An aris assisted backscatter vehicular networking communication system

Abstract

The application discloses an ARIS-assisted backscattering vehicle networking system, which comprises a radio frequency source (RS), a vehicle-mounted backscattering tag (Tag), an active intelligent reflecting surface (ARIS) and a reader (RD). Each reflecting unit of the ARIS simultaneously modulates the phase of the carrier signal emitted by the RS and amplifies the signal, and the Tag backscatters its own information to the RD on the roadside unit by using the amplified carrier signal. The application aims to maximize the achievable rate at the RD under the power constraint conditions at the RS and the ARIS, fully utilize the characteristics of the ARIS, significantly improve the capacity gain of the backscattering vehicle networking system, and realize the fusion of cellular networks after the RD receives the information and forwards the information to a base station (BS), so that the communication distance of the backscattering is expanded, the overspeed sensing and early warning of vehicles, the license plate information recognition and the driving track prediction are realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of wireless communication networks, and mainly relates to an ARIS-assisted backscattering vehicle networking communication system. BACKGROUND

[0002] In recent years, with the wide application of the Internet of Things in smart home, industrial logistics, agricultural production, city management and the like, the rapidly growing massive connection demand of the Internet of Things brings new challenges to future wireless communication systems, and the information interaction demand of hundreds of billions or even thousands of billions of Internet of Things devices puts forward higher requirements on network resource utilization, system energy consumption, system coverage range and data transmission rate.

[0003] The backscattering communication system becomes one of the key technologies for constructing the future Internet of Things due to its low power consumption, low cost and high spectrum efficiency. The scattering device sends data by modulating and reflecting the radio frequency source signal without generating a radio frequency signal by itself. The double-station backscattering communication system realizes the separation of the receiver and the transmitter, improves the system flexibility, and avoids the double-path loss in the single-station type, and weakens the double-far problem.

[0004] As a revolutionary technology for wireless channel control, the intelligent reflecting surface (RIS) has become one of the key technologies of the 6G system. In vehicle networking, the communication link between mobile vehicles is easily interrupted due to large channel fading, and the reconfigurable intelligent surface (RIS) can improve the communication environment. The active intelligent reflecting surface (ARIS) can overcome the "multiplicative fading" effect in the traditional RIS. Compared with the traditional passive RIS, the ARIS has the characteristics that each reflecting unit can simultaneously adjust the phase of the signal and amplify the signal, which can significantly improve the energy efficiency of the wireless communication system, and has important applications in improving the user SNR, green and safe communication, wireless power communication and the like.

[0005] The ARIS is used in the backscattering communication system, which can effectively improve the propagation environment, improve the coverage range, transmission rate and system capacity, and has important theoretical value and practical significance for constructing a practical backscattering communication system.

[0006] In the existing literature, the backscattering tags (Tag) in the vehicle networking scene are mostly arranged on the roadside, lack flexibility and require a large amount of energy resources. And the "multiplicative fading" effect in the traditional RIS is not considered. SUMMARY

[0007] The technical problem to be solved by the present application is to provide an ARIS-assisted backscattering vehicle networking communication system to overcome the shortcomings of the prior art, to determine the optimal RS beamforming vector and ARIS reflection coefficient matrix with the maximum power limit at the RS and ARIS as constraints, and to maximize the achievable rate at the RD.

[0008] To achieve the above object, the solution of the present application is:

[0009] An ARIS-assisted backscattering V2X communication system, comprising a radio frequency source RS, a vehicle-mounted backscattering tag Tag, an active intelligent reflecting surface ARIS and a reader RD; each reflecting unit in the ARIS simultaneously performs phase modulation and signal amplification on the carrier frequency signal transmitted by the RS; the Tag uses the amplified carrier frequency signal to backscatter its own information to the RD, completing backscattering communication.

[0010] Further, the channel coefficients between the RS and the ARIS, the ARIS and the Tag, and the Tag and the RD in the system all obey the Rician fading model.

[0011] Further, the system establishes an optimization problem with the maximum power limit at the RS and the ARIS as constraints and the maximum achievable rate at the RD as the target Determine the optimal RS beamforming vector and ARIS precoding matrix.

[0012]

[0013] s.t.C1:

[0014] C2:

[0015] wherein C1 and C2 are the power constraints at the RS and the ARIS respectively, denotes the maximum transmit power at the RS, denotes the maximum reflection power of the ARIS; R(w,Θ) denotes the achievable rate at the RD, w denotes the RS beamforming vector, Θ denotes the ARIS reflection coefficient matrix, α is the reflection coefficient of the Tag, and G denotes the channel between the RS and the ARIS, denotes the noise power at the ARIS.

[0016] Further, the achievable rate at the RD is wherein h denotes the backscattering channel between the Tag and the RD, f denotes the channel between the ARIS and the Tag, and σ 2 denotes the noise power at the RD.

[0017] Further, by introducing auxiliary variables ρ, is re-expressed as problem

[0018]

[0019] s.t.C1:​

[0020] C2:

[0021] where, denotes taking the real part.

[0022] Further, by alternating optimization of w, Θ, ρ, solving obtain a local optimal solution:

[0023] Step 1: Fix w, Θ, and solve for ρ solving equation obtain the optimal solution ρ opt :

[0024]

[0025] where, the intermediate variable

[0026] Step 2: Fix (w, Θ, ρ), and solve for obtain the optimal solution

[0027]

[0028] Step 3: Fix establish the optimization problem for w as follows, and solve to obtain the optimal solution w:

[0029]

[0030] Step 4: Fix let f H ΘG = ψ H diag(f H )G, where is the vectorized ARIS precoding matrix, Θ = diag(ψ H ), further reformulate as and solve to obtain the optimal solution ψ opt :

[0031]

[0032]

[0033] where, I N is the identity matrix;

[0034] ​Step 5: According to the results obtained in steps 1-4, the achievable rate at RD is calculated

[0035] Step 6: Repeat steps 1-5 to update w, Θ, ρ, Until the preset convergence condition is met, output the optimal RS beamforming vector, ARIS reflection coefficient matrix, and maximum value of the achievable rate at RD.

[0036] Further, ψ opt By using the Lagrange multiplier method, we have:

[0037] ψ opt = (Ω + uΠ) -1 v

[0038] Where u is the Lagrange multiplier.

[0039] Further, u satisfies the complementary relaxation condition of C2, and the optimal Lagrange multiplier u is obtained by binary search opt .

[0040] Further, the optimization problem of w in step 3 is solved by CVX.

[0041] Compared with the prior art, the present application has the following advantages:

[0042] On the one hand, RS serves as a radio frequency source to amplify the carrier frequency signal through ARIS assistance to serve vehicles, and the Tag on the vehicle transmits its information to the RD on the roadside unit through backscattering, which can effectively perform vehicle overspeed perception warning, license plate information recognition, and driving trajectory prediction, and expand the communication distance.

[0043] On the other hand, with the maximum power constraint at RS and ARIS, the optimal RS beamforming vector w and ARIS reflection coefficient matrix Θ can be determined to maximize the achievable rate at RD. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 It is a model diagram of an ARIS-assisted backscattering vehicle networking communication system;

[0045] Figure 2 It is a method for establishing an ARIS-assisted backscattering vehicle networking communication system achievable rate maximization model;

[0046] Figure 3 It is an optimization method for maximizing the achievable information rate under the power constraint of RS and ARIS. DETAILED DESCRIPTION

[0047] The present application will be further described in detail below with reference to specific embodiments.

[0048] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be described in detail below with reference to the drawings and specific embodiments.

[0049] According to the ARIS assisted backscattering vehicle networking communication system provided by the embodiment of the present application, as shown in the figure, Figure 1 The system is composed of an RS with L antennas, an ARIS with N reflecting units, a Tag with a single antenna on a vehicle and an RD with a single antenna. The RS as a radio frequency source cannot directly communicate with the Tag due to the obstruction of buildings, trees and the like. The carrier frequency signal transmitted by the RS is amplified by the ARIS and then received by the Tag. The Tag uses the carrier frequency signal of the RS to backscatter its own information to the nearby RD to complete the backscattering communication. The system can realize the overspeed sensing and early warning of vehicles, license plate information recognition and driving trajectory prediction.

[0050] In the embodiment, each reflecting unit of the ARIS can simultaneously adjust the phase of the signal and amplify the signal, thereby relieving the fading effect of the cascaded channel and improving the capacity gain of the wireless communication system. The backscattering Tag on the vehicle serves as an electronic license plate and moves with the vehicle, thereby realizing the flexibility of the Tag. The RD is hung on a roadside unit. After receiving the information of the backscattering Tag, the RD forwards the information to the nearby BS, thereby realizing the fusion of the cellular network and expanding the communication distance of the backscattering.

[0051] As shown in the figure, Figure 1 The channel coefficients between the RS and the ARIS, the ARIS and the Tag and the Tag and the RD in the system all obey the Rician fading model. Among them, the solid line represents a continuous wave signal, and the dashed line represents a backscattering signal.

[0052] As shown in the figure, Figure 2 The flow chart of the ARIS assisted backscattering vehicle networking communication system provided by the embodiment of the present application can maximize the rate, and the steps are specifically as follows:

[0053] Step 201: The ARIS reconfigures the wireless environment by changing the reflection coefficient matrix based on the instantaneous CSI, thereby improving the system performance. Each reflecting unit (RE) in the ARIS can amplify the incident signal based on the active load to relieve the fading effect of the cascaded channel. Among them, represents the amplification factor of the nth active element, and since the reflecting amplifier is integrated, p n may be greater than 1, n=1,…,N; θ m ∈[0,2π] represents the phase shift, m=1,…,N; the ARIS needs additional power to amplify the reflected signal, and the noise introduced by the ARIS element is Θz, which obeys the complex Gaussian distribution.

[0054] Linear precoding is used at the RS, and the beamforming vector is w, The received signal y at the vehicle's license plate (i.e., Tag) t may be expressed as:

[0055] y t = f H ΘGws(t) + f H Θz

[0056] where, are the channels of RS-ARIS and ARIS-Tag, respectively.

[0057] Step 202: Based on the parameters obtained in step 201, no signal processing is performed at the Tag, and the signal at the Tag is:

[0058]

[0059] where α is the reflection coefficient of the Tag, α ∈ [0, 1], and the Tag is semi-passive in this case, with the energy required by the Tag circuit being provided by the vehicle power supply; b(t) is the baseband signal of the Tag itself,

[0060] The signal received by the RD is:

[0061]

[0062] where denotes the backscattering channel of Tag-RD, n ~ CN(0, σ 2 is the noise signal at the RD.

[0063] Step 203: Based on the results obtained in step 202, the SINR at the RD is:

[0064]

[0065] The achievable information rate at the RD is expressed as:

[0066]

[0067] Step 204: Based on the parameters obtained in step 201, the RS transmit power P BS and the reflected power P A after ARIS amplification can be expressed as:

[0068]

[0069]

[0070] Step 205: According to the results calculated in the above steps, subject to the maximum power of RS and ARIS, the following optimization problem is established to maximize the achievable rate:

[0071]

[0072] s.t.C1:

[0073] C2: where C1, C2 are the power constraints at RS and ARIS, respectively. denotes the maximum transmit power at RS, denotes the maximum reflection power at ARIS.

[0074] By introducing auxiliary variables ρ∈R + , the original problem can be equivalently reformulated as follows:

[0075]

[0076] s.t.C1:

[0077] C2:

[0078] where the function denotes the real part of .

[0079] As shown in Figure 3 , a local optimal solution can be obtained by alternately optimizing the variables w, Θ, ρ, and so on until a preset convergence condition is met (in this embodiment, the convergence condition is set to be that the difference between two adjacent optimizations is less than 1). The specific steps are as follows Step 206: Fixing

[0080] solving the equation to obtain the optimal ρ:

[0081]

[0082] where

[0083] Step 207: Fixing (w, Θ, ρ), solving the equation to obtain the optimal

[0084]

[0085] Step 208: Fixing​ An optimization model for building the beamforming vector w is established:

[0086]

[0087] s.t.C1:

[0088] C2: The above convex optimization problem is solved by CVX.

[0089] Step 209: Fixing Let f H ΘG=ψ H diag(f H )G, where is the vectorized ARIS precoding matrix, Θ=diag(ψ H ), and the problem is further reformulated as follows:

[0090]

[0091] s.t.C2:

[0092] where,

[0093] The optimal solution ψ opt of ψ can be obtained by using the Lagrange multiplier method and is given by:

[0094] ψ opt =(Ω+uΠ) -1 v

[0095] where u is the Lagrange multiplier, which should satisfy the complementary relaxation condition of the power constraint C2. The optimal Lagrange multiplier u opt is obtained by using binary search.

[0096] Step 210: According to the results obtained in steps 206, 207, 208, and 209, calculate the achievable rate at RD and determine whether it converges.

[0097] Step 211: Repeat steps 206-210 to update w, Θ, ρ, until converges, and output the optimal RS beamforming vector, ARIS reflection coefficient matrix, and the maximum value of the achievable rate at RD.

[0098] The above examples only illustrate the technical idea of the present application, and cannot be used to limit the protection scope of the present application. Any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the present application.

Claims

1. An ARIS-assisted backscattering vehicular networking communication system, characterized by, The system comprises a radio frequency source RS, a vehicle-mounted backscattering tag Tag, an active intelligent reflecting surface ARIS and a reader RD; each reflecting unit in the ARIS simultaneously performs phase modulation and signal amplification on the carrier frequency signal transmitted by the RS; the Tag uses the amplified carrier frequency signal to backscatter its own information to the RD, thereby completing backscattering communication. The system takes the maximum power constraint at the RS and ARIS as a constraint, and maximizes the achievable rate at the RD as an objective, to establish an optimization problem determining the maximum value of the achievable rate at the RD, the optimal RS beamforming vector and the ARIS reflection coefficient matrix: wherein C1, C2 are the power constraints at RS and ARIS, respectively, denotes the maximum transmit power at RS, denotes the maximum reflection power at ARIS; R(w, Θ) denotes the achievable rate at RD, w denotes the RS beamforming vector, Θ denotes the ARIS reflection coefficient matrix, a is the reflection coefficient of Tag, G denotes the channel between RS and ARIS, denotes the noise power at ARIS; By introducing an auxiliary variable p, will be reformulated as a problem wherein denotes taking the real part.

2. An ARIS assisted backscatter vehicular networking communication system according to claim 1, wherein, Channel coefficients between the RS and the ARIS, the ARIS and the Tag and the Tag and the RD all conform to a Rician fading model.

3. An ARIS assisted backscatter vehicular networking communication system according to claim 1, wherein, The RD is hung on a roadside unit.

4. An ARIS assisted backscatter vehicular networking communication system according to claim 1, wherein, RD where h denotes the backscatter channel between the Tag and the RD, f denotes the channel between the ARIS and the Tag, σ 2 denotes the noise power at the RD.

5. An ARIS assisted backscatter vehicular networking communication system according to claim 1, wherein, By alternating optimization of w, Θ, p, solving obtaining a local optimum solution: Step 1: Fixing Solving the equation Obtaining the optimal solution p of p opt : wherein the intermediate variable Step 2: Fix (w, Θ, p) by solving the equation yielding the optimal solution Step 3: Fixing An optimization problem for w is set up as follows, and the optimal solution for w is obtained by solving: Step 4: Fixing Let f H ΘG= ψ H diag(f H )G, where is the vectorized ARIS precoding matrix, Θ = diag(ψ H ), is further reformulated as and solved to obtain the optimal solution ψ opt : wherein I N is the identity matrix; Step 5: Based on the results from steps 1 to 4, the achievable rate at RD is calculated Step 6: Repeat steps 1-5, updating w, Θ, p, Until a preset convergence condition is met, output the optimal RS beamforming vector, ARIS reflection coefficient matrix, and maximum value of the achievable rate at RD.

6. An ARIS assisted backscatter vehicular networking communication system according to claim 5, wherein, Ψ opt By employing the Lagrange multiplier method, we obtain ψ opt = (Ω + uΠ) -1 v Wherein u is a Lagrange multiplier.

7. An ARIS assisted backscatter vehicular networking communication system according to claim 6, wherein, u satisfies the complementary slackness condition of C2, the optimal Lagrange multiplier u is obtained by binary search opt .

8. An ARIS assisted backscatter vehicular networking communication system according to claim 5, wherein, The optimization problem of w in step 3 is solved by using CVX.

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