A method for reducing transmission power of IRS-assisted MIMO multi-demand wireless energy transmission

Abstract

The application provides a method for reducing the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission, and relates to the technical field of communication. The method is applied to a communication system comprising one multi-antenna energy transmission end ES, a plurality of multi-antenna energy receiving ends ER and at least one intelligent reflecting surface IRS. By optimizing ES beamforming and IRS reflecting beamforming, the transmission power of ES can be reduced under the premise of ensuring the energy collection demand of all ERs. Compared with MIMO multi-demand wireless energy transmission without IRS assistance, the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission after beamforming optimization using the method of the application is significantly reduced under the condition of the same energy collection demand. In addition, the application does not use semi-positive relaxation for IRS reflecting beamforming optimization, thereby ensuring relatively low complexity.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication technology, in particular to a method for reducing the transmission power of IRS-aided MIMO multi-demand wireless energy transfer. BACKGROUND

[0002] Wireless energy transfer is a promising key technology that can solve the energy limitation problem of small (micro) wireless communication devices (such as sensor nodes in wireless sensor networks). In order to improve the efficiency of wireless energy transfer and reduce the transmission power of the energy transmission end, Multiple-Input Multiple-Output (MIMO) technology is often combined with wireless energy transfer.

[0003] Intelligent Reflecting Surface (IRS) is a plane composed of a large number of micro units that can introduce phase shifts when reflecting wireless signals. By configuring the phase shift introduced by each micro unit when reflecting wireless signals, IRS can achieve fine reflected beamforming. Currently, there have been studies on IRS-aided MIMO wireless energy transfer, which further improve the efficiency of wireless energy transfer by optimizing the beamforming of the multi-antenna energy transmission end and the reflected beamforming of the IRS, for example, “Intelligent reflecting surface aided MIMO broadcasting for simultaneous wireless information and power transfer”

IEEE Journal on Selected Areas in Communications, vol. 38, no. 8, Aug. 2020.

[0004] To overcome the shortcomings of existing research in the field of IRS-aided MIMO multi-demand wireless energy transfer, the purpose of the present application is to provide a method for reducing the transmission power of IRS-aided MIMO multi-demand wireless energy transfer. Through beamforming optimization of the energy transmission end (including optimization of the number of energy beams and energy beamforming vectors) and reflected beamforming optimization of the IRS (including optimization of the reflected beamforming matrix), the transmission power of IRS-aided MIMO multi-demand wireless energy transfer is reduced while ensuring the energy collection needs of all ERs.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] This invention provides a method for reducing the transmit power of IRS-assisted MIMO multi-demand wireless power transmission. The method is applied to a communication system comprising a multi-antenna energy station (ES), K multi-antenna energy receivers (ER), and at least one smart reflector IRS. When there are multiple IRSs in the communication system, they are logically merged into one IRS.

[0007] In the communication system, the number of antennas for ES is: There are K energy emitters (ERs), N antennas per ER, and I I I I-cell reflector elements. With IRS assistance, the energy emitter (ES) transmits M energy beams to the ERs. Let the beamforming vector corresponding to the m-th energy beam be denoted as... The IRS reflected beamforming matrix is ​​Ψ=diag(ψ1,..,ψ I ),in express The set of dimensional complex matrices, ψ i =exp(jφ i ) represents the beamforming factor on the i-th IRS reflecting unit, φ i The phase shift introduced by the IRS reflection unit is represented by diag(·), which is the diagonal matrix generating function; the channels from ES to the k-th ER, from ES to IRS, and from IRS to the k-th ER are respectively denoted as... and

[0008] The method includes optimizing ES beamforming and IRS reflection beamforming:

[0009] S1. Obtain H using channel estimation. d,k H r,k And the value of G, and set the energy harvesting requirement P for the k-th ER according to the actual situation. r,k And the energy harvesting efficiency η of all ERs, with a preset penalty coefficient ρ>0, inner loop threshold ∈1>0, and outer loop threshold ∈2>0; let the outer loop counter v=0, and let Where I is the identity matrix;

[0010] S2, Solving the optimization problem (1):

[0011]

[0012] in, (·) Hdenotes the conjugate transpose operation, tr(·) denotes the trace operation; the optimization problem (1) is a standard convex optimization problem, which can be solved by interior point method, and the optimal solution is by eigenvalue decomposition is:

[0013]

[0014] where, and denote the m-th largest eigenvalue and its corresponding eigenvector, respectively, rank(·) denotes the rank of a matrix, and let

[0015] S3, set the inner loop counter l=0, and let the intermediate variable auxiliary variable dual variable where h r,k,n is the n-th column of H r,k , h d,k,n is the n-th column of H d,k , and is a diagonal matrix whose i-th diagonal element is (·) T denotes the transpose operation;

[0016] S4, calculate the vector θ (l+1) according to equation (3);

[0017]

[0018] where

[0019] S5, calculate the vector

[0020]

[0021] where,

[0022] S6, calculate the vector

[0023]

[0024] S7, let l=l+1;

[0025] S8, if continue to step S9, otherwise jump to step S4;

[0026] S9, let wherein denotes a conjugate operation;

[0027] S10, if v = 0, then let v = v + 1 and jump to step S2, otherwise continue step S11;

[0028] S11, if then jump to step S13, otherwise continue step S12;

[0029] S12, let v = v + 1, jump to step S2;

[0030] S13, let

[0031] S14, output the minimum ES transmit power and the number of energy beams M * , the energy beamforming vector and the reflection beamforming matrix Ψ * .

[0032] The method alternately optimizes ES beamforming and IRS reflection beamforming, wherein step S1 is initialization, steps S2-S12 are an outer alternating optimization loop, step S2 is ES beamforming optimization, steps S3-S9 are IRS reflection beamforming optimization, wherein step S3 is an initialization step of IRS reflection beamforming optimization, and steps S4-S8 are an inner loop.

[0033] The technical solution provided by the present application has at least the following beneficial effects:

[0034] The present application uses IRS-assisted MIMO multi-demand wireless energy transmission and proposes a method for reducing ES transmit power by optimizing energy transmitter beamforming and IRS reflection beamforming. Compared with MIMO multi-demand wireless energy transmission without IRS assistance, the transmit power of IRS-assisted MIMO multi-demand wireless energy transmission after beamforming optimization using the method of the present application is significantly reduced under the same energy collection demand. In addition, the present application does not use semi-positive relaxation for IRS reflection beamforming optimization, which ensures relatively low complexity. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0036] Figure 1 is a method flowchart for reducing the transmission power of an IRS-assisted MIMO multi-demand wireless energy transmission provided by an embodiment of the present application. DETAILED DESCRIPTION

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be described below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the described embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0038] In the embodiments of the present application, the words “exemplary”, “for example”, and the like are used to represent an example, an illustration, or a description. Any embodiment or design solution described as “exemplary” in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design solutions. Rather, the word “exemplary” is used to present the concept in a specific manner.

[0039] The embodiments of the present application provide a method for reducing the transmission power of an IRS-assisted MIMO multi-demand wireless energy transmission, as shown in Figure 1 , the method is applied to a communication system including one multi-antenna energy transmission end ES, multiple multi-antenna energy receiving ends ER, and at least one intelligent reflecting surface IRS (multiple IRSs in reality can be logically combined into one), by optimizing ES beamforming and IRS reflecting beamforming, the transmission power of ES is reduced under the premise of ensuring the energy collection demand of all ERs.

[0040] In the communication system, the number of antennas of ES is The number of ERs is K, the number of antennas of each ER is N, and the number of IRS reflecting units is I. Under the assistance of IRS, ES transmits M energy beams to ER Let the beamforming vector corresponding to the mth energy beam be The IRS reflecting beamforming matrix is Ψ = diag(ψ1,.., ψ I ), where represents a set of N × N complex matrices, ψ i = exp(jφ i ) represents the beamforming coefficient on the ith IRS reflecting unit, φ i represents the phase offset introduced by the IRS reflecting unit, φ i ∈ [0, 2π), and diag(·) is the diagonal matrix generation function. The channel from ES to the kth ER, the channel from ES to IRS, and the channel from IRS to the kth ER are denoted as and

[0041] The optimization of the ES beamforming and the IRS reflective beamforming comprises the following steps:

[0042] S1, obtaining H d,k , H r,k and the value of G, setting the energy collection requirement P r,k of the kth ER and the energy collection efficiency η of all ERs according to the actual situation. The preset penalty coefficient ρ>0, the inner loop threshold ∈1>0, and the outer loop threshold ∈2>0; set the outer loop counter v=0, and let I is a unit matrix.

[0043] Wherein, the penalty coefficient is related to the convergence speed of the optimization of the IRS reflective beamforming matrix, and the threshold value is related to the optimization accuracy.

[0044] S2, solving the optimization problem (1):

[0045]

[0046] Wherein, (·) H represents the conjugate transpose operation, and tr(·) represents the trace operation; the optimization problem (1) is a standard convex optimization problem, which can be solved by the interior point method, and the optimal solution obtained is By eigenvalue decomposition, decompose into:

[0047]

[0048] Wherein, and represent the mth largest eigenvalue and the corresponding eigenvector respectively, and rank(·) represents the rank of the matrix, let

[0049] In this step, the interior point method can refer to

S.Boyd and L.Vandenberghe,Convex Optimization.Cambridge,U.K.:Cambridge Univ.Press,2004

[0050] S3, set the inner loop counter l=0, and let the intermediate variable β k,n,n =||c k,m,n ||, the auxiliary variable the dual variable where h r,k,n is the nth column of H r,k where h d,k,n is the nth column of H d,k , is a diagonal matrix is the ith element on the diagonal, (·) T denotes the transpose operation.

[0051] S4, compute the vector θ (l+1) according to equation (3)

[0052]

[0053] where

[0054] S5, compute the vector according to equations (4) and (5) in parallel

[0055]

[0056] where

[0057] S6, compute the vector according to equation (6) in parallel

[0058]

[0059] S7, set l = l + 1.

[0060] S8, if then continue to step S9, otherwise jump to step S4.

[0061] S9, set where denotes the conjugate operation.

[0062] S10, if v = 0 then set v = v + 1 and jump to step S2, otherwise continue to step S11.

[0063] S11, if then jump to step S13, otherwise continue to step S12.

[0064] S12, set v = v + 1 and jump to step S2.

[0065] S13, set

[0066] S14, output the minimum ES transmit power reached and the number of energy beams M * corresponding to it, the energy beamforming vector and a reflection beamforming matrix Ψ * .

[0067] The method alternately optimizes ES beamforming and IRS reflection beamforming, wherein step S1 is initialization, steps S2-S12 are an outer alternating optimization loop, step S2 is ES beamforming optimization, steps S3-S9 are IRS reflection beamforming optimization, wherein step S3 is an initialization step of IRS reflection beamforming optimization, and steps S4-S8 are an inner loop.

[0068] Compared with the prior art, the present application has the following advantages:

[0069] The present application utilizes IRS-aided MIMO multi-demand wireless energy transmission, and proposes a method of reducing ES transmission power by optimizing energy transmitting end beamforming and IRS reflection beamforming. Compared with MIMO multi-demand wireless energy transmission without IRS assistance, under the condition of the same energy collection demand, the transmission power of the IRS-aided MIMO multi-demand wireless energy transmission after beamforming optimization using the method of the present application is significantly reduced. In addition, the present application does not use semi-positive relaxation for IRS reflection beamforming optimization, which ensures relatively low complexity.

[0070] It should be noted that, in the present document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, such that processes, methods, articles, or terminal devices that comprise a list of elements do not only include those elements, but can also include other elements that are not expressly listed, or other elements that are inherent to such processes, methods, articles, or terminal devices. Without more limitations, an element defined by the phrase "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0071] In the description, "one embodiment", "an embodiment", "exemplary embodiment", "some embodiments", and the like indicate that the described embodiment can include a particular feature, structure, or characteristic, but every embodiment can not necessarily include the particular feature, structure, or characteristic. In addition, when a particular feature, structure, or characteristic is described in connection with an embodiment, it should be understood that the implementation of this feature, structure, or characteristic in connection with other embodiments, whether or not explicitly described, should be within the knowledge of those skilled in the relevant art.

[0072] In the present application, "at least one" means one or more, and "multiple" means two or more. "At least one of the following" or the like means any combination of the items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0073] It should be understood that the size of the sequence number of each process described above in various embodiments of the present application does not mean the order of execution, and the execution order of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0074] If the function is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0075] The present application covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present application. In order to make the public have a thorough understanding of the present application, specific details are described in the following preferred embodiments of the present application, and the present application can also be completely understood without the description of these details to those skilled in the art. In addition, in order to avoid unnecessary confusion to the essence of the present application, well-known methods, processes, flows, elements and circuits, etc. are not described in detail.

[0076] The above is only the preferred embodiment of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for reducing the transmit power of IRS-assisted MIMO multi-demand wireless power transfer, characterized in that, The method is applied to a communication system comprising a multi-antenna energy transmitter (ES), K multi-antenna energy receivers (ER), and at least one intelligent reflector (IRS); when there are multiple IRS in the communication system, they are logically merged into one IRS. In the communication system, the number of antennas for ES is: There are K energy emitters (ERs), N antennas per ER, and I I I I-cell reflector elements. With IRS assistance, the energy emitter (ES) transmits M energy beams to the ERs. Let the beamforming vector corresponding to the m-th energy beam be denoted as... The IRS reflected beamforming matrix is ​​Ψ=diag(ψ1,..,ψ I ),in express The set of dimensional complex matrices, ψ i =exp(jφ i ) represents the beamforming factor on the i-th IRS reflecting unit, φ i The phase shift introduced by the IRS reflection unit is represented by diag(·), which is the diagonal matrix generating function; the channels from ES to the k-th ER, from ES to IRS, and from IRS to the k-th ER are respectively denoted as... and The method optimizes ES beamforming and IRS reflection beamforming to reduce the ES transmit power while ensuring all ER energy harvesting requirements are met. S1. Obtain H using channel estimation. d,k H r,k And the value of G, and set the energy harvesting requirement P for the k-th ER according to the actual situation. r,k And the energy harvesting efficiency η of all ERs, with a preset penalty coefficient ρ>0, inner loop threshold ∈1>0, and outer loop threshold ∈2>0; let the outer loop counter v=0, and let Where I is the identity matrix; S2, Solving the optimization problem (1): in, (·) H The conjugate transpose operation is represented by tr(·), and the trace operation is represented by tr(·). The optimization problem (1) is a standard convex optimization problem, which is solved by the interior point method. The optimal solution obtained is: Eigenvalue decomposition for: in, and Let represent the m-th largest eigenvalue and its corresponding eigenvector, respectively, and rank(·) denote the rank of the matrix. S3. Set the inner loop counter l = 0, and let the intermediate variable... β k,m,n =||c k,m,n ||, auxiliary variable Dual variables k = 1, ..., K n = 1, ..., N, where h r,k,n For H r,k The nth column, h d,k,n For H d,k The nth column, diagonal matrix The i-th element on the diagonal, (·) T Indicates the transpose operation; S4. Calculate vector θ according to equation (3). (l+1) ; in S5. Based on equations (4) and (5), calculate the vector in parallel. k = 1, ..., K n = 1, ..., N; in, b k,m,n =c k,m,n / β k,m,n ; S6. Calculate vectors in parallel according to equation (6). S7. Let l = l + 1; S8, if Continue to step S9; otherwise, proceed to step S4. S9, Order in Indicates conjugate operation; S10. If v = 0, then let v = v + 1 and jump to step S2; otherwise, continue to step S11. S11, if If so, proceed to step S13; otherwise, continue to step S12. S12. Let v = v + 1, then jump to step S2; S13, Order S14, Minimum ES transmit power achieved by the output And the corresponding number of energy beams M * Energy beamforming vector and the reflected beamforming matrix Ψ * .

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