Visible light communication channel modeling method for underground coal mine environment

Abstract

This invention discloses a visible light communication channel modeling method for underground coal mine environments, solving the problem that existing technologies fail to accurately quantify the impact of coal mine dust and obstacles on the attenuation of received optical power. The method includes: determining the link parameters of the visible light communication system, simulation parameters of the environment, and simulation parameters of the transmitter and receiver; calculating the attenuation coefficient of received optical power due to coal mine dust and obstacles; calculating the channel impulse response and characteristic parameters; determining the noise simulation parameters of the photodetector; and calculating the bit error rate of the communication system. This invention quantifies the impact of coal mine dust and obstacles on the channel, integrating the attenuation coefficient of received optical power due to coal mine dust and obstacles into the channel model, resulting in a visible light communication channel model that better reflects the underground coal mine environment. This invention enriches the modeling methods for visible light communication channels, and the modeling results provide guidance for the design and deployment of visible light communication systems in underground coal mine environments.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, and mainly relates to visible light communication channel modeling, specifically a visible light communication channel modeling method for underground coal mine environments. It can be used to analyze the impulse response, path loss, root mean square delay spread, received signal power delay distribution, and bit error rate performance of visible light communication channels in underground coal mines, providing quantitative guidance for the design of visible light communication systems in underground coal mine environments. Technical Background

[0002] As the modernization of underground mine production continues to increase, the demands on communication methods and system functions are also growing. Therefore, continuously improving underground communication systems to achieve timely, accurate, and rapid information transmission is a key measure to ensure safe mine production. Unlike traditional surface communication, the communication environment in underground mines is extremely harsh. In addition to the presence of hydraulic supports, roadheaders, scraper conveyors, and other electromechanical equipment, the air is also filled with large amounts of coal dust, harmful gases, and water vapor. These interfering factors place higher demands on the functionality and equipment of communication systems.

[0003] The development of visible light communication technology, which has emerged alongside LED lighting technology, has brought new opportunities for wireless communication in underground mines. Visible light communication systems use LED lighting sources as signal base stations, achieving signal modulation through rapid on / off switching of LEDs that is imperceptible to the human eye, and transmitting information in the form of light signals. Visible light communication can ensure simultaneous wireless communication and lighting, and is unaffected by electromagnetic interference, making it a highly suitable communication method for underground coal mines.

[0004] While some progress has been made in research on visible light communication channel modeling methods for underground coal mine environments, some problems still remain, such as:

[0005] The master's thesis from Shandong University, titled "Research on Visible Light Communication Channel Model," authored by Wang Jia and published in 2018, separates coal mine dust from the visible light communication channel for independent analysis. It only calculates the extinction efficiency factor and scattering efficiency factor of coal mine dust without quantifying their impact on the visible light communication channel. Therefore, the channel model formula in this thesis does not specifically reflect the influence of coal mine dust on the visible light communication channel. Similarly, for obstacles, the author also separates them from the visible light communication channel for independent analysis. The channel model formula in this thesis does not specifically reflect the influence of obstacles on the visible light communication channel; instead, it only uses a bilateral Gaussian distribution model to calculate the received light energy when occlusion occurs after modeling is completed.

[0006] The IEEE Access journal paper, "A VLC Channel Model for Underground Mining Environments With Scattering and Shadowing," authored by Pablo Palacios Játiva et al., was published in 2020. For coal mine dust, the authors developed a dot scattering model to quantify the impact of coal mine dust on visible light communication channels. This impact is a positive gain, but the negative gain effect of coal mine dust on the channel, i.e., the impact of coal mine dust on the attenuation of received optical power, is not quantified. For obstacles, the authors quantified the impact of obstacles on visible light communication channels based on Poisson processes and geometric models. However, the authors ignored the geometry of the obstacles, abstracting them only as a rectangular plane, and assumed that the obstacles were always perpendicular to the communication link.

[0007] Existing visible light communication channel modeling methods for underground mine environments have the following drawbacks: (1) They do not quantify the impact of coal dust in underground mines on the attenuation of received optical power. (2) They ignore the geometry of obstacles and abstract them as a rectangular plane, and assume that obstacles are always perpendicular to the communication link. These drawbacks reduce the accuracy of the channel model. Therefore, it is essential to establish a more accurate visible light channel model for underground mines. Summary of the Invention

[0008] The purpose of this invention is to address the problem that existing visible light communication channel modeling methods for underground coal mines do not accurately quantify the impact of coal dust and obstacles on the attenuation of received optical power. A more comprehensive and accurate visible light communication channel modeling method for underground coal mine environments is proposed.

[0009] This invention is a visible light communication channel modeling method for underground coal mine environments. Its key feature is that the impact of coal dust and obstacles in the underground coal mine environment on the received optical power is quantified into attenuation coefficients, and these attenuation coefficients are integrated into the channel model. The method includes the following steps:

[0010] (1) Step S1: Determine the link parameters of the visible light communication system in the underground coal mine environment: The visible light communication link consists of a line-of-sight link and a K-order non-line-of-sight link. Determine the order K of the non-line-of-sight link.

[0011] (2) Step S2, determine the simulation parameters of the underground mine environment: determine the length, width, height of the underground mine space, and the reflection coefficient ρ of the walls. w Size A of the wall reflective element ref ;

[0012] (3) Step S3, determine the simulation parameters of the transmitter and receiver: determine the position coordinates T(x) of the transmitter. T ,y T ,z T ), the normal direction of the transmitter n T The transmitter's half-power angle θ 1 / 2 Determine the receiver's position coordinates R(x) R ,y R Z R ), receiver normal direction n R Receiving surface area A PD Receiver field of view Receiver optical filter gain The internal refractive index α of the optical condenser and the photoelectric conversion efficiency γ of the receiver;

[0013] (4) Step S4: Calculate the attenuation coefficient of coal dust on the received optical power: Based on the determined complex refractive index m, radius r, density ρ1, concentration ρ2, wavelength λ of emitted light, and distance d of light propagation of coal dust in the environment, calculate the scattering efficiency factor Q of coal dust using Mie scattering theory. sca and absorption efficiency factor Q abs By combining the Lambert-Beer law, a formula was developed to calculate the attenuation coefficient of received optical power caused by suspended coal dust in the coal mine environment. The attenuation coefficient G of the coal dust on the received optical power was then calculated. ext (α,d);

[0014] (5) Step S5, calculate the attenuation coefficient of the received optical power due to the obstacle: based on the determined number K of obstacles in the environment. s Height h i Based on the probability density function g(w) of the light-blocking width and the joint probability density function f(x,y) of the x and y coordinates of the midpoint of the obstacle, a probability formula for the obstruction of a communication link by a single obstacle is constructed, and the attenuation coefficient G of the obstacle on the received optical power is calculated. sha (A,B);

[0015] (6) Step S6, calculate the channel impulse response: based on the attenuation coefficient G of coal dust on the received optical power calculated in step S4. ext (α,d) and the attenuation coefficient G of the obstacle to the received optical power calculated in step S5. sha (A,B), the channel impulse response h(t) is calculated using the Lambert radiation model;

[0016] (7) Step S7, calculate the characteristic parameters of the channel: Based on the channel impulse response h(t) calculated in step S6, calculate the delay distribution of the received signal power, path loss PL, and root mean square delay spread D in the channel characteristic parameters. RMS ;

[0017] (8) Step S8: Determine the simulation parameters of the photodetector's noise: The simulation parameters of the noise are used to calculate the power of additive white Gaussian noise in the received signal and to determine the equivalent noise bandwidth B of the photodetector inside the receiver during communication. w Background current I bg Type I noise bandwidth factor I2, Type II noise bandwidth factor I3, open-loop voltage gain G, MOSFET noise factor Γ, MOSFET transconductance g m Fixed capacitance per unit area η, thermodynamic temperature T of the coal mine environment k ;

[0018] (9) Step S9: Calculate the bit error rate of the visible light communication system in the underground coal mine environment: Based on the channel impulse response h(t) calculated in step S6 and the noise simulation parameters of the photodetector determined in step S8, calculate the bit error rate of the visible light communication system in the underground coal mine environment under the on-off keying modulation scheme and the 4-pulse amplitude modulation scheme.

[0019] Existing studies on visible light communication channel models for underground coal mines have neglected the impact of coal dust on the attenuation of received optical power. Furthermore, when quantifying the impact of obstacles on received optical power attenuation, they only model the situation as ideal, ignoring the geometry of the obstacles and abstracting them as a rectangular plane, and assuming that the obstacles are always perpendicular to the communication link. Therefore, current visible light communication channel modeling methods for underground coal mines cannot accurately reflect the real channel conditions, which interferes with related research on visible light communication systems in underground coal mine environments.

[0020] This invention solves the technical problem that existing visible light communication channel modeling methods for underground coal mines do not accurately quantify the impact of coal dust and obstacles on the attenuation of received optical power.

[0021] Compared with the prior art, the present invention has the following advantages:

[0022] (1) The influence of coal mine dust on the attenuation of received optical power is quantified: The present invention quantifies the influence of coal mine dust on received optical power as an attenuation coefficient. The scattering efficiency factor and absorption efficiency factor of coal mine dust are calculated using Mie scattering theory. Combined with Lambert-Beer law, a formula for calculating the attenuation coefficient of coal mine dust on received optical power in the coal mine environment is formed, and then the attenuation coefficient of coal mine dust on received optical power is calculated.

[0023] (2) The impact of obstacles on the attenuation of received optical power is quantified more accurately: The present invention quantifies the impact of obstacles on received optical power as an attenuation coefficient, models the obstacle as a cuboid with an arbitrary rotation angle, constructs a probability formula for a single obstacle to block the visible light communication link based on the geometric model when the occlusion occurs, and further calculates the attenuation coefficient of the obstacle on the received optical power based on probability theory.

[0024] (3) It has engineering application value: This invention integrates the attenuation coefficient of coal mine dust and obstacles on the received light power into the visible light communication channel model, and obtains a visible light communication channel model that is more in line with the underground coal mine environment. It has guiding significance for the design and deployment of visible light communication systems in underground mine environments. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0026] Figure 1 This is a flowchart of the present invention;

[0027] Figure 2 This is a schematic diagram of line-of-sight links and non-line-of-sight links;

[0028] Figure 3 This is a schematic diagram of the rectangular coordinate system established by the present invention for the underground coal mine shaft space;

[0029] Figure 4 This is a schematic diagram showing the direction of the transmitter's normal.

[0030] Figure 5 This is a schematic diagram showing the direction of the receiver's normal.

[0031] Figure 6 This is a schematic diagram of the geometric model of the communication link obstructed by obstacles according to the present invention;

[0032] Figure 7 This is a schematic diagram of the light-blocking width of the obstacle according to the present invention;

[0033] Figure 8 This is a schematic diagram of condition one of the obstacle-blocked communication link of the present invention;

[0034] Figure 9 This is a schematic diagram illustrating condition two of the present invention regarding the obstruction of the communication link by an obstacle;

[0035] Figure 10 This is a schematic diagram of the region Δ where the midpoint coordinates need to be located when the link is blocked by an obstacle according to the present invention;

[0036] Figure 11The diagram shows the channel impulse response calculation results provided by this invention;

[0037] Figure 12 The bit error rate calculation results provided by this invention are shown in the figure. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the present invention clearer, the following detailed description is provided in conjunction with the accompanying drawings and specific embodiments.

[0039] Example 1

[0040] Visible light communication systems consist of a transmitter, a receiver, and a free-space transmission channel. The transmitter emits light signals based on a light-emitting diode (LED) light source. These signals are transmitted through the free-space channel to the receiver, where they are received by a photodetector and converted into electrical signals. Visible light communication systems in common indoor environments such as classrooms and offices have been extensively studied. However, the environment of underground coal mines differs greatly from these indoor environments, exhibiting many channel interference factors not present in ordinary indoor environments, particularly coal dust and randomly moving mining equipment. Therefore, visible light communication channel models designed for ordinary indoor environments may not be applicable to underground coal mine environments, and channel modeling is the first step in the analysis and design of visible light communication systems. Thus, to improve the accuracy of research on visible light communication systems in underground coal mine environments, it is necessary to construct a visible light communication channel model that conforms to the underground coal mine environment.

[0041] To address the problem that existing technologies do not accurately quantify the impact of coal mine dust and obstacles on the attenuation of received optical power, this invention proposes a visible light communication channel modeling method for underground coal mine environments.

[0042] This invention is a visible light communication channel modeling method for underground coal mine environments. It is used to model visible light communication systems in this unique environment. The main method involves quantifying the impact of coal dust and obstacles on the received optical power in the underground coal mine environment as attenuation coefficients, and integrating these two attenuation coefficients into the channel model. (See [link to relevant documentation]). Figure 1 , Figure 1 The flowchart of this invention includes the following steps:

[0043] Step S1: Determine the link parameters of the visible light communication system in the underground coal mine environment. Specifically, the visible light communication channel includes two types of communication links: line-of-sight links and non-line-of-sight links. A schematic diagram of these two types of links is shown below. Figure 2 As shown, Figure 2 This is a schematic diagram of line-of-sight links and non-line-of-sight links.

[0044] Line-of-sight links refer to transmitted light signals traveling directly to the receiver along a straight path without being blocked or reflected by anything; they constitute a major part of visible light communication systems. Figure 2 In the diagram, line-of-sight links are represented by solid lines. Non-line-of-sight links refer to links where the transmitted optical signal does not travel directly to the receiver in a straight line, but rather is reflected by an object (such as a wall) before reaching the receiver. A first-order non-line-of-sight link is a link where the signal reaches the receiver after one reflection, and so on, up to a K-order non-line-of-sight link where the signal reaches the receiver after K reflections. Generally, non-line-of-sight links of order 2 and above have a very weak impact on the channel; therefore, K is usually set to ≤ 2.

[0045] Step S2, determine the simulation parameters of the underground mine environment: Specifically, the simulation parameters of the underground coal mine include the length L, width W, height H, and wall reflectance ρ of the coal mine space. w Size A of the wall reflective element ref .

[0046] The reflectance coefficient of a wall refers to the ratio of the intensity of light reflected back from the wall to the intensity of light incident on the wall. Generally, 0 < ρ. w <1, the reflectivity of a wall depends on factors such as wall material, color, and surface treatment.

[0047] In computer simulations, the wall surface needs to be discretized, dividing a single wall into multiple smaller reflective elements. Generally, these reflective elements are considered as square planes, i.e., A. ref =(Δd) 2 Δd is called the distance resolution.

[0048] Step S3, determine the simulation parameters of the transmitter and receiver: Specifically, the simulation parameters of the transmitter include determining the transmitter's position coordinates T(x) T ,y T ,z T ), the normal direction of the transmitter n T That is, the pointing direction of the transmitter's light-emitting center and the transmitter's half-power angle θ. 1 / 2 Receiver simulation parameters: Receiver position coordinates R(x) R ,y R ,z R ), receiver normal direction n R That is, the pointing direction of the receiver center and the receiving surface area A. PD Receiver field of view Receiver optical filter gain The internal refractive index α of the optical condenser and the photoelectric conversion efficiency γ of the receiver.

[0049] The transmitter's position coordinates are determined by its X-coordinate x. T Y coordinate y T Z-coordinate z T This indicates that the values ​​of these three coordinates are related to the established rectangular coordinate system. Figure 3 This is a schematic diagram of the rectangular coordinate system established by the present invention for the underground coal mine space. Specifically, a rectangular coordinate system is established with the lower left corner of the underground coal mine space as the origin, the width direction as the X-axis, the length direction as the Y-axis, and the height direction as the Z-axis.

[0050] Figure 4 n is the normal direction of the transmitter T A schematic diagram, n T Using the elevation angle β in three-dimensional space T and azimuth α T To represent. Specifically, β T For n T The angle between the z-axis and the positive z-axis; draw n T The projection onto the XOY plane, with projection point P. T Then α T For vectors The projection onto the positive X-axis. T The relationship between these two angles is as follows:

[0051]

[0052] half-power angle θ of the transmitter 1 / 2 θ refers to the angle between the light intensity and the angle that extends outwards from the direction of the light source's normal, decreasing from I to I / 2. 1 / 2 The larger the value, the more divergent the beam. 1 / 2 The smaller the value, the more concentrated the beam.

[0053] Figure 5 n is the normal direction of the receiver. R A schematic diagram, n R Using the elevation angle β in three-dimensional space R and azimuth α R To represent. Specifically, β R For n R The angle between the z-axis and the positive z-axis; draw n R The projection onto the XOY plane, with projection point P. R Then α R For vectors The projection onto the positive X-axis. R The relationship between these two angles is as follows:

[0054]

[0055] Receiver field of view This indicates the maximum angle at which the receiver can receive incident light, when the incident light is perpendicular to n. R The angle between them is greater than the receiver's field of view. When the light signal is at a certain time, no light signal will be received; conversely, when it is at a certain time, a light signal will be received.

[0056] Receiver optical filter gain This indicates the gain of an optical filter for different wavelengths of light signals. An optical filter is an optical element that can selectively allow or block light of specific wavelengths. In receivers, optical filters are typically used to select a specific wavelength range of the received light. Generally speaking... That is, light of all wavelengths can pass through the filter.

[0057] The photoelectric conversion efficiency γ of a receiver represents the ratio of the number of photoelectrons generated by the photodetector in the receiver per unit time to the number of photons in the incident light. Generally, 0 < γ < 1.

[0058] Step S4: Calculate the attenuation coefficient of the received optical power due to coal mine dust. Specifically, firstly, the scattering efficiency factor Q of the coal mine dust is calculated using Mie scattering theory. sca and absorption efficiency factor Q abs Then, combining the Lambert-Beer law, a formula is derived to calculate the attenuation coefficient of received optical power caused by suspended coal dust in the coal mine environment, and the attenuation coefficient G of received optical power caused by coal dust is calculated. ext (α,d).

[0059] More specifically, according to Mie scattering theory, the scattering efficiency factor Q of coal mine dust... sca and absorption efficiency factor Q abs The calculations are as follows:

[0060]

[0061]

[0062] in, Let χ be a real function, where χ is the diameter parameter of coal mine dust, and r is the radius of the coal dust, λ is the wavelength of the emitted light, and a n b is the first type of Mie scattering coefficient. n Let a be the Mie scattering coefficient of the second type. n and b n The calculations are as follows:

[0063]

[0064]

[0065] Where m is the complex refractive index of coal mine dust, ψ n (χ) is the Riccati-Bessel function of the first kind, ξ n (χ) is the Riccati-Bessel function of the second kind, ψ n (χ) and ξ n (χ) is calculated as follows:

[0066]

[0067]

[0068] in, and These are the Bessel function of semi-integer order and the Hankel function of the second kind, respectively.

[0069] Based on Lambert-Beer's law, a formula is derived to calculate the attenuation coefficient of received optical power due to coal mine dust, and G is calculated. ext (α,d) is as follows:

[0070] G ext (α,d)=exp(-αd)

[0071] Where d is the distance the light travels, and α is the extinction coefficient of coal mine dust. Based on the scattering efficiency factor Q of coal mine dust... sca and absorption efficiency factor Q abs Calculate the extinction coefficient α of coal mine dust:

[0072] α=Q sca πr 2 N+Q abs πr 2 N

[0073] Where N is the amount of coal dust per unit volume, and it is calculated as follows:

[0074]

[0075] Where ρ1 is the density of coal dust and ρ2 is the concentration of coal dust.

[0076] Step S5: Calculate the attenuation coefficient of the received optical power due to obstacles. Specifically, mine cars and fixed mining equipment in the mine will inevitably block the optical signal transmission between the LED light and other receivers, causing the propagation link to be interrupted, i.e., the occlusion effect. Due to the randomness of obstacle occlusion, this invention treats the occlusion effect as the average path loss, that is, it uses the probability of no occlusion as the attenuation coefficient to quantify the impact of obstacles on the channel. First, based on the geometric model when an obstacle blocks the link, a probability formula for the visible light communication link being blocked by a single obstacle is constructed, and then the attenuation coefficient G of the received optical power due to obstacles is calculated from this formula. sha (A,B)

[0077] This invention models obstacles as cuboids. For a point-to-point communication link, the coordinates of the transmitting end are represented as A(x...). ′ T ,y ′ T ,z ′ T The coordinates of the receiving end are represented as B(x). ′ R ,y R ′ ,z ′ R For an obstacle to block a communication link, two conditions must be met: (1) the communication link must be located within the light-blocking range of the obstacle, and (2) the obstacle must be sufficiently close to the receiver. Therefore, the obstacle must be located within a certain area Δ to block the link. Thus, the probability P of a visible light communication link being blocked by a single obstacle in an underground coal mine environment can be calculated. i The calculation formula for P i as follows:

[0078]

[0079] Where g(w) is the probability density function of the obstacle's shading width, f(x,y) is the joint probability density function of the x and y coordinates of the midpoint of the side of the obstacle closest to the receiver, W1 is the maximum value of the obstacle's shading width, and W2 is the minimum value of the obstacle's shading width. T >z′ R When Δ is:

[0080]

[0081] When z′ T <z′ R When Δ is:

[0082]

[0083] When z′ T =z′R When Δ is:

[0084]

[0085] Among them, h i Let ψ be the height of the obstacle, ψ be the angle between line segment CD and the X-axis, point C be the projection of the transmitter onto the XOY plane, point D be the projection of the receiver onto the XOY plane, and 0 ≤ ψ ≤ π / 2, and d0 be the horizontal distance between the transmitter and receiver.

[0086] Generally, if the midpoint coordinates and shading width of an obstacle satisfy independent and identical distribution, then based on the probability that a single obstacle blocks the link, the attenuation coefficient of the received optical power due to the obstacle is calculated as follows:

[0087]

[0088] Among them, K s The number of obstacles. This is the multiplication symbol.

[0089] Step S6, calculate the channel impulse response: Specifically, based on the attenuation coefficient G of the coal dust on the received optical power calculated in step S4. ext (α,d) and the attenuation coefficient G of the obstacle to the received optical power calculated in step S5. sha (A,B), the channel impulse response h(t) is calculated using the Lambert radiation model;

[0090] The impulse response of a visible light communication channel can be expressed as the sum of the impulse response of a line-of-sight link and the impulse response of a non-line-of-sight link:

[0091]

[0092] The channel impulse response of a line-of-sight link can be expressed as:

[0093]

[0094] Where θ is the angle of light emission, d ′ Indicates the length of the line-of-sight link. Let c be the angle of incidence of the received light, c be the speed of light, and m be the Lambertian radiation factor. Let be the gain of the optical condenser, δ(·) be the Dirichlet function, and Γ(·) be the rectangular function. and The calculations are as follows:

[0095]

[0096]

[0097]

[0098]

[0099] If the optical signal reaches the receiver after k reflections, the channel impulse response of a non-line-of-sight link can be expressed as:

[0100]

[0101] Where, θ i Let be the exit angle of the emitted light in the (i-1)th reflection link. Let d be the incident angle of the incident light in the (j-1)th reflection link. l Let be the length of the (l-1)th reflection link. The total impulse response of the non-line-of-sight link is the sum of the impulse responses of all non-line-of-sight links:

[0102]

[0103] Based on the attenuation coefficient of coal dust on received optical power calculated in step S4 and the attenuation coefficient of obstacles on received optical power calculated in step S5, the impulse response h(t) of the visible light communication channel in the underground mine environment is further calculated as follows:

[0104]

[0105]

[0106] Among them, T e Let R be the position coordinates of the emitted light in the (e-1)th reflection link. e The coordinates of the incident light in the (e-1)th reflection link are given.

[0107] Step S7: Calculate the channel characteristic parameters. Specifically, based on the channel impulse response h(t) calculated in step S6, calculate the received signal power delay distribution, path loss PL, and root mean square delay spread D among the channel characteristic parameters. RMS .

[0108] More specifically, let t0 be the arrival time of the signal on the line-of-sight link. For each order of non-line-of-sight link, the arrival time of the signal on the shortest propagation path is t1, and the arrival time of the signal on the longest propagation path is t2. Then the signal power delay distribution is the interval [t1-t0, t2-t0].

[0109] Based on the channel impulse response h(t) obtained in step S6, the path loss PL is calculated as follows:

[0110]

[0111] Where Δt is the sampling interval and M is the number of sampling points.

[0112] Based on the channel impulse response h(t) calculated in step S6, the root mean square delay spread D RMS Calculation as follows

[0113]

[0114]

[0115] Where μ represents the average delay spread. At this point, the channel model is complete.

[0116] Step S8, determine the simulation parameters of the photodetector noise: Specifically, the noise simulation parameters are used to calculate the power of additive white Gaussian noise in the received signal. The noise simulation parameters include determining the equivalent noise bandwidth B of the photodetector inside the receiver during communication and the background current I. bg Type I noise bandwidth factor I2, Type II noise bandwidth factor I3, open-loop voltage gain G, MOSFET noise factor Γ, MOSFET transconductance g m Fixed capacitance per unit area η, thermodynamic temperature T of the coal mine environment k .

[0117] Step S9: Calculate the bit error rate of the visible light communication system in the underground coal mine environment. Specifically, based on the channel impulse response h(t) calculated in step S6 and the noise simulation parameters of the photodetector determined in step S8, calculate the bit error rate of the visible light communication system in the underground coal mine environment under the on-off keying modulation scheme and the 4-pulse amplitude modulation scheme.

[0118] More specifically, using an on / off keying modulation scheme, with an amplitude of 2P t A light pulse is used to represent the transmitted bit 1, and a no-pulse signal is used to represent the transmitted bit 0, where P t Let be the average transmitted optical power. Based on the above principle, a transmitted pulse signal s1 is generated. The electrical signal y1 received by the receiver is then calculated as follows:

[0119]

[0120] Where γ is the photoelectric conversion efficiency of the receiver. is the convolution operator, and w is Gaussian white noise.

[0121] Next, the received electrical signal y1 is sampled and judged. If the sampled value is greater than the threshold T... OOK The decision is bit 1 if the sampled value is less than the threshold T. OOK The decision is then bit 0, thus obtaining the received bit sequence q1, where...

[0122] Finally, count the number of bits in q1 that are different from the transmitted bit sequence x1. The bit error rate of a visible light communication system in an underground coal mine environment under a switch-health modulation scheme is:

[0123]

[0124] Where, n total Indicates the number of bits transmitted.

[0125] Using a 4-pulse amplitude modulation scheme, with an amplitude of 2P t The transmitted bit 11 is represented by a light pulse with an amplitude of [missing information]. The transmitted bit 10 is represented by a light pulse with an amplitude of [missing information]. The transmitted bit 01 is represented by a light pulse, and the transmitted bit 0 is represented by a no-pulse signal. Based on the above principle, the transmitted pulse signal s2 is generated, and the received signal y2 is calculated as follows:

[0126]

[0127] Then based on the threshold Sampling decision for y2: If the sampled value is closest to The decision is bit 00 if the sampled value is closest to... The decision is bit 0 or 1 if the sampled value is closest. The decision is bit 10, if the sampled value is closest. The decision is then bit 11, resulting in the received bit sequence q2. The number of bits in q2 that do not match the transmitted bit sequence x2 is then counted. The bit error rate is:

[0128]

[0129] This invention establishes a visible light communication channel modeling method for underground mine environments. This method supports the analysis and quantification of the impact of coal mine dust and obstacles on the channel, improving the accuracy of channel modeling. After obtaining the channel model, the bit error rate performance of the communication system can also be simulated. This invention supports channel modeling under arbitrary environmental simulation parameters, arbitrary transmitter simulation parameters, arbitrary receiver simulation parameters, arbitrary coal mine dust simulation parameters, and arbitrary obstacle simulation parameters. This enriches the channel modeling methods for visible light communication systems, and the channel modeling results and analysis provide guidance for the design and deployment of visible light communication systems in underground mine environments.

[0130] Example 2

[0131] The visible light communication channel modeling method for underground coal mine environments is the same as in Example 1. The calculation of the attenuation coefficient of coal dust on the received optical power in step S4 of this invention includes the following steps:

[0132] Step S4.1: Calculate the scattering efficiency factor Q of coal mine dust. sca and absorption efficiency factor Q abs Specifically, according to measured data on the dispersion of coal dust in the air at coal mining faces in some regions of my country, about 90% of coal dust particles have a diameter of less than 5 μm. Since the wavelength of visible light is similar to the diameter of coal dust, the Mie scattering theory can be used to analyze the absorption and scattering of light by coal dust.

[0133] In Mie scattering theory, the key lies in calculating the scattering efficiency factor Q of coal mine dust. sca and absorption efficiency factor Q abs Scattering efficiency factor Q of coal mine dust sca and absorption efficiency factor Q abs The calculations are as follows:

[0134]

[0135]

[0136] in, Let χ be a real function, where χ is the diameter parameter of coal mine dust, and r is the radius of the coal dust, λ is the wavelength of the emitted light, and a n b is the first type of Mie scattering coefficient. n Let a be the Mie scattering coefficient of the second type. n and b n The calculations are as follows:

[0137]

[0138]

[0139] Where m is the complex refractive index of coal mine dust, ψ n (χ) is the Riccati-Bessel function of the first kind, ξ n (χ) is the Riccati-Bessel function of the second kind, ψ n (χ) and ξ n (χ) is calculated as follows:

[0140]

[0141]

[0142] in, and These are the Bessel function of semi-integer order and the Hankel function of the second kind, respectively.

[0143] Step S4.2, calculate the amount of coal dust N per unit volume: Specifically, the amount of coal dust N per unit volume is calculated as follows:

[0144]

[0145] Wherein, ρ1 is the density of coal dust and ρ2 is the concentration of coal dust. This parameter is used to calculate the extinction coefficient α of coal dust in step S4.3.

[0146] Step S4.3, calculate the extinction coefficient α of coal mine dust: Specifically, the extinction coefficient of coal mine dust is the sum of its scattering coefficient and absorption coefficient, i.e., α = α sca +α abs The scattering coefficient α of coal mine dust sca and absorption coefficient α abs The calculations are as follows:

[0147] α sca =Q sca πr 2 N

[0148] α abs =Q abs πr 2 N

[0149] The extinction coefficient of coal mine dust is calculated as follows:

[0150] α=Q sca πr 2 N+Q abs πr 2 N

[0151] Step S4.4, calculate the attenuation coefficient of coal dust on the received optical power: Generally, the coal dust concentration in mines needs to be lower than the highest national standard, i.e., 10 mg / m³. 3 Under these conditions, the scattering of coal mine dust satisfies the principles of uncorrelated scattering and single scattering. Uncorrelated scattering means that the scattering of a single particle is unaffected by other particles, while single scattering means that the total scattered light intensity can be considered as the superposition of the scattered light intensities of individual particles. Combining this with Lambert-Beer's law, we can formulate the attenuation coefficient G of coal mine dust on optical power. ext The formula for calculating (α,d) is used to calculate G. ext (α,d) is as follows:

[0152] G ext (α,d)=exp(-αd)

[0153] Where exp(·) is an exponential function with the natural constant as the base, and d is the distance the light ray travels.

[0154] This invention, by combining Mie scattering theory and Lambert-Beer's law, formulates a formula for calculating the attenuation coefficient of received optical power caused by coal mine dust, accurately quantifying the impact of coal mine dust on received optical power in underground coal mine environments. The calculated attenuation coefficient G of coal mine dust on received optical power is then used. ext Integrating (α,d) into the channel impulse response of the model can yield a visible light communication channel model that is more consistent with the underground coal mine environment.

[0155] Example 3

[0156] The visible light communication channel modeling method for underground coal mine environments is the same as in Examples 1-2. The calculation of the attenuation coefficient of the obstacle to the received optical power in step S5 of this invention includes the following steps:

[0157] Step S5.1, construct the probability formula for a single obstacle occlusion link: The invention models obstacles as cuboids, such as... Figure 6 The diagram shows a geometric model of a communication link obstructed by an obstacle. Let the coordinates of the transmitting end be A(x). ′ T ,y ′ T ,z ′ T Its projection onto the XOY axis is point C, and the coordinates of the receiving end are B(x). ′ R ,y R ′ ,z ′ R The projection of the obstacle onto the XOY axis is point D, and point G(x,y) is the midpoint of the side of the obstacle closest to the receiving end. For ease of description, it will be referred to as the midpoint of the obstacle below. w represents the light-blocking width, and h represents the height. The light-blocking width is not the same as the width of the object. Figure 7 The diagram shows the width of the light-blocking barrier. Draw a straight line L perpendicular to CD through point G, where w is the projection of the object's width w0 onto L. Therefore, for an obstacle S0:{G(x,y),(w0,h)} with any deflection angle, it can be considered as an obstacle S0:{G(x,y),(w,g)} whose width direction is always perpendicular to the straight line CD.

[0158] For an obstacle S:{G(x,y),(w,h)}, blocking the link requires the following two conditions to be met: (1) Figure 8The diagram shows the first condition for an obstacle blocking a communication link. The link needs to be located within the light-blocking range of the obstacle, that is, point G(x,y) needs to be located within a cuboid region with CD as the central axis and a width of w; (2) as Figure 9 The diagram illustrates condition two where an obstacle obstructs the communication link. Let point E be the position where the obstacle just barely blocks the LOS link. Then, the obstacle needs to be located closer to the receiver than point E to block the link.

[0159] Therefore, the midpoint coordinates of the obstacle S:{G(x,y),(w,h)} need to be within the region Δ to block the LOS link, where Δ is... Figure 10 The shaded area shown is represented as follows:

[0160]

[0161] Where ψ represents the angle between line segment CD and the x-axis, and 0 ≤ ψ ≤ π / 2, and d0 is the distance between points CD. It should be noted that the fourth inequality in this system of inequalities holds true on z′. T >z′ R Under the premise that z′ T <z′ R and z′ T =z′ R At that time, it needs to be modified as follows:

[0162]

[0163]

[0164] Then construct the probability P that a visible light communication link in an underground coal mine environment is blocked by a single obstacle. i The calculation formula for P i as follows:

[0165]

[0166] Where f(x,y) is the joint probability density function of the x and y coordinates of the midpoint of the obstacle, and g(w) is the probability density function of the obstacle's shading width w.

[0167] In particular, if the coordinates of the midpoint of the obstacle are uniformly distributed in the plane, i.e. X max X is the maximum x-coordinate of the midpoint of the obstacle. min Y is the minimum x-coordinate of the midpoint of the obstacle. max Y is the maximum value of the ordinate of the midpoint of the obstacle. max Let be the minimum value of the ordinate of the midpoint of the obstacle. The probability that a single obstacle will block the link is calculated as follows:

[0168]

[0169] Step S5.2, calculate the attenuation coefficient of the obstacle to the received optical power: Generally, the midpoint coordinates and the shading width of the obstacle satisfy independent and identical distribution. If there is K in space... s One obstacle: Based on the calculated probability of a single obstacle blocking the link, the attenuation coefficient G of the received optical power due to the obstacle is calculated. sha The following is an example of (A, B):

[0170]

[0171] in, This is the multiplication symbol.

[0172] Unlike existing technologies, this invention models obstacles as cuboids with arbitrary rotation angles and specific geometric shapes. By using the geometric model of an obstacle blocking the link, a formula is constructed to calculate the probability of a single obstacle blocking the link. From this, the attenuation coefficient G of the obstacle on the received optical power is further calculated. sha (A, B). Because existing technical solutions ignore the geometry of obstacles and abstract them as a rectangular plane, and assume that obstacles are always perpendicular to the communication link, the present invention provides a more accurate and universal model of obstacles.

[0173] Example 4

[0174] The visible light communication channel modeling method for underground coal mine environments is the same as in Examples 1-3. The calculation of channel impulse response in step S6 of this invention includes the following steps:

[0175] Step S6.1, calculate the impulse response h of the line-of-sight link. LOS (t): Combining the Lambertian radiation model, the attenuation coefficients of coal dust and obstacles on the received optical power are integrated into the channel model. The impulse response of the line-of-sight link is calculated as follows:

[0176]

[0177] Where θ is the emission angle of the emitted light, and d ′ The length of the line-of-sight link. Let c be the angle of incidence of the received light, c be the speed of light, and m be the Lambertian radiation factor. Let δ(·) be the optical condenser gain of the receiver, Γ(·) be the Dirichlet function, and m be the rectangular function. and The calculations are as follows:

[0178]

[0179]

[0180]

[0181]

[0182] Where ln(·) is the logarithmic function;

[0183] Step S6.2, calculate the impulse response h of the non-line-of-sight link. NLOS (t): The K-order non-line-of-sight link is the link through which the transmitter's light source is received by the receiver after K reflections. Combining the Lambertian radiation model, the attenuation coefficients of coal dust and obstacles on the received optical power are integrated into the channel model. The impulse response of the non-line-of-sight link is calculated as follows:

[0184]

[0185] Where, θ i Let be the exit angle of the emitted light in the (i-1)th reflection link. Let d be the incident angle of the incident light in the (j-1)th reflection link. l T is the length of the (l-1)th reflection link. e Let R be the position coordinates of the emitted light in the (e-1)th reflection link. e Let be the position coordinates of the incident light in the (e-1)th reflection link;

[0186] Step S6.3, calculate the channel impulse response h(t): The channel impulse response is the sum of the impulse responses of the line-of-sight link and the non-line-of-sight link. The channel impulse response is calculated as follows:

[0187] h(t) = h LOS (t)+h NLOS (t)

[0188] Among them, h LOS (t) represents the impulse response of the line-of-sight link calculated in step S6.1, h NLOS (t) represents the impulse response of the non-line-of-sight link calculated in step S6.2.

[0189] This invention integrates the attenuation coefficient of coal mine dust on received optical power and the attenuation coefficient of obstacles on received optical power into the channel impulse response of the model, which can obtain a visible light communication channel model that is more consistent with the underground coal mine environment.

[0190] Example 5

[0191] The visible light communication channel modeling method for underground coal mine environments is the same as in Examples 1-4. The calculation of channel characteristic parameters in step S7 of this invention includes the following steps:

[0192] Step S7.1, calculate the delay distribution of received signal power: Specifically, the delay distribution of received signal power refers to the delay range of each order of non-line-of-sight link compared to the line-of-sight link. Let the arrival time of the signal on the line-of-sight link be t0. For each order of non-line-of-sight link, the arrival time of the signal on the shortest propagation path is t1, and the arrival time of the signal on the longest propagation path is t2. Then the signal power delay distribution is the interval [t1-t0, t2-t0].

[0193] Step S7.2, calculate the path loss PL: Specifically, in visible light communication systems, path loss refers to the signal power loss caused by factors such as attenuation and reflection along the transmission path. Based on the channel impulse response h(t) calculated in step S6, the path loss is calculated as follows:

[0194]

[0195] Where Δt is the sampling interval and M is the number of sampling points;

[0196] Step S7.3, calculate the root mean square time delay spread D. RMS Specifically, in visible light communication systems, the different path lengths of line-of-sight and non-line-of-sight links cause the visible light signal to arrive at the receiver at different times, resulting in system delay and thus time delay spread. Time delay spread can explain inter-symbol interference and multipath effects in the channel, and it is often used to quantitatively describe the dispersion characteristics of the channel. Based on the channel impulse response h(t) calculated in step S6, the root mean square time delay spread is calculated as follows:

[0197]

[0198]

[0199] Where μ is the average time delay spread.

[0200] Based on the impulse response of the visible light communication channel in the underground coal mine environment calculated in this invention, more characteristic parameters of the visible light communication channel that better suit the underground coal mine environment can be calculated: namely, the delay distribution of the received signal power, path loss PL, and root mean square delay spread D. RMS These parameters can provide numerical guidance for the design and analysis of visible light communication systems in underground coal mine environments.

[0201] Example 6

[0202] The visible light communication channel modeling method for underground coal mine environments is the same as in Examples 1-5. The calculation of the bit error rate of the visible light communication system in the underground coal mine environment described in step S9 of this invention includes the following steps:

[0203] Step S9.1, generate the transmitted optical pulse signal s1 under the on / off keying modulation scheme: using a pulse with an amplitude of 2P t A light pulse is used to represent the transmitted bit 1, and a no-pulse signal is used to represent the transmitted bit 0, where P t The average emitted optical power is given. Based on the above principle, an emitted optical pulse signal s1 is generated.

[0204] Step S9.2, calculate the received electrical signal y1 under the on / off keying modulation scheme: The received electrical signal y1 is calculated as follows:

[0205]

[0206] Where γ is the photoelectric conversion efficiency of the receiver. This is the convolution operator, where w is a variable with a mean of 0 and a variance of σ. 2 Additive white Gaussian noise, σ 2 The calculation method is as follows:

[0207]

[0208]

[0209]

[0210] Where q represents the electron charge, B w I represents the equivalent noise bandwidth. bg I2 represents the background current, I3 is the first-order noise bandwidth factor, I2 is the second-order noise bandwidth factor, k is the Boltzmann constant, and T is the background current. k Let G be the thermodynamic temperature of the environment, G be the open-loop voltage gain, and A be the open-loop voltage gain. PD Let Γ be the receiving surface area, Γ be the channel noise factor of the field-effect transistor, η be the fixed capacitance per unit area of ​​the photodetector, and g be the signal strength. m Transconductance of a field-effect transistor;

[0211] Step S9.3: Sample and decide on the received electrical signal y1: If the sampled value is greater than the threshold T OOK The decision is bit 1 if the sampled value is less than the threshold T. OOK The decision is then bit 0, thus obtaining the received bit sequence q1, where...

[0212] Step S9.4: Calculate the bit error rate of the communication system under the on / off keyed modulation scheme: count the number of bits that are different between q1 and the transmitted bit sequence x1. The bit error rate is calculated as follows:

[0213]

[0214] Where, n total Indicates the number of bits transmitted.

[0215] Step S9.5, generate the emitted optical pulse signal s2 under the 4-pulse amplitude modulation scheme: using a pulse with an amplitude of 2P t The transmitted bit 11 is represented by a light pulse with an amplitude of [missing information]. The transmitted bit 10 is represented by a light pulse with an amplitude of [missing information]. The transmitted bit 01 is represented by a light pulse, and the transmitted bit 0 is represented by a no-pulse signal. Based on this principle, the transmitted pulse signal s2 is generated.

[0216] Step S9.6, calculate the received electrical signal y2 under the 4-pulse amplitude modulation scheme: The received electrical signal y2 is calculated as follows:

[0217]

[0218] Step S9.7: Sample and decide on the received electrical signal y2: then based on the threshold... Sampling decision for y2: If the sampled value is closest to The decision is bit 00 if the sampled value is closest to... The decision is bit 0 or 1 if the sampled value is closest. The decision is bit 10, if the sampled value is closest. The decision is then bit 11, and the received bit sequence q2 is obtained.

[0219] Step S9.8: Calculate the bit error rate of the communication system under the 4-pulse amplitude modulation scheme: count the number of bits that are different between q2 and the transmitted bit sequence x2. The bit error rate is calculated as follows:

[0220]

[0221] Based on the impulse response of the visible light communication channel in the underground coal mine environment calculated in this invention, the bit error rate of the visible light communication system in the underground coal mine environment can be simulated more accurately, providing numerical guidance for the design and analysis of the visible light communication system in the underground coal mine environment.

[0222] The invention is further illustrated below with a more complete and specific example.

[0223] Example 7

[0224] The visible light communication channel modeling method for underground coal mine environments is the same as in Examples 1-6, and includes the following steps:

[0225] Step 1: Determine the link parameters of the visible light communication system in the underground coal mine environment: In this example, the order K of the non-line-of-sight link is set to 2.

[0226] Step 2, determine the simulation parameters of the underground mine environment: In this example, the length L = 5m, width W = 2m, height H = 3m of the mine space are set, and the wall reflectance ρ w =0.6, the size A of the reflecting surface element ref =0.04m 3 .

[0227] Step 3, determine the simulation parameters of the transmitter and receiver: In this example, the position coordinates of the transmitter are set to T(1,2.5,3), and the normal direction of the transmitter is n. T =(0,0,-1) T ,(·) T Represents the vector transpose, and the transmitter's half-power angle θ. 1 / 2 =60°; Set the receiver's position coordinates to R(0.5,1,1.7), and the receiver's normal direction n R =(0,0,1) T Receiver surface area A PD =1cm 3 The receiver's field of view Receiver optical filter gain The internal refractive index of the optical condenser is a = 1.5, and the photoelectric conversion efficiency of the receiver is γ = 0.53 A / W.

[0228] Step 4: Calculate the attenuation coefficient of the received optical power due to coal dust. In this example, the complex refractive index of the coal dust is set to m = 1.57 - 0.56i, radius r = 2 μm, and density ρ1 = 1.56 g / cm³. 3 Concentration ρ2 = 10 mg / m³ 3 The wavelength of the incident light is λ = 475 nm. The scattering efficiency factor Q of the coal mine dust is calculated using Mie scattering theory. sca =28.302, absorption efficiency factor Q abs = -26.0982. Based on the Lambert-Beer law, the attenuation coefficient of coal dust on the received optical power is calculated. Among them, the attenuation coefficient of coal dust on the received optical power in the line-of-sight link is calculated to be 0.9892.

[0229] Step 5: Calculate the attenuation coefficient of the received optical power due to obstacles: In this example, the number of obstacles is set to K. s =1, height h1=2.5, probability density function g(w)=1 for shading width, and joint probability density function for midpoint x and y coordinates. X max =W-0.2,X min =0.2,Y max =L-0.2,Y min =0.2. The attenuation coefficient of the obstacle on the received optical power was calculated, and the attenuation coefficient of coal mine dust on the received optical power in the line-of-sight link was calculated to be 0.9339;

[0230] Step 6, calculate the channel impulse response: In this example, based on the attenuation coefficient of coal dust on the received optical power calculated in step S4 and the attenuation coefficient of obstacles on the received optical power calculated in step S5, the channel impulse response h(t) is calculated using the Lambertian radiation model as follows: Figure 11 As shown, Figure 11 The diagram shows the channel impulse response calculation results provided by this invention. It can be seen that the DC gain of the line-of-sight link is around 10. -5 The gain is orders of magnitude higher than that of a first-order non-line-of-sight link, and three orders of magnitude higher than that of a second-order non-line-of-sight link. The DC gain of the line-of-sight link accounts for 84.75% of the total gain, the first-order non-line-of-sight link accounts for 12.55% of the total gain, and the second-order non-line-of-sight link accounts for 2.7% of the total gain.

[0231] Step 7: Calculate the characteristic parameters of the channel. In this example, based on the channel impulse response h(t) calculated in step S6, the delay of the first-order NLOS link is mainly distributed between 1.5ns and 7.5ns; the delay of the second-order NLOS link is mainly distributed between 6.5ns and 23ns, the path loss PL = 49.99dB, and the root mean square delay spread D... RMS = 0.1597ns.

[0232] The visible light communication channel model for the coal mine environment has been established. To study the performance of the communication system, it is still necessary to calculate the system's bit error rate.

[0233] The following is an example of an engineering application: using the visible light communication channel model for underground coal mines calculated by this invention, the bit error rate of the communication system in the underground coal mine environment is calculated and analyzed.

[0234] Example 8

[0235] The visible light communication channel modeling method for underground coal mine environments is the same as in Examples 1-7, and includes the following steps:

[0236] Simulation parameters are set as follows: the simulation parameters for the underground coal mine environment, transmitter, receiver, coal mine dust, and obstacles are the same as in Example 7. The simulation parameters for the noise of the photodetector are shown in Table 1.

[0237] Table 1 Simulation parameters of noise for photodetectors

[0238]

[0239] Simulation content: The bit error rate (BER) of a visible light communication system in a defined underground coal mine environment is calculated and analyzed. This includes calculating and analyzing the BER of the visible light communication system under on / off keying modulation and 4-pulse amplitude modulation schemes. Simulation results are available in [reference needed]. Figure 12 .

[0240] Simulation Result Analysis: See simulation results. Figure 12 , Figure 12 The bit error rate calculation result graph provided by this invention shows that the horizontal axis represents the average transmitted optical power, and the vertical axis represents the bit error rate. The bit error rate curve of the communication system under the on-off keying modulation scheme is shown in... Figure 12 The solid line represents the bit error rate curve of the communication system under the 4-pulse amplitude modulation scheme. Figure 12 The average emitted optical power P is represented by a dashed line. t The sampling interval is 0.3W. From Figure 12 The results show that when using the on-off keying modulation scheme, an average transmitted optical power of 2W is sufficient to reduce the bit error rate of the communication system to below 0.01%; however, when using the 4-pulse amplitude modulation scheme, an average transmitted optical power of 5.5W is required for the bit error rate to be reduced to below 0.01%. The simulation results and analysis provide guidance for the design and deployment of visible light communication systems in underground coal mine environments.

[0241] In summary, this invention provides a visible light communication channel modeling method for underground coal mine environments, solving the technical problem that existing methods for modeling visible light communication channels in underground coal mines fail to accurately quantify the impact of coal dust and obstacles on the attenuation of received optical power. The method includes: determining the link parameters of the visible light communication system in an underground coal mine environment; determining the simulation parameters of the underground mine environment; determining the simulation parameters of the transmitter and receiver; calculating the attenuation coefficient of received optical power due to coal dust; calculating the attenuation coefficient of received optical power due to obstacles; calculating the channel impulse response; calculating the characteristic parameters of the channel; determining the simulation parameters of the photodetector noise; and calculating the bit error rate of the visible light communication system in an underground coal mine environment. This invention quantifies the impact of coal dust on the channel based on Mie scattering theory and Lambert-Beer's law, quantifies the impact of obstacles on the channel based on geometric and probabilistic models of the link obstructed by obstacles, and integrates the attenuation coefficients of coal dust and obstacles on received optical power into the visible light communication channel model formula, resulting in a visible light communication channel model that better reflects the underground coal mine environment. This invention enriches the modeling methods for visible light communication systems, and can be applied to calculate and analyze the impulse response, path loss, root mean square delay spread, received signal power delay distribution, and bit error rate performance of visible light communication channels in underground coal mine environments. The channel modeling results and analysis can provide quantitative guidance for the design and deployment of visible light communication systems in underground coal mine environments.

Claims

1. A visible light communication channel modeling method for underground coal mine environments, characterized in that, The impact of coal dust and obstacles in the underground coal mine environment on the received optical power is quantified into attenuation coefficients, and these attenuation coefficients are integrated into the channel model, including the following steps: (1) Step S1: Determine the link parameters of the visible light communication system in the underground coal mine environment: The visible light communication link consists of a line-of-sight link and a K-order non-line-of-sight link. Determine the order K of the non-line-of-sight link. (2) Step S2, determine the simulation parameters of the underground mine environment: determine the length, width, height of the underground mine space, and the reflection coefficient ρ of the walls. w Size A of the wall reflective element ref ; (3) Step S3, determine the simulation parameters of the transmitter and receiver: determine the position coordinates T(x) of the transmitter. T ,y T ,z T ), the normal direction of the transmitter n T The transmitter's half-power angle θ 1 / 2 Determine the receiver's position coordinates R(x) R ,y R ,z R ), receiver normal direction n R Receiving surface area A PD Receiver field of view Receiver optical filter gain The internal refractive index α of the optical condenser and the photoelectric conversion efficiency γ of the receiver; (4) Step S4: Calculate the attenuation coefficient of coal dust on the received optical power: Based on the determined complex refractive index m, radius r, density ρ1, concentration ρ2, wavelength λ of emitted light, and distance d of light propagation of coal dust in the environment, calculate the scattering efficiency factor Q of coal dust using Mie scattering theory. sca and absorption efficiency factor Q abs By combining the Lambert-Beer law, a formula was developed to calculate the attenuation coefficient of received optical power caused by suspended coal dust in the coal mine environment. The attenuation coefficient G of the coal dust on the received optical power was then calculated. ext (α,d); (5) Step S5, calculate the attenuation coefficient of the received optical power due to the obstacle: based on the determined number K of obstacles in the environment. s Height h i Based on the probability density function g(w) of the light-blocking width and the joint probability density function f(x,y) of the x and y coordinates of the midpoint of the obstacle, a probability formula for the obstruction of a communication link by a single obstacle is constructed, and the attenuation coefficient G of the obstacle on the received optical power is calculated. sha (A,d); (6) Step S6, calculate the channel impulse response: based on the attenuation coefficient G of coal dust on the received optical power calculated in step S4. ext (α,d) and the attenuation coefficient G of the obstacle to the received optical power calculated in step S5. sha (A,B), the channel impulse response h(t) is calculated using the Lambert radiation model; (7) Step S7, calculate the characteristic parameters of the channel: Based on the channel impulse response h(t) calculated in step S6, calculate the delay distribution of the received signal power, path loss PL, and root mean square delay spread D in the channel characteristic parameters. RMS ; (8) Step S8: Determine the simulation parameters of the photodetector's noise: The simulation parameters of the noise are used to calculate the power of additive white Gaussian noise in the received signal and to determine the equivalent noise bandwidth B of the photodetector inside the receiver during communication. w Background current I bg Type I noise bandwidth factor I2, Type II noise bandwidth factor I3, open-loop voltage gain G, MOSFET noise factor Γ, MOSFET transconductance g m Fixed capacitance per unit area η, thermodynamic temperature T of the coal mine environment k ; (9) Step S9: Calculate the bit error rate of the visible light communication system in the underground coal mine environment: Based on the channel impulse response h(t) calculated in step S6 and the noise simulation parameters of the photodetector determined in step S8, calculate the bit error rate of the visible light communication system in the underground coal mine environment under the on-off keying modulation scheme and the 4-pulse amplitude modulation scheme.

2. The visible light communication channel modeling method for underground coal mine environments according to claim 1, characterized in that, Step S4 involves calculating the attenuation coefficient of the received optical power due to coal mine dust, which includes the following steps: Step S4.1: Calculate the scattering efficiency factor Q of coal mine dust. sca and absorption efficiency factor Q abs Calculate the scattering efficiency factor Q of coal mine dust based on Mie scattering theory. sca and absorption efficiency factor Q abs : in, Let χ be a real function, where χ is the diameter parameter of coal mine dust, and a n b is the first type of Mie scattering coefficient. n The Mie scattering coefficient is of the second type. Among them, a n and b n The calculations are as follows: Where m is the complex refractive index of coal mine dust, ψ n (χ) is the Riccati-Bessel function of the first kind, ξ n (χ) is the second type of Riccati-Bessel function; Where, ψ n (χ) and ξ n (χ) is calculated as follows: in, and These are the Bessel function of semi-integer order and the Hankel function of the second kind, respectively. Step S4.2, calculate the amount of coal dust N per unit volume: Based on the determined radius r of the coal dust, the density ρ1 of the coal dust, and the concentration ρ2 of the coal dust, calculate the amount of coal dust N per unit volume. This parameter is used in step S4.3 to calculate the extinction coefficient α of coal mine dust; Step S4.3, calculate the extinction coefficient α of coal mine dust: based on the scattering efficiency factor Q of coal mine dust. sca and absorption efficiency factor Q abs Calculate the extinction coefficient α of coal mine dust: α=Q sca pr 2 N+Q abs pr 2 N The extinction coefficient α is used in step S4.4 to calculate the attenuation coefficient of the received optical power by coal mine dust. Step S4.4: Calculate the attenuation coefficient of the received optical power caused by coal mine dust: Based on the extinction coefficient α of coal mine dust and the Lambert-Beer law, formulate a formula for calculating the attenuation coefficient G of the received optical power caused by coal mine dust, and then calculate the attenuation coefficient G of the received optical power caused by coal mine dust. ext (α,d) is as follows: G ext (α,d)=exp(-ad) Where exp(·) is an exponential function with the natural constant as the base, and d is the distance the light travels.

3. The visible light communication channel modeling method for underground coal mine environments according to claim 1, characterized in that, Step S5 involves calculating the attenuation coefficient of the obstacle to the received optical power, which includes the following steps: Step S5.1: Construct the probability formula for the link being blocked by a single obstacle: Based on the probability density function g(w) of the determined obstacle's shading width and the joint probability density function f(x,y) of the obstacle's midpoint's x and y coordinates, and the geometric model of the obstacle blocking the link, construct the probability P of the visible light communication link being blocked by a single obstacle in the underground coal mine environment. i The calculation formula for P i as follows: Where W1 and W2 are the maximum and minimum values ​​of the obstacle's light-blocking width, respectively, when z′ T >z′ R When Δ is: When z′ T <z′ R When Δ is: When z′ T =z′ R When Δ is: Where, x′ T ,y′ T ,z′ T These are the X, Y, Z coordinates, and x′ of the transmitter, respectively. R ,y R ′,z′ R Here, X, Y, and Z are the X, Y, and Z coordinates of the receiver, respectively; ψ represents the angle between line segment CD and the X-axis; point C is the projection of the transmitter onto the XOY plane; point D is the projection of the receiver onto the XOY plane; w is the width of the light-blocking obstacle; h... i d is the height of the obstacle, and d0 is the horizontal distance between the transmitter and receiver; Step S5.2, calculate the attenuation coefficient G of the obstacle on the received optical power. sha (A,B): Based on the probability of the link being blocked by a single obstacle calculated in step S5.1, the attenuation coefficient of the obstacle on the received optical power is calculated as follows: in, K is the multiplication symbol. s Let A represent the number of obstacles, and let A represent the coordinates (x′) of the transmitter in the point-to-point communication link. T ,y′ T ,z′ T B represents the coordinates (x′) of the receiver in a point-to-point communication link. R ,y R ′,z′ R ).

4. The visible light communication channel modeling method for underground coal mine environments according to claim 1, characterized in that, Step S6, calculating the channel impulse response, includes the following steps: Step S6.1, calculate the impulse response h of the line-of-sight link. LOS (t): Combining the Lambertian radiation model, the attenuation coefficients of coal dust and obstacles on the received optical power are integrated into the channel model. The impulse response of the line-of-sight link is calculated as follows: Where θ is the emission angle of the emitted light, and d′ is the length of the line-of-sight link. Let c be the angle of incidence of the received light, c be the speed of light, and m be the Lambertian radiation factor. Let δ(·) be the optical condenser gain of the receiver, Γ(·) be the Dirichlet function, and m be the rectangular function. and The calculations are as follows: Where ln(·) is the logarithmic function; Step S6.2, calculate the impulse response h of the non-line-of-sight link. NLOS (t): The K-order non-line-of-sight link is the link through which the transmitter's light source is received by the receiver after K reflections. Combining the Lambertian radiation model, the attenuation coefficients of coal dust and obstacles on the received optical power are integrated into the channel model. The impulse response of the non-line-of-sight link is calculated as follows: Where, θ i Let be the exit angle of the emitted light in the (i-1)th reflection link. Let d be the incident angle of the incident light in the (j-1)th reflection link. l T is the length of the (l-1)th reflection link. e Let R be the position coordinates of the emitted light in the (e-1)th reflection link. e Let be the position coordinates of the incident light in the (e-1)th reflection link; Step S6.3, calculate the channel impulse response h(t): The channel impulse response is the sum of the impulse responses of the line-of-sight link and the non-line-of-sight link. The channel impulse response is calculated as follows: h(t)=h LOS (t)+h NLOS (t) Among them, h LOS (t) represents the impulse response of the line-of-sight link calculated in step S6.1, h NLOS (t) represents the impulse response of the non-line-of-sight link calculated in step S6.2.

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