Resource allocation method in back scattering assisted NOMA (Non-Orthogonal Multiple Access) system

Abstract

The invention discloses a resource allocation method in a backscatter-assisted NOMA (Non-Orthogonal Multiple Access) system, which is suitable for two RISs (Radio Information System) and the backscatter-assisted NOMA system. The method comprises the following steps of: firstly, establishing an optimization problem of maximizing backscatter communication energy efficiency by taking a threshold requirement on a signal to interference plus noise ratio when a user detects a signal as a constraint condition and taking RIS phase shift, total power of a base station, power distribution and a reflection coefficient of backscatter equipment as optimization parameters; then, an RIS phase shift optimization problem is separated from the optimization problem, and the optimization problem is solved by adopting an iteration method; and finally, substituting the obtained RIS phase shift into an optimization problem of maximizing backscatter communication energy efficiency, simplifying the optimization problem, solving the total power of the base station, and further obtaining a reflection coefficient and power distribution of backscatter equipment.

Description

Technical Field

[0001] The present invention belongs to the field of communications, and particularly relates to a resource allocation method in a backscatter-assisted NOMA system. Background Art

[0002] Backscatter communication is a wireless communication technology that designs an extremely low-power modulation and transmission technology by using the principle of radio frequency signal backscattering. Backscatter communication uses the existing radio frequency signals in the environment as the excitation source, absorbs energy from them on the one hand, and transmits signals using this energy on the other hand. Compared with traditional active communication technologies, backscatter communication does not require high-power active radio frequency modules and dedicated excitation radio frequencies and communication carriers, thus improving the communication energy efficiency and meeting the requirements of low power consumption and long battery life for Internet of Things devices.

[0003] A reconfigurable intelligent surface (RIS) is a planar array composed of multiple reconfigurable passive units. Each unit can reflect electromagnetic waves and change the amplitude and phase of the incident signal, so that the RIS can enhance the coverage of the wireless network and improve the system capacity. Compared with active relays, the RIS does not need to actively process signals, but only passively reflects the incident signals, thus avoiding additional delays. Due to its low cost, the RIS is an important part of future wireless networks. Applying the RIS to a backscatter communication system can improve its energy and spectral efficiency and reduce the impact of the unpredictable radio frequency environment on the system performance. Existing research shows that by changing the RIS phase shift, backscatter communication can more effectively change the equivalent channel to meet the needs of different users.

[0004] Non-orthogonal multiple access (NOMA) technology introduces a new dimension - the power domain. Its core idea is to multiplex the signals of multiple users with different powers on the same time-frequency resources, and the receiver uses successive interference cancellation technology to reduce the interference between users. Compared with traditional orthogonal multiple access, NOMA has the advantages of low latency, high reliability, etc., and can also improve the fairness between users and the system throughput. Therefore, NOMA has broad application prospects and has attracted great interest from the industry and academia. The combination of NOMA and backscatter communication allows the backscatter receiver (BR) and backscatter device (BD) to utilize the non-orthogonal resources originally belonging to NOMA, thus improving the spectral efficiency of the system and increasing the system capacity.

[0005] However, applying backscatter communication to the NOMA system still cannot solve the problem of poor signal quality of cell-edge users. If RIS is introduced into the backscatter-assisted NOMA system, each reflecting element of RIS can independently adjust the amplitude and phase of the incident signal, and transmit the signal to the expected position, 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 and backscatter-assisted NOMA system models, including a Base Station (BS), a BD, two RISs and two NOMA users. The near-user communicates with the BS through the direct link and the backscatter link. There is no direct link between the far-user and the BS, and it communicates with the BS with the assistance of RIS. This literature established an optimization problem to maximize the backscatter communication rate of the system and solved this optimization problem. However, when the power is low, both the rate and energy efficiency of the system increase with the increase of power. When the power increases to a certain extent, the rate of the system grows slowly and the energy efficiency of the system decreases, which leads to a waste of power resources. Therefore, it is necessary to study the resource allocation method to maximize the backscatter communication energy efficiency in this system. Summary of the Invention

[0006] In summary, to solve the existing technical problems, the present invention provides a resource allocation method in a backscatter-assisted NOMA system, which is applicable to a two-RIS and backscatter-assisted NOMA system.

[0007] First, taking the threshold requirement of the signal-to-interference-plus-noise ratio when the user detects the signal as a constraint condition, and using the RIS phase shift, the total power of the BS, the power allocation and the BD reflection coefficient as optimization parameters, an optimization problem to maximize the backscatter communication energy efficiency is established; then, 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 RIS phase shift is substituted into the optimization problem to maximize the backscatter communication energy efficiency, and this optimization problem is simplified to solve the total power of the BS, and then the BD reflection coefficient and power allocation are obtained.

[0008] To achieve the above object, the present invention adopts the following technical solutions:

[0009] A resource allocation method in a backscatter-assisted NOMA system, which is applicable to a two-RIS and backscatter-assisted NOMA system, includes the following steps:

[0010] Step A: Establish an optimization problem to maximize the backscatter communication energy efficiency of the system. The optimization parameters are the RIS phase shift, the total base station power, the power allocation, and the reflection coefficient of the backscatter device. The optimization objective is expressed by the formula:

[0011]

[0012] s.t.p 1 +p 2 =P≤P max

[0013] p 2 ≥p 1

[0014] p i ≥0,i∈{1,2}

[0015]

[0016]

[0017] α∈[0,α 0

[0018]

[0019] where P is the total base station power, 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=p 1 +p 2 ,P max is the maximum transmission power of the base station, h b and g b represent the channels between the base station and the backscatter device, the backscatter device and the channel, and are the phase - shift matrices of two RISs respectively, θ n ∈[0,2π), N is the number of reflection elements of each RIS, α is the reflection coefficient of the backscatter device, η is the energy conversion efficiency of the backscatter device, ζ is the energy required by the backscatter communication circuit, σ 2 is the variance of additive white Gaussian noise, is the threshold requirement for the signal - to - interference - plus - noise ratio when the near - distance user detects the signal, is the threshold requirement for the signal - to - interference - plus - noise ratio when the far - distance user detects the signal, γ 1→2 is the signal - to - interference - plus - noise ratio when the near - distance user detects the desired received signal of the far - distance user, h 1 ​Represents the channel between the base station and the nearby user, γ 1→1 is the signal-to-interference-plus-noise ratio when the nearby user detects its expected received signal, γ 2→2 is the signal-to-interference-plus-noise ratio when the faraway user detects its expected received signal, H = |h r Θ 1 SΘ 2 g 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 faraway user, and the channel between the first RIS and the second RIS;

[0020] Step B: Construct the RIS phase shift optimization problem and solve this optimization problem;

[0021] Step C: Let the expression of the variable α in the optimization problem in Step A be:

[0022] Step D: Substitute the value of the RIS phase shift obtained in Step B and the expression of α obtained in Step C into the optimization problem in Step A, and obtain:

[0023]

[0024] s.t. p 1 + p 2 = P ≤ P max

[0025] p 2 ≥ p 1

[0026] p i ≥ 0, i ∈ {1, 2}

[0027]

[0028] The optimization parameters of this optimization problem are the total power of the base station and the power allocation;

[0029] Step E: Simplify the optimization problem in Step D and solve this optimization problem, and then obtain the value of the reflection coefficient of the backscatter device and the power allocation.

[0030] Furthermore, the said Step B includes the following steps:

[0031] B1: Construct the RIS phase shift optimization problem

[0032]

[0033] B2: Set the value of threshold ε, set the maximum number of iterations K, let k = 1, θ n = 0, n = 1, 2, …, N;

[0034] B3: Substitute the value of θ n into Θ 1 to calculate v = h r Θ 1 S, let v n represent the n-th element of v, let arg(·) represent the phase angle, n = 1, 2, …, N, where g r,n represents the n-th element of g r , let Let k = k + 1;

[0035] B4: Substitute the value of obtained in step B3 into Θ 2 to calculate w = SΘ 2 g r , let w n represent the n-th element of w, let θ n = -arg(w n ) - arg(h r,n ), n = 1, 2, …, N, where h r,n represents the n-th element of h r , let Let k = k + 1;

[0036] B5: Repeat step B3 and step B4 until H k - H k-1 ≤ ε or k = K, at this time the values of θ n and are the solutions of the optimization problem in step B1, and also the solutions of the variables θ n and in step A, n = 1, 2, …, N.

[0037] Furthermore, the said step E includes the following steps:

[0038] E1: Simplify the optimization problem in step D to:

[0039]

[0040] s.t. p 1 + p 2 = P ≤ P max

[0041]

[0042]

[0043]

[0044] Among them, H * is the value obtained by substituting the RIS phase shift obtained in step B into |h r Θ 1 SΘ 2 g r |.

[0045] E2: Let P = P max , let m = 1, set the initial value of Δ, and Δ is a positive integer;

[0046] E3: According to the value of P, calculate and where If and execute step E4, otherwise let M = m and execute step E5;

[0047] E4: Let let m = m + 1 and P = P max -(m - 1)Δ, and execute step E3;

[0048] E5: Let e max = max{e(m), m = 1, 2,..., M}, and use m0 to represent the serial number of e max in the set {e(m), m = 1, 2,..., M}, then P = P max -(m0 - 1)Δ is the solution to the optimization problem in step E1 and also the solution to the variable P in the optimization problem in step A;

[0049] E6: Substitute the P obtained in step E5 into The value obtained is the solution to the variable α in the optimization problem in step A. Calculate and The solutions to the variables p 1 and p 2 in the optimization problem in step A are not unique, as long as they satisfy and p 1 + p 2 = P.

[0050] Beneficial effects:

[0051] For two RIS-assisted backscatter-assisted NOMA systems, there is no literature studying the resource allocation method for maximizing the energy efficiency of backscatter communication. The method proposed in the present invention optimizes the RIS phase shift, the total power of the BS, the power allocation, and the BD reflection coefficient according to the channel conditions and the threshold requirements for the signal-to-interference-plus-noise ratio when the user detects the signal, so as to maximize the energy efficiency of backscatter communication. Compared with the existing resource allocation methods in the same system, the proposed scheme makes full use of the power resources and improves the energy efficiency of backscatter communication while ensuring that the user can correctly detect the signal. Brief Description of the Drawings

[0052] Figure 1 is the system model diagram of the embodiment of the present invention;

[0053] Figure 2 is the flowchart of the present invention. Detailed Embodiment

[0054] The following further describes the present invention in detail in conjunction with an embodiment. The model of this embodiment is the same as the model in the literature "Resource allocation of backscatter communication based on reconfigurable intelligent surface". This system includes a BS, a BD, two RISs, and two NOMA users. S1 is the user in the center of the cell and can communicate with the BS through the direct link and the backscatter link. S2 is the user at the edge of the cell. Due to the obstruction of the building, there is no direct link between S2 and the BS. S2 can communicate with the BS with the assistance of the RIS. 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.

[0055] S1 and S2 are a pair of NOMA users. The BS superimposes the desired received signal of S1 and the desired received signal of S2 and transmits them. Both S1 and the BD receive the transmitted signal of the BS. 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 transmitted signal of the BS.

[0056] The RIS has N reflection elements. Respectively use h r , g r and S to represent the channels between the BS and RIS1, between RIS2 and S2, and between RIS1 and RIS2. The order of h r is 1×N, the order of g r is N×1, and the order of S is N×N. Respectively use h 1 , h band g b represent the channels between the BS and S1, between the BS and BD, and between the BD and S1. h 1 、h b and g b are all of order 1×1. The phase shift matrices of RIS1 and RIS2 are and θ n ∈[0, 2π), n = 1, 2, …, N.

[0057] The transmitted signal of the BS is expressed as:

[0058]

[0059] where x 1 and x 2 are the desired received signals of S1 and S2 respectively, E[|x 1 | 2 = E[|x 2 | 2 = 1, E[·] represents the mathematical expectation, |·| represents the absolute value, p 1 and p 2 are the powers respectively, p 1 ≤ p 2 .

[0060] The received signal of the BD is:

[0061] x b = h b x(2)

[0062] The BD divides the received signal energy into two parts. One part is used for backscatter communication with a proportion of α, and the other part is used for energy harvesting with a proportion of 1 - α. α is also called the reflection coefficient. The backscattered signal transmitted by the BD is expressed as:

[0063]

[0064] where c is the signal generated by the BD itself, and E[|c| 2 = 1. Since the circuit of the BD does not contain any active components, it is considered that the noise generated by it can be ignored. The energy E BD harvested by the BD is expressed as:

[0065] E BD = η(1 - α)P|h b | 2 (4)

[0066] where P is the transmitted power of the BS, P = p 1 + p2 , η is the energy conversion efficiency of BD.

[0067] Assume that the energy required by 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 collected by BD is not sufficient to maintain the backscatter communication circuit, if BD uses less energy in backscatter communication, resulting in a decrease in backscatter communication efficiency.

[0068] The received signal at S1 is expressed as:

[0069]

[0070] where is the backscattered signal received by S1, and n u,1 is additive white Gaussian noise with a mean of 0 and a variance of σ 2 . S1 can detect the backscattered signal only when the direct signal is known.

[0071] Assume that the channel gain from BS to S1 is better than the channel gain from BS to S2, i.e., |h 1 |≥|h r Θ 1 SΘ 2 g r |. S1 uses the successive interference cancellation method to detect the signal. First, it detects x 2 , then it detects x 1 , and finally it detects c. The signal-to-interference-plus-noise ratio (SINR) when S1 detects x 2 is:

[0072]

[0073] The SINR when S1 detects x 1 is:

[0074]

[0075] The SINR when S1 detects c is:

[0076]

[0077] The received signal at S2 is:

[0078] y 2 =h r Θ 1 SΘ2 g r x + n u,2 (9)

[0079] where n u,2 is additive white Gaussian noise with a mean of 0 and a variance of σ 2 . The signal-to-interference-plus-noise ratio (SINR) when S2 detects x 2 is given by:

[0080]

[0081] where H = |h r Θ 1 SΘ 2 g r |.

[0082] The backscatter communication rate of BD is expressed as:

[0083]

[0084] The optimization objective of the proposed scheme is to maximize the energy efficiency of the backscatter communication system. The optimization parameters are the RIS phase shift, the total power of the BS, the power allocation, and the BD reflection coefficient. This optimization objective is expressed by the formula:

[0085]

[0086] where is the threshold requirement for the signal-to-interference-plus-noise ratio when the user detects the signal, ensuring that S1 can correctly detect x 1 and x 2 , ensuring 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.

[0087] The optimization objective function in Equation (12) is independent of H. Due to the existence of the constraint condition , H indirectly affects the energy efficiency of the system. The value of H should satisfy and γ 2→2 increases as H increases. The larger γ 2→2 , the more conducive it is to meeting the constraint condition Therefore, the optimal solution of the optimization problem in Equation (12) should make H reach the maximum value.

[0088] $H$ is related to the RIS phase shift and the channel, and is independent of the total BS power, power allocation, and BD reflection coefficient. Therefore, the optimization problem corresponding to the RIS phase shift is as follows:

[0089]

[0090] According to the literature "Resource allocation of backscatter communication based on reconfigurable intelligent surface", the steps to solve the optimization problem in Equation (13) are as follows:

[0091] Step 1: Set the value of the threshold $\varepsilon$, set the maximum number of iterations $K$, let $k = 1$, $\theta$ n $= 0$ and $n = 1, 2, \ldots, N$;

[0092] Step 2: Substitute the value of $\theta$ n into $\Theta$ 1 , calculate $v = h$ r $\Theta$ 1 $S$, use $v$ n to represent the $n$-th element of $v$, and let $\arg(\cdot)$ represent the phase angle, $n = 1, 2, \ldots, N$, where $g$ r,n represents the $n$-th element of $g$ r , and let Let $k = k + 1$;

[0093] Step 3: Substitute the value of obtained in Step 2 into $\Theta$ 2 , calculate $w = S\Theta$ 2 $g$ r , use $w$ n to represent the $n$-th element of $w$, and let $\theta$ n $= -\arg(w$ n ) $-\arg(h$ r,n ), $n = 1, 2, \ldots, N$, where $h$ r,n represents the $n$-th element of $h$ r , and let Let $k = k + 1$;

[0094] Step 4: Repeat Step 2 and Step 3 until $H$ k $- H$ k-1 $\leq \varepsilon$ or $k = K$.

[0095] The $\theta$ n and obtained by the above four steps are the solutions to the optimization problem in Equation (13), and are also the variables $\theta$ n and solution. Substitute the θ obtained from 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 * .

[0096] As mentioned before, α 0 is the optimal BD reflection coefficient. In and given the RIS phase shift, the optimization problem in Equation (12) can be expressed as:

[0097]

[0098] Combined with the constraint p 1 + p 2 = P and the constraint we can obtain 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 we can obtain that the value of p 1 satisfies From we can obtain Since so From α = α 0 and the constraint p 1 + p 2 = P and p 2 ≥ p 1 we can obtain where Only and can P meet the threshold requirement of the signal-to-interference-plus-noise ratio when the user detects the signal. According to the above analysis, the optimization problem in Equation (14) can be expressed as:

[0099]

[0100] There is no analytical solution to the optimization problem in Equation (15). An iterative method can be used to solve this optimization problem. The idea is: start traversing the values of the total BS power from P max , reduce the value of the total BS power by a relatively small amount in each iteration, and calculate the value of the objective function at this time until the value of the total BS power cannot meet the constraint condition and Find the total BS power that maximizes the backscatter communication energy efficiency by comparing the values of the optimization objective function in each iteration process.

[0101] The specific steps to solve the optimization problem in Equation (15) are as follows:

[0102] Step 1: Let \(P = P max , let \(m = 1\), set the initial value of \(\Delta\), where \(\Delta\) is a positive integer;

[0103] Step 2: According to the value of \(P\), calculate and where If and Execute Step 3, otherwise let \(M = m\) and execute Step 4;

[0104] Step 3: Let Let \(m = m + 1\) and \(P = P max -(m - 1)\Delta\), and execute Step 2;

[0105] Step 4: Let \(e max =\max\{e(m), m = 1, 2, \ldots, M\}\), and use \(m_0\) to represent the serial number of \(e max in the set \(\{e(m), m = 1, 2, \ldots, M\}\), then \(P = P max -(m_0 - 1)\Delta\) is the solution to the optimization problem in Equation (15).

[0106] The solution to the optimization problem in Equation (15) is also the solution to the variable \(P\) of the optimization problem in Equation (12). Substitute the \(P\) obtained from the above 4 steps into The value obtained is the solution to the variable \(\alpha\) of the optimization problem in Equation (12). The optimization objective functions in Equation (12) and Equation (15) are related to the total BS power and independent of power allocation. Therefore, the solutions to the variables \(p 1 and \(p 2 are not unique, as long as they satisfy and \(p 1 +p 2 =P\).

[0107] Combined with the flowchart of the present invention, that is Figure 2 , the specific steps of the resource allocation method in the backscatter-assisted NOMA system are as follows:

[0108] Step A: Establish an optimization problem to maximize the backscatter communication energy efficiency of the system. The optimization parameters are the RIS phase shift, the total BS power, the power allocation, and the reflection coefficient of the backscatter device. This optimization objective is expressed by the formula:

[0109]

[0110] s.t.p 1 +p 2 =P≤P max

[0111] p 2 ≥p 1

[0112] p i ≥0,i∈{1,2}

[0113]

[0114]

[0115] α∈[0,α 0

[0116]

[0117] Among them, P is the total power of the base station, 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 = p 1 +p 2 , P max is the maximum transmission power of the base station, h b and g b represent the channels between the base station and the backscatter device, between the backscatter device and the 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, α is the reflection coefficient of the backscatter device, η is the energy conversion efficiency of the backscatter device, ζ is the energy required for the backscatter communication circuit, σ 2 is the variance of additive white Gaussian noise, is the threshold requirement for the signal - to - interference - plus - noise ratio when the near - distance user detects the signal, is the threshold requirement for the signal - to - interference - plus - noise ratio when the far - distance user detects the signal, γ 1→2 is the signal - to - interference - plus - noise ratio when the near - distance user detects the expected received signal of the far - distance user, h 1 represents the channel between the base station and the near - distance user, γ 1→1 is the signal - to - interference - plus - noise ratio when the near - distance user detects its own expected received signal, γ 2→2 ​is the signal-to-interference-plus-noise ratio when a long-distance user detects the signal it expects to receive, H = |h r Θ 1 SΘ 2 g r |, where |·| represents the absolute value, and 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 long-distance user, and the channel between the first RIS and the second RIS;

[0118] Step B: Construct the RIS phase shift optimization problem and solve this optimization problem;

[0119] Step C: Let the expression of the variable α in the optimization problem in Step A be

[0120] Step D: Substitute the value of the RIS phase shift obtained in Step B and the expression of α obtained in Step C into the optimization problem in Step A, and obtain:

[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] The optimization parameters of this optimization problem are the total power of the base station and the power allocation;

[0127] Step E: Simplify the optimization problem in Step D and solve this optimization problem, and then obtain the value of the reflection coefficient of the backscatter device and the power allocation.

[0128] The above embodiments are only 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 resource allocation method in a backscatter-assisted NOMA 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 energy efficiency of backscatter communication of the system. The optimization parameters are RIS phase shift, total power of base station, power allocation and reflection coefficient of backscatter device. The optimization objective is expressed as: Where P is the total power of the base station, p1 and p2 are the power allocated to close-range users and long-range users respectively, p1≤p2, P=p1+p2, P max is the maximum transmit power of the base station, h b and g b Indicates the channel between the base station and the backscatter device, and the backscatter device and the channel. and are the phase shift matrices of the two RIS, θ n ∈[0,2π), N is the number of reflective elements per RIS, α is the reflection coefficient of the backscattering device, η is the energy conversion efficiency of the backscatter device, ζ is the energy required by the backscatter communication circuit, and σ 2 is the variance of the additive white Gaussian noise, It is the threshold requirement for the signal-to-interference-noise ratio when a close-range user detects a signal. is the threshold requirement for the signal-to-interference-noise ratio when a long-distance user detects a 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. h1 represents the channel between the base station and the close-range user, γ 1→1 It is the signal-to-interference-to-noise ratio when a close-range user detects the signal it expects to receive. 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; Step B: constructing the RIS phase shift optimization problem and solving the optimization problem; Step C: Let the expression of variable α in the optimization problem in step A be: Step D: Substitute the value of the RIS phase shift obtained in step B and the expression of α obtained in step C into the optimization problem in step A to obtain: The optimization parameters of this optimization problem are the total power of the base station and the power allocation; Step E: Simplify the optimization problem in step D and solve the optimization problem, thereby obtaining the value of the reflection coefficient and the power distribution of the backscattering device.

2. The resource allocation method in the backscatter-assisted NOMA system according to claim 1, characterized in that: The step B comprises the following steps: B1: Constructing the RIS phase shift optimization problem B2: Set the value of the threshold ε, set the maximum number of iterations K, let k = 1, θ n =0, B3: Set θ n Substitute the value of into Θ1 and calculate v = h r Θ1S, with v n Denote 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; B4: The result obtained in step B3 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; B5: Repeat steps B3 and B4 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 B1, and is also the variable θ in the optimization problem in step A. n and The solution is n=1,2,…,N.

3. The resource allocation method in the backscatter-assisted NOMA system according to claim 1, characterized in that: The step E comprises the following steps: E1: Simplify the optimization problem in step D to: in, H * is to substitute the RIS phase shift obtained in step B into |h r Θ1SΘ2g r |The value obtained, E2: Let P = P max , let m = 1, set the initial value of Δ, Δ is a positive integer; E3: According to the value of P, calculate and in if and Execute step E4, otherwise set M = m and execute step E5; E4: Command Let m = m + 1 and P = P max -(m-1)Δ, execute step E3; E5: Let e max =max{e(m),m=1,2,…,M}, where m0 represents e max In the set {e(m), m = 1, 2, ..., M}, then P = P max -(m0-1)Δ is the solution to the optimization problem in step E1, and also the solution to the variable P in the optimization problem in step A; E6: Substitute P obtained in step E5 into The value obtained is the solution of the variable α in the optimization problem in step A, which is calculated based on P obtained in step E5. and The solutions of variables p1 and p2 in the optimization problem in step A are not unique, as long as And p1+p2=P.

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