Method for predicting large-scale fading of mine wireless channel

Abstract

The application discloses a mine wireless channel large-scale fading prediction method, which comprises the following steps: taking frequency as a breakpoint, dividing the mine wireless channel large-scale fading into two categories, respectively proposing the relationship between the wireless channel large-scale fading of the turning roadway and the branch roadway under different frequency bands and the corner angle, the branch angle, the section, the frequency and the distance, and constructing a mine wireless channel large-scale fading model to predict the mine wireless channel large-scale fading. The mine wireless channel large-scale fading prediction method has higher precision and can be used for guiding mine wireless network planning and optimization.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wireless channel modeling, in particular to a wireless channel large-scale fading prediction method for a mine. BACKGROUND

[0002] The design, planning and optimization of 5G, 5.5G, WiFi6, WiFi7, UWB, ZigBee and other mine mobile communication, personnel and vehicle positioning, wireless video and wireless sensing systems require mine wireless channel modeling analysis, and a wireless channel large-scale fading prediction model is an effective method for predicting wireless channel large-scale fading.

[0003] Currently, the design and planning of base stations and their optimal arrangement of antennas for mine mobile communication, personnel and vehicle positioning, wireless video and wireless sensing systems mainly rely on field tests, and the wireless channel large-scale fading test data of different mines cannot be used universally, which has problems such as complex measurement, low efficiency and difficulty in optimization. Therefore, a wireless channel large-scale fading prediction method is needed to predict the mine wireless channel large-scale fading. The existing wireless channel large-scale fading prediction methods mainly include the following three methods: full-wave analysis method, ray tracing method and statistical analysis method. The basic principle of the full-wave analysis method is to approximately solve Maxwell's equation by numerical algorithm, and accurate mine surrounding rock medium electromagnetic parameters are needed for solving, but the electromagnetic parameters of different mines are different, which are not easy to obtain, and the calculation amount is large when calculating the high-frequency wireless channel large-scale fading. The ray tracing method is to analyze the high-frequency radio wave by approximating it as a ray, and accurate mine surrounding rock medium electromagnetic parameters are also needed for solving, but the electromagnetic parameters of different mines are different, which are not easy to obtain, and it is not suitable for calculating low-frequency wireless channel large-scale fading. The statistical analysis method is based on field test data and uses numerical analysis method for induction and summary, which has the advantage of simple calculation, but the existing wireless channel large-scale fading prediction model based on statistical analysis method is only suitable for open space on the ground, not for limited space in the mine. Therefore, it is necessary to invent a mine wireless channel large-scale fading prediction method to guide the mine wireless network planning and optimization. SUMMARY

[0004] The present application is directed to the deficiencies of the prior art, and proposes a mine wireless channel large-scale fading prediction method, which is suitable for predicting the wireless channel large-scale fading at different frequencies and distances in the mine with different corner angles, branch angle angles and cornered tunnels and branch tunnels.

[0005] The technical scheme of the present application is as follows:

[0006] 1.A mine wireless channel large-scale fading prediction method, characterized in that: the influence of mine corner angle, branch angle, section on the large-scale fading of the corner roadway and branch roadway is studied, a mine wireless channel large-scale fading prediction model is constructed, and the large-scale fading of the corner roadway and branch roadway is predicted, the steps being as follows:

[0007] Step 1: the received power under different frequencies and distances is measured in the corner roadway and branch roadway with different corner angles, branch angles and sections, wherein the measurement of the branch roadway is divided into two cases of the main roadway of the branch roadway and the branch roadway of the branch roadway, and the received power measurement values under different frequencies and distances in the corner roadway and branch roadway with different corner angles, branch angles and sections are obtained;

[0008] Step 2: the large-scale fading under different frequencies and distances in the roadway with different sections is calculated according to the received power measurement values obtained in step 1;

[0009] Step 3: the large-scale fading data obtained in step 2 is divided into different frequency bands with Y MHz as the breakpoint, and the relationship between the large-scale fading of the corner roadway and branch roadway and the corner angle, branch angle, section, frequency and distance under different frequency bands is proposed respectively;

[0010] Step 4: a mine wireless channel large-scale fading prediction model is constructed to predict the large-scale fading in the mine.

[0011] In step 1, when the received power under different frequencies and distances is measured in the corner roadway and branch roadway with different corner angles, branch angles and sections, a plurality of corner roadways and branch roadways with different corner angles, branch angles and sections are selected, and the received power under different frequencies and distances is measured at the section center of the selected corner roadway and branch roadway.

[0012] The mine wireless channel large-scale fading prediction model is as follows:

[0013]

[0014] Wherein, L represents the large-scale fading of the wireless channel; c represents the speed of light; S represents the section area; f represents the frequency; d represents the distance; X σ represents a Gaussian random variable with a mean of zero and a standard deviation of σ; θ is the corner angle or branch angle, 0 < θ < π; α1, α2, α3, α4, ω1, ω2, ω3, ω4, ω5, ω6, β1, β2, β3, β4, β5, β6, β7, β8, γ1, γ2, γ3, γ4, ε1, ε2, t are correlation coefficients.

[0015] The frequency YMHz, including but not limited to 900MHz; the frequency takes 900MHz as a breakpoint, the wireless channel large-scale fading data of different frequencies and distances in the broken corner roadway according to the different corner angles obtained in step 3 is fitted using formula (8), and the wireless channel large-scale fading prediction model of the broken corner roadway is obtained as follows:

[0016]

[0017] The frequency YMHz, including but not limited to 900MHz; the frequency takes 900MHz as a breakpoint, the wireless channel large-scale fading data of different frequencies and distances in the broken corner roadway according to the different corner angles obtained in step 3 is fitted using formula (8), and the wireless channel large-scale fading prediction model of the broken corner roadway is obtained as follows:

[0018]

[0019]

[0020] The wireless channel large-scale fading of the mine broken corner roadway and the branch roadway can be represented as the sum of the wireless channel large-scale fading of the straight roadway with the same section and the additional loss caused by the corner and branch of the broken corner roadway and the branch roadway; the additional loss caused by the corner and branch of the broken corner roadway and the branch roadway can be represented as:

[0021]

[0022] Wherein, p, q, k, m, n are correlation coefficients.

[0023] The frequency YMHz, including but not limited to 900MHz; the frequency takes 900MHz as a breakpoint, the wireless channel large-scale fading data of different frequencies and distances in the broken corner roadway according to the different corner angles obtained in step 3 is fitted using formula (8), and the wireless channel large-scale fading prediction model of the broken corner roadway is obtained as follows:

[0024] BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 It is a mine wireless channel large-scale fading prediction method flow chart.

[0026] Figure 2 It is a broken corner roadway measurement plan view.

[0027] Figure 3 ​A top view of the branch roadway.

[0028] Figure 4 The figure shows a comparison between the predicted and measured values ​​of large-scale fading of the wireless channel in a bend in the alley based on formula (9).

[0029] Figure 5 The figure shows a comparison between the predicted and measured values ​​of the large-scale fading of the wireless channel in the branch roadway when the transmitting antenna is predicted in the main roadway of the branch roadway based on formula (10).

[0030] Figure 6 The figure shows a comparison between the predicted and measured values ​​of the large-scale fading of the wireless channel in the branch roadway when the transmitting antenna is predicted in the branch roadway based on formula (14). Detailed Implementation

[0031] To better understand the technical content of this invention, the invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0032] Step 1: Select a cross-sectional area of ​​19.3m² within the mine. 2 A winding alleyway, 40m long and with a 66° bend, such as Figure 2 As shown, a large-scale fading measurement system for mine wireless channels was constructed. The transmitting and receiving antennas were placed in the center of the cross-section of the bend in the roadway. Under the condition that other conditions remain unchanged, only the frequency of the transmitting signal or the axial distance between the transmitting and receiving antennas was changed. Multiple measurements were taken at each measurement point and the average was taken to obtain the received power measurement values ​​at different frequencies and distances in the roadway.

[0033] Step 2: Select a cross-sectional area of ​​19.3m² within the mine. 2 A branch tunnel, 40m long and with a branch angle of 90°, such as Figure 3 As shown, a large-scale fading measurement system for mine wireless channels was constructed. The transmitting and receiving antennas were placed in the center of the cross-section of the branch roadway. Under the condition that other conditions remain unchanged, only the transmitting signal frequency or the axial distance between the transmitting and receiving antennas was changed. Multiple measurements were taken at each measurement point and the average was taken to obtain the received power measurement values ​​at different frequencies and distances in the roadway.

[0034] Step 3: Based on the received power measurements obtained in Step 1 and Step 2, calculate the large-scale fading of the wireless channel at different frequencies and distances in the bend and branch tunnels.

[0035] Step 4: According to the mine wireless channel large-scale fading data obtained in step 3, the mine wireless channel large-scale fading data is divided into two groups at the frequency of 900 MHz, i.e. the mine wireless channel large-scale fading data of the frequency band less than 900 MHz is one group, and the mine wireless channel large-scale fading data of the frequency band greater than 900 MHz is one group, and the relationship between the mine wireless channel large-scale fading of the turning roadway and the branch roadway and the corner angle, the branch angle, the cross section, the frequency and the distance under different frequency bands is proposed respectively;

[0036] Step 5: Constructing a mine wireless channel large-scale fading prediction model to predict the mine wireless channel large-scale fading.

[0037] The mine wireless channel large-scale fading measurement system in steps 1 and 2 is composed of two parts of a transmitting device and a transmitting antenna and a receiving device and a receiving antenna, the transmitting device includes a notebook computer, a portable signal generator and a radio frequency feeder; the receiving device includes a notebook computer, a portable spectrum analyzer and a radio frequency feeder.

[0038] In step 3, the wireless channel large-scale fading under different frequencies and distances in the turning roadway and the branch roadway is calculated by using the following formula:

[0039] L = P i + G i - τ i -P r + G r - τ r (15)

[0040] Wherein, L represents the wireless channel large-scale fading; P i represents the transmitting power of the portable signal transmitter; G i represents the transmitting antenna gain; τ i represents the feeder loss of the transmitting device; P r represents the receiving power measured by the portable spectrum analyzer; G r represents the receiving antenna gain; τ r represents the feeder loss of the receiving device.

[0041] The mine wireless channel large-scale fading prediction model is:

[0042]

[0043] Wherein, c represents the speed of light; S represents the cross section area; f represents the frequency; d represents the distance; X σrepresents a Gaussian random variable with zero mean and standard deviation σ; θ is the corner angle, branch angle, i.e. the angle between the transmitting antenna and the receiving antenna, 0 < θ < π; α1, α2, α3, α4, ω1, ω2, ω3, ω4, ω5, ω6, β1, β2, β3, β4, β5, β6, β7, β8, γ1, γ2, γ3, γ4, ε1, ε2, t are correlation coefficients;

[0044] According to the large-scale fading data of the wireless channel at different frequencies and distances in the curved roadway with different corner angles and cross sections obtained in step 4, the large-scale fading prediction model of the wireless channel in the curved roadway is obtained by using formula (16):

[0045]

[0046] According to the large-scale fading data of the wireless channel at different frequencies and distances in the branch roadway with different branch angles and cross sections when the transmitting antenna is in the main roadway of the branch roadway, the large-scale fading prediction model of the wireless channel in the branch roadway when the transmitting antenna is in the main roadway of the branch roadway is obtained by using formula (16):

[0047]

[0048] The large-scale fading of the wireless channel in the curved roadway and the branch roadway of the mine can be represented as the sum of the large-scale fading of the wireless channel in the straight roadway with the same cross section and the additional loss caused by the corner and branch of the curved roadway and the branch roadway. It can be represented as:

[0049]

[0050] Wherein, p, q, k, m, n are correlation coefficients.

[0051] Based on formula (18), according to the large-scale fading data of the wireless channel at different frequencies and distances in the branch roadway with different branch angles and cross sections when the transmitting antenna is in the branch roadway of the branch roadway, the large-scale fading prediction model of the wireless channel in the branch roadway when the transmitting antenna is in the branch roadway of the branch roadway is obtained:

[0052]

[0053] The standard deviation σ is calculated using the following formula:

[0054]

[0055] Wherein, L r is the large-scale fading prediction value of the wireless channel, L tN is the number of sampling points.

[0056] The measured large-scale fading data of the wireless channel was used for verification, and the model prediction values were in good agreement with the measured values, as shown in Figures 4-6 the figure.

Claims

1. A method for large-scale fading prediction of wireless channels in mines, characterized in that: The effects of corner angle, branch angle, cross-section, frequency, and distance on large-scale fading of wireless channels in bends and branch roads were studied. A large-scale fading prediction model for mine wireless channels was constructed to predict the large-scale fading of wireless channels in bends and branch roads. The steps are as follows: Step 1: Measure the received power at different frequencies and distances at the center of the cross-section of the bend and branch roadways with different corner angles, branch angles, and cross-sections. The measurement of the branch roadways is divided into two cases: the transmitting antenna is in the main roadway of the branch roadway and the transmitting antenna is in the branch roadway. Obtain the received power measurement values ​​at different frequencies and distances in the bend and branch roadways with different corner angles, branch angles, and cross-sections. Step 2: Based on the received power measurement value obtained in Step 1, calculate the large-scale fading of the wireless channel at different frequencies and distances in different cross-sections of the tunnel. Step 3: Based on the large-scale fading data of the wireless channel obtained in Step 2, the large-scale fading data of the wireless channel is divided into two parts with frequency Y MHz as the breakpoint. The relationship between the large-scale fading of the wireless channel in the bend and branch lanes and the corner angle, branch angle, cross section, frequency and distance is proposed in different frequency bands. Step 4: Construct a large-scale fading prediction model for the mine wireless channel to predict large-scale fading in the mine; Step 5: Construct a large-scale fading prediction model for the mine wireless channel as follows: Where L represents large-scale fading of the wireless channel; c represents the speed of light; S represents the cross-sectional area; f represents the frequency; and d represents the distance. This indicates that the mean is zero and the standard deviation is... Gaussian random variables; For corner angles or branch angles, 0 < < ; , , , , , , , , , , , , , , , , , , , , , , , t represents the correlation coefficient.

2. The method for large-scale fading prediction of mine wireless channels according to claim 1, characterized in that: The frequency YMHz includes, but is not limited to, 900 MHz; taking 900 MHz as an example, the large-scale fading prediction model for wireless channels in winding alleyways is as follows: 。 3. The method for large-scale fading prediction of mine wireless channels according to claim 1, characterized in that: The frequency YMHz includes, but is not limited to, 900 MHz; taking 900 MHz as an example, when the transmitting antenna is in the main roadway of a branch roadway, the large-scale fading prediction model for the wireless channel in the branch roadway is as follows: 。 4. The method for large-scale fading prediction of mine wireless channels according to claim 1, characterized in that: Large-scale fading of wireless channels in mine bends and branch roads can be expressed as the sum of the large-scale fading of wireless channels in straight roads of the same cross-section and the additional losses caused by the bends and branches in the bends and branches; the additional losses caused by the bends and branches in the bends and branches of the bends and branches. It can be represented as: Where p, q, k, m, and n are the correlation coefficients.

5. The method for large-scale fading prediction of mine wireless channels according to claim 3, characterized in that: The frequency YMHz includes, but is not limited to, 900 MHz; taking 900 MHz as an example, when the transmitting antenna is in a branch roadway, the large-scale fading prediction model for the wireless channel in the branch roadway is as follows: 。

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