Communication network optimization method and device for rail transit

Abstract

The invention relates to the technical field of rail transit communication, and discloses a communication network optimization method and device for rail transit. According to the communication network optimization method and device for rail transit, the quality of the communication link is regulated and controlled according to the real-time state of train operation, the stability of data transmission can be guaranteed, the reliability of the communication network in the train operation process is improved, accurate transmission of key data such as train operation control is guaranteed, and the service life of the communication network is prolonged. Traffic is regulated and controlled according to load distribution of network nodes of a track area, network congestion of a hot spot area can be effectively relieved, network loads are balanced, the utilization efficiency of network resources is improved, network operation is smoother, normal development of various services is guaranteed, access priority is regulated and controlled according to different service requirements, and the service quality is improved. Therefore, the emergency message can be transmitted preferentially, the timeliness and the efficiency of emergency handling are improved, and the safety and the emergency response capability of the rail transit system are enhanced.

Description

Technical Field

[0001] This application relates to the technical field of rail transit communication, and particularly relates to a communication network optimization method and device for rail transit. Background Art

[0002] A communication network optimization method and device for rail transit aims to improve the stability and efficiency of communication links in the rail transit system through various means. This technology focuses on solving five key problems: First, it dynamically adjusts the communication link quality according to the real-time state of train operation to ensure stable data transmission even under complex operating conditions; Second, by real-time monitoring and analyzing the load distribution of network nodes in the track area, it reasonably allocates traffic to avoid network congestion in hot spots; Third, it adjusts the access priority according to different service requirements, especially ensuring that emergency messages can be processed preferentially to ensure unobstructed information transmission at critical moments; In addition, it intelligently adjusts the wireless channel allocation according to the signal strength and handover frequency, thereby reducing communication interruptions caused by vehicle movement; Finally, it optimizes the bandwidth resource allocation strategy by combining historical data with the current operation mode to effectively alleviate the shortage of bandwidth during peak hours. In short, this method greatly improves the overall performance and service quality of the rail transit communication network through comprehensive consideration and flexible adjustment of various factors. Summary of the Invention

[0003] To solve the problems raised in the above background art, this application provides a communication network optimization method and device for rail transit.

[0004] This application provides a communication network optimization method for rail transit, adopting the following technical solutions:

[0005] A communication network optimization method and device for rail transit includes:

[0006] S101. Monitor and evaluate the communication link quality according to the real-time state of train operation, and determine the unstable area of data transmission;

[0007] S102. Adjust relevant parameters based on the evaluation result of the communication link quality to optimize the data transmission stability;

[0008] S103. Reallocate traffic according to the load distribution of network nodes in the track area to ensure smooth network in hot spots;

[0009] S104. Dynamically adjust the access priority and bandwidth resource allocation according to service requirements to ensure the timely transmission of emergency messages and meet the requirements of different service types.

[0010] Preferably, the communication link quality is regulated based on the real-time state of the train to solve the problem of unstable data transmission. The specific steps are as follows:

[0011] Obtain the geographical location information of the current train;

[0012] Calculate the link margin L = SNR_min - current_SNR based on the following formula, where SNR_min represents the minimum required signal-to-noise ratio and current_SNR is the current actual signal-to-noise ratio;

[0013] If L is less than or equal to the preset threshold L_th, then trigger an adjustment instruction;

[0014] Dynamically adjust the power to compensate for the link margin loss and record the relevant adjustments.

[0015] Preferably, a method for regulating traffic based on the load distribution of track area network nodes to solve the problem of network congestion in hot spots includes:

[0016] Real-time monitor the connection number and average response time N and T_avr of each node;

[0017] Based on the weighted formula Q_i = Σ(w_k * N_k) + Σ(t_m * T_mk), where i refers to a specific node, N_k and T_mk are respectively the total connection number of the kth node in this area and the weighted time delay of all its sessions;

[0018] When the comprehensive evaluation value Q_i of a certain node is greater than the preset value Q_max, it is identified as a hot spot node;

[0019] Redirect new service requests to adjacent low-load areas to reduce the hot spot pressure.

[0020] Preferably, the measures for regulating the access priority according to service requirements to transmit emergency messages in a timely manner include:

[0021] Mark the emergency level C_level = F(D_type) by analyzing the data characteristics of each service;

[0022] Set a basic threshold Threshold_C, and compare the situation of C_level > Threshold_C to decide whether to enter high-priority processing;

[0023] For services higher than the threshold, reserve a fixed resource share X_percent in advance;

[0024] All high-importance and critical tasks higher than the given conditions are given priority to be sent and queued according to the regular queue rules for execution under normal conditions.

[0025] Preferably, the technical means for controlling wireless channel distribution based on signal quality and handover frequency to prevent disconnection during movement are as follows:

[0026] Record the number of times H_sw of channel state changes at the last N_frame moments;

[0027] Use an exponential average filter to estimate the channel stability degree E_H = α * current_E+(1 - α)*old_H_sw, where α is the forgetting factor;

[0028] If the newly obtained evaluation value E_H is less than the safety critical point H_min, the process of searching for the best available backup channel will be automatically started;

[0029] To avoid additional interference caused by frequent handovers, limit the maximum number of handovers per second Switch_cap_per_second not to exceed the upper limit specified.

[0030] Preferably, the method for formulating a more reasonable broadband allocation strategy based on historical and current operation modes to relieve the bottleneck situation during peak periods includes:

[0031] Collect the system work logs and occupancy statistics S_hist during historical similar periods, and establish a prediction model Y_pred;

[0032] Calculate the expected access load Est_Ld = β * Y_pred+γ*(sum(V_ex)) according to external variables V_ex such as the current passenger flow intensity and weather factors;

[0033] Judge whether the predicted overall load exceeds the warning line L_warm_line, where β and γ are both coefficients used to adjust the influence of different inputs on the output;

[0034] Pre-configure and increase the redundant bandwidth capacity by a certain percentage P_inc% before the upcoming peak period.

[0035] Preferably, the further enhancement measures for the adjustment mechanism based on the load situation include:

[0036] Track the user movement trend and estimate the infrastructure utilization density R_dens_est within the path coverage in the future period of time;

[0037] Combined with the vehicle formation plan, use the function R_ratio_est(F_t) to predict the maximum communication flow ratio that different sections may carry;

[0038] Formula R_diff = |Current_R_ratio_actual

[0039] Estimated_R_ratio_expected | Measure the difference between the actual usage efficiency and the plan. When the R_diff exceeds the reasonable floating range Delta_accept, take remedial measures;

[0040] Prepare sufficient elastic expansion space near stations or intersections so that even in the face of unexpected peaks, a high-quality communication experience can still be guaranteed.

[0041] Preferably, the operation method of combining dynamic routing selection to improve data forwarding efficiency and reduce potential failure risks consists of the following actions:

[0042] Traverse all options to determine the route path_best_select that currently has the lowest hop count value L_hop and is most likely to maintain long-term coherence;

[0043] Apply the algorithm M_metric(path_metrics) to comprehensively consider various indicators such as throughput and latency to select the theoretically best path;

[0044] Once a parameter such as P_jitter > Max_P_allotment (where Max_P_allotment refers to the maximum allowable delay jitter value) is detected in a segment of the selected path, the path is considered degraded;

[0045] Proactively switch to the sub-optimal alternative or trigger a local reconstruction program, and at the same time feedback the change details to the upper layer.

[0046] Preferably, the specific implementation plan for refining the aforementioned resource estimation and preventive control mechanism is as follows:

[0047] Design flexible Service-Level Agreements (SLAs) according to the changes in the number of people flow in different time periods;

[0048] Regularly update and maintain the device performance parameter table D_param_set to ensure that it meets the requirements described in the latest standards and technical guidance documents;

[0049] Set a decision-making basis, such as IF Current_Service_Utility >= Target_Expected_Usefulness THEN Proceed_with_Default else Adjust_for_Optimal, which involves comparing the gap between the existing service level and the ideal target;

[0050] Introduce a third-party audit and verification agency to ensure that all operations can effectively support efficient transportation management and a good user experience;

[0051] The process for optimizing routing decisions in a dynamic environment includes:

[0052] Evaluate the overall performance of alternative routes, especially considering their robustness Robu_factor = exp((Sum_Disturb / avg_dist)), which measures the ability of the entire path to resist the impact of sudden disturbances;

[0053] Determine the preferred chain that meets the fast convergence standard Convergence_Speed_Standard_CSs and has strong anti-interference characteristics;

[0054] If the failure probability P_failure_est of any middleware on the selected chain exceeds the allowable range Allow_fault_prob, it will be eliminated even if other aspects are excellent;

[0055] Prioritize selecting a line with higher redundancy and stronger recovery potential to ensure continuous and reliable communication without interruption;

[0056] In the long run, measures to strengthen the interconnection between network security and efficiency also include:

[0057] Collect abnormal traffic activities pattern_abnor and attack vectors attack_vectors during the operation of the entire network to create a behavior pattern library Patterns_library;

[0058] Perform feature matching on each newly added task flow and compare it with known cases Check_task_vector_violation(TF);

[0059] If the possibility score of malicious intent Score_attack_risk >= Thredhold_highRiskLevel (the threshold represents a very high level of security threat) in the comparison result, immediately execute the emergency response strategy;

[0060] Simultaneously strengthen the construction of the defense system to form a complementary protection relationship among subsystems and improve the overall protection level.

[0061] A communication network optimization device for rail transit, the device performs operations through a communication network optimization method for rail transit, and the system includes:

[0062] Monitoring and evaluation module: Collect various key data in the communication network in real time, including but not limited to signal strength, transmission rate, bit error rate, delay time, packet loss rate, etc.;

[0063] Adjustment parameter module: According to the signal strength information feedback by the monitoring and evaluation module, adjust parameters such as transmission power and antenna gain to make the signal in the complex environment of rail transit;

[0064] Traffic allocation module: For critical services such as train operation control, the traffic allocation module will ensure that it obtains sufficient and stable network bandwidth;

[0065] Resource allocation module: For critical services closely related to train operation safety such as train operation control, the resource allocation module will ensure that it obtains preferential resource allocation.

[0066] In summary, the present application includes at least one of the following beneficial technical effects:

[0067] 1. The communication network optimization method and device for rail transit can ensure the stability of data transmission, improve the reliability of the communication network during train operation, and ensure the accurate transmission of critical data such as train operation control by regulating the communication link quality according to the real-time state of train operation.

[0068] 2. The communication network optimization method and device for rail transit can effectively relieve network congestion in hot spots, balance network load, improve the utilization efficiency of network resources, make the network operation smoother, and ensure the normal development of various services by regulating traffic according to the load distribution of network nodes in the track area.

[0069] 3. The communication network optimization method and device for rail transit can ensure the priority transmission of emergency messages, improve the timeliness and efficiency of emergency handling, and enhance the safety and emergency response ability of the rail transit system by regulating the access priority according to different service requirements.

[0070] 4. The communication network optimization method and device for rail transit can avoid communication interruption during movement, ensure the continuity of communication during train movement, and improve the communication experience of passengers and the communication guarantee of train operation by regulating wireless channel allocation according to signal strength and handover frequency.

[0071] 5. The communication network optimization method and device for rail transit can reasonably allocate bandwidth resources during peak hours, relieve the situation of insufficient bandwidth, meet the service requirements during peak hours, improve the service quality of the network and the user experience by regulating the bandwidth resource allocation strategy according to historical data and the current operation mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 is a flowchart of the communication network optimization method for rail transit of the present invention;

[0073] Figure 2 is a flowchart of the communication network optimization device for rail transit of the present invention. Detailed implementation manners

[0074] The following details the implementation manners of the present application, and examples of the implementation manners are shown in the accompanying drawings.

[0075] In the description of this specification, the description with reference to the terms "certain implementation manners", "one implementation manner", "some implementation manners", "schematic implementation manners", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the implementation manner or example are included in at least one implementation manner or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same implementation manner or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more implementation manners or examples.

[0076] An embodiment of the present application discloses a communication network optimization method for rail transit. Next, with reference to the attached Figure 1 ..., a communication network optimization method and device for rail transit of the present invention are described. This method realizes the optimization of the rail transit communication network through multiple steps, and solves problems such as the influence of train operation status on data transmission, network congestion, access priority regulation, wireless channel switching interruption, and bandwidth resource allocation. This method and device can ensure the efficient and stable operation of the rail transit system.

[0077] Including: receiving real-time operation parameters of each node in the rail transit area. Specifically, this step uses sensor acquisition devices installed at various nodes such as stations, depots, tunnels, etc. to collect various parameters of equipment operation, including but not limited to speed information, positioning information, and vehicle interior and exterior environment information. Based on these raw data, the position and operation status of the train are analyzed. This is the key to ensuring the stable operation of the entire communication system. During this process, all collected data will be immediately transmitted to the background control center. For example, for a train running in a complex geographical terrain, it may frequently enter and exit signal blind spots or weak coverage areas. In this case, timely grasping the dynamic changes of the vehicle and feeding back to the system can effectively cope with the communication quality challenges caused thereby.

[0078] After that, a dynamic link quality assessment model is established based on the received communication quality detection results between stations. Miniaturized intelligent detection terminals deployed throughout the line continuously monitor the channel characteristics between adjacent stations and regularly upload the statistically summarized data to the server to update the evaluation index system. When the uplink and downlink throughput rates of a specific link suddenly drop, the problem location is quickly identified and marked, and then automatic fault troubleshooting and alarm push notifications are sent to maintenance personnel to take further measures until the normal state is fully restored. In one embodiment, once it is detected that a high-speed train during a fast journey is about to enter a key section where interference accidents have occurred before or packet loss phenomena have frequently occurred for a long time, an adjustment strategy is pre-triggered to reduce the error code threshold in advance, so as to ensure that good performance levels can be continuously maintained even under harsh conditions and avoid the impact of uncertainties brought by external uncontrollable factors on the overall service level provision.

[0079] Immediately afterwards, an adaptive traffic control algorithm is implemented for resource reallocation according to the internal service load conditions of each communication cell. This requires the system to accurately calculate the change law of the number of active users at different time intervals, estimate the peak demand in the future period, and reasonably allocate bandwidth shares while also taking into account the principle of fair competition to limit any single application from monopolizing too many shares to avoid forming a local bottleneck that hinders other normal services from achieving the expected service effect. For example, as described below, the peak and valley periods of urban rail transit vary greatly. Especially during the morning and evening rush hours, the subway stations are crowded with people, causing the wireless local area network to be severely saturated. If the number of Internet access requests is not restricted at this time, it will inevitably cause problems such as a large number of passengers being unable to connect to WIFI or even mobile payment failures, seriously affecting the satisfaction of the travel experience. Therefore, it is necessary to set up a crowd gathering early warning mechanism based on deep learning specifically designed for such hot spots to respond in real time and trigger an emergency evacuation plan to ensure that the service continuity and stability are not affected.

[0080] At the same time, different QoS level mapping relationships are set according to different priority tags to ensure the priority transmission of important transactions. The specific operation is to obtain from the database the various task categories and their corresponding important level identifiers specified by the railway dispatcher in advance as the rule input source. After being parsed by the logic operation unit, the corresponding transmission channels are matched, and then the priority sorting output is realized in a multi-channel concurrent environment to ensure that high-value information can be selected through the fastest and optimal path and reach the destination in the first time to play its due role, reduce unnecessary waiting delays, improve the overall cooperation efficiency, support the normal operation of the security guarantee system, and maintain the daily management order. For example, when a train approaches the platform and needs to broadcast the door opening and closing prompt sound file to the platform side, because this sound is directly related to the safety of passengers, its priority is higher than the content provided by the ordinary passenger entertainment information system.

[0081] Finally, the combination of self-organizing network technology and spectrum sensing technology is used to carry out intelligent wireless base station site selection and deployment plan planning. This step aims to measure and analyze the signal propagation strength around the potential location through the software platform to find a relatively ideal location to place a new or relocated transmission port. This will not only help to enhance the overall receiving sensitivity within the target coverage area, but also reduce the probability of unplanned frequent switching events to maintain good communication continuity. Especially in long-distance transportation, due to the changeable geographical environment, network disconnection is prone to occur. Therefore, this mechanism is needed to compensate and improve user experience. In addition, historical records are combined to mine potential patterns and optimize response strategies in similar scenarios in the future. That is, make full use of existing operational data precipitation to guide the decision-making process of the current actual application scenario. In an example, considering that the passenger capacity of some special popular routes during the peak holiday travel period will be doubled compared to usual, preparations can be made in advance to arrange for technical personnel to enter the site to temporarily increase and supplement hotspots and equipment resources to prevent network paralysis caused by excessive congestion.

[0082] In one embodiment, a communication network optimization device for rail transit is also disclosed. The evaluation system is executed by the above-mentioned communication network optimization method for rail transit. Figure 2 As shown, the system includes:

[0083] Monitoring and evaluation module: real-time collection of various key data in the communication network, including but not limited to signal strength, transmission rate, bit error rate, delay time, packet loss rate, etc.;

[0084] Parameter adjustment module: According to the signal strength information fed back by the monitoring and evaluation module, adjust the parameters such as transmission power and antenna gain to make the signal in the complex environment of rail transit;

[0085] Traffic distribution module: For key businesses such as train operation control, the traffic distribution module ensures that they have sufficient and stable network bandwidth;

[0086] Resource allocation module: For key businesses closely related to driving safety, such as train operation control, the resource allocation module will ensure that they receive priority resource allocation.

[0087] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A communication network optimization method for rail transit, characterized in that: include: S101, monitoring and evaluating the quality of the communication link according to the real-time status of the train operation, and determining the area where data transmission is unstable; S102, adjusting relevant parameters based on the evaluation result of the communication link quality to optimize data transmission stability; S103, redistribute traffic according to the load distribution of network nodes in the track area to ensure smooth network in the hot spot area; S104. Dynamically adjust access priority and bandwidth resource allocation according to business needs to ensure timely delivery of emergency messages and adapt to requirements of different business types.

2. A communication network optimization method for rail transit according to claim 1, characterized in that: The communication link quality is regulated based on the real-time status of the train to solve the problem of unstable data transmission. The specific steps are as follows: Get the geographic location information of the current train; The link margin L is calculated based on the following formula: SNR_min current_SNR, where SNR_min represents the minimum required signal-to-noise ratio, and current_SNR is the current actual signal-to-noise ratio; If L is less than or equal to the preset threshold value L_th, the adjustment instruction is triggered; Dynamically adjust power to compensate for link margin loss and record the adjustments.

3. A communication network optimization method for rail transit according to claim 1, characterized in that: The method for regulating traffic based on the load distribution of network nodes in the rail area to solve the network congestion problem in hot spots includes: Real-time monitoring of the number of connections and average response time N and T_avr of each node; Based on the weighted formula Q_i=Σ(w_k*N_k)+Σ(t_m*T_mk), where i refers to a specific node, N_k and T_mk are the total number of connections of the kth node in the area and the weighted time delay of all its sessions; When the comprehensive evaluation value Q_i of a node is greater than the preset value Q_max, it is identified as a hotspot node; Redirect new business requests to adjacent low-load areas to reduce hot spot pressure.

4. A communication network optimization method for rail transit according to claim 3, characterized in that: The measures for adjusting access priority according to business requirements and timely delivering emergency messages include: By analyzing the data characteristics of each service, the urgency level C_level=F(D_type) is marked; Set a basic threshold Threshold_C, and compare the situation where C_level>Threshold_C to decide whether to enter high priority processing; For services above the threshold, a fixed resource share X_percent is reserved in advance; All high-importance and critical tasks above the given conditions are sent first, and queued for execution according to the regular queue rules under normal conditions.

5. The communication network optimization method for rail transit according to claim 1, characterized in that: The technical means of controlling wireless channel distribution based on signal quality and switching frequency to prevent disconnection during mobility are as follows: Record the number of channel status changes H_sw in the last N_frame moments; Use exponential average filter to estimate channel stability E_H=α*current_E+(1α)*old_H_sw, where α is the forgetting factor; If the new evaluation value E_H obtained is less than the safety critical point H_min, the process of searching for the best available backup channel will be automatically started; To avoid additional interference caused by frequent switching, the maximum number of transfers per second is limited to Switch_cap_per_second and must not exceed the upper limit.

6. A communication network optimization method for rail transit according to claim 5, characterized in that: Using historical and current operating models to develop a more reasonable bandwidth allocation strategy. Ways to alleviate bottlenecks during busy periods include: Collect the system work logs and occupancy statistics S_hist in similar historical periods, and establish a prediction model Y_pred; Calculate the expected visit load Est_Ld = β*Y_pred+γ*(sum(V_ex)) according to the existing passenger flow intensity and weather factor external variable V_ex; Determine whether the predicted overall load exceeds the warning line L_warm_line. β and γ are coefficients used to adjust the impact of different inputs on the output; Before the upcoming peak period, a certain percentage of redundant bandwidth capacity, eg, P_inc%, is pre-configured.

7. A communication network optimization method for rail transit according to claim 6, characterized in that: Further enhancements to the load-based adjustment mechanism described above include: Track user mobility trends and estimate the infrastructure utilization density R_dens_est within the path coverage area in the future; Combined with the vehicle formation plan, the function R_ratio_est(F_t) is used to predict the maximum communication flow ratio that different road sections may carry; Formula R_diff=|Current_R_ratio_actual Estimated_R_ratio_expected|Measures the difference between actual efficiency and planned efficiency. When R_diff exceeds the reasonable floating range Delta_accept, take remedial measures; Prepare enough flexible expansion space near stations or intersections to ensure a high-quality communication experience even in the face of unexpected peaks.

8. A communication network optimization method for rail transit according to claim 7, characterized in that: The operation mode of improving data forwarding efficiency and reducing potential failure risks by combining dynamic routing selection consists of the following actions: Traverse all options to determine the route path_best_select that currently has the lowest hop value L_hop and maintains long-term continuity; The algorithm M_metric (path_metrics) is applied to comprehensively consider various indicators such as throughput and delay to select the theoretically best path; Once a segment on the selected path detects a parameter such as P_jitter>Max_P_allotment, it is considered a degraded path; Actively switch to the next best alternative option or trigger a local reconstruction procedure, while feeding back the change details to the upper layer.

9. A communication network optimization method for rail transit according to claim 8, characterized in that: The specific implementation plan to refine the above-mentioned resource estimation and preventive control mechanism is: Design flexible service level agreements (SLAs) based on the flow of people in different time periods; Regularly update and maintain the equipment performance parameter table D_param_set to ensure that it complies with the requirements described in the latest standards and technical guidance documents; Set a decision basis, such as IF Current_Service_Utility>=Target_Expected_Usefulness THEN Proceed_with_Default else Adjust_for_Optimal, which involves comparing the gap between the current service level and the ideal target; Introduce third-party audit and verification agencies to ensure that all operations can effectively support efficient transportation management and good user experience; The process of optimizing routing decisions in a dynamic environment includes: Evaluate the overall performance of the alternative route, considering its robustness Robu_factor = exp((Sum_Disturb / avg_dist)), which measures the ability of the entire path to resist the impact of sudden interference; Determine the optimal chain that meets the fast convergence standard Convergence_Speed_Standard_CSs and has anti-interference characteristics; If the failure probability P_failure_est of any middleware on the selected chain exceeds the allowed range Allow_fault_prob, it will be eliminated even if it is good in other aspects; Prioritize a line with higher redundancy and stronger recovery potential to ensure continuous and reliable communication without interruption; Strengthening the interconnectedness of cybersecurity and efficiency also includes: Collect abnormal traffic activities pattern_abnor and attack vectors attack_vectors in the whole network, and create a behavior pattern library Patterns_library; Perform feature matching on each newly added task flow and compare it with known cases Check_task_vector_violation(TF); If the comparison result shows that there is a malicious attempt possibility score Score_attack_risk>=Thredhold_highRiskLevel, the emergency response strategy is immediately executed; Simultaneously strengthen the construction of the defense system, form a mutually complementary protection relationship between each subsystem to improve the overall protection level.

10. The communication network optimization device for rail transit according to claim 1, characterized in that: The device is operated by a communication network optimization method for rail transit as described in any one of claims 1 to 9, and the system includes a monitoring and evaluation module: real-time collection of various key data in the communication network, including but not limited to signal strength, transmission rate, bit error rate, delay time, and packet loss rate; Parameter adjustment module: According to the signal strength information fed back by the monitoring and evaluation module, the transmission power and antenna gain parameters are adjusted to make the signal in the complex environment of rail transit; Traffic distribution module: For key businesses such as train operation control, the traffic distribution module ensures that they have sufficient and stable network bandwidth; Resource allocation module: For key businesses that are closely related to train operation control and driving safety, the resource allocation module will ensure that they receive priority resource allocation.

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