Method for reducing IRS-assisted MIMO multi-demand wireless energy transmission transmitting power

Abstract

The invention provides a method for reducing IRS-assisted MIMO multi-demand wireless energy transmission transmitting power, and relates to the technical field of communication. The method is applied to a communication system comprising a multi-antenna energy emission end (ES), a plurality of multi-antenna energy receiving ends (ER) and at least one intelligent reflecting surface (IRS), and ES beam forming and IRS reflection beam forming are optimized, so that the emission power of the ES can be reduced on the premise of ensuring all ER energy collection requirements. Compared with MIMO multi-demand wireless energy transmission without IRS assistance, the transmitting power of the IRS-assisted MIMO multi-demand wireless energy transmission subjected to beam forming optimization by using the method disclosed by the invention is remarkably reduced under the condition of the same energy collection demand. In addition, semi-definite relaxation is not used for IRS reflection beam forming optimization, and relatively low complexity is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method for reducing IRS-assisted MIMO multi-demand wireless energy transmission transmission power. Background Art

[0002] Wireless energy transmission 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 transmission and reduce the transmission power of the energy transmitter, Multiple-Input Multiple-Output (MIMO) technology is often combined with wireless energy transmission.

[0003] An intelligent reflecting surface (IRS) is a plane composed of a controller and 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 reflection beamforming. At present, some studies have considered using IRS to assist MIMO wireless energy transmission, and further improving the efficiency of wireless energy transmission by optimizing the beamforming of multi-antenna energy transmitters and IRS reflection beamforming, such as "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.]. This study optimizes IRS reflection beamforming based on continuous convex approximation and bisection. However, the optimization method proposed in this study can only be applied to single-demand scenarios (i.e., scenarios with only a single energy receiver), and cannot be applied to multi-demand scenarios (i.e., scenarios with multiple energy receivers). Summary of the invention

[0004] In order to overcome the defects of existing research on IRS-assisted MIMO multi-demand wireless energy transmission, the purpose of the present invention is to provide a method for reducing the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission, through the energy transmitting end beamforming optimization (including the optimization of the number of energy beams and the energy beamforming vector) and the IRS reflection beamforming optimization (including the optimization of the reflection beamforming matrix), under the premise of ensuring all ER energy collection requirements, the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission is reduced.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] The present invention provides a method for reducing the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission, the method is applied to a communication system including a multi-antenna energy transmitter (Energy Station, ES), K multi-antenna energy receivers (Energy Receivers, ER), and at least one intelligent reflective surface 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 of ES is The number of ERs is K, the number of antennas of each ER is N, and the number of IRS reflector units is I. With the assistance of IRS, ES transmits M energy beams to ER. The beamforming vector corresponding to the mth energy beam is The IRS reflection beamforming matrix is ​​Ψ=diag(ψ1,..,ψ I ),in express The set of complex matrices, ψ i =exp(jφ i ) represents the beamforming coefficient on the i-th IRS reflector unit, φ i represents the phase offset introduced by the IRS reflection unit, diag(·) is the diagonal matrix generating 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 respectively denoted as and

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

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

[0010] S2. Solve the optimization problem (1):

[0011]

[0012] in, (·) Hrepresents the conjugate transpose operation, 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 is Decomposition via eigenvalue decomposition for:

[0013]

[0014] in, and Represent the mth largest eigenvalue and its corresponding eigenvector respectively, rank(·) represents the rank of the matrix, let

[0015] S3, set the inner loop counter l = 0, let the intermediate variable Auxiliary variables Dual Variable where h r,k,n H r,k The nth column, h d,k,n H d,k The nth column of is a diagonal matrix The i-th element on the diagonal, (·) T Represents the transpose operation;

[0016] S4. Calculate vector θ according to formula (3) (l+1) ;

[0017]

[0018] in

[0019] S5. According to equations (4) and (5), vectors are calculated in parallel

[0020]

[0021] in,

[0022] S6. Parallel calculation of vectors according to formula (6)

[0023]

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

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

[0026] S9. Order in represents the conjugate operation;

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

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

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

[0030] S13. Order

[0031] S14, minimum ES transmission power achieved by output And the corresponding number of energy beams M * , 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 layer 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 layer loop.

[0033] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0034] The present invention utilizes IRS-assisted MIMO multi-demand wireless energy transmission, and proposes a method for 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 same energy collection demand, the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission after beamforming optimization using the method of the present invention has a significant decrease. In addition, the present invention does not use semi-definite relaxation for IRS reflection beamforming optimization, ensuring relatively low complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

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

[0037] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the word "exemplary" is used to present concepts in a specific way.

[0039] The embodiment of the present invention provides a method for reducing the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission, referring to Figure 1 As shown, the method is applied to a communication system including a multi-antenna energy transmitting end ES, multiple multi-antenna energy receiving ends ER, and at least one intelligent reflecting surface IRS (multiple IRSs in reality can be logically merged into one). By optimizing ES beamforming and IRS reflection beamforming, the transmission power of ES is reduced while ensuring all ER energy collection requirements.

[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 reflectors is I. With the assistance of IRS, ES transmits M energy beams to ER. The beamforming vector corresponding to the mth energy beam is The IRS reflection beamforming matrix is ​​Ψ=diag(ψ1,..,ψ I ),in express The set of complex matrices, ψ i =exp(jφ i ) represents the beamforming coefficient on the i-th IRS reflector unit, φ i represents the phase shift introduced by the IRS reflector, φ i ∈[0,2π), diag(·) is the diagonal matrix generating 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 respectively denoted as and

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

[0042] S1, using channel estimation to obtain H d,k , H r,k and the value of G, and set the energy collection requirement P of the kth ER according to the actual situation r,k And the energy collection efficiency η of all ERs. Preset the penalty coefficient ρ>0, the inner cycle threshold ∈1>0, the outer cycle threshold ∈2>0; set the outer cycle counter v=0, and let I is the identity matrix.

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

[0044] S2. Solve the optimization problem (1):

[0045]

[0046] in, (·) H represents the conjugate transpose operation, 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 is Decomposition via eigenvalue decomposition for:

[0047]

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

[0049] In this step, the interior point method can be used for solution. Please refer to [S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, UK: Cambridge Univ. Press, 2004].

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

[0051] S4. Calculate vector θ according to formula (3) (l+1) ;

[0052]

[0053] in

[0054] S5. According to equations (4) and (5), vectors are calculated in parallel

[0055]

[0056] in,

[0057] S6. Parallel calculation of vectors according to formula (6)

[0058]

[0059] S7. Let l=l+1.

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

[0061] S9. Order in Represents the conjugate operation.

[0062] S10, if v=0, 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. Order

[0066] S14, minimum ES transmission power achieved by output And the corresponding number of energy beams M * , energy beamforming vector and the 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 layer 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 layer loop.

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

[0069] The present invention utilizes IRS-assisted MIMO multi-demand wireless energy transmission, and proposes a method for 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 same energy collection demand, the transmission power of IRS-assisted MIMO multi-demand wireless energy transmission after beamforming optimization using the method of the present invention has a significant decrease. In addition, the present invention does not use semi-definite relaxation for IRS reflection beamforming optimization, ensuring relatively low complexity.

[0070] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0071] References in the specification to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments", etc. indicate that the described embodiments may include a particular feature, structure, or characteristic, but not every embodiment may include the particular feature, structure, or characteristic. In addition, when a particular feature, structure, or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the relevant art to implement such feature, structure, or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0072] In the present invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0073] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0074] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0075] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0076] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for reducing the transmit power of IRS-assisted MIMO multi-demand wireless energy transmission, characterized in that: The method is applied to a communication system comprising a multi-antenna energy transmitting end ES, K multi-antenna energy receiving ends ER, and at least one intelligent reflecting surface IRS; when there are multiple IRSs in the communication system, they are logically merged into one IRS; 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 reflector units is I. With the assistance of IRS, ES transmits M energy beams to ER. The beamforming vector corresponding to the mth energy beam is The IRS reflection beamforming matrix is ​​Ψ=diag(ψ1,..,ψ I ),in express The set of complex matrices, ψ i =exp(jφ i ) represents the beamforming coefficient on the i-th IRS reflector unit, φ i represents the phase offset introduced by the IRS reflection unit, diag(·) is the diagonal matrix generating 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 respectively denoted as and The method optimizes ES beamforming and IRS reflective beamforming to reduce the ES transmit power while ensuring all ER energy collection requirements: S1, using channel estimation to obtain H d,k , H r,k and the value of G, and set the energy collection requirement P of the kth ER according to the actual situation r,k And the energy collection efficiency η of all ERs, the preset penalty coefficient ρ>0, the inner cycle threshold ∈1>0, the outer cycle threshold ∈2>0; set the outer cycle counter v=0, let Where I is the identity matrix; S2. Solve the optimization problem (1): in, (·) H represents the conjugate transpose operation, tr(·) represents the trace operation; the optimization problem (1) is a standard convex optimization problem, which is solved by the interior point method, and the optimal solution is Decomposition via eigenvalue decomposition for: in, and Represent the mth largest eigenvalue and its corresponding eigenvector respectively, rank(·) represents the rank of the matrix, let S3, set the inner loop counter l = 0, let the intermediate variable β k,m,n =||c k,m,n ||, auxiliary variable Dual Variable k=1,..,K, n=1,..,N,where h r,k,n H r,k The nth column, h d,k,n H d,k The nth column of is a diagonal matrix The i-th element on the diagonal, (·) T Represents the transpose operation; S4. Calculate vector θ according to formula (3) (l+1) ; in S5. According to equations (4) and (5), vectors are calculated in parallel k=1,..,K, n=1,...,N; in, b k,m,n =c k,m,n / β k,m,n ; S6. Parallel calculation of vectors according to formula (6) S7, let l=l+1; S8, if Then continue to step S9, otherwise jump to step S4; S9. Order in represents the conjugate operation; S10, if v=0, set v=v+1 and jump to step S2, otherwise continue to step S11; S11, if Then jump to step S13, otherwise continue to step S12; S12, let v=v+1, jump to step S2; S13. Order S14, minimum ES transmission power achieved by output And the corresponding number of energy beams M * , energy beamforming vector and the reflection beamforming matrix Ψ * .

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