A polarization beamforming method for space-air-ground integrated network with simultaneous transmission and reception

Abstract

The application relates to the technical field of wireless communication, and discloses a polarization beamforming method for a space-air-ground integrated network with simultaneous transmission of energy and information, which comprises the following steps: constructing a space-air-ground integrated network comprising a ground wireless energy station, multiple unmanned aerial vehicles and low-orbit satellite nodes, and configuring a polarization reconfigurable antenna for each node; setting a time division multiple access protocol for the network; collecting time slots and polarization phase shifts of the network in a wireless energy collection stage and an information transmission stage; constructing a total throughput calculation model of the low-orbit satellite, taking the maximization of the total throughput of the low-orbit satellite as an optimization target, taking time slot scheduling and polarization phase shift as constraints, constructing a total throughput model of the network and solving the model; and substituting the optimal polarization phase shift and the optimal time slot allocation result into the total throughput calculation model to obtain the maximum total throughput of the network, so that the optimal balance between the energy transmission efficiency and the information transmission performance of the network is realized; the application realizes transmission optimization with high throughput, high energy efficiency and high reliability, and significantly improves the network transmission performance.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, specifically to a polarization shaping method for an integrated air-space-ground network that combines communication and energy transmission. Background Technology

[0002] With the increasing demands for global coverage, ultra-low latency, massive connectivity, and high reliability from future 6G mobile communication systems, the SAGIN (Space-Air-Ground Integrated Network) has become the core network architecture supporting various emerging 6G applications. This network integrates satellites, airborne platforms, high-altitude platforms, and terrestrial networks to construct a multi-layered heterogeneous infrastructure, adaptable to diverse scenarios such as remote sensing, autonomous driving, disaster recovery, and large-scale IoT services. Currently, related research mainly focuses on energy-efficient resource allocation for battery-constrained vehicle users, global transmission optimization for SAGIN-assisted robotic IoT systems, and network performance enhancement technologies that integrate reconfigurable smart surfaces with non-orthogonal multiple access.

[0003] While existing research has laid a solid foundation for the architecture design and resource management of integrated air-space-ground networks, most physical layer designs still rely on spatial beamforming and power control as core methods. To overcome this limitation, polarization shaping has emerged as a novel signal processing paradigm. This technology utilizes polarimetrically reconfigurable antennas to adaptively adjust the polarization characteristics of signals, treating the polarization domain as an additional degree of freedom to enhance the desired signal and suppress interference. By jointly optimizing the spatial and polarization domain characteristics of the signal, polarization shaping technology can effectively mitigate polarization mismatch loss and, compared to traditional beamforming techniques, further achieve diversity gain and interference suppression gain.

[0004] Although existing research has explored ways to improve the performance of integrated air-space-ground networks through resource allocation and global transmission optimization, and has proposed a new signal processing paradigm of polarization shaping, which uses the polarization domain as an additional degree of freedom to alleviate the polarization mismatch problem, and the polarization reconfigurable antenna (PRA) based on phase shifters can achieve polarization shaping with low complexity, and its polarization control capability has shown advantages in physical layer security, communication and sensing integration and other fields, a collaborative optimization scheme for time scheduling and polarization shaping has not yet been formed for SWIPT-enabled integrated air-space-ground networks. There is a lack of a joint design method for the phase shift parameters of polarization reconfigurable antennas and system time slot allocation, which makes it impossible to achieve efficient utilization of time domain and polarization domain resources and make it difficult to maximize the throughput of low-Earth orbit satellites. Summary of the Invention

[0005] To address the aforementioned shortcomings in existing technologies, this invention provides a polarization shaping method for an integrated air-space-ground network that combines information and energy transmission, thereby solving the problems of existing methods being unable to efficiently utilize time-domain and polarization-domain resources and unable to maximize the throughput of low-Earth orbit satellites.

[0006] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: A polarization shaping method for an integrated air-space-ground communication network for simultaneous information and energy transmission includes the following steps: Construct an integrated air-space-ground network that includes ground-based wireless energy stations, multiple drones, and low-orbit satellite nodes. Each node is equipped with a polarized reconfigurable antenna, and the drone nodes are also equipped with energy harvesting modules. The network is configured with a time division multiple access protocol that first collects energy and then transmits information. Its execution process includes a wireless energy collection phase and an information transmission phase. During the wireless energy harvesting phase, wireless energy is transmitted to all UAVs using ground-based wireless energy stations to obtain energy harvesting time slots, while simultaneously collecting the polarization phase shift of the ground-based wireless energy station transmitter and each UAV receiver. During the information transmission phase, the drone transmits information to the low-orbit satellite, obtains the information transmission time slot of the drone, and simultaneously collects the polarization phase shift of the drone transmitter and the low-orbit satellite receiver. Based on energy harvesting time slots, information transmission time slots, and polarization phase shifts, a model for calculating the total throughput of low-Earth orbit satellites is constructed. With the goal of maximizing the total throughput of low-Earth orbit satellites and with time slot scheduling and polarization phase shift as constraints, a total throughput model of the network is constructed and solved. First, the polarization phase shift of each node is alternately and iteratively optimized to generate the optimal polarization phase shift. Then, the optimal polarization phase shift is fixed, and the energy harvesting time slot and information transmission time slot are optimized to generate the optimal time slot allocation result. Substituting the optimal polarization phase shift and optimal time slot allocation results into the total throughput calculation model, the calculated total throughput is the maximum total throughput of the network, thereby achieving the optimal balance between network energy transmission efficiency and information transmission performance.

[0007] The present invention has the following beneficial effects: 1. The polarization shaping method for an integrated air-space-ground network proposed in this invention introduces a polarization-reconfigurable antenna into the integrated air-space-ground network. By combining the Lagrange duality method and the alternation optimization method, joint iterative optimization is carried out on the time slot allocation and phase shift of the polarization-reconfigurable antenna in the integrated air-space-ground network. This not only achieves high throughput, high energy efficiency, and high reliability transmission optimization, but also dynamically shapes the polarization characteristics of the wireless channel. Through polarization shaping, the channel transmission requirements are accurately matched, the depolarization effect and polarization mismatch loss are alleviated, the energy harvesting efficiency and signal gain are improved at the physical layer, and the time slot utilization efficiency of energy harvesting and information transmission are taken into account, thus achieving excellent transmission performance in the complex air-space-ground integrated wireless environment. 2. This invention also breaks through the performance limitations of traditional physical layer design, fully explores the value of polarization domain degrees of freedom, significantly improves network transmission performance, and provides important technical support for the integrated design of 6G air-space-ground communication and energy transmission. Attached Figure Description

[0008] Figure 1 This is a flowchart illustrating a polarization shaping method for an integrated air-space-ground network for simultaneous information and energy transmission proposed in this invention. Figure 2 This is a schematic diagram of the integrated space-air-ground network structure in the embodiment; Figure 3 A schematic diagram of a transceiver equipped with a polarized reconfigurable antenna; Figure 4 This is a schematic diagram illustrating the simulation results of the impact of transmit power on total throughput in the embodiment. Figure 5 This is a schematic diagram illustrating the simulation results of the impact of path loss on total throughput in the embodiment. Detailed Implementation

[0009] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0010] like Figure 1 As shown, a polarization shaping method for an integrated air-space-ground communication network includes the following steps: Step 1: Construct an integrated air-space-ground network including ground wireless energy stations, multiple drones, and low-orbit satellite nodes. Each node is equipped with a polarized reconfigurable antenna, and the drone nodes are also equipped with energy harvesting modules.

[0011] In this step, the energy harvesting module is used to collect energy via wireless energy transmission from a ground-based wireless energy station, and all the collected energy is used for information transmission from the UAV to a low-Earth orbit satellite. The polarization-reconfigurable antenna consists of two orthogonal antenna elements: a vertical (V) and a horizontal (H) antenna. A typical transceiver structure equipped with a polarization-reconfigurable antenna is as follows: Figure 3As shown, in this structure, each polarization-reconfigurable antenna is connected to a radio frequency (RF) link, and further connected to a signal processor via this RF link. Each polarization-reconfigurable antenna contains two orthogonal antenna elements and an embedded phase shifter. By dynamically adjusting the phase shift parameters of the phase shifter, the phase difference between the two orthogonal elements can be controlled, thereby achieving polarization shaping and reconfiguring the polarization channel. This mechanism can enhance the channel gain of the target signal and effectively suppress the depolarization effect generated during channel propagation. Specifically, the polarization-reconfigurable antenna of the ground wireless power station is used for transmitting-end polarization shaping, the polarization-reconfigurable antenna of the UAV has both receiving-end and transmitting-end polarization shaping functions, and the polarization-reconfigurable antenna of the low-Earth orbit (LEO) satellite is used for receiving-end polarization shaping. In addition, the LEO satellite is used to receive information transmitted by all UAVs, and the information transmission performance of the entire integrated air-space-ground network is characterized by the total throughput index.

[0012] To illustrate the constructed integrated air-space-ground network structure, Figure 2 This paper presents a simulation of constructing an integrated air-space-ground network, fitted in a three-dimensional coordinate system. The network nodes include a ground-based wireless power station, multiple UAVs, and a low-Earth orbit (LEO) satellite, each equipped with a polarization-reconfigurable antenna. The ground-based wireless power station is located at the origin. Multiple UAVs are randomly deployed within a circular area centered at (0, 0, 2) km with a radius of 500 m. The LEO satellite is positioned at (0, 0, 100) km. The channel coefficients consist of path loss and Ricean fading. A uniform path loss exponent of 2 is used for path loss modeling, and the carrier frequency is set to 2 GHz. All communication links incorporate an inverse cross-polarization discrimination factor to characterize channel depolarization. The channel coefficients for the ground-based wireless power station-UAV and UAV-LEO satellite communication are constructed using the polarization matrix combined with the Ricean fading model.

[0013] Step 2: Configure the network with a Time Division Multiple Access (TDMA) protocol that collects energy before transmitting information. The execution process includes a wireless energy collection phase and an information transmission phase.

[0014] Step 3: During the wireless energy harvesting phase, wireless energy is transmitted to all UAVs using the ground wireless energy station to obtain energy harvesting time slots, and the polarization phase shift of the ground wireless energy station transmitter and each UAV receiver is collected at the same time.

[0015] Step 4: During the information transmission phase, the UAV transmits information to the low-Earth orbit satellite to obtain the UAV's information transmission time slot, and at the same time, the polarization phase shift of the UAV transmitter and the low-Earth orbit satellite receiver is collected.

[0016] Step 5: Based on the energy harvesting time slot, information transmission time slot, and polarization phase shift, construct a calculation model for the total throughput of low-Earth orbit satellites.

[0017] Specifically, the calculation formula for the total throughput calculation model of low-Earth orbit satellites is as follows:

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] In the formula, This represents the total number of drones; For the first Single-user throughput when a drone transmits information to a low-Earth orbit satellite; For the first Information transmission time slots for drones; It is a logarithmic function; In order to harvest energy during time slots , No. Energy collected by a drone; For the first Channel coefficients of the information transmission link between the UAV and low-orbit satellite; For the first Polarization phase shift at the launch terminal of the UAV; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization phase shift occurs at the low-Earth orbit satellite receiver. This represents the noise power at the low-Earth orbit satellite receiver. For energy harvesting time slots; For the first Energy conversion efficiency of the energy harvesting module of the drone; This refers to the transmission power of the ground-based wireless power station; For ground-based wireless power stations and the first Channel coefficients of the energy transfer link between unmanned aerial vehicles (UAVs); Polarization phase shift for the transmitter of a ground-based wireless power station; For the first Polarization phase shift of the UAV receiver; For ground-based wireless power stations and the first The distance between drones; For ground-based wireless power stations and the first The path loss index of the energy transmission link between unmanned aerial vehicles; The polarization shaping vector for the transmitter of the ground-based wireless power station, and , It is an exponential function. The imaginary unit, This is a transpose operation; This is the conjugate transpose operation; For ground-based wireless power stations and the first Polarization matrix of the energy transfer link between unmanned aerial vehicles; For the first The polarization shaping vector of the UAV receiver, and ; The speed of light; For carrier frequency; For the first The altitude difference between the drone and the low-orbit satellite; For the first The path loss index of the information transmission link between the drone and the low-orbit satellite; For the first The polarization shaping vector of the UAV launcher, and ; For the first The polarization matrix of the information transmission link between the UAV and the low-orbit satellite; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization shaping vector at the low-Earth orbit satellite receiver, and ; For ground-based wireless power stations and the first Polarization phase shift matrix of the energy transfer link between unmanned aerial vehicles; For Hadamah accumulation; For ground-based wireless power stations and the first The elements of the power transmission link of the drone follow a matrix of independent, identically distributed, zero-mean complex Gaussian random variables; For the first The polarization phase shift matrix of the information transmission link between the UAV and the low-orbit satellite; For the first The complex Gaussian random variable matrix of the information transmission link between the UAV and the low-orbit satellite; For ground-based wireless power stations and the first Inverse cross-polarization discrimination factor for energy transfer links between unmanned aerial vehicles; For the first The inverse cross-polarization discrimination factor for the information transmission link between UAVs and low-orbit satellites.

[0024] Step 6: With maximizing the total throughput of low-Earth orbit satellites as the optimization objective and time slot scheduling and polarization phase shift as constraints, construct and solve the total throughput model of the network. First, alternately iterate to optimize the polarization phase shift of each node to generate the optimal polarization phase shift. Then, fix the optimal polarization phase shift and optimize the energy harvesting time slot and information transmission time slot to generate the optimal time slot allocation result.

[0025] In this step, firstly, using time slot scheduling and the phase shift (polarization phase shift) of the polarization-reconfigurable antenna at each stage as constraints, and maximizing the total throughput of low-Earth orbit satellites as the optimization objective, a total network throughput model is constructed, which is expressed as:

[0026]

[0027] in, This is for the operation of retrieving the maximum value; The set of time slot variables assigned to all time slots is represented as follows: , For the first Information transmission time slots for drones; Polarization phase shift for the transmitter of a ground-based wireless power station; For the first Polarization phase shift of the UAV receiver; For the first Polarization phase shift at the launch terminal of the UAV; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization phase shift occurs at the low-Earth orbit satellite receiver. This represents the total number of drones; For the first Single-user throughput when a drone transmits information to a low-Earth orbit satellite; For the first Information transmission time slots for drones; It is a logarithmic function; For energy harvesting time slots; For the first Energy conversion efficiency of the energy harvesting module of the drone; This refers to the transmission power of the ground-based wireless power station; For ground-based wireless power stations and the first Channel coefficients of the energy transfer link between unmanned aerial vehicles (UAVs); For the first Channel coefficients of the information transmission link between the UAV and low-orbit satellite; This represents the noise power at the low-Earth orbit satellite receiver. To make it meet a certain condition; For the complete operational cycle of the integrated air-space-ground network Secondly, the total throughput model of the network is solved. Due to the coupling relationship between time slot scheduling and polarization phase shift, the unit modulus constraint of phase shift, and the channel characteristics of wireless energy transmission, the optimization problem of maximizing throughput in the total throughput model of the network is a non-convex problem. In order to reduce the complexity of the problem and optimize the solution of the coupled variables, it is necessary to first iteratively optimize the polarization phase shift parameters of each node to generate the optimal polarization phase shift, and then fix the optimal polarization phase shift to optimize the energy harvesting time slot and the information transmission time slot to generate the optimal time slot allocation result.

[0028] Therefore, the solution process is as follows: (1) The process of iteratively optimizing the polarization phase shift of each node to generate the optimal polarization phase shift is as follows: First, the polarization phase shift of the wireless energy harvesting phase is fixed, and the polarization phase shift of the information transmission phase is optimized for the first time. Then, the optimized polarization phase shift of the information transmission phase is fixed, and the polarization phase shift of the wireless energy harvesting phase is optimized for the first time to generate the optimized polarization phase shift of the wireless energy harvesting phase. Finally, this alternating iterative optimization is continuously performed, and the optimal polarization phase shift is generated when all polarization phase shifts meet the convergence condition.

[0029] Alternatively, the polarization phase shift of the information transmission phase can be fixed first, and the polarization phase shift of the wireless energy harvesting phase can be optimized for the first time; then the optimized polarization phase shift of the wireless energy harvesting phase can be fixed, and the polarization phase shift of the information transmission phase can be optimized for the first time to generate the optimized polarization phase shift of the information transmission phase; finally, this alternating iterative optimization can be continuously performed, and the optimal polarization phase shift can be generated when all polarization phase shifts meet the convergence condition.

[0030] In this invention, there is no limitation on whether to prioritize fixing the polarization phase shift during the wireless energy harvesting phase or the polarization phase shift during the information transmission phase; the optimization solution processes of the two initial fixed orders are equivalent to each other, and the final iterative convergence results are consistent; therefore, either one can be selected to perform the specific solution.

[0031] Based on this, the present invention explains the process of first fixing the polarization phase shift of the wireless energy harvesting stage, then performing a first optimization on the polarization phase shift of the information transmission stage; then fixing the optimized polarization phase shift of the information transmission stage, and performing a first optimization on the polarization phase shift of the wireless energy harvesting stage to generate the optimized polarization phase shift of the wireless energy harvesting stage. The process of first fixing the polarization phase shift of the information transmission stage, then performing a first optimization on the polarization phase shift of the wireless energy harvesting stage, and then fixing the optimized polarization phase shift of the wireless energy harvesting stage, and performing a first optimization on the polarization phase shift of the information transmission stage to generate the optimized polarization phase shift of the information transmission stage, is the same as the former, and will not be elaborated further in this invention. The solution is as follows: 1) The process of first optimizing the polarization phase shift during the information transmission phase, while fixing the polarization phase shift during the wireless energy harvesting phase, is as follows: When the polarization phase shifts during the wireless energy harvesting phase With polarization phase shift Fixed polarization phase shift during information transmission With polarization phase shift In the first optimization, the objective problem of maximizing the total throughput of low-Earth orbit satellites is formulated as the first equivalent problem, namely:

[0032]

[0033] in, This is for the operation of retrieving the maximum value; As the first intermediate auxiliary variable; For the first The polarization shaping vector of the UAV launcher; For the first The polarization matrix of the information transmission link between the UAV and the low-orbit satellite; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization shaping vector at the low-Earth orbit satellite receiver; To make it meet a certain condition.

[0034] In this step, due to the existence of coupling variables, the first equivalence problem remains non-convex. To solve this problem, the present invention needs to decompose the problem into two sub-problems for solution. The solution process is as follows: Based on the first equivalence problem, by first fixing the polarization phase shift... polarization phase shift The first optimization involves decomposing the first equivalent problem into a first subproblem and a second subproblem, solving them, and generating the optimized polarization phase shift, specifically: Fixed polarization phase shift polarization phase shift To perform the first optimization, we construct the first sub-problem, namely:

[0035]

[0036] in, This is for the operation of retrieving the maximum value; As the second intermediate auxiliary variable; This is the conjugate transpose operation.

[0037] Define the Hermitian matrix and the phase shift vector, transform the first subproblem into a quadratic optimization objective function, and solve it to obtain the optimized polarization phase shift. ,Right now:

[0038] in, For the first When a drone transmits information to a low-Earth orbit satellite, the low-Earth orbit satellite receiver receives an optimized polarization phase shift. For angle calculation; This is to retrieve the element in the second row and first column of the matrix.

[0039] In this step, the Hermitian matrix and phase shift vector are defined. The principle of transforming the first subproblem into a quadratic optimization objective function is as follows: by defining a 2×2 Hermitian matrix P and a 1×2 phase shift vector... , For phase shift, the quadratic function can be maximized. Optimal phase shift Represented as: , To perform angle calculations, based on this principle, by defining the Hermitian matrix and phase shift vector, the first subproblem can be transformed into a quadratic optimization objective function. Solving this function yields the optimized polarization phase shift. .

[0040] Fixed optimized polarization phase shift polarization phase shift The first optimization is performed, constructing a solution based on the second subproblem, namely:

[0041]

[0042] in, This is for the operation of retrieving the maximum value; It is the third intermediate auxiliary variable.

[0043] Define the Hermitian matrix and the phase shift vector, transform the second subproblem into a quadratic optimization objective function, and solve it to obtain the optimized polarization phase shift. ,Right now:

[0044] in, For the first The optimized polarization phase shift of the UAV launcher.

[0045] Or by first fixing the polarization phase shift polarization phase shift The first optimization is performed by decomposing the first equivalent problem into a first subproblem and a second subproblem and solving them to generate the optimized polarization phase shift.

[0046] In this invention, for preferential fixed polarization phase shift Or should we prioritize fixing the polarization phase shift? There are no restrictions, and the two initial fixed order optimization solutions are equivalent to each other, and the final iteration converges in the same way; therefore, either one can be selected to perform the specific solution.

[0047] At the same time, by first fixing the polarization phase shift polarization phase shift The first optimization involves decomposing the first equivalent problem into a first subproblem and a second subproblem, solving them, and generating the optimized polarization phase shift. This process is similar to the one described above, where the polarization phase shift is first fixed. polarization phase shift The first optimization involves decomposing the first equivalent problem into a first subproblem and a second subproblem and solving them. The process of generating the optimized polarization phase shift is the same, and will not be described again in this invention.

[0048] 2) The process of optimizing the polarization phase shift in the fixed information transmission stage and then optimizing the polarization phase shift in the infinite energy harvesting stage is as follows: Based on the optimized polarization phase shift With polarization vector Fixed polarization phase shift polarization phase shift Perform the first optimization and construct the third sub-problem, namely:

[0049]

[0050] in, This is for the operation of retrieving the maximum value; It is the fourth intermediate auxiliary variable; For the first The polarization shaping vector of the UAV receiver; This is the fifth intermediate auxiliary variable; For ground-based wireless power stations and the first Polarization matrix of the energy transfer link between unmanned aerial vehicles; This is the polarization shaping vector of the transmitter at the ground-based wireless power station.

[0051] Define the Hermitian matrix and phase vector, transform the third subproblem into a quadratic optimization objective function, and solve it to obtain the optimized polarization phase shift. ,Right now:

[0052] in, For the first The optimized polarization phase shift of the UAV receiver.

[0053] Fixed optimized polarization phase shift polarization phase shift Perform the first optimization and construct the fourth sub-problem, namely:

[0054]

[0055] in, This is for the operation of retrieving the maximum value; It is the sixth intermediate auxiliary variable.

[0056] The fourth subproblem is solved using a one-dimensional search method, resulting in the optimized polarization phase shift.

[0057] In this step, the fourth subproblem is a question concerning polarization phase shift. Since this is a univariate optimization problem, a one-dimensional search method can effectively obtain its optimized solution. , The polarization phase shift optimized for the transmitter of the ground wireless power station.

[0058] In summary, the above describes the single-stage polarization phase shift optimization process (first optimization). After completing one round of iterative optimization, the above steps need to be repeated globally in alternating iterations, that is, repeating the phase shift optimization iterations of the information transmission and energy harvesting stages until all polarization phase shift parameters meet the convergence accuracy, ultimately obtaining the optimal polarization phase shift, including the optimal polarization phase shift at the ground wireless power station transmitter. , No. Optimal polarization phase shift of the UAV receiver , No. Optimal polarization phase shift at the UAV transmitter , No. When a drone transmits information to a low-Earth orbit satellite, the optimal polarization phase shift at the low-Earth orbit satellite receiver is... .

[0059] (2) The process of fixing the optimal polarization phase shift, optimizing the energy harvesting time slot and the information transmission time slot, and generating the optimal time slot allocation result is as follows: Based on energy harvesting time slots and information transmission time slots, the complete operating cycle of the integrated air-space-ground network is preset and used as a time slot scheduling constraint, which is expressed as follows:

[0060] in, For energy harvesting time slots; This represents the total number of drones; For the first Information transmission time slots for drones; This represents the complete operational cycle of an integrated air-space-ground network.

[0061] To determine the optimal polarization phase shift for the fixed UAV transmitter and low-orbit satellite receiver, we define the seventh and eighth intermediate auxiliary variables, which are expressed as follows:

[0062]

[0063] in, It is the seventh intermediate auxiliary variable; This is the eighth intermediate auxiliary variable; For the first Energy conversion efficiency of the energy harvesting module of the drone; This refers to the transmission power of the ground-based wireless power station; For ground-based wireless power stations and the first Channel coefficients of the energy transfer link between unmanned aerial vehicles (UAVs); The optimal polarization phase shift for the transmitter of the ground-based wireless power station; For the first Optimal polarization phase shift for the UAV receiver; This represents the noise power at the low-Earth orbit satellite receiver. For the first Channel coefficients of the information transmission link between the UAV and low-orbit satellite; For the first Optimal polarization phase shift at the launcher of the UAV; For the first When a drone transmits information to a low-Earth orbit satellite, the optimal polarization phase shift is achieved at the low-Earth orbit satellite receiver.

[0064] Based on the seventh and eighth intermediate auxiliary variables, the Lagrangian dual function of the optimization problem maximizing the total throughput of low-Earth orbit satellites is constructed, namely:

[0065] in, It is a Lagrange dual function; For Lagrange dual multipliers, and ; It is a logarithmic function.

[0066] When the optimal solution of the Lagrange dual function satisfies the Carlow-Kun-Tucker condition, it indicates that the equation for the time slot scheduling constraint holds, as shown below: ; In this step, the KARUSH–KUHN–TUCKE condition is expressed as follows: .

[0067] The purpose of using the KARUSH–KUHN–TUCKE condition in this step is to ensure that the equality of the time slot constraint holds when the optimal time slot allocation is obtained.

[0068] Once the equation for the time slot scheduling constraint holds, taking the partial derivative of the Lagrange dual function with respect to the information transmission time slot generates the partial derivative equation of the Lagrange dual function, namely:

[0069] in, To calculate the partial derivative with respect to the information transmission time slot.

[0070] Based on the partial derivative equation of the Lagrange dual function, the optimal information transmission time slot is obtained. ,Right now:

[0071] in, For the first The optimal information transmission time slot for drones.

[0072] Substituting the optimal information transmission time slots into the network's total throughput model, the optimization objective problem of maximizing the total throughput of low-Earth orbit satellites is transformed into an optimization problem with energy harvesting time slots as the optimization variable, as follows:

[0073]

[0074] in, This is for retrieving the maximum value.

[0075] Simultaneously, by setting the first derivative of the optimization problem with respect to the energy harvesting time slot to 0, the first-order partial derivative equation of the energy harvesting time slot is obtained, namely: .

[0076] Based on the first-order partial derivative equation of the energy harvesting time slot, the canonical form relation of the Lambertian function for the optimal energy harvesting time slot is obtained, namely:

[0077]

[0078] in, It is the ninth intermediate auxiliary variable.

[0079] Based on the Lambert function canonical form relation, the optimal energy harvesting time slot is obtained, namely:

[0080] in, The optimal energy harvesting time slot; It is an exponential function; It is a Lambert function; e is the natural constant.

[0081] In summary, this step completed the time slot scheduling optimization and obtained the optimal energy harvesting time slot. With the Optimal information transmission time slots for drones Thus, the optimization calculations for time slot scheduling and phase shifts at each stage of the polarization reconfigurable antenna have been completed.

[0082] Step 7: Substitute the optimal polarization phase shift and optimal time slot allocation results into the total throughput calculation model. The calculated total throughput is the maximum total throughput of the network, thereby achieving the optimal balance between network energy transmission efficiency and information transmission performance.

[0083] In this embodiment, to verify the effectiveness of the polarization shaping method for an integrated air-space-ground communication network proposed in this invention, the performance of the proposed method is compared with the performance of the following benchmark scheme in a simulation, as follows: First, the baseline scheme is set as follows: (1) Circularly polarized antenna scheme: The polarization vectors of the transmitting end and the receiving end are fixed as follows: and , The imaginary unit, This is a transpose operation; (2) Linearly polarized antenna scheme: The polarization vector of all nodes is fixed as follows: ; (3) Only low-Earth orbit satellites are equipped with polarized reconfigurable antennas: only low-Earth orbit satellites are equipped with polarized reconfigurable antennas, and all other terminals use linearly polarized antennas; (4) Only UAVs are equipped with polarized reconfigurable antennas: Only UAVs are equipped with polarized reconfigurable antennas, while all other terminals use linearly polarized antennas; (5) Only ground wireless power stations are equipped with polarized reconfigurable antennas: Only ground wireless power stations are equipped with polarized reconfigurable antennas, while all other terminals use linearly polarized antennas.

[0084] Then, simulations were performed on the method proposed in this invention and the above-mentioned benchmark scheme, and the simulation results are as follows: Figure 4 and Figure 5 As shown, where, Figure 4 Demonstrated transmission power Simulation results on the impact on total throughput; Figure 5 The simulation results show the impact of path loss on total throughput.

[0085] Ultimately, by Figures 4-5 Simulation results show that the joint time slot and polarization shaping optimization method proposed in this invention exhibits superior performance compared to other benchmark schemes. Furthermore, compared to traditional fixed-polarization antenna schemes, the performance gap between the proposed method and the proposed method gradually widens with parameter changes, further verifying the advantages of the proposed method in mitigating depolarization effects and improving energy harvesting efficiency and information transmission gain.

[0086] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0087] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A polarization shaping method for an integrated air-space-ground communication network for simultaneous information and energy transmission, characterized in that, Includes the following steps: Construct an integrated air-space-ground network that includes ground-based wireless energy stations, multiple drones, and low-orbit satellite nodes. Each node is equipped with a polarized reconfigurable antenna, and the drone nodes are also equipped with energy harvesting modules. The network is configured with a time division multiple access protocol that first collects energy and then transmits information. Its execution process includes a wireless energy collection phase and an information transmission phase. During the wireless energy harvesting phase, wireless energy is transmitted to all UAVs using ground-based wireless energy stations to obtain energy harvesting time slots, while simultaneously collecting the polarization phase shift of the ground-based wireless energy station transmitter and each UAV receiver. During the information transmission phase, the drone transmits information to the low-orbit satellite, obtains the information transmission time slot of the drone, and simultaneously collects the polarization phase shift of the drone transmitter and the low-orbit satellite receiver. Based on energy harvesting time slots, information transmission time slots, and polarization phase shifts, a model for calculating the total throughput of low-Earth orbit satellites is constructed. With the goal of maximizing the total throughput of low-Earth orbit satellites and with time slot scheduling and polarization phase shift as constraints, a total throughput model of the network is constructed and solved. First, the polarization phase shift of each node is alternately and iteratively optimized to generate the optimal polarization phase shift. Then, the optimal polarization phase shift is fixed, and the energy harvesting time slot and information transmission time slot are optimized to generate the optimal time slot allocation result. Substituting the optimal polarization phase shift and optimal time slot allocation results into the total throughput calculation model, the calculated total throughput is the maximum total throughput of the network, thereby achieving the optimal balance between network energy transmission efficiency and information transmission performance.

2. The polarization shaping method for an integrated air-space-ground communication network according to claim 1, characterized in that, The formula for calculating the total throughput of low-Earth orbit satellites is as follows: in, This represents the total number of drones; For the first Single-user throughput when a drone transmits information to a low-Earth orbit satellite; For the first Information transmission time slots for drones; It is a logarithmic function; In order to harvest energy during time slots , No. Energy collected by a drone; For the first Channel coefficients of the information transmission link between the UAV and low-orbit satellite; For the first Polarization phase shift at the launch terminal of the UAV; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization phase shift occurs at the low-Earth orbit satellite receiver. This represents the noise power at the low-Earth orbit satellite receiver. For energy harvesting time slots; For the first Energy conversion efficiency of the energy harvesting module of the drone; This refers to the transmission power of the ground-based wireless power station; For ground-based wireless power stations and the first Channel coefficients of the energy transfer link between unmanned aerial vehicles (UAVs); Polarization phase shift for the transmitter of a ground-based wireless power station; For the first Polarization phase shift of the UAV receiver; For ground-based wireless power stations and the first The distance between drones; For ground-based wireless power stations and the first The path loss index of the energy transmission link between unmanned aerial vehicles; Polarization shaping vector for the transmitter of the ground wireless power station; This is the conjugate transpose operation; For ground-based wireless power stations and the first Polarization matrix of the energy transfer link between unmanned aerial vehicles; For the first The polarization shaping vector of the UAV receiver; The speed of light; For carrier frequency; For the first The altitude difference between the drone and the low-orbit satellite; For the first The path loss index of the information transmission link between the drone and the low-orbit satellite; For the first The polarization shaping vector of the UAV launcher; For the first The polarization matrix of the information transmission link between the UAV and the low-orbit satellite; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization shaping vector at the low-Earth orbit satellite receiver; For ground-based wireless power stations and the first Polarization phase shift matrix of the energy transfer link between unmanned aerial vehicles; For Hadamah accumulation; For ground-based wireless power stations and the first The elements of the power transmission link of the drone follow a matrix of independent, identically distributed, zero-mean complex Gaussian random variables; For the first The polarization phase shift matrix of the information transmission link between the UAV and the low-orbit satellite; For the first The complex Gaussian random variable matrix of the information transmission link between the UAV and the low-orbit satellite; For ground-based wireless power stations and the first Inverse cross-polarization discrimination factor for energy transfer links between unmanned aerial vehicles; For the first The inverse cross-polarization discrimination factor for the information transmission link between UAVs and low-orbit satellites.

3. The polarization shaping method for an integrated air-space-ground communication network according to claim 1, characterized in that, The formula for calculating the total throughput model of a network is: in, This is for the operation of retrieving the maximum value; A set of time slot variables; Polarization phase shift for the transmitter of a ground-based wireless power station; For the first Polarization phase shift of the UAV receiver; For the first Polarization phase shift at the launch terminal of the UAV; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization phase shift occurs at the low-Earth orbit satellite receiver. This represents the total number of drones; For the first Single-user throughput when a drone transmits information to a low-Earth orbit satellite; For the first Information transmission time slots for drones; It is a logarithmic function; For energy harvesting time slots; For the first Energy conversion efficiency of the energy harvesting module of the drone; This refers to the transmission power of the ground-based wireless power station; For ground-based wireless power stations and the first Channel coefficients of the energy transfer link between unmanned aerial vehicles (UAVs); For the first Channel coefficients of the information transmission link between the UAV and low-orbit satellite; This represents the noise power at the low-Earth orbit satellite receiver. To make it meet a certain condition; This represents the complete operational cycle of an integrated air-space-ground network.

4. The polarization shaping method for the integrated air-space-ground communication network according to claim 3, characterized in that, The process of iteratively optimizing the polarization phase shift of each node to generate the optimal polarization phase shift is as follows: First, fix the polarization phase shift during the wireless energy harvesting phase, and then perform the first optimization on the polarization phase shift during the information transmission phase; then fix the optimized polarization phase shift during the information transmission phase, and perform the first optimization on the polarization phase shift during the wireless energy harvesting phase to generate the optimized polarization phase shift during the wireless energy harvesting phase. Finally, by continuously performing this alternating iterative optimization, the optimal polarization phase shift is generated when all polarization phase shifts satisfy the convergence condition. Alternatively, the polarization phase shift of the information transmission phase can be fixed first, and the polarization phase shift of the wireless energy harvesting phase can be optimized for the first time; then the optimized polarization phase shift of the wireless energy harvesting phase can be fixed, and the polarization phase shift of the information transmission phase can be optimized for the first time to generate the optimized polarization phase shift of the information transmission phase. Finally, by continuously performing this alternating iterative optimization, the optimal polarization phase shift is generated when all polarization phase shifts satisfy the convergence condition.

5. The polarization shaping method for an integrated air-space-ground communication network according to claim 4, characterized in that, The process of first optimizing the polarization phase shift during the information transmission phase, which is based on the fixed wireless energy harvesting phase, is as follows: When the polarization phase shifts during the wireless energy harvesting phase With polarization phase shift Fixed polarization phase shift during information transmission With polarization phase shift In the first optimization, the objective problem of maximizing the total throughput of low-Earth orbit satellites is formulated as the first equivalent problem, namely: in, This is for the operation of retrieving the maximum value; As the first intermediate auxiliary variable; For the first The polarization shaping vector of the UAV launcher; For the first The polarization matrix of the information transmission link between the UAV and the low-orbit satellite; For the first When a drone transmits information to a low-Earth orbit satellite, the polarization shaping vector at the low-Earth orbit satellite receiver; To make it meet a certain condition; Based on the first equivalence problem, by first fixing the polarization phase shift... polarization phase shift The first optimization is performed by decomposing the first equivalent problem into a first subproblem and a second subproblem and solving them to generate the optimized polarization phase shift. Or by first fixing the polarization phase shift polarization phase shift The first optimization is performed by decomposing the first equivalent problem into a first subproblem and a second subproblem and solving them to generate the optimized polarization phase shift.

6. The polarization shaping method for an integrated air-space-ground communication network according to claim 5, characterized in that, By first fixing the polarization phase shift polarization phase shift The first optimization involves decomposing the first equivalent problem into a first subproblem and a second subproblem, solving them, and generating the optimized polarization phase shift as follows: Fixed polarization phase shift polarization phase shift To perform the first optimization, we construct the first sub-problem, namely: in, This is for the operation of retrieving the maximum value; As the second intermediate auxiliary variable; This is the conjugate transpose operation; Define the Hermitian matrix and the phase shift vector, transform the first subproblem into a quadratic optimization objective function, and solve it to obtain the optimized polarization phase shift. ,Right now: in, For the first When a drone transmits information to a low-Earth orbit satellite, the low-Earth orbit satellite receiver receives an optimized polarization phase shift. For angle calculation; To retrieve the element in the second row and first column of the matrix; Fixed optimized polarization phase shift polarization phase shift The first optimization is performed, constructing a solution based on the second subproblem, namely: in, This is for the operation of retrieving the maximum value; As a third intermediate auxiliary variable; Define the Hermitian matrix and the phase shift vector, transform the second subproblem into a quadratic optimization objective function, and solve it to obtain the optimized polarization phase shift. ,Right now: in, For the first The optimized polarization phase shift of the UAV launcher.

7. The polarization shaping method for an integrated air-space-ground communication network according to claim 6, characterized in that, The polarization phase shift optimized during the fixed information transmission phase is then used to perform the first optimization on the polarization phase shift during the wireless energy harvesting phase. The process for generating the optimized polarization phase shift for the wireless energy harvesting phase is as follows: Based on the optimized polarization phase shift With polarization vector Fixed polarization phase shift polarization phase shift Perform the first optimization and construct the third sub-problem, namely: in, This is for the operation of retrieving the maximum value; It is the fourth intermediate auxiliary variable; For the first The polarization shaping vector of the UAV receiver; This is the fifth intermediate auxiliary variable; For ground-based wireless power stations and the first Polarization matrix of the energy transfer link between unmanned aerial vehicles; The polarization shaping vector of the transmitter at the ground-based wireless power station; Define the Hermitian matrix and phase shift vector, transform the third subproblem into a quadratic optimization objective function, and solve it to obtain the optimized polarization phase shift. ,Right now: in, For the first Optimized polarization phase shift for UAV receiver; Fixed optimized polarization phase shift polarization phase shift Perform the first optimization and construct the fourth sub-problem, namely: in, This is for the operation of retrieving the maximum value; It is the sixth intermediate auxiliary variable; The fourth subproblem is solved using a one-dimensional search method, yielding the optimized polarization phase shift. , The polarization phase shift optimized for the transmitter of the ground wireless power station.

8. The polarization shaping method for an integrated air-space-ground communication network according to claim 1, characterized in that, The process of fixing the optimal polarization phase shift, optimizing the energy harvesting time slot and the information transmission time slot, and generating the optimal time slot allocation result is as follows: Based on energy harvesting time slots and information transmission time slots, the complete operating cycle of the integrated air-space-ground network is preset and used as a time slot scheduling constraint, which is expressed as follows: in, For energy harvesting time slots; This represents the total number of drones; For the first Information transmission time slots for drones; This represents the complete operational cycle of an integrated air-space-ground network. To determine the optimal polarization phase shift for the fixed UAV transmitter and low-orbit satellite receiver, we define the seventh and eighth intermediate auxiliary variables, which are expressed as follows: in, It is the seventh intermediate auxiliary variable; This is the eighth intermediate auxiliary variable; For the first Energy conversion efficiency of the energy harvesting module of the drone; This refers to the transmission power of the ground-based wireless power station; For ground-based wireless power stations and the first Channel coefficients of the energy transfer link between unmanned aerial vehicles (UAVs); The optimal polarization phase shift for the transmitter of the ground-based wireless power station; For the first Optimal polarization phase shift for the UAV receiver; This represents the noise power at the low-Earth orbit satellite receiver. For the first Channel coefficients of the information transmission link between the UAV and low-orbit satellite; For the first Optimal polarization phase shift at the launcher of the UAV; For the first When a drone transmits information to a low-Earth orbit satellite, the optimal polarization phase shift is achieved at the low-Earth orbit satellite receiver. Based on the seventh and eighth intermediate auxiliary variables, the Lagrangian dual function of the optimization problem maximizing the total throughput of low-Earth orbit satellites is constructed, namely: in, It is a Lagrange dual function; For Lagrange dual multipliers; It is a logarithmic function; When the optimal solution of the Lagrange dual function satisfies the Carlow-Kun-Tucker condition, it indicates that the equation for the time slot scheduling constraint holds, as shown below: ； Once the equation for the time slot scheduling constraint holds, taking the partial derivative of the Lagrange dual function with respect to the information transmission time slot generates the partial derivative equation of the Lagrange dual function, namely: in, To calculate the partial derivative with respect to the information transmission time slot; Based on the partial derivative equation of the Lagrange dual function, the optimal information transmission time slot is obtained. ; Substituting the optimal information transmission time slots into the network's total throughput model, the optimization objective problem of maximizing the total throughput of low-Earth orbit satellites is transformed into an optimization problem with energy harvesting time slots as the optimization variable, as follows: in, This is for the operation of retrieving the maximum value; Simultaneously, by setting the first derivative of the optimization problem with respect to the energy harvesting time slot to 0, the first-order partial derivative equation of the energy harvesting time slot is obtained, namely: ； Based on the first-order partial derivative equation of the energy harvesting time slot, the canonical form relation of the Lambertian function for the optimal energy harvesting time slot is obtained, namely: in, This is the ninth intermediate auxiliary variable; Based on the Lambert function canonical form relation, the optimal energy harvesting time slot is obtained.

9. The polarization shaping method for an integrated air-space-ground communication network according to claim 8, characterized in that, The formula for calculating the optimal information transmission time slot is: in, For the first The optimal information transmission time slot for drones.

10. The polarization shaping method for an integrated air-space-ground communication network according to claim 9, characterized in that, The formula for calculating the optimal energy harvesting time slot is: in, The optimal energy harvesting time slot; It is an exponential function; It is a Lambert function; e is the natural constant.

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