Methods, devices, electronic equipment, and storage media for measuring the performance of vehicle-to-everything (V2X) systems

Abstract

This application provides a method, apparatus, electronic device, and storage medium for measuring the performance of a vehicle-to-everything (V2X) system. The method includes: determining simulation parameters; performing simulation based on the simulation parameters using a pre-constructed bit error rate (BER) performance model to obtain simulation results; wherein the BER performance model is constructed based on the communication channel of the V2X system; and measuring the performance of the V2X system based on the simulation results. The closed-form formula in the BER performance model is used as an upper bound for the BER, thus providing a reference for the BER performance of the V2X system.

Description

Technical Field

[0001] This application relates to the field of bit error rate performance technology for non-orthogonal multiple access systems, and in particular to a method, apparatus, electronic device, and storage medium for measuring the performance of a vehicle networking system. Background Technology

[0002] Existing research on pairwise error probability (PEP) in non-orthogonal multiple access (NOMA) systems mostly assumes the absence of residual hardware loss (RHI) or the availability of perfect channel state information at the receiver. However, these assumptions are difficult to achieve in practical applications, especially in vehicle-to-everything (V2X) systems, where the rapid movement of vehicles makes it challenging to obtain real-time channel information. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide an optimization method, apparatus, electronic device and storage medium for a vehicle networking system that overcomes or at least partially solves the above problems.

[0004] According to a first aspect of this application, a method for measuring the performance of a vehicle networking system is provided, the method comprising:

[0005] Determine the simulation parameters;

[0006] Based on the simulation parameters, simulation is performed using a pre-constructed bit error rate performance model to obtain simulation results; wherein, the bit error rate performance model is constructed based on the communication channel of the vehicle-to-everything (V2X) system.

[0007] The performance of the vehicle networking system is measured based on the simulation results.

[0008] Optionally, the simulation using a pre-built bit error rate performance model includes:

[0009] The communication channel of the vehicle-to-everything (V2X) system is determined, and the interference signal of the communication channel is determined, wherein the communication channel of the V2X system is determined to be an α-μ fading channel;

[0010] Construct an interference signal model and a probability density model of the target vehicle under the communication channel;

[0011] Based on the interference signal model and the probability density model, the bit error rate performance model of the target vehicle is constructed.

[0012] Optionally, the simulation parameters include communication channel parameters, reference distance, distance between signal transmitting nodes and signal receiving nodes, and power allocation factor.

[0013] Optionally, the interference signal includes: interference signal with non-ideal serial interference removal, interference signal with hardware residual loss, and interference signal with incomplete channel estimation conditions.

[0014] Optionally, the method for constructing the interference signal model of the target vehicle includes:

[0015] Acquire superimposed signals transmitted from the same transmitting node to multiple vehicles;

[0016] The interference signal model is constructed based on the superimposed signal;

[0017] The expression for the superimposed signal is:

[0018]

[0019] w l Let P be the power allocation factor for the l-th vehicle in the vehicle-to-everything (V2X) system, and let P be the transmit power of the base station's transmitting node.

[0020] The expression for the interference signal model is:

[0021]

[0022] in, The signals required by vehicle users, i.e., the signals that the signal receiving nodes need to receive. The noise interference signal caused by the removal of non-ideal serial interference, (h l +e l )η l This is noise interference signal caused by residual hardware wear and tear. For noise interference signals caused by incomplete channel estimation conditions, h l For communication channel condition estimation factors, θ l To express the summation, where This indicates the residual signal caused by the removal of interference signals due to non-ideal serial interference, n. l For BS→V l Gaussian white noise in the link, BS is the signal transmitting node, V l For vehicles in the vehicle-to-everything (V2X) system, obey in Let e ​​be the variance of the Gaussian white noise received by the l-th vehicle; l For channel estimation error, obey It is a function of the signal-to-noise ratio, i.e. in G represents large-scale fading. t and Let λ represent the gain of the signal transmitting node and the signal receiving node of the l-th vehicle, respectively, and let d0 represent the reference distance. lThis represents the distance between vehicle BS and vehicle l, where 'a' represents the path loss exponent, and δ > 0 depends on the ratio of pilot energy to data energy. η represents the average signal-to-noise ratio on the communication channel link from the signal transmitting node to the vehicle; l It is the total level of residual hardware loss between the signal transmitting node and the l-th vehicle, which follows the... in k represents the total residual hardware loss level in the vehicle-to-everything (V2X) system. S,t This indicates the severity of residual hardware degradation at the launch node. This indicates the severity of residual hardware degradation at the receiving node of vehicle l.

[0023] Optionally, the method for constructing the probability density model includes:

[0024] The initial probability density model for the target vehicle is expressed as follows:

[0025]

[0026] The probability density function and cumulative distribution function of the communication channel are coupled into the initial probability density model to obtain the probability density model;

[0027] The probability density function of the communication channel is:

[0028]

[0029] The cumulative distribution function of the communication channel is:

[0030]

[0031] The coupled probability density model is as follows:

[0032]

[0033] Where α > 0 represents the nonlinear power exponent, and μ > 0 represents the number of multipath clusters. Represents the α-th root of the communication channel envelope. Let X represent the unsorted |h l |,Γ(.) represents the gamma function.

[0034] Optionally, constructing the bit error rate performance model of the target vehicle based on the interference signal model and the probability density model includes:

[0035] Construct an initial bit error rate performance model;

[0036] By coupling the interference model and the probability density model to the initial bit error rate performance model, the expression for the bit error rate performance model is obtained as follows:

[0037]

[0038] in, τ μ =t-t1-t2Lt μ-1 t = L - l + k τ μ ,t, a t ,b t ,c t ,d t ,ψ l These are all parameters defined to simplify the representation.

[0039] According to another aspect of this application, an apparatus for constructing a bit error rate performance model is provided, comprising:

[0040] The determining module is adapted to determine the communication channel of the vehicle networking system;

[0041] The first construction module is suitable for constructing the interference signal model and probability density model of the target vehicle under the communication channel.

[0042] The second construction module is adapted to construct a bit error rate performance model of the target vehicle based on the interference signal model and the probability density model.

[0043] According to another aspect of this application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method as described above.

[0044] According to another aspect of this application, a non-transitory computer-readable storage medium is provided, the non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the above-described method.

[0045] As can be seen from the above, the bit error rate performance model construction method provided in this application is executed in a non-orthogonal multiple access vehicle network system. It involves determining the communication channel of the vehicle network system; constructing an interference signal model and a probability density model of the target vehicle under that communication channel; and constructing a bit error rate performance model of the target vehicle based on the interference signal model and the probability density model. The closed-form formula in the bit error rate performance model is used as an upper bound for the bit error rate, thus providing a reference for the bit error rate performance in the vehicle network system.

[0046] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This application provides an optimization method for a vehicle networking system according to one embodiment.

[0049] Figure 2 This is a schematic diagram illustrating a simulation method using a pre-built bit error rate performance model, according to one embodiment of this application.

[0050] Figure 3 This is a schematic diagram of a vehicle networking system according to an embodiment of this application;

[0051] Figure 4 This is a schematic diagram illustrating the variation of PEP for three users with Ps under an ideal scenario in one embodiment of this application;

[0052] Figure 5 This is a schematic diagram illustrating the variation of PEP for three users with Ps under a non-ideal scenario according to an embodiment of this application.

[0053] Figure 6 This is a schematic diagram illustrating the effect of channel parameters on the system PEP as a function of Ps under ideal conditions, according to one embodiment of this application.

[0054] Figure 7 This is a schematic diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0056] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word covers the element or object listed following the word and its equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect.

[0057] Currently, there is no research on the bit error rate performance of non-orthogonal multiple access (NOMA) systems under complex vehicular network environments and non-ideal factors, yet this research is crucial for the reliability analysis of vehicular network systems. Therefore, studying the bit error rate performance of NOMA systems under non-ideal conditions has become a technical problem that urgently needs to be solved by those skilled in the art.

[0058] The combination of NOMA and V2X technologies has been extensively studied. Among related technologies, based on NOMA-V2X systems, two schemes have been proposed: full-duplex intermediate cooperative NOMA and half-duplex intermediate cooperative NOMA. The optimal power allocation scheme was investigated to maximize the minimum achievable transmission rate for all users. In another related technology, a model combining full-duplex cooperative NOMA and distributed V2X systems was proposed, and the system capacity was calculated, showing that the system capacity increases with the number of communication devices. Finally, a novel power allocation scheme was proposed, improving the throughput of the downlink NOMA-V2X system.

[0059] However, the common thread among the above is the assumption of ideal transceiver RF hardware and ideal channel state information. In real communication systems, however, residual hardware loss (RHI) and incomplete channel estimation conditions (ipCSI) have a significant impact on the system. Related techniques have investigated the impact of RHI on the bit error rate performance of non-cooperative NOMA systems, deriving a closed-form expression for the pairwise error probability. Among these techniques, a D2D-based V2X system is proposed, considering ipCSI, deriving a closed-form expression for the system's total ergodic capacity, and solving the problem of maximizing the system's total ergodic capacity while ensuring the lowest signal-to-interference ratio and outage probability. To the authors' knowledge, there is still a lack of literature considering the joint impact of RHI and ipCSI on NOMA system performance. Related techniques have studied the joint impact of ipCSI and RHI on the outage probability, ergodicity, and rate of cooperative NOMA systems, but the joint impact of ipCSI and RHI on the PEP of NOMA-V2X systems has not yet been investigated.

[0060] To address the aforementioned issues, this application provides a method, system, electronic device, and storage medium for constructing a bit error rate performance model for vehicle received signals. This model considers the combined impact of residual hardware loss (RHI), actual incomplete channel estimation condition (ipCSI), and non-ideal serial interference cancellation (ipSIC) on the pairwise error probability (PEP) performance of non-orthogonal multiple access (NMO) vehicular networks, i.e., the combined impact on the bit error rate performance of NMO users.

[0061] To facilitate understanding, the following detailed explanation of the method for constructing the bit error rate performance model of the vehicle's received signal, in conjunction with the accompanying drawings, is provided.

[0062] Please see Figure 1 Here is a flowchart of an optimization method for a vehicle networking system provided in this application, the method comprising:

[0063] S100, Determine simulation parameters;

[0064] S200, Based on the simulation parameters, simulation is performed using a pre-built bit error rate performance model to obtain simulation results; wherein, the bit error rate performance model is constructed based on the communication channel of the vehicle-to-everything (V2X) system;

[0065] S300, the performance of the vehicle networking system is measured based on the simulation results.

[0066] See Figure 2 A flowchart for simulating the pre-built bit error rate performance model provided in this application, including:

[0067] S201, Determine the communication channel of the vehicle network system;

[0068] S202, Construct the interference signal model and probability density model of the target vehicle under this communication channel;

[0069] S203, Based on the interference signal model and probability density model, construct the bit error rate performance model of the target vehicle.

[0070] In step S201, this application considers the complex α-μ fading channel as the communication channel to simulate the rapid changes in the communication channel in the vehicle-to-everything (V2X) system, which is closer to the changes in the communication channel caused by the high speed of vehicle movement in the V2X system, thus better matching the commonly used NOMA-V2X system in the V2X system.

[0071] Based on the α-μ fading channel, considering the combined impact of interference signals generated by non-ideal serial interference cancellation (ipSIC), hardware residual loss (RHI), and incomplete channel estimation conditions (ipCSI) on the bit error rate performance of the NOMA-V2X system, in one optional implementation, superimposed signals transmitted from the same transmitting node to multiple target vehicles are obtained; the required transmission nodes include: one signal transmitting node and L destination nodes, i.e., signal receiving nodes.

[0072] The signal transmitting node transmits superimposed signals from L target vehicle users. Where w l Let P be the power allocation factor for vehicle l, and P be the transmit power of the base station's signal transmitting node. The signal received by the vehicle user includes not only the signal it needs, but also interference caused by ipSIC, RHI, ipCSI, and noise. Its specific expression can be represented by formula (I):

[0073]

[0074] in, The signals required by vehicle users, i.e., the signals that the signal receiving nodes need to receive. The noise interference signal caused by the removal of non-ideal serial interference, (h l +e l )η l This is noise interference signal caused by residual hardware wear and tear. For noise interference signals caused by incomplete channel estimation conditions, h l For communication channel condition estimation factors, θ l To express the summation, where This indicates the residual signal due to imperfect serial interference cancellation, n l For BS→V l The link has Gaussian white noise, which obeys... in Let e ​​be the variance of the Gaussian white noise received by the l-th vehicle; l For channel estimation error, obey It is a function of the signal-to-noise ratio, i.e. in G represents large-scale fading. t and Let λ represent the gain of the signal transmitting node and the signal receiving node of the l-th vehicle, respectively, and let d0 represent the reference distance. l This represents the distance between BS and the l-th vehicle, 'a' represents the path loss exponent, and δ > 0 depends on the ratio of pilot energy to data energy. η represents the average signal-to-noise ratio on the communication channel link from BS to the l-th vehicle; l It is the total level of residual hardware loss between BS and vehicle l, which follows in k represents the total residual hardware loss level in the vehicle-to-everything (V2X) system. S,t This indicates the severity of residual hardware degradation at the signal transmitting node. This indicates the severity of residual hardware degradation at the signal receiving node of vehicle l.

[0075] In step S202, an interference signal model and probability density model of the target vehicle under this communication channel are constructed; the pairwise error probability (PEP) is defined as the probability that signal x is mistransmitted as... If the probability is given, then the conditional PEP of vehicle l in the vehicle-to-everything (V2X) system can be expressed as formula (II):

[0076] Pr represents the probability. By substituting formula (Ⅰ) into formula (Ⅱ), we obtain the new PEP formula (Ⅲ):

[0077] in,

[0078] It follows a mean of 0 and a variance of .

[0079] The standard normal distribution The random variable Λ follows a pattern with mean 0 and variance σ. 2 The Gaussian distribution, i.e., Λ~N(m,σ) 2 When ), the probability that variable Λ≤λ is

[0080] Where Q(x) is the Gaussian Q-function, and its exact expression is: Combining this with the properties of the Gaussian Q-function, Q(-a) = 1 - Q(a), equation (III) simplifies to equation (IV), yielding the initial bit error rate performance model:

[0081] in

[0082] Due to the complexity of the V2X environment, considering the communication channel |h l |A channel that follows α-μ fading can describe complex non-geometric environments and can be transformed into other common channels depending on the parameters α and μ. Let X represent the unordered |h l Its probability density model (PDF) is written as formula (V): The cumulative distribution model CDF can be written as formula (VI): Where α > 0 represents the nonlinear power exponent, and μ > 0 represents the number of multipath clusters. Let represent the α-th root of the channel envelope; it is worth noting that for a system where communication channel conditions are arranged in order of strength, the communication channel |h l The PDF of | should be considered as an ordered statistical measure. Therefore, the PDF of the l-th vehicle in the vehicle-to-everything (V2X) system is given by formula (Ⅶ):

[0083] Substituting formulas (V) and (VI) into formula (VII) yields formula (VIII):

[0084] in

[0085] Γ(.) represents the gamma function.

[0086] In step S203, in order to obtain the PEP expression for the l-th vehicle in the vehicle-to-everything (V2X) system without a communication channel, the communication channel |h is... l By averaging all possible values, and according to formulas (Ⅳ) and (Ⅷ), the bit error rate performance model can be calculated as formula (Ⅸ):

[0087]

[0088] in,

[0089] τ μ =t-t1-t2Lt μ-1 t = L - l + k

[0090] τ μ ,t,a t , b t ,c t ,d t ,ψ l These are all parameters defined to simplify the representation.

[0091] when and At that time, the bit error rate performance model can be simplified to formula (X).

[0092]

[0093] Formula (XI) is obtained through calculation:

[0094]

[0095] And formula (XII):

[0096]

[0097] Represents complex hypergeometric functions.

[0098] Thus, a closed-form expression for the pairwise error probability (PEP) of a non-orthogonal access system under joint interference from ipSIC, RHI, and ipCSI has been calculated. This expression can serve as an upper bound for the bit error rate, providing a maximum estimation range for the bit error rate and offering a reference for measuring the bit error performance of vehicular network systems, thereby enabling the analysis of the reliability of vehicular network systems.

[0099] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0100] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0101] Based on the same inventive concept, corresponding to any of the above embodiments, this application also provides a vehicle networking system.

[0102] An error performance model construction apparatus includes: a determination module, adapted to determine the communication channel of the vehicle network system;

[0103] The first construction module is suitable for constructing the interference signal model and probability density model of the target vehicle under the communication channel.

[0104] The second construction module is adapted to construct a bit error rate performance model of the target vehicle based on the interference signal model and the probability density model.

[0105] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.

[0106] The apparatus of the above embodiments is used to implement the corresponding vehicle received signal bit error rate performance model construction method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0107] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method for constructing a bit error rate performance model of a vehicle received signal as described in any of the above embodiments.

[0108] Figure 7 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0109] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0110] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0111] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0112] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0113] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0114] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0115] The electronic devices described above are used to implement the corresponding vehicle received signal error performance model construction method in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0116] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the method for constructing a bit error rate performance model for vehicle received signals as described in any of the above embodiments.

[0117] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0118] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the error performance model construction method for vehicle received signals as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0119] In some embodiments, reference Figure 3 The signal transmitting node can be a signal transmitting base station (BS), and the signal receiving node can be a vehicle V1, V2, V3...V in the vehicle-to-everything (V2X) system. L .

[0120] Based on the traditional Non-Orthogonal Multiple Access (NOMA) system model, this paper examines the combined impact of non-ideal serial interference cancellation (ipSIC) and residual loss (RHI) in actual hardware on bit error rate performance when applying the traditional NOMA system to a vehicle-to-everything (V2X) system. A MATLAB simulation platform is used to verify the derived closed-form expression. The impact of non-ideal factors on system performance is also presented in a more intuitive way, providing a reference for the practical application design of this technology. As an optional approach, the number of vehicles implementing NOMA is L=3, assuming that the base station and each vehicle communicate using a single antenna. The signal transmitted to each vehicle is modulated using Binary Phase Shift Keying (BPSK), meaning that x and... Take 1 or -1, |Δ l |=2. Here, we assume that the first vehicle has the worst channel conditions among the three vehicles, and the third vehicle has the best channel conditions. The power allocation factors for each vehicle are α1=0.5, α2=0.3, and α3=0.2, respectively. Meanwhile, without loss of generality, various system parameters are assumed as follows: the distances between the vehicles and the base station are d1=300m, d2=200m, and d3=100m, respectively; the reference distance is d0=100m; the path loss exponent is a=2.7; the channel parameters are α=2 and μ=1; and the hardware residual loss is k. l =0.15, pilot energy to data energy ratio δ = 0.3, transmit and receive losses

[0121] As an optional solution, such as Figure 4 and Figure 5 As shown, the PEP of three vehicles under ideal and non-ideal conditions is depicted as the transmission power P increases. s The curve shows an ever-increasing change. Regardless of whether the situation is ideal or non-ideal, PEP will increase with P. s As it increases, it decreases, and gets closer and closer to its asymptote. Figure 4 The perfect overlap of the center line and the solid line proves the correctness of the derivation of the PEP closure expression under ideal conditions, but in Figure 5In the middle, the logo lines and solid lines are at low P s There are some differences because of the error caused by our Q-function approximation, while in the vehicle-to-everything (V2X) environment our P... s The error typically remains between 0dB and 60dB, therefore it does not affect the actual analysis. Next, through... Figure 4 and Figure 5 The comparison clearly shows that the presence of ipCSI and RHI degrades the system's bit error rate performance. For example, under ideal conditions, the PEP of vehicle V1 is only 0.8 × 10^(-3) at 20 dB, while under non-ideal conditions, this value reaches a full 19 × 10^(-3). Furthermore, under ideal conditions, the PEP will continuously increase with P... s It decreases as it increases, but from Figure 3 We can see that once the PEP of vehicle V1 exceeds 40dB, the increase in signal-to-noise ratio has a smaller and smaller impact on PEP performance.

[0122] As an optional solution, such as Figure 6 As shown, this depicts the effect of channel parameters on the PEP of three vehicles under ideal conditions as a function of transmit power P. s The curves show how the performance of a vehicle changes with increasing μ. It can be seen that for each vehicle, when μ remains constant and α = 4, the vehicle's PEP performance is better than the system's PEP performance when α = 2, indicating that PEP performance improves with increasing α. When α remains constant, the vehicle's PEP performance when μ = 1 is better than the system's PEP performance when μ = 0.5, indicating that PEP performance also improves with increasing μ. This also proves that non-geometric fading channels can be used to improve the performance of our vehicle-to-everything (V2X) systems.

[0123] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0124] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0125] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0126] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A method for measuring the performance of a vehicle networking system, characterized in that, include: Determine the simulation parameters; Based on the simulation parameters, simulation is performed using a pre-constructed bit error rate performance model to obtain simulation results; wherein, the bit error rate performance model is constructed based on the communication channel of the vehicle-to-everything (V2X) system. The performance of the vehicle networking system is measured based on the simulation results. The simulation using a pre-built bit error rate performance model includes: The communication channel of the vehicle-to-everything (V2X) system is determined, and the interference signal of the communication channel is determined, wherein the communication channel of the V2X system is determined to be an α-μ fading channel; Construct an interference signal model and a probability density model of the target vehicle under the communication channel; Based on the interference signal model and the probability density model, the bit error rate performance model of the target vehicle is constructed. The method for constructing the interference signal model of the target vehicle includes: Acquire superimposed signals transmitted from the same transmitting node to multiple vehicles; The interference signal model is constructed based on the superimposed signal; The expression for the superimposed signal is: For the first in the vehicle networking system The vehicle's power distribution factor. This refers to the transmit power of the base station's transmitting node; The expression for the interference signal model is: in, The signals required by vehicle users, i.e., the signals that the signal receiving nodes need to receive. This is noise interference signal caused by the removal of non-ideal serial interference. This is noise interference signal caused by residual hardware wear and tear. This refers to noise interference signals caused by incomplete channel estimation conditions. For communication channel condition estimation factors, , To express the summation, where This indicates the residual signal caused by the removal of interference signals due to non-ideal serial interference. for Gaussian white noise in the link, For signal transmitting nodes, For vehicles in the vehicle-to-everything (V2X) system, obey ,in For the first l The variance of the Gaussian white noise received by the vehicle; For channel estimation error, obey , It is a function of the signal-to-noise ratio, i.e. ,in This indicates large-scale decay. and Representing the signal transmitting node and the first Gain of the vehicle signal receiving node, Indicates wavelength. Indicates the reference distance. express arrive The distance between vehicles This represents the path loss index. Depends on the ratio of pilot energy to data energy. , Indicates the signal sending node to the vehicle Average signal-to-noise ratio on the communication channel link; It is the signal transmitting node and the first The overall level of residual hardware wear and tear between vehicles follows ,in This indicates the total residual hardware wear level in the vehicle-to-everything (V2X) system. This indicates the severity of residual hardware degradation at the launch node. Indicates the first The severity of residual hardware damage at the vehicle receiving node; The method for constructing the probability density model includes: The initial probability density model for the target vehicle is expressed as follows: The probability density function and cumulative distribution function of the communication channel are coupled into the initial probability density model to obtain the probability density model; The probability density function of the communication channel is: The cumulative distribution function of the communication channel is: The coupled probability density model is as follows: in, Indicates the nonlinear power index. Indicates the number of multipath clusters. Represents the communication channel envelope The right root, Let X represent unsorted , This represents the gamma function.

2. The method according to claim 1, characterized in that, The simulation parameters include communication channel parameters, reference distance, distance between signal transmitting nodes and signal receiving nodes, and power allocation factor.

3. The method according to claim 1, characterized in that, The interference signals include: interference signals removed by non-ideal serial interference removal, interference signals with residual hardware loss, and interference signals with incomplete channel estimation conditions.

4. The method according to claim 1, characterized in that, The step of constructing the bit error rate performance model of the target vehicle based on the interference signal model and probability density model includes: Construct an initial bit error rate performance model; By coupling the interference model and the probability density model to the initial bit error rate performance model, the expression for the bit error rate performance model is obtained as follows: ， in, , , , , , , , , , , , , , , These are all parameters defined to simplify the representation.

5. An error performance model construction device, characterized in that, include: The module is designed to determine the communication channels of a vehicle-to-everything (V2X) system. The first construction module is suitable for constructing the interference signal model and probability density model of the target vehicle under the communication channel. The second construction module is adapted to construct a bit error rate performance model of the target vehicle based on the interference signal model and the probability density model. Simulations using a pre-built bit error rate performance model include: The communication channel of the vehicle-to-everything (V2X) system is determined, and the interference signal of the communication channel is determined, wherein the communication channel of the V2X system is determined to be an α-μ fading channel; Construct an interference signal model and a probability density model of the target vehicle under the communication channel; Based on the interference signal model and the probability density model, the bit error rate performance model of the target vehicle is constructed. The method for constructing the interference signal model of the target vehicle includes: Acquire superimposed signals transmitted from the same transmitting node to multiple vehicles; The interference signal model is constructed based on the superimposed signal; The expression for the superimposed signal is: For the first in the vehicle networking system The vehicle's power distribution factor. This refers to the transmit power of the base station's transmitting node; The expression for the interference signal model is: in, The signals required by vehicle users, i.e., the signals that the signal receiving nodes need to receive. This is noise interference signal caused by the removal of non-ideal serial interference. This is noise interference signal caused by residual hardware wear and tear. This refers to noise interference signals caused by incomplete channel estimation conditions. For communication channel condition estimation factors, , To express the summation, where This indicates the residual signal caused by the removal of interference signals due to non-ideal serial interference. for Gaussian white noise in the link, For signal transmitting nodes, For vehicles in the vehicle-to-everything (V2X) system, obey ,in For the first l The variance of the Gaussian white noise received by the vehicle; For channel estimation error, obey , It is a function of the signal-to-noise ratio, i.e. ,in This indicates large-scale decay. and Representing the signal transmitting node and the first Gain of the vehicle signal receiving node, Indicates wavelength. Indicates the reference distance. express arrive The distance between vehicles This represents the path loss index. Depends on the ratio of pilot energy to data energy. , Indicates the signal sending node to the vehicle Average signal-to-noise ratio on the communication channel link; It is the signal transmitting node and the first The overall level of residual hardware wear and tear between vehicles follows ,in This indicates the total residual hardware wear level in the vehicle-to-everything (V2X) system. This indicates the severity of residual hardware degradation at the launch node. Indicates the first The severity of residual hardware damage at the vehicle receiving node; The method for constructing the probability density model includes: The initial probability density model for the target vehicle is expressed as follows: The probability density function and cumulative distribution function of the communication channel are coupled into the initial probability density model to obtain the probability density model; The probability density function of the communication channel is: The cumulative distribution function of the communication channel is: The coupled probability density model is as follows: in, Indicates the nonlinear power index. Indicates the number of multipath clusters. Represents the communication channel envelope The right root, Let X represent unsorted , This represents the gamma function.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as claimed in claims 1 to 4.

7. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of claims 1 to 4.

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