CN113438682A - SAGE-BEM5G wireless channel parameter extraction method based on beam forming - Google Patents

SAGE-BEM5G wireless channel parameter extraction method based on beam forming Download PDF

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CN113438682A
CN113438682A CN202110884867.8A CN202110884867A CN113438682A CN 113438682 A CN113438682 A CN 113438682A CN 202110884867 A CN202110884867 A CN 202110884867A CN 113438682 A CN113438682 A CN 113438682A
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angle
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CN113438682B (en
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杜飞
赵雄文
魏大才
富子豪
耿绥燕
周振宇
张磊
陈素红
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State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Shandong Electric Power Co Ltd
North China Electric Power University
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Electric Power Research Institute of State Grid Shandong Electric Power Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel
    • H04B17/3912—Simulation models, e.g. distribution of spectral power density or received signal strength indicator [RSSI] for a given geographic region
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention provides a SAGE-BEM5G wireless channel parameter extraction method based on beam forming, which comprises the following steps: determining a channel Noise threshold Noisegate(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

SAGE-BEM5G wireless channel parameter extraction method based on beam forming
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 and efficient signal transmission, channel parameters play a crucial role, so 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 research expectation in 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 knowledge optimization) method for improving the problems of low running efficiency and the like of SAGE during initialization by combining beam forming and 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 Noisegate；
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 channelgate。
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 multipath packet is determined based on the Bartlett power spectrum calculated in step S102 and the noise threshold determined in step S101, and the delay parameter in the multipath packet is 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 (4) determining. And reconstructing the channel according to the screened multipath packets, and storing the multipath packet time delay parameters as 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.
Drawings
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 ∈ [0, NH]，NHIs the length of the channel impulse response.
Calculating the maximum value P of the channel power according to the channel power P (tau)max：
Figure BDA0003193639230000031
Noise threshold NoisegateCalculated as follows:
Noisegate＝Pmax-σ (3)
where σ is a channel power threshold, and in the case of line-of-sight, the general empirical value of σ is 15 dB. In the non-line-of-sight case, the general empirical value for σ is 25 dB.
Step S102: calculating a 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 expressed as:
s(t；ρl)＝[s1(t；ρl)，...，sM(t；ρl)]T＝c(θl，φl)αl exp(j2πνlt)u(t-τl) (4)
where ρ isl＝[τl，θl，φl，νl，αl]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 called an antenna array response matrix, and the structure and each of the antenna arraysThe pattern of the antenna elements is relevant. For M receiving antennas, let its position be r1，r2，...rMThen, there are:
Figure BDA0003193639230000041
wherein f isM(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) 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)
Where φ is a horizontal angle and θ is a vertical angle. Then the response matrix output by the receiving antenna array has:
Figure BDA0003193639230000042
wherein N is0Is a positive constant, and N (t) represents M-dimensional white Gaussian noise.
The Bartlett power spectrum is calculated as follows:
P(θ,φ,τ)＝c(θ,φ)H×RH(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, (-)HIs a conjugate transpose, RH(τ) represents a spatial correlation matrix, given by:
RH(τ)＝vec(H(τ))×vec(H(τ))H (9)
where vec (·) represents the column-wise dimension reduction operation of the matrix.
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 obtainedτ) Horizontal angle power spectrum (P)φ) Perpendicular angle power spectrum (P)θ) Combining the Noise threshold Noise calculated in step S101gateExtracting multipath packets { tau, phi, theta }, sequentially representing time delay, horizontal angle and vertical angle, wherein the calculation formula is as follows:
Figure BDA0003193639230000051
wherein T is [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 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:
Figure BDA0003193639230000052
where τ, θ1，φ1，θ2，φ2，ν，xlSequentially representing time delay, vertical departure angle, horizontal departure angle, vertical arrival angle, horizontal arrival angle, Doppler shift, and reference signal, t' is signal duration, c1Representing the departure angle guide vector, c2Representing angle of arrival steering vectors [ ·]*And [ ·]H＝[[·]*]TThe conjugate and conjugate transpose operators are indicated separately. Each small scale parameter is given by the following formula:
Figure BDA0003193639230000053
Figure BDA0003193639230000061
D0denotes the total received signal time, I is 1,2, …, I denotes the fast beat number, TaRepresenting a snapshot period duration, PuRepresents the power of the reference signal u (t) [. degree]*And [ ·]H＝[[·]*]TThe conjugate and conjugate transpose operators are indicated separately.
The updating process of each small-scale parameter in the parameter set rho is as follows:
Figure BDA0003193639230000062
wherein the content of the first and second substances,
Figure BDA0003193639230000063
for the purpose of the maximum likelihood estimation of the parameters,
Figure BDA0003193639230000064
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 estimated value:
Figure BDA0003193639230000065
2) determining an initial angle estimation value:
Figure BDA0003193639230000066
Figure BDA0003193639230000067
3) determining an initial Doppler frequency shift estimated value:
Figure BDA0003193639230000071
4) determining an initial estimation value of the complex amplitude:
Figure BDA0003193639230000072
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.
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 SAGE-BEM5G wireless channel parameter extraction method based on beam forming provided by the invention has the operation speed 31% higher than that of the traditional SAGE algorithm, realizes accurate estimation of the channel parameters, and improves the operation efficiency and accuracy.
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 (7)

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 Noisegate；
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 S101gateDetermining a multipath packet and reconstructing a 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 extracting SAGE-BEM5G wireless channel parameters based on beam forminggateCalculated as follows:
Noisegate＝Pmax-σ
wherein, PmaxIs 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 15 dB; in the non-line-of-sight case, σ takes on a value of 25 dB.
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 expressed as:
s(t；ρl)＝[s1(t；ρl),...,sM(t；ρl)]T＝c(θl,φl)αlexp(j2πνlt)u(t-τl)
where ρ isl＝[τl,θl,φl,νl,αl]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 r1,r2,...rMThen, there are:
Figure FDA0003193639220000021
wherein f isM(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 (θ, Φ) is uniquely determined by unit spherical coordinates (θ, Φ) e [0, pi ] × [ -pi, pi) (r ═ 1), that is
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:
Figure FDA0003193639220000022
wherein N is0Is 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×RH(τ)×c(θ,φ)
where τ represents multipath delay, c represents steering vector, (. cndot.)HIs a conjugate transpose, RH(τ) represents a spatial correlation matrix, given by:
RH(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 4, wherein the step S103 comprises:
firstly, according to the Bartlett power spectrum calculated in the step S102, a time delay power spectrum P is obtainedτHorizontal angle power spectrum PφAnd vertical angle power spectrum PθCombining the channel Noise threshold Noise calculated in step S101gateExtracting multipath packets { tau, phi, theta }, and sequentially listingDelay, horizontal angle and vertical angle, and the calculation formula is as follows:
tau＝{τ|τ∈T,Pτ≥Noisegate}
Figure FDA0003193639220000031
theta＝{θ|θ∈Θ,Pθ≥Noisegate}
wherein T is [0, N ]H]Represents the time delay value range, phi [ -pi, pi) represents the horizontal angle value range, theta ═ 0, pi]Representing the vertical angle value range; and reconstructing the channel according to the screened multipath packets, and storing the multipath packet time delay parameters as labels of the reconstructed channel.
6. The method of claim 5, 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:
Figure FDA0003193639220000032
where τ, θ1,φ1,θ2,φ2,ν,xlSequentially representing time delay, vertical departure angle, horizontal departure angle, vertical arrival angle, horizontal arrival angle, Doppler shift, and reference signal, t' is signal duration, c1Representing the departure angle guide vector, c2Representing angle of arrival steering vectors [ ·]*And [ ·]H＝[[·]*]TRespectively representing conjugation and conjugation transpose operators; each small scale parameter is given by the following formula:
Figure FDA0003193639220000033
Figure FDA0003193639220000034
D0denotes the total received signal time, I1, 2aRepresenting a snapshot period duration, PuRepresents the power of the reference signal u (t) [. degree]*And [ ·]H＝[[·]*]TRespectively representing conjugation and conjugation transpose operators;
the updating process of each small-scale parameter in the parameter set rho is as follows:
Figure FDA0003193639220000041
Figure FDA0003193639220000042
Figure FDA0003193639220000043
Figure FDA0003193639220000044
Figure FDA0003193639220000045
Figure FDA0003193639220000046
Figure FDA0003193639220000047
wherein the content of the first and second substances,
Figure FDA0003193639220000048
for the purpose of the maximum likelihood estimation of the parameters,
Figure FDA0003193639220000049
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.
7. The method of claim 6, wherein the initial value of each parameter is calculated as follows:
initial estimation value of time delay:
Figure FDA00031936392200000410
initial angle estimation:
Figure FDA00031936392200000411
Figure FDA00031936392200000412
initial estimation value of doppler shift:
Figure FDA00031936392200000413
initial estimation of complex amplitude:
Figure FDA0003193639220000051
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