A SIM card multi-channel method for automatic cross-border network switching

Abstract

The present invention belongs to the field of communications technology and discloses a multi-channel method for SIM cards for automatic cross-border network switching, comprising: obtaining the current location of a terminal device, obtaining a list of MCCs supported by the SIM card that was most recently received from a cloud server and presented, and presenting a specific connectable target MCC; communicating via a transmission channel, digitizing the transmission channel into transmission channel data, and using the transmission channel data as input layer neurons of a BP neural network; obtaining a transmission request coefficient as an output layer neuron of the BP neural network, comparing the training sample test results with the test sample results to derive the transmission request coefficient; obtaining the transmission channel for the most recent transmission request in real time based on the transmission request coefficient presented on the terminal device by the connectable target MCC, and automatically switching networks according to actual needs.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and more particularly to a SIM card multi-channel method for automatically switching networks across countries. Background Art

[0002] The operating mode of existing SIM card technology is: SIM cards issued by country A need to obtain operator permission from country B before they can normally use the network permitted by the operator in country B. The network permitted by the operator generally polls all pre-stored available channels through the MCC list of country B. Therefore, before use, the user needs to set the optimal transmission channel as the preferred transmission channel of the SIM card. This results in a long network connection time and slow speed during use. Subsequently, the initial preferred transmission channel will be defaulted to the first transmission channel of the SIM card. The user end generally selects other transmission channels only when the first transmission channel cannot be used or the experience is particularly bad. This greatly limits the user's usage experience and cannot reasonably match the selection of the optimal transmission channel.

[0003] Therefore, for users who often go abroad, a SIM card that can automatically switch mobile networks in different countries and regions is needed. In view of this, the inventor of the present application has invented a SIM card multi-channel method for automatically switching networks across countries. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a SIM card multi-channel method for automatic cross-border network switching.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a multi-channel SIM card method for automatic cross-border network switching, comprising:

[0006] Obtain the current location of the terminal device where the SIM card is located, obtain the MCC list supported by the SIM card that was last received by the SIM card from the cloud server based on the current location of the terminal device, and present the specific connectable target MCC;

[0007] A communication connection between the connectable target MCC and the terminal device via a transmission channel is obtained, the transmission channel is digitized into transmission channel data, the transmission channel data includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz, and the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz are used as input layer neurons of a BP neural network.

[0008] Obtaining a transmission request coefficient csqq presented by the connectable target MCC on the terminal device as an output layer neuron of a BP neural network, wherein the transmission request coefficient is used to represent the signal strength of the connectable target MCC connected to the terminal device;

[0009] Obtaining a standard training sample set and a test sample set, and obtaining a standard training sample test result corresponding to the standard training sample set and a test sample test result corresponding to the test sample set based on a BP neural network;

[0010] Comparing the training sample test result and the test sample result to obtain the transmission request coefficient csqq,

[0011] According to the transmission request coefficient csqq presented on the terminal device by the connectable target MCC, the transmission channel for the most requested transmission is obtained in real time, and the network is automatically switched according to actual needs.

[0012] In a preferred embodiment, the analysis logic for generating the transmission channel data is as follows:

[0013] According to the current location of the terminal device, obtain the MCC list supported by the SIM card that was last received by the SIM card from the cloud server;

[0014] Analyze the MCC list supported by the SIM card to obtain a connectable target MCC, and establish a communication connection between the connectable target MCC and the terminal device through the transmission channel;

[0015] Each of the transmission channels under the cloud server is defined with a unique name, different resource quantities and computing capabilities;

[0016] Specifying different communication capabilities between any two of the transmission channels;

[0017] Each of the transmission channels is digitally processed into a certain number of transmission channel data, where the transmission channel data is a specific digital implementation of the transmission channel.

[0018] In a preferred embodiment, the transmission channel data includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz, and a transmission request coefficient csqq is generated by the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz;

[0019] Each transmission request coefficient csqq is requested on at least one transmission channel, and each transmission channel can receive one or more transmission requests.

[0020] In a preferred embodiment, the logic for generating the transmission signal loss coefficient xhsh is:

[0021] The formula for the transmission signal loss coefficient xhsh is:

[0022]

[0023] The signal strength at the nearest base station that can connect to the target MCC is B, the distance between the transmission signal at the nearest base station and the terminal device is d, and the efficiency of the transmission signal is p, which is the channel gain efficiency of the nearest base station in the transmission channel and the efficiency of the circuit energy consumption during the transmission process pc. μ represents the difference between the signal-to-noise ratio required in the actual system and the theoretical signal-to-noise ratio required when the system reaches theoretical capacity.

[0024] In a preferred embodiment, the logic for generating the resource allocation coefficient zyfp is:

[0025] The ratio of the resource requirements of the multiple transmission requests in the transmission channel to the number of resources in the transmission channel does not exceed the resource constraint threshold; the resource allocation weights of the multiple transmission requests in the transmission channel are normalized to obtain the resource allocation coefficient zyfp corresponding to the current transmission request;

[0026] The specific formula is:

[0027]

[0028] Among them, 0≤α≤1, 0≤β≤1, and α+β=1, α and β are weights, which are calculated by several groups of transmission request resource quantities Wn and resource transmission power CP; M is a constant correction coefficient, whose specific value can be preset by professional configuration personnel or generated by analytical function fitting; CT is the time difference between the current reception time and the issuance of the instruction.

[0029] In a preferred embodiment, the logic for generating the request constraint coefficient xthz is:

[0030]

[0031] Among them, the request constraint coefficient xthz is the ratio between the request arrival rate Vp and the request processing rate Vc in the transmission channel; Q is the correlation coefficient between the request arrival rate Vp and the request processing rate Vc, which is calculated by the request arrival rate Vp and the request processing rate Vc of several groups of transmission requests.

[0032] In a preferred embodiment, the logic for generating the transmission request coefficient csqq is:

[0033] The transmission request coefficient csqq can be obtained by formulating the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz. The specific formula is:

[0034]

[0035] in, ρ and ω are the correlation coefficients of the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz, respectively, which are calculated from several groups of transmission requests in actual applications.

[0036] In a preferred embodiment, the steps of obtaining a standard training sample set and a test sample set, and deriving the standard training sample test results corresponding to the standard training sample set and the test sample test results corresponding to the test sample set based on a BP neural network, include:

[0037] Obtain a standard training sample set and a test sample set; obtain a standard training sample test result of the standard training sample set based on a BP neural network; obtain a test sample test result of the standard training sample set based on a BP neural network; compare the standard training sample test result with the test sample test result to obtain a comparison result;

[0038] If all the comparison results are zero, it means that the network in the SIM card transmission channel can make a transmission request;

[0039] If there is a non-zero value in the comparison result, it means that the network in the SIM card transmission channel cannot make a transmission request.

[0040] In a preferred embodiment, the standard training sample set includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz;

[0041] The test sample set is a set of a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz in actual signal transmission.

[0042] In a preferred embodiment, the training sample test results and the test sample results are used to derive the transmission request coefficient csqq presented by the connectable target MCC on the terminal device, thereby verifying the predictive capability of the cable straightening prediction information;

[0043] And update the preset proportional coefficient of the transmission request coefficient csqq in real time. The preset proportional coefficient includes the difference μ between the signal-to-noise ratio required in the actual system and the signal-to-noise ratio required in theory when the system reaches the theoretical capacity, the weight α of the number of transmission request resources Wn and the weight β of the resource transmission power CP, the correlation coefficient Q between the request arrival rate Vp and the request processing rate Vc, and the correlation coefficient of the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz ρ, ω.

[0044] The technical effects and advantages of the present invention include: by digitally analyzing data in the transmission channel and outputting the results through a BP neural network, accurate detection and diagnosis can be achieved, thereby quickly and accurately diagnosing the transmission request coefficient csqq, thereby improving the polling time of the transmission request and greatly improving the accuracy of the transmission request coefficient csqq. By using the networks of multiple mobile network operators to provide services, good signal coverage and communication quality can be achieved in different locations. Even in international roaming services, networks can be automatically switched according to the MCC list supported by the SIM card.

[0045] The standard training sample test results and the test sample test results are compared to obtain the comparison results. The method of judging whether there is a zero value is used to judge whether the currently calculated transmission request coefficient csqq can be transmitted, which is more convenient for the machine to identify and judge, and also greatly facilitates the user to quickly switch networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 The figure is a schematic diagram of a multi-channel SIM card method for automatic cross-border network switching according to the present invention. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] In various embodiments of the present application, the terminal device may be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connection capabilities, or other processing devices connected to a wireless modem. The terminal device may be a mobile terminal, such as a mobile phone (or "cellular" phone) and a computer with a mobile terminal, for example, a portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted mobile device that exchanges voice and / or data with a wireless access network. For example, a MiFi device, a personal communication service (PCS) phone, a cordless phone, a personal digital assistant (PDA), and other devices. The terminal device may also be a mobile station (MS), a remote station (RS), an access point (AP), a remote terminal (RT), an access terminal (AT), a user terminal (UT), a user agent (UA), a user device, or a user equipment (UE), and the embodiments of the present application are not limited thereto.

[0049] The MiFi device is a portable broadband wireless device, similar to a credit card, combining the functions of a modem, router, and access point. The built-in modem can be used to access at least one wireless signal, while the router can share the connection between multiple users and wireless devices. The MiFi device can be used to set up a specific network and share the network connection from anywhere via a cellular connection, such as establishing a communication link with a cloud server.

[0050] The cloud server is used to generate and distribute a channel SIM card to the terminal device, enabling the terminal device to establish a communication connection with the cloud server based on the channel SIM card. The cloud server includes, but is not limited to, a server. The cloud server service configuration and business scale can be configured and flexibly adjusted based on user needs.

[0051] In addition, the cloud server in each embodiment of the present application is referred to as the cloud for short. The cloud can also be a server, manager or other network device, and this application does not limit this.

[0052] The channel SIM card in each embodiment of the present application includes a SIM card in the form of a soft card, that is, it can be a SIM card information record. The information record includes information such as IMSI (International Mobile Subscriber Identity), telephone number, KI, and OPC. The channel SIM card is used to establish a communication connection between the terminal device and the cloud. The SIM card includes SIM card, USIM card, RUIM card, UIMD card, etc.

[0053] Example 1

[0054] See also Figure 1 As shown, the SIM card multi-channel method for automatically switching networks across countries described in this embodiment includes:

[0055] Obtain the current location of the terminal device where the SIM card is located, obtain the MCC list supported by the SIM card that was last received by the SIM card from the cloud server based on the current location of the terminal device, and present the specific connectable target MCC;

[0056] It should be noted here that: MCC here is the abbreviation of mobile country code. By obtaining the mobile country code MCC corresponding to the current location, that is, the target MCC described in this application, after the terminal device is turned on, the current location is first obtained through the terminal device using GPS, base station positioning or other positioning technologies, and the MCC table of the mobile network operator is queried through the cloud server. The MCC table of the mobile network operator usually includes the MCC values ​​of all countries and regions, which can be stored in the terminal device or obtained through the network; determine the mobile country code MCC corresponding to the current location. Some countries have only one mobile country code MCC, such as China, but the United States has 4 network operators and 4 mobile country codes MCC. Therefore, there are multiple mobile country codes MCC at the current location of the terminal device, especially in border areas, where this division is more obvious. Therefore, in this case, we need to analyze the transmission channel of the target MCC in order to obtain the optimal transmission channel.

[0057] The method for obtaining the MCC list supported by the SIM card is as follows: the SIM card is installed in the terminal device, and the terminal device can obtain the identification code IMSI of the SIM card and parse the mobile country code MCC and mobile network code MNC contained therein; the terminal device connects to the cloud server that communicates with the SIM card through the SIM card, obtains the mobile country code MCC list to which the SIM card can connect, that is, the MCC list supported by the SIM card, and determines the list of mobile network operators supported by the SIM card, that is, in which countries or regions the terminal device can use the SIM card;

[0058] Comparing the current location with the MCC list supported by the SIM card: The terminal device compares the mobile country code (MCC) corresponding to the current location with the MCC list supported by the SIM card to determine whether the terminal device can use the SIM card at the current location. If the mobile country code (MCC) corresponding to the current location is in the MCC list supported by the SIM card, the terminal device can use the SIM card at the current location; otherwise, the device needs to search for and connect to other available mobile networks to establish a communication connection.

[0059] The analysis logic for generating the transmission channel data is as follows:

[0060] According to the current location of the terminal device, obtain the MCC list supported by the SIM card that was last received by the SIM card from the cloud server;

[0061] Analyze the MCC list supported by the SIM card to obtain a connectable target MCC, and establish a communication connection between the connectable target MCC and the terminal device through the transmission channel;

[0062] Each of the transmission channels under the cloud server is defined with a unique name, different resource quantities and computing capabilities;

[0063] Specifying different communication capabilities between any two of the transmission channels;

[0064] Each of the transmission channels is digitally processed into a certain number of transmission channel data, where the transmission channel data is a specific digital implementation of the transmission channel.

[0065] A communication connection between the connectable target MCC and the terminal device via a transmission channel is obtained, the transmission channel is digitized into transmission channel data, the transmission channel data includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz, and the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz are used as input layer neurons of a BP neural network.

[0066] It should be noted that current SIM cards basically establish a transmission channel between the target MCC and the cloud after obtaining the target MCC corresponding to the current location. The present invention directly digitally converts the previous polling detection steps into a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz; and obtains the optimal transmission request coefficient csqq through calculation of the BP neural network.

[0067] The transmission channel data includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz, and generates a transmission request coefficient csqq by using the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz;

[0068] Each transmission request coefficient csqq is requested on at least one transmission channel, and each transmission channel can receive one or more transmission requests.

[0069] The logic for generating the transmission signal loss coefficient xhsh is:

[0070] The formula for the transmission signal loss coefficient xhsh is:

[0071]

[0072] The signal strength at the nearest base station that can connect to the target MCC is B, the distance between the transmission signal at the nearest base station and the terminal device is d, and the efficiency of the transmission signal is p, which is the channel gain efficiency of the nearest base station in the transmission channel and the efficiency of the circuit energy consumption during the transmission process pc. μ represents the difference between the signal-to-noise ratio required in the actual system and the theoretical signal-to-noise ratio required when the system reaches theoretical capacity.

[0073] It should be noted here that the signal strength of the base station and the efficiency of the transmission signal (p) are fixed values. However, as the distance between the terminal device and the base station increases, the transmission signal will become weaker and weaker. This process is called transmission signal loss. Through formulating, we can know that the larger the transmission signal loss coefficient, the greater the transmission signal loss. The longer the signal transmission distance, the weaker the signal strength.

[0074] The logic for generating the resource allocation coefficient zyfp is:

[0075] The ratio of the resource requirements of the multiple transmission requests in the transmission channel to the number of resources in the transmission channel does not exceed the resource constraint threshold; the resource allocation weights of the multiple transmission requests in the transmission channel are normalized to obtain the resource allocation coefficient zyfp corresponding to the current transmission request;

[0076] The specific formula is:

[0077]

[0078] Among them, 0≤α≤1, 0≤β≤1, and α+β=1, α and β are weights, which are calculated by several groups of transmission request resource quantities Wn and resource transmission power CP; M is a constant correction coefficient, whose specific value can be preset by professional configuration personnel or generated by analytical function fitting; CT is the time difference between the current reception time and the issuance of the instruction.

[0079] It should be noted here that the resource amount Wn and resource transmission power CP of the transmission channel are related, and the resource amount Wn of the transmission channel is limited. During transmission on the transmission channel, as the resource amount Wn and resource transmission power CP increase, the larger the resource allocation coefficient zyfp is, the stronger the signal of the corresponding transmission channel is.

[0080] The logic for generating the request constraint coefficient xthz is:

[0081]

[0082] Among them, the request constraint coefficient xthz is the ratio between the request arrival rate Vp and the request processing rate Vc in the transmission channel; Q is the correlation coefficient between the request arrival rate Vp and the request processing rate Vc, which is calculated by the request arrival rate Vp and the request processing rate Vc of several groups of transmission requests.

[0083] It should be noted here that: the larger the ratio of the request arrival rate Vp to the request processing rate Vc of the transmission channel, the faster the processing speed is; the larger the request constraint coefficient xthz is, the stronger the signal of the corresponding transmission channel is.

[0084] The logic for generating the transmission request coefficient csqq is:

[0085] The transmission request coefficient csqq can be obtained by formulating the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz. The specific formula is:

[0086]

[0087] in, ρ and ω are the correlation coefficients of the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz, respectively, which are calculated from several groups of transmission requests in actual applications.

[0088] It should be noted here that: the larger the transmission signal loss coefficient xhsh of the transmission channel, the smaller the resource allocation coefficient zyfp, and the smaller the request constraint coefficient xthz, the slower the transmission request coefficient processing speed and the weaker the signal of the corresponding transmission channel. Conversely, the larger the transmission request coefficient csqq, the stronger the signal of the corresponding transmission channel.

[0089] Obtaining a transmission request coefficient csqq presented by the connectable target MCC on the terminal device as an output layer neuron of a BP neural network, wherein the transmission request coefficient is used to represent the signal strength of the connectable target MCC connected to the terminal device;

[0090] Obtaining a standard training sample set and a test sample set, and obtaining a standard training sample test result corresponding to the standard training sample set and a test sample test result corresponding to the test sample set based on a BP neural network;

[0091] The step of obtaining a standard training sample set and a test sample set, and deriving a standard training sample test result corresponding to the standard training sample set and a test sample test result corresponding to the test sample set based on a BP neural network, includes:

[0092] Obtain a standard training sample set and a test sample set; obtain a standard training sample test result of the standard training sample set based on a BP neural network; obtain a test sample test result of the standard training sample set based on a BP neural network; compare the standard training sample test result with the test sample test result to obtain a comparison result;

[0093] If all the comparison results are zero, it means that the network in the SIM card transmission channel can make a transmission request;

[0094] If there is a non-zero value in the comparison result, it means that the network in the SIM card transmission channel cannot make a transmission request.

[0095] The following example illustrates how to establish a standard training sample set and a test sample set.

[0096] The set of A1, A2, A3, and A4 is used as the standard training sample set.

[0097] Among them, the first target MCC supported by the S1M card: A1 = [1, 0.02, 0.02];

[0098] The second target MCC supported by the S1M card: A2, = [1, 0.0016, 0.0016];

[0099] The third target MCC supported by the S1M card: A3 = [1, 0.013, 0.011,];

[0100] The fourth target MCC supported by the S1M card: A4 = [1, 0.011, 0.012].

[0101] The standard output corresponding to the sample data is

[0102] The first transmission request coefficient csqq supported by the S1M card: A1 = [1,0,0]; indicating that the first transmission request coefficient csqq cannot perform a transmission request;

[0103] The second transmission request coefficient csqq:A2 supported by the S1M card = [0,1,0]; indicating that the second transmission request coefficient csqq cannot perform a transmission request;

[0104] The third transmission request coefficient csqq:A3 supported by the S1M card is [0,0,1]; indicating that the third transmission request coefficient csqq cannot perform a transmission request;

[0105] The fourth transmission request coefficient csqq:A4=[0,0,0] supported by the S1M card indicates that the fourth transmission request coefficient csqq can make a transmission request.

[0106] Several sets of samples A5, A6, A7, and A8 obtained through actual measurement are used as test sample sets:

[0107] Among them, the fifth target MCC supported by the S1M card: A1 = [0.89, 0.00102, 0.00095];

[0108] The sixth target MCC supported by the S1M card: A2, = [0.92, 0.0016, 0.0017];

[0109] The seventh target MCC supported by the S1M card: A3 = [0.91, 0.0015, 0.0015];

[0110] The eighth target MCC supported by the S1M card: A4 = [0.9, 0.0012, 0.0012].

[0111] The standard output corresponding to the sample data is

[0112] The fifth transmission request coefficient csqq supported by the S1M card: A1 = [0,0,0]; indicating that the fifth transmission request coefficient csqq can make a transmission request;

[0113] The sixth transmission request coefficient csqq:A2 supported by the S1M card = [0,1,0]; indicating that the sixth transmission request coefficient csqq cannot perform a transmission request;

[0114] The seventh transmission request coefficient csqq:A3=[0,0,1] supported by the S1M card indicates that the seventh transmission request coefficient csqq cannot be used for transmission request.

[0115] The eighth transmission request coefficient csqq:A4=[1,0,0] supported by the S1M card indicates that the eighth transmission request coefficient csqq cannot be used for transmission request.

[0116] The standard training sample set includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz;

[0117] The test sample set is a set of a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz in actual signal transmission.

[0118] It should be noted here that the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz are used as input signals, and the transmission request coefficient csqq can be obtained based on the input of these coefficients. The purpose of using the BP neural network is that the number of daily transmission requests is relatively large, and the results can be directly output through the BP neural network, which can accurately detect and diagnose, thereby quickly and accurately diagnosing the transmission request coefficient csqq, thereby improving the polling time of the transmission request and greatly improving the accuracy of the transmission request coefficient csqq;

[0119] Here, the standard training sample test results of the standard training sample set are obtained through the BP neural network to obtain the most appropriate transmission request coefficient csqq. The optimal transmission channel is obtained as the preferred transmission channel of the SIM card according to the size of the transmission request coefficient csqq. This allows us to shorten the networking time during use, thereby improving the networking speed. During subsequent networking, the preferred transmission channel is directly obtained in real time through the current location and the BP neural network, which greatly facilitates the user experience and reasonably matches the selection of the optimal transmission channel.

[0120] The training sample test results and the test sample results are used to derive the transmission request coefficient csqq presented by the connectable target MCC on the terminal device, thereby verifying the prediction capability of the cable straightening prediction information;

[0121] And update the preset proportional coefficient of the transmission request coefficient csqq in real time. The preset proportional coefficient includes the difference μ between the signal-to-noise ratio required in the actual system and the signal-to-noise ratio required in theory when the system reaches the theoretical capacity, the weight α of the number of transmission request resources Wn and the weight β of the resource transmission power CP, the correlation coefficient Q between the request arrival rate Vp and the request processing rate Vc, and the correlation coefficient of the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz ρ, ω.

[0122] It should be noted here that the main purpose of using the BP neural network is to first digitally analyze the transmission channel to form transmission channel data, and obtain the optimal transmission request coefficient csqq through digital operations. However, in this process, more relevant coefficients are set by professionals and continuously updated in combination with the BP neural network. After a large amount of data is used to perform the training sample test results and the test sample results, the optimization coefficient is continuously updated to ensure accuracy, and training sample sets and test sample sets are provided for training to test accuracy, thereby ensuring that the transmission request coefficient csqq we obtain is the optimal indicator coefficient for the transmission channel.

[0123] Comparing the training sample test result and the test sample result to obtain the transmission request coefficient csqq,

[0124] According to the transmission request coefficient csqq presented on the terminal device by the connectable target MCC, the transmission channel for the most requested transmission is obtained in real time, and the network is automatically switched according to actual needs.

[0125] The standard training sample test results and the test sample test results are compared to obtain the comparison results. The method of judging whether there is a zero value is used to judge whether the currently calculated transmission request coefficient csqq can be transmitted, which is more convenient for the machine to identify and judge, and also greatly facilitates the user to quickly switch networks.

[0126] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0127] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0128] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0129] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0130] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only one type. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0131] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0132] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0133] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0134] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0135] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-channel SIM card method for automatic cross-border network switching, characterized in that: include: Obtain the current location of the terminal device where the SIM card is located, obtain the MCC list supported by the SIM card that was last received by the SIM card from the cloud server based on the current location of the terminal device, and present the specific connectable target MCC; A communication connection between the connectable target MCC and the terminal device via a transmission channel is obtained, the transmission channel is digitized into transmission channel data, the transmission channel data includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz, and the transmission signal loss coefficient xhsh, resource allocation coefficient zyfp, and request constraint coefficient xthz are used as input layer neurons of a BP neural network; wherein: The logic for generating the transmission signal loss coefficient xhsh is: The formula for the transmission signal loss coefficient xhsh is: Among them, the signal strength of the nearest base station location that can connect to the target MCC is B, the distance between the transmission signal of the nearest base station location and the terminal device is d, and the efficiency of the transmission signal is , which is the channel gain efficiency of the nearest base station in the transmission channel, and the efficiency of circuit energy consumption during transmission p c ; It indicates the difference between the actual signal-to-noise ratio required in the system and the theoretical signal-to-noise ratio required when the system reaches its theoretical capacity; The logic for generating the resource allocation coefficient zyfp is: The ratio of the resource requirements of the multiple transmission requests in the transmission channel to the number of resources in the transmission channel does not exceed the resource constraint threshold; the resource allocation weights of the multiple transmission requests in the transmission channel are normalized to obtain the resource allocation coefficient zyfp corresponding to the current transmission request; The specific formula is: in, 1, 1, and 1, 、 is the weight, which is calculated by the number of transmission request resources Wn and the resource transmission power CP of several groups; M is a constant correction coefficient, the specific value of which can be preset by professional configuration personnel or generated by analytical function fitting; It is the time difference between the current receiving time and the issuing of the instruction; The logic for generating the request constraint coefficient xthz is: The request constraint coefficient xthz is the ratio of the request arrival rate Vp to the request processing rate Vc in the transmission channel; Q is the correlation coefficient between the request arrival rate Vp and the request processing rate Vc, which is calculated from the request arrival rate Vp and the request processing rate Vc of several groups of transmission requests; The logic for generating the transmission request coefficient csqq is: The transmission request coefficient csqq can be obtained by formulating the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz. The specific formula is: in, 、 、 They are the correlation coefficients of transmission signal loss coefficient xhsh, resource allocation coefficient zyfp, and request constraint coefficient xthz, which are calculated from several groups of transmission requests in actual applications; Obtaining a transmission request coefficient csqq presented by the connectable target MCC on the terminal device as an output layer neuron of a BP neural network, wherein the transmission request coefficient is used to represent the signal strength of the connectable target MCC connected to the terminal device; Obtaining a standard training sample set and a test sample set, and obtaining a standard training sample test result corresponding to the standard training sample set and a test sample test result corresponding to the test sample set based on a BP neural network; Comparing the training sample test result and the test sample result to obtain the transmission request coefficient csqq; According to the transmission request coefficient csqq presented on the terminal device by the connectable target MCC, the transmission channel for the most requested transmission is obtained in real time, and the network is automatically switched according to actual needs.

2. The SIM card multi-channel method for automatic cross-border network switching according to claim 1, characterized in that: The analysis logic for generating the transmission channel data is as follows: According to the current location of the terminal device, obtain the MCC list supported by the SIM card that was last received by the SIM card from the cloud server; Analyze the MCC list supported by the SIM card to obtain a connectable target MCC, and establish a communication connection between the connectable target MCC and the terminal device through the transmission channel; Each of the transmission channels under the cloud server is defined with a unique name, different resource quantities and computing capabilities; Specifying different communication capabilities between any two of the transmission channels; Each of the transmission channels is digitally processed into transmission channel data, where the transmission channel data is a specific digital implementation of the transmission channel.

3. The SIM card multi-channel method for automatic cross-border network switching according to claim 2, characterized in that: The transmission channel data includes a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz, and generates a transmission request coefficient csqq by using the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz; Each transmission request coefficient csqq is requested on at least one transmission channel, and each transmission channel can receive one or more transmission requests.

4. The SIM card multi-channel method for automatic cross-border network switching according to claim 3, characterized in that: The step of obtaining a standard training sample set and a test sample set, and deriving a standard training sample test result corresponding to the standard training sample set and a test sample test result corresponding to the test sample set based on a BP neural network, includes: Obtain a standard training sample set and a test sample set; obtain a standard training sample test result of the standard training sample set based on a BP neural network; obtain a test sample test result of the standard training sample set based on a BP neural network; compare the standard training sample test result with the test sample test result to obtain a comparison result; If all the comparison results are zero, it means that the network in the SIM card transmission channel can make a transmission request; If there is a non-zero value in the comparison result, it means that the network in the SIM card transmission channel cannot make a transmission request.

5. The SIM card multi-channel method for automatic cross-border network switching according to claim 4, characterized in that ,The standard training sample set includes the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz; The test sample set is a set of a transmission signal loss coefficient xhsh, a resource allocation coefficient zyfp, and a request constraint coefficient xthz in actual signal transmission.

6. The SIM card multi-channel method for automatically switching networks across countries according to claim 5, characterized in that , the training sample test results and the test sample results are used to derive the transmission request coefficient csqq presented by the connectable target MCC on the terminal device, thereby verifying the prediction capability of the cable straightening prediction information; And update the preset proportional coefficient of the transmission request coefficient csqq in real time, the preset proportional coefficient includes the difference between the signal-to-noise ratio required in the actual system and the signal-to-noise ratio required in theory when the system reaches the theoretical capacity , the weight of the number of transmission request resources Wn and the weight of resource transmission power CP , the correlation coefficient Q between the request arrival rate Vp and the request processing rate Vc, as well as the correlation coefficient of the transmission signal loss coefficient xhsh, the resource allocation coefficient zyfp, and the request constraint coefficient xthz 、 、 .

Images