Vehicle-mounted radio frequency band management method, system, equipment and medium

Abstract

A vehicle-mounted radio frequency band management method, system, device and medium, the method comprising: acquiring communication behavior data and first spectrum usage data of a first vehicle-mounted communication device in a target area, second spectrum usage data of a second vehicle-mounted communication device, and people flow density change characteristics of the target area within a preset time period; constructing a frequency band behavior portrait of a radio frequency band in the target area; determining a plurality of target time windows according to the people flow density change characteristics; dividing the frequency band behavior portrait according to the plurality of target time windows to obtain a plurality of frequency band behavior sub-portraits, and setting a frequency spectrum use baseline for each frequency band behavior sub-portrait; calculating the space-time correlation degree of the first vehicle-mounted communication equipment and the second vehicle-mounted communication equipment in the target sub-region; and determining a frequency spectrum management priority of the first vehicle-mounted communication equipment, and distributing a frequency band combination for the first vehicle-mounted communication equipment. According to the invention, the matching degree of resource allocation and actual communication load can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of frequency band management, in particular to a vehicle-mounted radio frequency band management method, system, device and medium. BACKGROUND

[0002] With the popularization of intelligent transportation infrastructure, vehicle-mounted communication technology plays an increasingly important role in realizing traffic information collaboration, improving road traffic efficiency and driving safety. In the vehicle-to-everything (V2X) environment, vehicles and roadside devices exchange information in real time through wireless communication, and the demand for wireless spectrum resources is constantly increasing. In the actual urban traffic environment, emergency law enforcement vehicles (such as police vehicles, fire vehicles, ambulance vehicles, etc.) as the key force for handling emergencies and executing public safety have higher requirements for the stability, low delay and anti-interference capability of the communication link of the vehicle-mounted communication system.

[0003] The existing spectrum management method usually relies on modeling the communication behavior of vehicles, collecting data such as communication frequency, channel occupancy, and interference strength, and combining the geographical position and communication density of vehicles to analyze and monitor the spectrum usage. On this basis, the system performs unified spectrum scheduling or resource allocation according to the communication pressure or interference risk of the entire region.

[0004] However, in the context of frequent changes in the number of people, usually accompanied by higher information interaction needs, when emergency law enforcement vehicles face areas with large changes in the number of people and concentrated communication needs, the strategy of scheduling frequency bands for the entire region based on average indicators cannot timely adjust the spectrum resource configuration, resulting in mismatch between resource allocation and actual communication load. SUMMARY

[0005] The present application provides a vehicle-mounted radio frequency band management method, system, device and medium for improving the matching degree of resource allocation and actual communication load.

[0006] In a first aspect of the present application, a vehicle-mounted radio frequency band management method is provided, applied in a server, the method comprising: obtaining communication behavior data of a first vehicle-mounted communication device in a target area, first spectrum usage data, second spectrum usage data of a second vehicle-mounted communication device in the communication area of the first vehicle-mounted communication device, and a people flow density change feature of the target area in a preset time period, the first vehicle-mounted communication device being a vehicle-mounted communication device of an emergency law enforcement vehicle, and the second vehicle-mounted communication device being a vehicle-mounted communication device of all types of vehicles in the target area except the emergency law enforcement vehicle; constructing a frequency band behavior portrait of the radio frequency band in the target area based on the communication behavior data, the first spectrum usage data, and the second spectrum usage data; determine a plurality of target time windows according to the human flow density change feature; divide the frequency band behavior image according to the plurality of target time windows to obtain a plurality of frequency band behavior sub-images, and set a spectrum use baseline for each of the frequency band behavior sub-images, one target time window corresponding to one frequency band behavior sub-image; calculate a spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in a target sub-region based on the target time window and the spectrum use baseline, the target sub-region being divided from the target region according to a preset rule; determine a spectrum management priority of the first vehicle-mounted communication device based on the spatio-temporal correlation degree and the frequency band behavior image, and allocate a frequency band combination to the first vehicle-mounted communication device.

[0007] Optionally, a frequency band behavior image of a radio frequency band in the target region is constructed based on the communication behavior data, the first spectrum use data and the second spectrum use data, specifically including: divide the signal-to-noise ratio time curve in the first spectrum use data into a plurality of evaluation units of equal time length, and combine the average value and fluctuation rate of the signal-to-noise ratio in each evaluation unit according to the time sequence of the evaluation unit to obtain a spectrum stability sequence; In the spectrum stability sequence, determine the evaluation unit with a fluctuation rate greater than a preset fluctuation rate threshold as a first evaluation unit, and determine a target frequency band with frequency overlap between the first spectrum use data and the second spectrum use data in the first evaluation unit, combine the first spectrum use data corresponding to the target frequency band and the second spectrum use data corresponding to the target frequency band according to the time sequence of the first evaluation unit to obtain a spectrum competition situation sequence; connect the interruption position, interruption times and interruption recovery time length of the communication service in the communication behavior data under the target frequency band according to the time sequence to obtain a spectrum disaster tolerance demand sequence; combine the spectrum stability sequence, the spectrum competition situation sequence and the spectrum disaster tolerance demand sequence according to the time sequence to obtain the frequency band behavior image.

[0008] Optionally, a spectrum use baseline is set for each of the frequency band behavior sub-images, specifically including: traverse the spectrum competition situation sub-sequence corresponding to each of the frequency band behavior sub-images, and determine the first evaluation unit with frequency overlap in the spectrum competition situation sub-sequence as a second evaluation unit; determine the time coincidence degree of the second evaluation unit and the interruption position in the spectrum disaster tolerance demand sub-sequence corresponding to the frequency band behavior sub-image, and set the time coincidence degree as the risk weight given to each of the second evaluation units; determining a target volatility rate corresponding to a timestamp of each second evaluation unit from the subsequence of spectrum competition situation, and calculating a risk weighted volatility benchmark value of the target time window by weighting the target volatility rate according to the risk weight, and setting the risk weighted volatility benchmark value as a benchmark value of the spectrum usage baseline.

[0009] Optionally, the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region is calculated based on the target time window and the spectrum usage baseline, and specifically includes: calculating a target spectrum usage deviation degree of the first spectrum usage data of each target time window and the spectrum usage baseline; constructing a communication load distribution map of the second vehicle-mounted communication device based on the second spectrum usage data for each target time window; calculating the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region based on the communication load distribution map and the target spectrum usage deviation degree.

[0010] Optionally, the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region is calculated based on the communication load distribution map and the target spectrum usage deviation degree, and specifically includes: determining the target sub-region in the communication load distribution map that has a communication region overlapping with the first vehicle-mounted communication device within the target time window, to obtain a number of communication requests of the second vehicle-mounted communication device in a preset unit time in the target sub-region; determining a spectrum synchronization section as a spectrum section corresponding to a deviation period in which the target spectrum usage deviation degree and the number of communication requests simultaneously meet a preset change requirement in the target sub-region; determining a number of occurrences of the spectrum synchronization section in each target sub-region and a duration of each occurrence, and calculating a product of the number of occurrences and the duration to obtain the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in each target sub-region.

[0011] Optionally, the spectrum management priority of the first vehicle-mounted communication device is determined based on the spatio-temporal correlation degree and the frequency band behavior image, and specifically includes: multiplying the spatio-temporal correlation degree of the target sub-region and a cumulative synchronization duration of the spectrum synchronization section in the target sub-region to obtain a spectrum competition index; determine an interruption recovery time length of a communication task in the target sub-region based on the spectrum disaster tolerance demand sequence in the frequency band behavior image, calculate a ratio of the spectrum competition index and the interruption recovery time length, obtain a priority coefficient of the first vehicle-mounted communication device in the target sub-region, and determine the spectrum management priority based on the priority coefficient.

[0012] Optionally, a frequency band combination is allocated to the first vehicle-mounted communication device, specifically comprising: The communication data packet quantity, transmission rate and service type of the communication behavior data in the target sub-region are weighted calculated with the spectrum management priority of the target sub-region to obtain a frequency band demand parameter of the target sub-region; candidate frequency bands in a preset candidate frequency band list are sorted in descending order of frequency interval, the candidate frequency bands are sequentially compared with the occupied frequency bands of the second vehicle-mounted communication device in the target sub-region, a frequency band combination with the largest interval from the occupied frequency bands of the second vehicle-mounted communication device and meeting the frequency band demand parameter is selected, and the frequency band combination is allocated to the first vehicle-mounted communication device.

[0013] In a second aspect of the present application, a vehicle-mounted radio frequency band management system is provided, comprising: The acquisition module is configured to acquire communication behavior data of a first vehicle-mounted communication device in a target region, first spectrum usage data, second spectrum usage data of a second vehicle-mounted communication device in a communication region of the first vehicle-mounted communication device, and a flow density change feature of the target region in a preset time period, wherein the first vehicle-mounted communication device is a vehicle-mounted communication device of an emergency law enforcement vehicle, and the second vehicle-mounted communication device is a vehicle-mounted communication device of all types of vehicles in the target region except the emergency law enforcement vehicle. The construction module is configured to construct a frequency band behavior image of a radio frequency band in the target region based on the communication behavior data, the first spectrum usage data and the second spectrum usage data. The determination module is configured to determine a plurality of target time windows according to the flow density change feature. The division module is configured to divide the frequency band behavior image according to the plurality of target time windows to obtain a plurality of frequency band behavior sub-images, and set a spectrum usage baseline for each frequency band behavior sub-image, wherein one target time window corresponds to one frequency band behavior sub-image. The calculation module is configured to calculate a space-time correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in a target sub-region based on the target time window and the spectrum usage baseline, wherein the target sub-region is divided from the target region according to a preset rule. The allocation module is configured to determine a spectrum management priority of the first vehicle-mounted communication device based on the spatio-temporal correlation degree and the frequency band behavior image, and allocate a frequency band combination for the first vehicle-mounted communication device.

[0014] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface, and a network interface. The memory is configured to store instructions. The user interface and the network interface are both configured to communicate with other devices. The processor is configured to execute the instructions stored in the memory, so that the electronic device performs the method according to any one of the preceding aspects.

[0015] In a fourth aspect of the present application, a computer-readable storage medium is provided, which stores instructions. When the instructions are executed, the method according to any one of the preceding aspects is performed.

[0016] In summary, the one or more technical solutions provided by the present application have at least the following technical effects or advantages: 1. By obtaining the communication behavior data, the first frequency spectrum usage data, the second frequency spectrum usage data, and the human flow density change feature of the first vehicle-mounted communication device in the target area, the communication subject behavior, the spectrum usage state, and the external dynamic environment can be comprehensively perceived. On this basis, the frequency band behavior image is constructed, and the target time window is divided in combination with the human flow density change feature. The frequency band behavior sub-image and the corresponding frequency spectrum usage baseline are generated, so that the spectrum usage model has time sequence response capability. Further, the target sub-area is divided according to the preset rule, and the spatio-temporal correlation degree between the first vehicle-mounted communication device and the second vehicle-mounted communication device is calculated in combination with the time window and the frequency spectrum usage baseline, so as to quantify the spectrum usage overlap. Finally, the spectrum management priority of the first vehicle-mounted communication device is determined based on the frequency band behavior image, the frequency spectrum usage baseline, and the spatio-temporal correlation degree, and the frequency band combination is allocated, so as to realize the precise scheduling of spectrum resources for emergency vehicles. By fusing the communication behavior, the human flow dynamics, and the interference relationship, the spatio-temporal adaptability and real-time control capability of spectrum allocation are enhanced, and the matching degree of resource allocation and actual communication load is improved.

[0017] 2、By dividing the signal-to-noise ratio time curve in the first spectrum usage data into multiple equal-length evaluation units, and calculating the average signal-to-noise ratio and fluctuation rate within each evaluation unit, a spectrum stability sequence reflecting the change in spectrum availability is obtained. On this basis, the first evaluation unit with a fluctuation rate exceeding a preset threshold is identified, and the frequency bands with frequency overlap are identified in combination with the second spectrum usage data, and a spectrum competition situation sequence that may have competitive interference is extracted. Further combined with the communication behavior data, the interruption position, interruption frequency and interruption recovery time length of the communication service in the spectrum competition situation sequence are identified, and a spectrum disaster tolerance demand sequence is constructed. Finally, the spectrum stability sequence, the spectrum competition situation sequence and the spectrum disaster tolerance demand sequence are integrated in chronological order to construct a frequency band behavior portrait that can dynamically reflect the interference intensity, conflict risk and communication fault tolerance demand of the frequency band. The portrait integrates spectrum quality fluctuation, frequency conflict situation and communication interruption characteristics, and can more truly restore the running situation of the spectrum environment, providing a more accurate and reliable basis for subsequent spectrum usage baseline setting, priority evaluation and frequency band allocation, thereby improving the adaptability and robustness of the spectrum management method in complex communication environments.

[0018] 3、By traversing each spectrum competition situation sub-sequence in the frequency band behavior sub-portrait, the second evaluation unit with frequency overlap is identified, and further combined with the interruption position in the communication behavior, the time overlap of each second evaluation unit and the interruption position is calculated to quantify the actual influence degree of spectrum conflict on communication interruption, and a risk weight is assigned based on the time overlap; then the target fluctuation rate of the corresponding second evaluation unit is extracted in the spectrum competition situation sub-sequence, and the target fluctuation rate is weighted calculated in combination with the aforementioned risk weight to obtain a risk weighted fluctuation reference value that can comprehensively reflect the frequency conflict intensity and communication interruption sensitivity. Finally, the reference value is taken as the spectrum usage baseline under the current target time window to realize the quantitative expression of the spectrum risk level. By introducing the time sequence correlation between communication interruption and spectrum conflict, the spectrum fluctuation rate and the service interruption risk are fused and evaluated to establish a spectrum usage baseline model with more service sensitivity. Compared with the traditional way of setting the baseline with statistical mean or fixed threshold, the real availability of spectrum resources under specific space-time conditions can be more accurately reflected, thereby providing more targeted and reliable judgment basis for subsequent spectrum priority setting and dynamic allocation. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a system architecture schematic diagram of an embodiment of a vehicle-mounted radio frequency band management method or a vehicle-mounted radio frequency band management system in the present application; Figure 2 is a flowchart of a vehicle-mounted radio frequency band management method in an embodiment of the present application; Figure 3This is a schematic structural diagram of a vehicle-mounted radio frequency band management system according to an embodiment of the present application; Figure 4 It is a structural diagram of an electronic device in an embodiment of the present application.

[0020] Explanation of the accompanying drawings: 301, acquisition module; 302, construction module; 303, determination module; 304, division module; 305, calculation module; 306, allocation module; 401, processor; 402, communication bus; 403, user interface; 404, network interface; 405, memory. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0022] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0023] Figure 1 An exemplary system architecture 100 is shown to which an embodiment of the vehicle-mounted radio frequency band management method or vehicle-mounted radio frequency band management system of the present application can be applied.

[0024] like Figure 1 As shown, the system architecture 100 may include multiple terminal devices 101, 102, 103, a network 104, and a server 105. Illustratively, the terminal device 101 may be a first vehicle-mounted communication device (e.g., a communication terminal on an emergency law enforcement vehicle), the terminal devices 102 and 103 may be second vehicle-mounted communication devices (e.g., communication terminals in public vehicles), and the server 105 is the core back-end processing unit that executes the spectrum management strategy.

[0025] The network 104 is a medium for providing a communication link between the terminal devices 101, 102, and 103 and the server 105, supporting multiple communication modes, including but not limited to a cellular network, V2X (Vehicle to Everything) direct communication, Wi-Fi, a private network communication link, and the like. The network 104 can also be used to upload perception data including communication behavior data, spectrum usage data, and vehicle location information. The terminal devices 101, 102, and 103 can be configured as devices supporting spectrum perception and communication behavior collection, having a communication module, a positioning module, a spectrum perception module, and the like, for collecting data such as the usage state of the current frequency band, channel interference, and communication interruption in real time, and uploading the data to the server 105 through the network 104. In addition, the system can also access people flow perception devices or platforms (such as cameras, thermal sensors, crowd flow analysis systems, etc.) in the region to obtain people flow density change characteristic data in the target region.

[0026] The server 105 is a central processing node for implementing a spectrum management strategy, which can obtain and process communication behavior data of the first vehicle-mounted communication device, first spectrum usage data, second spectrum usage data located in the communication region of the first device, and people flow density change characteristics in the target region. Based on the above multi-source heterogeneous data, the server 105 constructs a frequency band behavior portrait in the target region, divides a target time window, establishes a spectrum usage baseline, and calculates the spatio-temporal correlation degree between the first vehicle-mounted communication device and the second vehicle-mounted communication device, thereby dynamically setting a spectrum management priority and outputting a frequency band combination allocation strategy to ensure the communication stability and priority of the first vehicle-mounted communication device.

[0027] It should be noted that the server 105 can be a centralized computing platform or an edge computing node deployed at the edge of the communication, supporting fast response to communication strategy requirements locally. The terminal devices 101, 102, and 103 can be intelligent vehicle-mounted terminals with communication capabilities, and the server 105 can also be linked with a traffic control system and a spectrum supervision platform to realize spectrum resource optimization and scheduling across systems. It should be understood that Figure 1 The number of terminal devices, networks, and servers in the system architecture 1000 is only illustrative, and in actual deployment, the number can be flexibly expanded according to the communication coverage range and computing capability. In some cases, when the target data can be collected and processed locally, the system architecture can also not rely on a central network, but directly cooperate with a local edge node to complete the execution of the spectrum management strategy.

[0028] Figure 2 FIG. 1 is a flowchart of a vehicle-mounted radio frequency band management method according to an embodiment of the present application.

[0029] Referring to FIG. 1, Figure 2 A vehicle-mounted radio frequency band management method according to an embodiment of the present application is applied to a server, and the method comprises: S201, obtaining communication behavior data of a first vehicle-mounted communication device in a target area, first spectrum usage data, second spectrum usage data of a second vehicle-mounted communication device in a communication area of the first vehicle-mounted communication device, and a change feature of a people flow density in the target area in a preset time period, the first vehicle-mounted communication device being a vehicle-mounted communication device of an emergency law enforcement vehicle, and the second vehicle-mounted communication device being a vehicle-mounted communication device of all types of vehicles in the target area except the emergency law enforcement vehicle; Step S201 provides complete and accurate data basis for subsequent frequency band behavior portrait construction, spectrum risk assessment, and priority calculation, ensuring that the entire spectrum allocation process has high spatiotemporal resolution and service awareness capability.

[0030] In a specific implementation, the server first interfaces with the first vehicle-mounted communication device deployed in the target area, i.e., a communication terminal installed on an emergency law enforcement vehicle such as a fire truck, a police car, an ambulance, etc. This type of device is usually equipped with a communication module supporting LTE-V (Long Term Evolution for Vehicle), C-V2X (Cellular Vehicle-to-Everything), or a dedicated wireless frequency band, which can realize high-reliability and low-latency data communication. The first vehicle-mounted communication device records its communication behavior data in real time, including communication frequency, data packet quantity, transmission success rate, connection interruption event, average transmission delay, etc. These data are uploaded to the server through the vehicle-mounted system to reflect the communication status and service demand characteristics of the emergency vehicle in the target area. The target area is a geographical spatial range that currently needs to perform spectrum scheduling and management strategies, and is usually a specific area in the urban traffic network, such as a main road section, a crossroads, a high-density public activity area, or an emergency response range. The target area can be set with boundaries through geographic information system coordinates, or dynamically delimited by the urban traffic command platform.

[0031] Subsequently, the server obtains the first spectrum usage data through the spectrum sensing module in the first vehicle-mounted communication device, such as an integrated software-defined radio device. This module can scan the signal-to-noise ratio, bandwidth occupation, and interference intensity of each frequency point in the target frequency band in real time, and construct a signal-to-noise ratio time curve for subsequent calculation of spectrum stability and volatility.

[0032] To further understand the spectrum usage of other communication subjects in the environment, the server also needs to collect second spectrum usage data. The second vehicle-mounted communication device refers to the communication terminal equipped by all ordinary vehicles (including private cars, online car-hailing vehicles, buses, taxis, logistics transport vehicles, etc.) in the target area except for emergency vehicles. These terminals may communicate through cellular networks, vehicle-to-vehicle communication protocols (such as DSRC, C-V2X), or Wi-Fi. The server collects the communication frequency, load intensity, and device density of these devices in the target area by cooperating with road side units (RSUs), base stations, or edge computing nodes, and constructs the second spectrum usage data.

[0033] At the same time, the server also obtains the human flow density change feature data of the target area in a preset time period. The human flow density change feature data is collected by intelligent video collection devices, millimeter wave radars, infrared thermal imaging devices, or human flow perception devices based on Wi-Fi probes deployed in the target area. The preset time period refers to the time range for collecting and analyzing communication behavior data and environmental perception data, and is usually set to 1 hour, 2 hours, or a dynamically adjusted window length according to task requirements. The preset time period is used to cover typical traffic operation periods, such as the morning peak, evening peak, or major event response period, to ensure that the collected data is representative and timely. The setting of the time period can refer to the traffic flow statistical law or the historical human flow density change trend. The server can call a target recognition algorithm such as OpenPose or a heat map algorithm to generate a human flow density change sequence per unit area per unit time, reflecting the human flow mobility of the target area in different time periods. The human flow density feature directly affects the communication demand intensity of mobile terminals and is an important external factor for dynamic changes in spectrum resources.

[0034] Through the above operations, the server comprehensively covers the target area in space, throughout the preset analysis window in time, and covers high-priority communication devices, ordinary communication terminals, and human flow dynamic pressure sources in objects, forming a complete multi-source basic data system. This data system provides a solid data support for subsequent construction of frequency band behavior portraits, division of time windows, calculation of spectrum risk, and spatio-temporal correlation, ensuring that emergency vehicle communication has high availability and high-priority spectrum support capability in high-load and complex interference environments.

[0035] S202, constructing a frequency band behavior portrait of a radio frequency band in the target area based on the communication behavior data, the first spectrum usage data, and the second spectrum usage data; In step S202, the server performs comprehensive analysis on the radio frequency band in the target area based on the communication behavior data of the first vehicle-mounted communication device, the first spectrum usage data, and the second spectrum usage data, to construct a frequency band behavior portrait that can reflect the time-varying characteristics. The frequency band behavior portrait is the core data structure of the entire spectrum allocation strategy. The construction process not only needs to evaluate the availability and stability of the spectrum, but also needs to identify potential interference sources and disaster tolerance needs of communication services, so as to realize dynamic modeling of the spectrum environment. The following steps can be included: dividing the signal-to-noise ratio time curve in the first spectrum usage data into a plurality of equal-length evaluation units, combining the fluctuation rate of the signal-to-noise ratio in each evaluation unit according to the time sequence of the evaluation unit to obtain a spectrum stability sequence; in the spectrum stability sequence, determining the evaluation unit in which the fluctuation rate is greater than a preset fluctuation rate threshold as a first evaluation unit, and determining a target frequency band in which the first spectrum usage data and the second spectrum usage data exist frequency overlap in the first evaluation unit, combining the first spectrum usage data corresponding to the target frequency band and the second spectrum usage data corresponding to the target frequency band according to the time sequence of the first evaluation unit to obtain a spectrum competition situation sequence; connecting the interruption position, the interruption times, and the interruption recovery time length of the communication service in the communication behavior data under the target frequency band according to the time sequence to obtain a spectrum disaster tolerance demand sequence; combining the spectrum stability sequence, the spectrum competition situation sequence, and the spectrum disaster tolerance demand sequence according to the time sequence into the frequency band behavior portrait.

[0036] In the specific implementation process, the server first processes the signal-to-noise ratio time curve in the first spectrum usage data, and divides the signal-to-noise ratio time curve into a plurality of equal-length evaluation units. The signal-to-noise ratio is an important indicator reflecting the quality of the received signal. The higher the value, the clearer the signal and the lower the interference. The server extracts the average value and the fluctuation rate of the signal-to-noise ratio in each evaluation unit based on the set time resolution (such as one unit every 5 seconds). The fluctuation rate can be calculated by using methods such as standard deviation, range, or sliding window difference, to reflect the stability of the signal in that time period. By processing all the evaluation units, the server forms a spectrum stability sequence arranged according to time. The spectrum stability sequence can be used to judge the availability and interference fluctuation trend of any frequency band in a specific time window. For example, if the fluctuation rate of a plurality of consecutive evaluation units in a period of time is small, it indicates that the frequency band has high communication stability.

[0037] On the basis of the spectrum stability sequence, the server identifies all first evaluation units in which the volatility rate exceeds a preset volatility rate threshold. The preset volatility rate threshold can be determined according to historical data statistics or on-site deployment strategies, and the purpose is to screen out time segments that may have sudden interference or spectrum conflict. Within these first evaluation units, the server further performs frequency overlap analysis in combination with the second spectrum usage data. Frequency overlap refers to the fact that the first vehicle-mounted communication device and the second vehicle-mounted communication device simultaneously communicate in the same or adjacent frequency band, which may cause signal interference. The server identifies the frequency bands having a frequency overlap relationship by comparing the spectrum usage frequency and the bandwidth range, and marks them as a spectrum competition situation sequence, thereby reflecting the competition situation of the spectrum resources in the target area. For example, during the urban peak period, multiple vehicles communicating in the same frequency band will cause obvious spectrum competition situation.

[0038] In order to further analyze the influence of spectrum competition on communication services, the server identifies the corresponding communication interruption in the communication behavior data in the spectrum competition situation sequence, including the interruption position, the interruption times, and the interruption recovery time length. The interruption position refers to the specific time point at which the communication occurs in the time sequence. The interruption times count the number of continuous communication failures, and the interruption recovery time length represents the time experienced from the occurrence of the interruption to the recovery of the communication. The server extracts detailed communication interruption information by analyzing the connection state log in the communication protocol stack, the data packet retransmission situation, and the number of failed acknowledgement responses, and determines the causes thereof in combination with the competition situation. Then, a spectrum disaster recovery demand sequence is formed, which reflects the sensitivity and recovery ability of the communication service to spectrum interference. For example, if the frequency band interruption times are frequent and the recovery time is long, it indicates that the fault tolerance ability of the corresponding service is weak, and the resource allocation needs to be prioritized.

[0039] Finally, the server integrates the spectrum stability sequence, the spectrum competition situation sequence, and the spectrum disaster recovery demand sequence in chronological order to construct a frequency band behavior portrait. The frequency band behavior portrait not only describes the fluctuation characteristics and competition relationship of each frequency band in the target area, but also integrates the interruption recovery performance at the service level, so that the spectrum resource evaluation is no longer dependent on physical layer parameters, but has the ability to express the dynamic characteristics driven by the service. The formation of the frequency band behavior portrait enables the server to finely model and dynamically optimize the spectrum allocation strategy according to the time and space dimensions in the subsequent steps, ensuring that the first vehicle-mounted communication device obtains a frequency band support with stability, low conflict, and high service guarantee ability in a complex environment.

[0040] For example, at a peak intersection, the server detects that a frequency band has a large fluctuation in signal-to-noise ratio in multiple consecutive evaluation units, identifies that the surrounding ordinary vehicles are frequently using the frequency band, and records multiple communication interruption events and long recovery time in the frequency band. The server accordingly marks the frequency band as a high-risk frequency band, and assigns a high competition index and a high disaster tolerance demand value in the frequency band behavior portrait, providing a risk warning and intelligent adjustment basis for subsequent spectrum scheduling.

[0041] S203, determining a plurality of target time windows according to the human flow density change characteristics; In the implementation process of step S203, the server determines a plurality of target time windows for dynamic evaluation of spectrum resources according to the human flow density change characteristics collected in the early stage. The purpose of setting the target time window is to finely model the frequency band behavior in the time dimension, so as to dynamically reflect the change law of the spectrum environment under different human activity intensity, thereby improving the timeliness and adaptability of the spectrum resource scheduling strategy. As an important indicator of external driving of communication demand, human flow density can significantly affect the communication frequency, data volume and access behavior of vehicle-mounted communication equipment and mobile terminals in the region, so the timing change characteristics of human flow density must be fully considered.

[0042] In the specific implementation process, the server first models the timing change characteristics of human flow density in the analysis period in the target region. The human flow density data is collected by sensing devices deployed in the target region, such as crowd counting systems based on infrared thermal imaging, millimeter wave radar or video image recognition algorithms. These devices can output the number of people per unit area per unit time, forming a continuous human flow density time series. The server pre-processes the time series, including outlier rejection, moving average filtering and normalization processing, to eliminate the interference of device errors and instantaneous mutations on the results.

[0043] Next, the server divides the time period based on the inflection point characteristics and fluctuation trend of the human flow density change curve. The inflection point extraction uses a first-order derivative change analysis and extreme value detection algorithm to identify the time points of rapid rise or fall of human flow density as candidate division boundaries. In order to enhance the business relevance of window division, the server further calculates the human flow density change rate, i.e. the increase or decrease amplitude of human flow change per unit time, and sets a change rate threshold. When the change rate exceeds the threshold, it indicates that the crowd is significantly gathered or dispersed in the current time period, and the communication demand is expected to fluctuate sharply simultaneously, which needs to be divided into a target time window separately.

[0044] On the basis of the candidate boundaries, the server combines the absolute value level of the crowd density to perform window merging and fine adjustment. For example, in the late night period when the crowd density is low as a whole, one low-activity window can be merged. In the rush hour period when the crowd density fluctuates rapidly, multiple windows can be subdivided to improve the time resolution of the spectrum evaluation. Each target time window is finally marked with start and end time stamps and corresponds to the subsequent frequency band behavior sub-image, spectrum usage baseline, and spectrum competition index calculation process to form a logical index in the time dimension.

[0045] The multiple target time windows obtained by the above division can accurately reflect the key periods in which the communication demand in the target area may change significantly. In subsequent steps, the server will segment the frequency band behavior image based on these time windows, so that the spectrum modeling and allocation strategy in each time window are adaptive and targeted, significantly improving the resource guarantee efficiency of emergency communication equipment in a high-dynamic environment. For example, in a commercial street, the server identifies that the crowd density curve shows a rapid upward trend from 18:00 to 20:00 and fluctuates with multiple inflection points. Therefore, the period is divided into three target time windows to evaluate the spectrum competition situation and communication risk in different stages during the evening rush hour and achieve more fine frequency band resource regulation.

[0046] S204, divide the frequency band behavior image according to the multiple target time windows to obtain multiple frequency band behavior sub-images, and set a spectrum usage baseline for each frequency band behavior sub-image, one target time window corresponding to one frequency band behavior sub-image; in step S204, based on the multiple target time windows determined in step S203, the frequency band behavior image constructed is divided in the time dimension to obtain multiple frequency band behavior sub-images.

[0047] In the specific implementation process, the server first establishes a time index structure based on the time boundary information of the multiple target time windows determined in step S203. Each target time window is composed of a start time stamp and an end time stamp to define the time range covered by the window. The server traverses all the sequence data in the constructed frequency band behavior image, including the spectrum stability sequence, the spectrum competition situation sequence, and the spectrum disaster tolerance demand sequence. Each data item in the sequence is attached with a time stamp, and the server classifies these data items according to the target time window to which the time stamp belongs to form a data subset corresponding to the target time window.

[0048] Subsequently, the server combines the data subsets aggregated in each time window into a frequency band behavior sub-image. Each frequency band behavior sub-image contains a spectrum stability sub-sequence, a spectrum competition situation sub-sequence, and a spectrum disaster tolerance demand sub-sequence in the time period, maintaining the same data structure as the complete frequency band behavior image but limited to a specific time period. This division not only preserves the time sequence characteristics of the spectrum behavior, but also enables each sub-image to be independently analyzed for subsequent analysis, such as spectrum risk assessment, usage deviation calculation, and priority judgment. For example, if a frequency band behavior image covers the entire analysis period 0:00 to 24:00, the server divides it into six frequency band behavior sub-images according to the six target time windows identified in advance (e.g., early peak, flat peak, midday, post-lunch fluctuation, late peak, night). Each sub-image encapsulates the spectrum fluctuation, competition situation, and business interruption characteristics in the time period, providing independent basis for spectrum scheduling strategies in different time periods and significantly improving the time-varying adaptability of spectrum management.

[0049] To ensure the continuity and integrity of the frequency band behavior sub-image at the boundary, the server also processes data items that exist across the boundary during the division process. For example, when the time span of an evaluation unit spans two target time windows, the server can divide the evaluation unit into the two sub-images according to the proportion principle, or assign it to one of the sub-images according to the principal component timestamp attribution strategy (based on the middle time point of the evaluation unit) to ensure that no key data is missed.

[0050] After dividing the frequency band behavior image, a spectrum usage baseline is set for each frequency band behavior sub-image. Each frequency band behavior sub-image corresponds to a target time window, reflecting the usage characteristics, interference, and communication disaster tolerance requirements of the radio frequency band in the target area during the time period. By splitting the complete frequency band behavior image according to the time window, dynamic modeling of the spectrum state can be achieved, making the evaluation and configuration of spectrum resources more timely and business-sensitive. To further improve the accuracy of the spectrum scheduling strategy, the server needs to set a spectrum usage baseline for each frequency band behavior sub-image as a reference standard for spectrum availability and interference level in the time window. It can include the following steps: Iterate through the spectrum competition situation sub-sequence corresponding to each frequency band behavior sub-image, and determine the first evaluation unit as a second evaluation unit if there is a frequency overlap in the spectrum competition situation sub-sequence; Determine the time overlap degree of the second evaluation unit and the interruption position in the spectrum disaster tolerance demand sub-sequence corresponding to the frequency band behavior sub-image, and set the time overlap degree as the risk weight of each second evaluation unit; determining a target volatility corresponding to the timestamp of each second evaluation unit from the spectrum competition situation sub-sequence; calculating a risk-weighted volatility benchmark value of the target time window by weighting the target volatility according to the risk weight, and setting the risk-weighted volatility benchmark value as the benchmark value of the spectrum usage baseline.

[0051] In the process of setting the spectrum usage baseline, the server first traverses the spectrum competition situation sub-sequence in each frequency band behavior sub-image to identify all second evaluation units with frequency overlap. The spectrum competition situation sub-sequence is a set of evaluation units extracted from the frequency band behavior image, with volatility exceeding the threshold and frequency overlap existing at the same time, reflecting the frequency spectrum conflict hotspots in the time window. The evaluation unit is a time segment obtained by equally dividing the signal-to-noise ratio time curve, with a fixed time length. By comparing the frequency band information used by the first vehicle-mounted communication device and the second vehicle-mounted communication device in each evaluation unit, the server identifies the second evaluation units with frequency overlap, thereby determining the potential interference source. The purpose of this step is to accurately lock the key time segments of spectrum competition and provide a candidate unit set for subsequent risk analysis.

[0052] In this embodiment, in order to quantify the actual impact of spectrum volatility on communication interruption, the server further evaluates the time correlation between the second evaluation units with frequency overlap and historical communication interruption events after identifying the second evaluation units, i.e., calculates the time coincidence degree, and accordingly assigns a corresponding risk weight to each evaluation unit. Specifically, the server first extracts the occurrence time stamps of all communication interruption events from the communication behavior data, and obtains the center time point of each second evaluation unit as its timestamp, and then constructs a time coincidence degree model based on the Gaussian decay function: for any second evaluation unit i and any interruption event j, the time coincidence degree of any second evaluation unit i and any interruption event j is represented by the function γ i,j : where t i is the timestamp of the second evaluation unit i, t j is the timestamp of any interruption event j, and σ is a parameter controlling the decay rate. The server traverses all interruption events corresponding to each second evaluation unit, selects the maximum one as the final coincidence degree Γ i of the second evaluation unit, and directly takes it as the risk weight w i , i.e., w i = Γ i, for measuring the potential influence strength of the second evaluation unit on the communication interruption. In this way, the server not only establishes the time sequence causal relationship between the spectrum fluctuation and the communication interruption, but also provides dynamic, continuous and physically meaningful weight input for subsequent weighted fluctuation rate calculation. For example, when the timestamp of the second evaluation unit is 18:23:15, the timestamp of the nearest interruption event is 18:23:12, and σ=10s is set, the corresponding coincidence degree is γ=exp(-0.045)≈0.956, and then the risk weight is 0.956, indicating that the time segment is highly related to the communication interruption, and the weight influence should be increased in the spectrum use baseline setting.

[0053] After determining the risk weight, the server extracts the target fluctuation rate of each second evaluation unit from the spectrum competition situation sub-sequence. The target fluctuation rate refers to the fluctuation degree of the signal-to-noise ratio within the evaluation unit, usually represented by standard deviation or sliding window difference. The higher the fluctuation rate, the more unstable the frequency point is affected by external interference in that time period. After obtaining the target fluctuation rate of all second evaluation units, the server performs weighted calculation on the corresponding risk weight and target fluctuation rate to obtain the risk weighted fluctuation benchmark value of the current target time window. This benchmark value not only reflects the stability of the spectrum itself, but also integrates the actual influence of interference on communication interruption, and is a comprehensive expression of the risk strength of the spectrum.

[0054] Finally, the server sets the spectrum use baseline corresponding to the frequency band behavior sub-image based on the risk weighted fluctuation benchmark value. The spectrum use baseline can be used as a judgment standard to judge whether the current frequency band is in a normal state, and is used to evaluate the spectrum use deviation and develop spectrum allocation strategies in subsequent steps. For example, if the risk weighted fluctuation benchmark value in the time window is much higher than the historical average, it indicates that the spectrum environment in this time period is complex, and the reliability of emergency communication tasks in this frequency band is low. The system can accordingly preferentially avoid this frequency band or improve the redundancy configuration.

[0055] For example, during a large-scale event, the server divides 18:00-19:00 into a target time window, and identifies that multiple frequency overlapping second evaluation units highly coincide with the communication interruption event, and gives them a higher risk weight. Combined with the high fluctuation rate data in this time period, the server calculates the risk weighted fluctuation benchmark value as 0.82 (significantly higher than the normal value of 0.4), and accordingly sets the spectrum use baseline to be high, prompting the subsequent scheduling strategy to avoid using this frequency band or introducing alternative frequency band resources, in order to ensure the communication stability of the first vehicle-mounted communication device. This process realizes a spectrum baseline setting method centered on communication interruption sensitivity, which has better business orientation and dynamic adaptability compared to the traditional statistical mean method.

[0056] S205, calculate the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region based on the target time window and the spectrum use baseline, the target sub-region being divided by the target region according to a preset rule; On the basis of obtaining a plurality of target time windows and corresponding spectrum use baselines, the target region is further spatially divided to form a plurality of target sub-regions, and the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in each sub-region is calculated. The purpose of setting the spatio-temporal correlation degree is to depict the dynamic coupling relationship of the two types of communication subjects in spectrum resource use at different spatial positions, so as to identify potential interference risk areas and resource conflict hotspots, and provide quantitative basis for subsequent spectrum priority adjustment and interference avoidance strategies. The server models in both time and space dimensions by fusing spectrum use deviation behavior and communication load distribution characteristics, and realizes accurate perception of spectrum coordination conflict trend. It can include steps S2051-S2053: S2051, calculate the target spectrum use deviation degree of the first spectrum use data and the spectrum use baseline of each target time window; in the specific implementation process, the server obtains the risk weighted fluctuation reference value corresponding to the time window based on the spectrum use baseline set in the foregoing step S204, as the spectrum stability reference in the ideal state. Then, the server analyzes the actual fluctuation rate of each frequency point in the first spectrum use data, and calculates the difference with the baseline value. The difference can be measured by mean square error, standard deviation offset or relative offset percentage, etc., to form a numerical sequence representing the deviation degree. The server performs weighted average processing on the sequence to obtain the target spectrum use deviation degree of the target time window, which is used to reflect the change intensity of the spectrum state in the current period relative to the reference spectrum environment. For example, if the fluctuation rate of the first spectrum use data at a plurality of frequency points is significantly higher than the baseline value in the peak period, the target spectrum use deviation degree will be high, indicating that the spectrum use is abnormally fluctuating in this period, and the potential interference risk is larger.

[0057] S2052, for each target time window, construct a communication load distribution map of the second vehicle-mounted communication device based on the second spectrum use data; In constructing the communication load distribution map of the second vehicle-mounted communication device, the server first obtains the device communication activity data contained in the second spectrum use data, including communication timestamp, communication frequency band, initiator and receiver location information, etc. According to the spatial division rule of the target area, the server divides the area into several target sub-areas, and spatially attributes the communication events in each target time window. Specifically, the server determines the target sub-area to which each communication record belongs according to the geographic coordinates or base station access location of the communication device. Then, the server counts the number of communication requests per unit time in each sub-area and normalizes it to form a communication activity index with sub-area as the unit. The communication load values of each sub-area together form a two-dimensional matrix structure, i.e. the communication load distribution map, which describes the communication density characteristics of the second vehicle-mounted communication device in different regions and different time periods. For example, in a target time window in a commercial area, if the number of communication requests per unit time is much higher than that in other areas, the corresponding load value of this sub-area in the communication load distribution map will be significantly higher, indicating that this area is a high-density communication behavior area, which may have stronger competition pressure on spectrum resources.

[0058] S2053、Based on the communication load distribution map and the target spectrum use deviation, the spatio-temporal correlation degree between the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-area is calculated.

[0059] Further, the server further calculates the spatio-temporal correlation degree between the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-area based on the communication load distribution map and the target spectrum use deviation. The core purpose of this calculation process is to comprehensively consider the spectrum use fluctuation characteristics and communication behavior density, identify the potential coupling relationship between the two types of communication devices in the time and space dimensions, especially the synchronous use trend under the background of spectrum resource competition. It can include the following steps: in the target time window, determine the target sub-area in the communication load distribution map that overlaps with the first vehicle-mounted communication device, and obtain the number of communication requests per unit time of the second vehicle-mounted communication device in the target sub-area; In the target sub-area, the spectrum section corresponding to the deviation period that meets the preset change requirement simultaneously with the number of communication requests is determined as the spectrum synchronous section; Determine the number of occurrences of the spectrum synchronous section in each target sub-area and the duration of each occurrence, and calculate the product of the number of occurrences and the duration to obtain the spatio-temporal correlation degree between the first vehicle-mounted communication device and the second vehicle-mounted communication device in each target sub-area.

[0060] The server first identifies a target sub-region that overlaps with the communication region of the first vehicle-mounted communication device from the constructed communication load distribution map within the target time window. The communication region overlap refers to the spatial intersection between the communication activity track of the first vehicle-mounted communication device and the communication dense distribution range of the second vehicle-mounted communication device. The judgment basis can include device positioning information, signal coverage model, base station access record, etc. The server filters out the target sub-region that has the possibility of interaction in space by analyzing the actual communication path of the first vehicle-mounted communication device within the target time window and matching it with the boundaries of each sub-region in the communication load distribution map. Subsequently, the server extracts the number of communication requests of the second vehicle-mounted communication device within each target sub-region in a preset unit time (such as every 15 seconds) to form a time-ordered communication density sequence as the dynamic load indicator of the region for subsequent comparison and matching with the spectrum fluctuation data.

[0061] After obtaining the number of communication requests in the target sub-region, the server performs joint analysis of the target spectrum usage deviation and the number of communication requests in the time sequence in the region. The target spectrum usage deviation refers to the deviation index between the actual spectrum usage state of the first vehicle-mounted communication device within the time window and the spectrum usage baseline, which has been calculated in the preceding step. The server sets a group of preset change rules to identify the key "synchronous deviation period", that is, the spectrum usage deviation exceeds the threshold value at the same time, and the number of communication requests also exceeds the corresponding load threshold value in a unit time. The change rule can use a double-threshold triggering mechanism to find out the section where the spectrum fluctuation and the communication load significantly overlap in the time dimension through sliding window scanning. For all time segments that meet the above conditions at the same time, the server marks the corresponding spectrum section as a spectrum synchronization section, indicating that the usage behavior of the two types of communication devices in the same frequency band within this time period has a high consistency, and there is a potential interference risk.

[0062] After identifying the spectrum synchronization section, the server performs statistical analysis on each synchronization section in each target sub-region, extracts the number of occurrences within the target time window and the time length of each occurrence. The number of occurrences reflects the frequency of synchronization behavior in the region, while the duration length reflects the stability of synchronization conflict and the possible communication impact range. The product of the number of occurrences and the duration length of each target sub-region is calculated to obtain the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in each target sub-region, which is used to quantify the spatio-temporal coupling relationship between the first vehicle-mounted communication device and the second vehicle-mounted communication device in the use of spectrum resources.

[0063] By the above manner, the server establishes a space-time correlation degree modeling path with spectrum fluctuation-communication load-behavior synchronization as the core logic, effectively bridging the dynamic mapping relationship between the physical spectrum state and the upper-layer communication behavior. For example, in the target sub-region where the urban trunk road intersects with the business district, the server identifies that there are five significant spectrum synchronization segments between 18:00 and 18:30, each with a duration of more than 45 seconds, and the calculated synchronization intensity value is 0.89, which is much higher than the average value 0.41 of other regions. The result shows that the sub-region is a typical high-interference risk area in the time window, and the server can accordingly prioritize the first vehicle-mounted communication device in subsequent scheduling, such as frequency band switching, power boosting, or access priority adjustment, to ensure communication quality and service continuity.

[0064] In step S206, the server determines the spectrum management priority of the first vehicle-mounted communication device based on the space-time correlation degree and the frequency band behavior portrait, and allocates a frequency band combination for the first vehicle-mounted communication device.

[0065] After completing the construction of the spectrum behavior portrait in the target time window, the calculation of the spectrum usage deviation, the generation of the communication load distribution map, and the modeling of the space-time correlation degree in the preceding steps, the server enters the decision-making phase of spectrum resource management, i.e., step S206. Based on the key features in the calculated space-time correlation degree and the frequency band behavior portrait, the server determines the spectrum management priority of the first vehicle-mounted communication device in the current spectrum environment, and accordingly dynamically allocates the optimal frequency band combination to it to ensure the reliability and priority of its communication needs. Specifically, the server will evaluate the spectrum conflict intensity and the interruption recovery capability of the communication task in each target sub-region, quantify the priority coefficient, and thus determine the spectrum management priority of the first vehicle-mounted communication device; based on this priority, combined with the communication service features and frequency band resource distribution in the target region, the server calculates the frequency band demand parameters by weighting, and selects the frequency band combination with the smallest interference and the largest frequency interval from the candidate frequency band list, for allocation.

[0066] Determining the spectrum management priority of the first vehicle-mounted communication device based on the space-time correlation degree and the frequency band behavior portrait can include the following steps: multiplying the space-time correlation degree of the target sub-region by the cumulative synchronization duration of the spectrum synchronization segment in the target sub-region to obtain a spectrum competition index; Based on the spectrum disaster tolerance demand sequence in the frequency band behavior portrait, the interruption recovery duration of the communication task in the target sub-region is determined, the ratio of the spectrum competition index to the interruption recovery duration is calculated to obtain the priority coefficient of the first vehicle-mounted communication device in the target sub-region, and the spectrum management priority is determined based on the priority coefficient.

[0067] In the implementation process, the server first calls the spatiotemporal correlation data constructed within the target time window, which has integrated the spectrum use deviation and the communication load density, reflecting the synchronization use trend of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the spatial overlap area. On this basis, the server combines the statistical information of the spectrum synchronization section to obtain the cumulative synchronization duration of all synchronization sections in each target sub-region. The synchronization duration refers to the total time length of the spectrum synchronization section within the statistical period, representing the persistence of the potential conflict state. By multiplying the duration with the spatiotemporal correlation of the corresponding target sub-region, the server can calculate the spectrum competition index of the sub-region. The index is essentially a spectrum conflict intensity indicator, reflecting both the occurrence frequency of synchronization interference and the behavior coupling degree between interference subjects, and is used to quantify the risk level of spectrum resource availability.

[0068] Subsequently, the server extracts the spectrum disaster recovery demand sequence from the frequency band behavior portrait. The disaster recovery demand sequence is a time sequence generated by analyzing the time required for device recovery connection in historical communication behavior interruption events, representing the business recovery ability of the vehicle-mounted communication device in different frequency bands or time periods. The server locates the corresponding interruption recovery duration for the frequency band behavior in the current target sub-region. The longer the interruption recovery duration, the weaker the recovery ability of the communication device after spectrum interference or channel interruption, and the higher the dependence of the communication task on spectrum stability. The server calculates the ratio of the spectrum competition index as the numerator and the interruption recovery duration as the denominator to obtain the priority coefficient of the first vehicle-mounted communication device in the target sub-region. The larger the priority coefficient, the greater the spectrum competition pressure faced by the device in the current region, and the weaker the fault tolerance ability of the device itself, so it should be allocated a higher priority in spectrum resource scheduling.

[0069] The server finally sets the spectrum management priority for the first vehicle-mounted communication device in the target sub-region according to the size of the priority coefficient. The priority can be expressed in a hierarchical strategy (such as high, medium, and low) or a continuous numerical model (such as a floating point number in the interval 0-1), which is used to guide the selection strategy of the subsequent frequency band combination. In this way, the spectrum management decision not only reflects the objective resource competition situation, but also takes into account the business criticality and disaster recovery ability of the communication subject, achieving a dual consideration of "conflict intensity + business importance" and significantly improving the business sensitivity and scenario adaptability of spectrum resource scheduling.

[0070] For example, in a target sub-region of a traffic hub area, the server calculates a spatio-temporal correlation degree of 0.83, a cumulative synchronization duration of 180 seconds, and a spectrum competition index of 149.4. At the same time, the interruption and recovery duration of this region is reflected in the spectrum behavior image, which is 25 seconds. The server calculates a priority coefficient of 5.976 based on this. Since this coefficient is much higher than the average level, the server sets the spectrum management priority of this device in this region to "high", and in the subsequent spectrum allocation process, it preferentially allocates spectrum combinations with low interference risk and stable resources to ensure the continuity of its key communication services. Through the above implementation path, the system realizes the dynamic determination and precise control of spectrum priority, effectively supporting the high-reliability communication needs of vehicle-mounted communication devices in complex environments.

[0071] After determining the spectrum management priority of the first vehicle-mounted communication device, a spectrum combination is allocated to the first vehicle-mounted communication device. The goal is to reasonably select the optimal spectrum combination for the first vehicle-mounted communication device in a limited and competitive spectrum resource environment, according to the urgency of the communication task, the data transmission demand, and the interference avoidance principle, so as to guarantee the communication quality and service continuity. To achieve this goal, the server not only considers the characteristics of the communication behavior itself, such as data volume and business type, but also optimizes the spectrum avoidance and interval according to the spectrum occupation of the second vehicle-mounted communication device in the surrounding environment, so as to maximize the communication performance on the basis of minimizing interference. It can include the following steps: The server first obtains the communication behavior data of the first vehicle-mounted communication device in the target sub-region, which includes the number of data packets per unit time, the average transmission rate, and the type identification of various types of business tasks. The number of data packets and the transmission rate reflect the size of the communication load, and the business type determines the specific requirements of the communication on latency, bandwidth, or stability. The server performs weighted calculation on these communication behavior parameters and the spectrum management priority corresponding to the target sub-region to generate spectrum demand parameters for spectrum allocation. The weighting method can use empirical rules or machine learning models to set weight coefficients according to business types, such as voice communication sensitive to latency, video transmission sensitive to bandwidth, and control communication sensitive to stability. The spectrum management priority acts as a weight amplification factor, amplifying the spectrum demand of high-priority tasks, so as to obtain a larger spectrum width or a better spectrum location in resource scheduling. The final calculation result is a continuous numerical value representing the minimum available spectrum set width required by the first vehicle-mounted communication device in the current sub-region.

[0072] After obtaining the frequency band demand parameter, the server selects a set of available frequency bands from a preset candidate frequency band list, and sorts them in descending order according to the frequency interval. The frequency interval refers to the distance between the candidate frequency band and the currently known interference frequency band in the frequency spectrum space. The larger the interval, the less likely it is to be interfered. The server compares the candidate frequency band with the occupied frequency band of the second vehicle-mounted communication device in the target sub-region in turn, and identifies the candidate frequency band set with the farthest distance in the frequency spectrum. The comparison process is based on historical spectrum occupation map or real-time sensing results, combined with frequency band boundary information and frequency center point to calculate the interval distance. The server selects the frequency band with the largest interval from the occupied frequency band of the second vehicle-mounted communication device according to the interval priority strategy, and combines to form a continuous or discrete frequency band combination under the premise of meeting the bandwidth required by the frequency band demand parameter. The frequency band combination is the final spectrum resource allocated to the first vehicle-mounted communication device, which is used to support its communication task in the current target sub-region.

[0073] The advantage of this allocation method is that it considers both the bandwidth and latency requirements of the business side, and also takes into account the interference avoidance and resource utilization efficiency of the spectrum side, truly implementing a business-oriented dynamic spectrum resource scheduling strategy. For example, in the target sub-region of the urban viaduct section, the server identifies that the current business of the first vehicle-mounted communication device is high-definition video backhaul, with a large number of data packets and high transmission rate, and the communication behavior characteristic index is (2000 packets / second, 3.5 Mbps, service type: video). Combined with the spectrum management priority "high", the server calculates the frequency band demand parameter as 15MHz. After comparing the candidate frequency band list, the server finds that the frequency band combination with the largest interval from the occupied frequency band of the second vehicle-mounted communication device is [860MHz-875MHz], and the frequency width exactly meets the demand, so it allocates this frequency band combination to the first vehicle-mounted communication device, ensuring that it can still complete the key business communication stably in a high interference environment.

[0074] In the above manner, the server implements a frequency band combination dynamic allocation mechanism driven by spectrum priority, which not only effectively avoids high-risk interference areas, but also realizes differentiated service guarantee under the condition of limited spectrum resources, improving the spectrum utilization efficiency and communication service quality.

[0075] Please refer to Figure 3 A structure diagram of a vehicle-mounted radio frequency band management system provided for the embodiments of the present application, a vehicle-mounted radio frequency band management system 300 specifically includes: The acquisition module 301 is configured to acquire communication behavior data of a first vehicle-mounted communication device in a target area, first spectrum usage data, second spectrum usage data of a second vehicle-mounted communication device in a communication area of the first vehicle-mounted communication device, and a flow density change feature of the target area in a preset time period, the first vehicle-mounted communication device is a vehicle-mounted communication device of an emergency law enforcement vehicle, and the second vehicle-mounted communication device is a vehicle-mounted communication device of all types of vehicles in the target area except the emergency law enforcement vehicle. The construction module 302 is configured to construct a frequency band behavior image of a radio frequency band in the target area based on the communication behavior data, the first spectrum usage data, and the second spectrum usage data. The determination module 303 is configured to determine a plurality of target time windows according to the flow density change feature. The division module 304 is configured to divide the frequency band behavior image according to the plurality of target time windows to obtain a plurality of frequency band behavior sub-images, and set a spectrum usage baseline for each frequency band behavior sub-image, one target time window corresponds to one frequency band behavior sub-image. The calculation module 305 is configured to calculate a space-time correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in a target sub-area based on the target time window and the spectrum usage baseline, the target sub-area is divided from the target area according to a preset rule. The allocation module 306 is configured to determine a spectrum management priority of the first vehicle-mounted communication device based on the space-time correlation degree and the frequency band behavior image, and allocate a frequency band combination for the first vehicle-mounted communication device.

[0076] Optionally, the construction module 302 is specifically configured to: divide a signal-to-noise ratio time curve in the first spectrum usage data into a plurality of equal-length evaluation units, combine a fluctuation rate of the signal-to-noise ratio in each evaluation unit according to a time sequence of the evaluation unit to obtain a spectrum stability sequence; in the spectrum stability sequence, determine an evaluation unit with a fluctuation rate greater than a preset fluctuation rate threshold as a first evaluation unit, and determine a target frequency band in which the first spectrum usage data and the second spectrum usage data exist in frequency overlap in the first evaluation unit, combine the first spectrum usage data corresponding to the target frequency band and the second spectrum usage data corresponding to the target frequency band according to the time sequence of the first evaluation unit to obtain a spectrum competition situation sequence; connect an interruption position, an interruption times, and an interruption recovery time length of a communication service in the communication behavior data in the target frequency band according to a time sequence to obtain a spectrum disaster tolerance demand sequence; ​​​​​combining the spectrum stability sequence, the spectrum competition situation sequence and the spectrum disaster tolerance demand sequence in time sequence into the frequency band behavior image.

[0077] Optionally, the division module 304 is specifically used for: traversing each spectrum competition situation sub-sequence corresponding to the frequency band behavior sub-image, determining the first evaluation unit as a second evaluation unit if there is frequency overlap in the spectrum competition situation sub-sequence; determining the time coincidence degree of the second evaluation unit and the interruption position in the spectrum disaster tolerance demand sub-sequence corresponding to the frequency band behavior sub-image, and setting the time coincidence degree as the risk weight given to each second evaluation unit; determining the target volatility rate corresponding to the timestamp of each second evaluation unit from the spectrum competition situation sub-sequence; calculating the target volatility rate by weighting according to the risk weight, obtaining the risk weighted volatility benchmark value of the target time window, and setting the risk weighted volatility benchmark value as the benchmark value of the spectrum use baseline.

[0078] Optionally, the calculation module 305 is specifically used for: calculating the target spectrum use deviation of the first spectrum use data and the spectrum use baseline of each target time window; constructing a communication load distribution map of the second vehicle-mounted communication device based on the second spectrum use data for each target time window; calculating the space-time correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region based on the communication load distribution map and the target spectrum use deviation.

[0079] Optionally, the calculation module 305 is further specifically used for: determining the target sub-region in the communication load distribution map that overlaps with the first vehicle-mounted communication device in the target time window, obtaining the number of communication requests of the second vehicle-mounted communication device in a preset unit of time in the target sub-region; determining the spectrum synchronization section corresponding to the spectrum section in which the target spectrum use deviation and the number of communication requests simultaneously meet the preset change requirement as the spectrum synchronization section in the target sub-region; determining the number of occurrences of the spectrum synchronization section in each target sub-region and the duration of each occurrence, calculating the product of the number of occurrences and the duration to obtain the space-time correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in each target sub-region.

[0080] Optionally, the allocation module 306 is specifically used for: multiplying the spatiotemporal correlation degree of the target sub-region with a cumulative synchronization duration of the spectrum synchronization section in the target sub-region to obtain a spectrum competition index; determining an interruption recovery duration of a communication task in the target sub-region based on a spectrum disaster tolerance demand sequence in the frequency band behavior image, calculating a ratio of the spectrum competition index and the interruption recovery duration to obtain a priority coefficient of the first vehicle-mounted communication device in the target sub-region, and determining the spectrum management priority based on the priority coefficient.

[0081] Optionally, the allocation module 306 is further configured to: weighting and calculating the communication behavior data in the target sub-region and the spectrum management priority of the target sub-region to obtain a frequency band demand parameter of the target sub-region; sorting candidate frequency bands in a preset candidate frequency band list in descending order of frequency interval, sequentially comparing the candidate frequency bands with an occupied frequency band of the second vehicle-mounted communication device in the target sub-region, selecting a frequency band combination with the largest interval from the occupied frequency band of the second vehicle-mounted communication device and a quantity satisfying the frequency band demand parameter, and allocating the frequency band combination to the first vehicle-mounted communication device.

[0082] It should be noted that: the apparatus provided in the above embodiments is used to implement its functions, and the above division of functional modules is only used as an example for illustration. In actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0083] The embodiment further discloses an electronic device, which refers to Figure 4 The electronic device can include at least one processor 401, at least one communication bus 402, a user interface 403, a network interface 404, and at least one memory 405.

[0084] The communication bus 402 is used to realize the connection and communication between the components.

[0085] The user interface 403 can include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 can further include a standard wired interface and a wireless interface.

[0086] The network interface 404 can optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0087] The processor 401 can include one or more processing cores. The processor 401 connects various parts within the server through various interfaces and lines, performs various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Alternatively, the processor 401 can be implemented in at least one of a hardware form of digital signal processing, a field programmable gate array, and a programmable logic array. The processor 401 can integrate a combination of one or more of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes operating systems, user interfaces, and application programs; the GPU is responsible for rendering and drawing the content required to be displayed on the display screen; and the modem is used for processing wireless communication. It can be understood that the above-mentioned modem can also not be integrated into the processor 01, but can be realized by a separate chip.

[0088] The memory 405 can include a random access memory and can also include a read-only memory. Optionally, the memory 405 includes a non-transitory computer readable medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function, instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 405 can also be at least one storage device located away from the aforementioned processor 401. As shown, the memory 405 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an application program of a vehicle-mounted radio frequency band management method. Figure 4 As shown, the memory 405 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an application program of a vehicle-mounted radio frequency band management method.

[0089] In the electronic device shown in Figure 4 Figure 4 In the electronic device shown in, the user interface 403 is mainly used to provide an interface for user input and obtain user input data; and the processor 401 can be used to call an application program of a vehicle-mounted radio frequency band management method stored in the memory 405, and when executed by one or more processors 401, the electronic device executes the method of one or more of the above embodiments.

[0090] It should be noted that, for the method embodiments described above, the steps of various above-described methods can be performed in any suitable order, and the application should not be limited by the ordering of steps. Further, it should be noted that wherever possible one or more steps have been omitted or combined together for conciseness.

[0091] The above descriptions are only exemplary embodiments of the present disclosure, and cannot limit the scope of the present disclosure. Any equivalent changes and modifications made according to the teachings of the present disclosure shall still fall within the scope of the present disclosure. Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon considering the disclosure herein, with the scope of the present disclosure defined by the claims as follows. The scope of the present disclosure is not limited by the specific embodiments described herein.

Claims

1. A vehicle-mounted radio frequency band management method characterized by comprising: Applied in a server, the method comprises: Obtaining communication behavior data of a first vehicle-mounted communication device in a target area, first spectrum usage data, second spectrum usage data of a second vehicle-mounted communication device within the communication area of the first vehicle-mounted communication device, and flow density change characteristics of the target area within a preset time period, the first vehicle-mounted communication device being a vehicle-mounted communication device of an emergency law enforcement vehicle, and the second vehicle-mounted communication device being a vehicle-mounted communication device of all types of vehicles in the target area except the emergency law enforcement vehicle; Based on the communication behavior data, the first spectrum usage data and the second spectrum usage data, a frequency band behavior image of the radio frequency band in the target area is constructed; According to the flow density change characteristics, a plurality of target time windows are determined; According to a plurality of target time windows, the frequency band behavior image is divided to obtain a plurality of frequency band behavior sub-images, and a spectrum usage baseline is set for each frequency band behavior sub-image, one target time window corresponding to one frequency band behavior sub-image; Based on the target time window and the spectrum usage baseline, the spatio-temporal correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in a target sub-area is calculated, the target sub-area being divided according to a preset rule from the target area; Based on the spatio-temporal correlation degree and the frequency band behavior image, the spectrum management priority of the first vehicle-mounted communication device is determined, and a frequency band combination is allocated to the first vehicle-mounted communication device.

2. The method of claim 1, wherein, The construction of the frequency band behavior image of the radio frequency band in the target area based on the communication behavior data, the first spectrum usage data and the second spectrum usage data specifically comprises: The signal-to-noise ratio time curve in the first spectrum usage data is divided into a plurality of equal-length evaluation units, and the fluctuation rate of the signal-to-noise ratio in each evaluation unit is combined in the time sequence of the evaluation unit to obtain a spectrum stability sequence; In the spectrum stability sequence, the evaluation unit with a fluctuation rate greater than a preset fluctuation rate threshold is determined as a first evaluation unit, and a target frequency band with frequency overlap between the first spectrum usage data and the second spectrum usage data in the first evaluation unit is determined, and the first spectrum usage data corresponding to the target frequency band and the second spectrum usage data corresponding to the target frequency band are combined in the time sequence of the first evaluation unit to obtain a spectrum competition situation sequence; The interruption position, interruption times and interruption recovery time length of the communication service in the communication behavior data under the target frequency band are connected in time sequence to obtain a spectrum disaster tolerance demand sequence; The spectrum stability sequence, the spectrum competition situation sequence and the spectrum disaster tolerance demand sequence are combined in time sequence as the frequency band behavior image.

3. The method of claim 2, wherein, The spectrum usage baseline is set for each frequency band behavior sub-image, specifically comprising: Each spectrum competition situation sub-sequence corresponding to each frequency band behavior sub-image is traversed, and the first evaluation unit with frequency overlap in the spectrum competition situation sub-sequence is determined as a second evaluation unit; Determine the time coincidence degree of the interruption position in the spectrum disaster tolerance demand sub-sequence corresponding to the frequency band behavior sub-image of the second evaluation unit, and set the time coincidence degree as the risk weight given to each second evaluation unit; Determine the target volatility rate corresponding to the timestamp of each second evaluation unit from the spectrum competition situation sub-sequence; According to the risk weight, the target volatility rate is weighted and calculated to obtain the risk weighted volatility benchmark value of the target time window, and the risk weighted volatility benchmark value is set as the benchmark value of the spectrum use baseline.

4. The method of claim 1, wherein, The time-space correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region is calculated based on the target time window and the spectrum use baseline, specifically including: Calculate the target spectrum use deviation of the first spectrum use data and the spectrum use baseline of each target time window; For each target time window, a communication load distribution map of the second vehicle-mounted communication device is constructed based on the second spectrum use data; Based on the communication load distribution map and the target spectrum use deviation, the time-space correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region is calculated.

5. The method of claim 4, wherein, The time-space correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in the target sub-region is calculated based on the communication load distribution map and the target spectrum use deviation, specifically including: In the target time window, determine the target sub-region in the communication load distribution map that overlaps with the first vehicle-mounted communication device to obtain the number of communication requests of the second vehicle-mounted communication device in the target sub-region within a preset unit time; In the target sub-region, the spectrum segment corresponding to the deviation period that meets the preset change requirement simultaneously with the target spectrum use deviation and the number of communication requests is determined as the spectrum synchronization segment; Determine the number of occurrences of the spectrum synchronization segment in each target sub-region and the duration of each occurrence, and calculate the product of the number of occurrences and the duration to obtain the time-space correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in each target sub-region.

6. The method of claim 5, wherein, The spectrum management priority of the first vehicle-mounted communication device is determined based on the time-space correlation degree and the frequency band behavior image, specifically including: Multiply the time-space correlation degree of the target sub-region and the cumulative synchronization duration of the spectrum synchronization segment in the target sub-region to obtain a spectrum competition index; Determine the interruption recovery duration of the communication task in the target sub-region based on the spectrum disaster tolerance demand sequence in the frequency band behavior image, calculate the ratio of the spectrum competition index and the interruption recovery duration to obtain the priority coefficient of the first vehicle-mounted communication device in the target sub-region, and determine the spectrum management priority based on the priority coefficient.

7. The method of claim 1, wherein, The frequency band combination is allocated to the first vehicle-mounted communication device, specifically including: weighting the communication behavior data in the target sub-region and the spectrum management priority of the target sub-region to obtain a frequency band demand parameter of the target sub-region; sort candidate frequency bands in a preset candidate frequency band list in descending order of frequency interval, sequentially compare the candidate frequency bands with the occupied frequency bands of the second vehicle-mounted communication device in the target sub-region, select a frequency band combination with the largest interval from the occupied frequency bands of the second vehicle-mounted communication device and the number satisfying the frequency band demand parameter, and assign the frequency band combination to the first vehicle-mounted communication device.

8. An in-vehicle radio frequency band management system, characterized by, Comprise: an acquisition module configured to acquire communication behavior data of a first vehicle-mounted communication device in a target region, first spectrum usage data, second spectrum usage data of a second vehicle-mounted communication device in a communication region of the first vehicle-mounted communication device, and a flow density change feature of the target region in a preset time period, the first vehicle-mounted communication device being a vehicle-mounted communication device of an emergency law enforcement vehicle, and the second vehicle-mounted communication device being a vehicle-mounted communication device of all types of vehicles in the target region except the emergency law enforcement vehicle; a construction module configured to construct a frequency band behavior image of a radio frequency band in the target region based on the communication behavior data, the first spectrum usage data, and the second spectrum usage data; a determination module configured to determine a plurality of target time windows according to the flow density change feature; a division module configured to divide the frequency band behavior image according to the plurality of target time windows to obtain a plurality of frequency band behavior sub-images, and set a spectrum usage baseline for each frequency band behavior sub-image, one target time window corresponding to one frequency band behavior sub-image; a calculation module configured to calculate a space-time correlation degree of the first vehicle-mounted communication device and the second vehicle-mounted communication device in a target sub-region based on the target time window and the spectrum usage baseline, the target sub-region being divided from the target region according to a preset rule; an assignment module configured to determine a spectrum management priority of the first vehicle-mounted communication device based on the space-time correlation degree and the frequency band behavior image, and assign a frequency band combination to the first vehicle-mounted communication device.

9. An electronic device, comprising: Comprise: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is configured to store computer program code, the computer program code comprises computer instructions, and the one or more processors invoke the computer instructions to enable the electronic device to perform the method of any one of claims 1-7.

10. A computer-readable storage medium comprising instructions, characterized in that, When the instructions run on the electronic device, the electronic device is enabled to perform the method of any one of claims 1-7.

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