A method and system for optimizing performance of NR sidelink multihop relay in vehicle networking

Abstract

A method and system for optimizing the performance of multi-hop relay on the NR side in vehicular networks (V2X) include: establishing a system model of key messages in a multi-hop relay scenario on the NR side; constructing a performance analysis framework for multi-hop transmission of key messages in V2X; calculating the average performance under a multi-round random transmission scenario based on the system model and Monte Carlo simulation, and verifying the correctness of the performance analysis framework; formulating the multi-hop relay transmission process on the NR side as a multi-constraint, multi-objective mixed-integer linear programming problem; solving the mixed-integer linear programming problem under given key message transmission distance or end-to-end transmission probability and lifetime, and outputting the corresponding network parameters under optimal performance. This invention formulates the process of key messages in V2X via multi-hop relay on the NR side as a typical optimization problem and proposes a particle swarm optimization algorithm to determine the optimal settings of NR side parameters, thereby maximizing the multi-hop transmission probability or propagation distance.

Description

Technical Field

[0001] This invention belongs to the field of NR side travel link optimization technology in vehicle-to-everything (V2X) networks, and specifically relates to a method and system for optimizing the performance of multi-hop relays on the NR side travel link in V2X networks. Background Technology

[0002] The NR side-link offers advantages such as low latency, high capacity, and strong anti-interference capabilities. Utilizing the PC5 interface, it can be flexibly used for vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-traffic communication. Furthermore, the NR side-link can operate in two different modes: Mode 1 and Mode 2. Specifically, in Mode 1, the NR side-link is centrally managed by a Radio Resource Control (RRC) connection between the base station and the UE; in Mode 2, the UE autonomously selects transmission resources from the resource pool. Since the NR side-link evolved from traditional Device-to-Device (D2D) communication, it also faces limitations in transmission range, similar to D2D communication. To further improve the transmission range of the NR side-link, 3GPP Release 17 and Release 18 proposed NR side-link relay, where multiple NR side-links can be linked together in a multi-hop manner using other vehicles or Roadside Units (RSUs) as relay nodes. Through NR side-link multi-hop relay, key vehicle-to-everything (V2X) messages can be transmitted over longer distances even without cellular network coverage.

[0003] Defects and shortcomings of existing technology:

[0004] Existing solutions use Reference Signal Receiving Power (RSRP) measurement as the standard for NR-side walkway relay settings. While this approach is easy to implement in practical network deployments, the accuracy of RSRP measurements may be inaccurate in dense vehicular networks. Furthermore, RSRP measurements cannot guide network design and deployment. Other invention patents concerning NR-side walkway relays, such as CN114208072A, CN115699816A, and CN114902744A, neglect certain physical layer specifications of the NR-side walkway (resource allocation methods, power control, sub-channel selection, etc.). Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for optimizing the performance of multi-hop relays on the NR side in vehicle-to-everything (V2X) networks, in order to solve the above-mentioned problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a method for optimizing the performance of multi-hop relays on the NR side in a vehicle-to-everything (V2X) network, comprising:

[0008] Based on real-world NR-side multi-hop relay scenarios, a system model for critical messages in NR-side multi-hop relay scenarios is established.

[0009] Construct a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles, and analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages;

[0010] Based on the system model, the average performance results under multi-round random transmission scenarios are calculated to verify the correctness of the performance analysis framework;

[0011] Based on the validated performance analysis framework, the multi-hop relay transmission process of the NR side link is formalized as a mixed integer linear programming problem with multiple constraints and multiple objectives.

[0012] Given the critical message delivery distance or end-to-end delivery probability and lifecycle, solve the mixed-integer linear programming problem and output the corresponding network parameters with optimal performance.

[0013] Optionally, the system model is as follows:

[0014] Based on real-world NR-side multi-hop relay scenarios, we define the RSU spatial distribution model, resource allocation model, interference model, and traffic model for critical messages passing through NR-side multi-hop relay scenarios.

[0015] Optionally, analyze the multi-hop delivery probability, multi-hop transmission time, and total propagation distance of key messages:

[0016] Based on the system model, the average transmission rate, transmission delay, and maximum number of transmission hops of key messages in the multi-hop relay scenario of the NR side are derived using the stochastic geometric method. Furthermore, analytical formulas for transmission distance and end-to-end transmission probability are derived. The analytical formulas for transmission distance and end-to-end transmission probability together constitute the performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles.

[0017] Optional, verify the correctness of the performance analysis framework:

[0018] Based on the given system model, transmission scenarios are randomly generated through Monte Carlo experiments, and the average performance results under multiple rounds of random transmission scenarios are calculated and compared with the performance analysis deterministic calculation results. If the experimental results and the calculation results match, then the performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles is correct.

[0019] Optional, mixed-integer linear programming problems:

[0020] Based on the maximum lifespan of critical messages, transmission distance requirements, end-to-end transmission probability requirements, and the range of parameter selection for NR-side multi-hop relay networks, an optimization problem with multiple constraints is presented. This optimization problem takes end-to-end transmission probability or transmission distance as the optimization objective and the selection of NR-side multi-hop relay network parameters {ρ,ω,m} as optimization variables.

[0021] Optionally, output the corresponding network parameters for optimal performance:

[0022] Given the critical message delivery distance or end-to-end delivery probability and lifetime, the particle swarm optimization algorithm is used to solve for the optimal end-to-end delivery probability or delivery distance, and the corresponding network parameters {ρ} under optimal performance are given. * ,ω * ,m *}, where ρ * The proportion of RSUs selected for optimal performance in operating mode 2, ω * The RSU transmit power compensation factor under optimal performance, m * To select the size of the transmission subchannel for RSU with optimal performance, the particle swarm optimization algorithm is proposed based on a given multi-constraint, multi-objective mixed integer linear programming problem. The corresponding network parameters {ρ} for optimal performance are also given. * ,ω * ,m *}

[0023] Optionally, the overall operating modes include Mode 1 and Mode 2. In Mode 1, the NR-side walkway is centrally managed by the RRC connection between the base station and the RSU. In Mode 2, the RSUs on the NR-side walkway autonomously select transmission resources from the resource pool. The proportion of RSUs selecting Mode 2 is ρ, and the proportion selecting Mode 1 is 1-.

[0024] Secondly, the present invention provides a system for optimizing the performance of multi-hop relays on the NR side in a vehicle-to-everything (V2X) network, comprising:

[0025] The model building module is used to build a system model of key messages in the NR side crosslink multi-hop relay scenario based on the real NR side crosslink multi-hop relay scenario;

[0026] The performance analysis framework building module is used to build a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles, and to analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages.

[0027] The verification module is used to calculate the average performance results under multi-round random transmission scenarios based on the system model, and to verify the correctness of the performance analysis framework.

[0028] The planning problem construction module is used to formulate the NR-side multi-hop relay transmission process as a multi-constraint, multi-objective mixed integer linear programming problem based on the validated performance analysis framework.

[0029] The output module is used to solve mixed-integer linear programming problems given key message delivery distances or end-to-end delivery probabilities and lifecycles, and output the corresponding network parameters under optimal performance.

[0030] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a method for optimizing the performance of NR-side multi-hop relays in a vehicle-to-everything (V2X) network.

[0031] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a method for optimizing the performance of NR-side multi-hop relays in a vehicle-to-everything (V2X) network.

[0032] Compared with the prior art, the present invention has the following technical effects:

[0033] This invention proposes a general multi-hop NR side-link relay scheme for the efficient and flexible propagation of event-triggered non-periodic critical messages in V2X networks. The critical message is a Decentralized Environmental Notification Message (DENM). Specifically, the RSU acts as an intermediate relay from source to destination. Each RSU can independently select mode 2 with probability ρ and mode 1 with probability 1-; each RSU can independently select ω as the transmit power compensation factor; and each RSU can independently select m as the number of Physical Resource Blocks (PRBs) in the side-link sub-channel.

[0034] This invention constructs a performance analysis framework for NR-side multi-hop relay in vehicular networks based on stochastic geometry, where the RSU and interfering devices are modeled as a one-dimensional Poisson Point Process (PPP) and a two-dimensional PPP, respectively. With the help of this framework, this invention successfully derives several important performance indicators, including the multi-hop transmission probability and total propagation distance of DENM, by carefully addressing the interference problem caused by frequency domain resource sharing in the NR uplink and NR sidelink transmissions. Furthermore, the effectiveness of the theoretical framework is verified based on Monte Carlo experiments.

[0035] For a given DENM lifecycle, this invention formulates the process of DENM multi-hop relay via NR side travel link in vehicle-to-everything (V2X) as a typical optimization problem, and proposes a particle swarm optimization algorithm to determine the optimal settings of NR side travel link parameters, thereby maximizing the multi-hop transmission probability (or propagation distance).

[0036] Numerical results validate the effectiveness of this invention. This invention, through performance analysis and optimization, can determine the optimal network parameters {ρ} for the NR-side traveling link. * ,ω * ,m * This significantly enhances the achievable performance of NR sidelinks in terms of multi-hop delivery probability and propagation distance. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating the performance analysis and optimization method for multi-hop relay on the NR side in vehicle-to-everything (V2X) networks proposed in this invention.

[0038] Figure 2 This invention is designed for a multi-hop relay scenario on the NR side of the mobile link.

[0039] Figure 3 This is a schematic diagram of the NR-side multi-hop relay transmission resource pool configuration in this invention;

[0040] Figure 4 This is a schematic diagram of the k-th hop transmission of the NR-side multi-hop relay in the cross link of the present invention;

[0041] Figure 5 This is a schematic diagram of the time domain of the NR side's connecting link;

[0042] Table I presents the particle swarm optimization algorithm for optimizing the performance of multi-hop relays on the NR side in this invention.

[0043] Figure 6A , Figure 6B This is the Monte Carlo experimental verification result of the NR-side traveling link multi-hop relay performance analysis framework in this invention;

[0044] Figure 7 This describes the variation of NR-side multi-hop relay transmission performance with power compensation factor ω in this invention.

[0045] Figure 8A , Figure 8B This presents the performance optimization results and optimal parameter settings for the NR-side multi-hop relay in this invention.

[0046] In the diagram: 1. DENM message sent from the vehicle to its neighboring RSU1; 2. First-hop NR-side traversal transmission from RSU1 to RSU2; 3. Second-hop NR-side traversal transmission from RSU2 to RSU3; 4. Third-hop NR-side traversal transmission from RSU3 to RSU4; 5. NR uplink transmission interference of the UE to the target RSU; 6. NR uplink transmission from the UE to the gNB; 7. Shared resource pool allocated to each region for NR-side traversal transmission mode 2 and NR uplink transmission, containing n consecutive PRBs; 8. Resource pool allocated to each region for NR-side traversal transmission mode 1, containing (N z -n) consecutive PRBs; 9. Resource pools allocated to each region, containing N Z 10. A transmission subchannel for NR-side crosslink transmission mode 2, randomly selected from 7, containing m consecutive PRBs; 11. A transmission subchannel for NR-side crosslink transmission mode 2 or for NR uplink transmission, randomly selected from 7. If 11 represents a transmission subchannel for NR-side crosslink transmission mode 2, containing m consecutive PRBs; if 11 represents a transmission subchannel for NR uplink transmission, containing m′ consecutive PRBs. 12. From RSU k to RSU k+1 13. The central location of the area, situated on one side of the road; 14. The target RSU for the k-th NR side traversal transmission. k+1 The location is also the origin O of the polar coordinate system describing the relative positions of each device in the k-th NR side hop link transmission; 15. The polar coordinate system describing the relative positions of each device in the k-th NR side hop link transmission, with the origin O located at the target RSU of the k-th NR side hop link transmission. k+1 At this point, the polar axis points in the direction of DENM transmission along the road. In 15, RSU i This represents the i-th RUS, whose coordinates are determined by the RSU. i The distance r to the origin O i and RSU i The angle θ between the line connecting to the origin O and the polar axis is... i Represented as (r i ×cosθ i ,0). In 15, UE j This represents the UE that transmits the j-th NR uplink, and its coordinates are determined by the UE. j The distance r′ to the origin o j The angle θ′ between the line connecting UEj to the origin O and the polar axis is... j Represented as (r′) j ×cosθ′ j ,r′ j×sinθ′ j ); 16. NR side crosslink transmission time domain minimum scheduling granularity time slot, of which 2 η One consecutive time slot constitutes one subframe, and 10 subframes constitute one frame. Each frame occupies 10 milliseconds. Here, according to the 3GPP standard TS38.211, η is determined by the subcarrier spacing of NR, therefore the time of each time slot is 1 / 2. η 17. The arrival time of DENM in the transmission queue follows a uniform distribution U(0, 1 / 2) in each time slot. η ); 18. The time slot alignment time required for DENM to wait for the next time slot to start transmission after arriving in the transmission queue is denoted as T in this invention. a =0.5×1 / 2 η millisecond. Detailed Implementation

[0047] The technical problem to be solved by this invention is to propose a performance analysis and optimization method for multi-hop relays on the NR side of vehicular networks. The method is based on stochastic geometry theory and particle swarm optimization algorithm, and analyzes and optimizes the NR side traversal network parameters including: the proportion ρ of RSUs selecting operating mode 2 in the NR side traversal, the RSU transmit power compensation factor ω in the NR side traversal, and the size m of the RSU-selected transmission subchannel in the NR side traversal.

[0048] The scenario described in this invention is a multi-hop transmission scenario on the NR side traveling link. Based on the method described, multiple RSU cooperative relays can be completed to transmit key vehicle network messages to more distant target UEs, thereby enhancing the transmission range of the NR side traveling link.

[0049] The NR-side walkie-link conforms to the relevant 3GPP standards TS 38.213, TR 38.886, TR 38.885, TS38.331, TR 37.985, TS 38.104, TS 38.211, TS 38.214, TR 37.885, TR 38.785 and TS22.186.

[0050] The NR-side walkway relay process conforms to the relevant 3GPP standards TR 38.836 and TR 23.752.

[0051] The NR sidelink multi-hop transmission adopts a unicast transmission scheme, which is completed by specifying the device ID of the receiving RSU in the sidelink control information (SCI). When the target RSU receives the critical message, it first checks whether the message's lifecycle has expired. If the message has expired, it is discarded; if the message has not expired, it is forwarded to the next nearby RSU to complete the relay transmission of the message.

[0052] The key message in the vehicle-to-everything (V2X) communication is the Distributed Environment Notification Message (DENM) specified in the European Telecommunications Standards Institute (ETSI) standard ETSI EN 302 637-3. The DENM is used for road hazard warning applications and is an event-triggered, non-periodic message. Once a safety hazard event is detected by the connected vehicle, the relevant application of the onboard intelligent transportation system immediately sends the DENM to the nearest RSU via the NR side link.

[0053] The RSU internally stores the IDs of its neighboring RSU devices, supports NR-side unicast communication, and is an intelligent transportation system roadside unit. It can autonomously select the NR-side unicast communication mode (mode 1 or mode 2), the NR-side unicast power compensation factor, and the transmission sub-channel size. It also has multi-constellation high-precision global navigation satellite system positioning function.

[0054] The stochastic geometry method is considered the most suitable analytical tool in the deployment of wireless networks to elucidate the ultimate performance limits of innovative technologies applied in wireless networks and guide the design of optimal algorithms and protocols to achieve the ultimate performance goals. The stochastic geometry performance analysis method has been successfully applied multiple times to analyze coverage, power transmission, and energy efficiency optimization in scenarios such as cellular networks, multi-layer cellular networks, millimeter-wave cellular networks, and D2D wireless networks.

[0055] The particle swarm optimization (PSO) algorithm is a heuristic optimization algorithm derived from the foraging behavior of bird flocks. PSO has advantages such as fast convergence speed, few parameters, and simple implementation (it converges to the optimal solution faster than genetic algorithms for high-dimensional optimization problems), and has wide applications in the performance optimization of wireless networks.

[0056] The described operating modes generally include Mode 1 and Mode 2. In Mode 1, the NR-side walkie-talkie is centrally managed by the RRC connection between the base station and the RSU. In Mode 2, the RSUs on the NR-side walkie-talkie autonomously select transmission resources from the resource pool. In the method described, the proportion of RSUs selecting Mode 2 is ρ, and the proportion selecting Mode 1 is 1-.

[0057] The transmit power compensation factor ω conforms to 3GPP standard TS 38.214. Specifically, the transmit RSU can control its transmit power based on the NR-side link path loss between itself and the receive RSU.

[0058] P k =min{ max ,[P0+10lg(2 η ·m)+ω·PL k ]}

[0059] Where Pk is the actual transmit power of the RSU, min{·} is a function that returns the minimum value in a set of values, Pmax is the maximum transmit power of the RSU, P0 is the nominal transmit power of the RSU, η is the subcarrier spacing configuration factor of the NR network, m is the size of the transmission subchannel selected by the RSU, ω is the transmit power compensation factor of the RSU, and PLk is the NR-side link path loss between the transmitting RSU and the receiving RSU.

[0060] The NR-side link path loss is obtained from the following expression in 3GPP standard TR 37.885, and is used to estimate the actual NR-side link path loss between the transmitting RSU and the target RSU in this invention.

[0061] PL k =32.4+20lg(d) k )+20lg(f c )

[0062] Where, d k f is the Euclidean distance between the launching RSU and the target RSU. c This is the center frequency of NR.

[0063] The size of the transmission subchannel is the number of PRBs contained in the subchannel. The subchannel is the minimum frequency domain scheduling unit of the NR side travel link. According to the 3GPP standard TS 38.331 specification, the subchannel can be composed of m consecutive PRBs, where m∈{10,12,15,20,25,50,75,100}.

[0064] The performance analysis focuses on two key performance indicators of NR-side multi-hop relay in the downlink: end-to-end transmission probability S tot And message passing distance D tot The end-to-end transmission probability is defined as the probability that the signal-to-interference-plus-noise ratio (SINR) of the NR-side crosslink transmission at each hop is greater than a given threshold β, i.e., S tot =r(SINR1≥β,SINR2≥β,…,SINR k ≥β,…,SINR K≥β). Where Pr(·) is the probability calculation function, SINR k The signal-to-interference-plus-noise ratio (SIR) at the k-th hop receiver on the NR side's crosslink transmission is given, where K is the maximum number of hops transmitted within the DENM's lifetime. Message passing distance is defined as the total distance traveled by the DENM from the first hop to the k-th hop.

[0065] To achieve performance analysis and optimization of multi-hop relays on the NR side of vehicle-to-everything (V2X) networks, the technical solution adopted in this invention includes the following steps:

[0066] A method for optimizing the performance of multi-hop relays on the NR side in vehicle-to-everything (V2X) networks includes:

[0067] Based on real-world NR-side multi-hop relay scenarios, a system model for critical messages in NR-side multi-hop relay scenarios is established.

[0068] Construct a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles, and analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages;

[0069] Based on the system model, the average performance results under multi-round random transmission scenarios are calculated to verify the correctness of the performance analysis framework;

[0070] Based on the validated performance analysis framework, the multi-hop relay transmission process of the NR side link is formalized as a mixed integer linear programming problem with multiple constraints and multiple objectives.

[0071] Given the critical message delivery distance or end-to-end delivery probability and lifecycle, solve the mixed-integer linear programming problem and output the corresponding network parameters with optimal performance.

[0072] Specifically:

[0073] Step S1: Construct a system model to analyze the performance of key vehicle-to-everything (V2X) messages passing through the NR side multi-hop relay scenario.

[0074] Specifically, based on real-world NR-side multi-hop relay scenarios, we define the RSU spatial distribution model, resource allocation model, interference model, and traffic model for critical messages passing through NR-side multi-hop relay scenarios.

[0075] Step S2: Based on the stochastic geometry method, construct a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles, analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages, and give the deterministic formula for the above performance.

[0076] Specifically, based on the system model given in step S1, analytical formulas for the average transmission rate, transmission delay, and maximum number of transmission hops of key messages in a multi-hop relay scenario on the NR side are derived using stochastic geometric methods. Furthermore, analytical formulas for the transmission distance and end-to-end transmission probability are derived. These analytical formulas for the transmission distance and end-to-end transmission probability together constitute the performance analysis framework for multi-hop transmission of key messages in the vehicle-to-everything (V2X) network.

[0077] Step S3: Verify the correctness of the performance analysis framework based on the Monte Carlo experimental method.

[0078] Specifically, based on the system model given in step S1, transmission scenarios are randomly generated through Monte Carlo experiments. The average performance under multiple rounds of random transmission scenarios is calculated and compared with the performance analytical deterministic calculation results given in step S2. If the experimental results and the calculation results match, it indicates that the performance analysis framework for multi-hop transmission of key vehicle-to-everything (V2X) messages given in step S2 is correct.

[0079] Step S4: Based on the verified performance analysis framework, the NR side crosslink multi-hop relay transmission process is formulated as a mixed integer linear programming problem with multiple constraints and multiple objectives.

[0080] Specifically, based on the actual scenario requirements (including the maximum lifespan of critical messages, transmission distance requirements, and end-to-end transmission probability requirements) and the range of parameter selection requirements for the NR-side multi-hop relay network, an optimization problem with multiple constraints is presented. This optimization problem takes the end-to-end transmission probability or transmission distance as the optimization objective and the selection of NR-side multi-hop relay network parameters {ρ,ω,m} as the optimization variables.

[0081] Step S5: Given the critical message delivery distance (or end-to-end delivery probability) and lifecycle, use the particle swarm optimization algorithm to solve for the optimal end-to-end delivery probability (or delivery distance), and provide the corresponding network parameters {ρ} under optimal performance. * ,ω * ,m *}, where ρ * The proportion of RSUs selected for optimal performance in operating mode 2, ω * The RSU transmit power compensation factor under optimal performance, m * Select the size of the transmission subchannel for RSU to achieve optimal performance.

[0082] Specifically, based on the multi-constraint, multi-objective mixed-integer linear programming problem given in step S4, the particle swarm optimization algorithm can solve the problem with low time complexity, and provides the corresponding network parameters {ρ} under optimal performance. * ,ω * ,m *}

[0083] Example:

[0084] The following describes step S1 of the proposed technical solution: Analyzing the performance of key vehicle-to-everything (V2X) messages in a multi-hop relay scenario via the NR side, and establishing an RSU spatial distribution model, resource allocation model, interference model, and traffic model.

[0085] Step S1 provides a typical scenario example of DENM telemetry via the NR side traveling link relay RSU in the vehicle-to-everything (V2X) network. Following Figure 1 In the case of the method proposed in this invention shown in the flowchart, changes can be made to the functions and arrangements in step S1, and various processes or components can be omitted, replaced, or added as appropriate. For example, the situation where the NR side downlink and NR uplink share a resource pool can be ignored. The above omissions, replacements, or additions will be reflected in the performance analysis framework completed in step S2.

[0086] It should be noted that the detailed description below, in conjunction with the accompanying drawings, is intended to describe various configurations and is not intended to imply that only the configurations described in this specification can be practiced. The detailed description includes the numbering used to identify various types of equipment (e.g., RSU). i and UE j This includes the region to which the RSU belongs, the various variable symbols in the performance analysis framework, and the constraints considered in the optimization problem. Those skilled in the art, upon understanding these concepts, can practice this invention without or without these specific detailed descriptions.

[0087] like Figure 2 As shown, a typical DENM is generated by a sudden road event perceived by the vehicle. The vehicle can send this event-driven aperiodic DENM to its nearest RSU. Through the coordination of multiple RSUs, the DENM can be distributed over its lifecycle T. max The information is transmitted over a longer distance via NR side-link multi-hop relay, thereby transmitting road emergencies to more road vehicles.

[0088] like Figure 2 As shown, any number of wireless network access devices can be deployed in a given geographical area, and these devices are randomly distributed in space, with their locations following a Poisson process distribution. Specifically, in the scenario involved in this invention, RSUs are distributed along straight roads, following a one-dimensional Poisson process Φ with intensity λ; NR uplink transmission UEs are randomly distributed around the road, following a one-dimensional Poisson process Φ′ with intensity λ′.

[0089] like Figure 2As shown, RSUs can be divided into different regions based on their geographical location. For example, RSU1 and RSU2 are assigned to region 2, while RSU3 and RSU4 are assigned to region 3. Each region is a square area of ​​2×2A, indicated by a 12-bit region ID carried in the NR-side crosslink control information (SCI). To improve the utilization of NR-side crosslink frequency domain resources and reduce transmission interference from nearby devices, non-adjacent regions can be allocated the same frequency domain resource pool, while adjacent regions can be allocated mutually orthogonal frequency domain resource pools.

[0090] Based on the above regional division, transmission between RSUs will be divided into two cases: intra-regional transmission and cross-regional transmission. For example... Figure 2 As shown, 2 represents a single-hop NR-side crosslink transmission from RSU1 to RSU2, which is intra-regional transmission, and 3 represents a single-hop NR-side crosslink transmission from RSU2 to RSU3, which is cross-regional transmission.

[0091] like Figure 2 As shown, the UE uses NR uplink transmission 6 to communicate with its nearest gNB.

[0092] Figure 2 The location and distribution of gNBs shown in this invention can be omitted because this invention does not involve the analysis of downlinks related to the location and distribution of gNBs in relation to NRs.

[0093] like Figure 3 As shown, for each NR-side downlink transmission RSU and NR uplink transmission UE within a region, they are allocated a fixed resource pool 9. This resource pool consists of N... Z It consists of 1 PRB.

[0094] For resource pool 9, the present invention further divides it into, as follows: Figure 3 The two parts shown are: a shared resource pool 7 allocated to each region for NR-side crosslink transmission mode 2 and NR uplink transmission, containing n consecutive PRBs; and a resource pool 8 allocated to each region for NR-side crosslink transmission mode 1, containing ( Z -) consecutive PRBs.

[0095] In this invention, each RSU transmitting on the NR side can autonomously select its operating mode. Specifically, the probability of an RSU selecting mode 2 transmission is ρ; the probability of selecting mode 1 transmission is (1-).

[0096] Combination Figure 2 and Figure 3To explain, for example, NR-side downlink transmission within the area from RSU1 to RSU2, the probability that RSU1 selects mode 2 transmission (i.e., randomly selects a sub-channel from resource pool 7) is ρ; the probability that it selects mode 1 transmission (i.e., is centrally allocated a sub-channel from resource pool 8) is (1-). UEs transmitting via NR uplink randomly select a sub-channel from resource pool 7.

[0097] Therefore, randomly selecting a sub-channel from the resource pool for the RSU and UE will result in a certain probability of collision. For example... Figure 3 As shown, 10 is the sub-channel of DENM transmission described in this invention (composed of m consecutive PRBs), and 11 is the interference sub-channel that collides with the sub-channel of DENM transmission.

[0098] If m consecutive PRBs of an interfering subchannel are selected by other RSUs using NR-side crosslink mode 2 transmission, then the collision probability ξ between the two subchannels is:

[0099]

[0100] If the m′ consecutive PRBs of the interfering subchannel are selected by a UE using NR uplink transmission, then the collision probability ζ between the two subchannels is:

[0101]

[0102] Considering the cross-regional transmission described in this invention, additional configuration by N is required. C A public resource pool consisting of PRBs, for example Figure 2 The cross-regional NR-side walkway transmission from RSU2 to RSU3 shown provides transmission resources. It should be noted that when the transmitting RSU and the target RSU are located in different regions, the transmitting RSU can only operate in mode 1.

[0103] When the transmitting RSU operates in Mode 2, collisions between sub-channels can cause communication interference to the target RSU because resources are randomly selected from resource pool 7. This invention uses the symbol I to represent the sum of interference received by a single-hop target RSU from other NR-side downlink transmission RSUs that have collided with it, and the symbol I′ to represent the sum of interference received by a single-hop target RSU from other NR uplink transmission UEs that have collided with it. When the transmitting RSU operates in Mode 1, the interference caused by collisions between sub-channels can be ignored because resources are centrally scheduled by the network.

[0104] Based on the RSU spatial distribution model, resource allocation model, interference model, and traffic model established in step S1, this invention can clearly describe the multi-hop transmission scenario of key messages in the Internet of Vehicles (IoV), and thus construct a performance analysis framework for multi-hop transmission of key messages in the IoV.

[0105] The following description corresponds to step S2 of the proposed technical solution: Based on the stochastic geometry method, a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles is constructed to analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages, and to give the deterministic formula for the above performance.

[0106] like Figure 4 As shown, DENM transmits data from the RSU in the k-th NR side crosslink transmission 12. k Sent to RSU k+1 Its transmission distance is denoted as d. k . d k Determined by the RSU spatial distribution model provided in step S1, and based on the properties of a one-dimensional Poisson point process, d k The probability density function is:

[0107]

[0108] To facilitate the characterization of interference from different devices, this invention provides the following... Figure 4 The polar coordinates shown are 15. The origin O of polar coordinates 15 is located at the target RSU of the k-th NR side crosslink transmission. k+1 At this point, the polar axis points in the direction of DENM transmission along the road. In polar coordinates 15, RSU i This represents the i-th RUS, whose coordinates are determined by the RSU. i The distance r to the origin O i and RSU i The angle θ between the line connecting to the origin O and the polar axis is... i Represented as (r i ×cosθ i ,0). In 15, UE j This represents the UE that transmits the j-th NR uplink, and its coordinates are determined by the UE. j The distance r′ to the origin O j and UE j The angle θ′ between the line connecting to the origin O and the polar axis is... j Represented as (r′) j ×cosθ′ j ,r′ j ×sinθ′ j ).

[0109] In this invention, the symbol δ is used. k This represents the center location 13 of a 2A×2A area and the target RSU for NR side crosslink transmission at the k-th hop. k+1 The distance between positions 14. According to the properties of a one-dimensional Poisson point process, δ... k The probability density function is:

[0110]

[0111] This invention considers region-based resource reuse, where interference caused by sub-channel collisions originates only within the region. Therefore, the distance from the origin O to the k-th hop target RSU received from other NR-side linked line transmission RSUs that have collided should satisfy 0 ≤ r. i ≤r max ,in:

[0112]

[0113] Where, Θ k For an angle, when the origin O is located at or to the right of the center position 13 of the region, Θ k =0; otherwise, Θ k =π.

[0114] This invention considers roads of width W. Because UEs using NR uplink transmission are pedestrian-carried devices, they cannot be distributed on roads of width W. Therefore, the distance from the origin O to the k-th hop target RSU from other NR uplink transmission UEs that have collided should satisfy r′. min ≤r′ j ≤r′ max ,in:

[0115]

[0116]

[0117] Based on such Figure 4 Given the positional relationships shown, the probability that the (k+1)th hop NR side crosslink transmission is an intra-area transmission is:

[0118]

[0119] Since each hop in the NR-side crosslink transmission multi-hop relay process involved in this invention is independent of each other, the probability that the k-th NR-side crosslink transmission is an in-area transmission can be given as:

[0120] like Figure 5 As shown, the NR side's traveling link time domain structure is as follows: each frame is 10 milliseconds, containing 10 subframes; each subframe is 1 millisecond, containing 2... η 16 time slots. Each time slot is 1 / 2. η Milliseconds. The subcarrier spacing configuration factor η of the NR network is determined by the NR network subcarrier spacing. In this invention, the correspondence between parameter η and the NR network subcarrier spacing refers to 3GPP standard TS 38.214.

[0121] In the NR-side walkway, the time slot is the smallest time-domain scheduling granularity of the resource. For example... Figure 5 As shown in Figures 17 and 18, when the DENM arrives at the transmit queue, the transmission needs to be aligned to the start of the next time slot. Therefore, in this invention, the alignment delay T is considered. a The alignment delay T a =0.5×1 / 2 η millisecond.

[0122] In this invention, when the RSU operates in Mode 1, its transmission resources are centrally scheduled by the gNB. Due to the limited nature of transmission resources, transmission requires waiting for resource scheduling delays. Therefore, this invention considers the waiting delays for cross-regional transmissions. Waiting delay for Mode 1 transmission within the region

[0123] Cross-regional transmission latency Waiting delay for Mode 1 transmission within the region It is determined by the resource allocation model and flow model provided in step S1.

[0124] Cross-regional transmission latency The maximum number of sub-channels that the cross-regional transmission resource pool can provide simultaneously. Cross-regional message delivery rate λ c = (1-∈)λ and cross-regional single-hop transmission delay here, This is the floor function.

[0125] Specifically, based on queuing theory, the waiting delay for cross-regional transmission. for:

[0126]

[0127] Where, ΔT w This refers to the connection time for Radio Resource Control (RRC).

[0128] Waiting delay for mode 1 transmission within the area Determined by: the maximum number of sub-channels that the transmission resource pool can provide simultaneously within the region. The arrival rate λ of Mode 1 transmission within the area 1 = (1-ρ)∈λ and Mode 1 single-hop transmission delay within the region

[0129] Similarly, the waiting delay for mode 1 transmission within the region. for:

[0130]

[0131] It should be noted that, in order to ensure the stability of queuing theory, the scenarios involved in this invention need to meet the following conditions: and

[0132] In this invention, the cross-regional single-hop transmission delay is described. Single-hop transmission delay in mode 1 within the region and mode 2 single-hop transmission delay within the region Where Ω is the message size of DENM, E c For the average transmission rate of cross-regional single-hop transmission, E 1 The average transmission rate of mode 1 single-hop transmission within the region, E 2 This represents the average transmission rate of mode 2 single-hop transmission within the region.

[0133] In this invention, the average transmission rate E c E 1 and E 2 It can be obtained analytically from Shannon's formula and stochastic geometry theory:

[0134]

[0135]

[0136]

[0137] Where: B = m·B PRB For transmission sub-channel bandwidth, B PRB Bandwidth for each PRB and For the Laplace transform of interference I and I′, As a substitute variable, μ is the expected value of the fading coefficient, α is the path loss exponent, and P k The transmission power of the RSU transmitted in the k-th hop, σ 2 The power is the additivity Gaussian white noise.

[0138] Calculating the average transmission rate requires obtaining the interference received by the RSU. The interference strength involved in this invention is determined by the interference model constructed in step S1. The Laplace transforms of interferences I and I′ are:

[0139]

[0140]

[0141] Based on transmission waiting delay Single-hop transmission delay Time slot alignment delay T a And the execution latency T of the NR side crosslink higher-layer protocol stackh This invention can analytically provide the total delay T for cross-regional single-hop transmission. c The total delay T for single-hop transmission in mode 1 within the region 1 Total latency T for single-hop transmission in mode 2 within the region 2 :

[0142]

[0143]

[0144]

[0145] Based on the aforementioned cross-regional single-hop transmission total delay T c The total delay T for single-hop transmission in mode 1 within the region 1 Total latency T for single-hop transmission in mode 2 within the region 2 This invention can further analytically provide the total delay of single-hop transmission on the NR side of the cross link:

[0146] T k =(1-)T c +[(1-)T 1 +T 2 ]

[0147] Total delay T based on NR sidelink single-hop transmission k The maximum number of transmission hops K is:

[0148]

[0149] Among them, T max This represents the maximum lifespan of the DENM.

[0150] Based on the maximum transmission hop count K of the NR-side cross-link multi-hop relay, the end-to-end transmission probability of the DEMM's NR-side cross-link multi-hop relay can be analyzed as:

[0151] S tot =[S c +(1-)S 1 +S 2 ] K

[0152] The S c The probability of successful cross-regional NR side cross-link single-hop transmission, S 1 To determine the probability of successful single-hop transmission in NR-side crosslink mode 1 within the region, S 2 The probability of a successful single-hop transmission in NR-side mode 2 within the region can be analyzed as follows:

[0153]

[0154]

[0155]

[0156] in, As a replacement variable, β is the threshold for the information-to-dryness ratio in the probability of successful transmission. and The Laplace transforms of the interference I and I′ are determined by the interference model constructed in step S1.

[0157] The Laplace transforms of disturbances I and I′ are:

[0158]

[0159]

[0160] Based on the maximum transmission hop count K of the NR-side crosslink multi-hop relay, the transmission distance of the DEMM's NR-side crosslink multi-hop relay can be resolved as:

[0161]

[0162] Formulas (1) and (2) above constitute a performance analysis theoretical framework for multi-hop relay on the NR side in vehicle networking provided by this invention.

[0163] After obtaining the performance analysis theoretical framework for NR-side multi-hop relay in vehicle-to-everything (V2X) networks in step S2, it is necessary to first verify the correctness of the framework.

[0164] The following description corresponds to step S3 of the proposed technical solution: verifying the correctness of the performance analysis framework based on the Monte Carlo experimental method.

[0165] This invention provides a feasible Monte Carlo experiment method. In each round of the Monte Carlo experiment, the positions of the RSU and UE are randomly generated within an area of ​​5×5 square kilometers according to the Poisson point process Φ and Φ′ described in step S1. Independent and identically distributed fading coefficients h are randomly generated for each transmit sub-channel or interfering sub-channel according to an exponential distribution with a mean of μ. In each round of the Monte Carlo experiment, the received SINR of the receiving RSU and the distance between two adjacent RSUs can be calculated. By comparing the received SINR with a threshold β, the ratio of successful rounds to total rounds is obtained, which is a simulation result of the single-hop propagation probability. The simulation result of the single-hop propagation distance can be obtained from the average distance between two adjacent RSUs.

[0166] like Figure 6A and Figure 6BAs shown, continuous lines represent the theoretical analysis results of each performance, i.e. the results calculated according to step S2, while discrete points represent the Monte Carlo simulation results of each performance.

[0167] like Figure 6A and Figure 6B As shown, the close matching between the simulation results and the theoretical analysis results indicates that the performance analysis framework proposed in this invention for NR-side traveling link multi-hop relay in vehicle networking can effectively describe the transmission process of the typical DENM through NR-side traveling link multi-hop relay.

[0168] Based on the correct performance analysis framework verified by the S3 steps, this invention can formulate the multi-hop relay transmission of the NR side in the Internet of Vehicles into a solvable mathematical optimization problem based on optimization theory.

[0169] The following description corresponds to step S4 of the proposed technical solution: Based on the verified performance analysis framework, the multi-hop relay transmission process of the NR side link is formalized as a mixed integer linear programming problem with multiple constraints and multiple objectives.

[0170] The following section will combine optimization problems and algorithms to present a performance optimization method for NR-side traveling link multi-hop relay in vehicle-to-everything (V2X) networks, provided by this invention.

[0171] The optimization problem (3) is as follows:

[0172]

[0173] stT max >0

[0174] Transmission performance requirements:

[0175] 0≤ρ≤1,

[0176] 0<ω≤1,

[0177] m∈m sub ,

[0178] In optimization problem (3), F is the objective function. These are constraints on performance metrics. If the objective of this invention is to maximize the end-to-end transmission probability of DENM, then F = S tot That is, formula (1) given in step S2, and If the objective of this invention is to maximize the DENM transmission distance, then F = D tot That is, the formula given in step S2, and D req and S req These are the performance requirements for the two scenarios mentioned above.

[0179] The mode 2 selection probability for NR-side link transmission needs to satisfy: 0 ≤ ρ ≤ 1; the transmission power compensation factor for the transmitting RSU needs to satisfy: 0 < ≤ 1; m sub A subset of the subchannel sizes specified by 3GPP, i.e. And m sub The elements in the middle need to satisfy the requirement of the number of PRBs (n, N) in each resource pool. z N c Requirements. For example, given n = 36PRB, N z -n=46PRB、N c =100PRB, then m sub ={10,12,15,20,25}.

[0180] Optimization problem (3) is a mixed-integer linear programming problem. In this invention, to solve the mixed-integer linear programming problem for performance optimization of multi-hop relays on the NR side, the particle swarm optimization algorithm as described in Table I is used to solve the problem.

[0181] As described in step 13 of the algorithm in Table I, the u-th particle needs to update its position based on its position in generation τ-1 during the τ-th iteration. Specifically, the position of the u-th particle in generation τ is:

[0182]

[0183] in, Let u be the velocity vector of the u-th particle in the τ-th generation, which can be calculated by the following formula:

[0184]

[0185] Where w is the relation factor of the iteration, Let be the velocity vector of the u-th particle in the (τ-1)th generation, and rand1 and rand2 be two arbitrary random numbers in the range of 0 to 1. For the u-th particle's own historical best position, This represents the globally optimal position in the history of all particles. In the algorithm shown in Table I, the symbol... and The meaning is the same as above.

[0186] As described in step 2 of the algorithm in Table I, this invention divides the integer variable m into length(m sub ) clusters, and use m po Indicates the subset m corresponding to variable m during this round of optimization. subThe specific numerical value in the subset. Here, the function length(·) can give the number of elements contained in the subset. Using the method in step 2, a swarm of particles with a total number of U can be independently searched under different values ​​of variable m, until m... po Traverse the entire subset m sub Because length(m) sub Since the computational complexity is ≤8, the algorithm proposed in this invention has a low computational complexity.

[0187] During initialization, to ensure optimal network parameters {ρ} * ,ω * ,m * To satisfy all the constraints in optimization problem (3), as described in steps 5-8 of the algorithm in Table I, it is necessary to initialize a position that meets the requirements for each particle.

[0188] During the iteration process, to ensure the optimal network parameters {ρ} * ,ω * ,m * The constraints in optimization problem (3) are satisfied, as described in steps 14-16 of the algorithm in Table I. By assigning a penalty of -1, each particle is guaranteed to meet the requirements.

[0189] Table I:

[0190]

[0191] Based on the optimization problem proposed in step S4 and its corresponding solution, this invention will calculate and provide the optimal performance and corresponding optimal parameters for multi-hop relay transmission on the NR side in vehicle-to-everything (V2X) networks.

[0192] The following describes step S5 of the proposed technical solution: Given the critical message transmission distance (or end-to-end transmission probability) and lifecycle, the particle swarm optimization algorithm is used to solve for the optimal end-to-end transmission probability (or transmission distance), and the corresponding network parameters {ρ} under optimal performance are given. * ,ω * ,m *}, where ρ * The proportion of RSUs selected for optimal performance in operating mode 2, ω * The RSU transmit power compensation factor under optimal performance, m * Select the size of the transmission subchannel for RSU to achieve optimal performance.

[0193] The theoretical analysis and simulation results of this invention are presented simultaneously, and the effectiveness of the performance analysis and optimization provided by this invention is verified by combining the theoretical analysis and simulation results. Unless otherwise stated, the parameters involved in other simulation experiments are as follows:

[0194] The subcarrier spacing of the NR network is 15kHz, the corresponding subcarrier spacing configuration factor η = 0, and the bandwidth B of each PRB. PRB =180kHz. Region half-side length A = 0.025km, road width W = 0.01km, number of PRBs in each region's resource pool N z =100, Number of PRBs in cross-regional public resource pools N c =84. The number of PRBs reserved for NR side downlink mode 2 and NR uplink in each region is n=36.

[0195] RSU maximum transmit power P max =26dBm, RSU nominal transmit power P0 = -26dBm, expected value of fading coefficient μ = 1, path loss index α = 4, additable white Gaussian noise power σ 2 =1dBm, SINR threshold β = -20dB in successful transmission probability, RUS distribution intensity λ = 50RSUs / km.

[0196] The uplink transmission UE transmit power P′=26dBm, the number of uplink transmission UE subchannel PRBs m′=16, and the uplink transmission UE distribution intensity λ′=500UEs / km.

[0197] Execution latency T of the NR side-link higher layer protocol stack h =1.5ms, RRC connection time ΔT w =2ms. DENM message size Ω = 1000 Bytes, DENM lifecycle T max =100ms.

[0198] The total number of examples in the particle swarm optimization algorithm is U = 50, and the total number of iterations is τ. max =100, inertia factor w=0.5.

[0199] In the simulation experiment, the present invention uses 5×10 4 The average value of several independent Monte Carlo experiments was used as the simulation result.

[0200] Figure 6A The DENM single-hop propagation probability S and its components {S} are shown. c ,S 1 ,S 2 The variation of RSU distribution intensity λ.

[0201] Figure 6B The end-to-end propagation probability S of DENM multi-hop is shown. tot Total transmission distance D tot The variation of RSU distribution intensity λ.

[0202] like Figure 7 As shown, the dashed line illustrates the end-to-end DENM transmission probability S of the NR-side multi-hop relay in this invention. tot The solid line illustrates the variation of the power compensation factor ω with the total transmission distance D of the NR-side multi-hop relay in this invention. tot The effect of power compensation factor ω. From Figure 7 It can be seen that the two performance indicators S involved in this invention tot and D tot Both increase as ω increases.

[0203] Therefore, in this invention, we preferably use ω = 1 as the optimal RSU transmit power compensation factor ω under optimal performance. * .

[0204] Figure 8A This demonstrates a performance optimization method for NR-side multi-hop relay in vehicular networks based on the present invention, under given performance requirements. At km, the optimal end-to-end DENM transmission probability The transformation and optimal network parameters {ρ * ,m * Settings.

[0205] Figure 8B This demonstrates a performance optimization method for NR-side multi-hop relay in vehicular networks based on the present invention, under given performance requirements. At that time, the optimal total transmission distance The transformation and optimal network parameters {ρ * ,m * Settings.

[0206] Depend on Figure 8A and Figure 8B It can be seen that the performance analysis and optimization method for NR-side multi-hop relay in vehicle-to-everything (V2X) proposed in this invention can optimize the target performance by adjusting network parameters ρ and m under the constraints, and analytically give the values ​​of the corresponding network parameters.

[0207] In another embodiment of the present invention, a system for optimizing the performance of NR-side multi-hop relays in a vehicle-to-everything (V2X) network is provided. This system can be used to implement the aforementioned method for optimizing the performance of NR-side multi-hop relays in a V2X network. Specifically, the system includes:

[0208] The model building module is used to build a system model of key messages in the NR side crosslink multi-hop relay scenario based on the real NR side crosslink multi-hop relay scenario;

[0209] The performance analysis framework building module is used to build a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles, and to analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages.

[0210] The verification module is used to calculate the average performance results under multi-round random transmission scenarios based on the system model, and to verify the correctness of the performance analysis framework.

[0211] The planning problem construction module is used to formulate the NR-side multi-hop relay transmission process as a multi-constraint, multi-objective mixed integer linear programming problem based on the validated performance analysis framework.

[0212] The output module is used to solve mixed-integer linear programming problems given key message delivery distances or end-to-end delivery probabilities and lifecycles, and output the corresponding network parameters under optimal performance.

[0213] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0214] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of a method for optimizing the performance of multi-hop relays on the NR side in a vehicle-to-everything (V2X) network.

[0215] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the above embodiment regarding a method for optimizing the performance of multi-hop relays on the NR side in a vehicle-to-everything (V2X) network.

[0216] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0217] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0218] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0219] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0220] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing the performance of multi-hop relays on the NR side in vehicle-to-everything (V2X) networks, characterized in that, include: Based on real-world NR-side multi-hop relay scenarios, a system model for critical messages in NR-side multi-hop relay scenarios is established. Construct a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles, and analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages; Based on the system model, the average performance results under multi-round random transmission scenarios are calculated to verify the correctness of the performance analysis framework; Based on the validated performance analysis framework, the multi-hop relay transmission process of the NR side link is formalized as a mixed integer linear programming problem with multiple constraints and multiple objectives. Given the critical message delivery distance or end-to-end delivery probability and lifecycle, solve the mixed-integer linear programming problem and output the corresponding network parameters with optimal performance.

2. The method of claim 1, wherein, The system model is as follows: Based on real-world NR-side multi-hop relay scenarios, we define the RSU spatial distribution model, resource allocation model, interference model, and traffic model for critical messages passing through NR-side multi-hop relay scenarios. 3.The method of claim 1, wherein, Analysis of the multi-hop delivery probability, multi-hop transmission time, and total propagation distance of key messages: Based on the system model, the average transmission rate, transmission delay, and maximum number of transmission hops of key messages in the multi-hop relay scenario of the NR side are derived using the stochastic geometric method. Furthermore, analytical formulas for transmission distance and end-to-end transmission probability are derived. The analytical formulas for transmission distance and end-to-end transmission probability together constitute the performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles.

4. The method of claim 1, wherein, Verify the correctness of the performance analysis framework: Based on the given system model, transmission scenarios are randomly generated through Monte Carlo experiments, and the average performance results under multiple rounds of random transmission scenarios are calculated and compared with the performance analysis deterministic calculation results. If the experimental results and the calculation results match, then the performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles is correct.

5. The method of claim 1, wherein, Mixed-integer linear programming problem: Based on the maximum lifespan of critical messages, transmission distance requirements, end-to-end transmission probability requirements, and the range of parameter selection for NR-side multi-hop relay networks, an optimization problem with multiple constraints is presented. This optimization problem takes end-to-end transmission probability or transmission distance as the optimization objective and the selection of NR-side multi-hop relay network parameters {ρ,ω,m} as optimization variables.

6. The method of claim 1, wherein, Output the network parameters corresponding to the optimal performance: Given the critical message delivery distance or end-to-end delivery probability and lifetime, the particle swarm optimization algorithm is used to solve for the optimal end-to-end delivery probability or delivery distance, and the corresponding network parameters {ρ} under optimal performance are given. * ,ω * ,m * }, where ρ * The proportion of RSUs selected for optimal performance in operating mode 2, ω * The RSU transmit power compensation factor under optimal performance, m * To select the size of the transmission subchannel for RSU with optimal performance, the particle swarm optimization algorithm is proposed based on a given multi-constraint, multi-objective mixed integer linear programming problem. The corresponding network parameters {ρ} for optimal performance are also given. * ,ω * ,m * } 7. The method of Claim 6, wherein, The overall working modes include Mode 1 and Mode 2. In Mode 1, the NR side walkway is centrally managed by the RRC connection between the base station and the RSU. In Mode 2, the RSUs on the NR side walkway autonomously select transmission resources from the resource pool. The proportion of RSUs selecting Mode 2 is ρ, and the proportion selecting Mode 1 is 1-ρ.

8. A system for optimizing the performance of multi-hop relays on the NR side in a vehicle-to-everything (V2X) network, characterized in that, include: The model building module is used to build a system model of key messages in the NR side crosslink multi-hop relay scenario based on the real NR side crosslink multi-hop relay scenario; The performance analysis framework building module is used to build a performance analysis framework for multi-hop transmission of key messages in the Internet of Vehicles, and to analyze the multi-hop transmission probability, multi-hop transmission time and total propagation distance of key messages. The verification module is used to calculate the average performance results under multi-round random transmission scenarios based on the system model, and to verify the correctness of the performance analysis framework. The planning problem construction module is used to formulate the NR-side multi-hop relay transmission process as a multi-constraint, multi-objective mixed integer linear programming problem based on the validated performance analysis framework. The output module is used to solve mixed-integer linear programming problems given key message delivery distances or end-to-end delivery probabilities and lifecycles, and output the corresponding network parameters with optimal performance.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the NR-side traveling link multi-hop relay performance optimization method in a vehicle network as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. When the computer program is executed by the processor, it implements the steps of the NR-side traveling link multi-hop relay performance optimization method in a vehicle network as described in any one of claims 1 to 7.

Images