the sample cell, the base station device 101 can also generate multiple candidate BWP allocation information for the sample cell through an optimization algorithm, and then allocate a third BWP to each first sample terminal according to each candidate BWP allocation information, so as to obtain the communication quality information of each first sample terminal under each candidate BWP allocation information, thereby determining the comprehensive communication quality information corresponding to each candidate BWP allocation information. Then, according to the comprehensive communication quality information corresponding to each candidate BWP allocation information, the candidate BWP allocation information with the best comprehensive communication quality can be screened out as the target BWP allocation information of the sample cell.

[0066] For example, the candidate BWP allocation information includes candidate BWP allocation information 1, candidate BWP allocation information 2, and candidate BWP allocation information 3. The base station device 101 can allocate the third BWP to each first sample terminal in the sample cell according to the candidate BWP allocation information, and obtain the comprehensive communication quality information corresponding to each candidate BWP allocation information, which are comprehensive communication quality information 1, comprehensive communication quality information 2, and comprehensive communication quality information 3. Afterwards, the candidate BWP allocation information representing the best comprehensive communication quality of the sample cell can be screened out based on the comprehensive communication quality information. It can be that the comprehensive communication quality information 2 represents the best comprehensive communication quality, and then the candidate BWP allocation information 2 can be used as the target BWP allocation information of the sample cell.

[0067] In this embodiment, multiple candidate BWP allocation information of the sample cell can also be generated, so that each candidate BWP allocation information can be used to allocate a third BWP to each first sample terminal in the sample cell, thereby obtaining the comprehensive communication quality information corresponding to each candidate BWP allocation information, and screening the target BWP allocation information based on the comprehensive communication quality information corresponding to each candidate BWP allocation information. In this way, it can be ensured that the target BWP allocation information can be the optimal BWP allocation information for the sample cell, thereby ensuring that the first allocation model can output the comprehensive optimal BWP allocation information for the cell.

[0068] In addition, if Figure 4 As shown, step S303 may further include:

[0069] Step S401: training a first allocation model to be trained according to the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain a first allocation model to be updated.

[0070] Among them, the first allocation model to be updated refers to the first allocation model that needs to be further optimized and updated after training is completed. In this embodiment, the base station device 101 completes the preliminary training of the first allocation model using the difference between the first predicted BWP allocation information and the target BWP allocation information, and then the first allocation model to be updated can be obtained.

[0071] Step S402, obtaining second sample terminal information and second sample communication service information of a second sample terminal in the sample cell, inputting the second sample terminal information and the second sample communication service information into the first allocation model to be updated, and obtaining second predicted BWP allocation information of the sample cell.

[0072] The second sample terminal refers to the terminal device used in the sample cell for optimizing and updating the first allocation model, and may be the terminal device used in the actual test process before the first allocation model is put into actual use. The second predicted BWP allocation information is the BWP allocation information for the second sample terminal in the sample cell output by the first allocation model to be updated.

[0073] Specifically, before the first allocation model is put into actual use, an actual network test can be performed on the first allocation model to be updated. At this time, the base station device 101 can collect the terminal information and communication service information of the second sample terminal connected during the test operation as the second sample terminal information and the second sample communication service information. Afterwards, the second sample terminal information and the second sample communication service information can be input into the first allocation model to be updated, thereby obtaining the second predicted BWP allocation information of the sample cell.

[0074] Step S403, allocating a fourth BWP to each second sample terminal according to the second predicted BWP allocation information, and obtaining comprehensive communication quality information corresponding to the second predicted BWP allocation information;

[0075] Step S404: update the first allocation model to be updated using the comprehensive communication quality information corresponding to the second predicted BWP allocation information to obtain a pre-trained first allocation model.

[0076] After obtaining the second predicted BWP allocation information, the base station device 101 can use the second predicted BWP allocation information to allocate the fourth BWP to the second sample terminal, thereby obtaining the communication quality information of each second sample terminal, and then determining the comprehensive communication quality information corresponding to the second predicted BWP allocation information. After that, the comprehensive communication quality information can be used to further optimize and update the first allocation model, thereby obtaining a pre-trained first allocation model for deployment in an actual network.

[0077] In this embodiment, after completing the preliminary training of the first allocation model using the difference between the first predicted BWP allocation information and the target BWP allocation information, the first allocation model can be further updated using the second sample terminal information of the second sample terminal and the second sample communication service information. In this way, the accuracy of the predicted BWP allocation information for the entire cell output by the first allocation model can be further improved.

[0078] In one embodiment, Figure 5 As shown, before step S204, the following may also be included:

[0079] Step S501: Acquire communication service information of a third sample terminal and first communication quality information of the third sample terminal.

[0080] The third sample terminal is a terminal used for training the second allocation model for BWP adjustment of a single terminal. The first communication quality information refers to the original communication quality information of the third sample terminal. After the third sample terminal accesses the base station device 101, the base station device 101 can also obtain the communication service information of the current third sample terminal and the communication quality information of the third sample terminal on the current BWP as the first communication quality information of the third sample terminal.

[0081] Step S502: input the communication service information of the third sample terminal and the first communication quality information into the second allocation model to be trained, and obtain the BWP adjustment action information of the third sample terminal through the second allocation model.

[0082] The second allocation model to be trained refers to the second allocation model that needs to be trained. In this embodiment, after obtaining the communication service information and the first communication quality information of the third sample terminal, the base station device 101 can also input the communication service information and the first communication quality information into the second allocation model to be trained, and the second allocation model outputs the BWP adjustment action information for the third sample terminal.

[0083] Step S503, obtaining the second communication quality information of the third sample terminal after performing the BWP adjustment action according to the BWP adjustment action information of the third sample terminal, and obtaining the reward information of the second allocation model based on the first communication quality information and the second communication quality information;

[0084] Step S504: train the second allocation model to be trained using the reward information to obtain a pre-trained second allocation model.

[0085] The second communication quality information refers to the communication quality information of the third sample terminal after executing the BWP adjustment, and the reward information is the reward information output by the reward function based on the first communication quality information and the second communication quality information. For example, the reward information can be calculated based on the first communication quality information and the second communication quality information by defining a reward function, and then the reward information can be used to train the second allocation model through reinforcement learning to obtain a pre-trained second allocation model.

[0086] In this embodiment, the BWP adjustment action of the third sample terminal is outputted through the second allocation model, so that the BWP of the third sample terminal is adjusted according to the adjustment action, and then the reward information can be obtained according to the first communication quality information before the adjustment and the second communication quality information after the adjustment, so as to train the second allocation model through the reward information. In this way, the second allocation model is trained by reinforcement learning, which can improve the accuracy of the predicted BWP adjustment information for the terminal individual output by the second allocation model.

[0087] Furthermore, if Figure 6 As shown, step S504 may further include:

[0088] Step S601: Use the reward information to train the second allocation model to be trained to obtain a second allocation model to be evaluated.

[0089] The second allocation model to be evaluated refers to the second allocation model that needs to be evaluated. In this embodiment, after the training of the second allocation model is completed, the second allocation model needs to be tested and evaluated. Specifically, after the base station device 101 completes the training of the second allocation model using the reward information, it can also obtain the second allocation model that needs to be evaluated.

[0090] Step S602, obtaining communication service information of a fourth sample terminal and third communication quality information of the fourth sample terminal;

[0091] Step S603: input the communication service information of the fourth sample terminal and the third communication quality information of the fourth sample terminal into the second allocation model to be evaluated to obtain the BWP adjustment action of the fourth sample terminal.

[0092] The fourth sample terminal refers to the sample terminal used to evaluate the second allocation model. In this embodiment, when the base station device 101 performs model evaluation on the second allocation model, it is necessary to first obtain the communication service information of the fourth sample terminal used to evaluate the second allocation model and the current communication quality information of the fourth sample terminal as the third communication quality information of the fourth sample terminal. After that, the communication service information and the third communication quality information of the fourth sample terminal can be input into the second allocation model to be evaluated, so as to obtain the BWP adjustment action for the fourth sample terminal.

[0093] Step S604, obtaining fourth communication quality information of the fourth sample terminal after performing the BWP adjustment action according to the BWP adjustment action information of the fourth sample terminal, and obtaining a model evaluation result of the second allocation model to be evaluated based on the fourth communication quality information;

[0094] Step S605: When the model evaluation result satisfies the preset evaluation condition, the second allocation model to be evaluated is used as the pre-trained second allocation model.

[0095] After the base station device 101 obtains the BWP adjustment action of the fourth sample terminal, it can adjust the BWP where the fourth sample terminal is located according to the action, and obtain the communication quality information of the fourth sample terminal after adjusting the BWP as the fourth communication quality information, and then the fourth communication quality information can be used to evaluate the second allocation model to obtain the model evaluation result of the second allocation model. If the model evaluation result meets the preset evaluation condition, that is, the second allocation model passes the model evaluation, the base station device 101 can deploy the second allocation model to be evaluated as the pre-trained second allocation model.

[0096] In this embodiment, after the base station device 101 completes the training of the second allocation model, it can also use the fourth sample terminal to perform model evaluation on the second allocation model to obtain a model evaluation result of the second allocation model, and only when the model evaluation result meets the preset evaluation conditions, it is used as the pre-trained second allocation model. Through model evaluation, the BWP adjustment effect of the second allocation model for independent terminal devices can be further ensured.

[0097] In one embodiment, the terminal information includes the terminal type and terminal location of each terminal, and the communication service information includes the service priority and service required bandwidth of each terminal; step S201 may further include: obtaining the terminal type, terminal location and communication service type information of each terminal; and obtaining the service priority and service required bandwidth of each terminal according to the communication service type information.

[0098] In this embodiment, the terminal information of each terminal may include two parts: the terminal type of the terminal, such as whether the terminal is a low-altitude user terminal or a ground user terminal, and the current location of the terminal, including the location and altitude of the terminal, etc., and the communication service information may include the time priority of the communication service, such as expedited tasks, urgent tasks, general tasks, and non-urgent tasks, etc., and may also include the required bandwidth of the service executed by the terminal, such as ultra-large bandwidth, large bandwidth, medium bandwidth, small bandwidth, etc.

[0099] Specifically, the base station device 101 can first obtain the terminal type, terminal position, and service type of the communication service performed by each terminal in the target cell as the communication service type of each terminal. After that, it can identify the service priority and service requirement bandwidth of each terminal based on the communication service type information. It can be a pre-constructed correspondence between different service types and service priorities and service requirement bandwidth, so as to identify the service priority and service requirement bandwidth through the above correspondence.

[0100] In this embodiment, the base station device 101 can also identify the terminal type, terminal location and communication service type of each terminal in the target cell, thereby identifying the service priority and service demand bandwidth of each terminal based on the communication service type, which can improve the accuracy of terminal BWP allocation.

[0101] In one embodiment, a method for dynamic resource allocation of an air-ground integrated base station network is also provided. The method can be applied to an air-ground coverage base station, in which the first carrier is deployed on the ground, and the second carrier simultaneously realizes ground and air coverage, that is, part of the SSB beam of the second carrier covers the air, and part of the SSB beam covers the ground. And the second carrier can be configured into multiple different cells, covering low altitude and the ground respectively. The initial BWP of each cell is staggered in the frequency domain, and the dedicated BWP is dynamically allocated as needed. The air and ground cells each contain part of the SSB beam. Figure 7As shown, the first carrier of the air-to-ground coverage base station is on the ground, forming Cell1 f1, and the second carrier is on both air and ground coverage, forming Cell2 f2 and Cell3 f2. For the ground coverage base station, the first carrier and the second carrier are both on the ground, forming Cell1' f1 and Cell2' f2. Specifically, Cell1 f1, Cell1'f1, Cell2 f2, and Cell2' f2 frequencies are mainly used to access large network users, and Cell3 f2 frequencies are mainly used to access drone users. The specific resource allocation method needs to comprehensively consider the user service situation.

[0102] Based on the above networking solution, this embodiment proposes a method for dynamic resource allocation of an air-ground integrated base station network, which comprehensively considers different business needs, business needs of drone users and ground users, and network resource conditions, and realizes joint optimization and allocation of time domain, frequency domain, and air domain resources.

[0103] Drone users mainly provide uplink services, and usually need to transmit large-bandwidth data such as video and point cloud. At other times, when there is no data transmission or only status information is reported, the bandwidth requirement is very small. Therefore, the bandwidth requirements at different times vary greatly. In addition, in the scenario where drones perform emergency rescue services, the network latency requirements are very high, and highly reliable communication guarantees need to be provided. Ground users mainly provide downlink services, and there are also situations where different services have different requirements for the bandwidth latency provided by the network. In addition, the number of ground users and drone users may be distributed differently at different times, and the load on the air carrier and the ground carrier may be sometimes too heavy and sometimes too light, resulting in a waste of resources. Reasonable access is required based on the flight altitude of the drone and the location of the ground user. Therefore, it is necessary to make reasonable joint resource allocation in the time domain, frequency domain, and air domain according to the characteristics of the service to ensure the communication performance of different users and improve resource utilization.

[0104] In NR, the channel bandwidth span is very large. If drone UEs performing different tasks always work at full bandwidth, it will waste base station resources. Different UEs can be configured with different BWPs, and the bandwidth resources used by different drone UEs can be dynamically selected according to business needs. Figure 8As shown, for example: in the T0 period, the UE service load is large and is not sensitive to delay requirements (such as drone power line inspection services and agricultural and forestry plant protection related video backhaul services), and the system configures a large bandwidth BWP1 for the UE (BW is 40MHz, SCS is 15kHz); in the T1 period, due to the small service load (such as the perception results generated by the drone payload sensor), the system configures a small bandwidth BWP2 for the UE (BW is 10MHz, SCS is 15kHz), which can achieve the purpose of reducing power consumption while meeting basic communication needs; in the T2 period, the UE may have a sudden delay-sensitive service (such as drone emergency rescue related services), or find that the resources in the frequency band where BWP1 is located are scarce, so it switches to the new BWP3 (BW is 20MHz, SCS is 60kHz); in other different periods such as T3 and T4, the UE configures different BWP resources or switches between different BWPs according to real-time service needs.

[0105] Functionally, BWP is divided into two categories, namely initial BWP and dedicated BWP. Initial BWP is mainly used for UE to receive RMSI, OSI to initiate random access, etc. Dedicated BWP is mainly used for data service transmission. Fig. 9 As shown, for the initial BWP, this embodiment can configure different frequencies for the air and ground cells of the second carrier respectively. For the dedicated BWP, when the drone UE in the service cell performs BWP operation, a maximum of 4 BWPs are configured by the high layer. This embodiment comprehensively considers various aspects such as actual business needs and user load, and proposes a dynamic resource allocation method for an air-ground integrated base station network based on deep reinforcement learning to achieve coordinated management of time domain, frequency domain, and air domain resources. Fig.10 shown.

[0106] First, a large number of low-altitude drone users and ground users apply for network access. When network resources are sufficient, low-altitude users are given priority to stay in low-altitude cells, and ground users access the first and second carriers for ground coverage, while considering load balancing based on the number of users or PRB utilization. When low-altitude and ground resources are insufficient, in order to ensure the user experience of low-altitude and ground users, as well as the experience of high-priority services such as high reliability and low latency, a multi-dimensional collaborative resource allocation solution is launched.

[0107] 1. Classification strategy:

[0108] In the early stage of low-altitude network deployment, a fixed resource allocation selection strategy is provided. Users are marked as low-altitude users (user1), ground users (user2), etc.; service time priorities are marked as expedited (p1), urgent (p2), general (p3), non-urgent (p4), etc.; service bandwidth requirements are divided into ultra-large bandwidth (b1), large bandwidth (b2), medium bandwidth (b3), small bandwidth (b4), etc.; user location, altitude, cell load and other information are considered at the same time, and time domain, frequency domain, and air domain resources are allocated to users. Time priority, bandwidth selection, and beam resources are determined according to the service type. Different BWPs are configured for the user's frequency domain resources according to the corresponding bandwidth requirements, and BWP switching is performed when the service changes.

[0109] 2. Intelligent learning:

[0110] Through the initial deployment, the service performance corresponding to different resource allocation schemes, such as throughput, rate and other information, can be collected to form a large number of data sets. By establishing a deep learning prediction model, the global optimal resource allocation scheme is obtained. First, based on Shannon's theorem C=Blog2(1+S / N), considering the scheduling cycle, multi-user, multi-carrier, and multi-beam, by maximizing the channel capacity, the network-level low-altitude users and ground users can achieve the best experience.

[0111] 3. Dynamic update:

[0112] Based on the previous step, after allocating time-frequency-space resources to low-altitude users and ground users, there may be a situation where the allocation scheme is globally optimal, but not optimal for a single user. In the case where resources are not fully scheduled, the remaining resources can be used for further optimization on the basis of the above scheme, and the wireless resource scheme can be further updated. Through the reinforcement learning scheme, a reward and punishment mechanism is set up to continuously explore the resource allocation scheme. Set a single-user objective function, such as user rate. Optimize the remaining time domain, frequency domain, and space domain resources, and continuously update and allocate BWP resources according to specific business priorities. When the allocation scheme is updated, the performance is improved, and rewards are given; otherwise, penalties are imposed. The model is continuously learned, training updates are strengthened, and the overall network experience and single user experience are jointly optimized to obtain the optimal resource allocation scheme.

[0113] For specific implementation methods, please refer to the following example process:

[0114] (1) With the goal of global optimization, the process of using deep learning to allocate mobile network time domain, frequency domain and spatial domain resources is as follows:

[0115] 1. Data preparation:

[0116] Collect historical data of mobile networks, including network topology, user needs, channel status, etc. Preprocess and feature engineer the data as needed to construct input features and labels.

[0117] 2. Model design:

[0118] Design a deep learning model, which can be a convolutional neural network (CNN), recurrent neural network (RNN), or attention mechanism. Determine the structure of the input layer, hidden layer, and output layer, as well as the activation function, loss function, etc.

[0119] 3. Model training:

[0120] The prepared data is input into the deep learning model for training. The model parameters are continuously optimized through the back propagation algorithm to minimize the loss function.

[0121] 4. Resource allocation decisions:

[0122] Use the trained deep learning model to intelligently allocate the time, frequency and space domain resources of the mobile network. Dynamically adjust the resource allocation schemes such as time slots, subcarriers and beams based on the results of the model output.

[0123] 5. Model optimization:

[0124] Continuously collect data in the actual network, and optimize and update the deep learning model based on the feedback information. Online learning algorithms such as incremental learning or transfer learning can be used to adapt to changes in the network environment.

[0125] 6. Performance evaluation:

[0126] The performance of the optimized model is evaluated, including indicators such as network throughput, user experience, and energy efficiency.

[0127] 7. Deployment and real-time tuning:

[0128] The optimized model is deployed to the actual mobile network, and the network status is monitored in real time to perform real-time optimization of resource allocation.

[0129] (2) With the single user experience as the goal, deep reinforcement learning is used to update the time domain, frequency domain, and spatial domain resource allocation of the mobile network. The process can be divided into the following steps:

[0130] 1. Problem definition:

[0131] Determine the goal of resource allocation, such as maximizing user throughput, experience rate, minimizing interference between users, etc. Define the state space, action space, and reward function.

[0132] 2. Status indication:

[0133] The state of the mobile network is represented as a feature vector. The state includes information such as network topology, channel status, user demand, base station status, etc. The state vector can be constructed using historical data.

[0134] 3. Action selection:

[0135] Using deep reinforcement learning algorithms, such as Deep Q-Network (DQN) or policy gradient methods, the best action is selected from the action space. The action can be time domain resource allocation (such as adjusting the transmission time slot), frequency domain resource allocation (such as bandwidth allocation), or spatial domain resource allocation (such as beam selection).

[0136] 4. Reward calculation:

[0137] Define a reward function to reflect the impact of each action on system performance. The reward function can take into account indicators such as network throughput, user experience, and energy efficiency.

[0138] 5. Environmental Interaction:

[0139] In a simulated environment or a real network, we continuously interact with the environment, perform selected actions, and observe the feedback from the environment. We update the parameters of the policy network based on the feedback from the environment.

[0140] 6. Learning and Optimization:

[0141] Use deep reinforcement learning algorithms to learn the optimal strategy to maximize the cumulative reward. Classic reinforcement learning algorithms such as DQN and Deep Deterministic Policy Gradient (DDPG) can be used.

[0142] 7. Model Evaluation:

[0143] The trained model is evaluated, including performance testing on the test dataset and verification of the actual effect in the real network.

[0144] 8. Deployment and optimization:

[0145] The trained model is deployed to the actual mobile network and optimized and adjusted online according to real-time environmental changes.

[0146] Through this embodiment, simultaneous air and ground coverage is achieved through the mobile cellular network, and the same frequency band can be used to achieve two cells covering the ground and low altitude respectively through the adaptive BWP method. In this way, the same base station equipment can be used to achieve air and ground coverage, saving equipment deployment costs. At the same time, through the scheduling of BWP granularity, resources can be fully utilized to improve user experience. In addition, this embodiment can also classify users by priority, allocate time domain resources, BWP, and beam resources to users according to business needs, and use deep learning solutions to predict indicators and allocate resources with the goal of optimizing the global network experience, and use deep reinforcement learning to achieve the goal of optimizing the single user experience. Real-time dynamic update of the resource allocation plan, this method can flexibly and dynamically allocate resources according to business scenario requirements to ensure a balance between the optimal global experience and the optimal single user experience.

[0147] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0148] Based on the same inventive concept, the embodiment of the present application also provides a wireless resource allocation device for implementing the wireless resource allocation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more wireless resource allocation device embodiments provided below can refer to the limitations of the wireless resource allocation method above, and will not be repeated here.

[0149] In one embodiment, Fig.11 As shown, a wireless resource allocation device is provided, which is applied to a base station device, including: a terminal information acquisition module 1101, a first BWP allocation module 1102, a target terminal acquisition module 1103 and a second BWP allocation module 1104, wherein:

[0150] The terminal information acquisition module 1101 is used to acquire the terminal information and communication service information of each terminal in the target cell configured by the base station device; the target cell refers to the cell used to cover the ground area and the low-altitude area;

[0151] The first BWP allocation module 1102 is used to input the terminal information and the communication service information into the pre-trained first allocation model, obtain the BWP allocation information of the target cell, and allocate the first BWP to each terminal according to the BWP allocation information;

[0152] The target terminal acquisition module 1103 is used to determine the target terminal from each terminal according to the communication quality information of each terminal after the first BWP is allocated;

[0153] The second BWP allocation module 1104 is used to input the communication quality information and communication service information of the target terminal into the pre-trained second allocation model, obtain the BWP adjustment information of the target terminal, and allocate the second BWP to the target terminal according to the BWP adjustment information.

[0154] In one embodiment, the wireless resource allocation device also includes: a first model training module, used to obtain first sample terminal information and first sample communication service information of a first sample terminal in a sample cell, and obtain target BWP allocation information for the sample cell; input the first sample terminal information and the first sample communication service information into a first allocation model to be trained to obtain first predicted BWP allocation information of the sample cell; and train the first allocation model to be trained according to the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain a pre-trained first allocation model.

[0155] In one embodiment, the first model training module is further used to obtain candidate BWP allocation information of the sample cell; allocate a third BWP to each first sample terminal according to the candidate BWP allocation information to obtain comprehensive communication quality information corresponding to the candidate BWP allocation information; based on the comprehensive communication quality information corresponding to each candidate BWP allocation information, obtain the target BWP allocation information for the sample cell from each candidate BWP allocation information.

[0156] In one embodiment, the first model training module is further used to train the first allocation model to be trained according to the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain the first allocation model to be updated; obtain the second sample terminal information and the second sample communication service information of the second sample terminal in the sample cell, input the second sample terminal information and the second sample communication service information into the first allocation model to be updated to obtain the second predicted BWP allocation information of the sample cell; allocate the fourth BWP to each second sample terminal according to the second predicted BWP allocation information to obtain the comprehensive communication quality information corresponding to the second predicted BWP allocation information; and update the first allocation model to be updated using the comprehensive communication quality information corresponding to the second predicted BWP allocation information to obtain the pre-trained first allocation model.

[0157] In one embodiment, the wireless resource allocation device also includes: a second model training module, which is used to obtain communication service information of a third sample terminal and first communication quality information of the third sample terminal; input the communication service information and the first communication quality information of the third sample terminal into a second allocation model to be trained, and obtain BWP adjustment action information of the third sample terminal through the second allocation model; obtain the second communication quality information of the third sample terminal after performing a BWP adjustment action according to the BWP adjustment action information of the third sample terminal, and obtain reward information of the second allocation model based on the first communication quality information and the second communication quality information; and train the second allocation model to be trained using the reward information to obtain a pre-trained second allocation model.

[0158] In one embodiment, the second model training module is further used to train the second allocation model to be trained using the reward information to obtain the second allocation model to be evaluated; obtain the communication service information of the fourth sample terminal and the third communication quality information of the fourth sample terminal; input the communication service information of the fourth sample terminal and the third communication quality information of the fourth sample terminal into the second allocation model to be evaluated to obtain the BWP adjustment action of the fourth sample terminal; obtain the fourth communication quality information of the fourth sample terminal after performing the BWP adjustment action according to the BWP adjustment action information of the fourth sample terminal, and obtain the model evaluation result of the second allocation model to be evaluated based on the fourth communication quality information; when the model evaluation result meets the preset evaluation conditions, the second allocation model to be evaluated is used as the pre-trained second allocation model.

[0159] In one embodiment, the terminal information includes the terminal type and terminal location of each terminal, and the communication service information includes the service priority and service required bandwidth of each terminal; the terminal information acquisition module 1101 is further used to obtain the terminal type, terminal location and communication service type information of each terminal; according to the communication service type information, the service priority and service required bandwidth of each terminal are obtained.

[0160] Each module in the above-mentioned wireless resource allocation device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a base station device in the form of hardware, or can be stored in a memory in the base station device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0161] In one embodiment, a base station device is provided. The base station device may be a terminal, and its internal structure diagram may be as follows: Fig.12As shown. The base station device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the base station device is used to provide computing and control capabilities. The memory of the base station device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the base station device is used to exchange information between the processor and an external device. The communication interface of the base station device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (Near Field Communication, NFC) or other technologies. When the computer program is executed by the processor, a wireless resource allocation method is implemented.

[0162] Those skilled in the art will understand that Fig.12 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the base station device to which the scheme of the present application is applied. The specific base station device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0163] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0164] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0165] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0166] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0167] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0168] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0169] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A wireless resource allocation method, characterized in that: Applied to a base station device, the method comprises: Acquire terminal information and communication service information of each terminal in a target cell configured by the base station device; the target cell represents a cell used to cover a ground area and a low-altitude area; Inputting the terminal information and the communication service information into a pre-trained first allocation model to obtain BWP allocation information of the target cell, and allocating a first BWP to each terminal according to the BWP allocation information; determining a target terminal from among the terminals according to the communication quality information of the terminals after the first BWP is allocated; The communication quality information and communication service information of the target terminal are input into a pre-trained second allocation model to obtain BWP adjustment information of the target terminal, and a second BWP is allocated to the target terminal according to the BWP adjustment information.

2. The method according to claim 1, characterized in that Before inputting the terminal information and the communication service information into the pre-trained first allocation model, the method further includes: Acquire first sample terminal information and first sample communication service information of a first sample terminal in a sample cell, and acquire target BWP allocation information for the sample cell; Inputting the first sample terminal information and the first sample communication service information into a first allocation model to be trained to obtain first predicted BWP allocation information of the sample cell; According to the difference between the first predicted BWP allocation information and the target BWP allocation information, the first allocation model to be trained is trained to obtain the pre-trained first allocation model.

3. The method according to claim 2, characterized in that The obtaining of target BWP allocation information for the sample cell includes: Acquire candidate BWP allocation information of the sample cell; Allocate a third BWP to each of the first sample terminals according to the candidate BWP allocation information, and obtain comprehensive communication quality information corresponding to the candidate BWP allocation information; Based on the comprehensive communication quality information corresponding to each of the candidate BWP allocation information, the target BWP allocation information for the sample cell is acquired from each of the candidate BWP allocation information.

4. The method according to claim 2, characterized in that: The step of training the first allocation model to be trained according to the difference between the first predicted BWP allocation information and the target BWP allocation information to obtain the pre-trained first allocation model includes: According to the difference between the first predicted BWP allocation information and the target BWP allocation information, training the first allocation model to be trained to obtain the first allocation model to be updated; Acquire second sample terminal information and second sample communication service information of a second sample terminal in the sample cell, input the second sample terminal information and the second sample communication service information into the first allocation model to be updated, and obtain second predicted BWP allocation information of the sample cell; Allocate a fourth BWP to each of the second sample terminals according to the second predicted BWP allocation information, and obtain comprehensive communication quality information corresponding to the second predicted BWP allocation information; The first allocation model to be updated is updated using the comprehensive communication quality information corresponding to the second predicted BWP allocation information to obtain the pre-trained first allocation model.

5. The method according to claim 1, characterized in that Before inputting the communication quality information and the communication service information of the target terminal into the pre-trained second allocation model, the method further includes: Acquire communication service information of a third sample terminal and first communication quality information of the third sample terminal; Inputting the communication service information of the third sample terminal and the first communication quality information into a second allocation model to be trained, and obtaining the BWP adjustment action information of the third sample terminal through the second allocation model; After performing the BWP adjustment action according to the BWP adjustment action information of the third sample terminal, the second communication quality information of the third sample terminal is obtained, and the reward information of the second allocation model is obtained based on the first communication quality information and the second communication quality information; The second allocation model to be trained is trained using the reward information to obtain the pre-trained second allocation model.

6. The method according to claim 5, characterized in that The step of training the second allocation model to be trained by using the reward information to obtain the pre-trained second allocation model includes: Using the reward information to train the second allocation model to be trained to obtain a second allocation model to be evaluated; Acquire communication service information of a fourth sample terminal and third communication quality information of the fourth sample terminal; Inputting the communication service information of the fourth sample terminal and the third communication quality information of the fourth sample terminal into the second allocation model to be evaluated to obtain the BWP adjustment action of the fourth sample terminal; Acquire fourth communication quality information of the fourth sample terminal after performing the BWP adjustment action according to the BWP adjustment action information of the fourth sample terminal, and obtain a model evaluation result of the second allocation model to be evaluated based on the fourth communication quality information; When the model evaluation result satisfies a preset evaluation condition, the second allocation model to be evaluated is used as the pre-trained second allocation model.

7. The method according to any one of claims 1 to 6, characterized in that: The terminal information includes the terminal type and terminal location of each terminal, and the communication service information includes the service priority and service required bandwidth of each terminal; The acquiring terminal information and communication service information of each terminal in the target cell includes: Acquiring terminal type, terminal location, and communication service type information of each terminal; The service priority and service required bandwidth of each terminal are obtained according to the communication service type information.

8. A wireless resource allocation device, characterized in that: Applied to a base station device, the device comprises: A terminal information acquisition module, used to acquire terminal information and communication service information of each terminal in a target cell configured by the base station device; the target cell represents a cell used to cover a ground area and a low-altitude area; A first BWP allocation module, configured to input the terminal information and the communication service information into a pre-trained first allocation model, obtain BWP allocation information of the target cell, and allocate a first BWP to each terminal according to the BWP allocation information; A target terminal acquisition module, configured to determine a target terminal from the terminals according to the communication quality information of the terminals after the first BWP is allocated; The second BWP allocation module is used to input the communication quality information and communication service information of the target terminal into a pre-trained second allocation model to obtain the BWP adjustment information of the target terminal, and allocate a second BWP to the target terminal according to the BWP adjustment information.

9. A base station device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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