Dual-distributed IRS-assisted data and energy simultaneous transmission system and near-field beam forming method

Abstract

The invention provides a dual-distributed intelligent reflective surface (IRS)-assisted data and energy simultaneous transmission system and a near-field beam forming method. The system comprises a wireless access point, a dual-distributed IRS system, user equipment and an interference point. Wherein the wireless access point and the interference point are respectively provided with a single antenna, and the user equipment carries a multi-receiving antenna system. The method comprises the following steps: firstly, constructing a near-field channel model, then assisting a digital energy simultaneous transmission system to carry out joint near-field beam forming by virtue of a double-IRS system, and carrying out optimization design on a power division vector of a multi-receiving antenna system. According to the invention, the balance between the data transmission rate and the energy collection is effectively realized, the energy collection efficiency and the information transmission rate of the system are improved, the anti-interference capability is enhanced, technical breakthrough is realized in the aspects of green communication capability, information and energy cooperative transmission efficiency, system coverage range, flexibility and the like of a next-generation communication network, and the method is suitable for popularization and application. The important support is provided for the development.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication, and in particular, to a dual-distributed IRS-assisted simultaneous wireless information and power transfer system and a near-field beamforming method. Background Art

[0002] As the sixth-generation (6G) wireless communication technology moves towards the goals of ultra-high speed and ultra-low latency, sustainable energy supply and green and low-carbon development have become key indicators. Against this background, simultaneous wireless information and power transfer (SWIPT) has become an important support for 6G communication. However, traditional SWIPT systems face the problem of severe propagation loss between the transmitter and the receiver, resulting in a sharp reduction in the information-energy transmission area with the increase of distance, which greatly limits the system performance.

[0003] To break through this bottleneck, intelligent reflecting surface (IRS) has been introduced into the SWIPT system. By regulating the phase and amplitude of the incident signal, the intelligent reconstruction of the channel is realized, effectively enhancing the signal strength and expanding the coverage. However, existing research mainly focuses on the optimization of a single IRS. In the actual complex communication environment, it is difficult to cope with the challenges brought by interference problems to high-quality information transmission and efficient energy harvesting. Although the dual-IRS system shows higher performance potential compared with the single-IRS system, there are huge technical difficulties in the trade-off between information transmission and energy harvesting in its cooperative optimization.

[0004] In addition, when the IRS is deployed near the transmitter or the receiver to improve the signal-to-noise ratio, as the distance between the IRS and the transceiver decreases or the aperture of the IRS increases, its electromagnetic radiation characteristics change from a far-field plane wavefront to a near-field spherical wavefront. The traditional passive beamforming design based on the far-field assumption fails in the near-field environment, and it is necessary to optimize the near-field passive beamforming of the IRS in the distance domain to ensure the performance of the SWIPT system.

[0005] Through the retrieval of patent documents, it is found that the invention patent with the publication number CN118784037A discloses a beamforming method and system for a digital energy cooperative transmission system based on holographic MMO, including the following steps: determining the digital energy integrated holographic MIMO transmitter model; determining the electromagnetic channel model; determining the holographic MIMO information receiver model; determining the holographic MIMO energy receiver model; determining the final optimization problem according to the energy consumption requirements of the energy users and the power constraint of the holographic MIMO transmitter; solving the holographic MIMO beamforming according to the expression of the optimization objective and its constraint conditions. This patent does not adopt a dual-distributed IRS structure, does not construct a near-field channel model, and does not combine the joint beamforming of the user equipment and the IRS and the optimization of the power splitting vector, so it is difficult to improve the performance of simultaneous wireless information and power transfer.

[0006] In summary, in view of the problems of the above-mentioned existing technologies, researching a dual-distributed IRS-assisted simultaneous wireless information and power transfer (SWIPT) system and a near-field beamforming method has become a crucial task that urgently needs to be solved at present. Summary of the Invention

[0007] Aiming at the deficiencies in the existing technologies, the purpose of the present invention is to provide a dual-distributed IRS-assisted SWIPT system and a near-field beamforming method.

[0008] A dual-distributed IRS-assisted SWIPT system according to the present invention includes: a wireless access point, a dual-distributed IRS system, a user equipment, and an interference point.

[0009] Both the wireless access point and the interference point are equipped with a single antenna.

[0010] The dual-distributed IRS system includes multiple IRS panels and multiple corresponding FPGA intelligent controllers. Each IRS panel includes multiple reflection units.

[0011] The user equipment is equipped with a multi-receive antenna system, which includes a receive antenna array, multiple power splitters, an energy harvester, and an information decoder. The receive antenna array is used to receive signals from the wireless access point and the interference point. Each power splitter is connected to a corresponding receive antenna, and the power splitter applies a power splitting factor to split the signal to the energy harvester and the information decoder for energy harvesting and information decoding.

[0012] Both the wireless access point and the user equipment are located within the near-field region of the dual-distributed IRS.

[0013] Preferably, the dual-distributed IRS system includes two IRS panels and two corresponding FPGA intelligent controllers, so that the signals reflected by the IRS panels are aligned with the user equipment.

[0014] Preferably, the Rayleigh distance is calculated through the operating frequency and array aperture of the IRS panel, and the near-field region is determined according to the Rayleigh distance, so that the wireless access point and the user equipment are located within the near-field region.

[0015] Preferably, the near-field region is determined through the following steps: assuming that the SWIPT system includes M receive antennas, and the two IRS panels are denoted as IRS1 and IRS2 respectively, located on the x-z plane of the three-dimensional Cartesian coordinate system, and are respectively composed of and reflection units, where N a is the total number of units of IRS1, N b is the total number of units of IRS2, and respectively represent the number of units of IRS1 panel along the x-axis and z-axis, and respectively represent the number of cells of the IRS2 panel along the x-axis and z-axis. The subscripts a and b refer to IRS1 and IRS2 respectively. The area of each reflecting cell of the IRS panel is A, and the cell spacing is ε. For the uniform planar array of IRS1, the array aperture is calculated as The array aperture of IRS2 is D b , similar to D a Similar. Denote the operating frequency as f0, then the wavelength of the signal is λ0 = c / f0, where c = 3×10 8 m / s represents the speed of light. The near-field regions of IRS1 and IRS2 are divided by the Rayleigh distances and .

[0016] The present invention also provides a dual-distributed IRS-assisted near-field beamforming method, which adopts the above-mentioned dual-distributed IRS-assisted simultaneous wireless information and power transfer system, and includes the following steps:

[0017] Channel modeling step: Based on the projected-aperture non-uniform spherical wave model, establish a near-field channel model for the wireless access point-dual IRS panel and dual IRS panel-user equipment links;

[0018] Optimization step: Through joint optimization, obtain the optimal independent power splitting vector, the optimal active beamforming variable, and the optimal dual IRS passive beamforming matrix;

[0019] Independent power splitting step: Based on the optimal independent power splitting vector, the power splitter of the user equipment independently splits the signals of each receiving antenna;

[0020] Active beamforming step: Based on the optimal active beamforming vector, the user equipment performs active beamforming on the receiving antenna array to control the amplitude and phase of each antenna;

[0021] Passive beamforming step: Based on the optimal dual IRS passive beamforming matrix, the dual IRS panel controls the phase of each reflecting cell through the FPGA intelligent controller.

[0022] Preferably, the channel modeling step includes the following sub-steps:

[0023] Step X1, set the wireless access point at the origin of the three-dimensional Cartesian coordinate system, i.e., p A =(0,0,0), and the centers of the IRS1 and IRS2 panels are located at and and are respectively the coordinates of the center of the IRS1 panel along the x-axis and y-axis, and are the coordinates of the center of the IRS2 panel along the x-axis and y-axis, respectively. Then, the positions of the (n x ,n z )th cells of IRS1 and IRS2 are represented as and respectively. Where The distances between the (n x ,n z )th cells of IRS1 and IRS2 and the wireless access point are represented as:

[0024]

[0025] Where is a middle parameter;

[0026] Step X2: Through three-dimensional channel modeling, based on the projected aperture non-uniform spherical wave model, the channel power gain between the wireless access point and the th cell of IRS1 is represented as:

[0027]

[0028] Where u a represents the normal vector of each IRS1 cell placed on the x-z plane, that is, u a =(0, -1, 0). Let be represented as the channel response vector of the wireless access point-IRS1 link, represents the space composed of all N a ×1 complex-valued matrices. Where

[0029]

[0030] Where represents any and

[0031] The channel power gain between the wireless access point and the (n x ,n z )th cell of IRS2 is represented as

[0032]

[0033] The channel response vector of the wireless access point-IRS2 link has elements given by the following formula

[0034]

[0035] Where represents all N bThe space composed of ×1 complex-valued matrices, denote any and

[0036] Step X3, denote the antenna spacing of the receiving antenna array of the user equipment as d, set the linear array to be placed along the y-axis direction, and the starting point is Then the position of the m-th antenna of the user is where m = 1, 2,..., M, and the distance between the m-th antenna of the user and the th unit of IRS1 is

[0037]

[0038] The channel power gain between the m-th antenna of the user and the th unit of IRS1 is expressed as

[0039]

[0040] Accordingly, the channel response vector of the IRS1-user link is expressed as Consisting of the following elements

[0041]

[0042] where j represents the imaginary unit, denote any and m.

[0043] The channel power gain between the m-th antenna of the user and the th unit of IRS2 is expressed as:

[0044]

[0045] The channel response vector of the IRS2-user link is expressed as Consisting of the following elements:

[0046]

[0047] where j represents the imaginary unit, denote any and m.

[0048] Step X4, denote and as the passive beamforming matrices of IRS1 and IRS2 respectively, where, and represent the n x , n z) The reflection phase of the unit. The total combined channel of the wireless access point - dual IRS - user equipment link in the near - field model is expressed as

[0049] g(l)=G a Θ a h a +G b Θ b h b ,

[0050] where g(l)=[g1(l),g2(l),...,g M (l)] T . l is a set representing the coordinate information of the dual IRS and the user equipment.

[0051] Preferably, the optimization step includes the following sub - steps:

[0052] Step Y1, construct a received signal model. The power splitter performs power splitting using a power splitting factor for energy harvesting and information decoding;

[0053] Step Y2, jointly optimize the independent power splitting vector, the active beamforming vector, and the dual IRS passive beamforming matrix to obtain the optimal independent power splitting vector, the optimal active beamforming variable, and the optimal dual IRS passive beamforming matrix.

[0054] Preferably, step Y1 includes the following sub - steps:

[0055] Step Y1.1, assume that the channel from the interference point to the user equipment is statistically known at the user end, expressed as where f = [f1,f2,...,f M T , following the Rayleigh fading channel model. The transmit powers of the wireless access point and the interference point are denoted as P t and P in , respectively. Then the signal received at the user equipment is expressed as:

[0056]

[0057] where s1 and s2 are the normalized transmit signals at the wireless access point and the interference point, respectively, is the antenna noise at the user equipment, where, represents a circularly symmetric complex Gaussian (CSCG) random vector with mean 0 and covariance matrix , and "~" means "distributed as";

[0058] Step Y1.2, for the m - th receiving antenna of the user equipment, its power splitter splits ρ of the received signal power m ​(0 ≤ ρ m ≤ 1) is allocated to the information decoder, and 1 - ρ m of the signal power is allocated to the energy harvester. The independent power splitting vector of the power splitter is denoted as ρ = [ρ1, ρ2,..., ρ M T , where ρ m is the m-th element of the independent power splitting vector. Then the total energy obtained by the energy harvester is expressed as:

[0059]

[0060] In the formula, η ∈ (0, 1) represents the energy conversion efficiency of the energy harvester; g m represents the m-th element of the total combined channel g(l), and f m represents the m-th element of the interference channel f.

[0061] The signal split to the information decoder is expressed as

[0062]

[0063] where Λ = diag(ρ) is the independent power splitting matrix, is the additional noise introduced by the information decoder, is the active beamforming vector at the receiver, where, represents a circularly symmetric complex Gaussian (CSCG) random vector with mean 0 and covariance matrix δ 2 I, and "~" means "distributed as".

[0064] The signal-to-interference-plus-noise ratio (SINR) of the user is expressed as:

[0065]

[0066] Preferably, step Y2 includes the following sub-steps:

[0067] Step Y2.1, set the mathematical formulation of the original optimization problem as follows:

[0068]

[0069] 0 ≤ ρ m ≤ 1,

[0070]

[0071] where γ0 represents the SINR threshold to ensure the QoS requirements of the user. The user has a non-zero SINR threshold, and γ0 > 0;

[0072] Step Y2.2, use the least mean square error algorithm to solve the active beamforming vector w;​

[0073] Step Y2.3: Construct the Lagrangian function and apply the KKT conditions, and optimize the power splitting vector ρ through fixed-point iteration;

[0074] Step Y2.4: Convert the optimization problem into a difference of convex (DC) programming problem, and solve the dual IRS passive beamforming matrix {Θ a , Θ b} through convex optimization;

[0075] Step Y2.5: Repeat Steps Y2.2 to Y2.4 until the change in the energy harvesting amount is less than a preset threshold, and obtain the optimal dual IRS passive beamforming matrix, the optimal independent power splitting vector, and the optimal active beamforming variables.

[0076] Preferably, in the independent power splitting step, based on the near-field channel modeling and the optimal independent power splitting vector, the optimal power splitting of each receiving antenna is realized to balance the trade-off between the data transmission rate and the energy harvesting;

[0077] In the active beamforming step, based on the near-field channel modeling and the optimal active beamforming variables, the user equipment performs receive beamforming on the multi-antenna signal through an information decoder to obtain the multi-antenna signal after receive beamforming;

[0078] In the passive beamforming step, based on the near-field channel modeling and the optimal dual IRS passive beamforming matrix, passive beamforming is performed on the incident signal of the dual IRS panel to align the reflected signal with the user equipment.

[0079] Compared with the prior art, the present invention has the following beneficial effects:

[0080] 1. The present invention adopts a non-uniform spherical wave model with a projected aperture to perform refined near-field channel modeling on the dual distributed IRS-assisted simultaneous wireless information and power transfer system, accurately characterizing the channel propagation characteristics in the near-field environment, and providing a solid theoretical basis for realizing high-precision beamforming and system performance optimization.

[0081] 2. Based on the established near-field channel model, the present invention combines the dual distributed IRS with the multi-receive antenna system to realize the collaborative optimization of active and passive beamforming, effectively alleviating the interference problem faced by the system and improving the system transmission efficiency.

[0082] 3. The system architecture of the present invention is simple, has good deployability, and has obvious advantages in terms of hardware cost and energy consumption. Compared with traditional antenna arrays and other signal enhancement technologies, the IRS panel has low hardware complexity and small cost overhead, and can efficiently regulate and enhance signals, making it suitable for the construction of the next-generation high-energy efficiency wireless communication system.

[0083] 4. The present invention integrates a dual-distributed IRS system with a wireless access point transmitter, reducing the propagation loss of the reflection link through near-field deployment. The dual-distributed IRS system has the characteristic of low power consumption and is a new type of green data-energy co-transmission assisted system. Through the collaborative optimization of the system, the present invention significantly reduces the overall energy consumption while ensuring the communication performance, meeting the development requirements of high energy efficiency and low carbonization in the new generation of communication networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Other features, objects, and advantages of the present invention will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0085] Figure 1 It is a data-energy co-transmission system assisted by a dual-distributed IRS in an embodiment of the present invention;

[0086] Figure 2 It is the total collected energy varying with the user service quality ratio under different architectures in an embodiment of the present invention;

[0087] Figure 3 It is the total collected energy varying with the transmit power of the interference point under different architectures in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0088] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those of ordinary skill in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0089] The present invention proposes a dual-distributed intelligent reflecting surface (IRS)-assisted data-energy co-transmission system and a near-field beamforming method. The system includes a wireless access point, a dual-distributed IRS system, a user equipment, and an interference point. Among them, both the wireless access point and the interference point are configured with a single antenna, and the user equipment is equipped with a multi-receive antenna system. The method includes first constructing a near-field channel model, and then using the dual IRS system to assist the data-energy co-transmission system to carry out joint near-field beamforming and optimize the power splitting vector of the multi-receive antenna system. The present invention effectively realizes the balance between the data transmission rate and energy harvesting, improves the energy harvesting efficiency and information transmission rate of the system, and enhances the anti-interference ability, achieving technological breakthroughs in aspects such as the green communication ability, information and energy co-transmission efficiency, and system coverage and flexibility of the next-generation communication network, providing important support for its development.

[0090] Embodiment 1:

[0091] Figure 1This is the dual - distributed IRS - assisted simultaneous wireless information and power transfer (SWIPT) system in the embodiments of the present invention.

[0092] As Figure 1 shown, this embodiment provides a dual - distributed IRS - assisted SWIPT system, including: a wireless access point (transmitter), a dual - distributed IRS system, a user equipment, and an interference point.

[0093] Both the wireless access point and the interference point are equipped with a single antenna.

[0094] The dual - distributed IRS system includes multiple IRS panels and multiple corresponding FPGA intelligent controllers. The IRS panel includes multiple reflection units.

[0095] Specifically, the dual - distributed IRS system includes two relatively independent IRS panels and two corresponding FPGA intelligent controllers. The two IRS panels perform passive beamforming through the corresponding FPGA intelligent controllers respectively, controlling the phase and amplitude of each reflection unit to align the signals reflected by the IRS panels with the user equipment.

[0096] The user equipment is equipped with a multi - receive - antenna system, which includes a receive antenna array, multiple power splitters, an energy harvester, and an information decoder. The receive antenna array is used to receive the signals from the wireless access point and the interference point. Each power splitter is connected to the corresponding receive antenna, and the power splitter applies a power splitting factor to split the signal to the energy harvester and the information decoder for energy harvesting and information decoding.

[0097] In this embodiment, the receive antenna array is a uniform linear antenna array.

[0098] The information decoder performs active beamforming on the receive antenna array, controlling the amplitude and phase of each antenna to detect the received signal.

[0099] Both the wireless access point and the user equipment are located in the near - field region of the dual - distributed IRS. The direct - link between the wireless access point and the user equipment is weak. By deploying the dual - distributed IRS, it is ensured that there is a line - of - sight path between the wireless access point and the user equipment, thereby enhancing the quality of the communication link.

[0100] Specifically, the Rayleigh distance is calculated through the operating frequency and array aperture of the IRS panel, and the near - field region is determined according to the Rayleigh distance, so that the wireless access point and the user equipment are located in the near - field region.

[0101] Further, the near - field region is determined through the following steps: assume that the SWIPT system includes M receive antennas. The two IRS panels are denoted as IRS1 and IRS2 respectively, located on the x - z plane of the three - dimensional Cartesian coordinate system, and are respectively composed of and consists of N reflection units, where N a is the total number of units of IRS1, and N b is the total number of units of IRS2. and represent the number of units of IRS1 panel along the x-axis and z-axis respectively, and represent the number of units of IRS2 panel along the x-axis and z-axis respectively. Subscripts a and b refer to IRS1 and IRS2 respectively. The area of each reflection unit of the IRS panel is A, and the unit spacing is ε. For the uniform planar array of IRS1, the array aperture is calculated as The array aperture of IRS2 is D b , similar to D a . Denote the operating frequency as f0, then the wavelength of the signal is λ0 = c / f0, where c = 3×10 8 m / s represents the speed of light. The near-field regions of IRS1 and IRS2 are divided by the Rayleigh distances and .

[0102] The system performs joint near-field beamforming through a dual-distributed IRS system-assisted energy and data transmission system with interference disruption. The receiving-end multi-antenna system performs independent power splitting, providing a trade-off between data transmission rate and energy harvesting, while improving the system's energy harvesting efficiency, information transmission rate, and anti-interference ability.

[0103] In the embodiments of the present invention, with the maximization of the harvested power as the performance index, and subject to the user service quality requirements, power splitting ability, and reflection ability of the reflection units, based on near-field channel modeling, a joint near-field beamforming scheme design is carried out for the novel dual-distributed IRS-assisted energy and data transmission system.

[0104] Compared with the traditional energy and data transmission system, the dual-distributed IRS-assisted energy and data transmission system of the present invention does not add a large number of additional RF links and complex signal processing units, and is a design that achieves better performance with lower cost and power consumption. Through the design of the active and passive beamforming matrices jointly by the user equipment and the dual-distributed IRS, the harvested power of the present invention is significantly improved.

[0105] Compared with the single IRS configuration, the dual-distributed IRS system shows higher superiority in terms of coverage and communication performance. Through the passive beamforming of the dual-distributed IRS, the energy harvesting efficiency, information transmission rate, and anti-interference ability of the energy and data transmission system are improved.

[0106] In the dual - distributed IRS - assisted digital - energy co - transmission system, the user equipment needs to perform digital beamforming on the receiving antenna array to control the amplitude and phase of each antenna. The power splitter distributes the signals received by each antenna according to independent power splitting factors to control the received power ratio of the control - information decoder and the energy harvester. The IRS panel performs passive beamforming through an FPGA intelligent controller to control the phase of each reflecting element.

[0107] Dual - distributed IRS - assisted digital - energy co - transmission system: Joint beamforming design of the user equipment and the IRS and optimization of the independent power splitting vector are considered together. The user equipment generates corresponding control signals at the antenna array, the power splitter generates corresponding independent power splitting factors, and the IRS unit generates corresponding control signals at the intelligent controller.

[0108] Generation of the independent power splitting vector of the power splitter: Considering the received signal of the user - equipment antenna array as \(y\), the independent power vectors of each power splitter as \(\rho\), and \(\Lambda=\text{diag}(\rho)\) as the independent power splitting matrix, the power ratio allocated to the information decoder is \(\rho\), and the power ratio allocated to the energy harvester is \(1 - \rho\). Then the signal received by the information decoder is \(\Lambda\) 1 / 2 y.

[0109] Generation of the active beamforming control signal by the user equipment: Considering the signal split by the user - equipment antenna array to the information decoder as \(y'\), the received signal after the user equipment performs active beamforming design is \(w\) H y', which includes the design of amplitude and phase in beamforming.

[0110] Generation of the passive beamforming control signal by the dual - distributed IRS: The dual IRS performs reflection beamforming on the incident signal, and controls the dual IRS coefficient matrix as \(\{\Theta\) a ,\(\Theta\) b \} to perform the phase design of all elements so that the reflected signal can be aligned with the user.

[0111] Near - field beamforming scheme in the dual - distributed IRS transceiver system: Based on the near - field channel model, with maximizing the harvested power as the performance index, by constructing an optimization problem constrained by the user's quality - of - service requirements, power - splitting ability, and reflection ability of the reflecting elements, the present invention realizes the novel dual - distributed IRS - assisted digital - energy co - transmission system and the near - field beamforming method.

[0112] Design of Near-Field Beamforming Scheme for Dual-Distributed IRS-Assisted Simultaneous Wireless Information and Power Transfer: The constructed optimization problem of maximizing the harvested power is a non-convex optimization problem, and the global optimal solution cannot be directly obtained. In the following, based on the Lagrangian dual method and the convex difference programming algorithm, the present invention jointly realizes active and passive beamforming by combining the dual-distributed IRS and the multi-receive antenna system, alleviates interference, and improves the transmission efficiency. By alternately optimizing all the optimization variables, a sub-optimal solution with high quality is obtained.

[0113] Based on near-field channel modeling, the dual-distributed IRS system assists the interference-damaged simultaneous wireless information and power transfer system to jointly perform near-field beamforming to maximize the system's harvested energy, and obtain the optimal beamforming and power splitting schemes.

[0114] The user equipment's multi-receive antenna system performs independent power splitting, which can provide a more favorable trade-off between data transmission rate and energy harvesting, while improving the system's energy harvesting efficiency, information transmission rate, and anti-interference ability.

[0115] To meet the requirements of the next-generation wireless network for network coverage, energy sustainability, and communication reliability, the present invention provides a novel design of a dual-distributed IRS-assisted simultaneous wireless information and power transfer system.

[0116] According to the dual-distributed IRS-assisted simultaneous wireless information and power transfer system provided by the present invention, based on the near-field channel model, a joint design scheme of the user equipment antenna array receiving beamforming, independent power allocation, and dual-IRS beamforming is proposed.

[0117] The user equipment needs to consider the beamforming design when decoding the signal, and realizes active receiving beamforming by controlling the amplitude and phase of each antenna. The power splitter needs to consider the trade-off between information transmission and energy harvesting to achieve the optimal performance of the system. The IRS needs to control the phase of each reflecting unit when assisting the incident signal to realize passive transmitting beamforming.

[0118] As a revolutionary technology, IRS is expected to address the challenges of performance improvement and energy efficiency optimization in the development of simultaneous wireless information and power transfer (SWIPT) systems. For wireless communication systems, IRS enables programmable reconfiguration of the channel, providing sufficient multipath components to effectively improve spatial multiplexing efficiency and enhance system capacity. In addition, IRS can also solve the problem of insufficient coverage caused by non-line-of-sight channels in energy transfer. Specifically, relying on its passive beamforming function, IRS can accurately direct and reflect signals to target users, improving signal focusing ability and intensity. With a large number of controllable units, IRS also has the ability to flexibly regulate the multipath structure, significantly expanding the spatial degrees of freedom of communication systems. In addition, IRS does not require high-power-consuming components such as radio frequency chains, and its passive characteristics significantly reduce the deployment cost of the system and have good compatibility, enabling seamless integration into existing SWIPT systems. Compared with a single IRS architecture, the collaborative work of two IRSs brings higher reconfigurability, which can further improve beam control accuracy and overall system performance, and effectively overcome the problem of limited coverage of a single IRS, thereby enhancing system flexibility and scalability. Therefore, the introduction of a dual-distributed IRS structure can not only efficiently improve the energy harvesting and information transmission performance of SWIPT systems, but also demonstrate important application prospects and practical feasibility in next-generation wireless networks on the premise of ensuring low-cost deployment.

[0119] Figure 2 The total harvested energy in different architectures in the embodiments of the present invention changes with the user quality of service ratio. Figure 3 The total harvested energy in different architectures in the embodiments of the present invention changes with the transmit power of the interference point.

[0120] Figure 2 、 3 It represents the total system harvested energy gain of the architecture in this embodiment compared with other architectures. Under the conditions of changing user quality of service and transmit power of the interference point, the proposed architecture always achieves the highest total harvested energy.

[0121] Embodiment 2:

[0122] This embodiment provides a near-field beamforming method assisted by a dual-distributed IRS, which is implemented on the dual-distributed IRS-assisted SWIPT system in the above embodiment.

[0123] Specifically, the near-field beamforming method assisted by the dual-distributed IRS includes the following steps:

[0124] Channel modeling step: In three-dimensional space, based on the projected aperture non-uniform spherical wave model, establish a near-field channel model for the wireless access point-dual IRS panel and dual IRS panel-user equipment links to accurately describe the near-field channel characteristics.

[0125] Specifically, the channel modeling step includes the following sub-steps:

[0126] Step X1, set the wireless access point at the origin of the three-dimensional Cartesian coordinate system, i.e., p A =(0, 0, 0), and the centers of the IRS1 and IRS2 panels are located at and and are the coordinates of the center of the IRS1 panel along the x-axis and y-axis, and are the coordinates of the center of the IRS2 panel along the x-axis and y-axis. Then, the positions of the (n x , n z )-th cells of the IRS1 and IRS2 panels are respectively expressed as and where, set The distances between the (n x , n z )-th cells of the IRS1 and IRS2 and the wireless access point are respectively expressed as:

[0127]

[0128] where, set as an intermediate parameter;

[0129] Step X2, through three-dimensional channel modeling, based on the projected aperture non-uniform spherical wave model, the channel power gain between the wireless access point and the -th cell of the IRS1 is expressed as:

[0130]

[0131] where, u a represents the normal vector of each IRS1 cell placed on the x-z plane, i.e., u a =(0, -1, 0). Denote as the channel response vector of the wireless access point - IRS1 link, represents the space composed of all N a ×1 complex-valued matrices. Among them

[0132]

[0133] where, represents any and

[0134] The channel power gain between the wireless access point and the (n x , n z )-th cell of the IRS2 is expressed as

[0135]

[0136] Channel response vector of the wireless access point - IRS2 link The elements of are given by

[0137]

[0138] where represents the space composed of all N b × 1 complex-valued matrices, represents any and

[0139] In step X3, denote the antenna spacing of the receiving antenna array of the user equipment as d, and set the linear array to be placed along the y-axis direction with the starting point at Then the position of the m-th antenna of the user is where m = 1, 2,..., M, and the distance between the m-th antenna of the user and the th unit of IRS1 is

[0140]

[0141] The channel power gain between the m-th antenna of the user and the th unit of IRS1 is expressed as

[0142]

[0143] Accordingly, the channel response vector of the IRS1 - user link is expressed as consists of the following elements

[0144]

[0145] where j represents the imaginary unit, represents any and m.

[0146] The channel power gain between the m-th antenna of the user and the th unit of IRS2 is expressed as

[0147]

[0148] The channel response vector of the IRS2 - user link is expressed as consists of the following elements

[0149]

[0150] where j represents the imaginary unit, represents any and m.

[0151] Step X4, take and as the passive beamforming matrices denoted as IRS1 and IRS2 respectively, where and represent the reflection phases of the (n x , n z )-th element during the IRS1 and IRS2 assisted signal beamforming respectively.

[0152] The total combined channel of the wireless access point - dual IRS - user equipment link in the near - field model is expressed as

[0153] g(l)=G a Θ a h a +G b Θ b h b ,

[0154] where g(l)=[g1(l), g2(l),..., g M (l)] T . l is a set representing the coordinate information of the dual IRS and the user equipment.

[0155] Optimization steps: Through joint optimization, obtain the optimal independent power splitting vector, the optimal active beamforming variable, and the optimal dual IRS passive beamforming matrix;

[0156] Specifically, the optimization steps include the following sub - steps:

[0157] Step Y1, construct the received signal model, and the power splitter performs power splitting using the power splitting factor for energy harvesting and information decoding;

[0158] Specifically, step Y1 includes the following sub - steps:

[0159] Step Y1.1, assume that the channel from the interference point to the user equipment is statistically known at the user side, expressed as where f = [f1, f2,..., f M T , following the Rayleigh fading channel model, the transmit powers of the wireless access point and the interference point are denoted as P t and P in respectively, then the signal received at the user equipment is expressed as

[0160]

[0161] ​where \(s_1\) and \(s_2\) are the normalized transmitted signals at the wireless access point and the interference point respectively, is the antenna noise at the user equipment, where, denotes a circularly symmetric complex Gaussian (CSCG) random vector with mean 0 and covariance matrix , and “~” means “distributed as”;

[0162] Step Y1.2, for the \(m\)th receiving antenna of the user equipment, its power splitter allocates a portion \(\rho\) m (0 ≤ \(\rho\) m ≤ 1) of the received signal power to the information decoder and a portion 1 - \(\rho\) m of the signal power to the energy harvester. The independent power splitting vector of the power splitter is denoted as \(\rho = [\rho_1,\rho_2,...,\rho\) M T , and \(\rho\) m is the \(m\)th element of the independent power splitting vector. Then the total energy obtained by the energy harvester is expressed as:

[0163]

[0164] where \(\eta\in(0,1)\) represents the energy conversion efficiency of the energy harvester; \(g\) m represents the \(m\)th element of the total combined channel \(g(l)\), and \(f\) m represents the \(m\)th element of the interference channel \(f\).

[0165] Normalized time, the harvested energy is the harvested power. The signal split to the information decoder is represented as

[0166]

[0167] where \(\Lambda=\text{diag}(\rho)\) is the independent power splitting matrix, is the additional noise introduced by the information decoder, is the active beamforming vector at the receiver, where, denotes a circularly symmetric complex Gaussian (CSCG) random vector with mean 0 and covariance matrix \(\delta\) 2 \(I\), and “~” means “distributed as”.

[0168] The signal-to-interference-plus-noise ratio (SINR) of the user is expressed as:

[0169]

[0170] Step Y2, by jointly optimizing the independent power splitting vector \(\rho\), the active beamforming vector \(w\) and the double IRS passive beamforming matrix \(\{\Theta\) a ,\(\Theta\) b ​}, to maximize the harvested energy and obtain the optimal independent power splitting vector, optimal active beamforming variables, and optimal dual-IRS passive beamforming matrix. Specifically, step Y2 includes the following sub-steps:

[0171] Step Y2.1, set the mathematical formulation of the original optimization problem as follows:

[0172]

[0173] 0 ≤ ρ m ≤ 1,

[0174]

[0175] where γ0 represents the SINR threshold to ensure the QoS requirements of the user. The user has a non-zero SINR threshold, so γ0 > 0;

[0176] In this embodiment, when the original optimization problem is a non-convex optimization problem regarding the independent power splitting vector, active beamforming vector, and dual-IRS passive beamforming matrix, based on the Lagrangian dual method and the difference of convex (DC) programming algorithm, the dual-IRS passive beamforming matrix, independent power splitting vector, and active beamforming variables are alternately optimized and solved. Under the constraints of the preset user quality of service, power splitting ability, and reflection ability of the reflection unit, an optimization problem of maximizing the harvested energy of the user equipment is constructed, and the non-convex problem is transformed into a convex problem to obtain the optimal dual-IRS passive beamforming matrix, independent power splitting vector, and active beamforming variables, realizing efficient near-field beamforming.

[0177] Step Y2.2, use the minimum mean square error algorithm to solve the active beamforming vector w.

[0178] Specifically, when alternately solving for w, the minimum mean square error (MMSE) is applied to the active beamforming vector of the user equipment, that is where The SINR is re-expressed as

[0179]

[0180] Set and as intermediate parameters, and the signal-to-interference-plus-noise ratio is further expressed as where is an intermediate parameter, represents the conjugate transpose matrix of represents the inverse matrix of

[0181] Step Y2.3: Construct the Lagrangian function and apply the KKT conditions, and optimize the power splitting vector ρ through fixed-point iteration.

[0182] Specifically, when alternately solving for ρ, it is observed that the user's SINR at this time is a concave function of the independent power splitting vector ρ, and the first optimization problem P1 is transformed into

[0183]

[0184] This problem is convex, so the duality gap is zero. Applying the Lagrangian duality method, its optimal solution is obtained. The Lagrangian function corresponding to this problem is expressed as

[0185]

[0186] where λ is the Lagrange multiplier. Then, the Karush-Kuhn-Tucker (KKT) conditions are used to study the optimal solution of the dual problem. The KKT conditions are expressed as

[0187] K3: λ ≥ 0.

[0188] For the K1 condition, it is expanded as

[0189]

[0190] By examining the expansion of the K1 condition and the K3 condition, it is easy to obtain λ > 0. Therefore, substituting into the K2 condition, we have Optimal ρ m should satisfy the KKT conditions, which are expressed as

[0191]

[0192] It can be seen from this that since the right side of the above equation also contains ρ m , this equation is a non-closed form expression, and fixed-point iteration is used to update ρ m . Then, for the Lagrange multiplier λ, the subgradient method is applied to derive the optimal λ * . Finally, ρ m is updated again until convergence and the optimal ρ is obtained.

[0193] Step Y2.4: Transform the optimization problem into a difference-of-convex (DC) programming problem, and solve the dual IRS passive beamforming matrices {Θ a , Θ b} through convex optimization;

[0194] Specifically, when alternately solving for {Θ a , Θ b}, the second optimization problem P2 is transformed into

[0195]

[0196] Obviously, this optimization problem is non-convex. Let Then for and the constraints are equivalent to and Let Then ||G a Θ a h a +G b Θ b h b || 2 is re-expressed as ||Φ a u a +Φ b u b || 2 . Introduce auxiliary variables:

[0197]

[0198] Therefore, there is Note Define It needs to satisfy and In addition, let and Then is re-expressed as and is re-expressed as ||Υ a u a +Υ b u b || 2 . Continue to introduce auxiliary variables:

[0199]

[0200] Thus, is re-expressed as ||Υ a u a +Υ b u b || 2 is re-expressed as Note Therefore, the second optimization problem P2 is transformed into the second optimization problem P2.1:

[0201]

[0202] where N = N a +N b, representing the total number of dual IRS reflection elements. Due to the rank-1 constraint, the problem remains non-convex, and the difference of convex (DC) programming is applied to transform the non-convex rank-1 constraint. The core of DC programming is to linearize the concave term, is equivalent to The term is concave and is transformed into where is the solution obtained in the (t - 1)-th iteration, is the subgradient of the spectral norm in the (t - 1)-th iteration. Introducing the penalty factor μ, the second optimization problem P2.1 is transformed into the second optimization problem P2.2:

[0203]

[0204] This problem is a convex problem, and the optimal is obtained by solving it with the software for convex optimization problems. Then, the optimal {Θ a , Θ b} is obtained through matrix factorization.

[0205] Step Y2.5, repeat steps Y2.2 to Y2.4 until the change in the energy harvesting amount is less than the preset threshold, and the optimal independent power splitting vector, the optimal active beamforming variable, and the optimal dual IRS passive beamforming matrix are obtained.

[0206] Independent power splitting step: Based on the optimal independent power splitting vector, the power splitter of the user equipment independently splits the signals of each receiving antenna. The power splitters of each receiving antenna are independent of each other to achieve simultaneous data and energy transmission.

[0207] Specifically, in the independent power splitting step, based on the near-field channel modeling and the optimal independent power splitting vector, the optimal power splitting of each receiving antenna is achieved, balancing the trade-off between the data transmission rate and energy harvesting.

[0208] Active beamforming step: Based on the optimal active beamforming vector, the user equipment performs active beamforming on the receiving antenna array, controlling the amplitude and phase of each antenna;

[0209] Specifically, in the active beamforming step, based on the near-field channel modeling and the optimal active beamforming variable, the user equipment performs receive beamforming on the multi-antenna signal through the information decoder to obtain the multi-antenna signal after receive beamforming.

[0210] Passive beamforming step: Based on the optimal dual IRS passive beamforming matrix, the dual IRS panel controls the phase of each reflection unit through the FPGA intelligent controller.

[0211] Specifically, in the passive beamforming step, based on the near-field channel modeling and the phases of all elements in the optimal dual-IRS passive beamforming matrix, passive beamforming is performed on the incident signals of the dual-IRS panel so that the reflected signals are aligned with the user equipment.

[0212] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or the structures within the hardware component.

[0213] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, 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. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A dual - distributed IRS - assisted simultaneous wireless information and power transfer system, characterized in that, Comprising: A wireless access point, a dual-distributed IRS system, a user equipment, and an interference point, Both the wireless access point and the interference point are equipped with a single antenna; The dual-distributed IRS system includes a plurality of IRS panels and a plurality of corresponding FPGA intelligent controllers, and the IRS panel includes a plurality of reflection units; The user equipment is equipped with a multi-receive antenna system, and the multi-receive antenna system includes a receive antenna array, a plurality of power splitters, an energy harvester, and an information decoder. The receive antenna array is used to receive the signals of the wireless access point and the interference point. Each power splitter is connected to a corresponding receive antenna, and the power splitter applies a power splitting factor to split the signal to the energy harvester and the information decoder for energy harvesting and information decoding; Both the wireless access point and the user equipment are located within the near-field region of the dual-distributed IRS.

2. The dual-distributed IRS-assisted simultaneous wireless information and power transfer system according to claim 1, wherein The dual-distributed IRS system includes two IRS panels and two corresponding FPGA intelligent controllers to align the signals reflected by the IRS panels to the user equipment.

3. The dual-distributed IRS-assisted power and information co-transmission system according to claim 2, wherein Calculate the Rayleigh distance through the operating frequency and array aperture of the IRS panel, and determine the near-field region according to the Rayleigh distance, so that the wireless access point and the user equipment are located within the near-field region.

4. The dual-distributed IRS-assisted simultaneous wireless information and power transfer system according to claim 3, wherein The near-field region is determined through the following steps: Assume that the multi-energy simultaneous transmission system includes M receiving antennas, and the two IRS panels are denoted as IRS1 and IRS2 respectively, located on the x-z plane of the three-dimensional Cartesian coordinate system, and are composed of and reflecting elements respectively. Among them, N a is the total number of elements of IRS1, and N b is the total number of elements of IRS2. and respectively represent the number of elements of the IRS1 panel along the x-axis and z-axis. and respectively represent the number of elements of the IRS2 panel along the x-axis and z-axis. The subscripts a and b refer to IRS1 and IRS2 respectively. The area of each reflecting element of the IRS panel is A, and the element spacing is ε. For the uniform planar array of IRS1, the array aperture is calculated as The array aperture of IRS2 is D b , similar to D a , denote the operating frequency as f0, then the wavelength of the signal is λ0 = c / f0, where c = 3×10 8 m / s represents the speed of light. The near-field regions of IRS1 and IRS2 are divided by the Rayleigh distances and .

5. A dual-distributed IRS-assisted near-field beamforming method, characterized in that, Adopt a simultaneous wireless information and power transfer system assisted by a dual-distributed IRS according to any one of claims 1-4, including the following steps: Channel modeling step: Based on the projected aperture non-uniform spherical wave model, establish a near-field channel model for the wireless access point - dual IRS panel and dual IRS panel - user equipment links; Optimization step: Through joint optimization, obtain the optimal independent power splitting vector, the optimal active beamforming variable, and the optimal dual IRS passive beamforming matrix; Independent power splitting step: Based on the optimal independent power splitting vector, the power splitters of the user equipment perform independent power splitting on the signals of each receive antenna; Active beamforming step: Based on the optimal active beamforming vector, the user equipment performs active beamforming on the receive antenna array to control the amplitude and phase of each antenna; Passive beamforming step: Based on the optimal dual IRS passive beamforming matrix, the dual IRS panels control the phase of each reflection unit through the FPGA intelligent controller.

6. The dual-distributed IRS-assisted near-field beamforming method according to claim 5, wherein The channel modeling step includes the following sub-steps: Step X1, set the wireless access point at the origin of the three-dimensional Cartesian coordinate system, i.e., p A =(0, 0, 0), and the centers of the IRS1 and IRS2 panels are located at and and are the coordinates of the center of the IRS1 panel along the x-axis and y-axis respectively, and are the coordinates of the center of the IRS2 panel along the x-axis and y-axis respectively. Then, the positions of the (n x , n z )-th cells of the IRS1 and IRS2 panels are respectively expressed as and where, set The distances between the (n x , n z )-th cells of the IRS1 and IRS2 and the wireless access point are respectively expressed as: Among them, set as the intermediate parameter; Step X2, through three-dimensional channel modeling, based on the projected-aperture non-uniform spherical wave model, the channel power gain between the wireless access point and the th unit of IRS1 is expressed as: where, u a represents the normal vector of each IRS1 unit placed on the x-z plane, i.e., u a = (0, -1, 0), and is expressed as the channel response vector of the wireless access point-IRS1 link, represents the space composed of all N a ×1 complex-valued matrices, where Among them, represents any and The channel power gain between the wireless access point and the (n x , n z )-th unit of IRS2 is denoted as Channel response vector of the wireless access point-IRS2 link The elements of which are given by wherein represents the space composed of all N b ×1 complex-valued matrices, represents any and Step X3, record the antenna spacing of the receiving antenna array of the user equipment as d, and set the linear array to be placed along the y-axis direction, with the starting point being Then the position of the m-th antenna of the user is where m = 1, 2,..., M, and the distance between the m-th antenna of the user and the th unit of IRS1 is The channel power gain between the m-th antenna of the user and the element of IRS1 is denoted as Accordingly, the channel response vector of the IRS1-user link is expressed as composed of the following elements where \(j\) represents the imaginary unit, \(m\) represents any and \(m\), the channel power gain between the \(m\)-th antenna of the user and the element is expressed as: The channel response vector of the IRS2-user link is represented as and consists of the following elements: where j represents the imaginary unit, m represents any and m; Step X4, represent and as the passive beamforming matrices IRS1 and IRS2 respectively, where and represent the reflection phases of the (n x , n z )-th element respectively when IRS1 and IRS2 assist in signal beamforming, The total combined channel of the near-field model of the wireless access point - dual IRS - user equipment link is expressed as g(l) = G a Θ a h a +G b Θ b h b , where \(g(l)=[g_1(l),g_2(l),\cdots,g M (l)] T , \(l\) is a set representing the coordinate information of the dual IRS and the user equipment.

7. The dual-distributed IRS-aided near-field beamforming method according to claim 6, characterized in that, The optimization step includes the following sub-steps: Step Y1, construct a received signal model, and the power splitter applies a power splitting factor to perform power splitting for energy harvesting and information decoding; Step Y2, jointly optimize the independent power splitting vector, the active beamforming vector, and the dual IRS passive beamforming matrix to obtain the optimal independent power splitting vector, the optimal active beamforming variable, and the optimal dual IRS passive beamforming matrix.

8. The dual-distributed IRS-aided near-field beamforming method according to claim 7, wherein, The step Y1 includes the following sub-steps: Step Y1.

1. Set that the channel from the interference point to the user equipment is statistically known at the user side, expressed as where \(f = [f_1, f_2,\cdots, f M T , following the Rayleigh fading channel model, the transmit powers of the wireless access point and the interference point are respectively denoted as \(P t and \(P in , then the signal received at the user equipment is expressed as​ where \(s_1\) and \(s_2\) are the normalized transmitted signals at the wireless access point and the interference point respectively, is the antenna noise at the user equipment, where denotes a circularly symmetric complex Gaussian random vector with mean 0 and covariance matrix and "~" means "distributed as"; Step Y1.2, for the m-th receiving antenna of the user equipment, its power splitter divides ρ m portion of the received signal power to the information decoder, and divides 1 - ρ m portion of the signal power to the energy harvester. The independent power splitting vector of the power splitter is denoted as ρ = [ρ1, ρ2,..., ρ M T , where ρ m is the m-th element of the independent power splitting vector. Then the total energy obtained by the energy harvester is expressed as:​ where η∈(0,1) represents the energy conversion efficiency of the energy harvester; g m represents the m-th element of the total combined channel g(l), and f m represents the m-th element of the interference channel f. The signal split to the information decoder is expressed as after decoding where $\Lambda=\text{diag}(\rho)$ is the independent power splitting matrix, is the additional noise introduced by the information decoder, is the active beamforming vector at the receiver, where represents a circularly symmetric complex Gaussian random vector with mean 0 and covariance matrix $\delta$ 2 $I$, and "~" means "distributed as". The signal-to-interference-plus-noise ratio of the user is expressed as:

9. The dual-distributed IRS-assisted power and information co-transmission system according to claim 8, wherein, The step Y2 includes the following sub-steps: Step Y2.1, set the mathematical expression of the original optimization problem as follows: Among them, γ0 represents the SINR threshold to ensure the QoS requirements of users. Since users have non-zero SINR thresholds, γ0 > 0; Step Y2.2, use the least mean square error algorithm to solve the active beamforming vector w; Step Y2.3, construct the Lagrangian function and apply the KKT conditions to optimize the power splitting vector ρ through fixed-point iteration; Step Y2.4, convert the optimization problem into a difference-of-convex programming problem, and solve for the dual IRS passive beamforming matrices {Θ a , Θ b} through convex optimization; Step Y2.5, repeat Steps Y2.2 to Y2.4 until the change in the energy harvesting amount is less than the preset threshold to obtain the optimal dual-IRS passive beamforming matrix, the optimal independent power splitting vector, and the optimal active beamforming variable.

10. The dual-distributed IRS-assisted near-field beamforming method according to claim 9, characterized in that, In the independent power splitting step, based on the near-field channel modeling and the optimal independent power splitting vector, the optimal power splitting of each receiving antenna is achieved to balance the trade-off between the data transmission rate and energy harvesting; In the active beamforming step, based on the near-field channel modeling and the optimal active beamforming variable, the user equipment performs receive beamforming on the multi-antenna signal through the information decoder to obtain the multi-antenna signal after receive beamforming; In the passive beamforming step, based on the near-field channel modeling and the optimal dual-IRS passive beamforming matrix, the incident signal on the dual-IRS panel is passively beamformed so that the reflected signal is aligned with the user equipment.

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