CN108881074A - Broadband millimeter-wave channel estimation methods under a kind of low precision mixed architecture - Google Patents
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Abstract
The invention discloses broadband millimeter-wave channel estimation methods, the simulation precoding of optimization design Whole frequency band and hypothetical mergers devices under a kind of low precision mixed architecture, and design digital combiner is separately optimized for each subcarrier, estimate for broad-band channel.Isotropic analog transceiver is designed first, and analog transceiver is using full connection phase shifter network, each phase shifter uniform phase distribution；Then optimization design has the digital combiner of frequency selectivity, it is hereby achieved that optimal channel estimation results.For the millimeter wave channel sparse with multipath, before optimization design digital combiner, this method can find the corresponding element position of channel principal component using orthogonal matching pursuit (OMP), further decrease the complexity of channel estimation.The broad-band channel estimator that the present invention provides is suitable for general channel model, and in the hybrid structure multiaerial system using low precision analog-digital converter, the present invention has a distinct increment to the estimated accuracy of any channel than conventional method.
Description
Technical field
The present invention relates to the communications fields, are related to channel estimation methods, mix more particularly relate to a kind of low precision
Broadband millimeter-wave channel estimation methods under framework.
Background technique
In next generation wireless network, user data traffic will be sharply increased.However, middle low-frequency range frequency spectrum resource is limited,
It is difficult to meet user demand.For this purpose, millimere-wave band (mmWave) is exploited and has entered next generation mobile communication standard,
Frequency spectrum resource abundant greatly increases power system capacity.Nevertheless, the path loss of mmWave signal, shadow fading relatively in
Low-frequency range is even more serious, so that power system capacity is limited to lower received signal to noise ratio (SNR).For this reason, it may be necessary to make full use of more days
The advantage of line transmission, carrys out lifting system spectrum efficiency using large-scale antenna array.On the other hand, mmWave wavelength is shorter, greatly
Space needed for being equipped with large-scale antenna array is saved greatly.Therefore, extensive multi-antenna technology is answered with mmWave transmission technology
It is used cooperatively, to be obviously improved system performance.Traditional extensive multi-antenna technology needs sending and receiving end to be equipped with a large amount of radio frequency
Link, especially in the mmWave system of broadband, cost and power consumption are quite high.In order to reduce the extensive multi-antenna technology of mmWave
The cost and hardware complexity of system, are attracted wide attention using the hybrid structure of a small amount of radio frequency link.
In order to carry out high-property transmission, need to carry out channel estimation first.Traditional extensive multi-antenna technology system
Channel estimation inherently a major challenge.And in the extensive multi-antenna technology system of hybrid structure, due to not can be carried out cardinar number
Word operation, channel estimation become more difficult.In the mmWave multiaerial system of broadband, high-precision adc (ADC) is logical
It is often high cost high power consumption.Therefore, it is necessary to introduce low Precision A/D C to reduce implementation complexity.However, using low precision
When the quantization receiver of ADC, due to the quantization operation of nonlinearity, precision of channel estimation is decreased obviously.Therefore, using low
In the extensive multi-antenna technology system of the broadband mmWave of Precision A/D C and hybrid structure, it is big that high-precision channel estimation becomes one
Challenge.
Summary of the invention
To solve the above problems, the present invention proposes a kind of general channel estimation methods, it to be used for low Precision A/D C and mixing
In the extensive multi-antenna technology system of the broadband mmWave of framework.This method passes through the analog transceiver of optimization design frequency-flat
With the digital combiner of frequency selectivity, make it is suitable for any channel model, and estimated accuracy is higher than conventional method.If deposited
And can get the sparse prior information of channel, the present invention further decreases low Precision A/D C using orthogonal matching pursuit (OMP) and makes
At quantizing noise, to obtain better channel estimating performance.
In order to achieve the above object, the present invention provides the following technical solutions：
Broadband millimeter-wave channel estimation methods under a kind of low precision mixed architecture, including：
Transmitting terminal pilot signal transmitted is to receiver, and wherein sending and receiving end matches extensive antenna using a small amount of radio frequency link
In a period of time, using hybrid digital and analog transceiver technology, receiving end uses low Precision A/D C；
The hybrid digital and analog transceiver technology include analog radio frequency precoding, analog radio frequency combiner and digital baseband
Combiner, the analog radio frequency combiner and digital baseband combiner are connected by radio frequency link；
It is characterized in that：The channel estimation methods on the basis of hardware structure include the following steps：
(1) transmitting terminal pilot signal transmitted simulates precoding to pilot signal optimization design and sends it to receiving end.
Simulate precoding FAmIt calculates according to the following formula：
Wherein, []ijThe element that i-th row of representing matrix, jth arrange；FAmExpression dimension is Nt×NRFtSimulation precoding
Matrix, NtIndicate transmitting antenna number, NRFtIndicate transmitting terminal rf chain number；Indicate the i-th row, the jth of simulation pre-coding matrix
The phase of column element.
(2) receiving end optimization design hypothetical mergers matrix WAm。WAmIt calculates according to the following formula：
Wherein, WAmExpression dimension is Nr×NRFrHypothetical mergers matrix, NrIndicate receiving antenna number, NRFrIndicate receiving end
Rf chain number；Indicate the i-th row of hypothetical mergers matrix, the phase of jth column element.
(3) receiving end selectively carries out OMP process according to the prior information for whether possessing channel sparsity in system,
Obtain selection matrix Pv[k]。
(4) receiving end optimization design corresponds to k-th of subcarrier upper signal channel estimative figure and merges matrixIt is right
It receives signal to be detected, to obtain channel estimation value
Further, selection matrix P in the step (3)v[k] is：
Wherein, eπ(i)(π(i)∈{1,2,…,NrNt) expression dimension be NrNt× 1 a element of π (i) is 1, remaining is first
The vector that element is 0.
Further, selection matrix PvThe determination of [k] depends on the prior information for whether possessing channel sparsity in system.
Such as without the prior information of channel sparsity, i.e. parameter Nv=NrNt, then Pv[k] value is as follows：
If any the prior information of channel sparsity, i.e., known Nv< < NrNt, then N is obtained using OMPvA nonzero channel system
Several positions.At this point, Pv[k] byNonzero element position determine,It is calculated by following formula：
Wherein,Expression dimension is NrNt× 1 condition of sparse channel vector, | | | |l(l=1,2) vector l- model is indicated
Number；Y [k] indicates that dimension is MNRFrReception signal after × 1 low Precision A/D C；∈ indicates that OMP algorithm stops thresholding, Ke Yiqu
Value is the variance yields of equivalent noise in system.
Further, optimal conflation matrix in the step (4)Design criteria can be channel estimation
Mean square error minimizes.
Further, if using minimum mean square error criterion,It can be calculated as follows：
Wherein, k ∈ { 1,2 ..., K } indicates that k-th of subcarrier, K indicate total number of sub-carriers；Indicate k-th of son
Dimension MN on carrier waveRFr×NvOptimal conflation matrix, M indicates the channel estimation number in this method, NvIt indicates k-th
Dimension is N on subcarrierrNt× 1 channel vector projects to the vector component h in angle domainvThe number of nonzero element in [k]；
ηbIndicate distortion factor related with ADC quantizing bit number b；Ω [k] indicates that the dimension on k-th of subcarrier is MNRFr×Nv's
Calculation matrix；Indicate the variance of each element of equivalent noise vector；Indicate the large-scale fading coefficient of channel；It indicates
Dimension is Nv×NvUnit matrix.
Further, the minimum value of M is determined by following formula：
Wherein,Expression rounds up.
Further, the channel vector component h in angle domain is projected tov[k] is calculated as follows：
Wherein, AtExpression dimension is Nt×NtArray response vector composition transmitting dictionary matrix,Representing matrix At's
Conjugation；Indicate Kronecker product；ArExpression dimension is Nr×NrArray response vector composition reception dictionary matrix；H[k]
Indicate that the dimension on k-th of subcarrier is Nr×NtPhysical channel, vec (H [k]) be matrix H [k] vector quantization indicate.
Further, AtIt is expressed as：
Wherein,Expression dimension is Nt× 1 emission array response vector, wherein
Further, ArIt is expressed as：
Wherein,Expression dimension is Nr× 1 emission array response vector, wherein
Further, Ω [k] is expressed as：
Wherein, Φ [k] indicates that dimension is MNRFr×NrNtPilot tone correlation matrix；Pv[k] indicates that dimension is NrNt×Nv's
Selection matrix.
Further, Φ [k] is expressed as：
Wherein, sm[k] (m ∈ { 1,2 ..., M }) indicate the m time it is trained when dimension be NRFr× 1 transmitting pilot vector.
Further,It is calculated as follows：
Wherein,Indicate additive white Gaussian noise (AWGN) variance；P indicates transmitting pilot power.
Further, in step (4)It is calculated as follows：
Wherein,Indicate selection matrixInverse operation.
Compared with prior art, the invention has the advantages that and beneficial effect：
The present invention fully considers influence of the quantization error of low Precision A/D C to precision of channel estimation, will be under low Precision A/D C
Nonlinear estimation problem is converted into Linear Estimation problem.Broad-band channel is estimated, the present invention is modulated using OFDM, thus to each
Narrow-band sub-carriers carry out channel estimation in frequency domain.Under the hybrid structure using a small amount of RF link, design simulation precoding of the present invention
Specifically precoding and hypothetical mergers device are simulated to Whole frequency band optimization design, to each son with hybrid digital/analog combiner
Design digital combiner is separately optimized in carrier wave, and particularly, the statistical property based on equivalent noise is realized in the design of digital combiner,
Wherein equivalent noise contains low Precision A/D C quantizing noise and antenna end AWGN.The letter that the present invention uses mean square error to minimize
Road estimator is suitable for any channel model.If there is and capable of obtaining the sparse prior information of channel, closed in optimization design number
And before device, channel dimensions to be estimated first are reduced to reduce estimation complexity with OMP, while reducing caused by low Precision A/D C
Quantization error.The present invention has a distinct increment to the estimated accuracy of any channel than conventional method.
Detailed description of the invention
Fig. 1 is present system block diagram；
Fig. 2 is under the ADC quantization of 3 bit of receiving end, and channel estimation normalized mean squared error (NMSE) changes with SNR
Curve graph.
When Fig. 3 is fixed SNR, curve graph that channel estimation NMSE changes with ADC precision.
Specific embodiment
Technical solution provided by the invention is described in detail below with reference to specific embodiment, it should be understood that following specific
Embodiment is only illustrative of the invention and is not intended to limit the scope of the invention.
The invention proposes broadband millimeter-wave channel estimation methods under a kind of low precision mixed architecture, transmitting terminal sends pilot tone
Signal is to receiving end, and wherein sending and receiving end matches extensive antenna element using a small amount of radio frequency link, it is therefore desirable to using mixing
Number and analog transceiver technology, receiving end use low Precision A/D C.Hybrid digital includes that analog radio frequency prelists with analog transceiver technology
Code, analog radio frequency combiner and digital baseband combiner, the analog radio frequency combiner and digital baseband combiner are by rf chain
Road is connected.
In order to improve precision of channel estimation, the simulation precoding of optimization design Whole frequency band of the present invention and hypothetical mergers device,
And design digital combiner is separately optimized for each subcarrier, estimate for broad-band channel.Isotropic simulation is designed first
Transceiver, analog transceiver is using full connection phase shifter network, each phase shifter uniform phase distribution；Then optimization design has frequency
The digital combiner of rate selectivity, it is hereby achieved that optimal channel estimation results.For the millimeter wave sparse with multipath
Channel, before optimization design digital combiner, the present invention can find the corresponding element position of channel principal component using OMP,
Further decrease the complexity of channel estimation.The broad-band channel estimator that the present invention provides is suitable for general channel model, is adopting
In hybrid structure multiaerial system with low Precision A/D C, the present invention has the estimated accuracy of any channel than conventional method larger
It is promoted.
As shown in Figure 1, sending and receiving end is hybrid structure, design transmitting terminal first simulates precoding, in Unknown Channel direction
Property information when make pilot signal omnidirectional send.Receiving end design simulation combiner first, in Unknown Channel directivity information
Selection carries out omnidirectional's reception to signal is received.Then, according to the prior information for whether possessing channel sparsity in system, decision is
It is no to need to carry out OMP.If system possesses the prior information of channel sparsity, OMP is carried out first after low Precision A/D C to reduce
Quantizing noise, and reduce channel estimation complexity.Last optimization design digital combiner obtains channel estimation value.By excellent
Change the conflation weight of design frequency flat analog transceiver weight and frequency selectivity, and fully considers that millimeter wave channel can
The sparse characteristic that can possess, channel estimator proposed by the present invention can greatly reduce to be estimated caused by low Precision A/D C quantizing noise
Error is counted, good estimated accuracy can be obtained to any channel model.
Channel estimation methods proposed by the present invention include the following steps：
(1) transmitting terminal pilot signal transmitted simulates precoding to pilot signal optimization design and sends it to receiving end.
Simulate precoding FAmIt calculates according to the following formula：
Wherein, []ijThe element that i-th row of representing matrix, jth arrange；FAmExpression dimension is Nt×NRFtSimulation precoding
Matrix, NtIndicate transmitting antenna number, NRFtIndicate transmitting terminal rf chain number；Indicate the i-th row, the jth of simulation pre-coding matrix
The phase of column element.
(2) receiving end optimization design hypothetical mergers matrix WAm。WAmIt calculates as follows：
Wherein, WAmExpression dimension is Nr×NRFrHypothetical mergers matrix, NrIndicate receiving antenna number, NRFrIndicate receiving end
Rf chain number；Indicate the i-th row of hypothetical mergers matrix, the phase of jth column element.
(3) receiving end selectively carries out OMP process according to the prior information for whether possessing channel sparsity in system,
Obtain selection matrix Pv[k]：
Wherein, eπ(i)(π(i)∈{1,2,…,NrNt) expression dimension be NrNt× 1 a element of π (i) is 1, remaining is first
The vector that element is 0.Selection matrix PvThe form of [k] depends on the prior information for whether possessing channel sparsity in system.Do not have such as
There are the prior information of channel sparsity, i.e. parameter Nv=NrNt, then Pv[k] value is as follows：
If system possesses the prior information of channel sparsity, i.e., known Nv< < NrNt, then N is obtained using OMPvA non-zero
The position of channel coefficients.At this point, Pv[k] byNonzero element position determine,It is calculated by following formula：
Wherein,Expression dimension is NrNt× 1 condition of sparse channel vector, | | | |l(l=1,2) vector l- model is indicated
Number；Y [k] indicates that dimension is MNRFrReception signal after × 1 low Precision A/D C；∈ indicates that OMP algorithm stops thresholding, Ke Yiqu
Value is the variance yields of equivalent noise in system.
(4) receiving end optimization design corresponds to k-th of subcarrier upper signal channel estimative figure and merges matrixIt is right
It receives signal to be detected, to obtain channel estimation value Design criteria can be channel estimation mean square error
Difference minimizes.If using minimum mean square error criterion,It can be calculated as follows：
Wherein, k ∈ { 1,2 ..., K } indicates that k-th of subcarrier, K indicate total number of sub-carriers；Indicate k-th of son
Dimension MN on carrier waveRFr×NvOptimal conflation matrix, M indicates the channel estimation number in this method, NvIt indicates k-th
Dimension on subcarrier is NrNt× 1 channel vector projects to the vector component h in angle domainvNonzero element number in [k]；
ηbIndicate distortion factor related with ADC quantizing bit number b；Ω [k] indicates that the dimension on k-th of subcarrier is MNRFr×Nv's
Calculation matrix；Indicate the variance of each element of equivalent noise vector；Indicate the large-scale fading coefficient of channel；It indicates
Dimension is Nv×NvUnit matrix.The minimum value of M is determined by following formula：
Wherein,Expression rounds up.Project to the channel vector component h in angle domainv[k] is calculated as follows：
Wherein, AtExpression dimension is Nt×NtArray response vector composition transmitting dictionary matrix,Representing matrix At's
Conjugation；Indicate Kronecker product；ArExpression dimension is Nr×NrArray response vector composition reception dictionary matrix；H[k]
Indicate that the dimension on k-th of subcarrier is Nr×NtPhysical channel, vec (H [k]) be matrix H [k] vector quantization indicate.AtIt is fixed
Justice is as follows：
Wherein,Expression dimension is Nt× 1 emission array response vector, whereinArIt is defined as follows：
Wherein,Expression dimension is Nr× 1 emission array response vector, whereinΩ [k] is calculated as follows：
Wherein, Φ [k] indicates that dimension is MNRFr×NrNtPilot tone correlation matrix；Pv[k] indicates that dimension is NrNt×Nv's
Selection matrix.Φ [k] is calculated as follows：
Wherein, sm[k] (m ∈ { 1,2 ..., M }) indicate the m time it is trained when dimension be NRFr× 1 transmitting pilot vector.It is calculated as follows：
Wherein,Indicate additive white Gaussian noise (AWGN) variance；P indicates transmitting pilot power.As follows
It calculates：
Wherein,Indicate selection matrixInverse operation.
As shown in Fig. 2, channel estimation methods ratio LMMSE estimator proposed by the present invention is more accurate under Rayleigh channel, it is special
It is not at high SNR.Under condition of sparse channel, the present invention proposes to use OMP, further improves precision of channel estimation.
As shown in figure 3, NMSE is with ADC quantified precision monotone decreasing to different channels and different estimation methods.Auspicious
Under sharp channel and condition of sparse channel, the precision of channel estimation methods proposed by the present invention will be higher than conventional channel estimation method.This
Outside, the NMSE of channel estimation methods proposed by the present invention has different variation tendencies under different channels with ADC precision：Rayleigh
Under channel, when ADC precision is greater than 4 bit, channel estimation errors tend to be constant；Under condition of sparse channel, when ADC precision is greater than 2 ratios
When special, precision of channel estimation tends to be fixed.
The technical means disclosed in the embodiments of the present invention is not limited only to technological means disclosed in above embodiment, further includes
Technical solution consisting of any combination of the above technical features.It should be pointed out that for those skilled in the art
For, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also considered as
Protection scope of the present invention.
Claims (10)
1. broadband millimeter-wave channel estimation methods under a kind of low precision mixed architecture, which is characterized in that the method includes following
Step：(1) transmitting terminal pilot signal transmitted simulates precoding to pilot signal optimization design and sends it to receiving end, mould
Quasi- precoding FAmIt calculates according to the following formula：
Wherein, []ijThe element that i-th row of representing matrix, jth arrange；FAmExpression dimension is Nt×NRFtSimulation pre-coding matrix,
NtIndicate transmitting antenna number, NRFtIndicate transmitting terminal rf chain number；Indicate the i-th row, the jth column member of simulation pre-coding matrix
The phase of element；
(2) receiving end optimization design hypothetical mergers matrix WAm,WAmIt calculates according to the following formula：
Wherein, WAmExpression dimension is Nr×NRFrHypothetical mergers matrix, NrIndicate receiving antenna number, NRFrIndicate receiving end radio frequency
Number of links；Indicate the i-th row of hypothetical mergers matrix, the phase of jth column element；
(3) receiving end selectively carries out OMP process, obtains according to the prior information for whether possessing channel sparsity in system
Selection matrix Pv[k]；
(4) receiving end optimization design corresponds to k-th of subcarrier upper signal channel estimative figure and merges matrixDocking is collected mail
It number is detected, to obtain channel estimation value
2. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 1, which is characterized in that
Selection matrix P in the step (3)v[k] is：
Wherein, eπ(i)(π(i)∈{1,2,…,NrNt) expression dimension be NrNt× 1 a element of π (i) is 1, remaining element is
0 vector.
3. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 2, which is characterized in that
Selection matrix PvThe determination of [k] depends on the prior information for whether possessing channel sparsity in system, such as sparse without channel
The prior information of property, i.e. parameter Nv=NrNt, then Pv[k] value is as follows：
If any the prior information of channel sparsity, i.e., known Nv< < NrNt, then N is obtained using OMPvThe position of a non-zero channel coefficients
It sets, at this point, Pv[k] byNonzero element position determine,It is calculated by following formula：
Wherein,Expression dimension is NrNt× 1 condition of sparse channel vector, | | | |l(l=1,2) vector l- norm is indicated；y
[k] indicates that dimension is MNRFrReception signal after × 1 low Precision A/D C；∈ indicates that OMP algorithm stops thresholding, can be with value
The variance yields of equivalent noise in system.
4. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 3, which is characterized in that institute
State optimal conflation matrix in step (4)Design criteria can for channel estimation mean square error minimize；If making
With minimum mean square error criterion,It can be calculated as follows：
Wherein, k ∈ { 1,2 ..., K } indicates that k-th of subcarrier, K indicate total number of sub-carriers；Indicate k-th of subcarrier
On dimension MNRFr×NvOptimal conflation matrix, M indicates the channel estimation number in this method, NvIndicate that k-th of son carries
Dimension is N on waverNt× 1 channel vector projects to the vector component h in angle domainvThe number of nonzero element in [k]；ηbTable
Show distortion factor related with ADC quantizing bit number b；Ω [k] indicates that the dimension on k-th of subcarrier is MNRFr×NvMeasurement
Matrix；Indicate the variance of each element of equivalent noise vector；Indicate the large-scale fading coefficient of channel；Indicate dimension
For Nv×NvUnit matrix.
5. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 4, which is characterized in that
The minimum value of M is determined by following formula：
Wherein,Expression rounds up；
Project to the channel vector component h in angle domainv[k] is calculated as follows：
Wherein, AtExpression dimension is Nt×NtArray response vector composition transmitting dictionary matrix,Representing matrix AtConjugation；Indicate Kronecker product；ArExpression dimension is Nr×NrArray response vector composition reception dictionary matrix；H [k] indicates the
Dimension on k subcarrier is Nr×NtPhysical channel, vec (H [k]) be matrix H [k] vector quantization indicate.
6. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 5, which is characterized in that
The transmitting dictionary matrix is defined as follows：
AtIt is expressed as：
Wherein,Expression dimension is Nt× 1 emission array response vector, wherein
The reception dictionary matrix is defined as follows：
ArIt is expressed as：
Wherein,Expression dimension is Nr× 1 emission array response vector, wherein
7. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 6, which is characterized in that
The calculation matrix Ω [k] is expressed as：
Wherein, Φ [k] indicates that dimension is MNRFr×NrNtPilot tone correlation matrix；Pv[k] indicates that dimension is NrNt×NvSelection
Matrix.
8. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 7, which is characterized in that
The pilot tone correlation matrix Φ [k] is expressed as：
Wherein, sm[k] (m ∈ { 1,2 ..., M }) indicate the m time it is trained when dimension be NRFr× 1 transmitting pilot vector.
9. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 8, which is characterized in that
The variance of each element of equivalent noise vector is calculated as follows：
It is calculated as follows：
Wherein,Indicate additive white Gaussian noise (AWGN) variance；P indicates transmitting pilot power.
10. broadband millimeter-wave channel estimation methods under low precision mixed architecture according to claim 9, which is characterized in that
Channel estimation value in step (4)It is calculated as follows：
Wherein,Indicate selection matrixInverse operation.
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| CN112187323A (en) * | 2020-09-29 | 2021-01-05 | 国网江苏省电力有限公司丹阳市供电分公司 | IRS-based large-scale MIMO (multiple input multiple output) cascade channel estimation method under mixed low-precision architecture |
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