Method for reducing pilot frequency overhead and enhancing link reliability assisted by IRS (Inter-Reference Signal) in Internet of Vehicles environment

Abstract

The invention discloses an IRS-assisted pilot overhead reduction and link reliability enhancement method in an Internet of Vehicles environment, which comprises the following steps of: establishing an IRS-assisted multipath channel model, and receiving a signal by using a vehicle deployed with an IRS in the multipath channel model; projecting the received signal to an orthogonal subspace according to an angle of arrival; carrying out Wigner transform and Sheng Fourier transform on the time domain signal of the kth subspace to obtain a signal; for the signal of the kth subspace, constructing a corresponding fractional Doppler amplitude function and a fitness function, and solving through a DWO algorithm to obtain a channel matching parameter; performing channel matching on the kth subspace in the DD domain according to the channel matching parameter; and after channel matching of the DD domain is completed, time delay-Doppler domain channel state information is calculated, and the obtained time delay-Doppler domain channel state information is fed back to a sending end in the multipath channel model. The method obviously improves the frequency band utilization rate of the system and improves the reliability of the system.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method for reducing pilot overhead and enhancing link reliability in an IRS-assisted vehicle networking environment. Background Art

[0002] In recent years, wireless communications have developed rapidly. The next generation of mobile communication systems needs to support high-frequency bands and high-speed mobile vehicle-to-everything (V2X) scenarios. Communication technology is expected to play a key role in future autonomous driving systems. However, due to the high mobility of vehicles in the V2X, the V2X channel changes rapidly. Under fast time-varying channels, inter-carrier interference (ICI) becomes a serious problem, which will lead to the deterioration of the bit error rate performance of traditional orthogonal frequency division multiplexing (OFDM) systems. Therefore, highly robust modulation schemes that adapt to time-frequency dual-selective channels have been widely explored.

[0003] OTFS is considered to be one of the effective solutions for low-latency and high-reliability communications in this scenario. OTFS maps symbols to a two-dimensional delay-Doppler domain (DD), utilizing the slowly varying characteristics of the delay-Doppler domain channel. All symbols in the OTFS data frame experience slow fading that is independent of time selection, thereby achieving full time-frequency diversity of the channel. However, compared to traditional OFDM modulation, OTFS pilot design and channel estimation are more challenging. Most of the existing OTFS pilots and their overhead reduction methods are based on time-frequency domain or delay-Doppler domain level designs. The most popular embedded pilot method has a pilot overhead of 8% at a speed of 120 km / h.

[0004] In addition, there is a problem in vehicle network communication that the wireless link is easily blocked, which seriously affects the quality of V2X communication and is one of the most challenging problems in V2X. Intelligent Reflecting Surface (IRS) has been introduced into the V2X communication system as a promising technology that can solve high-frequency band communication congestion and improve the communication quality of the system. IRS can produce controllable amplitude and phase shift changes to the incident signal, changing the uncontrollable characteristics of traditional wireless channels. Thereby breaking through the limitations of traditional network wireless propagation channels and realizing the reconstruction of wireless channels. Compared with traditional multi-antenna systems, IRS has lower power consumption and lower hardware cost. In addition, IRS is small in size and can be installed on surfaces of any shape to meet different V2X application scenarios. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention proposes a method for reducing pilot overhead and enhancing link reliability in an IRS-assisted Internet of Vehicles environment. For the IRS-assisted Internet of Vehicles communication model, multi-antenna technology, V2X technology, and optimization algorithm technology are combined, and IRS assistance based on spatial subspace projection and channel matching significantly improves the system's frequency band utilization and enhances system reliability.

[0006] In order to solve the above technical problems, the technical solution of the present invention is:

[0007] A method for reducing pilot overhead and enhancing link reliability in an IRS-assisted vehicle networking environment comprises the following steps:

[0008] Step 1: Establish an IRS-assisted multipath channel model, and use the vehicle with IRS deployed in the multipath channel model to receive signals;

[0009] Step 2: Project the received signal into the orthogonal subspace according to the arrival angle;

[0010] Step 3: For the time domain signal y of the kth subspace k (n), and then perform Wigner transform and symplectic Fourier transform to obtain the signal

[0011] Step 4: For the signal of the kth subspace According to the DD domain fractional Doppler spread characteristics of the OTFS system, the corresponding fractional Doppler amplitude function and fitness function are constructed in the selected area through channel estimation in the kth subspace, and the channel matching parameters are obtained by solving the DWO algorithm.

[0012] Step 5: Perform channel matching on the kth subspace in the DD domain according to the channel matching parameters;

[0013] Step 6: After completing the channel matching in the DD domain, the delay-Doppler domain channel state information is calculated by the adaptive pilot overhead algorithm, and the calculated delay-Doppler domain channel state information is fed back to the transmitter in the multipath channel model. The transmitter then dynamically adjusts the pilot protection interval of each frame.

[0014] Preferably, the received signal is expressed as follows:

[0015]

[0016] Where L represents the number of IRS reflection elements, θ tr,i ,θ i,re ,θ d They represent the arrival angles from the base station to the i-th IRS, from the i-th IRS to the target vehicle, and from the base station to the target vehicle, respectively. tr,i , μi,re , μ d represents the path loss coefficient of the corresponding path, β(n) is the corresponding path at nT s The complex fading coefficient at , λ is the carrier wavelength, v is the speed of the mobile station, a(θ) and b(θ) represent the normalized antenna array vectors related to the arrival angle, θ R is the angle of the target vehicle's moving direction.

[0017] Preferably, in step 2, the received signal y(n) is compared with the subspace projection filter matrix U r Point product, projecting the signal into each orthogonal subspace, the expression is as follows:

[0018] y a (n) = U r T y(n)

[0019] Define the subspace projection filter matrix U r :

[0020]

[0021] In the formula, is the filter vector of the kth subspace:

[0022]

[0023] Among them, Δ r is the normalized receive antenna separation defined by the carrier wavelength, is the received signal arrival angle, n r is the number of antennas.

[0024] Preferably, the The corresponding power azimuth spectrum has at least one main lobe, while different The main lobe position and width are different.

[0025] Preferably, the method for constructing the fractional Doppler amplitude function and the fitness function is:

[0026] First, define the time delay and Doppler of each path as p k represents the number of inner paths in the kth subspace, and defines the integer taps of each path delay and Doppler corresponding to the DD domain as round[·] means rounding up, and the fractional Doppler amplitude function of the i-th path after channel matching is expressed as:

[0027]

[0028] Among them, J pis the initial energy of the pilot symbol, is the channel amplitude of the corresponding path, κ'∈(-0.5,0.5] represents the fractional Doppler coefficient of the channel, τ x =Mρ t , represents the channel matching parameter in the delay dimension, is the channel matching parameter in the Doppler dimension;

[0029] Then the objective function can be expressed as:

[0030]

[0031] in, in Indicates the maximum guard interval in the Doppler dimension

[0032] Preferably, the channel matching parameters include time domain matching parameters and Doppler domain matching parameters.

[0033] Preferably, the method for obtaining the channel matching parameters by using the DWO algorithm is:

[0034] Determine the maximum number of iterations R, population size Υ, and dimension K n =2, upper and lower limits of position vector in, Represents the maximum protection interval of the delay dimension, initializes i=1, and randomly generates the initial channel matching parameter matrix Calculate the objective function Q corresponding to X, select the first three values ​​with the best fitness, and represent their corresponding positions as α, β, and γ.

[0035] Preferably, the calculation method of the objective function Q corresponding to X is:

[0036] First, a nonlinear update method is used to update the convergence factor a, a = 1 + cos (π × i / R), A = 2ar1-a, C = 2r2, where i is the current iteration number, A is used to simulate the attack behavior of desert wolves on prey, r1, r2 are random numbers between (0, 1], and the random number C is involved in determining the distance d between the current solution and the optimal solution;

[0037] For every x j ∈X, calculate the position vector x according to the following two formulas j,a , x j,β , x j,γ

[0038] d=|C×x p (i)-x(i)|

[0039] x(i+1)=xp (i)-Ad

[0040] x p and x are the position vectors of the optimal solution and the current solution, respectively. A is used to simulate the attack behavior of desert wolves on prey;

[0041] The weights are calculated using the improved weight calculation method, namely

[0042] ξ j,y =|x j,y | / ∑ r＝α,β,γ |x j,r |,y∈{α,β,γ}

[0043] And calculate x j New Location

[0044] Calculate each x j Corresponding fitness, update the top three best solutions α, β, γ;

[0045] Store the position and fitness value corresponding to the optimal solution α, and update i=i+1;

[0046] Repeat steps 4-2 to 4-6 until i>R, and select the solution with the best fitness from the stored optimal solution set, and the solution is the time domain matching parameter and the Doppler domain matching parameter of the channel matching parameter.

[0047] Preferably, in step 5, the channel matching method in the DD domain is as follows:

[0048]

[0049] in, express represents the time domain matching parameters in the kth subspace, is the compensation angle of the k-th subspace wave number spectrum translation, They represent the resolution of the delay and Doppler dimensions in the DD domain, Δf represents the system subcarrier spacing, and M and N are the number of grids divided in the delay-Doppler plane of the OTFS system.

[0050] Preferably, in step 6, the adaptive pilot overhead algorithm calculates the delay-Doppler domain channel state information in the following manner:

[0051] Assume that the minimum distance between the vehicle and the IRS set on the roadside in the multipath channel model is r, the inter-frame interval is ΔT, and f c is the carrier frequency of the system, c is the speed of light, the maximum moving speed of the vehicle is v, the delay and Doppler vector obtained by channel estimation are τ and f, then the maximum Doppler dimension protection interval that can be set by the transmitter can be calculated according to the following formula: and the maximum delay dimension protection interval

[0052]

[0053] In the formula, ||·|| represents the norm.

[0054] The present invention has the following characteristics and beneficial effects:

[0055] 1. Combining IRS technology with Internet of Vehicles technology not only solves the line-of-sight (LOS) blocking problem caused by the high dynamics of vehicles in the Internet of Vehicles system, but also improves the system Doppler diversity in the Internet of Vehicles system, thereby enhancing the reliability of the system and making the model more valuable for practical application.

[0056] 2. Combining the OTFS system with multi-antenna receiving technology, the received signal is projected into different orthogonal subspaces for processing, which reduces the inter-path interference. At the same time, combined with the channel matching technology, the overall pilot overhead is reduced. Finally, the simulation results verify the effectiveness and convergence of the proposed method.

[0057] 3. The adaptive method is applied to the problem of poor pilot overhead flexibility of the OTFS system. By changing the setting of the pilot protection interval from relying on fixed channel parameters to relying on the channel estimation of the previous frame, the large amount of pilot overhead waste in the actual driving process of the vehicle is effectively reduced. Finally, the simulation results verify the effectiveness and convergence of the proposed method.

[0058] 4. This paper proposes a Desert Wolf Optimization (DWO) algorithm, which optimizes the channel matching parameters in the subspace to obtain the best channel estimation. Simulation results show that the algorithm proposed in this paper can achieve satisfactory system throughput and bit error rate performance in the Internet of Vehicles scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0060] Figure 1 This is a principle framework diagram of the method for reducing pilot overhead and enhancing link reliability assisted by IRS in a vehicle networking environment in the present invention;

[0061] Figure 2 Schematic diagram of the IRS-assisted multipath channel model in the present invention;

[0062] Figure 3 Schematic diagram of the effect expected to be achieved by the DWO algorithm in the present invention in different scenarios;

[0063] Figure 4 It is a schematic diagram of the effect that the DWO algorithm of the present invention is expected to achieve in another scenario;

[0064] Figure 5 This is a comparison chart of the bit error rates of the DWO algorithm in different scenarios in the present invention;

[0065] Figure 6 This is a performance comparison diagram of the DWO algorithm and the GWO algorithm in the application scenario of the present invention;

[0066] Figure 7 is a comparison diagram of bit error rates under different IRS numbers and different subspace numbers in the present invention;

[0067] Figure 8 It is a comparison chart of the throughput (the proportion of correctly transmitted bits to the total number of bits, and the bit error rate and pilot overhead) of the pilot overhead reduction and link reliability enhancement algorithm based on orthogonal subspace projection combined with the adaptive pilot overhead method in the present invention. DETAILED DESCRIPTION

[0068] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0069] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and the like are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0070] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0071] The present invention provides an algorithm for reducing pilot overhead and enhancing link reliability based on IRS assistance and multi-antenna technology. The purpose is to improve the diversity of the system while reducing inter-path interference through orthogonal subspace projection and IRS reflection enhancement characteristics in wireless communications, improve the system's frequency band utilization, and combine with an adaptive pilot overhead method to further improve the system's throughput in actual vehicle network communication scenarios.

[0072] The specific implementation method of the technical solution of the present invention is as follows:

[0073] A method for reducing pilot overhead and enhancing link reliability in an IRS-assisted vehicle networking environment, such as Figure 1 As shown, specifically including:

[0074] Step 1: Establish an IRS-assisted multipath channel model to obtain a specific representation of the received signal. Specifically, Figure 2 As shown, by deploying IRS on buildings and roadside units, virtual LOS enhanced communication can be established when LOS is blocked, thereby improving the diversity of the system.

[0075] It should be noted that the establishment of the IRS-assisted multipath channel model belongs to conventional technical means, so this embodiment will not further explain in detail how to establish the IRS-assisted multipath channel model.

[0076] Furthermore, the signal received by the multi-antenna vehicle in the multipath channel model can be expressed as:

[0077]

[0078] Where L represents the number of IRS reflection elements, θ tr,i ,θ i,re ,θ d They represent the arrival angles from the base station to the i-th IRS, from the i-th IRS to the target vehicle, and from the base station to the target vehicle, respectively. tr,i , μ i,re , μ d represents the path loss coefficient of the corresponding path, β(n) is the corresponding path at nT sThe complex fading coefficient at , which can be assumed to be approximately fixed within the demodulation symbol period. λ is the carrier wavelength, and v is the speed of the mobile station. a(θ) and b(θ) represent the normalized antenna array vectors related to the arrival angle. Taking b(θ) as an example, for a uniform linear array, f c ,c,d are the carrier frequency, speed of light and distance between antennas respectively. R is the angle of the target vehicle's direction of motion, which is defined relative to the wide side of the antenna array. Typically, in high-speed vehicle-to-vehicle communications, the spacing between antenna elements is less than half the carrier wavelength. Therefore, in this embodiment, the direction of motion is perpendicular to the wide side of the antenna array, i.e.

[0079] Step 2: Combine the received signal y(n) with the subspace projection filter matrix U r Point product, projecting the signal into each orthogonal subspace, that is:

[0080] y a (n) = U r T y(n)

[0081] Figure 2 The overall algorithm block diagram is shown in Figure 2.

[0082] At the receiving end, for a uniform linear array in a MIMO system, we define the subspace projection filter matrix U r :

[0083]

[0084] In the formula, is the filter vector of the kth subspace:

[0085]

[0086] Among them, Δ r is the normalized receive antenna separation defined by the carrier wavelength, each basis vector The corresponding power azimuth spectrum has at least one main lobe, and the main lobe position and width are different for different basis vectors. This means that the received signal of any AoA is There is a main power on the defined subspace, while other basis vectors have almost no energy in the direction of the subspace, thereby realizing orthogonal subspace projection of the signal in different directions.

[0087] Step 3: For the time domain signal y of the kth subspace k, and then perform Wigner Transform (WT) and Symplectic Finite Fourier Transform (SFFT) to obtain

[0088] Step 4: Calculate the channel matching parameters by the DWO method proposed in this embodiment. First, how to establish the objective function is introduced. For the signal in the kth subspace The time delay and Doppler of each path are denoted as Define the integer taps of each path delay and Doppler corresponding to the DD domain as According to the DD domain fractional Doppler spread characteristics of the OTFS system, the channel h[τ' k,i ,f′ k,i ]The corresponding fractional Doppler amplitude function in the area selected for channel estimation is:

[0089]

[0090] Among them, J p is the initial energy of the pilot symbol, τ x =Mρ t ,

[0091] Then the fitness of the objective function can be expressed as:

[0092]

[0093] in,

[0094] In addition, the region selected for channel estimation is:

[0095]

[0096] Furthermore, the specific contents of the DWO algorithm are as follows:

[0097] Step 4-1: Determine the maximum number of iterations R, population size Υ, and dimension K n =2, upper and lower limits of position vector g h and g l ,in, Initialize i=1 and randomly generate the initial channel matching parameter matrix Calculate the fitness function Q corresponding to X, select the first three values ​​with the best fitness, and represent their corresponding positions as α, β, and γ.

[0098] Step 4-2: Update the convergence factor a using a nonlinear update method:

[0099] a=1+cos(π×i / R), A=2ar1-a, C=2r2.

[0100] Step 4-3: For each x j ∈X, calculate the position vector x according to the following two formulas of Gray Wolf Optimization (GWO) algorithm: j,a , x j,β , x j,γ

[0101] d=|C×x p (i)-x(i)|

[0102] x(i+1)=x p (i)-Ad

[0103] x p and x are the position vectors of the optimal solution and the current solution respectively. A is used to simulate the attack behavior of desert wolves on their prey.

[0104] Step 4-4: Calculate the weight using the improved weight calculation method, that is

[0105] ξ j,y =|x j,y | / ∑ r＝α,β,γ |x j,r |,y∈{α,β,γ}

[0106] And calculate x j New location:

[0107]

[0108] Step 4-5: Calculate each x j Corresponding fitness, update the top three optimal solutions α, β, γ.

[0109] Step 4-6: Store the position and fitness value corresponding to the optimal solution α, and update i=i+1.

[0110] Repeat steps 4-2 to 4-6 until i>R, and select the solution with the best fitness from the stored optimal solution set. It can be understood that since the objective function (i.e., the fitness function, which is generally referred to as fitness in the optimization algorithm) is a negative number, the best fitness means that the objective function is the smallest, and its solution is the time domain matching parameters and Doppler domain matching parameters of the channel matching parameters.

[0111] Figure 3 and Figure 4The figure shows the expected effect of channel matching using the channel matching parameters calculated by the DWO algorithm in the three-path scenario. The power corresponding to the three paths satisfies P2>P3>P1. The orange area indicates the area that needs to be selected when estimating the channel at the receiving end. It can be observed that before channel matching, P3 is outside the guard interval and will be omitted in channel estimation and equalization. After channel matching, Figure 3 As shown in the figure, there is no missing path in the selected area in the first scenario, such as Figure 4 As shown in FIG. 1 , in another scenario, the selected area retains the path with relatively high power. Figure 5 This is a comparison diagram of the bit error rates of the DWO algorithm in different scenarios in the present invention. The simulation results show that the DWO algorithm achieves the expected effect. Figure 6 The diagram shows a comparison of the effects of the DWO algorithm and the GWO algorithm in the scenario of the present invention. The results show that the DWO algorithm has stronger global search capability and local development capability.

[0112] Step 5: Perform channel matching on the kth subspace in the DD domain according to the channel matching parameters, which can be expressed as:

[0113]

[0114] in, represents the time domain matching parameters in the kth subspace, is the compensation angle of the k-th subspace wave number spectrum translation. They represent the resolution of DD domain delay and Doppler dimension respectively, Δf represents the system subcarrier spacing, M and N The number of grids divided in the delay-Doppler plane of the OTFS system.

[0115] Figure 7 This is a comparison diagram of bit error rates under different IRS numbers and different subspace numbers in the present invention. The results show that the increase in the number of receiving antennas and the increase in IRS can improve system reliability.

[0116] Step 6: Right After channel estimation, the delay-Doppler channel state information (DD_CSI) is calculated according to the adaptive pilot overhead scheme we proposed. Assuming that the minimum distance between the vehicle and the IRS set on the roadside is r, the inter-frame interval is ΔT, the maximum moving speed of the vehicle is v, and the delay and Doppler vectors obtained by channel estimation are τ and f, the DD_CSI can be calculated according to the following formula:

[0117]

[0118] In this way, the slowly changing characteristics of the DD domain channel state information of the OTFS system are fully utilized, and the setting of the guard interval is transformed from a fixed dependence on the channel parameters to a dependence on the channel estimation of the previous frame. and The information is fed back to the transmitter, and the transmitter can dynamically adjust the pilot protection interval of each frame, thereby further saving the pilot overhead. Figure 8 As shown, the gain in frequency band utilization obtained by the proposed algorithm is evaluated, and the results show that the channel matching algorithm has a higher system throughput under the adaptive pilot overhead reduction scheme.

[0119] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, various changes, modifications, substitutions and variations of these embodiments including components are made without departing from the principles and spirit of the present invention, and still fall within the scope of protection of the present invention.

Claims

1. A method for reducing pilot overhead and enhancing link reliability in an IRS-assisted vehicle networking environment, characterized in that: The steps include: Step 1: Establish an IRS-assisted multipath channel model, and use the vehicle with IRS deployed in the multipath channel model to receive signals; Step 2: Project the received signal into the orthogonal subspace according to the arrival angle; Step 3: For the time domain signal y of the kth subspace k , and then perform Wigner transform and symplectic Fourier transform to obtain the signal Step 4: For the signal of the kth subspace According to the DD domain fractional Doppler spread characteristics of the OTFS system, the corresponding fractional Doppler amplitude function and fitness function are constructed in the selected area through channel estimation in the kth subspace, and the channel matching parameters are obtained by solving the DWO algorithm. Step 5: Perform channel matching on the kth subspace in the DD domain according to the channel matching parameters; Step 6: After completing the channel matching in the DD domain, the delay-Doppler domain channel state information is calculated by the adaptive pilot overhead algorithm, and the calculated delay-Doppler domain channel state information is fed back to the transmitter in the multipath channel model. The transmitter then dynamically adjusts the pilot protection interval of each frame.

2. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 1, characterized in that: The received signal is expressed as follows: Where L represents the number of IRS reflection elements, θ tr,i ,θ i,re ,θ d They represent the arrival angles from the base station to the i-th IRS, from the i-th IRS to the target vehicle, and from the base station to the target vehicle, respectively. tr,i , μ i,re , μ d represents the path loss coefficient of the corresponding path, β(n) is the corresponding path at nT s The complex fading coefficient at , λ is the carrier wavelength, v is the speed of the mobile station, a(θ) and b(θ) represent the normalized antenna array vectors related to the arrival angle, θ R is the angle of the target vehicle's moving direction.

3. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 2, characterized in that: In step 2, the received signal y(n) is compared with the subspace projection filter matrix U r Point product, projecting the signal into each orthogonal subspace, the expression is as follows: and a (n)=U r T y(n) Define the subspace projection filter matrix U r : In the formula, is the filter vector of the kth subspace: Among them, Δ r is the normalized receive antenna separation defined by the carrier wavelength, is the i-th spatial filter parameter of the k-th subspace, is the received signal arrival angle, n r is the number of antennas.

4. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 3, characterized in that: Said The corresponding power azimuth spectrum has at least one main lobe, while different The main lobe position and width are different.

5. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 3, characterized in that: The method for constructing the fractional Doppler amplitude function and the fitness function is: First, define the time delay and Doppler of each path as and p k represents the number of inner paths in the kth subspace, and defines the integer taps of each path delay and Doppler corresponding to the DD domain as round[·] means rounding up, and the fractional Doppler amplitude function of the i-th path after channel matching is expressed as: Among them, J p is the initial energy of the pilot symbol, is the channel amplitude of the corresponding path, κ'∈(-0.5,0.5] represents the fractional Doppler coefficient of the channel, τ x =Mρ t , represents the channel matching parameter in the delay dimension, is the channel matching parameter in the Doppler dimension; Then the fitness function can be expressed as: in, in Indicates the maximum guard interval in the Doppler dimension.

6. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 5, characterized in that: The channel estimation selected area is expressed as follows:

7. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 6, characterized in that: The channel matching parameters include time domain matching parameters and Doppler domain matching parameters.

8. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 7, characterized in that: The method for obtaining the channel matching parameters by the DWO algorithm is as follows: Determine the maximum number of iterations R, population size Υ, and dimension K n =2, upper and lower limits of position vector g h and g l , initialize i = 1, randomly generate the initial channel matching parameter matrix Calculate the fitness function Q corresponding to X, select the first three values ​​with the best fitness, and represent their corresponding positions as α, β, and γ.

9. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 8, characterized in that: The calculation method of the fitness function Q corresponding to X is: First, a nonlinear update method is used to update the convergence factor a, a = 1 + cos (π × i / R), A = 2ar1-a, C = 2r2, where i is the current iteration number, A is used to simulate the attack behavior of desert wolves on prey, r1, r2 are random numbers between (0, 1], and the random number C is involved in determining the distance d between the current solution and the optimal solution; For every x j ∈X, calculate the position vector x according to the following two formulas j,a , x j,β , x j,γ d=|C×x p (i)-x(i)| x(i+1)=x p (i)-Ad x p and x are the position vectors of the optimal solution and the current solution, respectively. A is used to simulate the attack behavior of desert wolves on prey; The weights are calculated using the improved weight calculation method, namely x j,y =|x j,y | / ∑ r＝α,β,γ |x j,r |,y∈{a,b,c} And calculate x j New Location Calculate each x j Corresponding fitness, update the top three best solutions α, β, γ; Store the position and fitness value corresponding to the optimal solution α, and update i=i+1; Repeat steps 4-2 to 4-6 until i>R, and select the solution with the best fitness from the stored optimal solution set, and the solution is the time domain matching parameter and the Doppler domain matching parameter of the channel matching parameter.

10. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 9, characterized in that: In step 5, the channel matching method in the DD domain is as follows: in, represents the time domain matching parameters in the kth subspace, is the compensation angle of the k-th subspace wave number spectrum translation, They represent the resolution of the delay and Doppler dimensions in the DD domain, Δf represents the system subcarrier spacing, and M and N are the number of grids divided in the delay-Doppler plane of the OTFS system.

11. The method for reducing pilot overhead and enhancing link reliability by IRS assistance in a vehicle networking environment according to claim 10, characterized in that: In step 6, the adaptive pilot overhead algorithm calculates the delay-Doppler domain channel state information in the following manner: First, assuming that the minimum distance between the vehicle and the IRS set on the roadside in the multipath channel model is r, the inter-frame interval is ΔT, the maximum moving speed of the vehicle is v, and the delay and Doppler vector obtained by channel estimation are τ and f, they can be calculated according to the following formula: In the formula, ||·|| represents the norm.

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