Hybrid PLC and wireless communication transmission design method, system, equipment and medium

Abstract

The invention discloses a hybrid PLC and wireless communication transmission design method, system and device and a medium. The method comprises the steps that a double-link communication system between a data concentrator and an electric energy meter is established; the method comprises the following steps: establishing a joint optimization model for a double-link communication system, and decomposing the joint optimization model into a subcarrier allocation problem and a power allocation problem; and solving the subcarrier allocation problem and the power allocation problem. According to the method, a subcarrier allocation problem is modeled into a multi-arm bandit problem, and the problem is solved by utilizing an iterative upper confidence bound strategy, so that the problem that complete channel estimation needs to be carried out on all subcarriers in a traditional method is avoided, and the pilot frequency overhead is reduced. According to the method, the channel information can be learned from the historical data, intelligent subcarrier distribution is realized, and the signaling burden and the calculation complexity are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of electricity consumption information collection, and in particular to a hybrid PLC and wireless communication transmission design method, system, equipment and medium. Background Art

[0002] In recent years, with the explosive demand for communication transmission speeds, communication systems using different media have been widely studied. In areas such as electricity consumption information collection, wireless communication and power line communication (PLC) have attracted widespread attention as two effective communication media.

[0003] However, both wireless and power line communication have their own shortcomings. Wireless communication is susceptible to environmental interference and signal fading, while power line communication faces noise interference and frequency-selective fading. To further improve communication performance, hybrid dual-mode communication combining wireless and power line communication can effectively compensate for their respective shortcomings, thereby improving overall system performance.

[0004] In hybrid communication systems, channel state information (CSI) can be obtained through channel estimation. CSI is required for designing precoding and combining procedures at the transmitter and receiver. Traditional channel estimation methods require complete channel estimation for all subcarriers, which results in high pilot overhead and reduces the system's spectral efficiency. Summary of the Invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a hybrid PLC and wireless communication transmission design method, system, device and medium to solve the problems of high computational complexity of subcarrier allocation and power allocation, large pilot overhead and low system spectrum efficiency in the prior art.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a hybrid PLC and wireless communication transmission design method, comprising:

[0009] Establish a dual-link communication system between the data concentrator and the energy meter;

[0010] Establishing a joint optimization model for a dual-link communication system, and decomposing the joint optimization model into a subcarrier allocation problem and a power allocation problem;

[0011] The subcarrier allocation problem and the power allocation problem are solved.

[0012] As a preferred solution of the hybrid PLC and wireless communication transmission design method of the present invention, wherein: the dual-link communication system includes a power line communication link and a wireless communication link;

[0013] Among them, both the power line communication link and the wireless communication link adopt orthogonal frequency division multiplexing modulation;

[0014] The number of subcarriers of the power line communication link is less than the number of subcarriers of the wireless communication link;

[0015] The data concentrator acts as a transmitter and sends signals to the electric energy meter through two links at the same time.

[0016] The beneficial effects of this preferred technical solution are: clarifying the specific composition and modulation method of the dual-link system, and ensuring the compatibility of the power line communication link and the wireless communication link.

[0017] As a preferred solution of the hybrid PLC and wireless communication transmission design method of the present invention, the step of establishing the joint optimization model includes:

[0018] The electric energy meter serves as a receiving end to receive signals;

[0019] At the receiving end, the signals from the two links are combined and processed, and a joint optimization model is constructed with the goal of maximizing the system spectrum efficiency, subject to the total power constraints and the minimum spectrum efficiency of each subcarrier.

[0020] The beneficial effects of this preferred technical solution are: building a system-level joint optimization framework that can uniformly consider spectrum efficiency, power constraints and service quality requirements, and fully utilizing the diversity gain of dual links through signal merging processing.

[0021] As a preferred solution of the hybrid PLC and wireless communication transmission design method of the present invention, the step of decomposing the joint optimization model into a subcarrier allocation problem and a power allocation problem includes:

[0022] By matching the subcarriers of each power line communication link with the optimal subcarrier of the wireless communication link, a subcarrier allocation problem is formed;

[0023] The power allocation problem is formulated by determining the power of all subcarriers.

[0024] The beneficial effects of this preferred technical solution are: decomposing the complex joint optimization problem into two relatively independent sub-problems, reducing the computational complexity, and realizing the coordinated operation of the power line communication link and the wireless communication link through the subcarrier matching strategy.

[0025] As a preferred solution of the hybrid PLC and wireless communication transmission design method of the present invention, the steps of solving the subcarrier allocation problem include:

[0026] Model the subcarrier allocation problem as a multi-armed bandit problem;

[0027] Taking the wireless communication link subcarrier wave as the arm and the subcarrier channel energy as the reward, an iterative upper confidence bound strategy is adopted to obtain the optimal wireless communication link subcarrier corresponding to each power line communication link subcarrier.

[0028] The beneficial effects of this preferred technical solution are: introducing a multi-armed bandit model to avoid the high computational complexity of traditional exhaustive search, using historical channel information for intelligent decision-making, eliminating the need for complete channel estimation for all subcarriers, and reducing pilot overhead.

[0029] As a preferred solution of the hybrid PLC and wireless communication transmission design method of the present invention, wherein: the iterative upper confidence bound strategy selects the optimal subcarrier by calculating the upper confidence bound value of the wireless communication link subcarrier;

[0030] The calculation formula of the upper confidence limit is:

[0031]

[0032] Where u k (t) is the upper confidence bound of subcarrier k in t time slots, which is used to evaluate and select the optimal subcarrier; c x is the confidence adjustment factor; is the empirical average channel gain of subcarrier k in the tth time slot; m k,t is the cumulative number of times subcarrier k is selected up to the tth time slot, is the standard confidence interval based on time; are the confidence intervals adjusted to account for the total number of arms.

[0033] The beneficial effects of this preferred technical solution are: the optimal balance between exploration and utilization is achieved through the upper confidence bound strategy, which can fully utilize known good subcarriers and explore unknown potential high-quality subcarriers. The piecewise function design ensures that each subcarrier has a chance to be selected, avoiding the problem of some subcarriers never being explored.

[0034] As a preferred solution of the hybrid PLC and wireless communication transmission design method of the present invention, the steps of solving the power allocation problem include:

[0035] After determining the allocation relationship between the subcarriers of the power line communication link and the subcarriers of the wireless communication link, estimating the channel of each subcarrier;

[0036] Formulate a power allocation optimization problem with the goal of maximizing the system spectrum efficiency, subject to the total power constraint and the minimum spectrum efficiency of each subcarrier;

[0037] The power allocation optimization problem is solved by using a convex optimization method to obtain the optimal power allocation for each subcarrier.

[0038] The beneficial effects of this preferred technical solution are: the use of a convex optimization method ensures a global optimal solution for power allocation, avoiding the problem that the heuristic algorithm may fall into a local optimum.

[0039] In a second aspect, the present invention provides a hybrid PLC and wireless communication transmission design system, comprising a dual-link communication system module, a joint optimization model establishment module, and a sub-problem solving module;

[0040] The dual-link communication system module is used to build a physical communication link;

[0041] The joint optimization model establishment module establishes a joint optimization model according to the performance requirements of the dual-link communication system;

[0042] The sub-problem solving module solves the decomposed sub-carrier allocation problem and power allocation problem.

[0043] In a third aspect, the present invention provides an electronic device, comprising:

[0044] memory and processor;

[0045] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the hybrid PLC and wireless communication transmission design method are implemented.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the hybrid PLC and wireless communication transmission design method.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] By modeling the subcarrier allocation problem as a multi-armed bandit problem and solving it using an iterative upper confidence bound strategy, this approach avoids the traditional requirement of complete channel estimation for all subcarriers and reduces pilot overhead. This approach can learn channel information from historical data, enabling intelligent subcarrier allocation and reducing signaling overhead and computational complexity.

[0049] The dual-reset confidence interval design effectively balances exploration and utilization, fully utilizing known high-performing subcarriers while exploring unknown, potentially high-quality subcarriers, thus preventing the algorithm from falling into local optimal solutions. The piecewise function design ensures that every subcarrier has a chance to be selected, improving the fairness and efficiency of system resource utilization.

[0050] Decomposing the complex joint optimization problem into two relatively independent subproblems—subcarrier allocation and power allocation—significantly reduces computational complexity, enabling the algorithm to be quickly solved in practical applications. The power allocation phase employs a convex optimization method, ensuring a globally optimal solution and avoiding the performance penalties associated with heuristic algorithms. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 any creative work.

[0052] Figure 1 The figure is a schematic diagram of the overall process of a hybrid PLC and wireless communication transmission design method according to an embodiment of the present invention.

[0053] Figure 2 A schematic diagram of the system framework of a hybrid PLC and wireless communication transmission design method according to an embodiment of the present invention.

[0054] Figure 3 The performance comparison of the method of the present invention and other methods for different signal-to-noise ratios is shown.

[0055] Figure 4 The performance comparison between the method of the present invention and other methods for different numbers of wireless subcarriers is shown. DETAILED DESCRIPTION

[0056] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0057] Example 1, reference Figures 1 and 2 , as an embodiment of the present invention, provides a hybrid PLC and wireless communication transmission design method, including steps S1 to S3:

[0058] S1. Establish a dual-link communication system between the data concentrator and the electricity meter.

[0059] S2. Establish a joint optimization model for the dual-link communication system, and decompose the joint optimization model into a subcarrier allocation problem and a power allocation problem.

[0060] S3. Solve the subcarrier allocation problem and the power allocation problem.

[0061] It should be noted that in electricity consumption information collection, communication between the data concentrator and the energy meter faces challenges such as long transmission distances, complex environments, and high reliability requirements. Traditional single communication methods often cannot meet these requirements. Wireless communication is susceptible to environmental interference and signal fading, while power line communication faces noise interference and frequency-selective fading. Therefore, through steps S1-S3, a hybrid dual-link communication system is constructed, fully leveraging the advantages of power line communication and wireless communication. Through intelligent subcarrier allocation and power allocation strategies, efficient resource utilization and reliable data transmission are achieved, significantly improving overall spectrum efficiency and transmission reliability.

[0062] In an embodiment of the present application, a dual-link communication system is established between the data concentrator and the electric energy meter in step S1, and dual-path transmission is achieved by constructing a power line communication link and a wireless communication link. Both links adopt orthogonal frequency division multiplexing modulation, wherein the number of subcarriers of the power line communication link is less than the number of subcarriers of the wireless communication link. The data concentrator acts as a transmitter and sends signals to the electric energy meter through the two links at the same time.

[0063] In an optional embodiment, the dual-link communication system established in step S1 can also dynamically adjust the subcarrier configuration according to the actual deployment environment, and optimize the ratio of the number of subcarriers of the power line communication link and the wireless communication link through an adaptive algorithm to adapt to different channel environments and transmission requirements.

[0064] In another optional implementation, the dual-link communication system in step S1 may also introduce a link quality monitoring mechanism to evaluate the transmission performance of each link in real time and dynamically switch the primary transmission link according to the channel status to ensure the continuity and reliability of communication.

[0065] Example 2, reference Figures 1 to 4 , which is an embodiment of the present invention, provides a hybrid PLC and wireless communication transmission design method based on the above embodiment.

[0066] In the embodiment of the present application, in step S1, the dual-link communication system includes a power line communication link and a wireless communication link;

[0067] Among them, both the power line communication link and the wireless communication link adopt orthogonal frequency division multiplexing modulation; the number of subcarriers in the power line communication link is smaller than the number of subcarriers in the wireless communication link; the data concentrator acts as a transmitting end and sends signals to the electric energy meter through two links at the same time.

[0068] In step S1, establishing a dual-link communication system includes the following steps A1-A2:

[0069] A1. Establish a wireless channel model. The received signal on the s-th subcarrier in the t-th time slot is:

[0070]

[0071] Among them, x s,t Refers to the transmitted signal on the sth subcarrier in the tth time slot, n s,t Refers to the noise received by the tth sth subcarrier, and the noise energy is h s,t The channel gain of the sth subcarrier has a mean of 0 and a variance of Gaussian distribution, p 1,s,t is the power of the transmitted signal on subcarrier s in the wireless link.

[0072] A2. Establish PLC channel model:

[0073] Among them, x k,t is the transmitted symbol on subcarrier k after conversion in PLC, r k,t is the received signal on subcarrier k in PLC, λ k,t is the channel on the PLC link subcarrier k, p 2,k,t is the power of the transmitted signal on subcarrier k in PLC, w k,t is the noise on subcarrier k.

[0074] In this embodiment, in step S2, the steps of the joint optimization model include B1 to B2:

[0075] B1, the electric energy meter serves as a receiving end to receive signals;

[0076] B2. At the receiving end, the signals from the two links are combined and processed to construct a joint optimization model with the goal of maximizing spectrum efficiency, subject to the total power constraint and the minimum spectrum efficiency constraint of each subcarrier.

[0077] In the embodiment of the present application, in step B1, the electric energy meter as a receiving end receives signals including simultaneously receiving signals from the power line communication link and the wireless communication link, thereby improving the reliability and anti-interference capability of signal reception through the dual-path receiving mechanism.

[0078] In the embodiment of the present application, the step B2 of combining the signals from the two links at the receiving end includes the following steps B2.1 to B2.3:

[0079] B2.1. Process the two received signals using the maximum ratio combining algorithm;

[0080] B2.2. Calculate the spectral efficiency of the combined signal;

[0081] B2.3. Construct the optimization problem of maximizing system spectrum efficiency under the condition of limited system total energy.

[0082] Specifically, in step B2.1, the implementation process of the maximum ratio combining algorithm is as follows: at the same time is the received signal on subcarrier k in PLC, through maximum ratio combining, x k,t Estimated to be:

[0083]

[0084] in, is a vector containing the channel gains of the two links, is a vector containing the received signals of the two links.

[0085] Specifically, in step B2.2, the maximum ratio combining algorithm is used to combine the signal x k,t The spectral efficiency can be calculated as:

[0086]

[0087] and are the noise power of radio link subcarrier s and the noise power of PLC link subcarrier k respectively;

[0088] The total spectrum efficiency of the system is Where T is the total number of time slots and K is the total number of PLC subcarriers.

[0089] Specifically, in step S2.3, the total energy of the system is limited, that is, the power on all subcarriers meets The problem of maximizing the system spectral efficiency while constraining the spectral efficiency of each subcarrier can be described as:

[0090]

[0091] Where P is the total power, R min is the minimum spectral efficiency for each subcarrier.

[0092] It should be noted that the maximum ratio combining algorithm effectively utilizes the diversity gain of the two links by weightedly combining the received signals, improving the signal-to-noise ratio of the combined signal. The algorithm automatically assigns combining weights based on the channel gain of each link, giving links with better channel quality a greater weight, thereby maximizing the quality of the combined signal.

[0093] In an optional implementation, the signal merging process in step B2 may also adopt a selective merging method, which compares the instantaneous channel qualities of the two links and selects the link with better channel conditions for data reception. This method is suitable for application scenarios with lower requirements for computational complexity.

[0094] In another optional implementation, the joint optimization model in step B2 may also introduce a transmission delay constraint, and simultaneously consider maximizing spectrum efficiency and minimizing delay through a multi-objective optimization framework, which is suitable for power consumption information collection applications with high real-time requirements.

[0095] In this embodiment, in step S2, decomposing the joint optimization model into the subcarrier allocation problem and the power allocation problem includes steps C1 to C2:

[0096] C1. Forming a subcarrier allocation problem by matching the optimal wireless communication link subcarrier to each power line communication link subcarrier;

[0097] Assume that the channel gain on the power line communication link satisfies represents the square of the channel gain of each subcarrier in the power line communication link, while the gain on the wireless link satisfies Represents the square of the channel gain of each subcarrier in the wireless communication link;

[0098] Defining a Collection The subcarrier set of the signal transmitted on the wireless link is selected as Ω t , and the subcarrier set of the signal transmitted on the power line communication link is selected as in

[0099]

[0100] Specifically, the purpose of channel gain sorting is to provide a basis for subsequent subcarrier matching. By sorting the subcarriers of the two links according to channel quality, the subcarriers with better channel conditions can be preferentially selected for pairing.

[0101] Assume x k The channel gain of the transmitted subcarrier is is the optimal channel gain squared when subcarrier k is transmitted, and the spectrum efficiency becomes:

[0102]

[0103] At this point, problem P1 is transformed into:

[0104]

[0105] Among them, R k is the transmit power of subcarrier k in time slot t, R min is the minimum power requirement for each subcarrier, and P3 is the converted subcarrier allocation optimization problem number.

[0106] It should be noted that the core of the subcarrier allocation problem is to find the most matching wireless communication link subcarrier for each power line communication link subcarrier. By comparing the channel gains of the corresponding subcarriers on the two links, the link with better channel quality is selected for data transmission, thereby maximizing the spectrum efficiency of this method.

[0107] C2. The power allocation problem is formed by determining the power of all subcarriers.

[0108] In the embodiment of the present application, forming the power allocation problem in step C2 includes constructing a power allocation optimization problem to determine the optimal transmission power of each subcarrier after determining the subcarrier allocation scheme.

[0109] Specifically, the power allocation problem in C2 can be expressed as:

[0110]

[0111] Among them, P k,t is the transmission power of subcarrier k in time slot t, P is the total power constraint, P k,min The minimum power requirement for each subcarrier.

[0112] In an optional implementation, the subcarrier allocation problem in step C1 may also consider interference constraints, and by introducing the effects of co-channel interference and adjacent-channel interference, a more accurate subcarrier matching model is established to improve actual performance.

[0113] In another optional implementation, the power allocation problem in step C2 may also adopt the idea of ​​a water filling algorithm, allocating power according to the channel gain of each subcarrier, allocating more power to subcarriers with good channel conditions, and achieving efficient utilization of power resources.

[0114] It should be noted that by decomposing the complex joint optimization problem into two relatively independent sub-problems, subcarrier allocation and power allocation, the computational difficulties of directly solving the high-dimensional non-convex optimization problem are avoided, significantly reducing the algorithmic complexity. The subcarrier allocation problem primarily addresses resource matching, while the power allocation problem primarily addresses resource allocation. This separation of the two makes the algorithm design more flexible and the solution more efficient.

[0115] In this embodiment, in step S3, the steps for solving the subcarrier allocation problem include S3.1.1 to S3.1.2:

[0116] S3.1.1. Model the subcarrier allocation problem as a multi-armed bandit problem;

[0117] The core idea of ​​modeling the multi-armed bandit problem is to transform the subcarrier selection problem into an online learning problem, learn the performance characteristics of each subcarrier through historical observation data, and avoid complete channel estimation for all subcarriers.

[0118] S3.1.2. Taking the wireless communication link subcarrier wave as the arm and the subcarrier channel energy as the reward, an iterative upper confidence bound strategy is used to obtain the optimal wireless communication link subcarrier corresponding to the subcarrier of each power line communication link.

[0119] The channel energy of each subcarrier is used as the reward obtained when the arm is selected, and the reward function is designed as the channel energy of the subcarrier|h s,t | 2 ,This design can directly reflect the transmission quality of the subcarrier.,Subcarriers with larger channel energy can provide higher,spectral efficiency.

[0120] The iterative upper confidence bound strategy selects the optimal subcarrier by calculating the upper confidence bound value of the wireless communication link subcarrier; the calculation formula of the upper confidence bound value is:

[0121]

[0122] Where u k (t) is the upper confidence bound of subcarrier k in t time slots, which is used to evaluate and select the optimal subcarrier; c x is the confidence adjustment factor; is the empirical average channel gain of subcarrier k in the tth time slot; m k,t is the cumulative number of times subcarrier k is selected up to the tth time slot, is the standard confidence interval based on time; are the confidence intervals adjusted to account for the total number of arms.

[0123] The algorithm flow of the upper confidence bound strategy includes the following steps D1 to D4:

[0124] D1. Initialize the number of selections m for all subcarriers k,0 = 0 and empirical average channel gain

[0125] D2. In each time slot t, calculate the upper confidence limit u of all wireless communication link subcarriers k (t);

[0126] D3. Select the subcarrier k with the largest upper confidence limit value. * =arg max k u k (t);

[0127] D4. Update the statistical information of the selected subcarrier: m k*,t+1 =m k*,t +1,

[0128] It should be noted that the double reset confidence interval design and The exploration intensity can be adaptively adjusted according to different system parameters. When the total number of subcarriers K is small, it is mainly Dominant; when K is larger, Provide stronger exploration incentives to ensure that the algorithm maintains good performance at different scales.

[0129] For example, assuming K = 128 wireless subcarriers, current time slot t = 50, and confidence adjustment factor c x =1.0:

[0130] For subcarrier i, m selected 20 times i,50 =20, empirical average channel gain h i (50) = 0.6:

[0131] Standard confidence interval:

[0132] Modified confidence interval:

[0133] Select the maximum value: max{1.58,10.09}=10.09;

[0134] Upper confidence bound: u i (50)=0.6+1.0×10.09=10.69.

[0135] In summary, by modeling the subcarrier allocation problem as a multi-armed bandit and solving it using an iterative upper confidence bound strategy, we avoid the traditional method's requirement for complete channel estimation for all subcarriers and reduce pilot overhead. This method can learn channel information from historical data, enabling intelligent subcarrier allocation and reducing signaling overhead and computational complexity.

[0136] The dual-reset confidence interval design effectively balances exploration and utilization, fully utilizing known high-performing subcarriers while exploring unknown, potentially high-quality subcarriers, thus preventing the algorithm from falling into local optimal solutions. The piecewise function design ensures that every subcarrier has a chance to be selected, improving both fair and efficient resource utilization.

[0137] Decomposing the complex joint optimization problem into two relatively independent subproblems—subcarrier allocation and power allocation—significantly reduces computational complexity, enabling the algorithm to be quickly solved in practical applications. The power allocation phase employs a convex optimization method, ensuring a globally optimal solution and avoiding the performance penalties associated with heuristic algorithms.

[0138] The present invention uses simulation to verify the effectiveness of the proposed method. The number of PLC subcarriers is set to 156. Figure 3 and Figure 4 The performance comparison of the proposed method with other methods is described. Figure 3 The number of wireless subcarrier data is 300. Figure 4 The transmission power is 5dBm. Simulation results show that the proposed method is superior to other methods.

[0139] exist Figure 3 and Figure 4 In the random subcarrier allocation method, in this process, the subcarrier allocated to user k in the PLC channel is k, and at this time each user in the wireless channel is randomly allocated subcarriers, that is, user 1 randomly selects a subcarrier from all subcarriers for transmission, and user 2 randomly selects a user from the remaining subcarriers for subcarrier allocation, until all users have obtained subcarriers for transmission. After the user obtains the transmitted subcarrier, the channel transmitted by each user is estimated using the channel estimation method, that is, by sending a pilot, and then estimating the channels of all users based on the pilot and the received signal. After obtaining the subcarrier,

[0140] Then, power is allocated to the users. The traditional power allocation scheme is used to establish a power-constrained mathematical optimization problem with the goal of maximizing the system spectrum efficiency. Then, mathematical optimization methods (such as the penalty function method) are used to solve the problem and obtain the power transmitted by each user.

[0141] Channel estimation-based methods: In this process, users transmit long pilot signals on all subcarriers of the PLC and wireless channels. Channel estimation is then performed for all channels based on the pilot signals and the received signals on each subcarrier. Once all channels are estimated, an optimization problem for subcarrier and power allocation is formulated, aiming to maximize system capacity within the constraints of total power and subcarrier limitations. This problem is then solved using a convex optimization algorithm. During the solution, a user allocates all their energy to the channel with the highest gain (such as the PLC or wireless channel), simplifying the algorithm design.

[0142] Example 3. The above is a schematic scheme of a hybrid PLC and wireless communication transmission design method. It should be noted that the technical solution of this hybrid PLC and wireless communication transmission design system and the technical solution of the hybrid PLC and wireless communication transmission design method described above are based on the same concept. For details not described in detail in the technical solution of the hybrid PLC and wireless communication transmission design system in this embodiment, please refer to the description of the technical solution of the hybrid PLC and wireless communication transmission design method described above.

[0143] This embodiment also provides a hybrid PLC and wireless communication transmission design system, including a dual-link communication system module, a joint optimization model establishment module, and a sub-problem solving module;

[0144] The dual-link communication system module is used to build a physical communication link;

[0145] The joint optimization model establishment module establishes a joint optimization model according to the performance requirements of the dual-link communication system;

[0146] The sub-problem solving module solves the decomposed sub-carrier allocation problem and power allocation problem.

[0147] This embodiment also provides an electronic device suitable for hybrid PLC and wireless communication transmission design, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the hybrid PLC and wireless communication transmission design method proposed in the above embodiment.

[0148] This embodiment further provides a storage medium having a computer program stored thereon. When the program is executed by a processor, the method for designing hybrid PLC and wireless communication transmission proposed in the above embodiment is implemented.

[0149] The storage medium proposed in this embodiment and the design method for implementing hybrid PLC and wireless communication transmission proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0150] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general hardware, and of course can also be implemented by hardware. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0151] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A hybrid PLC and wireless communication transmission design method, characterized in that: include: Establish a dual-link communication system between the data concentrator and the energy meter; Establishing a joint optimization model for a dual-link communication system, and decomposing the joint optimization model into a subcarrier allocation problem and a power allocation problem; The subcarrier allocation problem and the power allocation problem are solved.

2. The hybrid PLC and wireless communication transmission design method according to claim 1, characterized in that: The dual-link communication system includes a power line communication link and a wireless communication link; Among them, both the power line communication link and the wireless communication link adopt orthogonal frequency division multiplexing modulation; The number of subcarriers of the power line communication link is less than the number of subcarriers of the wireless communication link; The data concentrator acts as a transmitter and sends signals to the electric energy meter through two links at the same time.

3. The hybrid PLC and wireless communication transmission design method according to claim 2, characterized in that: The steps of establishing the joint optimization model include: The electric energy meter serves as a receiving end to receive signals; At the receiving end, the signals from the two links are combined and processed, and a joint optimization model is constructed with the goal of maximizing the system spectrum efficiency, subject to the total power constraints and the minimum spectrum efficiency of each subcarrier.

4. The hybrid PLC and wireless communication transmission design method according to claim 3, characterized in that: The steps of decomposing the joint optimization model into a subcarrier allocation problem and a power allocation problem include: By matching the subcarriers of each power line communication link with the optimal subcarrier of the wireless communication link, a subcarrier allocation problem is formed; The power allocation problem is formulated by determining the power of all subcarriers.

5. The hybrid PLC and wireless communication transmission design method according to claim 4, characterized in that: The steps of solving the subcarrier allocation problem include: Model the subcarrier allocation problem as a multi-armed bandit problem; Taking the wireless communication link subcarrier wave as the arm and the subcarrier channel energy as the reward, an iterative upper confidence bound strategy is adopted to obtain the optimal wireless communication link subcarrier corresponding to each power line communication link subcarrier.

6. The hybrid PLC and wireless communication transmission design method according to claim 5, characterized in that: The iterative upper confidence bound strategy selects the optimal subcarrier by calculating the upper confidence bound value of the wireless communication link subcarrier; The calculation formula of the upper confidence limit is: Where u k (t) is the upper confidence bound of subcarrier k in t time slots, which is used to evaluate and select the optimal subcarrier; c x is the confidence adjustment factor; is the empirical average channel gain of subcarrier k in the tth time slot; m k,t is the cumulative number of times subcarrier k is selected up to the tth time slot, is the standard confidence interval based on time; are the confidence intervals adjusted to account for the total number of arms.

7. The hybrid PLC and wireless communication transmission design method according to claim 6, characterized in that: The steps for solving the power allocation problem include: After determining the allocation relationship between the subcarriers of the power line communication link and the subcarriers of the wireless communication link, estimating the channel of each subcarrier; Formulate a power allocation optimization problem with the goal of maximizing the system spectrum efficiency, subject to the total power constraint and the minimum spectrum efficiency of each subcarrier; The power allocation optimization problem is solved by using a convex optimization method to obtain the optimal power allocation for each subcarrier.

8. A hybrid PLC and wireless communication transmission design system, applying the method according to any one of claims 1 to 7, characterized in that: It includes a dual-link communication system module, a joint optimization model building module, and a sub-problem solving module; The dual-link communication system module is used to build a physical communication link; The joint optimization model establishment module establishes a joint optimization model according to the performance requirements of the dual-link communication system; The sub-problem solving module solves the decomposed sub-carrier allocation problem and power allocation problem.

9. An electronic device comprising: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the hybrid PLC and wireless communication transmission design method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the hybrid PLC and wireless communication transmission design method according to any one of claims 1 to 7.

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