Mine wireless channel large-scale fading prediction method

Abstract

The invention discloses a method for predicting large-scale fading of a mine wireless channel, which comprises the following steps of: dividing the large-scale fading of the mine wireless channel into two types by taking a frequency as a breakpoint, 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, constructing a mine wireless channel large-scale fading model, and predicting the mine wireless channel large-scale fading. The mine wireless channel large-scale fading prediction method provided by the invention has higher precision and is used for guiding mine wireless network planning and optimization.

Description

Technical Field

[0001] The invention relates to the field of wireless channel modeling, and in particular to a large-scale fading prediction method for wireless channels in mines. Background Art

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

[0003] At present, the design and planning of mine mobile communication, personnel and vehicle positioning, wireless video and wireless sensor systems, and the optimal layout of base stations and antennas mainly rely on field tests. The large-scale fading test data of wireless channels in different mines cannot be universal, and there are problems such as complex measurement, low efficiency and difficulty in optimization. Therefore, a large-scale fading prediction method for wireless channels is needed to predict the large-scale fading of mine wireless channels. The existing large-scale fading prediction methods for wireless channels are mainly divided into the following three methods: full-wave analysis method, ray tracing method, and statistical analysis method. Among them, the basic principle of the full-wave analysis method is to approximate the Maxwell equations through numerical algorithms. When solving, accurate electromagnetic parameters of the surrounding rock medium of the mine are required. However, the electromagnetic parameters of the surrounding rock medium of different mines are different, and their electromagnetic parameters are not easy to obtain. In addition, when calculating the large-scale fading of high-frequency wireless channels, the amount of calculation is large. The ray tracing method approximates high-frequency radio waves as rays for analysis. When solving, accurate electromagnetic parameters of the surrounding rock medium of the mine are also required. However, the electromagnetic parameters of the surrounding rock medium of different mines are different, and their electromagnetic parameters are not easy to obtain. It is not suitable for calculating the large-scale fading of low-frequency wireless channels. The statistical analysis method is based on field measured data and is summarized by numerical analysis method. It has the advantage of simple calculation. However, the existing large-scale fading prediction model of wireless channel based on statistical analysis method is only applicable to open space on the ground, not to limited space underground. Therefore, it is necessary to invent a large-scale fading prediction method for mine wireless channel to guide the planning and optimization of mine wireless network. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes a method for predicting large-scale fading of mine wireless channels. The method is suitable for predicting large-scale fading of wireless channels at different frequencies and distances in turning tunnels and branch tunnels with different corner angles, branch angles and sections.

[0005] The technical solution of the present invention:

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

[0007] Step 1: Measure the received power at different frequencies and distances in the turning lanes and branch lanes with different corner angles, branch angles, and cross sections. The measurement of the branch lane is divided into two cases: the transmitting antenna is in the main lane of the branch lane and the transmitting antenna is in the branch lane of the branch lane. Obtain the received power measurement values ​​at different frequencies and distances in the turning lanes and branch lanes with different corner angles, branch angles, and cross sections.

[0008] Step 2: Based on the received power measurement value obtained in step 1, calculate the large-scale fading at different frequencies and distances in the tunnels of different sections;

[0009] Step 3: Based on the large-scale fading data obtained in step 2, the large-scale fading data is taken as the breakpoint at frequency Y MHz, and the relationship between the large-scale fading of the turning lane and the branch lane and the corner angle, branch angle, cross section, frequency and distance in different frequency bands is proposed;

[0010] Step 4: Construct a large-scale fading prediction model for mine wireless channels to predict large-scale fading in mines.

[0011] In step 1, when measuring the received power at different frequencies and distances in the turning lanes and branch lanes with different corner angles, branch angles, and cross-sections, it includes selecting multiple turning lanes and branch lanes with different corner angles, branch angles, and cross-sections, and measuring the received power at different frequencies and distances in the center of the cross-section of the selected turning lanes and branch lanes.

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

[0013]

[0014] Where L represents the large-scale fading of the wireless channel; c represents the speed of light; S represents the cross-sectional area; f represents the frequency; d represents the distance; X σ represents a Gaussian random variable with mean zero and standard deviation σ; θ is the corner angle and 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, and t are correlation coefficients.

[0015] The frequency Y MHz includes but is not limited to 900 MHz; the frequency is taken as an example of a breakpoint of 900 MHz. According to the large-scale fading data of wireless channels at different frequencies and distances in the turning lanes with different corner angles and cross-sections obtained in step 3, the large-scale fading prediction model of the wireless channel in the turning lane is obtained by fitting using formula (8):

[0016]

[0017] The frequency Y MHz includes but is not limited to 900 MHz; the frequency is taken as an example of a breakpoint of 900 MHz. According to the large-scale fading data of the wireless channel at different frequencies and distances in the branch lanes of different branch angles and cross sections obtained in step 3 when the transmitting antenna is in the main lane of the branch lane, the large-scale fading prediction model of the wireless channel in the branch lane is obtained by fitting using formula (8) when the transmitting antenna is in the main lane of the branch lane:

[0018]

[0019]

[0020] The large-scale fading of the wireless channel in the mine turning tunnel and branch tunnel can be expressed as the sum of the large-scale fading of the wireless channel in the straight tunnel of the same section and the additional loss caused by the turning and branching of the turning tunnel and branch tunnel; the additional loss caused by the turning and branching of the turning tunnel and branch tunnel It can be expressed as:

[0021]

[0022] Among them, p, q, k, m, and n are correlation coefficients.

[0023] The frequency Y MHz includes but is not limited to 900 MHz; the frequency is taken as an example of a breakpoint of 900 MHz. Based on formula (10), according to the large-scale fading data of the wireless channel at different frequencies and distances in the turning lanes of the branch lanes with different branch angles and sections when the transmitting antenna is in the branch lanes of the branch lanes obtained in step 3, the large-scale fading prediction model of the wireless channel in the branch lanes is obtained as follows:

[0024] BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a flow chart of the large-scale fading prediction method for mine wireless channels.

[0026] Figure 2 Measure the top view of the curved tunnel.

[0027] Figure 3Measure the top view for the branch roadway.

[0028] Figure 4 The figure shows the comparison between the predicted value and the measured value of the large-scale fading of the wireless channel in the curved lane based on formula (9).

[0029] Figure 5 This is a comparison chart between the predicted value and the measured value of the large-scale fading of the wireless channel in the branch lane when the transmitting antenna is in the main lane of the branch lane based on formula (10).

[0030] Figure 6 This is a comparison chart between the predicted value and the measured value of the large-scale fading of the wireless channel in the branch lane when the transmitting antenna is in the branch lane of the branch lane based on formula (14). DETAILED DESCRIPTION

[0031] In order to better understand the technical content of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and specific implementation methods.

[0032] Step 1: Select a cross-sectional area of ​​19.3m in the mine. 2 , a curved lane with a length of 40m and a turning angle of 66°, such as Figure 2 As shown in the figure, a large-scale fading measurement system for mine wireless channels is built, and the transmitting antenna and the receiving antenna are placed in the center of the cross-section of the curved tunnel. When other conditions remain unchanged, only the transmitting signal frequency or the axial distance between the transmitting and receiving antennas is changed, and multiple measurements are performed at each measuring point and the average is taken to obtain the received power measurement values ​​at different frequencies and distances in the tunnel.

[0033] Step 2: Select a cross-sectional area of ​​19.3m in the mine. 2 , a branch tunnel with a length of 40m and a branch angle of 90°, such as Figure 3 As shown in the figure, a large-scale fading measurement system for mine wireless channels is built, and the transmitting antenna and the receiving antenna are placed in the center of the branch tunnel section. When other conditions remain unchanged, only the transmitting signal frequency or the axial distance between the transmitting and receiving antennas is changed, and multiple measurements are performed at each measuring point and the average is taken to obtain the received power measurement values ​​at different frequencies and distances in the tunnel.

[0034] Step 3: Based on the received power measurement values ​​obtained in step 1 and step 2, the large-scale fading of the wireless channel at different frequencies and distances in the turning lanes and branch lanes is calculated respectively.

[0035] Step 4: Based on the large-scale fading data of the mine wireless channel obtained in step 3, the large-scale fading data of the mine wireless channel is divided into a group with a frequency of 900MHz as the breakpoint, that is, the large-scale fading data of the mine wireless channel in the frequency band less than 900MHz is grouped as one group, and the large-scale fading data of the mine wireless channel in the frequency band greater than 900MHz is grouped as one group, and the relationship between the large-scale fading of the wireless channel of the turning tunnel and the branch tunnel and the corner angle, branch angle, cross section, frequency and distance under different frequency bands is respectively proposed;

[0036] Step 5: Construct a large-scale fading prediction model for mine wireless channels to predict large-scale fading of mine wireless channels.

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

[0038] In step 3, the following formula is used to calculate the large-scale fading of the wireless channel at different frequencies and distances in the turning lanes and branch lanes:

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

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

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

[0042]

[0043] Where c is the speed of light; S is the cross-sectional area; f is the frequency; d is the distance; X σrepresents a Gaussian random variable with mean zero and standard deviation σ; θ is the corner angle and branch angle, that is, 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] Based on the large-scale fading data of wireless channels at different frequencies and distances in the turning lanes with different corner angles and cross-sections obtained in step 4, the large-scale fading prediction model of the wireless channel in the turning lane is obtained by fitting using formula (16):

[0045]

[0046] According to the large-scale fading data of wireless channels at different frequencies and distances in branch lanes with different branch angles and cross-sections obtained in step 4 when the transmitting antenna is in the main lane of the branch lane, the large-scale fading prediction model of the wireless channel in the branch lane is obtained when the transmitting antenna is in the main lane of the branch lane:

[0047]

[0048] The large-scale fading of the wireless channel in the mine turning tunnel and branch tunnel can be expressed as the sum of the large-scale fading of the wireless channel in the straight tunnel of the same section and the additional loss caused by the turning and branching of the turning tunnel and branch tunnel. It can be expressed as:

[0049]

[0050] Among them, p, q, k, m, and n are correlation coefficients.

[0051] Based on formula (18), according to the large-scale fading data of wireless channels at different frequencies and distances in branch lanes of different branch angles and cross sections when the transmitting antenna is in the branch lane of the branch lane obtained in step 4, the large-scale fading prediction model of the wireless channel in the branch lane is obtained as follows:

[0052]

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

[0054]

[0055] Among them, L r is the predicted value of large-scale fading of wireless channel, L tis the measured value of large-scale attenuation of the wireless channel, and N is the number of sampling points.

[0056] Verification is performed based on the measured large-scale fading data of wireless channels, such as Figures 4 to 6 As shown in the figure, the model predictions are in good agreement with the measured values.

Claims

1. A method for predicting large-scale fading of mine wireless channels, characterized by: The effects of corner angle, branch angle, cross section, frequency and distance on large-scale fading of wireless channels in turning lanes and branch lanes are studied, and a large-scale fading prediction model for mine wireless channels is constructed to predict large-scale fading of wireless channels in turning lanes and branch lanes. The steps are as follows: Step 1: Measure the received power at different frequencies and distances in the turning lanes and branch lanes with different corner angles, branch angles, and cross sections. The measurement of the branch lane is divided into two cases: the transmitting antenna is in the main lane of the branch lane and the transmitting antenna is in the branch lane of the branch lane. Obtain the received power measurement values ​​at different frequencies and distances in the turning lanes and branch lanes 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 the lanes of different sections; 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 taken as the breakpoint at frequency Y MHz, and the relationship between the large-scale fading of the wireless channel of the turning lane and the branch lane and the corner angle, branch angle, cross section, frequency and distance in different frequency bands is proposed respectively; Step 4: Construct a large-scale fading prediction model for mine wireless channels to predict large-scale fading in mines.

2. The method for predicting large-scale fading of mine wireless channels according to claim 1, characterized in that: In step 1, when measuring the received power at different frequencies and distances in the turning lanes and branch lanes with different corner angles, branch angles, and cross-sections, it includes selecting multiple turning lanes and branch lanes with different corner angles, branch angles, and cross-sections, and measuring the received power at different frequencies and distances in the center of the cross-section of the selected turning lanes and branch lanes.

3. The method for predicting large-scale fading of mine wireless channels according to claim 1, characterized in that: The large-scale fading prediction model of mine wireless channel is: Where L represents the large-scale fading of the wireless channel; c represents the speed of light; S represents the cross-sectional area; f represents the frequency; d represents the distance; X σ represents a Gaussian random variable with mean zero and standard deviation σ; θ is the corner angle and 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, and t are correlation coefficients.

4. The method for predicting large-scale fading of mine wireless channels according to claim 3, characterized in that: The frequency Y MHz includes but is not limited to 900 MHz; the frequency is taken as an example with 900 MHz as a breakpoint, and the large-scale fading prediction model of the wireless channel in the curved lane is: 。 5. The method for predicting large-scale fading of mine wireless channels according to claim 3 is characterized in that: The frequency YMHz includes but is not limited to 900MHz; the frequency is taken as an example with 900MHz as a breakpoint. When the transmitting antenna is in the main lane of the branch lane, the large-scale fading prediction model of the branch lane wireless channel is: 。 6. The method for predicting large-scale fading of mine wireless channels according to claim 1, characterized in that: The large-scale fading of the wireless channel in the mine turning tunnel and branch tunnel can be expressed as the sum of the large-scale fading of the wireless channel in the straight tunnel of the same section and the additional loss caused by the turning and branching of the turning tunnel and branch tunnel; the additional loss caused by the turning and branching of the turning tunnel and branch tunnel It can be expressed as: Among them, p, q, k, m, and n are correlation coefficients.

7. The method for predicting large-scale fading of mine wireless channels according to claim 5, characterized in that: The frequency Y MHz includes but is not limited to 900 MHz; the frequency is taken as an example with 900 MHz as a breakpoint. When the transmitting antenna is in a branch lane of a branch lane, the large-scale fading prediction model of the branch lane wireless channel is: 。

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