Heterogeneous network intelligent switching method and equipment for multi-mode terminal

Abstract

The invention discloses a heterogeneous network intelligent switching method and equipment of a multi-mode terminal. The method comprises the following steps: acquiring first real-time signal information of at least two heterogeneous networks; the first real-time signal information comprises network state parameters; the at least two heterogeneous networks comprise a currently used network; normalizing the first real-time signal information, and determining second real-time signal information; and determining network scores of all heterogeneous networks according to a preset evaluation rule, and selecting whether to switch the network or not according to the network scores. The invention further comprises a device for implementing the method. According to the invention, the problem that parameters are not uniform when a plurality of network indexes are used as network switching basis is solved.

Description

Technical Field

[0001] This application relates to the field of communication technologies, and in particular, to a heterogeneous network intelligent switching method and device for a multi-mode terminal. Background Art

[0002] With the rapid development of 5G, satellite communication, and public and private network technologies, multi-mode terminals (supporting any heterogeneous networks such as public networks, narrowband private networks, broadband private networks, WiFi, and satellite networks) have been widely used in scenarios such as emergency communication and industrial Internet of Things. However, the coordination and intelligent switching between different networks have become one of the core technologies for improving service continuity and resource utilization efficiency.

[0003] The current network switching has the following problems: First, the decision-making dimension and network detection means are single. Most of the existing technologies only rely on a single signal strength (RSSI) as the basis for switching decisions, without considering other key indicators such as network latency, packet loss rate, and service urgency, resulting in frequent switching (i.e., the "ping-pong switching" phenomenon) in the edge area with large signal fluctuations. Second, the switching decision-making and execution mechanisms are simple and lack stability. Due to the lack of a hysteresis control and trend prediction mechanism, the existing solutions are prone to unnecessary network mode switching due to short-term signal fluctuations in the face of a rapidly changing network environment, reducing the overall communication stability and user experience. In complex heterogeneous network scenarios, more flexible strategies are needed, such as real-time network status feedback, service demand analysis, load balancing, and manual intervention prompts, to ensure that the best network can be switched to in various complex environments. Third, the dynamic adaptation ability is weak. Some technical solutions use fixed parameters and static rules, and do not respond flexibly enough to changes in terminal service requirements and network status. They cannot dynamically optimize switching weights and threshold parameters based on historical switching data or real-time network conditions, making it difficult to achieve the best network resource allocation and cost control. At the same time, there is also a problem of limited cross-protocol adaptation ability. Most technologies only focus on the switching between single networks (such as WiFi and cellular, WLAN and LTE), lacking a seamless interconnection solution between multiple network protocols such as public networks, private networks, and satellite networks, and cannot fully meet the requirements of multi-protocol comprehensive coordination in actual scenarios.

[0004] In addition, there is also a problem of high hardware dependence. Some solutions focus on switching control at the hardware circuit or SIM card level, requiring high hardware deployment, resulting in high cost investment and limited applicability.

[0005] At the same time, the human-computer interaction and status feedback are insufficient. Few solutions provide intuitive network status feedback and interaction prompts, making it difficult for users or administrators to understand the reasons and results of switching in a timely manner, which is not conducive to manual intervention and strategy optimization. Summary of the Invention

[0006] This application proposes a heterogeneous network intelligent switching method and device for a multi-mode terminal, which solves the problem of inconsistent parameters when multiple network metrics are used as the basis for network switching.

[0007] In a first aspect, an embodiment of this application provides a heterogeneous network intelligent switching method for a multi-mode terminal, including the following steps: Obtain first real-time signal information of at least two heterogeneous networks; the first real-time signal information includes network status parameters; at least two of the heterogeneous networks include the currently used network; Normalize the first real-time signal information to determine second real-time signal information; Determine the network scores of all heterogeneous networks according to a preset evaluation rule, and select whether to switch the network according to the network scores.

[0008] In a second aspect, an embodiment of this application further provides a heterogeneous network intelligent switching method for a multi-mode terminal, which is used for a network device, including the following steps: Obtain first real-time signal information of at least two heterogeneous networks; the first real-time signal information includes network status parameters; at least two of the heterogeneous networks include the currently used network; Send the first real-time signal information; Receive an instruction to switch the network.

[0009] Further, switching the network specifically includes the following steps: Receive a switching instruction; the switching instruction includes target network access parameters; Deregister the current network and maintain continuous transmission of service data during the deregistration process; Register the target network.

[0010] In a third aspect, an embodiment of this application further provides a heterogeneous network intelligent switching method for a multi-mode terminal, which is used for a master control device, including the following steps: Receive the first real-time signal information; Normalize the first real-time signal information to determine second real-time signal information; Determine the network scores of all heterogeneous networks according to a preset evaluation rule, and select whether to switch the network according to the network scores; Send an instruction to switch the network. Preferably, selecting to switch the network satisfies the following conditions: The score difference between the current network and the optimal candidate network is greater than a set hysteresis threshold; The score advantage time of the optimal candidate network is greater than a first set time threshold; The score of the current network does not rebound within a second set time threshold, or the optimal candidate network does not deteriorate within a third set time threshold.

[0011] In one embodiment, the normalization process specifically includes the steps of: Unify the units or formats of the data of the heterogeneous network according to a preset data format; Perform outlier detection on the data, eliminate noise points and outlier data, and supplement missing data; Preset the ideal values of each index, and use a linear normalization formula for an index where a larger value indicates better quality; use reverse normalization for an index where a smaller value indicates better quality.

[0012] In one embodiment, determining the network score specifically includes the steps of: Perform weighted summation on the normalized indexes to generate a comprehensive score signal.

[0013] In one embodiment, the master control device includes a human-computer interaction interface for manually adjusting the parameters of the network score.

[0014] In a fourth aspect, an embodiment of the present application further provides a heterogeneous network intelligent switching device for a multi-mode terminal, which is used to implement the heterogeneous network intelligent switching method for the multi-mode terminal described in any one of the first to third aspects, and includes: a network device and a master control device. The network device includes at least two heterogeneous network modules for obtaining first real-time signal information. The master control device includes a network detection module and a network decision module. The network detection module is used to perform normalization processing on the first real-time signal information to determine second real-time signal information. The network decision module is used to determine the network scores of all heterogeneous networks according to a preset evaluation rule, and select whether to switch the network according to the network scores.

[0015] The present application also proposes a communication device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the computer program is executed by the processor, it implements the steps of the method described in any one of the first aspects of the present application.

[0016] The present application also proposes a computer-readable medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the method described in any one of the first aspects of the present application.

[0017] The present application also proposes a mobile communication system, including at least one network device for implementing the method described in any one of the embodiments of the present application and / or at least one master control device for implementing the method described in any one of the embodiments of the present application.

[0018] The above at least one technical solution adopted in the embodiments of the present application can achieve the following beneficial effects: This application adopts multi-dimensional dynamic decision-making, breaks through the decision-making limitations of single signal strength (RSSI), and constructs an intelligent decision-making model that integrates signal quality, service requirements, network status, and user strategies. A hysteresis control mechanism is introduced, a signal strength threshold difference is set, and combined with a signal prediction algorithm, the changing trend of network coverage is predicted, frequent handovers in the network edge area are eliminated, and the stability of handover decisions is improved. The reinforcement learning model trains strategies through historical handover data, dynamically optimizes network selection weights, and fuzzifies network status parameters to generate adaptive handover rules, realizing the upgrade of the handover strategy from "static rules" to "dynamic learning". The wide and narrow integration solution realizes real-time intercommunication of any heterogeneous network protocols such as public networks, narrowband private networks, broadband private networks, WiFi, and satellite networks through core network integration, meeting the service requirements in complex scenarios. The present invention realizes intelligent handover at the pure software level, without the need for a large number of hardware modifications, and has low deployment costs and wide compatibility. Visual feedback of the real-time network status, handover reasons, and results is provided, making the handover decision more transparent and controllable, and supporting manual intervention and policy adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation of the present application. In the drawings: Figure 1 is a flowchart of an embodiment of the method of the present application; Figure 2 is a flowchart of an embodiment of the method of the present application for network devices; Figure 3 is a flowchart of an embodiment of the method of the present application for master control end devices; Figure 4 is a schematic diagram of an embodiment of a network device; Figure 5 is a schematic diagram of an embodiment of a master control end device; Figure 6 is a schematic structural diagram of a network device according to another embodiment of the present invention; Figure 7 is a block diagram of a master control end device according to another embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below in conjunction with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0021] This application is based on an intelligent switching system for multi-mode signals of multi-mode terminals. Through the integration of four core technological innovations, namely, a multi-dimensional decision-making model, a hysteresis control mechanism, a dynamic learning algorithm, and a cross-protocol gateway, as well as unified data normalization, dynamic weight weighting, a smooth switching strategy, and a user-defined intervention mechanism, it systematically solves the problems of rigid decision-making, poor stability, fixed strategies, and protocol fragmentation in the prior art. At the same time, it overcomes the problems of frequent switching and service interruption caused by signal fluctuations in heterogeneous network environments. Through the dynamic optimization and adaptive strategies of access parameters and service data, this system provides a highly reliable, low-latency, and adaptive multi-mode signal switching solution for scenarios such as emergency communication and industrial Internet of Things, significantly improving the accuracy of network switching decisions and the user experience, and achieving seamless and stable connection and intelligent resource scheduling across protocols and frequency bands.

[0022] The following will, in conjunction with the accompanying drawings, elaborate on the technical solutions provided by each embodiment of this application.

[0023] Figure 1 It is a flowchart of an embodiment of the method of this application.

[0024] This application proposes a heterogeneous network intelligent switching method for multi-mode terminals, which includes the following steps 110 to 130: Step 110: Obtain the first real-time signal information of at least two heterogeneous networks; the first real-time signal information includes network status parameters; at least two of the heterogeneous networks include the currently used network; Step 120: Normalize the first real-time signal information to determine the second real-time signal information; Step 130: Determine the network scores of all heterogeneous networks according to a preset evaluation rule, and select whether to switch the network according to the network scores.

[0025] Further, continuously collect signals in the new network mode, and at the same time monitor the network performance and service quality.

[0026] If switching failures or network quality not meeting the standards continuously occur, the "network adjudication system" can perform self-learning or adjust the switching strategy, and trigger the next round of switching process until the optimal network is found to meet the current service requirements.

[0027] It should be noted that the above steps are used for network entities in a wireless communication system, including a master control device, a network device, or other intermediate devices; the above steps can also be used for a service device that provides information processing for the network entity device; the above steps can also be used for any device, system, subsystem, circuit, chip, or software entity that provides information reception, transmission, identification, and processing for a master control device or a network device.

[0028] Figure 2Flowchart of an embodiment of the method of this application for a network device.

[0029] The method described in any embodiment of the first aspect of this application, when used in a network device, includes the following steps 210 to 230: Step 210: Obtain the first real-time signal information of at least two heterogeneous networks; the first real-time signal information includes network status parameters; at least two of the heterogeneous networks include the currently used network. For example, each heterogeneous network module (public network, narrowband private network, broadband private network, WiFi, satellite network, etc.) in the CP network module (network device) continuously collects its own signal metrics, including but not limited to signal strength, latency, bandwidth, packet loss rate, network load, etc.

[0030] The core responsibility of the CP network module is to coordinate the continuous and accurate output of signals between sub-modules, ensure the continuity and real-time nature of signal acquisition data, and solve possible signal conflicts and interference problems, ensuring that each module can work properly in any network mode and can correctly feedback the current user's network environment.

[0031] Step 220: Send the first real-time signal information. For example, each heterogeneous network module reports the collected signal data to the AP main control module (main control device) in real-time or periodically.

[0032] Furthermore, if the CP module detects a special state, such as flight mode, no signal, SIM card invalidation, etc., it will notify the AP main control module of the status information for subsequent decision-making.

[0033] Step 230: Receive an instruction to switch networks.

[0034] Send a switching command to the CP network module according to the adjudication instruction, specifying the target network mode.

[0035] The CP network module performs the switching operation and returns the switching result (success, failure, or exception) to the AP main control module after completion for updating the status.

[0036] Furthermore, after step 230, when switching networks, it specifically includes the steps of: Receive a switching instruction; the switching instruction includes target network access parameters. Receive the switching command and transfer the access parameters and service data. Receive the switching instruction from the network adjudication system, which includes the target network access parameters and the attached access parameters and service data, to ensure that the access parameters and service data are retained and transferred during the switching process.

[0037] Deregister the current network and maintain continuous transmission of service data during the deregistration process. Log off the current network, send a logoff instruction to the current network, and terminate the existing connection. During the logoff process, the network switching module uses a caching mechanism and relay technology to achieve continuous transmission of access parameters and service data, ensuring seamless docking when registering the target network subsequently.

[0038] Register the target network.

[0039] Register the target network, send a registration request to the target network, and transmit a switching command containing access parameters and service data. The registration request contains extended information to support the target network to automatically resume the original service during the access process.

[0040] Furthermore, for the handover completion and status feedback, whether the handover is successful or failed, the system will automatically resume to the listening state, continuously monitor the network environment, prepare for the next handover, and return the final handover status to the upper management system for subsequent analysis and policy optimization.

[0041] Figure 3 This is the flowchart of the method of this application for the implementation example of the master control device.

[0042] The method described in any of the embodiments of the first aspect of this application, for the master control device, includes the following steps 310 to 340: Step 310, receive the first real-time signal information; The "network detection system" under the AP master control module receives signal data from each network module.

[0043] The AP master control module is the core decision-making and execution unit of the entire network intelligent switching process, and can be internally divided into four subsystems: "user intervention system", "network detection system", "network adjudication system", and "network switching system".

[0044] The user intervention system, for example, the master control device includes a human-computer interaction interface for manually regulating the parameters of network scoring. It includes functions: User / Administrator preference management: Used to provide a graphical user interface (GUI) or open API, allowing users or administrators to configure personalized preference parameters, preferentially select a certain network (save traffic, speed priority, reliability priority, etc.), or prohibit access to specific networks in certain scenarios.

[0045] It is also used to respond to detecting a conflict between the user's preset preference and the automatic decision result. The user intervention system will feedback the current network status and switching suggestions to the user in the form of pop-up prompts, message notifications, or voice alerts for manual confirmation or adjustment.

[0046] Abnormal interaction and prompt are used to respond to the situation where the network detection system or network adjudication system detects serious network instability, extremely weak signal or hardware failure. The user intervention system starts an abnormal feedback mechanism, automatically generates and sends abnormal alarm information.

[0047] It is also used to visually display the switching results (current network mode, signal quality, reasons for successful or failed switching) in the form of charts, logs and real-time curves, helping users intuitively understand the network status and switching process.

[0048] Manual forced intervention is used for administrators to manually trigger the network to switch to a specified network through the user interface or remote management platform in special scenarios such as emergency command and industrial control.

[0049] In this application, the manual intervention system is an important part of the AP main control module. It displays real-time network quality information to users (or remote administrators) through an intuitive man-machine interaction interface, and allows users to autonomously adjust the adjudication parameters to achieve real-time intervention and optimization of network switching behavior. The adjudication parameters are used to quantitatively evaluate various indicators in a multi-mode network environment, and its specific parameters and descriptions are shown in Table 1: Table 1

[0050] It is also used during the operation of critical services, allowing administrators to intervene immediately to ensure that network switching operations prioritize business continuity and security requirements, thus effectively preventing service interruptions caused by insufficient intelligent switching judgment.

[0051] Feedback algorithm and closed-loop regulation are used to closely couple with the network detection, network adjudication and network switching systems. This system real-time collects historical switching data, abnormal events, network fluctuations and user regulation records. Using statistical analysis methods such as moving average, exponential smoothing or linear regression, and combining machine learning models such as random forest, gradient boosting tree and multi-layer perceptron, a dynamic prediction model is established to calculate the deviation between the actual switching effect and the preset target.

[0052] It is also used to generate adaptive optimization suggestions according to the above error calculation results, automatically adjust the switching sensitivity, the time interval to prevent switching ping-pong phenomenon, and modify the signal threshold. The feedback results (including error trend, optimization suggestions and parameter changes) are displayed in real time through graphs, trend curves and statistical reports, supporting users to understand the internal operation of the system and optimize the switching strategy through the user intervention interface. The above real-time data collection, statistical analysis, prediction model output, error calculation and parameter adjustment constitute a continuous iterative closed-loop intelligent feedback system.

[0053] A security guarantee mechanism is used in the user intervention system to achieve secure communication between the user interface and the remote management platform through end-to-end encryption, multi-factor authentication, digital signature, and security audit mechanisms, and to ensure that all control commands are signed, verified, and logged, thereby preventing unauthorized modification and tampering.

[0054] The network detection system includes the following functions: Signal data parsing and verification is used to receive real-time signal data from the CP network module, including RSSI, SINR, latency, and packet loss rate.

[0055] It is also used to filter, correct, or compensate for abnormal data to ensure the accuracy and reliability of the signal information input to the network decision-making system.

[0056] Multi-dimensional network status evaluation is used to comprehensively evaluate the current network environment based on network metrics, combined with historical data and threshold parameters, including network congestion level, available bandwidth, coverage area, and device online status.

[0057] It is also used to issue an alarm to the user intervention system or the network decision-making system in response to detecting specific abnormal states, including SIM card failure and WiFi authentication failure.

[0058] It is also used for special environment detection, performing additional processing (using backup parameters) in flight mode, offline mode, or signal weakening environment to improve the comprehensiveness of detection.

[0059] A security guarantee mechanism is used in the network detection system. Before reporting data, each heterogeneous network sub-module performs identity authentication and encrypts the collected data for transmission through symmetric encryption algorithms such as AES. At the same time, digital signature and checksum and / or hash algorithms are used to verify data integrity to ensure that the data is not stolen or tampered with during the transmission process.

[0060] The network decision-making system includes the following functions: An intelligent decision-making algorithm is used to adopt multiple algorithms, including weighted scoring, fuzzy logic, reinforcement learning, or machine learning models, to comprehensively score the signals reported by the network detection system and select the best or candidate network.

[0061] It is also used to dynamically adjust the decision-making strategy according to business requirements (real-time voice, video stream, file transfer, etc.) and user preferences (cost priority, speed priority, low power consumption, etc.).

[0062] An anti-shake and hysteresis mechanism is used to introduce hysteresis or time threshold control in response to the network signal fluctuating around the critical value to prevent frequent "ping-pong switching", and only perform the switch when a certain time has elapsed or the threshold difference is satisfied.

[0063] It is also used for trend prediction of signal strength or data rate (linear regression or moving average based on short-term historical data), reducing incorrect handovers caused by instantaneous fluctuations.

[0064] Mutex management and load balancing. In response to detecting mutual exclusion or conflict effects between two network modes, the adjudication system can take measures such as taking the lower-priority network offline and delaying handovers to ensure the overall stability of the system.

[0065] It is also used in response to enabling multiple networks simultaneously in a multi-mode and multi-standby scenario to achieve load balancing or multi-link aggregation, and is overall managed by the adjudication system.

[0066] Security guarantee mechanism. In the network adjudication system, all adjudication parameters used for decision-making are digitally signed and hash-verified, and in the decision-making process, security auditing and exception recording mechanisms are combined to protect the input data and decision output, ensuring the authenticity and integrity of the entire decision-making process and preventing potential security risks.

[0067] Furthermore, the dynamic adjustment decision-making strategy is that the network adjudication system makes adaptive decisions driven by historical business data and dynamically adjusts the adjudication strategy based on historical business data.

[0068] Network handover system, including functions: Instruction generation and distribution, used to generate handover instructions according to the decision result of the network adjudication system, including specific parameters such as the target network type, access point information, authentication method, power configuration, etc.

[0069] It is also used to send handover commands to the CP network module and monitor the status feedback during the execution process (whether the handover is successful, whether a retry is required, etc.).

[0070] Handover process control, responsible for scheduling the entire handover process, first disconnecting the original network and releasing relevant resources, then connecting to the target network and completing necessary authentication or configuration information updates.

[0071] It is also used in response to exceptions during the handover process (authentication failure, network access denied, etc.), recording error information and notifying the user to intervene in the system or the network adjudication system for processing.

[0072] Status write-back and log recording, used to write the handover result into the system log or database after the handover is completed for subsequent analysis and optimization.

[0073] It is also used to update the global status of the AP main control module simultaneously to ensure that other subsystems can obtain the latest network mode and related resource information.

[0074] For the security guarantee mechanism, the handover commands (including target network access parameters, access parameters, service data, and session context information) are all transmitted using digital signatures and end-to-end encryption, combined with secure session management, data buffering, and fault-tolerant automatic fallback mechanisms to ensure the security of data transmission and service continuity during the handover process, and effectively protect sensitive data even in abnormal situations.

[0075] This application adopts a modular hierarchical architecture design and constructs an intelligent handover system framework of "three horizontals and four verticals". At the horizontal level, it includes: The information perception layer (network detection system) realizes millisecond-level signal measurement and data acquisition through multimode terminals, and supports synchronous monitoring of 12 indicators such as RSSI and latency of heterogeneous networks such as 5G / satellite / WiFi.

[0076] The resource optimization layer (network adjudication system + network handover system) integrates prediction models and service perception strategies to complete nanosecond-level intelligent decision-making and seamless handover execution.

[0077] The terminal interaction layer (user intervention system) provides a visual decision-making dashboard to support dynamic adjustment of network scoring parameters and emergency intervention.

[0078] Functionally in the vertical direction, the four subsystems form a closed-loop data stream: The detection system realizes high-frequency sampling, the adjudication system dynamically optimizes the decision model through reinforcement learning, the handover system ensures zero-loss transmission of service data, and the user system realizes human-machine collaboration of "decision-making - feedback - optimization".

[0079] Step 320: Normalize the first real-time signal information to determine the second real-time signal information; And perform data parsing, cleaning, verification, and exception handling. For example, correct noise points, missing values, or duplicate values.

[0080] Furthermore, if there is a conflict with user preferences or business policies, the "user intervention system" issues a warning or prompt on the human-machine interaction terminal through the human-machine interface for manual adjustment by the user or administrator.

[0081] Step 330: Determine the network scores of all heterogeneous networks according to the preset evaluation rules, and select whether to switch the network based on the network scores; For example, the "network adjudication system" under the AP master control module comprehensively evaluates the cleaned signal data, and calculates the current best network or retains multiple candidate networks in combination with factors such as user policies, service requirements, and historical data.

[0082] Furthermore, if the mutual exclusion effect between networks or the risk of "ping-pong handover" is detected, start the anti-shake or hysteresis mechanism to delay or ignore short-term fluctuations and improve the handover stability.

[0083] Preferably, in step 330, select to switch the network. By presetting multiple decision-making parameters and using a dynamic calculation model to comprehensively evaluate the real-time signal data of each network, and ensuring the stability and rationality of the switch through a hysteresis strategy and an accumulation judgment mechanism. Finally, generate a switching decision. Through signal acquisition, obtain the real-time signal data reported by each sub-module from the network detection system, and at the same time obtain decision-making parameters such as a preset target signal priority switch, signal threshold, switching sensitivity, anti-ping-pong switching time interval, and switching threshold, which need to meet the following conditions: The score difference between the current network and the optimal candidate network is greater than the set hysteresis threshold.

[0084] For example, for the switching threshold calculation, where the sensitivity is a user-configurable parameter that can dynamically adjust the switching sensitivity of the entire system; the higher the sensitivity, the lower the cumulative amount required to trigger a switch, making it easier to switch; conversely, a lower sensitivity makes the system more stable and less likely to switch frequently due to short-term fluctuations.

[0085] The switching threshold is a dynamically calculated version of the hysteresis threshold, and its value = hysteresis threshold × sensitivity coefficient.

[0086] The score advantage time of the optimal candidate network is greater than the first set time threshold; For example, for the hysteresis strategy algorithm, set a minimum switching interval. Even if the switching condition is met, it needs to be stable for N seconds before execution to achieve a smooth switch. After one switch, it must wait N seconds before the next switch can be made, effectively preventing frequent switching and ineffective back-switching caused by signal fluctuations in a short period while ensuring the rationality of the switch. The fixed minimum switching interval is the basic version of the dynamic time window.

[0087] For example, for the dynamic time window constraint, the duration requirement: the score advantage of the optimal candidate network needs to remain above the dynamically calculated time window (the first set time threshold).

[0088] The length of the time window is dynamically adjusted according to signal stability (the greater the fluctuation, the longer the time window).

[0089] If the score of the optimal candidate network is only higher than that of the current network within the set time window, no switching is triggered.

[0090] The score of the current network does not rebound within the second set time threshold, or the optimal candidate network does not deteriorate within the third set time threshold.

[0091] Trend prediction veto power. Even if the score of the currently optimal candidate network is higher, if the prediction model determines that: The current network score will rebound within a set future time; or, if the optimal candidate network signal deteriorates rapidly (e.g., a satellite network is about to leave the coverage area), the system will actively suppress the handover.

[0092] For example, dynamically adjust the handover interval time. On the above basis, instead of being limited to a fixed N seconds, it is based on respective thresholds + signal trend analysis + short-term fluctuations + long-term signal stability to dynamically decide the waiting time for handover. It can also be further optimized to exponential adjustment, adjusting the handover interval in a non-linear manner. If the signal gap before and after handover is large, the short-term signal fluctuates greatly and the signal change is long-term unstable, it indicates that the current signal is deteriorating rapidly, and the target signal is better than the current signal. Therefore, the signal environment brought by the handover will improve, and it should be quickly handed over to reduce the waiting time to adapt to the rapid adjustment of the network environment. If the signal gap before and after handover is small, the short-term signal fluctuates little and the signal change is long-term stable, it indicates that the current signal environment is stable, and the waiting time should be appropriately extended to avoid repeated handovers and reduce the jitter risk. If the short-term signal changes and the signal change is long-term stable, and the signal has short-term fluctuations, the waiting time should be adjusted conservatively.

[0093] Cumulative judgment and handover decision. Start the periodic adjudication algorithm. Calculate the handover amount by cumulative summation in each cycle. When the total handover amount is less than or equal to the bottom threshold, the adjudication algorithm is exited. When the total handover amount is greater than the handover standard and all handover conditions are met, enter the target network mode handover state, and the AP side completes the seamless handover.

[0094] Furthermore, the cumulative handover amount = , cumulative strategy. Iteratively accumulate in units of 1 second, which can smooth out instantaneous fluctuations, so that only when the current signal environment continues to deteriorate (or the target network continues to be superior), the cumulative amount will gradually increase to the preset threshold, thereby triggering a handover and avoiding mis-handovers or jitters.

[0095] Single handover amount calculation is set based on the comprehensive signal quality difference between the current network and the target network. The value range of the single handover amount is preset for different signal difference levels to obtain the single handover amount.

[0096] Core service protection and decision-making judgment. In the core service scenario, the system will give priority to maintaining the current network connection and avoid handovers. At the same time, according to the decline speed of the current signal quality and the preset service factor, the system adjusts the signal query interval, making the query interval shorter when the signal is worse, so as to timely capture network deterioration information.

[0097] In one embodiment, the present application realizes intelligent forward-looking decision-making through the network trend simulation analysis module of the prediction model. This module uses time series analysis (ARIMA / LSTM) algorithms to predict the change trends of key indicators such as future RSSI, latency, and packet loss rate based on real-time signal sampling data. At the same time, it integrates the Monte Carlo simulation method, and through the simulation calculation of multiple potential handover paths, quantitatively evaluates the benefit-cost ratio of each path (Benefit = Target network score gain × Service weight - Handover time × Service priority), and outputs the Pareto optimal solution set. Finally, a handover strategy that takes into account both short-term stability and long-term benefits is generated through the TD3 reinforcement learning algorithm. This module is intelligently linked with the service strategy matching module, and when the standard deviation of signal fluctuation or service priority is detected to be greater than the set threshold, it automatically triggers the real-time prediction-simulation process to ensure that the handover interruption time of critical services is controlled within the set time threshold, realizing the closed-loop control of network state prediction, benefit evaluation, and strategy optimization.

[0098] The present application realizes differential intelligent handover control through the service-aware handover strategy. This strategy establishes a dynamic mapping model of service type - handover parameters, and automatically adjusts the handover threshold parameters according to real-time service characteristics (such as voice / video / industrial control, etc.) and preset priorities: for high-bandwidth services such as video streams, the latency handover threshold is tightened and the bandwidth weight is increased; for critical services such as industrial control, the packet loss rate threshold is strictly limited within the set threshold and the hysteresis threshold is expanded; when the service priority is greater than the set threshold level, the system automatically triggers the prediction-simulation linkage mechanism, and under the premise of ensuring the set handover interruption time limit, the optimal handover scheme is selected from 1000 paths through Monte Carlo simulation.

[0099] In one embodiment, in step 330, the normalization process specifically includes the steps: The core of the normalization process is to uniformly parse, normalize, and comprehensively score the heterogeneous data reported by different network sub-modules (including public network, narrowband private network, broadband private network, WiFi, satellite network, etc.), so as to generate a unified network quality indicator: "signal", providing a quantitative basis for subsequent network adjudication and handover decision-making.

[0100] Each heterogeneous network sub-module continuously collects key indicators on its communication link. For communication networks such as WiFi, public network, and private network, the collected data includes signal strength (RSSI), latency, bandwidth, packet loss rate, and network load, as shown in Table 2; for the positioning network, parameters such as signal-to-noise ratio, signal stability and packet loss rate, Doppler effect, and time delay are collected. Each sub-module ensures the real-time and continuous data collection, and immediately reports abnormal information when detecting abnormal states (such as flight mode, no signal, or SIM card failure, etc.).

[0101] Table 2

[0102] Step 330-1: Unify the units or formats of the data in the heterogeneous network according to a preset data format. For example, use the preset data format conversion rules to unify the units and formats of data of different network types.

[0103] Step 330-2: Perform outlier detection on the data, remove noise points and outlier data, and supplement missing data. For example, use statistical analysis methods (including Z-Score or box plot method) to perform outlier detection on the data, identify and remove noise points and outlier data; for missing data, use median imputation, mean filling or prediction methods based on historical data to complete. Finally, perform strict range and logical verification on the cleaned data to ensure that each index falls within the preset reasonable threshold.

[0104] Step 330-3: Preset the ideal values of each index, and use the linear normalization formula for the index where the larger the value, the better the quality; use the reverse normalization for the index where the smaller the value, the better the quality.

[0105] For the mapping and normalization processing of multi-mode network data, the present invention presets the ideal value Vmax and the worst value Vmin of each index. For the indexes that are better with larger values, including signal strength and bandwidth, the linear normalization formula is used; for the indexes that are better with smaller values, including delay, packet loss rate, and network load, the reverse normalization is used.

[0106] Further, determine the network score, specifically including the steps: Step 330-4: Weight and sum the normalized indexes to generate a comprehensive score signal.

[0107] According to the degree of attention of different network types to key indexes, introduce dynamic weights and necessary constants or offsets, weight and sum each normalized index, and generate a unified comprehensive score "signal". Further preferably, unify the signal output and trigger the subsequent process. After the processing of steps 330-1 to 330-3, all heterogeneous network data are purified and uniformly converted into a single index "signal", and the signal value is within a predetermined interval, which can comprehensively reflect the overall quality of the current network. This unified "signal" is then transmitted to the network decision module.

[0108] Step 340: Send an instruction to switch the network.

[0109] If the adjudication result shows that switching is required, the "network switching system" issues a switching command to the CP network module according to the adjudication instruction, specifying the target network mode.

[0110] The AP master control module receives the handover result sent by the CP network module, reports the current network handover result to the user or the background system, and records the handover process in the log.

[0111] Figure 4 It is a schematic diagram of an embodiment of a network device.

[0112] An embodiment of the present application also proposes a network device for implementing the method of any one of the embodiments of the present application. The network device is used to: obtain the first real-time signal information of at least two heterogeneous networks and send it to the master control device.

[0113] To implement the above technical solution, a network device 400 proposed by the present application includes a network sending module 401, a network determination module 402, and a network receiving module 403 that are connected to each other.

[0114] The network sending module is used to send the first real-time signal information.

[0115] The network determination module is used to obtain the first real-time signal information of at least two heterogeneous networks.

[0116] The network receiving module is used to receive the instruction to switch the network.

[0117] The specific methods for implementing the functions of the network sending module, the network determination module, and the network receiving module are as described in the method embodiments of the present application and will not be elaborated here.

[0118] The network device described in the present application may refer to a base station facility, a network device or a server connected to the base station, may also be a system providing services for the above devices, and may also be any system, subsystem, module, circuit, chip or software running device for receiving, sending, identifying, and processing information for the above devices.

[0119] Figure 5 It is a schematic diagram of an embodiment of the master control device.

[0120] The present application also proposes a master control device for implementing the method of any one of the embodiments of the present application. The master control device is used to: receive the first real-time signal information; Normalize the first real-time signal information to determine the second real-time signal information; Determine the network scores of all heterogeneous networks according to the preset evaluation rules, and select whether to switch the network according to the network scores; Send the instruction to switch the network.

[0121] To implement the above technical solution, a master control device 500 proposed by the present application includes a master control sending module 501, a master control determination module 502, and a master control receiving module 503 that are connected to each other.

[0122] The master control end receiving module is configured to receive the first real-time signal information.

[0123] The master control end determining module is configured to normalize the first real-time signal information to determine the second real-time signal information. It is also configured to determine the network scores of all heterogeneous networks according to a preset evaluation rule, and select whether to switch the network according to the network scores.

[0124] The master control end sending module is configured to send an instruction to switch the network.

[0125] The specific methods for implementing the functions of the master control end sending module, the master control end determining module, and the master control end receiving module are as described in the method embodiments of this application, and will not be elaborated here.

[0126] The master control end device described in this application may refer to a user equipment (UE), a personal mobile terminal, a smart terminal, a mobile phone, a computer with communication functions, or may also be a system that provides services for the above devices, or may also be any system, subsystem, module, circuit, chip, or software running device that provides information reception, sending, identification, and processing for the above devices.

[0127] The embodiments of this application further provide a heterogeneous network intelligent switching device for a multi-mode terminal, which is used to implement the heterogeneous network intelligent switching method for the multi-mode terminal described in any one of the first to third aspects, and includes: a network device and a master control end device; The network device includes at least two heterogeneous network modules, and is configured to obtain the first real-time signal information; The master control end device includes a network detection module and a network arbitration module; The network detection module is configured to normalize the first real-time signal information to determine the second real-time signal information; The network arbitration module is configured to determine the network scores of all heterogeneous networks according to a preset evaluation rule, and select whether to switch the network according to the network scores.

[0128] Furthermore, it further includes a network switching module, which is configured to send a switching instruction to the network device.

[0129] Figure 6The structural schematic diagram of a network device according to another embodiment of the present invention is shown. As shown in the figure, the network device 400 includes a network-side processor 405, a wireless interface 404, and a network-side memory 406. Among them, the wireless interface may be multiple components, that is, including a transmitter and a receiver, and provides a unit for communicating with various other devices on a transmission medium. The wireless interface realizes the communication function with the master control device, processes wireless signals through the receiving and transmitting devices, and the data carried by its signals communicates with the network-side memory or the network-side processor through an internal bus structure. The network-side memory 406 contains a computer program for implementing any embodiment of the present application, and the computer program runs or changes on the network-side processor 405. When the network-side memory, the network-side processor, and the wireless interface circuit are connected through a bus system, the bus system includes a data bus, a power bus, a control bus, and a status signal bus, which will not be elaborated here.

[0130] Figure 7 The block diagram of the master control device according to another embodiment of the present invention is shown. The master control device 500 includes at least one master control processor 504, a master control memory 505, a user interface 506, and at least one network interface 507. Each component in the master control device 500 is coupled together through a bus system. The bus system is used to realize the connection and communication between these components. The bus system includes a data bus, a power bus, a control bus, and a status signal bus.

[0131] The user interface 506 may include a display, a keyboard, or a pointing device, for example, a mouse, a trackball, a touchpad, or a touch screen, etc.

[0132] The master control memory 505 stores executable modules or data structures. The master control memory may store an operating system and application programs. Among them, the operating system contains various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application programs contain various application programs, such as a media player, a browser, etc., for implementing various application services.

[0133] In the embodiment of the present invention, the master control memory 505 contains a computer program for implementing any embodiment of the present application, and the computer program runs or changes on the master control processor 504.

[0134] The master control memory 505 contains a computer-readable storage medium. The master control processor 504 reads the information in the master control memory 506 and combines its hardware to complete the steps of the above method. Specifically, a computer program is stored on the computer-readable storage medium, and when the computer program is executed by the master control processor 504, it realizes the steps of the method embodiment as described in any of the above embodiments.

[0135] The master control processor 504 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the method of this application can be completed by the integrated logic circuit of the hardware in the master control processor 504 or the instructions in the form of software. The master control processor 504 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.

[0136] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. In a typical configuration, the device of this application includes one or more processors (CPUs), an input / output user interface, a network interface, and a master control memory.

[0137] It should be noted that the network-side processor, network-side memory, master control processor, or master control memory described in this application all fall within the scope of the processor or memory of the communication device described in this application, and no further limitation will be made here.

[0138] In addition, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0139] Therefore, this application also proposes a computer-readable medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the method described in any one of the embodiments of this application. For example, the network-side memory 406 or the master control memory 505 of the present invention may include non-permanent memories in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM.

[0140] Based on the embodiments of the above device of this application, this application also proposes a mobile communication system, which includes at least one embodiment of any master control device in this application and / or at least one embodiment of any network device in this application.

[0141] It should be noted that the specific mobile communication technology described in the present invention is not limited, and may be WCDMA, CDMA2000, TD-SCDMA, WiMAX, LTE / LTE-A, LAA, MuLTEfire, and the fifth-generation, sixth-generation, and Nth-generation mobile communication technologies that may appear in the future.

[0142] The terminal described in the present invention refers to a terminal-side product that can support the communication protocol of a land mobile communication system, especially a wireless modem module for communication, which can be integrated into various types of terminal forms such as mobile phones, tablets, and data cards to complete the communication function.

[0143] For the sake of convenience of description, the fourth-generation mobile communication system LTE / LTE-A and its derivative MulteFire are taken as examples. Among them, the mobile communication terminal can be represented as UE (User Equipment), and the access device on the network side can be represented as a base station or an access point.

[0144] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent in such process, method, commodity or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, commodity or device including the said element.

[0145] Those skilled in the art of the present technology can understand that unless expressly stated, the singular forms "a", "an", "the" and "said" used may also include the plural form. It should be understood that when a device or component is "connected" to another device or component, it can be directly connected to other devices or components, or there may also be intermediate devices or components. In addition, the "connection" used here can include partial wireless connection and can also include partial wired connection.

[0146] In the description of the present application, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances. In addition, in the description of the present application, unless otherwise specified, "a plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0147] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various modifications and changes can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A heterogeneous network intelligent switching method for a multi-mode terminal, characterized in that, The following steps are involved: Acquire first real-time signal information of at least two heterogeneous networks; the first real-time signal information includes network status parameters; the at least two heterogeneous networks include a currently used network; Normalizing the first real-time signal information to determine second real-time signal information; The network scores of all heterogeneous networks are determined according to the preset evaluation rules, and whether to switch networks is determined based on the network scores.

2. A heterogeneous network intelligent handover method for a multi-mode terminal, used for a network device, characterized in that The following steps are involved: Acquire first real-time signal information of at least two heterogeneous networks; the first real-time signal information includes network status parameters; the at least two heterogeneous networks include a currently used network; Sending first real-time signal information; Receive instructions to switch networks.

3. The heterogeneous network intelligent handover method of the multi-mode terminal according to claim 1 or 2, characterized in that, Switching networks includes the following steps: Receiving a switching instruction; the switching instruction includes a target network intervention parameter; Log out of the current network and keep the business data transmitted continuously during the logout process; Register the target network.

4. A heterogeneous network intelligent switching method for a multi-mode terminal, which is used for a master device, and is characterized in that, The following steps are involved: Receiving first real-time signal information; Normalizing the first real-time signal information to determine second real-time signal information; Determine the network scores of all heterogeneous networks according to the preset evaluation rules, and choose whether to switch networks according to the network scores; Send a command to switch networks.

5. The heterogeneous network intelligent handover method of the multi-mode terminal according to claim 1 or 4, characterized in that, Select Switch Network and meet the following conditions: The score difference between the current network and the best candidate network is greater than the set hysteresis threshold; The scoring advantage time of the best candidate network is greater than the first set time threshold; The current network score does not rebound within the second set time threshold, or the optimal candidate network does not deteriorate within the third set time threshold.

6. The heterogeneous network intelligent handover method of the multi-mode terminal according to claim 1 or 4, characterized in that, The normalization process specifically comprises the following steps: Unify the units or formats of data in heterogeneous networks according to the preset data format; Perform outlier detection on the data, remove noise and outlier data, and supplement missing data; The ideal value of each indicator is preset. For indicators with larger values, indicating better quality, a linear normalization formula is used; for indicators with smaller values, indicating better quality, a reverse normalization formula is used.

7. The heterogeneous network intelligent handover method of the multi-mode terminal according to claim 1 or 4, characterized in that, Determine the network score, including the following steps: The normalized indicators are weighted and summed to generate a comprehensive scoring signal.

8. The heterogeneous network intelligent handover method of the multi-mode terminal according to claim 1 or 4, characterized in that, The main control device includes a human-computer interaction interface for manually adjusting the parameters of the network score.

9. A heterogeneous network intelligent switching device for a multi-mode terminal, which is used to implement the heterogeneous network intelligent switching method of the multi-mode terminal according to any one of claims 1 to 8, characterized in that, Includes: network equipment and master control equipment; The network device comprises at least two heterogeneous network modules, which are used to obtain first real-time signal information; The main control terminal device includes a network detection module and a network decision module; The network detection module is used to normalize the first real-time signal information and determine the second real-time signal information; The network decision module is used to determine the network scores of all heterogeneous networks according to preset evaluation rules, and to select whether to switch networks according to the network scores.

10. A communication device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method as claimed in any one of claims 1 to 8.

11. A computer-readable medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method according to any one of claims 1 to 8.

12. A mobile communication system, comprising at least one network device for implementing the method described in claim 2 or 3 and / or at least one master device for implementing the method described in any one of claims 4 to 8.

Images