Communication data management system and method based on multi-modal network

Abstract

The application relates to the field of multi-mode communication, in particular to a communication data management system and method based on a multi-mode network, which comprises a fading sampling module, a channel modeling module, an optical fiber transmission module, a link gain module and a channel solidification module, the fading sampling module is used for collecting pilot signals, the channel modeling module is used for calculating signal loss and constructing a channel model, the optical fiber transmission module is used for setting an optical fiber repeating antenna to perform cross-area signal repeating, the link gain module is used for broadcasting addressing signals, and the channel solidification module is used for solidifying a signal communication mode; the application can help to optimize receiver antenna design, reduce the error code phenomenon caused by signal fading, realize cross-blank area communication under a wireless signal shielding state, construct a three-dimensional communication network, improve the performance, reliability and applicability of a communication system, simultaneously realize dynamic resource scheduling, guarantee communication link stability and reduce the probability of communication interruption.

Description

Technical Field

[0001] This invention relates to the field of multimodal communication, specifically to a communication data management system and method based on multimodal networks. Background Technology

[0002] Multimodal networks refer to network architectures that support multiple communication modes or data types. They can integrate various communication media such as fiber optics, wireless channels, and satellites to adapt to different communication scenarios and solve the problem of insufficient single-mode data. Common multimodal network architectures use fiber optics + wireless base stations to achieve lossless signal switching and coverage.

[0003] 4G or 5G communication networks employ massive cellular antenna coverage to cover cells. By dividing the service area into smaller zones and using multiple low-power transmitters to cover these smaller zones, data transmission efficiency is increased. However, due to factors such as terrain and route planning, large gaps may exist between cells, where signals cannot penetrate and potentially fragment the cell's communication system. Using massive fiber optic communication would reduce signal coverage, increase cell communication costs, and easily lead to insufficient single-mode data.

[0004] Furthermore, wireless signals experience spatial fading during transmission. When the same signal propagates along multiple paths, arriving at the receiver with minute time differences, interference can occur, leading to further fading. Existing multimode fiber-to-wireless signal conversion circuits struggle to detect this fading, and in multimode fiber, the fading can be amplified, distorting the terminal communication signal and affecting signal transmission quality. Summary of the Invention

[0005] The purpose of this invention is to provide a communication data management system and method based on multimodal networks to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a communication data management system based on multimodal networks, comprising: a fading sampling module, a channel modeling module, an optical fiber transmission module, a link gain module, and a channel fixing module;

[0007] The fading sampling module is used to control the base station to transmit known pilot signals. It uses a mobile signal receiving device equipped with a high-precision spectrum analyzer and GPS / IMU positioning module to collect the signal strength, signal-to-noise ratio and delay spread data of the pilot signals in real time. The data is then connected to the signal analysis platform, and the collected signals are classified according to the base station type and receiving location to generate a data table and keep it updated in real time.

[0008] The channel modeling module is used in single base station testing to record location coordinates and received power, use a logarithmic distance model and introduce random variables to determine the path loss exponent, and after multiple samplings at different locations, use the least squares method to fit the path loss exponent to obtain the large-scale fading of the signal. In the full base station network testing process, the large-scale fading loss is eliminated from the received signal, the root mean square delay spread is calculated, and the small-scale fading of the signal is obtained. The large-scale fading is used as the basis, and the small-scale fading is used as a superimposed disturbance to construct the channel model, output the model basis kernel function, and construct a regional loss heatmap.

[0009] The fiber optic transmission module is used to set up fiber optic forwarding antennas within a range where the path loss is below a threshold, receive signals from the communication base station, and after the antenna receives the signal, removes noise components according to the channel model, forwards the original signal to another cell through multimode fiber, determines the destination receiving address, generates an addressing signal containing the target cell ID, fiber optic path ID, and priority label, and selects the fiber optic communication path with the highest communication efficiency based on Dijkstra's or Q-learning algorithm according to the destination receiving address.

[0010] The link gain module is used to encapsulate the addressing signal using the JSON protocol. At the end of the optical fiber transmission, the addressing signal is broadcast periodically by the terminal antenna. At the same time, the CRC check confirms the affiliation of the neighboring base station, marks the first responding base station as the destination, determines the base station's ID and location, and determines the antenna transmit gain according to the channel model to ensure that the signal power before and after transmission is consistent.

[0011] The channel solidification module is used to optimize the modes of the communication link in the optical fiber after a stable cross-regional link is built, select the signal mode with the least interference, and solidify it. When a coherent mode exists, communication resources are scheduled according to the resource requirements, communication frequency, and channel loss of each user.

[0012] Furthermore, the fading sampling module includes: a receiver unit and a platform access unit;

[0013] The receiver unit is used to perform multiple rounds of signal sampling on the cellular network using mobile signal receiving equipment;

[0014] The platform access unit is used to build a data analysis and processing platform and store signal sampling data and positioning data.

[0015] Furthermore, the channel modeling module includes: a mean fitting unit, a scaling fading unit, and a basis kernel function unit;

[0016] The mean fitting unit is used to control the target base station to transmit a known pilot signal and determine the mean value of the received power;

[0017] The scale fading unit is used to determine the large-scale fading and small-scale fading of the signal based on the signal sampling results;

[0018] The basis kernel function units are superimposed with scale fading, and an LSTM network is used to predict the fading trend and generate a channel model.

[0019] Furthermore, the optical fiber transmission module includes: an optical fiber antenna unit, a multimode optical fiber unit, and a signal broadcasting unit;

[0020] The fiber optic antenna unit is used to achieve cross-cell signal transmission and routing optimization through a fiber optic repeater antenna;

[0021] The multimode fiber unit is used to perform electro-optic conversion using a direct modulated laser, and to increase fiber capacity through C-band or L-band multi-wavelength multiplexing.

[0022] The signal broadcasting unit is used to transmit target addressing signals using an integrated LoRa / UWB low-power wide-area communication antenna.

[0023] Furthermore, the link gain module includes: a node addressing unit and a fading compensation unit;

[0024] The node addressing unit is used to calculate the comprehensive efficiency index of each optical fiber path and select the path with the highest index for communication hopping.

[0025] The fading compensation unit is used to calculate signal fading according to the channel model and to compensate for path loss at the antenna.

[0026] Furthermore, the channel solidification module includes: an interference analysis unit and a resource scheduling unit;

[0027] The interference analysis unit is used to calculate the interference state of each signal in the optical fiber and solidify the signal mode with the least interference.

[0028] The resource scheduling unit is used for distributed power control according to user type and communication needs.

[0029] A communication data management method based on multimodal networks includes the following steps:

[0030] Step S1. Control the base station to transmit known pilot signals, and use mobile signal receiving equipment to collect the signal strength, signal-to-noise ratio and delay spread data of the pilot signals in real time at different locations. Store the collected data and collection locations in the signal analysis platform.

[0031] Step S2. During the single base station test, after multiple samplings at different locations, the path loss exponent of the signal is fitted using a logarithmic distance model to obtain the large-scale fading of the signal. During the full base station network test, the large-scale fading loss is eliminated from the sampled signal, and the root mean square delay spread and the small-scale fading of the signal are calculated.

[0032] Step S3. Based on large-scale fading, a channel model is constructed using small-scale fading as superimposed disturbance. Fiber optic relay antennas are set up at locations where the regional loss is below a threshold. After receiving the original signal, the destination receiving address is determined, the fiber optic communication path with the highest communication efficiency is selected, and an addressing signal containing the target cell ID, fiber optic path ID, and priority label is generated.

[0033] Step S4. Compensate for fading components from the actual reception according to the channel model, forward the original signal to another cell through multimode fiber, and at the end of the fiber transmission, periodically broadcast the addressing signal with the terminal antenna and confirm the base station affiliation with CRC check.

[0034] Step S5. Calculate the signal fading according to the channel model, apply gain to the signal at the terminal antenna, build a stable cross-regional link, and optimize the mode of the communication link in the optical fiber to solidify the signal mode with the least interference.

[0035] Furthermore, step S1 includes:

[0036] Step S11. Generate a regional base station map according to the location of the base station in the cell, and conduct single base station test and full base station network test respectively. In the single base station test, shut down the surrounding base stations and keep only the target base station working. In the full base station network test, activate all cell base stations, build a cellular network environment, and make the target base station transmit known pilot signals.

[0037] Step S12. Using a mobile signal receiving device equipped with a Keysight high-precision spectrum analyzer and a GPS / IMU positioning module, the signal strength, signal-to-noise ratio and delay spread data of the pilot signal are collected within the communication range of the target base station, and multiple samples are taken at different distances from the target base station.

[0038] Step S13. Construct a data analysis and processing platform, connect the sampled data to the signal analysis platform, classify the collected signals according to the base station type and receiving location, generate a data table and keep it updated in real time. Each time sampling is performed, record the sampled data and sampling location in the data table.

[0039] Furthermore, step S2 includes:

[0040] Step S21. During the single-base station test, record the location coordinates and received power, and use the logarithmic distance model and introduce random variables to determine the path loss model:

[0041] ;

[0042] Where P(d) is the received signal power, P0 is the transmitted signal power, n is the path loss exponent, d is the distance between the sampling point and the base station, d0 is the reference distance of the far field region of the transmit antenna, and X is the shadow fading random variable, and X conforms to a log-normal distribution with the receiver power as the mean.

[0043] Based on the path loss model obtained from each single base station test in the data table, the path loss exponent n is fitted using the least squares method to obtain the large-scale fading function of the signal PL(d)=P0-P(d).

[0044] Step S22. During the full base station network testing phase, the signal frequency is determined using Fourier transform, and the root mean square delay spread and small-scale signal fading are calculated:

[0045] ;

[0046] Where Fs(d) is the small-scale fading of the signal, τ is the root mean square delay, N is the number of test paths, ai is the time-varying amplitude function of the i-th path, f is the signal frequency, τi and τ0 represent the delay and average delay of the i-th path, respectively, Pi(d) is the function of power and distance of the i-th path, j is the imaginary sign, and e is the base of the natural logarithm.

[0047] Furthermore, step S3 includes:

[0048] Step S31. Construct a channel model based on large-scale fading and small-scale fading as superimposed disturbances. The basic kernel function of the channel model is Pr(d) = P(d) + Fs(d) + X. Construct a regional loss heatmap according to the channel model.

[0049] Step S32. Based on the regional loss heat map, select a location where the regional loss is below the threshold to set up an optical fiber forwarding antenna. Use the forwarding antenna to receive the forwarding signal of the communication base station on a fixed frequency band. After the antenna receives the signal, remove the noise component according to the channel model, and forward the original signal to another cell through multimode optical fiber. The multimode optical fiber uses a direct modulation laser for electro-optic conversion and improves the optical fiber capacity through C-band or L-band multi-wavelength multiplexing.

[0050] Step S33. Determine the destination receiving address, generate an addressing signal containing the target cell ID, fiber path ID, and priority label, and select the fiber communication path with the highest communication efficiency based on Dijkstra's or Q-learning algorithm according to the destination receiving address.

[0051] Furthermore, step S4 includes:

[0052] Step S41. Input the distance between the antenna and the base station, the signal transmission power and the signal frequency into the channel model, compensate for the fading components from the actual received signal, and convert the compensated signal into an optical signal through a photoelectric converter and enter the multimode fiber.

[0053] Step S42. Encapsulate the addressing signal using the JSON protocol. At the end of the fiber optic transmission, broadcast the addressing signal using an integrated LoRa / UWB low-power wide-area communication antenna. Simultaneously, confirm the affiliation of the neighboring base station through CRC check, mark the first responding base station as the destination, and determine the ID and location of the destination base station.

[0054] Furthermore, step S5 includes:

[0055] Step S51. Simultaneously increase the signal transmitted by the terminal antenna to make the signal power before and after transmission consistent. Based on the ID and location of the source base station and the destination base station, construct a stable cross-regional link.

[0056] Step S52. Using fiber optic sensors, calculate the interference state of each signal in the fiber optic cable, optimize the modes of the communication link in the fiber optic cable, select the signal mode with the least interference, and solidify it. When coherent modes exist, schedule communication resources according to the resource requirements of each user, communication frequency, and channel loss, and select the signal mode with the highest overall signal transmission efficiency for transmission.

[0057] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0058] This invention determines the large-scale fading of a signal by fitting the mean of a random signal, turns on all communication base stations, resamples the signal, and determines the small-scale fading according to the signal fading difference. This allows for transmission modeling of the wireless channel, which can be used to determine signal attenuation, find the optimal communication configuration, help optimize receiver antenna design, and reduce bit errors caused by signal fading.

[0059] This invention involves setting up an optical fiber relay antenna within a cell to receive signals from a communication base station. The original signal is then relayed to another cell via multimode optical fiber to generate an addressing signal. This addressing signal is broadcast on the terminal antenna. After confirming the response from the base station, signal gain is adjusted according to the positions of the base station and the antenna. This invention can enable cross-area communication under conditions of wireless signal obstruction, integrate multiple communication methods, construct a three-dimensional communication network, and improve the performance, reliability, and applicability of the communication system.

[0060] After constructing a stable cross-regional link, this invention optimizes the modes of the communication link in the optical fiber, selects the signal mode with the least interference, and solidifies it in the optical fiber. When coherent modes exist, resource scheduling is performed according to the resource requirements of each user, communication frequency, and channel loss. This enables dynamic resource scheduling, ensures the stability of the communication link, and reduces the probability of communication interruption. Attached Figure Description

[0061] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0062] Figure 1 This is a schematic diagram of the communication data management system based on multimodal networks according to the present invention;

[0063] Figure 2 This is a schematic diagram illustrating the steps of the communication data management method based on multimodal networks according to the present invention. Detailed Implementation

[0064] 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.

[0065] Please see Figure 1 The present invention provides a technical solution: a communication data management system based on multimodal networks, comprising: a fading sampling module, a channel modeling module, an optical fiber transmission module, a link gain module, and a channel fixing module;

[0066] The fading sampling module is used to control the base station to transmit known pilot signals. It uses a mobile signal receiving device equipped with a high-precision spectrum analyzer and GPS / IMU positioning module to collect the signal strength, signal-to-noise ratio and delay spread data of the pilot signals in real time. The data is then connected to the signal analysis platform, and the collected signals are classified according to the base station type and receiving location to generate a data table and keep it updated in real time.

[0067] The fading sampling module includes: a receiver unit and a platform access unit;

[0068] The receiver unit is used to perform multiple rounds of signal sampling on the cellular network using mobile signal receiving equipment;

[0069] The platform access unit is used to build a data analysis and processing platform and store signal sampling data and positioning data.

[0070] The channel modeling module is used in single base station testing to record location coordinates and received power, use a logarithmic distance model and introduce random variables to determine the path loss exponent, and after multiple samplings at different locations, use the least squares method to fit the path loss exponent to obtain the large-scale fading of the signal. In the full base station network testing process, the large-scale fading loss is eliminated from the received signal, the root mean square delay spread is calculated, and the small-scale fading of the signal is obtained. The large-scale fading is used as the basis, and the small-scale fading is used as a superimposed disturbance to construct the channel model, output the model basis kernel function, and construct a regional loss heatmap.

[0071] The channel modeling module includes: a mean fitting unit, a scaling fading unit, and a basis kernel function unit;

[0072] The mean fitting unit is used to control the target base station to transmit a known pilot signal and determine the mean value of the received power;

[0073] The scale fading unit is used to determine the large-scale fading and small-scale fading of the signal based on the signal sampling results;

[0074] The basis kernel function units are superimposed with scale fading, and an LSTM network is used to predict the fading trend and generate a channel model.

[0075] The fiber optic transmission module is used to set up fiber optic forwarding antennas within a range where the path loss is below a threshold, receive signals from the communication base station, and after the antenna receives the signal, removes noise components according to the channel model, forwards the original signal to another cell through multimode fiber, determines the destination receiving address, generates an addressing signal containing the target cell ID, fiber optic path ID, and priority label, and selects the fiber optic communication path with the highest communication efficiency based on Dijkstra's or Q-learning algorithm according to the destination receiving address.

[0076] The optical fiber transmission module includes: an optical fiber antenna unit, a multimode optical fiber unit, and a signal broadcasting unit;

[0077] The fiber optic antenna unit is used to achieve cross-cell signal transmission and routing optimization through a fiber optic repeater antenna;

[0078] The multimode fiber unit is used to perform electro-optic conversion using a direct modulated laser, and to increase fiber capacity through C-band or L-band multi-wavelength multiplexing.

[0079] The signal broadcasting unit is used to transmit target addressing signals using an integrated LoRa / UWB low-power wide-area communication antenna.

[0080] The link gain module is used to encapsulate the addressing signal using the JSON protocol. At the end of the optical fiber transmission, the addressing signal is broadcast periodically by the terminal antenna. At the same time, the CRC check confirms the affiliation of the neighboring base station, marks the first responding base station as the destination, determines the base station's ID and location, and determines the antenna transmit gain according to the channel model to ensure that the signal power before and after transmission is consistent.

[0081] The link gain module includes: a node addressing unit and a fading compensation unit;

[0082] The node addressing unit is used to calculate the comprehensive efficiency index of each optical fiber path and select the path with the highest index for communication hopping.

[0083] The fading compensation unit is used to calculate signal fading according to the channel model and to compensate for path loss at the antenna.

[0084] The channel solidification module is used to optimize the modes of the communication link in the optical fiber after a stable cross-regional link is built, select the signal mode with the least interference, and solidify it. When a coherent mode exists, communication resources are scheduled according to the resource requirements, communication frequency, and channel loss of each user.

[0085] The channel solidification module includes: an interference analysis unit and a resource scheduling unit;

[0086] The interference analysis unit is used to calculate the interference state of each signal in the optical fiber and solidify the signal mode with the least interference.

[0087] The resource scheduling unit is used for distributed power control according to user type and communication needs.

[0088] like Figure 2 As shown, the communication data management method based on multimodal networks includes the following steps:

[0089] Step S1. Control the base station to transmit known pilot signals, and use mobile signal receiving equipment to collect the signal strength, signal-to-noise ratio and delay spread data of the pilot signals in real time at different locations. Store the collected data and collection locations in the signal analysis platform.

[0090] Step S1 includes:

[0091] Step S11. Generate a regional base station map according to the location of the base station in the cell, and conduct single base station test and full base station network test respectively. In the single base station test, shut down the surrounding base stations and keep only the target base station working. In the full base station network test, activate all cell base stations, build a cellular network environment, and make the target base station transmit known pilot signals.

[0092] Step S12. Using a mobile signal receiving device equipped with a Keysight high-precision spectrum analyzer and a GPS / IMU positioning module, the signal strength, signal-to-noise ratio and delay spread data of the pilot signal are collected within the communication range of the target base station, and multiple samples are taken at different distances from the target base station.

[0093] Step S13. Construct a data analysis and processing platform, connect the sampled data to the signal analysis platform, classify the collected signals according to the base station type and receiving location, generate a data table and keep it updated in real time. Each time sampling is performed, record the sampled data and sampling location in the data table.

[0094] Step S2. During the single base station test, after multiple samplings at different locations, the path loss exponent of the signal is fitted using a logarithmic distance model to obtain the large-scale fading of the signal. During the full base station network test, the large-scale fading loss is eliminated from the sampled signal, and the root mean square delay spread and the small-scale fading of the signal are calculated.

[0095] Step S2 includes:

[0096] Step S21. During the single-base station test, record the location coordinates and received power, and use the logarithmic distance model and introduce random variables to determine the path loss model:

[0097] ;

[0098] Where P(d) is the received signal power, P0 is the transmitted signal power, n is the path loss exponent, d is the distance between the sampling point and the base station, d0 is the reference distance of the far field region of the transmit antenna, and X is the shadow fading random variable, and X conforms to a log-normal distribution with the receiver power as the mean.

[0099] Based on the path loss model obtained from each single base station test in the data table, the path loss exponent n is fitted using the least squares method to obtain the large-scale fading function of the signal PL(d)=P0-P(d).

[0100] Step S22. During the full base station network testing phase, the signal frequency is determined using Fourier transform, and the root mean square delay spread and small-scale signal fading are calculated:

[0101] ;

[0102] Where Fs(d) is the small-scale fading of the signal, τ is the root mean square delay, N is the number of test paths, ai is the time-varying amplitude function of the i-th path, f is the signal frequency, τi and τ0 represent the delay and average delay of the i-th path, respectively, Pi(d) is the function of power and distance of the i-th path, j is the imaginary sign, and e is the base of the natural logarithm.

[0103] Step S3. Based on large-scale fading, a channel model is constructed using small-scale fading as superimposed disturbance. Fiber optic relay antennas are set up at locations where the regional loss is below a threshold. After receiving the original signal, the destination receiving address is determined, the fiber optic communication path with the highest communication efficiency is selected, and an addressing signal containing the target cell ID, fiber optic path ID, and priority label is generated.

[0104] Step S3 includes:

[0105] Step S31. Construct a channel model based on large-scale fading and small-scale fading as superimposed disturbances. The basic kernel function of the channel model is Pr(d) = P(d) + Fs(d) + X. Construct a regional loss heatmap according to the channel model.

[0106] Step S32. Based on the regional loss heat map, select a location where the regional loss is below the threshold to set up an optical fiber forwarding antenna. Use the forwarding antenna to receive the forwarding signal of the communication base station on a fixed frequency band. After the antenna receives the signal, remove the noise component according to the channel model, and forward the original signal to another cell through multimode optical fiber. The multimode optical fiber uses a direct modulation laser for electro-optic conversion and improves the optical fiber capacity through C-band or L-band multi-wavelength multiplexing.

[0107] Step S33. Determine the destination receiving address, generate an addressing signal containing the target cell ID, fiber path ID, and priority label, and select the fiber communication path with the highest communication efficiency based on Dijkstra's or Q-learning algorithm according to the destination receiving address.

[0108] Step S4. Compensate for fading components from the actual reception according to the channel model, forward the original signal to another cell through multimode fiber, and at the end of the fiber transmission, periodically broadcast the addressing signal with the terminal antenna and confirm the base station affiliation with CRC check.

[0109] Step S4 includes:

[0110] Step S41. Input the distance between the antenna and the base station, the signal transmission power and the signal frequency into the channel model, compensate for the fading components from the actual received signal, and convert the compensated signal into an optical signal through a photoelectric converter and enter the multimode fiber.

[0111] Step S42. Encapsulate the addressing signal using the JSON protocol. At the end of the fiber optic transmission, broadcast the addressing signal using an integrated LoRa / UWB low-power wide-area communication antenna. Simultaneously, confirm the affiliation of the neighboring base station through CRC check, mark the first responding base station as the destination, and determine the ID and location of the destination base station.

[0112] Step S5. Calculate the signal fading according to the channel model, apply gain to the signal at the terminal antenna, build a stable cross-regional link, and optimize the mode of the communication link in the optical fiber to solidify the signal mode with the least interference.

[0113] Step S5 includes:

[0114] Step S51. Simultaneously increase the signal transmitted by the terminal antenna to make the signal power before and after transmission consistent. Based on the ID and location of the source base station and the destination base station, construct a stable cross-regional link.

[0115] Step S52. Using fiber optic sensors, calculate the interference state of each signal in the fiber optic cable, optimize the modes of the communication link in the fiber optic cable, select the signal mode with the least interference, and solidify it. When coherent modes exist, schedule communication resources according to the resource requirements of each user, communication frequency, and channel loss, and select the signal mode with the highest overall signal transmission efficiency for transmission.

[0116] Example: A tall steel structure building blocks the signal between cell 1 and cell 2. A signal is sent from base station (2,1) in cell 1 to base station (2,3) in cell 2. The fiber optic relay antenna is searched in the relay band to determine the distance between the fiber optic relay antenna and base station (2,1). The base station transmits a power of 50W and the signal is a 200MHz modulated sine wave. The path loss is 0.8W. After the relay antenna compensates for the signal, the most efficient path is selected through the underground fiber optic cable to transmit the signal to cell 2. The terminal antenna broadcasts the address to determine the destination base station (2,3). A stable communication line is established between base station (2,1) and base station (2,3), and the current signal mode is fixed in the multimode fiber.

[0117] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0118] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A communication data management method based on multimodal networks, characterized in that, The method includes the following steps: Step S1. Control the base station to transmit known pilot signals, and use mobile signal receiving equipment to collect the signal strength, signal-to-noise ratio and delay spread data of the pilot signals in real time at different locations. Store the collected data and collection locations in the signal analysis platform. Step S2. During the single base station test, after multiple samplings at different locations, the path loss exponent of the signal is fitted using a logarithmic distance model to obtain the large-scale fading of the signal. During the full base station network test, the large-scale fading loss is eliminated from the sampled signal, and the root mean square delay spread and the small-scale fading of the signal are calculated. Step S3. Based on large-scale fading, a channel model is constructed using small-scale fading as superimposed disturbance. Fiber optic relay antennas are set up at locations where the regional loss is below a threshold. After receiving the original signal, the destination receiving address is determined, the fiber optic communication path with the highest communication efficiency is selected, and an addressing signal containing the target cell ID, fiber optic path ID, and priority label is generated. Step S4. Compensate for fading components from the actual reception according to the channel model, forward the original signal to another cell through multimode fiber, and at the end of the fiber transmission, periodically broadcast the addressing signal with the terminal antenna and confirm the base station affiliation with CRC check. Step S5. Calculate the signal fading according to the channel model, apply gain to the signal at the terminal antenna, build a stable cross-regional link, and optimize the mode of the communication link in the optical fiber to solidify the signal mode with the least interference. Step S1 includes: Step S11. Generate a regional base station map according to the location of the base station in the cell, and conduct single base station test and full base station network test respectively. In the single base station test, shut down the surrounding base stations and keep only the target base station working. In the full base station network test, activate all cell base stations, build a cellular network environment, and make the target base station transmit known pilot signals. Step S12. Using a mobile signal receiving device equipped with a Keysight high-precision spectrum analyzer and a GPS / IMU positioning module, the signal strength, signal-to-noise ratio and delay spread data of the pilot signal are collected within the communication range of the target base station, and multiple samples are taken at different distances from the target base station. Step S13. Construct a data analysis and processing platform, connect the sampled data to the signal analysis platform, classify the collected signals according to the base station type and receiving location, generate a data table and keep it updated in real time. Each time sampling is performed, record the sampled data and sampling location in the data table.

2. The communication data management method based on multimodal networks according to claim 1, characterized in that: Step S2 includes: Step S21. During the single-base station test, record the location coordinates and received power, and use the logarithmic distance model and introduce random variables to determine the path loss model: ； Where P(d) is the received signal power, P0 is the transmitted signal power, n is the path loss exponent, d is the distance between the sampling point and the base station, d0 is the reference distance of the far field region of the transmit antenna, and X is the shadow fading random variable, and X conforms to a log-normal distribution with the receiver power as the mean. Based on the path loss model obtained from each single base station test in the data table, the path loss exponent n is fitted using the least squares method to obtain the large-scale fading function of the signal PL(d)=P0-P(d). Step S22. During the full base station network testing phase, the signal frequency is determined using Fourier transform, and the root mean square delay spread and small-scale signal fading are calculated: ； Where Fs(d) represents the small-scale fading of the signal, Let be the root mean square time delay, N be the number of test paths, ai be the time-varying amplitude function of the i-th path, and f be the signal frequency. and Let Pi(d) represent the time delay and average time delay of the i-th path, respectively. Let Pi(d) be the function of power and distance of the i-th path, j be the imaginary number, and e be the base of the natural logarithm.

3. The communication data management method based on multimodal networks according to claim 2, characterized in that: Step S3 includes: Step S31. Construct a channel model based on large-scale fading and small-scale fading as superimposed disturbances. The basic kernel function of the channel model is Pr(d) = P(d) + Fs(d) + X. Construct a regional loss heatmap according to the channel model. Step S32. Based on the regional loss heat map, select a location where the regional loss is below the threshold to set up an optical fiber forwarding antenna. Use the optical fiber forwarding antenna to receive the forwarding signal of the communication base station on a fixed frequency band. After receiving the signal, the optical fiber forwarding antenna removes noise components according to the channel model and forwards the original signal to another cell through a multimode optical fiber. The multimode optical fiber uses a direct modulation laser for electro-optic conversion and improves the optical fiber capacity through C-band or L-band multi-wavelength multiplexing. Step S33. Determine the destination receiving address, generate an addressing signal containing the target cell ID, fiber path ID, and priority label, and select the fiber communication path with the highest communication efficiency based on Dijkstra's or Q-learning algorithm according to the destination receiving address.

4. The communication data management method based on multimodal networks according to claim 3, characterized in that: Step S4 includes: Step S41. Input the distance between the fiber optic relay antenna and the base station, the signal transmission power and the signal frequency into the channel model, compensate for the fading components from the actual received signal, and convert the compensated signal into an optical signal through a photoelectric converter and enter the multimode fiber. Step S42. Encapsulate the addressing signal using the JSON protocol. At the end of the fiber optic transmission, broadcast the addressing signal using an integrated LoRa / UWB low-power wide-area communication antenna. Simultaneously, confirm the affiliation of the neighboring base station through CRC check, mark the first responding base station as the destination, and determine the ID and location of the destination base station. Step S5 includes: Step S51. Simultaneously increase the signal transmitted by the terminal antenna to make the signal power before and after transmission consistent. Based on the ID and location of the source base station and the destination base station, construct a stable cross-regional link. Step S52. Using fiber optic sensors, calculate the interference state of each signal in the fiber optic cable, optimize the modes of the communication link in the fiber optic cable, select the signal mode with the least interference, and solidify it. When coherent modes exist, schedule communication resources according to the resource requirements of each user, communication frequency, and channel loss, and select the signal mode with the highest overall signal transmission efficiency for transmission.

5. A communication data management system based on multimodal networks, characterized in that, The system includes the following modules: fading sampling module, channel modeling module, optical fiber transmission module, link gain module, and channel hardening module; The fading sampling module is used to control the base station to transmit known pilot signals. It uses a mobile signal receiving device equipped with a high-precision spectrum analyzer and GPS / IMU positioning module to collect the signal strength, signal-to-noise ratio and delay spread data of the pilot signals in real time. The data is then connected to the signal analysis platform, and the collected signals are classified according to the base station type and receiving location to generate a data table and keep it updated in real time. The channel modeling module is used in single base station testing to record location coordinates and received power, use a logarithmic distance model and introduce random variables to determine the path loss exponent, and after multiple samplings at different locations, use the least squares method to fit the path loss exponent to obtain the large-scale fading of the signal. In the full base station network testing process, the large-scale fading loss is eliminated from the received signal, the root mean square delay spread is calculated, and the small-scale fading of the signal is obtained. The large-scale fading is used as the basis, and the small-scale fading is used as a superimposed disturbance to construct the channel model, output the model basis kernel function, and construct a regional loss heatmap. The fiber optic transmission module is used to set up fiber optic forwarding antennas within a range where the path loss is below a threshold. The fiber optic forwarding antennas receive signals from the communication base station. After receiving the signal, the fiber optic forwarding antennas remove noise components according to the channel model and forward the original signal to another cell through multimode fiber. At the same time, the destination receiving address is determined, and an addressing signal containing the target cell ID, fiber optic path ID, and priority label is generated. According to the destination receiving address, the fiber optic communication path with the highest communication efficiency is selected based on Dijkstra's algorithm or Q-learning algorithm. The link gain module is used to encapsulate the addressing signal using the JSON protocol. At the end of the optical fiber transmission, the addressing signal is broadcast periodically by the terminal antenna. At the same time, the CRC check confirms the affiliation of the neighboring base station, marks the first responding base station as the destination, determines the base station's ID and location, and determines the terminal antenna transmit gain according to the channel model to ensure that the signal power before and after transmission is consistent. The channel solidification module is used to optimize the modes of the communication link in the optical fiber after a stable cross-regional link is built, select the signal mode with the least interference, and solidify it. When a coherent mode exists, communication resources are scheduled according to the resource requirements, communication frequency, and channel loss of each user.

6. The communication data management system based on a multimodal network according to claim 5, characterized in that: The fading sampling module includes: a receiver unit and a platform access unit; The receiver unit is used to perform multiple rounds of signal sampling on the cellular network using mobile signal receiving equipment; The platform access unit is used to build a data analysis and processing platform and store signal sampling data and positioning data.

7. The communication data management system based on a multimodal network according to claim 6, characterized in that: The channel modeling module includes: a mean fitting unit, a scaling fading unit, and a basis kernel function unit; The mean fitting unit is used to control the target base station to transmit a known pilot signal and determine the mean value of the received power; The scale fading unit is used to determine the large-scale fading and small-scale fading of the signal based on the signal sampling results; The basis kernel function units are superimposed with scale fading, and an LSTM network is used to predict the fading trend and generate a channel model.

8. The communication data management system based on a multimodal network according to claim 7, characterized in that: The optical fiber transmission module includes: an optical fiber antenna unit, a multimode optical fiber unit, and a signal broadcasting unit; The fiber optic antenna unit is used to achieve cross-cell signal transmission and routing optimization through a fiber optic repeater antenna; The multimode fiber unit is used to perform electro-optic conversion using a direct modulated laser, and to increase fiber capacity through C-band or L-band multi-wavelength multiplexing. The signal broadcasting unit is used to transmit target addressing signals using an integrated LoRa / UWB low-power wide-area communication antenna.

9. The communication data management system based on a multimodal network according to claim 8, characterized in that: The link gain module includes: a node addressing unit and a fading compensation unit; The node addressing unit is used to calculate the comprehensive efficiency index of each optical fiber path and select the path with the highest index for communication hopping. The fading compensation unit is used to calculate signal fading according to the channel model and perform path loss compensation on the signal at the terminal antenna. The channel solidification module includes: an interference analysis unit and a resource scheduling unit; The interference analysis unit is used to calculate the interference state of each signal in the optical fiber and solidify the signal mode with the least interference. The resource scheduling unit is used for distributed power control according to user type and communication needs.

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