Method for maximizing sum rate in dual-RIS-assisted backscatter communication system

Abstract

The invention discloses a method for maximizing the sum rate in a backscatter communication system assisted by two RISs (Radio Information System), which is suitable for the backscatter communication system assisted by the two RISs. Firstly, an optimization problem of maximization and rate in the double-RIS-assisted backscatter communication system is established, optimization parameters are RIS phase shift, power distribution and a reflection coefficient of backscatter equipment, and constraint conditions are power limitation and threshold requirements for a signal to interference plus noise ratio when a user detects a signal; then, obtaining a solution of a reflection coefficient of the backscattering equipment, separating an RIS phase shift optimization problem from the optimization problem, and solving the optimization problem by adopting an iterative method; and finally, substituting the obtained reflection coefficient of the backscattering equipment and the RIS phase shift into an optimization problem of maximizing the sum rate, and solving the optimization problem to obtain power distribution.

Description

Technical Field

[0001] The present invention belongs to the field of communications, and particularly relates to a method for maximizing the sum rate in a dual-RIS-assisted backscatter communication system. Background Art

[0002] A reconfigurable intelligent surface (RIS) is a plane composed of a large number of low-cost passive and passive reflection elements, and each element can independently change the phase and amplitude of the incident signal. If placed at an appropriate position between a base station (BS) and a user, the RIS can reflect the BS's transmitted signal to a user at a farther distance, and can also reflect the transmitted signal of a user at a farther distance to the BS. Therefore, the RIS can improve the system capacity and expand the network coverage. Compared with relay technology, the RIS passively reflects the incident signal without actively processing the signal, which not only has a lower cost but also avoids additional delay. In addition, the RIS is light in weight and can be easily installed or removed on walls, ceilings, building facades or advertising panels. Therefore, RIS devices can be deployed and integrated in an actual network at a lower cost.

[0003] Backscatter communication is an important wireless communication means with high spectral efficiency and low energy consumption. It uses the existing signals in the surrounding environment as carriers, and completes the information loading through the secondary modulation of the electromagnetic environment signals in the radio frequency domain, thereby avoiding occupying new spectrum resources and reducing energy consumption through passive transmission. It is a key technology for realizing wide-area low-energy-consumption wireless network coverage. However, the performance of backscatter communication is affected by environmental radio frequency sources and uncontrollable wireless fading channels. Environmental radio frequency sources are usually dynamically random and uncontrollable, which is very unfriendly to passive devices. Especially when the signal propagation environment is poor, it is only possible to reduce the negative impact of the adverse propagation environment on the system performance by combining different technologies such as cooperative relay, RIS, and non-orthogonal multiple access (NOMA). Existing research has shown that applying RIS to a backscatter communication system can improve its energy efficiency and spectral efficiency, and reduce the impact of the unpredictable radio frequency environment on the system performance; the combination of NOMA and backscatter communication allows the backscatter receiver (BR) and the backscatter device (BD) to utilize the non-orthogonal resources originally belonging to NOMA, thereby improving the spectral efficiency of the system and increasing the system capacity.

[0004] However, applying backscatter communication to the NOMA system still cannot solve the problem of poor signal quality for cell-edge users. If RIS is introduced into the combined system of backscatter and NOMA, each reflection element of RIS can independently adjust the amplitude and phase of the incident signal, enabling the signal to be transmitted to the desired location, thereby expanding the communication coverage and increasing the throughput. Therefore, scholars have conducted research on the system combining RIS, backscatter communication, and NOMA. The literature "Resource allocation of backscatter communication based on reconfigurable intelligent surface" proposed two RIS-assisted backscatter communication system models, including one BS, one BD, two RISs, and two NOMA users. This literature established an optimization problem to maximize the backscatter communication rate of the system and solved this optimization problem. However, this literature only considered the backscatter communication rate and did not take into account the rates of the two NOMA users. Summary of the Invention

[0005] In summary, to solve the existing technical problems, the present invention provides a method for maximizing the sum rate in a dual-RIS-assisted backscatter communication system, which is applicable to a two-RIS-assisted backscatter communication system.

[0006] First, an optimization problem for maximizing the sum rate in a dual-RIS-assisted backscatter communication system is established, with the optimization parameters being the RIS phase shift, power allocation, and BD reflection coefficient. The constraint conditions are power limitations and the threshold requirements for the signal-to-interference-plus-noise ratio when detecting signals by users. Then, the solution of the BD reflection coefficient is obtained, and the RIS phase shift optimization problem is separated from this optimization problem, and an iterative method is used to solve this optimization problem. Finally, the obtained BD reflection coefficient and RIS phase shift are substituted into the optimization problem of maximizing the sum rate, and this optimization problem is solved to obtain the power allocation.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] A method for maximizing the sum rate in a dual-RIS-assisted backscatter communication system, which is applicable to a two-RIS-assisted backscatter communication system, includes the following steps:

[0009] Step A: Establish an optimization problem for maximizing the sum rate of the system, with the optimization parameters being the RIS phase shift, power allocation, and reflection coefficient of the backscatter device. This optimization objective is expressed by the formula:

[0010]

[0011] s.t.p 1 +p2 = P ≤ P max

[0012] p 2 ≥ p 1

[0013] p i ≥ 0, i ∈ {1, 2}

[0014]

[0015]

[0016] α ∈ [0, α 0

[0017]

[0018] where p 1 and p 2 are the powers allocated to the near - distance user and the far - distance user respectively, p 1 ≤ p 2 , P is the total power of the base station, P = p 1 + p 2 , P max is the maximum transmission power of the base station, and are the phase - shift matrices of two RISs respectively, θ n ∈ [0, 2π), n = 1, 2, …, N, N is the number of reflection elements of each RIS, R 1 = log 2 (1 + γ 1→1 ), γ 1→1 is the signal - to - interference - plus - noise ratio when the near - distance user detects its desired received signal, α is the reflection coefficient of the backscatter device, h 1 , h b and g b represent the channels between the base station and the near - distance user, between the base station and the backscatter device, and between the backscatter device and the near - distance user respectively, σ 2 is the variance of additive white Gaussian noise, R 2 = log 2 (1 + γ 2→2 ), γ 2→2 is the signal - to - interference - plus - noise ratio when the far - distance user detects its desired received signal, H = |h r Θ 1 SΘ 2 g r |, |·| represents the absolute value, h r 、g​r and \(S\) denote the channels between the base station and the first RIS, between the second RIS and the far - away user, and between the first RIS and the second RIS, \(R\) BD =\(\log\) 2 (1 + \(\gamma\) 1→b ) \(\gamma\) 1→b is the signal - to - interference - plus - noise ratio when the near - distance user detects the backscattered signal, and \(\gamma\) 1→2 is the signal - to - interference - plus - noise ratio when the near - distance user detects the desired received signal of the far - away user. is the threshold requirement for the signal - to - interference - plus - noise ratio when the near - distance user detects the signal, and \(\gamma\) 2 min is the threshold requirement for the signal - to - interference - plus - noise ratio when the far - away user detects the signal. \(\zeta\) is the energy required by the backscatter communication circuit, and \(\eta\) is the energy conversion efficiency of the backscatter device;

[0019] Step B: Simplify the optimization problem in Step A to:

[0020]

[0021] s.t. \(p\) 1 +\(p\) 2 =\(P\leq P\) max

[0022] \(p\) 2 \(\geq p\) 1

[0023] \(p\) i \(\geq0\), \(i\in\{1,2\}\)

[0024]

[0025]

[0026] \(\alpha\in[0,\alpha\) 0 )

[0027]

[0028] Step C: Let the solution of the variable \(\alpha\) in the optimization problem in Step B be Separate the RIS phase - shift optimization problem from Step B and solve this optimization problem;

[0029] Step D: Substitute the solution of the RIS phase - shift obtained in Step C and the solution of \(\alpha\) into the optimization problem in Step B, and get:

[0030]

[0031] s.t. \(p\)1 +p 2 = P ≤ P max

[0032] p 2 ≥ p 1

[0033] p i ≥ 0, i ∈ {1, 2}

[0034]

[0035]

[0036] wherein, H * is the value obtained by substituting the solution of the RIS phase shift obtained in step C into |h r Θ 1 SΘ 2 g r |;

[0037] Step E: Solve the optimization problem in step D. If |h 1 | 2 σ 2 - H *2 c 2 ≥ 0, let If |h 1 | 2 σ 2 - H *2 c 2 < 0, let wherein, Let p 2 = P - p 1 .

[0038] Furthermore, the said step C includes the following steps:

[0039] C1: Let the solution of the variable α in the optimization problem in step B be

[0040] C2: Construct the RIS phase shift optimization problem:

[0041]

[0042] C3: Set the value of the threshold ε, set the maximum number of iterations K, let k = 1, θ n = 0, n = 1, 2,..., N;

[0043] C4: Substitute the value of θ n into Θ 1 and calculate v = h rΘ 1 Let \(S\) be denoted by \(v\), n where \(v_n\) represents the \(n\)-th element of \(v\). Let \(\arg(\cdot)\) denote the phase angle, \(n = 1, 2, \ldots, N\). Here, \(g\) r,n is denoted by r where \(g_n\) represents the \(n\)-th element of \(g\). Let Let \(k=k + 1\);

[0044] C5: Substitute the value of obtained in step C4 into \(\Theta\) 2 and calculate \(w = S\Theta\) 2 where \(g\) r is denoted by \(w\). Let \(w_n\) represent the \(n\)-th element of \(w\). Let \(\theta\) n be \(\theta=- \arg(w_n)-\arg(h_n)\), \(n = 1, 2, \ldots, N\). Here, \(h\) n is denoted by n where \(h_n\) represents the \(n\)-th element of \(h\). Let r,n Let \(k=k + 1\); r,n is denoted by r where \(h_n\) represents the \(n\)-th element of \(h\). Let Let \(k=k + 1\);

[0045] C6: Repeat steps C4 and C5 until \(H - \hat{H}\leq\epsilon\) or \(k = K\). At this time, the values of \(\theta\) k and k-1 are the solutions to the optimization problem in step C2 and also the variables \(\theta\) n and in the optimization problem in step B, \(n = 1, 2, \ldots, N\). n and in the optimization problem in step B, \(n = 1, 2, \ldots, N\).

[0046] Advantageous effects:

[0047] For two RIS-assisted backscatter communication systems, there is no literature on resource allocation methods to maximize the system sum rate. The method proposed in the present invention optimizes the RIS phase shift, power allocation, and BD reflection coefficient according to the threshold requirements of the signal-to-interference-plus-noise ratio when users detect signals, so as to maximize the system sum rate. Compared with the existing resource allocation methods for maximizing the backscatter communication rate in the same system, the proposed scheme also considers the rates of two NOMA users and maximizes the sum of the rates of the two NOMA users and the backscatter communication rate. Description of the drawings

[0048] Figure 1 is the system model diagram of the embodiment of the present invention;

[0049] Figure 2 is the flowchart of the present invention. Detailed implementation manners

[0050] Combined with an embodiment below, the present invention will be further described in detail. The model of this embodiment is the same as the model in the literature "Resource allocation of backscatter communication based on reconfigurable intelligent surface". The system includes a BS, a BD, two RISs, and two NOMA users. S1 is a cell center user and can communicate with the BS through a direct link and a backscatter link. S2 is a cell edge user and there is no direct link with the BS, and can only communicate with the BS with the assistance of the two RISs. The BD has a backscatter communication circuit and an energy harvesting circuit. The energy collected by the BD can only be used immediately or dissipated. The two RISs are represented by RIS1 and RIS2 respectively, and each RIS has N reflection elements.

[0051] S1 and S2 are a pair of NOMA users. S1 is a near user and S2 is a far user. The BS superimposes the desired received signal of S1 and the desired received signal of S2 and sends them out. Both S1 and the BD receive the transmission signal of the BS, and the BD forwards its received signal to S1. Therefore, S1 is not only a NOMA user but also a BR. With the assistance of the two RISs, S2 receives the transmission signal of the BS.

[0052] Let g r , h r and S represent the channel between RIS2 and S2, the channel between the BS and RIS1, and the channel between RIS1 and RIS2 respectively. The order of g r is N×1, the order of h r is 1×N, and the order of S is N×N. Let h 1 , h b and g b represent the channel between the BS and S1, the channel between the BS and the BD, and the channel between the BD and S1 respectively. The orders of h 1 , h b and g b are all 1×1. The phase shift matrices of RIS1 and RIS2 are and θ n ∈ [0, 2π), n = 1, 2,..., N.

[0053] The transmission signal of the BS is expressed as:

[0054]

[0055] Among them, x 1 and x 2They are the expected received signals of S1 and S2, E[|x 1 | 2 = E[|x 2 | 2 = 1, E[·] represents the mathematical expectation, |·| represents the absolute value, p 1 and p 2 are powers, p 1 ≤ p 2 .

[0056] The received signal at BD is:

[0057] x b = h b x(2)

[0058] BD divides the received signal energy into two parts. One part is used for energy harvesting with a proportion of 1 - α, and the other part is used for backscatter communication with a proportion of α. α is also called the reflection coefficient. The backscattered signal sent by BD is expressed as:

[0059]

[0060] where c is the signal generated by BD itself, and E[|c| 2 = 1. The energy E BD harvested by BD is expressed as:

[0061] E BD = η(1 - α)P|h b | 2 (4)

[0062] where P is the transmission power of the BS, P = p 1 + p 2 , and η is the energy conversion efficiency of BD.

[0063] Assume that the energy required for the backscatter communication circuit is ζ. Only when η(1 - α)P|h b | 2 ≥ ζ can BD successfully backscatter the signal. When the equation holds, the value of the reflection coefficient α of BD is α 0 is the optimal BD reflection coefficient. If the energy harvested by BD is not enough to maintain the backscatter communication circuit, if BD uses less energy in backscatter communication, resulting in a decrease in the backscatter communication efficiency.

[0064] The received signal of S1 is expressed as:

[0065]

[0066] where nu,1 is additive white Gaussian noise with a mean of 0 and a variance of σ 2 . is the backscattered signal received by S1. S1 can detect the backscattered signal only when the direct signal is known.

[0067] Since S1 is a near - user and S2 is a far - user, assume that the channel gain from the BS to S1 is better than the channel gain from the BS to S2, i.e., |h 1 |≥|h r Θ 1 SΘ 2 g r |. S1 uses the successive interference cancellation method to detect signals and detects x 2 , x 1 and c in sequence. The signal - to - interference - plus - noise ratio (SINR) when S1 detects x 2 is:[[]]

[0068]

[0069] After S1 cancels x 2 from the received signal, it detects x 1 . The SINR when S1 detects x 1 is:[[]]

[0070]

[0071] After S1 cancels x 2 and x 1 from the received signal, it detects c. The SINR when S1 detects c is:[[]]

[0072]

[0073] The received signal of S2 is:[[]]

[0074] y 2 = h r Θ 1 SΘ 2 g r x + n u,2 (9)

[0075] where n u,2 is additive white Gaussian noise with a mean of 0 and a variance of σ 2 . Since S2 is a far - user, S2 treats x 1 as interference and detects x 2 . The SINR is:[[]]

[0076]

[0077] where H = |h r Θ 1SΘ 2 g r |。

[0078] The backscatter communication rate of BD is expressed as:

[0079]

[0080] The rates of S1 and S2 are respectively:

[0081]

[0082]

[0083] The optimization objective of the proposed scheme is: to maximize the sum rate of the system, and the optimization parameters are the RIS phase shift, power allocation, and BD reflection coefficient. This optimization objective is expressed by the formula as:

[0084]

[0085] where, is the threshold requirement for the signal-to-interference-plus-noise ratio when the user detects the signal, ensures that S1 can correctly detect x 1 and x 2 , ensures that S2 can correctly detect x 2 . P max is the maximum transmit power of the BS. It is assumed that P max is large enough to meet the threshold requirement for the signal-to-interference-plus-noise ratio when the user detects the signal. α ∈ [0, α 0 ensures the normal operation of the backscatter communication circuit.

[0086] Substituting equations (11), (12), and (13) into the optimization objective function in equation (14), we can obtain:

[0087]

[0088] Since the logarithmic function is a monotonically increasing function, the optimization objective function in equation (14) can be equivalently expressed as:

[0089]

[0090] Therefore, the optimization problem in equation (14) can be equivalently expressed as:

[0091]

[0092] In the optimization objective function in equation (17), is related to the RIS phase shift, while and Both are independent of the IRS phase shift. Therefore, the RIS phase shift optimization problem can be separated from Equation (17) and expressed as:

[0093]

[0094] The value of H should satisfy And γ 2→2 increases as H increases. γ 2→2 The larger γ is, that is, the larger H is, the more conducive it is to satisfy the constraint condition In addition, p 2 ≥ p 1 , is an increasing function of H. Therefore, the optimization problem in Equation (18) can be equivalently expressed as:

[0095]

[0096] According to the literature "Resource allocation of backscatter communication based on reconfigurable intelligent surface", the steps to solve the optimization problem in Equation (19) are as follows:

[0097] Step 1: Set the value of the threshold ε, set the maximum number of iterations K, let k = 1, θ n = 0 and n = 1, 2,..., N;

[0098] Step 2: Substitute the value of θ n into Θ 1 , calculate v = h r Θ 1 S, use v n to represent the nth element of v, and let arg(·) represents the phase angle, n = 1, 2,..., N, where, g r,n represents the nth element of g r , and let Let k = k + 1;

[0099] Step 3: Substitute the value of obtained in Step 2 into Θ 2 , calculate w = SΘ 2 g r , use w n to represent the nth element of w, and let θ n = -arg(w n ) - arg(h r,n ), n = 1, 2,..., N, where, h r,n represents the h rThe n-th element of, let Let k = k + 1;

[0100] Step 4: Repeat Step 2 and Step 3 until H k -H k-1 ≤ ε or k = K.

[0101] The θ obtained by the above 4 steps n and is the solution of the optimization problem in Equation (19), and is also the variable θ in the optimization problem in Equation (17) n and The solution. Substitute the θ obtained by the above 4 steps n and into |h r Θ 1 SΘ 2 g r | to obtain the maximum value of H, denoted by H * as shown.

[0102] As mentioned before, α 0 is the optimal BD reflection coefficient. Substitute and H = H * into the optimization objective function in Equation (17) to obtain:

[0103]

[0104] where,

[0105] At this time, the optimization problem in Equation (17) is expressed as:

[0106]

[0107] Next, deduce the value range of p 1 and p 2 Combined with the constraint condition p 1 + p 2 = P and the constraint condition it can be obtained that is a decreasing function of H. Therefore, when H = H * , obtains the minimum value, and the minimum value is That is From α = α 0 and the constraint condition it can be obtained that the value of p 1 satisfies From it can be obtained that Since so From α = α 0 and the constraint condition p 1 +p 2 =P and p 2 ≥p 1 It can be obtained that wherein Since p 1 +p 2 =P and p 2 ≥p 1 , p 1 The value range of is

[0108] Let Find the first derivative of f(p 1 ) with respect to p 1 , it can be obtained that If |h 1 | 2 σ 2 -H *2 c 2 ≥0, f(p 1 ) is an increasing function of p 1 , then When, the optimization objective function in Equation (20) reaches the maximum value; if |h 1 | 2 σ 2 -H *2 c 2 <0, f(p 1 ) is a decreasing function of p 1 , then When, the optimization objective function in Equation (20) reaches the maximum value.

[0109] Combined with the flowchart of the present invention, that is Figure 2 , the specific steps of the method for maximizing the sum rate in the dual-RIS-assisted backscatter communication system are as follows:

[0110] Step A: Establish an optimization problem for maximizing the system sum rate, and the optimization parameters are the RIS phase shift, power allocation, and the reflection coefficient of the backscatter device. This optimization objective is expressed by the formula as:

[0111]

[0112] s.t. p 1 +p 2 =P≤P max

[0113] p 2 ≥p 1

[0114] p i ≥0, i∈{1,2}

[0115]

[0116]

[0117] α ∈ [0, α 0

[0118]

[0119] where p 1 and p 2 are the powers allocated to the near - distance user and the far - distance user respectively, p 1 ≤ p 2 , P is the total power of the base station, P = p 1 + p 2 , P max is the maximum transmission power of the base station, and are the phase - shift matrices of two RISs respectively, θ n ∈ [0, 2π), n = 1, 2, …, N, N is the number of reflection elements of each RIS, R 1 = log 2 (1 + γ 1→1 ), γ 1→1 is the signal - to - interference - plus - noise ratio when the near - distance user detects its desired received signal, α is the reflection coefficient of the backscatter device, h 1 , h b and g b represent the channels between the base station and the near - distance user, between the base station and the backscatter device, and between the backscatter device and the near - distance user respectively, σ 2 is the variance of additive white Gaussian noise, R 2 = log 2 (1 + γ 2→2 ), γ 2→2 is the signal - to - interference - plus - noise ratio when the far - distance user detects its desired received signal, H = |h r Θ 1 SΘ 2 g r |, |·| represents the absolute value, h r , g r and S represent the channels between the base station and the first RIS, between the second RIS and the far - distance user, and between the first RIS and the second RIS respectively, R BD = log 2 (1 + γ 1→b ), γ 1→b ​is the signal-to-interference-plus-noise ratio when the near user detects the backscattered signal, γ 1→2 is the signal-to-interference-plus-noise ratio when the near user detects the desired received signal of the far user, is the threshold requirement for the signal-to-interference-plus-noise ratio when the near user detects the signal, is the threshold requirement for the signal-to-interference-plus-noise ratio when the far user detects the signal, ζ is the energy required by the backscatter communication circuit, and η is the energy conversion efficiency of the backscatter device;

[0120] Step B: Simplify the optimization problem in Step A to:

[0121]

[0122] s.t.p 1 +p 2 =P≤P max

[0123] p 2 ≥p 1

[0124] p i ≥0,i∈{1,2}

[0125]

[0126]

[0127] α∈[0,α 0

[0128]

[0129] Step C: Let the solution of the variable α in the optimization problem in Step B be Separate the RIS phase shift optimization problem from Step B and solve this optimization problem;

[0130] Step D: Substitute the solution of the RIS phase shift and the solution of α obtained in Step C into the optimization problem in Step B, and get:

[0131]

[0132] s.t.p 1 +p 2 =P≤P max

[0133] p 2 ≥p 1

[0134] p i ≥0,i∈{1,2} ​

[0135]

[0136]

[0137] Among them, H * is the value obtained by substituting the solution of the RIS phase shift obtained in step C into |h r Θ 1 SΘ 2 g r |;

[0138] Step E, solve the optimization problem in step D. If |h 1 | 2 σ 2 -H *2 c 2 ≥0, let If |h 1 | 2 σ 2 -H *2 c 2 <0, let Among them, Let p 2 =P - p 1 .

[0139] The above embodiments are merely illustrative examples of the present invention, and those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A method for maximizing the sum rate in a dual RIS-assisted backscatter communication system, characterized in that: Applicable to a system including one base station, one backscatter device, two RIS and two NOMA users, including the following steps: Step A: Establish an optimization problem to maximize the system and rate. The optimization parameters are RIS phase shift, power allocation, and reflection coefficient of the backscattering device. The optimization objective is expressed as: Among them, p1 and p2 are the power allocated to close-range users and long-range users respectively, p1≤p2, P is the total power of the base station, P=p1+p2, P max is the maximum transmit power of the base station, and are the phase shift matrices of the two RIS, θ n ∈[0,2π), N is the number of reflection elements in each RIS, R1 = log2(1+γ 1→1 ), γ 1→1 It is the signal-to-interference-to-noise ratio when a close-range user detects the signal it expects to receive. α is the reflection coefficient of the backscattering device, h1, h b and g b They represent the channel between the base station and the close-range user, the channel between the base station and the backscattering device, and the channel between the backscattering device and the close-range user, respectively. 2 is the variance of additive Gaussian white noise, R2=log2(1+γ 2→2 ), γ 2→2 It is the signal-to-interference-to-noise ratio when a long-distance user detects the signal it expects to receive. H=|h r Θ1SΘ2g r |,|·| represents the absolute value, h r , g r and S represent the channel between the base station and the first RIS, the channel between the second RIS and the remote user, and the channel between the first RIS and the second RIS. BD =log2(1+γ 1→b ), γ 1→b is the signal-to-interference-to-noise ratio when a close-range user detects the backscattered signal, γ 1→2 is the signal-to-interference-to-noise ratio when a close user detects the desired received signal of a long-distance user. It is the threshold requirement for the signal-to-interference-noise ratio when a close-range user detects a signal. It is the threshold requirement for the signal-to-interference-noise ratio when a long-distance user detects a signal. ζ is the energy required by the backscatter communication circuit, η is the energy conversion efficiency of the backscatter device; Step B: Simplify the optimization problem in step A to: Step C: Let the solution of variable α in the optimization problem in step B be Separating the RIS phase shift optimization problem from step B and solving the optimization problem; Step D: Substitute the solution of RIS phase shift and α obtained in step C into the optimization problem in step B to obtain: in, H * is to substitute the solution of RIS phase shift obtained in step C into |h r Θ1SΘ2g r |The obtained value; Step E: Solve the optimization problem in step D. If |h1| 2 σ 2 -H *2 c2≥0, let If |h1| 2 σ 2 -H *2 c2<0, let in, Let p2=P-p1.

2. The method for maximizing the sum rate in a dual RIS-assisted backscatter communication system according to claim 1, characterized in that: The step C comprises the following steps: C1: Let the solution of variable α in the optimization problem in step B be: C2: Construct RIS phase shift optimization problem: C3: Set the value of the threshold ε, set the maximum number of iterations K, let k = 1, θ n =0, C4: Set θ n Substitute the value of into Θ1 and calculate v = h r Θ1S, with v n represents the nth element of v, let arg(·) represents the phase angle, n=1,2,…,N, where g r,n Indicates g r The nth element of Let k = k + 1; C5: The result obtained in step C4 Substitute the value of into Θ2 and calculate w = SΘ2g r , use w n represents the nth element of w, let θ n =-arg(w n )-arg(h r,n ), n=1,2,…,N, where h r,n Indicates h r The nth element of Let k = k + 1; C6: Repeat steps C4 and C5 until H k -H k-1 ≤ε or k=K, then θ n and The value of is the solution to the optimization problem in step C2, and is also the variable θ in the optimization problem in step B. n and The solution is n=1,2,…,N.

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