IRS-assisted pilot overhead reduction and link reliability enhancement method in connected vehicle environments

Abstract

The present invention discloses a method for reducing pilot overhead and enhancing link reliability in an IRS-assisted vehicle networking environment. The method comprises the following steps: establishing an IRS-assisted multipath channel model, applying an IRS-equipped vehicle in the multipath channel model to receive signals; projecting the received signals into orthogonal subspaces based on the angle of arrival; performing a Wigner transform and a sigmoid Fourier transform on the time domain signal in the kth subspace to obtain a signal; constructing a corresponding fractional Doppler amplitude function and a fitness function for the signal in the kth subspace, and solving them using a DWO algorithm to obtain channel matching parameters; performing channel matching in the D / D domain for the kth subspace based on the channel matching parameters; and calculating delay-Doppler domain channel state information after completing the DD domain channel matching. The obtained delay-Doppler domain channel state information is fed back to the transmitter in the multipath channel model. This method significantly improves the system's frequency band utilization and enhances system reliability.

Description

Technical Field

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

[0002] In recent years, wireless communications have developed rapidly. Next-generation mobile communication systems need to support high-frequency bands and high-speed 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, V2X channels change rapidly. In rapidly time-varying channels, inter-carrier interference (ICI) becomes a serious problem, causing the bit error rate performance of traditional orthogonal frequency division multiplexing (OFDM) systems to deteriorate. 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 the 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, the pilot design and channel estimation of OTFS 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 design. 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-to-vehicle communications where wireless links are easily obstructed, which seriously affects the quality of V2X communications 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 system communication quality. IRS can produce controllable amplitude and phase shift changes to the incident signal, changing the uncontrollable characteristics of traditional wireless channels. This breaks through the limitations of traditional network wireless propagation channels and realizes 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 response to the shortcomings of the existing technology, the present invention proposes an IRS-assisted method for reducing pilot overhead and enhancing link reliability in a vehicle network environment. For the IRS-assisted vehicle network communication model, multi-antenna technology, V2X technology, and optimization algorithm technology are combined. 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 includes 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 k-th subspace, and the channel matching parameters are obtained by 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 using 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 guard 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, the i-th IRS to the target vehicle, and the base station to the target vehicle, μ tr,i 、μi,re 、μ d represents the path loss coefficient of the corresponding path, β(n) is the path loss coefficient of 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] As an advantage, 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] Where, 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 arrival angle of the received signal, n r is the number of antennas.

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

[0025] Preferably, the fractional Doppler amplitude function and the fitness function are constructed as follows:

[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 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 guard interval in 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 objective function Q corresponding to X is calculated as follows:

[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 and r2 are random numbers between (0, 1), and the random number C is used to determine the distance d between the current solution and the optimal solution;

[0037] For each 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 optimal 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. 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 parameter in the kth subspace, is the compensation angle of the k-th subspace wave number spectrum shift, They represent the resolution of the DD domain delay and Doppler dimensions, Δf represents the system subcarrier spacing, and M and N are the number of grids divided into 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 vehicle speed is v, the delay and Doppler vector obtained by channel estimation are τ and f, then the maximum Doppler dimension guard interval that can be set by the transmitter can be calculated according to the following formula: and maximum delay dimension protection interval

[0052]

[0053] Where ||·|| represents the norm.

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

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

[0056] 2. Combining the OTFS system with multi-antenna reception technology projects the received signal into different orthogonal subspaces for processing, reducing inter-path interference. Simultaneously, combined with channel matching technology, the overall pilot overhead is reduced. Simulation results verify the effectiveness and convergence of the proposed method.

[0057] 3. An adaptive method is applied to address the inflexibility of pilot overhead in the OTFS system. By changing the pilot guard interval setting from relying on fixed channel parameters to relying on the channel estimate of the previous frame, the large amount of pilot overhead waste during actual vehicle driving is effectively reduced. Simulation results verify the effectiveness and convergence of the proposed method.

[0058] 4. This paper proposes a Desert Wolf Optimization (DWO) algorithm, which optimizes channel matching parameters within a subspace to achieve optimal channel estimation. Simulation results demonstrate that this algorithm achieves satisfactory system throughput and bit error rate performance in the connected vehicle (IoV) 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 following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0060] Figure 1 This is a principle framework diagram of the method for reducing pilot overhead and enhancing link reliability in an IRS-assisted 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 expected effect of the DWO algorithm in the present invention in different scenarios;

[0063] Figure 4 This is a schematic diagram of the effect expected to be achieved by the DWO algorithm of the present invention 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 chart of the DWO algorithm and the GWO algorithm in the application scenario of the present invention;

[0066] Figure 7 1 is a comparison diagram of bit error rates under different IRS numbers and different subspace numbers in the present invention;

[0067] Figure 8 This is a comparison chart of the throughput (the proportion of correctly transmitted bits to the total number of bits, and the comparison of 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 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, 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", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, features defined as "first", "second", etc. 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 expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on 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 the characteristics of orthogonal subspace projection and IRS reflection enhancement in wireless communications, improve the system's frequency band utilization, and combine it 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 network 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 in FIG, by deploying IRS on buildings and roadside units, a virtual LOS can be established to enhance communication and improve the diversity of the system when LOS is blocked.

[0075] It should be noted that the establishment of the IRS-assisted multipath channel model is a conventional technical means, so this embodiment will not further elaborate on how to establish the IRS-assisted multipath channel model.

[0076] Furthermore, the signal received by a 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, the i-th IRS to the target vehicle, and the base station to the target vehicle, μ tr,i 、μ i,re 、μ d represents the path loss coefficient of the corresponding path, β(n) is the path loss coefficient of 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 antenna array's broadside. 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 antenna array's broadside, 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 This is the overall algorithm block diagram.

[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] Where, is the filter vector of the kth subspace:

[0085]

[0086] Among them, Δ r The normalized receive antenna separation defined by the carrier wavelength is given by 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 at a certain basis vector. 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 using the DWO method proposed in this embodiment. First, we will introduce how to establish the objective function. For the signal in the kth subspace Denote the time delay and Doppler of each path 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 area 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 Y, 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, and 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, i.e.

[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 a 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 performing channel estimation at the receiver. 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 first scenario, there is no missing path in the selected area, as shown in Figure 4 As shown in FIG, in another scenario, the path with relatively high power is retained in the selected area. Figure 5 This is a comparison chart 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 figure shows the 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 ability and local development ability.

[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 parameter in the kth subspace, is the compensation angle of the k-th subspace wave number spectrum shift. 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 into the delay-Doppler plane of the OTFS system.

[0115] Figure 7 This is a comparison diagram of the bit error rate 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, we calculate the Delay-Doppler Channel State Information (DD_CSI) using our proposed adaptive pilot overhead scheme. Assuming the minimum distance between the vehicle and the roadside IRS is r, the interframe interval is ΔT, the maximum vehicle speed is v, and the delay and Doppler vectors obtained from the channel estimation are τ and f, we can calculate DD_CSI using 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 Feedback to the transmitter can then dynamically adjust the pilot protection interval of each frame, thereby further saving pilot overhead. Figure 8 As shown in the figure, the gain in frequency band utilization obtained by the proposed algorithm is evaluated. 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. It will be apparent to those skilled in the art that various changes, modifications, substitutions, and variations of these embodiments, including components, without departing from the principles and spirit of the present invention are still 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 network 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 k-th subspace, and the channel matching parameters are obtained by the DWO algorithm. 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; 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 using 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 guard interval of each frame.

2. The method for reducing pilot overhead and enhancing link reliability in an IRS-assisted vehicle network environment according to claim 1, characterized in that: 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 : Where, 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 arrival angle of the received signal, n r is the number of antennas.

3. The method for reducing pilot overhead and enhancing link reliability in an IRS-assisted vehicle networking environment according to claim 2, characterized in that: described The corresponding power azimuth spectrum has at least one main lobe, and the different The main lobe position and width are different.

4. The method for reducing pilot overhead and enhancing link reliability with IRS assistance in a connected vehicle environment according to claim 3, characterized in that: The channel matching parameters include time domain matching parameters and Doppler domain matching parameters.

Images