A method and system for optimizing backlinks in conjunction with IRS and wireless power supply

Abstract

This invention relates to the field of 6G wireless communication network technology, and discloses a system backlink optimization method and system combining IRS and wireless power supply, comprising: S1, a base station sends a main link signal to a smart reflector and multiple clusters, the smart reflector reflects and forwards the main link signal to the multiple clusters, each cluster including a receiver and multiple backscattering devices; S2, the multiple BD devices use the received main link signal as a carrier to modulate and transmit their respective IoT information to the corresponding receiver in corresponding time slots. During transmission, the time slot is divided into two stages. In the first stage, the BD devices perform passive backscattering transmission while simultaneously using wireless power supply technology to collect energy. In the second stage, the BD devices perform active backscattering transmission using the collected energy. This invention maximizes the sum rate of the system backscattering link and combats inter-BD interference.

Description

Technical Field

[0001] This invention relates to the field of 6G wireless communication network technology, specifically to a system backlink optimization method and system that combines IRS and wireless power supply. Background Technology

[0002] With the development of wireless communication technology, high bandwidth and low latency have laid the foundation for the future Internet of Things (IoT). However, the arrival of the IoT era has also brought a series of problems. For example, the massive number of IoT devices accessing wireless communication networks results in huge spectrum resource consumption, which not only wastes a lot of spectrum resources but also affects normal communication between cellular users to some extent. In addition, the simultaneous operation of a large number of IoT nodes will bring huge energy consumption problems, and of course, the construction of such infrastructure will also bring huge costs.

[0003] Symbiotic radio (SR) is a cooperative environmental backscatter communication technology with advantages such as high spectral efficiency, high energy efficiency, and low cost. The system consists of two main communication links: a primary link (cellular link, WiFi, etc., serving the user) and a secondary link (IoT link, transmitting IoT information collected by IoT nodes). The secondary link modulates its own IoT information onto the received primary link signal and then reflects the modulated information back to the receiver (user) via a passive IoT device (backscatter device, BD), achieving the purpose of IoT information communication. In this process, the secondary link not only shares the spectrum of the primary link but also shares the primary link's transmitter (base station, BS) and receiver (user), among other infrastructure. Furthermore, the backscatter device is passive, consuming no additional energy resources and incurring low cost. Therefore, symbiotic radio technology is considered one of the most effective solutions for connecting massive numbers of IoT devices to wireless communication networks in the future.

[0004] Meanwhile, Intelligent Reflecting Surfaces (IRS) are a wireless communication aid technology with high spectral efficiency, high energy efficiency, and low cost, which has attracted widespread attention in the field of wireless communication in recent years and is considered one of the key technologies for next-generation wireless communication. Intelligent Reflecting Surfaces consist of a large number of low-cost passive reflective elements, each of which can independently adjust its reflection coefficient (including amplitude and phase). Through optimization of mathematical theory, the wireless channel environment is intelligently reconstructed according to the needs of the actual communication system to achieve purposes such as enhancing useful signals, suppressing interference signals, and protecting security and privacy.

[0005] Patent No. 202210198813.0 discloses "A Method and System for Optimizing IoT Links Using a Combination of IRS and SR Technologies" (referred to as "the previous case"). This method leverages the advantages of symbiotic radio and smart reflective surfaces, namely high spectral efficiency, high energy efficiency, and low cost. It allows secondary links to share not only the spectrum of the primary link but also the primary link's transmitters and receivers, as well as other infrastructure. Furthermore, the introduction of smart reflective surfaces dynamically adjusts the channel between the base station, receiver, and IoT devices, enhancing useful signals and suppressing interference signals. These two methods work together to effectively solve the problem in multi-user scenarios where massive numbers of IoT devices occupy large amounts of spectrum resources, reducing information transmission rates and affecting cellular user communication. Moreover, IoT devices are passive and do not consume additional energy resources. In addition, this IoT link optimization method introduces user matching strategies and model calculation methods to match each IoT device with a receiver that can achieve the optimal rate in multi-user scenarios, thereby maximizing the total IoT information transmission rate while meeting the minimum transmission rate requirement of the primary link. However, the previous case did not consider the following situation:

[0006] Currently, there are scenarios with multiple users and large-scale BD devices. The access of large-scale BD devices will exacerbate the double fading effect of the symbiotic communication system (that is, due to the passive characteristics of BD devices, the two links of base station-BD device and BD device-receiver will fade). The scenario is more complex and accommodates more network nodes. In this scenario, how to optimize the sum rate of the backscattered links is an urgent problem to be solved. Summary of the Invention

[0007] This invention provides a backlink optimization method and system that combines IRS and wireless power supply. It introduces intelligent reflective surface technology to intelligently reconstruct the wireless communication environment. While ensuring the minimum data rate requirement for cellular users in the main link, it enhances information transmission in the backscatter link by optimizing the reflection coefficient of each reflective unit. Simultaneously, considering multi-user, large-scale BD scenarios, it introduces wireless power supply technology, adopts a NOMA+TDMA access method to accommodate a large number of BD nodes, and optimizes the active and passive transmission time allocation strategy to achieve the optimal sum rate of the backscatter link in the symbiotic communication system. These two technical means ensure that the symbiotic communication system maximizes its advantages in multi-user and large-scale BD scenarios.

[0008] This invention is achieved through the following technical solution:

[0009] A method for optimizing the backlink of a system that combines IRS and wireless power supply includes:

[0010] S1. The base station sends the main link signal to the smart reflector and multiple clusters. The smart reflector reflects and forwards the main link signal to the multiple clusters. Each cluster includes a receiver and multiple BD devices.

[0011] S2. Multiple BD devices use the received main link signal as a carrier to modulate and transmit their respective IoT information to the corresponding receiver in the corresponding time slot. During transmission, the time slot is divided into two stages. In the first stage, the BD devices perform passive backscatter transmission and simultaneously use wireless power supply technology to collect energy. In the second stage, the BD devices perform active backscatter transmission using the collected energy.

[0012] As an optimization, the base station and the smart reflective surface use TDMA to transmit information to the receiver and the BD device, and each cluster uses NOMA to transmit information to the corresponding receiver in the cluster.

[0013] As an optimization, the specific process by which the intelligent reflective surface reflects and forwards the main link signal to multiple clusters is as follows: the intelligent reflective surface receives the main link signal sent by the base station, dynamically adjusts the reflection coefficient of each reflection unit of the intelligent reflective surface, reconstructs the channel environment from the base station to the cluster, and after reconstruction, the intelligent reflective surface sends the main link signal to the cluster.

[0014] As an optimization, the signal received by the receiver is:

[0015] y m = y m+y m ;

[0016]

[0017]

[0018] Where, y′ m y″ represents the signal received by the receiver in the first stage. m x represents the signal received by the receiver in the second stage. m c represents the information symbol sent by the base station to the receiver in the m-th cluster. m，n P represents the information symbol sent to the receiver by the nth BD device in the mth cluster, where P = ||w|| 2 μ' is the base station's transmit power. m In the first stage, the power is σ. 2 Zero-mean additive white Gaussian noise, Φ=diag{φ1,φ2,…,φ Q} represents the reflection coefficient matrix of the intelligent reflective surface, w = [w1, w2, ..., w R ] T This represents the active beamforming vector of the base station. Let m be the channel between the base station and the m-th receiver. This refers to the channel between the base station and the nth BD device in the mth cluster. For the channel between the base station and the smart reflective surface, Let be the channel between the smart reflective surface and the receiver in the m-th cluster. Let Q be the channel between the smart reflective surface and the nth BD in the m-th cluster, and let Q be the number of reflective elements on the smart reflective surface. Let α be the channel between the nth BD in the mth cluster and the receiver in that cluster. m，n α represents the reflection coefficient of the nth BD device in the mth cluster. m，n ∈[0,1], P m，n This represents the active transmission power of the nth BD device in the mth cluster. Let t be the energy collected by the nth BD device in the mth cluster during the first phase, and t be the time slot length. Let μ″ be the proportion of time slots occupied by the BD device in the m-th cluster during the first phase. m The second stage is additive white Gaussian noise, which follows a Gaussian distribution with a mean of 0 and a variance of σ.

[0019] As an optimization, in the first stage:

[0020] The signal-to-noise ratio of the main link signal received by the receiver in the m-th cluster is:

[0021]

[0022] The expected transmission rate of the main link signal received by the receiver in the m-th cluster is:

[0023]

[0024] Where t is the time slot length. This represents the proportion of time slots occupied by the BD device in the m-th cluster during the first phase. c represents the expectation of the backscattered link transmission symbols. m，n The symbol represents the information transmitted by the IoT link of the BD device in the m-th cluster, where N is the total number of BD devices in the m-th cluster.

[0025] The signal-to-noise ratio of the IoT signal received by the receiver in the m-th cluster from the n-th BD device is:

[0026]

[0027] Where K is the ratio of the period of the IoT information symbol to the period of the main link information symbol;

[0028] The transmission rate of IoT information received by the receiver in the m-th cluster from the n-th BD device is:

[0029]

[0030] The formula for energy harvesting at the nth BD in the m-th cluster is:

[0031]

[0032] η is the energy ratio of active information transmission in the second stage, η∈(0,1);

[0033] In the second stage:

[0034] The transmission rate of the main link signal received by the receiver in the m-th cluster is:

[0035]

[0036] In the m-th cluster, the transmission rate of the secondary link between the n-th BD device and the receiver is:

[0037]

[0038] As an optimization, in S2, before the BD device uses the received main link signal as a carrier to modulate and transmit its respective IoT information to the corresponding receiver, it ensures the minimum communication rate requirement of the main transmission link. Under the premise of the base station's active beamforming vector w, the reflection coefficient matrix of the intelligent reflective surface's passive beamforming, and the time allocation coefficient vector, A backscattering propagation rate maximization model is established and solved to maximize the sum rate of backscattering propagation.

[0039] As an optimization, the backscattering transmission rate maximization model is specifically as follows:

[0040] P1:

[0041] st

[0042] P≤P max ,

[0043]

[0044]

[0045] Among them, Φ=diag{φ1,φ2,…,φ Q} represents the reflection coefficient matrix of the intelligent reflective surface, w = [w1, w2, ..., w R ] T This represents the active beamforming vector of the base station. Let R be the time allocation coefficient vector for the first stage; where R m =R' m +R” m P is the base station's transmit power, expressed as P = ||w|| 2 The first constraint ensures that the transmission rate of the main link is not lower than [a certain value]. The second constraint at the base station (BS) limits its maximum transmit power to no more than P. max The third constraint is the time allocation constraint, and both the time allocation coefficient and the reflection coefficient of BD are between 0 and 1; the fourth constraint is the unit modulus constraint of IRS.

[0046] As an optimization, the specific steps for solving the backscattering transmission rate maximization model are as follows:

[0047] A1. Define the backscattering transmission rate maximization model as a non-convex optimization problem P1;

[0048] A2. Decouple the three variables of the non-convex optimization problem P1 into three sub-problems. The three variables are the reflection coefficient matrix φ of the intelligent reflective surface, the active beamforming vector w of the base station, and the time allocation coefficient vector of the first stage.

[0049] A3. In each subproblem, a semi-definite relaxation algorithm and a Lagrange algorithm are used for solution. Simultaneously, the three coupled variables are iteratively solved using gradient descent, thereby obtaining the reflection coefficient matrix φ of the intelligent reflective surface, the active beamforming vector w of the base station, and the time allocation coefficient vector for the first stage. A joint optimization design scheme for backscattering links in a symbiotic communication system.

[0050] As an optimization, the specific process for A3 is as follows:

[0051] A3.1 During the j-th iteration, for a given base station active beamforming vector w {j-1} and the passive beamforming matrix Φ of the intelligent reflective surface {j-1} The non-convex optimization problem P1 is transformed into a first subproblem concerning the allocation of active and passive time:

[0052] P1-(1):

[0053] st

[0054]

[0055] A3.2 Solve the first subproblem to obtain the time allocation vector for the j-th iteration.

[0056] A3.3 In the (j+1)th iteration, the time allocation vector of the j-th iteration is... Substitute this into the non-convex optimization problem P1, and simultaneously, in the i-th iteration, provide the base station active beamforming vector w. {i-1} The non-convex optimization problem P1 is transformed into a second subproblem:

[0057] P1-(1-1):

[0058] st

[0059] t≥0,0≤α m,n ≤1,

[0060]

[0061] A3.4. The semidefinite relaxation algorithm is used to solve the second subproblem, obtaining the reflection coefficient matrix Φ of the intelligent reflective surface in the i-th iteration. {i} And the reflection coefficient matrix Φ of the smart reflective surface in the i-th iteration {i} Substituting the non-convex optimization problem P1 into the (i+1)th iteration yields the third subproblem:

[0062] P1-(1-2):

[0063] st

[0064] P≤P max ,

[0065] t≥0,0≤α m,n ≤1,

[0066] A3.5 Solving the third sub-problem yields the given base station active beamforming vector w in the (i+1)th iteration. {i+1} And substitute the value back into the second subproblem to solve it, when |w {i+1} -w {i-1} When |≤Δ, where Δ is the minimum error allowed by the iterative algorithm, the iteration stops, and the optimal base station active beamforming vector w for this iteration (j+1) is obtained. {j+1} and the passive beamforming matrix Φ of the intelligent reflective surface {j+1};

[0067] A3.6, The base station active beamforming vector w {j+1} and the passive beamforming matrix Φ of the intelligent reflective surface {j+1} Substituting into the first subproblem, when |w {j+1} -w {j-1} |≤Δ and|Φ {j+1} -Φ {j-1} When |≤Δ, where Δ is the minimum error allowed by the iterative algorithm, the iteration stops, and the base station active beamforming vector w, the passive beamforming matrix Φ of the smart reflector surface, and the time allocation strategy vector are obtained. A joint optimization design scheme for backscattering links in a symbiotic communication system was proposed, and the solution of the backscattering transmission rate maximization model was obtained.

[0068] This invention also discloses a backlink optimization system combining IRS and wireless power supply, comprising: a base station, a smart reflective surface with multiple reflective elements, and multiple clusters, each cluster including a receiver and multiple BD devices; the smart reflective surface is connected to a smart controller; the base station communicates with the receiver in the m-th cluster via channel h. m The connection is established between the base station and the nth BD device in the mth cluster via channel h. m，n The connection between the base station and the smart reflective surface is via channel H. BR The connection is established between the smart reflective surface and the nth BD device in the mth cluster via channel g. m，n The connection is established between the smart reflective surface and the receiver in the m-th cluster via channel g. m The connection is established between the nth BD device in the mth cluster and the receiver in that cluster via channel h′. m，n connect.

[0069] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0070] This invention proposes a system and method for optimizing the backlink of a system that combines IRS and wireless power supply. The BD (Browser Detector) device modulates and reflects its own IoT information using the main link signals from the base station and the smart reflector surface, while ensuring main link transmission. A novel TDMA+NOMA access method is adopted to accommodate more BD devices. With the assistance of the smart reflector surface and wireless power supply technology, the low transmission rate caused by the passive nature of BD devices and the interference between multiple BD devices are improved through optimization of the base station-BD link and the BD-receiver link. This invention designs an efficient optimization algorithm to jointly optimize the active beamforming vector w of the base station (BS), the passive beamforming matrix Φ of the smart reflector surface (IRS), and the active and passive time allocation vectors. While meeting the minimum requirements of the main link rate, it maximizes the sum rate of the system's backscatter links and combats inter-BD interference, demonstrating strong application value and development potential. Attached Figure Description

[0071] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0072] Figure 1 This is a schematic diagram of the structural composition of the symbiotic system of the present invention;

[0073] Figure 2 This is a design diagram of the transmission frame structure of the symbiotic system of the present invention. Detailed Implementation

[0074] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0075] Example

[0076] This invention discloses a backlink optimization method for a system combining IRS and wireless power supply. The technical solution is a backscattering link optimization design for a multi-user, large-scale BD co-occurrence communication system assisted by intelligent reflective surfaces and wireless power supply technology. The system structure is as follows: Figure 1 As shown, the system consists of a multi-antenna base station, a smart reflective surface IRS with Q reflective elements, M users (receivers), and M*N BD devices. The M*N BD devices are divided into M clusters. Inter-cluster access is achieved through TDMA. Within a cluster, BDs transmit information to the receiver in that cluster through NOMA. The receiver uses SIC continuous interference cancellation for decoding.

[0077] Transmission frame structure as follows Figure 2 As shown, in the m-th cluster, m∈M, the time slot length t is divided into two parts. In the first stage, passive backscatter transmission is performed, and energy is collected using wireless power supply technology. In the second stage, the energy collected in the first stage is used for active information transmission.

[0078] The intelligent reflective surface is connected to an intelligent controller, which can dynamically adjust the reflection coefficient (including amplitude and phase shift) of each unit of the intelligent reflective surface to intelligently reconstruct the wireless communication channel environment.

[0079] The basic working principle of a multi-user, large-scale BD co-communication system assisted by intelligent reflective surfaces and wireless power supply technology is as follows: The base station (BS) serves M clusters in the area through TDMA (Time Division Multiple Access). Due to the long distance between the base station and the clusters and the presence of certain obstacles, the intelligent reflective surface is used to assist the main link transmission. On the other hand, M*N BD devices are allocated to each time slot and work in collaboration with the corresponding users using NOMA (Normally Oscillating Multiple Access). The BD devices use the received main link signal as a carrier to modulate and transmit their own IoT information. Because the backscatter link's BD device uses passive transmission in the first stage of transmission, and because the IoT information symbol period is much longer than the main link information symbol period in order to accurately decode IoT and cellular information at the receiver, and considering the distance between the BD device and the BS and the existence of some obstruction, the IoT link transmission rate is weak. In this case, the intelligent reflective surface can dynamically adjust the reflection coefficient of each unit, reconstruct the channel environment from the base station to the BD device, and enhance the secondary link signal strength. Simultaneously, each time slot is divided into two stages: the first stage performs passive backscatter transmission while using wireless power supply technology to collect energy; the second stage uses the energy collected in the first stage for active information transmission. This improves the fading problem caused by purely passive transmission without increasing the system's additional energy consumption. Optimizing the time allocation coefficient maximizes the total rate of the backscatter link.

[0080] At the BD (Browser Detection) device, Binary Phase Shift Keying (BPSK) is used to modulate its IoT information onto the main link signal and reflect it back to the corresponding receiver (user). Therefore, in each time slot, the user receives two signals: the main link signal and the IoT signal. Considering that the symbol period of the IoT information in the symbiotic system is much longer than the symbol period of the main link, both signals can be accurately decoded at the receiver using Successive Interference Cancellation (SIC) technology. The main link signal includes the signal directly sent to the user by the base station (BS), the signal reflected by the smart reflector, and the main link information decoded from the IoT information reflected back to the user by the BD device, while the IoT signal originates entirely from the BD device.

[0081] The first stage of backscatter transmission in BD equipment:

[0082] In Phase 1, the signal received by the receiver in the m-th cluster can be obtained as follows:

[0083]

[0084] Where, x mc represents the information symbol sent by the BS to the user in the m-th cluster. m,n Let P represent the information symbols sent by device n in the m-th cluster to the user. To accurately decode the main link information and IoT information at the user's location, assume that the symbol period of the IoT information is much longer than the symbol period of the main link information, and that the former is K times the latter (K>>1). Let P = ||w|| 2 For the base station (BS) transmit power, μ' m The power is represented by σ. 2 Zero-mean additive white Gaussian noise, Φ=diag{φ1,φ2,…,φ Q} represents the reflection coefficient matrix of the intelligent reflective surface, and the channel between the main link (BS) and receiver m is represented as follows: The channel between the m-th cluster and the n-th BD of the BS is represented as follows: The channel between BS-IRS is represented as The channel between the IRS and the receiver m is represented as follows: The channel between the m-th cluster and the n-th BD of the IRS is represented as follows: The channel between the nth BD and user m in the m-th cluster is represented as follows:

[0085] The signal received at the user's location (receiver) in the m-th cluster is divided into two parts: the main link signal and the IoT link signal. Therefore, to ensure accurate decoding of the main link message and the IoT message, assume that the information symbol c sent by the IoT link is... m,n The symbol period is much longer than the main link information symbol x. m The symbol period allows the IoT signal to be used as a multipath component of the main link signal for decoding main link information, reflecting the mutually beneficial symbiotic nature of the main and secondary links in the SR system (Symbiotic Communication System). Therefore, the SNR of the main link signal received at the user's location is:

[0086]

[0087] On the one hand, since the information reflected from the BD device to the receiver uses BPSK binary phase shift keying, c has 2 N The value can be chosen; on the other hand, due to the information c sent by the nth BD device m,n ={0,1} is unknown to the user, therefore, according to Shannon's formula, the expected value of the achievable rate of the main transmission link can be obtained:

[0088]

[0089] Where t is the time slot length. This represents the proportion of time slots occupied by the BD device in the m-th cluster during the first phase. c represents the expectation of the backscattered link transmission symbols. m，n Let N represent the information symbols transmitted by the IoT link of the BD device in the m-th cluster, where N is the total number of BD devices in the m-th cluster. In this invention, the user decodes the IoT information reflected from the BD device using Successive Interference Cancellation (SIC). Since the symbol period of the IoT information is much longer than the symbol period of the main link information, it is assumed that the user can completely decode the IoT information. The SNR of the IoT signal received by the user from the n-th BD device in the m-th cluster is:

[0090]

[0091] Due to the main link signal x m It typically follows a complex Gaussian distribution, therefore the SNR of the IoT signal received by the user at the m-th cluster from the n-th BD device can be written as:

[0092]

[0093] Based on Shannon's formula and the characteristics of symbiotic systems, the transmission rate of BD n in the m-th cluster is obtained as follows:

[0094]

[0095] Meanwhile, the formula for energy harvesting at the nth BD in the m-th cluster is:

[0096]

[0097] The (1-η) part of the energy signal collection efficiency includes the energy consumed by the BD device circuit, and the η part is entirely used for the active information transmission in the second stage.

[0098] Phase Two:

[0099] During this phase, the signal received by the receiver in the m-th cluster is represented as:

[0100]

[0101] in, μ” m The second stage is additive white Gaussian noise, which follows a Gaussian distribution with a mean of 0 and a variance of σ.

[0102] Therefore, the main link transmission rate is:

[0103]

[0104] In the m-th cluster, the secondary link transmission rate between the n-th BD and user m is:

[0105]

[0106] Then, to address the low transmission rate of the backscattering link in the symbiotic system and improve the overall performance of the symbiotic system, the following optimization problem was established: [The problem is to] ensure the minimum communication rate requirement of the main transmission link. Under the premise of jointly optimizing the active beamforming vector w of the base station (BS), the passive beamforming matrix Φ of the intelligent reflector surface (IRS), and the time allocation coefficient vector, Maximize the backscatter link and rate of this multi-user, large-scale BD symbiotic communication system.

[0107] P1:

[0108] st

[0109] P≤P max ,

[0110]

[0111]

[0112] Among them, Φ=diag{φ1,φ2,…,φ Q} represents the reflection coefficient matrix of the intelligent reflective surface, w = [w1, w2, ..., w R ] T This represents the active beamforming vector of the BS. Let R be the time allocation coefficient vector for the two transmission stages; where R m =R' m +R' m ', P is the base station's transmit power, expressed as P = ||w|| 2 The objective function is to maximize the sum rate of the backscattered links in the system. This is achieved by jointly optimizing the active beamforming vector w of the base station, the passive beamforming matrix Φ of the IRS, and the time allocation coefficient vectors for the active and passive transmission stages. It also satisfies the minimum main link rate requirement constraint, the maximum base station transmit power constraint, the time allocation constraint, and the IRS unit modulus constraint.

[0113] The optimization targets include the BS active beamforming matrix w, the intelligent reflector surface IRS passive beamforming matrix Φ, and the active / passive transmission stage time allocation coefficient vector. Problem P1 is a non-convex optimization problem because the objective function and constraints are highly coupled, and both the objective function and constraint have logarithmic summation terms.

[0114] Therefore, to solve this nonconvex optimization problem, we consider decoupling the three coupled variables into three subproblems, which are solved using the semi-definite relaxation (SDR) algorithm and the Lagrange algorithm, respectively. The three coupled variables are then iteratively solved using the block coordinate descent (BCD) algorithm with gradient descent, resulting in the BS active beamforming vector w, the intelligent reflector surface IRS passive beamforming matrix Φ, and the time allocation strategy vector. A joint optimization design scheme for backscattering links in a symbiotic communication system. The specific operation is as follows:

[0115] The three variables with a coupling relationship are decomposed into three corresponding subproblems:

[0116] During the j-th iteration, for a given BS active beamforming vector w {j-1} and intelligent reflective surface IRS passive beamforming matrix Φ {j-1} The original optimization problem is transformed into a subproblem concerning the allocation of active and passive time:

[0117] P1-(1):

[0118] st

[0119]

[0120] By solving this problem, the time allocation vector for the j-th iteration is obtained.

[0121] In the (j+1)th iteration, Substitute this into problem P1, and in the i-th iteration, give the BS active beamforming vector w. {i-1} The optimization problem is transformed into:

[0122] P1-(1-1):

[0123] st

[0124] t≥0,0≤α m,n ≤1,

[0125]

[0126] The SDR algorithm is used to solve for Φ. {i} Substituting this into the original optimization problem in the (i+1)th iteration, we get:

[0127] P1-(1-2):

[0128] st

[0129] P≤P max ,

[0130] t≥0,0≤α m,n ≤1,

[0131] Solving for w {i+1} Substitute the value back into problem P1-(1-1), and when |w {i+1} -w {i-1} When |≤Δ, the iteration stops, and the optimal BS active beamforming vector w for this iteration (j+1) is obtained. {j+1} and intelligent reflective surface IRS passive beamforming matrix Φ {j+1} Substituting this into problem P1-(1), when |w {j+1} -w {j-1} |≤Δ and|Φ {j+1} -Φ {j-1} When |≤Δ (where Δ is the minimum error allowed by the iterative algorithm), the iteration stops, thus obtaining the BS active beamforming vector w, the intelligent reflector surface IRS passive beamforming matrix Φ, and the time allocation strategy vector. A joint optimization design scheme for backscattering links in a symbiotic communication system.

[0132] This invention further considers the exacerbated dual fading effect under large-scale BD access (i.e., fading of both the BS-BD and BD-user links due to the passive characteristics of BD devices), making the scenario more complex and accommodating more network nodes. Simultaneously, this invention employs IRS intelligent reflective surface technology to assist in enhancing the transmission of the backscattered link, thus strengthening the BS-BD link. Previous optimizations of the BD-receiver link adaptively matched the optimal user receiver for each BD device based on channel conditions, but this did not fundamentally solve the fading problem caused by the passive characteristics of BD. Therefore, this invention considers using wireless power supply technology, dividing a transmission time slot into two stages. Stage one uses the original... The invention employs a passive backscatter transmission method initially, while simultaneously utilizing wireless power supply technology for energy harvesting. In the second stage, the energy harvested in the first stage is used for active information transmission. This improves the fading problem caused by purely passive transmission without increasing the system's additional energy consumption. In other words, in large-scale BD scenarios, this invention divides the time slot into two stages to add an active transmission method to fundamentally combat the fading problem caused by passive BD. Furthermore, regarding the node access method, the previous invention used a TDMA time-division access method, while this invention considers large-scale BD device scenarios and adopts a TDMA+NOMA access method to accommodate more BD devices, thereby improving the capacity of the symbiotic system.

[0133] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the backlink of a system combining IRS and wireless power supply, characterized in that, include: S1. The base station sends the main link signal to the smart reflector and multiple clusters. The smart reflector reflects and forwards the main link signal to the multiple clusters. Each cluster includes a receiver and multiple BD devices. The specific process by which the intelligent reflective surface reflects and forwards the main link signal to multiple clusters is as follows: the intelligent reflective surface receives the main link signal sent by the base station, dynamically adjusts the reflection coefficient of each reflection unit of the intelligent reflective surface, reconstructs the channel environment from the base station to the cluster, and after reconstruction, the intelligent reflective surface sends the main link signal to the cluster. S2. Multiple BD devices use the received main link signal as a carrier to modulate and transmit their respective IoT information to the corresponding receiver in the corresponding time slot. During transmission, the time slot is divided into two stages. In the first stage, the BD devices perform passive backscatter transmission and collect energy using wireless power supply technology. In the second stage, the BD devices perform active backscatter transmission using the collected energy. The base station and the smart reflective surface transmit information to the receiver and the BD device using TDMA, and each cluster transmits information to the corresponding receiver in the cluster using NOMA. In S2, before the BD device uses the received main link signal as a carrier to modulate and transmit its respective IoT information to the corresponding receiver, it ensures the minimum communication rate requirement of the main transmission link. Under the premise of the base station's active beamforming vector w, the reflection coefficient matrix of the intelligent reflective surface's passive beamforming, and the time allocation coefficient vector, Establish and solve a backscatter transmission rate maximization model to maximize the sum rate of all backscatter links; The signal received by the receiver is: ； ； ； in, This represents the signal received by the receiver in the first stage. This represents the signal received by the receiver in the second stage. Indicates that the base station sends to the first m Information symbols of receivers in a cluster Indicates the first m The information symbol sent by the nth BD device in the cluster to the receiver This refers to the base station's transmission power. Indicates that the power in the first stage is Zero-mean additive white Gaussian noise, This represents the reflection coefficient matrix of the intelligent reflective surface. This represents the active beamforming vector of the base station. Let m be the channel between the base station and the m-th receiver. For base station to the m The first in the cluster n Channels between BD devices For the channel between the base station and the smart reflective surface, Let be the channel between the smart reflective surface and the receiver in the m-th cluster. For intelligent reflective surfaces to the first m The first cluster n The channel between BDs, where Q is the number of reflective elements on the smart reflective surface. For the first m In the cluster, the first n Channels between each BD and the receivers in the cluster This represents the reflection coefficient of the nth BD device in the mth cluster. , , This represents the active transmission power of the nth BD device in the mth cluster. Let t be the energy collected by the nth BD device in the mth cluster during the first phase, and t be the time slot length. This represents the proportion of time slots occupied by the BD device in the m-th cluster during the first phase. The second stage is additive white Gaussian noise with a mean of 0 and a variance of 1. Gaussian distribution; In the first stage: The signal-to-noise ratio of the main link signal received by the receiver in the m-th cluster is: ； The expected transmission rate of the main link signal received by the receiver in the m-th cluster is: ； Where t is the time slot length, This represents the proportion of time slots occupied by the BD device in the m-th cluster during the first phase. This indicates the expectation of the backscattered link transmission symbols. The symbol represents the information transmitted by the IoT link of the BD device in the m-th cluster, where N is the total number of BD devices in the m-th cluster. The signal-to-noise ratio of the IoT signal received by the receiver in the m-th cluster from the n-th BD device is: ； Where K is the ratio of the period of the IoT information symbol to the period of the main link information symbol; The transmission rate of IoT information received by the receiver in the m-th cluster from the n-th BD device is: ； No. m The cluster, the first n The formula for energy harvesting at point BD is: ； This refers to the energy ratio of active information transmission in the second stage. ; In the second stage: The transmission rate of the main link signal received by the receiver in the m-th cluster is: ； No. m In the cluster, the first n The transmission rate of the secondary link between each BD device and the receiver is: ； The backscattering transmission rate maximization model is specifically as follows: ； in, This represents the reflection coefficient matrix of the intelligent reflective surface. This represents the active beamforming vector of the base station. This is the time allocation coefficient vector for the first stage; where , P The base station's transmit power is expressed as The constraints are as follows: the transmission rate of the main link is not less than... The maximum transmit power at the base station (BS) shall not exceed Time allocation constraints, with both the time allocation coefficient and the reflection coefficient of the BD device between 0 and 1; unit modulus constraints on the intelligent reflective surface; The specific steps for solving the backscattering transmission rate maximization model are as follows: A1. Define the backscattering transmission rate maximization model as a non-convex optimization problem P1; A2. Decouple the three variables of the non-convex optimization problem P1 into three sub-problems, where the three variables are the reflection coefficient matrix of the intelligent reflective surface. The active beamforming vector w of the base station and the time allocation coefficient vector of the first stage. ; A3. The semi-definite relaxation algorithm and the Lagrange algorithm are used to solve each subproblem. Simultaneously, the three coupled variables are iteratively solved using gradient descent to obtain the reflection coefficient matrix of the intelligent reflective surface. The active beamforming vector w of the base station and the time allocation coefficient vector of the first stage. A joint optimization design scheme for backscattering links in symbiotic communication systems; The specific process for A3 is as follows: A3.1, in the... j During each iteration, for a given base station active beamforming vector Passive beamforming matrix of intelligent reflective surface The non-convex optimization problem P1 is transformed into a first subproblem concerning the allocation of active and passive time: ； A3.2 Solve the first subproblem to obtain the... j The time allocation vector for the next iteration ; A3.3, in the... j In the +1 iteration, the th j The time allocation vector for the next iteration Substitute this into the non-convex optimization problem P1, and simultaneously in the... i In the next iteration, the base station active beamforming vector is given. The non-convex optimization problem P1 is transformed into a second subproblem: ； A3.

4. The semidefinite relaxation algorithm is used to solve the second subproblem, obtaining the reflection coefficient matrix of the intelligent reflective surface in the i-th iteration. And the reflection coefficient matrix of the smart reflective surface in the i-th iteration Substituting the nonconvex optimization problem P1 into the first... i The third subproblem is obtained in +1 iterations: ； A3.5, Solving the third subproblem yields the... i+ Given the base station active beamforming vector in one iteration And substitute the value back into the second subproblem to solve it, when At that time, among them The iteration stops when the minimum allowable error of the iterative algorithm is reached, and the result of this iteration is obtained. j +1) Optimal base station active beamforming vector Passive beamforming matrix of intelligent reflective surface ; A3.6, Apply active beamforming vectors to base stations Passive beamforming matrix of intelligent reflective surface Substituting into the first subproblem, when and At that time, among them The iteration stops when the minimum allowable error of the iterative algorithm is reached, thus obtaining the active beamforming vector w of the base station and the passive beamforming matrix of the smart reflector. and time allocation strategy vector A joint optimization design scheme for backscattering links in a symbiotic communication system was proposed, and the solution of the backscattering transmission rate maximization model was obtained.

2. A backscatter link optimization system for a symbiotic system combining IRS and wireless power supply, used to execute the backscatter link optimization method for a system combining IRS and wireless power supply as described in claim 1, characterized in that, include: The system comprises a base station, a smart reflective surface with multiple reflective elements, and multiple clusters, each cluster including a receiver and multiple BD devices; the smart reflective surface is connected to a smart controller; the base station communicates with the receiver in the m-th cluster via a channel. The connection is established between the base station and the nth BD device in the mth cluster via a channel. The connection between the base station and the smart reflective surface is via a channel. The connection is made between the smart reflective surface and the nth BD device in the mth cluster via a channel. The connection between the smart reflective surface and the receiver in the m-th cluster is via a channel. The connection is established between the nth BD device in the mth cluster and the receiver in that cluster via a channel. connect.

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