Underground 5g communication beam alignment method based on millimeter wave array beam pattern

Abstract

The application discloses a millimeter wave array beam pattern based underground 5G communication beam alignment method, and belongs to the field of physical layer signal processing of wireless communication.The application aims to solve the problem that the real-time performance and safety of underground industrial communication cannot be ensured by using existing beam alignment methods.The application equates a constant modulus super large antenna array to a discrete time complex exponential signal, controls the spectral gain by adjusting the time variation rate of the signal frequency, and then generates an accurate triangular beam pattern for fast beam alignment based on the antenna array satisfying the constant modulus constraint.The transmitting end transmits triangular beam patterns in different directions in different training frames and accumulates the beam patterns at the receiving end in a staggered manner, and the receiving end can perform fast channel angle estimation and beam alignment by analyzing the gain difference caused by the geometric shape and channel angle of different frame beam patterns, so that the real-time performance and safety of underground industrial communication are ensured.The method can be applied to communication beam alignment.

Description

Technical Field

[0001] This invention belongs to the field of physical layer signal processing in wireless communication, and specifically relates to a method for beam alignment in underground 5G communication based on millimeter-wave array beam patterns. Background Technology

[0002] With the rapid development of wireless communication technology, 5G mobile communication technology has gradually matured and is empowering digital industrial production. Among these technologies, 5G wireless communication technology used in coal mining provides a technical guarantee for low-latency, high-reliability, and fully automated "digital smart mines." 5G wireless communication, utilizing millimeter-wave frequencies (30GHz-300GHz), significantly improves information transmission rates, ensuring the real-time nature of industrial information transmission in mines. By increasing the carrier frequency to reduce antenna size, it allows for the integration of ultra-large-scale antenna arrays (which can include hundreds or thousands of antennas), providing precise beam pointing suitable for the complex and winding channel environment of mine tunnels. However, if the communication beam is not correctly pointed at the communication terminal, it will cause a decline in communication performance. Therefore, beam alignment technology is a crucial guarantee for supporting 5G wireless communication in mines.

[0003] Existing beam alignment methods assume that the amplitude and phase of each antenna are independently adjustable, employ rectangular beam patterns for beam scanning, and use a binary tree method for angle search to make the beam alignment error converge exponentially with the beam training time. However, millimeter-wave VMI arrays typically use analog antenna array structures, where each antenna has the same amplitude, so only the phase is adjustable. Furthermore, the algorithm does not converge when the beam training time is short, meaning the alignment error is large during short training times, thus hindering rapid beam alignment. In conclusion, existing beam alignment methods cannot guarantee the real-time performance and security of industrial communications in mines. Summary of the Invention

[0004] The purpose of this invention is to solve the problem that existing beam alignment methods cannot guarantee the real-time performance and security of underground industrial communication, and to propose a beam alignment method for 5G communication in mines based on millimeter-wave array beam patterns.

[0005] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0006] A method for beam alignment in underground 5G communication based on millimeter-wave array beam patterns, the method specifically includes the following steps:

[0007] Step 1: The transmitter consists of N T An analog antenna array consisting of N antennas, the receiver of which includes N antennas. R A hybrid antenna array composed of roots and L RA radio frequency chain; and in both analog and hybrid antenna arrays, the spacing between adjacent elements is d;

[0008] The channel incident angle is θ∈[θ min ,θ max ), θ min It is the minimum angle of incidence of the channel, θ max It is the maximum angle of incidence of the channel, and the channel exit angle is φ∈[φ min ,φ max ), φ min It is the minimum angle at which the channel exits, φ max This is the maximum angle of channel emission. Given that there are M training frames in the communication beam training phase, the transmitter uses G... T Different beam patterns, and G T =M, the receiving end uses G R Different beam patterns, and G R =L R ;

[0009] Step 2: Based on the beam pattern Solving for the analog weighted beamforming vector of the transmitting antenna array

[0010] Step 3: According to the beam pattern Solving for the analog weighted beamforming vector of the receiver antenna array

[0011] Step 4, according to Constructing the transmitter codebook dictionary according to Constructing the receiver codebook dictionary The transmitter uses a weighted beamforming vector in the m-th training frame. The receiver consistently uses a weighted beam aggregation matrix during the training process of M training frames. Then, based on the weighted beamforming matrix, the received signal y of the m-th frame at the receiver is obtained. (m) m = 1, 2, ..., M;

[0012] Step 5: Obtain the estimated value of the strongest radial incidence angle based on the received signals of each frame at the receiver.

[0013] Step 6: Obtain the estimated value of the strongest radial emission angle based on the received signals of each frame at the receiver.

[0014] Step 7: Utilize the estimated value and Complete beam alignment.

[0015] Furthermore, the spacing d = λ / 2, where λ is the carrier wavelength.

[0016] Furthermore, the beam pattern used by the transmitting end is as follows:

[0017]

[0018] in, The g-th type used in the transmitting end T A beam pattern Beam pattern The angle at the geometric center;

[0019] The beam pattern used at the receiver is:

[0020]

[0021] in, The g-th method used by the receiving end R A beam pattern Beam pattern The angle at the geometric center.

[0022] Furthermore, the specific process of step two is as follows:

[0023] Step 2: Let ω = (2πd / λ)sin(φ), according to φ∈[φ min ,φ max ) to obtain ω∈[ω min ,ω max ), ω min It is the lower bound of ω, ω max It is the upper bound of ω. Substitute ω into the beam pattern. Get function

[0024]

[0025] in, The superscript H represents the conjugate transpose;

[0026] Step 22: Solve for the function In the interval ω∈[ω min ,ω max The antiderivative on ) is used to obtain the continuous-time function:

[0027]

[0028] Where t is time;

[0029] constant term C and They are respectively:

[0030]

[0031]

[0032] Steps 2 and 3: Find the inverse function ω = f(t) of equation (4), and then... Find the antiderivative of f(t). The complex exponential time signal s(t) is then defined as:

[0033]

[0034] Where e is the base of the natural logarithm, j is the imaginary unit, and rect(·) denotes the rectangle function;

[0035] Step 24, according to t=n T Sampling the complex exponential time signal s(t) at T, T=1 yields the discrete time signal s[n]. T ],n T =0,...,N T -1, which gives the transmitter beamforming vector. for:

[0036]

[0037] in, express The nth T Each element.

[0038] Furthermore, the specific process of step three is as follows:

[0039] Step 3: Let ω = (2πd / λ)sin(θ), according to θ∈[θ min ,θ max ) to obtain ω∈[ω min ,ω max Substitute ω into the beam pattern. Get function

[0040]

[0041] in, The superscript H represents the conjugate transpose;

[0042] Step 3.2: Solve for the function In the interval ω∈[ω min ,ω max The antiderivative on ) is used to obtain the continuous-time function:

[0043]

[0044] Where t is time;

[0045] constant term C and They are respectively:

[0046]

[0047]

[0048] Step 3: Find the inverse function ω = f(t) of equation (10), and then... Find the antiderivative of f(t). The complex exponential time signal s(t) is then defined as:

[0049]

[0050] Where e is the base of the natural logarithm, j is the imaginary unit, and rect(·) denotes the rectangle function;

[0051] Steps three and four: According to t=n R Sampling is performed on s(t) at T, T=1 to obtain the discrete-time signal s[n]. R ],n R =0,...,N R -1, which gives the receiver beamforming vector. for:

[0052]

[0053] in, express The nth R Each element.

[0054] Furthermore, the receiving end receives signal y in the m-th frame. (m) for:

[0055]

[0056] Where L represents the number of channel path clusters, α l Let be the complex gain of the l-th path cluster. Represents a complex number. This is the channel steering vector at the receiver. Let θ be the channel steering vector at the transmitter. l Let φ be the incident angle of the l-th path cluster. l Let be the emission angle of the l-th path cluster. For the m-th frame, receive signal y (m) Gaussian white noise in;

[0057]

[0058]

[0059] Furthermore, the step of estimating the angle of incidence based on the received signals of each frame at the receiving end... The specific process is as follows:

[0060] Step 51, y (m) Simplify and rewrite it in the following form:

[0061]

[0062] in, g θ (θ l ) = (W RF W BS ) H a R (θ l );

[0063] Step 52, from y (m) Select the frame m containing the most received signal energy from m = 1, 2, ..., M. * :

[0064]

[0065] Where ||·||2 is the 2-norm;

[0066] Step 53: [The m-th...] * Frame received signal Simplified to:

[0067]

[0068] in, This indicates interference from other multipath signals on the strongest path received signal. For the mth * Gaussian white noise in the frame received signal The complex gain of the strongest path, The launch angle is the maximum radius. The angle of incidence is the longest radius.

[0069] Step 54, according to and Estimate the angle of incidence

[0070] Furthermore, the specific process of step five-four is as follows:

[0071] Step 541: Ignore interference and have right The l R Modulo the elements yields:

[0072]

[0073] in, Yes The l R The result of taking the modulo of each element;

[0074]

[0075] in, This represents the count of the element corresponding to the largest modulo result;

[0076] Then the angle of incidence is obtained. For the first The angle at the geometric center of the beam pattern;

[0077] Step 542, Definition Yes The The result of taking the modulo of each element Yes The The result of taking the modulo of each element is the incident angle. Reduced to:

[0078]

[0079] When Σ≥0, proceed to step 543; when Σ<0, proceed to step 544.

[0080] Step 543: According to formula (2), and Further expressed as:

[0081]

[0082]

[0083] definition Then there is

[0084]

[0085]

[0086]

[0087] in, For the first The angle at the geometric center of the beam pattern;

[0088] Calculate the estimated value of u for:

[0089]

[0090] in, This represents the "pseudo-inverse" of A;

[0091] Then the angle of incidence The estimated value is yes The first element in yes The second element in;

[0092] Step 544: According to formula (2), and Further expressed as:

[0093]

[0094]

[0095] in, For the first The angle at the geometric center of the beam pattern For the first The angle at the geometric center of the beam pattern;

[0096] definition Then there is

[0097]

[0098]

[0099]

[0100] The estimated value of u is calculated as follows:

[0101]

[0102] in, Indicates the "pseudo-inverse" of A′;

[0103] Then the angle of incidence The estimated value is yes The first element in yes The second element in.

[0104] Furthermore, the specific process of step six is ​​as follows:

[0105] Step 61, y (m) Simplify and rewrite it in the following form:

[0106]

[0107] in,

[0108] Step 62, from y (m) L, m = 1, 2, ..., M R Select the element containing the most received signal energy from the given elements, i.e.:

[0109]

[0110] Step 63: Utilize the received signals from the M training frames... Composed of elements

[0111]

[0112]

[0113] in, The complex gain of the strongest path, The angle of incidence of the strongest radius. This indicates that the M training frames from the transmitter each have an angle of... Beamforming gain in the direction, The launch angle is the maximum radius. This indicates interference from other multipath signals on the strongest path received signal. Gaussian white noise in the first frame of the received signal The first in One element, Gaussian white noise in the received signal of the Mth frame The first in One element,

[0114] Step Six Four, according to and Obtain the estimated value of the strongest radial incidence angle.

[0115] Furthermore, the specific process of step seven is as follows:

[0116] The mean absolute errors of the incident angle estimation and the exit angle estimation are respectively:

[0117]

[0118]

[0119] in, Represents the desire for expectation;

[0120] The transmitting and receiving ends use the following beam patterns respectively:

[0121]

[0122]

[0123] Substitute g(φ) into step two to obtain the transmitting end weighted beamforming vector Ff; substitute g(θ) into step three to obtain the receiving end weighted beamgathering vector Ww;

[0124] The transmitting and receiving antenna arrays use Ff and Ww for beamforming and beamgathering, respectively, to complete beam alignment.

[0125] The beneficial effects of this invention are:

[0126] This invention equates a constant-mode VML antenna array to a discrete-time complex exponential signal. The spectral gain is controlled by adjusting the time rate of change of the signal frequency. Then, based on the antenna array satisfying the constant-mode constraint, a precise triangular beam pattern for rapid beam alignment is generated. The transmitter transmits triangular beam patterns in different directions in different training frames, which are then accumulated at the receiver in a staggered manner. By analyzing the gain differences caused by the geometry and channel angle of the beam patterns in different frames, the receiver can perform rapid channel angle estimation and beam alignment. Compared with existing beam alignment methods, this invention can obtain more channel angle information through precise beam patterns and achieves faster convergence of channel angle estimation errors during beam training. Therefore, it can achieve rapid beam alignment, ensuring the real-time performance and security of underground industrial communication. Attached Figure Description

[0127] Figure 1 This is a flowchart of the transmitter and receiver of the present invention;

[0128] Figure 2 The beam pattern of the transmitting end;

[0129] In the figure: dashed lines represent theoretical values, and solid lines represent simulated values;

[0130] Figure 3a The mean absolute error of the incident angle under different signal-to-noise ratios;

[0131] Figure 3b The root mean square error of the incident angle under different signal-to-noise ratios;

[0132] Figure 3c The mean absolute error of the emission angle under different signal-to-noise ratios;

[0133] Figure 3d The root mean square error of the exit angle under different signal-to-noise ratios. Detailed Implementation

[0134] Specific implementation method one: Combining Figure 1 This embodiment describes a method for 5G communication beam alignment in mines based on millimeter-wave array beam patterns. The millimeter-wave array refers to an array with a carrier frequency of millimeter waves. The method specifically includes the following steps:

[0135] Step 1: The transmitter consists of N T An analog antenna array consisting of N antennas, the receiver of which includes N antennas. R A hybrid antenna array composed of roots and L R A radio frequency chain; and in both analog and hybrid antenna arrays, the spacing between adjacent elements is d;

[0136] The channel incident angle is θ∈[θ min ,θ max ), θ min It is the minimum angle of incidence of the channel, θ max It is the maximum angle of incidence of the channel, and the channel exit angle is φ∈[φ min ,φ max ), φ min It is the minimum angle at which the channel exits, φ max This is the maximum angle of channel emission. Given that there are M training frames in the communication beam training phase, the transmitter uses G... T Different beam patterns, and G T =M, the beam pattern of the transmitting end is as follows Figure 2 As shown, the beam pattern of the receiver is similar to that of the transmitter. The receiver uses G... R Different beam patterns, and G R =L R ;

[0137] Step 2: Based on the beam pattern Solving for the analog weighted beamforming vector of the transmitting antenna array

[0138] Step 3: According to the beam pattern Solving for the analog weighted beamforming vector of the receiver antenna array

[0139] Step 4, according to Constructing the transmitter codebook dictionary according to Constructing the receiver codebook dictionary The transmitter uses a weighted beamforming vector in the m-th training frame. The receiver consistently uses a weighted beam aggregation matrix during the training process of M training frames. Then, based on the weighted beamforming matrix, the received signal y of the m-th frame at the receiver is obtained. (m) m = 1, 2, ..., M;

[0140] Step 5: Obtain the estimated value of the strongest radial incidence angle based on the received signals of each frame at the receiver.

[0141] Step 6: Obtain the estimated value of the strongest radial emission angle based on the received signals of each frame at the receiver.

[0142] Step 7: Utilize the estimated value and Complete beam alignment.

[0143] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that the spacing d = λ / 2, where λ is the carrier wavelength.

[0144] The other steps and parameters are the same as in Specific Implementation Method 1.

[0145] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method Two in that the beam pattern used by the transmitting end is as follows:

[0146]

[0147] in, The g-th type used in the transmitting end T A beam pattern Beam pattern The angle at the geometric center;

[0148] The beam pattern used at the receiver is:

[0149]

[0150] in, The g-th method used by the receiving end R A beam pattern Beam pattern The angle at the geometric center.

[0151] The other steps and parameters are the same as in Specific Implementation Method Two.

[0152] Specific Implementation Method Four: This implementation method differs from Specific Implementation Method Three in that the specific process of step two is as follows:

[0153] Step 2: Let ω = (2πd / λ)sin(φ), according to φ∈[φ min ,φ max ) to obtain ω∈[ω min ,ω max ), ω min It is the lower bound of ω, ω max It is the upper bound of ω. Substitute ω into the beam pattern. Get function

[0154]

[0155] in, The superscript H represents the conjugate transpose;

[0156] Step 22: Solve for the function In the interval ω∈[ω min ,ω max The antiderivative on ) is used to obtain the continuous-time function:

[0157]

[0158] Where t is time;

[0159] It is easy to know that the continuous time function t = f -1 (ω) is an increasing function, defined as t∈[0,N] T If f, then f -1 (ω min ) = 0, f -1 (ω max ) = N T Thus, the constant term C and They are respectively:

[0160]

[0161]

[0162] Steps 2 and 3: Find the inverse function ω = f(t) of equation (4), and then... Find the antiderivative of f(t). The complex exponential time signal s(t) is then defined as:

[0163]

[0164] Where e is the base of the natural logarithm, j is the imaginary unit, and rect(·) denotes the rectangular function. It is easy to see that t∈[0,N] T );

[0165] Step 24, according to t=n TSampling the complex exponential time signal s(t) at T, T=1 yields the discrete time signal s[n]. T ],n T =0,...,N T -1, which gives the transmitter beamforming vector. for:

[0166]

[0167] in, express The nth T Each element.

[0168] The other steps and parameters are the same as in Specific Implementation Method 3.

[0169] Specific Implementation Method Five: This implementation method differs from Specific Implementation Method Three in that the specific process of step three is as follows:

[0170] Step 3: Let ω = (2πd / λ)sin(θ), according to θ∈[θ min ,θ max ) to obtain ω∈[ω min ,ω max Substitute ω into the beam pattern. Get function

[0171]

[0172] in, The superscript H represents the conjugate transpose;

[0173] Step 3.2: Solve for the function In the interval ω∈[ω min ,ω max The antiderivative on ) is used to obtain the continuous-time function:

[0174]

[0175] Where t is time;

[0176] It is easy to know that the continuous time function t = f -1 (ω) is an increasing function, defined as t∈[0,N] R If f, then f -1 (ω min ) = 0, f -1 (ω max ) = N R Thus, the constant term C and They are respectively:

[0177]

[0178]

[0179] Step 3: Find the inverse function ω = f(t) of equation (10), and then... Find the antiderivative of f(t). The complex exponential time signal s(t) is then defined as:

[0180]

[0181] Where e is the base of the natural logarithm, j is the imaginary unit, and rect(·) denotes the rectangular function. It is easy to see that t∈[0,N] R );

[0182] Steps three and four: According to t=n R Sampling is performed on s(t) at T, T=1 to obtain the discrete-time signal s[n]. R ],n R =0,...,N R -1, which gives the receiver beamforming vector. for:

[0183]

[0184] in, express The nth R Each element.

[0185] The other steps and parameters are the same as in Specific Implementation Method 3.

[0186] Specific Implementation Method Six: This implementation method differs from Specific Implementation Method Four or Five in that the receiving end receives the signal y in the m-th frame. (m) for:

[0187]

[0188] Where L represents the number of channel path clusters, α l Let be the complex gain of the l-th path cluster. Represents a complex number. This is the channel steering vector at the receiver. Let θ be the channel steering vector at the transmitter. l Let φ be the incident angle of the l-th path cluster. l Let be the emission angle of the l-th path cluster. For the m-th frame, receive signal y (m) Gaussian white noise in;

[0189]

[0190]

[0191] The other steps and parameters are the same as in specific implementation methods four or five.

[0192] Specific Implementation Method Seven: This implementation method differs from Specific Implementation Method Six in that the strongest path of the multipath channel is defined as l. * The step of estimating the angle of incidence based on the received signals of each frame at the receiving end. The specific process is as follows:

[0193] Step 51, y (m) Simplify and rewrite it in the following form:

[0194]

[0195] in, Right now

[0196] Step 52, from y (m) Select the frame m containing the most received signal energy from m = 1, 2, ..., M. * :

[0197]

[0198] Where ||·||2 is the 2-norm;

[0199] Step 53: [The m-th...] * Frame received signal Simplified to:

[0200]

[0201] in, This indicates interference from other multipath signals on the strongest path received signal. For the mth * Gaussian white noise in the frame received signal The complex gain of the strongest path, The launch angle is the maximum radius. The angle of incidence of the strongest radius.

[0202] Step 54, according to and Estimate the angle of incidence

[0203] The other steps and parameters are the same as in Specific Implementation Method Six.

[0204] Specific Implementation Method Eight: This implementation method differs from Specific Implementation Method Seven in that the specific process of step five-four is as follows:

[0205] Step 541: Ignore interference and have right The l R Modulo the elements yields:

[0206]

[0207] in, Yes The l R The result of taking the modulo of each element;

[0208]

[0209] in, This represents the count of the element corresponding to the largest modulo result;

[0210] but Located at the largest modulus Within the angular range, the angle of incidence is obtained. For the first The angle at the geometric center of the beam pattern;

[0211] Step 542: By comparing beam patterns and At angle The gain can be increased to further reduce the angle of incidence. The range of values ​​for is defined as follows. Yes The The result of taking the modulo of each element Yes The The result of taking the modulo of each element is the incident angle. Reduced to:

[0212]

[0213] When Σ≥0, proceed to step 543; when Σ<0, proceed to step 544.

[0214] Step 543: According to formula (2), and Further expressed as:

[0215]

[0216]

[0217] definition Then there is

[0218]

[0219]

[0220]

[0221] in, For the first The angle at the geometric center of the beam pattern;

[0222] The estimated value of u is calculated using the LS algorithm. for:

[0223]

[0224] in, This represents the "pseudo-inverse" of A, i.e. Then the angle of incidence The estimated value is yes The first element in yes The second element in;

[0225] Step 544: According to formula (2), and Further expressed as:

[0226]

[0227]

[0228] in, For the first The angle at the geometric center of the beam pattern For the first The angle at the geometric center of the beam pattern;

[0229] definition Then there is

[0230]

[0231]

[0232]

[0233] The estimated value of u is calculated using the LS algorithm:

[0234]

[0235] in, The "pseudo-inverse" of A′ is... Then the angle of incidence The estimated value is yes The first element in yes The second element in.

[0236] The other steps and parameters are the same as in Specific Implementation Method Seven.

[0237] Specific Implementation Method Nine: This implementation method differs from Specific Implementation Method Six in that the specific process of step six is ​​as follows:

[0238] Step 61, y (m) Simplify and rewrite it in the following form:

[0239]

[0240] in,

[0241] Step 62, from y (m) L, m = 1, 2, ..., M R Select the element containing the most received signal energy from the given elements, i.e.:

[0242]

[0243] Step 63: Utilize the received signals from the M training frames... Composed of elements

[0244]

[0245]

[0246] in, The complex gain of the strongest path, The angle of incidence of the strongest radius. This indicates that the M training frames from the transmitter each have an angle of... Beamforming gain in the direction, The launch angle is the maximum radius. This indicates interference from other multipath signals on the strongest path received signal. Gaussian white noise in the first frame of the received signal The first in One element, Gaussian white noise in the received signal of the Mth frame The first in One element, g φ (φ l )=[g1(φ l ),...,g M (φ l )] T ,

[0247] Step Six Four, according to and Obtain the estimated value of the strongest radial incidence angle. The estimation method is the same as in step five four.

[0248] The other steps and parameters are the same as in Specific Implementation Method Six.

[0249] The specific process of step six-four is as follows:

[0250] Step 641: Ignore interference and have right Taking the modulo of the m-th element yields:

[0251]

[0252]

[0253] Where, m max This represents the frame corresponding to the largest modulo result;

[0254] but Located at the largest modulus Within the angular range, the emission angle of the strongest radius is obtained. For the mth transmitter max The angle at the geometric center of the beam pattern;

[0255] Step 642: By comparing beam patterns and At angle The gain can be increased to further reduce the emission angle. The range of values ​​for is defined as follows. Yes The mth max The result of taking the modulo of -1 element Yes The mth max The result of taking the modulo of +1 element will be the emission angle. Reduced to:

[0256]

[0257] When Σ≥0, proceed to step 643; when Σ<0, proceed to step 644.

[0258] Step 643: According to formula (1), and Further expressed as:

[0259]

[0260]

[0261] definition Then there is

[0262]

[0263]

[0264]

[0265] in, For the mth transmitter max -1 Angle at the geometric center of the beam pattern;

[0266] The estimated value of u is obtained by calculating using the LS algorithm. for:

[0267]

[0268] in, If A is the "pseudo-inverse", then the angle of emission is... The estimated value is yes The first element in yes The second element in;

[0269] Step 644: According to formula (1), and Further expressed as:

[0270]

[0271]

[0272] in, For the mth transmitter max +1 Angle at the geometric center of the beam pattern;

[0273] definition Then there is

[0274]

[0275]

[0276]

[0277] The estimated value of u is obtained by calculating using the LS algorithm:

[0278]

[0279] Then the angle of departure The estimated value is yes The first element in yes The second element in.

[0280] Specific Implementation Method Ten: This implementation method differs from Specific Implementation Method Eight or Nine in that the specific process of step seven is as follows:

[0281] The mean absolute error (MAE) of the incident angle estimation and the mean absolute error (MAE) of the exit angle estimation are respectively:

[0282]

[0283]

[0284] in, Represents the desire for expectation;

[0285] The transmitting and receiving ends use the following beam patterns respectively:

[0286]

[0287]

[0288] Substitute g(φ) into step two to obtain the transmitting end weighted beamforming vector Ff; substitute g(θ) into step three to obtain the receiving end weighted beamgathering vector Ww;

[0289] The transmitting and receiving antenna arrays use Ff and Ww for beamforming and beamgathering, respectively, to complete beam alignment.

[0290] The other steps and parameters are the same as in specific implementation method eight or nine.

[0291] Simulation verification:

[0292] like Figure 2As shown, the feasibility of the beam pattern design method proposed in this invention is verified by simulation analysis of the beam pattern. Taking the transmitting beam pattern as an example (the receiving beam pattern is similar), let N... T =1024, G T =10, based on the method proposed in this invention according to a given beam pattern Solving for the corresponding like Figure 2 As shown, The simulated beam pattern values ​​(represented by solid lines) fit the theoretical values ​​(represented by dashed lines) well, verifying the feasibility of the beam pattern design method of the present invention.

[0293] like Figure 3a , Figure 3b , Figure 3c and Figure 3d As shown, the effectiveness of the proposed method is verified by simulating and analyzing the channel angle error of beam alignment. Let N... T =512, N R =1024, L R =4, the number of beam training frames M=4. Channel multipath quantity L ~ min{max{1,Poisson(μ)},L max}, where Poisson(μ) represents a Poisson distribution with mean μ, L max The maximum possible value for the number of path clusters is μ = 1.6 in the case of millimeter-wave carrier frequency. max =4. Channel gain in U l ~U[0,1], r τ =2.8, ζ=4. Channel angle φ l ,θ l ∈U[-π / 3,π / 3].

[0294] like Figure 3a and Figure 3c As shown, this invention uses the mean absolute error of the angle. To analyze the angle alignment error, the method proposed in this invention uses a triangular beam pattern with a beamwidth of 45° in the m=1, 2, 3, and 4th training frames. By comparing the gain differences of different beam patterns, the MAE can be reduced to infinitesimal (theoretically). Figure 3c As shown, in the case of a single-path channel, the MAE of the AoD (angle of departure) can be reduced to less than 1°. Because a triangular beam pattern can acquire more channel angle information than a traditional rectangular beam pattern, the method proposed in this invention significantly reduces beam training time and enables rapid beam alignment. Figure 3b and Figure 3dAs shown, this invention uses root mean square error. To analyze extreme outliers in angle alignment error, the proposed method exhibits significantly fewer extreme outliers in single-path channel conditions. It should be noted that, since the receiver can simultaneously employ L... R The RF chain is used for beam training. Therefore, AoA (incident angle) has a faster error convergence speed than AoD (outcrystal angle). After M=4 beam training frames, AoA has a significantly smaller angle alignment error than AoD.

[0295] Depend on Figure 3a , Figure 3b , Figure 3c and Figure 3d It is known that, under the condition that the signal-to-noise ratio at the receiving end of the communication system is not less than 10dB, the method proposed in this invention only requires M=4 beam training frames to reduce the beam alignment error of the single-path channel to within 2° and the beam alignment error of the multipath channel to within 5°. Considering that the actual channel will also have channel angle spread (the channel angle spread of millimeter wave is about 10°), the beam alignment accuracy of the beam alignment method proposed in this invention can meet the requirements of the 5G wireless communication system in the mine and achieve fast beam alignment.

[0296] The above examples of the present invention are merely illustrative of the computational model and process of the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is impossible to exhaustively list all possible implementations here. Any obvious variations or modifications derived from the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for beam alignment in underground 5G communication based on millimeter-wave array beam patterns, characterized in that, The method specifically includes the following steps: Step 1: The transmitter includes... An analog antenna array composed of three antennas, the receiver of which includes... Hybrid antenna array composed of roots and antennas and A single radio frequency chain; and in both analog and hybrid antenna arrays, the spacing between adjacent elements is... ; Channel incident angle is , Indicates the incident angle of the channel. It is the minimum angle of incidence of the channel. It is the maximum angle of incidence of the channel, and the channel exit angle is... , Indicates the channel emission angle. It is the minimum angle at which the channel exits. It is the maximum angle emitted from the channel, defining the total number of communication beams during the training phase. If there are 10 training frames, the transmitter will use... Different beam patterns, and The receiving end adopts Different beam patterns, and , Indicates the total number of beam patterns; Step 2: Based on the method used by the transmitter... Beam pattern Solving for the analog weighted beamforming vector of the transmitting antenna array ; Step 3: Based on the method used by the receiving end... Beam pattern Solving for the analog weighted beamforming vector of the receiver antenna array ; Step 4, according to Constructing the transmitter codebook dictionary ,according to Constructing the receiver codebook dictionary The transmitter is in the Each training frame uses a weighted beamforming vector The receiving end is A weighted beam aggregation matrix is ​​consistently used throughout the training process. Then, based on the weighted beamforming matrix, the receiver's first... Frame received signal , ; in, For constant terms, For the first transmitter Each beamforming vector For constant terms, Indicates the receiver's first Each beamforming vector This represents the first weighted beamforming vector at the transmitter. Indicates the first transmitter A weighted beamforming vector, This represents the first weighted beamforming vector at the receiver. Indicates the receiver's first A weighted beamforming vector; Step 5: Obtain the estimated value of the strongest radial incidence angle based on the received signals of each frame at the receiver. ; Step 6: Obtain the estimated value of the strongest radial emission angle based on the received signals of each frame at the receiver. ; Step 7: Utilize the estimated value and Complete beam alignment.

2. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 1, characterized in that, The spacing , The carrier wavelength.

3. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 2, characterized in that, The beam pattern used by the transmitter is: (1) in, The first type used in the transmitting end A beam pattern The first type used for the transmitting end Beam pattern The angle at the geometric center; The beam pattern used at the receiver is: (2) in, The receiving end uses the first A beam pattern The first method used by the receiving end Beam pattern The angle at the geometric center.

4. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 3, characterized in that, The specific process of step two is as follows: Step Two One, Order ,according to get , yes The lower bound, yes The upper realm will Substitute the first one used by the transmitter Beam pattern Get function : (3) in, The superscript H represents the conjugate transpose; Step 22: Solve for the function In the interval From the antiderivative on the time axis, we obtain the continuous-time function: (4) in, It is time. express In the interval The original function on; constant term and They are respectively: (5) (6) Steps 2 and 3: Find the inverse function of equation (4) Then through Seeking original function ,in, The inverse function of expression (4) express If the original function is given, then the complex exponential time signal is defined. for: (7) in, It is the base of the natural logarithm. It is the imaginary unit. Represents a rectangular function; Step Two Four, according to For complex exponential time signals Sampling is performed to obtain discrete-time signals. That is, to obtain the beamforming vector at the transmitting end. for: (8) in, express The first in One element, Indicates length is A complex vector.

5. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 3, characterized in that, The specific process of step three is as follows: Step 31, Order ,according to get , express The lower bound, express The upper realm will Substitute the first one used by the receiving end Beam pattern Get function : (9) in, The superscript H represents the conjugate transpose; Step 3.2: Solve for the function In the interval From the antiderivative on the time axis, we obtain the continuous-time function: (10) in, It is time. Representation function In the interval The original function on; constant term and They are respectively: (11) (12) Step 3: Find the inverse function of equation (10) Then through Seeking original function Then, a complex exponential time signal is defined. for: (13) in, It is the base of the natural logarithm. It is the imaginary unit. Represents a rectangle function. It is the inverse function of equation (10). express The original function; Steps three and four, according to right Sampling is performed to obtain discrete-time signals. That is, to obtain the beamforming vector at the receiving end. for: (14) in, express The first in One element, Indicates length is A complex vector.

6. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 4 or 5, characterized in that, The receiving end Frame received signal for: (15) in, Indicates the number of channel path clusters. For the first Complex gain of a path family , Represents a complex number. This is the channel steering vector at the receiver. Indicates length is complex vectors This is the steering vector of the channel at the transmitting end. Indicates length is Complex vectors, For the first The angle of incidence of a cluster of paths For the first The exit angle of a path cluster For the first Frame received signal Gaussian white noise in Indicates length is Complex vectors, This represents the weighted beam aggregation matrix. This represents the m-th analog weighted beamforming vector of the transmitting antenna array; (16) (17)。 7. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 6, characterized in that, The angle of incidence is estimated based on the received signals of each frame from the receiver. The specific process is as follows: Step 51, Simplify and rewrite it in the following form: (18) in, , ; Step 52, from , Select the frame containing the most received signal energy. : (19) in, It is a 2-norm. Indicates from , Select the frame containing the most received signal energy and denote it as . ; Step 53, the first Frame received signal Simplified to: (20) in, This indicates interference from other multipath signals on the strongest path received signal. , , The steering vector representing the channel at the transmitter. The conjugate transpose of . For the first Complex gain of a path family Indicates the first antenna array of the transmitting end A simulated weighted beamforming vector, For the first Gaussian white noise in the frame received signal , The complex gain of the strongest path, The launch angle is the maximum radius. express The corresponding transmitter steering vector, express The conjugate transpose of . , The angle of incidence of the strongest radius. express The corresponding receiver steering vector; Step 54, according to and Estimate the angle of incidence , This represents the codebook dictionary of the receiving end.

8. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 7, characterized in that, The specific process of step five-four is as follows: Step 541: Ignore interference and , For the first Gaussian white noise in the frame received signal has , ,right The Modulo the elements yields: (21) in, Yes The The result of taking the modulo of each element; (22) in, This represents the count of the element corresponding to the largest modulo result; Then the angle of incidence is obtained. , For the first The angle at the geometric center of the beam pattern; Step 542, Definition , Yes The The result of taking the modulo of each element Yes The The result of taking the modulo of each element is the incident angle. Reduced to: (23) when If so, proceed to step five, four, three. Then proceed to step 544; Step 543: According to formula (2), and Further expressed as: (24) (25) definition Then there is (26) (27) (28) in, For the first The angle at the geometric center of the beam pattern Yes The The result of taking the modulo of each element; calculate The estimated value for: (29) in, express The false reversal; Then the angle of incidence The estimated value is , yes The first element in yes The second element in; Step 544: According to formula (2), and Further expressed as: (30) (31) in, For the first The angle at the geometric center of the beam pattern For the first The angle at the geometric center of the beam pattern; definition Then there is (32) (33) (34) calculate The estimated value is: (35) in, express The false reversal; Then the angle of incidence The estimated value is , yes The first element in yes The second element in.

9. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 6, characterized in that, The specific process of step six is ​​as follows: Step 61, Simplify and rewrite it in the following form: (36) in, , Indicates the receiver's first A weighted beamforming vector; Step 62, from , of Select the element containing the most received signal energy from the given elements, i.e.: (37) in, Indicates from Select the element containing the most received signal energy from the given elements; Step 63, Utilize The received signal of the nth training frame Composed of elements : (38) (39) in, , This represents the first training frame's received signal. One element, Indicates the first The received signal of the nth training frame One element, Let M represent a complex vector of length M. , The complex gain of the strongest path, The angle of incidence of the strongest radius. Indicates the transmitting end Each training frame has its own angle. Beamforming gain in the direction, This indicates that the first training frame at the transmitter is at an angle. Beamforming gain in the direction, This indicates that the Mth training frame at the transmitter is at an angle Beamforming gain in the direction, Indicates the first antenna array of the receiving end A simulated weighted beamforming vector, , The launch angle is the maximum radius. This indicates interference from other multipath signals on the strongest path received signal. , , Gaussian white noise in the first frame of the received signal The first in One element, Gaussian white noise in the received signal of the Mth frame The first in One element, , ; Step Six Four, according to and Obtain the estimated value of the strongest radial incidence angle. , This represents the transmitter's codebook dictionary.

10. The method for beam alignment of 5G communication in mines based on millimeter-wave array beam patterns according to claim 8 or 9, characterized in that, The specific process of step seven is as follows: The mean absolute errors of the incident angle estimation and the exit angle estimation are respectively: (55) (56) in, Represents expectations, The launch angle is the maximum radius. This represents the estimated value of the radial angle of incidence. The angle of incidence of the strongest radius. This is an estimate of the angle of incidence of the strongest diameter; The transmitting and receiving ends use the following beam patterns respectively: (57) (58) in, This represents the mean absolute error of the incident angle estimation. This represents the mean absolute error of the estimated angle of departure. Represents a rectangular function; Will Substituting into step two, the weighted beamforming vector at the transmitter is obtained. ;Will Substituting into step three, the weighted beam convergence vector at the receiver is obtained. ; The transmitting and receiving antenna arrays respectively adopt and Beamforming and beam convergence are performed to complete beam alignment.

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