An efficient power allocation method in connected vehicles

Abstract

The present invention discloses an efficient power allocation method in a vehicle network. The method comprises the following steps: step 1, channel information acquisition and beamforming; step 2, RSU power allocation; step 3, signal transmission; step 4, performance calculation. The beneficial effect of the present invention is that it not only comprehensively solves the total transmission power constraint and the maximum vehicle limit of the vehicle, but also solves the fairness problem between vehicles; by minimizing the ratio of the maximum RSU transmission power consumption to the vehicle speed and proposing the optimal transmission power and vehicle speed allocation scheme, the power consumption of the system is reduced while ensuring fairness between users, which can reduce the transmission power of the vehicle network and improve traffic efficiency.

Description

Technical Field

[0001] The present invention belongs to the fields of vehicle networking, large-scale multiple-input multiple-output (MIMO) technology, and power allocation technology, and in particular to an efficient power allocation method in vehicle networking. Background Art

[0002] The current vehicle networking technology, massive MIMO technology, and the concept of location-related business information in the vehicle networking are introduced as follows. With the progress of social and economic development, the number of vehicles is increasing, leading to many problems such as increased traffic accidents and traffic congestion. In order to solve these problems, the intelligent traffic management system based on the vehicle networking came into being. The vehicle networking interconnects vehicles with everything (vehicles, roads, pedestrians, and the Internet, etc.), intelligently manages traffic and vehicles, and provides dynamic information for drivers. As the core of intelligent transportation, the vehicle networking technology occupies an increasingly large proportion in the automobile and transportation industries. The vehicle networking uses wireless communication technology for data transmission, and can complete the real-time transmission of business data and real-time monitoring and control of vehicles in the network under the control of the server. The vehicle networking is a special branch of the Internet of Things application, and communication technology is an important application in the vehicle networking. V2X communication is the process of information exchange between vehicles and various elements of the intelligent transportation system. V2X communication includes: vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrian (V2P) and vehicle to network (V2N).

[0003] In order to improve the spectrum utilization of the system, 5G adopts a key physical layer technology, namely massive antenna technology or massive MIMO technology. Massive MIMO technology refers to the use of a large number of antennas in the base station, establishing multiple communication links between the transmitter and the receiver, and serving multiple users on the same time and frequency resources. The application of massive MIMO can significantly improve the spectrum efficiency and communication capabilities of the system. Massive MIMO technology has the following advantages: ① Improved the average throughput of the cell; ② Reduced interference to surrounding base stations; ③ Improved the average throughput of vehicles at the edge of the cell; ④ Improved the reliability of communication; ⑤ The deployment of massive MIMO base stations can support space division multiple access technology, so massive MIMO technology can increase capacity by 10 times or more through simple signal processing, and can also improve energy efficiency by 100 times.

[0004] The invention patent application with application number CN201811289008.9 discloses a method and device for power allocation, including: when a network device determines to be connected to a first PSE, determining the power allocation mode of the first PSE; if the power allocation mode of the first PSE is dynamic allocation, and the applied power of the first PSE exceeds the idle power that can be allocated by the network device, then allocating idle power to the first PSE; if the power allocation mode of the first PSE is static allocation, and the original power of the first PSE exceeds the idle power that can be allocated by the network device, then obtaining a first preempted power and allocating the original power to the first PSE, the original power being the sum of the idle power and the first preempted power.

[0005] Therefore, in the Internet of Vehicles system, in order to improve the traffic efficiency of the city, ensure the normal operation of autonomous driving vehicles, and avoid accidents such as traffic congestion and vehicle collisions, a large amount of information needs to be transmitted and exchanged in real time between vehicles and the infrastructure of the Internet of Vehicles. Among them, location-related business information is indispensable, which includes the real-time positioning information of the vehicle and the high-precision map information required for the vehicle's autonomous driving. These location-related business information has the characteristics of large data volume, delay sensitivity, and real-time update, which will cause a large amount of energy consumption, bringing huge challenges to the communication transmission of the Internet of Vehicles with limited communication resources. In addition, the transmission rate required for location-related business information is positively correlated with the speed of the vehicle. The higher the speed of the vehicle, the higher the transmission rate of the required information, otherwise the normal driving of the vehicle cannot be guaranteed. The existing technologies for the transmission of business information of the Internet of Vehicles do not take into account the relationship between the location-related business information required by the vehicle and the vehicle speed. Therefore, the technical problems of how to efficiently transmit location-related business information in the Internet of Vehicles, reduce system power consumption, improve traffic efficiency, and take into account the individual differences of the information required by the vehicle in the power allocation scheme need to be solved urgently. Summary of the invention

[0006] The object of the present invention is to provide an efficient power distribution method in a connected vehicle network that can overcome the above-mentioned technical problems.

[0007] The method of the present invention comprises the following steps:

[0008] Step 1: Channel information acquisition and beamforming:

[0009] Step 1.1, the information transmitter, namely the Road Side Unit (RSU), is set at the center of the intersection. Each vehicle is equipped with a signal receiving device, referred to as the On Board Unit (OBU). The RSU communicates with the OBUs of multiple vehicles simultaneously in the bandwidth range B. The coverage range is L meters. It is assumed that the RSU has a total of M transmitting antennas, and each vehicle is equipped with a receiving antenna. The channel vector from the M antennas to vehicle k is expressed as in, φ is the antenna gain constant, ε k is shadow fading and 10log 10 ε k It has a mean of zero and a variance of Gaussian distribution, d k is the distance between vehicle k and RSU, α is the path loss exponent; h km It is a small-scale fading and independently follows a complex Gaussian distribution with a mean of 0 and a variance of 1;

[0010] Step 1.2: RSU estimates the channel information from all vehicles to RSU based on the orthogonal pilot information sent by the user. The channel information includes large-scale fading and small-scale fading. RSU allocates power to all users based on the channel information. The total transmission power is constant and there are multiple users. RSU uses the obtained optimal transmission power to send location-related service information to the user and control the speed of the vehicle at the same time. The power-speed ratio is introduced for optimization to jointly optimize communication power consumption and traffic efficiency, as shown in the following formula (1):

[0011]

[0012] In formula (1), p Tk is the transmission power allocated by RSU to vehicle k, p Rk is the circuit power consumed by vehicle k after receiving the information, p C is the circuit power consumed by the RSU when sending information to vehicle k, v k is the speed of vehicle k;

[0013] Step 1.3: Obtain RSU channel information. The base station estimates the channel g from user k to RSU based on the pilot information transmitted by the user. k , (k=1,2,…,K) and using the channel reciprocity of the time division duplex system, the channel vector from RSU to user k is

[0014] Step 1.4, beamforming, RSU uses matched filter beamforming, that is, the beamforming vector of vehicle k is represented as w k =g k / ||g k ||;

[0015] Step 2, RSU power allocation:

[0016] Step 2.1, calculate the optimal power allocation scheme for a single vehicle:

[0017] In the case of a single vehicle, the power-speed ratio is related to the vehicle speed v k The relationship between is shown in the following formula (2):

[0018]

[0019] In formula (2), N0 is the power spectrum density of Gaussian white noise, B is the system bandwidth, m is the amount of information required by the vehicle for location-related service information, power-to-speed ratio and transmission power p Tk The relationship between is shown in the following formula (3):

[0020]

[0021] Let dη / dv k =0, the theoretical optimal speed and power for a single vehicle are shown in the following formulas (4) and (5):

[0022]

[0023]

[0024] Where W0 is the Lambert W function;

[0025] The theoretical optimal speed and power The maximum power p allowed by a bicycle in practice M and the maximum rate v M Compare and get the actual optimal speed of the vehicle and power This includes the following three situations:

[0026] when is the optimal power and Then the actual optimal transmission power and speed of vehicle k are shown in the following formula (6):

[0027]

[0028]

[0029] when For optimal power Then the actual optimal transmission power and speed of vehicle k are shown in the following formula (7):

[0030]

[0031]

[0032] when The optimal power can only take the maximum transmission power. The actual optimal transmission power and speed of vehicle k are as follows:

[0033] Formula (8) shows:

[0034]

[0035]

[0036] Step 2.2, calculate the optimal power allocation scheme for multiple vehicles:

[0037] The actual optimal power of the bicycle calculated in step 2.1 The sum is added and compared with the total transmission power p M The comparison includes the following steps:

[0038] Step 2.2.1: When the sum of the optimal transmission powers is less than or equal to the total transmission power, It means that all vehicles can obtain the optimal power. At this time, the power and speed allocated to vehicle k are shown in the following formula (9):

[0039]

[0040]

[0041] Step 2.2.2, when the sum of the optimal transmission power is greater than the total transmission power Indicates that not all vehicles can obtain the optimal transmission power, then the following calculation is performed:

[0042] The optimal vehicle power obtained in step 2.2.1 and optimal speed Substituting into the power-speed ratio definition formula (1), the optimal power-speed ratio for each vehicle is obtained: The maximum value of the optimal power-speed ratio in the vehicle is calculated as shown in the following formula (10):

[0043]

[0044] The functional relationship between the transmission power and the power-speed ratio is shown in the following formula (11):

[0045]

[0046] Formula (11) is simplified to the following formula (12):

[0047] p Tk =f k (η k )……(12),

[0048] Let the power speed ratio of each vehicle be equal to Then the transmission power of vehicle k is as shown in the following formula (13):

[0049]

[0050] The vehicle's transmission power The sum is added to the total transmission power p M The comparison includes the following steps:

[0051] Step 2.2.2.1, when the transmission power The sum is less than the total transmission power. It shows that some vehicles can be allocated the optimal transmission power. First, the vehicles are allocated according to the optimal power-speed ratio. Sort them in descending order, and then calculate the number of vehicles J with the optimal transmission power and the power-speed ratio η of the remaining KJ vehicles according to the following steps:

[0052] Step a) Initialization, the power-speed ratio has a lower bound of η1, an upper bound of η2, and an algorithm accuracy of e;

[0053] Step b) i=2,

[0054] Step c)

[0055] Step d) When Then i=i+1, continue step c); when

[0056] Then J=i-1, continue with step e);

[0057] Step e) Let η3 = (η1 + η2) / 2,

[0058] Step f) When Then let η1=η3; when Then let η2 = η3;

[0059] Step g) When η1-η2>e, continue with steps e) and f); when η1-η2<e, then η=(η1+η2) / 2, J=i-1;

[0060] Then the transmission power and driving speed allocated to vehicle k are shown in the following formulas (14) and (15):

[0061]

[0062]

[0063] Step 2.2.2.2, when the transmission power The sum is greater than the total transmission power. This means that all vehicles cannot be allocated the optimal transmission power. In the current situation, the power-speed ratio of all vehicles is equal. Solving the power-speed ratio of the vehicle specifically includes the following steps:

[0064] Step 2.2.2.2.1, initialization: the lower bound of the power-speed ratio is η1, the upper bound is η2, and the algorithm accuracy is e;

[0065] Step 2.2.2.2.2, let η3 = (η1 + η2) / 2,

[0066] Step 2.2.2.2.3, when Then let η1=η3; when Then let η2 = η3;

[0067] Step 2.2.2.2.4, when η2-η1>e, continue with steps 2.2.2.2.2 and 2.2.2.2.3; when η2-η1≤e, then η=(η1+η2) / 2;

[0068] Then the transmission power and driving speed allocated to vehicle k are shown in the following formulas (16) and (17):

[0069] p Tk =f k (η)……(16),

[0070]

[0071] Step 3, signal transmission;

[0072] RSU sends high-precision map information to all vehicles, and the signal received by user k is shown in the following formula (18):

[0073]

[0074] Among them, p Tk is the transmission power allocated by RSU to vehicle k, s k is the location-related service information sent by the RSU to vehicle k and |s k |=1,n k is the received Gaussian white noise of the kth vehicle, and obeys a complex Gaussian distribution with a mean of 0 and a variance of N0B;

[0075] Step 4, performance calculation;

[0076] When all vehicles obtain the optimal transmission power p Tk and the optimal speed v k When , the power-speed ratio of vehicle k under the efficient power allocation scheme is as shown in the following formula (19):

[0077]

[0078] The method of the present invention has the following beneficial effects:

[0079] 1. The method of the present invention considers the scenario where an RSU at a city intersection sends location-related service information to multiple vehicles within the coverage area. The RSU uses the estimated channel information and matched filter beamforming to send information to the vehicle. After beamforming, the method minimizes the ratio of the maximum RSU transmission power consumption to the vehicle speed and proposes an optimal transmission power and vehicle speed allocation scheme, thereby reducing the power consumption of the system and improving traffic efficiency while ensuring fairness among users.

[0080] 2. The method of the present invention proposes an efficient power allocation scheme in the Internet of Vehicles. The RSU obtains the channel information between the vehicle user and forms a beam with the information required by the user through a matched filter beamforming algorithm; the RSU calculates the optimal power and optimal speed of each vehicle according to the maximum value of the ratio of power consumption to vehicle speed when minimizing the transmission of location-related service information, and proposes three transmission schemes in combination with the limitation of the total transmission power of the RSU. Therefore, the method of the present invention not only comprehensively solves the total transmission power constraint and the limitation of the maximum number of vehicles, but also solves the fairness problem between vehicles;

[0081] 3. In the method described in the present invention, the base station estimates the channel matrix from the base station to the user according to the pilot information sent by the user. The base station forms a beam with the location-related service information required by the user through a matched filter beamforming algorithm, and distributes power to different vehicles. In order to comprehensively measure the power consumption and traffic efficiency of the vehicle system, the method described in the present invention introduces a new metric, namely, the power-speed ratio. The base station first calculates the optimal transmission power and optimal speed of each vehicle, and then based on the optimal power allocation of each vehicle, the total power constraint of multiple workshops, and the fairness problem between vehicles, three power allocation schemes are introduced. According to the transmission power, the base station sends the location-related service information required by the vehicle to the vehicle user;

[0082] 4. The method described in the present invention uses vehicle speed to measure traffic efficiency and introduces the concept of power-speed ratio, that is, a new measurement parameter "power-speed ratio" is introduced, and the ratio of transmission power consumption to vehicle speed is used as the target for power allocation, thereby jointly optimizing the consumption of communication resources and traffic efficiency; at the same time, the method described in the present invention introduces three power allocation schemes for the constraints of total transmission power in different situations. The three power allocation schemes of the method described in the present invention fully consider the constraints of total transmission power and measure the contradiction between system power consumption and traffic efficiency. Under the premise of ensuring the fairness of power acquisition among different users, it can not only reduce the transmission power of the Internet of Vehicles, but also improve traffic efficiency. The algorithm proposed by the method described in the present invention has good effect and stability in terms of the number of vehicles, RSU coverage distance and total transmission power that is too large or too small. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 It is a schematic diagram of the process of the method of the present invention. DETAILED DESCRIPTION

[0084] The following describes the embodiments of the present invention in detail with reference to the accompanying drawings. Figure 1 As shown, the method of the present invention comprises the following steps:

[0085] Step 1: Channel information acquisition and beamforming:

[0086] Step 1.1, the information transmitter, namely the Road Side Unit (RSU), is set at the center of the intersection. Each vehicle is equipped with a signal receiving device, referred to as the On Board Unit (OBU). The RSU communicates with the OBUs of multiple vehicles simultaneously in the bandwidth range B. The coverage range is L meters. It is assumed that the RSU has a total of M transmitting antennas, and each vehicle is equipped with a receiving antenna. The channel vector from the M antennas to vehicle k is expressed as in, φ is the antenna gain constant, ε k is shadow fading and 10log 10 ε k It has a mean of zero and a variance of Gaussian distribution, d k is the distance between vehicle k and RSU, α is the path loss exponent; h km It is a small-scale fading and independently follows a complex Gaussian distribution with a mean of 0 and a variance of 1;

[0087] Step 1.2, RSU estimates the channel information from all vehicles to RSU based on the orthogonal pilot information sent by the user. The channel information includes large-scale fading and small-scale fading. RSU allocates power to all users based on the channel information. The total transmission power is certain and there are multiple users. RSU uses the obtained optimal transmission power to send location-related service information to the user and control the speed of the vehicle at the same time. The power-speed ratio is introduced for optimization to jointly optimize communication power consumption and traffic efficiency, as shown in the following formula (1):

[0088]

[0089] In formula (1), p Tk is the transmission power allocated by RSU to vehicle k, p Rk is the circuit power consumed by vehicle k after receiving the information, p C is the circuit power consumed by the RSU when sending information to vehicle k, v k is the speed of vehicle k;

[0090] Step 1.3: Obtain RSU channel information. The base station estimates the channel g from user k to RSU based on the pilot information transmitted by the user. k , (k=1,2,…,K) and using the channel reciprocity of the time division duplex system, the channel vector from RSU to user k is

[0091] Step 1.4, beamforming, RSU uses matched filter beamforming, that is, the beamforming vector of vehicle k is represented as w k =g k / ||g k ||;

[0092] Step 2, RSU power allocation:

[0093] Step 2.1, calculate the optimal power allocation scheme for a single vehicle;

[0094] In the case of a single vehicle, the power-speed ratio is related to the vehicle speed v k The relationship between is shown in the following formula (2):

[0095]

[0096] In formula (2), N0 is the power spectrum density of Gaussian white noise, B is the system bandwidth, m is the amount of information required by the vehicle for location-related service information, power-to-speed ratio and transmission power p Tk The relationship between is shown in the following formula (3):

[0097]

[0098] Let dη / dv k =0, the theoretical optimal speed and power for a single vehicle are shown in the following formulas (4) and (5):

[0099]

[0100]

[0101] Where W0 is the Lambert W function;

[0102] The theoretical optimal speed and power The maximum power p allowed by a bicycle in practice M and the maximum rate v M Compare and get the actual optimal speed of the vehicle and power This includes the following three situations:

[0103] Step 2.1.1, when is the optimal power and The actual optimal transmission power and speed of vehicle k are as follows:

[0104] The following formula (6) shows:

[0105]

[0106]

[0107] Step 2.1.2, when For optimal power The actual optimal transmission power and speed of vehicle k are as follows:

[0108] The following formula (7) shows:

[0109]

[0110]

[0111] Step 2.1.3, when The optimal power can only take the maximum transmission power, and the actual optimal transmission power of vehicle k and

[0112] The speed is shown in the following formula (8):

[0113]

[0114]

[0115] Step 2.2, calculating the optimal power allocation scheme for multiple vehicles;

[0116] The actual optimal power of the bicycle calculated in step 2.1 The sum is added and compared with the total transmission power p M The comparison includes the following steps:

[0117] Step 2.2.1: When the sum of the optimal transmission powers is less than or equal to the total transmission power, This means that all vehicles can obtain the optimal power. At this time, the power and speed allocated to vehicle k are shown in the following formula (9):

[0118]

[0119]

[0120] Step 2.2.2, when the sum of the optimal transmission power is greater than the total transmission power This means that not all vehicles can obtain the optimal transmission power, so the following calculation is performed:

[0121] The optimal vehicle power obtained in step 2.2.1 and optimal speed Substituting into the power-speed ratio definition formula (1), the optimal power-speed ratio for each vehicle is obtained: The maximum value of the optimal power-speed ratio in the vehicle is calculated as shown in the following formula (10):

[0122]

[0123] The functional relationship between the transmission power and the power-speed ratio is shown in the following formula (11):

[0124]

[0125] Formula (11) is simplified to the following formula (12):

[0126] p Tk =f k (η k )……(12),

[0127] Let the power speed ratio of each vehicle be equal to Then the transmission power of vehicle k is as shown in the following formula (13):

[0128]

[0129] The vehicle's transmission power The sum is added to the total transmission power p M The comparison includes the following steps:

[0130] Step 2.2.2.1, when the transmission power The sum is less than the total transmission power. It shows that some vehicles can be allocated the optimal transmission power. First, the vehicles are allocated according to the optimal power-speed ratio. Sort them in descending order, and then calculate the number of vehicles J with the optimal transmission power and the power-speed ratio η of the remaining KJ vehicles according to the following steps:

[0131] Step a) Initialization, the power-speed ratio has a lower bound of η1, an upper bound of η2, and an algorithm accuracy of e;

[0132] Step b) i=2,

[0133] Step c)

[0134] Step d) When Then i=i+1, continue step c); when

[0135] Then J=i-1, continue with step e);

[0136] Step e) Let η3 = (η1 + η2) / 2,

[0137] Step f) When Then let η1=η3; when Then let η2 = η3;

[0138] Step g) When η1-η2>e, continue with steps e) and f); when η1-η2<e, then η=(η1+η2) / 2, J=i-1;

[0139] Then the transmission power and driving speed allocated to vehicle k are shown in the following formulas (14) and (15):

[0140]

[0141]

[0142] Step 2.2.2.2, when the transmission power The sum is greater than the total transmission power. This means that all vehicles cannot be allocated the optimal transmission power. In the current situation, the power-speed ratio of all vehicles is equal. Solving the power-speed ratio of the vehicle specifically includes the following steps:

[0143] Step 2.2.2.2.1, initialization: the lower bound of the power-speed ratio is η1, the upper bound is η2, and the algorithm accuracy is e;

[0144] Step 2.2.2.2.2, let η3 = (η1 + η2) / 2,

[0145] Step 2.2.2.2.3, when Then let η1=η3; when Then let η2 = η3;

[0146] Step 2.2.2.2.4, when η2-η1>e, continue with steps 2.2.2.2.2 and 2.2.2.2.3; when η2-η1≤e, then η=(η1+η2) / 2;

[0147] Then the transmission power and driving speed allocated to vehicle k are shown in the following formulas (16) and (17):

[0148] p Tk =f k (η)……(16),

[0149]

[0150] Step 3, signal transmission;

[0151] RSU sends high-precision map information to all vehicles, and the signal received by user k is shown in the following formula (18):

[0152]

[0153] Among them, p Tk is the transmission power allocated by RSU to vehicle k, s k is the location-related service information sent by the RSU to vehicle k and |s k |=1,n k is the received Gaussian white noise of the kth vehicle, and obeys a complex Gaussian distribution with a mean of 0 and a variance of N0B;

[0154] Step 4, performance calculation;

[0155] When all vehicles obtain the optimal transmission power p Tk and the optimal speed v k When , the power-speed ratio of vehicle k under the efficient power allocation scheme is as shown in the following formula (19):

[0156]

[0157] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the scope disclosed in the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A power distribution method in a vehicle network, characterized in that: The following steps are involved: Step 1: Channel information acquisition and beamforming: Step 1.1, the information transmitter, namely the roadside unit, is set at the center of the intersection. Each vehicle is equipped with a signal receiving device, referred to as the on-board unit. The RSU communicates with the OBUs of multiple vehicles simultaneously in the bandwidth range B. The coverage range is L meters. It is assumed that the RSU has a total of M transmitting antennas, and each vehicle is equipped with a receiving antenna. The channel vector from the M antennas to vehicle k is expressed as in, φ is the antenna gain constant, ε k is shadow fading and 10log 10 ε k It has a mean of zero and a variance of Gaussian distribution, d k is the distance between vehicle k and RSU, α is the path loss exponent; h km It is a small-scale fading and independently follows a complex Gaussian distribution with a mean of 0 and a variance of 1; Step 1.2: RSU estimates the channel information from all vehicles to RSU based on the orthogonal pilot information sent by the user. The channel information includes large-scale fading and small-scale fading. RSU allocates power to all users based on the channel information. The total transmission power p M If there are multiple users, the RSU uses the obtained optimal transmission power to send location-related service information to the user and control the speed of the vehicle at the same time. The power-speed ratio is introduced for optimization to jointly optimize communication power consumption and traffic efficiency, as shown in the following formula (1): In formula (1), p Tk is the transmission power allocated by RSU to vehicle k, p Rk is the circuit power consumed by vehicle k after receiving the information, p C is the circuit power consumed by the RSU when sending information to vehicle k, v k is the speed of vehicle k; Step 1.3: Obtain RSU channel information. The base station estimates the channel g from user k to RSU based on the pilot information transmitted by the user. k , k = 1, 2, ..., K and using the channel reciprocity of the time division duplex system, the channel vector from RSU to user k is Step 1.4, beamforming, RSU uses matched filter beamforming, that is, the beamforming vector of vehicle k is represented as w k =g k / ||g k ||; Step 2, RSU power allocation: Step 2.1, calculate the optimal power allocation scheme for a single vehicle; In the case of a single vehicle, the power-speed ratio is related to the vehicle speed v k The relationship between is shown in the following formula (2): In formula (2), N0 is the power spectrum density of Gaussian white noise, B is the system bandwidth, m is the amount of information required by the vehicle for location-related service information, power-to-speed ratio and transmission power p Tk The relationship between is shown in the following formula (3): Let dη / dv k =0, the theoretical optimal speed and power for a single vehicle are shown in the following formulas (4) and (5): Where W0 is the Lambert W function; The theoretical optimal speed and power The maximum transmission power p allowed by a single vehicle in practice Tkmax and the maximum rate v M Compare and get the actual optimal speed of the vehicle and power Step 2.1.1, when is the optimal power and Then the actual optimal transmission power and speed of vehicle k are shown in the following formula (6): Step 2.1.2, when For optimal power Then the actual optimal transmission power and speed of vehicle k are shown in the following formula (7): Step 2.1.3, when When , the optimal power can only take the maximum transmission power. The actual optimal transmission power and speed of vehicle k are shown in the following formula (8): Step 2.2, calculating the optimal power allocation scheme for multiple vehicles; The actual optimal power of the bicycle calculated in step 2.1 The sum is added and compared with the total transmission power p M For comparison: Step 2.2.1: When the optimal transmission power sum is less than or equal to the total transmission power p M Rate This means that all vehicles can obtain the optimal power. At this time, the power and speed allocated to vehicle k are shown in the following formula (9): Step 2.2.2, when the sum of the optimal transmission powers is greater than the total transmission power p M Right now This means that not all vehicles can obtain the optimal transmission power, so the following calculation is performed: The optimal vehicle power obtained in step 2.2.1 and optimal speed Substituting into the power-speed ratio definition formula (1), the optimal power-speed ratio for each vehicle is obtained: The maximum value of the optimal power-speed ratio in the vehicle is calculated as shown in the following formula (10): The functional relationship between the transmission power and the power-speed ratio is shown in the following formula (11): Formula (11) is simplified to the following formula (12): p Tk =f k (η k )……(12), Let the power speed ratio of each vehicle be equal to Then the transmission power of vehicle k is as shown in the following formula (13): The vehicle's transmission power The sum is added to the total transmission power p M For comparison: Step 2.2.2.1, when the transmission power The sum is less than the total transmission power p M Right now It shows that some vehicles can be allocated the optimal transmission power. First, the vehicles are allocated according to the optimal power-speed ratio. Sort them in descending order, and then calculate the number of vehicles J with the optimal transmission power and the power-speed ratio η of the remaining KJ vehicles according to the following steps: Step a) Initialization, the power-speed ratio has a lower bound of η1, an upper bound of η2, and an algorithm accuracy of e; Step b) i=2, Step c) Step d) When Then i=i+1, continue step c); when Then J=i-1, continue with step e); Step e) Let η3 = (η1 + η2) / 2, Step f) When Then let η1=η3; when Then let η2 = η3; Step g) When η1-η2>e, continue with steps e) and f); when η1-η2<e, then η=(η1+η2) / 2, J=i-1; Then the transmission power and driving speed allocated to vehicle k are shown in the following formulas (14) and (15): Step 2.2.2.2, when the transmission power The sum is greater than the total transmission power p M Right now This means that all vehicles cannot be allocated the optimal transmission power. In the current situation, the power-speed ratio of all vehicles is equal. Solving the power-speed ratio of the vehicle specifically includes the following steps: Step 2.2.2.2.1, initialization: the lower bound of the power-speed ratio is η1, the upper bound is η2, and the algorithm accuracy is e; Step 2.2.2.2.2, let η3 = (η1 + η2) / 2, Step 2.2.2.2.3, when Then let η1=η3; when Then let η2 = η3; Step 2.2.2.2.4, when η2-η1>e, continue with steps 2.2.2.2.2 and 2.2.2.2.3; when η2-η1≤e, Then η=(η1+η2) / 2; Then the transmission power and driving speed allocated to vehicle k are shown in the following formulas (16) and (17): p Tk =f k (η)……(16), Step 3, signal transmission; RSU sends high-precision map information to all vehicles, and the signal received by user k is shown in the following formula (18): Among them, p Tk is the transmission power allocated by RSU to vehicle k, s k is the location-related service information sent by the RSU to vehicle k and |s k |=1,n k is the received Gaussian white noise of the kth vehicle, and obeys a complex Gaussian distribution with a mean of 0 and a variance of N0B; Step 4, performance calculation; When all vehicles obtain the optimal transmission power p Tk and the optimal speed v k When , the power-speed ratio of vehicle k under the power allocation scheme is as shown in the following formula (19):

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