A 5G CPE router communication system compatible with multiple antenna configurations

Abstract

This invention belongs to the field of computer network communication technology. It discloses a 5G CPE router communication system compatible with multiple antenna configurations. The system includes: a scene data acquisition module, a network load data acquisition module, a data preprocessing module, a path loss generation module, a signal allocation module, a signal verification module, and a decision output module. The system preprocesses scene datasets and network load data, analyzes second scene datasets and second network load data to obtain path loss reference values, processes the path loss reference values ​​to obtain a signal allocation report, verifies the path loss reference values, analyzes the second scene dataset to obtain an adjustment report, and outputs both the adjustment report and the signal allocation report. Overall, this invention has significant advantages such as strong dynamic fluctuation handling capabilities, high signal output accuracy, and improved user comfort.

Description

Technical Field

[0001] This invention relates to the field of computer network communication technology, and more specifically, to a 5GCPE router communication system compatible with multiple antenna configurations. Background Technology

[0002] A router is a hardware device that connects two or more networks, acting as a gateway between them. It's a dedicated, intelligent network device that reads the address in each data packet and determines how to transmit it. It understands different protocols, such as Ethernet used by a local area network (LAN) and TCP / IP used by the Internet. This allows the router to analyze the destination address of data packets from various types of networks, converting non-TCP / IP addresses to TCP / IP addresses, or vice versa. Then, based on the selected routing algorithm, it transmits each data packet to the designated location along the optimal route. Therefore, a router can connect non-TCP / IP networks to the Internet. Thanks to the rapid economic development in my country in recent years, the wireless communication industry has become widely popular, and routers, as an important carrier of wireless communication, are gradually entering households. However, in home use, the transmission of router signals is often severely affected by obstructions, resulting in poor signal transmission and impacting the user experience.

[0003] Patent application CN113285935A discloses a communication system and an on-chip network router. Each input circuit includes a data parsing circuit, an access address firewall circuit, an access policy firewall circuit, and a first interception circuit. The data parsing circuit can parse the type of each transmission micro-segment of the received data packet and extract transmission information from the data header transmission micro-segment. The access address firewall circuit can determine whether the transmission information conforms to the address access setting rules; if not, it outputs the first information. The access policy firewall circuit can determine the destination ID based on the transmission information and, combined with the transmission information, determine the access relationship, and determine whether the access relationship conforms to the access relationship setting rules; if not, it outputs the second information. As can be seen, when the first or second information is output, it indicates that the current access has a security risk. Therefore, the first interception circuit will block the current data packet upon receiving the first or second information, which helps improve transmission security and avoids meaningless data transmission, thus preventing waste of power and bandwidth. Furthermore, this application includes an access address firewall circuit to determine whether the transmitted information conforms to the address access rules, and an access policy firewall circuit to determine whether the access relationship conforms to the access relationship rules, thus achieving more comprehensive access security. In summary, the solution of this application effectively improves the transmission security of the on-chip network router.

[0004] However, although the aforementioned communication system and on-chip network router can parse the types of each transmission chip in the received data packet through a data parsing circuit to determine whether the transmitted information conforms to the address access setting rules, thereby improving the router's transmission security, the router is easily affected by obstacles in the space during use, which can reduce signal transmission performance. Therefore, in home use scenarios, how to ensure signal transmission based on the distance between the user's receiving end and the device's transmitting end and the degree of obstacle influence, and ensure user comfort during use, is particularly important in current router usage.

[0005] In view of this, the present invention proposes a 5GCPE router communication system compatible with multiple antenna configurations to solve the above problems. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution, wherein the system comprises:

[0007] The scene data acquisition module is used to collect scene datasets, which include user coordinate data, device coordinate data, occlusion data, and path distance data.

[0008] The network load data acquisition module is used to collect network load data.

[0009] The data preprocessing module is used to preprocess the scene dataset and network load data to obtain the second scene dataset and the second network load data.

[0010] Furthermore, specific methods for preprocessing the scene dataset and network load data include:

[0011] The distance between the user end and the device end is filtered and calculated. The specific distance filtering calculation formula includes: Adx=α×Ad+(1-α)×Ads, where α is the smoothing coefficient and Ads is the path distance data of the previous time step.

[0012] The state of obstructions is quantified, and the specific formula for quantifying the state of obstructions is as follows: Where Acs is the total number of obstructions, and β is the indicator function;

[0013] The network load data is standardized using the following formula: The second network load data Aes is obtained, where Ae is the network load data, Aemax is the maximum network load, and Aemin is the minimum network load.

[0014] Pack the second path distance data Adx and the path obstacle data Acs to obtain the second device dataset;

[0015] The path loss generation module is used to analyze the second scenario dataset and the second network load data to obtain a path loss reference value.

[0016] Furthermore, the path loss generation module also includes a historical data retrieval module, a parameter retrieval module, a data input module, a model support module, and a data output module;

[0017] The historical data retrieval module is used to retrieve the historical second scene dataset and historical second network load data stored in the database;

[0018] The parameter retrieval module is used to retrieve wall data, equipment power data, and received signal strength data stored in the database;

[0019] The data input module is used to support manual input of attenuation coefficient datasets and measured path loss reference values;

[0020] The model support module is used to support the creation of the models required by the system;

[0021] The data output module is used to transmit path loss reference values;

[0022] Furthermore, the specific steps for analyzing the second scenario dataset and the second network load data include:

[0023] Step 1: Based on the historical data retrieval module, retrieve a set of historical second scenario datasets and historical second network load data stored in the database, and group and label them according to the timestamp from oldest to most recent, labeled as L1, L2, L3, ..., Ln respectively;

[0024] Step 2: Based on the model support module, parameter retrieval module, and data input module, establish an initial loss calculation model according to the historical second scenario dataset and historical second network load data marked in Step 1;

[0025] Step 3: Substitute into the calculation formula: The reference value for predicted transmission path loss is obtained, where Hj is the average thickness of the j-th type of wall, B1 is the distance attenuation coefficient, B2 is the wall attenuation coefficient, B3 is the shading correction coefficient, and B4 is the basic attenuation coefficient.

[0026] Step 4: Minimize the predicted transmission path loss reference value and the measured transmission path loss reference value. The specific calculation formula includes: Where Bas is the measured transmission path loss reference value;

[0027] Step 5: Define the model confidence threshold and calculate the model confidence value. The specific calculation formula includes: When the model confidence value is less than the model confidence threshold, return to step three, where Px is the mean square error of historical data and Var(Bas) is the variance of the measured transmission path loss reference value.

[0028] Step Six: After reaching the preset number of iterations, the loss calculation model is obtained;

[0029] Step 7: Input the second scenario dataset and the second network load data into the loss calculation model, output the path loss reference value, and output the path loss reference value based on the data output module;

[0030] The signal allocation module is used to process the path loss reference value to obtain a signal allocation report;

[0031] Furthermore, the specific methods for processing the path loss reference value include:

[0032] The specific calculation formula for processing the path loss reference value is as follows:

[0033] Obtain the signal evaluation value;

[0034] Where Cb is the minimum signal strength threshold, ΔCc is the total obstruction attenuation value, Ba is the path loss reference value, λ is the channel allocation weight factor, and Cd is the maximum supported channel value;

[0035] Select the antenna configuration with the highest signal evaluation value to obtain the signal allocation report;

[0036] The signal verification module is used to verify the path loss reference value;

[0037] Furthermore, methods for verifying the path loss reference value include:

[0038] The specific verification formula for verifying the path loss reference value is as follows:

[0039] Fa-(Ba+ΔCc)≥Cb;

[0040] Where Fa represents the device power data;

[0041] When the path loss reference value does not meet the verification formula, the channel allocation weight factor is recalculated.

[0042] The decision output module is used to analyze the second scenario dataset, obtain an adjustment report, and output the adjustment report and the signal allocation report.

[0043] Furthermore, the specific methods for analyzing the second scene dataset include:

[0044] Preset distance threshold and load threshold;

[0045] When the distance to the second path is less than the distance threshold, a reduction signal is generated.

[0046] The power reduction signal contains a set of fields representing data on reduced device power.

[0047] When the load data of the second network exceeds the load threshold, a boost signal is generated;

[0048] The boost signal contains a set of fields representing the activation of multi-antenna multi-user MIMO;

[0049] Pack the signal reduction and signal enhancement to obtain an adjustment report;

[0050] Furthermore, the specific methods for outputting adjustment reports and signal allocation reports include directly mapping the adjustment reports and signal allocation reports to the router driver layer;

[0051] Furthermore, the following work steps are included:

[0052] S1: Collect scene dataset, which includes user coordinate data, device coordinate data, occlusion data, and path distance data;

[0053] S2: Collect network load data;

[0054] S3: Preprocess the scene dataset and network load data to obtain the second scene dataset and the second network load data;

[0055] S4: Analyze the second scenario dataset and the second network load data to obtain the path loss reference value;

[0056] S5: Process the path loss reference value to obtain a signal allocation report;

[0057] S6: Verify the path loss reference value;

[0058] S7: Analyze the second scenario dataset to obtain an adjustment report, and output the adjustment report and signal allocation report.

[0059] The technical effects and advantages of the 5GCPE router communication system compatible with multiple antenna configurations of the present invention are as follows:

[0060] This invention collects scene datasets and network load data, preprocesses the scene datasets and network load data to obtain second scene datasets and second network load data, analyzes the second scene datasets and second network load data to obtain path loss reference values, processes the path loss reference values ​​to obtain signal allocation reports, verifies the path loss reference values, analyzes the second scene dataset to obtain adjustment reports, and outputs the adjustment reports and signal allocation reports. This ensures sufficient signal transmission under the dynamic influence of network load variables and signal path loss, significantly reducing the poor user comfort caused by poor data signals due to excessive obstructions in traditional router use. Furthermore, this invention optimizes the system's ability to adjust signal transmission in real time based on path loss reference values, greatly improving the ability to quickly adjust and output optimal signals when affected by variable data. It effectively enhances the system's adaptability and responsiveness to fluctuations in variable factors, solving the inconvenience caused by the need for manual adjustment of the user's receiver or device coordinates when the signal is poor in traditional routers. Overall, this invention has significant advantages such as strong dynamic fluctuation handling capabilities, high signal output accuracy, and a significant improvement in user comfort. Attached Figure Description

[0061] Figure 1 This is a schematic diagram of a 5GCPE router communication system compatible with multiple antenna configurations according to the present invention;

[0062] Figure 2 This is a schematic diagram of a 5GCPE router communication method compatible with multiple antenna configurations according to the present invention. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0065] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0066] Furthermore, the timing of the steps in the following method embodiments is merely an example and not a strict limitation.

[0067] In practice, the server-side equipment deployed using the 5GCPE router communication method compatible with multiple antenna configurations may consist of one or more devices. This 5GCPE router communication method can be implemented as a service instance, a virtual machine, or a hardware device. For example, it can be implemented as a service instance deployed on one or more devices in a cloud node. Simply put, it can be understood as software deployed on a cloud node to provide 5GCPE router communication with multiple antenna configurations to various user terminals. Alternatively, it can be implemented as a virtual machine deployed on one or more devices in a cloud node, with application software installed to manage various user terminals. Or, it can also be implemented as a server composed of numerous identical or different types of hardware devices, with one or more hardware devices configured to provide 5GCPE router communication with multiple antenna configurations to various user terminals.

[0068] In terms of implementation, the 5GCPE router communication method compatible with multiple antenna configurations and the user terminal are mutually adaptable. That is, if the 5GCPE router communication method compatible with multiple antenna configurations is used as an application installed on a cloud service platform, then the user terminal acts as a client that establishes a communication connection with that application; or if the 5GCPE router communication method compatible with multiple antenna configurations is implemented as a website, then the user terminal acts as a webpage; or if the 5GCPE router communication method compatible with multiple antenna configurations is implemented as a cloud service platform, then the user terminal acts as a mini-program in an instant messaging application.

[0069] like Figure 1 The diagram shown is a system architecture diagram of a 5GCPE router communication method compatible with multiple antenna configurations provided in an embodiment of the present invention.

[0070] The 5G CPE router communication method compatible with multiple antenna configurations described in this invention can be set up in a cloud server. In terms of implementation, it can be used as one or more service devices, or as an application installed in the cloud (e.g., a mobile service operator's server, server cluster, etc.), or it can be developed into a website. Depending on the implemented functions, the 5G CPE router communication method compatible with multiple antenna configurations may include a scene data acquisition module, a network load data acquisition module, a data preprocessing module, a path loss generation module, a signal allocation module, a signal verification module, and a decision output module. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0071] In this embodiment of the invention, in the 5GCPE router communication method compatible with multiple antenna configurations, each of the above modules can be implemented independently and called by other modules. This calling can be understood as a module connecting to multiple modules of another type and providing corresponding services to those connected modules. For example, the sharing and evaluation module can call the same information acquisition module to obtain the information collected by that module. Based on the above characteristics, in the 5GCPE router communication method compatible with multiple antenna configurations provided in this embodiment of the invention, without modifying the program code, the applicable scope of the 5GCPE router communication method architecture compatible with multiple antenna configurations can be adjusted by adding modules and directly calling them, achieving cluster-style horizontal expansion, so as to achieve the purpose of quickly and flexibly expanding the 5GCPE router communication method compatible with multiple antenna configurations. In practical applications, the above modules can be set in the same device or different devices, or they can be set in a virtual device, such as a service instance in a cloud server.

[0072] Example 1

[0073] Please see Figure 1 As shown in this embodiment, a 5GCPE router communication system compatible with multiple antenna configurations is described. The system includes:

[0074] The scene data acquisition module is used to acquire scene datasets, which include user coordinate data, device coordinate data, obstruction data, and path distance data.

[0075] It needs to be explained that, through indoor positioning technology, the two-dimensional plane coordinates of the user's current location within a specified area are collected to obtain user coordinate data; through manual input, the two-dimensional plane coordinates of the device's installation location within the specified area are collected to obtain device coordinate data; and through building information import, the set of signal attenuation values ​​caused by the material of obstructions within the specified area is collected. For example, the set of signal attenuation values ​​caused by the material of obstructions is represented as: Obstruction data is obtained; by substituting user coordinate data and device coordinate data into the path distance calculation formula: Obtain the path distance data, where (Xy, Yy) are the user coordinate data and (Xs, Ys) are the device coordinate data;

[0076] The network load data acquisition module is used to collect network load data;

[0077] It should be explained that the number of currently active devices is counted through DHCP logs, and then divided by the maximum load capacity of the devices to obtain network load data;

[0078] The data preprocessing module is used to preprocess the scene dataset and network load data to obtain the second scene dataset and the second network load data.

[0079] Furthermore, specific methods for preprocessing scene datasets and network load data include:

[0080] The distance between the user end and the device end is filtered and calculated. The specific distance filtering calculation formula includes: Adx=α×Ad+(1-α)×Ads, where α is the smoothing coefficient and Ads is the path distance data of the previous time step.

[0081] It should be explained that the smoothing coefficient ranges from 0 to 1, for example, an empirical value of 0.8 can be taken;

[0082] The state of obstructions is quantified, and the specific formula for quantifying the state of obstructions is as follows: Where Acs is the total number of obstructions, and β is the indicator function;

[0083] It should be explained that the indicator function means that when there is an obstruction between the user coordinate point and the device coordinate point, the indicator function takes a value of 1, and otherwise takes a value of 0.

[0084] The network load data is standardized using the following formula: The second network load data Aes is obtained, where Ae is the network load data, Aemax is the maximum network load, and Aemin is the minimum network load.

[0085] Pack the second path distance data Adx and the path obstacle data Acs to obtain the second device dataset;

[0086] The path loss generation module is used to analyze the second scenario dataset and the second network load data to obtain a path loss reference value.

[0087] Furthermore, the path loss generation module also includes a historical data retrieval module, a parameter retrieval module, a data input module, a model support module, and a data output module;

[0088] The historical data retrieval module is used to retrieve the historical second scene dataset and historical second network load data stored in the database;

[0089] The parameter retrieval module is used to retrieve wall data, equipment power data, and received signal strength data stored in the database;

[0090] The data input module is used to support manual input of attenuation coefficient datasets and measured path loss reference values;

[0091] It should be explained that the attenuation coefficient dataset includes distance attenuation coefficient, wall attenuation coefficient, shading correction coefficient, and base attenuation coefficient;

[0092] The model support module is used to support the creation of the models required by the system;

[0093] The data output module is used to transmit path loss reference values;

[0094] Furthermore, the specific steps for analyzing the second scenario dataset and the second network load data include:

[0095] Step 1: Based on the historical data retrieval module, retrieve a set of historical second scenario datasets and historical second network load data stored in the database, and group and label them according to the timestamp from oldest to most recent, labeled as L1, L2, L3, ..., Ln respectively;

[0096] Step 2: Based on the model support module, parameter retrieval module, and data input module, establish an initial loss calculation model according to the historical second scenario dataset and historical second network load data marked in Step 1;

[0097] Step 3: Substitute into the calculation formula: The reference value for predicted transmission path loss is obtained, where Hj is the average thickness of the j-th type of wall, B1 is the distance attenuation coefficient, B2 is the wall attenuation coefficient, B3 is the shading correction coefficient, and B4 is the basic attenuation coefficient.

[0098] It should be explained that the basic attenuation coefficient is a constant term, which refers to other fixed losses generated during signal transmission;

[0099] Step 4: Minimize the predicted transmission path loss reference value and the measured transmission path loss reference value. The specific calculation formula includes: Where Bas is the measured transmission path loss reference value;

[0100] It should be explained that the measured transmission path loss reference value is obtained by subtracting the received signal strength data from the device power data;

[0101] Step 5: Define the model confidence threshold and calculate the model confidence value. The specific calculation formula includes: When the model confidence value is less than the model confidence threshold, return to step three, where Px is the mean square error of historical data and Var(Bas) is the variance of the measured transmission path loss reference value.

[0102] It should be explained that the mean square error of historical data refers to the mean square error between the input historical second scenario dataset and the historical second network load data;

[0103] Step Six: After reaching the preset number of iterations, the loss calculation model is obtained;

[0104] Step 7: Input the second scenario dataset and the second network load data into the loss calculation model, output the path loss reference value, and output the path loss reference value based on the data output module;

[0105] The signal allocation module is used to process the path loss reference value to obtain a signal allocation report;

[0106] Furthermore, specific methods for processing the path loss reference value include:

[0107] The specific calculation formula for processing the path loss reference value is as follows:

[0108] Obtain the signal evaluation value;

[0109] Where Cb is the minimum signal strength threshold, ΔCc is the total obstruction attenuation value, Ba is the path loss reference value, λ is the channel allocation weight factor, and Cd is the maximum supported channel value;

[0110] It should be explained that the total obstruction attenuation value is obtained by the formula: ΔCc=Acs×γ, where γ is the attenuation of a single obstacle; the channel allocation weighting factor is obtained by the formula: λ=1-Aes;

[0111] Select the antenna configuration with the highest signal evaluation value to obtain the signal allocation report;

[0112] It should be explained that antenna configuration schemes include, but are not limited to, multiple antenna modes, beam angles, or transmit power;

[0113] The signal verification module is used to verify the path loss reference value;

[0114] Furthermore, methods for verifying the path loss reference value include:

[0115] The specific verification formula for verifying the path loss reference value is as follows:

[0116] Fa-(Ba+ΔCc)≥Cb;

[0117] Where Fa represents the device power data;

[0118] When the path loss reference value does not meet the verification formula, the channel allocation weight factor is recalculated.

[0119] The decision output module is used to analyze the second scenario dataset, obtain an adjustment report, and output the adjustment report and the signal allocation report.

[0120] Furthermore, the specific methods for analyzing the second scene dataset include:

[0121] Preset distance threshold and load threshold;

[0122] When the distance to the second path is less than the distance threshold, a reduction signal is generated.

[0123] The power reduction signal contains a set of fields representing data on reduced device power.

[0124] When the load data of the second network exceeds the load threshold, a boost signal is generated;

[0125] The boost signal contains a set of fields representing the activation of multi-antenna multi-user MIMO;

[0126] Pack the signal reduction and signal enhancement to obtain an adjustment report;

[0127] Furthermore, specific methods for outputting adjustment reports and signal allocation reports include directly mapping the adjustment reports and signal allocation reports to the router driver layer;

[0128] This embodiment offers several advantages. By collecting scene datasets and network load data, preprocessing these datasets to obtain second scene datasets and second network load data, analyzing these datasets to obtain path loss reference values, processing these reference values ​​to generate signal allocation reports, verifying the reference values, analyzing the second scene dataset to generate adjustment reports, and outputting both the adjustment and signal allocation reports. This ensures sufficient signal transmission under the dynamic influence of network load variables and signal path loss, significantly reducing the poor user comfort caused by excessive obstructions in traditional routers. Furthermore, this invention optimizes the system's ability to adjust signal transmission in real-time based on path loss reference values, greatly improving the ability to quickly adjust and output optimal signals when affected by variable data. This effectively enhances the system's adaptability and responsiveness to fluctuations in variable factors, solving the inconvenience of manually adjusting the user's receiver or device coordinates when traditional routers have poor signal strength. Overall, this invention has significant advantages in terms of strong dynamic fluctuation handling capabilities, high signal output accuracy, and improved user comfort.

[0129] Example 2

[0130] Please see Figure 2 As shown, parts not described in detail in this embodiment are described in Embodiment 1. A 5G CPE router communication method compatible with multiple antenna configurations is provided, the method including:

[0131] Example 3

[0132] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0133] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0134] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0135] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. The terms "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A 5GCPE router communication system compatible with multiple antenna configurations, comprising: The system includes: a scene data acquisition module, a network load data acquisition module, a data preprocessing module, a path loss generation module, a signal allocation module, a signal verification module, and a decision output module, wherein: The scene data acquisition module is used to acquire scene datasets, which include user coordinate data, device coordinate data, obstruction data, and path distance data. The network load data acquisition module is used to collect network load data; The data preprocessing module is used to preprocess the scene dataset and network load data to obtain the second scene dataset and the second network load data. The path loss generation module is used to analyze the second scenario dataset and the second network load data to obtain a path loss reference value. The signal allocation module is used to process the path loss reference value to obtain a signal allocation report; The signal verification module is used to verify the path loss reference value; The decision output module is used to analyze the second scenario dataset, obtain an adjustment report, and output the adjustment report and the signal allocation report. Specific methods for preprocessing scene datasets and network load data include: The distance between the user terminal and the device terminal is filtered and calculated. The specific distance filtering calculation formula includes: ,in, For smoothing coefficients, This is the path distance data from the previous time step. This is path distance data. This is the second path distance data obtained after distance filtering; The state of obstructions is quantified, and the specific formula for quantifying the state of obstructions is as follows: ,in, Quantify path obstacle data. For indicator functions, The number of obstructions within the path range; The network load data is standardized using the following formula: Obtain the second network load data ,in, For network load data, This represents the maximum network load. This represents the minimum network load. Packing second path distance data Quantification data of path obstacles This yields the second device dataset; The path loss generation module also includes a historical data retrieval module, a parameter retrieval module, a data input module, a model support module, and a data output module. The historical data retrieval module is used to retrieve the historical second scene dataset and historical second network load data stored in the database; The parameter retrieval module is used to retrieve wall data, equipment power data, and received signal strength data stored in the database; The data input module is used to support manual input of attenuation coefficient datasets and measured path loss reference values; The model support module is used to support the creation of the models required by the system; The data output module is used to transmit path loss reference values; The specific steps for analyzing the second scenario dataset and the second network load data include: Step 1: Based on the historical data retrieval module, retrieve a set of historical second scenario datasets and historical second network load data stored in the database, and group and label them according to the timestamp from oldest to most recent, labeled as L1, L2, L3, ..., Ln respectively; Step 2: Based on the model support module, parameter retrieval module, and data input module, establish an initial loss calculation model according to the historical second scenario dataset and historical second network load data marked in Step 1; Step 3: Substitute into the calculation formula: The reference value for predicted transmission path loss is obtained, where, For the first The average thickness of the wall-like structure This is the distance attenuation coefficient. The wall attenuation coefficient is... For occlusion correction factor, The basic attenuation coefficient; Step 4: Minimize the predicted transmission path loss reference value and the measured transmission path loss reference value. The specific calculation formula includes: ,in, This is a reference value for the measured transmission path loss; Step 5: Define the model confidence threshold and calculate the model confidence value. The specific calculation formula includes: When the model confidence value is less than the model confidence threshold, return to step three, where... This represents the mean square error of historical data. The variance of the measured transmission path loss is used as a reference value. Step Six: After reaching the preset number of iterations, the loss calculation model is obtained; Step 7: Input the second scenario dataset and the second network load data into the loss calculation model, output the path loss reference value, and output the path loss reference value based on the data output module; The specific methods for processing the path loss reference value include: The specific calculation formula for processing the path loss reference value is as follows: obtaining a signal evaluation value; in, The minimum signal strength threshold, This represents the total occlusion attenuation value. This serves as a reference value for path loss. Assign weighting factors to the channel. This is the maximum supported channel value; Select the antenna configuration with the highest signal evaluation value to obtain the signal allocation report; Furthermore, methods for verifying the path loss reference value include: The specific verification formula for verifying the path loss reference value is as follows: ； wherein is the device power data; When the path loss reference value does not meet the verification formula, the channel allocation weight factor is recalculated.

2. The 5GCPE router communication system compatible with multiple antenna configurations of claim 1, wherein, The specific methods for analyzing the second scenario dataset include: Preset distance threshold and load threshold; When the distance to the second path is less than the distance threshold, a reduction signal is generated. The power reduction signal contains a set of fields representing data on reduced device power. When the load data of the second network exceeds the load threshold, a boost signal is generated; The boost signal contains a set of fields representing the initiation of multi-antenna multi-user MIMO; Pack the signal down and the signal up to obtain an adjustment report.

3. The 5GCPE router communication system compatible with multiple antenna configurations of claim 2, wherein, The specific methods for outputting adjustment reports and signal allocation reports include directly mapping the adjustment reports and signal allocation reports to the router driver layer. 4.A method for 5GCPE router communication compatible with multiple antenna configurations, implemented by the 5GCPE router communication system compatible with multiple antenna configurations according to any one of claims 1-3, characterized in that, The work includes the following steps: S1: Collect scene dataset, which includes user coordinate data, device coordinate data, occlusion data, and path distance data; S2: Collect network load data; S3: Preprocess the scene dataset and network load data to obtain the second scene dataset and the second network load data; S4: Analyze the second scenario dataset and the second network load data to obtain the path loss reference value; S5: Process the path loss reference value to obtain a signal allocation report; S6: Verify the path loss reference value; S7: Analyze the second scenario dataset to obtain an adjustment report, and output the adjustment report and signal allocation report.

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