U.S. patent application number 16/234134 was filed with the patent office on 2020-07-02 for millimeter wave channel estimation method.
This patent application is currently assigned to INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE. The applicant listed for this patent is INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE. Invention is credited to Kuo Chen HO, Hsin Yuan LO, Shang-Ho TSAI.
Application Number | 20200213162 16/234134 |
Document ID | / |
Family ID | 71124254 |
Filed Date | 2020-07-02 |
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United States Patent
Application |
20200213162 |
Kind Code |
A1 |
LO; Hsin Yuan ; et
al. |
July 2, 2020 |
MILLIMETER WAVE CHANNEL ESTIMATION METHOD
Abstract
A millimeter wave channel estimation method comprises sending
signals through a millimeter wave channel according to a first
beamforming matrix, performing a channel estimation on the
millimeter wave to generate a first measured matrix, and estimating
and obtaining at least one angle of departure of the millimeter
wave channel according to the first measured matrix and an angle
compressive sensing matrix. The first beamforming matrix comprises
a plurality of first beamforming vectors, and the first beamforming
vectors respectively corresponds to a plurality of first
beamforming patterns. The first measured matrix comprises a
plurality of first measured parameters respectively corresponding
to the first beamforming vectors.
Inventors: |
LO; Hsin Yuan; (Taoyuan
City, TW) ; TSAI; Shang-Ho; (Hsinchu City, TW)
; HO; Kuo Chen; (Hsinchu County, TW) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE |
Hsinchu |
|
TW |
|
|
Assignee: |
INDUSTRIAL TECHNOLOGY RESEARCH
INSTITUTE
Hsinchu
TW
|
Family ID: |
71124254 |
Appl. No.: |
16/234134 |
Filed: |
December 27, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04B 7/0617 20130101;
H04B 7/0663 20130101; H04L 25/0246 20130101 |
International
Class: |
H04L 25/02 20060101
H04L025/02; H04B 7/06 20060101 H04B007/06 |
Claims
1. A millimeter wave channel estimation method, comprising: sending
signals through a millimeter wave channel according to a first
beamforming matrix, with the first beamforming matrix comprising a
plurality of first beamforming vectors, and the first beamforming
vectors respectively corresponding to a plurality of first
beamforming patterns; performing a channel estimation on the
millimeter wave channel to generate a first measured matrix, with
the first measured matrix comprising a plurality of first measured
parameters respectively corresponding to the first beamforming
vectors; and estimating and obtaining at least one angle of
departure of the millimeter wave channel according to the first
measured matrix and an angle compressive sensing matrix; wherein
the millimeter wave channel estimation method further comprising
generating the first beamforming matrix, wherein generating the
first beamforming matrix comprises: creating a basic compressive
sensing matrix; performing a least squares estimation on the basic
compressive sensing matrix to obtain a first least squares matrix;
performing normalization on the first least squares matrix to
obtain a normalized matrix; performing another least squares
estimation on the normalized matrix to obtain a second least
squares matrix; and multiplying the second least squares matrix by
an inverse matrix of an angle matrix to obtain the first
beamforming matrix.
2. The millimeter wave channel estimation method according to claim
1, further comprising: sending signals through the millimeter wave
channel according to a second beamforming matrix, with the second
beamforming matrix comprising a plurality of second beamforming
vectors, and the second beamforming vectors respectively
corresponding to a plurality of second beamforming patterns;
performing another channel estimation on the millimeter wave
channel to generate a second measured matrix, with the second
measured matrix comprising a plurality of second measured
parameters respectively corresponding to the second beamforming
vectors; and estimating and obtaining at least one signal gain
corresponding to said at least one angle of departure according to
the second measured matrix, a gain compressive sensing matrix and
said at least one angle of departure.
3. (canceled)
4. The millimeter wave channel estimation method according to claim
2, further comprising generating the second beamforming matrix,
wherein generating the second beamforming matrix comprises:
creating a basic compressive sensing matrix; performing a least
squares estimation on the basic compressive sensing matrix to
obtain a least squares matrix; and multiplying the least squares
matrix by an inverse matrix of an angle matrix to obtain the second
beamforming matrix.
5. The millimeter wave channel estimation method according to claim
1, wherein the basic compressive sensing matrix is a Gabor
frame.
6. The millimeter wave channel estimation method according to claim
4, wherein the basic compressive sensing matrix is a Gabor
frame.
7. A millimeter wave channel estimation method, comprising:
receiving signals from a millimeter wave channel according to a
first beamforming matrix to generate a first measured matrix; and
estimating and obtaining at least one angle of arrival of the
millimeter wave channel according to the first measured matrix and
an angle compressive sensing matrix; wherein the first beamforming
matrix comprises a plurality of first beamforming vectors
respectively corresponding to a plurality of first beamforming
patterns, and the first measured matrix comprises a plurality of
first measured parameters respectively corresponding to the first
beamforming vectors; wherein the millimeter wave channel estimation
method further comprising generating the first beamforming matrix,
wherein the step of generating the first beamforming matrix
comprises: creating a basic compressive sensing matrix; performing
a least squares estimation on the basic compressive sensing matrix
to obtain a first least squares matrix; performing normalization on
the first least squares matrix to obtain a normalized matrix;
performing another least squares estimation on the normalized
matrix to obtain a second least squares matrix; and multiplying the
second least squares matrix by an inverse matrix of an angle matrix
to obtain the first beamforming matrix.
8. The millimeter wave channel estimation method according to claim
7, further comprising: receiving signals from the millimeter wave
channel according to a second beamforming matrix to generate a
second measured matrix; and estimating and obtaining at least one
signal gain corresponding to said at least one angle of arrival
according to the second measured matrix, a gain compressive sensing
matrix and said at least one angle of arrival; wherein the second
beamforming matrix comprises a plurality of second beamforming
vectors respectively corresponding to a plurality of second
beamforming patterns, and the second measured matrix comprises a
plurality of second measured parameters respectively corresponding
to the second beamforming vectors.
9. (canceled)
10. The millimeter wave channel estimation method according to
claim 8, further comprising generating the second beamforming
matrix, wherein the step of generating the second beamforming
matrix comprises: creating a basic compressive sensing matrix;
performing a least squares estimation on the basic compressive
sensing matrix to obtain a least squares matrix; and multiplying
the least squares matrix by an inverse matrix of an angle matrix to
obtain the second beamforming matrix.
11. The millimeter wave channel estimation method according to
claim 1, wherein the basic compressive sensing matrix is a Gabor
frame.
12. The millimeter wave channel estimation method according to
claim 10, wherein the basic compressive sensing matrix is a Gabor
frame.
Description
BACKGROUND
1. Technical Field
[0001] This disclosure relates to a channel estimation method, and
particularly to a millimeter wave channel estimation method.
2. Related Art
[0002] With the development of wireless communication technology,
in order to meet the requirements of higher speed and wider
bandwidth, the fifth generation mobile communication standard has
been established. However, since the low and medium frequency bands
in the current spectrum have been used by other wireless
communication technologies, the application of millimeter waves in
the high frequency band becomes the focus of recent and future
wireless communication technology.
[0003] At present, the millimeter wave channel estimation is
implemented by exhaustive search. The implementation of exhaustive
search comprises sending beams at regular intervals of angle of
resolution, receiving the beams so as to generate measurement data
by the receiving terminal, and using the measurement data to
calculate and estimate the channel. However, as the requirements
for resolution increase, the number of times of measurements and
the quantity of calculation of this method also increase
significantly, resulting in a large amount of time consumption.
SUMMARY
[0004] According to an embodiment of this disclosure, a millimeter
wave channel estimation method comprises sending signals through a
millimeter wave channel according to a first beamforming matrix,
performing a channel estimation on the millimeter wave to generate
a first measured matrix, and estimating and obtaining at least one
angle of departure of the millimeter wave channel according to the
first measured matrix and an angle compressive sensing matrix. The
first beamforming matrix comprises a plurality of first beamforming
vectors, and the first beamforming vectors respectively corresponds
to a plurality of first beamforming patterns. The first measured
matrix comprises a plurality of first measured parameters
respectively corresponding to the first beamforming vectors.
[0005] According to an embodiment of this disclosure, a millimeter
wave channel estimation method comprises receiving signals from a
millimeter wave channel according to a first beamforming matrix to
generate a first measured matrix, and estimating and obtaining at
least one angle of arrival of the millimeter wave channel according
to the first measured matrix and an angle compressive sensing
matrix. The first beamforming matrix comprises a plurality of first
beamforming vectors respectively corresponding to a plurality of
first beamforming patterns, and the first measured matrix comprises
a plurality of first measured parameters respectively corresponding
to the first beamforming vectors.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] FIG. 1 is a flowchart of a millimeter wave channel
estimation method according to an exemplary embodiment of this
disclosure;
[0007] FIG. 2 is a flowchart of the step of generating a first
beamforming matrix in a millimeter wave channel estimation method
according to an exemplary embodiment of this disclosure;
[0008] FIG. 3 is a functional block diagram of a communication
system according to an exemplary embodiment of this disclosure;
[0009] FIG. 4 is a flowchart of the step of generating the measured
matrix in a millimeter wave channel estimation method according to
an exemplary embodiment of this disclosure;
[0010] FIG. 5 is a flowchart of a millimeter wave channel
estimation method according to another exemplary embodiment of this
disclosure; and
[0011] FIG. 6 is a flowchart of the step of generating a second
beamforming matrix in a millimeter wave channel estimation method
according to another exemplary embodiment of this disclosure.
DETAILED DESCRIPTION
[0012] In the following detailed description, for purposes of
explanation, numerous specific details are set forth in order to
provide a thorough understanding of the disclosed embodiments. It
will be apparent, however, that one or more embodiments may be
practiced without these specific details. In other instances,
well-known structures and devices are schematically shown in order
to simplify the drawings.
[0013] This disclosure provides a millimeter wave channel
estimation method applied to a communication system which transmits
wireless signals through a millimeter wave channel. Please refer to
FIG. 1 which is a flowchart of a millimeter wave channel estimation
method according to an exemplary embodiment of this disclosure. In
step S11, the communication system, as described above for
transmitting wireless signals through the millimeter wave channel,
generates a first beamforming matrix, with the first beamforming
matrix comprising first beamforming vectors which respectively
correspond to first beamforming patterns. It should be noted that
the step S11 of generating the first beamforming matrix is an
optional step; that is, in other exemplary embodiments, the first
beamforming matrix can be pre-stored in the communication system,
so that the communication system can performs steps S12 and S13 as
follows without step S11 during the implementation of a millimeter
wave channel estimation method.
[0014] In step S12, the communication system generates a first
measured matrix associated with the millimeter wave channel
according to the first beamforming matrix generated in step S11.
The first measured matrix comprises first measured parameters which
respectively correspond to the first beamforming vectors in the
first beamforming matrix. More particularly, the first measured
parameters in the first measured matrix can have a one-to-one
relationship with the first beamforming vectors in the first
beamforming matrix. In an exemplary embodiment, the step of
generating the first measured matrix associated with the millimeter
wave channel according to the first beamforming matrix can be
implemented by the communication system by sending signals through
the millimeter wave channel according to the first beamforming
matrix, and performing a channel estimation to generate the first
measured matrix; in another exemplary embodiment, the step can be
implemented by receiving signals from the millimeter wave channel
according to the first beamforming matrix so as to generate the
first measured matrix. The operating environment for these two
exemplary embodiments is described in details later.
[0015] In step S13, the communication system estimate and obtain
the estimation result of the angle characteristic of the millimeter
wave channel according to the first measured matrix and an angle
compressive sensing matrix. The angle compressive sensing matrix
comprises the aforementioned first beamforming matrix and an angle
matrix, wherein the angle matrix comprises angle parameters each of
which has a base number and an exponent. In an exemplary
embodiment, the base number of every angle parameter has is a
mathematical constant e, and the exponents of these angle parameter
respectively involve different angle values. For example, the angle
parameters can be represented by e.sup.jkd sin.theta..sup.i.
[0016] Please refer to FIG. 2 for particularly describing the step
of generating the first beamforming matrix (i.e. step S11 of FIG.
1). FIG. 2 is a flowchart of the step of generating a first
beamforming matrix in a millimeter wave channel estimation method
according to an exemplary embodiment of this disclosure. In step
S111, the communication system creates a basic compressive sensing
matrix. For example, the basic compressive sensing matrix is a
Gabor frame which is a m*m2 matrix. More particularly, m can be a
prime number of 5 or more; that is, the dimension of a Gabor frame
can be greater than 5*25. In an exemplary embodiment, the Gabor
frame can be represented by an exponential function, wherein the
base number of the exponential function is a mathematical constant
e, and its exponent involves a constant m which associated with the
number of times the estimation is to be performed in the subsequent
estimation step. For example, the basic compressive sensing matrix
A.sub.G can be represented by the following equation:
A G ( i 1 + 1 , ( i 2 + 1 ) + m ( i 3 + 1 ) ) = e j 2 .pi. ( ( i 1
- i 3 ) 3 + i 1 i 2 ) m , ##EQU00001##
wherein i.sub.1, i.sub.2, i.sub.3=0, 1, . . . , m-1; that is,
i.sub.1 is 0, 1, . . . , m-2 or m-1; i.sub.2 is 0, 1, . . . , m-2
or m-1; and i.sub.3 is 0, 1, . . . , m-2 or m-1.
[0017] In step S113, the communication system performs a least
squares estimation on the basic compressive sensing matrix to
obtain a first least squares matrix. More specifically, the
communication system designs a precoding matrix F, calculates the
matrix product of the conjugate transpose of the angle matrix
A.sub..theta. and the precoding matrix F, and then obtains the
matrix solution F.sub.opt of the precoding matrix for minimizing
the sum of squares of the difference between the transpose of the
basic compressive sensing matrix A.sub.G and the above matrix
product. Another matrix product of the transpose of the matrix
solution F.sub.opt and the conjugate transpose of the angle matrix
A.sub..theta. is considered to be the first least squares matrix
A.sub.LS. The calculation procedure of step S113 can be exemplarily
shown in the following equation:
F.sub.opt=(A.sub..theta.A.sub..theta..sup.H).sup.-1A.sub..theta.A.sub.G.-
sup.T; let F.sub.opt.sup.TA*.sub..theta.=A.sub.LS.
[0018] In step S115, the communication system performs
normalization on the first least squares matrix obtained in step
S113 to obtain a normalized matrix, wherein the detailed
calculation of the normalization can be understood by those having
ordinary skills in the art, and is not described herein. In step
S117, the communication system performs another least squares
estimation on the normalized matrix to obtain a second least
squares matrix, wherein the detailed calculation of the least
squares estimation is the same as or similar to that of step S113
as previously mentioned, and is not repeated. In step S119, the
communication system multiplies the second least squares matrix by
the inverse matrix of the angle matrix to obtain the first
beamforming matrix.
[0019] As aforementioned, the millimeter wave channel estimation
method provided in this disclosure is applied to the communication
system transmitting wireless signals through a millimeter wave
channel. More particularly, please refer to FIGS. 1, 3 and 4 for
illustrating one exemplary embodiment of the communication system
and the details of the millimeter wave channel estimation method.
FIG. 3 is a functional block diagram of a communication system
according to an exemplary embodiment of this disclosure, and FIG. 4
is a flowchart of the step of generating the measured matrix in a
millimeter wave channel estimation method according to an exemplary
embodiment of this disclosure.
[0020] As shown in FIG. 3, the communication system 1 comprises a
base station 10 and a user terminal 20 which transmit wireless
signals to each other through a millimeter wave channel 30. The
base station 10 comprises a baseband circuit 101, a radio frequency
chain 103 and signal transceivers 105. Each signal transceiver 105
comprises a phase modulation circuit 1051, an impedance modulation
circuit 1053 and an antenna 1055. The base station 10 can also
comprise a signal generator and a precoder such as a computer, or
be externally connected with a generator and a precoder in the
communication system 1. The user terminal 20 can receive the
wireless signals from the base station 10 through the millimeter
wave channel 30 so as to download data, and can also send wireless
signals to the base station 10 through the millimeter wave channel
30 so as to upload data. For example, the user terminal 20 is a
mobile phone, a notebook computer or other user device with a
wireless signal transceiver, which is not limited in this
disclosure.
[0021] In an exemplary embodiment, the estimation of the millimeter
wave channel 30 can be implemented by the communication system 1 by
using the base station 10 to send wireless signals and using the
user terminal 20 to receive them. This implementation includes
steps S12 and S13, or steps S11-S13 in FIG. 1 as aforementioned. In
step S11 in this exemplary embodiment, the communication system 1
generates the first beamforming matrix which comprises first
beamforming vectors by the precoder of the base station 10. The
details of this generating step are the same as or similar to those
in the aforementioned exemplary embodiments, and are not repeated
herein.
[0022] In step S12, the communication system 1 generates the first
measured matrix according to the first beamforming matrix. More
particularly, the communication system 1 generates and emits a beam
according to one of the first beamforming vectors generated by the
base station 10 in step S11. For example, the base station 10 can
generate the beam having a radiation field of the first beamforming
pattern corresponding to said one of the first beamforming vectors.
More specifically, each of the first beamforming vectors comprises
phase modulation values respectively for the antennas 1055 and
impedance modulation values respectively for the antennas 1055. The
base station 10 can control the phase modulation circuit 1051 and
the impedance modulation circuit 1053 of each signal transceiver
105 according to the selected first beamforming vector, so as to
modulate the phase and amplitude of the electromagnetic wave
(wireless signal) emitted by a respectively one of the antennas
1055. The electromagnetic waves respectively emitted by the
antennas 1055 together form the radiation field of the first
beamforming pattern corresponding to the selected first beamforming
vector. The communication system 1 receives the beam with the
radiation field of the first beamforming pattern to generate a
first measured parameter. This first measured parameter corresponds
to the first beamforming vector as aforementioned for generating
the beam, and serves one of parameters in the first measured
matrix.
[0023] In this exemplary embodiment, the base station 10 serves as
the terminal of sending wireless signals, and the user terminal 20
serves as the terminal of receiving the wireless signals. More
specifically, step S12 in FIG. 1 can comprise steps S121, S123,
S125, S127 and S129 as shown in FIG. 4. In step S121, the base
station 10 generates and emits a beam according to one of the
beamforming vectors, such as the first one, in the beamforming
matrix (the aforementioned first beamforming matrix). In step S123,
the user terminal 20 receives the beam from the base station 10
through the millimeter wave channel 30, so as to generate the
corresponding measured parameter. In step S125, the base station 10
determines whether the beamforming vector used last time is the
last one in the beamforming matrix. When the determining result is
no, as shown in the description of step S127, the base station 10
generates and emits another beam according to the beamforming
vector next to that used last time in the beamforming matrix, and
then the user terminal 20 preformed step S123; if the determining
result is yes, as shown in the description of step S129, the user
terminal 20 integrates the generated measured parameters into the
measured matrix. For example, if the beamforming matrix has m of
beamforming vectors, the receiving terminal of wireless signals can
correspondingly generate m of measured parameters so as to from a
m*1 measured matrix (i.e. first measured matrix) after the steps
described above.
[0024] In sum, the communication system 1 can use the base station
10 to generate beams multiple times respectively according to the
beamforming vectors, and use the user terminal 20 to receive these
beams to respectively generate measured parameters and to integrate
these measured parameters into a measured matrix. The exemplary
embodiment of FIG. 4 exemplarily illustrates that the base station
10 generates beams sequentially according to the beamforming
vectors in the beamforming matrix; however, this disclosure does
not limit the order in which the base station uses beamforming
vectors is equivalent to the order in the matrix.
[0025] In step S13, the user terminal 20 obtains the estimation
result of the angle characteristic of the millimeter wave channel
30 according to the first measured matrix and the angle compressive
sensing matrix. In this exemplary embodiment, the estimation result
of the angle characteristic comprises at least one angle of
departure (AOD). More specifically, a compressive sensing recovery
algorithm is stored in the user terminal 20, such as the following
equation:
y=.PHI..alpha.
[0026] y indicates the measured matrix; .PHI. indicates the angle
compressive sensing matrix; .alpha. indicates the desired
estimation result of the angle characteristic. As aforementioned in
step S119 of generating the first beamforming matrix in FIG. 2, the
first beamforming matrix is obtained by multiplying the angle
compressive sensing matrix (i.e. the aforementioned second least
squares matrix) by the inverse matrix of the angle matrix. In other
words, the millimeter wave channel estimation method provided in
this disclosure separates the angle compressive sensing matrix as
the first beamforming matrix and the angle matrix, as shown in the
following equation:
y = .phi..alpha. = [ f 1 f 2 f m ] T [ e jkd sin .theta. i ] [
.alpha. ] . ##EQU00002##
[0027] By the above recovery algorithm, the estimation result of
the angle characteristic can be calculated using the first
beamforming matrix generated in step S11, the first measured matrix
obtained in step S12 and the known angle matrix. The estimation
result of the angle characteristic can comprise angle estimated
parameters which have a one-to-one relationship with the angle
parameters in the angle matrix, and each of these angle estimated
parameters can indicate whether there is a wireless signal (beam)
is received at the angle represented by the respective one of the
angle parameters, or indicate whether the strength of the wireless
signal received at the angle represented by the respective one of
the angle parameters is larger than the predetermined threshold.
For example, when the strength of the wireless signal which passes
through the millimeter wave channel and is then received at a
specific angle by the signal receiving terminal is not larger than
the predetermined threshold, the angle estimated parameter
corresponding to the specific angle is zero; when the strength of
the wireless signal which passes through the millimeter wave
channel and is then received at a specific angle by the signal
receiving terminal is larger than the predetermined threshold, the
angle estimated parameter corresponding to the specific angle is
not zero.
[0028] In comparison with the conventional exhaustive search
method, the number of times of measurements in the millimeter wave
channel estimation method of this disclosure depends on the
parameter design of the beamforming matrix, and might not increase
as the resolution of wireless communication increases; therefore,
it may avoid a large amount of measurement data and calculation
time due to high-resolution requirements, and then achieve rapid
millimeter wave channel estimation.
[0029] In another exemplary embodiment, the estimation of the
millimeter wave channel 30 can be implemented by the communication
system 1 by using the user terminal 20 to send wireless signals and
using the base station 10 to receive them. This implementation
includes steps S12 and S13, or steps S11-S13 in FIG. 1 as
aforementioned. In step S11 in this exemplary embodiment, the
communication system 1 generates the first beamforming matrix which
comprises first beamforming vectors by the base station 10. The
details of this generating step are the same as or similar to those
in the aforementioned exemplary embodiments, and are not repeated
herein.
[0030] In step S12, the communication system 1 generates the first
measured matrix according to the first beamforming matrix first
measured matrix. More particularly, the communication system 1 uses
the user terminal 20 to send signals, and then uses the base
station 10 to receive the signals through one of the first
beamforming vectors generated in step S11, so as to generate the
corresponding first measured parameter which serves as one of
parameters in the first measured matrix. In this exemplary
embodiment, the base station 10 can receive signals multiple times
respectively through the first beamforming vectors, so as to
generate the first measured parameters respectively corresponding
to the first beamforming vectors. For example, the base station 10
can receive the signals sequentially according to the first
beamforming vectors in the first beamforming matrix, which is
similar but not limited to the procedure shown in FIG. 4. The base
station 10 can integrate the generated first measured parameters
into the first measured matrix.
[0031] In step S13, the base station 10 can obtain the estimation
result of the angle characteristic of the millimeter wave channel
30 according to the first measured matrix, the angle compressive
sensing matrix, the first beamforming matrix and the angle matrix.
The estimation result of the angle characteristic comprises at
least one angle of arrival (AOA). A compressive sensing recovery
algorithm is stored in the base station 10 wherein the equation and
the detailed calculation of the compressive sensing recovery
algorithm are similar to those described in the preceding exemplary
embodiment, and are not repeated. In this exemplary embodiment, the
base station 10 has both functions of generating beamforming
vectors and calculating angle characteristics.
[0032] In yet another exemplary embodiment, each of the base
station 10 and the user terminal 20 of the communication system 1
has the compressive sensing recovery algorithm stored therein. By
the millimeter wave channel estimation method as described in any
one of the above exemplary embodiments, whether the user terminal
performs uploading or downloading, the communication system 1 can
estimate the millimeter wave channel 30.
[0033] Please refer to FIGS. 3, 5 and 6, wherein FIG. 5 is a
flowchart of a millimeter wave channel estimation method according
to another exemplary embodiment of this disclosure, and FIG. 6 is a
flowchart of the step of generating a second beamforming matrix in
a millimeter wave channel estimation method according to another
exemplary embodiment of this disclosure. The millimeter wave
channel estimation method as shown in FIG. 5 is also applied to the
communication system 1 as shown in FIG. 3, so the implementation of
the millimeter wave channel estimation method in FIG. 5 is
exemplarily described below by the communication system 1. In steps
S21-S23, the communication system 1 generates a first beamforming
matrix by the base station 10, generates a first measured matrix
associated with the millimeter wave channel 30 according to the
first beamforming matrix, and obtains the estimation result of the
angle characteristic of the millimeter wave channel 30 according to
the first measured matrix and an angle compressive sensing matrix.
These steps are the same as or similar to steps S11-S13 in the
aforementioned exemplary embodiment of FIG. 1, so the detailed
implementation of each step is not repeated.
[0034] In the exemplary embodiment as shown in FIG. 5, after
obtaining the estimation result of the angle characteristic of the
millimeter wave channel 30, the communication system 1 further
performs another channel estimation on the millimeter wave channel
30 using the second beamforming matrix. In step S24, the
communication system 1 generates a second beamforming matrix by the
base station 10, wherein the second beamforming matrix comprises
second beamforming vectors. More particularly, FIG. 6 illustrates
an implementation of generating the second beamforming matrix. In
step S241, the base station 10 creates a basic compressive sensing
matrix, such as a Gabor frame. In step S243, the base station 10
performs a least squares estimation on the basic compressive
sensing matrix to obtain a least squares matrix. The above steps
S241 and S243 are the same as or similar to steps S111 and S113 in
the aforementioned exemplary embodiment of FIG. 2, so their details
are not repeated. In step S245, the base station 10 multiplies the
least squares matrix by the inverse matrix of the angle matrix (as
mentioned in the aforementioned exemplary embodiment) to obtain the
second beamforming matrix.
[0035] It should be noted that, FIG. 5 just exemplarily illustrates
step S24 of generating the second beamforming matrix after step S23
of obtaining the estimation result of the angle characteristic;
however, in other embodiments, step S24 can be performed before or
after any one of steps S21-S23, which is not limited in this
disclosure. Moreover, as described previously, steps S241 and S243
of generating the second beamforming matrix are the same as or
similar to steps S111 and 113 of generating the first beamforming
matrix; therefore, in an exemplary embodiment, the base station 10
can generate the second beamforming matrix while it performs step
S21 to generate the first beamforming matrix. In addition, both of
the aforementioned step S21 and step S24 are optional steps, so in
other exemplary embodiments, the first and second beamforming
matrices can be pre-stored in the communication system 1, and the
communication system 1 can perform steps S22 and S23 as above and
then steps S25 and S26 as below without steps S21 and S24 during
the implementation of a millimeter wave channel estimation
method.
[0036] After obtaining the second beamforming matrix, the
communication system 1 can estimate another characteristic of the
millimeter wave channel 30 by this beamforming matrix, as shown in
steps S25 and S26 in FIG. 5. In step S25, the communication system
1 generates a second measured matrix associated with the millimeter
wave channel 30 according to the second beamforming matrix, wherein
the second measured matrix comprises second measured parameters
which respectively correspond the second beamforming vectors. More
particularly, the second measured parameters in the second measured
matrix can have a one-to-one relationship with the second
beamforming vectors in the second beamforming matrix. The detailed
implementation of step S25 is similar to that of generating the
first measured matrix according to the first beamforming matrix as
aforementioned, so is not repeated herein.
[0037] In step S26, the communication system 1 obtains the
estimation result of the gain characteristic of the millimeter wave
channel 30 according to the second measured matrix, a gain
compressive sensing matrix and the estimation result of the angle
characteristic obtained in step S23. The gain compressive sensing
matrix comprises the second beamforming matrix and the angle
matrix. More particularly, the communication system 1 can obtain
the estimation result of the gain characteristic by the compressive
sensing recovery algorithm as described in the above exemplary
embodiment; that is, the gain corresponding to the estimation
result of the angle characteristic can be obtained according to the
estimation result of the angle characteristic.
[0038] In the exemplary embodiment of sending signals according to
the second beamforming matrix and performing the channel
estimation, the estimation result of the gain characteristic
obtained by the communication system 1 comprises at least one
signal gain which corresponds to said at least one angle of
departure obtained in the first stage of the estimation (i.e. steps
S21-S23). In the exemplary embodiment of receiving signals
according to the second beamforming matrix and performing the
channel estimation, the estimation result of the gain
characteristic obtained by the communication system 1 comprises at
least one signal gain which corresponds to said at least one angle
of arrival obtained in the first stage of the estimation. By
performing the aforementioned steps S21-S26, the communication
system 1 can obtain the estimated value of the angle of departure
or the angle of arrival and the estimated value of the
corresponding gain respectively through two stages of estimation,
so that an accurate millimeter wave channel estimation may be
achieved.
[0039] In view of the above description, the millimeter wave
channel estimation method provided in this disclosure generates
beamforming vectors based on the theory of compressive sensing,
generates measured parameters associated with a millimeter wave
channel according to these beamforming vectors, and obtains the
estimation result of the angle characteristic of the millimeter
wave channel from the measured parameters, the beamforming vectors
and angle parameters by compressive sensing recovery technique. The
millimeter wave channel estimation method in this disclosure may
have no need for producing the feedback of the measurement data,
and may estimate the characteristic parameters of the channel by a
small number of measurement times so as to achieve rapid millimeter
wave channel estimation and to improve the quality of the
subsequent transmission of signals/data. More particularly, in
comparison with estimating all characteristic parameters of a
channel in a single stage, estimating angle characteristic
parameters and gain characteristic parameters respectively in two
stage may obtain the more accurate estimation results.
* * * * *