Rapid switching method and system for indoor Wi-Fi communication

Abstract

The invention discloses a method and a system for quickly switching indoor Wi-Fi (Wireless Fidelity) communication. The method comprises the following steps: firstly, detecting the Wi-Fi signal intensity received by the mobile equipment in real time, and when the signal intensity is lower than a first threshold value, predicting a future track of the mobile equipment by a current access point (AP); the switching position is then determined based on the future trajectory and a wireless signal propagation attenuation model. And the current AP updates network topology information, calculates weighted quality indexes of candidate APs near the switching position, generates an optimal candidate AP list, and sends the optimal candidate AP list to the mobile equipment. And the mobile device actively initiates an association request according to the list priority to complete switching. According to the access point switching method and device, the sticky terminal phenomenon is prevented through threshold setting, access point selection is carried out in advance by predicting the future trajectory of the terminal, so that the switching access point is optimal in a period of time in the future, the network packet loss rate and the end-to-end time delay are reduced, and the network throughput is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless Wi-Fi fast switching, and relates to a fast switching method and system for indoor Wi-Fi communication. Background Art

[0002] With the rapid development of Internet technology, users' demand for network connection has been increasing day by day, and 4G / 5G cellular data networks have become standard configurations for modern mobile phones. However, even so, Wi-Fi technology still enjoys wide applications in homes, offices and public places with its characteristics of high speed and convenience, and has quickly become an indispensable part of daily life. The popularization of Wi-Fi technology not only improves the convenience of network access, but also promotes the interconnection and data exchange of wireless devices.

[0003] However, when enjoying the convenience brought by Wi-Fi, users also face some challenges. Especially when choosing an access point (AP for short), it is often difficult to determine which AP can provide the best service quality only based on the signal strength displayed by the device. This is because the signal strength cannot fully reflect the actual load situation of the AP, and too high a load may lead to network congestion and a decrease in throughput. Therefore, the traditional AP selection mechanism based on the Received Signal Strength Indicator (RSSI for short) has been difficult to meet the requirements of the modern network environment.

[0004] To address this challenge, standards such as IEEE 802.11 k / v / r have emerged, aiming to reduce the interruption when wireless terminals (STA for short) switch between APs in a Wi-Fi network environment. However, due to hardware limitations, many commercial devices do not support these standards, thus limiting their effects in practical applications. Therefore, how to more effectively select APs to achieve load balancing and seamless switching has become a hot topic of current research.

[0005] During the AP selection process, many studies have adopted the method of uniform load, aiming to more effectively allocate STAs to optimize the performance of the WLAN (Wireless Local Area Network). However, these methods often require modifications to the existing IEEE 802.11 standard or the wireless cards of STAs, which face great difficulties in practical applications.

[0006] In addition, ultra-dense Wi-Fi networks also face two fundamental challenges: handover prediction and AP selection. Handover prediction aims to predict the connection status of mobile devices to achieve seamless connection and reduce handover latency. The selection of APs directly affects the quality of service of devices and the overall network performance. Traditional AP selection strategies based on the strongest signal first are prone to overuse of APs, which can lead to packet loss and increased end-to-end latency. Adopting a load balancing strategy may sacrifice the quality of service, resulting in devices connecting to more distant APs.

[0007] To address these issues, most existing Wi-Fi handover algorithms only focus on the optimal choice at the current moment and lack the ability to predict future moments. This leads to a significant impact on network performance due to the increased number of handovers in ultra-dense networking scenarios. For example, the literature "Research on IEEE802.11 Roaming Technology" uses fingerprint positioning technology to match trajectories and predicts AP signal strength based on historical data to perform handovers. However, this method is applicable to fixed scenarios and fixed mobile routes, and the algorithm is deployed on the STA side, increasing the workload of the STA. At the same time, when the scenario changes or there are obstacles, fingerprint data needs to be re-collected.

[0008] Another invention with the publication number CN119136271A redesigned the roaming method and proposed a terminal device to solve the problem of long Wi-Fi handover time. However, this method also faces the problems of non-support of STA devices and increased workload of the terminal, and only considers the optimal AP list at the current moment when performing roaming. Summary of the Invention

[0009] The purpose of the present invention is to solve the technical problem in the prior art that only the optimal AP list at the current moment is considered during Wi-Fi handover, and to provide a fast handover method and system for indoor Wi-Fi communication.

[0010] To achieve the above object, the present invention adopts the following technical solutions: The first aspect of the present invention provides a fast handover method for indoor Wi-Fi communication, including the following steps: Real-time detect the Wi-Fi signal strength received by the mobile device; when the Wi-Fi signal strength received by the mobile device is lower than the first threshold, the current AP predicts the future trajectory of the mobile device; Based on the future trajectory of the mobile device, obtain the handover position through the wireless signal propagation attenuation model; The current AP updates the current network topology information and calculates the weighted quality index of candidate APs near the handover position, and generates an optimal candidate AP list; The current AP sends the optimal candidate AP list to the mobile device, and the mobile device actively initiates an association request according to the priority of the optimal candidate AP list to complete the handover.

[0011] Furthermore, the specific method for the current AP to predict the predicted trajectory of the mobile device is as follows: The mobile device sends inertial navigation information and location information to the current AP; Based on the inertial navigation information and location information, the AP uses the Bayesian-LSTM algorithm to predict the future trajectory of the mobile device.

[0012] Furthermore, based on the future trajectory of the mobile device, the handover position is obtained through a wireless signal propagation attenuation model, specifically as follows: Based on the future trajectory of the mobile device, the Log-Distance logarithmic attenuation model is used to determine the location information where the Wi-Fi signal strength received by the mobile device is lower than the second threshold, and the handover position is obtained.

[0013] Furthermore, the current AP updates the current network topology information and calculates the weighted quality index of candidate APs near the handover position to generate an optimal candidate AP list, specifically as follows: Based on the handover position, a second predicted position is obtained; The current AP updates the current network topology information, and based on the current network topology information, selects a pre-handover AP list at the handover position and a second candidate AP list at the second predicted position; Based on the pre-handover AP list and the second candidate AP list, calculate the quality index of each candidate AP, sort the candidate APs, and obtain the optimal candidate AP list.

[0014] Furthermore, the method for obtaining the second predicted position based on the handover position is specifically as follows: Select the position after the handover position on the future trajectory of the mobile device as the second predicted position; The distance between the second predicted position and the position when the Wi-Fi signal strength received by the mobile device is lower than the first threshold satisfies:

[0015] where, ( , ) represents the position when the Wi-Fi signal strength received by the mobile device is lower than the first threshold, represents the distance between the second predicted position and ( , ), and ( , ) represents the handover position.

[0016] Furthermore, both the method of selecting the pre-handover AP list at the handover position and the second candidate AP list at the second predicted position based on the current network topology information adopt the method of covering with communication coverage distance.

[0017] Further, calculating a quality index for each candidate AP based on the pre-switching AP list and the second candidate AP list, specifically:

[0018] Wherein, represents the quality index of the i th candidate AP in the pre-switching AP list; represents the Wi-Fi signal strength received by the mobile device at the switching position; represents the number of mobile devices of the pre-switching AP; N represents the maximum number of mobile device connections; represents the distance from the i th candidate AP in the pre-switching AP list to the switching position; D represents the maximum communication distance between the mobile device and the access point; R represents the absolute value of the minimum RSSI value; is the quality index of the candidate AP corresponding to the pre-switching AP list in the second candidate AP list, ; wherein, , , , , and are all weight coefficients.

[0019] Further, the mobile device actively initiates an association request according to the priority of the optimal candidate AP list to complete the handover, specifically: When it is detected that the Wi-Fi signal strength received by the mobile device is lower than the second threshold, perform the handover; The execution of the handover is specifically: the mobile device performs a handover request on the candidate APs according to the optimal candidate AP list sent by the current AP according to the priority.

[0020] A second aspect of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the above-mentioned fast handover method for indoor Wi-Fi communication is implemented.

[0021] A third aspect of the present invention provides a fast handover system for indoor Wi-Fi communication, including: A trajectory prediction module, configured to detect in real time the Wi-Fi signal strength received by the mobile device; when the Wi-Fi signal strength received by the mobile device is lower than the first threshold, the current AP predicts the future trajectory of the mobile device; A handover position determination module, configured to obtain the handover position based on the future trajectory of the mobile device through a radio signal propagation attenuation model; A candidate AP selection module, which is used for the current AP to update the current network topology information, calculate the weighted quality index of candidate APs near the handover location, and generate a list of optimal candidate APs; A handover module. The current AP sends the list of optimal candidate APs to the mobile device, and the mobile device initiatively sends an association request according to the priority of the list of optimal candidate APs to complete the handover.

[0022] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a fast handover method for indoor Wi-Fi communication. By real-time detecting the Wi-Fi signal strength received by the mobile device and starting the handover process when the signal weakens below a preset threshold, it effectively avoids the connection interruption problem caused by unstable signals. A future trajectory prediction mechanism of the mobile device is introduced. Combining with the wireless signal propagation attenuation model, it can accurately calculate the optimal handover position. This predictive handover strategy not only reduces the delay during the handover process but also ensures the network quality after the handover, thus improving the overall communication stability and continuity. In addition, the current AP can intelligently screen out a list of optimal candidate APs by updating the network topology information and calculating the weighted quality index of candidate APs. This process fully considers multiple dimensions such as network load, signal strength, and stability, ensuring the optimal network performance after the handover. The mobile device initiatively sends an association request according to the priority of the received list of optimal candidate APs, realizing a fast and smooth network handover. This autonomous handover mechanism not only simplifies the user operation but also improves the handover efficiency and success rate, bringing a more fluent and seamless network experience to users.

[0023] Furthermore, by obtaining a second prediction position based on the handover position and combining with the current network topology information, the method can more accurately predict and screen out a list of pre-handover APs and a list of second candidate APs. This strategy not only considers the current position and signal strength of the mobile device but also prospectively predicts the possible future positions of the mobile device, thus ensuring the forward-looking and accuracy of the handover process. When selecting candidate APs, the method adopts the method of communication coverage distance coverage to ensure that the candidate APs at the handover position have sufficient signal coverage strength and stability. This helps to reduce signal fluctuations and interruptions during the handover process and improve the reliability and success rate of the handover. When calculating the quality index of each candidate AP, the method comprehensively considers multiple dimensions, including signal strength, distance, network load, and the quality index of the candidate AP at the second prediction position, etc. This multi-dimensional quality evaluation method can more comprehensively reflect the comprehensive performance of the candidate AP, thus ensuring the optimal network quality after the handover. By setting weight coefficients for different evaluation dimensions, the method can be flexibly adjusted according to different scenarios and requirements, further improving the adaptability and intelligent level of the handover process. Description of the Drawings

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0025] Figure 1 This is a flowchart of the implementation process of the routing protocol function in the embodiments of the present invention; Figure 2 This is a flowchart of the method for fast handover of indoor Wi-Fi communication in the embodiments of the present invention; Figure 3 This is an effect diagram of the packet loss rate curve versus the moving speed in the embodiments of the present invention; Figure 4 This is an effect diagram of the network throughput - moving speed curve in the embodiments of the present invention; Figure 5 This is an effect diagram of the end-to-end delay - moving speed curve in the embodiments of the present invention; Figure 6 This is a schematic diagram of the network structure in the embodiments of the present invention. Detailed implementation manners

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and marked in the accompanying drawings here can be arranged and designed in various different configurations.

[0027] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed present invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0028] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0029] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper", "lower", "horizontal", "inner", etc. are used to indicate the orientation or positional relationship, it is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the invention product is usually placed during use. This is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be construed as a limitation of the present invention. In addition, terms such as "first", "second", etc. are only used for distinguishing descriptions and cannot be construed as indicating or implying relative importance.

[0030] In addition, if the term "horizontal" appears, it does not mean that the component is required to be absolutely horizontal, but it can be slightly inclined. For example, "horizontal" only means that its direction is more horizontal relative to "vertical", and does not mean that the structure must be completely horizontal, but it can be slightly inclined.

[0031] In the description of the embodiments of the present invention, it should also be noted that unless otherwise clearly specified and limited, if terms such as "set", "installed", "connected", "connected" are used, they should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0032] The following further describes the present invention in detail with reference to the drawings: See Figure 1 and Figure 2 , the present invention provides a method for rapid switching of indoor Wi-Fi communication, including the following steps: S1. First, an Ad Hoc network is implemented and Wi-Fi services are provided. As Figure 6 shown, each wireless node acts as an AP device, and AP parameters are set to achieve full coverage of indoor Wi-Fi signals, and each AP maintains the entire network topology information.

[0033] S1.1. The wireless nodes are initialized, the OLSR protocol is used for networking, and the entire network topology information is obtained. The network topology information includes routing information to the entire network, neighbor information, other node location information, and terminal number information. On the wireless network nodes, the nodes establish a one-hop neighbor table and a two-hop neighbor table through HELLO packet packets, establish a topology packet through TC packet packets, and finally establish a routing table to all devices in the network. When there is traffic between wireless nodes, data forwarding is achieved by querying the pre-established routing information.

[0034] S1.2. The wireless node acts as an access point (AP). On the premise of realizing networking, it provides Wi-Fi services to achieve full Wi-Fi coverage within the scenario. During the process of route establishment, the node maintains the device information of all wireless nodes within two hops.

[0035] S1.3. When the state of the wireless node changes, it sends broadcast information through MPR (Multipoint Relay) nodes to notify other wireless nodes, so that when the wireless node provides Wi-Fi handover algorithm services, it can calculate the candidate AP list based on the current topology information.

[0036] S2: When the device moves in the scenario and the RSSI signal value is lower than the first threshold, the AP predicts the future trajectory and handover position of the mobile device by the wireless signal propagation model and the Bayesian-LSTM position prediction algorithm (BOLSTM).

[0037] S2.1: When the device receives the RSSI value lower than the first threshold through the Beacon frame, it notifies the AP and sends the inertial navigation information and position information of the mobile device to the current AP.

[0038] S2.2: The current AP combines the wireless signal propagation model and the position information to predict the position where the RSSI value of the mobile device decays to the second threshold, that is, the handover position is obtained.

[0039] The position trajectory prediction in this embodiment adopts the BOLSTM algorithm. BOLSTM is a position prediction algorithm based on Bayesian-LSTM. Its architecture includes a sequence input layer, an LSTM layer with 125 neurons, a dropout layer with a dropout rate of 0.5, a pre-connection layer, and a regression layer. The input layer receives position coordinates and inertial navigation information. The LSTM layer improves the prediction performance of the model by learning spatio-temporal sequence information. The dropout layer helps prevent the model from overfitting. The pre-connection layer further processes the LSTM output, and the regression layer is responsible for outputting the position information at the next moment and optimizes the hyperparameters of LSTM using the Bayesian estimation algorithm, including the training duration, the number of LSTM layers, the number of neurons in each layer, the proportion of neurons discarded in each layer, and the initial learning rate.

[0040] S3: The current AP updates the entire network topology information through the routing protocol, calculates the weighted values of the APs near the predicted position, and sorts the optimal AP list.

[0041] S3.1: The AP combines the topology information of the current network to select a candidate AP list. The criteria for selecting an AP include: pre-AP position information, RSSI value of the pre-AP, and load condition of the pre-AP.

[0042] S3.2: Obtain the preset weight ratio, weight the network performance corresponding to each candidate AP based on the preset weight ratio, and calculate the quality index of each candidate AP.

[0043] S3.3: Sort the quality indexes of all candidate APs from largest to smallest, and select the AP with the largest quality index as the pre-switching AP.

[0044] S4: Before the device switches, the current AP sends the optimal AP list to the mobile device.

[0045] The mobile device performs an association request process according to the priority based on the candidate list provided by the AP, obtains AP-related information by sending probe request frames, and adopts an active request method to execute the Wi-Fi switching process to achieve maximum compatibility with different Wi-Fi devices.

[0046] An embodiment of the present invention provides a fast switching method for indoor Wi-Fi communication, including the following steps: S1, complete the networking function S101, In this embodiment, the OLSR routing protocol is used for networking. Nodes establish a one-hop neighbor table and a two-hop neighbor table through HELLO packets, establish a topology packet through TC packets, and finally establish a routing table to all devices in the network. When there is traffic between wireless nodes, data forwarding is achieved by querying the pre-established routing information.

[0047] S102, During the routing establishment process, nodes will maintain the device information of all wireless nodes within two hops. After the routing establishment is completed, when the device information of wireless nodes changes, the local MPR set is used for broadcasting to update the device information of wireless nodes within two hops about themselves. The device information includes location information and load conditions. In this way, each node will have information about the APs near the pre-switching point of the mobile device.

[0048] S103, On the premise of realizing networking, wireless nodes realize Wi-Fi coverage and provide services.

[0049] S2, handover prediction: S201, When the mobile device moves in a large-area Wi-Fi coverage environment implemented by an ad hoc network, by detecting the RSSI value of the Wi-Fi frame and determining whether the RSSI value is lower than the first threshold , update its own location information as the basis for location prediction.

[0050] S202, When the mobile terminal detects that the RSSI value is lower than the first threshold at this time, send the location information of the mobile device to the current AP ( ) and inertial navigation information enable the current AP to execute a prediction algorithm.

[0051] S203. After the current AP associated with the mobile terminal obtains the location information and inertial navigation information uploaded by the mobile terminal, the current AP executes a location prediction algorithm. First, the trajectory of the mobile device is predicted through the BOLSTM algorithm to obtain the future trajectory of the mobile device within a future period of time , and then combined with the Log-Distance logarithmic attenuation model, the location where the mobile terminal reaches the second threshold ( ) is obtained ( ), which is the handover location. The logarithmic attenuation formula is as follows:

[0052] where represents the path loss at distance , represents the path loss at the reference distance , represents the path loss exponent describing the rate at which the signal decays with distance, is the reference distance, represents the distance, is a random variable of the normal distribution representing shadow fading, with a standard deviation of .

[0053] Select the second predicted location ( ) from the future trajectory of the mobile device. The second predicted location needs to be after the handover location ( ), and the distance between the second predicted location and location satisfies:

[0054] S3. Optimal AP selection: S301. The current AP will initially screen out a list of pre-switching APs for the predicted location ( ) based on the device information maintained by the ad hoc network; the screening condition is that the communication distance of the pre-switching AP can cover the handover location.

[0055] S302. Screen out the second candidate AP list at the second predicted location ( ) in the same way, but the candidate APs in the second candidate AP list do not care about the number of mobile devices of the pre-switching AP compared to the list of pre-switching APs at the handover location ( ). The information obtained at the second predicted location is used to ensure that the pre-switching AP is also optimal at a future time.

[0056] S303. Weight the data obtained in S302 and calculate the quality index of each candidate AP:

[0057] Where, represents the quality index of the pre - handover AP, represents the i th AP in the pre - handover AP list, represents the RSSI value at the position ( , ), represents the number of terminals of the pre - handover AP, represents the distance from the pre - handover AP to the position ( , ), and satisfies the following relational expression: .

[0058] ( , ) represents the coordinate of the AP location.

[0059] Where, represents the quality index at the position ( ), .

[0060] The weight coefficient satisfies the following relational expression:

[0061]

[0062] S304. Sort the calculated values to obtain the optimal candidate AP list.

[0063] S4. Execute the handover: When the mobile terminal detects that the RSSI reaches the second threshold ( ), it executes the handover process and actively sends probe requests in sequence from the optimal one downwards according to the optimal candidate AP list provided by the current AP.

[0064] One embodiment of the routing protocol of the present invention can also select AODV, DSDV, and a special ZRP routing protocol, etc., and the most suitable routing protocol can be selected according to the current network environment when implementing.

[0065] The indoor location prediction algorithm of the embodiment of the present invention can be replaced by kinematic methods, Kalman filter prediction, time - series prediction, etc.

[0066] The present invention migrates the handover algorithm to the AP side. By leveraging the comprehensive understanding of the overall network topology state provided by the wireless ad-hoc network, it can dynamically and intelligently select the optimal handover target according to the current network conditions, effectively reducing the workload of the terminal. Traditional handover algorithms lack the ability to predict future network states during execution, which may lead to handover decisions that are optimal immediately but not in the long term, thus increasing unnecessary handover times. The present invention innovatively integrates a location prediction function to ensure that the handover strategies for the current and a period of time in the future are all optimal, significantly reducing the handover frequency and enhancing the stability and efficiency of network connections. By predicting future locations and combining the characteristics of the ad-hoc network, this solution can more effectively plan handovers, significantly shortening the scanning time and reducing the latency problems caused by network handovers. Precise prediction and intelligent handover strategies effectively reduce the handover frequency, thereby reducing packet loss caused by frequent handovers and enhancing the reliability of data transmission. The present invention also solves the sticky terminal problem, that is, the terminal is overly dependent on the current access point and is reluctant to switch to a better option. This improvement helps to enhance the overall service quality, reduce service quality fluctuations, and increase network throughput, providing users with a smoother network experience.

[0067] To further illustrate the superiority of the present invention, a simulation experiment was conducted on the fast handover method for indoor Wi-Fi communication in an embodiment of the present invention. Twelve AP nodes were placed in a wireless scenario, among which three were used as stationary AP nodes, eight were respectively connected to different APs, and one node was used as a mobile terminal to verify the handover algorithm. The nodes moved in an indoor scenario at a speed of 1.2 m / s, and the nodes sent data streams at a rate of v, with the packet size being 1024 Byte. To verify the effectiveness of the algorithm of the present invention, the algorithm was simulated respectively under the conditions of data rates v = 10 Mbps, 20 Mbps, 30 Mbps, 40 Mbps, 50 Mbps, 60 Mbps, 70 Mbps, 80 Mbps, 90 Mbps, and 100 Mbps. The simulation duration was 47 s, and network packet delivery rate, throughput, and end-to-end experimental data were obtained.

[0068] Figure 3 It is a curve graph showing the variation of packet loss rate with data rate. The abscissa represents the data rate, and the ordinate represents the packet loss rate of data packets. The purple curve represents the 802.11 algorithm, and the green curve represents the fast handover algorithm FAPS proposed by the present invention. From Figure 3 it can be seen that as the data rate increases, the packet loss rate of the 802.11 algorithm gradually increases. Although the packet loss rate of the FAPS handover algorithm also increases with the increase of the data rate, the packet loss rate of FAPS is always lower than that of the 802.11 algorithm. This means that the FAPS algorithm can maintain a lower packet loss rate, ensuring the reliability of communication.

[0069] Figure 4 It is a graph showing the variation of throughput with data rate. The abscissa represents the data rate, and the ordinate represents the network packet throughput. The purple curve represents the 802.11 algorithm, and the green curve represents the FAPS algorithm. It can be seen from the figure that the throughput performance of the proposed FAPS handover algorithm is better than that of the 802.11 algorithm, which means that the FAPS handover algorithm can provide higher network capacity and carry larger services.

[0070] Figure 5 It is a graph showing the variation of network end-to-end delay with mobile speed. The purple curve represents the 802.11 algorithm, and the green curve represents the FAPS algorithm. From Figure 5 it can be seen that the delay of the FAPS handover algorithm is lower than that of the 802.11 algorithm, so it can better ensure the real-time performance of communication.

[0071] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in the terminal device, used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device, and of course, can also include the extended storage medium supported by the terminal device. It can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, device, or component. The computer-readable storage medium provides a storage space, and this storage space stores the operating system of the terminal. And, in this storage space, one or more instructions suitable for being loaded and executed by the processor are also stored. These instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: electrical connections with one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0072] The computer-readable storage medium also includes data signals propagated in the baseband or as part of a carrier wave, which carry the readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than the readable storage medium, and this readable medium can send, propagate, or transmit a program used by or in combination with an instruction execution system, device, or component. The program code contained on the readable storage medium can be transmitted by any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination of the above.

[0073] The program code for performing the operations of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0074] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the fast switching method for indoor Wi-Fi communication in the above embodiments.

[0075] An embodiment of the present invention provides a fast switching system for indoor Wi-Fi communication, including: A trajectory prediction module for real-time detecting the Wi-Fi signal strength received by a mobile device; when the Wi-Fi signal strength received by the mobile device is lower than a first threshold, the current AP predicts the future trajectory of the mobile device; A handover location determination module for obtaining the handover location through a radio signal propagation attenuation model based on the future trajectory of the mobile device; A candidate AP selection module for the current AP to update the current network topology information and calculate the weighted quality index of candidate APs near the handover location, and generate an optimal candidate AP list; A handover module, the current AP sends the optimal candidate AP list to the mobile device, and the mobile device actively initiates an association request according to the priority of the optimal candidate AP list to complete the handover.

[0076] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A fast switching method for indoor Wi-Fi communication, characterized in that: The following steps are involved: Detecting the Wi-Fi signal strength received by the mobile device in real time; when the Wi-Fi signal strength received by the mobile device is lower than a first threshold, the current AP predicts the future trajectory of the mobile device; Based on the future trajectory of the mobile device, the switching position is obtained through the wireless signal propagation attenuation model; The current AP updates the current network topology information and calculates the weighted quality index of the candidate APs near the switching location to generate the optimal candidate AP list; The current AP sends the optimal candidate AP list to the mobile device, and the mobile device actively initiates an association request according to the priority of the optimal candidate AP list to complete the handover.

2. The fast switching method for indoor Wi-Fi communication according to claim 1, characterized in that: The predicted trajectory of the mobile device predicted by the current AP is specifically: The mobile device sends inertial navigation information and location information to the current AP; Based on the inertial navigation information and location information, the AP uses the Bayesian-LSTM algorithm to predict the future trajectory of the mobile device.

3. The fast switching method for indoor Wi-Fi communication according to claim 1, characterized in that: The switching position is obtained based on the future trajectory of the mobile device through the wireless signal propagation attenuation model, specifically: Based on the future trajectory of the mobile device, the Log-Distance logarithmic attenuation model is used to determine the location information where the Wi-Fi signal strength received by the mobile device is lower than the second threshold, and obtain the switching location.

4. The fast switching method for indoor Wi-Fi communication according to claim 1, characterized in that: The current AP updates the current network topology information and calculates the weighted quality index of the candidate APs near the switching location to generate the optimal candidate AP list, specifically: Based on the switching position, obtaining a second predicted position; The current AP updates the current network topology information, and selects a pre-switching AP list of the switching location and a second candidate AP list of the second predicted location based on the current network topology information; Based on the pre-switching AP list and the second candidate AP list, the quality index of each candidate AP is calculated, and the candidate APs are sorted to obtain an optimal candidate AP list.

5. The method for fast switching of indoor Wi-Fi communication according to claim 4, characterized in that: The second predicted position is obtained based on the switching position, specifically: Selecting the position after the switching position on the future trajectory of the mobile device as the second predicted position; The distance between the second predicted position and the position when the Wi-Fi signal strength received by the mobile device is lower than the first threshold satisfies: in,( , ) represents the location when the Wi-Fi signal strength received by the mobile device is lower than the first threshold, Indicates the second predicted position and ( , ) distance, ( , ) indicates switching position.

6. The method for fast switching of indoor Wi-Fi communication according to claim 4, characterized in that: The pre-switching AP list for selecting the switching position based on the current network topology information and the second candidate AP list for the second predicted position both adopt the communication coverage distance coverage method.

7. The fast switching method for indoor Wi-Fi communication according to claim 4, characterized in that: The calculation of the quality index of each candidate AP based on the pre-switching AP list and the second candidate AP list is specifically as follows: in, Indicates the number of APs in the pre-switching AP list. i The quality index of the candidate APs; Indicates the Wi-Fi signal strength received by the mobile device at the handover location; Indicates the number of mobile devices that are expected to switch APs; N Indicates the maximum number of mobile device connections; Indicates the number of APs in the pre-switching AP list. i The distance from the candidate AP to the switching location; D Indicates the maximum communication distance between a mobile device and an access point; R Indicates the absolute value of the minimum RSSI value; is the quality index of the candidate AP in the second candidate AP list corresponding to the pre-switching AP list, ;in, , , , , and are all weight coefficients.

8. The fast switching method for indoor Wi-Fi communication according to claim 1, characterized in that: The mobile device actively initiates an association request according to the priority of the optimal candidate AP list to complete the handover, specifically: When it is detected that the Wi-Fi signal strength received by the mobile device is lower than a second threshold, performing switching; The execution of the switching specifically includes: the mobile device executes a switching request to the candidate APs according to the priority according to the optimal candidate AP list sent by the current AP.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for fast switching of indoor Wi-Fi communication according to any one of claims 1 to 8 is implemented.

10. A fast switching system for indoor Wi-Fi communication, characterized in that: include: Trajectory prediction module, used to detect the Wi-Fi signal strength received by the mobile device in real time; When the Wi-Fi signal strength received by the mobile device is lower than a first threshold, the current AP predicts a future trajectory of the mobile device; A switching position determination module, used to obtain a switching position based on a future trajectory of the mobile device through a wireless signal propagation attenuation model; The candidate AP selection module is used for the current AP to update the current network topology information and calculate the weighted quality index of the candidate APs near the switching location to generate the optimal candidate AP list; In the switching module, the current AP sends the optimal candidate AP list to the mobile device, and the mobile device actively initiates an association request according to the priority of the optimal candidate AP list to complete the switching.

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