Low-power-consumption transmission method applied to symbiotic radio system

Abstract

The invention discloses a low-power-consumption transmission method applied to a symbiotic radio system, which comprises the following steps: step 1, establishing a symbiotic radio system based on RIS, transmitting primary information to a primary receiver PRx by a primary transmitter, transmitting secondary information to a secondary receiver BRx by the RIS serving as a transmitter to modulate and reflect a primary signal, decoding the primary information by the PRx by using an ML detector, and transmitting the decoded primary information to a secondary receiver BRx; the BRx restores secondary information from the RIS using an energy detector. And step 2, based on the system model, establishing a transmitting power optimization problem of PRx primary information rate constraint and secondary receiver detection bit error rate (BER) constraint, for the problem, equivalently transforming the BER constraint, and decomposing the original problem into two similar sub-problems for solving. And step 3, replacing the non-convex PRx rate constraint with the proxy rate, and providing a method for iteratively solving the problem of transmitting beam forming and RIS coefficient alternate optimization. For an RIS-based symbiotic radio system, the method realizes information transmission and reduces the transmitting power.

Description

Technical Field

[0001] The invention relates to a low-power transmission method applied to a symbiotic radio system, and belongs to the technical field of wireless communications. Background Art

[0002] The Internet of Things (IoT) is considered to be one of the main driving forces of the future sixth generation (6G) system. IoT applications require strong self-sufficiency, so IoT devices must maintain extremely low power consumption. A promising low-power communication technology is ambient backscatter communication (AmBC), in which the backscatter device (BDx) transmits information by modulating the ambient radio frequency (RF) signal. Obviously, BDx eliminates the need to integrate a dedicated RF chain to send signals, thereby reducing cost and energy consumption. However, in the AmBC system, the backscatter receiver (BRx) is subject to direct link interference from ambient RF sources, which is much stronger than the backscatter signal. In order to eliminate the performance degradation caused by the above interference, existing studies have proposed a symbiotic radio (SR) system, in which the main transmitter (PTx) and the receiver (PRx) constitute the primary system, and the BDx and BRx constitute the secondary system, where both the primary system and the secondary system use ML detectors to obtain the transmitted information, the former converts the backscatter link into beneficial multipath components, and the latter eliminates the impact of the direct link. At the same time, in RIS-based SR systems, RIS is usually used as a backscatter device (RIS-BDx), not only for transmitting information for BRx, but also for improving the link between the main transceiver. However, in traditional SR systems based on smart metasurface RIS, PTx needs to adjust the direction of the information beam to meet the signal-to-noise ratio (SNR) constraint at BRx, which will result in higher transmission power, which will cause unnecessary waste of resources. In addition, the ML detection device used in the BRx decoder in traditional SR systems will increase the complexity of the BRx device. Summary of the invention

[0003] The purpose of the present invention is to propose a receiver decoding method for secondary information different from the traditional SR system in view of the defects and shortcomings of the existing RIS-based SR system with high transmission power, and then consider the joint design problem of joint transmit beamforming TBF and RIS reflection coefficient RC, establish the transmitter transmission power optimization problem, and propose an effective algorithm framework to solve the transmission power optimization problem in the RIS-based SR system, and optimize the transmission power in the SR system.

[0004] The specific plan is as follows:

[0005] A low-power transmission method applied to a symbiotic radio system comprises the following steps:

[0006] Step 1: Establish a symbiotic radio system based on RIS, where the primary transmitter transmits primary information to the primary receiver PRx, the RIS acts as a transmitter to modulate and reflect the primary signal to pass the secondary information to the secondary receiver BRx, the primary receiver PRx uses an ML detector to decode the primary information, and BRx uses an energy detector to recover the secondary information from the RIS;

[0007] Step 2: Based on the symbiotic radio system in step 1, establish the transmit power optimization problem under the constraints of the primary information rate of the primary receiver PRx and the bit error rate BER of the secondary receiver BRx. For this problem, the bit error rate BER of the secondary receiver BRx is equivalently transformed, and the transmit power optimization problem is decomposed into two similar sub-problems to be solved;

[0008] Step 3: The two sub-problems decomposed in step 2 are solved in the same way. For one of the sub-problems, the non-convex PRx rate constraint is replaced by the proxy rate, and a method for alternately optimizing the transmit beamforming TBF and RIS coefficients is proposed to iteratively solve the current sub-problem.

[0009] As a further improvement of the present invention, step 1 comprises:

[0010] Step 1-1: Consider a RIS-based symbiotic radio system with N t The antenna transmitter PTx delivers LT data symbols to the single antenna primary receiver PRx At the same time, Using equipment N r Independent reflection unit RIS modulates and reflects the main signal to transmit L single antenna backscatter receivers BRx Data symbol, where Q s and Q c They are data symbol sets for primary information and secondary information respectively. and are the index sets of L main symbols and T time points respectively; the channels from PTx to PRx, PTx to BRx, PTx to RIS, RIS to PTx, and RIS to PRx are defined as Where N t and N r are the number of antennas of the transmitter and the number of reflection units of the RIS, is a set of complex numbers, w is the transmit precoding vector, Φ = diag (φ) represents the RIS reflection matrix; The received signals of PRx and BRx are expressed as follows:

[0011]

[0012] in, and is zero and has a variance of δ 2 Additive Gaussian white noise;

[0013] Step 1-2: In the RIS-based symbiotic radio system, PRx uses an ML detector to decode the primary and secondary information, while BRx uses an energy detector to recover the secondary information from RIS;

[0014] PRx uses a maximum likelihood detector to decode the primary information, assuming The PRx implementation rate is:

[0015]

[0016] BRx uses an energy detector to decode secondary information. Assuming RIS uses BPSK modulation, The BRx receive signal is expressed as:

[0017]

[0018] in i=0,1,δ 2 is the noise power, and The related received signal is expressed as i=0,1.

[0019] Then BRx uses the energy detector to detect the secondary information The BER closed-form solution is:

[0020]

[0021] have

[0022] As a further improvement of the present invention, step 2 comprises:

[0023] Step 2-1: For the symbiotic radio system based on smart metasurface RIS, based on formula (3) PRx in step 1-2, the main information can achieve rate R p And formula (5) BRx energy detector detects secondary information BER, the transmitter transmission power optimization problem is established:

[0024]

[0025] In the problem established, the PRx master information can achieve rate R p Not less than the given r p , BRx detection secondary information The bit error rate BER is not higher than the given Λ s, by jointly designing the transmitter transmit beamforming and RIS reflection coefficient, the transmit power is minimized;

[0026] Step 2-2: For the transmitter power optimization problem, the BRx detection BER constraint is equivalently transformed and the original problem is decomposed into two similar sub-problems for solution; BRx detection The BER constraint equivalent transformation of two similar sub-problems is as follows:

[0027]

[0028]

[0029] Among them, λ s is to constrain P b ≤Λ s Convert to So, formula (7) is So, formula (8) is It is found that the solutions to the two sub-problems are the same. The following takes formula (7) as an example.

[0030] As a further improvement of the present invention, step 3 comprises:

[0031] Step 3-1: For formula (7), the non-convex PRx rate constraint R p The problem is still difficult to solve, so we use the proxy rate instead of R p :

[0032]

[0033] Based on formula (9), the problem model of formula (7) is equivalent to:

[0034]

[0035] in, h E,i =h 1 +GΦh r1 d i ,i=0,1.g E,i The specific expression of is reflected in step 1-2.

[0036] Step 3-2: To solve this problem, an alternating optimization (AO) method is found to deal with the problem. A method of alternating optimization of transmit beamforming TBF and RIS coefficients is proposed to iteratively solve the current sub-problem, fixing one of w and φ in turn to update the other;

[0037] When φ is given to update w, its updated subproblem is formula (11):

[0038]

[0039] In formula (11) Let auxiliary variable A = αα H , solve this problem to get α, then w * =H 0 α;

[0040] When updating φ given w, the subproblem of updating is formula (12):

[0041]

[0042] Among them, φ n is the nth element of the RIS reflection vector φ. If the optimal solution is feasible, the optimal solution should be the closest to The specific expressions of the elements involved are:

[0043]

[0044] Among them, w i (n) and v i (n) are w i and v i The nth element of n ,w i,n ,v i,n They are w i ,v i Remove the nth element from the vector, H r1 =diag(h r1 ),w i =[GH r1 d i ,h 1 ] H w,i=0,1,G r1 =diag(g r1 ),v i =[GG r1 d i ,g 1 ] H w;

[0045] Step 3-3: The optimal solution of formula (7) After the solution is obtained, the same method is used to solve formula (8) to obtain the optimal solution if Then the optimal solution of the original problem formula (6) is Otherwise, the optimal solution is

[0046] The present invention also provides a low-power transmission device for use in a symbiotic radio system, comprising: a symbiotic radio system establishment module, a transmission power optimization problem construction module and a sub-step solving module; wherein,

[0047] The symbiotic radio system establishment module is used to establish a symbiotic radio system based on RIS, wherein a primary transmitter transmits primary information to a primary receiver PRx, the RIS acts as a transmitter to modulate and reflect the primary signal to transmit secondary information to a secondary receiver BRx, the primary receiver PRx decodes the primary information using an ML detector, and the secondary receiver BRx recovers the secondary information from the RIS using an energy detector;

[0048] The transmit power optimization problem solving module is used to establish a transmit power optimization problem under the constraints of the primary information receiving rate of the primary receiver PRx and the secondary information receiving bit error rate BER of the secondary receiver BRx based on the symbiotic radio system. For this problem, the bit error rate BER constraint of the secondary receiver BRx is equivalently transformed, and the transmit power optimization problem is decomposed into two similar sub-problems for solution;

[0049] The sub-step solving module is used to replace the non-convex PRx rate constraint with a proxy rate for one of the sub-problems, propose a method for alternately optimizing the transmit beamforming TBF and RIS coefficients, and iteratively solve the current sub-problem, wherein the solution methods of the two decomposed sub-problems are the same.

[0050] The present invention also provides a computer storage medium having a computer program stored thereon, wherein the steps of the method are implemented when the computer program is executed by a processor.

[0051] The present invention also provides an electronic device, characterized in that it includes a memory and one or more processors, wherein the memory is used to store one or more programs; when the one or more programs are executed by the one or more processors, the described method is implemented.

[0052] Beneficial effects of the present invention:

[0053] 1. The present invention is directed to a symbiotic radio system based on a smart metasurface RIS, wherein a primary transmitter transmits primary information to a primary receiver, and the RIS acts as a transmitter to modulate and reflect the primary signal to transmit secondary information to a secondary receiver BRx, and the primary receiver PRx uses an ML detector to decode the primary information, and the secondary receiver BRx uses an energy detector to recover the secondary information from the RIS.

[0054] 2. The present invention is directed to the above-mentioned symbiotic radio system, and establishes a transmission power optimization problem under the constraints of the primary receiver PRx receiving primary information rate and the secondary receiver BRx receiving secondary information bit error rate, and minimizes the transmission power by jointly designing the transmitter transmit beamforming and RIS reflection coefficient.

[0055] 3. The present invention is aimed at the established transmit power optimization problem, transforms the bit error rate constraint of the secondary information received by the secondary receiver BRx, and divides the solution of the original problem into two sub-problems. Taking one sub-problem as an example, the non-convex main receiver receiving main information rate constraint is replaced with a proxy rate, and a method of alternately optimizing the transmit beamforming TBF and RIS coefficient is proposed to iteratively solve the current sub-problem, establish an algorithm framework for the sub-problem, and solve another sub-problem based on the algorithm framework, thereby solving the original problem.

[0056] 4. The present invention realizes the transmission of primary and secondary information and the reduction of transmission power in the proposed system, and because the BRx decoder is changed from an ML detection device to an energy detection device, the complexity of the BRx device is reduced. Simulation results show that in addition to ensuring information transmission and achievable rate, the transmission power of the proposed system is lower than that of the SR system in some scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 The figure is a flow chart of the method of the present invention.

[0058] Figure 2 Schematic diagram of the system model of the present invention.

[0059] Figure 3 A schematic diagram showing that one secondary symbol period of the system of the present invention includes T primary symbols.

[0060] Figure 4 This is a scene diagram of the initial positions of the transmitter and receiver of the system of the present invention.

[0061] Figure 5 The method of the present invention is based on the initial setting of the average transmission power under different schemes and the rate that the main receiver can achieve and the main rate constraint r p The left figure shows the relationship between the average transmission power and the main rate constraint r p The right figure shows the relationship between the rate that the main receiver can achieve and the main rate constraint r p relationship diagram.

[0062] Figure 6 is the average transmission power of the method of the present invention and the rate R that the main receiver can achieve p The left figure shows the average transmit power changing with the PRx position, and the right figure shows the rate R that the main receiver can achieve. p Plot of changes with PRx position.

[0063] Figure 7 The average transmission power and the rate R that the main receiver can achieve under different schemes of the present invention are pThe left figure shows the trend of the average transmission power changing with the position of BRx, and the right figure shows the rate R that the main receiver can achieve. p Trend chart with changes in BRx position.

[0064] Figure 8 This is a relationship diagram between the average transmission power and the number of antennas in the RIS under different schemes of the present invention. DETAILED DESCRIPTION

[0065] The invention will be further described in detail below in conjunction with the accompanying drawings.

[0066] like Figure 1 to Figure 2 As shown, the present invention provides a low-power transmission method applied to a symbiotic radio system, and the specific steps of the method are as follows:

[0067] Step 1: The present invention is based on the symbiotic radio system of the intelligent metasurface RIS. The following is an introduction to the system transmitter and receiver of the present invention:

[0068] PTx (primary transmitter) means transmitter.

[0069] RIS-BDx (backscatter device) means that the smart metasurface acts as a backscatter device, which not only enhances the transmission of primary information, but also modulates and reflects the primary signal to transmit secondary information to the backscatter receiver (BRx).

[0070] BRx (backscatter receiver) represents a backscatter receiver, which uses an energy detector to detect the secondary information modulated by RIS.

[0071] PRx (primary receiver) represents a receiver, which uses a maximum likelihood detector to detect primary information.

[0072] Specifically, step 1 includes:

[0073] Step 1-1: Consider a RIS-based symbiotic radio system with N t The antenna transmitter PTx delivers LT data symbols to the single antenna primary receiver PRx At the same time, Using equipment N r Independent reflection unit RIS modulates and reflects the main signal to transmit L single antenna backscatter receivers BRx Data symbol, where Q s and Q c They are data symbol sets for primary information and secondary information respectively. and are the index sets of L main symbols and T time points respectively; the channels from PTx to PRx, PTx to BRx, PTx to RIS, RIS to PTx, and RIS to PRx are defined as Where N t and N r are the number of antennas of the transmitter and the number of reflection units of the RIS, is a set of complex numbers, w is the transmit precoding vector, Φ = diag (φ) represents the RIS reflection matrix; The received signals of PRx and BRx are expressed as follows:

[0074]

[0075] in, and is zero and has a variance of δ 2 Additive white Gaussian noise.

[0076] Step 1-2: In the RIS-based symbiotic radio system, PRx uses an ML detector to decode the primary and secondary information, while BRx uses an energy detector to recover the secondary information from RIS.

[0077] PRx uses the Maximum Likelihood Detector (MLD) to decode the main information. Assume PRx can achieve the rate of:

[0078]

[0079] The secondary receiver BRx uses an energy detector to decode the secondary information. Assuming that RIS uses BPSK modulation, The BRx receive signal is expressed as:

[0080]

[0081] in i=0,1,δ 2 is the noise power, and The related received signal is expressed as i=0,1.

[0082] Then BRx uses the energy detector to detect the secondary information The BER closed-form solution is:

[0083]

[0084] have

[0085] Step 2: For the RIS-based symbiotic radio system, establish the transmission power optimization problem under the constraints of the primary receiver receiving the main information rate and the secondary receiver BRx receiving the secondary information bit error rate BER, transform the BRx detection BER constraint equivalently, and decompose the problem into two similar sub-problems for solution. Specifically, step 2 includes:

[0086] Step 2-1: For the symbiotic radio system based on smart metasurface RIS, the rate R can be achieved based on the PRx main information in step 1-2 p and BRx energy detectors detect secondary information BER, the transmitter transmission power optimization problem is established:

[0087]

[0088] In the above problem, the PRx main information can achieve a rate R p Not less than the given r p , BRx detection secondary information The bit error rate BER is not higher than the given Λ s , the transmit power is minimized by jointly designing the transmitter transmit beamforming and RIS reflection coefficient.

[0089] Step 2-2: For the transmitter power optimization problem, the BRx detection BER constraint is equivalently transformed and the original problem is decomposed into two similar sub-problems for solution. The BER constraint equivalence transforms two similar sub-problems:

[0090]

[0091] λ s is to constrain P b ≤Λ s Convert to Formula (7) is So, formula (8) is The solution methods of the two sub-problems are the same. The following takes formula (7) as an example to solve it.

[0092] Step 3: For the problem in formula (7), the non-convex PRx rate constraint is replaced by the proxy rate, and a method of alternately optimizing the transmit beamforming TBF and RIS coefficients is proposed to iteratively solve the current sub-problem. Formula (8) is solved in the same way. Finally, the solution of formula (6) is obtained by combining the optimal solutions of formula (7) and formula (8).

[0093] Specifically, step 3 includes:

[0094] Step 3-1: For formula (7), the non-convex PRx rate constraint Rp The problem is still difficult to solve, so we use the proxy rate instead of R p :

[0095]

[0096] Based on formula (9), the problem in formula (7) is equivalent to:

[0097]

[0098] in, h E,i =h 1 +GΦh r1 d i ,i=0,1.g E,i The specific expression is reflected in steps 1-2 of the claims.

[0099] Step 3-2: To solve this problem, an alternating optimization (AO) method is found to deal with the problem. A method of alternating optimization of transmit beamforming TBF and RIS coefficients is proposed to iteratively solve the current sub-problem, fixing one of w and φ in turn to update the other;

[0100] When φ is given to update w, its updated subproblem is formula (11):

[0101]

[0102] In formula (11) Let auxiliary variable A = αα H , solve this problem to get α, then w * =H 0 α;

[0103] When updating φ given w, the subproblem of updating is formula (12):

[0104]

[0105] Among them, φ n is the nth element of the RIS reflection vector φ. If the optimal solution is feasible, the optimal solution should be the closest to The specific expressions of the elements involved are:

[0106]

[0107] Among them, w i (n) and v i (n) are w i and v i The nth element of n ,w i,n ,vi,n They are w i ,v i Remove the n-th element from the vector, H r1 =diag(h r1 ),w i =[GH r1 d i ,h 1 ] H w,i=0,1,G r1 =diag(g r1 ),v i =[GG r1 d i ,g 1 ] H w;

[0108] Step 3-3: The optimal solution of formula (7) After the solution is obtained, the same method is used to solve formula (8) to obtain the optimal solution if Then the optimal solution of the original problem formula (6) is Otherwise, the optimal solution is

[0109] The detailed algorithm flow framework for solving formula (7) is shown in Table 1.

[0110] Table 1 AO algorithm flow chart

[0111]

[0112] The performance of the low-power transmission scheme in the above symbiotic radio system was simulated using MATLAB for the corresponding scenarios, and the CVX software package was used to solve the optimization problem.

[0113] The simulation scenario is programmed using MATLAB software, and the specific parameters that conform to the actual scenario are given in the specific implementation method. The transmitter transmission power, BRx secondary information bit error rate, PRx SNR and PRx, BRx position are used as performance indicators. For each simulation scenario, the average result of 100 channel performances is generated.

[0114] The SR system simulation design is as follows:

[0115] PTx is located at (0,0) and is equipped with a uniform linear array of 10 antennas, with a normal vector direction of 0; RIS is located at (20,25) and is equipped with a uniform linear array of 1000 antennas, with a normal vector direction of PRx is located at (35,0), BRx is located at (45,20); one secondary symbol contains T = 50 primary symbols, PRx rate constraint rp = 3.46bps, BRx constraint Λ s =10 -3 ; The channel fading model is β(d) = C 0 d -α , refer to the distance of one meter to C 0 Set to -20dB, α is the path loss exponent, and d represents the link distance. The channel from PTx to RIS in the SR system can be expressed as G LoS is the line of sight (LoS) component, G NLoS is the Rayleigh fading component, whose elements follow the CN(0,1) distribution. For G, set α=2.2,κ=0.7; for channel g 1 and h 1 , constructed in the same way, setting α = 2.8, κ = 0, for channel g r1 and h r1 , constructed in the same way, setting κ = 0.7; noise power δ 2 =-70dB; in the algorithm, set ε = 3×10 -3 ,All the results are achieved by running the channel 100 times.

[0116] In this embodiment, two benchmark schemes are considered: (1) under the PRx rate constraint, there is no RIS or BRx maximum wireless transmission (MRT) precoding, denoted as "WO"; (2) based on the traditional SR system, BRx decodes the secondary information using the maximum likelihood decoder MLD, then the joint design problem is

[0117]

[0118] BRx Using MLD to decode the main information: Γ s is the required SNR for the secondary transmission, when BRx Medium SNR(Γ s ) and BER(Λ s ) is: s =(Q -1 (Λ s )) 2 / 2. Merge R s ≥r p and γ s2 ≥Γ s Constraints This problem is solved using the proposed algorithm framework.

[0119] The subscripts "SUR", "SR", and "WO" represent the scheme of the method of the present invention, the conventional SR system scheme, and the scheme without RIS or BRx using MRT precoding, respectively; the subscripts "0" and "1" represent and sub-problem of .

[0120] Figure 5 The two figures are based on the above setting scenario and use Matlab to plot the average transmit power and the main rate constraint r under different schemes. p From the two figures, it can be seen that the transmission power and the rate Rp that the main receiver can achieve are both proportional to r. p By comparing the WO curve with other curves, it can be found that with the help of RIS, the "SR" and "SUR" schemes can reduce the transmission power while transmitting secondary information. In addition, it can be found that in the currently set scenario, the transmission power of the proposed scheme is lower than that of the SR system, but the achievable rate of PRx of the proposed "SUR" scheme is lower than that of "SR".

[0121] Figure 6 The two graphs show the transmit power and the achievable rate R p Changes with the position of PRx. It can be seen that as the position of PRx gets closer to PTx, the transmission power of the proposed "SUR" scheme decreases; while the transmission power of the SR scheme hardly changes. The main reason is that in the SR system, the rate constraint of BRx on the main signal hinders the reduction of the transmission power; while in the "SUR" scheme, BRx does not need to demodulate the main signal, so when PRx is close to PTx, the average transmission power will be lower than the transmission power of SR.

[0122] Figure 7 The two graphs show the transmit power and the achievable rate R p As the position of BRx changes. When BRx is close to PTx and RIS, the transmit power of the SR system is less than that of the "SUR" scheme system. However, as BRx continues to move away, the main signal rate constraint at BRx will cause the transmit power of the SR system to increase rapidly. It is worth noting that as BRx moves away, the transmit power of the "SUR" scheme system continues to decrease. The reason may be that the direct link interference from PTx decreases rapidly at this time, resulting in improved energy detection performance and reduced average transmit power. It can be seen that the proposed "SUR" scheme has a slightly increased average transmit power as the distance between BRx and RIS and PTx gradually increases, but the overall average transmit power is still much lower than that of the SR system.

[0123] Figure 8The graph shows the average transmit power as a function of the number of antennas in the RIS. It can be seen that in the RIS-enabled system, the transmit power decreases as the number of RIS antennas increases, and eventually becomes lower than that of the system without RIS. It can also be seen that under the PRx achievable rate constraint, within a certain range of RIS antennas, the transmit power of the "SUR" scheme is lower than that of the SR system.

[0124] In the present invention, a low-power transmission method for a symbiotic radio system is proposed, wherein a main transmitter transmits main information to a main receiver, and a RIS acts as a transmitter to modulate and reflect the main signal to pass the secondary information to a secondary receiver BRx. The main receiver PRx uses an ML detector to decode the main information, and the secondary receiver BRx uses an energy detector to recover the secondary information from the RIS, and a transmission power optimization problem under the constraints of the rate of the main information received by the main receiver PRx and the bit error rate of the secondary information received by the secondary receiver BRx is established. In response to this problem, the bit error rate constraint of the secondary receiver BRx receiving the secondary information is transformed, and the solution of the original problem is divided into two sub-problems. Taking a sub-problem as an example, the non-convex main receiver receiving main information rate constraint is replaced with a proxy rate, and a method of alternating optimization of the transmit beamforming TBF and the RIS coefficient is proposed to iteratively solve the current sub-problem, establish an algorithm framework for the sub-problem, and solve another sub-problem based on the algorithm framework, thereby solving the original problem. According to Figure 5 , Figure 6 and Figure 7 The simulation diagram and the above analysis show that the transmission power of the "SUR" scheme proposed based on the SR system is related to the relative position of the primary receiver and the transmitter, the relative position of the secondary receiver and the RIS and the transmitter, and the number of reflection units of the RIS. When the primary receiver is close to the transmitter (within 35m) or the secondary receiver is far away from the transmitter (greater than 45m) and the RIS, or the number of reflection units of the RIS is small (less than 2 11 ), the transmission power of the transmitter will be lower than that of the traditional SR system.

[0125] The above is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiment. There may be local minor structural changes during the implementation process. If the various changes or modifications of the present invention do not depart from the spirit and scope of the present invention and fall within the scope of the claims and equivalent technologies of the present invention, the present invention is also intended to include these changes and modifications.

Claims

1. A low-power transmission method applied to a symbiotic radio system, characterized in that: The steps include: Step 1: Establish a symbiotic radio system based on RIS. The primary transmitter transmits the primary information to the primary receiver PRx. The RIS acts as a transmitter to modulate and reflect the primary signal to pass the secondary information to the secondary receiver BRx. PRx uses an ML detector to decode the primary information, and BRx uses an energy detector to recover the secondary information from the RIS. Step 2: Based on the symbiotic radio system in step 1, establish the transmit power optimization problem under the constraints of the primary information rate of the primary receiver PRx and the bit error rate BER of the secondary receiver BRx. For this problem, the bit error rate BER of the secondary receiver BRx is equivalently transformed, and the transmit power optimization problem is decomposed into two similar sub-problems to be solved; Step 3: The two sub-problems decomposed in step 2 are solved in the same way. For one of the sub-problems, the non-convex PRx rate constraint is replaced by the proxy rate, and a method for alternately optimizing the transmit beamforming TBF and RIS coefficients is proposed to iteratively solve the current sub-problem.

2. A low power transmission method for a symbiotic radio system as claimed in claim 1, characterized in that: Step 1 includes: Step 1-1: Consider a RIS-based symbiotic radio system with N t The antenna transmitter PTx delivers LT data symbols s to the single antenna primary receiver PRx l (t) at the same time, Using equipment N r The independent reflection unit RIS modulates and reflects the main signal to transmit L c to the single antenna backscatter receiver BRx l Data symbol, where and They are data symbol sets for primary information and secondary information respectively. and are the index sets of L main symbols and T time points respectively; the channels from PTx to PRx, PTx to BRx, PTx to RIS, RIS to PTx, and RIS to PRx are defined as Where N t and N r are the number of antennas of the transmitter and the number of reflection units of the RIS, is a set of complex numbers, w is the transmit precoding vector, Φ=diag(φ) represents the RIS reflection matrix; in the lth minor symbol period, the received signals of PRx and BRx are respectively expressed as: y l (t)=(h1+GΦh r1 c l ) H ws l (t)+n p,l (t),t∈T (1) z l (t)=(g1+GΦg r1 c l ) H ws l (t)+n s,l (t),t∈T (2) Among them, n p,l (t) and n s,l (t) has a mean of zero and a variance of δ 2 Additive Gaussian white noise; Step 1-2: In the RIS-based symbiotic radio system, PRx uses an ML detector to decode the primary and secondary information, while BRx uses an energy detector to recover the secondary information from RIS; PRx uses a maximum likelihood detector to decode the main information, assuming E|s l (t)| 2 =1, the PRx implementation rate is: BRx uses an energy detector to decode secondary information. Assuming RIS uses BPSK modulation, The BRx receive signal is expressed as: in δ 2 is the noise power, and c l The related received signal is denoted as z l =[z l (1),...,z l (T)] T , Then BRx uses the energy detector to detect the secondary information c l The BER closed-form solution is: have 3. A low-power transmission method for a symbiotic radio system as claimed in claim 2, characterized in that: Step 2 includes: Step 2-1: For the symbiotic radio system based on smart metasurface RIS, based on formula (3) PRx in step 1-2, the main information can achieve rate R p And formula (5) BRx energy detector detects secondary information c l BER, the transmitter transmission power optimization problem is established: In the problem established, the PRx master information can achieve rate R p Not less than the given r p , BRx detects secondary information c l The bit error rate BER is not higher than the given Λ s , by jointly designing the transmitter transmit beamforming and RIS reflection coefficient, the transmit power is minimized; Step 2-2: For the transmitter power optimization problem, the BRx detection BER constraint is equivalently transformed and the original problem is decomposed into two similar sub-problems for solution; BRx detection c l The BER constraint equivalent transformation of two similar sub-problems is as follows: Among them, λ s is to constrain P b ≤Λ s Convert to So, formula (7) is So, formula (8) is It turns out that the solutions to the two sub-problems are consistent.

4. A low power transmission method for a symbiotic radio system as claimed in claim 3, characterized in that: Step 3 includes: Step 3-1: For formula (7), the non-convex PRx rate constraint R p The problem is still difficult to solve, so we use the proxy rate instead of R p : Based on formula (9), the problem model of formula (7) is equivalent to: in, h E,i =h1+GΦh r1 d i ,i=0,1. Step 3-2: To solve this problem, an alternating optimization method is found to solve the problem. A method of alternating optimization of transmit beamforming TBF and RIS coefficients is proposed to iteratively solve the current sub-problem, and one of w and φ is fixed in turn to update the other; When w is updated given φ, the updated subproblem is formula (11): In formula (11) Let auxiliary variable A = αα H , solve this problem to get α, then w * =H0α; When updating φ given w, the subproblem of updating is formula (12): Among them, φ n is the nth element of the RIS reflection vector φ. If the optimal solution is feasible, the optimal solution should be the closest to The specific expressions of the elements involved are: c a (n)=c al (n))+c a0 (n), c b (n)=c b1 ( n )-λ s c b0 (n), Among them, w i (n) and v i (n) are w i and v i The nth element of n ,w i,n ,v i,n They are w i ,v i Remove the vector with the nth element removed, H r1 =diag(h r1 ),w i =[GH r1 d i ,h1] H w,i=0,1,G r1 =diag(g r1 ),v i =[GG r1 d i ,g1] H w; Step 3-3: The optimal solution of formula (7) After the solution is obtained, the same method is used to solve formula (8) to obtain the optimal solution if Then the optimal solution of the original problem formula (6) is Otherwise, the optimal solution is 5. A low-power transmission device used in a symbiotic radio system, characterized in that: include: Symbiotic radio system building module, transmit power optimization problem building module and sub-step solving module; wherein, The symbiotic radio system establishment module is used to establish a symbiotic radio system based on RIS, wherein a primary transmitter transmits primary information to a primary receiver PRx, the RIS acts as a transmitter to modulate and reflect the primary signal to transmit secondary information to a secondary receiver BRx, the primary receiver PRx decodes the primary information using an ML detector, and the secondary receiver BRx recovers the secondary information from the RIS using an energy detector; The transmit power optimization problem solving module is used to establish a transmit power optimization problem under the constraints of the primary information receiving rate of the primary receiver PRx and the secondary information receiving bit error rate BER of the secondary receiver BRx based on the symbiotic radio system. For this problem, the bit error rate BER constraint of the secondary receiver BRx is equivalently transformed, and the transmit power optimization problem is decomposed into two similar sub-problems for solution; The sub-step solving module is used to replace the non-convex PRx rate constraint with a proxy rate for one of the sub-problems, propose a method for alternately optimizing the transmit beamforming TBF and RIS coefficients, and iteratively solve the current sub-problem, wherein the solution methods of the two decomposed sub-problems are the same.

6. A computer storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

7. An electronic device, characterized in that: The method comprises a memory and one or more processors, wherein the memory is used to store one or more programs; when the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 4 is implemented.

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