CN111385006A - Millimeter wave channel estimation method - Google Patents
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Abstract
A millimeter wave channel estimation method includes performing channel measurement on a millimeter wave channel to generate a first measurement matrix according to a first beamforming matrix, and estimating at least one angle of transmission (AOD) of the millimeter wave channel according to the first measurement matrix and an angle compressed sensing matrix. The first beamforming matrix comprises a plurality of first beamforming vectors, the plurality of first beamforming vectors respectively correspond to a plurality of first beamforming modes, and the first measurement matrix comprises a plurality of first measurement parameters respectively corresponding to the plurality of first beamforming vectors.
Description
Technical Field
The present invention relates to a channel estimation method, and more particularly, to a millimeter wave channel estimation method.
Background
With the development of wireless communication technology, a fifth generation mobile communication standard is established to meet the requirements of higher speed and larger bandwidth. However, nowadays, the middle and low frequency bands in the spectrum are mostly used by other wireless communication technologies, so the millimeter wave application of the high frequency band becomes the key point of the future wireless communication technology.
Currently, the millimeter wave channel estimation is performed by using an extreme Search method (explicit Search). The exhaustive search method is performed by transmitting a beam for each analysis angle and receiving the beam by the receiving end to generate measurement data, which is then calculated to estimate the channel. However, as the requirement for resolution is increased, the number of measurements and the amount of calculation are also increased, which results in a large amount of time and resources.
Disclosure of Invention
In view of the foregoing, the present invention provides a millimeter wave channel estimation method.
The millimeter wave channel estimation method according to an embodiment of the present invention includes transmitting signals via a millimeter wave channel according to a first beamforming matrix, performing channel measurement on the millimeter wave channel to generate a first measurement matrix, and estimating at least one angle of transmission (AOD) of the millimeter wave channel according to the first measurement matrix and an angle compressed sensing matrix. The first beamforming matrix comprises a plurality of first beamforming vectors, the plurality of first beamforming vectors respectively correspond to a plurality of first beamforming modes, and the first measurement matrix comprises a plurality of first measurement parameters respectively corresponding to the plurality of first beamforming vectors.
Another embodiment of the present invention provides a millimeter wave channel estimation method, which includes receiving signals through a millimeter wave channel according to a first beamforming matrix to generate a first measurement matrix, and estimating at least one received signal angle (AOA) of the millimeter wave channel according to the first measurement matrix and an angle compressed sensing matrix. The first beamforming matrix comprises a plurality of first beamforming vectors, the plurality of first beamforming vectors respectively correspond to a plurality of first beamforming modes, and the first measurement matrix comprises a plurality of first measurement parameters respectively corresponding to the plurality of first beamforming vectors.
With the above structure, the millimeter wave channel estimation method disclosed in the present application forms a plurality of beamforming vectors based on the compressive sensing theory, thereby generating a plurality of measurement parameters associated with the millimeter wave channel, and obtains an angle characteristic estimation result of the millimeter wave channel from the plurality of measurement parameters, the plurality of beamforming vectors, and the plurality of angle parameters by using the compressive sensing reduction technique. The millimeter wave channel estimation method disclosed by the scheme does not need to execute the step of feeding back measurement information, can estimate the characteristic parameters of the channel by a small number of measurement times, achieves quick millimeter wave channel estimation and further improves the quality of subsequent signal/data transmission.
The foregoing description of the disclosure and the following description of the embodiments are provided to illustrate and explain the spirit and principles of the invention and to provide further explanation of the invention as claimed.
Drawings
Fig. 1 is a flowchart illustrating a millimeter wave channel estimation method according to an embodiment of the invention.
Fig. 2 is a flowchart illustrating a step of forming a first beamforming matrix in the millimeter wave channel estimation method according to an embodiment of the present invention.
Fig. 3 is a functional block diagram of a communication system according to an embodiment of the invention.
Fig. 4 is a flowchart illustrating a step of generating a measurement matrix in the millimeter wave channel estimation method according to an embodiment.
Fig. 5 is a flowchart illustrating a millimeter wave channel estimation method according to another embodiment of the invention.
Fig. 6 is a flowchart illustrating a second beamforming matrix forming step in the millimeter wave channel estimation method according to another embodiment of the present invention.
Description of the symbols
1 communication system
10 base station
101 baseband circuit
103 radio frequency link
105 signal transceiver
1051 phase modulation circuit
1053 impedance modulation circuit
1055 antenna
20 user terminal
30 mm wave channel
S11-S13, S111-S119, and S121-S129
S21-S26, S241-S245
Detailed Description
The detailed features and advantages of the present invention are described in detail in the embodiments below, which are sufficient for anyone skilled in the art to understand the technical contents of the present invention and to implement the present invention, and the related objects and advantages of the present invention can be easily understood by anyone skilled in the art from the disclosure of the present specification, the claims and the accompanying drawings. The following examples further illustrate the aspects of the present invention in detail, but are not intended to limit the scope of the present invention in any way.
The millimeter wave channel estimation method provided by the invention is suitable for a communication system for transmitting wireless signals through a millimeter wave channel. Referring to fig. 1, fig. 1 is a flowchart illustrating a millimeter wave channel estimation method according to an embodiment of the invention. In step S11, the communication system for wireless signal transmission through the mm wave channel forms a first beamforming matrix, where the first beamforming matrix includes a plurality of first beamforming vectors respectively corresponding to a plurality of first beamforming modes. It should be particularly noted that the step S11 of forming the first beamforming matrix is an optional step, that is, in other embodiments, the first beamforming matrix may be pre-stored in the communication system, so that only the following steps S12 and S13 may be performed when the millimeter wave channel estimation method is performed.
In step S12, the communication system generates a first measurement matrix associated with the mm wave channel according to the first beamforming matrix formed in step S11, wherein the first measurement matrix includes a plurality of first measurement parameters respectively corresponding to a plurality of first beamforming vectors in the first beamforming matrix. Further, the plurality of first measurement parameters in the first measurement matrix may have a one-to-one relationship with the plurality of first beamforming vectors in the first beamforming matrix. In an embodiment, a method for generating a first measurement matrix associated with a millimeter wave channel by a communication system according to a first beamforming matrix may be to transmit signals through the millimeter wave channel according to the first beamforming matrix and perform channel measurement on the millimeter wave channel; in another embodiment, the first measurement matrix may be generated by receiving signals through the mm wave channel according to the first beamforming matrix. The structure for operating these two embodiments will be described in detail later.
In step S13, the communication system performs estimation according to the first measurement matrix and the angle-compressed sensing matrix to obtain an angle characteristic estimation result of the mm wave channel. The angle compressed sensing matrix includes the first beamforming matrix and an angle matrix, wherein the angle matrix includes a plurality of angle parameters, each angle parameter has a base number and an index, the base number is a mathematical constant (e), and the indexes include different angle values. For example, the angle parameter may be ejkdsinθi。
Referring to fig. 2, the step of forming the first beamforming matrix in step S11 of fig. 1 is further described. Fig. 2 is a flowchart illustrating a step of forming a first beamforming matrix in the millimeter wave channel estimation method according to an embodiment of the present invention. In step S111, the communication system establishes a basic compressed sensing matrix. The basic compressed sensing matrix is, for example, a Gabor Frame (Gabor Frame), which is one dimension m × m2Of the matrix of (a). In particular, m may be a prime number above 5, that is to say the dimension of the Gabor framework may be greater than 5 × 25. In one embodiment, the Gabor framework may be formed by an exponential function, wherein the base of the exponential function is a mathematical constant (e), and the exponent comprises a constant m, where m is associated with the number of measurements performed in the subsequent estimation step. For example, the basic compressed sensing matrix AGCan be represented by the following mathematical formula:
Next, in step S113, the communication system performs a least square operation on the basic compressed sensing matrix to obtain a first least square matrix. In detail, the communication system willDesigning a pre-coding matrix F, and calculating an angle matrix AθThe matrix product of the conjugate transpose matrix and the precoding matrix F is obtained, and then the basic compressed sensing matrix A is obtainedGThe matrix solution F of the precoding matrix having the least sum of squares of the difference between the transposed matrix and the matrix product ofoptAnd using the matrix to solve FoptThe transposed matrix and the angle matrix A ofθThe matrix product of the conjugate transpose matrix of (a) is taken as the first least square matrix aLS. The calculation process of step S113 can be exemplarily represented by the following mathematical formula:
In step S115, the communication system performs a normalization operation on the first least square matrix obtained in step S113 to obtain a normalized matrix, wherein the detailed operation of the normalization operation is understood by those skilled in the art and will not be described herein. In step S117, the communication system performs the least square operation on the normalized matrix again to obtain a second least square matrix, wherein the detailed operation of the least square operation is similar to that in step S113, and is not repeated herein. In step S119, the communication system multiplies the second least square matrix by the inverse of the angle matrix to obtain the first beamforming matrix.
As described above, the millimeter wave channel estimation method provided by the present invention is suitable for a communication system that performs wireless signal transmission through a millimeter wave channel. Further, please refer to fig. 1, fig. 3, and fig. 4 to illustrate an embodiment of the communication system and a detailed millimeter wave channel estimation method thereof. Fig. 3 is a functional block diagram of a communication system according to an embodiment of the present invention; fig. 4 is a flowchart illustrating a step of generating a measurement matrix in the millimeter wave channel estimation method according to an embodiment.
As shown in fig. 3, the communication system 1 includes a base station 10 and a user terminal 20, which transmit wireless signals through a millimeter wave channel 30. The base station 10 includes a baseband circuit 101, an rf link 103, and a plurality of signal transceivers 105, wherein each signal transceiver 105 includes a phase modulation circuit 1051, an impedance modulation circuit 1053, and an antenna 1055. The base station 10 may also include a signal generator and a precoder (e.g., a computer), or a signal generator and a precoder external to the communication system 1. The ue 20 can receive the wireless signal from the base station 10 through the mm wave channel 30 to perform data downloading, and can also transmit the wireless signal to the base station 10 through the mm wave channel 30 to perform data uploading. For example, the user terminal 20 may be a mobile phone, a notebook computer or other user devices with wireless signal transceivers, and the invention is not limited thereto.
In one embodiment, the communication system 1 can perform the estimation of the mm wave channel 30 by transmitting the wireless signal from the base station 10 and receiving the wireless signal from the ue 20, including the aforementioned steps S12 and S13, or steps S11 to S13 in fig. 1. In step S11, the communication system 1 can form a beamforming matrix including a plurality of first beamforming vectors through the precoder of the base station 10, and the detailed forming steps are as described in the previous embodiments and are not described herein again.
In step S12, the communication system 1 generates a first measurement matrix according to the first beamforming matrix. Further, the communication system 1 generates and transmits a beam by the base station 10 according to one of the first beamforming vectors formed in step S11. For example, the base station 10 may generate a beam having a radiation field of a first beamforming pattern corresponding to a first beamforming vector based on the first beamforming vector. Specifically, each first beamforming vector includes a phase modulation value and an impedance modulation value of each antenna 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 first beamforming vector to adjust the phase and amplitude of the electromagnetic waves (wireless signals) emitted by each antenna 1055, and the electromagnetic waves emitted by each antenna 1055 together form a radiation pattern having a first beamforming mode corresponding to the first beamforming vector according to the radiation pattern. Then, the communication system 1 receives the beam and generates a first measurement parameter through the ue 20. The first measurement parameter corresponds to the first beamforming vector for generating the beam and is one of the parameters in the first measurement matrix.
In this embodiment, the wireless signal transmitting end is the base station 10 and the wireless signal receiving end is the user end 20, and step S12 in fig. 1 may include steps S121, S123, S125, S127 and S129 shown in fig. 4. In step S121, the base station 10 generates and transmits beams according to a beamforming vector (e.g., a first one) in the beamforming matrix (i.e., the first beamforming matrix) formed in step S11. In step S123, the ue 20 receives the beam from the base station 10 through the mm wave channel 30 to generate corresponding measurement parameters. In step S125, the base station 10 determines whether the beamforming vector used last time is the last beamforming matrix. If the determination result is negative, in step S127, the base station 10 generates and transmits a beam according to the next beamforming vector in the beamforming matrix, and the ue 20 performs step S123; if the determination result is yes, the ue 20 integrates the generated measurement parameters into a measurement matrix, as shown in step S129. Therefore, for example, if the beamforming matrix has m beamforming vectors, after the above steps, the wireless signal receiving end may generate m measurement parameters correspondingly to form a measurement matrix of m × 1 (i.e., the first measurement matrix).
In short, the communication system 1 can generate the beam by the base station 10 multiple times according to the multiple beamforming vectors, and receive the beam by the ue 20 multiple times to generate multiple measurement parameters respectively, and integrate the measurement parameters into the measurement matrix. The embodiment of fig. 4 illustrates the base station 10 sequentially generating beams according to the beamforming vectors in the beamforming matrix, however, the invention is not limited to the base station using the beamforming vectors in the same order as the array order in the matrix.
In step S13, the ue 20 performs estimation to obtain an estimation result of the angular characteristic of the mm wave channel 30 according to the first measurement matrix and the angle compressed sensing matrix. In this embodiment, the angle characteristic estimation result includes at least one angle of transmission (AOD). In detail, the ue 20 stores a compressed sensing reduction algorithm, which includes the following equations:
y＝φα。
in other words, the millimeter wave channel estimation method provided by the present application decomposes the angle compressed sensing matrix into a first beamforming matrix and an angle matrix, as shown in the following equation, in which y is a measurement matrix, phi is an angle compressed sensing matrix, and α is an estimation result of the desired angle characteristic, as described in the forming step S119 of the first beamforming matrix shown in fig. 2, the first beamforming matrix is obtained by multiplying the angle compressed sensing matrix (the second least squares matrix) by an inverse matrix of the angle matrix:
by the above-mentioned reduction algorithm, the angle characteristic estimation result can be calculated by proceeding to the first beamforming matrix generated in step S11, the first measurement matrix measured in step S12, and the known angle matrix. The angle characteristic estimation result includes a plurality of angle estimation parameters, which have a one-to-one relationship with the angle parameters in the angle matrix, and the angle estimation parameters can indicate whether a wireless signal (beam) is received at the angle represented by the corresponding angle parameter or whether the strength of the received wireless signal is greater than a threshold value. For example, when the intensity of the wireless signal received by the signal receiving end through the millimeter wave channel at a specific angle is not greater than the threshold, the angle estimation parameter corresponding to the specific angle is zero; when the intensity of the wireless signal received by the signal receiving end through the millimeter wave channel at a specific angle is greater than the threshold value, the angle estimation parameter corresponding to the specific angle is not zero.
Compared with the conventional exhaustive search method, the measurement times of the millimeter wave channel estimation method provided by the present application are determined by the parameter design of the beamforming matrix, so that the measurement times are not increased along with the improvement of the resolution, a large amount of measurement data and operation time caused by the requirement of high resolution can be avoided, and the estimation of the millimeter wave channel can be rapidly completed.
In another embodiment, the communication system 1 can perform the estimation of the mm wave channel 30 by the wireless signal transmitted by the ue 20 and received by the base station 10, including the aforementioned steps S12 and S13 or steps S11 to S13 in fig. 1. In step S11, the communication system 1 forms a first beamforming matrix including a plurality of first beamforming vectors by the base station 10, and the detailed forming steps are as described in the previous embodiments and are not described herein again.
In step S12, the communication system 1 generates a first measurement matrix according to the first beamforming matrix. Further, the communication system 1 transmits a signal through the ue 20, and the base station 10 receives the signal through one of the first beamforming vectors formed in step S11 to generate a corresponding first measurement parameter, which is one of the parameters in the first measurement matrix. In this embodiment, the base station 10 can receive signals through a plurality of first beamforming vectors respectively for a plurality of times to generate a plurality of first measurement parameters respectively corresponding to the first beamforming vectors. For example, the base station 10 can receive signals sequentially according to the first beamforming vectors in the first beamforming matrix, similar to the procedure shown in fig. 4, but not limited thereto. The base station 10 can integrate the generated first measurement parameters into a first measurement matrix.
In step S13, the base station 10 obtains an angle characteristic estimation result of the mm wave channel 30 according to the first measurement matrix, the angle compressed sensing matrix, the first beamforming matrix and the angle matrix. The angle characteristic estimation result includes at least one received signal angle (AOA), and the base station 10 has a compressed sensing reduction algorithm, and the mathematical expressions and the detailed operation process included in the algorithm are similar to those described in the previous embodiment, and therefore are not described again. In this embodiment, the base station 10 has the functions of forming beam forming vectors and calculating the angular characteristics.
In another embodiment, both the base station 10 and the user equipment 20 of the communication system 1 have a compressed sensing recovery algorithm. With the millimeter wave channel estimation method similar to the two embodiments, the communication system 1 can estimate the millimeter wave channel no matter when the ue 20 performs the uploading or the downloading.
Referring to fig. 3, fig. 5 and fig. 6, wherein fig. 5 is a flowchart illustrating a millimeter wave channel estimation method according to another embodiment of the invention, and fig. 6 is a flowchart illustrating a step of forming a second beamforming matrix in the millimeter wave channel estimation method according to another embodiment of the invention. The millimeter wave channel estimation method shown in fig. 5 is also applicable to the communication system 1 shown in fig. 3, and therefore, the implementation of the millimeter wave channel estimation method of fig. 5 performed by the communication system 1 will be exemplarily described below. In steps S21 to S23, the communication system 1 forms a first beamforming matrix by the base station 10, generates a first measurement matrix associated with the mm wave channel 30 according to the first beamforming matrix, and estimates an angle characteristic estimation result of the mm wave channel 30 according to the first measurement matrix and the angle compressive sensing matrix, which are similar to steps S11 to S13 in the embodiment of fig. 1, and detailed embodiments of the steps are as described in the previous embodiments, and thus are not described again.
In the embodiment shown in fig. 5, after obtaining the estimation result of the angular characteristic of the millimeter wave channel 30, the communication system 1 further performs the estimation of the millimeter wave channel 30 by using the second beamforming matrix. In step S24, the communication system 1 forms a second beamforming matrix by the base station 10, wherein the second beamforming matrix comprises a plurality of second beamforming vectors. Further, fig. 6 illustrates an embodiment of forming a second beamforming matrix. In step S241, the base station 10 establishes a basic compressed sensing matrix, such as a Gabor frame. In step S243, the base station 10 performs a least square operation on the compressed sensing matrix to obtain a least square matrix. The steps S241 and S243 are the same as the steps S111 and S113 in the embodiment of fig. 2, and detailed description thereof is omitted here. Next, in step S245, the base station 10 multiplies the least square matrix by the inverse of the angle matrix to obtain a second beamforming matrix.
It should be noted that fig. 5 exemplarily illustrates the step S24 of forming the second beamforming matrix after the step S23 of obtaining the angle characteristic estimation result, however, in other embodiments, the step S24 may be performed before or after any of the previous steps S21 to S23, and the present invention is not limited thereto. In addition, as described above, steps S241 and S243 for forming the second beamforming matrix are the same as steps S111 and S113 for forming the first beamforming matrix, so in the embodiment, the base station 10 can form the second beamforming matrix in the process of performing step S21 to form the first beamforming matrix. In addition, the steps S21 and S24 are optional steps, and in other embodiments, the first and second beamforming matrices may be pre-stored in the communication system 1, so that only the steps S22 and S23 and the steps S25 and S26 may be performed when the millimeter wave channel estimation method is performed.
After obtaining the second beamforming matrix, the communication system 1 may estimate other characteristic parameters of the millimeter wave channel 30 through the beamforming matrix, as shown in steps S25 to S26 of fig. 5. In step S25, the communication system 1 generates a second measurement matrix associated with the mm wave channel 30 according to a second beamforming matrix, wherein the second measurement matrix includes a plurality of second measurement parameters respectively corresponding to the plurality of second beamforming vectors. Further, there may be a one-to-one relationship between the second measurement parameters in the second measurement matrix and the second beamforming vectors in the second beamforming matrix. The detailed implementation of step S25 is similar to the above-mentioned implementation of generating the measurement matrix according to the first beamforming matrix, and is not described herein again.
In step S26, the communication system 1 obtains the gain characteristic estimation result of the mm wave channel 30 according to the second measurement matrix gain compression sensing matrix and the angle characteristic estimation result obtained in step S23. Wherein the gain compressed sensing matrix comprises a second beamforming matrix and an angle matrix. Further, the communication system 1 may obtain the estimation result of the gain characteristic by the compressed sensing reduction algorithm mentioned in the foregoing embodiment, that is, obtain the gain corresponding to the estimation result of the angle characteristic according to the estimation result of the angle characteristic.
In the embodiment where the signal is transmitted according to the second beamforming matrix and the channel measurement is performed, the gain characteristic estimation result obtained by the communication system 1 comprises at least one transmission signal gain corresponding to at least one transmission signal angle obtained by the first stage estimation (steps S21-S23); in the embodiment of receiving signals according to the second beamforming matrix and performing channel measurement, the gain characteristic estimation result obtained by the communication system 1 includes at least one received signal gain corresponding to at least one received signal angle obtained by the first stage estimation. Through the execution of the above steps S21-S26, the communication system 1 can obtain the estimation value of the transmission signal angle or the reception signal angle of the millimeter wave channel 30 and the estimation value of the gain corresponding to the angle respectively through a two-stage estimation method, so as to achieve accurate estimation of the millimeter wave channel.
With the above structure, the millimeter wave channel estimation method disclosed in the present application forms a plurality of beamforming vectors based on the compressive sensing theory, thereby generating a plurality of measurement parameters associated with the millimeter wave channel, and obtains an angle characteristic estimation result of the millimeter wave channel from the plurality of measurement parameters, the plurality of beamforming vectors, and the plurality of angle parameters by using the compressive sensing reduction technique. The millimeter wave channel estimation method disclosed by the scheme does not need to execute the step of feeding back measurement information, can estimate the characteristic parameters of the channel by a small number of measurement times, achieves quick millimeter wave channel estimation and further improves the quality of subsequent signal/data transmission. Furthermore, compared with the estimation mode of obtaining all parameters in a single stage, the angle characteristic parameter and the gain characteristic parameter of the millimeter wave channel are obtained through two-stage estimation, and a more accurate estimation result can be obtained.
Claims (10)
1. A millimeter wave channel estimation method includes:
transmitting signals through a millimeter wave channel according to a first beamforming matrix, wherein the first beamforming matrix comprises a plurality of first beamforming vectors, and the first beamforming vectors correspond to a plurality of first beamforming modes respectively;
performing channel measurement on the millimeter wave channel to generate a first measurement matrix, wherein the first measurement matrix comprises a plurality of first measurement parameters respectively corresponding to the first beamforming vectors; and
estimating to obtain at least one transmitted signal angle of the millimeter wave channel according to the first measurement matrix and the angle compressed sensing matrix.
2. The millimeter wave channel estimation method according to claim 1, further comprising:
transmitting signals through the millimeter wave channel according to a second beamforming matrix, the second beamforming matrix comprising a plurality of second beamforming vectors, the second beamforming vectors corresponding to a plurality of second beamforming modes, respectively;
performing channel measurement on the millimeter wave channel to generate a second measurement matrix, wherein the second measurement matrix comprises a plurality of second measurement parameters respectively corresponding to the second beamforming vectors; and
estimating to obtain at least one transmission signal gain respectively corresponding to the at least one transmission signal angle according to the second measurement matrix, the gain compressed sensing matrix and the at least one transmission signal angle.
3. The millimeter wave channel estimation method of claim 1, further comprising forming the first beamforming matrix, wherein the step of forming the first beamforming matrix comprises:
establishing a basic compressed sensing matrix;
performing a least squares operation on the basic compressed sensing matrix to obtain a first least squares matrix;
performing a normalization operation on the first least square matrix to obtain a normalized matrix;
performing the least squares operation on the normalized matrix to obtain a second least squares matrix; and
the second least squares matrix is multiplied by the inverse of the angle matrix to obtain the first beamforming matrix.
4. The millimeter wave channel estimation method of claim 2, further comprising forming the second beamforming matrix, wherein the step of forming the second beamforming matrix comprises:
establishing a basic compressed sensing matrix;
performing a least squares operation on the basic compressed sensing matrix to obtain a least squares matrix; and
the least squares matrix is multiplied by the inverse of the angle matrix to obtain the second beamforming matrix.
5. The millimeter wave channel estimation method according to claim 3 or 4, wherein the basic compressed sensing matrix is a Gabor framework.
6. A millimeter wave channel estimation method includes:
receiving signals through a millimeter wave channel according to the first beam forming matrix to generate a first measurement matrix; and
estimating to obtain at least one received signal angle of the millimeter wave channel according to the first measurement matrix and the angle compressed sensing matrix;
the first measurement matrix includes a plurality of first measurement parameters respectively corresponding to the first beamforming vectors.
7. The millimeter wave channel estimation method according to claim 6, further comprising:
receiving signals through the millimeter wave channel according to a second beamforming matrix to generate a second measurement matrix; and
estimating to obtain at least one received signal gain respectively corresponding to the at least one received signal angle according to the second measurement matrix, the gain compressed sensing matrix and the at least one received signal angle;
the second beamforming matrix comprises a plurality of second beamforming vectors, the second beamforming vectors correspond to a plurality of second beamforming modes respectively, and the second measurement matrix comprises a plurality of second measurement parameters corresponding to the second beamforming vectors respectively.
8. The millimeter wave channel estimation method of claim 6 further comprising forming the first beamforming matrix, wherein the step of forming the first beamforming matrix comprises:
establishing a basic compressed sensing matrix;
performing a least squares operation on the basic compressed sensing matrix to obtain a first least squares matrix;
performing a normalization operation on the first least square matrix to obtain a normalized matrix;
performing the least squares operation on the normalized matrix to obtain a second least squares matrix; and
the second least squares matrix is multiplied by the inverse of the angle matrix to obtain the first beamforming matrix.
9. The millimeter wave channel estimation method of claim 7 further comprising forming the second beamforming matrix, wherein the step of forming the second beamforming matrix comprises:
establishing a basic compressed sensing matrix;
performing a least squares operation on the basic compressed sensing matrix to obtain a least squares matrix; and
multiplying the least squares matrix by the inverse of the angle matrix to obtain the second beamforming matrix.
10. The millimeter wave channel estimation method according to claim 8 or 9, wherein the basic compressed sensing matrix is a Gabor frame.
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