An indoor high-frequency band wireless body area network off-body channel modeling method

Abstract

The application discloses a kind of indoor high-frequency band wireless body area network off-body channel modeling method.For the influence caused by the relative angle between the sending end human body and the receiving end human body to the path loss of off-body channel, the application first analyzes the influence of the relative angle between body-to-body on channel characteristics using wireless propagation theory;Then, using the path loss exponent related to the relative angle between body-to-body, the floating intercept, and the path loss caused by the change of the relative angle between body-to-body, a new path loss model is established;Finally, the least squares method is used to fit and determine the related parameters of the established model, so that it can more accurately represent the wireless propagation characteristics of the actual communication scenario.Compared with the traditional logarithmic path loss model, the application can be closer to the actual measurement results due to the consideration of the influence of the relative angle between body-to-body.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of wireless communication, and particularly relates to a modeling method for an off-body channel of an indoor high-frequency band wireless body area network. BACKGROUND

[0002] A WBAN (wireless body area network) is a communication network with a human body as the center, and is composed of network elements related to the human body, including personal terminals, sensors distributed on the human body, clothes, a certain distance range around the human body, and even inside the human body. The WBAN has a wide range of applications in the fields of medical health, consumer electronics, entertainment, sports, and military affairs, and can be particularly used in the medical field for remote patient monitoring, sports monitoring, long-term monitoring, and emergency response.

[0003] Since an indoor environment is the main scene of people's daily life, it is particularly important to study the WBAN communication in an indoor scene. In the numerous related studies on indoor WBAN communication, the study on the wireless channel propagation characteristics is the basis and the key to the design of the WBAN communication system. At present, the study on the wireless channel propagation characteristics of the indoor WBAN can be divided into two categories: one is the study on the low-frequency band indoor WBAN wireless channel characteristics, and the other is the study on the high-frequency band indoor WBAN wireless channel propagation characteristics. The study on the low-frequency band indoor WBAN wireless channel propagation characteristics has been mature, while with the explosive growth of wireless data traffic, it is urgent to solve the problem of spectrum resource shortage. Therefore, it is of great significance to explore the wireless channel propagation characteristics of the indoor WBAN at a higher frequency band.

[0004] At present, in the study on the high-frequency band indoor WBAN channel characteristics, COTTON, CHUN and SCANLON (COTTON S L, CHUN Y J, SCANLON W G, et al. Path loss models for indoor off-body communications at 60GHz [C] / / 2016IEEE International Symposium on Antennas and Propagation (APSURSI), 2016: 1441-1442.) have studied the off-body channel characteristics in the 60GHz frequency band indoor LOS and NLOS scenes, and analyzed the influence of the indoor space size on the wireless channel propagation characteristics.

[0005] LIU, SHAO and LUO et al. (LIU J, SHAO Y, LUO J, et al. On-Body channel modeling based on different body heights at 28GHz [C] / / 2019 International Symposium on Antennas and Propagation (ISAP), 2019: 1-3.) studied the wireless propagation characteristics of the body surface channel in the 28GHz frequency band in the hospital scene, analyzed the relationship between the path loss exponent and the body height, and established a body height related path loss model; their team (LIU J, SHAO Y, WANG P, et al. Dynamic Channel Modeling of at 28GHz [C] / / 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, 2020: 1481-1482.) also analyzed the path loss characteristics of the waist to the chest, the waist to the knee, the waist to the wrist, and the waist to the head when the human body is walking and running at 28GHz frequency band, and established a dynamic channel path loss model.

[0006] However, most of the existing literature is to study the case where only one end of the sending end and the receiving end is placed on the human body, and there are few studies on the case where both the sending end and the receiving end are on the human body. In addition, since the wearable device in the WBAN scene is too close to the surface of the human body, it is easily affected by the direction and angle of the human body, and in actual life scenes, the position and direction of the human body will change, which will cause the relative angle between the sending end and the receiving end to change, thereby affecting the propagation characteristics of the wireless channel in this scene. SUMMARY

[0007] The technical problem to be solved by the present application is to provide an indoor high-frequency off-body channel modeling method with the influence of the body-to-body relative angle, which better represents the influence of the body-to-body relative angle on the path loss.

[0008] To solve the above technical problems, the present application provides the following technical scheme: an indoor high-frequency wireless body area network off-body channel modeling method, specifically comprising the following steps:

[0009] S1, collecting measurement data of different body-to-body relative angles, and constructing a body-to-body relative angle path loss initial model;

[0010] S2, calculating the path loss index, floating intercept, and path loss caused by the body-to-body relative angle according to the body-to-body relative angle path loss initial model;

[0011] S3, fitting the expression of the path loss index, floating intercept, and path loss caused by the body-to-body relative angle by using the least square method;

[0012] S4, constructing the indoor high-frequency off-body channel path loss model affected by the body-to-body relative angle according to the expression obtained in step S3 to represent the influence of different body-to-body relative angles on the path loss.

[0013] Further, in the aforementioned step S1, the body-to-body relative angle path loss initial model is constructed as follows:

[0014] PL(d, θ) = β(θ) + 10n(θ)lg(d / d0) + RA(d, θ) + χ σ ,

[0015] wherein d is the distance between the transceiver, θ is the body-to-body relative angle, n(θ) is the path loss index related to the relative angle, β(θ) is the floating intercept related to the relative angle, d0 is the reference distance, RA(d, θ) is the path loss caused by the change of the relative angle θ when the distance d is the transceiver distance, χ σ is the shadow fading.

[0016] Further, the aforementioned step S2 includes the following sub-steps:

[0017] S201, calculating the path loss value when the distance d is the transceiver distance and the body-to-body relative angle is θ; substituting the transceiver distance d and the corresponding path loss value when the distance d is the transceiver distance and the body-to-body relative angle is θ into the body-to-body relative angle path loss initial model, and calculating the path loss index n(θ) and the floating intercept β(θ) at different relative angles according to the following formula:

[0018] PL(d) = β(θ) + 10n(θ)lg(d / d0) + χ σ ;

[0019] S202, substituting the path loss index n(θ) and the floating intercept β(θ) obtained by solving the above formula into the following formula to calculate RA(d, θ):

[0020] RA(d, θ) = PL(d, θ) - β(θ) - 10n(θ)lg(d / d0) - χ σ ,

[0021] Further, in the step S3, the least square method is used to fit the path loss exponent n(θ) related to the relative angle between the body-to-body, the floating intercept β(θ), and the path loss RA(d, θ) caused by the relative angle between the body-to-body.

[0022] The expression of the path loss exponent n(θ) related to the relative angle between the body-to-body fitted by the least square method is as follows:

[0023] n(θ) = a0 + a1 sin(ω1θ) + b1 cos(ω1θ);

[0024] wherein a0, a1, b1 and ω1 are preset coefficients of the model.

[0025] Further, in the step S3, the expression of the floating intercept β(θ) fitted by the least square method is as follows:

[0026] β(θ) = b0 + a2 sin(ω2θ) + b2 cos(ω2θ),

[0027] wherein b0, a2, b2 and ω2 are preset coefficients of the model.

[0028] Further, in the step S3, the expression of the path loss RA(d, θ) caused by the relative angle between the body-to-body fitted by the least square method is as follows:

[0029] RA(d, θ) = c0 + a3 sin(ω3θ) + b3 cos(ω3θ),

[0030] wherein c0, a3, b3 and ω3 are coefficients of the model, which are related to the measured environment, the length of the distance between the transmitter and the receiver, and the size of the relative angle.

[0031] Further, the step S4 is specifically: according to the obtained expression of n(θ), the expression of β(θ), and the expression of RA(d, θ), constructing an indoor high-frequency off-body channel path loss model affected by the relative angle between the body-to-body, as follows:

[0032] PL(d, θ) = b0 + a2 sin(ω1θ) + b2 cos(ω1θ) + [a0 + a1 sin(ω2θ) + b1 cos(ω2θ)]lg(d / d0) + c0 + a3 sin(ω3θ) + b3 cos(ω3θ) + χ σ .

[0033] Further, the indoor high-frequency wireless body area network off-body channel modeling method further comprises: using the indoor high-frequency off-body channel path loss model affected by the relative angle between the body-to-body to solve the shadow fading χ σ , and calculating χσ The mean and standard deviation verify the accuracy of the model, specifically:

[0034] χ σ = PL(d, θ) - [b0 + a2 sin(ω1θ) + b2 cos(ω1θ) + [a0 + a1 sin(ω2θ) + b1 cos(ω2θ)] lg(d / d0) + c0 + a3 sin(ω3θ) + b3 cos(ω3θ)].

[0035] Further, the aforementioned measurement data of the body-to-body relative angle includes the human body-to-body distance d, the body-to-body relative angle θ, and the path loss value PL of each position point.

[0036] Compared with the prior art, the technical scheme of the present application introduces the information of the body-to-body relative angle into the traditional logarithmic path loss model, which more accurately represents the path loss when the body-to-body relative angle changes. According to the actual measurement data research and analysis of the indoor wireless body area network off-body channel scene, it is shown that the model can more accurately represent the influence of the body-to-body relative angle on the path loss. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 The specific modeling process framework diagram in the technical scheme of the present application.

[0038] Figure 2 The measurement scene diagram in the technical scheme of the present application.

[0039] Figure 3 The relationship between the path loss exponent and the body-to-body relative angle in the actual measurement scene of the present application.

[0040] Figure 4 The relationship between the floating intercept and the body-to-body relative angle in the actual measurement scene of the present application.

[0041] Figure 5 The relationship between the path loss caused by the body-to-body relative angle and the body-to-body relative angle in the actual measurement scene of the present application.

[0042] Figure 6 The comparison between the traditional logarithmic path loss model and the path loss measurement value of the present application.

[0043] Figure 7 The comparison between the path loss model and the path loss measurement value of the present application. DETAILED DESCRIPTION

[0044] In order to better understand the technical content of the present application, specific embodiments are described below with reference to the accompanying drawings.

[0045] Aspects of the present application are described herein with reference to the drawings, which are described below. Embodiments of the present application are not limited to the described drawings. It should be understood that the present application is realized by any one of the above-described various concepts and embodiments, and the concepts and embodiments described in detail below, since the disclosed concepts and embodiments of the present application are not limited to any embodiment. In addition, some aspects disclosed by the present application can be used alone, or in any appropriate combination with other aspects disclosed by the present application.

[0046] As Figure 2 shown in the in-vivo channel measurement scenario of the indoor high-frequency band wireless body area network, the subject of the receiving end stands at the center position of the room, so that the sending end increases the rotation angle and the moving distance, and the subject always remains stationary. The sending antenna is placed on another human body, and the receiving and sending antennas are placed at the navel position of the human body with a height of 1.2 m. The distance between the receiving end antenna and the sending end antenna gradually moves from 0.5 m to 3.5 m, a total of 7 measurement points, and the measurement points are spaced 0.5 m apart. A measurement grid is designed at each measurement point, and the grid contains 9 grid points distributed in a 30 cm x 30 cm network, with a 10 cm interval between each two points. In addition, the sending end human body takes the receiving end subject as the center, and measures from 0° to 315° at each measurement grid point (angle interval 45°), wherein the angle is the relative angle of the two persons.

[0047] As Figure 1 shown, the present application proposes an in-vivo channel modeling method for indoor high-frequency band wireless body area network, based on the in-vivo channel measurement scenario of indoor high-frequency band wireless body area network, comprising the following steps:

[0048] S1, collecting measurement data of different relative angles between the two bodies, including the distance d between the receiving and sending ends of the human body, the relative angle θ between the two bodies, and the path loss value PL of each position point, and constructing an initial model of the relative angle path loss between the two bodies; as follows:

[0049] PL(d, θ) = β(θ) + 10n(θ)lg(d / d0) + MA(d, θ) + χ σ

[0050] Wherein, d is the distance between the receiving and sending ends, θ is the relative angle between the two bodies, n(θ) is the path loss index related to the relative angle, β(θ) is the floating intercept related to the relative angle, d0 is the reference distance, RA(d, θ) is the path loss caused by the change of the relative angle θ when the distance d is changed, χ σ is the shadow fading.

[0051] S2, according to the body-to-body relative angle path loss initial model, calculating the path loss index n(θ) related to the body-to-body relative angle, the floating intercept β(θ), and the path loss RA(d,θ) caused by the body-to-body relative angle; specifically including the following sub-steps S201 to S202:

[0052] S201, calculating the path loss value at the transceiver distance d and the body-to-body relative angle θ; substituting the transceiver distance d and the corresponding path loss value at the transceiver distance d and the body-to-body relative angle θ into the body-to-body relative angle path loss initial model, and calculating the path loss index n(θ) and the floating intercept β(θ) at different relative angles according to the following formula:

[0053] PL(d) = β(θ) + 10n(θ)lg(d / d0) + χ σ ;

[0054] S202, substituting the path loss index n(θ) and the floating intercept β(θ) obtained by the above formula into the following formula to calculate RA(d,θ);

[0055] RA(d,θ) = PL(d,θ) - β(θ) - 10n(θ)lg(d / d0).

[0056] S3, using the least square method to fit the expression of the path loss index n(θ) related to the body-to-body relative angle, the floating intercept β(θ), and the path loss RA(d,θ) caused by the body-to-body relative angle as follows:

[0057] n(θ) = a0 + a1 sin(ω1θ) + b1 cos(ω1θ),

[0058] β(θ) = b0 + a2 sin(ω2θ) + b2 cos(ω2θ),

[0059] RA(d,θ) = c0 + a3 sin(ω3θ) + b3 cos(ω3θ),

[0060] wherein a0, a1, a2, a3, b0, b1, b2, b3, c0, and ω1, ω2, ω3 are coefficients of the model, which are related to the measured environment, the length of the transceiver distance, and the size of the relative angle.

[0061] S4, according to the obtained n(θ) expression, β(θ) expression, and RA(d,θ) expression, constructing the indoor high-frequency off-body channel path loss model affected by the body-to-body relative angle as follows:

[0062] PL(d, θ) = b0 + a2 sin(ω1θ) + b2 cos(ω1θ) + [a0 + a1 sin(ω2θ) + b1 cos(ω2θ)]lg(d / d0) + c0 + a3 sin(ω3θ) + b3 cos(ω3θ) + χ σ .

[0063] The application also comprises an indoor high-frequency band ex vivo channel path loss model using the influence of the body-to-body relative angle, solving the shadow fading χ σ , and calculating the mean and standard deviation of χ σ , verifying the accuracy of the model, specifically:

[0064] χ σ = PL(d, θ) - [b0 + a2 sin(ω1θ) + b2 cos(ω1θ) + [a0 + a1 sin(ω2θ) + b1 cos(ω2θ)]lg(d / d0) + c0 + a3 sin(ω3θ) + b3 cos(ω3θ)].

[0065] Figure 3 The application gives the relationship diagram between the path loss exponent and the different relative angles of body-to-body in the actual measurement scene. It can be found from the diagram that the path loss exponent and the relative angle show a trigonometric function relationship, the correlation coefficients a0 = 1.083, a1 = 0.8719, b1 = 0.253, and ω1 = 0.01902.

[0066] Figure 4 The application gives the relationship diagram between the floating intercept and the different relative angles of body-to-body in the actual measurement scene. It can be found from the diagram that the floating intercept and the relative angle also show a trigonometric function relationship, the correlation coefficients b0 = 30.77, a2 = -35.67, b2 = 6.795, and ω2 = 0.01647.

[0067] Figure 5 The application gives the relationship between the path loss caused by the relative angle of body-to-body and the different relative angles of body-to-body in the actual measurement scene. It can be seen from the diagram that the path loss RA(d, θ) caused by the relative angle of body-to-body and the relative angle of body-to-body show a trigonometric function relationship, the correlation coefficients c0 = 21.67, a3 = 17.48, b3 = 5.046, and ω3 = 0.01942.

[0068] Figure 6 , Figure 7 The application respectively gives the comparison between the traditional logarithmic path loss model, the proposed path loss model, and the measurement data. Through Figure 6 , Figure 7It can be seen that the proposed path loss model is closer to the measured data, while the deviation between the traditional logarithmic path loss model and the measured value is larger, which shows that the proposed path loss model can more accurately represent the path loss of body-to-body at different relative angles in the indoor body area network environment.

[0069] Although the present application has been described in connection with the preferred embodiment thereof with reference to the drawings, it will be apparent to those skilled in the art that various changes and modifications can be made thereto without departing from the scope of the present application. Accordingly, it is intended that all possible changes and modifications be included within the scope of the application as set forth in the following claims.

Claims

1. A method for modeling off-site channels in indoor high-frequency wireless body area networks, characterized in that, Specifically comprising the following steps: S1, collecting measurement data of different relative angles between bodies, and constructing an initial model of path loss of relative angles between bodies; S2, calculating path loss indexes, floating intercepts, and path loss caused by relative angles between bodies according to the initial model of path loss of relative angles between bodies, including the following sub-steps: S201、calculating to obtain the path loss value when the body-to-body relative angle is at the transceiver distance S202、calculating to obtain the path loss value when the body-to-body relative angle is at the transceiver distance S203、calculating to obtain the path loss value when the body-to-body relative angle is at the transceiver distance S204、calculating to obtain the path loss value when the body-to-body relative angle is at the transceiver distance S205、calculating to obtain the path loss value when the body-to-body relative angle is at the transceiver distance S206、calculating to obtain the path loss value when the body-to-body relative angle is at the transceiver distance S207、calculating to obtain the path loss value when the body-to-body relative angle is at the transceiver distance : ； S202, Solve the above formula to obtain the path loss index. and floating intercept Substituting into the following formula, we can calculate the result. ; ； S3, fitting the path loss exponent, the floating intercept, and the expression of the path loss caused by the body-to-body relative angle using a least square method; wherein the path loss exponent related to the body-to-body relative angle is fitted using a least square method The expression is as follows: ； wherein, , , and are preset coefficients of the model; S4, constructing an indoor high-frequency off-body channel path loss model affected by relative angles between bodies according to the expression obtained in step S3, to represent the influence of different relative angles between bodies on path loss.

2. The method of claim 1, wherein, In step S1, the initial model of path loss of relative angles between bodies is constructed as follows: ， where d is the distance between the transceiver and the receiver, is the body-to-body relative angle, is the relative angle dependent path loss exponent, is the relative angle dependent floating intercept, is the reference distance, is the relative angle when the transceiver distance d is the path loss variation caused by the change of the relative angle, is the shadow fading.

3. The method of claim 2, wherein, In step S3, the least square method is used to fit the floating intercept The expression is as follows: ， wherein , , and are preset coefficients of the model.

4. The method of claim 3, wherein, In step S3, the path loss caused by the body-to-body relative angle is fitted using a least squares method The expression is as follows: ， wherein, , , and are coefficients of the model, which are related to the measured environment, the length of the distance between the transmitter and the receiver, and the size of the relative angle.

5. The method of claim 4, wherein, Step S4 is specifically: according to the obtained Expression, Expression, and Expression, the indoor high-frequency band off-body channel path loss model of the relative angle influence of the construct pair, is as follows: 。 6. The method of claim 5, wherein, Also include the indoor high frequency band ex vivo channel path loss model using the influence of body-to-body relative angle, solve the shadow fading And calculate The mean and standard deviation, verify the accuracy of the model, specifically: 。 7. The method of claim 1, wherein, The measurement data of different relative angles of the collection body includes the distance d of the human body receiving and transmitting end at each position point, the relative angle of the body to body and the path loss value PL of each position point.

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