Method for maximizing energy efficiency in dual-RIS-assisted backscatter communication system

Abstract

The invention discloses a method for maximizing energy efficiency 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 maximum energy efficiency in the system is established, optimization parameters are RIS phase shift, total power, power distribution and a reflection coefficient of backscattering equipment, and constraint conditions are power limitation and threshold requirements on a signal to interference plus noise ratio when a user detects a signal; then, the optimization problem is simplified, an RIS phase shift optimization problem is separated from the optimization problem, the optimization problem is solved by adopting an iteration method, and RIS phase shift with the maximum system energy efficiency is obtained; and finally, substituting the expression of the reflection coefficient of the backscattering equipment and the obtained RIS phase shift into the optimization problem of maximizing the system energy efficiency, solving the optimization problem by adopting an iteration and function extremum method, obtaining the total power of the maximized system energy efficiency, and further obtaining the reflection coefficient and power distribution of the backscattering equipment.

Description

Technical Field

[0001] The present invention belongs to the field of communications, and particularly relates to a method for maximizing energy efficiency in a double-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 reflection elements. Each element can independently change the amplitude and phase of an incident signal, so as to collaboratively achieve three-dimensional reflection beamforming. By intelligently reflecting signals, the RIS can change the wireless channel to enhance the power of the desired signal at the receiver, or eliminate undesired received signals such as co-channel interference, paving the way for the realization of an intelligent programmable wireless environment. Since the RIS only works within a short distance, it can be densely deployed, and there is no need for complex interference management between passive RISs.

[0003] The rapid development of the Internet of Things has led to a sharp increase in the number of wireless devices, resulting in an increase in power consumption, while power resources are limited. Since backscatter communication is a low-power wireless communication means, it has received extensive attention from the academic and business communities. A Backscatter Receiver (BR) and a Backscatter Device (BD) are two main devices in a backscatter communication system. The BD harvests energy from ambient radio frequency signals and uses this energy to power its own circuits, thus eliminating the need for a dedicated transmitter. In addition, to improve spectral efficiency, the BD can change the phase and amplitude of the received signal and then transmit it to the BR. However, backscatter communication still faces some problems. For example, the type and location of the radio frequency source affect the transmission efficiency, and if there are obstacles between the BD and the radio frequency source, the channel quality will be affected, and only by combining different technologies such as cooperative relaying, RIS, and Non-Orthogonal Multiple Access (NOMA) can the negative impact of the adverse propagation environment on the system performance be reduced. Existing research has shown that applying the 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 BR and the 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] Existing research has shown that if RIS is introduced into a system that combines backscattering with NOMA, each reflecting element of RIS can independently adjust the amplitude and phase of the incident signal to transmit the signal to the desired location, thereby expanding the communication coverage and increasing the throughput. Therefore, scholars have conducted research on systems that combine 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 a Base Station (BS), a 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, when the power is low, both the rate and energy efficiency of the system increase with the increase in 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 that maximizes the energy efficiency in this system. Summary of the Invention

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

[0006] First, establish an optimization problem for maximizing the energy efficiency in a dual-RIS-assisted backscatter communication system. The optimization parameters are the RIS phase shift, total power, power allocation, and BD reflection coefficient, and the constraints are the power limit and the threshold requirement for the signal-to-interference-plus-noise ratio when the user detects the signal. Then, simplify the optimization problem and isolate the RIS phase shift optimization problem from it, and use an iterative method to solve this optimization problem to obtain the RIS phase shift that maximizes the energy efficiency of the system. Finally, substitute the expression of the BD reflection coefficient and the obtained RIS phase shift into the optimization problem for maximizing the energy efficiency of the system, and use an iterative and function extreme value method to solve this optimization problem to obtain the total power that maximizes the energy efficiency of the system, and further obtain the BD reflection coefficient and power allocation.

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

[0008] A method for maximizing the energy efficiency 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 to maximize the system energy efficiency, with the optimization parameters being the RIS phase shift, total power, power allocation, and reflection coefficient of the backscatter device. The optimization objective is expressed by the formula:

[0010]

[0011] s.t.p 1 +p 2 =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 - user and far - 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 transmit power of the base station, α is the reflection coefficient of the backscatter device, R 1 =log 2 (1 + γ 1→1 ), γ 1→1 is the signal - to - interference - plus - noise ratio when the near - user detects its desired received signal, σ 2 is the variance of the additive white Gaussian noise, h 1 、h b and g b represent the channels between the base station and the near - user, between the base station and the backscatter device, and between the backscatter device and the near - user respectively, |·| represents the absolute value, R 2 =log 2 (1 + γ 2→2 ), γ 2→2 is the signal - to - interference - plus - noise ratio when the far - user detects its desired received signal, H=|h r Θ 1 SΘ​2 g r |, h r , g r and S represent 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 + γ 1→b ), γ 1→b is the signal - to - interference - plus - noise ratio (SINR) when the near - distance user detects the backscattered signal, and are the phase - shift matrices of the two RISs respectively, θ n ∈[0, 2π), n = 1, 2, …, N, where N is the number of reflecting elements of each RIS, γ 1→2 is the signal - to - interference - plus - noise ratio (SINR) 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, is the threshold requirement for the signal - to - interference - plus - noise ratio when the far - away 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;

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

[0020]

[0021] s.t. p 1 + p 2 = P ≤ P max

[0022] p 2 ≥ p 1

[0023] p i ≥ 0, i ∈ {1, 2}

[0024]

[0025] α ∈ [0, α 0

[0026]

[0027] Step C: Isolate the RIS phase - shift optimization problem from Step B and solve this optimization problem;

[0028] Step D: Substitute the solution of the RIS phase - shift obtained in Step C and into the optimization problem in Step B to obtain:​

[0029]

[0030] s.t.p 1 +p 2 =P≤P max

[0031] p 2 ≥p 1

[0032] p i ≥0,i∈{1,2}

[0033]

[0034] 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 |;

[0035] Step E: Solve the optimization problem in step D to obtain the total power that maximizes the system energy efficiency, and further obtain the power allocation that maximizes the system energy efficiency and the reflection coefficient of the backscatter device.

[0036] Furthermore, the said step C includes the following steps:

[0037] C1: Construct the RIS phase shift optimization problem:

[0038]

[0039] C2: Set the value of the threshold ε, set the maximum number of iterations K, let k = 1, θ n =0, n = 1,2,…,N;

[0040] C3: Substitute the value of θ n into Θ 1 and 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, wherein, g r,n represents the nth element of g r and let Let k = k + 1;

[0041] C4: Substitute the value of obtained in step C3 into Θ 2 and calculate w = SΘ2 g r , let \(w\) n denote 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 denotes the \(n\)th element of \(h\), and let r Let \(k = k + 1\);

[0042] C5: Repeat steps C3 and C4 until \(H\) k - \(H\) k-1 \(\leq \epsilon\) or \(k = K\), at this time the values of \(\theta\) n and are the solutions of the optimization problem in step C1, and also the variables \(\theta\) n and in the optimization problem in step B, \(n = 1, 2, \ldots, N\).

[0043] Furthermore, step E includes the following steps:

[0044] E1: Let \(P = P\) max , let \(m = 1\), and set the initial value of \(\Delta\), where \(\Delta\) is a positive integer;

[0045] E2: According to the value of \(P\), calculate and If and , execute step E3, otherwise let \(M = m\) and execute step E4;

[0046] E3: Calculate \(c\) 1 and \(c\) 2 values. If \(|h\) 1 | 2 \(\sigma\) 2 - \(H\) *2 \(c\) 2 \(\geq 0\), then let and \(p\) 2 = \(P - p\) 1 . If \(|h\) 1 | 2 \(\sigma\) 2 - \(H\) *2 \(c\) 2 \(< 0\), then let and \(p\) 2 = \(P - p\) 1 . Let Let \(m = m + 1\) and \(P = P\) max - \((m - 1)\Delta\), and execute step E2;

[0047] E4: Let \(g\) max ​= max{g(m), m = 1, 2, …, M}, where m0 represents the sequence number of g max in the set {g(m), m = 1, 2, …, M}, then P = P max -(m0 - 1)Δ is the total power that maximizes the system energy efficiency;

[0048] E5: Calculate according to the value of P and the value of, if |h 1 | 2 σ 2 -H *2 c 2 ≥ 0, let and p 2 = P - p 1 , if |h 1 | 2 σ 2 -H *2 c 2 < 0, let and p 2 = P - p 1 , then p 1 and p 2 are the power allocations that maximize the system energy efficiency;

[0049] E6: Calculate according to the value of P the value of, then this α is the reflection coefficient of the backscatter device that maximizes the system energy efficiency.

[0050] Beneficial effects:

[0051] For two RIS-assisted backscatter communication systems, there is no literature studying the resource allocation method for maximizing the system energy efficiency. The method proposed in the present invention optimizes the RIS phase shift, total power, power allocation, and BD reflection coefficient according to the power constraint and the threshold requirement of the signal-to-interference-plus-noise ratio when the user detects the signal, so as to maximize the energy efficiency of the system. Compared with the existing resource allocation method for maximizing the backscatter communication rate in the same system, the proposed scheme not only ensures that the user can correctly detect the signal, but also makes full use of the power resources, improves the energy efficiency of the system, and takes into account both effectiveness and reliability. 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 implementation manners

[0054] The present invention will be further described in detail below 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". The system includes a BS, a BD, two RISs, and two NOMA users. S1 and S2 are a pair of NOMA users. S1 is a near - distance user and S2 is a far - distance user. S1 communicates with the BS through a direct link and a backscatter link. There is no direct link between S2 and the BS, and S2 can only communicate with the BS with the assistance of two RISs. Both S1 and the BD receive the transmission signal from the BS, and the BD forwards its received signal to S1. Therefore, S1 is not only a NOMA user but also a BR. The BD has a backscatter communication circuit and an energy harvesting circuit. The energy harvested by the BD can only be used immediately or dissipated.

[0055] The two RISs are represented by RIS1 and RIS2 respectively, and each RIS has N reflecting elements. The channels between RIS2 and S2, between the BS and RIS1, and between RIS1 and RIS2 are represented by g r , h r and S 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. The channels between the BS and S1, between the BS and the BD, and between the BD and S1 are represented by h 1 , h b and g b respectively, and 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.

[0056] The transmission signal of the BS is expressed as:

[0057]

[0058] 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 1and p 2 is the power. Since S1 is a near - distance user and S2 is a far - distance user, the powers allocated to S1 and S2 satisfy p 1 ≤p 2 .

[0059] The received signal at BD is:

[0060] x b =h b x(2)

[0061] 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 y b and the harvested energy E BD are respectively expressed as:

[0062]

[0063] E BD =η(1 - α)P|h b | 2 (4)

[0064] where c is the signal generated by BD itself, E[|c| 2 =1, P is the transmission power of BS, P = p 1 +p 2 , and η is the energy conversion efficiency of BD.

[0065] 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 BD reflection coefficient α 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 backscatter communication efficiency.

[0066] The received signal at S1 is expressed as:

[0067]

[0068] where n u,1 is the 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 - link signal is known.

[0069] Since S1 is a near - distance user and S2 is a far - distance user, assuming 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 successively detects x 2 、x 1 and c. The signal - to - interference - plus - noise ratio (SINR) when S1 detects x 2 is:

[0070]

[0071] After S1 cancels x 2 from the received signal, it detects x 1 . The signal - to - interference - plus - noise ratio (SINR) when S1 detects x 1 is:

[0072]

[0073] After S1 cancels x 2 and x 1 from the received signal, it detects c. The signal - to - interference - plus - noise ratio (SINR) when S1 detects c is:

[0074]

[0075] The received signal of S2 is:

[0076] y 2 =h r Θ 1 SΘ 2 g r x + n u,2 (9)

[0077] 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 - distance user, when S2 treats x 1 as interference and detects x 2 , the signal - to - interference - plus - noise ratio (SINR) is:

[0078]

[0079] where, H=|h r Θ 1 SΘ 2 g r |.

[0080] The backscatter communication rate of BD is expressed as:

[0081]

[0082] The rates of S1 and S2 are respectively:

[0083]

[0084]

[0085] The optimization objective of the proposed scheme is: to maximize the energy efficiency of the system, and the optimization parameters are RIS phase shift, total power, power allocation, and BD reflection coefficient. This optimization objective is expressed by the formula as:

[0086]

[0087] Wherein, is the threshold requirement for the signal-to-interference-plus-noise ratio when the user detects the signal, and P max is the maximum transmission 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.

[0088] Substituting Equation (11), Equation (12), and Equation (13) into the optimization objective function in Equation (14), we can obtain:

[0089]

[0090] Since the logarithmic function is a monotonically increasing function, the optimization objective function in Equation (14) can be equivalently expressed as:

[0091]

[0092] Therefore, the optimization problem in Equation (14) can be equivalently expressed as:

[0093]

[0094] In the optimization objective function in Equation (17), is related to the RIS phase shift, while and are both independent of the RIS phase shift. Therefore, the RIS phase shift optimization problem can be separated from Equation (17) and expressed as:

[0095]

[0096] The value of H should satisfy and γ 2→2 increases as H increases. The larger γ 2→2 , that is, the larger H, the more conducive it is to meeting the constraint condition In addition, p2 ≥ p 1 , is an increasing function of H. Therefore, the optimization problem in Equation (18) can be equivalently expressed as:

[0097]

[0098] 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:

[0099] Step 1: Set the value of the threshold ε, set the maximum number of iterations K, and let k = 1, θ n = 0 and n = 1, 2, …, N;

[0100] Step 2: Substitute the value of θ n into Θ 1 , calculate v = h r Θ 1 S, use v n to represent the n-th element of v, and let arg(·) represents the phase angle, n = 1, 2, …, N, where g r,n represents the n-th element of g r , and let Let k = k + 1;

[0101] 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 n-th element of w, and 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 , and let Let k = k + 1;

[0102] Step 4: Repeat Step 2 and Step 3 until H k - H k-1 ≤ ε or k = K.

[0103] The θ n and obtained by the above four steps are the solutions to the optimization problem in Equation (19) and also the variable θ in Equation (17).n and solution. Substitute 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 * .

[0104] 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:

[0105]

[0106] where At this time, the optimization problem in Equation (17) is expressed as:

[0107]

[0108] Next, deduce the value ranges of p 1 and p 2 according to the constraint conditions. From 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 the constraint condition p 1 + p 2 = P and p 2 ≥ p 1 it can be obtained that the value range of p 2 is where Therefore, the value range of p 1 is

[0109] For each value of P, there is a pair of values of p 1 and p 2 such that the optimization objective function Reach the maximum value. Therefore, the idea of solving the optimization problem in Equation (20) is as follows: taking a relatively small value as the interval, traverse the values of P until the value of P no longer satisfies the constraint conditions and For each value of P, find the p 1 ) that makes f(p 1 and p 2 , and thus obtain the maximum value of the optimized objective function corresponding to each P; find the P that maximizes the system energy efficiency by comparing the maximum values of the optimized objective function corresponding to each P.

[0110] Next, a method for finding the maximum value of f(p 1 ) when P is known is given. Take the first-order derivative of f(p 1 ) with respect to p 1 , and we can get If |h 1 | 2 σ 2 -H *2 c 2 ≥0, f(p 1 ) is an increasing function of p 1 , then when, f(p 1 ) 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, f(p 1 ) reaches the maximum value.

[0111] Based on the above analysis, the steps to solve the optimization problem in Equation (20) are as follows:

[0112] Step 1: Let P = P max , let m = 1, and set the initial value of Δ. Δ is a positive integer;

[0113] Step 2: According to the value of P, calculate and If and execute Step 3, otherwise let M = m and execute Step 4;

[0114] Step 3: Calculate the values of c 1 and c 2 If |h 1 | 2 σ 2 -H *2 c 2If ≥ 0, then let and p 2 = P - p 1 If |h 1 | 2 σ 2 - H *2 c 2 < 0, then let and p 2 = P - p 1 Let Let m = m + 1 and P = P max - (m - 1)Δ, and execute Step 2;

[0115] Step 4: Let g max = max{g(m), m = 1, 2, …, M}, and denote the sequence number of g max in the set {g(m), m = 1, 2, …, M} by m0. Then let P = P max - (m0 - 1)Δ.

[0116] The value of P obtained from the above 4 steps is the total power that maximizes the system energy efficiency. Calculate the values of c 1 and c 2 If |h 1 | 2 σ 2 - H *2 c 2 ≥ 0, let and p 2 = P - p 1 If |h 1 | 2 σ 2 - H *2 c 2 < 0, let and p 2 = P - p 1 Then p 1 and p 2 are the power allocations that maximize the system energy efficiency. Calculate the value of Then this α is the BD reflection coefficient that maximizes the system energy efficiency.

[0117] Combined with the flowchart of the present invention, that is Figure 2 The specific steps of the method for maximizing the energy efficiency in a dual - RIS - assisted backscatter communication system are as follows:

[0118] Step A: Establish an optimization problem for maximizing the system energy efficiency. The optimization parameters are the RIS phase shift, total power, power allocation, and the reflection coefficient of the backscatter device. This optimization objective is expressed by the formula:

[0119]

[0120] s.t.p 1 +p 2 =P≤P max

[0121] p 2 ≥p 1

[0122] p i ≥0,i∈{1,2}

[0123]

[0124] α∈[0,α 0

[0125]

[0126] 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, α is the reflection coefficient of the backscatter device, 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 expected received signal, σ 2 is the variance of additive white Gaussian noise, 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, |·| represents the absolute value, 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 expected received signal, H=|h r Θ 1 SΘ 2 g r |, 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, and are the phase shift matrices of two RISs respectively, θ n ∈ [0, 2π), n = 1, 2, …, N, where N is the number of reflecting elements of each RIS, 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, γ 2 min 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;

[0127] Step B: Simplify the optimization problem in Step A to:

[0128]

[0129] s.t. p 1 + p 2 = P ≤ P max

[0130] p 2 ≥ p 1

[0131] p i ≥ 0, i ∈ {1, 2}

[0132]

[0133] α ∈ [0, α 0 )

[0134]

[0135] Step C: Isolate the RIS phase shift optimization problem from Step B and solve this optimization problem;

[0136] Step D: Substitute the solution of the RIS phase shift obtained in Step C and into the optimization problem in Step B to obtain:

[0137]

[0138] s.t. p 1 + p 2 = P ≤ P max

[0139] p 2 ≥ p 1

[0140] p i ≥ 0, i ∈ {1, 2}

[0141]

[0142] 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 |;

[0143] Step E: Solve the optimization problem in step D to obtain the total power that maximizes the system energy efficiency, and further obtain the power allocation that maximizes the system energy efficiency and the reflection coefficient of the backscatter device.

[0144] 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 energy efficiency 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 energy efficiency. The optimization parameters are RIS phase shift, total power, power distribution, 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 transmission power of the base station, α is the reflection coefficient of the backscattering device, 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. σ 2 is the variance of additive white Gaussian noise, h1, h b and g b represents 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. |·| represents the absolute value. 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 |,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, and are the phase shift matrices of the two RIS, θ n ∈[0,2π), N is the number of reflection elements per RIS, 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: separating the RIS phase shift optimization problem from step B and solving the optimization problem; Step D: Solve the RIS phase shift obtained in step C and Substituting into the optimization problem in step B, we get: in, H* is the solution of the RIS phase shift obtained in step C substituted into |h r Θ1SΘ2g r |The obtained value; Step E, solving the optimization problem in step D, obtaining the total power that maximizes the system energy efficiency, and then obtaining the power allocation that maximizes the system energy efficiency and the reflection coefficient of the backscattering device.

2. The method for maximizing energy efficiency in a dual RIS-assisted backscatter communication system according to claim 1, characterized in that: The step C comprises the following steps: C1: Constructing the RIS phase shift optimization problem C2: Set the value of the threshold ε, set the maximum number of iterations K, let k = 1, θ n =0, C3: 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; C4: The result obtained in step C3 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; C5: Repeat steps C3 and C4 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 C1, and is also the variable θ in the optimization problem in step B. n and The solution is n=1,2,…,N.

3. The method for maximizing energy efficiency in a dual RIS-assisted backscatter communication system according to claim 1, characterized in that: The step E comprises the following steps: E1: Let P = P max , let m = 1, set the initial value of Δ, Δ is a positive integer; E2: According to the value of P, calculate and if and Execute step E3, otherwise set M=m and execute step E4; E3: Calculate the values ​​of c1 and c2. If |h1| 2 σ 2 -H *2 c2≥0, then let And p2=P-p1, if |h1| 2 σ 2 -H *2 c2<0, then let And p2=P-p1, let Let m = m + 1 and P = P max -(m-1)Δ, execute step E2; E4: Let g max = max{g(m), m = 1, 2, ..., M}, where m0 represents g max In the set {g(m), m=1,2,…,M}, then P=P max -(m0-1)Δ is the total power that maximizes the energy efficiency of the system; E5: Calculate based on the value of P and The value of, if |h1| 2 σ 2 -H *2 c2≥0, let And p2=P-p1, if |h1| 2 σ 2 -H *2 c2<0, let And p2 = P-p1, then p1 and p2 are the power allocations that maximize the energy efficiency of the system; E6: Calculate based on the value of P The value of α is the reflection coefficient of the backscattering device that maximizes the energy efficiency of the system.

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