A novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interface

Abstract

This invention discloses a novel vehicle-to-everything (V2X) congestion simulation method for the 5G V2X Uu interface. It includes a hardware-in-the-loop (HIL) simulation test platform for the 5G V2X Uu interface. The platform architecture comprises a traffic simulator, data packet software, a receiving OBU, a transmitting OBU, and a 5G comprehensive test instrument. This invention overcomes the problem of HIL being limited by the number of terminals, making it difficult to simulate congestion scenarios. By limiting available network resources, the requirement for the number of terminals in HIL is reduced, while increasing network traffic load simulates an increase in the number of vehicles in the network. Adjustments to the traffic load are achieved by setting the data packet transmission period and data packet size. The required channel model is selected based on the traffic simulation scenario and vehicle time-location information to calculate fading, which is then added to the corresponding data packets. For V2N2V links, uplink and downlink fading are added to the data packets according to the different environments and locations of the transmitting and receiving vehicles.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and specifically to a novel method for simulating congestion in vehicle-to-everything (V2X) services using the 5G V2X Uu interface. Background Technology

[0002] As cellular systems evolve from 4G Long Term Evolution (LTE) to 5G, C-V2X has evolved from LTE-V2X to NR-V2X. NR-V2X is a V2X technology based on 5G NR. 5G NR is designed to reduce latency and improve the reliability and spectrum efficiency of cellular networks; therefore, its introduction can improve communication performance such as latency at the Uu interface. In traditional cellular networks, to reduce latency, critical V2X services related to vehicle safety are implemented through the PC5 interface, i.e., through direct or sidechain connections between V2V or V2I. Services based on the Uu interface are typically used for infotainment, comfort, or traffic management services. However, the high speeds and functionalities introduced by 5G NR can reduce latency, greatly increasing the possibility of supporting safety-related V2X services through the Uu interface, i.e., V2N, V2N2V, and N2V. On the other hand, vehicle-to-everything (V2X) is a typical scenario for 5G's ultra-reliable low-latency technology, which is related to vehicle safety and requires ensuring the necessary reliability and latency even under network congestion. Therefore, it is necessary to test, verify, and study the communication performance of the Uu interface, such as latency, in congested vehicle-to-everything (V2X) scenarios.

[0003] Currently, there are three main simulation testing methods for vehicle-to-everything (V2X) congestion scenarios: software simulation, field testing, and hardware-in-the-loop (HIL) simulation. Software simulation uses specialized traffic and network simulation software to create V2X models, simulating behaviors related to communication protocols, vehicle movement, and signal transmission. It boasts advantages such as powerful functionality, ease of operation, repeatability, and high flexibility, making it the most widely used method for congestion scenario simulation. However, the software tools used in this method often require significant computing resources, and the consumption of computing resources increases rapidly with the number of vehicles in the simulation scenario. Furthermore, software simulation is often overly idealistic, resulting in a low degree of fit to the actual transmission environment. This is especially true for complex simulation systems like V2X, which exhibit time-varying characteristics, rapid fading, and multiple propagation scenarios; pure software simulation results deviate significantly from real-world scenarios. Unlike software simulation, field testing is conducted in a real-world environment, obviously offering higher accuracy in simulating the propagation environment. However, simulating congestion scenarios through field testing requires substantial human and material resources, as well as more time and resources, and the test results are highly susceptible to environmental influences, making effective reproduction difficult. Moreover, vehicle-to-everything (V2X) communication is characterized by complex scenarios, rapid changes in network topology, and diverse service types, making it difficult to effectively construct many test scenarios.

[0004] To reduce testing costs and shorten testing cycles while ensuring the accuracy and repeatability of test results, hardware-in-the-loop (HIL) simulation has emerged. HIL simulation is a hybrid simulation method that combines actual in-vehicle terminal equipment with a virtual network environment, allowing testing to be conducted indoors while maintaining simulation accuracy.

[0005] Vehicle-to-everything (V2X) communication congestion scenarios oriented towards the Uu interface are characterized by numerous terminal devices and complex propagation environments. Current research on V2X communication performance analysis using hardware-in-the-loop simulation has limitations in simulation testing of congestion scenarios.

[0006] Traditional hardware-in-the-loop (HIL) simulations for connected vehicles employ a large number of terminal devices to simulate congestion scenarios under conditions of idle resources. Because HIL simulations use actual connected vehicle terminal devices, the number of supported devices is limited. They cannot simulate scenarios with a large number of vehicles in real time, lack good scalability, and are difficult to use for simulating congestion.

[0007] Current hardware-in-the-loop (HIL) simulations of congested propagation environments often assume that each vehicle terminal signal experiences the same fading. However, in real-world propagation environments, the fading experienced by each vehicle differs due to its varying location and surrounding environment. Specifically, for V2N2V links, the different locations of the sending and receiving vehicles result in different fading experiences for data packets in the uplink and downlink.

[0008] One of the existing technical solutions (publication number: CN202010603223.2, titled: A Method for Rapidly Assessing the Congestion Status of a Vehicle-to-Everything (V2X) Network) is the closest prior art to this invention application. It discloses a method for rapidly assessing the congestion status of a V2X network. First, a physical resource block allocation model is established under a C-field V2 scenario X. Then, a theoretical relationship is established between the number of physical resource blocks within a macrocell and the transmission distance. This leads to the derivation of the probability that the required number of physical resource blocks is not less than the number of available physical resource blocks under different scenarios—that is, the theoretical analytical expression for the network congestion probability. The congestion status under certain network parameter configurations is then rapidly assessed using this theoretical expression. System simulation results verify the theoretical analytical expression for the network congestion probability and show that adding roadside units under a C-field V2 scenario X can significantly reduce the network congestion probability and improve the quality of network communication services. This invention mainly focuses on assessing the congestion status of a V2X network and proposes an assessment theoretical model, but it does not involve the simulation of V2X congestion scenarios or the testing and verification of key performance aspects such as latency under these scenarios.

[0009] "Modeling, Simulation and Analysis of Multiple Scenarios in Urban Traffic Mobility in the Internet of Vehicles" analyzes urban traffic vehicle mobility application scenarios in an onboard ad hoc network environment. In a collaborative simulation environment using the VanetMobiSim traffic simulator and the NS-2 network simulator, models were constructed for two typical application scenarios in urban intelligent transportation: intersections and two-way four-lane expressways. Simulations and analyses of the AODV and DSDV routing protocols were conducted in these two scenarios. The performance of different protocols in the same scenario was compared using four evaluation indicators: end-to-end latency, jitter rate, packet loss rate, and control packet overhead. Furthermore, for the AODV protocol, the impact of environmental factors such as vehicle speed, vehicle density, maximum number of connections, and number of packets sent per unit time on the protocol's communication performance was analyzed.

[0010] Difference: This article uses software simulation tools to simulate congestion scenarios in the Internet of Vehicles (IoV). Unlike the congestion scenario simulation in this invention, this article directly simulates performance indicators such as latency and packet loss rate under different congestion levels by increasing the vehicle traffic density in the network.

[0011] The paper, "A Congestion Control Strategy Based on Channel Load Prediction (C2SLP)," published in *Electronic Design Applications*, 2022, No. 3, addresses the channel congestion problem by designing and implementing a congestion control strategy based on channel load prediction (C2SLP) for vehicular networks. This strategy consists of three modules. First, it uses the detection function in a carrier sense multiple access protocol (CSMP) to obtain the channel idle / busy status for load assessment. Then, it substitutes the obtained results into an autoregressive integrated moving average (ARIMA) model to predict the channel load value at the next time step. Finally, it compares the predicted load value with a preset standard value and adjusts the transmission power using a power control algorithm based on the comparison results to proactively avoid channel congestion.

[0012] The difference lies in the fact that this method focuses more on congestion control than congestion simulation in the study of vehicle-to-everything (V2X) congestion scenarios. It predicts the load in the next moment by observing the current network load, thereby adjusting network parameters in advance to avoid network congestion.

[0013] In recent years, 5G NR has attracted widespread attention, and its introduction has increased the possibility of supporting low-latency and high-reliability applications in vehicle-to-everything (V2X) networks using the 5G Uu interface. V2X networks need to guarantee the required reliability and latency even under network congestion. Therefore, a testing method needs to be designed to test and study the transmission performance of the 5G Uu interface under traffic congestion. After comparing the advantages and disadvantages of field testing, simulation software testing, and hardware-in-the-loop (HIL) testing, this invention adopts HIL testing. However, due to limitations in the number of onboard units (OBUs), HIL testing has shortcomings in large-scale terminal device testing.

[0014] To address this issue, this invention presents a novel method for simulating congestion in vehicle-to-everything (V2X) services. This method enables the testing and verification of the transmission performance of the 5G Uu interface under congested scenarios, providing a reference for 5G V2X network configuration and system optimization. Summary of the Invention

[0015] To address the shortcomings of existing technologies, the purpose of this invention is to design a hardware-in-the-loop (HIPL) simulation test platform for 5G V2X Uu interfaces. This platform allows for testing of key communication performance indicators such as latency and packet loss rate for three communication modes: V2N, N2V, and V2N2V. Based on this platform, a novel method for simulating congestion scenarios is provided using limited vehicle terminal equipment, overcoming the difficulty of traditional HIPL simulation tests in simulating congestion scenarios.

[0016] To achieve the above objectives, the present invention adopts the following technical solution:

[0017] A novel vehicle-to-everything (V2X) congestion simulation method for the 5G V2X Uu interface includes a hardware-in-the-loop (HIT) simulation test platform for the 5G V2X Uu interface. The test platform architecture includes a traffic simulator, packet software, a receiving OBU, a transmitting OBU, a 5G comprehensive test instrument, and a clock synchronization unit. The packet software includes packet transmission configuration software, packet forwarding software, and packet reception statistics software.

[0018] The traffic simulator simulates multi-vehicle traffic scenarios and transmits vehicle time-location information to the corresponding data packet software.

[0019] The data packet transmission configuration software adds fading to the generated data packets based on the time-location information of the originating vehicle, and the originating OBU sends the data packets. The integrated test instrument receives the data packets, and the added fading is uplink fading.

[0020] The integrated tester adds fading to the received data packets based on the time-location information of the receiving vehicle and forwards the data packets to the receiving OBU. The added fading is downlink fading.

[0021] The receiving OBU receives data packets, and the data packet receiving software calculates key performance indicators, including but not limited to latency and packet loss rate.

[0022] Clock synchronization ensures that the OBU and the test instrument are synchronized to ensure accurate delay test results;

[0023] The congestion simulation process includes:

[0024] Step S1: First, configure the 5G network parameters;

[0025] Step S2, then limit the available uplink resources to increase traffic load;

[0026] Traffic load is configured by adjusting the packet sending period and packet size; the shorter the sending period and the larger the packet size, the more vehicles can be detected.

[0027] Step S3: The data packet sending configuration software selects the appropriate channel model and calculates the uplink fading based on the simulated road traffic scenario and the time-location information of the originating vehicle;

[0028] Step S4, then add the corresponding uplink fading to the data packet and send the data packet by the sending OBU;

[0029] Step S5: The forwarding software selects the appropriate channel model to calculate downlink fading based on the simulated road traffic scenario and the time-location information of the receiving vehicle;

[0030] Step S6, then add downlink fading and forward the data packets;

[0031] Step S7: Data packets are received and performance tests are performed.

[0032] Preferred,

[0033] The traffic simulator refers to software with traffic simulation capabilities. It constructs typical traffic scenarios and sets traffic flow within these scenarios to simulate multi-vehicle traffic scenarios.

[0034] Preferred,

[0035] The packet sending configuration software and packet forwarding software set the channel model according to the vehicle's time-location information and test requirements, and added fading to the data packets;

[0036] The data packet sending configuration software supports the generation of vehicle-to-everything (V2X) Uu interface data packets. The information set in the data packet sending configuration software includes, but is not limited to, data packet type, size, and sending period.

[0037] Preferred,

[0038] Both the receiving OBU and the transmitting OBU support sending and receiving data packets via the Uu interface. The transmitting OBU sends data packets at a set power according to the data packet sending configuration software's settings for data packet type, size, and sending period. The receiving OBU receives data packets forwarded by the integrated tester.

[0039] Preferred,

[0040] The 5G comprehensive tester is used to simulate a 5G network. The network parameters can be configured, including but not limited to the 5G networking mode, duplex mode, test frequency range, subcarrier spacing and number of available resource blocks, or it can be used as a 5G base station simulator to send and receive data packets at a set frequency and power.

[0041] Preferred,

[0042] The V2X mentioned refers to a V2N2V link;

[0043] In step S7, data packets are received and a latency model and a packet loss rate model are constructed; wherein,

[0044] The aforementioned time delay model is specifically as follows:

[0045] The overall latency of V2N2V is as follows:

[0046] D V2N2V =D V2N +D proc +D N2V +D que (Formula 1)

[0047] Among them, D V2N It is the latency from the originating vehicle to the 5G base station, D N2V It is the latency from the 5G base station to the receiving vehicle, D proc This refers to the network processing latency of data packets. Network processing latency is the time between when the base station receives the data packet from the vehicle in the uplink and when it sends the data packet in the downlink; D que The queuing delay is due to congestion.

[0048] The latency from the vehicle terminal data packet i to the 5G base station is calculated as follows:

[0049]

[0050] Among them, U i It is the size of the data packet. It is the link capacity from data packet i to the base station. B represents the transmission bandwidth; P is the signal-to-noise ratio of data packet i from the originating vehicle to the 5G base station. t，v It is the transmission power of the vehicle terminal. It is path loss. It represents the small-scale fading experienced by the uplink, and n0 is the noise power spectral density.

[0051] The network processing latency of the on-board terminal data packets is calculated as follows:

[0052]

[0053] Where, α i E represents the complexity of the service carried by data packet i, and E represents the network processing capacity.

[0054] The specific latency of data packet i from the 5G base station to the receiving vehicle is as follows:

[0055]

[0056] In V2N2V communication links, the latency caused by network congestion can be modeled using a queuing model.

[0057] Queuing latency in congested scenarios depends on traffic load and network service rate.

[0058] Traffic load is configured using the packet sending period T and packet size U; assuming each vehicle's sending period is T, the packet size is U, and the number of originating vehicles is N, traffic load can be modeled as the packet arrival rate, i.e., ... Service rate is μ m =(1-α)C m α is the resource utilization rate, C m It is the capacity of link m.

[0059] If m∈{V2N,N2V}, then the queuing delay is:

[0060]

[0061] Based on the above model, the metrics for measuring network congestion are as follows:

[0062] γ cong =max(λ / μ) V2N ,λ / μ N2V #(6)

[0063] γ cong A larger value indicates a greater degree of network congestion, with the highest congestion level being 1. V2N and μ N2V When any one of these values ​​reaches the value λ, it indicates that the current vehicle terminal has occupied all available resources;

[0064] Preferred,

[0065] The packet loss rate model is as follows:

[0066] The criteria for determining whether data packet i is lost are as follows:

[0067]

[0068] Loss = 0 and 1 represent successful data packet reception and reception failure, respectively.

[0069] D req It's about the latency requirements of connected vehicle services, P r It is the data packet receiving power, P thre It is the data packet reception power threshold;

[0070] If the delay of data packet i is higher than the required delay or the receiving power is lower than the threshold, the data packet is considered to have failed to be received; otherwise, the reception is successful.

[0071] The present invention also provides an electronic device, comprising: a memory, a processor, and a congestion simulation method program stored in the memory and executable on the processor, wherein the congestion simulation method program, when executed by the processor, implements the novel vehicle-to-everything (V2X) congestion simulation method for the 5G V2X Uu interface as described in any one of claims 1 to 8.

[0072] The present invention also provides a computer-readable storage medium storing a congestion simulation method program, which, when executed by a processor, implements the novel vehicle-to-everything (V2X) congestion simulation method for the 5G V2X Uu interface as described in any one of claims 1 to 8.

[0073] Beneficial effects:

[0074] This invention addresses the problem that traditional hardware-in-the-loop (HIL) simulations struggle to simulate congestion scenarios due to the limited number of supported terminal devices. It provides a novel method for simulating congestion scenarios in the vehicle-to-everything (V2N2V) network, enabling the simulation of congestion scenarios using a limited number of terminal devices. To address the low accuracy of HIL simulations in simulating the propagation environment of congestion scenarios, this invention selects the required channel model based on the traffic simulation scenario and vehicle time-location information, calculates fading, and then adds the fading to the corresponding data packets. Specifically, for V2N2V links, uplink and downlink fading are added to the data packets according to the different environments and locations of the transmitting and receiving vehicles.

[0075] This invention overcomes the problem of hardware-in-the-loop (HIL) simulation being limited by the number of terminals, making it difficult to simulate congestion scenarios. By restricting available network resources, the requirement for a large number of terminals in HIL simulation is reduced. Simultaneously, by increasing network traffic load, the increase in the number of vehicles in the network is simulated. Adjustment of traffic load is achieved by setting the data packet sending cycle and data packet size. Attached Figure Description

[0076] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the train emergency braking control method and system based on brainwaves will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0077] Figure 1 This is a schematic diagram of the hardware-in-the-loop simulation test platform architecture for the 5G V2X Uu interface of the present invention;

[0078] Figure 2 This is a schematic diagram of the congestion scenario simulation process of the present invention;

[0079] Figure 3 This is a schematic diagram of a V2N2V scenario provided in this embodiment;

[0080] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0081] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0082] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0083] To facilitate understanding of the embodiments of the present invention, two specific embodiments are provided below for further explanation, and these two embodiments do not constitute a limitation on the embodiments of the present invention.

[0084] This invention designs a hardware-in-the-loop (HIPL) simulation test platform for 5G V2X Uu interfaces. This platform allows for testing of key communication performance indicators such as latency and packet loss rate in three communication modes: V2N, N2V, and V2N2V. Based on this platform, a novel method for simulating congestion scenarios is provided using limited vehicle terminal equipment, overcoming the difficulty of traditional HIPL simulation tests in simulating congestion scenarios. Figure 1The diagram shows the architecture of a semi-physical simulation test platform for the 5G V2X Uu interface. The hardware primarily includes transceiver units (OBUs) and a comprehensive test instrument, while the software includes a traffic simulator and data packet transmission configuration, forwarding, and reception statistics software. Since the V2N2V link encompasses both V2N and N2V links, therefore... Figure 1 The discussion will mainly focus on V2N2V, and the simulation of V2N and N2V will not be elaborated upon.

[0085] exist Figure 1 In the hardware-in-the-loop simulation platform architecture for the 5G V2X Uu interface shown, the main functions of each module in the V2N2V mode are as follows:

[0086] 1) Traffic Simulator: A traffic simulator is software with traffic simulation capabilities. It constructs typical traffic scenarios and allows for setting traffic flow to simulate multi-vehicle traffic situations. The traffic simulator sends vehicle time-location information to the corresponding data packet software.

[0087] 2) Packet Data Software: The packet data software mainly includes packet transmission configuration, forwarding, and reception statistics software. The packet transmission configuration and forwarding software set the channel model based on the vehicle's time-location information and test requirements, adding fading to the packets. The packet transmission configuration software supports generating Uu interface packets for vehicle-to-everything (V2X) communication, and can also set information such as packet type, size, and transmission period. The packet reception statistics software analyzes the received packet information and calculates key performance indicators such as latency and packet loss rate.

[0088] 3) Transceiver OBU: The OBU supports sending and receiving data packets through the Uu interface. The transmitting OBU sends data packets at the set power according to the configuration software for data packet type, size, sending period, etc. The receiving OBU receives data packets forwarded by the integrated tester.

[0089] 4) 5G Comprehensive Tester: The comprehensive tester is used to simulate 5G networks. It can configure network parameters such as 5G networking mode, duplex mode, test frequency range, subcarrier spacing, and number of available resource blocks. It can also be used as a 5G base station simulator to send data packets at the set frequency and power, and can also receive data packets.

[0090] 5) Clock synchronization: Ensure that the clock of the OBU is synchronized with that of the integrated test instrument to ensure accurate delay test results.

[0091] In this architecture, the traffic simulator simulates multi-vehicle traffic scenarios, transmitting vehicle time-location information to the corresponding data packet software. The data packet transmission configuration software adds fading to the generated data packets based on the time-location information of the originating vehicles, and the originating OBU sends the data packets. The integrated test instrument receives the data packets; the added fading is uplink fading. The integrated test instrument adds fading to the received data packets based on the time-location information of the receiving vehicles, and forwards the data packets to the receiving OBU; the added fading is downlink fading. The receiving OBU receives the data packets, and the data packet receiving software calculates key performance indicators such as latency and packet loss rate.

[0092] Figure 1 The hardware-in-the-loop simulation test shown includes a receiving OBU and a transmitting OBU, totaling two OBUs. To simulate congestion scenarios, this invention provides a novel method for simulating congestion scenarios in the vehicle-to-everything (V2X) network, which can simulate congestion scenarios using a limited number of terminal devices. Specifically, on the one hand, it reduces the requirement for the number of terminals in the hardware-in-the-loop simulation by limiting available network resources; on the other hand, it simulates an increase in the number of vehicles in the network by increasing network traffic load.

[0093] like Figure 2 As shown, it is based on Figure 1 The congestion scenario simulation process of the hardware-in-the-loop simulation test platform includes the following steps:

[0094] Step S1: First, configure the 5G network parameters;

[0095] The comprehensive test instrument is used to configure network parameters including but not limited to 5G networking mode, duplex mode, test frequency range, subcarrier spacing, and number of available resource blocks;

[0096] Step S2, then limit the available uplink resources to increase traffic load;

[0097] Traffic load is configured by adjusting the packet sending period and packet size; the shorter the sending period and the larger the packet size, the more vehicles can be detected.

[0098] Step S3: The data packet sending configuration software selects the appropriate channel model and calculates the uplink fading based on the simulated road traffic scenario and the time-location information of the originating vehicle;

[0099] Step S4, then add the corresponding uplink fading to the data packet and send the data packet by the sending OBU;

[0100] Step S5: The forwarding software selects the appropriate channel model to calculate downlink fading based on the simulated road traffic scenario and the time-location information of the receiving vehicle;

[0101] Step S6, then add downlink fading and forward the data packets;

[0102] Step S7: Data packets are received and performance tests are performed.

[0103] against Figure 2 The congestion scenario simulation process described herein, through theoretical analysis, has led to the construction of the following latency and packet loss rate models.

[0104] by Figure 3 Taking the V2N2V scenario shown below as an example, the overall latency of V2N2V is as follows:

[0105] D V2N2V =D V2N +D proc +D N2V +D que #(1)

[0106] Among them, D V2N It is the latency from the originating vehicle to the 5G base station, D N2V It is the latency from the 5G base station to the receiving vehicle, D proc This refers to the network data packet processing delay, which is the time between when the base station receives the data packet from the vehicle in the uplink and when it sends the data packet in the downlink. (D) que The queuing delay is due to congestion.

[0107] The latency from the vehicle terminal data packet i to the 5G base station is calculated as follows:

[0108]

[0109] Among them, U i It is the size of the data packet. It is the link capacity from data packet i to the base station. B represents the transmission bandwidth. P is the signal-to-noise ratio of data packet i from the originating vehicle to the 5G base station. t，v It is the transmission power of the vehicle terminal. It is path loss. It represents the small-scale fading experienced by the uplink, and n0 is the noise power spectral density.

[0110] The network processing latency of the on-board terminal data packets is calculated as follows:

[0111]

[0112] Where, α i E represents the complexity of the service carried by data packet i, and E represents the network processing capacity.

[0113] The latency of data packet i from the 5G base station to the receiving vehicle and The calculation is similar, as follows:

[0114]

[0115] In V2N2V communication links, latency caused by network congestion can be modeled using a queuing model. Queuing latency in congested scenarios depends on traffic load and network service rate. Figure 2 In the congestion scenario simulation method shown, the traffic load can be configured by the packet sending period T and the packet size U. Assuming the sending period for each vehicle is T, the packet size is U, and the number of originating vehicles is N, the traffic load can be modeled as the packet arrival rate, i.e., ... Service rate is μ m =(1-α)C m ,

[0116] α is the resource utilization rate, C m If the capacity of link m is m∈{V2N, N2V}, then the queuing delay is:

[0117]

[0118] Based on the above model, the metrics for measuring network congestion are as follows:

[0119] γ cong =max(λ / μ) V2N ,λ / μ N2V )#(6)

[0120] γ cong A larger value indicates a greater degree of network congestion, with the highest congestion level being 1. V2N and μ N2V When any one of the values ​​reaches the λ value, it indicates that the current vehicle terminal has occupied all available resources.

[0121] The criteria for determining whether data packet i is lost are as follows:

[0122]

[0123] Loss = 0, 1 represents successful data packet reception and reception failure, respectively. req It's about the latency requirements of connected vehicle services, P r It is the data packet receiving power, P thre This is the data packet reception power threshold. When the delay of data packet i exceeds the required delay or the reception power falls below the threshold, the data packet is considered to have failed to be received; otherwise, the reception is successful.

[0124] The present invention provides a hardware-in-the-loop simulation test platform architecture for the Uu interface of 5G vehicle networking. This platform can be used to test key communication performance indicators such as latency and packet loss rate in three communication modes: V2N, N2V, and V2N2V.

[0125] This invention overcomes the problem of hardware-in-the-loop (HIL) simulation being limited by the number of terminals, making it difficult to simulate congestion scenarios. By restricting available network resources, the requirement for a large number of terminals in HIL simulation is reduced. Simultaneously, by increasing network traffic load, the increase in the number of vehicles in the network is simulated. Adjustment of traffic load is achieved by setting the data packet sending cycle and data packet size.

[0126] This invention proposes a method for simulating congested traffic propagation environments. Based on the traffic simulation scenario and vehicle time-location information, a required channel model is selected to calculate fading, and then the fading is added to the corresponding data packets. Specifically, for V2N2V links, uplink and downlink fading are added to the data packets according to the different environments and locations of the transmitting and receiving vehicles.

[0127] Based on the novel congestion scenario simulation method proposed above, a theoretical model of latency and packet loss rate in congestion scenarios is derived using a queuing model. Furthermore, an evaluation index for measuring network congestion status is proposed, providing a theoretical basis for setting simulation test parameters.

[0128] Furthermore, embodiments of this application also propose a computer-readable storage medium, which can be a non-volatile computer-readable storage medium storing the congestion simulation program of the present invention. When the congestion simulation program is executed by a processor, it implements the method of the present application as described above.

[0129] The various embodiments of the electronic devices and computer-readable storage media of this application can be referred to the various embodiments of the congestion simulation method of this application, which will not be repeated here.

[0130] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0131] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0132] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause an electronic device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0133] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interfaces, characterized in that, This includes a semi-physical simulation test platform for the 5G V2XUu interface. The test platform architecture includes a traffic simulator, data packet software, a receiving OBU, a transmitting OBU, a 5G comprehensive test instrument, and a clock synchronization. The data packet software includes data packet transmission configuration software, data packet forwarding software, and data packet reception statistics software. The traffic simulator simulates multi-vehicle traffic scenarios and transmits vehicle time-location information to the corresponding data packet software. The data packet transmission configuration software adds fading to the generated data packets based on the time-location information of the originating vehicle, and the originating OBU sends the data packets. The integrated test instrument receives the data packets, and the added fading is uplink fading. The integrated tester adds fading to the received data packets based on the time-location information of the receiving vehicle and forwards the data packets to the receiving OBU. The added fading is downlink fading. The receiving OBU receives data packets, and the data packet receiving software calculates key performance indicators, including but not limited to latency and packet loss rate. Clock synchronization ensures that the OBU and the test instrument are synchronized to ensure accurate delay test results; The congestion simulation process includes: Step S1: First, configure the 5G network parameters; Step S2, then limit the available uplink resources to increase traffic load; Traffic load is configured by adjusting the packet sending period and packet size; the shorter the sending period and the larger the packet size, the more vehicles can be detected. Step S3: The data packet sending configuration software selects the appropriate channel model and calculates the uplink fading based on the simulated road traffic scenario and the time-location information of the originating vehicle; Step S4, then add the corresponding uplink fading to the data packet and send the data packet by the sending OBU; Step S5: The forwarding software selects the appropriate channel model to calculate downlink fading based on the simulated road traffic scenario and the time-location information of the receiving vehicle; Step S6, then add downlink fading and forward the data packets; Step S7: Data packets are received and performance tests are performed.

2. The novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interface according to claim 1, characterized in that, The traffic simulator refers to software with traffic simulation capabilities. It constructs typical traffic scenarios and sets traffic flow within these scenarios to simulate multi-vehicle traffic scenarios.

3. A novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interfaces according to claim 1, characterized in that, The packet sending configuration software and packet forwarding software set the channel model according to the vehicle's time-location information and test requirements, and added fading to the data packets; The data packet sending configuration software supports the generation of vehicle-to-everything (V2X) Uu interface data packets. The information set in the data packet sending configuration software includes, but is not limited to, data packet type, size, and sending period.

4. A novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interfaces according to claim 1, characterized in that, Both the receiving OBU and the transmitting OBU support sending and receiving data packets via the Uu interface. The transmitting OBU sends data packets at a set power according to the data packet sending configuration software's settings for data packet type, size, and sending period. The receiving OBU receives data packets forwarded by the integrated tester.

5. A novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interfaces according to claim 1, characterized in that, The 5G comprehensive tester is used to simulate a 5G network. The network parameters can be configured, including but not limited to the 5G networking mode, duplex mode, test frequency range, subcarrier spacing and number of available resource blocks, or it can be used as a 5G base station simulator to send and receive data packets at a set frequency and power.

6. A novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interfaces according to claim 1, characterized in that, The V2X mentioned refers to a V2N2V link; In step S7, data packets are received and a latency model and a packet loss rate model are constructed; wherein, The aforementioned time delay model is specifically as follows: The overall latency of V2N2V is as follows: D V2N2V =D V2N +D proc +D N2V +D que (1) Among them, D V2N It is the latency from the originating vehicle to the 5G base station, D N2V It is the latency from the 5G base station to the receiving vehicle, D proc This refers to the network processing latency of data packets. Network processing latency is the time between when the base station receives the data packet from the vehicle in the uplink and when it sends the data packet in the downlink; D que The queuing delay is due to congestion; The latency from the vehicle terminal data packet i to the 5G base station is calculated as follows: Among them, U i It is the size of the data packet. It is the link capacity from data packet i to the base station. B represents the transmission bandwidth; P is the signal-to-noise ratio of data packet i from the originating vehicle to the 5G base station. t，v It is the transmission power of the vehicle terminal. It is path loss. It represents the small-scale fading experienced by the uplink, and n0 is the noise power spectral density. The network processing latency of the on-board terminal data packets is calculated as follows: Where, α i E represents the complexity of the service carried by data packet i, and E represents the network processing capacity. The specific latency of data packet i from the 5G base station to the receiving vehicle is as follows: In V2N2V communication links, the latency caused by network congestion is modeled according to the queuing model; Queuing latency in congested scenarios depends on traffic load and network service rate; Traffic load is configured using the packet sending period T and packet size Ui; assuming the sending period for each vehicle is T, the packet size is Ui, and the number of originating vehicles is N, the traffic load is modeled as the packet arrival rate, i.e., Service rate is μ m =(1-α)C m α is the resource utilization rate, C m If the capacity of link m is m∈{V2N, N2V}, then the queuing delay is: Based on the above model, the metrics for measuring network congestion are as follows: γ cong A larger value indicates a greater degree of network congestion, with the highest congestion level being 1. V2N and μ N2V When any one of the values ​​reaches the λ value, it indicates that the current vehicle terminal has occupied all available resources.

7. A novel vehicle-to-everything (V2X) congestion simulation method for 5G V2X Uu interfaces according to claim 6, characterized in that, The packet loss rate model is as follows: The criteria for determining whether data packet i is lost are as follows: Loss = 0 and 1 represent successful data packet reception and reception failure, respectively. D req It's about the latency requirements of connected vehicle services, P r It is the data packet receiving power, P thre It is the data packet reception power threshold; If the delay of data packet i is higher than the required delay or the receiving power is lower than the threshold, the data packet is considered to have failed to be received; otherwise, the reception is successful.

8. An electronic device, characterized in that, include: The present invention includes a memory, a processor, and a congestion simulation method program stored in the memory and executable on the processor, wherein the congestion simulation method program, when executed by the processor, implements the novel vehicle-to-everything (V2X) congestion simulation method for a 5G V2X Uu interface as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a congestion simulation method program, which, when executed by a processor, implements the novel vehicle-to-everything (V2X) congestion simulation method for the 5G V2X Uu interface as described in any one of claims 1 to 7.

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