A method for optimizing wi-fi network throughput by integrating terminal association and mobile roaming

Abstract

The application proposes a Wi-Fi network throughput optimization method for terminal association and mobile roaming in the background of AP networking in a three-dimensional complex environment of an industrial wireless scene. The optimization goal of the method is to optimize the association state of AP and terminal, thereby improving the throughput of the entire network. First, the AP optimization deployment position and the AP signal strength heat map are obtained, and the throughput model of the fixed terminal and the mobile terminal is established, thereby constructing the optimization model for the normalized throughput. The optimization problem is decomposed into two sub-problems, the throughput optimization for mobile terminal roaming and the throughput optimization for fixed terminal. The throughput optimization algorithm considering mobile terminal roaming needs to be executed, and then the initial solution of the AP association state matrix considering only the fixed terminal is solved. The throughput of the fixed terminal can be optimized by comprehensively considering the above two steps. The scheme can more efficiently obtain better network throughput.

Description

Technical Field

[0001] This application relates to the fields of industrial internet and wireless networks, and in particular to a method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming. Background Technology

[0002] With the rapid development of the Industrial Internet, wireless local area networks (WLANs) have become a widely adopted solution in industrial communication. Wireless access points (APs) are commonly used devices for building small WLANs, offering advantages such as long wireless transmission distances, high reliability, and strong device flexibility. To better cover wireless signals, multiple wireless APs are typically deployed in Industrial Internet networks.

[0003] However, when considering mobile and fixed terminals, the inability to transmit data during the re-association process with a roaming target AP when their associated AP switches can lead to throughput loss. Furthermore, severe wireless media conflicts when too many terminals are simultaneously associated with the same AP can cause throughput loss. Without a reasonable throughput optimization scheme, this can result in degraded communication quality, equipment redundancy, and resource waste. Therefore, in the Industrial Internet, we need to balance signal strength and throughput requirements to directly improve economic efficiency in production. Summary of the Invention

[0004] The main objective of this application is to provide a method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming, aiming to achieve better network throughput more efficiently while meeting the real-world needs of both fixed and mobile terminals.

[0005] To achieve the above objectives, this application provides a method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming, comprising the following steps:

[0006] Step 1: Obtain the optimized deployment location of the APs and the heat map of AP signal strength;

[0007] Step 2: Based on the AP optimized deployment location and AP signal strength heatmap, establish throughput models for fixed terminals and mobile terminals, thereby constructing an optimization model;

[0008] Step 3: Throughput optimization algorithm for mobile terminal roaming;

[0009] Step 4: Without considering mobile terminals, generate the initial solution of the AP association state matrix for fixed terminals;

[0010] Step 5: Based on Steps 3 and 4, adjust the AP association of fixed terminals to obtain the terminal association and mobile roaming scheme with the optimal global throughput.

[0011] In step one, the obtained AP optimized deployment location can be based on experience, signal strength or other methods to optimize the deployment of APs, and the obtained AP signal strength heat map can be a signal strength heat map matrix obtained based on a signal loss model or actual measurement.

[0012] In step two, for fixed terminals, the throughput of an AP can be determined using the Bianchi model based on the association between the AP and the fixed terminal. For mobile terminals, considering the movement speed of each segment of the path, the location of the mobile terminal at each moment is determined, leading to the number of terminals associated with each AP at a given moment and the number of terminals roaming from one AP to another. The network throughput is then calculated using the Bianchi throughput model. Therefore, the total throughput within a system cycle can be expressed as...

[0013]

[0014] Where, N a t represents the number of APs. s The system's runtime period is the least common multiple of the runtime periods of all mobile terminals, where t0 is the length of each time slice. This represents the number of terminals associated with the i-th AP at time slice k. Let S(n) represent the number of roaming terminals associated with the i-th AP at time slot k. Let S(n) represent the relationship curve between the AP normalized throughput and the number of associated terminals calculated by the Bianchi model. Therefore, the optimization problem is maxS, and the optimization variables are the association status between mobile terminals and fixed terminals and APs at each time slot. The constraint is that each terminal needs to obtain signal coverage from at least one AP in any time slot.

[0015] In step three, the throughput loss caused by the number of APs associated with the terminal is temporarily disregarded; only the throughput loss caused by mobile terminals roaming between APs is considered. Subsequent steps will perform overall optimization for both fixed and mobile terminals. The throughput optimization algorithm for mobile terminal roaming is based on a greedy algorithm, which seeks target APs that minimize the number of AP roaming attempts required for the mobile terminal to maintain coverage.

[0016] In step four, when calculating the initial solution, the AP signal strength heatmap is used to prioritize associating each AP with the terminal with the strongest signal, and to make the number of fixed terminals associated with each AP as equal as possible, so as to achieve a fast solution for the initial solution.

[0017] In step four, only fixed terminals are considered, and an initial solution for associated APs is quickly generated using a greedy algorithm. However, the throughput decrease caused by a mobile terminal associating with an AP is not considered. Therefore, in step five, based on the association matrix of the mobile terminal in step three, a new associated AP is randomly selected for the fixed terminal from the list of associatable APs. This adjusts the AP association matrix of the fixed terminal in step four, and the mobile and fixed terminals are collaboratively optimized at the overall level to improve throughput.

[0018] Step three, the throughput optimization algorithm for mobile terminals includes the following steps:

[0019] Step 3-1: The algorithm iterates through each mobile terminal and selects the AP with the highest signal strength as the initial associated AP at the starting point of the mobile terminal.

[0020] Step 3-2: At each time slot corresponding to the cube block in the mobile terminal's movement path, determine whether the currently associated AP can continue to provide coverage for the mobile terminal at this location by using the AP signal strength heatmap;

[0021] Step 3-3: If coverage can be provided, then the AP should continue to provide coverage to the mobile terminal.

[0022] Steps 3-4: If coverage cannot be provided, at that point, use the AP heatmap of the current mobile terminal to determine the number of time slices that all other APs besides the original AP can provide continuous coverage after roaming, and roam to the target AP that can provide the most continuous coverage time slices.

[0023] Steps 3-5: Calculate the next AP and repeat the above steps.

[0024] In step four, the throughput optimization algorithm for fixed terminals includes the following steps:

[0025] Step 4-1: Calculate the initial solution of the AP association state matrix for fixed terminals;

[0026] Step 4-2: Initialize the solution set for the search. Copy the initial solution of the fixed terminal and AP association obtained in Step 4-1 Np times as the solution set for random search.

[0027] Step 4-3: Perform heuristic iterative optimization. In each iteration, the associated APs are reassigned to each fixed terminal with probability p, and the targets for assignment are derived from the list of associable APs in step 4-1.

[0028] Step 4-4: Calculate the current objective function. If the objective function is better than the historical best solution, then update the historical best solution to this individual.

[0029] Steps 4-5: Move all individuals in the solution set to the position of the historical best solution;

[0030] Step 4-6: Repeat step 4-2 until the maximum number of iterations is reached, then stop iterating and output the historical best solution at this point as the result of the algorithm.

[0031] Compared with the prior art, the advantages of the present invention are as follows:

[0032] This application provides a method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming. First, it obtains the optimized deployment locations of access points (APs) and AP signal strength heatmaps, and establishes throughput models for both fixed and mobile terminals, thereby constructing an optimization model for normalized throughput. The optimization problem is decomposed into two sub-problems: throughput optimization for mobile terminal roaming and throughput optimization for fixed terminals. Based on this, a throughput optimization algorithm considering mobile terminal roaming needs to be executed, and then the initial solution of the AP association state matrix considering only fixed terminals is obtained. Combining these two steps, the throughput of fixed terminals can be iteratively optimized.

[0033] Experimental results show that, considering the real-world requirements for terminal roaming, this invention achieves better network throughput performance and shorter optimization time compared to traditional methods. Furthermore, the algorithm proposed in this invention is an AC control strategy based on the IEEE 802.11k / v / r protocol. By optimizing the timing of mobile terminal roaming and its association with the AP of fixed terminals in various time slices within the system cycle, it reduces throughput loss. It integrates well with existing Wi-Fi 6 devices supporting the IEEE 802.11k / v / r protocol. Compared to ordinary heuristic algorithms, it offers faster response times, controlling Wi-Fi 6 network roaming to the tens of milliseconds level, demonstrating significant advantages in industrial interconnection scenarios. In addition, the algorithm proposed in this invention can dynamically adjust the association strategy, exhibiting better adaptability than the default association strategy and maintaining excellent network performance across various scales of scenarios. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0035] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart illustrating the first embodiment of a Wi-Fi network throughput optimization method that integrates terminal association and mobile roaming, as proposed in this invention.

[0037] Figure 2 This is a schematic diagram of the mobile terminal throughput optimization algorithm in the first embodiment of the Wi-Fi network throughput optimization method that integrates terminal association and mobile roaming proposed in this invention.

[0038] Figure 3 This is a schematic diagram of the fixed terminal throughput optimization algorithm in the first embodiment of the Wi-Fi network throughput optimization method that integrates terminal association and mobile roaming proposed in this invention.

[0039] Figure 4 This is a second embodiment of a Wi-Fi network throughput optimization method that integrates terminal association and mobile roaming proposed in this invention, comparing the proposed algorithm with the default association strategy under different numbers of mobile terminals;

[0040] Figure 5 This is a third embodiment of a Wi-Fi network throughput optimization method that integrates terminal association and mobile roaming proposed in this invention, comparing the proposed algorithm with the default association strategy under different fixed numbers of terminals;

[0041] Figure 6 This is the fourth embodiment of a Wi-Fi network throughput optimization method that integrates terminal association and mobile roaming proposed in this invention, comparing the algorithm proposed in this invention with the default association strategy under different numbers of APs; Detailed Implementation

[0042] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings.

[0043] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application.

[0044] Example: The first embodiment of the present invention provides a method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming, such as... Figure 1 As shown in the embodiment of the Wi-Fi network throughput optimization method for integrated terminal association and mobile roaming proposed in this invention, the method includes the following steps:

[0045] Step S10: Obtain the optimized deployment location of the AP and the heat map of the AP signal strength;

[0046] In this embodiment, it should be noted that the environmental information used in the three-dimensional space includes the x-axis, y-axis, and z-axis information, which represents the coverage area of ​​the wireless AP (e.g., if the size of the three-dimensional space is 50m × 50m × 10m, then the size in the x-axis direction is 50m, the size in the y-axis direction is 50m, and the size in the z-axis direction is 10m). After performing grid discretization processing on this three-dimensional space, the location information of fixed terminals and the trajectory and speed information of mobile terminals can be obtained. The optimized deployment locations of APs are distributed in this three-dimensional space, and the AP signal strength heatmap is a signal strength heatmap based on this space.

[0047] Step S20: Based on the AP optimized deployment location and AP signal strength heat map, establish throughput models for fixed terminals and mobile terminals, thereby constructing an optimization model;

[0048] In this embodiment, it should be noted that step S20 does not consider the throughput reduction caused by wireless media conflicts resulting from different APs operating on the same channel. That is, it is assumed that APs with overlapping BSS ranges can be allocated to non-overlapping channels, and the AP throughput reduction is determined only by the number of associated terminals.

[0049] Step S30: Throughput optimization algorithm for mobile terminal roaming;

[0050] In this embodiment, it should be noted that in step S30, since the number of mobile terminals is less than that of fixed terminals, and for mobile terminals, the throughput loss caused by roaming between APs is much greater than the throughput loss caused by the excessive number of AP-associated terminals, the throughput loss caused by the number of AP-associated terminals can be temporarily ignored in this step. Only the throughput loss caused by mobile terminals roaming between APs is considered. In subsequent steps, overall optimization will be performed for fixed terminals and mobile terminals.

[0051] Step S40: Without considering mobile terminals, generate the initial solution of the AP association state matrix for fixed terminals;

[0052] In this embodiment, it should be noted that, to avoid frequent verification of constraints, an AP heatmap of fixed terminals is used before the algorithm to establish a list D of APs that each fixed terminal can associate with. This algorithm and the subsequent random optimization algorithm will be based on this list, avoiding constraint verification during iteration and improving solution efficiency. It should also be noted that in step S40, the number of mobile terminals is less than that of fixed terminals, and the time to associate each AP is much shorter than that of fixed terminals. Therefore, when generating the initial solution for the APs associated with fixed terminals, the AP association with mobile terminals can be temporarily ignored. This also avoids traversing and allocating across all time slices, further improving the algorithm's efficiency.

[0053] Step S50: Based on steps three and four, adjust the AP association of fixed terminals to obtain the terminal association and mobile roaming scheme with the optimal global throughput.

[0054] In this embodiment, it should be noted that step S40 only considers fixed terminals and uses a greedy algorithm to quickly generate an initial solution for associating with an AP, without considering the throughput decrease caused to an AP when a mobile terminal is associated with one. Therefore, in step S50, the initial solution can be determined based on A... m The correlation matrix of mobile terminals given in the figure can be adjusted by A. s The AP association matrix of fixed terminals in the system optimizes the collaboration between mobile and fixed terminals at the overall level, thereby achieving further throughput improvement.

[0055] The first embodiment of the present invention provides a method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming, wherein the mobile terminal throughput optimization algorithm is as follows: Figure 2 As shown in the embodiment of the Wi-Fi network throughput optimization method integrating terminal association and mobile roaming proposed in this invention, the mobile terminal throughput optimization algorithm includes the following steps:

[0056] Step A10: The algorithm iterates through each mobile terminal and selects the AP with the highest signal strength at the starting point of the mobile terminal as the initial associated AP.

[0057] Step A20: At each time slot corresponding to the cube block in the mobile terminal's movement path, determine whether the currently associated AP can continue to provide coverage for the mobile terminal at this location by using the AP signal strength heatmap;

[0058] Step A30: If coverage can be provided, the AP shall continue to provide coverage to the mobile terminal.

[0059] Step A40: If coverage cannot be provided, at that point, use the AP heatmap of the current mobile terminal to determine the number of time slices that all other APs besides the original AP can provide continuous coverage after roaming, and roam to the target AP that can provide the most continuous coverage time slices.

[0060] Step A50: Calculate the next AP and repeat the above steps.

[0061] The first embodiment of the present invention provides a method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming, wherein the fixed terminal throughput optimization algorithm is as follows: Figure 3 As shown in the embodiment of the Wi-Fi network throughput optimization method integrating terminal association and mobile roaming proposed in this invention, the fixed terminal throughput optimization algorithm includes the following steps:

[0062] Step B10: Calculate the initial solution of the AP association state matrix for the fixed terminal;

[0063] Step B20: Initialize the solution set for the search by copying the initial solution of the fixed terminal and AP association obtained in step one Np times as the solution set for random search.

[0064] Step B30 involves heuristic iterative optimization. In each iteration, associated APs are reassigned to each fixed terminal with probability p, and the targets for assignment are derived from the list of associable APs in Step 1.

[0065] Step B40: Calculate the current objective function. If the objective function is better than the historical best solution, then update the historical best solution to this individual.

[0066] Step B50: Move all individuals in the solution set to the position of the historical best solution;

[0067] Step B60: Repeat step two until the iteration reaches the maximum number of iterations, then stop the iteration and output the historical best solution at this point as the result of the algorithm.

[0068] This application employs the aforementioned scheme, namely, obtaining the optimized deployment location of access points (APs) and AP signal strength heatmaps. Based on this, it establishes throughput models for fixed and mobile terminals, thereby constructing an optimization model. It calculates the throughput optimization for mobile terminal roaming and the initial solution of the AP association state matrix for fixed terminals without considering mobile terminals. Finally, based on this, it adjusts the AP association for fixed terminals to obtain the globally optimal terminal association and mobile roaming scheme. This algorithm has lower computational complexity compared to traditional throughput optimization schemes, thus achieving higher throughput while maintaining signal strength.

[0069] Furthermore, in the specific second embodiment of this application, considering a three-dimensional space of 50m×50m×10m, 80 fixed terminals, and 8 access points (APs), multiple experiments were conducted with different numbers of mobile terminals, wherein the number of transport robots and patrol robots was equal, referring to... Figure 4 .

[0070] In the specific third embodiment of this application, considering a three-dimensional space of 50m×50m×10m, 4 mobile terminals (2 transport robots and 2 patrol robots respectively), and an AP count of 8, multiple experiments were conducted with different numbers of fixed terminals, referring to... Figure 5 .

[0071] In the specific fourth embodiment of this application, considering a three-dimensional space of 50m×50m×10m, 80 fixed terminals, and 4 mobile terminals (2 transport robots and 2 patrol robots respectively), multiple experiments were conducted with different numbers of APs, referring to... Figure 6 .

[0072] In the second, third, and fourth embodiments, it should be noted that the experimental results show that, in all three embodiments, the objective function decreases to some extent with the increase in the number of mobile terminals. This is due to the throughput loss caused by the inevitable AP switching of mobile terminals. However, in the two objective function curves using the algorithm proposed in this invention, the decrease in the objective function with the increase in the number of mobile terminals is significantly lower than that without the algorithm proposed in this invention, proving that the algorithm proposed in this invention is effective in optimizing the throughput of mobile terminals. Furthermore, the objective function curve after using the 802.11r protocol is higher than that without it, and the rate of decrease is lower than before, proving that the algorithm of this invention combined with the 802.11r fast roaming protocol is effective in improving throughput. At the same time, with the increase in the number of fixed terminals, the number of fixed terminals associated with each AP will inevitably increase as well. Therefore, the objective function will also decrease with the increase in the number of fixed terminals. Moreover, the two objective function curves using the algorithm proposed in this invention are higher than the curve of the default association strategy. Whether the algorithm of this invention is combined with the 802.11r fast roaming protocol or not does not affect the rate of decrease of the objective function curve corresponding to the algorithm proposed in this invention. As the number of access points (APs) increases, the objective functions of the three compared cases all show a significant increase. This is because increasing the number of APs directly improves the total throughput. Furthermore, in the two curves corresponding to the algorithm proposed in this invention, the increase in the objective function is significantly greater than that of the unoptimized curve, proving that the algorithm proposed in this invention can better utilize the throughput improvement brought about by the increase in the number of APs compared to the unoptimized version.

[0073] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for optimizing Wi-Fi network throughput by integrating terminal association and mobile roaming, characterized in that, The optimization method includes the following steps: Step 1: Obtain the optimized deployment location of the APs and the heat map of AP signal strength; Step 2: Based on the AP optimized deployment location and AP signal strength heatmap, establish throughput models for fixed terminals and mobile terminals, thereby constructing an optimization model; Step 3: Throughput optimization algorithm for mobile terminal roaming; Step 4: Without considering mobile terminals, generate the initial solution of the AP association state matrix for fixed terminals; Step 5: Based on Steps 3 and 4, adjust the AP association of fixed terminals to obtain the terminal association and mobile roaming scheme with the optimal global throughput. In step two, for fixed terminals, the throughput of an AP is determined using the Bianchi model based on the association between the AP and the fixed terminal. For mobile terminals, the location of the mobile terminal at each moment is determined by considering the movement speed of each segment of the movement path. This leads to the number of terminals associated with each AP at a given moment, as well as the number of terminals roaming from one AP to another. The network throughput is then calculated using the Bianchi throughput model. Therefore, the total throughput within one system cycle is expressed as... in, Indicates the number of APs. The system's runtime period is the least common multiple of the runtime periods of all mobile terminals. For each time slice length, This represents the number of terminals associated with the i-th AP at time slice k. This represents the number of roaming terminals associated with the i-th AP at time slice k. This represents the relationship between the AP normalized throughput and the number of associated terminals calculated by the Bianchi model. Therefore, the optimization problem is... The optimization variables are the association status between mobile terminals and fixed terminals and APs in each time slot, and the constraint is that each terminal needs to obtain signal coverage from at least one AP in any time slot. In step three, the throughput optimization algorithm for mobile terminals includes the following steps: Step 3-1: The algorithm iterates through each mobile terminal and selects the AP with the highest signal strength as the initial associated AP at the starting point of the mobile terminal. Step 3-2: At each time slot corresponding to the cube block in the mobile terminal's movement path, determine whether the currently associated AP can continue to provide coverage for the mobile terminal at this location by using the AP signal strength heatmap; Step 3-3: If coverage can be provided, then the AP should continue to provide coverage to the mobile terminal. Steps 3-4: If coverage cannot be provided, at that point, use the AP heatmap of the current mobile terminal to determine the number of consecutive coverage time slots that all other APs besides the original AP can provide after roaming, and roam to the target AP that can provide the most consecutive coverage time slots. Steps 3-5: Calculate the next AP and repeat the above steps.

2. The Wi-Fi network throughput optimization method for integrated terminal association and mobile roaming as described in claim 1, characterized in that, In step one, the optimized deployment location of the AP is obtained, and the AP is optimized based on the signal strength. The obtained AP signal strength heatmap is a signal strength heatmap matrix obtained from the signal loss model or actual measurement.

3. The Wi-Fi network throughput optimization method for integrated terminal association and mobile roaming as described in claim 1, characterized in that, Step four, the throughput optimization algorithm for fixed terminals includes the following steps: Step 4-1: Calculate the initial solution of the AP association state matrix for fixed terminals; Step 4-2: Initialize the solution set for the search. Copy the initial solution of the fixed terminal and AP association obtained in Step 4-1 Np times as the solution set for random search. Step 4-3: Perform heuristic iterative optimization. In each iteration, the associated APs are reassigned to each fixed terminal with a probability of p. The target of the assignment comes from the list of associable APs in step 4-1. Step 4-4: Calculate the current objective function. If the objective function is better than the historical best solution, then update the historical best solution to this individual. Steps 4-5: Move all individuals in the solution set to the position of the historical best solution; Step 4-6: Repeat step 4-2 until the maximum number of iterations is reached, then stop iterating and output the historical best solution at this point as the result of the algorithm.

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