Wireless energy-carrying communication method and system

Abstract

The embodiment of the present application provides a wireless energy-carrying communication method and system, which belongs to the field of wireless communication technology. The method includes: obtaining a preset power allocation function; wherein the power allocation function is a function obtained according to a pre-built reference communication system, and the reference communication system includes a reference base station, a reference information receiver, and a reference energy receiver; determining a first number of target energy receivers in the target communication system, and determining a second number of target information receivers in the target communication system; performing power calculation on the power allocation function according to the first number, the second number, and the preset constraint conditions to obtain the target power; and performing power allocation on the target energy receiver and the target information receiver according to the target power. The embodiment of the present application can realize wireless energy-carrying communication in a mixed scenario of near-field communication and far-field communication.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a wireless energy-carrying communication method and system. Background Art

[0002] Simultaneous Wireless Information and Power Transfer (SWIPT) is a technology that can transmit signals and energy at the same time, that is, it can provide energy to wireless devices while exchanging information with wireless devices. In related technologies, the research on wireless energy communication methods mainly considers near-field communication or far-field communication, but in practical applications, the mixed situation of near-field communication and far-field communication is more likely to occur, that is, near-field terminals and far-field terminals appear in the wireless communication network at the same time. Therefore, if a wireless energy communication method is provided to adapt to the mixed situation of near-field communication and far-field communication, it has become a technical problem to be solved urgently. Summary of the invention

[0003] The main purpose of the embodiments of the present application is to propose a wireless power-carrying communication method and system, aiming to realize wireless power-carrying communication in a mixed scenario of near-field communication and far-field communication.

[0004] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a wireless energy-carrying communication method, the method comprising:

[0005] Obtain a preset power allocation function; wherein the power allocation function is a function obtained according to a pre-constructed reference communication system, the reference communication system includes a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is within a first preset distance range, the distance between the reference information receiver and the reference base station is within a second preset distance range, and the maximum value of the first preset distance range is less than the minimum value of the second preset distance range;

[0006] determining a first number of target energy receivers in a target communication system, and determining a second number of target information receivers in the target communication system;

[0007] Performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power;

[0008] Power is allocated to the target energy receiver and the target information receiver according to the target power.

[0009] In some embodiments, the method of constructing the power allocation function according to the reference communication system includes:

[0010] determining a first distance between the reference base station and the reference energy receiver;

[0011] Obtaining a near-field channel model according to the first distance, a first spatial angle between the reference base station and the reference energy receiver;

[0012] determining a second distance between the reference base station and the reference information receiver;

[0013] Obtaining a far-field channel model according to the second distance, a second spatial angle between the reference base station and the reference information receiver;

[0014] Constructing a received signal model of the reference information receiver according to the far-field channel model;

[0015] Constructing a collection power model of the reference energy receiver according to the near-field channel model;

[0016] A reference correlation matrix of the reference information receiver and the reference energy receiver is obtained, and the power allocation function is constructed according to the reference correlation matrix, the received signal model, and the collection power model.

[0017] In some embodiments, performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint to obtain a target power includes:

[0018] If the first number is equal to zero and the second number is not equal to zero, transforming the power allocation function to obtain a first allocation function;

[0019] The power of the first allocation function is calculated according to the preset constraint conditions to obtain the target power; wherein the preset constraint conditions include and ID ≥0, M represents the second number, represents the coefficient vector of the target information receiver m, y ID represents a power allocation vector of the target information receiver, represents a target correlation matrix between the target information receiver and the target energy receiver, represents the noise of the target information receiver m, and R represents the achievable rate of the target information receiver.

[0020] In some embodiments, performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint to obtain a target power includes:

[0021] If the first number is not equal to zero and the second number is equal to zero, transforming the power allocation function to obtain a second allocation function;

[0022] The power of the second allocation function is calculated according to the preset constraint condition to obtain the target power; wherein the preset constraint condition includes and EH ≥0, K represents the first number, M represents the second number, y EH represents the power allocation vector of the target energy receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

[0023] In some embodiments, performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint to obtain a target power includes:

[0024] If the first number is not equal to zero, and the second number is equal to 1, transforming the power allocation function to obtain a third allocation function;

[0025] The power of the third allocation function is calculated according to the preset constraint conditions to obtain the target power; wherein the preset constraint conditions include c ID represents the coefficient vector of the target information receiver, represents the power allocation vector of the target energy receiver and the target information receiver, represents a target correlation matrix between the target information receiver and the target energy receiver, represents the noise of the target information receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

[0026] In some embodiments, performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint to obtain a target power includes:

[0027] If the first number is not equal to zero, and the second number is not equal to zero, obtaining a preset variable;

[0028] The power allocation function is used to calculate the power according to the preset variables and the preset constraints to obtain the target power; wherein the preset constraints include y≥0, M represents the second quantity, S m and I m All represent preset variables, R represents the achievable rate of the target information receiver, represents the coefficient vector of the target information receiver m, and y represents the power allocation vector of the target energy receiver and the target information receiver.

[0029] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application proposes a wireless energy-carrying communication system, the system comprising:

[0030] A power allocation function acquisition module, used to acquire a preset power allocation function; wherein the power allocation function is a function obtained according to a pre-built reference communication system, the reference communication system includes a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is within a first preset distance range, the distance between the reference information receiver and the reference base station is within a second preset distance range, and the maximum value of the first preset distance range is less than the minimum value of the second preset distance range;

[0031] a quantity determination module, configured to determine a first quantity of target energy receivers in a target communication system, and to determine a second quantity of target information receivers in the target communication system;

[0032] a power calculation module, configured to perform power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power;

[0033] A power allocation module is used to allocate power to the target energy receiver and the target information receiver according to the target power.

[0034] To achieve the above objectives, a third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0035] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0036] The wireless energy-carrying communication method and system proposed in the present application constructs a power allocation function through a pre-constructed reference communication system, and solves the power allocation function according to the first number of target energy receivers and the second number of target information receivers in the target communication system to obtain the target power. Since the reference communication system includes a reference energy receiver set within a first preset distance range and a reference information receiver set within a second preset distance range, the constructed power allocation function can adapt to the target communication system including the target energy receiver and the target information receiver, thereby realizing wireless energy-carrying communication in a mixed far-field and near-field situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of a wireless energy carrying communication method provided in an embodiment of the present application;

[0038] Figure 2 is a schematic diagram of a reference communication system provided in an embodiment of the present application;

[0039] Figure 3 is a flow chart of constructing a power allocation function provided by an embodiment of the present application;

[0040] Figure 4 yes Figure 1 Flow chart of step S103 in FIG.

[0041] Figure 5 yes Figure 1 A flowchart of another embodiment of step S103 in FIG.

[0042] Figure 6 yes Figure 1 A flowchart of another embodiment of step S103 in FIG.

[0043] Figure 7 yes Figure 1 A flowchart of another embodiment of step S103 in FIG.

[0044] Figure 8 is a schematic diagram of the structure of a wireless energy-carrying communication system provided in an embodiment of the present application;

[0045] Fig. 9 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] It should be noted that, although the functional modules are divided in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0049] First, refer to Table 1 below to analyze several terms involved in this application:

[0050]

[0051]

[0052] Table 1

[0053] The sixth generation (6G) of wireless networks is expected to support the growing demand for ultra-high data rates, ultra-high reliability, ultra-low latency, and extremely low power consumption. However, the existing fifth generation (5G) technology may not be able to fully meet these requirements, so new technologies need to be developed for 6G. For example, 6G communications are expected to migrate to higher frequency bands, such as millimeter wave (mmWave) and terahertz (THz), to take advantage of the huge available bandwidth. In addition, by dramatically increasing the number of antennas to another order of magnitude, ultra-high spectral efficiency and spatial resolution can be achieved through ultra-large-scale arrays / surfaces (XL-array / surface), which can greatly compensate for the severe path loss in high-frequency bands.

[0054] With the significant increase in carrier frequency and the number of antennas, the well-known Rayleigh distance will be extended to tens or even hundreds of meters. This will lead to a fundamental paradigm shift in the characteristics of electromagnetic fields, moving from traditional far-field communications to new near-field communications. Specifically, unlike far-field communications where the electromagnetic field can be approximated as a plane wave, radio propagation in near-field communications should be accurately modeled with spherical waves. This unique channel characteristic enables a new capability of beam focusing, which is able to focus the beam energy at a specific location (area) rather than a specific direction as in traditional far-field communications. In order to obtain the beam focusing gain of XL-array, near-field channel estimation / beam training is essential, which is, however, more challenging than far-field communication. For example, near-field beam training requires two-dimensional beam search in both the angle domain and the distance domain, which is very different from the far-field case where only one-dimensional angular domain beam search is required. Therefore, applying the DFT-based far-field codebook to near-field beam training will result in a degradation in training accuracy and rate performance. This phenomenon can be explained by the near-field energy diffusion effect, where the energy of the far-field beam along a specific direction will be dispersed to multiple angles in the near field, making it difficult to determine the true terminal angle based on the maximum received signal power. To solve this problem, a new polar codebook is proposed in the related art, where each beam codeword points to a specific location with a target angle and distance. A direct beam training method using this codebook is to perform a two-dimensional exhaustive search for all possible beam codewords. However, this method results in extremely high beam training overhead, leaving less time for data transmission. To reduce the training overhead, an efficient two-phase beam training method is proposed in the related art, which first estimates the terminal spatial angle and then determines the terminal distance. This method relies on a key fact that when using far-field DFT beams for beam training, the true terminal spatial angle is roughly in the middle of the main angle region where the received signal power is high enough. The required training overhead can be further reduced by designing hierarchical near-field beam training and using deep learning methods for beam training.

[0055] Near-field or far-field communication is mainly considered in related technologies, but in practical applications, hybrid near-field and far-field communication is more likely to occur, that is, near-field and far-field terminals exist in the network at the same time. For example, assume that a base station (BS) has an antenna diameter of 0.5 meters (m) and an operating frequency of 30GHz. The well-known Rayleigh distance in this case is about 50m. This means that in a representative communication scenario, the terminal may be located in the near-field or far-field area of ​​the base station, resulting in more complex interference problems. More specifically, due to the energy diffusion effect, the near-field terminal may be strongly interfered by the DFT-based far-field beam when the spatial angle of the near-field terminal is near the far-field terminal angle. On the other hand, the energy leakage of the DFT-based far-field beam can also be used to effectively charge near-field users, resulting in a new application of hybrid near-far-field wireless energy transmission (SWIPT), in which the energy harvester (EH) is located in the near field and the information decoding (ID) receiver is located in the far field.

[0056] The related technologies focus on the design of traditional far-field SWIPT and near-field SWIPT systems. However, for the phenomenon of mixed far-field and near-field, the related technologies will face the problem of performance loss due to system mismatch. Moreover, there is no effective design for mixed-field SWIPT systems.

[0057] In addition, the system design of hybrid near- and far-field SWIPT faces several new challenges. For example, by exploiting the near-field beam focusing characteristics, the beamforming of the near-field EH receiver should be carefully designed to maximize the EH efficiency while minimizing the interference to the far-field ID receiver. Second, the energy spreading effect should be considered when designing the beamforming for the far-field ID receiver, which can opportunistically charge the near-field EH receiver when it is located at a similar angle. In addition, the power allocation of the BS should be carefully designed to balance the new near- and far-field trade-off in hybrid-field SWIPT with the effects of beam focusing and energy spreading.

[0058] Based on this, the embodiments of the present application provide a wireless energy-carrying communication method and system, aiming to realize wireless energy-carrying communication in mixed far-field and near-field conditions.

[0059] The wireless energy-carrying communication method provided in the embodiment of the present application is described below.

[0060] Reference Figure 1 , an embodiment of the present application provides a wireless energy-carrying communication method, which includes but is not limited to steps S101 to S104.

[0061] Step S101, obtaining a preset power allocation function; wherein the power allocation function is a function obtained according to a pre-constructed reference communication system, the reference communication system includes a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is within a first preset distance range, the distance between the reference information receiver and the reference base station is within a second preset distance range, and the maximum value of the first preset distance range is less than the minimum value of the second preset distance range;

[0062] Step S102, determining a first number of target energy receivers in a target communication system, and determining a second number of target information receivers in the target communication system;

[0063] Step S103, performing power calculation on the power allocation function according to the first quantity, the second quantity, and the preset constraint condition to obtain the target power;

[0064] Step S104: Allocate power to the target energy receiver and the target information receiver according to the target power.

[0065] In steps S101 to S104 shown in the embodiment of the present application, a power allocation function is constructed through a pre-constructed reference communication system, and the power allocation function is solved according to the first number of target energy receivers and the second number of target information receivers in the target communication system to obtain the target power. Since the reference communication system includes a reference energy receiver set within a first preset distance range and a reference information receiver set within a second preset distance range, the constructed power allocation function can adapt to the target communication system including the target energy receiver and the target information receiver, thereby realizing wireless energy-carrying communication in a mixed far-field and near-field situation.

[0066] In step S101 of some embodiments, referring to Figure 2 The power allocation function is based on Figure 2 The power allocation function is a function obtained by constructing the reference communication system shown in the figure, and is used to describe the power allocated to each receiver. In the reference communication system, a reference base station, a reference information receiver (i.e., an ID receiver), and a reference energy receiver (i.e., an EH receiver) are included. The area within a first preset distance range from the reference base station is regarded as a near-field area, and the area within a second preset distance range from the reference base station is regarded as a far-field area. The reference energy receiver is in the near-field area, and the reference information receiver is in the far-field area. The second preset distance range is greater than the so-called Rayleigh distance, defined as Where D represents the antenna array aperture, and λ represents the carrier wavelength. It can be understood that the reference base station is in the form of a very large-scale array, such as including N antennas. The reference information receiver and the reference energy receiver are both single-antenna receivers. The reference communication system may include multiple reference information receivers and multiple reference energy receivers, such as including K single-line reference energy receivers and M reference energy receivers. The reference base station uses a hybrid beamforming method to allocate power to K+M reference energy receivers and reference information receivers, where the number of reference base station RF circuits satisfies N RF ≥K+M.

[0067] refer to Figure 3 The method for constructing a power allocation function according to a reference communication system includes but is not limited to steps S301 to S307.

[0068] Step S301, determining a first distance between a reference base station and a reference energy receiver;

[0069] Step S302, obtaining a near-field channel model according to a first distance, a first spatial angle between a reference base station and a reference energy receiver;

[0070] Step S303, determining a second distance between the reference base station and the reference information receiver;

[0071] Step S304, obtaining a far-field channel model according to the second distance, a second spatial angle between the reference base station and the reference information receiver;

[0072] Step S305, constructing a received signal model of a reference information receiver according to the far-field channel model;

[0073] Step S306, constructing a collection power model of a reference energy receiver according to the near-field channel model;

[0074] Step S307, obtaining a reference correlation matrix of a reference information receiver and a reference energy receiver, and constructing a power allocation function according to the reference correlation matrix, a received signal model, and a collection power model.

[0075] In steps S301 to S302 of some embodiments, for a reference energy receiver k in the near field region, its channel from the XL-array BS can be modeled as:

[0076]

[0077] There is a LoS path and L between the reference base station and the reference energy receiver k. kIn the embodiment of the present application, considering that the SWIPT channels in high frequency bands (such as mmWave and THz) are easily blocked, the LoS channel components of the reference energy receiver and the reference information receiver are mainly considered, and the NLoS component is ignored due to its low power. Therefore, the channel from the reference base station to the reference energy receiver k can be approximated as

[0078] The modeling process of the near-field channel model is as follows. First, based on the near-field spherical wavefront propagation model, the nth antenna of the reference base station (i.e. (0, δ n d)) Distance from reference energy receiver k As shown in the following formula (1).

[0079]

[0080] in, represents the distance between the center of the reference base station and the reference energy receiver k (i.e., the first distance), represents the spatial angle at the reference base station (i.e., the first spatial angle), φ k represents the physical AoD from the reference base station center to the reference energy receiver k.

[0081] Then, using the second-order Taylor expansion The LoS channel between the nth antenna of the reference base station and the reference energy receiver k can be modeled as in, is the complex channel gain in the direction of the reference energy receiver k antenna. It can be understood that when the distance between the reference base station and the reference energy receiver k is r k When the distance is less than the Rayleigh distance, the second-order Taylor expansion is used is accurate enough.

[0082] Assume that the reference energy receiver k is located in the Fresnel Zone of radiation, that is, Under the above assumptions, we can get in is the shared complex-valued channel gain for different antennas.

[0083] Based on the above, the near-field channel dominated by LoS from the reference base station to the reference energy receiver k (i.e., the near-field channel model) can be simply modeled as shown in the following equation (2).

[0084]

[0085] Among them, b(θ k ,r k) represents the normalized near-field channel steering vector, which can be calculated by the following formula (3).

[0086]

[0087] In steps S303 to S304 of some embodiments, for each reference information receiver (such as reference information receiver m) located in the far-field area of ​​the reference base station, the channel of the reference information receiver from the reference base station can be characterized based on the plane wavefront propagation model as shown in the following equation (4).

[0088]

[0089] There is a LoS path and L between the reference base station and the reference information receiver m. m By ignoring the negligible NLoS components in the high frequency band, the channel between the reference base station and the reference information receiver m (i.e., the far-field channel model) can be approximated by the corresponding LoS components, as shown in the following equation (5).

[0090]

[0091] in, represents the complex-valued channel gain of the reference information receiver m, r m represents the distance between the center of the reference base station and the reference information receiver m (i.e., the second distance). a(θ m ) represents the normalized far-field channel steering vector, a(θ m ) is calculated by the following formula (6).

[0092]

[0093] in represents the spatial angle of the reference base station (i.e., the second spatial angle), where φ m represents the physical AoD from the reference base station center to the reference information receiver m.

[0094] In step S305 of some embodiments, Indicates power The transmitted energy carrying signal of each reference energy receiver k is, Indicates power Each reference information receiver m transmits an information-bearing signal. By applying hybrid beamforming, the signal vector sent by the reference base station is shown in equation (7).

[0095]

[0096] in, F Drepresents a (K+M)×(K+M) digital precoder, represents an N×(K+M) analog precoder, represents the simulated beamforming vector for reference energy receiver k, represents the simulated beamforming vector of the reference information receiver m.

[0097] In the embodiment of the present application, in order to obtain effective results and reduce the hardware cost of XL-array, a pure analog beamforming design is used to evaluate the performance gain achieved only by analog beamforming, so the digital precoder is set to the unit matrix. In addition, in order to further improve the performance, the analog precoder F can be set to the unit matrix. A In the case of , beamforming is performed based on weighted minimum mean square error or digital zero forcing.

[0098] make represents the beam scheduling indication set, where represents the binary scheduling variable for each reference energy receiver k, represents the binary scheduling variable of the reference information receiver m. Specifically, if the reference energy receiver k is scheduled by the reference base station, then otherwise is defined similarly to I will not go into details about this.

[0099] The received signal model is modeled as follows:

[0100]

[0101] in, represents the AWGN received at the reference signal receiver m, with a mean of zero and a power of On this basis, the signal to interference plus noise ratio (SINR) received at the reference signal receiver m can be calculated according to the following formula:

[0102]

[0103] in,

[0104] The corresponding achievable rate in units of one hertz per second is calculated as:

[0105]

[0106] In step S306 of some embodiments, for wireless energy transmission, based on the broadcast characteristics of the wireless channel, each reference energy receiver can collect wireless energy from the energy and information signals. Therefore, by ignoring the negligible noise power on the reference energy receiver and assuming a linear energy collection model, the power collected at the reference energy receiver k (i.e., the collection power model) is as follows:

[0107]

[0108] in, Represents the energy harvesting efficiency.

[0109] In step S307 of some embodiments, it is assumed that the reference base station has the best CSI of all reference energy receivers and all reference information receivers, that is, it has a near-field channel control vector a, a far-field channel control vector b, and a channel gain and CSI can be obtained through estimation of far-field signals and near-field channels, as well as beam training methods, which will not be elaborated in the embodiments of the present application.

[0110] In addition, for ease of implementation, it is assumed that if a reference energy receiver (or reference information receiver) is scheduled, the reference base station will steer the beam toward the reference energy receiver (or reference information receiver) to maximize the received power of the reference energy receiver (or reference information receiver) based on, for example, codebook-based beamforming, i.e. Under the above assumptions, the achievable rate for each reference information receiver m can be rewritten as:

[0111]

[0112] The collected energy of each reference energy receiver k is:

[0113]

[0114] The goal of the present embodiment is to jointly optimize the beam scheduling of XL-array BS and power distribution To maximize the weighted collected energy sum. In this process, the total rate constraint R of all reference information receivers and the total transmit power P0 of the reference base station are constrained.

[0115] Let α k ≥0 indicates the predefined power weight of each reference energy receiver k. When the α corresponding to a reference energy receiver k k When the value is large, it indicates that the reference base station prefers energy transmission to this reference energy receiver over other energy receivers. The weighted sum energy transmitted to all reference energy receivers is represented by Q, which can be expressed as:

[0116]

[0117] Based on the above, the power allocation function can be shown as follows (P1).

[0118] (P1):

[0119]

[0120]

[0121]

[0122]

[0123] It can be understood that the content after st represents a constraint condition.

[0124] Based on binary beam scheduling and continuous power allocation, the power allocation function (P1) is a mixed integer optimization problem. In addition, beam scheduling and power allocation optimization are strongly coupled in the objective function and constraints, which makes it more difficult to obtain the optimal solution of the power allocation function (P1). In order to solve the above problems, an embodiment of the present application proposes an effective algorithm to obtain the optimal solution (i.e., target power) of the power allocation function (P1) in the target communication system. The effective algorithm is described below.

[0125] The effective algorithm actually reformulates the power allocation function (P1) into a more compact form. The effective algorithm includes two important steps: eliminating binary optimization variables and determining the correlation between the reference energy receiver and the reference signal receiver. The following describes these two important steps respectively.

[0126] First, the elimination of binary optimization variables is described.

[0127] In order to solve this problem, the embodiment of the present application eliminates the binary optimization variables by introducing the following continuous variables:

[0128]

[0129] Based on this, we can get:

[0130]

[0131] It should be noted that and There is a one-to-one correspondence between when Therefore, we can get the following equivalent formula:

[0132]

[0133] as well as,

[0134] Based on the above, the power allocation function (P1) can be equivalent to the following (P2):

[0135] (P2):

[0136]

[0137]

[0138] Secondly, the determination of the correlation between the reference energy receiver and the reference signal receiver is described.

[0139] Define any two near-field steering vectors b H (θ p ,r p ) and b(θ q ,r q ) is:

[0140] η(θ p ,θ q ,r p ,r q )=|b H (θ p ,r p )b(θ q ,r q )|

[0141] Based on the above definition, by calling the Fresnel function, we can get the approximate expression of the above near-field steering vector correlation:

[0142]

[0143] in,

[0144] Finally, based on the above operations of eliminating binary variables and determining correlation, we can obtain:

[0145]

[0146]

[0147] In order to further simplify the power allocation function, the following reference correlation matrix is ​​defined:

[0148]

[0149] in The correlation between the channel steering vectors of the reference energy receiver p and the reference information receiver q is shown in the following formula:

[0150]

[0151] In order to obtain a more compact form, the power allocation function (P2) is transformed. Specifically, the form of the reference correlation matrix Λ is further changed by setting some diagonal elements to zero, and a new correlation matrix is ​​obtained:

[0152]

[0153] make represents the vector containing all power allocation optimization variables. On this basis, the power allocation function (P2) can be equivalently rewritten as the power allocation function (P3):

[0154] (P3):

[0155]

[0156]

[0157] y≥0

[0158] Among them, c EH and Calculated according to the following formula:

[0159]

[0160]

[0161] In step S102 of some embodiments, the reference communication system is a hypothetical model system. In order to match the power allocation function with the communication system under actual conditions (i.e., the target communication system), it is also necessary to determine the actual conditions of the communication system, i.e., determine the first number of target energy receivers (i.e., EH receivers) and the second number of target information receivers (i.e., ID receivers) included in the communication system under actual conditions.

[0162] In step S103 of some embodiments, a power allocation function is solved according to the first quantity, the second quantity and a preset constraint condition to obtain a target power.

[0163] Reference Figure 4 In some embodiments, step S103 includes but is not limited to steps S401 to S402.

[0164] Step S401, if the first number is equal to zero and the second number is not equal to zero, transform the power allocation function to obtain a first allocation function;

[0165] Step S402, performing power calculation on the first allocation function according to preset constraints to obtain target power; wherein the preset constraints include and ID ≥0, M represents the second quantity, represents the coefficient vector of the target information receiver m, y ID represents the power allocation vector of the target information receiver, represents the target correlation matrix between the target information receiver and the target energy receiver, represents the noise of the target information receiver m, and R represents the achievable rate of the target information receiver.

[0166] In steps S401 to S402 of some embodiments, when the first number is equal to zero and the second number is not equal to zero, it indicates that the target communication system only includes a target information receiver. At this time, the power allocation function (P3) can be optimized to the following first allocation function (P4):

[0167] (P4): find y ID

[0168]

[0169]

[0170] y ID ≥0

[0171] Among them, y ID represents the power allocation vector of the target information receiver, From the representation of the first allocation function (P4) above, it can be seen that the first allocation function (P4) is a feasibility check problem. Therefore, the feasibility check problem can be equivalently transformed into the following problem:

[0172] If R * ≥R, then the first allocation function (P4) is feasible. Where R represents the achievable rate constraint of the target information receiver, R * represents the achievable rate of function (P5), that is, R * is the maximum value of the following function (P5):

[0173] (P5):

[0174]

[0175] y ID ≥0

[0176] It can be seen that when the constraints of the first allocation function (P4) are all met, the first allocation function (P4) is feasible. If the total power budget is not fully utilized, the total rate can be increased by allocating more power to the target information receiver, so the total power constraint equation holds. Secondly, if the maximum value of function (P5) is greater than R, the total rate constraint (i.e., the objective function of function (P5)) holds. In other words, whether the first allocation function (P4) is feasible can be determined based on function (P5). When the first allocation function (P4) is feasible, the optimal solution y of the first allocation function (P4) is ID This indicates the target power.

[0177] It can be understood that since the objective function of function (P5) includes complex ratio terms, function (P5) is a non-convex optimization problem. In order to solve this problem, the fractional programming method can be called to convert the objective function into a more tractable form. Specifically, function (P5) is a concave-convex fractional programming problem. The concave-convex objective function can be converted into a series of easily solved concave sub-problems through quadratic transformation, thereby obtaining the solution of function (P5).

[0178] Reference Figure 5 In some other embodiments, step S103 includes but is not limited to steps S501 to S502.

[0179] Step S501, if the first number is not equal to zero and the second number is equal to zero, transform the power allocation function to obtain a second allocation function;

[0180] Step S502, performing power calculation on the second allocation function according to preset constraints to obtain target power; wherein the preset constraints include and EH ≥0, K represents the first quantity, M represents the second quantity, y EH represents the power allocation vector of the target energy receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

[0181] In steps S501 to S502 of some embodiments, when the first number is not equal to zero and the second number is equal to zero, it indicates that the target communication system only includes the target energy receiver. In this case, y can be expressed as In this case, the goal is to maximize the weighted sum power of the target energy receivers in the near-field region given the transmission power constraint. Therefore, the power allocation function (P3) can be optimized as the second allocation function (P6) as follows:

[0182] (P6):

[0183]

[0184] y EH ≥0

[0185] It can be seen that the second allocation function (P6) is a linear programming problem. In order to obtain the optimal solution of the second allocation function (P6), the embodiment of the present application defines an energy harvesting priority function and obtains the optimal beam scheduling and power allocation. It can be understood that according to the optimal solution y of the second allocation function (P6) EH This indicates the target power.

[0186] Specifically, It is defined as the energy harvesting priority of each target energy receiver k, where the highest energy harvesting priority is expressed as:

[0187]

[0188] It can be understood that the defined energy harvesting priority corresponds to the objective function coefficient of each target energy receiver k in the second allocation function (P6), and the energy harvesting priority essentially represents the energy harvesting capability of the target energy receiver k in the near-field area WPT system. In the near-field area WPT system, each target energy receiver can not only collect energy from the energy beam directed to itself, but also collect leaked energy from other target energy receivers.

[0189] In the optimal solution of the second allocation function (P6), all the transmission power should be allocated to the target energy receiver with the highest energy harvesting priority. In other words, the optimal power allocation is as follows:

[0190]

[0191] Since the second allocation function (P6) is a linear programming problem, its optimal solution can be obtained through the Karush-Kuhn-Tucker (KKT) condition.

[0192] It can be seen from step S401 to step S402 and step S501 to step S502 that the above two special cases with a target information receiver or a target energy receiver show different principles of beam scheduling and power allocation in the near-field area (or far-field area). Specifically, the power allocation of the target information receiver in the far-field area follows the water injection structure, while the target energy receiver in the near-field area allocates all power to the receiver with the highest energy collection priority. However, for the new hybrid field SWIPT system with both a target energy receiver and a target information receiver, it is unknown how to reasonably allocate the target base station transmission power.

[0193] To solve the above problems, refer to Figure 6 In some embodiments, in other embodiments, step S103 includes but is not limited to steps S601 to S602.

[0194] Step S601, if the first number is not equal to zero and the second number is equal to 1, transform the power allocation function to obtain a third allocation function;

[0195] Step S602, performing power calculation on the third allocation function according to preset constraints to obtain target power; wherein the preset constraints include c ID represents the coefficient vector of the target information receiver, represents the power allocation vector of the target energy receiver and the target information receiver, represents the target correlation matrix between the target information receiver and the target energy receiver, represents the noise of the target information receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

[0196] In steps S601 to S602 of some embodiments, when the first number is not equal to zero and the second number is equal to 1, it indicates that the target communication system includes multiple target energy receivers and one target information receiver. At this time, the power allocation function (P3) can be optimized to the following third allocation function (P7):

[0197]

[0198]

[0199]

[0200] in,

[0201] The third allocation function (P7) is a linear programming problem. The optimal solution of the third allocation function (P7) is The optimal solution of the third allocation function (P7) is as follows:

[0202] If ρ≠K+1, then

[0203]

[0204] If ρ=K+1, then

[0205]

[0206] The optimal solution of the third allocation function (P7) It can also be obtained through KKT conditions.

[0207] From the above optimal solution, it can be seen that the optimal power allocation is determined by the defined energy harvesting priority function. Specifically, if the target energy receiver with the highest energy harvesting priority is taken as the best target energy receiver (i.e., ρ≠K+1), the optimal power allocation scheme is to allocate part of the power to the target information receiver to meet the rate and constraints, and the remaining power should be allocated to the best target energy receiver. In addition, if the target information receiver has the highest energy priority (i.e., ρ=K+1), all power should be allocated to the target information receiver.

[0208] Reference Figure 7 In some other embodiments, step S103 includes but is not limited to steps S701 to S702.

[0209] Step S701, if the first quantity is not equal to zero and the second quantity is not equal to zero, obtain a preset variable;

[0210] Step S702, performing power calculation on the power allocation function according to preset variables and preset constraints to obtain target power; wherein the preset constraints include y≥0, M represents the second quantity, S m and I m All represent preset variables, R represents the achievable rate of the target information receiver, represents the coefficient vector of the target information receiver m, and y represents the power allocation vector of the target energy receiver and the target information receiver.

[0211] In step S701 of some embodiments, if the first number is not equal to zero and the second number is not equal to zero, it indicates that the target communication system includes multiple target energy receivers and multiple target information receivers. m} and {I m}Determine the target power. Among them, the slack variables satisfy the following formula:

[0212]

[0213]

[0214] On this basis, the power allocation function (P3) can be changed into the following form (P8):

[0215] (P8):

[0216]

[0217]

[0218]

[0219]

[0220] y≥0

[0221] It is understandable that when assuming x>0, y>0, we can get is a convex function of x and y. Therefore, the complex constraints in the function (P8) can be handled based on the SCA method.

[0222] It should be noted that when x>0, y>0, we can get It is a convex function about x and y. Therefore, the complex constraints in the function (P8) can be handled based on the SCA method.

[0223] Specifically, by applying the first-order Taylor expansion, The lower bound of can be defined as:

[0224]

[0225] in, represents any feasible point. Therefore, function (P8) is approximated by the following function (P9):

[0226] (P9):

[0227]

[0228]

[0229]

[0230]

[0231] y≥0

[0232] Function (P9) is a convex optimization problem that can be solved by a standard solver such as CVX. It should be noted that the target power obtained from function (P9) requires an iterative process until the score of the objective function increases below a threshold ξ, ξ>0. It can be understood that the suboptimal solution y of function (P9) is the target power.

[0233] In step S104 of some embodiments, beam scheduling and target power are combined to allocate power to the target energy receiver and the target information receiver, thereby achieving efficient SWIPT of a far-field and near-field hybrid channel. It is understandable that when the target power corresponding to the target energy receiver (or target information receiver) is equal to zero, beam scheduling is not performed. When the target power corresponding to the target energy receiver (or target information receiver) is not equal to zero, beam scheduling is performed.

[0234] The beneficial effects of the wireless energy-carrying communication method provided by the embodiment of the present application include:

[0235] (1) In view of the fact that the related art only focuses on the far-field SWIPT and the near-field SWIPT, the embodiment of the present application sets up a SWIPT system of a hybrid far-near channel. In addition, since the related art cannot be directly applied to the SWIPT system of a hybrid far-near channel, the embodiment of the present application also provides a power allocation method according to the SWIPT system of a hybrid far-near channel, and realizes efficient SWIPT by jointly optimizing beam scheduling and power allocation.

[0236] (2) For the SWIPT system with mixed near and far channels, the present application provides four power allocation methods in different scenarios.

[0237] (3) For the scenario where the target communication system includes multiple target energy receivers and multiple target information receivers, an effective function (P9) is obtained by calling the SCA technology, which can obtain a more general beam scheduling and power allocation method with lower complexity.

[0238] The wireless energy-carrying communication system provided in the embodiments of the present application is described below.

[0239] Reference Figure 8 The embodiment of the present application further provides a wireless energy-carrying communication system, which can implement the above-mentioned wireless energy-carrying communication method, and the system includes:

[0240] A power allocation function acquisition module 801 is used to acquire a preset power allocation function; wherein the power allocation function is a function obtained according to a pre-built reference communication system, the reference communication system includes a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is within a first preset distance range, the distance between the reference information receiver and the reference base station is within a second preset distance range, and the maximum value of the first preset distance range is less than the minimum value of the second preset distance range;

[0241] A quantity determination module 802 is used to determine a first quantity of target energy receivers in a target communication system and to determine a second quantity of target information receivers in the target communication system;

[0242] A power calculation module 803 is used to perform power calculation on the power allocation function according to the first quantity, the second quantity, and the preset constraint condition to obtain the target power;

[0243] The power allocation module 804 is used to allocate power to the target energy receiver and the target information receiver according to the target power.

[0244] The specific implementation of the wireless power-carrying communication system is substantially the same as the specific implementation of the wireless power-carrying communication method described above, and will not be described in detail herein.

[0245] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above wireless energy communication method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0246] See also Fig. 9 , Fig. 9 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0247] The processor 901 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0248] The memory 902 may be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 may store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 902, and the processor 901 calls and executes the wireless energy communication method of the embodiment of this application;

[0249] Input / output interface 903, used to implement information input and output;

[0250] Communication interface 904, used to realize communication interaction between the device and other devices, which can be realized by wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0251] A bus 905 that transmits information between various components of the device (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904);

[0252] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0253] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned wireless power carrying communication method is implemented.

[0254] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0255] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0256] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0257] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0258] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0259] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0260] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "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 mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0261] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0262] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0263] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0264] If the integrated unit is implemented in the form of a software functional 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 solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0265] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A wireless energy communication method, characterized in that: The method comprises: Obtaining a preset power allocation function; wherein the power allocation function is a function obtained according to a pre-constructed reference communication system, the reference communication system comprising a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is within a first preset distance range, the distance between the reference information receiver and the reference base station is within a second preset distance range, and the maximum value of the first preset distance range is less than the minimum value of the second preset distance range; determining a first number of target energy receivers in a target communication system, and determining a second number of target information receivers in the target communication system; Performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power; Allocating power to the target energy receiver and the target information receiver according to the target power; The step of performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power includes: If the first number is not equal to zero, and the second number is not equal to zero, obtaining a preset variable; The power allocation function is used to calculate the power according to the preset variables and the preset constraints to obtain the target power; wherein the preset constraints include K represents the first number, M represents the second number, S m and I m All represent preset variables, R represents the achievable rate of the target information receiver, represents the coefficient vector of the target information receiver m, y represents the power allocation vector of the target energy receiver and the target information receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

2. The method according to claim 1, characterized in that: The method for constructing the power allocation function according to the reference communication system comprises: determining a first distance between the reference base station and the reference energy receiver; Obtaining a near-field channel model according to the first distance, a first spatial angle between the reference base station and the reference energy receiver; determining a second distance between the reference base station and the reference information receiver; Obtaining a far-field channel model according to the second distance, a second spatial angle between the reference base station and the reference information receiver; Constructing a received signal model of the reference information receiver according to the far-field channel model; Constructing a collection power model of the reference energy receiver according to the near-field channel model; A reference correlation matrix of the reference information receiver and the reference energy receiver is obtained, and the power allocation function is constructed according to the reference correlation matrix, the received signal model, and the collection power model.

3. The method according to claim 2, characterized in that The performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power includes: If the first number is equal to zero and the second number is not equal to zero, transforming the power allocation function to obtain a first allocation function; The power of the first allocation function is calculated according to the preset constraint conditions to obtain the target power; wherein the preset constraint conditions include and ID ≥0, K represents the first number, M represents the second number, represents the coefficient vector of the target information receiver m, y ID represents a power allocation vector of the target information receiver, represents a target correlation matrix between the target information receiver and the target energy receiver, represents the noise of the target information receiver m, R represents the achievable rate of the target information receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

4. The method according to claim 2, characterized in that: The performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power includes: If the first number is not equal to zero and the second number is equal to zero, transforming the power allocation function to obtain a second allocation function; The power of the second allocation function is calculated according to the preset constraint condition to obtain the target power; wherein the preset constraint condition includes and EH ≥0, K represents the first number, M represents the second number, y EH represents the power allocation vector of the target energy receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

5. The method according to claim 2, characterized in that: The performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power includes: If the first number is not equal to zero, and the second number is equal to 1, transforming the power allocation function to obtain a third allocation function; The power of the third allocation function is calculated according to the preset constraint conditions to obtain the target power; wherein the preset constraint conditions include c ID represents the coefficient vector of the target information receiver, represents the power allocation vector of the target energy receiver and the target information receiver, represents a target correlation matrix between the target information receiver and the target energy receiver, represents the noise of the target information receiver, P0 represents the maximum transmission signal power of the target base station in the target communication system, K represents the first number, M represents the second number, and R represents the achievable rate of the target information receiver.

6. A wireless energy-carrying communication system, characterized in that: The system comprises: A power allocation function acquisition module, used to acquire a preset power allocation function; wherein the power allocation function is a function obtained according to a pre-built reference communication system, the reference communication system includes a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is within a first preset distance range, the distance between the reference information receiver and the reference base station is within a second preset distance range, and the maximum value of the first preset distance range is less than the minimum value of the second preset distance range; a quantity determination module, configured to determine a first quantity of target energy receivers in a target communication system, and to determine a second quantity of target information receivers in the target communication system; a power calculation module, configured to perform power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power; A power allocation module, used for allocating power to the target energy receiver and the target information receiver according to the target power; The step of performing power calculation on the power allocation function according to the first quantity, the second quantity, and a preset constraint condition to obtain a target power includes: If the first number is not equal to zero, and the second number is not equal to zero, obtaining a preset variable; The power allocation function is used to calculate the power according to the preset variables and the preset constraints to obtain the target power; wherein the preset constraints include K represents the first number, M represents the second number, S m and I m All represent preset variables, R represents the achievable rate of the target information receiver, represents the coefficient vector of the target information receiver m, y represents the power allocation vector of the target energy receiver and the target information receiver, and P0 represents the maximum transmission signal power of the target base station in the target communication system.

7. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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