Method for establishing intelligent reflecting surface auxiliary wireless energy supply communication system for wireless body area network

Abstract

The invention discloses a method for establishing an intelligent reflecting surface auxiliary wireless energy supply communication system for a wireless body area network. The method comprises the following steps: constructing an initial wireless energy supply communication system model consisting of wearable equipment, an access point and an intelligent reflecting surface equipped with N reflecting elements; constructing channel path loss distribution based on channel parameters in the wireless energy supply communication system model; determining a composite channel distribution function based on channel path loss distribution by adopting a moment matching method; and under a preset threshold value and constraint conditions, the outage probability in the information transmission process is calculated in combination with the channel parameters and the composite channel distribution function, so that target reflection element data of the intelligent reflection surface are determined, and then a target wireless energy supply communication system model is determined for wireless transmission. According to the wireless energy supply communication system established by the invention, the energy collection performance of the WET network can be remarkably improved, and meanwhile, the energy transmission efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method for establishing an intelligent reflective surface-assisted wireless energy supply communication system for a wireless body area network. Background Art

[0002] Wireless body area network (WBAN) is a network composed of low-power, intelligent and compact sensor devices, and is an important part of advanced e-health systems. These devices can exchange data through wireless communication technology, that is, work inside, on or around the human body, and are mainly used to evaluate the physical characteristics of human entities and record abnormal or critical conditions of human entities. Common sensor device application scenarios include: measuring cardiac electrical activity through electrocardiogram (ECG), measuring brain electrical activity through electroencephalogram (EEG), and determining muscle electrical activity through electromyography (EMG). In traditional WBAN, the data collected by the sensor device will be transmitted to the control device, such as a receiver or gateway / PDA, for data aggregation processing and non-aggregation (personal digital assistant) processing, and the data obtained can be further transmitted to the remote monitoring center for diagnosis and analysis. However, in traditional WBAN, since the sensor devices are placed inside or on the human body, energy collection is difficult and the efficiency of energy transmission is low. Summary of the invention

[0003] The present invention provides a method for establishing an intelligent reflective surface-assisted wireless energy supply communication system for a wireless body area network, which is used to solve the technical problems of the existing WBAN that energy collection is difficult and the energy transmission efficiency is low.

[0004] The present invention provides a method for establishing an intelligent reflective surface-assisted wireless energy supply communication system for a wireless body area network, the method comprising:

[0005] Construct an initial wireless power supply communication system model consisting of a wearable device, an access point, and an intelligent reflective surface equipped with N reflective elements; wherein the intelligent reflective surface is set between the wearable device and the access point;

[0006] Constructing a channel path loss distribution of the initial wireless power supply communication system model based on channel parameters in the initial wireless power supply communication system model;

[0007] Determine a composite channel distribution function of the initial wireless power supply communication system model based on the channel path loss distribution by using a moment matching method;

[0008] Under preset thresholds and constraints, the interruption probability of the initial wireless power supply communication system model during information transmission is calculated in combination with the channel parameters and the composite channel distribution function, thereby determining the target reflective element data of the smart reflective surface, and then determining the target wireless power supply communication system model for wireless transmission.

[0009] Furthermore, the transmission process of the initial wireless power supply communication system model is divided into a wireless energy transmission stage and a wireless information transmission stage; in the wireless energy transmission stage, the access point transmits a wireless energy signal to the wearable device through a downlink, and in the wireless information transmission stage, the wearable device transmits a wireless information signal to the access point through an uplink; wherein the downlink is composed of a line-of-sight path from the access point to the wearable device and a reflection path from the access point and the smart reflective surface to the wearable device, and the uplink is composed of a line-of-sight path from the wearable device to the access point and a reflection path from the wearable device and the smart reflective surface to the access point.

[0010] Further, the channel path loss distribution of the initial wireless energy supply communication system model includes the channel path loss distribution between the smart reflective surface and the access point, and the channel path loss distribution between the wearable device and the smart reflective surface and the access point;

[0011] Among them, the channel path loss distribution between the smart reflective surface and the access point is It is expressed as:

[0012]

[0013] Where: z represents the random variable of the channel path loss between the intelligent reflection surface IRS and the access point AP, represents a shape parameter greater than 0, represents the diffusion parameter of the distribution, represents the gamma function.

[0014] Further, when the link distribution between the wearable device and the smart reflective surface and the access point satisfies the gamma distribution model, the channel path loss distribution between the wearable device and the smart reflective surface and the access point is expressed as:

[0015]

[0016] Where: z represents the channel path loss random variable between the wearable device S and the smart reflective surface IRS or the channel path loss random variable between the wearable device S and the access point AP; θ represents the scale parameter, and k represents the shape parameter.

[0017] Further, the step of using the matrix matching method to determine the composite channel distribution function of the initial wireless power supply communication system model based on the channel path loss distribution of the initial wireless power supply communication system model comprises: using the matrix matching method to determine the parameters of the composite channel distribution of the initial wireless power supply communication system model based on the channel path loss distribution of the wireless power supply communication system model; establishing a composite channel distribution function based on the parameters of the composite channel distribution;

[0018] Wherein, the composite channel distribution function Specifically expressed as:

[0019]

[0020] Where: Represents the signal-to-noise ratio function of the composite channel H.

[0021] Furthermore, the step of calculating the interruption probability of the initial wireless power supply communication system model during information transmission by combining the channel parameters and the composite channel distribution function under preset thresholds and constraints, thereby determining the target reflective element data of the smart reflective surface, and then determining the target wireless power supply communication system model for wireless transmission includes:

[0022] Establishing an interruption function of the initial wireless power supply communication system model during information transmission based on the channel parameters and a preset threshold value, thereby determining a CDF value;

[0023] Under the constraint condition, the CDF value is input into the composite channel distribution function to calculate the minimum interruption probability of the initial wireless power supply communication system model during the information transmission process;

[0024] The number of reflective elements corresponding to the minimum interruption probability is used as the target number of reflective elements of the smart reflective surface, thereby determining the target wireless power supply communication system model for wireless transmission.

[0025] Furthermore, the interrupt function P is expressed as:

[0026]

[0027] Where: Pr(·) represents the probability function, Indicates the signal-to-noise ratio of the signal received at the access point AP. represents the preset threshold; η is the energy conversion efficiency coefficient, α represents the time allocation ratio, Indicates the transmit power of the AP. represents the channel path loss from the nth reflective element to S, ∈[0,2π] represents the adjustable phase shift of the nth reflective element, represents the channel path loss of the reflection path between the wearable device S and the smart reflective surface IRS, represents the channel path loss from AP to the nth reflective element; Indicates the noise power of the access point AP.

[0028] Furthermore, the interruption probability of the initial wireless power supply communication system model during information transmission is The calculation formula is expressed as:

[0029] .

[0030] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for establishing an intelligent reflective surface-assisted wireless power supply communication system for a wireless body area network as described above are implemented.

[0031] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for establishing an intelligent reflective surface-assisted wireless power supply communication system for a wireless body area network as described above are implemented.

[0032] It can be seen from the above technical solutions that the present invention has the following advantages:

[0033] The present invention provides a method for establishing an intelligent reflective surface-assisted wireless power supply communication system for a wireless body area network, the method comprising: constructing an initial wireless power supply communication system model consisting of a wearable device, an access point and an intelligent reflective surface equipped with N reflective elements; wherein the intelligent reflective surface is arranged between the wearable device and the access point; based on the channel parameters in the initial wireless power supply communication system model, constructing the channel path loss distribution of the initial wireless power supply communication system model; using a moment matching method, based on the channel path loss distribution, determining the composite channel distribution function of the initial wireless power supply communication system model; under preset thresholds and constraints, combining the channel parameters and the composite channel distribution function to calculate the interruption probability of the initial wireless power supply communication system model during information transmission, thereby determining the target reflective element data of the intelligent reflective surface, and then determining the target wireless power supply communication system model for wireless transmission.

[0034] In the present invention, combined with the dynamic characteristics of the wireless body area network, the target number of reflective elements of the IRS in the target wireless power supply communication system model is determined by the interruption probability, so that the established wireless power supply communication system can enhance the signal strength at the receiving end, thereby improving the efficiency of energy transmission; at the same time, the wireless power supply communication system model established with the help of IRS can reduce the energy consumption and hardware complexity of the source-end equipment, so that the energy collection performance of the WET network can be significantly improved, thereby solving the technical problems of the existing WBAN energy collection being difficult and the energy transmission efficiency being low. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative labor.

[0036] Figure 1 A flowchart of the steps of a method for establishing an intelligent reflective surface-assisted wireless energy supply communication system for a wireless body area network provided by an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a wireless energy supply communication system model provided by an embodiment of the present invention;

[0038] Figure 3 A schematic diagram of simulation of the number of reflective elements, outage probability and transmit SNR under different channel distributions provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The embodiment of the present invention provides a method for establishing an intelligent reflective surface-assisted wireless energy supply communication system for a wireless body area network, which is used to solve the technical problems of the existing WBAN energy collection being difficult and the energy transmission efficiency being low.

[0040] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments 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.

[0041] See also Figure 1 The present invention provides a method for establishing an intelligent reflective surface-assisted wireless energy supply communication system for a wireless body area network, the method comprising:

[0042] Step 101, constructing an initial wireless power supply communication system model consisting of a wearable device S, an intelligent reflective surface IRS and an access point AP; wherein the intelligent reflective surface is arranged between the wearable device and the access point.

[0043] Among them, intelligent reflecting surface (IRS), also known as reconfigurable intelligent surface (RIS), is a technology that uses metasurfaces to reflect signals to users, and can achieve energy and spectrum efficient wireless communication by providing additional communication links between transmitters and receivers. IRS is a planar array composed of a controller and a large number of reconfigurable reflective elements (REs). Under the control of the IRS controller, each passive RE can independently adjust its phase shift and reflection coefficient, thereby achieving three-dimensional (3D) passive beamforming and suppressing interference.

[0044] To this end, in the present invention, the wireless power supply communication system model established with the help of IRS can reduce the energy consumption and hardware complexity of the source device, so that the energy collection performance of the WET network can be significantly improved. At the same time, by configuring the reflection characteristics of IRS, additional direct links can be generated to achieve amplitude and phase changes of the incident signal.

[0045] For details, please refer to Figure 2 , Figure 2 The schematic diagram of the wireless body area network system model in the off-body channel measurement scenario based on the indoor high-frequency band wireless body area network provided by this embodiment is shown. In the figure, the subject at the receiving end stands in the center of the room and remains still. The wearable device S is placed on the chest of the human body, and the AP is placed indoors. In the wireless power supply communication system model, the channels (paths) between the sensor devices are independent of each other, and the composite channel from AP to S is a cascade of the AP-IRS link and the IRS-S link components. In this way, each element of the IRS receives the superimposed multipath signal from the transmitter, and then the IRS scatters the combined signal with adjustable amplitude and phase, thereby generating a "multiplication" channel model.

[0046] exist Figure 2 In the figure, h0 represents the channel path loss (channel loss) of the line-of-sight path between the access point and the wearable device, h1 represents the channel path loss of the reflection path between the wearable device and the smart reflective surface, and g represents the channel path loss of the line-of-sight path between the access point and the smart reflective surface.

[0047] It is worth noting that the establishment of a body area network channel within the intelligent reflector-assisted wireless power supply communication system needs to comply with the IEEE 802.15.6 international standard for wireless body area networks, and the devices involved in biomedical applications must follow the rules adopted by the Federal Communications Commission (FCC) in terms of frequency bands and power limits. Among them, the frequency bands used for medical applications include the Medical Implant Communications Service (MICS) band (402–405MHz) and the Industrial, Scientific and Medical (ISM) band (2360–2400MHz).

[0048] In addition, a communication protocol is deployed between the system nodes (i.e., sensor devices) of the wireless power supply communication system model to collect energy first and then send information. The transmission process T is divided into two stages, namely, the wireless energy transmission stage (0, αT) and the wireless information transmission stage (αT, T), where α represents the time allocation ratio, 0<α<1; in the wireless energy transmission stage, the access point transmits a wireless energy signal to the wearable device through a downlink, and the wearable device receives and stores the energy signal to provide energy support for the subsequent wireless information transmission stage; correspondingly, in the wireless information transmission stage, the wearable device transmits a wireless information signal to the access point through an uplink; wherein the downlink is composed of a line-of-sight path from the access point to the wearable device and a reflection path from the access point and the smart reflective surface to the wearable device, and the uplink is composed of a line-of-sight path from the wearable device to the access point and a reflection path from the wearable device and the smart reflective surface to the access point.

[0049] The following combination Figure 2 , further explanation is given for the signal transmission process of the wireless energy supply communication system model of the present invention:

[0050] In the case of slowly varying and flat fading channels, the reflected signal of the nth element of the IRS is given by To represent this, we transform the corresponding incident signal and complex reflection coefficient Multiplying together, we get: n = 1, 2, ... N, where N represents the total number of reflective elements of the IRS. = [0,1] and =[0,2π] represents the reflection amplitude coefficient and the phase shift adjustment of IRS respectively.

[0051] Then, the baseband signal received at the S end is reflected by the N passive reflective elements of the smart reflective surface. It can be expressed as:

[0052]

[0053] Where: Indicates the transmit power of the AP. represents the channel path loss from the nth reflective element to S, ∈[0,2π] represents the adjustable phase shift of the nth reflective element. For simplicity, the reflection amplitude coefficient of the reflective element is set to 1; represents the channel path loss from AP to the nth reflective element, Indicates the data signal transmitted by the AP. Represents the noise signal at the S terminal.

[0054] The energy collected by S It can be expressed as:

[0055]

[0056] Where η is the energy conversion efficiency coefficient.

[0057] Similarly, the signal received at the AP It can be expressed as:

[0058]

[0059] Where: Indicates the noise signal at the AP end;

[0060] Energy collected by AP It can be expressed as:

[0061]

[0062] because and are all complex channels and can be expressed in polar coordinates, that is, and At the same time, the channel fading between IRS and AP follows the Nakagami-m distribution, that is, ~Nakagami(mi,Ωi), where mi represents a shape parameter greater than 0 and Ωi represents the diffusion parameter of the distribution.

[0063] Step 102: construct a channel path loss distribution of the initial wireless power supply communication system model based on channel parameters in the initial wireless power supply communication system model.

[0064] It should be noted that the channel parameters in the initial wireless power supply communication system model include the channel path loss of the link between the wearable device S and the AP and IRS ( , and ), AP's transmit power and signal-to-noise ratio, etc., while the channel path loss of the link between the wearable device S and the AP and IRS depends on the distance and direction between the device nodes, the body part where the wearable device is located, and the movement of the human body. The best fitting distribution of the application scenarios of the above system model mainly conforms to the log-normal distribution or the gamma distribution.

[0065] 1) Lognormal distribution model:

[0066]

[0067] Where: represents the distance between S and IRS, and b are the coefficients of the linear fit, is a normally distributed random variable with mean zero and standard deviation .

[0068] S-IRS link channel loss The square of the absolute value can be expressed as:

[0069]

[0070] Then, the signal-to-noise ratio of the S-IRS link can be expressed as: .in, Indicates the noise power at the AP.

[0071] 2) Gamma distribution model:

[0072] S-IRS link channel loss The square of the absolute value can be expressed as:

[0073]

[0074] in Represents a gamma distribution with shape parameter k and scale parameter θ.

[0075] This indicates that the signal-to-noise ratio of the S-IRS link It also conforms to the gamma distribution, where the signal-to-noise ratio It can be expressed as: .

[0076] It should be noted that the channel path loss distribution of the wireless power supply communication system model includes the channel path loss distribution between the smart reflecting surface IRS and the access point AP, and the channel path loss distribution between the wearable device S and the smart reflecting surface IRS and the access point AP.

[0077] Due to the channel path loss between the intelligent reflecting surface IRS and the access point AP ~Nakagami(mi,Ωi), then The channel path loss distribution (PDF distribution, probability density function) is expressed as:

[0078]

[0079] Wherein, z represents the random variable of the channel path loss between the intelligent reflection surface IRS and the access point AP; represents the gamma function.

[0080] When the link distribution between the wearable device S and the AP and IRS satisfies the log-normal distribution model, the channel path loss between the wearable device S and the smart reflective surface IRS and the access point AP ( and )’s PDF distribution is:

[0081]

[0082] Wherein, z represents the random variable of the channel path loss between the wearable device S and the intelligent reflective surface IRS or the random variable of the channel path loss between the wearable device S and the access point AP; represents the mean signal-to-noise ratio of the channel, , represents a fixed parameter of the signal-to-noise ratio; represents the square of the standard deviation of the noise power, , is a fixed parameter of noise power.

[0083] When the link distribution between the wearable device S and the AP and IRS is a gamma distribution model, the channel path loss between the wearable device S and the smart reflective surface IRS and the access point AP ( and ) are all distributed as follows:

[0084]

[0085] Where: k = k n , θ = θ n *Pap / N0, k n and θ n represents the fixed parameter of the gamma distribution; z represents the random variable of the channel path loss between the wearable device S and the smart reflective surface IRS or the random variable of the channel path loss between the wearable device S and the access point AP.

[0086] Step 103: using a moment matching method and based on the channel path loss distribution, determine a composite channel distribution function of the initial wireless power supply communication system model.

[0087] make , using the moment matching method, the distribution of the composite channel H can be approximated by the Gamma distribution, that is, H~Gamma(k,θ), where the shape parameter k and the scale parameter θ are expressed as:

[0088]

[0089] Where: represents the first-order moment of the composite channel H, represents the second-order moment of the composite channel H.

[0090] CDF (Cumulative Distribution Function) of the composite channel H It is expressed as:

[0091]

[0092] In addition, the PDF of the composite channel H is expressed as:

[0093] .

[0094] Step 104, under preset thresholds and constraints, the interruption probability of the initial wireless power supply communication system model during information transmission is calculated in combination with the channel parameters and the composite channel distribution function, thereby determining the target reflective element data of the smart reflective surface, and then determining the target wireless power supply communication system model for wireless transmission.

[0095] It should be noted that when the signal-to-noise ratio received at the AP is less than the preset threshold, data transmission will be interrupted. Therefore, in this step, firstly, the interruption function of the initial wireless power supply communication system model during information transmission is established based on the signal-to-noise ratio received at the AP in the channel parameters and the preset threshold, so as to determine the CDF value;

[0096] Among them, the interrupt function The expression is as follows:

[0097]

[0098] Where: is the signal-to-noise ratio of the signal received at the AP, γth is the preset threshold, and Pr(·) represents the probability function. Then, the determined CDF value is .

[0099] Then, under the constraint conditions, the CDF value is input into the composite channel distribution function to calculate the minimum interruption probability of the initial wireless power supply communication system model during the information transmission process.

[0100] Among them, the interruption probability of the wireless power supply communication system model during information transmission (uplink) The calculation formula is expressed as:

[0101]

[0102] In order to further verify the relationship between the outage probability, the reflection of the reflective elements of the smart reflective surface, and the transmission SNR, this example provides a simulation diagram of the relationship between the number of reflective elements, the outage probability, and the transmission SNR under different channel distributions. Figure 3 In the system model used in this example, the number of reflective elements N of the smart reflective surface is 30, 40, and 50 respectively, the maximum mutual information R is 1, and the preset threshold γ th =2R-1=1, the distance between S and AP is 2m, and IRS is placed between AP and S, with a distance of 1m from S and 2m from AP.

[0103] in, Figure 3 (a) shows the relationship between the outage probability and the transmit SNR under the log-normal channel. Under the log-normal channel, the log-normal channel between S and IRS, =-0.31, =0.12, the channel path loss is 41.91dBm, the log-normal channel between S and AP, =-0.41, =0.19, and the channel path loss is 48.19 dBm. In this figure, the theoretical results are consistent with the simulation results, which verifies the proposed analysis. It can also be seen that the outage probability is related to the transmit SNR and the number of reflective elements of the smart reflective surface. The larger the transmit SNR and the more reflective elements, the smaller the outage probability of the system.

[0104] and Figure 3 (b) shows the relationship between the outage probability and the transmit SNR in the gamma channel. In the gamma channel, the gamma channel between S and IRS, k=0.82, θ=0.26, the channel path loss is 30.97dBm, the gamma channel between S and AP, k=1.03, θ=0.13, the channel path loss is 34.67dBm; in this figure, the theoretical results are consistent with the simulation results. Figure 3 By comparison, it can be seen that the outage probability is related to the transmission SNR and the number of reflective elements of the smart reflective surface. The larger the transmission SNR and the more reflective elements, the smaller the outage probability of the system.

[0105] At the same time, according to the MICS standard recommendations formulated by the Federal Communications Commission (FCC) of the United States, in order to avoid electromagnetic (EM) radiation that is harmful to human health, the effective radiated power (ERP) on the human body surface must not exceed -20dBm; in order to minimize the interruption probability of the system while meeting the power limit on the human body surface, this step also sets constraints.

[0106] Among them, the constraints include the human body surface power limit function, which is expressed as:

[0107]

[0108] Thus, the present invention combines the calculation formula of the interruption probability and the power limit function on the human body surface to determine the minimum interruption probability and the number of target reflective elements N. max , thereby determining the target wireless power supply communication system model for wireless transmission.

[0109] The present invention utilizes the IRS interference construction method, combines the dynamic characteristics of the wireless body area network, and determines the target number of reflective elements for constructing the IRS through the interruption probability, which can enhance the signal strength at the receiving end, thereby improving the efficiency of energy transmission.

[0110] In particular, in order to further enhance the efficiency of energy collection and data transmission, the time allocation ratio α can also be combined for optimization. It is understandable that if α is too large, the energy collection time is too long, and the time left for data transmission may be insufficient, which may lead to a decrease in data transmission rate or an increase in the probability of interruption; conversely, if α is too small, the energy collection is insufficient, and the sensor device may not have enough energy for effective data transmission, which will also increase the probability of interruption.

[0111] Therefore, the constraint condition may also include a constraint on the time allocation ratio α. The specific optimal value of the time allocation ratio α may be determined by the following mathematical modeling:

[0112] S-to-noise ratio It is expressed as:

[0113]

[0114] Where: N1 represents the noise power at the S terminal.

[0115] Correspondingly, the calculation formula of the interruption probability of the wireless power supply communication system model during energy transmission (downlink) is expressed as:

[0116]

[0117] Based on the relationship between the uplink and downlink outage probabilities and the time allocation ratio α, the comparison function can be obtained:

[0118]

[0119] In this way, the optimal time allocation ratio α can be calculated.

[0120] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for establishing an intelligent reflective surface-assisted wireless power supply communication system for a wireless body area network as described above are implemented.

[0121] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for establishing an intelligent reflective surface-assisted wireless power supply communication system for a wireless body area network as described above are implemented.

[0122] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0123] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0124] The units described 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.

[0125] In addition, each functional unit in each embodiment of the present invention 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.

[0126] 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 invention, in essence, 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. The computer software product is stored in a storage medium, including several instructions for 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 method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0127] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for establishing an intelligent reflective surface-assisted wireless energy supply communication system for a wireless body area network, characterized in that: The method comprises: Construct an initial wireless power supply communication system model consisting of a wearable device, an access point, and an intelligent reflective surface equipped with N reflective elements; wherein the intelligent reflective surface is set between the wearable device and the access point; Constructing a channel path loss distribution of the initial wireless power supply communication system model based on channel parameters in the initial wireless power supply communication system model; Determine a composite channel distribution function of the initial wireless power supply communication system model based on the channel path loss distribution by using a moment matching method; Under preset thresholds and constraints, the interruption probability of the initial wireless power supply communication system model during information transmission is calculated in combination with the channel parameters and the composite channel distribution function, thereby determining the target reflective element data of the smart reflective surface, and then determining the target wireless power supply communication system model for wireless transmission.

2. The method for establishing a smart reflective surface-assisted wireless energy supply communication system for a wireless body area network according to claim 1, characterized in that: The transmission process of the initial wireless energy supply communication system model is divided into a wireless energy transmission stage and a wireless information transmission stage; in the wireless energy transmission stage, the access point transmits a wireless energy signal to the wearable device through a downlink; in the wireless information transmission stage, the wearable device transmits a wireless information signal to the access point through an uplink; wherein the downlink is composed of a line-of-sight path from the access point to the wearable device and a reflection path from the access point and the smart reflective surface to the wearable device, and the uplink is composed of a line-of-sight path from the wearable device to the access point and a reflection path from the wearable device and the smart reflective surface to the access point.

3. The method for establishing a smart reflective surface-assisted wireless energy supply communication system for a wireless body area network according to claim 2, characterized in that: The channel path loss distribution of the initial wireless energy supply communication system model includes the channel path loss distribution between the smart reflective surface and the access point, and the channel path loss distribution between the wearable device and the smart reflective surface and the access point; Among them, the channel path loss distribution between the smart reflective surface and the access point is It is expressed as: Where: z represents the random variable of the channel path loss between the intelligent reflection surface IRS and the access point AP, represents a shape parameter greater than 0, represents the diffusion parameter of the distribution, represents the gamma function.

4. The method for establishing a smart reflective surface-assisted wireless energy supply communication system for a wireless body area network according to claim 3, characterized in that: When the link distribution between the wearable device and the smart reflective surface and the access point satisfies the gamma distribution model, the channel path loss distribution between the wearable device and the smart reflective surface and the access point is expressed as: Where: z represents the channel path loss random variable between the wearable device S and the smart reflective surface IRS or the channel path loss random variable between the wearable device S and the access point AP; θ represents the scale parameter, and k represents the shape parameter.

5. The method for establishing a smart reflective surface-assisted wireless energy supply communication system for a wireless body area network according to claim 4, characterized in that: The step of using the moment matching method to determine the composite channel distribution function of the initial wireless power supply communication system model based on the channel path loss distribution of the initial wireless power supply communication system model comprises: using the moment matching method to determine the parameters of the composite channel distribution of the initial wireless power supply communication system model based on the channel path loss distribution of the wireless power supply communication system model; establishing a composite channel distribution function based on the parameters of the composite channel distribution; Wherein, the composite channel distribution function Specifically expressed as: Where: Represents the signal-to-noise ratio function of the composite channel H.

6. The method for establishing a smart reflective surface-assisted wireless energy supply communication system for a wireless body area network according to claim 2, characterized in that: The step of calculating the interruption probability of the initial wireless power supply communication system model during information transmission by combining the channel parameters and the composite channel distribution function under preset thresholds and constraints, thereby determining the target reflective element data of the smart reflective surface, and then determining the target wireless power supply communication system model for wireless transmission, comprises: Establishing an interruption function of the initial wireless power supply communication system model during information transmission based on the channel parameters and a preset threshold value, thereby determining a CDF value; Under the constraint condition, the CDF value is input into the composite channel distribution function to calculate the minimum interruption probability of the initial wireless power supply communication system model during the information transmission process; The number of reflective elements corresponding to the minimum interruption probability is used as the target number of reflective elements of the smart reflective surface, thereby determining the target wireless power supply communication system model for wireless transmission.

7. The method for establishing a smart reflective surface-assisted wireless energy supply communication system for a wireless body area network according to claim 6, characterized in that: The interrupt function P is expressed as: Where: Pr(·) represents the probability function, Indicates the signal-to-noise ratio of the signal received at the access point AP. Indicates the preset threshold; η is the energy conversion efficiency coefficient, α represents the time allocation ratio, Indicates the transmit power of the AP. represents the channel path loss from the nth reflective element to S, ∈[0,2π] represents the adjustable phase shift of the nth reflective element, represents the channel path loss of the reflection path between the wearable device S and the smart reflective surface IRS, represents the channel path loss from AP to the nth reflective element; Indicates the noise power of the access point AP.

8. The method for establishing a smart reflective surface-assisted wireless energy supply communication system for a wireless body area network according to claim 6, characterized in that: The interruption probability of the initial wireless power supply communication system model during information transmission The calculation formula is expressed as: 。 9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for establishing the intelligent reflective surface-assisted wireless power supply communication system for a wireless body area network as described in any one of claims 1-8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for establishing an intelligent reflective surface-assisted wireless power supply communication system for a wireless body area network as described in any one of claims 1 to 8 are implemented.

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