CN113438682B - SAGE-BEM5G wireless channel parameter extraction method based on beam forming - Google Patents
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Abstract
The invention provides a beam forming-based SAGE-BEM5G wireless channel parameter extraction method, which comprises the following steps: determining a channel Noise threshold Noise gate (ii) a Calculating a Bartlett power spectrum by using a Bartlett beam forming method; determining a multipath packet and reconstructing a channel according to the selected noise threshold and the calculated Bartlett power spectrum; and inputting SAGE algorithm based on the obtained reconstructed channel for iteration to obtain a preliminary parameter estimation result, and recovering according to the reconstructed channel label to obtain a final parameter estimation result. The method can realize the rapid estimation of the channel parameters and effectively and accurately extract the multipath of the channel; the method has very important application value for wireless channel link level and system level performance simulation evaluation and network design based on the 5G technology.
Description
Technical Field
The invention belongs to the technical field of wireless channel modeling, and particularly relates to a SAGE-BEM5G wireless channel parameter extraction method based on beam forming.
Background
With the rapid development of Fifth Generation (5G) mobile communication, network connection capability and data processing capability have been greatly improved. As a transmission technology of a core of the 5G mobile communication system, a Multiple-Input Multiple-Output (MIMO) technology has unique advantages in improving transmission rate and spectrum utilization rate. The 5G wireless MIMO communication channel is also evolving towards sophistication and diversity. In order to ensure high-quality communication, efficient signal transmission, and the crucial role of channel parameters, it is very meaningful to study a channel parameter estimation method in 5G communication. In addition, millimeter wave technology has wide spectrum resources, and is rapidly becoming a 5G focus research field. The introduction of millimeter wave technology enables the big datamation of wireless channel modeling, and the traditional channel estimation algorithm cannot meet the expectations of research on speed and accuracy.
The existing channel characteristic estimation algorithm such as the twiddle factor invariant method (ESPRIT) is not suitable for the case of coherent source and low Signal-to-noise ratio, and the joint estimation of multidimensional characteristics is difficult to realize. An Expectation-Maximization (EM) algorithm realizes Maximization of an incomplete data log-likelihood function through iteration of log-likelihood function Expectation of complete data, so that seven-dimensional parameter joint estimation of a Multi-Path Component (MPC) is realized, but the EM algorithm has the problems of low convergence speed and high complexity. The Space-Alternating Generalized Expectation maximization (SAGE) algorithm overcomes the defects of the EM algorithm, the parameter Space is divided into a plurality of subsets, only part of parameters need to be updated in each iteration, and the rest of parameters are kept unchanged, so that the complexity is obviously reduced, and the convergence speed is obviously accelerated. With the improvement of the resolution of millimeter-wave band channel characteristic parameters in a time delay domain and an angle domain, and the extraction precision of the SAGE algorithm is influenced by the performance and calibration precision of a measurement system, an antenna directional diagram and the like, the SAGE algorithm needs to be adjusted and improved for a 5G frequency band measurement system.
Disclosure of Invention
Aiming at the problems, the invention provides an SAGE-BEM (SAGE-Bartlett expection mapping) method for improving the problems of low running efficiency and the like of SAGE during initialization by combining beam forming with SAGE, improving the channel small-scale parameter extraction precision and reducing the algorithm running time, and the method comprises the following steps:
step S101: determining a channel Noise threshold Noise gate ；
Step S102: calculating Bartlett power spectral density by using a Bartlett beam forming method;
step S103: determining a multipath packet and reconstructing a channel according to the selected noise threshold by using the calculated Bartlett power spectrum;
step S104: iterating the reconstructed channel by using an SAGE algorithm to obtain a preliminary channel parameter estimation result, and recovering according to a reconstructed channel label to obtain a final parameter estimation result;
in step S101, calculating channel power according to the channel impulse response, and solving the maximum power of the channel according to the channel power; in the 5G wireless channel, the channel part which is lower than the maximum power of the channel by a certain value sigma is a Noise part, so the maximum power of the channel minus the sigma is used for determining a Noise threshold Noise of the channel gate 。
In step S102, a signal model and a parameter set to be estimated are determined according to a channel measurement method and a plan; defining a complete correlation matrix according to the channel matrix; the Bartlett power spectrum is calculated in combination with the directional pattern and the directional vector.
In step S103, a multi-path packet is determined based on the Bartlett power spectrum calculated in step S102 and the noise threshold determined in step S101, wherein the multi-path packet includesIs determined by the delay power spectrum (P) τ ) Determining that the horizontal angle is represented by a horizontal angle power spectrum (P) φ ) Determining that the vertical angle is determined by the vertical angle power spectrum (P) θ ) And (5) determining. And reconstructing the channel according to the screened multipath packets, and storing the multipath packet delay parameters as the labels of the reconstructed channel.
In step S104, a target z function and a small-scale estimation function are given, and each small-scale parameter is updated until the result is converged to obtain a preliminary parameter estimation result; and recovering according to the reconstructed channel label to obtain a final parameter estimation result.
The invention has the beneficial effects that:
the SAGE-BEM method based on Bartlett beam forming is more consistent with a transmission mechanism that the middle diameter of a broadband system exists in a cluster, and the method improves an SAGE algorithm and improves operation efficiency and accuracy aiming at the problems that the traditional SAGE algorithm is low in efficiency and the like under the condition of large data volume. Based on the method of the invention, the accurate estimation of the channel parameters can be realized, and the multi-path validity of the channel is verified; the method has very important application value for wireless channel link level and system level performance simulation evaluation and network design based on the 5G technology.
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FIG. 1 is a block flow diagram of the method of the present invention;
fig. 2 is a Bartlett power spectrum calculated in the present invention;
FIGS. 3 (a) and 3 (b) are graphs of the effect of extracting parameters by the conventional SAGE algorithm and the effect of extracting parameters by the method of the present invention.
Detailed Description
The embodiments are described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a flow of a beam forming based SAGE-BEM5G wireless channel parameter extraction method of the present invention is shown, including:
step S101: determining a channel noise threshold:
first, the channel power P (τ) is calculated according to the channel impulse response H (t, τ), and the calculation formula is as follows:
P(τ)＝E[|H(t，τ)| 2 ] (1)
wherein tau is equal to 0, N H ]，N H Is the length of the channel impulse response.
Calculating the maximum value P of the channel power according to the channel power P (tau) max ：
Noise threshold Noise gate Calculated as follows:
Noise gate ＝P max -σ (3)
where σ is a channel power threshold, and in the case of line-of-sight, the general empirical value of σ is 15dB. In the non-line-of-sight case, a general empirical value for σ is 25dB.
Step S102: calculate Bartlett power spectrum:
firstly, a signal model and a parameter set to be estimated are determined according to a channel measurement method and a plan, an input signal is defined as u (t), and after an electric wave passes through a 5G wireless channel, the signal of the ith multipath can be represented as:
s(t；ρ l )＝[s 1 (t；ρ l )，...，s M (t；ρ l )] T ＝c(θ l ，φ l )α l exp(j2πν l t)u(t-τ l ) (4)
wherein ρ l ＝[τ l ，θ l ，φ l ，ν l ，α l ]The parameter set of the ith multipath is obtained, and symbols in the set sequentially represent time delay, vertical arrival angle, horizontal arrival angle, doppler shift and complex amplitude. c (theta, phi) is a steering vector, also referred to as an antenna array response matrix, associated with the structure of the antenna array and the pattern of each antenna element. For M receiving antennas, let its position be r 1 ，r 2 ，...r M Then, there are:
wherein, f M (theta, phi) represents an antenna complex pattern of the Mth antenna array element, lambda is the wavelength of the corresponding carrier frequency, e (theta, phi) is a unit direction vector of a spherical coordinate,<·>representing an inner product operation. The unit direction vector e (theta, phi) belongs to [0, phi ] by the unit spherical coordinate (theta, phi)]X [ -pi, pi) (r = 1) is uniquely determined, i.e.
e(θ,φ)＝[cos(φ)sin(θ),sin(φ)sin(θ),cos(θ)] T (6)
Wherein φ is a horizontal angle and θ is a vertical angle. The response matrix output by the receiving antenna array is:
wherein N is 0 Is a positive constant and N (t) represents M-dimensional white gaussian noise.
The Bartlett power spectrum is calculated as:
P(θ,φ,τ)＝c(θ,φ) H ×R H (τ)×c(θ,φ) (8)
where φ represents a horizontal angle, θ represents a vertical angle, τ represents a multipath delay, c represents a steering vector, (-) H Is a conjugate transpose, R H (τ) represents a spatial correlation matrix, given by:
R H (τ)＝vec(H(τ))×vec(H(τ)) H (9)
wherein vec (-) indicates that the matrix is reduced in dimension by columns.
Fig. 2 is a Bartlett power spectrum obtained by calculation, and the rough distribution situation of the multipath in the angle and delay dimensions can be visually observed through the Bartlett power spectrum.
Step S103: determining a multipath packet reconstruction channel:
firstly, according to the Bartlett power spectrum calculated in the step S102, a time delay power spectrum (P) is obtained τ ) Horizontal angle power spectrum (P) φ ) Perpendicular angle power spectrum (P) θ ) Combining the Noise threshold Noise calculated in step S101 gate Extracting multipath packets { tau, phi, theta }, sequentially representing time delay, horizontal angle and vertical angle, wherein the calculation formula is as follows:
wherein T = [0, N H ]Represents the time delay value range, phi = [ -pi, pi) represents the horizontal angle value range, theta = [0, pi =]Indicating the range of vertical angles.
And reconstructing the channel according to the screened multipath packets, and storing the multipath packet time delay parameters as labels of the reconstructed channel.
Step S104: estimating the reconstructed channel by SAGE algorithm:
the number of antenna elements at the transmitting end is set as N, the number of antenna elements at the receiving end is set as M, and the definition of a z function is given as follows:
where τ, θ 1 ，φ 1 ，θ 2 ，φ 2 ，ν，x l Sequentially representing time delay, vertical departure angle, horizontal departure angle, vertical arrival angle, horizontal arrival angle, doppler shift and reference signal, t' is signal duration, c 1 Representing the departure angle steering vector, c 2 Representing angle of arrival steering vectors [ ·] * And [ ·] H ＝[[·]*] T The conjugate and conjugate transpose operators are indicated separately. Each small scale parameter is given by the following formula:
D 0 representing the total received signal time, I =1,2, \ 8230;, I represents the number of fast beats, T a Representing a snapshot period duration, P u Represents the power of the reference signal u (t) [. Degree] * And [ ·] H ＝[[·]*] T The conjugate and conjugate transpose operators are indicated separately.
The updating process of each small-scale parameter in the parameter set rho is as follows:
wherein,
is a maximum likelihood estimate of the parameter(s),
for the first iteration, initial values of the parameters are given as guesses of the parameters. The initialization steps are as follows:
1) Determining an initial time delay estimation value:
2) Determining an initial angle estimation value:
3) Determining an initial Doppler frequency shift estimated value:
4) Determining an initial estimation value of the complex amplitude:
and obtaining an initial parameter set according to the algorithm steps, obtaining a final parameter set by using the channel label stored in the step S103, and finishing parameter estimation.
FIGS. 3 (a) and 3 (b) show the effect of extracting parameters by the conventional SAGE algorithm and the effect of extracting parameters by the present invention, respectively. As can be seen from the figure, for the same channel, the operation speed of the SAGE-BEM5G wireless channel parameter extraction method based on beam forming provided by the invention is 31% higher than that of the traditional SAGE algorithm, the accurate estimation of the channel parameters is realized, and the operation efficiency and accuracy are improved.
The present invention is not limited to the above embodiments, and any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention are also within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A SAGE-BEM5G wireless channel parameter extraction method based on beam forming is characterized by comprising the following steps:
step S101: determining a channel Noise threshold Noise gate ；
Step S102: calculating a Bartlett power spectrum by using a Bartlett beam forming method;
step S103: utilizing the Bartlett power spectrum calculated in the step S102, and according to the Noise channel Noise threshold Noise determined in the step S101 gate Determining the multipath packet and reconstructing the channel specifically comprises the following steps: firstly, according to the Bartlett power spectrum calculated in the step S102, a time delay power spectrum P is obtained τ Horizontal angle power spectrum P φ And vertical angle power spectrum P θ And extracting multipath packets { tau, phi, theta } by combining the channel noise threshold Noisegate calculated in the step S101, and sequentially representing time delay, horizontal angle and vertical angle, wherein the calculation formula is as follows:
tau＝{τ|τ∈Τ,P τ ≥Noise gate }
theta＝{θ|θ∈Θ,P θ ≥Noise gate }
where < T > = [0, N H ]Represents the time delay value range, phi = [ -pi, pi) represents the horizontal angle value range, theta = [0, pi =]Indicating the vertical angle value range; reconstructing a channel according to the screened multipath packets, and storing the multipath packet time delay parameters as labels of the reconstructed channel;
step S104: and utilizing SAGE algorithm to iterate the reconstructed channel of the step S103 to obtain a preliminary channel parameter estimation result, and recovering according to the reconstructed channel label to obtain a final parameter estimation result.
2. The method of claim 1, wherein the channel Noise threshold Noise is Noise for SAGE-BEM5G wireless channel parameter extraction based on beamforming gate Calculated as follows:
Noise gate ＝P max -σ
wherein, P max Is the maximum value of the channel power, and σ is the channel power threshold.
3. The SAGE-BEM5G wireless channel parameter extraction method based on beam forming as claimed in claim 2, wherein in case of line of sight, σ takes a value of 15dB; in the non-line-of-sight case, σ takes on a value of 25dB.
4. The method of claim 2, wherein the step S102 comprises:
firstly, a signal model and a parameter set to be estimated are determined according to a channel measurement method and a plan, an input signal is defined as u (t), and after an electric wave passes through a 5G wireless channel, the signal of the ith multipath can be represented as:
s(t；ρ l )＝[s 1 (t；ρ l ),...,s M (t；ρ l )] T ＝c(θ l ,φ l )α l exp(j2πν l t)u(t-τ l )
wherein ρ l ＝[τ l ,θ l ,φ l ,ν l ,α l ]The parameter set of the ith multipath, wherein symbols in the set sequentially represent time delay, a vertical arrival angle, a horizontal arrival angle, doppler frequency shift and complex amplitude, and c (theta, phi) is a guide vector;
for M receiving antennas, let its position be r 1 ,r 2 ,...r M Then, there are:
wherein, f M (theta, phi) represents the antenna complex pattern of the Mth antenna element, lambda is the wavelength of the corresponding carrier frequency, e (theta, phi) is the unit direction vector of the spherical coordinate,<·>representing an inner product operation;
the unit direction vector e (theta, phi) is uniquely determined by the unit sphere coordinates (theta, phi) epsilon [0, pi ] × [ -pi, pi) (r = 1), i.e.
e(θ,φ)＝[cos(φ)sin(θ),sin(φ)sin(θ),cos(θ)] T
Wherein phi is a horizontal angle, and theta is a vertical angle;
then the response matrix output by the receiving antenna array has:
wherein N is 0 Is a positive constant, N (t) represents M-dimensional white Gaussian noise;
the Bartlett power spectrum is calculated as follows:
P(θ,φ,τ)＝c(θ,φ) H ×R H (τ)×c(θ,φ)
where τ represents multipath delay, c represents steering vector, (. Cndot.) H Is a conjugate transpose, R H (τ) represents a spatial correlation matrix, given by:
R H (τ)＝vec(H(τ))×vec( H (τ)) H
where vec (·) represents the column-wise dimension reduction operation of the matrix.
5. The method of claim 1, wherein the step S104 comprises:
the number of antenna units at the transmitting end is set as N, the number of antenna units at the receiving end is set as M, and the definition of a z function is given as follows:
where τ, θ 1 ,φ 1 ,θ 2 ,φ 2 ,ν,x l Sequentially representing time delay, vertical departure angle, horizontal departure angle, vertical arrival angle, horizontal arrival angle, doppler shift, and reference signal, t' is signal duration, c 1 Representing the departure angle guide vector, c 2 Representing angle of arrival steering vector, [ ·] * And [ ·] H ＝[[·] * ] T Respectively representing conjugation and conjugation transpose operators; each small scale parameter is given by the following formula:
D 0 representing the total received signal time, I =1,2, \ 8230;, I represents the number of fast beats, T a Representing a snapshot period duration, P u Representing the power of the input signal u (t) [. Degree] * And [ · C] H ＝[[·] * ] T Respectively representing conjugation and conjugation transpose operators;
the updating process of each small-scale parameter in the parameter set rho is as follows:
wherein,
is a maximum likelihood estimate of the parameter(s),
for the guess quantity of the parameters, setting the initial value of each parameter for the first iteration; and obtaining an initial parameter set according to the algorithm steps, and obtaining a final parameter set by using the channel label stored in the step S103 to finish parameter estimation.
6. The method of claim 5, wherein an initial value of each parameter is calculated by the following formula:
initial estimation value of time delay:
initial angle estimation:
initial estimation value of doppler shift:
initial complex amplitude estimation:
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