A conflict-avoiding Wi-Fi network channel allocation method

Abstract

In order to solve the actual needs of Wi-Fi network channel allocation in reality, the present invention proposes a conflict-avoiding Wi-Fi network channel allocation method. This method takes the total network throughput as the optimization target, proposes the concept of throughput weakening degree to quantitatively characterize the impact of the conflict between adjacent APs on the same channel, and establishes a corresponding graph model. In a greedy manner, the APs to be allocated channels are selected in turn and the specific channels to be allocated are determined. Experimental results show that the present invention can achieve better network performance than the traditional method.

Description

Technical Field

[0001] The present invention relates to a conflict-avoiding Wi-Fi network channel allocation method, and belongs to the field of industrial Internet and wireless networks. Background Art

[0002] Channel resources have always been a scarce resource for wireless networks, and are even more scarce under the current reality of a sharp increase in network access devices. In a Wi-Fi network, before the network is running and data is transmitted, it is necessary to allocate channels for communication to each AP in the network. Only then can each terminal perform data transmission on the channel through scanning, authentication, and connection with the associated AP. When two adjacent APs in space use the same channel, they will cause serious interference to each other, greatly reducing network performance. At the same time, Wi-Fi channel resources are very scarce. For example, there are only three completely non-overlapping channels in the 2.4GHz frequency band. Existing studies lack in-depth quantitative characterization of the impact of AP conflicts, and most of them focus on interference rather than direct network performance indicators such as throughput. Therefore, as the network gradually becomes large-scale and high-density, a new channel allocation solution is urgently needed to solve this technical problem.

[0003] This method uses the Bianchi model to model the throughput of a single BSS (Basic Service Set), the effectiveness of which has been verified by many studies. The model reflects the mathematical relationship between network throughput and the number of participating sites. Summary of the invention

[0004] Technical issues:

[0005] The present invention proposes a conflict-avoiding Wi-Fi network channel allocation method, which determines the channel used by each AP for given geographical conditions and AP and STA location distribution, so as to reduce conflict interference between APs, spatially reuse channel resources as much as possible, and improve the overall network throughput performance.

[0006] Technical solution: In order to achieve the above-mentioned purpose, the technical solution of the present invention is as follows: a conflict-avoiding Wi-Fi network channel allocation method, the method comprising the following steps:

[0007] Step 1: Graph model initialization: Build a graph model based on environmental geographic information, AP and terminal distribution.

[0008] First, based on the signal strength, determine whether the terminals are competing with each other.

[0009]

[0010] Where P ij For STA i At STA j The signal strength at is the carrier sense signal strength threshold.

[0011] It can then be determined whether the terminal will cause a conflict with the specified BSS when communicating with it.

[0012]

[0013] Among them, β ij Indicates BSS i With STA j Will there be conflicts when using the same channel? For BSS i The set of STAs contained.

[0014] Then calculate the BSS i With BSS j BSS when on the same channel i For BSS j The number of additional STAs participating in the competition introduced,

[0015]

[0016] The throughput degradation is defined to indicate the impact of two BSSs on each other when a co-channel conflict occurs.

[0017] χ ij =S(n j )-S(n j +π ij )

[0018] Among them, χ ij is the throughput degradation, indicating that BSS i With BSS j BSS when on the same channel i About BSS j The throughput loss caused, n j For BSS j The number of STAs of the network itself, and S is the normalized throughput corresponding to the number of STAs in the Bianchi model.

[0019] According to the above formula, the throughput weakening degree between each AP is calculated in turn, and thus a throughput weakening graph can be established, which is represented by a two-dimensional array χ, where χ ij Indicates node AP i To Node AP j The throughput reduction graph established in step 1 is the basis for AP selection and channel selection priority in subsequent channel allocation. Compared with traditional methods, it further quantitatively describes the impact of conflicts between APs on throughput, so that better decisions can be made during channel allocation on how to reduce the possibility of conflicts, reduce the impact of conflicts, reuse channel resources, and obtain better channel resources.

[0020] Step 2: Neighbor relationship calculation: Calculate the neighbor table of each AP according to the throughput reduction graph.

[0021] The throughput weakening graph is traversed. If the throughput weakening degree between two nodes is not 0, it means that the two nodes are adjacent and each node adds the other to its neighbor set.

[0022] Step 3, initialization of intermediate variables: Initialize the intermediate variables to allocate channel AP set and select non-conflicting channel set for each AP.

[0023] The set of APs with allocated channels is initialized to an empty set. When the algorithm is running, each AP is added to this set when a channel is allocated. Each AP's set of optional non-conflicting channels is initialized to the total set of optional channels. When a neighboring AP is allocated a channel, the channel is removed from its own optional non-conflicting set.

[0024] Step 4, iteration end judgment: When the AP set of allocated channels includes all APs, the iteration ends and the algorithm result is output.

[0025] Step 5: Select the AP to which the channel will be assigned in this iteration:

[0026] Traverse all APs. If the AP has been assigned, ignore it. If the AP has not been assigned a channel, calculate the size of its optional non-conflicting channel set and select the AP(s) with the smallest optional non-conflicting channel set. Traverse the AP with the smallest optional non-conflicting channel set and calculate the corresponding potential impact size δ:

[0027]

[0028] Among them, δ i Indicates AP i Potential impact on neighboring APs that have not yet been assigned a channel, The set of neighboring APs to which no channels have been allocated.

[0029] The AP with the largest delta in the AP set with the smallest optional non-conflicting channel set is used as the AP to which the channel is to be allocated in this iteration.

[0030] Step 6: Assign a channel to the specified AP:

[0031] If the set of optional non-conflicting channels of the AP is not empty, traverse the neighbor table of the AP and calculate the set of neighbor APs whose channels have been allocated. Then traverse the set and calculate the set of APs of the allocated neighbor APs (not adjacent to the AP) of the allocated neighbor nodes of the AP. If the set is not empty, select an AP at random and use its channel as the result of this allocation. If the set is empty, select the first one from the set of optional non-conflicting channels as the result of this allocation.

[0032] If the optional non-conflicting channel set of the AP is empty, the total channel set is traversed, the total throughput reduction degree caused to the neighboring APs on the same channel is calculated respectively, and the smallest channel is selected as the result this time.

[0033] Step 7, update the intermediate variable: add the AP determined in step 4 to the allocated channel set, traverse the neighbor node set of the AP, and remove the channel determined in step 5 from the optional non-conflicting channel set of the neighbor node.

[0034] The present invention proposes a conflict-avoiding Wi-Fi network channel allocation method, which determines the channel used by each AP for given geographical conditions and AP and STA location distribution, so as to reduce conflict interference between APs, spatially reuse channel resources as much as possible, and improve the overall network throughput performance.

[0035] Beneficial effects: Compared with traditional technologies, the present invention further quantitatively describes the impact of mutual interference between APs on throughput on the graph model on which channel allocation decisions rely, thereby using this as the weight of the edges in the graph model to better make channel allocation decisions; in terms of channel allocation priority strategy, it not only considers avoiding interference as much as possible, but also further considers reducing the impact caused by interference, as well as how to better reuse channel resources. Therefore, the channel allocation results obtained by the present invention can achieve better network throughput performance than traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is the algorithm flow chart of the present invention;

[0037] Figure 2 is a schematic diagram of a throughput weakening diagram of the present invention;

[0038] Figure 3 The figure is a comparison of the objective function value (network throughput) corresponding to the channel allocation result when the number of APs is different in Example 2 of the present invention and the calculation time of the method;

[0039] Figure 4 The figure is a comparison of the objective function value (network throughput) corresponding to the channel allocation result when the number of channels is different in Example 2 of the present invention and the calculation time of the method. DETAILED DESCRIPTION

[0040] The following will describe the implementation modes of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0041] Example 1: See Figure 1 — Figure 4, a conflict avoidance Wi-Fi network channel allocation algorithm, the method comprising the following steps:

[0042] Figure 1 This is a flow chart of a channel allocation algorithm according to Embodiment 1 of the present invention. Figure 1 Describe each step in detail.

[0043] Step 1: Graph model initialization: Build a graph model based on environmental geographic information, AP and terminal distribution.

[0044] First, based on the signal strength, determine whether the terminals are competing with each other.

[0045]

[0046] Where P ij For STA i At STA j The signal strength at is the carrier sense signal strength threshold.

[0047] It can then be determined whether the terminal will cause a conflict with the specified BSS when communicating with it.

[0048]

[0049] Among them, β ij Indicates BSS i With STA j Will there be conflicts when using the same channel? For BSS i The set of STAs contained.

[0050] Then calculate the BSS i With BSS j BSS when on the same channel i For BSS j The number of additional STAs participating in the competition introduced,

[0051]

[0052] The throughput degradation is defined to indicate the impact of two BSSs on each other when a co-channel conflict occurs.

[0053] χ ij =S(n j )-S(n j +π ij )

[0054] Among them, χ ij is the throughput degradation, indicating that BSS i With BSS j BSS when on the same channel iAbout BSS j The throughput loss caused, n j For BSS j The number of STAs of the network itself, and S is the normalized throughput corresponding to the number of STAs in the Bianchi model.

[0055] According to the above formula, the throughput weakening degree between each AP is calculated in turn, and thus a throughput weakening graph can be established, which is represented by a two-dimensional array χ, where χ ij Indicates node AP i To Node AP j The weight of the directed edge between nodes (throughput weakening degree).

[0056] Step 2: Neighbor relationship calculation: Calculate the neighbor table of each AP according to the throughput reduction graph.

[0057] The throughput weakening graph is traversed. If the throughput weakening degree between two nodes is not 0, it means that the two nodes are adjacent and each node adds the other to its neighbor set.

[0058] Step 3, initialization of intermediate variables: Initialize the intermediate variables to allocate channel AP set and select non-conflicting channel set for each AP.

[0059] The set of APs with allocated channels is initialized to an empty set. When the algorithm is running, each AP is added to this set when a channel is allocated. Each AP's set of optional non-conflicting channels is initialized to the total set of optional channels. When a neighboring AP is allocated a channel, the channel is removed from its own optional non-conflicting set.

[0060] Step 4, iteration end judgment: When the AP set of allocated channels includes all APs, the iteration ends and the algorithm result is output.

[0061] Step 5: Select the AP to which the channel will be assigned in this iteration:

[0062] Traverse all APs. If the AP has been assigned, ignore it. If the AP has not been assigned a channel, calculate the size of its optional non-conflicting channel set and select the AP(s) with the smallest optional non-conflicting channel set. Traverse the AP with the smallest optional non-conflicting channel set and calculate the corresponding potential impact size δ:

[0063]

[0064] Among them, δ i Indicates AP i Potential impact on neighboring APs that have not yet been assigned a channel, The set of neighboring APs to which no channels have been allocated.

[0065] The AP with the largest delta in the AP set with the smallest optional non-conflicting channel set is used as the AP to which the channel is to be allocated in this iteration.

[0066] Step 6: Assign a channel to the specified AP:

[0067] If the set of optional non-conflicting channels of the AP is not empty, traverse the neighbor table of the AP and calculate the set of neighbor APs whose channels have been allocated. Then traverse the set and calculate the set of APs of the allocated neighbor APs (not adjacent to the AP) of the allocated neighbor nodes of the AP. If the set is not empty, select an AP at random and use its channel as the result of this allocation. If the set is empty, select the first one from the set of optional non-conflicting channels as the result of this allocation.

[0068] If the optional non-conflicting channel set of the AP is empty, the total channel set is traversed, the total throughput reduction degree caused to the neighboring APs on the same channel is calculated respectively, and the smallest channel is selected as the result this time.

[0069] Step 7, update the intermediate variable: add the AP determined in step 4 to the allocated channel set, traverse the neighbor node set of the AP, and remove the channel determined in step 5 from the optional non-conflicting channel set of the neighbor node.

[0070] Example 2: Example 2 of the present invention considers a Wi-Fi network, the AP topology network is randomly generated, and the number of STAs associated with each AP is a random number between 3 and 10. A conflict-avoiding Wi-Fi network channel allocation method (CAATWG) proposed by the present invention is compared with a traditional channel allocation method graph coloring algorithm (GCA) and an existing Monte Carlo method (MONTECALO) in the field of operations research.

[0071] Figure 3 Comparison of the objective function value (network throughput) corresponding to the channel allocation results for different numbers of APs and the calculation time of the method.

[0072] Figure 4 Comparison of the objective function value (network throughput) corresponding to the channel allocation results for different numbers of channels and the calculation time of the method.

[0073] As can be seen from the figure, the method proposed in the present invention is superior to the traditional GCA algorithm and MONTECARLO algorithm in terms of channel allocation result quality (network throughput performance), especially when channel resources are scarce and conflicts are more frequent. At the same time, the calculation time of the method proposed in the present invention is basically close to that of the traditional GCA method, and is much shorter than that of the MONTECARLO algorithm.

[0074] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A conflict avoidance Wi-Fi network channel allocation method, characterized in that: The method comprises the following steps: Step 1: Initialize the graph model: Establish a graph model based on the environment geographic information, AP and terminal distribution. Step 2, neighbor relationship calculation: Calculate the neighbor table of each AP based on the throughput reduction graph. Step 3, initialization of intermediate variables: Initialize the intermediate variables to allocate channel AP set and the non-conflicting channel set that each AP can choose. Step 4, iterative end judgment: when the set of allocated channel APs contains all APs, the iteration ends and the algorithm results are output. Step 5: Select the AP to which the channel is to be allocated in this iteration. Step 6: Allocate a channel to the specified AP. Step 7, update the intermediate variables and return to step 4; In step 1, firstly, it is determined whether the terminals are competing with each other based on the signal strength. Where P ij For STA i At STA j The signal strength at is the carrier sense signal strength threshold, It can then be determined whether the terminal will cause a conflict with the specified BSS when communicating with it. Among them, β ij Indicates BSS i With STA j Will there be conflicts when using the same channel? For BSS i The STA set contained, Then calculate the BSS i With BSS j BSS when on the same channel i For BSS j The number of additional STAs participating in the competition introduced, The throughput degradation is defined to indicate the impact of two BSSs on each other when a co-channel conflict occurs. x ij =S(n j )-S(n j +p ij ) Among them, χ ij is the throughput degradation, indicating that BSS i With BSS j BSS when on the same channel i About BSS j The throughput loss caused, n j For BSS j The number of STAs in the system, S is the normalized throughput corresponding to the number of STAs in the Bianchi model, According to the above formula, the throughput weakening degree between each AP is calculated in turn, and thus a throughput weakening graph can be established, which is represented by a two-dimensional array χ, where χ ij Indicates node AP i To Node AP j The weight of the directed edge between nodes (throughput weakening degree); In step 2, the throughput weakening graph is traversed. If the throughput weakening degree between two nodes is not 0, it means that the two nodes are adjacent and each node adds the other node to its neighbor set. In step 3, the AP set of allocated channels is initialized to an empty set. When the algorithm is running, each AP is added to this set when a channel is allocated. The set of optional non-conflicting channels for each AP is initialized to the total set of optional channels. When a neighboring AP is allocated a channel, the channel is removed from its own optional non-conflicting set. In step 4, the iteration ends when the set of APs with allocated channels contains all APs, and the iteration ends, and the algorithm results are output. In step 5, all APs are traversed. If the AP has been assigned a channel, it is ignored. If the AP has not been assigned a channel, the size of its optional non-conflicting channel set is calculated, and the AP (s) with the smallest optional non-conflicting channel set is selected. The AP with the smallest optional non-conflicting channel set is traversed, and the corresponding potential impact size δ is calculated: Among them, δ i Indicates AP i Potential impact on neighboring APs that have not yet been assigned a channel, For the neighbor AP set that has not yet been assigned a channel, the AP with the largest δ in the AP set with the smallest optional non-conflicting channel set is used as the AP to be assigned a channel in this iteration; In step 6, if the set of optional non-conflicting channels of the AP is not empty, the neighbor table of the AP is traversed to calculate the set of neighbor APs of its allocated channels; the set is traversed again to calculate the set of APs of the allocated neighbor APs of the AP's allocated neighbor nodes (and not adjacent to the AP). If the set is not empty, an AP is randomly selected from the set and its channel is used as the result of this allocation. If the set is empty, the first one is selected from the set of optional non-conflicting channels as the result of this allocation. If the AP's optional non-conflicting channel set is empty, then traverse the total channel set, calculate the total throughput reduction caused to the neighboring APs on the same channel, and select the smallest channel as the result. In step 7, the intermediate variable is updated: the AP determined in step 5 is added to the allocated channel set, and the neighbor node set of the AP is traversed to remove the channel determined in step 6 from the optional non-conflicting channel set of the neighbor node.

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