A method and device for intelligent handover of heterogeneous networks for multi-mode terminals

Abstract

This application discloses a method and device for intelligent switching between heterogeneous networks for multi-mode terminals. The method includes the following steps: acquiring first real-time signal information from at least two heterogeneous networks; the first real-time signal information includes network status parameters; the at least two heterogeneous networks include the currently used network; normalizing the first real-time signal information to determine second real-time signal information; determining network scores for all heterogeneous networks according to preset evaluation rules, and selecting whether to switch networks based on the network scores. This application also includes apparatus for implementing the method. This application addresses the problem of inconsistent parameters when multiple network indicators are used as the basis for network switching.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method and device for intelligent switching of heterogeneous networks for multi-mode terminals. Background Technology

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

[0003] Current network handover suffers from several problems: First, the decision-making dimensions and network detection methods are limited. Most existing technologies rely solely on RSSI (Resonance Signal Strength Index) as the basis for handover decisions, neglecting other key indicators such as network latency, packet loss rate, and service urgency. This leads to frequent handovers (the "ping-pong handover" phenomenon) in edge areas with significant signal fluctuations. Second, the handover decision-making and execution mechanisms are simplistic and lack stability. Due to the lack of lag control and trend prediction mechanisms, existing solutions are prone to unnecessary network mode switching due to short-term signal fluctuations in rapidly changing network environments. This reduces overall communication stability and user experience. Complex heterogeneous network scenarios require more flexible strategies, such as those based on real-time network status feedback, service demand analysis, load balancing, and manual intervention prompts, to ensure optimal network switching under various complex environments. Third, dynamic adaptability is weak. Some technical solutions use fixed parameters and static rules, which are not flexible enough in responding to changes in terminal service demands and network status. They cannot dynamically optimize handover weights and threshold parameters based on historical handover data or real-time network conditions, making it difficult to achieve optimal network resource allocation and cost control. At the same time, there is also the problem of limited cross-protocol adaptability. Most technologies only focus on switching between single networks (such as WiFi and cellular, WLAN and LTE), and lack seamless interoperability solutions between multiple network protocols such as public networks, private networks, and satellite networks, which cannot fully meet the needs of multi-protocol integrated collaboration in real-world scenarios.

[0004] Another issue is the high hardware dependency. Some solutions focus on switching control at the hardware circuit or SIM card level, which has high requirements for hardware deployment, resulting in high cost and limited applicability.

[0005] Meanwhile, human-computer interaction and status feedback are insufficient. Few solutions provide intuitive network status feedback and interactive 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 method and device for intelligent handover of heterogeneous networks for multi-mode terminals, which solves the problem of inconsistent parameters when multiple network indicators are used as the basis for network handover.

[0007] In a first aspect, embodiments of this application provide a method for intelligent handover of heterogeneous networks for multi-mode terminals, comprising the following steps:

[0008] Acquire first real-time signal information from at least two heterogeneous networks; the first real-time signal information includes network state parameters; the at least two heterogeneous networks include the currently used network;

[0009] The first real-time signal information is normalized to determine the second real-time signal information;

[0010] The network scores of all heterogeneous networks are determined according to the preset evaluation rules, and the network switching is selected based on the network scores.

[0011] Secondly, embodiments of this application also provide a method for intelligent handover of heterogeneous networks for multi-mode terminals, used in network devices, comprising the following steps:

[0012] Acquire first real-time signal information from at least two heterogeneous networks; the first real-time signal information includes network state parameters; the at least two heterogeneous networks include the currently used network;

[0013] Send the first real-time signal information;

[0014] Receive instructions to switch networks.

[0015] Furthermore, switching networks involves the following steps:

[0016] Receive a handover command; the handover command includes target network access parameters;

[0017] Cancel the current network while maintaining continuous transmission of business data during the cancellation process;

[0018] Register the target network.

[0019] Thirdly, this application also provides a method for intelligent switching of heterogeneous networks for multi-mode terminals, used in a master control device, comprising the following steps:

[0020] Receive first real-time signal information;

[0021] The first real-time signal information is normalized to determine the second real-time signal information;

[0022] The network scores of all heterogeneous networks are determined according to the preset evaluation rules, and the network switching is selected based on the network scores.

[0023] Send a command to switch networks.

[0024] Preferably, the network to be switched is selected based on the following conditions:

[0025] The score difference between the current network and the optimal candidate network is greater than the set hysteresis threshold;

[0026] The optimal candidate network's score advantage time is greater than the first set time threshold;

[0027] 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.

[0028] In one embodiment, the normalization process specifically includes the following steps:

[0029] According to the preset data format, the units or formats of data in heterogeneous networks are unified;

[0030] The data is subjected to outlier detection to remove noise and outlier data, and missing data is supplemented.

[0031] Ideal values ​​are preset for each indicator. For indicators with larger values, which indicate better quality, a linear normalization formula is used; for indicators with smaller values, which indicate better quality, an inverse normalization formula is used.

[0032] In one embodiment, determining the network score specifically includes the following steps:

[0033] The normalized indicators are weighted and summed to generate a comprehensive score signal.

[0034] In one embodiment, the main control device includes a human-computer interaction interface for manually adjusting the parameters of the network scoring.

[0035] Fourthly, embodiments of this application also provide a heterogeneous network intelligent switching device for multi-mode terminals, used to implement the heterogeneous network intelligent switching method for multi-mode terminals described in any one of the embodiments of the first to third aspects, comprising: a network device and a master control device. The network device includes at least two heterogeneous network modules for acquiring 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 normalize the first real-time signal information and determine second real-time signal information. The network decision module is used to determine the network score of all heterogeneous networks according to preset evaluation rules, and select whether to switch networks based on the network score.

[0036] This application also proposes a communication device, comprising: 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 described in any embodiment of the first aspect of this application.

[0037] This application also proposes a computer-readable medium on which a computer program is stored, which, when executed by a processor, implements the steps of the method as described in any embodiment of the first aspect of this application.

[0038] This application also proposes a mobile communication system, comprising at least one network device for implementing the method described in any embodiment of this application and / or at least one master control device for implementing the method described in any embodiment of this application.

[0039] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects:

[0040] This application employs multi-dimensional dynamic decision-making, overcoming the limitations of single-signal strength (RSSI) decision-making, and constructs an intelligent decision-making model that integrates signal quality, service requirements, network status, and user policies. A hysteresis control mechanism is introduced, setting a signal strength threshold difference and combining it with a signal prediction algorithm to predict network coverage change trends, eliminating frequent handovers in network edge areas and improving the stability of handover decisions. A reinforcement learning model is used to train strategies using historical handover data, dynamically optimizing network selection weights, and fuzzifying network status parameters to generate adaptive handover rules, achieving an upgrade from "static rules" to "dynamic learning" handover strategies. The broadband-narrowband convergence solution achieves real-time interoperability of any heterogeneous network protocols such as public networks, narrowband private networks, broadband private networks, WiFi, and satellite networks through core network convergence, meeting service needs in complex scenarios. This invention achieves intelligent handover at the pure software level, requiring no extensive hardware modifications, resulting in low deployment costs and broad compatibility. It provides visualized feedback on real-time network status, handover reasons, and results, making handover decisions more transparent and controllable, and supporting manual intervention and policy adjustments. Attached Figure Description

[0041] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0042] Figure 1 This is a flowchart illustrating an embodiment of the method of this application;

[0043] Figure 2 This is a flowchart illustrating an embodiment of the method of this application used in a network device;

[0044] Figure 3 This is a flowchart illustrating an embodiment of the method of this application used in a master control device;

[0045] Figure 4 This is a schematic diagram of a network device implementation example;

[0046] Figure 5 This is a schematic diagram of an embodiment of the main control device;

[0047] Figure 6 This is a schematic diagram of the structure of a network device according to another embodiment of the present invention;

[0048] Figure 7 This is a block diagram of a master control device according to another embodiment of the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0050] This application presents an intelligent handover system for multi-mode signals based on multi-mode terminals. By integrating four core technological innovations—a multi-dimensional decision-making model, hysteresis control mechanism, dynamic learning algorithm, and cross-protocol gateway—along with unified data normalization, dynamic weighting, smooth handover strategies, and user-defined intervention mechanisms, it systematically solves problems such as rigid decision-making, poor stability, fixed strategies, and protocol fragmentation in existing technologies. It also overcomes the challenges of frequent handovers and service interruptions caused by signal fluctuations in heterogeneous network environments. Through dynamic optimization and adaptive strategies carrying access parameters and service data, this system provides a highly reliable, low-latency, and adaptive multi-mode signal handover solution for scenarios such as emergency communication and industrial IoT, significantly improving the accuracy of network handover decisions and user experience, and achieving seamless and stable connections and intelligent resource scheduling across protocols and frequency bands.

[0051] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0052] Figure 1 This is a flowchart illustrating an embodiment of the method of this application.

[0053] This application proposes a method for intelligent handover of heterogeneous networks for multi-mode terminals, comprising the following steps 110-130:

[0054] Step 110: Obtain first real-time signal information from at least two heterogeneous networks; the first real-time signal information includes network state parameters; the at least two heterogeneous networks include the currently used network;

[0055] Step 120: Normalize the first real-time signal information to determine the second real-time signal information;

[0056] Step 130: Determine the network score of all heterogeneous networks according to the preset evaluation rules, and select whether to switch networks based on the network scores.

[0057] Furthermore, under the new network model, signals are continuously collected while monitoring network performance and service quality.

[0058] If switching failures or network quality issues persist, the "network adjudication system" can learn on its own or adjust the switching strategy and trigger the next round of switching processes until the optimal network is found to meet current business needs.

[0059] It should be noted that the above steps are used for network entities in wireless communication systems, including master control devices, network devices, or other intermediate devices; the above steps can also be used for service devices that provide information processing for the network entity devices; 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 master control devices or network devices.

[0060] Figure 2 This is a flowchart illustrating an embodiment of the method of this application used in a network device.

[0061] The method described in any embodiment of the first aspect of this application, used in a network device, includes the following steps 210-230:

[0062] Step 210: Obtain first real-time signal information from at least two heterogeneous networks; the first real-time signal information includes network status parameters; the at least two heterogeneous networks include the currently used network;

[0063] 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 indicators, including but not limited to signal strength, latency, bandwidth, packet loss rate, network load, etc.

[0064] The core responsibility of the CP network module is to coordinate the continuous and accurate output of signals between various sub-modules, ensure the continuity and real-time nature of signal acquisition data, resolve potential signal conflicts and interference issues, and ensure that each module can work normally and correctly reflect the current user's network environment under any network mode.

[0065] Step 220: Send the first real-time signal information;

[0066] For example, each heterogeneous network module will package and report the collected signal data to the AP main control module (main control device) in real time or periodically.

[0067] Furthermore, if the CP module detects a special state, such as airplane mode, no signal, or invalid SIM card, it will notify the AP main control module of the status information for subsequent decision-making.

[0068] Step 230: Receive the instruction to switch networks.

[0069] According to the ruling instruction, a switching command is issued to the CP network module, specifying the target network mode.

[0070] The CP network module performs the handover operation and returns the handover result (success, failure, or error) to the AP master module after completion so that the status can be updated.

[0071] Further, after step 230, the network is switched, which specifically includes the following steps:

[0072] Receive a handover command; the handover command includes target network access parameters;

[0073] The handover command is received and access parameters and service data are transmitted. The handover instruction is received from the network adjudication system. The instruction includes the target network access parameters and the accompanying access parameters and service data, ensuring that the access parameters and service data are preserved and transmitted during the handover process.

[0074] Cancel the current network while maintaining continuous transmission of business data during the cancellation process;

[0075] The current network is deregistered by sending a deregistration command to the current network to terminate the existing connection. During the deregistration process, the network switching module uses a caching mechanism and relay technology to ensure continuous transmission of access parameters and service data, so as to ensure seamless connection when registering the target network in the future.

[0076] Register the target network.

[0077] Register with the target network by sending a registration request and transmitting a switching command containing access parameters and service data. The registration request includes extended information to support the target network in automatically restoring its original services during the access process.

[0078] Furthermore, upon completion of the handover and status feedback, regardless of whether the handover was successful or failed, the system automatically resumes to the listening state, continuously monitors the network environment, prepares for the next handover, and returns the final handover status to the upper-level management system for subsequent analysis and strategy optimization.

[0079] Figure 3 This is a flowchart illustrating an embodiment of the method of this application used in a master control device.

[0080] The method described in any embodiment of the first aspect of this application, used in a master control device, includes the following steps 310-340:

[0081] Step 310: Receive the first real-time signal information;

[0082] The "Network Detection System" under the AP main control module receives signal data from various network modules.

[0083] The AP main control module is the core decision-making and execution unit of the entire network intelligent switching process. It can be divided into four subsystems: "user intervention system", "network detection system", "network adjudication system" and "network switching system".

[0084] The user intervention system, for example, includes a human-computer interaction interface in the main control device for manual adjustment of network scoring parameters. Functions include:

[0085] User / administrator preference management:

[0086] Used to provide a graphical user interface (GUI) or open API, allowing users or administrators to configure personalized preference parameters, prioritize a certain network (saving traffic, speed priority, reliability priority, etc.), or block access to specific networks in certain scenarios.

[0087] It is also used to respond to the detection of a conflict between the user's preset preferences and the results of the automatic decision. The user intervention system will provide feedback on the current network status and switching suggestions to the user through pop-up prompts, message notifications or voice alarms, so that manual confirmation or adjustment can be made.

[0088] Abnormal interaction and prompts are used to respond when the network detection system or network adjudication system detects severe network instability, extremely weak signal, or hardware failure. The user intervention system activates the abnormal feedback mechanism to automatically generate and send abnormal alarm information.

[0089] It is also used to visualize the handover results (current network mode, signal quality, and reasons for handover success or failure) in the form of charts, logs, and real-time curves, helping users to intuitively understand the network status and handover process.

[0090] Manual forced intervention is used by administrators in special scenarios such as emergency command and industrial control to manually trigger network switching to a designated network through a user interface or remote management platform.

[0091] In this application, the manual intervention system, as an important component of the AP main control module, displays real-time network quality information to users (or remote administrators) through an intuitive human-computer interaction interface, and allows users to autonomously adjust the decision parameters to achieve real-time intervention and optimization of network handover behavior. The decision parameters are used to quantitatively evaluate various indicators in a multi-mode network environment, and their specific parameters and descriptions are shown in Table 1:

[0092] Table 1

[0093]

[0094] It is also used to allow administrators to intervene in a timely manner during critical business operations to ensure that network switching operations prioritize business continuity and security requirements, thereby effectively preventing business interruptions caused by insufficient intelligent switching judgment.

[0095] The feedback algorithm and closed-loop control are used to tightly couple with the network detection, network adjudication, and network handover systems. This allows the system to collect historical handover data, abnormal events, network fluctuations, and user control records in real time. Statistical analysis methods such as moving averages, exponential smoothing, or linear regression are used, combined with machine learning models such as random forests, gradient boosting trees, and multilayer perceptrons, to establish a dynamic prediction model to calculate the deviation between the actual handover effect and the preset target.

[0096] Based on the aforementioned error calculation results, the system generates adaptive optimization suggestions, automatically adjusts the switching sensitivity, the time interval to prevent switching ping-pong, and modifies the signal threshold. Feedback results (including error trends, optimization suggestions, and parameter changes) are displayed in real-time through graphs, trend curves, and statistical reports, allowing users to understand the system's internal operation and optimize switching strategies through user intervention interfaces. The aforementioned real-time data acquisition, statistical analysis, predictive model output, error calculation, and parameter adjustment constitute a continuously iterative closed-loop intelligent feedback system.

[0097] The security 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 signatures and security auditing mechanisms, and to ensure that all control commands are signed and logged, thereby preventing unauthorized modification and tampering.

[0098] The network detection system includes the following functions:

[0099] Signal data parsing and verification is used to receive real-time signal data from the CP network module, including RSSI, SINR, delay, and packet loss rate.

[0100] It is also used to filter, correct, or compensate for abnormal data to ensure that the signal information input to the network adjudication system is accurate and reliable.

[0101] Multi-dimensional network status assessment 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, and device online status.

[0102] It is also used to issue alarms to the user intervention system or network adjudication system in response to the detection of specific abnormal states, including SIM card failure and WiFi authentication failure.

[0103] It is also used for detection in special environments, performing additional processing (using backup parameters) in flight mode, offline mode, or signal weakened environments to improve the comprehensiveness of detection.

[0104] The security mechanism is used in the network detection system to authenticate the identity of each heterogeneous network submodule before reporting data, and to encrypt the collected data through symmetric encryption algorithms such as AES. At the same time, digital signatures and checksums / or hash algorithms are used to verify the integrity of the data, ensuring that the data is not stolen or tampered with during the transmission process.

[0105] The online adjudication system includes the following functions:

[0106] Intelligent decision-making algorithms employ a variety of 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 networks.

[0107] It is also used to dynamically adjust decision-making strategies based on business needs (real-time voice, video streaming, file transfer, etc.) and user preferences (cost priority, speed priority, low power consumption, etc.).

[0108] The anti-jitter and hysteresis mechanism is used to respond to network signal fluctuations around the critical value. To prevent frequent "ping-pong switching", hysteresis or time threshold control is introduced, and switching is only performed when the signal lasts for a certain period of time or when the threshold difference is met.

[0109] It is also used to predict trends in signal strength or data rate (based on linear regression or moving average of short-term historical data) to reduce false switching caused by instantaneous fluctuations.

[0110] Mutual exclusion management and load balancing are used to respond to the detection of mutual exclusion or conflict between two network modes. The adjudication system can take measures such as taking the lower priority network offline or delaying the switching to ensure the overall stability of the system.

[0111] It is also used to respond to the simultaneous activation of multiple networks in multi-mode, multi-standby scenarios to achieve load balancing or multi-link aggregation, and is managed in a unified manner by the adjudication system.

[0112] In the network adjudication system, all adjudication parameters used for decision-making are digitally signed and hashed for verification. Security auditing and anomaly logging mechanisms are also incorporated into the decision-making process to protect input data and decision outputs, ensuring the authenticity and integrity of the entire decision-making process and preventing potential security risks.

[0113] Furthermore, the dynamic adjustment decision strategy is an adaptive decision-making process driven by historical business data, in which the network adjudication system dynamically adjusts the adjudication strategy based on historical business data.

[0114] The network switching system includes the following functions:

[0115] Command generation and issuance are used to generate switching commands based on the decision results of the network adjudication system, including specific parameters such as target network type, access point information, authentication method, and power configuration.

[0116] It is also used to issue switching commands to the CP network module and to listen for status feedback during the execution process (whether the switching was successful, whether a retry is needed, etc.).

[0117] The handover process control is responsible for scheduling the entire handover process. It first disconnects the original network and releases related resources, and then connects to the target network and completes the necessary authentication or configuration information updates.

[0118] It is also used to respond to anomalies (authentication failure, network access denial, etc.) that occur during the handover process, record error information and notify the user intervention system or network adjudication system for processing.

[0119] Status write-back and logging are used to write the switch results to the system log or database after the switch is completed, so as to facilitate subsequent analysis and optimization.

[0120] It is also used to simultaneously update the global status of the AP master control module to ensure that other subsystems can obtain the latest network mode and related resource information.

[0121] The security mechanism ensures that all handover commands (including target network access parameters, access parameters, service data, and session context information) are transmitted using digital signatures and end-to-end encryption. Combined with secure session management, data buffering, and fault-tolerant automatic rollback mechanisms, it ensures data transmission security and service continuity during the handover process and effectively protects sensitive data even in abnormal situations.

[0122] This application adopts a modular, layered architecture design, constructing a "three horizontal and four vertical" intelligent switching system framework. The horizontal layers include:

[0123] The information perception layer (network detection system) achieves millisecond-level signal measurement and data acquisition through multi-mode terminals, and supports simultaneous monitoring of 12 indicators such as RSSI and latency of heterogeneous networks such as 5G / satellite / WiFi.

[0124] The resource optimization layer (network adjudication system + network switching system) integrates predictive models and business-aware strategies to achieve nanosecond-level intelligent decision-making and seamless switching execution.

[0125] The terminal interaction layer (user intervention system) provides a visual decision dashboard, supporting dynamic adjustment of network scoring parameters and emergency intervention.

[0126] In terms of vertical functionality, the four subsystems form a closed-loop data flow:

[0127] The detection system achieves high-frequency sampling, the adjudication system dynamically optimizes the decision-making model through reinforcement learning, the switching system ensures zero-loss transmission of business data, and the user system realizes human-machine collaboration of "decision-feedback-optimization".

[0128] Step 320: Normalize the first real-time signal information to determine the second real-time signal information;

[0129] It also performs data parsing, cleaning, validation, and anomaly handling, such as correcting noise, missing values, or duplicate values.

[0130] Furthermore, if there is a conflict with user preferences or business strategies, the "user intervention system" will issue warnings or prompts through the human-computer interaction terminal via the human-computer interface, allowing users or administrators to make manual adjustments.

[0131] Step 330: Determine the network score of all heterogeneous networks according to the preset evaluation rules, and select whether to switch networks based on the network scores;

[0132] For example, the "Network Adjudication System" under the AP main control module comprehensively evaluates the cleaned signal data, and calculates the current best network or retains multiple candidate networks by combining factors such as user policies, business needs and historical data.

[0133] Furthermore, if mutual exclusion effects or "ping-pong handover" risks are detected between networks, anti-jitter or hysteresis mechanisms are activated to delay or ignore short-term fluctuations and improve handover stability.

[0134] Preferably, in step 330, a switching network is selected. Multiple decision parameters are preset, and a dynamic calculation model is used to comprehensively evaluate the real-time signal data of each network. A hysteresis strategy and cumulative judgment mechanism are used to ensure the stability and rationality of the switching, ultimately generating a switching decision. Through signal acquisition, real-time signal data reported by each submodule is obtained from the network detection system. Simultaneously, preset decision parameters such as target signal priority switch, signal threshold, switching sensitivity, anti-ping-pong switching time interval, and switching threshold are acquired, which must meet the following conditions:

[0135] The score difference between the current network and the optimal candidate network is greater than the set hysteresis threshold.

[0136] For example, in the calculation of the switching threshold, sensitivity is used as a user-configurable parameter, which 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, the lower the sensitivity, the more stable the system is, and it will not switch frequently due to short-term fluctuations.

[0137] The switching threshold is a dynamically calculated version of the hysteresis threshold, and its value is equal to the hysteresis threshold multiplied by the sensitivity coefficient.

[0138] The optimal candidate network's score advantage time is greater than the first set time threshold;

[0139] For example, the hysteresis strategy algorithm sets a minimum handover interval. Even if the handover conditions are met, it needs to remain stable for N seconds before execution, achieving a smooth handover. After one handover, it must wait N seconds before the next handover can proceed, ensuring the rationality of the handover while effectively preventing frequent handovers and invalid back-switching caused by short-term signal fluctuations. The fixed minimum handover interval is the basic version of the dynamic time window.

[0140] For example, dynamic time window constraints and duration requirements: the scoring advantage of the best candidate network must be maintained for more than the dynamically calculated time window (the first set time threshold).

[0141] The length of the time window is dynamically adjusted based on the signal stability (the greater the fluctuation, the longer the time window).

[0142] If the score of the best candidate network is higher than that of the current network only within a set time window, the switching will not be triggered.

[0143] 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.

[0144] Trend prediction veto power: Even if the current best candidate network has a higher score, if the prediction model determines that:

[0145] If the current network score is expected to rebound within a set timeframe, or if the signal of the best candidate network is expected to deteriorate rapidly (e.g., the satellite network is about to leave the coverage area), the system will actively suppress the handover.

[0146] For example, dynamically adjusting the handover interval, based on the above, is not limited to a fixed N seconds. Instead, it dynamically decides the handover waiting time based on each threshold, signal trend analysis, short-term fluctuations, and long-term signal stability. Further optimization can be achieved through exponential adjustment, using a non-linear approach to adjust the handover interval. If the signal difference before and after the handover is large, with significant short-term signal fluctuations and long-term unstable signal changes, it indicates that the current signal is rapidly deteriorating, and the target signal is better than the current signal. The signal environment will therefore improve due to the handover, and a rapid handover should be initiated to reduce waiting time and adapt to the rapid adjustment of the network environment. If the signal difference before and after the handover is small, with minimal short-term signal fluctuations and long-term stable signal changes, it indicates that the current signal environment is stable. The waiting time should be appropriately extended to avoid back-and-forth handovers and reduce jitter risk. If there are short-term signal changes that are long-term stable, and short-term signal fluctuations, the waiting time should be adjusted conservatively.

[0147] The algorithm performs cumulative judgment and handover decision-making, and initiates a periodic adjudication algorithm. The handover amount is calculated by summing the results in each period. When the total handover amount is less than or equal to the bottom line threshold, the adjudication algorithm is terminated. When the total handover amount is greater than the handover standard and all handover conditions are met, the algorithm enters the target network mode handover state, and the AP side completes the seamless handover.

[0148] Furthermore, the cumulative number of handovers = The cumulative strategy, which iterates and accumulates in units of 1 second, can smoothly handle instantaneous fluctuations. This ensures that the accumulated amount will only gradually increase to a preset threshold when the current signal environment continues to deteriorate (or the target network continues to be superior), thereby triggering a switch and avoiding false switches or jitter.

[0149] The single handover quantity is calculated based on the comprehensive signal quality difference between the current network and the target network. The range of single handover quantity values ​​is preset under different signal difference levels to obtain the single handover quantity.

[0150] In core business protection and decision-making scenarios, the system will prioritize maintaining the current network connection and avoid switching. At the same time, based on the rate of decline in current signal quality and preset business factors, the system will adjust the signal query interval, so that the query interval is shorter when the signal is worse, thereby capturing network degradation information in a timely manner.

[0151] In one embodiment, this application achieves intelligent forward-looking decision-making through a network trend simulation analysis module of a predictive model. This module employs a time series analysis (ARIMA / LSTM) algorithm to predict future trends in key indicators such as RSSI, latency, and packet loss rate based on real-time signal sampling data. Simultaneously, it integrates a Monte Carlo simulation method to quantitatively evaluate the cost-benefit ratio of each path (benefit = target network score gain × service weight - handover time × service priority) through multiple simulation calculations of potential handover paths, outputting a Pareto optimal solution set. Finally, it generates a handover strategy that balances short-term stability and long-term benefits using the TD3 reinforcement learning algorithm. This module intelligently links with the service policy matching module, automatically triggering a real-time prediction-simulation process when the standard deviation of signal fluctuation or the service priority exceeds a set threshold. This ensures that the handover interruption time for critical services is controlled within the set time threshold, achieving closed-loop control of network state prediction, benefit assessment, and strategy optimization.

[0152] This application achieves differentiated intelligent handover control through a service-aware handover strategy. This strategy establishes a dynamic mapping model between service type and handover parameters, and automatically adjusts the handover threshold parameters according to real-time service characteristics (voice / video / industrial control, etc.) and preset priorities: for high-bandwidth services such as video streaming, the delay 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 to 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 a prediction-simulation linkage mechanism, and selects the optimal handover scheme from 1000 paths through Monte Carlo simulation, while ensuring the set handover interruption time limit.

[0153] In one embodiment, step 330, the normalization process specifically includes the following steps:

[0154] The normalization process is essentially about uniformly parsing, normalizing, and comprehensively scoring heterogeneous data reported from different network sub-modules (including public networks, narrowband private networks, broadband private networks, WiFi, satellite networks, etc.) to generate a unified network quality indicator: "signal," which provides a quantitative basis for subsequent network adjudication and handover decisions.

[0155] Each heterogeneous network submodule continuously collects key metrics on its communication link. For communication networks such as WiFi, public networks, and private networks, 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 latency are collected. Each submodule ensures the real-time and continuous nature of data collection and immediately reports abnormal information when abnormal states are detected (airplane mode, no signal, or SIM card failure, etc.).

[0156] Table 2

[0157]

[0158] Step 330-1: Standardize the units or format of the data in the heterogeneous network according to the preset data format;

[0159] For example, by using preset data format conversion rules, the units and formats of data from different network types can be standardized.

[0160] Step 330-2: Perform outlier detection on the data, remove noise and outlier data, and supplement missing data;

[0161] For example, statistical analysis methods (including Z-score or box plot methods) are used to detect outliers, identify and remove noise and outliers; for missing data, median imputation, mean imputation, or prediction methods based on historical data are used to complete the data. Finally, the cleaned data undergoes rigorous range and logic checks to ensure that all indicators fall within preset reasonable thresholds.

[0162] Step 330-3: Preset the ideal values ​​for each indicator. For indicators with larger values, which indicate better quality, use a linear normalization formula; for indicators with smaller values, which indicate better quality, use inverse normalization.

[0163] In the multi-mode network data mapping and normalization process, this invention pre-sets the ideal value Vmax and the worst value Vmin for each indicator. For indicators where larger values ​​are better, including signal strength and bandwidth, a linear normalization formula is used; for indicators where smaller values ​​are better, including latency, packet loss rate, and network load, inverse normalization is used.

[0164] Further, determining the network rating involves the following steps:

[0165] Step 330-4: Weighted summation of the normalized indicators to generate a comprehensive scoring signal.

[0166] Based on the different network types' focus on key indicators, dynamic weights and necessary constants or offsets are introduced to perform a weighted summation of the normalized indicators, generating a unified comprehensive score "signal".

[0167] More preferably, after processing steps 330-1 to 330-3, all heterogeneous network data are purified and uniformly converted into a single indicator "signal" with a value within a predetermined range, which can comprehensively reflect the overall quality of the current network. This unified "signal" is then transmitted to the network adjudication module.

[0168] Step 340: Send the command to switch networks.

[0169] If the ruling indicates that a switch is required, the "network switching system" issues a switching command to the CP network module according to the ruling instructions, specifying the target network mode.

[0170] 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 backend system, and logs the handover process.

[0171] Figure 4 This is a schematic diagram of a network device implementation.

[0172] This application also proposes a network device for implementing the method of any embodiment of this application. The network device is used to: acquire first real-time signal information of at least two heterogeneous networks and send it to a master control device.

[0173] To implement the above technical solution, this application proposes a network device 400, which includes a network transmitting module 401, a network determining module 402, and a network receiving module 403 that are interconnected.

[0174] The network transmission module is used to transmit first real-time signal information.

[0175] The network determination module is used to acquire the first real-time signal information of at least two heterogeneous networks.

[0176] The network receiving module is used to receive instructions to switch networks.

[0177] The specific methods for implementing the functions of the network sending module, network determining module, and network receiving module are as described in the various method embodiments of this application, and will not be repeated here.

[0178] The network equipment described in this application may refer to base station facilities, network equipment or servers connected to base stations, systems that provide services for the aforementioned equipment, or any system, subsystem, module, circuit, chip or software operating device that provides information reception, transmission, identification and processing for the aforementioned equipment.

[0179] Figure 5 This is a schematic diagram of an embodiment of the main control device.

[0180] This application also proposes a master control device for implementing the method of any embodiment of this application, wherein the master control device is used to: receive first real-time signal information;

[0181] The first real-time signal information is normalized to determine the second real-time signal information;

[0182] The network scores of all heterogeneous networks are determined according to the preset evaluation rules, and the network switching is selected based on the network scores.

[0183] Send a command to switch networks.

[0184] To implement the above technical solution, this application proposes a master control terminal device 500, which includes a master control terminal transmitting module 501, a master control terminal determining module 502, and a master control terminal receiving module 503 that are interconnected.

[0185] The main control receiving module is used to receive the first real-time signal information.

[0186] The main control module is used to normalize the first real-time signal information and determine the second real-time signal information. It is also used to determine the network score of all heterogeneous networks according to preset evaluation rules, and to select whether to switch networks based on the network score.

[0187] The main control terminal sending module is used to send instructions for switching networks.

[0188] 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 various method embodiments of this application, and will not be repeated here.

[0189] The main control 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 a system that provides services for the above-mentioned devices. It may also refer to any system, subsystem, module, circuit, chip, or software running device that provides information reception, transmission, identification, and processing for the above-mentioned devices.

[0190] This application also provides a heterogeneous network intelligent switching device for multi-mode terminals, used to implement the heterogeneous network intelligent switching method for multi-mode terminals described in any one of the embodiments of the first to third aspects, comprising: a network device and a master control device;

[0191] The network device includes at least two heterogeneous network modules for acquiring first real-time signal information;

[0192] The main control device includes a network detection module and a network adjudication module;

[0193] The network detection module is used to normalize the first real-time signal information and determine the second real-time signal information;

[0194] The network adjudication module is used to determine the network score of all heterogeneous networks according to preset evaluation rules, and to select whether to switch networks based on the network score.

[0195] Furthermore, it also includes a network switching module for sending switching commands to network devices.

[0196] Figure 6A schematic diagram of a network device according to another embodiment of the present invention is shown. As shown, the network device 400 includes a network-side processor 405, a wireless interface 404, and a network-side memory 406. The wireless interface may consist of multiple components, including a transmitter and a receiver, providing a unit for communication with various other devices over a transmission medium. The wireless interface implements communication functions with the main control device, processes wireless signals through receiving and transmitting devices, and the data carried by the signals is communicated with the network-side memory or network-side processor via an internal bus structure. The network-side memory 406 contains a computer program that executes any embodiment of this application, and the computer program runs or modifies the network-side processor 405. When the network-side memory, network-side processor, and 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 described in detail here.

[0197] Figure 7 This is a block diagram of a master control device according to another embodiment of the present invention. 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. The various components in the master control device 500 are coupled together via a bus system. The bus system is used to implement communication between these components. The bus system includes a data bus, a power bus, a control bus, and a status signal bus.

[0198] User interface 506 may include a display, keyboard, or clicking device, such as a mouse, trackball, touchpad, or touchscreen.

[0199] The main control terminal memory 505 stores executable modules or data structures. The main control terminal memory can store the operating system and application programs. The operating system includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application programs include various applications, such as media players and browsers, used to implement various application functions.

[0200] In an embodiment of the present invention, the master control memory 505 contains a computer program that executes any embodiment of the present application, and the computer program runs or is modified on the master control processor 504.

[0201] The main control memory 505 includes a computer-readable storage medium. The main control processor 504 reads information from the main control memory 506 and, in conjunction with its hardware, completes the steps of the above method. Specifically, the computer-readable storage medium stores a computer program. When the computer program is executed by the main control processor 504, it implements the steps of the method embodiments described in any of the above embodiments.

[0202] The main control processor 504 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the method in this application can be completed by the integrated logic circuitry in the hardware of the main control processor 504 or by instructions in software form. The main control processor 504 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, an off-the-shelf programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor.

[0203] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely 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 host memory.

[0204] It should be noted that the network-side processor, network-side memory, main control processor, or main control memory mentioned 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 is made here.

[0205] Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0206] Therefore, this application also proposes a computer-readable medium storing a computer program that, when executed by a processor, implements the steps of the method described in any embodiment of this application. For example, the network-side memory 406 or the host-side memory 505 of this invention may include non-permanent memory in the form of computer-readable medium, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM.

[0207] Based on the embodiments of the above-described apparatus in this application, this application also proposes a mobile communication system, including 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.

[0208] It should be noted that the specific mobile communication technology described in this invention is not limited, and can be WCDMA, CDMA2000, TD-SCDMA, WiMAX, LTE / LTE-A, LAA, MuLTEfire, and subsequent fifth-generation, sixth-generation, and Nth-generation mobile communication technologies.

[0209] The terminal described in this invention refers to a terminal-side product that can support the communication protocols of terrestrial mobile communication systems, and a specially designed wireless modem module that can be integrated into various types of terminal forms such as mobile phones, tablets, and data cards to complete communication functions.

[0210] For ease of description, the fourth-generation mobile communication system LTE / LTE-A and its derivative MulteFire are used as examples, where the mobile communication terminal can be represented as UE (User Equipment), and the network-side access equipment can be represented as a base station or access point.

[0211] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0212] Those skilled in the art will understand that, unless otherwise stated, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be understood that when a device or component is “connected” to another device or component, it may be directly connected to the other device or component, or there may be an intermediary device or component. Furthermore, the term “connection” as used herein may include partially wireless connections as well as partially wired connections.

[0213] In the description of this application, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0214] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for intelligent handover of heterogeneous networks for multi-mode terminals, characterized in that, Includes the following steps: The network scores of all heterogeneous networks are determined according to the preset evaluation rules, and the network switching is selected based on the network scores. To switch networks, the following conditions must be met: Based on the network score difference between the current network and the target network, the single handover amount is set, and the range of single handover amount values ​​for different signal difference levels is preset to obtain the single handover amount; The total number of handovers is calculated by summing the results over the period. If the total number of handovers is less than or equal to the bottom line threshold, the decision algorithm is terminated. If the total number of handovers is greater than the handover standard, the target network mode handover state is entered. The switching interval is dynamically adjusted. If the signal difference is large, the short-term signal fluctuation is large or the change is unstable in the long term, the waiting time is reduced; if the signal difference is small, the short-term signal fluctuation is small or the signal change is stable in the long term, the waiting time is extended.

2. The heterogeneous network intelligent handover method for multi-mode terminals as described in claim 1, characterized in that, Switching networks involves the following steps: Receive a handover command; the handover command includes target network access parameters; Cancel the current network while maintaining continuous transmission of business data during the cancellation process; Register the target network.

3. The heterogeneous network intelligent handover method for multi-mode terminals as described in claim 1, characterized in that, The preset evaluation rule is to quantify and evaluate various indicators in a multi-mode network environment through adjudication parameters; The decision parameters include: target signal priority switch, signal threshold, switching sensitivity, anti-ping-pong switching time interval, switching threshold, service factor, and weighting factor.

4. The heterogeneous network intelligent handover method for multi-mode terminals as described in claim 1, characterized in that, The handover threshold is calculated, where sensitivity is a user-configurable parameter that dynamically adjusts the handover sensitivity of the entire system; the higher the sensitivity, the lower the cumulative amount required to trigger a handover.

5. The heterogeneous network intelligent handover method for multi-mode terminals as described in claim 1, characterized in that, The process before switching networks also includes the following steps: Collect historical handover data, abnormal events, network fluctuations, or user control records; Utilize machine learning models to build dynamic prediction models; Automatically adjust switching sensitivity and modify signal threshold.

6. The heterogeneous network intelligent handover method for multi-mode terminals as described in claim 1, characterized in that, During the switching process, any of the following applies: Customizable interruption strategy with access parameters and service data carrying and recovery mechanism; Customize the delay or suppression of switching operations during critical core business processes.

7. The heterogeneous network intelligent handover method for multi-mode terminals as described in claim 1, characterized in that, It includes a human-computer interaction interface for manual adjustment of parameters for network scoring.

8. A heterogeneous network intelligent handover device for a multi-mode terminal, used to implement the heterogeneous network intelligent handover method for the multi-mode terminal according to any one of claims 1 to 7, characterized in that, Includes: network equipment and main control equipment; The network device includes at least two heterogeneous network modules for acquiring first real-time signal information; The main control device includes a network detection module and a network adjudication 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 adjudication module is used to determine the network score of all heterogeneous networks according to preset evaluation rules, and to select whether to switch networks based on the network score.

9. 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 described in any one of claims 1 to 7.

10. A computer-readable medium storing a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 7.

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