CN117424781A - Channel estimation method, device and equipment based on super nested structure pilot frequency distribution - Google Patents
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Abstract
The embodiment of the application provides a channel estimation method, device and equipment based on super-nested structure pilot frequency distribution. The method comprises the following steps: performing OFDM demodulation and pilot compensation according to the received original signal to obtain a first received signal on a pilot subcarrier; determining a corresponding target pilot carrier covariance matrix according to the first received signal; constructing a pilot frequency position difference set according to the pilot frequency distribution of the super-nested structure, screening and rearranging the pilot frequency position difference set, and determining a section of continuous position difference with the maximum length; selecting elements corresponding to the continuous position difference from the vectorized target pilot carrier covariance matrix as a second receiving signal; and based on the second received signal, carrying out channel estimation by constructing a dictionary matrix and adopting an OMP algorithm. The technical scheme of the embodiment of the application can improve the performance of channel estimation while reducing the pilot frequency redundancy required by the channel estimation.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method, an apparatus, and a device for channel estimation based on super nested structure pilot distribution.
Background
In recent years, the development of underwater wireless communication technology has driven the evolution and transformation of the human marine activity pattern. Among the common underwater acoustic communication technologies, OFDM (Orthogonal frequency-division multiplexing, orthogonal frequency division multiplexing) technology has become one of the key technologies for high-speed communication due to its advantages of high-frequency band utilization, strong multipath interference resistance, low complexity, etc. In the current technical scheme, for an OFDM underwater acoustic communication system, a common pilot frequency distribution scheme includes a uniform pilot frequency distribution and a random pilot frequency distribution, and if the uniform pilot frequency distribution is adopted, if a large delay spread underwater acoustic channel is to be estimated effectively, pilot frequency data needs to be added, more bandwidth resources are occupied, and if the random pilot frequency distribution is adopted, the performance of channel estimation is reduced, so that the performance of the underwater acoustic communication system is affected. Therefore, how to improve the performance of channel estimation while reducing the pilot redundancy required for channel estimation is a technical problem to be solved.
Disclosure of Invention
The embodiment of the application provides a channel estimation method, device and equipment based on super nested structure pilot frequency distribution, and further can improve the performance of channel estimation while reducing pilot frequency redundancy required by the channel estimation at least to a certain extent.
Other features and advantages of the present application will be apparent from the following detailed description, or may be learned in part by the practice of the application.
According to an aspect of an embodiment of the present application, there is provided a channel estimation method based on super nested structure pilot distribution, including:
performing OFDM demodulation and pilot compensation according to a received original signal to obtain a first received signal on a pilot subcarrier, wherein a transmitting signal corresponding to the original signal has super-nested structure pilot distribution and is subjected to OFDM modulation;
determining a corresponding target pilot carrier covariance matrix according to the first received signal;
constructing a pilot frequency position difference set according to the pilot frequency distribution of the super-nested structure, screening and rearranging the pilot frequency position difference set, and determining a section of continuous position difference with the maximum length;
vectorizing the target pilot carrier covariance matrix, and selecting elements corresponding to the continuous position difference from the vectorized target pilot carrier covariance matrix as a second receiving signal;
and based on the second received signal, carrying out channel estimation by constructing a dictionary matrix and adopting an OMP algorithm.
According to an aspect of an embodiment of the present application, there is provided a channel estimation apparatus based on super nested structure pilot distribution, including:
the receiving module is used for carrying out OFDM demodulation and pilot frequency compensation according to the received original signals to obtain first receiving signals on pilot frequency subcarriers, and the transmitting signals corresponding to the original signals have super-nested structure pilot frequency distribution and are subjected to OFDM modulation;
the first determining module is used for determining a corresponding target pilot carrier covariance matrix according to the first received signal;
the second determining module is used for constructing a pilot frequency position difference set according to the pilot frequency distribution of the super-nested structure, screening and rearranging the pilot frequency position difference set, and determining a section of continuous position difference with the maximum length;
the screening module is used for vectorizing the target pilot carrier covariance matrix and selecting elements corresponding to the continuous position difference from the vectorized target pilot carrier covariance matrix as a second receiving signal;
and the processing module is used for carrying out channel estimation by constructing a dictionary matrix and adopting an OMP algorithm based on the second received signal.
According to an aspect of the embodiments of the present application, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements a channel estimation method based on super nested structure pilot distribution as described in the above embodiments.
According to an aspect of an embodiment of the present application, there is provided an electronic device including: one or more processors; and a storage means for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the channel estimation method based on super-nested structure pilot distribution as described in the above embodiments.
According to an aspect of embodiments of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the channel estimation method based on the super-nested structure pilot distribution provided in the above embodiment.
In the technical schemes provided by some embodiments of the present application, OFDM demodulation and pilot compensation are performed according to a received original signal, so as to obtain a first received signal on a pilot subcarrier, where a transmission signal corresponding to the original signal has a pilot distribution with a super-nested structure and is subjected to OFDM modulation, so that, in combination with advantages of a super-nested array technology in the field of array signal processing, the pilot distribution is designed into a super-nested structure, and pilot redundancy required by channel estimation can be reduced. And, through constructing pilot frequency position difference and pilot frequency covariance matrix, screen the element of pilot frequency covariance matrix corresponding to the continuous position difference of rearrangement, regard it as the signal received on the continuous even virtual pilot frequency to carry on the channel estimation, can improve the performance of the channel estimation.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. It is apparent that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art. In the drawings:
fig. 1 shows a flow diagram of a method of channel estimation based on super-nested structure pilot distribution according to one embodiment of the present application;
fig. 2 illustrates a block diagram of a channel estimation device based on super-nested structure pilot distribution according to one embodiment of the present application;
fig. 3 shows a schematic diagram of a computer system suitable for use in implementing the electronic device of the embodiments of the present application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the present application. One skilled in the relevant art will recognize, however, that the aspects of the application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the application.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
Fig. 1 shows a flow diagram of a channel estimation method based on super-nested structure pilot distribution according to an embodiment of the present application, which can be applied to an OFDM underwater acoustic communication system.
As shown in fig. 1, the method at least includes steps S110 to S150, and is described in detail as follows:
in step S110, OFDM demodulation and pilot compensation are performed according to the received original signal, so as to obtain a first received signal on a pilot subcarrier, where a transmission signal corresponding to the original signal has a pilot distribution with a super-nested structure and is subjected to OFDM modulation.
In this embodiment, for an OFDM underwater acoustic communication system, pilot design may be performed based on the super-nested array principle such that a transmission signal has a super-nested structure pilot distribution and is OFDM-modulated before being transmitted. Then, after the receiving end receives the signal, the receiving end performs OFDM demodulation and pilot compensation on the received original signal, so as to obtain a first received signal on a pilot subcarrier.
In step S120, a corresponding target pilot carrier covariance matrix is determined according to the first received signal.
In one embodiment, after passing through one multipath channel with L paths, the expression of the first received signal in the frequency domain is:
wherein n is an equivalent noise vector;N P p is the total frequency guide m For the position of the mth pilot frequency, L is the number of channel multipaths, τ l For the delay of the first multipath, A l Is the equivalent amplitude of the first multipath.
Assuming that the number of samples N of the first received signal X is large enough and that the paths of signals are independent of each other, the theoretical pilot carrier covariance matrix R xx Can be modeled as:
wherein ( H Represents the conjugate transpose operator, a= [ ζ ] 1 ,ξ 2 ,…ξ L ]The method comprises the steps of carrying out a first treatment on the surface of the Covariance matrix R of channel s ＝diag{A 1 2 ,…A L 2 }，A i 2 (i=1, 2 … L) represents the power of the ith multipath, δ n 2 In order for the noise power to be high,is an identity matrix.
Thus, based on the above formula, the corresponding target pilot carrier covariance matrix can be determined based on the first received signal.
In one embodiment of the present application, determining a corresponding target pilot carrier covariance matrix according to the first received signal includes:
if the number of the first received signals is smaller than a preset threshold value, determining the channel time delay and the amplitude corresponding to the first received signals by constructing a dictionary matrix and adopting an OMP algorithm based on the first received signals;
according to the channel time delay and the amplitude, determining a cross-correlation value between each multipath signal and other multipath signals to obtain a multipath cross-correlation matrix;
determining an initial pilot carrier covariance matrix corresponding to the first received signal according to the first received signal;
subtracting the multipath cross correlation matrix from the initial pilot carrier covariance matrix to obtain a corrected initial pilot carrier covariance matrix, and taking the corrected initial pilot carrier covariance matrix as a target pilot carrier covariance matrix corresponding to the first received signal.
In this embodiment, when the number of signals of the first reception signal X is small, that is, smaller than a predetermined threshold, the mutual interference R between noise and signals of each path is taken into consideration cor The initial pilot carrier covariance matrix corresponding to the first received signal is:
wherein, for calculating R cor The channel delay and amplitude of the first received signal X can be determined by constructing a dictionary matrix and using OMP algorithm according to the first received signal X, so as to estimate the cross-correlation value between each multipath signal and other multipath signals, thereby obtaining a multipath cross-correlation matrix Is an estimated value. Then subtracting the multipath cross-correlation matrix from the initial pilot carrier covariance matrix corresponding to the first received signal>To correct, obtain corrected initial pilot carrier covariance matrix +.>
For the followingThe (i, j) th element of which comes from contribution xi of all paths l [i]ξ l [j] H L is from 0 to L-1. And for all l, ζ l [i]ξ l [j] H The value of (2) depends on the difference between the positions of the ith and jth pilots. Thus, the corrected initial pilot carrier covariance matrix is used as a target pilot carrier covariance matrix for subsequent calculation.
In step S130, pilot frequency position differences are constructed according to the pilot frequency distribution of the super nested structure, and the pilot frequency position differences are screened and rearranged to determine a segment of continuous position differences with the maximum length.
In one embodiment, pilot design is based on the principle of super-nested arrays, which can be subdivided into 1 st order, 2 nd order, 3 rd order, 4 th order, etc. The common nested array structure is a super-nested array when the order is 1, and taking a 2-order super-nested array as an example, the pilot frequency position index satisfies the following relation:
let the number of pilots in the two sub-arrays be N 1 And N 2 Satisfy N 1 ≥4,N 2 And (3) the pilot frequency position set P with the super nested structure meets the following conditions:
P＝X 1 ∪Y 1 ∪X 2 ∪Y 2 ∪Z 1 ∪Z 2
wherein,
X 1 ＝{1+2l|0≤l≤A 1 }
Y 1 ＝{(N 1 +1)-(1+2l)|0≤l≤B 1 }
X 2 ＝{(N 1 +1)+(2+2l)|0≤l≤A 2 }
Y 2 ＝{2(N 1 +1)-(2+2l)|0≤l≤B 2 }
Z 1 ＝{l(N 1 +1)|2≤l≤N 2 }
Z 2 ＝{N 2 (N 1 +1)-1}
reference parameter A 1 ,B 1 ,A 2 ,B 2 Defined by:
where r is an integer.
By adopting the pilot frequency distribution with the super nested structure, the pilot frequency position difference set is constructed as follows:
C P ＝{k|k＝u-v,u∈P，v∈P}
wherein P is the pilot frequency position set of the super nested structure. It is clear that there are many repeating elements in the pilot position difference set, i.e. there are many repeating elements in the target pilot covariance matrix.
Thus, based on the above super nested structure pilot distribution, the pilot position difference set C P The longest continuous and uniform position difference is selected, and according to the operation rule of Khatri-Rao product, the array element number of the differential array of the structure is 2N 1 N 2 +2N 2 -1,(N 1 ≥N 2 ) I.e. the maximum length of the successive position differences is 2N 1 N 2 +2N 2 -1，N 1 And N 2 The number of pilots in the two subarrays, respectively.
In step S140, the target pilot carrier covariance matrix is vectorized, and an element corresponding to the continuous position difference is selected from the vectorized target pilot carrier covariance matrix as a second received signal.
In this embodiment, the target pilot carrier covariance matrix is vectorized based on it, and in one example, the elements at the same position in each column thereof may be accumulated to obtain a corresponding vector. Specifically, vectorization is performed according to the following formula:
p＝[A 1 2 ,A 2 2 ,…A L 2 ] T
wherein,the representation will->Each row is accumulated to form a vector, ">As a rule, khatri-Rao product, A * Representing the conjugate matrix of matrix a.
The obtained vector Z is ranged from-N according to the pilot position difference 1 N 2 -N 2 -1 to N 1 N 2 +N 2 -1, screening and rearranging in sequence. Finally, the product with 2N 1 N 2 +2N 2 -1 a second received signal Z corresponding to a virtual pilot of successive position differences 1 ，Z 1 The following formula is satisfied:
wherein A is 1 And i 1 Respectively is opposite toAnd->And processing according to the screening rules.
In step S150, based on the second received signal, channel estimation is performed by constructing a dictionary matrix and using OMP algorithm.
In this embodiment, the second received signal Z is acquired 1 Then, a dictionary vector A 'with high precision is sampled by constructing' 1 (i.e., dictionary matrix) estimating the delay [ tau ] of each path of the channel by using OMP algorithm 1 ,…,τ L ]And corresponding power [ A 1 2 ,…A L 2 ] T 。
In one embodiment of the present application, an estimated cross-correlation matrix is first utilizedCorrecting to obtain initial pilot carrier covariance matrix +.>Then according to the corrected initial pilot carrier covariance matrix +.>Establishing an optimization problem by adopting a covariance matrix fitting criterion, and solving a covariance matrix meeting the minimum covariance matrix fitting criterion, namely an ideal pilot carrier covariance matrix R xx The ideal pilot carrier covariance matrix R obtained by fitting xx And serving as a target pilot carrier covariance matrix corresponding to the first received signal.
In this embodiment, the above-described modified initial pilot carrier covariance matrix is implemented using a sparse iterative covariance SPICE estimation algorithmFitting to an ideal pilot carrier covariance matrix R xx Further improving the channel estimation performance.
Specifically, it is assumed that the signal passes through a multipath channel of L paths, and the multipath delay range is [0, T]Using N P The pilot estimates L channels, the signal and noise being uncorrelated. In the multipath delay range [0, T]Q delay grid points are internally divided, and Q > L is that the delay of L multipath channels is contained on the Q delay grid points, then in the frequency domain, the received signal on the pilot subcarrier can be expressed as:
wherein N represents the number of samples of the received signal on the pilot subcarrier, Y (N) represents the nth received signal, s k (n) represents the equivalent amplitude at the kth multipath delay under the nth received signal, e (n) is zero-mean additive white gaussian noise.P m For the position of the mth pilot, m=0, 1, … N p -1，τ k K=1, 2, …, Q for the kth candidate multipath delay.
The pilot carrier covariance matrix can be written as:
wherein R is s ＝E[S(n)S H (n)]Representing the covariance matrix of the channel, S (n) = [ S ] 1 (n),s 2 (n),…,s Q (n)] T B represents N p Array popularity matrix of XQ, sigma n ,n＝1,2…N p Representing the noise power. The covariance matrix may be further expressed as:
wherein,s k is the equivalent amplitude on the kth multipath delay.
The covariance matrix fitting criterion adopted is as follows:
wherein R is xx For an ideal pilot carrier covariance matrix,for the covariance matrix estimated with the number of N received signal samples, in the example, the estimated cross-correlation matrix is used +.>Correction-derived->Instead of it. At the same time, in order to solve the above formula, by simple operationThe minimization f can be converted into
Wherein the method comprises the steps of
Equivalent to a minimization functionConverting it to minimization problems with limitations:
wherein,solving the above-mentioned minimization problem by means of covariance matrix fitting criterion, and finally fitting the obtained covariance matrix +.>Can be approximated as an ideal pilot carrier covariance matrix R xx . During the iterative process, the algorithm estimates covariance matrix +_due to the initial initialization>The first step, which directly affects the algorithm execution, is to initialize the power spectrum estimation, so if the number of received signal samples N is larger, the noise pair estimation covariance matrix can be reduced>The influence of the (B) is that the SPICE algorithm can further reduce the estimated covariance matrix in the fitting process>And ideal covariance matrix R xx Is a fitting error of (a). Therefore, under the condition that the number of the received signal samples is large, the SPICE algorithm is used for estimating the covariance matrix, so that the error is greatly reduced, and meanwhile, the channel estimation performance can be further improved.
SPICE algorithm can be summarized in two major steps: initially initializing a power spectrum estimation:
the following iterative process is then repeated until convergence:
updating p at each iteration k At the same time utilize p k Updating the estimated covariance matrix to power p of the last iteration k Calculating an estimated covariance matrixThe covariance matrix estimated at this time +.>Meets the minimization fit criterion f and usesAs the covariance matrix of the target pilot carrier corresponding to the first received signal, so as to perform subsequent channel estimation.
The following describes an embodiment of an apparatus of the present application, which may be used to perform the channel estimation method based on super-nested structure pilot distribution in the above embodiment of the present application. For details not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the channel estimation method based on super-nested structure pilot distribution described in the present application.
Fig. 2 illustrates a block diagram of a channel estimation device based on super-nested structured pilot distribution, according to one embodiment of the present application.
Referring to fig. 2, a channel estimation apparatus based on super nested structure pilot distribution according to an embodiment of the present application includes:
the receiving module 210 is configured to perform OFDM demodulation and pilot compensation according to a received original signal, so as to obtain a first received signal on a pilot subcarrier, where a transmission signal corresponding to the original signal has a pilot distribution with a super-nested structure and is subjected to OFDM modulation;
a first determining module 220, configured to determine a corresponding target pilot carrier covariance matrix according to the first received signal;
a second determining module 230, configured to construct a pilot position difference set according to the pilot distribution of the super nested structure, and screen and reorder the pilot position difference set to determine a continuous position difference with a maximum length;
a screening module 240, configured to vectorize the target pilot carrier covariance matrix, and select an element corresponding to the continuous position difference from the vectorized target pilot carrier covariance matrix as a second received signal;
a processing module 250, configured to perform channel estimation by constructing a dictionary matrix and using OMP algorithm based on the second received signal.
In one embodiment of the present application, the first determining module 220 is configured to:
if the number of the first received signals is smaller than a preset threshold value, determining the channel time delay and the amplitude corresponding to the first received signals by constructing a dictionary matrix and adopting an OMP algorithm based on the first received signals;
according to the channel time delay and the amplitude, determining a cross-correlation value between each multipath signal and other multipath signals to obtain a multipath cross-correlation matrix;
determining an initial pilot carrier covariance matrix corresponding to the first received signal according to the first received signal;
subtracting the multipath cross correlation matrix from the initial pilot carrier covariance matrix to obtain a corrected initial pilot carrier covariance matrix, and taking the corrected initial pilot carrier covariance matrix as a target pilot carrier covariance matrix corresponding to the first received signal.
In one embodiment of the present application, after obtaining the corrected initial pilot carrier covariance matrix, the first determining module 220 is further configured to:
and establishing an optimization problem by adopting a covariance matrix fitting criterion according to the corrected initial pilot carrier covariance matrix, solving a covariance matrix meeting the minimized covariance matrix fitting criterion, and taking the covariance matrix obtained by fitting as a target pilot carrier covariance matrix corresponding to the first received signal.
In one embodiment of the present application, the screening module 240 is configured to:
and accumulating the elements at the same position in each column of the target pilot carrier covariance matrix to obtain a corresponding vector.
Fig. 3 shows a schematic diagram of a computer system suitable for use in implementing the electronic device of the embodiments of the present application.
It should be noted that, the computer system of the electronic device shown in fig. 3 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present application.
As shown in fig. 3, the computer system includes a central processing unit (Central Processing Unit, CPU) 301 that can perform various appropriate actions and processes, such as performing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 302 or a program loaded from a storage section 308 into a random access Memory (Random Access Memory, RAM) 303. In the RAM 303, various programs and data required for the system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. An Input/Output (I/O) interface 305 is also connected to bus 304.
The following components are connected to the I/O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output portion 307 including a Cathode Ray Tube (CRT), a liquid crystal display (Liquid Crystal Display, LCD), and the like, a speaker, and the like; a storage section 308 including a hard disk or the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. The drive 310 is also connected to the I/O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage section 308 as needed.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 309, and/or installed from the removable medium 311. When executed by a Central Processing Unit (CPU) 301, performs the various functions defined in the system of the present application.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by means of software, or may be implemented by means of hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
As another aspect, the present application also provides a computer-readable medium that may be contained in the electronic device described in the above embodiment; or may exist alone without being incorporated into the electronic device. The computer-readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to implement the methods described in the above embodiments.
It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit, in accordance with embodiments of the present application. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a usb disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the method according to the embodiments of the present application.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains.
It is to be understood that the present application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (9)
1. The channel estimation method based on the pilot frequency distribution of the super-nested structure is characterized by comprising the following steps:
performing OFDM demodulation and pilot compensation according to a received original signal to obtain a first received signal on a pilot subcarrier, wherein a transmitting signal corresponding to the original signal has super-nested structure pilot distribution and is subjected to OFDM modulation;
determining a corresponding target pilot carrier covariance matrix according to the first received signal;
constructing a pilot frequency position difference set according to the pilot frequency distribution of the super-nested structure, screening and rearranging the pilot frequency position difference set, and determining a section of continuous position difference with the maximum length;
vectorizing the target pilot carrier covariance matrix, and selecting elements corresponding to the continuous position difference from the vectorized target pilot carrier covariance matrix as a second receiving signal;
and based on the second received signal, carrying out channel estimation by constructing a dictionary matrix and adopting an OMP algorithm.
2. The method of claim 1, wherein determining a corresponding target pilot carrier covariance matrix from the first received signal comprises:
if the number of the first received signals is smaller than a preset threshold value, determining the channel time delay and the amplitude corresponding to the first received signals by constructing a dictionary matrix and adopting an OMP algorithm based on the first received signals;
according to the channel time delay and the amplitude, determining a cross-correlation value between each multipath signal and other multipath signals to obtain a multipath cross-correlation matrix;
determining an initial pilot carrier covariance matrix corresponding to the first received signal according to the first received signal;
subtracting the multipath cross correlation matrix from the initial pilot carrier covariance matrix to obtain a corrected initial pilot carrier covariance matrix, and taking the corrected initial pilot carrier covariance matrix as a target pilot carrier covariance matrix corresponding to the first received signal.
3. The method of claim 2, wherein after obtaining the modified initial pilot carrier covariance matrix, the method further comprises:
and establishing an optimization problem by adopting a covariance matrix fitting criterion according to the corrected initial pilot carrier covariance matrix, solving a covariance matrix meeting the minimized covariance matrix fitting criterion, and taking the covariance matrix obtained by fitting as a target pilot carrier covariance matrix corresponding to the first received signal.
4. The method of claim 1, wherein vectoring the target pilot carrier covariance matrix comprises:
and accumulating the elements at the same position in each column of the target pilot carrier covariance matrix to obtain a corresponding vector.
5. A channel estimation device based on super nested structure pilot distribution, comprising:
the receiving module is used for carrying out OFDM demodulation and pilot frequency compensation according to the received original signals to obtain first receiving signals on pilot frequency subcarriers, and the transmitting signals corresponding to the original signals have super-nested structure pilot frequency distribution and are subjected to OFDM modulation;
the first determining module is used for determining a corresponding target pilot carrier covariance matrix according to the first received signal;
the second determining module is used for constructing a pilot frequency position difference set according to the pilot frequency distribution of the super-nested structure, screening and rearranging the pilot frequency position difference set, and determining a section of continuous position difference with the maximum length;
the screening module is used for vectorizing the target pilot carrier covariance matrix and selecting elements corresponding to the continuous position difference from the vectorized target pilot carrier covariance matrix as a second receiving signal;
and the processing module is used for carrying out channel estimation by constructing a dictionary matrix and adopting an OMP algorithm based on the second received signal.
6. The apparatus of claim 5, wherein the first determining module is configured to:
if the number of the first received signals is smaller than a preset threshold value, determining the channel time delay and the amplitude corresponding to the first received signals by constructing a dictionary matrix and adopting an OMP algorithm based on the first received signals;
according to the channel time delay and the amplitude, determining a cross-correlation value between each multipath signal and other multipath signals to obtain a multipath cross-correlation matrix;
determining an initial pilot carrier covariance matrix corresponding to the first received signal according to the first received signal;
subtracting the multipath cross correlation matrix from the initial pilot carrier covariance matrix to obtain a corrected initial pilot carrier covariance matrix, and taking the corrected initial pilot carrier covariance matrix as a target pilot carrier covariance matrix corresponding to the first received signal.
7. The apparatus of claim 6, wherein the first determining means is further for, after obtaining the modified initial pilot carrier covariance matrix:
and establishing an optimization problem by adopting a covariance matrix fitting criterion according to the corrected initial pilot carrier covariance matrix, solving a covariance matrix meeting the minimized covariance matrix fitting criterion, and taking the covariance matrix obtained by fitting as a target pilot carrier covariance matrix corresponding to the first received signal.
8. A computer readable medium on which a computer program is stored, which when executed by a processor implements a channel estimation method based on super nested structure pilot distribution as claimed in any one of claims 1 to 4.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of channel estimation based on super-nested structure pilot distribution as claimed in any one of claims 1 to 4.
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