IRS-assisted mixed field beam forming data and energy simultaneous transmission system and method

Abstract

The invention provides an IRS-assisted mixed field beam forming data and energy simultaneous transmission system and method. The IRS-assisted mixed field beam forming data and energy simultaneous transmission system comprises a base station, an information user, an energy user and an IRS system, the multi-antenna system of the base station controls combination and emission of information signals and energy signals according to beam scheduling variables provided by the FPGA intelligent controller of the IRS system; the IRS panel of the IRS system comprises a plurality of reflection units, the FPGA intelligent controller of the IRS system can perform passive beam forming and control the phase and the amplitude of each reflection unit; the base station is located in a near field area of the IRS panel, and the information user and the energy user are located in a far field area of the IRS panel. According to the method, active beam scheduling and IRS passive beam forming are combined, joint optimization of user selection and channel enhancement can be achieved, and better balance is achieved between system fairness and overall performance.

Description

Technical Field

[0001] This invention belongs to the technical field of wireless communication, specifically relating to an IRS-assisted hybrid field beamforming digital transmission system and method. Background Technology

[0002] As sixth-generation wireless communication technology, namely 6G wireless communication technology, evolves towards ultra-high speed and ultra-low latency, sustainable energy supply and green and low-carbon capabilities are becoming increasingly important.

[0003] Under this trend, Simultaneous Wireless Information and Power Transfer (SWIPT) has become a key technology supporting 6G networks. However, traditional SWIPT systems are constrained by severe path loss between the transmitter and receiver, and the reachable area of ​​information and power shrinks rapidly with distance, thus significantly limiting system performance.

[0004] To overcome the aforementioned bottlenecks, intelligent reflective surfaces, or IRS, have been introduced into the SWIPT system. By programmably controlling the phase and amplitude of the incident signal, intelligent channel reconstruction is achieved, thereby effectively improving signal power gain and expanding coverage. Existing research mainly focuses on far-field beamforming design, which struggles to address the challenges of high-quality information transmission and efficient energy harvesting in complex real-world communication environments. Since IRSs are typically deployed near the transmitter or receiver, their electromagnetic radiation characteristics gradually transition from far-field plane waves to near-field spherical waves as the distance decreases or the IRS aperture increases. Therefore, passive beamforming of near-field IRSs requires adjustment in the additional range domain to ensure system performance; traditional far-field passive beamforming schemes fail in IRS-assisted SWIPT systems.

[0005] In more practical scenarios, when a user is located beyond the Rayleigh distance of the IRS, and the base station (BS) is deployed in the near-field range of the IRS, the BS–IRS link will exhibit near-field characteristics, causing the incident wave amplitude and phase distribution between IRS units to become non-uniform. Simultaneously, the IRS–user link is in the far-field region. Such a mixed-field model significantly increases the complexity of system analysis, modeling, and performance optimization.

[0006] Furthermore, given the complexity of multi-user scenarios, active beam scheduling at the transmitter is often incorporated into SWIPT system design to better balance the trade-offs between information transmission and energy harvesting among users. Research combining active beam scheduling with IRS passive beamforming remains relatively scarce.

[0007] Patent document WO2025237358A1 discloses a beamforming and user selection method based on a distributed IRSs-aided MIMO communication system. This method includes: constructing a distributed IRSs-aided MIMO communication system model; constructing a joint optimization problem P of active beamforming at the base station, IRSs phase shift, and user selection strategy; decoupling the joint optimization problem P into a joint optimization sub-problem P1 of user selection strategy and active beamforming at the base station, and an IRSs phase shift optimization sub-problem P2; solving the joint optimization sub-problem P1 to obtain the user selection strategy and the beamforming vector at the base station; solving the optimization sub-problem P2 to obtain the IRSs phase shift; repeating the solution steps until the joint optimization problem P converges, obtaining the optimal user selection strategy, the optimal beamforming vector at the base station, and the optimal IRSs phase shift, and then executing the solution. This method cannot simultaneously consider data transmission rate and energy harvesting requirements, failing to achieve an efficient trade-off between the two. Furthermore, the lack of a mixed-field model makes it difficult for the model to meet the complex variations of user scenarios.

[0008] In summary, the problems with the aforementioned existing technologies urgently need to be addressed. Summary of the Invention

[0009] To address the shortcomings of existing technologies, the purpose of this invention is to provide an IRS-assisted hybrid field beamforming digital energy transmission system and method.

[0010] According to the present invention, an IRS-assisted hybrid field beamforming data and energy transmission system includes: a base station, an information user, an energy user, and an IRS system; The base station's multi-antenna system controls the combination and transmission of information and energy signals based on beam scheduling variables provided by the FPGA intelligent controller of the IRS system; the IRS panel of the IRS system includes multiple reflection units; the FPGA intelligent controller of the IRS system is capable of passive beamforming, controlling the phase and amplitude of each reflection unit. The base station is located in the near-field region of the IRS panel, while the information user and energy user are located in the far-field region of the IRS panel.

[0011] Preferably, the multi-antenna system determines the scheduling variables of the information user, i.e. If the value is 0, then the corresponding information signal is suppressed, that is... ; Determine the scheduling variables for information users, i.e. If the value is 1, then the transmitting antenna of the multi-antenna system transmits information signals, i.e. ; The multi-antenna system determines the first The scheduling variables for each energy user, namely If the value is 0, then the corresponding energy signal is suppressed, that is... Determine the scheduling variables of energy users, i.e. If the value is 1, then the transmitting antenna of the multi-antenna system transmits an energy signal, i.e. ; It is a constant.

[0012] Preferably, the near-field region and far-field region of the IRS panel are separated by Rayleigh distance, the expression for which is:

[0013] in, This represents the Rayleigh distance; if the IRS distance range is less than... If the distance to the IRS is greater than 1, then it is the near-field region; if the distance to the IRS is greater Then it is the far-field region; D Indicates the array aperture of the IRS; Indicates wavelength.

[0014] Preferably, the reflected signal from the IRS panel is aligned with the equipment of the information user and the energy user.

[0015] According to the present invention, an IRS-assisted hybrid field beamforming method for simultaneous data and energy transfer is implemented based on an IRS-assisted hybrid field beamforming system, comprising: Channel modeling steps: Establish a near-field channel model for the base station-IRS link and a far-field channel model for the IRS-user equipment link, and then obtain a hybrid channel field model; Optimization steps: Based on the hybrid channel field model, establish the problem of maximizing total collected power, jointly optimize and obtain the optimal active beam scheduling vector, the optimal IRS passive beamforming matrix and the optimal transmit power variable; Scheduling and allocation steps: The base station schedules the transmit beams of the transmit antenna array according to the optimal active beam scheduling vector; the base station allocates transmit power to the information signal and the energy signal according to the optimal transmit power variable; the IRS system controls the phase of the reflection unit of each IRS panel according to the optimal IRS passive beamforming matrix.

[0016] Preferably, in the channel modeling step, the near-field channel model is the channel response matrix of the base station-IRS link, i.e., F; , Indicates all The space formed by complex-valued matrices, where, This refers to the number of transmitting antennas; This refers to the number of reflective elements in the IRS panel. This represents the number of cells in the IRS panel along the x-axis. For IRS panel along Number of elements in the axial direction, ; , , ;F's There are 1 element, and the expression is:

[0017] in, Describe the first of F One element, The base station's number The first antenna and the IRS Channel power gain between units Represents the imaginary unit. Indicates any , and , Indicates the ordinal number of the transmitting antenna. Let be the ordinal number of the reflective element of the IRS panel along the x-axis. The ordinal number of the IRS panel reflective element along the y-axis; Indicates the wavelength of the signal; The base station's number The first antenna and the IRS The distance between units; The far-field channel model is derived from the Rayleigh fading model, and its expression is:

[0018] in, Indicates IRS-Information User Channel, Indicates IRS- One energy user channel, Indicates "distribution as", This is the path loss index for the IRS-User Equipment link. This represents the path gain at a reference distance of 1 meter. and These represent the distances between the IRS and the information user, respectively, and are related to the IRS and the [other information]. The distance between energy users Let CSCG be a random vector, and assume that K One energy user, =1,..., K ; I represents a unit vector; The expression for the hybrid field channel model is:

[0019]

[0020] in, This represents a hybrid field combination channel for the base station-IRS-information user link. Indicates base station-IRS-number Hybrid field combination channel for individual energy user links, This indicates the conjugate transpose. This represents the passive beamforming matrix of the IRS. , Indicates all The space formed by complex-valued matrices.

[0021] Preferably, in the optimization step, the problem of maximizing the total collected power is P0, and its expression is:

[0022] in, Represents the active beam scheduling vector. Indicates the first The set of transmitted power of energy signals. Represents the set of energy users. Indicates the first The radio frequency power collected by each EU, and Representing information signals and the first The transmission power of an energy signal, The binary scheduling variable representing IU, This represents the combined channel gain of the base station-IRS-information user link. Indicates the SINR threshold. Describing covariance, Indicates the first One energy user scheduling variable, Indicates the first step during IRS auxiliary signal beamforming. The reflection phase of each unit, Indicates the position coordinates of the IRS panel unit. This indicates the maximum transmit power of the base station.

[0023] Preferably, the joint optimization includes: Step A1: Introduce auxiliary variables and integrate the optimization vectors to transform the problem of maximizing the total collected power, i.e., P0, into the optimization problem P1; Step A2: Based on the optimization problem P1, construct the corresponding Lagrangian function and apply the KKT conditions to solve the optimization vector, thereby obtaining the optimized active beam scheduling vector and transmit power variables; Step A3: The problem of maximizing the total collected power, i.e., P0, is transformed into an optimization problem P2 by optimizing the variables. Then, a semidefinite relaxation algorithm is applied to transform the optimization problem into an optimization problem P3. Finally, the optimization variables are solved by a successive convex approximation algorithm to optimize the IRS passive beamforming matrix. Step A4: Repeat steps A2 to A3 until the change in energy harvesting is less than a preset threshold, and obtain the optimal active beam scheduling vector, the optimal IRS passive beamforming matrix, and the optimal transmit power variable.

[0024] Preferably, in step A1, the auxiliary variable is, and The expressions are respectively, and Optimize vector The expression is The expression for the optimization problem P1 is:

[0025] in, Represents the auxiliary matrix. Indicates the number of rows. K A vector of all 1s with 1 column. Indicates the number of rows. A vector of all 1s with 1 column, symbol denoted by element-wise nonnegativity, c represents the transition vector; The auxiliary matrix The expression for the line is:

[0026] Where h represents the hybrid field combination channel of the base station-IRS-information user link, Indicates base station-IRS-number Hybrid field combination channel for individual energy user links, Indicates base station-IRS-number K Hybrid field combination channel for individual energy user links, This indicates the conjugate transpose. Represents the first of the matrix OK, Represents the L2 norm; In step A2, the Lagrangian function corresponding to optimization problem P1 is expressed as:

[0027] in, Represent the Lagrange function, , Both are Lagrange multipliers; KKT conditions K1~K8 are as follows:

[0028] in, Indicates the optimization vector The partial derivatives are defined as follows: express From 1 to The position corresponding to the maximum element can be used to derive: when When the value is not 1, optimize the vector. The optimal solution is:

[0029] when When the value is 1, optimize the vector. The optimal solution is:

[0030] in, express The One element, Represents arbitrary; separate optimization vectors The optimal solution yields the optimal active beam scheduling vector, i.e. Optimal transmit power variable, i.e. and ; In step A3, optimization variables are introduced. The expression is This transforms the problem of maximizing total collected power, P0, into an optimization problem P2; the expression for optimization problem P2 is:

[0031] in, To maximize To optimize the objective function of the variables, the uniform energy conversion efficiency of all EU energy harvesters is required. Represents optimization variables , Represents optimization variables The One element; ,in This means placing the vectors on the diagonal to form a diagonal matrix; Set auxiliary variables , , and ,definition , Satisfying constraints and ,in, To represent the 'yi', we then introduce slack variables. and The expressions are respectively and ,in, Represent the trace; thus, the optimization problem P2 is transformed into the optimization problem P3, expressed as:

[0032] The optimal solution is obtained using software for solving convex optimization problems. Then, the IRS passive beamforming matrix is ​​obtained through matrix decomposition.

[0033] Preferably, the optimization problem P3 is obtained using the SCA algorithm. and The lower bound is then determined, and problem P3 is transformed into a convex optimization problem. The optimal passive beamforming matrix of the IRS is obtained through software iteration. The and The lower bound of the expression, from top to bottom, is as follows:

[0034]

[0035] In this context, the superscript * indicates complex conjugation, and Re represents the real part. and Indicates intermediate quantity; The and The mathematical expressions are as follows, from top to bottom:

[0036]

[0037] in, yes During the next iteration The value of .

[0038] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention employs a non-uniform spherical wave model with projected aperture to perform refined mixed-field channel modeling for IRS-assisted digital-energy simultaneous transmission systems, accurately characterizing the channel propagation characteristics under mixed near-field and far-field environments, and laying a solid theoretical foundation for achieving high-precision beamforming and system performance optimization.

[0039] 2. This invention has achieved key technological breakthroughs in green communication capabilities, efficiency of information and energy coordinated transmission, system coverage and flexibility, providing important technical support for the sustainable development of future communication networks.

[0040] 3. Based on the established hybrid field channel model, this invention combines the IRS with a multi-transmit antenna system to achieve coordinated optimization of active beam scheduling and passive beamforming, effectively balancing the data transmission rate and energy harvesting capability of the data transmission system and improving the system transmission efficiency.

[0041] 4. The system architecture provided by this invention is simple and highly deployable, with outstanding advantages in cost and energy efficiency. Furthermore, the hardware complexity and overhead of the IRS panel are far lower than those of traditional antenna arrays, yet it can achieve excellent signal modulation capabilities, making it an ideal solution for building next-generation high-efficiency wireless communication networks.

[0042] 5. This invention integrates the IRS system with the base station, effectively reducing propagation loss of the reflection link through near-field deployment. The inherent low-power characteristics of the IRS make it an ideal green data-energy simultaneous transmission auxiliary component. Through collaborative optimization of the system, this invention significantly reduces overall energy consumption while ensuring communication performance, precisely aligning with the development direction of high energy efficiency and low carbon emissions in next-generation communication networks. In other words, this invention achieves an efficient trade-off between data transmission rate and energy harvesting requirements, significantly improving the energy harvesting efficiency and information transmission performance of the hybrid field data-energy simultaneous transmission system. Attached Figure Description

[0043] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 A schematic diagram of the IRS-assisted hybrid field beamforming digital energy transmission system provided by the present invention; Figure 2 A schematic diagram illustrating the variation of total collected energy with user service quality ratio under different architectural scenarios provided by the present invention; Figure 3 This diagram illustrates how the total collected energy varies with the base station's transmit power under different architectural configurations provided by the present invention. Detailed Implementation

[0044] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0045] This invention proposes an intelligent reflective surface, namely an IRS-assisted hybrid field beamforming digital energy transmission system and method. The system includes a base station, an IRS system, an information user, and multiple energy users.

[0046] The base station is equipped with a multi-transmit antenna system, while the user equipment is configured with a single antenna. The method includes first constructing a hybrid field channel model, then using an IRS system to assist the data transmission system in performing joint hybrid field beamforming, and optimizing the active beam scheduling vector of the multi-transmit antenna system.

[0047] This invention achieves a highly efficient balance between data transmission rate and energy harvesting, significantly improving the system's energy acquisition efficiency and information transmission capabilities. Furthermore, this technology represents a breakthrough in green communication, coordinated information and energy transmission, and system coverage and flexibility, providing strong support for the development of next-generation communication networks.

[0048] According to the present invention, an IRS-assisted hybrid field beamforming data transmission system includes: a base station, an IRS system, information users, and energy users. The base station is equipped with a multi-antenna system with multiple transmitting antennas; the IRS system includes an IRS panel and an FPGA intelligent controller. The IRS panel includes multiple passive reflector elements, and the IRS performs passive beamforming through the FPGA intelligent controller, controlling the phase and amplitude of each reflector element; the information users and energy users are each equipped with a single receiving antenna. The base station is located in the near-field region of the IRS, while the information users and energy users are located in the far-field region of the IRS.

[0049] Specifically, the base station's multi-antenna system controls the combination and transmission of information and energy signals based on beam scheduling variables. When the system determines the information user scheduling variable, that is... When it is 0, the information signal, that is Suppressed; when When it is 1, the information signal, that is Transmitted by the transmitting antenna. When the system determines the... One energy user scheduling variable, namely When it is 0, the energy signal, i.e. Suppressed; when When it is 1, the energy signal, i.e. It was transmitted by the transmitting antenna.

[0050] Specifically, the IRS system includes an IRS panel and a corresponding FPGA intelligent controller, which directs the signal reflected by the IRS panel toward the user equipment.

[0051] Specifically, the Rayleigh distance is calculated using the operating frequency and array aperture of the IRS panel. The near-field / far-field regions are then determined based on the Rayleigh distance, ensuring the base station is located in the near-field region and the user equipment is located in the far-field region. More specifically, the base station is positioned within the near-field region of the IRS, while the information user and energy user are positioned within the far-field region of the IRS.

[0052] Specifically, the near-field / far-field regions are determined through the following steps.

[0053] The configuration of the digital simultaneous transmission system includes The transmitting antenna and the IRS panel are located in the x-axis of a three-dimensional Cartesian coordinate system. On the plane, respectively by It consists of several reflective units, among which... This represents the total number of units in the IRS. and These represent the number of cells along the x-axis and z-axis of the IRS panel, respectively. The area of ​​each reflective cell in the IRS panel is... S The unit spacing is .

[0054] For a uniform planar array of IRS, the array aperture is calculated as follows: The expression is:

[0055] The operating frequency is denoted as Then the wavelength of the signal is ,in, Represents the speed of light. The near-field / far-field regions of the IRS are represented by Rayleigh distances. Division.

[0056] According to the present invention, an IRS-assisted hybrid field beamforming method for simultaneous digital energy transfer includes: Channel modeling steps: Based on the projection aperture non-uniform spherical wave model and Rayleigh fading model, establish the near-field channel model of the base station-IRS link and the far-field channel model of the IRS-user equipment link; Optimization steps: Through joint optimization, the optimal active beam scheduling vector, the optimal transmit power variable, and the optimal IRS passive beamforming matrix are obtained; Active beam scheduling steps: Based on the optimal active beam scheduling vector, the base station performs transmit beam scheduling on the transmit antenna array to control the transmission and suppression of information signals and energy signals; Transmission power allocation steps: Based on the optimal transmission power variables, the base station allocates transmission power to information signals and energy signals; Passive beamforming steps: Based on the optimal IRS passive beamforming matrix, the IRS panel controls the phase of each reflection unit through an FPGA intelligent controller.

[0057] Specifically, the channel modeling steps include the following sub-steps: Step T1.1: Set the starting point of the base station's transmitting antenna array to the origin of the three-dimensional Cartesian coordinate system, place the array along the y-axis, and set the antenna spacing to be... There are a total of The first transmitting antenna, then the base station's first... The coordinates of the root transmitting antenna are, ,in, The center of the IRS panel is located at .in, and Let x and y be the coordinates of the center of the IRS panel along the x-axis and y-axis, respectively. Then the first... The position of each unit is represented as ,in, , , For the IRS cell spacing, then the IRS's first... The distance between each cell and the base station is represented as:

[0058] in, This represents the IRS array occupancy rate.

[0059] Step T1.2, through three-dimensional channel modeling, based on the projection aperture non-uniform spherical wave model, the base station's first... The first antenna and the IRS The channel power gain between units is expressed as:

[0060] in, The base station's number The coordinates of the root transmitting antenna, Represents the L2 norm, e This represents the normal vector of each IRS element placed on the xz plane, i.e. e =(0,-1,0). S This represents the area of ​​each reflective unit in the IRS panel. This indicates transpose. This is represented as the channel response matrix of the base station-IRS link. , Indicates all The space formed by complex-valued matrices. The first... The elements are:

[0061] in, Represents the imaginary unit. Indicates any , and . The base station's number The first antenna and the IRS Channel power gain between units; The base station's number The first antenna and the IRS The distance between units.

[0062] Step T1.3, setting the data transmission system to include an information user and K One energy user. Considering the abundant scattering near the user and the long distance between the IRS and the user, the IRS-information user channel... and IRS- One energy user channel All follow the Rayleigh fading model, that is:

[0063] in, The distribution is defined as a circularly symmetric complex Gaussian vector with zero mean and covariance matrix C, denoted as CSCG. . This is the path loss index for the IRS-User Equipment link. This represents the path gain at a reference distance of 1 meter. and Represent the distance between the IRS and the information user, and the distance between the IRS and the first... The distance between energy users, where I represents a unit vector.

[0064] Step T1.4, will Represented as the passive beamforming matrix of the IRS, Indicates all The space formed by complex-valued matrices. The expression is:

[0065] in, Indicates the first step during IRS auxiliary signal beamforming. The reflection phase of each unit, diag represents the vector placed on the diagonal to form a diagonal matrix.

[0066] Base Station-IRS-Information User Link and Base Station-IRS-First The hybrid field combination channels for each energy user link are represented as follows:

[0067]

[0068] in This represents the conjugate transpose. Applying the central limit theorem, the combined channel of the base station-IRS-information user link... Each element in They all approximately follow a normal distribution The element-wise average combined channel gain Given by the following formula:

[0069] The optimization steps include the following sub-steps: Step T2: Establish the problem of maximizing total collected power; Step T3: Jointly optimize the active beam scheduling vector Transmission power variables and and IRS passive beamforming matrix To maximize the collected energy, the optimal active beam scheduling vector, the optimal transmit power variable, and the optimal IRS passive beamforming matrix are obtained.

[0070] Specifically, step T2 includes the following sub-steps: Step T2.1, let and Representing the information-carrying signal and the first An energy-carrying signal. Information-carrying signals and energy-carrying signals are simply referred to as information signals and energy signals. and These respectively represent information users, namely IU and the first. Each energy user, i.e., the EU, transmits beamforming vectors. Therefore, the signal transmitted from the base station is represented as:

[0071] in, Represents the set of energy users, i.e. .definition As a set of active beam scheduling indicators for base stations, among which, and IU and - EU's binary scheduling variable.

[0072] Specifically, This indicates that the IU is being scheduled by the base station, and the information signal is... It was transmitted by the transmitting antenna. This indicates that the IU has not been scheduled by the base station; this is an information signal. Suppressed; Indicates the first The EU is scheduled by the base station, the first An energy signal, namely It was transmitted by the transmitting antenna. Indicates the first The EU was not scheduled by the base station. An energy signal, namely It is suppressed. Therefore, the received signal of the IU is:

[0073] in, The Gaussian noise at the IU receiver. This indicates that the expression has a mean of 0 and a covariance of . The circularly symmetric complex Gaussian, i.e., CSCG random variable, where "~" indicates "distribution". The square root of covariance is used to represent the variance.

[0074] Step T2.2: Since the energy beam carries no information and is composed of pseudo-random signals known to both the base station and the user equipment, its interference can be eliminated at the user equipment. This invention uses maximum ratio transmission, i.e., MRT transmit beamforming, that is... and .

[0075] in, and Representing information signals and the first The transmission power of an energy signal, This indicates the conjugate transpose, i.e., the upper right corner. This represents the conjugate transpose. Therefore, the average signal-to-noise ratio of IU is expressed as:

[0076] Then the first The collected radio frequency power of each EU is expressed as:

[0077] in, η ∈(0,1] represents the uniform energy conversion efficiency of all EUs, i.e., the energy harvesters of all energy users, and h represents the hybrid field combination channel of the base station-IRS-information user link. Indicates base station-IRS-number Hybrid field combination channel for individual energy user links, Indicates base station-IRS-number K Hybrid field combination channel for individual energy user links, This indicates the conjugate transpose. Represents the first of the matrix OK, This represents the L2 norm. Step T2.3, the mathematical expression for maximizing the total collected power P0 is set as follows:

[0078] in, This represents the SINR threshold, ensuring the user's QoS requirements. Users with a non-zero SINR threshold have... ; This indicates the maximum transmit power of the base station.

[0079] Where P0 represents the problem of maximizing total collection power, Represents the active beam scheduling vector; and Representing information signals and the first The transmission power of an energy signal; The ordinal number representing the collected radio frequency power; Represents the set of energy users; Indicates the first The radio frequency power collected by each EU; st indicates a constraint; Represents the binary scheduling variable of IU; Indicates the number of transmitting antennas; Indicates the ordinal number of the transmitting antenna; This represents the combined channel gain of the base station-IRS-information user link; Indicates the SINR threshold; Represents covariance; Indicates the first One energy user scheduling variable; Indicates the first step during IRS auxiliary signal beamforming. The reflection phase of each unit, This indicates the position coordinates of the IRS panel unit.

[0080] Specifically, step T3 includes the following sub-steps: Step T3.1: Introduce auxiliary variables, construct the Lagrangian function, and apply the KKT conditions to solve for the active beam scheduling vector. Transmission power variables and ; Step T3.2: Apply semidefinite relaxation, i.e., SDR and successive convex approximation, i.e., SCA algorithm, to optimize the IRS passive beamforming matrix. .

[0081] Step T3.3: Repeat steps T3.1 to T3.2 until the change in energy harvesting is less than a preset threshold, and obtain the optimal active beam scheduling vector, the optimal transmit power variable, and the optimal IRS passive beamforming matrix.

[0082] Specifically, in the active beam scheduling step, based on hybrid field channel modeling and the optimal active beam scheduling vector, information users or energy users are selected for scheduling, balancing the trade-off between data transmission rate and energy harvesting. In the transmit power allocation step, based on hybrid field channel modeling and optimal transmit power variables, transmit power is allocated to information signals and energy signals to maximize the total collected power; In the passive beamforming step, based on the hybrid field channel modeling and the phase of all elements in the optimal IRS passive beamforming matrix, the incident signal on the IRS panel is passively beamformed so that the reflected signal is aligned with the scheduled user equipment.

[0083] Example 1: Figure 1 This is an IRS-assisted hybrid field beamforming digital energy transmission system in an embodiment of the present invention.

[0084] like Figure 1 As shown, this embodiment provides an IRS-assisted hybrid field beamforming digital-energy simultaneous transmission system, including: a base station, an IRS system, an information user, and... K One energy user.

[0085] The base station is equipped with a multi-antenna system, which has multiple transmitting antennas.

[0086] Specifically, the base station's multi-antenna system controls the combination and transmission of information and energy signals based on beam scheduling variables. When the system determines the information user scheduling variable, that is... When it is 0, the information signal, that is Suppressed; when When it is 1, the information signal, that is Transmitted by the transmitting antenna. When the system determines the... One energy user scheduling variable, namely When it is 0, the energy signal, i.e. Suppressed; when When it is 1, the energy signal, i.e. It was transmitted by the transmitting antenna.

[0087] The IRS system includes an IRS panel and a corresponding FPGA intelligent controller. The IRS panel includes multiple passive reflective units. The IRS performs passive beamforming through the FPGA intelligent controller, controlling the phase and amplitude of each reflective unit so that the signal reflected by the IRS panel is aligned with the user equipment.

[0088] Both information users and energy users are equipped with a single receiving antenna.

[0089] In this embodiment, the transmitting antenna array is a uniform linear antenna array.

[0090] The base station is located in the near-field area of ​​the IRS, and the user equipment is located in the far-field area of ​​the IRS. The direct link between the base station and the user equipment is weak. By deploying the IRS, a line-of-sight path is ensured between the wireless access point and the user equipment, thereby enhancing the quality of the communication link.

[0091] Specifically, the Rayleigh distance is calculated using the operating frequency and array aperture of the IRS panel. The near-field / far-field regions are determined based on the Rayleigh distance, so that the base station is located in the near-field region of the IRS, while the user equipment is located in the far-field region.

[0092] The near-field / far-field regions are determined through the following steps: The data transmission system is configured including... The transmitting antenna and the IRS panel are located in the x-axis of a three-dimensional Cartesian coordinate system. On the plane, respectively by It consists of several reflective units, among which... This represents the total number of units in the IRS. and These represent the number of cells along the x-axis and z-axis of the IRS panel, respectively. The area of ​​each reflective cell in the IRS panel is... S The unit spacing is For a uniform planar array of IRS, the array aperture is calculated as follows: The operating frequency is denoted as... Then the wavelength of the signal is ,in Represents the speed of light. The near-field / far-field regions of the IRS are represented by Rayleigh distances. Division.

[0093] The system uses the IRS system to assist in the simultaneous transmission of data and energy for joint hybrid field beamforming, and the base station multi-antenna system to perform active beam scheduling, providing a trade-off between data transmission rate and energy harvesting, while improving the system's energy harvesting efficiency and information transmission rate.

[0094] This invention uses maximizing collection power as the performance indicator and takes user service quality requirements, base station transmit power requirements, beam scheduling requirements, and reflection unit reflection capabilities as constraints. Based on hybrid field channel modeling, it designs a joint active beam scheduling and passive beamforming scheme for a novel IRS-assisted hybrid field data and energy simultaneous transmission system.

[0095] The IRS-assisted beamforming data transmission system proposed in this invention achieves superior performance at a lower cost and power consumption compared to traditional solutions, eliminating the need for numerous additional RF links or complex signal processing units. Through the combined active beam scheduling and passive beamforming design of the base station and IRS, the collected power of this invention is significantly improved.

[0096] This invention establishes an accurate channel model for hybrid field IRS systems. Compared with traditional far-field IRS-assisted communication system design, it accurately characterizes the channel propagation characteristics in hybrid near-field and far-field environments, laying a solid theoretical foundation for achieving high-precision beamforming and system performance optimization in hybrid fields.

[0097] In an IRS-assisted data and energy transmission system, the base station's multi-antenna system controls the combination and transmission of information and energy signals based on beam scheduling variables. The IRS panel uses an FPGA intelligent controller for passive beamforming, controlling the phase of each reflecting unit.

[0098] IRS-assisted data and energy transmission system: The base station and IRS are jointly designed with active beam scheduling and passive beamforming. The base station generates the corresponding control signals in the antenna array system, and the IRS unit generates the corresponding control signals in the intelligent controller.

[0099] The base station generates active beam scheduling control signals: Definition As a set of active beam scheduling indicators for base stations, among which, and IU and - EU's binary scheduling variable.

[0100] Specifically, This indicates that the IU is being scheduled by the base station, and the information signal is... It was transmitted by the transmitting antenna. This indicates that the IU has not been scheduled by the base station; this is an information signal. Suppressed; Indicates the first The EU is scheduled by the base station, the first An energy signal, namely It was transmitted by the transmitting antenna. Indicates the first The EU was not scheduled by the base station. An energy signal, namely It is suppressed.

[0101] IRS generates passive beamforming control signals: The IRS performs reflected beamforming on the incident signal, controlling the IRS coefficient matrix, i.e., the IRS passive beamforming matrix. This is used to design the phase of all elements so that the reflected signal can be aligned with the user. The IRS passive beamforming matrix is ​​also known as the IRS phase shift matrix.

[0102] Hybrid field beamforming scheme in IRS transceiver system: Based on hybrid field channel model, with maximizing collection power as the performance index, this invention realizes a novel IRS-assisted hybrid field beamforming digital and energy simultaneous transmission system and method by constructing an optimization problem constrained by user service quality requirements, base station transmit power requirements, beam scheduling index requirements and reflection unit reflection capability.

[0103] Design of a Hybrid-Field Beamforming Scheme for IRS-Assisted Data and Energy Transmission: The optimization problem for maximizing collected power is a non-convex optimization problem, and a globally optimal solution cannot be directly obtained. This invention, based on the Lagrange duality method, semi-definite relaxation (SDR algorithm), and successive convex approximation (SCA algorithm), jointly implements active and passive beamforming with the base station and IRS to mitigate interference and improve transmission efficiency. Furthermore, all optimization variables are alternately optimized to obtain a relatively high-quality suboptimal solution.

[0104] Based on hybrid field channel modeling, the IRS system assists the data and energy transmission system in jointly performing hybrid field active beam scheduling and passive beamforming to maximize the system's energy collection and obtain the optimal active beam scheduling and passive beamforming scheme.

[0105] To address the requirements of next-generation wireless networks for network coverage, energy sustainability, and communication reliability, this invention provides a novel design for an IRS-assisted hybrid field data transmission system.

[0106] The IRS-assisted hybrid field digital energy simultaneous transmission system provided by the present invention is based on a hybrid field channel model and a joint design scheme of active beam scheduling of base station antenna array, independent transmit power and IRS beamforming.

[0107] Base stations need to consider scheduling design when modulating signals, achieving active beam scheduling by controlling the transmission of information and energy signals. Power dividers need to consider the trade-off between information transmission and energy harvesting to achieve optimal system performance. IRS needs to control the phase of each reflecting unit to achieve passive transmit beamforming when assisting with incident signals.

[0108] As a disruptive technology, IRS offers a new approach to addressing the bottlenecks in performance improvement and energy efficiency optimization faced by data and energy transmission systems. In wireless communication, IRS enables programmable channel reconfiguration, creating more controllable multipath components, thereby improving spatial multiplexing efficiency and expanding system capacity. Furthermore, IRS can alleviate coverage deficiencies caused by non-line-of-sight environments in energy transmission. Specifically, leveraging passive beamforming capabilities, IRS can directionally reflect incident signals to target users, enhancing signal focusing and improving reception strength. The introduction of numerous tunable units allows IRS to flexibly adjust the multipath structure, significantly increasing the system's spatial degrees of freedom. Simultaneously, IRS does not rely on high-power devices such as RF chains; its passive nature not only reduces deployment costs but also provides excellent system compatibility, allowing for seamless integration into existing data and energy transmission architectures. Therefore, introducing the IRS structure can effectively improve the energy harvesting and information transmission performance of data and energy transmission systems at low cost, demonstrating significant application potential and feasibility in next-generation wireless networks.

[0109] Figure 2 This illustrates how the total collected energy varies with the user service quality ratio under different architectural scenarios in the embodiments of the present invention. Figure 3 The total collected energy varies with the base station transmit power under different architecture scenarios in the embodiments of the present invention.

[0110] Figure 2 , 3 This indicates that the architecture of this embodiment achieves the highest total collected energy gain compared to other architectures, regardless of changes in user service quality and base station transmit power.

[0111] Example 2: This example provides an IRS-assisted hybrid field beamforming digital-energy simultaneous transmission method, which is implemented on the IRS-assisted hybrid field beamforming digital-energy simultaneous transmission system in the above example.

[0112] Specifically, the IRS-assisted hybrid field beamforming method for simultaneous propagation of energy includes the following steps: Channel modeling steps: Based on the projected aperture non-uniform spherical wave model and Rayleigh fading model, establish the near-field channel model of the base station-IRS link and the far-field channel model of the IRS-user equipment link to accurately describe the mixed-field channel characteristics; specifically, the channel modeling steps include the following sub-steps: Step T1.1: Set the starting point of the base station's transmitting antenna array to the origin of the three-dimensional Cartesian coordinate system, and set the array along... The antennas are placed on an axis with a spacing of [missing information]. There are a total of The first transmitting antenna, then the base station's first... The coordinates of the root transmitting antenna are, ,in, The center of the IRS panel is located at .in, and Let x and y be the coordinates of the center of the IRS panel along the x-axis and y-axis, respectively. Then the first... The position of each unit is represented as ,in, , , For the IRS cell spacing, then the IRS's first... The distance between each cell and the base station is represented as:

[0113] in, This represents the IRS array occupancy rate.

[0114] Step T1.2, through three-dimensional channel modeling, based on the projection aperture non-uniform spherical wave model, the base station's first... The first antenna and the IRS The channel power gain between units is expressed as:

[0115] in, e This represents the normal vector of each IRS element placed on the xz plane, i.e. e =(0,-1,0). S This represents the area of ​​each reflective unit in the IRS panel. Indicates transpose. This is represented as the channel response matrix of the base station-IRS link. Indicates all The space formed by complex-valued matrices. The first... The elements are :

[0116] in, Represents the imaginary unit. Indicates any , and . The base station's number The first antenna and the IRS Channel power gain between units; The base station's number The first antenna and the IRS The distance between units.

[0117] Step T1.3, setting the data transmission system to include an information user and K One energy user. Considering the abundant scattering near the user and the long distance between the IRS and the user, the IRS-information user channel... and IRS- One energy user channel All follow the Rayleigh fading model, that is:

[0118] in, The distribution is defined as a circularly symmetric complex Gaussian vector with zero mean and covariance matrix C, denoted as CSCG. . This is the path loss index for the IRS-User Equipment link. This represents the path gain at a reference distance of 1 meter. and Represent the distance between the IRS and the information user, and the distance between the IRS and the first... The distance between energy users.

[0119] Step T1.4, will Represented as the passive beamforming matrix of the IRS, Indicates all The space formed by complex-valued matrices. The expression is:

[0120] in, Indicates the first step during IRS auxiliary signal beamforming. The reflection phase of each unit, diag represents the vector placed on the diagonal to form a diagonal matrix.

[0121] Base Station-IRS-Information User Link and Base Station-IRS-First The hybrid field combination channels for each energy user link are represented as follows:

[0122]

[0123] in This represents the conjugate transpose. Applying the central limit theorem, the combined channel of the base station-IRS-information user link... Each element in They all approximately follow a normal distribution The element-wise average combined channel gain Given by the following formula:

[0124] Optimization steps: Through joint optimization, the optimal active beam scheduling vector, the optimal transmit power variable, and the optimal IRS passive beamforming matrix are obtained; Specifically, the optimization steps include the following sub-steps: Step T2: Establish the problem of maximizing total collected power; Specifically, step T2 includes the following sub-steps: Step T2.1, let and Representing the information-carrying signal and the first One energy-carrying signal, and These respectively represent information users and the first The transmit beamforming vector of each energy user. Therefore, the signal transmitted from the base station is represented as:

[0125] in, Represents the set of energy users, i.e. .definition As a set of active beam scheduling indicators for base stations, among which, and IU and - EU's binary scheduling variable.

[0126] Specifically, This indicates that the IU is being scheduled by the base station, and the information signal is... It was transmitted by the transmitting antenna. This indicates that the IU has not been scheduled by the base station; this is an information signal. Suppressed; Indicates the first The EU is scheduled by the base station, the first An energy signal, namely It was transmitted by the transmitting antenna. Indicates the first The EU was not scheduled by the base station. An energy signal, namely It is suppressed. Therefore, the received signal of the IU is:

[0127] in, The Gaussian noise at the IU receiver. This indicates that the expression has a mean of 0 and a covariance of . The circularly symmetric complex Gaussian, i.e., CSCG random variable, where "~" indicates "distribution". The square root of covariance is used to represent the variance.

[0128] Step T2.2: Since the energy beam carries no information and is composed of pseudo-random signals known to both the base station and the user equipment, its interference can be eliminated at the user equipment. This invention uses maximum ratio transmission, i.e., MRT transmit beamforming, that is... and .

[0129] in, and Representing information signals and the first The transmission power of an energy signal, This indicates the conjugate transpose, i.e., the upper right corner. This represents the conjugate transpose. Therefore, the average signal-to-noise ratio of IU is expressed as:

[0130] Then the first The collected radio frequency power of each EU is expressed as:

[0131] in, η ∈(0,1] represents the uniform energy conversion efficiency of all EUs, i.e., the energy harvesters of all energy users, and h represents the hybrid field combination channel of the base station-IRS-information user link. Indicates base station-IRS-number Hybrid field combination channel for individual energy user links, Indicates base station-IRS-number K Hybrid field combination channel for individual energy user links, This indicates the conjugate transpose. Represents the first of the matrix OK, This represents the L2 norm.

[0132] Step T2.3, the mathematical formulation of the optimization problem P0 to maximize the total collected power is set as follows:

[0133] In this embodiment, when the original optimization problem is a non-convex optimization problem concerning the active beam scheduling vector, transmit power variable, and IRS passive beamforming matrix, the IRS passive beamforming matrix, active beam scheduling vector, and transmit power variable are alternately optimized and solved based on the Lagrange duality method, semidefinite relaxation (SDR), and successive convex approximation (SCA) algorithms. Under the preset constraints of user service quality, base station transmit power requirements, beam scheduling index requirements, and reflective unit reflection capability, an optimization problem that maximizes the total collected energy of energy users is constructed, transforming the non-convex problem into a convex problem, and obtaining the optimal IRS passive beamforming matrix, active beam scheduling vector, and transmit power variable, thus achieving efficient mixed-field beamforming.

[0134] Step T3: Jointly optimize the active beam scheduling vector Transmission power variables and and IRS passive beamforming matrix To maximize the collected energy, the optimal active beam scheduling vector, the optimal transmit power variable, and the optimal IRS passive beamforming matrix are obtained.

[0135] Specifically, step T3 includes the following sub-steps: Step T3.1: Introduce auxiliary variables, construct the Lagrangian function, and apply the KKT conditions to solve for the active beam scheduling vector. Transmission power variables and .

[0136] Specifically, solve alternately and and When introducing auxiliary variables and Then the optimized vector integration is .

[0137] Set auxiliary matrix , Represents the first of the matrix Okay. The original optimization problem P0 is transformed into optimization problem P1:

[0138] in, Represents the auxiliary matrix. Indicates the number of rows. K A vector consisting entirely of 1s with 1 column. Indicates the number of rows. A vector consisting of only 1s with 1 column. For transition vectors, This indicates that the number of rows is 1 and the number of columns is... K The vector consisting entirely of zeros. Problem P1 is a linear programming problem, and its optimal solution can be found using the Karush-Kuhn-Tucker (KKT) conditions.

[0139] The Lagrangian function corresponding to optimization problem P1 is expressed as:

[0140] in, Represent the Lagrange function, , Both are Lagrange multipliers; KKT conditions K1~K8 are as follows:

[0141] in, Indicates the optimization vector Definition of partial derivatives Prioritize energy collection for all energy users. express From 1 to The position corresponding to the largest element. This can be derived from the KKT conditions: when When the value is not 1, optimize the vector. The optimal solution is:

[0142] when When the value is 1, optimize the vector. The optimal solution is:

[0143] in, express The One element, Represents arbitrary; separate optimization vectors The optimal solution yields the optimal active beam scheduling vector, i.e. Optimal transmit power variable, i.e. and ; Step T3.2: Apply the semidefinite relaxation algorithm and the successive convex approximation algorithm to optimize the IRS passive beamforming matrix. .

[0144] Specifically, solve alternately When, define , , where diag means to place the vectors on the diagonal to form a diagonal matrix.

[0145] Optimization variables transformed into By introducing variable transformation and The original optimization problem P0 simplifies to optimization problem P2:

[0146] in, To maximize The objective function is used to optimize the variables.

[0147] Problem P2 is still a non-convex problem, and this invention uses the SDR and SCA algorithms to solve it.

[0148] Specifically, setting auxiliary variables , , and .

[0149] Notice, , , , in, Indicates a trace.

[0150] definition , Satisfying constraints and ,in Let represent the rank. Since the rank-one constraint is non-convex, this invention first applies SDR to relax it. The objective function is rewritten as:

[0151] Introducing slack variables and Then, optimization problem P2 can be equivalently transformed into optimization problem P3:

[0152] because and For non-convex structures, this invention uses SCA to obtain their lower bounds:

[0153]

[0154] in, , . yes During the next iteration The value of is given by the superscript *, which indicates complex conjugate. At this point, problem P3 has been transformed into a convex optimization problem, and the optimal value can be obtained using convex optimization software. Then, the optimal value is obtained through matrix decomposition. .

[0155] Step T3.3: Repeat steps T3.1 to T3.2 until the change in energy harvesting is less than a preset threshold, and obtain the optimal active beam scheduling vector, the optimal transmit power variable, and the optimal IRS passive beamforming matrix.

[0156] Active beam scheduling steps: Based on the optimal active beam scheduling vector, the base station performs transmit beam scheduling on the transmit antenna array to control the transmission and suppression of information signals and energy signals.

[0157] Specifically, in the active beam scheduling step, based on hybrid field channel modeling and the optimal active beam scheduling vector, information users or energy users are selected for scheduling, balancing the trade-off between data transmission rate and energy harvesting. Transmission power allocation steps: Based on the optimal transmission power variables, the base station allocates transmission power to information signals and energy signals.

[0158] Specifically, in the transmit power allocation step, based on the hybrid field channel modeling and the optimal transmit power variables, the transmit power is allocated to the information signal and the energy signal to maximize the total collected power.

[0159] Passive beamforming steps: Based on the optimal IRS passive beamforming matrix, the IRS panel controls the phase of each reflection unit through an FPGA intelligent controller.

[0160] Specifically, in the passive beamforming step, based on the hybrid field channel modeling and the phase of all elements in the optimal IRS passive beamforming matrix, the incident signal of the IRS panel is passively beamformed so that the reflected signal is aligned with the scheduled user equipment.

[0161] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0162] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. An IRS-aided hybrid field beamforming simultaneous transmission and reception of energy system, characterized in that, include: Base stations, information users, energy users, and IRS systems; The base station's multi-antenna system controls the combination and transmission of information and energy signals based on beam scheduling variables provided by the FPGA intelligent controller of the IRS system; the IRS panel of the IRS system includes multiple reflection units; the FPGA intelligent controller of the IRS system is capable of passive beamforming, controlling the phase and amplitude of each reflection unit. The base station is located in the near-field region of the IRS panel, while the information user and energy user are located in the far-field region of the IRS panel.

2. The IRS-assisted hybrid field beamforming digital energy simultaneous transmission system according to claim 1, characterized in that, The multi-antenna system determines the scheduling variables of the information user, namely If the value is 0, then the corresponding information signal is suppressed, that is... ; Determine the scheduling variables for information users, i.e. If the value is 1, then the transmitting antenna of the multi-antenna system transmits information signals, i.e. ; The multi-antenna system determines the first The scheduling variables for each energy user, namely If the value is 0, then the corresponding energy signal is suppressed, i.e. Determine the scheduling variables of energy users, i.e. If the value is 1, then the transmitting antenna of the multi-antenna system transmits an energy signal, i.e. ; It is a constant.

3. The IRS-assisted hybrid field beamforming digital energy simultaneous transmission system according to claim 1, characterized in that, The near-field region and far-field region of the IRS panel are separated by Rayleigh distance, the expression for which is: in, This represents the Rayleigh distance; if the IRS distance range is less than... If the distance to the IRS is greater than 1, then it is the near-field region; if the distance to the IRS is greater Then it is the far-field region; D Indicates the array aperture of the IRS; Indicates wavelength.

4. The IRS-assisted hybrid field beamforming digital energy simultaneous transmission system according to claim 1, characterized in that, The reflected signal from the IRS panel is aligned with the equipment of information users and energy users.

5. An IRS-assisted hybrid field beamforming method for simultaneous digital and energy transfer, implemented based on any one of the IRS-assisted hybrid field beamforming systems of claims 1 to 4, characterized in that, include: Channel modeling steps: Establish a near-field channel model for the base station-IRS link and a far-field channel model for the IRS-user equipment link, and then obtain a hybrid channel field model; Optimization steps: Based on the hybrid channel field model, establish the problem of maximizing total collected power, jointly optimize and obtain the optimal active beam scheduling vector, the optimal IRS passive beamforming matrix and the optimal transmit power variable; Scheduling and allocation steps: The base station schedules the transmit beams of the transmit antenna array according to the optimal active beam scheduling vector; The base station is instructed to allocate transmission power to the information signal and the energy signal according to the optimal transmission power variable; The IRS system controls the phase of the reflection unit of each IRS panel according to the optimal IRS passive beamforming matrix.

6. The IRS-assisted hybrid field beamforming method for simultaneous transmission of energy according to claim 5, characterized in that, In the channel modeling step, the near-field channel model is the channel response matrix of the base station-IRS link, i.e., F; , Indicates all The space formed by complex-valued matrices, where, This refers to the number of transmitting antennas; This refers to the number of reflective units in the IRS panel. This represents the number of cells in the IRS panel along the x-axis. For IRS panel along Number of elements in the axial direction, ; , , ;F's There are 1 element, and the expression is: in, Describe the first of F One element, The base station's number The first antenna and the IRS Channel power gain between units Represents the imaginary unit. Indicates any , and , Indicates the ordinal number of the transmitting antenna. Let be the ordinal number of the reflective element of the IRS panel along the x-axis. The ordinal number of the IRS panel reflective element along the y-axis; Indicates the wavelength of the signal; The base station's number The first antenna and the IRS The distance between units; The far-field channel model is derived from the Rayleigh fading model, and its expression is: in, Indicates IRS-Information User Channel, Indicates IRS- One energy user channel, Indicates "distribution is", This is the path loss index for the IRS-User Equipment link. This represents the path gain at a reference distance of 1 meter. and These represent the distances between the IRS and the information user, respectively, and are related to the IRS and the [other information]. The distance between energy users Let CSCG be a random vector, and assume that K One energy user, =1,..., K ; I represents a unit vector; The expression for the hybrid field channel model is: in, This represents a hybrid field combination channel for the base station-IRS-information user link. Indicates base station-IRS-number Hybrid field combination channel for individual energy user links, This indicates the conjugate transpose. This represents the passive beamforming matrix of the IRS. , Indicates all The space formed by complex-valued matrices.

7. The IRS-assisted hybrid field beamforming method for simultaneous transmission of energy and signal according to claim 6, characterized in that, In the optimization step, the problem of maximizing the total collected power is P0, and its expression is: in, Represents the active beam scheduling vector. Indicates the first The set of transmitted power of energy signals. Represents the set of energy users. Indicates the first The radio frequency power collected by each EU, and Representing information signals and the first The transmission power of an energy signal, The binary scheduling variable representing IU. This represents the combined channel gain of the base station-IRS-information user link. Indicates the SINR threshold. Describing covariance, Indicates the first One energy user scheduling variable, Indicates the first step during IRS auxiliary signal beamforming. The reflection phase of each unit, Indicates the position coordinates of the IRS panel unit. This indicates the maximum transmit power of the base station.

8. The IRS-assisted hybrid field beamforming method for simultaneous transmission of energy and signal according to claim 7, characterized in that, The joint optimization includes: Step A1: Introduce auxiliary variables and integrate the optimization vectors to transform the problem of maximizing the total collected power, i.e., P0, into the optimization problem P1; Step A2: Based on the optimization problem P1, construct the corresponding Lagrangian function and apply the KKT conditions to solve the optimization vector, thereby obtaining the optimized active beam scheduling vector and transmit power variables; Step A3: The problem of maximizing the total collected power, i.e., P0, is transformed into an optimization problem P2 by optimizing the variables. Then, a semidefinite relaxation algorithm is applied to transform the optimization problem into an optimization problem P3. Finally, the optimization variables are solved by a successive convex approximation algorithm to optimize the IRS passive beamforming matrix. Step A4: Repeat steps A2 to A3 until the change in energy harvesting is less than a preset threshold, and obtain the optimal active beam scheduling vector, the optimal IRS passive beamforming matrix, and the optimal transmit power variable.

9. The IRS-assisted hybrid field beamforming method for simultaneous transmission of energy and signal according to claim 8, characterized in that, In step A1, the auxiliary variable is, and The expressions are respectively, and Optimize vector The expression is The expression for the optimization problem P1 is: in, Represents the auxiliary matrix. Indicates the number of rows. K A vector of all 1s with 1 column. Indicates the number of rows. A vector of all 1s with 1 column, symbol denoted by element-wise nonnegativity, c represents the transition vector; The auxiliary matrix The expression for the line is: Where h represents the hybrid field combination channel of the base station-IRS-information user link, Indicates base station-IRS-number Hybrid field combination channel for individual energy user links, Indicates base station-IRS-number K Hybrid field combination channel for individual energy user links, This indicates the conjugate transpose. Represents the first of the matrix OK, Represents the L2 norm; In step A2, the Lagrangian function corresponding to optimization problem P1 is expressed as: in, Represent the Lagrange function, , Both are Lagrange multipliers; KKT conditions K1~K8 are as follows: in, Indicates the optimization vector The partial derivatives are defined as follows: express From 1 to The position corresponding to the maximum element can be used to derive: when When the value is not 1, optimize the vector. The optimal solution is: when When the value is 1, optimize the vector. The optimal solution is: in, express The One element, Represents arbitrary; separate optimization vectors The optimal solution yields the optimal active beam scheduling vector, i.e. Optimal transmit power variable, i.e. and ; In step A3, optimization variables are introduced. The expression is This transforms the problem of maximizing the total collected power, P0, into an optimization problem P2; the expression for optimization problem P2 is: in, To maximize To optimize the objective function of the variables, the uniform energy conversion efficiency of all EU energy harvesters is required. Represents optimization variables , Represents optimization variables The One element; ,in This means placing the vectors on the diagonal to form a diagonal matrix; Set auxiliary variables , , and ,definition , Satisfying constraints and ,in, To represent the 'yi', we introduce slack variables. and The expressions are respectively and ,in, Represent the trace; thus, the optimization problem P2 is transformed into the optimization problem P3, expressed as: The optimal solution is obtained using software for solving convex optimization problems. Then, the IRS passive beamforming matrix is ​​obtained through matrix decomposition.

10. The IRS-assisted hybrid field beamforming method for simultaneous digital energy transmission according to claim 9, characterized in that, The optimization problem P3 is solved using the SCA algorithm. and The lower bound is then determined, and problem P3 is transformed into a convex optimization problem. The optimal passive beamforming matrix of the IRS is obtained through software iteration. The and The lower bound of the expression, from top to bottom, is as follows: In this context, the superscript * indicates complex conjugation, and Re represents the real part. and Indicates intermediate quantity; The and The mathematical expressions are as follows, from top to bottom: in, yes During the next iteration The value of .

Images