Dual-mode communication network real-time optimization method based on optimization algorithm

Abstract

The invention relates to the technical field of low-voltage power line dual-mode communication, and discloses a dual-mode communication network real-time optimization method based on an optimization algorithm, and the method comprises the following steps: S101, planning a traversal period and an iteration period through a CCO after networking is completed; s102, the PCO in the traversal period sends a communication test frame in the modes of HPLC and HRF; s103, the STA receives the traversal completion signal and then calculates an HRF expected frequency point; s104, the STA sends the expected frequency points to a PCO, and the PCO receives and counts the expected frequency points of the child nodes to obtain coordinated expected frequency points; s105, the PCO takes the coordination expectation frequency point as a target frequency point, the communication test is carried out again, and the steps 103-104 are repeated until the iteration period is finished; s106, after the iteration period, the STA checks network optimization information, and if the target function value is not minimum, agent request change is initiated; and S107, after the communication network topology structure is adjusted, the CCO enters the next round of optimization. According to the method, the problems of channel resource waste, low communication quality, deep hierarchy and the like in the existing dual-mode communication network optimization are solved. The purpose of improving the communication quality of the electricity utilization information acquisition system is achieved.

Description

Technical Field

[0001] This invention relates to the field of low-voltage power line dual-mode communication technology, and in particular to a real-time optimization method for dual-mode communication networks based on optimization algorithms. Background Technology

[0002] Optimization algorithms, by reasonably adjusting decision variables, aim to minimize or maximize the value of the objective function while satisfying various constraints. They are computational methods used to find the optimal or near-optimal solution to a specific problem. They have wide applications in mathematics, computer science, industry, and economics.

[0003] Dual-mode low-voltage power line communication technology combines HPLC (High-Speed ​​Power Line Communication) with HRF (High-Power Radio Frequency) to enable two channels to independently conduct communication services, jointly forming a low-voltage distribution area communication network. Compared to a single HPLC communication network, it offers advantages such as complementary communication blind spots and increased channel capacity, providing a new solution for the in-depth application and expansion of electricity consumption information collection systems. It has now become the mainstream solution for low-voltage distribution area communication in electricity consumption information collection systems.

[0004] A dual-mode communication network is a tree-structured communication network characterized by a Central Coordinator (CCO) acting as the master node, several Stations (STAs) acting as slave nodes, and nodes with proxy forwarding capabilities being called Platform Coordinators (PCOs). Dual-mode communication networks establish communication connections between CCOs and STAs or between CCOs and PCOs and STAs via HPLC or HRF. Dual-mode communication networks form the basis for data acquisition, transmission, and command exchange in power information acquisition systems. The quality of the network links and the communication hierarchy directly determine the effectiveness and timeliness of the acquisition system; therefore, real-time optimization of the communication network is necessary.

[0005] Current optimization methods for dual-mode communication networks primarily involve STAs maintaining their own neighbor lists, calculating the communication success rate with each neighbor node in HPLC mode, and prioritizing neighbor nodes with high communication success rates as parent or child nodes in their communication network. When a communication connection cannot be established with any node via HPLC, an attempt is made to establish a communication connection with a neighbor node via HRF. Since HRF has numerous frequency points, it often requires traversing all HRF communication frequencies, resulting in a long connection establishment time. Therefore, once a communication connection is established via HRF, the HRF frequencies between the two nodes remain unchanged. Because traditional dual-mode communication network optimization employs a strategy of prioritizing HPLC and fixing HRF frequencies, it not only leads to a serious waste of channel resources but also causes problems such as low communication link quality and deep hierarchical structures, thus affecting the normal operation of the acquisition system. Summary of the Invention

[0006] This invention addresses the shortcomings and defects of existing technologies by providing a real-time optimization method for dual-mode communication networks based on optimization algorithms. This method solves problems such as channel resource waste, low communication quality, and excessively deep hierarchical structures inherent in existing dual-mode communication network optimization methods, thereby improving the communication quality of electricity information collection systems.

[0007] The objective of this invention can be achieved through the following technical solutions: A real-time optimization method for a dual-mode communication network based on an optimization algorithm includes the following steps: S101: The dual-mode communication network is completed. The CCO plans the traversal period and iteration period according to the scale of the distribution area.

[0008] Furthermore, the basic time unit for the traversal period and the iteration period is the routing cycle, the traversal period is the traversal period of the preferred frequency point, and the iteration period is the iteration period of the desired frequency point.

[0009] Furthermore, the CCO will send the information about whether the current routing cycle is in the traversal or iteration phase to the entire network in real time via beacon frames.

[0010] S102: During the traversal period, the PCO sends communication test frames to the channel via HPLC and HRF.

[0011] Furthermore, the communication test frame is transmitted in parallel using HPLC and HRF. HPLC transmits at a fixed period on its own frequency band, while HRF selects to transmit by sequentially traversing preferred frequency points.

[0012] Furthermore, the preferred frequency point is an HRF frequency point with good communication performance commonly used in practical engineering applications.

[0013] Furthermore, the HRF traversal of the preferred frequency points includes the following steps: S201: CCO performs group time slot allocation based on the communication network topology.

[0014] Preferably, the group time slot allocation method assigns each PCO to a group, and all nodes directly proxies by the PCO belong to that group. The CCO allocates the bound CSMA time slots to the group proportionally based on the total number of nodes and the number of nodes in each group.

[0015] S202: The CCO distributes the group time slots to the entire network via beacons.

[0016] S203: After receiving the beacon, each PCO parses and obtains the group time slot corresponding to its own PCO. Within the corresponding time slot, it sends a frequency negotiation frame via HRF to inform the user of the HRF frequency to be switched.

[0017] S204: All STAs that receive the HRF frequency negotiation frame shall adjust their HRF receiving frequency to the target frequency.

[0018] S205: The PCO transmits a fixed number of communication test frames within the planned time slot and on the target frequency.

[0019] S206: The STA that receives the communication test frame calculates the communication success rate with the PCO, sends back the communication success rate, and fills the relevant information into the network optimization information list.

[0020] Furthermore, the STA receiving the communication test frame may not belong to the same group as the PCO, but may simply be located at the target frequency.

[0021] Furthermore, if the STA does not receive a communication test frame after switching the receiving frequency to the target frequency, it needs to switch back to the original frequency after the time slot is divided.

[0022] Furthermore, the network optimization information list is used to store network optimization information for all neighboring nodes. Each neighboring node is an element, and each element contains sub-elements such as node address, HPLC communication success rate, HPLC communication level, HPLC objective function value, HRF communication frequency, HRF communication success rate at that frequency, HRF communication level at that frequency, and HRF objective function value at that frequency.

[0023] Preferably, the formula for calculating the objective function value is: (1) In the formula, w1 is the communication level weight; w2 is the communication success rate weight; L is the communication level; and Q is the communication success rate.

[0024] S207: The PCO performs frequency switching only once per CCO cycle, and the frequency switching order of the entire network is synchronized. After completing the traversal of all preferred frequencies, the PCO sends a traversal completion signal to the child nodes and enters the iteration period.

[0025] S103: After receiving the traversal completion signal, the child node begins to calculate the desired HRF frequency.

[0026] Furthermore, the calculation of the desired HRF frequency point includes the following steps: S301: Calculate the value of the optimization function.

[0027] Preferably, the formula for calculating the optimized function value is: (2) In the formula, f i f is the HRF objective function value; min The minimum HRF objective function value for neighboring nodes in the network optimization information list; N is the number of preferred frequency points.

[0028] S302: Calculate the frequency point movement traction value.

[0029] Preferably, the formula for calculating the frequency shift traction value is: (3) In the formula, T i The moving traction value at the frequency point; F i This represents the frequency value.

[0030] S303: Perform frequency shifting.

[0031] Preferably, the frequency shift formula is: (4) In the formula, This represents the frequency value of the (n+1)th iteration. The step size reflects the degree of frequency shift.

[0032] S304: The frequency points calculated at this time usually do not conform to the frequency point selection specifications of HRF, and frequency point normalization is required.

[0033] Furthermore, the frequency point normalization is to select the nearest frequency point as the desired frequency point from the HRF frequency point lookup table.

[0034] S104: The STA sends the calculated desired frequency point to the PCO. The PCO receives the desired frequency points of all child nodes and performs statistics to obtain the coordinated desired frequency point.

[0035] Furthermore, the calculation of the desired coordinated frequency point includes the following steps: S401: If the communication success rate of each preferred frequency point of the sub-node is less than the HPLC communication success rate, then the sub-node shall be removed from the frequency point coordination list.

[0036] S402: Calculate the standard deviation of the expected frequency reported by each sub-node in the remaining frequency coordination list, set a threshold, and remove sub-nodes whose errors exceed the threshold from the coordination list.

[0037] S403: Calculate the average expected frequency reported by each sub-node in the remaining frequency coordination list, and select the nearest frequency from the HRF frequency lookup table as the expected coordination frequency.

[0038] S105: The PCO uses the desired frequency point for coordination as the target frequency point, performs communication testing again, and calculates the desired frequency point and the desired frequency point for coordination in steps 103 and 104 until the end of the iteration period.

[0039] S106: After the iteration period ends, each STA checks its own network optimization information list. If the objective function value at the final negotiated frequency point of the HPLC or HRF of its PCO is not the minimum, it initiates a proxy request for change.

[0040] Furthermore, the target proxy node and connection method for the proxy request to change are the neighboring node and communication method that minimizes the objective function of the network optimization information list.

[0041] S107: After completing the adjustment of the communication network topology, CCO enters the next round of dual-mode communication network optimization.

[0042] The beneficial technical effects of this invention are as follows: This invention provides a real-time optimization method for dual-mode communication networks based on an optimization algorithm. First, it iterates through preferred frequency points and obtains the success rate of each frequency point. Second, it obtains the desired frequency point through an optimization algorithm. Then, it iterates continuously to obtain the most convergent negotiated desired frequency point for each PCO. Finally, each node comprehensively considers the objective function values ​​between itself and its neighboring nodes during the frequency point traversal and iteration process to determine the selection of the proxy node. This solves the problems of channel resource waste, low communication quality, and deep hierarchical structures in existing dual-mode communication network optimization methods. It achieves the goal of improving the communication quality of electricity information collection systems. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the network topology of a certain distribution area in an embodiment of the present invention.

[0044] Figure 2 This is a flowchart of a real-time optimization method for a dual-mode communication network based on an optimization algorithm, according to the present invention.

[0045] Figure 3 This is a flowchart of the HRF traversal and frequency point selection process of the present invention.

[0046] Figure 4 This is the grouping result of time slots in an embodiment of the present invention.

[0047] Figure 5 This is a flowchart of the HRF desired frequency point calculation process of the present invention.

[0048] Figure 6 This is a flowchart illustrating the calculation process for coordinating the desired frequency point in this invention.

[0049] Figure 7 This is a schematic diagram of the updated network topology in an embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and do not limit the scope of the invention.

[0051] This invention provides a real-time optimization method for a dual-mode communication network based on an optimization algorithm, performing real-time optimization of the dual-mode communication network in an apartment building area. The communication network topology of the apartment building area is as follows: Figure 1 As shown, there is a total of 1 CCO and 9 STAs, among which CCO, 1, 2, 3 and 8 assume the role of PCO. Figure 2 The flowchart of a real-time optimization method for a dual-mode communication network based on an optimization algorithm according to the present invention is shown, as follows: Figure 2 As shown, the process includes the following steps: S101: The dual-mode communication network completes the network setup. The CCO plans the traversal period and iteration period according to the scale of the distribution area and distributes them to the entire network in real time in the form of beacon frames.

[0052] S102: During the traversal period, the PCO sends communication test frames to the channel via HPLC and HRF. HRF is transmitted by sequentially traversing the preferred frequency points, which are shown in Table 1. The HRF traversal process for the preferred frequency points is as follows: Figure 3 As shown, the process includes the following steps: Table 1 Example of Preferred Frequency Point List S201: The CCO performs group time slot allocation based on the communication network topology, and the grouping results are as follows: Figure 4 As shown, it is divided into 5 groups.

[0053] S202: The CCO distributes the group time slots to the entire network via beacons.

[0054] S203: After receiving the beacon, each PCO parses and obtains the group time slot corresponding to its own PCO. Within the corresponding time slot, it sends a frequency negotiation frame via HRF to inform the user of the HRF frequency to be switched.

[0055] S204: All STAs that receive the HRF frequency negotiation frame shall adjust their HRF receiving frequency to the target frequency.

[0056] S205: The PCO transmits a fixed number of communication test frames within the planned time slot and on the target frequency.

[0057] S206: The STA that receives the communication test frame counts the communication success rate with the PCO, returns the communication success rate, calculates the objective function value according to formula (1), and fills the relevant information into the network optimization information list. For example, the network optimization information list of STA9 is shown in Table 2. It can simultaneously detect the HRF signals of STA8 and STA2.

[0058] Table 2 Example of a Network Optimization Information List S207: The PCO performs frequency switching only once per CCO cycle, and the frequency switching order of the entire network is synchronized. After completing the traversal of all preferred frequencies, the PCO sends a traversal completion signal to the child nodes and enters the iteration period.

[0059] S103: After receiving the traversal completion signal, the child node begins to calculate the desired HRF frequency. The HRF desired frequency calculation process is as follows: Figure 5 As shown, the process includes the following steps: S301: Calculate the optimization function value according to formula (2). For example, the optimization function value of STA9 at each HRF frequency point between STA8 and STA9 is shown in Table 3.

[0060] Table 3 Examples of Optimized Function Values S302: Calculate the frequency point movement traction value according to formula (3). For example, the frequency point movement traction value of STA9 and STA8 at each HRF frequency point is calculated as shown in Table 4.

[0061] Table 4. Examples of Frequency Point Motion Traction Values S303: Frequency point shift is performed according to formula (4), with a step size factor of 10. For example, the frequency point shift between STA9 and STA8 at each HRF frequency point is calculated as shown in Table 5.

[0062] Table 5 Examples of Frequency Shift Values S304: Select the nearest frequency point as the desired frequency point from the HRF frequency lookup table. For example, the desired frequency points for each HRF frequency point between STA9 and STA8 are shown in Table 6.

[0063] Table 6 Examples of Desired Frequency Points S104: The STA sends the calculated desired frequency point to the PCO. The PCO receives the desired frequency points of all child nodes, performs statistical analysis, and obtains the coordinated desired frequency point. The calculation process for the coordinated desired frequency point is as follows: Figure 6 As shown, the process includes the following steps: S401: If the communication success rate of each preferred frequency point of the sub-node is less than the HPLC communication success rate, then the sub-node shall be removed from the frequency point coordination list. For example, STA8 and STA9 cannot communicate through HPLC, so STA9 shall not be removed.

[0064] S402: Calculate the standard deviation of the expected frequency reported by each sub-node in the remaining frequency coordination list, set a threshold, and remove sub-nodes whose errors exceed the threshold from the coordination list. For example, STA8 only has one sub-node, STA9, so STA9 is not removed.

[0065] S403: Calculate the average expected frequency point reported by each sub-node in the remaining frequency point coordination list, and select the nearest frequency point from the HRF frequency point lookup table as the expected coordination frequency point. For example, the final expected coordination frequency point is the expected frequency point corresponding to each communication frequency point in Table 6.

[0066] S105: The PCO uses the desired frequency point as the target frequency point, performs communication testing again, and repeats the calculation of the desired frequency point and the desired frequency point in steps 103 and 104 until the end of the iteration period.

[0067] S106: After the iteration period ends, the STA checks its own network optimization information list. If the objective function value at the final negotiated frequency point of the HPLC or HRF of its PCO is not the minimum, it initiates a proxy request to change. For example, if STA9 and STA2 have the minimum objective function value at 483MHz, then the PCO of STA9 will be changed to STA2.

[0068] S107: After completing the communication network topology adjustment, the CCO proceeds to the next round of dual-mode communication network optimization. The new network topology is as follows: Figure 7 As shown.

[0069] The above embodiments are descriptions of specific implementations of the present invention, and not limitations thereof. Those skilled in the art can make various modifications and changes without departing from the spirit and scope of the present invention to obtain corresponding equivalent technical solutions. Therefore, all equivalent technical solutions should be included in the patent protection scope of the present invention.

Claims

1. A real-time optimization method for a dual-mode communication network based on an optimization algorithm, characterized in that, Includes the following steps: S101: The dual-mode communication network is completed. The CCO plans the traversal period and iteration period according to the scale of the distribution area. S102: During the traversal period, the PCO sends communication test frames to the channel via HPLC and HRF. HPLC sends at a fixed period on its own frequency band, while HRF selects to traverse the preferred frequency points sequentially. S103: After receiving the traversal completion signal, the child node begins to calculate the desired HRF frequency. S104: The STA sends the calculated desired frequency point to the PCO. The PCO receives the desired frequency points of all child nodes and performs statistics to obtain the coordinated desired frequency point. S105: The PCO uses the desired frequency point as the target frequency point and performs communication tests again, repeating the calculation of the desired frequency point and the desired frequency point in steps 103 and 104 until the end of the iteration period. S106: After the iteration period ends, each STA checks its own network optimization information list. If the objective function value at the final negotiated frequency point of the HPLC or HRF of its PCO is not the minimum, it initiates a proxy request for change. S107: After completing the adjustment of the communication network topology, CCO enters the next round of dual-mode communication network optimization.

2. The real-time optimization method for a dual-mode communication network based on an optimization algorithm according to claim 1, characterized in that, The process of transmitting HRF sequentially through the preferred frequency points includes the following steps: S201: The CCO divides time slots according to the communication network topology; S202: The CCO distributes the group time slots to the entire network via beacons; S203: After receiving the beacon, each PCO parses and obtains the group time slot corresponding to its own PCO, and sends a frequency negotiation frame through HRF in the corresponding time slot to inform the HRF frequency point that is about to be switched. S204: All STAs that receive the HRF frequency negotiation frame shall adjust their HRF receiving frequency to the target frequency. S205: The PCO transmits a fixed number of communication test frames within the planned time slot and on the target frequency. S206: The STA that receives the communication test frame calculates the communication success rate with the PCO, sends back the communication success rate, and fills the relevant information into the network optimization information list; S207: The PCO performs frequency switching only once per CCO cycle, and the frequency switching order of the entire network is synchronized. After completing the traversal of all preferred frequencies, the PCO sends a traversal completion signal to the child nodes and enters the iteration period.

3. The real-time optimization method for a dual-mode communication network based on an optimization algorithm according to claim 2, characterized in that, The group time slot allocation method is that each PCO is a group, and the nodes directly proxies by the PCO belong to the group. The CCO allocates the bound CSMA time slots to the group proportionally according to the total number of nodes and the number of nodes in each group.

4. The real-time optimization method for a dual-mode communication network based on an optimization algorithm according to claim 2, characterized in that, The network optimization information list is used to store network optimization information for all neighboring nodes. Each neighboring node is an element, and each element contains sub-elements such as node address, HPLC communication success rate, HPLC communication level, HPLC objective function value, HRF communication frequency, HRF communication success rate at that frequency, HRF communication level at that frequency, and HRF objective function value at that frequency.

5. The real-time optimization method for a dual-mode communication network based on an optimization algorithm according to claim 2, characterized in that, The formula for calculating the objective function value is as follows: In the formula, w1 is the communication level weight; w2 is the communication success rate weight; L is the communication level; and Q is the communication success rate.

6. The real-time optimization method for a dual-mode communication network based on an optimization algorithm according to claim 1, characterized in that, The HRF desired frequency point calculation includes the following steps: S301: Calculate the optimization function value; S302: Calculate the frequency point movement traction value; S303: Perform frequency shift; S304: The frequency point calculated at this time usually does not conform to the frequency point selection specification of HRF. It is necessary to select the nearest frequency point as the desired frequency point from the HRF frequency point lookup table.

7. The real-time optimization method for a dual-mode communication network based on an optimization algorithm according to claim 1, characterized in that, The calculation of the desired frequency point for coordination includes the following steps: S401: If the communication success rate of each preferred frequency point of the sub-node is less than the HPLC communication success rate, then the sub-node shall be removed from the frequency point coordination list. S402: Calculate the standard deviation of the expected frequency reported by each sub-node in the remaining frequency coordination list, set a threshold, and remove sub-nodes whose errors exceed the threshold from the coordination list; S403: Calculate the average expected frequency reported by each sub-node in the remaining frequency coordination list, and select the nearest frequency from the HRF frequency lookup table as the expected coordination frequency.

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