Adaptive PLC network resource allocation method, device and storage medium

Abstract

The present application discloses a method, device and storage medium for allocating adaptive PLC network resources. The method includes: obtaining queue status information, channel status information and data arrival rate of the PLC network; using the Lyapunov optimization method to perform queue stability constraints according to the queue status information, and obtaining flow splitting decisions and joint power subcarrier allocation decisions, wherein the queue stability constraints are used to maximize the utility of the PLC network; solving the flow splitting decision according to the data arrival rate, and solving the joint power subcarrier allocation decision according to the channel status information, to achieve the allocation of PLC network resources. The method allocates subcarriers and power based on the current channel status information, and designs a trade-off mechanism between PLC network utility and PLC network delay, thereby achieving a compromise between PLC network delay and PLC network utility and improving the energy efficiency of the PLC network.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to an adaptive PLC network resource allocation method, device and storage medium. Background Art

[0002] PLC (Power Line Communication) broadband access technology has become one of the most competitive technologies for solving the "last 1 km" problem of broadband networks due to its unique advantages. For PLC communication systems, its modulation technology depends on the characteristics of the communication medium. In addition to controlling the implementation cost, the modulation technology applied to PLC communication systems must also overcome unfavorable factors in the channel, such as nonlinear characteristics. For this reason, OFDM (Orthogonal Frequency Division Multiplexing) technology is proposed in related technologies.

[0003] OFDM is an orthogonal multi-carrier modulation method. The main idea is to divide a given channel into several orthogonal sub-channels in the frequency domain, allocate and modulate one sub-channel to each sub-channel, and transmit each sub-channel in parallel. Therefore, although the entire channel may be uneven and frequency selective, each sub-channel is relatively flat and narrowband transmission occurs on each sub-channel. Moreover, since the signal bandwidth is much smaller than the corresponding bandwidth of the channel, the interference between signal waveforms can be greatly eliminated. However, with the development of PLC technology, limited spectrum resources seem to be increasingly scarce. Therefore, how to improve the efficiency of spectrum utilization and solve the problem of insufficient spectrum resources has become a hot topic of research. Summary of the invention

[0004] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, the first purpose of this application is to propose an adaptive PLC network resource allocation method. The method allocates subcarriers and power based on current channel state information, designs a trade-off mechanism between PLC network utility and PLC network delay, achieves a compromise between PLC network delay and PLC network utility, and improves the working efficiency of the PLC network.

[0006] A second object of the present application is to provide a computer-readable storage medium.

[0007] The third objective of the present application is to provide an adaptive PLC network resource allocation device.

[0008] To achieve the above-mentioned purpose, the adaptive PLC network resource allocation method proposed in the first aspect embodiment of the present application includes obtaining queue status information, channel status information and data arrival rate of the PLC network; using the Lyapunov optimization method to perform queue stability constraints according to the queue status information, and obtaining flow splitting decisions and joint power subcarrier allocation decisions, wherein the queue stability constraints are used to maximize the utility of the PLC network; solving the flow splitting decision according to the data arrival rate, and solving the joint power subcarrier allocation decision according to the channel status information, so as to realize the allocation of the PLC network resources.

[0009] According to the adaptive PLC network resource allocation method of this embodiment, the network traffic management subcarrier and power allocation decision are adjusted in each time slot according to the current network status information. By introducing the weighted device transmission rate and the difference in total network energy consumption as the network utility, a virtual queue is established to characterize the network delay. The Lyapunov optimization method is used to achieve a compromise between PLC network delay and PLC network utility.

[0010] To achieve the above-mentioned purpose, a computer-readable storage medium is proposed in the second aspect of the present application, on which a computer program is stored. When the computer program is executed by a processor, the adaptive PLC network resource allocation method described in the first aspect of the present application is implemented.

[0011] To achieve the above-mentioned purpose, the adaptive PLC network resource allocation device proposed in the third aspect embodiment of the present application includes: an acquisition module, used to obtain queue status information, channel status information and data arrival rate of the PLC network; an optimization module, used to use the Lyapunov optimization method to perform queue stability constraints according to the queue status information, and obtain flow splitting decisions and joint power subcarrier allocation decisions, wherein the queue stability constraints are used to maximize the utility of the PLC network; a calculation module, used to solve the flow splitting decision according to the data arrival rate, and solve the joint power subcarrier allocation decision according to the channel status information, to obtain the allocation result of the PLC network resources.

[0012] According to the adaptive PLC network resource allocation device of this embodiment, the network traffic management subcarrier and power allocation decision are adjusted in each time slot according to the current network status information. By introducing the weighted device transmission rate and the difference in total network energy consumption as the network utility, a virtual queue is established to characterize the network delay. The Lyapunov optimization method is used to achieve a compromise between PLC network delay and PLC network utility.

[0013] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0015] Figure 1 is a flow chart of a method for allocating adaptive PLC network resources according to an embodiment of the present application;

[0016] Figure 2 It is a structural diagram of an adaptive PLC network resource allocation device according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0018] The following describes the adaptive PLC network resource allocation method, device and storage medium according to the embodiments of the present application with reference to the accompanying drawings.

[0019] Figure 1 It is a flow chart of a method for allocating adaptive PLC network resources according to an embodiment of the present application.

[0020] like Figure 1 As shown, the adaptive PLC network resource allocation method may include:

[0021] S110, obtaining queue status information, channel status information and data arrival rate of the PLC network.

[0022] Among them, the queue status information of the PLC network indicates the queue occupancy of the PLC network; the channel status information indicates the information of the signal in the process of sending and receiving, including the influence of distance, scattering, fading, etc. on the signal; the data arrival rate is the data transmission rate when the data is received, and the data arrival rate is not constant due to factors such as the network environment.

[0023] Exemplarily, queue status information, channel status information and data arrival rate of each time slot may be obtained through a base station in a centralized management manner.

[0024] It is understandable that, affected by factors such as the network environment and signal-to-noise ratio, the queue status information, channel status information and data arrival rate change in real time. The queue status information, channel status information and data arrival rate are different in different time slots. The queue status information, channel status information and data arrival rate of each time slot can be obtained in real time.

[0025] S120, using a Lyapunov optimization method to perform queue stability constraints according to queue state information, to obtain a flow splitting decision and a joint power subcarrier allocation decision, wherein the queue stability constraint is used to maximize the utility of the PLC network.

[0026] Specifically, in this embodiment, queue stability is used as a constraint condition, under which the utility of the PLC network is maximized. According to the Lyapunov optimization method, the resource allocation problem is transformed into two problems: one is the flow splitting decision problem, and the other is the joint power subcarrier allocation decision problem.

[0027] It can be understood that, in this embodiment, queue stability is used as a constraint condition to maximize the utility of the PLC network and solve the flow splitting decision problem and the joint power subcarrier allocation decision problem.

[0028] S130, solving the flow splitting decision according to the data arrival rate, and solving the joint power subcarrier allocation decision according to the channel state information, so as to realize the allocation of PLC network resources.

[0029] Exemplarily, the allocation of PLC network resources can be achieved by solving the stream splitting decision according to the data arrival rate through an optimization algorithm, and solving the joint power subcarrier allocation decision according to the channel state information.

[0030] As an example, the utility of a PLC network is expressed by the following equation (1):

[0031]

[0032] Among them, F PLC (t) represents the utility of the PLC network in time slot t, Indicates the number of subcarriers, m l Represents a device set with service type l. Indicates the number of devices on subcarrier n, Indicates device m on subcarrier n l The weight of Indicates that device m is on subcarrier n in time slot t l The enqueue rate is, c represents the price per unit transmission power, represents device m on subcarrier n in time slot t l The allocation indicator variable, Indicates that device m is on subcarrier n in time slot t l of transmission power.

[0033] Specifically, Represents the set of all subcarriers. For one subcarrier n, it can be Device services, is the set of all devices on subcarrier n, m l Represents a set of devices with service type l, where service type l provides a certain stream for the device, for example, service type 1 provides video stream and service type 2 provides voice stream. If all service types have M types, the set of subcarriers that can be obtained is

[0034] Understandably, represents the weighted device transmission rate, represents the total energy consumption of the network, F PLC (t)The utility of a PLC network can be expressed as the difference between the weighted device transmission rate and the total energy consumption of the network.

[0035] As an example, when the Lyapunov optimization method is used to perform queue stability constraints according to queue state information, the following optimization function is obtained as shown in formula (2):

[0036]

[0037] Where V represents the Lyapunov control parameter, which is a non-negative system control parameter, γ(t) represents the dequeue rate information of the PLC network in time slot t, and γ(t) H represents the transpose of γ(t), r(t) represents the queue rate information of the PLC network in time slot t, r(t) H represents the transpose of r(t), Q(t) represents the queue status information of the PLC network in time slot t, Indicates that device m is on subcarrier n in time slot t l The dequeue rate, Indicates that device m is on subcarrier n in time slot t l The queue status information.

[0038] Specifically, we construct the Lyapunov optimization L(Q(t)), define the sum of the squares of all queues in each time slot as the Lyapunov function L(Q(t)), and L(Q(t)) is used to measure the scalar of network congestion. If L(Q(t)) is small, then all queues are small. If L(Q(t)) is large, then at least one queue is large. It can be expressed as According to the functional framework of the Lyapunov optimization method, the drift penalty of the system utility can be expressed as Where E represents the average value operation of the time slot, satisfying Where D is a finite constant. Then the above problem is mapped to the optimization function in equation (2).

[0039] As a feasible implementation method, the optimization function of equation (2) above can be converted into solving two independent sub-problems, respectively solving and That is, the joint power subcarrier allocation subproblem and the stream splitting subproblem are solved separately.

[0040] It should be noted that, according to the architecture of the Lyapunov optimization function and the drift penalty of the PLC network utility, the original problem can be converted into the optimization function of formula (2) under the condition of ensuring the queue stability constraint.

[0041] As an example, the flow splitting decision can be solved by the following formula (3):

[0042]

[0043] in, Indicates time slot t device m l The data flow arrival rate is express The value of n when the value of is minimum.

[0044] As an example, the joint power subcarrier allocation decision is solved by the following equation (4):

[0045]

[0046] Among them, ρ l Indicates device m l C3 ensures that the mutual interference between devices sharing the same channel does not exceed the predefined threshold IT max , g n,min express.

[0047] It should be noted that due to the deployment of cognitive radio technology, different devices can transmit simultaneously on the same subchannel. In order to ensure that the mutual interference between them does not exceed the predefined threshold, the constraint C3 is used to meet the interference limit of each subchannel of the cognitive radio transmission device, where g n,min Indicates the channel gain of the two nearest neighboring devices.

[0048] As an example, solving the joint power subcarrier allocation decision may include:

[0049] 1) Relax the integer variable and assign the subcarrier assignment indicator variable Relax to the continuous interval [0,1] and let

[0050] 2) Establish Lagrange function and introduce dual multiplier and Corresponding to C1 and C3 respectively, we get the dual function Among them, M and N represent the number of devices and the number of subcarriers respectively, and s represents x represents a subcarrier allocation indicator variable.

[0051] 3) Use KKT conditions to solve the optimal continuous variable. Bring in Get the objective function According to the objective function, the subcarrier allocation is Power distribution is in, represents the calculation parameters, Indicates that the optimization variable is x;

[0052] in, represents the maximum predefined threshold for mutual interference between devices on subcarrier n, It can be obtained according to the following formula (5):

[0053]

[0054] Among them, ε n It represents the utility (effective proportion) corresponding to subcarrier n, and B represents the subcarrier bandwidth of the PLC network.

[0055] 4) Update the dual multiplier according to the gradient descent algorithm, and feed the updated dual multiplier back to the Lagrange function.

[0056] Specifically, according to the subcarrier allocation indicator variable Relax to the continuous interval [0,1] and let The discrete variables in the joint power subcarrier allocation problem can be eliminated. The Lagrange function is established and the dual multiplier is introduced to transform the joint power subcarrier allocation decision into a function about the dual multiplier. First, the dual multiplier μ and Fix and then optimize variables and Get subcarrier allocation and and then determine the dual multiplier.

[0057] For example, it can be obtained by taking the derivative of the Lagrange function The expression is

[0058] Then Bring in The objective function is obtained from express When the value of is positive, The calculation results are meaningful.

[0059] Furthermore, before updating the dual multiplier according to the gradient descent method, that is, at t = 0, the initial value of the dual multiplier is first given to obtain the original variable subcarrier allocation and power distribution When the next iteration is performed, that is, when t = 1 iteration, by and get Get the new Lagrange function and use the KKT condition to solve the corresponding and According to the above step 3), the dual multipliers μ and The value of further determines whether the Lagrange function meets the convergence condition. If the convergence condition is met, the subcarrier allocation in this time slot is achieved. and power distribution The value of is taken as the optimal solution. If the Lagrange function does not meet the convergence condition, continue according to and Further, we get μ and The value of μ and Feedback is given to the Lagrange function to continue to determine whether the Lagrange function meets the convergence conditions.

[0060] It should be noted that, in some embodiments, the network delay of the PLC network is proportional to the Lyapunov control parameter, and the network utility of the PLC network is inversely proportional to the Lyapunov control parameter.

[0061] For example, when the Lyapunov control parameter increases, the network delay of the PLC network will also increase, and the network utility of the PLC network will decrease. By selecting appropriate Lyapunov control parameters, a trade-off between the network utility of the PLC network and the network delay of the PLC network can be achieved.

[0062] According to the adaptive PLC network resource allocation method of this embodiment, the network traffic management subcarrier and power allocation decision are adjusted in each time slot according to the current network status information. By introducing the weighted device transmission rate and the difference in total network energy consumption as the network utility, a virtual queue is established to characterize the network delay. The Lyapunov optimization method is used to achieve a compromise between the PLC network delay and the PLC network utility.

[0063] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the adaptive PLC network resource allocation method described in any of the above embodiments of the present application is implemented.

[0064] Based on the same inventive concept as the adaptive PLC network resource allocation method of the above embodiment, the present application also proposes an adaptive PLC network resource allocation device.

[0065] Figure 2 Schematic diagram of the structure of the adaptive PLC network resource allocation device of the embodiment of the present application. Figure 2 As shown, the adaptive PLC network resource allocation device 100 includes: an acquisition module 10, an optimization module 20 and a calculation module 30.

[0066] Among them, the acquisition module 10 is used to obtain the queue state information, channel state information and data arrival rate of the PLC network; the optimization module 20 is used to use the Lyapunov optimization method to perform queue stability constraints according to the queue state information, and obtain the flow splitting decision and the joint power subcarrier allocation decision, wherein the queue stability constraint is used to maximize the utility of the PLC network; the calculation module 30 is used to solve the flow splitting decision according to the data arrival rate, and solve the joint power subcarrier allocation decision according to the channel state information, and obtain the allocation result of the PLC network resources.

[0067] Exemplarily, the acquisition module 10 can obtain the queue state information, channel state information and data arrival rate of each time slot in real time. The acquisition module 10 can also obtain the queue state information, channel state information and data arrival rate of each time slot through the base station in a centralized management manner.

[0068] Further, according to the above embodiment of the present application, the adaptive PLC network resource allocation device, wherein the utility of the PLC network is expressed by the following formula (6):

[0069]

[0070] Among them, F PLC (t) represents the utility of the PLC network in time slot t, N represents the number of subcarriers, M n Indicates the number of devices on subcarrier n, Indicates device m on subcarrier n l The weight of Indicates that device m is on subcarrier n in time slot t l The enqueue rate is, c represents the price per unit transmission power, represents device m on subcarrier n in time slot t l The allocation indicator variable, Indicates that device m is on subcarrier n in time slot t l of transmission power.

[0071] According to the adaptive PLC network resource allocation device of this embodiment, the network traffic management subcarrier and power allocation decision are adjusted in each time slot according to the current network status information. By introducing the weighted device transmission rate and the difference in total network energy consumption as the network utility, a virtual queue is established to characterize the network delay, and the Lyapunov optimization method is used to achieve a compromise between PLC network delay and PLC network utility.

[0072] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0073] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0074] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0075] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0076] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0077] In this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0078] In the present application, unless otherwise clearly specified and limited, a first feature being “above” or “below” a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being “above”, “above”, and “above” a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being “below”, “below”, and “below” a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0079] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for allocating adaptive PLC network resources, characterized in that: The method comprises: Obtain queue status information, channel status information and data arrival rate of the PLC network; Using a Lyapunov optimization method to perform queue stability constraints according to the queue state information, a flow splitting decision and a joint power subcarrier allocation decision are obtained, wherein the queue stability constraints are used to maximize the utility of the PLC network; Solving the stream splitting decision according to the data arrival rate, and solving the joint power subcarrier allocation decision according to the channel state information, so as to realize the allocation of the PLC network resources; The flow splitting decision is solved by the following formula: in, Indicates the number of subcarriers, m l Represents a device set with service type l. Indicates the number of devices on subcarrier n, Indicates that device m is on subcarrier n in time slot t l The queue status information, Indicates that device m is on subcarrier n in time slot t l The dequeue rate, Indicates time slot t device m l The data flow arrival rate; The optimal flow splitting decision is obtained as in The joint power subcarrier allocation decision is solved by the following equation: Where V represents the Lyapunov control parameter, Indicates device m on subcarrier n l The weight of Indicates that device m is on subcarrier n in time slot t l The enqueue rate is, c represents the price per unit transmission power, represents device m on subcarrier n in time slot t l The allocation indicator variable, Indicates that device m is on subcarrier n in time slot t l The transmission power, ρ l Indicates device m l C3 ensures that the mutual interference between devices sharing the same channel does not exceed the predefined threshold IT max , g n,min Indicates that g n,min Indicates the channel gain of the two nearest neighboring devices.

2. The method for allocating adaptive PLC network resources according to claim 1, characterized in that: The utility of the PLC network is expressed by the following equation: Among them, F PLC (t) represents the utility of the PLC network at time slot t.

3. The method for allocating adaptive PLC network resources according to claim 2, characterized in that: When the Lyapunov optimization method is used to perform queue stability constraints according to the queue state information, the following optimization function is obtained: Where V represents the Lyapunov control parameter, γ(t) represents the dequeue rate information of the PLC network at time slot t, and γ(t) H represents the transpose of γ(t), r(t) represents the queue rate information of the PLC network at time slot t, r(t) H represents the transpose of r(t), and Q(t) represents the queue status information of the PLC network at time slot t.

4. The method for allocating adaptive PLC network resources according to claim 1, characterized in that: Solving the joint power subcarrier allocation decision includes: Relax integer variable, subcarrier allocation indicator variable Relax to the continuous interval [0,1] and let Establish Lagrange function and introduce dual multiplier and Corresponding to C1 and C3 respectively, we get the dual function Where M and N represent the number of devices and subcarriers respectively, and s represents x represents a subcarrier allocation indicator variable; Using KKT conditions to solve the optimal continuous variable, Bring in Get the objective function And according to the objective function, the subcarrier allocation is obtained as Power distribution is in, is the calculation parameter, Indicates that the optimization variable is x; The dual multiplier is updated according to a gradient descent algorithm, and the updated dual multiplier is fed back to the Lagrange function.

5. The method for allocating adaptive PLC network resources according to claim 3, characterized in that: The network delay of the PLC network is proportional to the Lyapunov control parameter, and the network utility of the PLC network is inversely proportional to the Lyapunov control parameter.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for allocating adaptive PLC network resources as described in any one of claims 1 to 5 is implemented.

7. An adaptive PLC network resource allocation device, characterized in that: The device comprises: An acquisition module, used to obtain queue status information, channel status information and data arrival rate of the PLC network; An optimization module, configured to perform queue stability constraints according to the queue state information using a Lyapunov optimization method, and obtain a flow splitting decision and a joint power subcarrier allocation decision, wherein the queue stability constraints are used to maximize the utility of the PLC network; A calculation module, used to solve the stream splitting decision according to the data arrival rate, and solve the joint power subcarrier allocation decision according to the channel state information, to obtain an allocation result of the PLC network resources; The flow splitting decision is solved by the following formula: in, Indicates the number of subcarriers, m l Represents a device set with service type l. Indicates the number of devices on subcarrier n, Indicates that device m is on subcarrier n in time slot t l The queue status information, Indicates that device m is on subcarrier n in time slot t l The dequeue rate, Indicates time slot t device m l The data flow arrival rate; The optimal flow splitting decision is obtained as in The joint power subcarrier allocation decision is solved by the following equation: Where V represents the Lyapunov control parameter, Indicates device m on subcarrier n l The weight of Indicates that device m is on subcarrier n in time slot t l The enqueue rate is, c represents the price per unit transmission power, represents device m on subcarrier n in time slot t l The allocation indicator variable, Indicates that device m is on subcarrier n in time slot t l The transmission power, ρ l Indicates device m l C3 ensures that the mutual interference between devices sharing the same channel does not exceed the predefined threshold IT max , g n,min Indicates that g n,min Indicates the channel gain of the two nearest neighboring devices.

8. The adaptive PLC network resource allocation device according to claim 7, characterized in that: The utility of the PLC network is expressed by the following equation: Among them, F PLC (t) represents the utility of the PLC network at time slot t.

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