WO2018014197A1 - 一种信道估计方法及装置 - Google Patents
一种信道估计方法及装置 Download PDFInfo
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- WO2018014197A1 WO2018014197A1 PCT/CN2016/090480 CN2016090480W WO2018014197A1 WO 2018014197 A1 WO2018014197 A1 WO 2018014197A1 CN 2016090480 W CN2016090480 W CN 2016090480W WO 2018014197 A1 WO2018014197 A1 WO 2018014197A1
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- the present invention relates to the field of communications, and in particular, to a channel estimation method and apparatus.
- Millimeter wave communication provides a new type of communication scenario that allows communication systems to have wider bandwidth and more available spectrum resources, operating at frequencies ranging from tens of megabytes to hundreds of gigahertz.
- Massive MIMO Multiple-Input Multiple-Output
- millimeter-wave communication technology can be combined with millimeter-wave communication technology to take advantage of the gain from beamforming of multiple transmit and receive antennas to combat path loss. The decline.
- channel estimation is required to acquire channel state information (CSI), and a precoding design on the transmitter side and a detection reception design on the receiver side are performed according to CSI.
- CSI channel state information
- the Compressive Sensing Based Channel Estimation (CSCE) technology utilizes the finite multipath channel characteristics in millimeter wave propagation, and reduces the training overhead by reducing the length of the pilot sequence on the transmitter side.
- the received signal is vectorized, and then the CS reconstruction algorithm is used for channel reconstruction.
- the CSCE technology needs to convert the channel matrix into a vector by vectorization operation and then perform the CS reconstruction algorithm to estimate the CSI of the channel. Due to the expansion of the problem to be solved, the computational complexity of the CSCE is increased, and the calculation is improved. The complexity and the operation time of the channel estimation are prolonged, which will cause the hardware power consumption to increase and the response time to become longer in practical applications.
- the invention provides a channel estimation method and device, which can improve the efficiency of channel estimation.
- a first aspect of the present invention provides a channel estimation method, the method comprising:
- angle domain signal matrix Determining the angle of arrival AoA information of the scattering diameter and the leaving angle AoD information of the scattering diameter
- the channel estimation result is determined based on the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter.
- Angle domain signal matrix among them, Respectively represent the angular domain channel matrix, the transmitted signal matrix and the additive noise matrix, U r and U t represent the discrete Fourier transform matrix, and H represents the conjugate transpose;
- the angle domain signal matrix The AoA information for determining the angle of arrival of the scattering path includes:
- the angle domain signal matrix The AoD information for determining the departure angle of the scattering path includes:
- angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows.
- the Determining the angular domain channel matrix Non-zero lines including:
- the Determining the angular domain channel matrix Non-zero columns in non-zero rows including:
- i corresponds to the angular domain channel matrix Any of the non-zero rows
- the j corresponding to the angular domain channel matrix Any of the i rows
- the number of i is the number of receiving antennas
- the number of j is the number of transmitting antennas
- the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter determine the channel estimation result, including:
- Angle domain channel matrix The non-zero row and the non-zero column in the non-zero row get the angular domain channel matrix The row and column coordinates of the zero element in the middle;
- a channel estimation result is obtained based on row coordinates and column coordinates of the non-zero element, and values of the non-zero elements.
- a second aspect of the present invention provides a channel estimation apparatus, the apparatus comprising:
- a transceiver unit configured to receive a signal Y sent by the transmitter
- a processing unit configured to perform spatial Fourier transform processing on the signal Y to obtain an angle domain signal matrix According to the angle domain signal matrix
- the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter are determined; the channel estimation result is determined based on the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter.
- Angle domain signal matrix among them, Respectively represent the angular domain channel matrix, the transmitted signal matrix and the additive noise matrix, U r and U t represent the discrete Fourier transform matrix, and H represents the conjugate transpose;
- the processing unit is configured to use the angle domain signal matrix
- the AoA information for determining the angle of arrival of the scattering path includes:
- the processing unit is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero line;
- the processing unit is configured to use the angle domain signal matrix
- the AoD information for determining the departure angle of the scattering path includes:
- the processing unit is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows.
- the processing unit is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero lines, including:
- the processing unit is configured to acquire the angle domain signal matrix The average received energy corresponding to each row; determining the target behavior angle domain channel matrix when the average received energy corresponding to the target row is greater than a preset threshold Non-zero line; wherein the target behavior is the angular domain signal matrix Any line in .
- the processing unit is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows, including:
- the processing unit is configured to calculate the angle domain signal matrix I-line and the transmitted signal matrix Correlation of j rows; wherein i corresponds to the angular domain channel matrix Any of the non-zero rows, the j corresponding to the angular domain channel matrix Any of the i rows, the number of i is the number of receiving antennas, and the number of j is the number of transmitting antennas;
- the processing unit is used by the processing unit
- the channel estimation result is determined according to the arrival angle AoA information of the scattering path and the departure angle AoD information of the scattering path, including:
- the processing unit is configured to use the angle domain channel matrix
- the non-zero row and the non-zero column in the non-zero row get the angular domain channel matrix
- a channel estimation result is obtained based on row coordinates and column coordinates of the non-zero element, and values of the non-zero elements.
- a third aspect of the present invention provides a receiver, the receiver comprising:
- a transceiver for receiving a signal Y sent by the transmitter
- a processor configured to perform spatial Fourier transform processing on the signal Y to obtain an angular domain signal matrix According to the angle domain signal matrix
- the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter are determined; the channel estimation result is determined based on the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter.
- Angle domain signal matrix among them, Respectively represent the angular domain channel matrix, the transmitted signal matrix and the additive noise matrix, U r and U t represent the discrete Fourier transform matrix, and H represents the conjugate transpose;
- the processor is configured to use the angle domain signal matrix Determining the angle of arrival of the scattering path AoA information includes:
- the processor is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero line;
- the processor is configured to use the angle domain signal matrix
- the AoD information for determining the departure angle of the scattering path includes:
- the processor is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows.
- the processor is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero lines, including:
- the processor is configured to acquire the angle domain signal matrix The average received energy corresponding to each row; determining the target behavior angle domain channel matrix when the average received energy corresponding to the target row is greater than a preset threshold Non-zero line; wherein the target behavior is the angular domain signal matrix Any line in .
- the processor is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows, including:
- the processor is configured to calculate the angle domain signal matrix I-line and the transmitted signal matrix Correlation of j rows; wherein i corresponds to the angular domain channel matrix Any of the non-zero rows, the j corresponding to the angular domain channel matrix Any of the i rows, the number of i is the number of receiving antennas, and the number of j is the number of transmitting antennas;
- the channel estimation result is determined according to the arrival angle AoA information of the scattering path and the departure angle AoD information of the scattering path, including:
- the processor is configured to use the angle domain channel matrix
- the non-zero row and the non-zero column in the non-zero row get the angular domain channel matrix
- a channel estimation result is obtained based on row coordinates and column coordinates of the non-zero element, and values of the non-zero elements.
- a fourth aspect of the present invention provides a storage medium storing program code, when the program code is run by a receiver in the third aspect, performing the first aspect or any one of the implementation manners of the first aspect
- the proposed channel estimation method includes, but is not limited to, a flash memory (English: flash memory), a hard disk (HDD) or a solid state drive (SSD).
- the receiver performs spatial Fourier transform processing on the signal Y transmitted by the transmitter to obtain an angle domain signal matrix.
- the receiver is based on the angular domain signal matrix.
- the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter can be determined; then the channel estimation result is obtained by the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter. Since the technical solution of the present invention is to decompose the channel estimation into several sub-modules, and the problem size of each sub-module becomes smaller, the computational complexity of the channel estimation is reduced, and the efficiency of channel estimation is improved.
- FIG. 1 is a schematic structural diagram of an antenna array provided by the present invention.
- FIG. 2 is another schematic structural diagram of an antenna array provided by the present invention.
- FIG. 3 is a schematic structural diagram of a channel matrix provided by the present invention.
- FIG. 4 is a schematic structural diagram of a receiver provided by the present invention.
- FIG. 5 is a schematic flowchart diagram of a channel estimation method provided by the present invention.
- FIG. 6 is a schematic structural diagram of a channel estimation apparatus according to the present invention.
- channel estimation is required to acquire CSI, and a precoding design on the transmitter side and a detection reception design on the receiver side are performed according to CSI.
- the channel matrix dimension representing CSI becomes larger (the number of rows of the channel matrix is equal to the number of receiving antennas, and the number of columns is equal to the number of transmitting antennas), resulting in channel estimation.
- the training and feedback overhead will be greatly increased, making the communication efficiency of the wireless communication system itself lower.
- Compressive Sensing CS
- the CSCE technology utilizes the finite multipath channel characteristics in millimeter wave propagation and reduces the pilot on the transmitter side.
- the length of the sequence reduces the training overhead, but the CSCE technique on the receiver side cannot directly estimate the two-dimensional channel matrix, but needs to convert the channel matrix into a vector by vectorization operation and then perform the CS reconstruction algorithm to estimate the CSI of the channel, thus resulting in CSCE.
- the computational complexity is large, which increases the computational complexity of the problem solving and prolongs the computation time of the channel estimation. In practical applications, the hardware power consumption and response time will be increased.
- the technical solution of the present invention will use the correspondence between the structural characteristics of the channel matrix and the channel parameters from the structural characteristics of the millimeter-wave massive MIMO channel matrix in the angular domain.
- the estimation problem is decomposed into several sub-problems of dimensionality reduction and then solved sequentially.
- a fast estimation method and flow (Fast Channel Estimation, FCE) is designed.
- FCE Fast Channel Estimation
- the technical solution of the present invention utilizes the structural characteristics of the channel matrix in the millimeter-wave massive MIMO scene and the correspondence between the structural characteristics and the channel parameters.
- the specific explanations of the structural characteristics and the correspondence with the channel parameters are as follows:
- the channel matrix has sparsity and meshiness in the angle domain.
- Sparseness is a finite multipath channel characteristic derived from the millimeter wave band (the number of effective scatterers in the millimeter wave band propagation space is limited, and the number of multipaths after the scatterer is sparse), as shown in Fig. 1, the finite multipath
- the number of channels is L, which is much smaller than the channel matrix dimension (determined by the number of transmitting and receiving antennas).
- the meshiness is an increase in the number of antennas in a large antenna array of massive MIMO.
- the resolution of the beam in the angular domain increases (the resolution of the beam in the angle domain is determined by the number of antennas, The more the number of antennas, the thinner the beam and the higher the resolution.
- the beam resolution in the angular domain increases, and each potential scattering path in the wireless propagation spatial domain increases.
- the angle of arrival (AoA) and the angle of departure (AoD) of the scattering path can be approximated by the row and column coordinates of the channel matrix of the angular domain.
- the non-zero row of the sparse channel matrix in the angular domain corresponds to the angle of arrival (AoA) of each of the scattering paths in the multipath channel in the spatial domain
- the non-zero column in the non-zero row corresponds to the scattering
- the departure angle of the path (AoD) the value of the non-zero element corresponding to the row and the column reflects the channel gain of the scattering path.
- the receiver side of FIG. 1 can be implemented by the receiver 200 of FIG. 4.
- the organization structure of the receiver 200 is as shown in FIG. 4, and includes a processor 202, a memory 204, and a transceiver 206, and can also include a bus 208.
- the processor 202, the memory 204, and the transceiver 206 can implement communication connection with each other through the bus 208, and can also implement communication by other means such as wireless transmission.
- the memory 204 may include a volatile memory (English: volatile memory), such as a random access memory (English: random-access memory, abbreviation: RAM); the memory 204 may also include a non-volatile memory (English: non-volatile memory) ), such as read-only memory (English: read-only memory, abbreviation: ROM), flash memory (English: flash memory), hard disk (English: hard disk drive, abbreviation: HDD) or solid state drive (English: solid state drive , abbreviation: SSD); the memory 204 may also include a combination of the above types of memory.
- the program code for implementing the receiver side in the channel estimation method provided in FIG. 5 of the present application is saved in the memory 204 and executed by the processor 202.
- Receiver 200 communicates with the transmitter via transceiver 206.
- Processor 202 can be a central processing unit CPU.
- the transceiver 206 is configured to receive a signal Y sent by a transmitter
- the processor 202 is configured to perform spatial Fourier transform processing on the signal Y to obtain an angle domain signal matrix. According to the angle domain signal matrix The arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter are determined; the channel estimation result is determined based on the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter.
- the angle domain signal matrix among them, Respectively represent the angular domain channel matrix, the transmitted signal matrix and the additive noise matrix, U r and U t represent the discrete Fourier transform matrix, and H represents the conjugate transpose;
- the processor 202 is configured to use the angle domain signal matrix
- the AoA information for determining the angle of arrival of the scattering path includes:
- the processor 202 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero line;
- the processor 202 is configured to use the angle domain signal matrix
- the AoD information for determining the departure angle of the scattering path includes:
- the processor 202 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows.
- the processor 202 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero lines, including:
- the processor 202 is configured to acquire the angle domain signal matrix The average received energy corresponding to each row; determining the target behavior angle domain channel matrix when the average received energy corresponding to the target row is greater than a preset threshold Non-zero line; wherein the target behavior is the angular domain signal matrix Any line in .
- the processor 202 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows, including:
- the processor 202 is configured to calculate the angle domain signal matrix i line with the transmitted signal matrix Correlation of j rows; wherein i corresponds to the angular domain channel matrix Any of the non-zero rows, the j corresponding to the angular domain channel matrix Any of the i rows, the number of i is the number of receiving antennas, and the number of j is the number of transmitting antennas;
- the processor 202 is configured to determine a channel estimation result according to the angle of arrival AoA information of the scatter path and the departure angle AoD information of the scatter path, including:
- the processor 202 is configured to use the angle domain channel matrix The non-zero row and the non-zero column in the non-zero row get the angular domain channel matrix The row and column coordinates of the zero element in the middle;
- a channel estimation result is obtained based on row coordinates and column coordinates of the non-zero element, and values of the non-zero elements.
- the processor 202 performs spatial Fourier transform processing on the signal Y sent by the transmitter to obtain an angle domain signal matrix. Using the correspondence between the structural characteristics of the channel matrix in the angular domain and the channel parameters, the processor 202 is based on the angular domain signal matrix. The arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter can be determined; then the channel estimation result is obtained by the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter. Since the technical solution of the present invention is to decompose the channel estimation into several sub-modules, and the problem size of each sub-module becomes smaller, the computational complexity of the channel estimation is reduced, and the efficiency of channel estimation is improved.
- the present application also provides a channel estimation method.
- the receiver side of FIG. 1 and the receiver 200 of FIG. 2 are executed when the method is executed.
- the receiver when it receives the signal Y, it first performs spatial Fourier transform on the received signal Y, and transforms the received signal Y from the spatial domain to the angular domain, and the angular domain signal matrix.
- the channel matrix, the transmission signal matrix, and the additive noise matrix in the angular domain are respectively represented, U r and D t represent a discrete Fourier transform (DFT) matrix, and H represents a conjugate transpose.
- DFT discrete Fourier transform
- the channel matrix of the angular domain The structural features of sparsity and mesh are presented.
- the row coordinates and column coordinates of the non-zero elements respectively reflect the arrival angle AoA information and the exit angle AoD information of the corresponding scattering diameter, and the values of the non-zero elements indicate the scattering diameter.
- Channel gain As mentioned earlier, in millimeter-wave and massive MIMO scenarios, the channel matrix of the angular domain The structural features of sparsity and mesh are presented.
- the row coordinates and column coordinates of the non-zero elements respectively reflect the arrival angle AoA information and the exit angle AoD information of the corresponding scattering diameter, and the values of the non-zero elements indicate the scattering diameter.
- Channel gain As mentioned earlier, in millimeter-wave and massive MIMO scenarios, the channel matrix of the angular domain The structural features of sparsity and mesh are presented.
- the row coordinates and column coordinates of the non-zero elements respectively reflect the arrival angle AoA information and the exit angle AoD information of
- the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter are determined.
- the angle domain signal matrix obtained after the spatial Fourier transform in step 304 is described.
- the non-zero lines are one-to-one correspondence, that is, according to Non-zero line to detect Non-zero line. But when there is noise in the actual application, the noise will cause All the rows are non-zero.
- the technical solution uses an energy detection based method to detect Non-zero line.
- the angle domain signal matrix Determining the angular domain channel matrix Non-zero lines, including:
- the threshold can be set according to noise prior information such as noise variance to determine the line. Whether it is zero or not, when the average received energy of a certain line is greater than the detection threshold, it is judged that the behavior is non-zero, otherwise the behavior is judged to be zero, and the non-zero line AoA detection based on energy detection is described as follows:
- the sparse matrix The non-zero column in the non-zero row corresponds to the exit angle (AoD) information of the scattering path, so the target of the AoD detection is The position information of the non-zero column continues to be detected among the non-zero lines.
- the above-mentioned AoA detection method has been found one by one, for example, a certain non-zero line that has been detected by the i-th behavior, and the corresponding line operation is performed only for the i-th line in the AoD detection, that is, from the received signal. Extract the i-th line, the mathematical representation of the line is as follows:
- Non-zero columns in non-zero rows including:
- i corresponds to the angular domain channel matrix Any of the non-zero rows
- the j corresponding to the angular domain channel matrix Any of the i rows
- the number of i is the number of receiving antennas
- the number of j is the number of transmitting antennas
- the determining the channel estimation result according to the arrival angle AoA information of the scattering path and the departure angle AoD information of the scattering path including:
- Angle domain channel matrix The non-zero row and the non-zero column in the non-zero row get the angular domain channel matrix The row and column coordinates of the zero element in the middle;
- a channel estimation result is obtained based on row coordinates and column coordinates of the non-zero element, and values of the non-zero elements.
- the final step needs to estimate the value of the non-zero element as an estimate of the channel gain size.
- the technical solution uses the least squares parameter estimation to calculate The value of the non-zero element row found by the above AoA detection and AoD detection is i, and the column coordinate is j, then the channel gain estimate is expressed as follows:
- the above operation obtains the row and column coordinates of its non-zero elements and the element value. Since all other elements are zero, the matrix can be obtained according to the position information and value information of the above non-zero elements.
- the receiver performs spatial Fourier transform processing on the signal Y transmitted by the transmitter to obtain an angle domain signal matrix.
- the receiver is based on the angular domain signal matrix.
- the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter can be determined; then the channel estimation result is obtained by the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter. Since the technical solution of the present invention is to decompose the channel estimation into several sub-modules, and the problem size of each sub-module becomes smaller, the computational complexity of the channel estimation is reduced.
- the computational complexity of the prior art solution is The computational complexity of the technical solution is O(N r T+LN t T+KT), so that the computational complexity of the technical solution is smaller than the computational complexity of the existing solution.
- the embodiment of the present application further provides a channel estimation apparatus 400.
- the channel estimation apparatus 600 can be implemented by the receiver 200 shown in FIG. 4, and can also be implemented by an application-specific integrated circuit (ASIC). Or programmable logic device (English: programmable logic device, abbreviation: PLD) implementation.
- the PLD may be a complex programmable logic device (CPLD), an FPGA, a general array logic (GAL), or any combination thereof.
- the channel estimation apparatus 400 is for implementing a method performed by the receiver side in the channel estimation method shown in FIG. When the channel estimation method shown in FIG. 5 is implemented by software, the channel estimation apparatus 400 may also be a software module.
- the schematic diagram of the organization of the channel estimation apparatus 400 includes a processing unit 402 and a transceiver unit 404.
- the transceiver unit 404 is configured to receive a signal Y sent by the transmitter;
- the processing unit 402 is configured to perform spatial Fourier transform processing on the signal Y to obtain an angular domain signal matrix. According to the angle domain signal matrix The arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter are determined; the channel estimation result is determined based on the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter.
- the angle domain signal matrix among them, Respectively represent the angular domain channel matrix, the transmitted signal matrix and the additive noise matrix, U r and U t represent the discrete Fourier transform matrix, and H represents the conjugate transpose;
- the processing unit 402 is configured to use the angle domain signal matrix
- the AoA information for determining the angle of arrival of the scattering path includes:
- the processing unit 402 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero line;
- the processing unit 402 is configured to use the angle domain signal matrix
- the AoD information for determining the departure angle of the scattering path includes:
- the processing unit 402 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows.
- the processing unit 402 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero lines, including:
- the processing unit 402 is configured to acquire the angle domain signal matrix The average received energy corresponding to each row; determining the target behavior angle domain channel matrix when the average received energy corresponding to the target row is greater than a preset threshold Non-zero line; wherein the target behavior is the angular domain signal matrix Any line in .
- the processing unit 402 is configured to use the angle domain signal matrix Determining the angular domain channel matrix Non-zero columns in non-zero rows, including:
- the processing unit 402 is configured to calculate the angle domain signal matrix I-line and the transmitted signal matrix Correlation of j rows; wherein i corresponds to the angular domain channel matrix Any of the non-zero rows, the j corresponding to the angular domain channel matrix Any of the i rows, the number of i is the number of receiving antennas, and the number of j is the number of transmitting antennas;
- the processing unit 402 is configured to determine a channel estimation result according to the arrival angle AoA information of the scatter path and the departure angle AoD information of the scatter path, including:
- the processing unit 402 is configured to use the angle domain channel matrix The non-zero row and the non-zero column in the non-zero row get the angular domain channel matrix The row and column coordinates of the zero element in the middle;
- a channel estimation result is obtained based on row coordinates and column coordinates of the non-zero element, and values of the non-zero elements.
- the processing unit 402 performs spatial Fourier transform processing on the signal Y sent by the transmitter to obtain an angle domain signal matrix. Using the correspondence between the structural characteristics of the channel matrix in the angular domain and the channel parameters, the processing unit 402 is based on the angular domain signal matrix. The arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter can be determined; then the channel estimation result is obtained by the arrival angle AoA information of the scattering diameter and the departure angle AoD information of the scattering diameter. Since the technical solution of the present invention is to decompose the channel estimation into several sub-modules, and the problem size of each sub-module becomes smaller, the computational complexity of the channel estimation is reduced, and the efficiency of channel estimation is improved.
- the disclosed system, apparatus, and method may be implemented in other manners.
- the device embodiments described above are merely illustrative.
- the division of the unit is only a logical function division.
- there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
- the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
- the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. You can choose some or all of them according to actual needs.
- the unit is to achieve the purpose of the solution of the embodiment.
- each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
- the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
- the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
- a computer readable storage medium A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application.
- the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .
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Abstract
本发明提供了一种信道估计方法及装置,能够提高信道估计的效率。本发明方法包括:接收发射机发送的信号Y;对所述信号Y进行空间傅里叶变换处理,得到角度域信号矩阵Ϋ;根据所述角度域信号矩阵Ϋ确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果。
Description
本发明涉及通信领域,特别涉及一种信道估计方法及装置。
毫米波通信提供了一种新型的通信场景使得通信系统可以具有更宽的带宽和更多可利用频谱资源,其工作频率范围在几十吉到几百吉赫兹。massive MIMO(Multiple-Input Multiple-Output,多发多收)技术(也称为大天线阵列技术)可以与毫米波通信技术相结合,从而利用多收发天线的波束成形带来的增益来对抗路损引起的衰落。
在无线通信中,需要采用信道估计来获取信道的状态信息(Channel State Information,CSI),并根据CSI来进行发射机侧的预编码设计以及接收机侧的检测接收设计。基于CS的信道估计技术(Compressive Sensing based Channel Estimation,CSCE)是利用了毫米波传播中的有限多径信道特性,在发射机侧通过降低导频序列的长度来减少训练开销,在接收机侧将接收到的信号进行向量化处理,再利用CS重建算法进行信道重建。
然而,在接收机侧,CSCE技术需要通过向量化操作把信道矩阵转换为向量再执行CS重建算法来估计信道的CSI,由于待求解问题规模的扩大,导致CSCE的运算量增大,提高了计算复杂度、延长了信道估计的运算时间,在实际应用中将造成硬件功耗变大和响应时间变长。
发明内容
本发明提供了一种信道估计方法及装置,能够提高信道估计的效率。
本发明第一方面提供了一种信道估计方法,该方法包括:
接收发射机发送的信号Y;
根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果。
结合本发明的第一方面,在第一方面的第一种实现方式中,
计算所述角度域信号矩阵的i行与所述发送信号矩阵的j行的相关性;其中,所述i对应为所述角度域信道矩阵的非零行中的任意行,所述j对应为所述角度域信道矩阵的所述i行中的任意列,i的数量为接收天线个数,j的数量为发射天线个数;
结合本发明第一方面的第一种实现方式、第一方面的第二种实现方式或第一方面的第三种实现方式,在第一方面的第四种实现方式中,所述根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果,包括:
采用基于最小二乘的参数估计计算所述非零元素的值;
根据所述非零元素的行坐标和列坐标,以及所述非零元素的值得到信道估计结果。
本发明第二方面提供了一种信道估计装置,该装置包括:
收发单元,用于接收发射机发送的信号Y;
处理单元,用于对所述信号Y进行空间傅里叶变换处理,得到角度域信号矩阵根据所述角度域信号矩阵确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果。
结合本发明的第二方面,在第二方面的第一种实现方式中,
所述处理单元,用于获取所述角度域信号矩阵的每一行所对应的平均接收能量;当目标行所对应的平均接收能量大于预设门限值时,确定所述目标行为角度域信道矩阵的非零行;其中,所述目标行为所述角度域信号矩阵中的任意一行。
所述处理单元,用于计算所述角度域信号矩阵的i行与所述发送信号矩阵的j行的相关性;其中,所述i对应为所述角度域信道矩阵的非零行中的任意行,所述j对应为所述角度域信道矩阵的所述i行中的任意列,i的数量为接收天线个数,j的数量为发射天线个数;
结合本发明第二方面的第一种实现方式、第二方面的第二种实现方式或第二方面的第三种实现方式,在第二方面的第四种实现方式中,所述处理单元用于根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果,包括:
采用基于最小二乘的参数估计计算所述非零元素的值;
根据所述非零元素的行坐标和列坐标,以及所述非零元素的值得到信道估计结果。
本发明第三方面提供了一种接收机,该接收机包括:
收发器,用于接收发射机发送的信号Y;
处理器,用于对所述信号Y进行空间傅里叶变换处理,得到角度域信号矩阵根据所述角度域信号矩阵确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果。
结合本发明的第三方面,在第三方面的第一种实现方式中,
所述处理器,用于获取所述角度域信号矩阵的每一行所对应的平均接收能量;当目标行所对应的平均接收能量大于预设门限值时,确定所述目标行为角度域信道矩阵的非零行;其中,所述目标行为所述角度域信号矩阵中的任意一行。
所述处理器,用于计算所述角度域信号矩阵的i行与所述发送信号矩阵的j行的相关性;其中,所述i对应为所述角度域信道矩阵的非零行中的任意行,所述j对应为所述角度域信道矩阵的所述i行中的任意列,i的数量为接收天线个数,j的数量为发射天线个数;
结合本发明第三方面的第一种实现方式、第三方面的第二种实现方式,或第三方面的第三种实现方式,在第三方面的第四种实现方式中,所述处理器用于根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果,包括:
采用基于最小二乘的参数估计计算所述非零元素的值;
根据所述非零元素的行坐标和列坐标,以及所述非零元素的值得到信道估计结果。
本发明第四方面还提供了一种存储介质,该存储介质中存储了程序代码,该程序代码被第三方面中的接收机运行时,执行第一方面或第一方面的任意一种实现方式提供的信道估计方法。该存储介质包括但不限于快闪存储器(英文:flash memory),硬盘(英文:hard disk drive,HDD)或固态硬盘(英文:solid state drive,SSD)。
本发明技术方案中,接收机对发射机发送的信号Y进行空间傅里叶变换处理,得到角度域信号矩阵利用信道矩阵在角度域的结构特性和信道参数的对应关系,该接收机根据角度域信号矩阵可以确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;然后通过散射径的到达角度AoA信息和散射径的离开角度AoD信息得到信道估计结果。由于本发明技术方案是将信道估计分解为若干子模块来进行,且每个子模块的问题规模都变小,从而降低了信道估计的计算复杂度,提高了信道估计的效率。
图1为本发明所提供的天线阵列的一个结构示意图;
图2为本发明所提供的天线阵列的另一结构示意图;
图3为本发明所提供的信道矩阵的一个结构示意图;
图4为本发明所提供的接收机的一个结构示意图;
图5为本发明所提供的信道估计方法的一个流程示意图;
图6为本发明所提供的信道估计装置的一个结构示意图。
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为了使本技术领域的人员更好地理解本申请方案,下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本申请一部分的实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都应当属于本申请保护的范围。
本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”等(如果存在)是用于区别类似的对象,而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换,以便这里描述的实施例能够以除了在这里图示或描述的内容以外的顺序实施。此外,术语“包括”和“具有”以及他们的任何变形,意图在于覆盖不排他的包含,例如,包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元,而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
贯穿本说明书,在无线通信中,需要采用信道估计来获取CSI,并根据CSI来进行发射机侧的预编码设计以及接收机侧的检测接收设计。但是,随着massive MIMO天线数的急剧增加,使得表示CSI的信道矩阵维度变大(信道矩阵的行数等于接收天线的个数,列数等于发射天线的个数),导致用于信道估计的训练和反馈开销将大大增加,使得无线通信系统自身的通信效率降低。为减少用于信道估计的训练开销,压缩感知技术(CS,Compressive Sensing)被引入信道估计之中,CSCE技术是利用了毫米波传播中的有限多径信道特性,在发射机侧通过降低导频序列的长度来减少训练开销,但是在接收机侧CSCE技术无法直接估计二维的信道矩阵,而需要通过向量化操作把信道矩阵转换为向量再执行CS重建算法来估计信道的CSI,这样导致CSCE的运算量巨大,增大了问题求解的计算复杂度、延长了信道估计的运算时间,在实际应用中将加大硬件功耗和响应时间。
针对以上所述的高计算复杂度和长响应时间的问题,本发明技术方案将从毫米波massive MIMO信道矩阵在角度域的结构特性出发,利用信道矩阵结构特性和信道参数的对应关系,将信道估计问题分解为若干降维的子问题再进行依次求解,设计了一种对信道的快速估计方法和流程(Fast Channel Estimation,FCE)。仿真结果表明,本发明技术方案相比于对比方案的计算复杂度明显降低,响应时间明显缩短。
本发明技术方案利用了毫米波massive MIMO场景下的信道矩阵在角度域的结构特性和该结构特性与信道参数的对应关系,所述结构特性和与信道参数对应关系的具体解释如下:
在毫米波massive MIMO场景下,信道矩阵在角度域具有稀疏性和网格性。稀疏性是来源于毫米波频段的有限多径信道特性(在毫米波频段传播空间的有效散射体数量有限,经散射体后的多径数量是稀疏的),如图1所示,有限多径信道数量为L,远远小于信道矩阵维度(由收发天线的个数决定)。
网格性是来源于massive MIMO大天线阵列中的天线数目的增加,随着天线数目的增加在角度域的波束的分辨率随之增大(在角度域中波束的分辨率由天线数决定,天线数越多,波束越细,分辨率越高),如图2所示,随着天线数的增大,角度域内波束分辨率随之增大,无线传播空间域中的每一条潜在散射径将与角度域中的一对收发波束相对应,近而使该散射径的到达角度(AoA)和离开角度(AoD)可以由角度域的信道矩阵的行坐标和列坐标所表示。
以毫米波massive MIMO传播空间中存在L=5条有效散射径为例,如图3所示,表示了随着天线数的增加,信道的稀疏性和网格性体现在了角度域的信道矩阵的稀疏矩阵结构中。图3中从(a)(收发天线数为16乘16)到(d)(收发天线数增大为128乘128)子图的趋势可见,随着天线数的增加,信道矩阵的稀疏性和网格性结构逐渐清晰的显现出来。近而,在角度域稀疏信道矩阵的非零行对应了空间域中的多径信道中的每一条散射径的到达角度(AoA),在该非零行中的非零列则对应了该散射径的离开角度(AoD),该行和该列所对应非零元素的值则反映了该散射径的信道增益大小。
图1中的接收机侧可以通过图4中的接收机200实现,该接收机200的组织结构示意图如图4所示,包括处理器202、存储器204和收发器206,还可以包括总线208。
其中,处理器202、存储器204和收发器206可以通过总线208实现彼此之间的通信连接,也可以通过无线传输等其他手段实现通信。
存储器204可以包括易失性存储器(英文:volatile memory),例如随机存取存储器(英文:random-access memory,缩写:RAM);存储器204也可以包括非易失性存储器(英文:non-volatile memory),例如只读存储器(英文:read-only memory,缩写:ROM),快闪存储器(英文:flash memory),硬盘(英文:hard disk drive,缩写:HDD)或固态硬盘(英文:solid state drive,缩写:SSD);存储器204还可以包括上述种类的存储器的组合。在通过软件
来实现本申请提供的技术方案时,用于实现本申请图5提供的信道估计方法中接收机侧执行的程序代码保存在存储器204中,并由处理器202来执行。
接收机200通过收发器206与发射机通信。
处理器202可以为中央处理器CPU。
所述收发器206,用于接收发射机发送的信号Y;
所述处理器202,用于对所述信号Y进行空间傅里叶变换处理,得到角度域信号矩阵根据所述角度域信号矩阵确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果。
所述处理器202,用于获取所述角度域信号矩阵的每一行所对应的平均接收能量;当目标行所对应的平均接收能量大于预设门限值时,确定所述目标行为角度域信道矩阵的非零行;其中,所述目标行为所述角度域信号矩阵中的任意一行。
所述处理器202,用于计算所述角度域信号矩阵的i行与所述发送信号
矩阵的j行的相关性;其中,所述i对应为所述角度域信道矩阵的非零行中的任意行,所述j对应为所述角度域信道矩阵的所述i行中的任意列,i的数量为接收天线个数,j的数量为发射天线个数;
可选的,所述处理器202用于根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果,包括:
采用基于最小二乘的参数估计计算所述非零元素的值;
根据所述非零元素的行坐标和列坐标,以及所述非零元素的值得到信道估计结果。
本发明实施例中,处理器202对发射机发送的信号Y进行空间傅里叶变换处理,得到角度域信号矩阵利用信道矩阵在角度域的结构特性和信道参数的对应关系,该处理器202根据角度域信号矩阵可以确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;然后通过散射径的到达角度AoA信息和散射径的离开角度AoD信息得到信道估计结果。由于本发明技术方案是将信道估计分解为若干子模块来进行,且每个子模块的问题规模都变小,从而降低了信道估计的计算复杂度,提高了信道估计的效率。
本申请还提供了一种信道估计方法,图1中的接收机侧以及图2中的接收机200运行时执行该方法,其流程示意图如图5所示。
302、接收发射机发送的信号Y。
需要说明的是,接收机接收到发射机发出的经过无线多径信道后的导频训练序列信号,该信号矩阵表示如下:Y=HX+W。其中,表示空间域的信道矩阵,Nr为接收天线个数,Nt为发射天线个数,表示发射机发送的导频信号矩阵,该矩阵的Nt个行表示时长为T的Nt个训练序列从发射机侧的Nt个发射天线发出,表示独立于信道和导频训练序列的加性白高斯噪声。
需要说明的是,当接收机接收到信号Y后,首先对接收信号Y进行空间傅里叶变换,将接收到的信号Y从空间域变换到角度域,角度域信号矩阵表示如下:其中,分别表示在角度域的信道矩阵、发送信号矩阵、加性噪声矩阵,Ur和Dt表示离散傅里叶变换(DFT,Discrete Fourier Transform)矩阵,H表示共轭转置。
如前所述,在毫米波和massive MIMO场景下,角度域的信道矩阵呈现稀疏性和网格性的结构特征,其非零元素的行坐标和列坐标分别反映了对应散射径的到达角度AoA信息和离开角度AoD信息,且其非零元素的值表示了该散射径的信道增益。
需要说明的是,根据步骤304中空间傅里叶变换后获得的角度域信号矩阵来检测潜在散射径的到达角度(AoA),由于角度域信道矩阵是稀疏矩阵,在理想无噪声情况下,即的非零行与的非零行是一一对应的,即可以根据的非零行来检测的非零行。但对于实际应用中存在噪声时,噪声将导致的所有行均为非零,为了对抗噪声对检测的影响,本技术方案采用基于能量检测的方法来检测出的非零行。可选的,所述角度域信号矩阵确定角度域信道矩阵的非零行,包括:
即通过采集的每一行上的平均能量,再将每一行上的平均能量与事先设定的能量检测门限(实际应用中该门限可根据噪声先验信息例如噪声方差来设定)进行比较,来判断该行是否为零,当某一行的平均接收能量大于检测门限时即判断该行为非零,否则判断该行为零,基于能量检测的非零行AoA检测描述如下:
然后,在AoA检测结果的基础上进行AoD检测,如前所述,稀疏矩阵
的非零行中的非零列对应了散射径的离开角度(AoD)信息,所以AoD检测的目标是在的非零行之中继续检测出非零列的位置信息。基于非零行已经通过上述AoA检测方法逐一找到,例如第i行为已经检测到的某一非零行,在AoD检测中仅仅针对第i行进行对应行操作,即从接收到的信号中提取出第i行,该行的数学表示如下:
计算所述角度域信号矩阵的i行与所述发送信号矩阵的j行的相关性;其中,所述i对应为所述角度域信道矩阵的非零行中的任意行,所述j对应为所述角度域信道矩阵的所述i行中的任意列,i的数量为接收天线个数,j的数量为发射天线个数;
308、根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果。
可选的,所述根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果,包括:
采用基于最小二乘的参数估计计算所述非零元素的值;
根据所述非零元素的行坐标和列坐标,以及所述非零元素的值得到信道估计结果。
需要说明的是,在检测出中非零元素的行坐标和列坐标之后,最后一步需要估计出该非零元素的值作为对信道增益大小的估计,本技术方案采用基于
最小二乘的参数估计来计算中非零元素值,例如,已通过上述AoA检测和AoD检测找出的某一非零元素行坐标是i,其列坐标是j,则信道增益估计表示如下:
是稀疏矩阵,以上操作获得了其非零元素的行坐标和列坐标以及元素值,由于其它元素均为零,即根据以上非零元素的位置信息和值信息即可得到矩阵的完整估计由于信道表示在角度域和空间域之间满足傅里叶变换的变换关系,所以最终的信道估计结果可表示为
本发明技术方案中,接收机对发射机发送的信号Y进行空间傅里叶变换处理,得到角度域信号矩阵利用信道矩阵在角度域的结构特性和信道参数的对应关系,该接收机根据角度域信号矩阵可以确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;然后通过散射径的到达角度AoA信息和散射径的离开角度AoD信息得到信道估计结果。由于本发明技术方案是将信道估计分解为若干子模块来进行,且每个子模块的问题规模都变小,从而降低了信道估计的计算复杂度。现有技术方案的计算复杂度为而本技术方案的计算复杂度为O(NrT+LNtT+KT),由此可见本技术方案的计算复杂度小于现有方案的计算复杂度。
本申请实施例还提供了信道估计装置400,该信道估计装置600可以通过图4所示的接收机200实现,还可以通过专用集成电路(英文:application-specific integrated circuit,缩写:ASIC)实现,或可编程逻辑器件(英文:programmable logic device,缩写:PLD)实现。上述PLD可以是复杂可编程逻辑器件(英文:complex programmable logic device,缩写:CPLD),FPGA,通用阵列逻辑(英文:generic array logic,缩写:GAL)或其任意组合。该信道估计装置400用于实现图5所示的信道估计方法中接收机侧执行的方法。通过软件实现图5所示的信道估计方法时,该信道估计装置400也可以为软件模块。
信道估计装置400的组织结构示意图如图6所示,包括:处理单元402和收发单元404。
所述收发单元404,用于接收发射机发送的信号Y;
所述处理单元402,用于对所述信号Y进行空间傅里叶变换处理,得到角度域信号矩阵根据所述角度域信号矩阵确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果。
所述处理单元402,用于获取所述角度域信号矩阵的每一行所对应的平均接收能量;当目标行所对应的平均接收能量大于预设门限值时,确定所述目标行为角度域信道矩阵的非零行;其中,所述目标行为所述角度域信号矩阵中的任意一行。
所述处理单元402,用于计算所述角度域信号矩阵的i行与所述发送信号矩阵的j行的相关性;其中,所述i对应为所述角度域信道矩阵的非零行中的任意行,所述j对应为所述角度域信道矩阵的所述i行中的任意列,i的数量为接收天线个数,j的数量为发射天线个数;
可选的,所述处理单元402用于根据所述散射径的到达角度AoA信息和散射径的离开角度AoD信息确定信道估计结果,包括:
采用基于最小二乘的参数估计计算所述非零元素的值;
根据所述非零元素的行坐标和列坐标,以及所述非零元素的值得到信道估计结果。
本发明实施例中,处理单元402对发射机发送的信号Y进行空间傅里叶变换处理,得到角度域信号矩阵利用信道矩阵在角度域的结构特性和信道参数的对应关系,该处理单元402根据角度域信号矩阵可以确定散射径的到达角度AoA信息和散射径的离开角度AoD信息;然后通过散射径的到达角度AoA信息和散射径的离开角度AoD信息得到信道估计结果。由于本发明技术方案是将信道估计分解为若干子模块来进行,且每个子模块的问题规模都变小,从而降低了信道估计的计算复杂度,提高了信道估计的效率。
上述装置的相关描述可以对应参阅方法实施例部分的相关描述和效果进行理解,本处不做过多赘述。
所属领域的技术人员可以清楚地了解到,为描述的方便和简洁,上述描述的系统,装置和单元的具体工作过程,可以参考前述方法实施例中的对应过程,在此不再赘述。
在本申请所提供的几个实施例中,应该理解到,所揭露的系统,装置和方法,可以通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如,所述单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个单元或组件可以结合或者可以集成到另一个系统,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口,装置或单元的间接耦合或通信连接,可以是电性,机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的,作为单元显示的部件可以是或者也可以不是物理单元,即可以位于一个地方,或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部
单元来实现本实施例方案的目的。
另外,在本申请各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现,也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读取存储介质中。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质中,包括若干指令用以使得一台计算机设备(可以是个人计算机,服务器,或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括:U盘、移动硬盘、只读存储器(ROM,Read-Only Memory)、随机存取存储器(RAM,Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述,以上实施例仅用以说明本申请的技术方案,而非对其限制;尽管参照前述实施例对本申请进行了详细的说明,本领域的普通技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分技术特征进行等同替换;而这些修改或者替换,并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。
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