Base station resource management method and system

Abstract

The invention belongs to the field of base station resource management, and provides a base station resource management method and system, and the method comprises the steps: collecting the service demands and network load information of user equipment; constructing an optimization objective function of base station resource allocation; introducing a Lagrange multiplier, and constructing a Lagrange function; calculating a preliminary resource allocation scheme of each user, wherein the preliminary resource allocation scheme comprises spectrum resource allocation and power resource allocation of the users; each user adjusts the power strategy to maximize the utility function according to the preliminarily distributed frequency spectrum and power; the base station updates a resource allocation strategy of the user through feedback interaction with the user; after multiple times of adjustment, the system reaches Nash equilibrium, and finally a resource allocation scheme of each user is determined.

Description

Technical Field

[0001] The present invention belongs to the field of base station resource management, and in particular relates to a base station resource management method and system. Background Art

[0002] With the rapid development of mobile communication technology and the widespread application of Internet of Things (IoT) devices, base station resource management in cellular networks faces increasing challenges. Especially in low-power wide area networks such as narrowband Internet of Things (NB-IoT), base station resources (such as spectrum, power, etc.) are limited, the number of user devices is increasing, and business needs are diversified. How to efficiently allocate and manage these limited resources has become a key issue in optimizing network performance.

[0003] Traditional base station resource allocation methods are mostly based on fixed resource allocation rules, which often fail to fully consider the dynamic needs of user devices and changes in the network environment. For example, some user devices may require a higher transmission rate to meet the needs of large data transmission, while other users only need to maintain a lower data rate for periodic low-power data transmission. Traditional methods are difficult to adaptively adjust according to real-time user needs and network loads, resulting in low resource utilization and inability to effectively meet the needs of different types of user devices. In addition, unreasonable allocation of spectrum resources and power resources may also lead to aggravated interference problems, thereby affecting the communication quality of the entire network.

[0004] On the other hand, as the network scale expands and the number of users increases, the base station must not only consider the utility of a single user, but also the mutual interference and resource competition among multiple users. When user devices compete for limited resources, they need to ensure the overall balance and stability of the system. However, many current resource management strategies lack the analysis of game relationships in a multi-user competition environment, making it difficult to achieve global optimal resource allocation.

[0005] Therefore, in order to solve the above problems, there is an urgent need for an intelligent base station resource management method, which can dynamically adjust the resource allocation strategy according to the actual needs of users and network status while meeting the spectrum and power resource constraints. Summary of the invention

[0006] In order to solve the problems in the prior art, the present invention provides a base station resource management method, the method comprising the following steps: The base station collects the service requirements and network load information of user equipment in real time; Constructing an optimization objective function for base station resource allocation, where the optimization objective function is based on maximizing a user's utility function and is subject to constraints of spectrum resources and power resources; According to the spectrum resource constraints and power resource constraints, Lagrangian multipliers are introduced and Lagrangian functions are constructed; By iteratively optimizing the Lagrange multiplier, a preliminary resource allocation scheme for each user is calculated, including the user's spectrum resource allocation and power resource allocation; Each user adjusts its power strategy to maximize its utility function based on the initially allocated spectrum and power; The base station updates the user's resource allocation strategy through feedback interaction with the user; After multiple adjustments, the system reaches a Nash equilibrium and ultimately determines the resource allocation plan for each user.

[0007] Another aspect of the present invention further provides a base station resource management system, the system comprising the following modules: The acquisition module is used by the base station to collect the service requirements and network load information of user equipment in real time; A construction module, used to construct an optimization objective function for base station resource allocation, where the optimization objective function is based on maximizing a user's utility function and is subject to constraints of spectrum resources and power resources; An optimization module, used to introduce Lagrangian multipliers and construct Lagrangian functions according to spectrum resource constraints and power resource constraints; A second optimization module is used to calculate a preliminary resource allocation scheme for each user, including spectrum resource allocation and power resource allocation of the user, by iteratively optimizing Lagrange multipliers; An allocation module, for each user to adjust its power strategy to maximize its utility function according to the initially allocated spectrum and power; A feedback module, used for the base station to update the user's resource allocation strategy through feedback interaction with the user; The adjustment module is used to achieve Nash equilibrium in the system after multiple adjustments and finally determine the resource allocation plan for each user.

[0008] The base station resource management method and system proposed in the present invention combine the Lagrange relaxation method and the Nash equilibrium theory in game theory, and have the following beneficial effects: The present invention introduces the Lagrangian relaxation method, fully considers the constraints of spectrum resources and power resources, realizes dynamic optimization allocation of resources while ensuring user communication needs, and significantly improves the utilization rate of spectrum and power resources.

[0009] This method is based on the real-time needs of user devices and network status, and continuously optimizes resource allocation strategies through feedback interaction. It can dynamically respond to changes in the network environment and the business needs of user devices, ensuring the flexibility and accuracy of resource allocation.

[0010] By maximizing the user's utility function, especially in multi-user scenarios, the system can provide fair resource allocation while taking into account the communication needs and priorities of each user, ensuring the communication quality of critical tasks and improving the user's overall communication experience.

[0011] The present invention is based on the Nash equilibrium theory in game theory, which enables multiple users to minimize interference when sharing spectrum resources and power resources, ensures balanced resource allocation for each user device, avoids mutual interference during resource allocation, and improves the stability of the entire network.

[0012] Through multiple iterations of optimization and feedback adjustments, the system eventually reaches a Nash equilibrium state, ensuring that the resource allocation of each user's device is optimal on a global scale. This solves the problem that traditional resource management methods cannot effectively handle multi-user competition for resources, and achieves the optimal effect of global resource allocation.

[0013] The present invention is particularly suitable for resource management of narrowband base stations, especially in the Internet of Things and low-power wide area network scenarios, and can effectively cope with complex network environments with multiple users and high concurrency, thereby improving the overall performance of the system.

[0014] In summary, the present invention realizes efficient utilization of narrowband base station resources through an intelligent resource management method, significantly improves the communication performance and user experience of the network, and at the same time has flexibility and global optimization capabilities, providing strong technical support for resource management of next-generation communication networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0017] Below, the invention is preferably described in conjunction with the accompanying drawings and specific implementation methods.

[0018] This embodiment solves the above problem through the following steps: In one embodiment, reference Figure 1The present invention provides a base station resource management method, which is particularly suitable for resource management and optimization of narrowband base stations. The narrowband base stations are mainly used in the Internet of Things (NB-IoT) or low-rate communication networks, and have the characteristics of wide coverage and limited bandwidth resources. The base station resources include but are not limited to spectrum resources, power resources, channel resources, etc. The method of the present invention realizes efficient management of narrowband base station resources through intelligent and dynamic scheduling and allocation. The method is particularly suitable for optimizing the utilization of limited resources in narrowband base stations, aiming to improve spectrum utilization, network communication efficiency and user experience, so as to meet the communication needs in multi-user and multi-service scenarios and realize refined and real-time management of resources.

[0019] The base station collects the service requirements and network load information of user equipment in real time.

[0020] The base station continuously and in real time collects and processes the service requirements and network load information of multiple user devices connected to the base station through its built-in monitoring module. The service requirements include but are not limited to the current data transmission rate of the user device, the requested quality of service (QoS) requirements, transmission delay, bandwidth requirements, data throughput, connection status, signal strength, and the type of communication protocol used. In addition, the base station can also detect the mobility information of the user device, including the changes in the geographical location of the user device, the trend of changes in signal strength, etc., in order to predict future resource requirements.

[0021] At the same time, the base station obtains network load information in real time, including but not limited to the spectrum resource occupancy, power resource allocation, channel congestion, number of active users, number of connected devices, data packet flow, and total load pressure of the base station. Through the continuous collection and dynamic monitoring of the above information, the base station can grasp the current network operation status and the changes in the communication needs of each user device in real time, and provide basic data support for the subsequent optimization and allocation of resources and dynamic adjustment, thereby ensuring the accuracy of resource scheduling and the timeliness of response. Based on the collected information, the base station can adaptively adjust resources in different time periods to ensure the stable operation of the system, especially during peak load periods, to ensure the stable communication quality of high-priority services.

[0022] An optimization objective function for base station resource allocation is constructed, where the optimization objective function is based on maximizing a user's utility function and is subject to constraints of spectrum resources and power resources.

[0023] The present invention constructs an optimization objective function for base station resource allocation to achieve optimal resource allocation for multiple user devices under limited resource conditions. Specifically, the base station optimizes the utility function of each user device to maximize the communication performance and resource utilization of the user device. The utility function represents the utility of user i, usually its data transmission rate R i The utility function is defined as follows: , Among them, R i is the user i in a given spectrum resource S i and power distribution P i The transmission rate under the condition. Utility function It can be a reflection of users' requirements for different communication qualities, including factors such as transmission rate, delay sensitivity and quality of service (QoS).

[0024] In order to optimize the resource utilization of the overall system, the present invention constructs the following optimization objective function to maximize the sum of the utilities of all user devices: , Where N is the number of active users currently connected to the base station. The base station seeks a solution that can provide the best resource allocation for all user devices by solving the objective function.

[0025] The optimization objective function is also subject to the following resource constraints: Spectrum resource constraints: , Among them, S i represents the spectrum resources allocated to user i, S total is the total spectrum resource available to the base station. This constraint ensures that the base station does not exceed its spectrum capacity during resource allocation.

[0026] Power resource constraints: , Among them, P i is the power allocated to user i, P total is the total power budget of the base station. This constraint is used to ensure that the base station meets the power limit when allocating transmit power to all users, avoiding excessive power consumption and interference.

[0027] According to the spectrum resource constraints and power resource constraints, Lagrangian multipliers are introduced and Lagrangian functions are constructed.

[0028] In order to meet the constraints of spectrum resources and power resources in the resource allocation process, the present invention introduces the Lagrange multiplier method to convert the above constraints into Lagrange functions for optimization and solution. The resource allocation optimization goal of the base station is to maximize the user utility function , and the constraints of spectrum resources and power resources must be met. To this end, for each constraint, the corresponding Lagrangian multiplier is defined to construct the Lagrangian function of the optimization problem.

[0029] In order to incorporate these constraints into the solution process of the optimization objective function, the present invention introduces the Lagrange multiplier and , corresponding to the spectrum resource constraints and power resource constraints respectively. Based on this, the Lagrangian function is constructed as follows: , in: is the total utility function of the system, which represents the sum of the utilities of all users.

[0030] It is the Lagrange multiplier corresponding to the spectrum resource constraint and is used to adjust the penalty weight when allocating spectrum resources.

[0031] It is the Lagrange multiplier corresponding to the power resource constraint and is used to adjust the penalty weight when allocating power resources.

[0032] By iteratively optimizing the Lagrange multiplier, the preliminary resource allocation scheme for each user is calculated, including the user's spectrum resource allocation and power resource allocation.

[0033] The base station performs iterative optimization through the following steps: Initial value setting: The base station first initializes the Lagrange multiplier and , corresponding to the initial weights of spectrum resource constraints and power resource constraints.

[0034] Resource allocation solution calculation: In each iteration, the base station calculates the resource allocation solution based on the current Lagrange multiplier value. and , calculate the resource allocation scheme for each user. Specifically, by solving the following optimization problem, the base station calculates the optimal spectrum resource allocation for each user i and : , This optimization process ensures that the user utility function is satisfied while satisfying system resource constraints. Get maximized.

[0035] Lagrange multiplier update: After each iteration, the base station updates the Lagrange multiplier according to the resource allocation. and , to gradually approach the optimal solution that satisfies the spectrum and power resource constraints. The update rule of the Lagrange multiplier is as follows: , , in, and is the step size factor, which is used to control the update speed of the Lagrange multiplier.

[0036] Convergence determination: The base station optimizes the Lagrange multiplier through multiple iterations. When the following conditions are met at the same time, the algorithm is determined to have converged and the iteration is stopped: , , in, is the preset convergence threshold.

[0037] Preliminary resource allocation plan: After iterative optimization, the base station finally calculates the preliminary resource allocation plan for each user, which is the spectrum resource allocation for user i. and power resource allocation ,These allocation schemes satisfy the constraints of both spectrum resources and power resources.

[0038] Each user adjusts its power strategy to maximize its utility function based on the initially allocated spectrum and power; the base station updates the user's resource allocation strategy through feedback interaction with the user; after multiple adjustments, the system reaches Nash equilibrium and finally determines the resource allocation plan for each user.

[0039] The base station initially allocates spectrum resources to users. and power resources After that, each user equipment is allowed to further optimize its transmission power P according to the allocated resources. i , in order to maximize its utility function At the same time, the base station continuously updates its resource allocation strategy through real-time feedback interaction with each user device. After multiple interactions and adjustments, the system finally converges to the Nash equilibrium state and determines the optimal spectrum and power allocation plan for each user.

[0040] The transmission rate of the user equipment R i It is given by the following formula: , in: B i is the bandwidth of user i (with spectrum resource S i proportional to).

[0041] h i is the channel gain of user i.

[0042] P i is the transmit power of user i.

[0043] is the background noise power.

[0044] represents the interference of other users to user i.

[0045] User's utility function With its transmission rate R i Closely related, the optimization goal is to maximize Therefore, the user equipment has a current channel gain h i and interference levels , adjust the transmission power P i To maximize its utility function: , In each adjustment step, the user equipment gradually increases or decreases the transmission power to find the optimal power strategy P i , to improve the channel capacity and maximize the utility function.

[0046] During the process of the user equipment adjusting the power strategy, the base station continuously obtains the communication status of the user equipment through feedback interaction with the user equipment, including but not limited to the following parameters: The current signal-to-noise ratio (SNR); Current transfer rate; The level of interference faced by user equipment.

[0047] Based on the information fed back by the user equipment, the base station analyzes the current network resource usage, including the allocation status of spectrum resources and power resources. After each feedback, the base station dynamically adjusts the resource allocation strategy through the following steps: Spectrum adjustment: The base station evaluates the current spectrum resource allocation based on user feedback and readjusts the spectrum resources S allocated to each user based on network load and interference. i .

[0048] Power adjustment: The base station analyzes the interference and channel status of the user equipment and further optimizes the power P allocated to each user. i , ensuring that the transmission rate for all users is improved.

[0049] The base station makes each user's utility function Keep approaching its optimal value.

[0050] After multiple interactions and adjustments between the base station and the user equipment, the system gradually approaches the Nash equilibrium state. Under the Nash equilibrium, the resource allocation schemes of all users are optimal, that is, any user cannot further improve his utility function by adjusting his power or spectrum resources without changing the resource allocation of other users. The Nash equilibrium condition can be described as: , in, and They represent the optimal spectrum resources and power allocation of user i in the equilibrium state, respectively, and and are other allocation strategies that user i may choose. This condition indicates that no user can further improve his utility through unilateral strategy adjustment.

[0051] When the system reaches Nash equilibrium, the base station determines the final resource allocation plan for each user, including spectrum resources. and power resources At this time, the utility function of each user is The maximum value has been reached, and the system resource utilization and communication performance are optimally guaranteed. After the final resource allocation plan is determined, the base station will continue to monitor the network status. When user demand or network load changes, the base station can re-enter the above feedback and optimization process to ensure continuous optimization of resource allocation.

[0052] On the other hand, the present invention also provides a base station resource management system, comprising: The acquisition module is used by the base station to collect the service requirements and network load information of user equipment in real time; A construction module, used to construct an optimization objective function for base station resource allocation, where the optimization objective function is based on maximizing a user's utility function and is subject to constraints of spectrum resources and power resources; An optimization module, used to introduce Lagrangian multipliers and construct Lagrangian functions according to spectrum resource constraints and power resource constraints; A second optimization module is used to calculate a preliminary resource allocation scheme for each user, including spectrum resource allocation and power resource allocation of the user, by iteratively optimizing Lagrange multipliers; An allocation module, for each user to adjust its power strategy to maximize its utility function according to the initially allocated spectrum and power; A feedback module, used for the base station to update the user's resource allocation strategy through feedback interaction with the user; The adjustment module is used to achieve Nash equilibrium in the system after multiple adjustments and finally determine the resource allocation plan for each user.

[0053] The prior art mentioned in the above background technology section and specific embodiment section of the present invention can be used as part of the present invention to understand the meaning of some technical features or parameters.

Claims

1. A base station resource management method, characterized in that: The method comprises the following steps: The base station collects the service requirements and network load information of user equipment in real time; Constructing an optimization objective function for base station resource allocation, where the optimization objective function is based on maximizing a user's utility function and is subject to constraints of spectrum resources and power resources; According to the spectrum resource constraints and power resource constraints, Lagrangian multipliers are introduced and Lagrangian functions are constructed; By iteratively optimizing the Lagrange multiplier, a preliminary resource allocation scheme for each user is calculated, including the user's spectrum resource allocation and power resource allocation; Each user adjusts its power strategy to maximize its utility function based on the initially allocated spectrum and power; The base station updates the user's resource allocation strategy through feedback interaction with the user; After multiple adjustments, the system reaches a Nash equilibrium and ultimately determines the resource allocation plan for each user.

2. The base station resource management method according to claim 1, characterized in that: The service requirements of the user equipment include: The user equipment’s current data transmission rate, requested quality of service requirements, transmission delay, bandwidth requirements, data throughput, connection status, signal strength, and the type of communication protocol used.

3. The base station resource management method according to claim 1, characterized in that: The network load information includes: spectrum resource occupancy of the base station, power resource allocation, channel congestion, number of active users, number of connected devices, data packet traffic, and total load pressure of the base station.

4. The base station resource management method according to claim 1, characterized in that: The constructing of the optimization objective function of base station resource allocation, wherein the optimization objective function is based on maximizing the user's utility function and is subject to the constraints of spectrum resources and power resources, includes: The utility function is defined as follows: ， Among them, R i is the user i in a given spectrum resource S i and power distribution P i The transmission rate under the condition, the utility function It is a reflection of users’ requirements for different communication quality; The optimization objective function consists in maximizing the sum of utilities of all user devices: ， Where N is the number of active users currently connected to the base station; Spectrum resource constraints: ， Among them, S i represents the spectrum resources allocated to user i, S total is the total spectrum resources available to the base station; Power resource constraints: ， Among them, P i is the power allocated to user i, P total is the total power budget of the base station.

5. The base station resource management method according to claim 4, characterized in that: The introduction of Lagrangian multipliers and construction of Lagrangian functions according to spectrum resource constraints and power resource constraints include: Introducing Lagrange multipliers and , which correspond to spectrum resource constraints and power resource constraints respectively. Based on this, the Lagrangian function is constructed. as follows: ， in: is the total utility function of the system, which represents the sum of the utilities of all users; It is the Lagrange multiplier corresponding to the spectrum resource constraint, which is used to adjust the penalty weight when allocating spectrum resources; It is the Lagrange multiplier corresponding to the power resource constraint and is used to adjust the penalty weight when allocating power resources.

6. The base station resource management method according to claim 5, characterized in that: The calculating of the preliminary resource allocation scheme for each user, including the spectrum resource allocation and power resource allocation of the user, by iteratively optimizing the Lagrange multiplier comprises: Initialize the Lagrange multipliers and ; In each iteration, the base station calculates the Lagrange multiplier value according to the current value. and , calculate the resource allocation plan for each user; by solving the following optimization problem, the base station provides each user Calculate the optimal spectrum resource allocation and : ， After each iteration, the base station updates the Lagrange multiplier according to the resource allocation. and , in order to gradually approach the optimal solution that satisfies the spectrum and power resource constraints, the update rule of the Lagrange multiplier is as follows: ， ， in, and is the step size factor, which is used to control the update speed of the Lagrange multiplier; The base station optimizes the Lagrange multiplier through multiple iterations. When the following conditions are met at the same time, the algorithm is considered to have converged and the iteration is stopped: ， ， in, is the preset convergence threshold; After iterative optimization, the base station finally calculates the preliminary resource allocation plan for each user, which is the spectrum resource allocation for user i. and power resource allocation .

7. The base station resource management method according to claim 6, characterized in that: Each user adjusts its power strategy to maximize its utility function according to the initially allocated spectrum and power, including: Transmission rate of user equipment It is given by the following formula: ， in: B i is the bandwidth of user i; h i Is a user The channel gain P i is the transmit power of user i; is the background noise power; represents the interference of other users to user i; The user equipment adjusts its current channel gain and interference levels , adjust the transmission power P i To maximize its utility function: ， In each adjustment step, the user equipment gradually increases or decreases the transmission power to find the optimal power strategy P i , to improve the channel capacity and maximize the utility function.

8. The base station resource management method according to claim 7, characterized in that: The base station updates the resource allocation strategy of the user through feedback interaction with the user, including: The base station evaluates the current spectrum resource allocation based on the information fed back by the users, and readjusts the spectrum resources S allocated to each user based on the network load and interference. i ; The base station analyzes the interference and channel status of the user equipment and further optimizes the power P allocated to each user. i , ensuring that the transmission rate of all users is improved; The base station makes each user's utility function Keep approaching its optimal value.

9. The base station resource management method according to claim 8, characterized in that: After multiple adjustments, the system reaches Nash equilibrium, and the resource allocation plan for each user is finally determined to include: After multiple interactions and adjustments between the base station and the user equipment, the system gradually approaches the Nash equilibrium state. Under the Nash equilibrium, the resource allocation schemes of all users are optimal, that is, any user cannot further improve his utility function by adjusting his power or spectrum resources without changing the resource allocation of other users. The Nash equilibrium condition is described as: ， in, and They represent the optimal spectrum resources and power allocation of user i in the equilibrium state, respectively, and and are other allocation strategies that user i may choose; When the system reaches Nash equilibrium, the base station determines the final resource allocation plan for each user, including spectrum resources and power resources.

10. A base station resource management system, characterized in that: The system includes the following modules: The acquisition module is used by the base station to collect the service requirements and network load information of user equipment in real time; A construction module, used to construct an optimization objective function for base station resource allocation, where the optimization objective function is based on maximizing a user's utility function and is subject to constraints of spectrum resources and power resources; An optimization module, used to introduce Lagrangian multipliers and construct Lagrangian functions according to spectrum resource constraints and power resource constraints; A second optimization module is used to calculate a preliminary resource allocation scheme for each user, including spectrum resource allocation and power resource allocation of the user, by iteratively optimizing Lagrange multipliers; An allocation module, for each user to adjust its power strategy to maximize its utility function according to the initially allocated spectrum and power; A feedback module, used for the base station to update the user's resource allocation strategy through feedback interaction with the user; The adjustment module is used to achieve Nash equilibrium in the system after multiple adjustments and finally determine the resource allocation plan for each user.

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