CN116319199A - Method, device and medium for solving closed solution of maximum throughput of wireless power communication network - Google Patents
Method, device and medium for solving closed solution of maximum throughput of wireless power communication network Download PDFInfo
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Abstract
The invention discloses a method, a device and a medium for solving a closed solution of the maximum throughput of a wireless power communication network, wherein the method uses intelligent super-surface assistance to enhance signals; the energy of the transmitted signal is more concentrated by utilizing the energy and the information precoding; obtaining optimal information precoding by using a maximum merging ratio algorithm; determining an optimal energy precoding by beamforming; a closed-form solution of the maximum throughput of the network is obtained through derivation. The invention separates the energy collection link from the information transmission link, which is beneficial to the large-scale wireless power communication network; the energy and information precoding is used to reduce the path transmission loss; only one intelligent super surface is used, so that the complexity of a communication system is reduced, hardware resources are saved, and the communication system is easier to deploy in an actual communication system; the obtained closed solution can be directly used for evaluating the maximum throughput of a communication system after the intelligent super-surface assistance is added, and has strong practical significance.
Description
Technical Field
The invention relates to a method, a device, computer equipment and a storage medium for solving a closed-type solution of the maximum throughput of a wireless power communication network, and belongs to the technical field of wireless communication.
Background
In the future, communication technology will enter the sixth generation (6G) era. And ultra-dense links are established among people, machines and objects to form a land-sea-air integrated network, so that full coverage is realized. At that time, all-weather sensing and monitoring of the real world will be realized through various sensors, and a large number of wireless sensor networks need to be deployed and maintained in various scenes. In order to maintain continuous and uninterrupted collection and transmission of information, reduce maintenance costs and improve energy efficiency, it is necessary to provide environmental energy to the wireless sensor network. In a wireless power-supplied communication network, wireless energy acquisition capability is weak due to fading characteristics of a wireless link, and it is difficult to supply energy.
In recent years, intelligent super-surfaces (RIS) have been able to flexibly manipulate electromagnetic properties in a channel environment, and as soon as they appear, they have attracted widespread attention in the industry. RIS is typically composed of a number of well-designed arrangements of electromagnetic units. By applying control signals to the adjustable elements on the electromagnetic units, the RIS can dynamically control the electromagnetic properties of the electromagnetic units, so that the electromagnetic fields with controllable phases, amplitudes, polarizations and frequencies are formed by actively and intelligently regulating and controlling the space electromagnetic waves in a programmable manner. As the two-dimensional implementation of the metamaterial, the RIS has the characteristics of low cost, low complexity and easy deployment, and by constructing an intelligent controllable wireless environment, the RIS has the opportunity to break through the constraint of traditional wireless communication, and brings a brand new paradigm for a future mobile communication network, so that the RIS has wide technical and industrial prospects. RIS is a multidisciplinary fusion technique. Before the birth of RIS concept, the metamaterial related basic theory has been developed for more than half a century, which lays a solid foundation for the establishment of RIS theoretical system, and is considered as a very promising wireless power supply communication network performance enhancement technology, which can improve energy and spectrum efficiency, expand network coverage and thus improve throughput.
Disclosure of Invention
In view of this, the present invention provides a method, an apparatus, a computer device, and a storage medium for solving a closed solution of a maximum throughput of a wireless power communication network, which can solve the problem of large-scale wireless power communication network, reduce path transmission loss by using energy and information precoding, reduce complexity of a communication system by using an intelligent super-surface, and solve a closed solution to directly evaluate the maximum throughput of a communication system after adding the intelligent super-surface assistance.
The first object of the present invention is to provide a method for solving a closed-form solution of maximum throughput of a wireless power communication network.
A second object of the present invention is to provide a device for solving a closed-form solution of maximum throughput of a wireless power communication network.
A third object of the present invention is to provide a computer device.
A fourth object of the present invention is to provide a storage medium.
The first object of the present invention can be achieved by adopting the following technical scheme:
a method for solving a closed-form solution of maximum throughput of a wireless power communication network, which is applied to a communication system added with intelligent super-surface assistance, the method comprising:
setting energy precoding according to a first singular vector, wherein the first singular vector refers to a first singular vector of a right unitary matrix after singular value decomposition of an energy collection link;
calculating optimal information precoding according to a maximum merging ratio method;
according to the energy precoding and the information precoding, obtaining an objective function for solving the maximum throughput of the communication system;
and equivalent transformation objective functions are realized by utilizing a sea plug matrix, complex quadratic form and eigenvalue decomposition, and a closed solution form of the throughput maximum value is obtained.
Further, the equivalent channel H of the energy harvesting link e ＝H RA ΘH PR +H PA Equivalent channel H e The singular value decomposition of (2) is as follows:
H e ＝U e Λ e V e H
wherein matrix U e And V e A left unitary matrix and a right unitary matrix respectively; Λ type e Is a diagonal matrix, and the diagonal elements satisfy H e Singular value lambda 1 ≥λ 2 ≥…≥λ n >0；
And setting energy precoding according to the first singular vector, wherein the energy precoding comprises the following formula:
wherein G is energy precoding, P 0 Representing maximum transmit power of a power station, b 1 Is the first singular vector, i.e. (H) RA ΘH PR +H PA ) Maximum singular value lambda of (2) 1 Is used for the feature vector of (a),
representation b 1 Is a conjugate transpose of (2); Θ represents the phase matrix of the reconfigurable intelligent subsurface; h PR 、H PA 、H R ugly The baseband equivalent channel from the power station to the intelligent super surface, the baseband equivalent channel from the power station to the access point and the baseband equivalent channel from the intelligent super surface to the access point are respectively represented.
Further, the calculating the optimal information precoding according to the maximum combining ratio method specifically includes:
for the access point, the direct path and the reflection path are regarded as a whole, which is equivalent to a channel matrix, and the optimal information precoding is obtained through a maximum combination ratio algorithm, as follows:
wherein w is * Is information precoding, P 1 Representing transmit power at access point, H AR Representing a baseband equivalent channel from an access point to an intelligent subsurface; h is a RU 、h AU The baseband equivalent channels from the intelligent super surface to the user and the access point to the user are respectively represented.
Further, in the case that the access point does not store energy, it is the best choice to use all the collected energy when sending the message, and the objective function is as follows:
wherein Θ represents the phase matrix of the reconfigurable intelligent subsurface; h PR 、H PA 、H R ugly The method comprises the steps of respectively representing a baseband equivalent channel from a power station to an intelligent super surface, a baseband equivalent channel from the power station to an access point and a baseband equivalent channel from the intelligent super surface to the access point; h is a RU 、h AU Respectively representing a baseband equivalent channel from the intelligent super surface to the user and a baseband equivalent channel from the access point to the user; b 1 Is the first singular vector, i.e. (H) RA ΘH PR +H P ugly ) Maximum singular value lambda of (2) 1 Is used for the feature vector of (a),
representation b 1 Is a conjugate transpose of (a).
Further, in the case that the access point does not store energy, the equivalent form of the channel capacity of the communication system is as follows:
where v is the vectorized form of the phase matrix, P 0 Representing maximum transmit power, P, of a power station 1 Representing transmit power at an access point, T el And T il Is a sea plug matrix, R el ＝H RA diag(H PR b 1 )，
H PR 、H PA 、H RA The method comprises the steps of respectively representing a baseband equivalent channel from a power station to an intelligent super surface, a baseband equivalent channel from the power station to an access point and a baseband equivalent channel from the intelligent super surface to the access point; h is a RU 、h AU Respectively representing a baseband equivalent channel from the intelligent super surface to the user and a baseband equivalent channel from the access point to the user; b 1 Is the first singular vector, i.e. (H) RA ΘH PR +H PA ) Maximum singular value lambda of (2) 1 Feature vector of>
Representation b 1 Is a conjugate transpose of (a).
Further, the equivalent transformation objective function is performed by utilizing a sea plug matrix, a complex quadratic form and eigenvalue decomposition to obtain a closed solution form of the throughput maximum value, which specifically comprises:
matrix T of sea plug el And T il Is decomposed into
And->
Wherein U is el Is of the column vector of (2)
Forming an orthogonal group, U il Column vector +.>
Forming an orthogonal group; Λ type el Sum lambda il Is a diagonal matrix, Λ el Is singular value +.>
Λ il Is singular value +.>
The maximum throughput optimization problem is rewritten as:
wherein, |v m |=1, m=1, 2,..m+1, adjusted by v
When v will be->
When the phases of all the elements in the array are adjusted to the same direction, < >>
Has a maximum value; by v adjustment->
When v will be->
When the phases of all the elements in the array are adjusted to the same direction, < >>
Has a maximum value;
order the
And->
At lambda el Sum lambda il In which the characteristic values are arranged in descending order, i.e. +.>
And->
Make the following steps
When v is used to adjust the corresponding lambda max The throughput is maximized when the eigenvector direction of (a).
Further, the channel capacity of the communication system is as follows:
for a certain communication system, an upper limit of the channel capacity of the communication system is determined when the channel condition and the transmit power of the power station are known.
The second object of the invention can be achieved by adopting the following technical scheme:
a wireless power communication network maximum throughput closed solution device applied to a communication system with intelligent super-surface assistance, the device comprising:
the energy precoding setting module is used for setting energy precoding according to a first singular vector, wherein the first singular vector is the first singular vector of the right unitary matrix after the energy collection link carries out singular value decomposition;
the information precoding calculation module is used for calculating optimal information precoding according to a maximum combination ratio method;
the objective function acquisition module is used for acquiring an objective function for solving the maximum throughput of the communication system according to the energy precoding and the information precoding;
and the closed solution solving module is used for equivalently converting the objective function by utilizing the sea plug matrix, the complex quadratic form and the eigenvalue decomposition to obtain a closed solution form of the throughput maximum value.
The third object of the present invention can be achieved by adopting the following technical scheme:
the computer equipment comprises a processor and a memory for storing a program executable by the processor, and is characterized in that the method for solving the maximum throughput closed-form solution of the wireless power communication network is realized when the processor executes the program stored by the memory.
The fourth object of the present invention can be achieved by adopting the following technical scheme:
a storage medium storing a program which, when executed by a processor, implements the method for solving a closed-loop solution for maximum throughput of a wireless power communication network described above.
Compared with the prior art, the invention has the following beneficial effects:
the present invention uses intelligent subsurface assistance to enhance signals; the energy of the transmitted signal is more concentrated by utilizing the energy and the information precoding; obtaining optimal information precoding by using a maximum merging ratio algorithm; determining an optimal energy precoding by beamforming; the closed solution of the maximum throughput of the network is obtained through deduction, so that an energy collection link and an information transmission link can be separated, and the large-scale wireless power communication network is facilitated; the energy and information precoding is used to reduce the path transmission loss; only one intelligent super surface is used, so that the complexity of a communication system is reduced, hardware resources are saved, and the communication system is easier to deploy in an actual communication system; the obtained closed solution can be directly used for evaluating the maximum throughput of a communication system after the intelligent super-surface assistance is added, and has strong practical significance.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a communication system model diagram of embodiment 1 of the present invention.
Fig. 2 is a flowchart of a method for solving a closed-form solution of maximum throughput of a wireless power communication network according to embodiment 1 of the present invention.
Fig. 3 is a graph showing the relationship between the average throughput and the distances between the receiving unit and the access point in embodiment 1 of the present invention.
Fig. 4 is a block diagram of a device for solving a closed-form solution of maximum throughput of a wireless power communication network according to embodiment 2 of the present invention.
Fig. 5 is a block diagram showing the structure of a computer device according to embodiment 3 of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by persons of ordinary skill in the art without making any inventive effort based on the embodiments of the present invention are within the scope of protection of the present invention.
Example 1:
the embodiment provides a method for solving a closed solution of maximum throughput of a wireless power communication network, which obtains a closed solution of maximum throughput of a communication system through a correlation method, and the closed solution can be used for evaluating the best effect that channel conditions can be improved after the communication system is added with intelligent super surface (Reconfigurable intelligent surface, abbreviated as RIS) assistance.
As shown in fig. 1, an Access Point (AP) obtains energy from a power station; the access point is fully operating in full duplex mode; in addition, by changing the phase of the incident signal, an intelligent super-surface system is designed, so that the energy and the information are more concentrated, and the transmission efficiency is improved; the intelligent super-surface is provided with M uniform plane array reflecting units; is provided with
Respectively representing a baseband equivalent channel from a Power Station (PS) to an intelligent super surface, a baseband equivalent channel from the Power Station to an access point and a baseband equivalent channel from the intelligent super surface to the access point; at the same time->
Respectively representing a baseband equivalent channel from an intelligent super surface to a User (IU) and a baseband equivalent channel from an access point to the User; the present embodiment assumes that the channel state information of all channels is completely known, so that the channels can be directly modeled.
As shown in fig. 2, the method for solving the closed-form solution of the maximum throughput of the wireless power communication network according to the present embodiment includes the following steps:
s201, setting energy precoding according to the first singular vector.
Wherein the first singular vector is the first singular vector of the right unitary matrix after singular value decomposition by the energy collection link, and the equivalent channel H of the energy collection link e ＝H RA ΘH PR +H PA Equivalent channel H e The singular value decomposition of (2) is as follows:
H e ＝U e Λ e V e H (1)
wherein matrix U e And V e A left unitary matrix and a right unitary matrix respectively; Λ type e Is a diagonal matrix, and the diagonal elements satisfy H e Singular value lambda 1 ≥λ 2 ≥…≥λ n >0；
According to the first singular vector, setting energy precoding as follows:
where G is energy precoding, P0 represents the maximum transmit power of the power station, b 1 Is the first singular vector, i.e. (H) RA ΘH PR +H PA ) Maximum singular value lambda of (2) 1 Is used for the feature vector of (a),
representation b 1 Is a conjugate transpose of (2); Θ represents the phase matrix of the reconfigurable intelligent subsurface; h PR 、H PA 、H R ugly The baseband equivalent channel from the power station to the intelligent super surface, the baseband equivalent channel from the power station to the access point and the baseband equivalent channel from the intelligent super surface to the access point are respectively represented.
S202, calculating optimal information precoding according to a maximum combination ratio method.
For the access point, the direct path and the reflection path are regarded as a whole, which is equivalent to a channel matrix, and the optimal information precoding is obtained through a maximum combination ratio algorithm, as follows:
wherein w is * Is information precoding, P 1 Representing transmit power at the access point; h is a RU 、h AU The baseband equivalent channels from the intelligent super surface to the user and the access point to the user are respectively represented.
S203, obtaining an objective function of the maximum throughput solution of the communication system according to the energy precoding and the information precoding.
The present embodiment assumes that the access point does not store energy, so using all the collected energy is the best choice when sending information, and the objective function can be rewritten as:
the equivalent of the channel capacity of the communication system can be written as equation (5) with the basic assumption that the access point will not store energy:
where v is the vectorized form of the phase matrix, T el And T il Is a sea plug matrix, R el ＝H RA diag(H PR b 1 )，
S204, utilizing the sea plug matrix, the complex quadratic form and the eigenvalue decomposition to equivalently transform the objective function, and obtaining a closed solution form of the throughput maximum value.
The present embodiment derives an optimal closed-form solution (closed-form solution) of the system at the time of calculating the maximum throughput using the relevant mathematical knowledge for the maximum throughput optimization problem, in step S203, because of T el And T il Is a sea plug matrix, so there must be a left unitary matrix U el And right unitary matrix U il So that the complex quadratic form can be converted into standard form, and the sea plug matrix T el And T il Is decomposed into
And->
Wherein U is el Column vector +.>
Forming an orthogonal group, U il Is of the column vector of (2)
Forming an orthogonal group; Λ type el Sum lambda il Is a diagonal matrix, Λ el Is a singular value
Λ il Is singular value +.>
Therefore, the maximum throughput optimization problem is rewritten as:
wherein, |v m |=1, m=1, 2,..m+1, adjusted by v alone
Without changing the amplitude, when v will +.>
When the phases of all the elements in the array are adjusted to the same direction, < >>
Has a maximum value; similarly, only by v-adjustment +.>
Without changing the amplitude, when v will +.>
When the phases of all the elements in the array are adjusted to the same direction, < >>
There is a maximum.
Order the
And->
At lambda el Sum lambda il In which the characteristic values are arranged in descending order, i.e. +.>
And->
Make the following steps
When v is used to adjust the corresponding lambda max The throughput is maximized when the eigenvector direction of (a).
The channel capacity of a communication system is represented by the following formula:
thus, for a certain communication system, when the channel condition and transmit power of the power station are known, an upper limit of the channel capacity of the communication system is determined.
As shown in fig. 3, is a verification of a closed-form solution derived from a single-user model. The solid line is the calculated maximum theoretical average throughput of the system, the dashed line is the calculated throughput according to equation (7), from which it can be seen that the throughput of both curves decreases slowly as the distance between the receiving unit and the access point increases, and the result of equation (7) is very close to the theoretical value, which also demonstrates the correctness of the derived closed-form solution. That is, when the channel state information of the model is known, the optimal effect of the intelligent subsurface on the beamforming of the channel can be determined.
It should be noted that while the method operations of the above embodiments are described in a particular order, this does not require or imply that the operations must be performed in that particular order or that all of the illustrated operations be performed in order to achieve desirable results. Rather, the depicted steps may change the order of execution. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform.
Example 2:
as shown in fig. 4, the present embodiment provides a device for solving a closed solution of a maximum throughput of a wireless power communication network, where the device includes an energy precoding setting module 401, an information precoding calculating module 402, an objective function obtaining module 403, and a closed solution solving module 404, and specific functions of the modules are as follows:
an energy precoding setting module 401, configured to set energy precoding according to a first singular vector, where the first singular vector is a first singular vector of a right unitary matrix after singular value decomposition by an energy collection link;
an information precoding calculation module 402, configured to calculate an optimal information precoding according to a maximum combining ratio method;
an objective function obtaining module 403, configured to obtain an objective function for solving a maximum throughput of the communication system according to the energy precoding and the information precoding;
the closed solution module 404 is configured to equivalently transform the objective function by using a sea plug matrix, a complex quadratic form and eigenvalue decomposition, and obtain a closed solution form of the throughput maximum value.
Specific implementation of each module in this embodiment may be referred to embodiment 1 above, and will not be described in detail; it should be noted that, the apparatus provided in this embodiment is only exemplified by the division of the above functional modules, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure is divided into different functional modules, so as to perform all or part of the functions described above.
Example 3:
the present embodiment provides a computer apparatus, which may be a computer, as shown in fig. 5, including a processor 502, a memory, an input device 503, a display 504 and a network interface 505 connected by a device bus 501, where the processor is configured to provide computing and control capabilities, the memory includes a nonvolatile storage medium 506 and an internal memory 507, where the nonvolatile storage medium 506 stores an operating device, a computer program and a database, and the internal memory 507 provides an environment for the operation of the operating device and the computer program in the nonvolatile storage medium, and when the processor 502 executes the computer program stored in the memory, the method for solving a closed-loop maximum throughput of a wireless power communication network according to the above embodiment 1 is implemented as follows:
setting energy precoding according to a first singular vector, wherein the first singular vector refers to a first singular vector of a right unitary matrix after singular value decomposition of an energy collection link;
calculating optimal information precoding according to a maximum merging ratio method;
according to the energy precoding and the information precoding, obtaining an objective function for solving the maximum throughput of the communication system;
and equivalent transformation objective functions are realized by utilizing a sea plug matrix, complex quadratic form and eigenvalue decomposition, and a closed solution form of the throughput maximum value is obtained.
Example 4:
the present embodiment provides a storage medium, which is a computer readable storage medium storing a computer program, and when the computer program is executed by a processor, the method for solving a closed-form solution of maximum throughput of a wireless power communication network in the foregoing embodiment 1 is implemented as follows:
setting energy precoding according to a first singular vector, wherein the first singular vector refers to a first singular vector of a right unitary matrix after singular value decomposition of an energy collection link;
calculating optimal information precoding according to a maximum merging ratio method;
according to the energy precoding and the information precoding, obtaining an objective function for solving the maximum throughput of the communication system;
and equivalent transformation objective functions are realized by utilizing a sea plug matrix, complex quadratic form and eigenvalue decomposition, and a closed solution form of the throughput maximum value is obtained.
The computer readable storage medium of the present embodiment may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an apparatus, device, or means of electronic, magnetic, optical, electromagnetic, infrared, or semiconductor, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In this embodiment, the computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution apparatus, device, or apparatus. In the present embodiment, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with a computer-readable program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable storage medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution apparatus, device, or apparatus. A computer program embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable storage medium may be written in one or more programming languages, including an object oriented programming language such as Java, python, C ++ and conventional procedural programming languages, such as the C-language or similar programming languages, or combinations thereof for performing the present embodiments. The program may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
In summary, the present invention uses intelligent subsurface assistance to enhance signals; the energy of the transmitted signal is more concentrated by utilizing the energy and the information precoding; obtaining optimal information precoding by using a maximum merging ratio algorithm; determining an optimal energy precoding by beamforming; the closed solution of the maximum throughput of the network is obtained through deduction, so that an energy collection link and an information transmission link can be separated, and the large-scale wireless power communication network is facilitated; the energy and information precoding is used to reduce the path transmission loss; only one intelligent super surface is used, so that the complexity of the system is reduced, hardware resources are saved, and the system is easier to deploy in an actual system; the obtained closed solution can be directly used for evaluating the maximum throughput of a system after the intelligent super-surface assistance is added, and has strong practical significance.
The above description is only of the preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can substitute or change the technical solution and the inventive conception of the present invention equally within the scope of the disclosure of the present invention.
Claims (10)
1. A method for solving a closed solution of maximum throughput of a wireless power communication network, which is applied to a communication system with an intelligent super-surface assistance, the method comprising the following steps:
setting energy precoding according to a first singular vector, wherein the first singular vector refers to a first singular vector of a right unitary matrix after singular value decomposition of an energy collection link;
calculating optimal information precoding according to a maximum merging ratio method;
obtaining an objective function for solving the maximum throughput according to the energy precoding and the information precoding;
and equivalent transformation objective functions are realized by utilizing a sea plug matrix, complex quadratic form and eigenvalue decomposition, and a closed solution form of the throughput maximum value is obtained.
2. The method of claim 1, wherein the equivalent channel H of the energy harvesting link is a closed solution for maximum throughput of a wireless power communication network e ＝H RA ΘH PR +H PA Equivalent channel H e The singular value decomposition of (2) is as follows:
wherein matrix U e And V e A left unitary matrix and a right unitary matrix respectively; Λ type e Is a diagonal matrix, and the diagonal elements satisfy H e Singular value lambda 1 ≥λ 2 ≥…≥λ n >0；
And setting energy precoding according to the first singular vector, wherein the energy precoding comprises the following formula:
wherein G is energy precoding, P 0 Representing maximum transmit power of a power station, b 1 Is the first singular vector, i.e. (H) RA ΘH PR +H PA ) Maximum singular value lambda of (2) 1 Is used for the feature vector of (a),
representation b 1 Is a conjugate transpose of (2); Θ represents the phase matrix of the reconfigurable intelligent subsurface; h PR 、H PA 、H RA The baseband equivalent channel from the power station to the intelligent super surface, the baseband equivalent channel from the power station to the access point and the baseband equivalent channel from the intelligent super surface to the access point are respectively represented.
3. The method for solving the closed-form solution of the maximum throughput of the wireless power communication network according to claim 1, wherein the calculating the optimal information precoding according to the maximum combining ratio method specifically comprises:
for the access point, the direct path and the reflection path are regarded as a whole, which is equivalent to a channel matrix, and the optimal information precoding is obtained through a maximum combination ratio algorithm, as follows:
wherein w is * Is information precoding, P 1 Representing transmit power at access point, H AR Representing a baseband equivalent channel from an access point to an intelligent subsurface; h is a RU 、h AU The baseband equivalent channels from the intelligent super surface to the user and the access point to the user are respectively represented.
4. The method of claim 1, wherein using all collected energy when sending a message is the best choice if the access point does not store energy, the objective function is as follows:
wherein Θ represents the phase matrix of the reconfigurable intelligent subsurface; h PR 、H PA 、H RA The method comprises the steps of respectively representing a baseband equivalent channel from a power station to an intelligent super surface, a baseband equivalent channel from the power station to an access point and a baseband equivalent channel from the intelligent super surface to the access point; h is a RU 、h AU Respectively representing a baseband equivalent channel from the intelligent super surface to the user and a baseband equivalent channel from the access point to the user; b 1 Is the first singular vector, i.e. (H) RA ΘH PR +H PA ) Maximum singular value lambda of (2) 1 Is used for the feature vector of (a),
representation b 1 Is a conjugate transpose of (a).
5. The method for closed-form solution of maximum throughput of a wireless power communication network according to claim 1, wherein the equivalent form of channel capacity of the communication system is as follows in the case that an access point does not store energy:
where v is the vectorized form of the phase matrix, P 0 Representing maximum transmit power, P, of a power station 1 Representing access pointsTransmit power at T el And T il Is a sea plug matrix, R el ＝H RA diag(H PR b 1 )，
H PR 、H PA 、H RA The method comprises the steps of respectively representing a baseband equivalent channel from a power station to an intelligent super surface, a baseband equivalent channel from the power station to an access point and a baseband equivalent channel from the intelligent super surface to the access point; h is a RU 、h AU Respectively representing a baseband equivalent channel from the intelligent super surface to the user and a baseband equivalent channel from the access point to the user; b 1 Is the first singular vector, i.e. (H) RA ΘH PR +H PA ) Maximum singular value lambda of (2) 1 Feature vector of>
Representation b 1 Is a conjugate transpose of (a).
6. The method for solving the closed-form solution of the maximum throughput of the wireless power communication network according to claim 5, wherein the equivalent transformation objective function is obtained by utilizing a sea-plug matrix, a complex quadratic form and eigenvalue decomposition, and the method specifically comprises the following steps:
matrix T of sea plug el And T il Is decomposed into
And->
Wherein U is el Is of the column vector of (2)
Forming an orthogonal group, U il Column vector +.>
Forming an orthogonal group; Λ type el Sum lambda il Is a diagonal matrix, Λ el Is singular value +.>
Λ il Is singular value +.>
The maximum throughput optimization problem is rewritten as:
wherein, |v m |=1, m=1, 2,..m+1, adjusted by v
When v will be->
When the phases of all the elements in the array are adjusted to the same direction, < >>
Has a maximum value; by v adjustment->
When v will be->
When the phases of all the elements in the array are adjusted to the same direction, < >>
Has a maximum value;
order the
And->
At lambda el Sum lambda il Wherein the characteristic values are arranged in descending order to obtain +.>
And->
Make the following steps
When v is used to adjust the corresponding lambda max The throughput is maximized when the eigenvector direction of (a).
7. The method of claim 6, wherein the channel capacity of the communication system is as follows:
for a certain communication system, an upper limit of the channel capacity of the communication system is determined when the channel condition and the transmit power of the power station are known.
8. A wireless power communication network maximum throughput closed solution device applied to a communication system with intelligent super-surface assistance, the device comprising:
the energy precoding setting module is used for setting energy precoding according to a first singular vector, wherein the first singular vector is the first singular vector of the right unitary matrix after the energy collection link carries out singular value decomposition;
the information precoding calculation module is used for calculating optimal information precoding according to a maximum combination ratio method;
the objective function acquisition module is used for acquiring an objective function for solving the maximum throughput of the communication system according to the energy precoding and the information precoding;
and the closed solution solving module is used for equivalently converting the objective function by utilizing the sea plug matrix, the complex quadratic form and the eigenvalue decomposition to obtain a closed solution form of the throughput maximum value.
9. A computer device comprising a processor and a memory for storing a processor executable program, wherein the processor, when executing the program stored in the memory, implements the method of solving for a closed-loop maximum throughput solution for a wireless power communication network as claimed in any one of claims 1 to 7.
10. A storage medium storing a program which, when executed by a processor, implements the method of solving for a closed-loop maximum throughput solution for a wireless power communication network according to any one of claims 1 to 7.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107332595A (en) * | 2017-05-22 | 2017-11-07 | 华南理工大学 | A kind of MIMO wireless energies communication network maximize handling capacity method |
| CN112272384A (en) * | 2020-11-03 | 2021-01-26 | 广东工业大学 | Communication system throughput optimization method based on reconfigurable intelligent surface |
| CN112769461A (en) * | 2020-12-11 | 2021-05-07 | 华南理工大学 | Large-scale antenna channel estimation method based on millimeter wave intelligent reflector communication |
| CN112822703A (en) * | 2021-02-03 | 2021-05-18 | 广东工业大学 | Intelligent reflecting surface assisted performance gain optimization method for non-orthogonal multiple access system |
| CN113114317A (en) * | 2021-04-13 | 2021-07-13 | 重庆邮电大学 | IRS-assisted phase shift optimization method for downlink multi-user communication system |
| CN113411115A (en) * | 2021-06-15 | 2021-09-17 | 河南科技大学 | Intelligent reflection surface assisted millimeter wave physical layer security communication joint optimization method |
| CN113709687A (en) * | 2021-08-23 | 2021-11-26 | 郑州大学 | Intelligent reflector assisted resource allocation method for wireless sensor network |
| CN113726383A (en) * | 2021-08-18 | 2021-11-30 | 深圳大学 | Intelligent reflector assisted wireless communication system |
| CN113746578A (en) * | 2021-08-18 | 2021-12-03 | 南京邮电大学 | Communication system transmission method based on assistance of intelligent reflection surface |
| CN114039632A (en) * | 2021-11-26 | 2022-02-11 | 江苏科技大学 | Optimization method, storage medium and system of IRS auxiliary MIMO system |
| CN114172547A (en) * | 2021-12-16 | 2022-03-11 | 华南理工大学 | Wireless energy-carrying communication hybrid precoding design method based on intelligent reflecting surface |
| WO2022055196A1 (en) * | 2020-09-11 | 2022-03-17 | 삼성전자 주식회사 | Multi-antenna-based precoding method and device in wireless communication system |
| CN114531699A (en) * | 2022-01-11 | 2022-05-24 | 广东工业大学 | Optimization method of RIS auxiliary wireless power supply communication network |
| CN115396917A (en) * | 2022-07-29 | 2022-11-25 | 中国人民解放军陆军工程大学 | Intelligent reflector-assisted communication and interference system throughput maximum optimization method |
| WO2022262104A1 (en) * | 2021-06-17 | 2022-12-22 | 清华大学 | Resource allocation and precoding method and apparatus for cell-free network capable of achieving energy efficiency equilibrium |
| KR20230013542A (en) * | 2021-07-19 | 2023-01-26 | 세종대학교산학협력단 | MIMO system including intelligent reflective surface and optimal phase transformation matrix acquisition method for intelligent reflective surface to improve sum capacity of channels applied to it |
-
2023
- 2023-03-02 CN CN202310194325.7A patent/CN116319199B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107332595A (en) * | 2017-05-22 | 2017-11-07 | 华南理工大学 | A kind of MIMO wireless energies communication network maximize handling capacity method |
| WO2022055196A1 (en) * | 2020-09-11 | 2022-03-17 | 삼성전자 주식회사 | Multi-antenna-based precoding method and device in wireless communication system |
| CN112272384A (en) * | 2020-11-03 | 2021-01-26 | 广东工业大学 | Communication system throughput optimization method based on reconfigurable intelligent surface |
| CN112769461A (en) * | 2020-12-11 | 2021-05-07 | 华南理工大学 | Large-scale antenna channel estimation method based on millimeter wave intelligent reflector communication |
| CN112822703A (en) * | 2021-02-03 | 2021-05-18 | 广东工业大学 | Intelligent reflecting surface assisted performance gain optimization method for non-orthogonal multiple access system |
| CN113114317A (en) * | 2021-04-13 | 2021-07-13 | 重庆邮电大学 | IRS-assisted phase shift optimization method for downlink multi-user communication system |
| CN113411115A (en) * | 2021-06-15 | 2021-09-17 | 河南科技大学 | Intelligent reflection surface assisted millimeter wave physical layer security communication joint optimization method |
| WO2022262104A1 (en) * | 2021-06-17 | 2022-12-22 | 清华大学 | Resource allocation and precoding method and apparatus for cell-free network capable of achieving energy efficiency equilibrium |
| KR20230013542A (en) * | 2021-07-19 | 2023-01-26 | 세종대학교산학협력단 | MIMO system including intelligent reflective surface and optimal phase transformation matrix acquisition method for intelligent reflective surface to improve sum capacity of channels applied to it |
| CN113746578A (en) * | 2021-08-18 | 2021-12-03 | 南京邮电大学 | Communication system transmission method based on assistance of intelligent reflection surface |
| CN113726383A (en) * | 2021-08-18 | 2021-11-30 | 深圳大学 | Intelligent reflector assisted wireless communication system |
| WO2023020080A1 (en) * | 2021-08-18 | 2023-02-23 | 深圳大学 | Wireless communication system assisted by intelligent reflecting surface |
| CN113709687A (en) * | 2021-08-23 | 2021-11-26 | 郑州大学 | Intelligent reflector assisted resource allocation method for wireless sensor network |
| CN114039632A (en) * | 2021-11-26 | 2022-02-11 | 江苏科技大学 | Optimization method, storage medium and system of IRS auxiliary MIMO system |
| CN114172547A (en) * | 2021-12-16 | 2022-03-11 | 华南理工大学 | Wireless energy-carrying communication hybrid precoding design method based on intelligent reflecting surface |
| CN114531699A (en) * | 2022-01-11 | 2022-05-24 | 广东工业大学 | Optimization method of RIS auxiliary wireless power supply communication network |
| CN115396917A (en) * | 2022-07-29 | 2022-11-25 | 中国人民解放军陆军工程大学 | Intelligent reflector-assisted communication and interference system throughput maximum optimization method |
Non-Patent Citations (11)
| Title |
|---|
| CHENGHONG YANG; KAI YU; XIANGBIN YU: "Energy Efficiency Optimization for Distributed RIS-Assisted MISO System Based on Statistical CSI", 《2022 IEEE 22ND INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY (ICCT)》, 31 December 2022 (2022-12-31) * |
| EDUARD E. BAHINGAYI; KYUNGCHUN LEE: "Low-Complexity Beamforming Algorithms for IRS-Aided Single-User Massive MIMO mmWave Systems", 《IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS》, 31 December 2022 (2022-12-31) * |
| FENG KE ET AL.: "Sum Throughput Maximization for MIMO Wireless Powered Communication Networks with Discrete Signal Inputs", 《IEICE TRANSACTIONS ON COMMUNICATIONS》, 31 May 2019 (2019-05-31) * |
| XIAOWEI PANG ET AL.: "Energy-efficient design for mmWave-enabled NOMA-UAV networks", 《SCIENCE CHINA INFORMATION SCIENCES》, 30 April 2021 (2021-04-30) * |
| YING ZHANG; HUAN HUANG; CHONGFU ZHANG; ZIXIN ZHAO; JIE PENG; SONGNIAN FU; KUN QIU: "Joint Precoding and User Grouping for RIS-Aided mmWave NOMA System", 《2022 IEEE 14TH INTERNATIONAL CONFERENCE ON ADVANCED INFOCOMM TECHNOLOGY (ICAIT)》, 31 December 2022 (2022-12-31) * |
| 周儒雅;唐万恺;李潇;金石;: "基于可重构智能表面的移动通信简要综述", 移动通信, no. 06 * |
| 周儒雅;唐万恺;李潇;金石;: "基于可重构智能表面的移动通信简要综述", 移动通信, no. 06, 15 June 2020 (2020-06-15) * |
| 啜钢;裴静;刘洪来;唐兴伟;: "协同通信系统中一种新的分析吞吐量的方法", 电子与信息学报, no. 06, 15 June 2010 (2010-06-15) * |
| 徐勇军;谢豪;陈前斌;林金朝;刘期烈;: "基于不完美CSI的异构NOMA网络能效优化算法", 通信学报, no. 07, 31 December 2020 (2020-12-31) * |
| 朱佳佳;吴润泽;唐良瑞;: "基于用户体验质量的异构网络资源分配策略", 计算机工程与设计, no. 05, 15 May 2019 (2019-05-15) * |
| 杨协宜: "新一代无线能量采集通信系统关键技术研究", 《《中国硕士学位论文全文数据库》》, 15 January 2023 (2023-01-15) * |
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