TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method and device

Abstract

The present application relates to a TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method and device, comprising: establishing a system model of a wireless energy station, a RIS, an Internet of Things device, a jammer, and an information receiver; constructing an anti-interference total throughput calculation model with time slot scheduling and phase shift as constraints, wherein the model takes maximizing the anti-interference total throughput as the objective function; based on the objective function, deriving a closed-form optimal solution for time slot scheduling using the Lagrangian duality method and the KKT condition; after completing the time scheduling optimization, iteratively deriving a closed-form solution for the phase shift using the unit block coordinate descent (EBCD) algorithm and the complex circular manifold (CCM) algorithm, and on this basis, deriving a closed-form optimal solution for the phase shift using an alternating optimization algorithm, thereby significantly optimizing the total anti-interference throughput of the communication system.

Description

Technical Field

[0001] The present application relates to the field of wireless communications, and in particular to a TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method and device. Background Art

[0002] With the commercialization of fifth-generation (5G) networks and the active deployment of next-generation 6G network technologies, mobile data traffic is expected to increase a thousandfold over the next decade. The Internet of Things, a core component of 5G and its subsequent developments, has significantly increased the access speed of large-scale IoT devices. However, with the explosive growth in the number of IoT devices, battery powering of sensor nodes has become a challenge. To address this challenge, a wireless power communication network solution has been proposed. This solution utilizes wireless energy stations to wirelessly power sensors during downlink wireless energy transmission periods, and uses the collected energy to transmit information to receivers during uplink wireless information transmission periods. With this architecture, the wireless energy stations in a wireless power communication network can be viewed as an alternative to traditional battery charging, avoiding expensive periodic maintenance and replacement costs.

[0003] Wireless networks play a vital role in enabling ubiquitous computing. Networked devices deployed in the environment provide continuous connectivity and services, thereby improving the quality of life. However, due to the exposed nature of wireless links, current wireless networks are vulnerable to jamming techniques. Furthermore, in traditional wireless networks, the channel is typically viewed as a random and uncontrollable medium, necessitating optimized transmission and reception strategies to overcome signal attenuation. While strategies such as beamforming and power control algorithms can mitigate signal attenuation to some extent, they cannot fundamentally reconfigure the channel. Against this backdrop, reconfigurable smart surfaces (RIS) have been introduced. RIS, with its low cost, low energy consumption, programmability, and ease of deployment, can dynamically adapt to the wireless environment, offering innovative solutions for wireless communication networks. Importantly, as an emerging anti-interference technology, RIS leverages its unique capabilities to improve network performance and anti-interference characteristics, thereby enhancing the stability and security of wireless communications. By precisely controlling signal reflection and refraction, RIS contributes to building a more robust and reliable wireless network environment. Summary of the Invention

[0004] This application provides a TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method and device. The specific technical solution is as follows:

[0005] According to a first aspect of an embodiment of the present application, a TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method is provided, the method comprising:

[0006] S1: Establish a system model of wireless energy stations, RIS, IoT devices, jammers, and information receivers;

[0007] S2: Using time slot scheduling and phase shift as constraints, a total anti-interference throughput calculation model is constructed. The objective function of this model is to maximize the total anti-interference throughput.

[0008] S3: Based on the objective function, the closed-form optimal solution of time slot scheduling is derived using the Lagrange dual method and KKT conditions;

[0009] S4: After the time scheduling optimization is completed, the closed-form solution of the phase shift is iteratively derived using the unit block coordinate descent (EBCD) algorithm and the complex circle manifold (CCM) algorithm. On this basis, the closed-form optimal solution of the phase shift is derived using the alternating optimization algorithm.

[0010] Optionally, the system model in step S1 specifically includes: a wireless energy station, a RIS, K IoT devices, a jammer, and an information receiver, wherein D k represents the kth IoT device, the jammer is located between the RIS and the information receiver, J represents the jammer, and it emits a signal with power P to the information receiver. J The interference signal is transmitted, IR represents the information receiver, and the RIS is equipped with M reflective elements; wherein,

[0011] The wireless energy station is used to provide energy to a total of K IoT devices through wireless transmission; the IoT devices are used to receive energy supplies from the wireless energy station and use the received energy to send their information to an information receiver; the RIS is used to form a directional beam by adjusting the phase of each RIS reflection unit to enhance the signal strength to the information receiver; the jammer is used to emit an interference signal during the period when the IoT device sends information to the information receiver; and the information receiver is used to receive information sent and uploaded by the IoT device.

[0012] Optionally, the system model adopts a time division multiple access protocol, and the total time slot of the system satisfies A complete operation cycle is divided into K time slots. In the downlink energy transmission phase, within the time slot τ0, the wireless energy station transmits power P t Transmit energy to K IoT devices; in the uplink information transmission phase, that is, in the time slot τ1 to τ K The kth IoT device is in the corresponding time slot τ k Transmitting information to an information receiver;

[0013] And, during the entire system uplink transmission phase, the jammer transmits a constant power P to the information receiver. j Transmitting interference signals.

[0014] Optionally, the RIS is further equipped with a controller for switching between a channel estimation reception mode and a transmission reflection mode and providing real-time channel state information feedback; wherein the diagonal matrix Θ reflecting the phase shift of the RIS element of the k-th IoT device is k =diag[β k,1 exfracp(jα k,1 ),...,β k,M exp(jα k,M )],|exp(jα k,m )|=1, in and is the phase shift and amplitude associated with the Mth reflection element. When k = 0, Θ0 is also called the energy reflection phase shift matrix. When k∈[1,K], Θ k It is called the information reflection phase shift matrix.

[0015] Optionally, a total anti-interference throughput calculation model is constructed with time slot scheduling and phase shift as constraints. The model takes maximizing the total anti-interference throughput as the objective function, specifically including:

[0016] The energy collected by the kth IoT in the τ0 time slot is expressed as:

[0017]

[0018] where η c is the energy conversion efficiency of the kth IoT device, P t is the transmission power of the wireless energy station, |h r Θ0h r,k +h d,k | 2 The power received by the IoT device;

[0019] The achievable throughput of the kth IoT device in the remaining time slot is obtained as:

[0020]

[0021] Among them, P j is the transmit power at the jammer, σ 2 is the noise power at the information receiver;

[0022] The total anti-interference throughput calculation model is:

[0023]

[0024]

[0025]

[0026] Among them, the channel state information between the wireless energy station and the kth IoT device is represented as h d,k ∈C 1×1 , the channel state information between the wireless energy station and RIS is expressed as h r ∈C 1×M , the channel state information between RIS and the kth IoT device is represented as h r,k ∈C M×1 , RIS and the channel state information of the information receiver are expressed as g r ∈C M×1 , the channel state information between the kth IoT device and the information receiver is expressed as g d,k ∈C 1×1 , the channel state information between the kth IoT device and RIS is expressed as g r,k ∈C 1×M , the channel state information of the jammer and the information receiver is expressed as g d,j ∈C 1×1 , the channel state information of the jammer and RIS link is expressed as h j ∈C 1×M .

[0027] In a second aspect, the present application provides a TDMA-based RIS-assisted wireless power supply IoT anti-interference transmission device, comprising:

[0028] A system model building unit, used to build system models of wireless energy stations, RIS, IoT devices, jammers, and information receivers;

[0029] An anti-interference total throughput calculation model building unit is used to build an anti-interference total throughput calculation model based on time slot scheduling and phase shift as constraints, and the model takes maximizing the anti-interference total throughput as the objective function;

[0030] A time slot scheduling optimal solution derivation unit, for the objective function, using the Lagrange dual method and the KKT condition to derive a closed-form optimal solution for the time slot scheduling;

[0031] The phase shift optimal solution derivation unit, after completing the time scheduling optimization, uses the unit block coordinate descent EBCD algorithm and the complex circle manifold CCM algorithm to iteratively derive the closed-form solution of the phase shift, and on this basis, derives the closed-form optimal solution of the phase shift through the alternating optimization algorithm.

[0032] Optionally, the system model established by the system model establishment unit specifically includes:

[0033] A wireless energy station, a RIS, K IoT devices, a jammer, and an information receiver, where D krepresents the kth IoT device, the jammer is located between the RIS and the information receiver, J represents the jammer, and it emits a signal with power P to the information receiver. J The interference signal is transmitted, IR represents the information receiver, and the RIS is equipped with M reflective elements; wherein,

[0034] The wireless energy station is used to provide energy to a total of K IoT devices through wireless transmission; the IoT devices are used to receive energy supplies from the wireless energy station and use the received energy to send their information to an information receiver; the RIS is used to form a directional beam by adjusting the phase of each RIS reflection unit to enhance the signal strength to the information receiver; the jammer is used to emit an interference signal during the period when the IoT device sends information to the information receiver; and the information receiver is used to receive information sent and uploaded by the IoT device.

[0035] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0036] The present application relates to a TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method and device, comprising: establishing a system model of a wireless energy station, RIS, Internet of Things equipment, a jammer, and an information receiver; constructing an anti-interference total throughput calculation model with time slot scheduling and phase shift as constraints, the model taking maximizing the anti-interference total throughput as the objective function; for the objective function, deriving a closed-form optimal solution for time slot scheduling using the Lagrangian duality method and the KKT condition; after completing the time scheduling optimization, iteratively deriving a closed-form solution for the phase shift using the unit block coordinate descent (EBCD) algorithm and the complex circular manifold (CCM) algorithm, and on this basis, deriving a closed-form optimal solution for the phase shift using an alternating optimization algorithm, thereby significantly optimizing the total anti-interference throughput of the communication system.

[0037] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application, and do not constitute an improper limitation on the present application.

[0039] Figure 1 is a model diagram of a TDMA-based RIS-assisted wireless power supply IoT system according to an exemplary embodiment;

[0040] Figure 2 1 is a schematic diagram showing a TDMA-based RIS-assisted wireless power supply IoT anti-interference transmission method according to an exemplary embodiment;

[0041] Figure 3 A schematic diagram illustrating deployment of a TDMA-based RIS-assisted wireless power supply IoT system according to an exemplary embodiment is provided;

[0042] Figure 4 FIG1 is a schematic diagram of simulation results for evaluating the impact of transmit power P0 on total throughput against interference according to an exemplary embodiment;

[0043] Figure 5 is an example embodiment of the estimated jammer power P J Schematic diagram of simulation results for the impact of interference on total throughput;

[0044] Figure 6 FIG. 4 is a diagram showing simulation results for evaluating the impact of the number M of RIS reflection units on the total throughput according to an exemplary embodiment. DETAILED DESCRIPTION

[0045] In order to enable ordinary people in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings.

[0046] It should be noted that the terms "first," "second," and the like in the specification and claims of this application and in the above-mentioned figures are used to distinguish similar objects, rather than to describe a specific order or precedence. Therefore, the numbers used in this manner are interchangeable where appropriate, and the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0047] The application scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0048] In radio, time division multiple access (TDMA) is a communication technology for implementing a shared transmission medium or network. It allows multiple users to use the same frequency in different time slots. Users transmit rapidly, one after another, each using their own time slot. This allows multiple users to share the same transmission medium (e.g., radio frequency).

[0049] This application uses TDMA technology to provide a TDMA-based RIS-assisted wireless power supply IoT system model, such as Figure 1 As shown, in this system, there is a wireless energy station, a RIS, K IoT devices, a jammer, and an information receiver.

[0050] Wireless Energy Station: Provides energy to a total of K IoT devices through wireless transmission.

[0051] IoT devices: These devices are powered by batteries, which are used only for information processing. The energy for transmitting information to wireless receivers is provided by wireless energy stations.

[0052] RIS participates in both wireless energy transfer (WET) and wireless information transfer (WIT). During the WET phase, it reflects energy transmitted by wireless energy stations to increase the amount of energy collected by wireless devices. During the WIT phase, it reflects information from wireless IoT devices, reducing interference signals and increasing receiver throughput. The RIS is also associated with a RIS controller, which connects to the RIS and switches between channel estimation and reception modes and transmission and reflection modes, adjusting the RIS's reflection parameters.

[0053] Jammer: Powered by a battery, the jammer is located near the wireless information receiver and RIS. During the time slot when the device transmits information to the information receiver, the jammer simultaneously sends jamming signals to the RIS and the information receiver.

[0054] Information receiver: Receives information sent and uploaded by IoT devices.

[0055] TDMA transmission protocol: The system adopts the time division multiple access protocol, which divides the complete operation cycle into K time slots. First, in the downlink energy transmission phase, within the time slot τ0, the wireless energy station transmits power P t Energy is transmitted to K IoT devices. Then, in the uplink information transmission phase, i.e., the time slot τ1 to τ K The kth IoT device is in the corresponding time slot τ k In addition, during the entire system uplink transmission phase, the jammer transmits information to the information receiver at a constant power P j The total time slot of the system satisfies

[0056] In some embodiments, IoT devices charge and store energy through wireless energy stations and use this energy to transmit data to information receivers. However, while the IoT is transmitting information to the information receiver, a jammer simultaneously transmits an interference signal to the information receiver. Furthermore, the RIS participates in both wireless energy and wireless information transmission through an information passive beamformer. The RIS is equipped with M reflective elements, while the other devices (i.e., the wireless energy station, jammer, information receiver, and all IoT devices) are single-antenna nodes.

[0057] RIS is also equipped with a controller for switching between channel estimation reception mode and transmission reflection mode and providing real-time channel status information feedback. The diagonal matrix Θ of the phase shift of the RIS element reflecting the kth IoT device is given as k =diag[β k,1 exfracp(jα k,1 ),...,β k,M exp(jα k,M )],|exp(jα k,m )|=1, in and is the phase shift and amplitude associated with the Mth reflection element. When k = 0, Θ0 is also called the energy reflection phase shift matrix. When k∈[1,K], Θ k It is called the information reflection phase shift matrix.

[0058] Based on the above system, such as Figure 2 As shown, the present application provides a TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method, specifically including:

[0059] S1: Establish a system model of wireless energy stations, RIS, IoT devices, jammers, and information receivers.

[0060] S2: With time slot scheduling and phase shift as constraints, a total anti-interference throughput calculation model is constructed. The objective function of this model is to maximize the total anti-interference throughput.

[0061] In some embodiments, the network adopts a time division multiple access protocol, and sets a complete operation cycle as T, that is, In the downlink energy transmission phase, during the time slot τ0, the wireless energy station transmits power P t Energy is transmitted to K IoT devices. Then, in the uplink information transmission phase, i.e., the time slot τ1 to τ K The kth IoT device is in the corresponding time slot τ k In addition, the channel state information between the wireless energy station and the kth IoT device is expressed as h d,k ∈C1×1 , the channel state information between the wireless energy station and RIS is expressed as h r ∈C 1×m , the channel state information between RIS and the kth IoT device is represented as h r,k ∈C M×1 , RIS and the channel state information of the information receiver are expressed as g r ∈C M×1 , the channel state information between the kth IoT device and the information receiver is expressed as g d,k ∈C 1×1 , the channel state information between the kth IoT device and RIS is expressed as g r,k ∈C 1×M , the channel state information of the jammer and the information receiver is expressed as g d,j ∈C 1×1 , the channel state information of the jammer and RIS link is expressed as h j ∈C 1×M .

[0062] In some embodiments, D k represents k IoT devices, the jammer is located between the RIS and the information receiver, J represents the jammer, and it emits power P to the information receiver. J Transmits interference signals. IR stands for Information Receiver, RIS is equipped with M reflective elements, while all other terminals have only one antenna.

[0063] The energy collected by the kth IoT in the τ0 time slot is expressed as:

[0064]

[0065] where η c is the energy conversion efficiency of the kth IoT device, P t is the transmission power of the wireless energy station, |h r Θ0h r,k +h d,k | 2 is the power received by the IoT device. It can be concluded that the achievable throughput of the kth IoT device in the remaining time slot is:

[0066]

[0067] Among them, P j is the transmit power at the jammer, σ 2 is the noise power at the information receiver.

[0068] against Figure 1The goal of the RIS-assisted wireless power IoT anti-interference transmission system based on time division multiple access is to maximize the total throughput by optimizing the design time scheduling and phase shift. The problem can be modeled as:

[0069]

[0070]

[0071]

[0072] The problem defined above is non-convex due to the coupled variables and unit mode constraints.

[0073] To make the problem tractable, first define the following equation:

[0074]

[0075]

[0076] According to the above definition, the above optimization problem can be equivalently expressed as:

[0077]

[0078]

[0079]

[0080] S3: For the objective function, the Lagrange dual method and KKT condition are used to derive the closed-form optimal solution of time slot scheduling.

[0081] In some embodiments, a time slot scheduling solution is obtained, and a closed-form optimal solution for the time slot scheduling is derived using the Lagrange dual method and the KKT condition.

[0082] First, optimize the time scheduling, that is, optimize τ0 and τ k .

[0083] First, we derive τ for k∈[1,k] k The closed-form solution of the objective function of the above optimization problem is:

[0084]

[0085] in is the Lagrange dual multiplier of the first constraint of the optimization problem. And its dual problem is given by

[0086]

[0087] Where S represents any τ kThe optimization problem is a convex problem about τ, which satisfies the Slater condition, making the strong duality valid, and the optimal solution also satisfies the following KKT conditions:

[0088]

[0089] because It is always true, and it is obvious that it can be deduced from the above formula Then use the first-order derivative of the above formula get:

[0090]

[0091] make Then the above formula can be transformed into It is obvious that this formula is monotonically increasing, and the above formula requires Then there is only one value that satisfies the condition or all x values ​​are equal, so we can get:

[0092]

[0093] definition Can get The obtained τ k Bring in You can get:

[0094]

[0095] Substitute the obtained ρ into the equation Find τ k The optimal solution is:

[0096]

[0097] The above τ k Substituting the closed-form optimal solution into the objective function of the optimization problem, the optimization problem can be reformulated as follows:

[0098]

[0099]

[0100] in The above formula has already calculated τ k The optimal solution is to optimize the design of τ0 under the condition of determining Θ. Let the objective function of the above optimization problem be f(τ0). Taking the derivative of f(τ0)=0, we can get:

[0101]

[0102] From the above formula, it can be clearly seen that Then, dividing both sides of the equation by e and rearranging it gives:

[0103]

[0104] Final definition Then the above equation conforms to the Lambert equation x = W(x), so the optimal time scheduling formula τ0 is:

[0105]

[0106] S4: After the time scheduling optimization is completed, the closed-form solution of the phase shift is iteratively derived using the unit block coordinate descent (EBCD) algorithm and the complex circle manifold (CCM) algorithm. On this basis, the closed-form optimal solution of the phase shift is derived through the alternating optimization algorithm.

[0107] After optimizing the time schedule, the phase shift Θ is optimized. First, determine Θ k To find Θ0, for the convenience of calculation, define the equation |h r Θ0h r,k +h d,k | 2 =|b k θ0+h d,k | 2 , where b k =diag(h r )h r,k ,θ0=[θ 0,1 ,…,θ 0,M ]=[exp(jα 0,1 ),…,exp(jα 0,M )]. Then the optimization problem becomes as follows:

[0108]

[0109]

[0110] Due to the non-convexity of this problem, an alternating optimization algorithm is used to solve it. First, given θ k To optimize θ0. This application proposes the EBCD algorithm and the CCM algorithm, which iteratively find the closed-form optimal solution of θ0.

[0111] Expand the above objective function into:

[0112]

[0113] in

[0114] make and d0=0, so the problem becomes:

[0115]

[0116] This application proposes two methods to optimize the phase shift. The first method is the EBCD algorithm.

[0117] (1) EBCD method: Iteratively optimize one element of the phase shift θ0 while giving other elements of the phase shift, that is, Perform optimization iterations, Fixed, and c≠l, expand and redefine the problem as:

[0118]

[0119] st|θ0(l)|=1

[0120] in Also using θ0(n), v(n) and denote θ0, v0 and The nth term and (n,m) term of because The Hermitian property. Since |θ0(l)| 2 =1, so the above problem is simplified to:

[0121]

[0122] For the above problem, the optimal solution of θ0(l) is:

[0123]

[0124] Fixed Phase shift elements, thus converging to a local optimum. Assume Initialized at the i-th iteration, the target value is f1(θ0(l) * ), if EBCD is updated satisfy The algorithm converges.

[0125] Based on the above derivation, Algorithm 1 briefly summarizes the steps of the EBCD algorithm

[0126] Algorithm 1: EBCD algorithm

[0127] 1) Initialization: number of iterations i, feasible solution Convergence accuracy ε

[0128] 2) Repeat:

[0129] Calculate target value

[0130] for l=1:1:M

[0131] For given other elements θ0(c), To calculate (θ0(l)) *

[0132] End

[0133] get

[0134] renew and i=i+1

[0135] When the convergence condition is met When , stop the iteration.

[0136] 3) Get: the optimal solution of θ0

[0137] This application proposes two methods to optimize phase shift. The second method is CCM algorithm.

[0138] (2) CCM method: This algorithm derives a gradient descent algorithm on the manifold space, which can be obtained by iteratively solving the following equivalent problem The optimal solution:

[0139]

[0140]

[0141] Among them, κ>0 is a constant that controls the convergence of the CCM algorithm, It can be proved that the problem is equivalent. To solve the above problem using CCM algorithm, we should first find the search direction. Assume that the search direction is the same as the Euclidean space. The gradient of is opposite, then the search direction is:

[0142]

[0143] Then find the projection of the direction on the tangent space, i.e. (m) Projection to on, on The Riemann gradient is obtained

[0144]

[0145] The third step is to update the tangent space where ζ is the step size:

[0146]

[0147] Finally, due to Not present So use the retract operation to Mapping to manifold In Chinese, that is:

[0148]

[0149] Based on the above analysis, Algorithm 2 briefly summarizes the steps of the CCM algorithm:

[0150] Algorithm 2: CCM algorithm

[0151] 1) Initialization: number of iterations i, feasible solution Convergence accuracy ε

[0152] 2) Repeat:

[0153] Calculate target value Calculate search direction ι (i) , then calculate the search direction ι (i) In the cut

[0154] Projection on the room

[0155] Update: Update right Perform retraction operation, i=i+1

[0156] When the convergence condition is met When , stop the iteration.

[0157] 3) Get: the optimal solution of θ0

[0158] τ0,τ have been calculated in the previous formula k , and use EBCD and CCM methods to get θ0 respectively. Consider the following sub-problems to find θ k The optimal solution of .

[0159]

[0160] To make the problem easier to handle, the phase shift term in the above equation is rewritten as .

[0161] |h j θ k g r +g d,j | 2 =|θ k c r +g d,j | 2

[0162] |g r,k θ k g r +g d,k | 2 =|θ k a k+g d,k | 2

[0163] In the above formula, a k =diag(g r )g r,k ,c r =diag(h j )g r ,θ k =[θ k,1 ,…,θ k,M ]=[exp(jα k,1 ),…,exp(jα k,M )]. The problem is redefined as

[0164]

[0165] in In the above problem, since θ k is a fraction, which is not very convenient to calculate. Use the quadratic transformation to rewrite the objective function in the problem into a subtraction form:

[0166]

[0167] where λ k , is an auxiliary variable introduced. k The closed-form solution of k Export, expressed as:

[0168]

[0169] Rephrase the question as:

[0170]

[0171]

[0172] The alternating optimization method can be used to obtain λ k and θ k The optimal solution of θ is obtained by using EBCD and CCM. k , so for the convenience of calculation, we need to reformulate the problem as:

[0173]

[0174]

[0175] In the above formula

[0176]

[0177]

[0178] Finally, θ k The solution process for θ0 is similar to that for θ0, using EBCD and CCM, respectively. For detailed algorithms, refer to Algorithm 1 and Algorithm 2. Finally, the optimal design of phase shift is summarized, namely Algorithm 3.

[0179] Algorithm 3: Overall algorithm

[0180] 1) Initialization: number of iterations i, feasible solution and Convergence accuracy ε

[0181] 2) Repeat:

[0182] Calculation: Target value

[0183] Calculation: Given Calculated by Algorithm 1 or Algorithm 2

[0184] Calculation: Given and Calculated by Algorithm 1 or Algorithm 2

[0185] renew: and i=i+1

[0186] The iteration stops until the convergence requirement is met.

[0187] 3) Get: The optimal solution

[0188] 4) Calculation: Calculate through the corresponding formula and

[0189] The present application relates to a TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method and device, comprising: establishing a system model of a wireless energy station, RIS, Internet of Things equipment, a jammer, and an information receiver; constructing an anti-interference total throughput calculation model with time slot scheduling and phase shift as constraints, the model taking maximizing the anti-interference total throughput as the objective function; for the objective function, deriving a closed-form optimal solution for time slot scheduling using the Lagrangian duality method and the KKT condition; after completing the time scheduling optimization, iteratively deriving a closed-form solution for the phase shift using the unit block coordinate descent (EBCD) algorithm and the complex circular manifold (CCM) algorithm, and on this basis, deriving a closed-form optimal solution for the phase shift using an alternating optimization algorithm, thereby significantly optimizing the total anti-interference throughput of the communication system.

[0190] According to the optimization method proposed above, the model is simulated and the numerical results are used to evaluate the performance of the proposed solution. Figure 3 The system deployment is described by the three-dimensional coordinates in , where the wireless energy station, RIS, information receiver, and jammer are located at (20, 0, 0), (8, 0, 6), (-20, 0, 0), and (0, 10, 0), respectively. IoT devices are randomly deployed within the specified radius. The channel coefficient consists of path loss and fading. The path loss is modeled as P L =A*d -k ,A=10 -2 , k is the path loss exponent, and d represents the distance between any two devices. Here, the path loss exponent for RIS-related links is set to 2, and for the remaining links to 2.5. Furthermore, the Rice fading model is used for the RIS-related channels, while the Rayleigh fading model is used for the remaining channels. The performance of this application is compared with the following benchmark solutions in simulations:

[0191] (1) RIS-assisted wireless power supply IoT with fixed time slot allocation (τ0 = 0.25): The transmission time slot is fixed and the phase shift is optimized.

[0192] (2) No anti-interference: Under the same interference conditions, the phase shift and time scheduling are optimized without considering the interference signal.

[0193] (3) RIS-free wireless power supply IoT: Optimize phase shift and time scheduling without RIS.

[0194] (4) Random phase shift: Phase shift is generated randomly, and only the time scheduling is optimized.

[0195] (5) Discrete phase shift: Each phase shift comes from Where B represents the phase resolution bit, which is used to optimize the time slot scheduling.

[0196] Figure 4 This is a simulation result diagram to evaluate the impact of transmit power P0 on the total throughput against interference; Figure 5 To evaluate the jammer power P J Simulation results of the total throughput against interference; Figure 6 The following simulation results illustrate the impact of the number of RIS reflector units (M) on total throughput. This simulation demonstrates that this application demonstrates superior performance compared to other algorithms. Furthermore, when compared with a solution without anti-interference measures, the performance gap between the two approaches widens, further validating its anti-interference performance.

[0197] In some embodiments of the present application, a TDMA-based RIS-assisted wireless power supply IoT anti-interference transmission device is provided, including:

[0198] A system model building unit, used to build system models of wireless energy stations, RIS, IoT devices, jammers, and information receivers;

[0199] An anti-interference total throughput calculation model building unit is used to build an anti-interference total throughput calculation model based on time slot scheduling and phase shift as constraints, and the model takes maximizing the anti-interference total throughput as the objective function;

[0200] A time slot scheduling optimal solution derivation unit, for the objective function, using the Lagrange dual method and the KKT condition to derive a closed-form optimal solution for the time slot scheduling;

[0201] The phase shift optimal solution derivation unit, after completing the time scheduling optimization, uses the unit block coordinate descent EBCD algorithm and the complex circle manifold CCM algorithm to iteratively derive the closed-form solution of the phase shift, and on this basis, derives the closed-form optimal solution of the phase shift through the alternating optimization algorithm.

[0202] Optionally, the system model established by the system model establishment unit specifically includes:

[0203] A wireless energy station, a RIS, K IoT devices, a jammer, and an information receiver, where D k represents the kth IoT device, the jammer is located between the RIS and the information receiver, J represents the jammer, and it emits a signal with power P to the information receiver. J The interference signal is transmitted, IR represents the information receiver, and the RIS is equipped with M reflective elements; wherein,

[0204] The wireless energy station is used to provide energy to a total of K IoT devices through wireless transmission; the IoT devices are used to receive energy supplies from the wireless energy station and use the received energy to send their information to an information receiver; the RIS is used to form a directional beam by adjusting the phase of each RIS reflection unit to enhance the signal strength to the information receiver; the jammer is used to emit an interference signal during the period when the IoT device sends information to the information receiver; and the information receiver is used to receive information sent and uploaded by the IoT device.

[0205] In some embodiments, the present application also provides a TDMA-based RIS-assisted wireless power supply IoT anti-interference transmission device, including:

[0206] processor;

[0207] a memory for storing instructions executable by the processor;

[0208] The processor executes the computer-executable instructions stored in the memory to implement the solution provided by any of the above method embodiments. The specific functions and technical effects that can be achieved are not described in detail here.

[0209] Those skilled in the art will appreciate that various aspects of the present application can be implemented as systems, methods, or program products. Therefore, various aspects of the present application can be specifically implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation that combines hardware and software aspects, which may be collectively referred to herein as a "circuit," "module," or "system."

[0210] In some possible implementations, an electronic device according to the present application includes at least one processor and at least one memory. The memory stores program code that, when executed by the processor, causes the processor to perform the operational data management methods according to various exemplary embodiments of the present application described above. For example, the processor may perform the steps described in the operational data management method.

[0211] Furthermore, the TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission device according to this embodiment of the present application can execute the steps of the TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method mentioned in the above embodiment.

[0212] In exemplary embodiments, various aspects of the TDMA-based RIS-assisted wireless power supply IoT anti-interference transmission method and apparatus provided herein may also be implemented as a program product, including program code, etc. When the program product is executed on a computer device, the program code is used to cause the computer device to perform the steps described in this specification, which are included in the method for maximizing the quality of experience in a multi-antenna drone video transmission system according to various exemplary embodiments of the present application.

[0213] It should be noted that although several units or subunits of the device are mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, depending on the embodiment of the application, the features and functions of two or more units described above can be embodied in a single unit. Conversely, the features and functions of a single unit described above can be further divided into multiple units for embodied.

[0214] Furthermore, although the operations of the method of the present application are described in a particular order in the figures, this does not require or imply that the operations must be performed in that particular order, or that all of the operations shown must be performed to achieve the desired results. During execution, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0215] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0216] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable image scaling device to produce a machine, so that the instructions executed by the processor of the computer or other programmable image scaling device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0217] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable image scaling device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, the instruction device being implemented in the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0218] These computer program instructions can also be loaded onto a computer or other programmable image scaling device so that a series of operating steps are performed on the computer or other programmable device to produce a computer-implemented process, thereby executing the instructions on the computer or other programmable device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A functional step specified in one or more boxes.

[0219] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims will be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0220] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. If these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application shall also include these modifications and variations.

Claims

1. A TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method, characterized in that: The method comprises: S1: Establish a system model of wireless energy stations, RIS, IoT devices, jammers, and information receivers; S2: Using time slot scheduling and phase shift as constraints, a total anti-interference throughput calculation model is constructed. The objective function of this model is to maximize the total anti-interference throughput. S3: Based on the objective function, the closed-form optimal solution of time slot scheduling is derived using the Lagrange dual method and KKT conditions; S4: After the time slot scheduling optimization is completed, a closed-form solution of the phase shift is iteratively derived using the block coordinate descent (EBCD) algorithm and the complex circular manifold (CCM) algorithm. Based on this, a closed-form optimal solution of the phase shift is derived using an alternating optimization algorithm. Where, the diagonal matrix reflecting the phase shift of the RIS elements of the k-th IoT device is in and is the phase shift and amplitude associated with the Mth reflection element. When k = 0, Θ0 is also called the energy reflection phase shift matrix. When k∈[1,K], Θ k It is called the information reflection phase shift matrix; With time slot scheduling and phase shift as constraints, a total anti-interference throughput calculation model is constructed. The objective function of this model is to maximize the total anti-interference throughput. Specifically, it includes: The energy collected by the kth IoT device in the τ0 time slot is expressed as: where η c is the energy conversion efficiency of the kth IoT device, P t is the transmission power of the wireless energy station, τ0|h r Θ0h r,k +h d,k | 2 The power received by the IoT device; The achievable throughput of the kth IoT device in the remaining time slot is obtained as: Among them, P j is the transmit power at the jammer, σ 2 is the noise power at the information receiver; The total anti-interference throughput calculation model is: Among them, the channel state information between the wireless energy station and the kth IoT device is represented as h d,k ∈C 1×1 , the channel state information between the wireless energy station and RIS is expressed as h r ∈C 1×M , the channel state information between RIS and the kth IoT device is represented as h r,k ∈C M×1 , RIS and the channel state information of the information receiver are expressed as g r ∈C M×1 , the channel state information between the kth IoT device and the information receiver is expressed as g d,k ∈C 1×1 , the channel state information between the kth IoT device and RIS is expressed as g r,k ∈C 1×M , the channel state information of the jammer and the information receiver is expressed as g d,j ∈C 1×1 , the channel state information of the jammer and RIS link is expressed as h j ∈C 1×M .

2. The anti-interference transmission method according to claim 1, characterized in that: The system model in S1 specifically includes: a wireless energy station, a RIS, K IoT devices, a jammer, and an information receiver, where D k represents the kth IoT device, the jammer is located between the RIS and the information receiver, J represents the jammer, and it emits a signal with power P to the information receiver. J The interference signal is transmitted, IR represents the information receiver, and the RIS is equipped with M reflective elements; wherein, The wireless energy station is used to provide energy to a total of K IoT devices through wireless transmission; the IoT devices are used to receive energy supplies from the wireless energy station and use the received energy to send their information to an information receiver; the RIS is used to form a directional beam by adjusting the phase of each RIS reflection unit to enhance the signal strength to the information receiver; the jammer is used to emit an interference signal during the period when the IoT device sends information to the information receiver; and the information receiver is used to receive information sent and uploaded by the IoT device.

3. The anti-interference transmission method according to claim 2, characterized in that: The system model adopts the time division multiple access protocol, and the total time slot of the system satisfies A complete operation cycle is divided into K time slots. In the downlink energy transmission phase, within the time slot τ0, the wireless energy station transmits power P t Transmit energy to k IoT devices; in the uplink information transmission phase, that is, in the time slot τ1 to τ K The kth IoT device is in the corresponding time slot τ k Transmitting information to an information receiver; And, during the entire system uplink transmission phase, the jammer transmits a constant power P to the information receiver. j Transmitting interference signals.

4. The anti-interference transmission method according to claim 3, characterized in that: The RIS is also equipped with a controller for switching between a channel estimation reception mode and a transmission reflection mode and providing real-time channel status information feedback; wherein the diagonal matrix of the RIS element phase shift reflecting the kth IoT device is in and is the phase shift and amplitude associated with the Mth reflection element. When k = 0, Θ0 is also called the energy reflection phase shift matrix. When k∈[1,K], Θ k It is called the information reflection phase shift matrix.

5. A TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission device, used to implement the TDMA-based RIS-assisted wireless power supply Internet of Things anti-interference transmission method according to any one of claims 1 to 4, characterized in that: include: A system model building unit, used to build system models of wireless energy stations, RIS, IoT devices, jammers, and information receivers; An anti-interference total throughput calculation model building unit is used to build an anti-interference total throughput calculation model based on time slot scheduling and phase shift as constraints, and the model takes maximizing the anti-interference total throughput as the objective function; A time slot scheduling optimal solution derivation unit, for the objective function, using the Lagrange dual method and the KKT condition to derive a closed-form optimal solution for the time slot scheduling; The phase shift optimal solution derivation unit, after completing the time scheduling optimization, uses the unit block coordinate descent EBCD algorithm and the complex circle manifold CCM algorithm to iteratively derive the closed-form solution of the phase shift, and on this basis, derives the closed-form optimal solution of the phase shift through the alternating optimization algorithm.

6. The anti-interference transmission device according to claim 5, characterized in that: The system model established by the system model establishment unit specifically includes: A wireless energy station, a RIS, K IoT devices, a jammer, and an information receiver, where D k represents the kth IoT device, the jammer is located between the RIS and the information receiver, J represents the jammer, and it emits a signal with power P to the information receiver. J The interference signal is transmitted, IR represents the information receiver, and the RIS is equipped with M reflective elements; wherein, The wireless energy station is used to provide energy to a total of K IoT devices through wireless transmission; the IoT devices are used to receive energy supplies from the wireless energy station and use the received energy to send their information to an information receiver; the RIS is used to form a directional beam by adjusting the phase of each RIS reflection unit to enhance the signal strength to the information receiver; the jammer is used to emit an interference signal during the period when the IoT device sends information to the information receiver; and the information receiver is used to receive information sent and uploaded by the IoT device.

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