User resource scheduling method

Abstract

The present application relates to the technical field of wireless communications. Disclosed is a user resource scheduling method. The user resource scheduling method comprises: calculating, at a MAC layer, a reachable rate range of each user on the basis of user joint channel state information of a current time interval; determining first data to be transmitted of each user in the current time interval; determining, at an application layer, a target rate of each user on the basis of the reachable rate range and said first data of the user, wherein the target rate is within the reachable rate range; allocating a transmission resource to each user on the basis of the target rate of the user, such that the transmission rate of the user reaches its own target rate; at the application layer, each user using the transmission resource to transmit said first data, and second data to be transmitted of each user in a subsequent time interval being determined; and at the MAC layer and on the basis of said second data, adjusting user joint channel state information of the subsequent time interval, and returning to the first step. In the present application, power resources are allocated to users by jointly considering the MAC layer and the application layer, so as to improve the effective transmission rate of each user.

Description

A user resource scheduling method

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] The present application claims priority to the Chinese patent application No. 202410899797.7, filed on July 5, 2024, and entitled "A user resource scheduling method", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0003] The present application relates to the technical field of wireless communication, in particular to a user resource scheduling method. BACKGROUND

[0004] Real-time multimedia and other 5.5G new services have data integrity constraints and delay constraints, that is, the amount of data to be transmitted by a user must be transmitted within the constraint time, otherwise the previous transmission is invalid transmission. Traditional services need to optimize the transmission scheme in each transmission time slot (TTI), while real-time multimedia transmission services need to consider the data transmission scheme in multiple transmission time slots (TTI).

[0005] The effective transmission rate of the user has a long-term attribute, and maximizing the achievable rate of a specific user in a certain TTI can maximize the amount of data transmitted by the specific user in the TTI, but it does not mean that the total transmission data amount of all users in the multi-TTI scale is optimal, so the power resource allocation of the application layer user is unreasonable, resulting in unreasonable MAC layer resource scheduling, low effective transmission rate of the user, and the problem that the transmission cannot be completed within the agreed time. SUMMARY

[0006] Therefore, the present application provides a user resource scheduling method, which allocates power resources to users jointly in the MAC layer and the application layer to improve the effective transmission rate of the user.

[0007] The present application provides a user resource scheduling method, which comprises: calculating the achievable rate range of each user based on the user joint channel state information of the current time slot in the MAC layer; determining the first data to be transmitted by each user in the current time slot; determining the target rate of each user according to the achievable rate range and the first data to be transmitted by each user in the application layer, the target rate being within the achievable rate range; allocating transmission resources to each user based on the target rate of each user, so that the transmission rate of each user reaches the target rate of each user; in the application layer, each user transmits the first data to be transmitted using the transmission resources, and determines the second data to be transmitted by each user in the next time slot; in the MAC layer, adjusting the user joint channel state information of the next time slot based on the second data to be transmitted, and returning to the first step.

[0008] In this implementation, by considering the data scheduling at the application layer and the specific implementation at the MAC layer, the optimal data transmission rate can be determined, and appropriate power can be allocated to users. At the same time, the channel allocation of users can be adjusted based on data transmission, thereby obtaining a spectrum access scheme and user power allocation scheme that meet data integrity and delay constraints, and improving the effective transmission rate of users.

[0009] In one optional implementation, determining the target rate of each user at the application layer based on the achievable rate range of each user and the first data to be transmitted includes: determining the initial rate of each user based on the achievable rate range, wherein the initial rate is within the achievable rate range; calculating the initial data transmission amount corresponding to the initial rate based on the initial rate of each user and the first data to be transmitted; adjusting the initial rate using a neural network algorithm to maximize the initial data transmission amount; and taking the initial rate corresponding to the maximum initial data transmission amount as the target rate of each user.

[0010] In one optional implementation, calculating the initial data transmission volume corresponding to the initial rate based on the initial rate of each user and the first data to be transmitted includes: constructing a state space, which includes the first data to be transmitted at different deadlines for each user in the current time slot; constructing an action space, which includes the initial transmission resources for each user in the current time slot, the initial transmission resources being allocated based on the initial rate; and constructing a reward function using the state space and the action space, the reward function being used to characterize the initial data transmission volume.

[0011] In one alternative implementation, the state space is [B1(t),…,B i (t),…,B N [(t),c(t)], where, B i Let c(t) represent the first data to be transmitted by user i at different deadlines at time t, and let c(t) represent the channel conditions at time t; the action space is [e1(t),…,e...]. N [t], where, e i (t) represents the initial transmission resources allocated to user i at time t.

[0012] In one optional implementation, adjusting the initial rate using a neural network algorithm to maximize the initial data transmission volume includes: maximizing the reward function using a recurrent neural network, where the reward function is: r(t) = D(t) - λE(t); where, E(t) represents the amount of transmission resources consumed at time t. D(t) represents the amount of data successfully transmitted; the initial rate corresponding to the largest initial data transmission volume is used as the target rate for each user, including determining the initial rate when the reward function is maximized as the target rate for each user.

[0013] In an optional implementation, the recurrent neural network comprises an actor network and a critic network, and the constructing the action space comprises: the actor network obtaining initial rates of the users in the current time slot based on the achievable rate range; allocating initial transmission resources to the users based on the initial rates of the users; and the actor network adjusting the initial rates according to the reward function to re-allocate the initial transmission resources.

[0014] In an optional implementation, the maximizing the reward function by using the recurrent neural network comprises: training a Q value function by using the critic network, the Q value function being:

[0015] In this implementation, the target rates of the users are determined by using the neural network algorithm based on the determination of the achievable rate range, which can ensure that the overall data transmission effect of all users is optimal and improve the data transmission success rate.

[0016] In an optional implementation, the adjusting, at the MAC layer, the user joint channel state information of the next time slot based on the second to-be-transmitted data comprises: determining, at the MAC layer, to-be-transmitted users of the next time slot based on the second to-be-transmitted data; constructing a plurality of transmission resource scheduling tables of the to-be-transmitted users and transmission frequency bands, one transmission resource scheduling table representing one transmission resource scheduling manner; calculating data throughputs of each transmission resource scheduling manner by using the transmission resource scheduling tables, taking the transmission resource scheduling manner with the largest data throughput as a target transmission resource scheduling manner; and determining the user joint channel state information corresponding to the target transmission resource scheduling manner.

[0017] In an optional implementation, the calculating the data throughputs of each transmission resource scheduling manner by using the transmission resource scheduling tables comprises: wherein, wherein, A is obtained based on iteration; wherein,

[0018] In an optional implementation, the taking the transmission resource scheduling manner with the largest data throughput as the target transmission resource scheduling manner comprises: sequentially calculating data throughputs corresponding to each transmission resource scheduling table; replacing a previous transmission resource scheduling table with a current transmission resource scheduling table when the data throughput of the current transmission resource scheduling table is greater than the data throughput of the previous transmission resource scheduling table; traversing all the transmission resource scheduling tables to obtain a transmission resource scheduling manner corresponding to a transmission resource scheduling table with the largest data throughput; and taking the transmission resource scheduling manner as the target transmission resource scheduling manner.

[0019] In the embodiment, the user combination optimization is completed in the MAC layer, the heuristic algorithm based on the field search is used, the complexity of the algorithm is reduced by reducing the number of inverse operations in the calculation of the throughput function, the optimal spectrum access scheme of the user is realized, and the subsequent data transmission efficiency is improved. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the specific embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0021] Fig. 1 is a flowchart of a user resource scheduling method according to an embodiment of the present application;

[0022] Fig. 2 is a schematic diagram of a specific user resource scheduling method according to an embodiment of the present application;

[0023] Fig. 3 is a structural block diagram of a user resource scheduling device according to an embodiment of the present application;

[0024] Fig. 4 is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0026] For a downlink of a MIMO-OFDM system deploying frequency division multiple access (FDMA), time division multiple access (TDMA) and space division multiple access (SDMA) technologies. A TDMA frame includes a plurality of TTIs, and a TTI includes a plurality of OFDM symbols.

[0027] The MIMO-OFDM system performs channel estimation at the beginning of each TTI, and assumes that the channel state information within a TTI is constant. There are K users in the MIMO-OFDM system, denoted as The base station is equipped with T antennas, and each user is equipped with M antennas. The complex channel matrix from the base station to the user g is The user combination on the time slot t and the frequency band rb is The received signal of user g ∈ G(t, rb) can be represented as:

[0028] where, is the transmit signal vector of the base station, is the precoding matrix of the base station to user g, n g,t,rb ~ CN(0, σ 2 I) is the additive complex Gaussian noise generated by the user receiver.

[0029] The signal-to-interference-plus-noise ratio (SINR) of the lth data stream of user g is:

[0030] where, w g,t,l,rb is the lth column of W g,t,rb , and is the interference of the multiple data streams in the massive MIMO system, which can be eliminated by using the nonlinear equalization technology at the user receiver end. is the inter-user interference generated by the users sharing the frequency band rb in G(t, rb), which can be eliminated by using the zero-forcing precoding. The zero-forcing precoding is to find W g,t,rb such that On this basis, the SINR can be simplified as:

[0031] where, is the normalized precoding vector of w g,t,l,rb , and P g,t,rb is the power allocated to user g on rb in time slot t, and the sum of the powers of all frequency bands and all users is P t , i.e.,

[0032] where, W g,t,rb can be obtained by singular value decomposition of the joint channel matrix H (For the sake of simple representation of symbols, the subscripts t and rb are omitted) to obtain the above formula (1).

[0033] According to the Shannon formula, the data transmission rate of user g in time slot t can be represented as:

[0034] The 5.5G new service with data integrity constraint and delay constraint needs to consider data transmission on the time scale of multiple TTIs. It not only pursues the maximum data transmission rate in each TTI, but more importantly, it requires the data to be transmitted completely within the constraint time. Let be the amount of data to be transmitted by all users, and τ = {τ1, …, τ K} be the remaining transmission time of the user. For user g, if τ gIf the data transmission task is completed within the specified time, then the user is considered to have completed the task within τ. g Effective transmission rate R within g for Otherwise, the rate is 0, that is:

[0035] The goal of joint data and resource scheduling is to maximize the effective transmission rate for all users. Let τ be the denoted τ. max =maxτ1,…,τ K , τ max The effective transmission rate of all users in each time slot. Let G(t) denote the user scheduling matrix at time t. G(t) is a matrix with elements of either 0 or 1. (g,rb) =1 indicates that user g accesses frequency band rb. Let G = {G(1), ...,G(τ)} max Let P(t) represent the set of user scheduling matrices over a given time period. Similarly, let P(t) represent the user power allocation matrix at time t. (g,rb) =P g,t,rb Let P represent the power allocated to user g in frequency band rb. Let P = P(1), ..., P(τ) max () represents the set of user power allocation matrices over a period of time. The joint scheduling optimization problem of data and resources with data integrity constraints and delay constraints can be formalized as follows:

[0036] To address the aforementioned issues, this application proposes a user resource scheduling method that, by considering data scheduling at the application layer and the specific implementation at the MAC layer, determines the optimal data transmission rate, allocates appropriate power to users, and adjusts user channel allocation based on data transmission. This method achieves a spectrum access scheme and user power allocation scheme that satisfy data integrity and delay constraints, thereby improving the effective transmission rate of users.

[0037] According to an embodiment of this application, a user resource scheduling method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0038] This embodiment provides a user resource scheduling method. Figure 1 is a schematic diagram of the user resource scheduling method according to an embodiment of this application. As shown in Figure 1, the process includes the following steps:

[0039] Step S101: Calculate the reachable rate range of each user at the MAC layer based on the user joint channel state information of the current time slot.

[0040] The user joint channel state information is used to represent the channel resource allocation of each user under the current frequency band access scheme. The MAC layer calculates the rate of each user for data transmission according to the user joint channel state information, and obtains the achievable rate range.

[0041] It can be understood that the actual transmission rate of each user cannot exceed the achievable rate range under the current channel resource allocation.

[0042] Step S102, determining the first to-be-transmitted data of each user in the current time slot.

[0043] The data transmission task is used to allocate the first to-be-transmitted data of each user in the current time slot.

[0044] Step S103, determining the target rate of each user according to the achievable rate range and the first to-be-transmitted data of each user in the application layer.

[0045] The target rate is within the achievable rate range.

[0046] The data scheduling of the first to-be-transmitted data is modeled according to the optimal control theory in the application layer, and the optimal transmission rate of each user is determined as the target rate of each user based on the achievable rate range of each user.

[0047] Step S104, allocating transmission resources to each user based on the target rate of each user, so that the transmission rate of each user reaches the target rate of each user.

[0048] The power allocation scheme is determined according to the target rate of each user, and the transmission resources are allocated to each user based on the power allocation scheme, so that each user can transmit data at the target rate.

[0049] Step S105, each user transmits the first to-be-transmitted data using the transmission resources in the application layer, and determines the second to-be-transmitted data of each user in the next time slot.

[0050] Each user transmits data according to the allocated transmission resources in the current time slot, and allocates the second to-be-transmitted data of each user in the next time slot according to the data transmission task.

[0051] The data transmission task of each time slot is different, and the number of transmission users in each time slot may increase or decrease. For example, when user a has completed the transmission task in the current time slot, there is no second to-be-transmitted data of user a in the next time slot.

[0052] Step S106, adjusting the user joint channel state information of the next time slot based on the second to-be-transmitted data in the MAC layer.

[0053] The MAC layer determines user information to be transmitted in the second time slot according to the second data to be transmitted, and determines a frequency band access scheme of the second time slot according to the user information to be transmitted and the channel frequency band information, to obtain user joint channel state information of the next time slot.

[0054] Optionally, the user joint channel state information of the next time slot is used to determine a power allocation scheme for the user. For details, please return to step S101.

[0055] The user resource scheduling method provided in the embodiment can determine an optimal data transmission rate by considering data scheduling of the application layer and specific implementation of the MAC layer, allocate appropriate power to the user, and adjust channel allocation of the user based on data transmission, so that a spectrum access scheme and a user power allocation scheme that meet data integrity and delay constraints can be obtained, and the effective transmission rate of the user is improved.

[0056] In the embodiment, a user resource scheduling method is provided, which is divided into two parts, a power allocation scheme and a frequency band access scheme. FIG. 2 is a flowchart of the user resource scheduling method according to the embodiment of the application. As shown in FIG. 2, the user resource scheduling method is as follows: at time t, the Rate estimator of the MAC layer estimates the achievable rate range of all users based on the user joint channel state information H t estimate the achievable rate range of all users and solves the modeling and solving of the application layer data scheduling based on the optimal control theory to obtain the target rate of the MAC layer as the optimization target of the MAC layer Rate optimizer. The target rate is used for data transmission of all users. The frequency band access relationship table of different user combinations is constructed according to users with transmission tasks, the user combination optimization method is used to select the frequency band access scheme with the optimal throughput, and the frequency band access scheme is used to determine the user joint channel state information at time t+1. The specific implementation is as follows:

[0057] First, the power allocation scheme is determined based on reinforcement learning.

[0058] The initial rate of each user is determined based on the achievable rate range, wherein the initial rate is within the achievable rate range. The initial data transmission amount corresponding to the initial rate is calculated according to the initial rate of each user and the first data to be transmitted, the initial rate is adjusted by using a neural network algorithm to maximize the initial data transmission amount, and the initial rate corresponding to the maximum initial data transmission amount is taken as the target rate of each user.

[0059] Step S201, construct a state space and an action space.

[0060] Specifically, the state space includes first to-be-transmitted data of each user corresponding to different deadlines in the current time slot. The state space is represented as [B1(t),…,B i (t),…,B N (t),c(t)],wherein, B i (t) represents the first to-be-transmitted data of user i at time t corresponding to different deadlines, and c(t) represents the channel condition at time t.

[0061] Specifically, the action space includes initial transmission resources of each user in the current time slot, and the initial transmission resources are allocated based on initial rates. The action space is represented as [e1(t),…,e N (t)],wherein, e i (t) represents the initial transmission resource allocated to user i at time t.

[0062] Step S202, constructing a reward function by using the state space and the action space.

[0063] The reward function is used to represent the initial data transmission amount.

[0064] Specifically, the reward function is r(t)=D(t)-λE(t).

[0065] wherein, E(t) represents the transmission resource consumption at time t, D(t) represents the successfully transmitted data amount.

[0066] Step S203, maximizing the reward function by using a recurrent neural network to determine the initial rate at which the reward function is maximum as the target rate of each user.

[0067] Specifically, the reward function is maximized by performing state updating on the state space and the action space. The process of state updating is as follows: placing to-be-transmitted data packets in a buffer, and each buffer contains N user corresponding to an infinite delay-sensitive queue. represents the state of each sensitive queue i at time slot t. For user i with initial transmission resource e and channel condition c, the probability of successful transmission is represented as P i (e,c), wherein e=0 represents that the data is not successfully transmitted, and P i (0,c)=0. Meanwhile, for all e>0, P i (e)>0, if the to-be-transmitted data is not successfully transmitted, and it is judged that the to-be-transmitted data does not exceed the transmission time limit, the to-be-transmitted data is still placed in the buffer.

[0068] The recurrent neural network is trained based on the state update. The recurrent neural network includes an actor network and a critic network.

[0069] The actor network determines initial rates of the users in the current time slot based on the achievable rate range, and allocates initial transmission resources to the users based on the initial rates of the users, and outputs [e1(t),…,e N The critic network trains a Q value function in reinforcement learning according to data in the Replay buffer, where the Q value function is:

[0070] The actor network adjusts the initial rates according to the reward function to re-allocate the initial transmission resources, so that the reward function is maximized. The initial rate corresponding to the maximum reward function is taken as a target rate of each user, and the transmission resources are allocated to the users by using the target rate.

[0071] In this embodiment, the target rate of each user is determined by using a neural network algorithm based on the determination of the achievable rate range, which can ensure that the overall data transmission effect of all users is optimal, and improve the data transmission success rate.

[0072] Step S204, each user transmits the data to be transmitted in the current time slot by using the transmission resources, and determines the data to be transmitted by each user in the next time slot.

[0073] Second, determine the frequency band access scheme based on user combination optimization.

[0074] Step S205, construct a plurality of transmission resource scheduling tables of the users to be transmitted and the transmission frequency bands.

[0075] Determine the users to be transmitted in the next time slot based on the second data to be transmitted at the MAC layer, and construct a plurality of transmission resource scheduling tables of the users to be transmitted and the transmission frequency bands.

[0076] Each transmission resource scheduling table represents a transmission resource scheduling mode.

[0077] Specifically, based on the l users to be transmitted and the g transmission frequency bands, an l×g 0-1 resource scheduling table is constructed for the l users to be transmitted and the g transmission frequency bands in the next time slot. Wherein, element 1 in the table indicates that the corresponding user accesses the corresponding frequency band, and element 0 indicates that the corresponding user does not access the corresponding frequency band.

[0078] Step S206, determine the target transmission resource scheduling mode from the transmission resource scheduling table.

[0079] Specifically, data throughput of each transmission resource scheduling mode is calculated by using the transmission resource scheduling table, wherein the data throughput calculation mode is: wherein, wherein, A is based on iteration, wherein, channel correlation matrix

[0080] The transmission resource mode with the largest data throughput is taken as the target transmission resource scheduling mode.

[0081] Specifically, data throughput corresponding to each transmission resource scheduling table is calculated in turn, and when the data throughput of the current transmission resource scheduling table is greater than that of the previous transmission resource scheduling table, the current transmission resource scheduling table replaces the previous transmission resource scheduling table. All transmission resource scheduling tables are traversed to obtain the transmission resource scheduling mode corresponding to the transmission resource scheduling table with the largest data throughput, and the transmission resource scheduling mode is taken as the target transmission resource scheduling mode.

[0082] Optionally, user joint channel state information corresponding to the target transmission resource scheduling mode is determined, and the user joint channel state information is used to determine the achievable rate range at t+1 time, so as to perform user resource scheduling in a cycle.

[0083] In this embodiment, the user combination optimization is completed in the MAC layer, the heuristic algorithm based on field search is used, and the algorithm complexity is reduced by reducing the number of inverse operations in the calculation of the throughput function, and the optimal spectrum access scheme of the user is realized, and the subsequent data transmission efficiency is improved. By considering the data scheduling of the application layer and the specific implementation of the MAC layer, the optimal data transmission rate can be determined, the appropriate power is allocated to the user, and the channel allocation of the user is adjusted based on the data transmission. The spectrum access scheme and the user power allocation scheme that meet the data integrity and delay constraints can be obtained, and the effective transmission rate of the user is improved.

[0084] In this embodiment, a user resource scheduling device is also provided, which is used to implement the above embodiments and optional embodiments, and details are not repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware is also possible and is contemplated.

[0085] The present embodiment provides a user resource scheduling device, as shown in FIG. 3, comprising:

[0086] The calculation module 301 is configured to calculate the achievable rate range of each user based on the user joint channel state information of the current time slot in the MAC layer.

[0087] The first determining module 302 is configured to determine first to-be-transmitted data of each user in a current time slot.

[0088] The second determining module 303 is configured to determine target rates of each user according to the reachable rate range of each user and the first to-be-transmitted data in an application layer.

[0089] The allocating module 304 is configured to allocate transmission resources for each user based on the target rate of each user, so that the transmission rate of each user reaches the target rate of each user.

[0090] The transmission module 305 is configured to transmit the first to-be-transmitted data of each user in the application layer by using the transmission resources, and determine second to-be-transmitted data of each user in a next time slot.

[0091] The adjusting module 306 is configured to adjust user joint channel state information in a next time slot based on the second to-be-transmitted data in a MAC layer.

[0092] Further function descriptions of the above modules are the same as those of the above corresponding embodiments, and are not described herein again.

[0093] The user resource scheduling apparatus in the embodiment is presented in the form of functional units. The units refer to ASIC (Application Specific Integrated Circuit) circuits, processors and memories executing one or more software or fixed programs, and / or other devices that can provide the above functions.

[0094] The embodiment of the present application further provides a computer device having the user resource scheduling apparatus shown in FIG. 3.

[0095] Please refer to FIG. 4, which is a structural schematic diagram of a computer device according to an optional embodiment of the present application. As shown in FIG. 4, the computer device includes one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components communicate and cooperate with each other by using different buses, and can be installed on a common mainboard or in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in the memory or graphics information stored in the memory to display a GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, multiple processors and / or multiple buses can be used with multiple memories and multiple storage devices, if necessary. Similarly, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). In FIG. 4, one processor 10 is taken as an example.

[0096] The processor 10 can be a central processing unit, a network processing unit, or a combination thereof. The processor 10 can further include a hardware chip. The hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device can be a complex programmable logic device, a field programmable logic device, a general array logic, or any combination thereof.

[0097] The memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the methods illustrated in the above embodiments.

[0098] The memory 20 can include a program storage area and a data storage area. The program storage area can store an operating system and application programs required by at least one function. The data storage area can store data created according to the use of the computer device, and the like. In addition, the memory 20 can include a high-speed random access memory, and can further include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some alternative embodiments, the memory 20 can optionally include a memory disposed remotely with respect to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0099] The memory 20 can include a volatile memory, such as a random access memory, and can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid state disk. The memory 20 can further include a combination of the above-mentioned types of memories.

[0100] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 can be connected through a bus or other means, and are connected through a bus in FIG. 4 as an example.

[0101] The input device 30 can receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, and the like. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), a tactile feedback device (e.g., a vibration motor), and the like. The display device includes, but is not limited to, a liquid crystal display, a light emitting diode, a display, and a plasma display. In some alternative embodiments, the display device can be a touch screen.

[0102] The embodiments of the present application further provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or be implemented as computer code originally stored in a remote storage medium or a non-transitory machine readable storage medium and downloaded through a network and stored in a local storage medium, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Alternatively, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that the computer, processor, microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, processor, or hardware, the method shown in the above embodiments is implemented.

[0103] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, the method and / or technical solutions according to the present application can be invoked or provided. Those skilled in the art should understand that the form of computer program instructions in a computer readable medium includes but is not limited to source files, executable files, installation package files, etc. Correspondingly, the way of executing computer program instructions by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0104] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A method for scheduling user resources, characterized by, The method comprises: calculating the achievable rate range of each user based on the user joint channel state information of the current time slot at the MAC layer; determining the first data to be transmitted of each user in the current time slot; determining the target rate of each user according to the achievable rate range and the first data to be transmitted of each user at the application layer, the target rate being within the achievable rate range; allocating transmission resources for each user based on the target rate of each user, so that the transmission rate of each user reaches the target rate of each user; transmitting the first data to be transmitted of each user using the transmission resources at the application layer, and determining the second data to be transmitted of each user in the next time slot; adjusting the user joint channel state information of the next time slot based on the second data to be transmitted at the MAC layer, and returning to the first step.

2. The method of claim 1, wherein, The method comprises: determining the initial rate of each user based on the achievable rate range, the initial rate being within the achievable rate range; calculating the initial data transmission amount corresponding to the initial rate according to the initial rate and the first data to be transmitted of each user; adjusting the initial rate using a neural network algorithm to maximize the initial data transmission amount; taking the initial rate corresponding to the maximum initial data transmission amount as the target rate of each user.

3. The method of claim 2, wherein, The method comprises: constructing a state space, the state space comprising the first data to be transmitted of each user corresponding to different deadlines in the current time slot; constructing an action space, the action space comprising the initial transmission resources of each user in the current time slot, the initial transmission resources being allocated based on the initial rate; constructing a reward function using the state space and the action space, the reward function being used to represent the initial data transmission amount.

4. The user resource scheduling method of claim 3, wherein The state space is [B1(t),...,B i (t),...,B N (t), c(t)], where, B i (t) denotes the first data to be transmitted of user i at time t with different deadlines, c(t) denotes the channel condition at time t; The action space is [e1(t),...,e N (t)], wherein, e i (t) denotes the initial transmission resource allocated to user i at time t.

5. The method of claim 4, wherein, the adjusting of the initial rate using a neural network algorithm to maximize the initial data transmission amount comprises: maximizing the reward function using a recurrent neural network, the reward function being: r(t) = D(t) - λE(t); wherein E(t) represents the transmission resource consumption amount at time t, D(t) represents the amount of successfully transmitted data; the taking of the initial rate corresponding to the maximum initial data transmission amount as the target rate of each user comprises: determining the initial rate when the reward function is maximum as the target rate of each user.

6. The method of claim 5, wherein, The recurrent neural network comprises an actor network and a critic network, and the constructing of the action space comprises: the actor network obtains the initial rate of each user in the current time slot based on the achievable rate range; allocating the initial transmission resources for each user based on the initial rate of each user; the actor network adjusts the initial rate according to the reward function to re-allocate the initial transmission resources.

7. The method of claim 5, wherein, the maximizing of the reward function using a recurrent neural network comprises: training a Q-value function using the critic network, the Q-value function being:

8. The method of claim 1, wherein, The user joint channel state information of the next time slot is adjusted based on the second to-be-transmitted data at the MAC layer, including: At the MAC layer, the to-be-transmitted user of the next time slot is determined based on the second to-be-transmitted data; A plurality of transmission resource scheduling tables of the to-be-transmitted user and the transmission frequency band are constructed, and one of the transmission resource scheduling tables represents one transmission resource scheduling mode; The data throughput of each transmission resource scheduling mode is calculated by using the transmission resource scheduling table, and the transmission resource scheduling mode with the largest data throughput is taken as a target transmission resource scheduling mode; The user joint channel state information corresponding to the target transmission resource scheduling mode is determined.

9. The method of claim 8, wherein, The calculating the data throughput of each transmission resource scheduling mode by using the transmission resource scheduling table comprises: wherein wherein The A is based on iteration acquisition; wherein 10. The method of claim 9, wherein, The transmission resource scheduling mode with the largest data throughput is taken as the target transmission resource scheduling mode, including: The data throughput corresponding to each transmission resource scheduling table is calculated in turn; When the data throughput of the current transmission resource scheduling table is greater than the data throughput of the previous transmission resource scheduling table, the current transmission resource scheduling table is replaced by the previous transmission resource scheduling table; All transmission resource scheduling tables are traversed to obtain the transmission resource scheduling mode corresponding to the transmission resource scheduling table with the largest data throughput; The transmission resource scheduling mode is taken as the target transmission resource scheduling mode.

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