CN112929305A - Multipath channel gain estimation method based on IQ imbalance millimeter wave communication system - Google Patents

Multipath channel gain estimation method based on IQ imbalance millimeter wave communication system Download PDF

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CN112929305A
CN112929305A CN202110172037.2A CN202110172037A CN112929305A CN 112929305 A CN112929305 A CN 112929305A CN 202110172037 A CN202110172037 A CN 202110172037A CN 112929305 A CN112929305 A CN 112929305A
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imbalance
matrix
multipath channel
channel gain
millimeter wave
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CN112929305B (en
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侯卫兵
雷伟龙
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Wuhan Litong Communication Co ltd
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    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • 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
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    • H04L25/024—Channel estimation channel estimation algorithms
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Abstract

The invention discloses a multipath channel gain estimation method based on an IQ imbalance millimeter wave communication system, S1, adopting a digital-analog mixed architecture to construct a millimeter wave MIMO system, comprising a transmitting end and a receiving end with IQ imbalance, wherein the channel is a sparse multipath channel; s2, modeling the millimeter wave MIMO system to obtain an IQ imbalance model of the receiving signal of the receiving end, and carrying out vectorization deformation to obtain
Figure DDA0002939246030000011
S3, an optimization target for estimating sparse multipath channel gain is provided, specifically:
Figure DDA0002939246030000012
s.t.‖ha‖0l; s4, using orthogonal matchingAnd solving the optimization target by a tracking algorithm to obtain an estimation result. The invention has the advantages of solving the problem of radio frequency distortion in the baseband processing module so as to reduce the power consumption and the burden in the radio frequency link.

Description

Multipath channel gain estimation method based on IQ imbalance millimeter wave communication system
Technical Field
The present invention relates to the field of wireless communication channel estimation. More specifically, the present invention relates to a multipath channel gain estimation method based on an IQ imbalance millimeter wave communication system.
Background
Millimeter wave communication technology will be widely applied to 5G communication systems and plays an important role. Since the channel of the millimeter wave communication system is mostly a sparse channel, the digital-analog mixed signal processing architecture is one of the advantageous solutions. The digital-analog hybrid architecture is composed of a beam former at an analog end and a MIMO digital processor at a digital end, and the digital-analog hybrid architecture can effectively reduce the number of radio frequency links. In the radio frequency link, the main components include a mixer, a low pass filter, an amplifier and a digital-to-analog/analog-to-digital converter. Due to the amplitude and phase imbalance of the local oscillation of the I branch and the Q branch and the resistance and capacitance deviation of the amplifier, IQ imbalance occurs in the signal, and is unavoidable in the radio frequency transceiver.
In a millimeter wave MIMO communication system, channel state information is crucial to designing both beamforming and baseband signal processing. Because most of channels of the millimeter wave MIMO communication system are sparse multipath channels, a general channel estimation calculation method is based on a compressed sensing technology, and mainly comprises a channel estimation algorithm and a matching tracking algorithm based on codebook design. Conventional compressed sensing technology-based matching pursuit algorithms do not take into account the correction of IQ imbalanced signals, which can affect the signal processing at baseband, including channel estimation. How to provide a multipath channel gain estimation method in an IQ unbalanced millimeter wave MIMO system, and solving the problem of radio frequency distortion in a baseband processing module to reduce power consumption and burden in a radio frequency link is a problem which is urgently needed to be solved at present.
Disclosure of Invention
An object of the present invention is to solve at least the above problems and to provide at least the advantages described later.
It is still another object of the present invention to provide a multipath channel gain estimation method based on IQ imbalance mm-wave communication system, which solves the problem of rf distortion in the baseband processing module to reduce power consumption and burden in the rf link.
In order to achieve these objects and other advantages according to the present invention, a multipath channel gain estimation method based on an IQ imbalance millimeter wave communication system is provided, S1, a millimeter wave MIMO system is constructed by using a digital-analog hybrid architecture, wherein the millimeter wave MIMO system includes a transmitting end and a receiving end having IQ imbalance, and the channel is a sparse multipath channel;
s2, modeling the millimeter wave MIMO system to obtain an IQ imbalance model of the receiving signal of the receiving end, and carrying out vectorization deformation to obtain
Figure BDA0002939246010000021
Figure BDA0002939246010000022
Wherein x ispIs a pilot signal, WBBFor processing the signals of the receiving end baseband, WRFFor the receive-side beamforming matrix, FBBProcessing matrix for transmitting side baseband signals, FRFFor the transmit-end beamforming matrix, KMSIs the coefficient of IQ imbalance at the receiving end, ARAs a receiving end angle response matrix, ATFor the transmit end angle response matrix, HaIs an amplitude response matrix, n is white gaussian noise, (·) is a conjugate matrix; (. H) is a conjugate transpose matrix; (. T) is a transposed matrix;
in addition
Figure BDA0002939246010000023
Then it can be obtained
Figure BDA0002939246010000024
S3, simplification-based
Figure BDA0002939246010000025
An optimization target for estimating sparse multipath channel gain is provided, which specifically comprises the following steps:
Figure BDA0002939246010000026
Figure BDA0002939246010000027
s.t.‖ha‖0l, wherein, haIn the form of sparse multipath channel gain vectorization, L isThe number of sparse multipath channels;
and S4, solving the optimization target by using an orthogonal matching pursuit algorithm to obtain an estimation result.
Preferably, the IQ imbalance model is:
Figure BDA0002939246010000028
where s is the transmit signal, H is the channel matrix, and H ═ aRHaAT。
It is preferable that the first and second liquid crystal layers are formed of,
Figure BDA0002939246010000029
wherein, gR＝diag{gR，1，gR，2，…，gR，NThe coefficient matrix of amplitude imbalance of the receiving-end antenna interface is used as the coefficient matrix, N is the number of the receiving-end antennas, j is an imaginary number unit, phiR＝diag{φR，1，φR，2，…，φR，NAnd the coefficient matrix is the phase imbalance coefficient matrix of the receiving end antenna interface.
Preferably, A isR＝[aR(θR,1),aR(θR,2),…,aR(θR,L)]L is the number of sparse multipath channels, θR,nAngle of arrival, α, for the nth pathR(θR,n) The receiving end array response vector is specifically expressed as:
Figure BDA00029392460100000210
in the formula, λ is the signal wavelength, and d is the antenna spatial state.
Preferably, A isT＝[aT(θT,1),aT(θT,2),…,aT(θT,L)]，θT,nIs the off-angle of the nth path, αT(θT,n) The response vector of the sending end array is specifically expressed as:
Figure BDA00029392460100000211
preferably, HaIs an amplitude response matrix, Ha＝diag(α1,α2,…,αL)，αLThe complex gain of the lth path is indicated.
Preferably, the solving of the optimization target by using the orthogonal matching pursuit algorithm specifically includes:
sa, initialization residual
Figure BDA0002939246010000031
Index set
Figure BDA0002939246010000032
The iteration number i is 1;
sb, calculating Q1Sum residual uiInner product of (2):
Figure BDA0002939246010000033
sc, search | gi|/‖Q1Index of | maximum value: k is a radical ofi＝argmax(|gi|/‖Q1‖)；
Sd, update index set: t isi＝Ti-1∪ki；
Se, calculation
Figure BDA0002939246010000034
Least squares solution of (c):
Figure BDA0002939246010000035
sf, updating residual ui：
Figure BDA0002939246010000036
Sg, i ═ i +1, and whether or not i is satisfied is determined<L +1, if satisfying, executing step Sb, if not, stopping circulation according to the index set TiDetermining
Figure BDA0002939246010000037
And input of element positions ofDeriving an estimate of sparse multipath channel gain
Figure BDA0002939246010000038
Wherein,
Figure BDA0002939246010000039
the invention at least comprises the following beneficial effects:
the baseband processing module improves the orthogonal matching tracking algorithm into a channel gain estimation algorithm adaptive to the IQ imbalance millimeter wave MIMO system under the condition of knowing IQ imbalance parameters and an angle response matrix so as to estimate the channel gain of a sparse multipath channel in the IQ imbalance millimeter wave MIMO system, and solves the problem of radio frequency distortion in the baseband processing module so as to reduce the power consumption and the burden in a radio frequency link.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
Fig. 1 is a millimeter wave MIMO system constructed by using a digital-analog hybrid architecture according to an embodiment of the present invention;
fig. 2 is a minimum mean square error diagram of different channel gain estimation algorithms under different snr conditions.
Detailed Description
The present invention is further described in detail below with reference to examples so that those skilled in the art can practice the invention with reference to the description.
The invention provides a multipath channel gain estimation method based on an IQ imbalance millimeter wave communication system, which comprises the following steps:
s1, constructing a millimeter wave MIMO system (as shown in figure 1) by adopting a digital-analog mixed architecture, wherein the millimeter wave MIMO system comprises a transmitting end and a receiving end with IQ imbalance, and the channel is a sparse multipath channel;
s2, modeling the down link of the millimeter wave MIMO system to obtain the IQ imbalance model of the receiving signal of the receiving end, and carrying out vectorization deformation to obtain
Figure BDA0002939246010000041
Figure BDA0002939246010000042
Wherein x ispIs a pilot signal, WBBFor processing the signals of the receiving end baseband, WRFFor the receive-side beamforming matrix, FBBProcessing matrix for transmitting side baseband signals, FRFFor the transmit-end beamforming matrix, KMSIs the coefficient of IQ imbalance at the receiving end, ARAs a receiving end angle response matrix, ATFor the transmit end angle response matrix, HaIs an amplitude response matrix, n is white gaussian noise, (·) is a conjugate matrix; (. H) is a conjugate transpose matrix; (. T) is a transposed matrix;
in addition
Figure BDA0002939246010000043
Then it can be obtained
Figure BDA0002939246010000044
S3, simplification-based
Figure BDA0002939246010000045
An optimization target for estimating sparse multipath channel gain is provided, which specifically comprises the following steps:
Figure BDA0002939246010000046
Figure BDA0002939246010000047
s.t.‖ha‖0l, wherein, haThe method is a sparse multipath channel gain vectorization form, and L is the number of sparse multipath channels;
and S4, solving the optimization target by using an orthogonal matching pursuit algorithm to obtain an estimation result.
In the above embodiment, the radio frequency transceiver includes a transmitter and a receiver, where the transmitter constitutes a transmitting end, and the receiver constitutes a receiving end with IQ imbalance, where the specific transmitting end and receiving end both include a baseband (signal) processing module, a beamforming module, multiple radio frequency links arranged between the baseband processing module and the beamforming module, and multiple antennas connected to the beamforming module, where the number of the receiving end antennas is N, parameters of the IQ imbalance include amplitude imbalance and phase imbalance, and a downlink link, and an IQ imbalance model is established in step S2 according to the constructed millimeter wave MIMO system, and is subjected to vectorization deformation, and an optimization target for estimating sparse multipath channel gain is provided, so as to obtain an objective equation to be optimized, so that the objective equation is more compact and is suitable for the form of the proposed algorithm; the implementation steps in step S4 are "select an atom from the overcomplete atom (dictionary matrix) library that matches best with the received signal, construct a sparse approximation, and find the signal residual, then continue to select the atom that matches best with the signal residual, and iterate repeatedly to obtain a sparse multipath channel gain estimate". By adopting the embodiment, a sparse multipath channel gain estimation scheme of the millimeter wave MIMO system with IQ imbalance at the receiving end is provided, the large-scale millimeter wave MIMO system is composed of a certain number of radio frequency links, and the I path and Q path parameters in the radio frequency links are not matched, so that the channel estimation, equalization and the like of baseband signal processing can be caused to fail, and the sensitivity of a receiver is seriously influenced. In the present embodiment, it is assumed that an IQ imbalance phenomenon exists at a receiving end in a millimeter wave MIMO system, and an IQ imbalance parameter is estimated by a radio frequency transceiving end and transmitted to a baseband processing module. Under the condition of assuming that the angle of the sparse multipath channel is known, the gain of the multipath channel is estimated, and the problem of radio frequency distortion is solved in a baseband processing module so as to reduce the power consumption and the burden in a radio frequency link.
In another embodiment, the IQ imbalance model is:
Figure BDA0002939246010000051
where s is the transmit signal, H is the channel matrix, and H ═ aRHaAT. By adopting the scheme, the sending signal s in the downlink passes through the base band processing module, the radio frequency link and the beam forming module of the sending end in sequence and then passes through the antenna of the sending endAnd line transmission, wherein a receiving end receives a signal through an antenna, and then the signal is processed through a corresponding beam forming module, a radio frequency link and a baseband processing module to obtain a signal r, wherein r is expressed as the following formula:
Figure BDA0002939246010000052
based on the IQ imbalance model r representing IQ imbalance of the receiver in the millimeter wave MIMO systemIQWherein the radial signal due to IQ imbalance is considered.
In another embodiment of the present invention, the substrate is,
Figure BDA0002939246010000053
wherein, gR＝diag{gR，1，gR，2，…，gR，NThe coefficient matrix of amplitude imbalance of the receiving-end antenna interface is used as the coefficient matrix, N is the number of the receiving-end antennas, j is an imaginary number unit, phiR＝diag{φR，1，φR，2，…，φR，NAnd the coefficient matrix is the phase imbalance coefficient matrix of the receiving end antenna interface. With this scheme, an IQ imbalance model is constructed by considering the radial signal due to IQ imbalance.
In another embodiment, AR＝[aR(θR,1),aR(θR,2),…,aR(θR,L)]L is the number of sparse multipath channels, θR,nAngle of arrival, α, for the nth pathR(θR,n) The receiving end array response vector is specifically expressed as:
Figure BDA0002939246010000054
in the formula, λ is the signal wavelength, and d is the antenna spatial state. By adopting the scheme, the receiving end angle response matrix is obtained.
In another embodiment, AT＝[aT(θT,1),aT(θT,2),…,aT(θT,L)]，θT,nIs the off-angle of the nth path, αT(θT,n) The response vector of the sending end array is specifically expressed as:
Figure BDA0002939246010000055
the method is adopted to obtain the angle response matrix of the sending end.
In another embodiment, HaIs an amplitude response matrix, Ha＝diag(α1,α2,…,αL)，αLThe complex gain of the lth path is indicated. With this scheme, an amplitude response matrix is obtained.
In another embodiment, the solving of the optimization objective by using the orthogonal matching pursuit algorithm specifically includes:
sa, initialization residual
Figure BDA0002939246010000056
Index set
Figure BDA0002939246010000057
The iteration number i is 1;
sb, calculating Q1Sum residual uiInner product of (2):
Figure BDA0002939246010000061
sc, search | gi|/‖Q1Index of | maximum value: k is a radical ofi＝argmax(|gi|/‖Q1‖)；
Sd, update index set: t isi＝Ti-1∪ki；
Se, calculation
Figure BDA0002939246010000062
Least squares solution of (c):
Figure BDA0002939246010000063
Figure BDA0002939246010000064
is Q1A subset (sub-matrix) of the sub-sets,
Figure BDA0002939246010000065
is Q2Subsets (submatrices), each according to TiCarrying out value taking;
sf, updating residual ui：
Figure BDA0002939246010000066
Sg, i ═ i +1, and whether or not i is satisfied is determined<l +1, if yes, executing the step Sb, if not, stopping circulation and according to the index set TiDetermining
Figure BDA0002939246010000067
And outputs an estimate of the sparse multipath channel gain
Figure BDA0002939246010000068
Wherein,
Figure BDA0002939246010000069
by adopting the scheme, the optimized target is solved by utilizing an improved orthogonal matching pursuit algorithm to obtain an estimation result.
< example 1>
The invention provides a multipath channel gain estimation method based on an IQ imbalance millimeter wave communication system, which comprises the following steps:
s1, constructing a millimeter wave MIMO system (as shown in fig. 1) by using a digital-analog hybrid architecture, where the millimeter wave MIMO system includes a transmitting end and a receiving end with IQ imbalance, the channel is a sparse multipath channel, the transmitting end is formed by a transmitter, and the receiving end is formed by a receiver, the transmitting end and the receiving end both include a baseband (signal) processing module, a beamforming module, a plurality of radio frequency links disposed between the baseband processing module and the beamforming module, and a plurality of antennas connected to the beamforming module, and the number of the receiving end antennas is N;
s2, modeling the down link of the millimeter wave MIMO system to obtain the IQ imbalance model of the receiving signal of the receiving end,
Figure BDA00029392460100000610
where s is the transmit signal, H is the channel matrix, and H ═ aRHaAT，WBBFor processing the signals of the receiving end baseband, WRFFor the receive-side beamforming matrix, FBBProcessing matrix for transmitting side baseband signals, FRFFor the transmit-end beamforming matrix, KMSIs the coefficient of IQ imbalance at the receiving end, ARAs a receiving end angle response matrix, ATFor the transmit end angle response matrix, HaIs an amplitude response matrix, n is white gaussian noise, (·) is a conjugate matrix; (. H) is a conjugate transpose matrix; (. T) is a transposed matrix;
specifically, the method comprises the following steps:
Figure BDA00029392460100000611
wherein, gR＝diag{gR，1，gR，2，…，gR，NThe coefficient matrix of amplitude imbalance of the receiving-end antenna interface is used as the coefficient matrix, N is the number of the receiving-end antennas, j is an imaginary number unit, phiR＝diag{φR，1，φR，2，…，φR，NThe coefficient matrix of phase imbalance of the receiving end antenna interface is used as the coefficient matrix;
AR＝[aR(θR,1),aR(θR,2),…,aR(θR,L)]l is the number of sparse multipath channels, θR,nAngle of arrival, α, for the nth pathR(θR,n) The receiving end array response vector is specifically expressed as:
Figure BDA0002939246010000071
in the formula, lambda is signal wavelength, and d is antenna space state;
AT＝[aT(θT,1),aT(θT,2),…,aT(θT,L)]，θT,nis the off-angle of the nth path, αT(θT,n) The response vector of the sending end array is specifically expressed as:
Figure BDA0002939246010000072
Hais an amplitude response matrix, Ha＝diag(α1,α2,…,αL)，αLRepresents the complex gain of the lth path;
s3, carrying out vectorization deformation on the IQ imbalance model to obtain
Figure BDA0002939246010000073
Figure BDA0002939246010000074
Wherein x ispIs a pilot signal;
in addition
Figure BDA0002939246010000075
Then it can be obtained
Figure BDA0002939246010000076
S4, simplification-based
Figure BDA0002939246010000077
An optimization target for estimating sparse multipath channel gain is provided, which specifically comprises the following steps:
Figure BDA0002939246010000078
Figure BDA0002939246010000079
s.t.‖ha‖0l, wherein, haThe method is a sparse multipath channel gain vectorization form, and L is the number of sparse multipath channels;
s5, solving the optimization target by using an orthogonal matching pursuit algorithm to obtain an estimation result, which specifically comprises the following steps:
sa, initialization residual
Figure BDA00029392460100000710
Index set
Figure BDA00029392460100000711
The iteration number i is 1;
sb, calculating Q1Sum residual uiInner product of (2):
Figure BDA00029392460100000712
sc, search | gi|/‖Q1Index of | maximum value: k is a radical ofi＝argmax(|gi|/‖Q1‖)；
Sd, update index set: t isi＝Ti-1∪ki；
Se, calculation
Figure BDA00029392460100000713
Least squares solution of (c):
Figure BDA00029392460100000714
sf, updating residual error u:
Figure BDA00029392460100000715
sg, i ═ i +1, and whether or not i is satisfied is determined<L +1, if satisfying, executing step Sb, if not, stopping circulation according to the index set TiDetermining
Figure BDA00029392460100000716
And outputs an estimate of the sparse multipath channel gain
Figure BDA00029392460100000717
Wherein,
Figure BDA00029392460100000718
simulation analysis
The embodiment is shown in a simulation form, and two systems are constructed, specifically:
the millimeter wave MIMO system (system 1) with IQ imbalance in the radio frequency link of the receiving end: considering the downlink in a cell, there are 32 antennas and 8 rf chains in each of the base station side (transmitting side) and the mobile side (receiving side). The radio frequency link of the receiving end has IQ imbalance, IQ imbalance parameters accord with uniform distribution in a certain interval, a propagation channel is a sparse multipath channel, channel gain follows Gaussian distribution and is a slow fading channel, and a beam forming module and a baseband processing module are Mach matrix;
the millimeter wave MIMO system (system 2) without IQ imbalance of the radio frequency link of the receiving end: considering the downlink in a cell, there are 32 antennas and 8 rf chains in each of the base station side (transmitting side) and the mobile side (receiving side). The radio frequency link of the receiving end has no IQ imbalance, the propagation channel is a sparse multipath channel, the channel gain follows Gaussian distribution and is a slow fading channel, and the beam forming module and the baseband processing module are Mach matrix;
the minimum Mean Square Error (MSE) of different channel gain estimation algorithms respectively showing different situations under different signal-to-noise ratios (SNRs) comprises:
(example 1) channel gain estimation was performed for system 1 using the method of embodiment 1 (improved orthogonal matching algorithm);
(comparative example 1) a general orthogonal matching algorithm is adopted for the system 1 to carry out channel gain estimation;
(comparative example 2) channel gain estimation is performed by using a least square algorithm for the system 1;
(comparative example 3) a general orthogonal matching algorithm is adopted for the system 2 to carry out channel gain estimation;
(comparative example 4) channel gain estimation was performed using the least squares algorithm for system 2.
As a result, as shown in fig. 2, the conventional orthogonal matching pursuit algorithm (conventional algorithm) employed in example 1 is nearly ineffective in the face of the presence of the image signal, but the improved orthogonal matching algorithm employed in example 1 can effectively solve this problem. Further, the improved orthogonal matching algorithm employed in example 1 has a lower MSE than the algorithms of comparative examples 2 and 3 under the same SNR conditions, and is close to the algorithm in the case of the ideal radio link (comparative example 4).
While embodiments of the invention have been disclosed above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in a variety of fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein and that the examples and illustrations contained herein are to be given the full breadth of the appended claims and their equivalents.

Claims (7)

1. The multipath channel gain estimation method based on the IQ imbalance millimeter wave communication system is characterized by comprising the following steps of:
s1, constructing a millimeter wave MIMO system by adopting a digital-analog mixed architecture, wherein the millimeter wave MIMO system comprises a transmitting end and a receiving end with IQ imbalance, and the channel is a sparse multipath channel;
s2, modeling the millimeter wave MIMO system to obtain an IQ imbalance model of the receiving signal of the receiving end, and carrying out vectorization deformation to obtain
Figure FDA0002939244000000011
Figure FDA0002939244000000012
Wherein x ispIs a pilot signal, WBBFor processing the signals of the receiving end baseband, WRFFor the receive-side beamforming matrix, FBBProcessing matrix for transmitting side baseband signals, FRFFor the transmit-end beamforming matrix, KMSIs the coefficient of IQ imbalance at the receiving end, ARAs a receiving end angle response matrix, ATFor the transmit end angle response matrix, HaIs an amplitude response matrix, n is white gaussian noise, (·) is a conjugate matrix; (. H) is a conjugate transpose matrix; (. T) is a transposed matrix;
in addition
Figure FDA0002939244000000013
Then it can be obtained
Figure FDA0002939244000000014
S3, simplification-based
Figure FDA0002939244000000015
An optimization target for estimating sparse multipath channel gain is provided, which specifically comprises the following steps:
Figure FDA0002939244000000016
Figure FDA0002939244000000017
s.t.‖ha‖0l, wherein, haThe method is a sparse multipath channel gain vectorization form, and L is the number of sparse multipath channels;
and S4, solving the optimization target by using an orthogonal matching pursuit algorithm to obtain an estimation result.
2. The IQ imbalance millimeter wave communication system-based multipath channel gain estimation method according to claim 1, wherein the IQ imbalance model is:
Figure FDA0002939244000000018
where s is the transmit signal, H is the channel matrix, and H ═ aRHaAT。
3. The IQ imbalance millimeter-wave communication system-based multipath channel gain estimation method according to claim 1,
Figure FDA0002939244000000019
wherein, gR＝diag{gR，1，gR，2，…，gR，NThe coefficient matrix of amplitude imbalance of the receiving-end antenna interface is used as the coefficient matrix, N is the number of the receiving-end antennas, j is an imaginary number unit, phiR＝diag{φR，1，φR，2，…，φR，NAnd the coefficient matrix is the phase imbalance coefficient matrix of the receiving end antenna interface.
4. The IQ imbalance millimeter-wave communication system-based multipath channel gain estimation method according to claim 1, wherein A isR＝[aR(θR,1),aR(θR,2),…,aR(θR,L)]L is the number of sparse multipath channels, θR,nAngle of arrival, α, for the nth pathR(θR,n) The receiving end array response vector is specifically expressed as:
Figure FDA0002939244000000021
in the formula, λ is the signal wavelength, and d is the antenna spatial state.
5. The IQ imbalance millimeter-wave communication system-based multipath channel gain estimation method according to claim 4, wherein AT＝[aT(θT,1),aT(θT,2),…,aT(θT,L)]，θT,nIs the off-angle of the nth path, αT(θT,n) The response vector of the sending end array is specifically expressed as:
Figure FDA0002939244000000022
6. the IQ imbalance millimeter-wave communication system-based multipath channel gain estimation method according to claim 1, wherein HaIs an amplitude response matrix, Ha＝diag(α1,α2,…,αL)，αLThe complex gain of the lth path is indicated.
7. The IQ imbalance millimeter wave communication system-based multipath channel gain estimation method according to claim 1, wherein solving the optimization objective by applying an orthogonal matching pursuit algorithm specifically comprises:
sa, initialization residual
Figure FDA0002939244000000023
Index set
Figure FDA0002939244000000024
The iteration number i is 1;
sb, calculating Q1Sum residual uiInner product of (2):
Figure FDA0002939244000000025
sc, search | gi|/‖Q1Index of | maximum value: k is a radical ofi＝argmax(|gi|/‖Q1‖)；
Sd, update index set: t isi＝Ti-1∪ki；
Se, calculation
Figure FDA0002939244000000026
Least squares solution of (c):
Figure FDA0002939244000000027
sf, updating residual ui：
Figure FDA0002939244000000028
Sg, i ═ i +1, and whether or not i is satisfied is determined<L +1, if satisfying, executing step Sb, if not, stopping circulation according to the index set TiDetermining
Figure FDA0002939244000000029
And outputs an estimate of the sparse multipath channel gain
Figure FDA00029392440000000210
Wherein,
Figure FDA00029392440000000211
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