A multi-task offloading method based on NOMA in connected vehicles

Abstract

The present invention belongs to the field of wireless communication technology in a vehicle networking system, and relates to a multi-task offloading method based on NOMA in a vehicle networking system, including: initializing a network model, determining the number of vehicle users requesting offloading, the offloading tasks of the vehicle users, and the network channel capacity; judging whether the number of vehicle users requesting offloading exceeds the network channel capacity, if the current number of vehicle users does not exceed the network channel capacity, then selecting an offloading method based on OMA for task offloading, if it exceeds the network channel capacity, then selecting an offloading method based on NOMA for task offloading. The present invention solves the problems of insufficient channel resources and task offloading sorting faced by multiple vehicle users when offloading at the same time, and uses an offloading method based on NOMA for offloading, which can improve channel resource utilization and system throughput, and can effectively reduce task transmission delay.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communication in an Internet of Vehicles system, and in particular to a multi-task offloading method based on NOMA in an Internet of Vehicles. Background Art

[0002] With the rapid development of the Internet of Vehicles, new types of vehicle-mounted application devices are becoming increasingly popular, such as emergency warning, route navigation, travel entertainment, etc., providing people with great convenient services. These vehicle-mounted applications will generate corresponding task data in the process of providing services. As the number of services increases, the amount of data increases accordingly. At the same time, the task data needs to be processed quickly, which requires the vehicle's on-board unit (OBU) to have a certain computing power. However, for vehicle users, due to their limited processing power, they cannot support such a large amount of data. For this reason, Mobile Edge Computing (MEC) technology is introduced to provide the data processing computing power required by the vehicle nearby with the computing resources on the network edge devices, providing vehicle users with low-latency, high-bandwidth network services. However, as more and more vehicle task data is offloaded to the network edge devices, it will bring about problems such as insufficient network channel resources and multi-task offloading sorting.

[0003] As one of the key technologies of 5G communication technology, Non Orthogonal Multiple Access (NOMA) technology allocates different powers to terminal users, allows different users to transmit in parallel on the same channel resources, and performs Successive Interference Cancellation (SIC) at the receiving end to eliminate interference, providing services for multiple users, thereby improving system capacity. Compared with traditional Orthogonal Multiple Access (OMA) technology, NOMA technology can support more users, improve spectrum resource utilization, and thus reduce latency. Since the main function of NOMA is to increase capacity by having multiple users share the same channel resources, introducing NOMA technology into the Internet of Vehicles also plays the same role.

[0004] In the Internet of Vehicles system that introduces both NOMA and MEC, in order to provide better services, multiple vehicle users need to determine which vehicles choose to transmit on the same channel resources according to a certain user grouping strategy, and allocate transmission power to the same group of vehicle users according to the power allocation strategy. Only by obtaining the best user grouping and the best power allocation can the advantages of NOMA in improving the Internet of Vehicles system be fully utilized. Due to the rapid movement and instability of vehicle users, reasonable user grouping strategy and power allocation strategy have a great impact on improving system performance. Summary of the invention

[0005] In order to solve the problem of insufficient channel resources faced by the current multi-vehicle task offloading to RSU, the present invention proposes a multi-task offloading method based on NOMA in the Internet of Vehicles, which includes initializing data, determining the number of vehicle users requesting offloading, the offloading tasks of the vehicle users and the network channel capacity; judging whether the number of vehicle users requesting offloading exceeds the network channel capacity, if not, the vehicle user selects the OMA-based offloading method to offload the task; if exceeded, the vehicle user selects the NOMA-based offloading method to offload the task; wherein, the process for the vehicle user to select the NOMA-based offloading method to offload the task specifically includes:

[0006] Under the constraints of channel capacity and maximum tolerable delay threshold, an objective function that minimizes the total task transmission delay is established, namely, the NOMA-based objective function.

[0007] A utility function is constructed based on the inverse of the transmission delay, and a game theory model is constructed based on the vehicle user set, subchannel set and utility function. A cooperative game algorithm is used to obtain the optimal user grouping under the condition of maximizing the utility function.

[0008] A power allocation strategy based on the maximum delay constraint and the characteristics of the SIC acceptance mechanism is adopted to allocate the optimal transmission power to each vehicle user in the optimal user group;

[0009] Based on the optimal transmission power, tasks of vehicle users in the same group are transmitted and unloaded in a non-orthogonal manner on the same sub-channel, and tasks of vehicle users in different groups are transmitted and unloaded in a mutually orthogonal manner on different sub-channels.

[0010] Beneficial effects of the present invention:

[0011] The present invention proposes a multi-task unloading method based on NOMA in the urban straight highway traffic scenario in the Internet of Vehicles. By introducing both NOMA technology and MEC technology into the Internet of Vehicles, the method can meet the needs of multiple vehicle users to unload simultaneously under the condition of channel resource shortage. A cooperative game algorithm is used to obtain the optimal user grouping, and a power allocation strategy is designed to allocate the optimal transmission power to each vehicle user, thereby improving spectrum utilization and throughput, and reducing the transmission delay of vehicle users during task unloading. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A network model of an embodiment of the present invention;

[0013] Figure 2 is a flow chart of the present invention;

[0014] Figure 3This is a flow chart of the cooperative game algorithm used in the present invention;

[0015] Figure 4 This is an example of a uniform channel difference grouping strategy. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Figure 1 is a schematic diagram of a network model of a vehicle networking scenario used in an embodiment of the present invention, such as Figure 1 As shown, the network model implemented in the present invention mainly includes an RSU equipped with an MEC server, N vehicle users and Q communication sub-channels. Among them:

[0018] (1) The height of RSU is H and the coverage radius is r.

[0019] (2) The vehicle user set is denoted as V = {V1, V2, …, V N}.

[0020] (3) Each vehicle user has a task that needs to be offloaded to the RSU for processing. The offloaded task is recorded as

[0021] (3)D i Represents vehicle user V i The task data size, Represents vehicle user V i The maximum tolerable delay threshold during transmission.

[0022] (4) The set of vehicle users in the subchannel is denoted as S = {S1, S2, …, S Q},S Q represents the vehicle users of the Qth subchannel, that is, the vehicle user set of the i-th (1≤i≤Q) subchannel is denoted as S i = {V i,1 ,V i,2 ,…,V i,M}.

[0023] (5) Different vehicle users {V1, V2, …, V N} corresponds to different channel gains {h1,h2,…,h N}.

[0024] Based on the above scenario analysis, Figure 2 As shown, the present invention proposes a flow chart of a multi-task offloading method based on NOMA in a connected vehicle network, which specifically includes the following steps:

[0025] The first step is to determine the number of users N who request to unload vehicles and the unloading tasks of vehicle users and network channel capacity Q.

[0026] In the embodiment of the present invention, data needs to be initialized first. In the embodiment of the present invention, the invention is set to a straight road with a single RSU and multiple vehicle users, including an RSU configured with an MEC server and N vehicle users with unloading tasks within the coverage of the RSU, where the vehicle user set is recorded as V = {V1, V2, ..., V n ,…,V N}, where V n represents the nth vehicle user. The unloading task of each vehicle user is recorded as Among them, D i Represents vehicle user V i The task data size, Represents vehicle user V i The maximum tolerable delay threshold in the transmission process. The network communication model contains Q sub-channels, and the set of vehicle users in the sub-channel is recorded as S = {S1, S2, ..., S Q}, where S Q represents the vehicle user of the Qth sub-channel.

[0027] The second step is to determine whether the number of vehicle users N requesting to unload exceeds the network channel capacity Q. If the number of vehicle users N exceeds the network channel capacity Q, proceed to the fourth step; otherwise, proceed to the third step.

[0028] In the embodiment of the present invention, if the number N of users requesting to unload vehicles does not exceed the network channel capacity Q, the third step is executed; if it exceeds the network channel capacity Q, the fourth step is executed.

[0029] In the third step, since N≤Q, each vehicle user can choose to transmit simultaneously on a sub-channel, so the vehicle user chooses the OMA-based offloading method to offload tasks. Different vehicle users perform transmission offloading in an orthogonal manner on different sub-channels without interfering with each other.

[0030] In the embodiment of the present invention, since the number of vehicle users requesting to offload does not exceed the network channel capacity, the OMA-based offloading method is directly used in this embodiment to offload tasks, and the core of the OMA-based offloading method for offloading tasks is that different vehicle users transmit and offload in an orthogonal manner on different sub-channels without interfering with each other. The uplink transmission rate formula of each vehicle user is expressed as:

[0031]

[0032] Among them, R i Represents vehicle user V i The uplink transmission rate, w represents the noise power, B represents the channel transmission bandwidth, p i Represents vehicle user V i The transmission power, h i Represents vehicle user V i The channel gain, (d i ) -σ Represents vehicle user V i The path loss, d i Represents vehicle user V i The distance between the vehicle and the roadside unit, σ represents the path loss index; the vehicle user V i Distance d from RSU i The calculation formula is expressed as:

[0033]

[0034] Where H represents the height of the roadside unit, r represents the coverage radius of the roadside unit, Represents vehicle user V i The initial position of .

[0035] The fourth step is to construct the NOMA-based objective function. Under the constraint of , the objective function that minimizes the total task transmission delay is established, which is expressed as:

[0036]

[0037]

[0038]

[0039] Where T represents the total task transmission delay, Q represents the subchannel capacity, M represents the number of vehicle users in each subchannel, and t i,j represents the transmission delay of the jth vehicle user in the i-th subchannel, D i,j represents the offloading task of the jth vehicle user in the i-th subchannel, R i,j is the task uplink transmission rate of the jth vehicle user in the i-th subchannel, p i,j and p i,k are the transmission powers of the jth and kth vehicle users in the ith subchannel, respectively, and h i,j and h i,kis the channel gain of the jth and kth vehicle users in the i-th subchannel, (d i.j ) -σ and (d i.k ) -σ is the path loss of the jth and kth vehicle users in the i-th subchannel; σ represents the path loss index, B represents the channel transmission bandwidth, w represents the noise power, C1 is the constraint that the transmission delay of the task cannot exceed the maximum allowable delay threshold, represents the maximum tolerable delay threshold during the transmission process; C2 is the transmission power constraint of the vehicle user, Indicates the maximum transmit power.

[0040] Step 5: Use cooperative game algorithm to obtain the optimal user grouping. Since the number of vehicle users N exceeds the network channel capacity Q, it is necessary to divide the N vehicle users into Q groups for transmission offloading. Figure 3 The figure shows the flowchart of the cooperative game algorithm used:

[0041] First, a game theory model (V, S, Γ) is constructed, where V represents the set of all vehicle users, S represents the set of subchannels, and Γ represents the utility function, which is composed of the inverse of the transmission delay;

[0042] Among them, the vehicle user determines the number of users M in each subchannel according to the number of users N and the subchannel capacity Q, that is, the user set S of the i-th subchannel is obtained i = {V i,1 ,V i,2 ,…,V i,M},satisfy

[0043] A game theory model (V, S, Γ) is established, where V represents the set of all vehicle users, S represents the set of subchannels, and Γ represents the utility function, which is composed of the inverse of the transmission delay. Its formula is expressed as follows:

[0044]

[0045] Among them, the utility function is inversely proportional to the transmission delay. By maximizing the utility function, the offloading delay can be optimized.

[0046] Secondly, the uniform channel difference grouping strategy is used to initialize the user group S start , and define the original group S cur =S start ;

[0047] Arrange all vehicle users in descending order of channel gain, i.e. h1≥h2≥…≥h N; Select the {n, n+Q, n+2Q, …}th users to be grouped into a group, where n≤Q; finally, divide the vehicle users into Q groups, that is, generate the user grouping set S start , where Q represents the subchannel capacity, n∈{1,2,...,N}, and N represents the number of all vehicle users within the coverage area of ​​the roadside unit.

[0048] like Figure 4 Shown is the initialization user group S start Example of using uniform channel difference grouping strategy. Assume that there are 10 vehicle users in total, and the vehicle users are arranged in descending order of channel gain; there are 3 sub-channels, so the vehicle users need to be divided into 3 groups, where vehicles 1, 4, 7, 10 are in user group 1, vehicles 2, 5, 8 are in user group 2, and vehicles 3, 6, 9 are in user group 3, so that the channel differences between vehicle users in each group are uniform and interference is reduced.

[0049] Then select vehicle user V in sequence i , generate a new group S different from the previous one new , calculate the utility function Γ(S new ), compare Γ(S new ) and Γ(S cur ) size; then update the original grouping:

[0050] If Γ(S new )>Γ(S cur ), then S cur =S new , otherwise S cur =S cur ; Repeat the iterative operation until a new user group S is generated by arbitrarily selecting a vehicle user new The calculated Γ(S new ) is always less than Γ(S cur ), the iteration is terminated, that is, the optimal user grouping is finally obtained. This embodiment adopts the method of updating and comparing to iteratively obtain the optimal user grouping. The grouping of the optimal user grouping is stable, and the utility function calculated by any grouping is smaller than the utility function of the stable grouping. Therefore, the optimal user grouping has global optimality.

[0051] In the embodiment of the present invention, a cooperative game algorithm is adopted to optimize the utility function in each sub-channel, obtain the optimal user grouping, and minimize the interference between vehicle users in the grouping.

[0052] Step 6: Allocate optimal transmission power to vehicle users according to the power allocation strategy.

[0053] In the embodiment of the present invention, for the vehicle user set S of the i-th subchanneli = {V i,1 ,V i,2 ,…,V i,M}, according to the characteristics of the SIC acceptance mechanism, first allocate the last decoded vehicle user V i,M , that is, the user with the smallest channel gain, is the last to be decoded and is not interfered by other users during the decoding process, so it is assigned the maximum transmission power p max ,Right now p i,m represents the transmission power of the mth vehicle user in the i-th subchannel; secondly, the penultimate decoded vehicle user V i,M-1 , since it is only affected by the last vehicle user V i,M If the interference is present and the power has been allocated, the transmission power that satisfies both the maximum delay constraint and the SIC acceptance mechanism characteristics is taken; and so on, the power is allocated to all vehicle users respectively, where 1≤i≤Q, Q represents the subchannel capacity; where:

[0054] The expression of the transmit power that satisfies the maximum delay constraint includes:

[0055]

[0056] Among them, p′ i,m-1 represents the transmission power of the m-1th vehicle user in the ith subchannel that satisfies the maximum delay constraint, B represents the channel transmission bandwidth, w represents the noise power, and h i,m represents the channel gain of the mth vehicle user in the ith subchannel, (d i.m ) -σ represents the path loss of the mth vehicle user in the ith subchannel, σ represents the path loss index; D i,m-1 Represents the data size of the m-1th vehicle user in the ith subchannel.

[0057] The expressions of transmit power that meet the characteristics of the SIC acceptance mechanism include:

[0058]

[0059] Among them, p″ i,m-1 represents the transmission power of the m-1th vehicle user in the ith subchannel that satisfies the SIC acceptance mechanism characteristics, ξ represents the user V i,m With V i,m-1 The information difference between i,m represents the channel gain of the mth vehicle user in the ith subchannel, (d i.m ) -σ represents the path loss of the mth vehicle user in the ith subchannel, and σ represents the path loss exponent.

[0060] In the embodiment of the present invention, this power allocation strategy allocates transmission power to vehicle users in each group while satisfying the maximum delay constraint and the SIC acceptance mechanism characteristics, thereby reducing the task transmission delay of the vehicle users.

[0061] In the seventh step, N vehicle users select the NOMA-based offloading method to offload tasks according to the optimal user grouping and optimal transmission power. The tasks of the vehicle users in the same group are offloaded in a non-orthogonal manner on the same subchannel, and the vehicle users in different groups are offloaded in an orthogonal manner on different subchannels. The uplink transmission rate formula they meet is:

[0062]

[0063] Among them, R i,j is the task uplink transmission rate of the jth vehicle user in the i-th subchannel, B represents the channel transmission bandwidth, and p i,j and p i,k are the transmission powers of the jth and kth vehicle users in the ith subchannel, respectively, and h i,j and h i,k is the channel gain of the jth and kth vehicle users in the i-th subchannel, (d i.j ) -σ and (d i.k ) -σ is the path loss of the j-th and k-th vehicle users in the i-th subchannel; σ represents the path loss index; w represents the noise power.

[0064] In the description of the present invention, it is necessary to understand that the terms "coaxial", "bottom", "one end", "top", "middle", "the other end", "upper", "one side", "top", "inside", "outside", "front", "center", "both ends" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0065] In the present invention, unless otherwise clearly stipulated and limited, the terms such as "installation", "setting", "connection", "fixation" and "rotation" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. Unless otherwise clearly defined, ordinary technicians in this field can understand the specific meanings of the above terms in the present invention according to the specific circumstances.

[0066] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-task offloading method based on NOMA in a vehicle network, the method comprising: Initialize data to determine the number of vehicle users requesting to unload vehicles, the unloading tasks of vehicle users, and the capacity of network channels; Determine whether the number of vehicle users requesting to offload exceeds the network channel capacity. If not, the vehicle users select an offloading method based on OMA to offload tasks. If it exceeds, the vehicle user selects the NOMA-based offloading method to offload the task; It is characterized in that the vehicle user selects the NOMA-based offloading method to offload tasks, specifically including: Under the constraints of channel capacity and maximum tolerable delay threshold, an objective function that minimizes the total task transmission delay is established, that is, an objective function based on NOMA. The objective function based on NOMA is expressed as: Where T represents the total task transmission delay, Q represents the subchannel capacity, M represents the number of vehicle users in each subchannel, and t i,j represents the transmission delay of the jth vehicle user in the i-th subchannel, D i,j represents the offloading task of the jth vehicle user in the i-th subchannel, R i,j is the task uplink transmission rate of the jth vehicle user in the i-th subchannel, p i,j and p i,k are the transmission powers of the jth and kth vehicle users in the ith subchannel, respectively, and h i,j and h i,k is the channel gain of the jth and kth vehicle users in the i-th subchannel, (d i.j ) -σ and (d i.k ) -σ is the path loss of the jth and kth vehicle users in the i-th subchannel; σ represents the path loss index, B represents the channel transmission bandwidth, w represents the noise power, C1 is the constraint that the transmission delay of the task cannot exceed the maximum allowable delay threshold, represents the maximum tolerable delay threshold of the jth vehicle user in the i-th subchannel during the transmission process; C2 is the transmission power constraint of the vehicle user, Indicates the maximum transmit power; A utility function is constructed according to the inverse of the transmission delay, a game theory model is constructed with the vehicle user set, the subchannel set and the utility function, and a cooperative game algorithm is used to obtain the optimal user grouping under the maximization of the utility function; the method of obtaining the optimal user grouping under the maximization of the utility function by using the cooperative game algorithm specifically includes: 1) Initialize user group S using uniform channel difference grouping strategy start , and define the current user group Scur = Sstart and calculate the utility function Γ (S cur ); The uniform channel difference grouping strategy includes: arranging all vehicle users in descending order of channel gain, that is, h1≥h2≥"≥h N ; Select the {n,n+Q,n+2Q,"}th users to be grouped together, where n≤Q; finally, divide the vehicle users into Q groups, i.e. generate the user grouping set S start , n∈{1,2,...,N}, N represents the number of all vehicle users within the coverage area of ​​the roadside unit; 2) Sequentially select vehicle users V i , generate a new user group S different from the current user group new , calculate the utility function Γ(S new ), compare the utility functions Γ(S new ) and Γ(S cur ) size, if Γ(S new )>Γ(S cur ), then Scur=Snew, otherwise Scur=Scur; 3) Through iterative operation 2), a new user group S is generated by randomly selecting a vehicle user new The calculated Γ(S new ) is always less than Γ(S cur ), the iteration is terminated, and the optimal user grouping is obtained; The optimal transmission power is allocated to each vehicle user in the optimal user group by adopting a power allocation strategy based on the maximum delay constraint and the SIC acceptance mechanism characteristics; the optimal transmission power is allocated to each vehicle user in the optimal user group by adopting a power allocation strategy based on the maximum delay constraint and the SIC acceptance mechanism characteristics, including: For the vehicle user set S of the i-th subchannel i = {V i,1 ,V i,2 ,",V i,M }, according to the characteristics of the SIC acceptance mechanism, first allocate the last decoded vehicle user V i,M , that is, the user with the smallest channel gain, is the last to be decoded and is not interfered by other users during the decoding process, so it is assigned the maximum transmission power p max ,Right now p i,M represents the transmission power of the Mth vehicle user in the i-th subchannel; secondly, the penultimate decoded vehicle user V i,M-1 , since it is only affected by the last vehicle user V i,M If there is interference and the power has been allocated, the transmission power that satisfies both the maximum delay constraint and the SIC acceptance mechanism characteristics is taken; and so on, the power is allocated to all vehicle users respectively, where 1≤i≤Q; The expression of the transmit power that satisfies the maximum delay constraint includes: Among them, p i ' ,m-1 represents the transmission power of the m-1th vehicle user in the ith subchannel that satisfies the maximum delay constraint, h i,m represents the channel gain of the mth vehicle user in the ith subchannel, (d i.m ) -σ represents the path loss of the mth vehicle user in the ith subchannel, D i,m-1 represents the data size of the m-1th vehicle user in the i-th subchannel, represents the maximum tolerable delay threshold of the m-1th vehicle user in the i-th subchannel during the transmission process; The expressions of transmit power that meet the characteristics of the SIC acceptance mechanism include: Among them, p i ' , ' m-1 represents the transmission power of the m-1th vehicle user in the ith subchannel that satisfies the SIC reception mechanism characteristics, p i,m represents the transmission power of the mth vehicle user in the ith subchannel, ξ represents the vehicle user V i,m With V i,m-1 The information difference between Based on the optimal transmission power, tasks of vehicle users in the same group are transmitted and unloaded in a non-orthogonal manner on the same sub-channel, and tasks of vehicle users in different groups are transmitted and unloaded in a mutually orthogonal manner on different sub-channels.

2. The multi-task offloading method based on NOMA in the Internet of Vehicles according to claim 1 is characterized in that: The vehicle user selects the OMA-based offloading method to offload tasks, including different vehicle users transmitting and offloading in an orthogonal manner on different sub-channels without interfering with each other; wherein the uplink transmission rate formula of each vehicle user is expressed as: Among them, R i Represents vehicle user V i The uplink transmission rate, p i Represents vehicle user V i The transmission power, h i Represents vehicle user V i The channel gain, (d i ) -σ Represents vehicle user V i The path loss, d i Represents vehicle user V i Distance from roadside unit; Vehicle user V i Distance d from RSU i The calculation formula is expressed as: Where H represents the height of the roadside unit, r represents the coverage radius of the roadside unit, Represents vehicle user V i The initial position of .

3. The multi-task offloading method based on NOMA in the Internet of Vehicles according to claim 1 is characterized in that: The tasks of the vehicle users in the same group are transmitted and unloaded in a non-orthogonal manner on the same sub-channel, and the vehicle users in different groups are transmitted and unloaded in a mutually orthogonal manner on different sub-channels. The uplink transmission rate of the tasks of the vehicle users in the unloading is expressed as:

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