CN116132225A - Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium - Google Patents

Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium Download PDF

Info

Publication number
CN116132225A
CN116132225A CN202310025439.9A CN202310025439A CN116132225A CN 116132225 A CN116132225 A CN 116132225A CN 202310025439 A CN202310025439 A CN 202310025439A CN 116132225 A CN116132225 A CN 116132225A
Authority
CN
China
Prior art keywords
pilot
channel matrix
end antenna
coordinate
equivalent channel
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310025439.9A
Other languages
Chinese (zh)
Inventor
唐燕群
尹浩然
魏玺章
赖涛
邓天伟
姜园
赵磊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sun Yat Sen University
Original Assignee
Sun Yat Sen University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sun Yat Sen University filed Critical Sun Yat Sen University
Priority to CN202310025439.9A priority Critical patent/CN116132225A/en
Publication of CN116132225A publication Critical patent/CN116132225A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention relates to the technical field of wireless communication, and discloses a pilot frequency auxiliary diagonal reconstruction channel estimation method, a system, equipment and a medium, which are applied to a multi-input multi-output radio frequency division multiplexing wireless communication system. The method is realized in a discrete affine Fourier transform domain, the positions of pilot symbols in a transmission signal are reasonably arranged on any transmitting end antenna according to the cycle characteristic of an equivalent channel matrix, the pilot symbols received by any receiving end antenna are non-zero bands of a certain column in the equivalent channel matrix between the transmitting end antenna and the receiving end antenna, then the diagonal reconstruction is carried out on the received pilot symbols according to the diagonal reconstruction characteristic of the equivalent channel matrix in an AFDM domain, the non-zero bands of other columns in the equivalent channel matrix are deduced, and then the equivalent channel matrix between each pair of transmitting end antennas and the receiving end antenna is estimated, so that the channel estimation is realized. The method has the advantages of high channel estimation accuracy, low calculation complexity and very wide application prospect in engineering.

Description

Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium
Technical Field
The present invention relates to the field of wireless communications technologies, and in particular, to a method, a system, an apparatus, and a medium for pilot-assisted diagonal reconstruction channel estimation.
Background
Currently, in a multiple-input-multiple-output (MIMO) system based on an analog radio frequency division multiplexing (AFDM, affine frequency division multiplexing), in order to equalize and detect a received signal of each receiving antenna, a complex channel through which the signals pass needs to be estimated to obtain all channel state information, and the detection performance of a receiver directly depends on the accuracy of channel estimation. How to implement low complexity and accurate channel estimation is a problem to be solved in a multiple-input multiple-output radio frequency-imitated multiplexing (MIMO-AFDM) wireless communication system, compared to a single antenna radio frequency-imitated multiplexing system.
Disclosure of Invention
The invention provides a pilot frequency auxiliary diagonal reconstruction channel estimation method, a system, equipment and a medium, which solve the problem of how to implement low-complexity and accurate channel estimation in a multi-input multi-output radio frequency division multiplexing wireless communication system.
To solve the above technical problem, a first aspect of the present invention provides a pilot-assisted diagonal reconstruction channel estimation method, which is applied to a mimo-rf-like multiplexing wireless communication system, and the method includes the following steps:
Setting pilot symbols at preset positions of transmission signals sent by any transmitting end antenna, and determining first coordinates corresponding to the pilot symbols at the preset positions;
in the received signal of any receiving end antenna, determining a second coordinate of the pilot symbol in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna according to the first coordinate;
performing threshold-based energy detection according to the absolute amplitude of the second coordinate to obtain a non-zero value with a large value in a column to which the first coordinate belongs in the equivalent channel matrix;
and carrying out diagonal reconstruction on the non-zero values with large values in the columns to which the first coordinates belong, delivering out the non-zero values with large values in the rest columns in the equivalent channel matrix, and obtaining the equivalent channel matrix of all the transmitting end antennas and the receiving end antennas in the discrete affine Fourier transform domain according to the non-zero values with large values in all the columns.
Further, the preset positions are in one-to-one correspondence with the first coordinates, and the first coordinates are determined through the following formula:
Figure BDA0004044666890000021
wherein t=1, 2, … …, N t X is the transmitting end antenna t [m]For the transmission signal transmitted by the t-th transmitting-end antenna, m1 is a first coordinate,
Figure BDA0004044666890000022
Is a first numerical value, l max For maximum time delay, alpha max Is the maximum integer Doppler shift, k v Is a non-negative integer for the spacing factor.
Further, a matrix expression between a transmission signal transmitted by any one of the transmitting-end antennas and a reception signal received by any one of the receiving-end antennas is as follows:
y＝H r,t x+w
wherein y is a received signal vector of a receiving end antenna in a DAFT domain, x is a transmitted signal vector of a transmitting end antenna in the DAFT domain, w is a noise vector, and H r,t Is an equivalent channel matrix between any transmitting antenna and any receiving antenna.
Further, the second coordinate is as follows:
Figure BDA0004044666890000023
wherein m2 is a second coordinate.
Further, threshold-based energy detection is performed by the following formula:
Figure BDA0004044666890000024
in the method, in the process of the invention,
Figure BDA0004044666890000031
the method is characterized in that the method is a non-zero value with large numerical value in a column to which a first coordinate belongs in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna; r=1, 2, … …, N r Is a receiving end antenna; y is r [m2]The pilot frequency symbol corresponding to the second coordinate position in the received signal of the r receiving end antenna; />
Figure BDA0004044666890000032
The first coordinate of the t-th transmitting-end antenna.
Further, performing diagonal reconstruction on the non-zero value with large value in the column to which the first coordinate belongs, and delivering out the non-zero value with large value in the rest columns in the equivalent channel matrix, including:
Setting a conversion factor, multiplying the conversion factor by a non-zero value with a large value in a column to which the first coordinate belongs according to the cycle characteristic of the equivalent channel matrix to obtain the non-zero value with the large value in an unknown column to which the right lower diagonal of the column to which the first coordinate belongs in the equivalent channel matrix, and pushing out the non-zero values with the large value in the rest columns in the equivalent channel matrix.
Further, the conversion factor is of the formula:
Figure BDA0004044666890000033
in the method, in the process of the invention,
Figure BDA0004044666890000034
as a conversion factor, N is the number of subcarriers, subcarrier numbers m, m' =0, 1, … …, N-1, c 2 Is any irrational number or a rational number far smaller than 1/(2N), l' is a specific time delay () N Representing modulo N operation.
A second aspect of the present invention provides a pilot-aided diagonal reconstruction channel estimation system, the system being applied to a multiple-input multiple-output radio frequency division multiplexing-like wireless communication system, the system comprising:
the pilot frequency setting module is used for setting pilot frequency symbols at preset positions of transmission signals sent by any transmitting end antenna and determining first coordinates corresponding to the pilot frequency symbols at the preset positions;
the second coordinate acquisition module is used for determining a second coordinate of the pilot symbol in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna according to the first coordinate in a received signal of any receiving end antenna;
The energy detection module is used for carrying out threshold-based energy detection according to the absolute amplitude value of the second coordinate to obtain a non-zero value with a large value in a column to which the first coordinate belongs in the equivalent channel matrix;
and the channel estimation module is used for carrying out diagonal reconstruction on the non-zero values with large values in the columns to which the first coordinates belong, delivering out the non-zero values with large values in the rest columns in the equivalent channel matrix, and obtaining the equivalent channel matrix of all the transmitting end antennas and the receiving end antennas in the discrete affine Fourier transform domain according to the non-zero values with large values in all the columns.
A third aspect of the present invention provides an electronic device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the pilot-aided diagonal reconstruction channel estimation method according to any one of the first aspects above when the computer program is executed.
A fourth aspect of the present invention provides a computer readable storage medium comprising a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the pilot-aided diagonal reconstruction channel estimation method according to any one of the first aspects above.
The invention provides a pilot auxiliary diagonal reconstruction channel estimation method, a system, equipment and a medium, which have the beneficial effects that compared with the prior art, the embodiment of the invention has the following advantages: the method can be applied to a multi-input multi-output radio frequency division multiplexing wireless communication system, has low bit error rate and high accuracy when estimating the channel, occupies fewer communication resources compared with the traditional pilot auxiliary channel estimation method, has lower calculation complexity, greatly improves the efficiency of channel estimation, and has wide prospect in engineering.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of N provided by one embodiment of the present invention t ×N r A multiple-input multiple-output radio frequency division multiplexing imitated wireless communication system model diagram;
fig. 2 is a flow chart of a method for pilot-assisted diagonal reconstruction channel estimation according to an embodiment of the present invention;
Fig. 3 is an equivalent channel matrix H of a transmitting antenna and a receiving antenna according to an embodiment of the present invention 1,1 Wherein delta is a non-zero value of large value and blank is a non-zero value of small value;
FIG. 4 is a diagram of H provided by one embodiment of the present invention 1,1 A time domain Doppler correspondence graph of the 0 th row and the N-1 th column with multipath in the channel;
FIG. 5 is a schematic diagram of EPA-DR channel estimation implemented in a 2×1MISO-AFDM system (i.e., two transmitting antennas and one receiving antenna) according to one embodiment of the present invention, where P is a pilot symbol, 0 is a guard symbol, and x is a data symbol;
FIG. 6 is a graph of bit error rate versus SNR for different SNRps at integer Doppler according to an embodiment of the present invention;
FIG. 7 is a graph of bit error rate versus threshold for different SNRps for integer Doppler according to an embodiment of the present invention;
fig. 8 is a graph of bit error rate versus signal-to-noise ratio SNR at fractional doppler, srnp=45 dB for different separation factors according to an embodiment of the present invention;
fig. 9 is a graph of bit error rate versus noise power ratio SNRp at fractional doppler, srnp=14 dB for different separation factors, according to an embodiment of the present invention;
Fig. 10 is a diagram of a pilot-aided diagonal reconstruction channel estimation system according to an embodiment of the present invention
Fig. 11 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings and examples, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the step numbers used herein are for convenience of description only and are not limiting as to the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Term interpretation:
discrete affine fourier transform: the discrete affine fourier transform is a mathematical transform proposed by scientist Tomaso Erseghe in 2005, and the commonly used fourier transform is a special case. The transformation may implement a transformation of the discrete affine fourier transform domain with the time domain.
Double dispersion channel: the multipath delay spread and the Doppler spread of the channel can respectively cause a time domain dispersion effect and a frequency domain dispersion effect, and the channel which simultaneously presents the characteristics of the time domain dispersion and the frequency domain dispersion is called a double-dispersion channel and is also called a double-fading channel.
Imitation radio frequency division multiplexing: the simulated radio frequency division multiplexing is a novel waveform discovered in 2021 by Nassar Ksairi of French mathematics and algorithm laboratory and by Ali Bemani of European communication system laboratory. The waveform uses discrete affine Fourier transformation to realize the modulation and demodulation of information symbols, can overcome the problem of double dispersion caused by high-speed movement to a channel, and is one of the most potential candidate waveforms in a future 6G wireless communication network.
Channel estimation: channel estimation is a key technology for implementing wireless communications. In the process of wireless communication, a signal needs to pass through a wireless channel from a transmitting end to a receiving end, the channel can affect the signal, the receiving end needs to remove distortion and noise applied by the channel from the received signal in order to accurately extract information from the received signal, and in order to achieve the goal, the characteristic of the wireless channel needs to be estimated, and the process is called "channel estimation", and is generally classified into three types of estimation based on a reference signal, blind estimation and semi-blind estimation.
Pilot-assisted method: the pilot aided method is a method for channel estimation based on a reference signal. The pilot is one of the reference signals, and all information thereof is known to both the transmitting end and the receiving end. After the transmitting end places the pilot frequency at a proper position in the signal, the receiving end can estimate the channel according to the received pilot frequency symbol.
Multiple input multiple output system: the mimo system refers to a technical system for transmitting and receiving signals using multiple antennas in the field of wireless communication, which allows multiple transmitting antennas to simultaneously transmit signals and multiple receiving antennas to simultaneously receive signals, and improves system capacity, coverage and signal-to-noise ratio without increasing occupied bandwidth through space division multiplexing, space diversity and other technologies.
The first aspect of the present invention provides a pilot-aided diagonal reconstruction channel estimation method, which can be applied to N as shown in fig. 1 t ×N r The method comprises the steps that in a multi-input multi-output radio frequency division multiplexing imitated wireless communication system model diagram; wherein N is t N is the number of transmitting end antennas r The number of the antennas at the receiving end is an integer greater than zero. Let x be 1 ,x 2 ,……,x Nt A signal vector to be transmitted (each vector size is n×1) composed of N quadrature amplitude modulation (QAM, quadrature amplitude modulation) symbols in a discrete affine fourier transform domain, which represent signals transmitted by the transmitting-end antennas 1. Each transmitting-end antenna performs serial-parallel conversion on a discrete affine Fourier transform (discrete affine Fourier transform, DAFT) domain signal, N-point inverse discrete affine Fourier transform, adds a linear modulation cyclic prefix (CPP) and performs parallel-serial conversion to obtain N t Time-domain signal vectors s 1 ,s 2 ,……,s Nt And then transmitted to the double-dispersion wireless channel through the antenna. Each receiving end antenna receives the time domain signal vector d 1 ,d 2 ,……,d Nr Performing serial-parallel conversion, cutting CPP and N point discrete affine Fourier transform, and obtaining a received DAFT domain signal vector y after the parallel-serial conversion 1 ,y 2 ,…,y Nr (each vector has a size of n×1) and represents signals received by the receiving- end antennas 1,2, …, nr, respectively. For successful subsequent equalization and detection, the channel must be estimated.
In order to achieve low complexity and accurate channel estimation in a mimo-rf-like wireless communication system, a method for efficient pilot-assisted diagonal reconstruction channel estimation implemented in the DAFT domain, which may also be referred to as an embedded pilot-assisted diagonal reconstruction (EPA-DR) method, as shown in fig. 2, includes the following steps:
s1, setting pilot symbols at preset positions of transmission signals sent by any transmitting end antenna, and determining first coordinates corresponding to the pilot symbols at the preset positions;
specifically, in the channel estimation, the common pilot auxiliary method needs to determine a proper position to set a pilot symbol in a signal sent by a sending end, and since pilot is one of reference signals, the sending end and a receiving end are both aware of all information of the reference signal, and the receiving end can estimate a channel according to the received pilot symbol. In the MIMO-type radio frequency division multiplexing wireless communication system, the transmitting end antenna and the receiving end antenna are multiple and are in a corresponding relationship of many-to-many. In the EPA-DR channel estimation method adopted in the application, pilot symbols are set at preset positions of transmitting signals sent by any transmitting end antenna, and first coordinates corresponding to the pilot symbols at the preset positions are determined.
In a specific embodiment, the preset positions are in one-to-one correspondence with the first coordinates, and the first coordinates are determined by the following formula:
Figure BDA0004044666890000081
wherein t=1, 2, … …, N t X is the transmitting end antenna t [m]For the transmission signal transmitted by the t-th transmitting-end antenna, m1 is a first coordinate,
Figure BDA0004044666890000082
is a first numerical value, l max For maximum time delay, alpha max Is the maximum integer Doppler shift, k v Is a non-negative integer for the spacing factor.
Optionally, a transmitting antenna is used to set the pilot signal, and then the preset position in the transmitting signal of the transmitting antenna is corresponding to the first coordinate. The EPA-DR channel estimation method firstly estimates the equivalent channel matrix between a single pair of receiving and transmitting antennas, and then pushes out the equivalent channel matrix between all receiving and transmitting antennas in the MIMO-AFDM wireless communication system according to the equivalent channel matrix between the single pair of receiving and transmitting antennas, thereby realizing channel estimation. The method reduces the computational complexity, can improve the accuracy of channel estimation, and has a wide application prospect.
S2, determining a second coordinate of the pilot symbol in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna according to the first coordinate in a received signal of any receiving end antenna;
Specifically, when there is only one transmitting antenna and one receiving antenna, the relationship between the received signal of the receiving end and the transmitted signal of the transmitting end is:
Figure BDA0004044666890000091
wherein y [ m ]]Is a receiving signal of a receiving end; x [ m ]']Is a transmitting signal of a transmitting end; w [ m ]]For the noise of the receiving end antenna in the m sub-carrier wave, obeys zero mean value, and the variance is N 0 Is a gaussian distribution of (c); n is the number of subcarriers; subcarrier sequence number m, m' =0, 1, … …, N-1; p is more than or equal to 1, which is the number of multipaths between the receiving end antenna and the transmitting end antenna; h is a i Is the channel gain of the ith sub-path; l (L) i Is the integer time delay normalized by the sampling interval of the ith sub-path; v i ＝α i +β i Is Doppler frequency shift normalized by the sub-carrier interval of the ith sub-path, alpha i ∈(-α max ,α max ) Is v i Integer part, beta i E (-0.5, 0.5) is v i Fractional part, alpha max Is the maximum integer Doppler shift, ind i ＝(α i +2Nc 1 l i ) N Is a coordinate factor () N Representing modulo N operation;
Figure BDA0004044666890000092
Figure BDA0004044666890000093
k v is a non-negative integer, c 2 Is any irrational number or far less than +.>
Figure BDA0004044666890000094
Is a rational number of (c).
For convenience, let:
first reduction factor
Figure BDA0004044666890000095
Second reduction factor
Figure BDA0004044666890000096
Third reduction factor
Figure BDA0004044666890000097
Then, the relationship between the reception signal at the reception end and the transmission signal at the transmission end is simplified as follows:
Figure BDA0004044666890000098
the matrix corresponding to the above formula is expressed as:
y＝H 1,1 x+w
Wherein y is a received signal vector of a receiving end antenna in a DAFT domain, x is a transmitted signal vector of a transmitting end antenna in the DAFT domain, w is a noise vector, and the sizes of the noise vector and the noise vector are N multiplied by 1, H 1,1 Is an equivalent channel matrix between the first transmitting end antenna and the first receiving end antenna, the size is n×n, as shown in fig. 3, the equivalent channel matrix has a characteristic of cyclic diagonal angle, delta represents a non-zero value with a large value, and blank represents a non-zero value with a small value.
Then have N t Strip transmitting end antenna and N r Strip receivingThe following relationship is satisfied between a received signal in the DAFT domain of any receiving end antenna and a transmitted signal in the DAFT domain of any transmitting end antenna of the wireless communication system of the end antennas:
Figure BDA0004044666890000101
wherein y is r [m]For the received signal of the r-th receiving end antenna in the DAFT domain, x t [m']For the transmission signal of the t-th transmitting end antenna in the DAFT domain, w r [m]The noise of the r receiving end antenna in the m sub-carrier is subjected to zero mean value, and the variance is N 0 Is used for the distribution of the gaussian distribution of (c),
Figure BDA0004044666890000102
is the gain of the ith path between the (r) receiving end antenna and the (t) transmitting end antenna (the number of paths between the different receiving end antennas and the transmitting end antenna, the Doppler and time delay of each path are the same, only the path gains are different).
In a specific embodiment, the matrix expression between the transmission signal transmitted by any transmitting end antenna and the reception signal received by any receiving end antenna is as follows:
y＝H r,t x+w
wherein H is r,t Is an equivalent channel matrix between any transmitting antenna and any receiving antenna.
Customizing a first numerical value
Figure BDA0004044666890000103
Is arranged such that the equivalent channel matrix H 1,1 Non-zero values in (1) correspond to the paths of the particular delay and Doppler, H 1,1 The time domain Doppler correspondence between row 0 and column N-1 of (1) and multipath in the channel is shown in FIG. 4, it can be seen that H 1,1 Each row and each column has +.>
Figure BDA0004044666890000104
A large number of non-zero values, each darkeningNon-zero values respectively correspond to the paths of a specific delay and Doppler, and delta representing the same delay forms a delay block, so that each row and each column can be divided into (l) max +1) delay blocks. While determining parameter c 1 After that, equivalent channel matrix H 1,1 The correspondence of non-zero values in (c) to multipath is uniquely determined.
Since the pilot signal is a signal with the content known to both the receiving end and the transmitting end of the MIMO-AFDM wireless communication system, in the received signal of any receiving end antenna, the second coordinate of the pilot symbol in the equivalent channel matrix between any transmitting end antenna and any receiving end antenna can be determined according to the first coordinate. In one embodiment, the second coordinate is of the formula:
Figure BDA0004044666890000111
Wherein m2 is a second coordinate. The position of the pilot symbol in the received signal, the second coordinate, is determined, i.e., the content of the pilot symbol can be determined by threshold detection.
S3, carrying out energy detection based on a threshold according to the absolute amplitude value of the second coordinate to obtain a non-zero value with a large value in a column to which the first coordinate belongs in the equivalent channel matrix;
in one embodiment, threshold-based energy detection is performed by the following formula:
Figure BDA0004044666890000112
in the method, in the process of the invention,
Figure BDA0004044666890000113
the method is characterized in that the method is a non-zero value with large numerical value in a column to which a first coordinate belongs in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna; y is r [m2]The pilot frequency symbol corresponding to the second coordinate position in the received signal of the r receiving end antenna; />
Figure BDA0004044666890000114
Figure BDA0004044666890000115
The first coordinate of the t-th transmitting-end antenna.
The non-zero value with large value in the column to which the first coordinate belongs in the equivalent channel between any transmitting end antenna and any receiving end antenna is determined through threshold-based energy detection. Generally, the energy detection method is a common single-user spectrum sensing method, and adopts threshold-based energy detection to sense spectrum holes in a channel, so that a cognitive user can utilize the spectrum holes to transmit information, thereby relieving the contradiction between spectrum resource tension and communication service requirements. When the content of the pilot frequency symbol is determined, the application of the energy detection method greatly saves communication resources.
S4, carrying out diagonal reconstruction on the non-zero values with large values in the columns to which the first coordinates belong, pushing out the non-zero values with large values in the rest columns in the equivalent channel matrix, and obtaining the equivalent channel matrix of all the transmitting end antennas and the receiving end antennas in the discrete affine Fourier transform domain according to the non-zero values with large values in all the columns;
the equivalent channel matrix in EPA-DR channel estimation method has the characteristic of being capable of diagonally reconstructing; specific:
for convenience of expression, an equivalent channel matrix H between the first transmitting antenna and the first receiving antenna is used 1,1 The rewriting is as follows:
Figure BDA0004044666890000121
wherein H is 1,1 [m,m']For an equivalent channel matrix with a specific time delay, l' is the specific time delay; p (P) l' The number h of the sub-paths corresponding to the specific time delay l',j Gain, v for the j-th specific delay corresponding to the sub-path l',j The j-th specific delay corresponds to the fractional doppler.
Wherein H is r,t [m,m']Is the transmitted mth'The effect of the symbol on the subcarrier on the received mth subcarrier.
From the relation between the received signal at the receiving end and the transmitted signal at the transmitting end when there is only one transmitting antenna and one receiving antenna, it can be seen that for any subcarrier m, m' =0,..
Figure BDA0004044666890000122
Both the numerator and denominator of (2) are in relation to m-m' with N as period, therefore, the second reduction factor + >
Figure BDA0004044666890000123
Also, since m to m' are periodic with N, there are:
Figure BDA0004044666890000124
the conversion factor is defined as follows:
Figure BDA0004044666890000125
simplifying the conversion factor to obtain:
Figure BDA0004044666890000126
according to the first simplification factor, the simplified conversion factor has the following values according to m, m':
Figure BDA0004044666890000131
as can be seen from the above description,
Figure BDA0004044666890000132
the Doppler v of the path corresponding to the j-th specific time delay is related to the specific time delay l' only l',j Irrelevant (in particular, when parameter c 2 When set to 0, ++>
Figure BDA0004044666890000133
The computation is simplified).
Then the first time period of the first time period,
Figure BDA0004044666890000134
that is to say: as long as one ε (l', v) is obtained l',j M, m'), can be obtained by multiplying a conversion factor +.>
Figure BDA0004044666890000135
To obtain epsilon (l', v) l',j ,(m+1) N ,(m'+1) N )。/>
According to H after rewriting 1,1 The expression shows that H 1,1 [m,m']Lower right diagonal element H 1,1 [m+1) N ,(m'+1) N ]The method comprises the following steps:
Figure BDA0004044666890000136
convert it to be expressed by a conversion factor:
Figure BDA0004044666890000137
suppose (m, m') belongs to the first delay block, i.e. at H 1,1 The coordinates (m, m ') in (b) represent a certain sub-path with a delay of l, and when l ' +.l, ε (l ', ν) l',j The values of m, m ') are very small, and when l ' =l, ε (l ', v) l',j The values of m, m' are very large, so H 1,1 [m,m']Can be decomposed into the following main components
Figure BDA0004044666890000138
And minor ingredient->
Figure BDA0004044666890000139
Figure BDA00040446668900001310
Wherein the main components are
Figure BDA00040446668900001311
The minor component is
Figure BDA00040446668900001312
Similarly, H 1,1 [(m+1) N ,(m'+1) N ]Can also be decomposed into main components
Figure BDA00040446668900001313
Figure BDA00040446668900001314
And minor ingredient->
Figure BDA00040446668900001315
Figure BDA0004044666890000141
Wherein the main components are
Figure BDA0004044666890000142
The minor component is
Figure BDA0004044666890000143
According to an equivalent channel matrix H with a specific time delay 1,1 [m,m']Expression of the principal component of (c) and the lower right diagonal element H of the equivalent channel matrix with a specific delay 1,1 [(m+1) N ,(m'+1) N ]As can be seen from the expression of the main component of (c),
Figure BDA0004044666890000144
that is, H 1,1 [(m+1) N ,(m'+1) N ]The main component of (2) may be composed of H 1,1 [m,m']The main component conversion formula of the equivalent channel matrix with specific time delay at the right lower diagonal position of the equivalent channel matrix can be obtained by multiplying the main component of the equivalent channel matrix by a conversion factor:
Figure BDA0004044666890000145
the same principle is as follows:
Figure BDA0004044666890000146
by recursion, only a non-zero value with a large value in a certain column of the equivalent channel matrix is obtained, and the non-zero value with a large value in the right lower diagonal column of the column can be obtained by multiplying the non-zero value with a large value in the certain column by a conversion factor, so that the non-zero value with a large value in the whole equivalent channel matrix can be reconstructed diagonally in a recursion manner, and then the whole equivalent channel matrix is obtained, and channel estimation can be completed.
In a specific embodiment, performing diagonal reconstruction on the non-zero value with large value in the column to which the first coordinate belongs, and delivering out the non-zero value with large value in the other columns in the equivalent channel matrix, including:
setting a conversion factor, multiplying the conversion factor by a non-zero value with a large value in a column to which the first coordinate belongs according to the cycle characteristic of the equivalent channel matrix to obtain the non-zero value with the large value in an unknown column to which the right lower diagonal of the column to which the first coordinate belongs in the equivalent channel matrix, and pushing out the non-zero values with the large value in the rest columns in the equivalent channel matrix; wherein the conversion factor is of the formula:
Figure BDA0004044666890000151
In the method, in the process of the invention,
Figure BDA0004044666890000152
is a conversion factor.
The diagonal reconstruction characteristic of the equivalent channel matrix is applied to channel estimation, namely, the periodic characteristic of a subcarrier in the relation between a receiving signal of a receiving end and a transmitting signal of a transmitting end is utilized through a defined conversion factor, according to a known non-zero value with a certain column number value in the equivalent channel matrix between a certain pair of transmitting end antennas and the receiving end antennas, the non-zero value with a large value in the right lower diagonal column of the column is obtained through the product of the conversion factor and the non-zero value with a large column number value, and then according to the periodic characteristic of the equivalent channel matrix, the non-zero values with a large column number value in the equivalent channel matrix are recursively deduced, and then the equivalent channel matrix of the right lower diagonal position of the known equivalent channel matrix is deduced, and then the equivalent channel matrix between each pair of transmitting end antennas and the receiving end antennas in the multi-input multi-output imitated radio frequency division multiplexing wireless communication system is deduced, so that channel estimation is realized. The embedded diagonal reconstruction channel estimation method has the greatest advantages that the complexity is low, meanwhile, the accurate estimation of the channel can be realized, and the method has a very wide prospect in engineering.
Then there will be N t Strip transmitting end antenna and N r The relation between the received signal of the r receiving end antenna in the DAFT domain and the transmitted signal of the t transmitting end antenna in the DAFT domain in the wireless communication system of the receiving end antennas is expressed in the following compact matrix form:
Figure BDA0004044666890000153
Figure BDA0004044666890000161
in the method, the equivalent channel matrix of the DAFT domain between the r receiving end antenna and the t transmitting end antenna is H r,t ；w r Is the noise vector of the DAFT domain of the r-th receiving end antenna.
The compact matrix form is expressed in the following more compact form:
y MIMO ＝H MIMO x MIMO +w MIMO
in the method, in the process of the invention,
Figure BDA0004044666890000162
is the N t Transmitting DAFT domain signal vector of strip transmitting end antenna,>
Figure BDA0004044666890000163
is the N r Receiving DAFT domain signal vector of strip receiving end antenna,>
Figure BDA0004044666890000164
is the N r The strip receiving end antenna receives the DAFT domain noise vector.
Then N t ×N r The equivalent channel matrix of the MIMO radio frequency division multiplexing wireless communication system in the DATF domain is as follows:
Figure BDA0004044666890000165
obtaining y at the receiving end MIMO Then, to solve the signal x transmitted from the transmitting end MIMO Must estimate H MIMO Will estimate H MIMO Called channel estimation, while estimating H MIMO I.e. N therein r ×N t The sub-equivalent channel matrices are estimated simultaneously. Implementation of EPA-DR channel estimation in 2X 1MISO-AFDM system (i.e. two transmitting side antennas and one receiving side antenna) is shown in FIG. 5, where P is pilot symbol, 0 is guard symbol, x is data symbol, and in FIG. 5, equivalent channel matrix H 1,1 Above the upper part
Figure BDA0004044666890000166
For the transmission signal of the first transmitting-end antenna, y on the right side 1 For the reception signal of the first receiver antenna, in +.>
Figure BDA0004044666890000167
The position of the pilot symbol P in the middle is m t,p Corresponding to equivalent channel matrix H 1,1 The position of the column of the large non-zero values in the delta is the large non-zero values in the column, and the large non-zero values are extracted from the equivalent channel matrix and found in the row and y of the large non-zero values 1 The position of the pilot symbol corresponds to the position of the pilot symbol. After the non-zero values with large values in the equivalent channel matrix are known, the non-zero values with large values in the equivalent channel matrix can be recursively deduced through the diagonal reconstruction characteristic of the equivalent channel matrix, so that the content of the rest of the equivalent channel matrix is recursively deduced, and then all the equivalent channel matrices of the communication system in the discrete affine Fourier transform domain are obtained, so that channel estimation is completed.
The EPA-DR based channel estimation method is summarized by the following table:
Figure BDA0004044666890000171
/>
Figure BDA0004044666890000181
in a specific embodiment, the performance of the above-mentioned EPA-MG channel estimation method in a 2×2MIMO-AFDM system is verified through numerical simulation, and Bit Error Rate (BER) is taken as a criterion of channel estimation accuracy. The number of the paths between each pair of the transmitting end antenna and the receiving end antenna is 4, and the time delay of the five paths is [0,0,0.98,1.96 ] ](microseconds) the Doppler shift for each multipath is generated using the Jakes equation, i.e., v i ＝v max cos (θ), θ is [ -pi, pi]Obeying the average distribution among v max =2 is the maximum doppler shift normalized for subcarrier spacing, corresponding to a maximum movement speed of 540 km/h at the 4G carrier frequency. Other main simulation parameters are shown in the following table, wherein the Message passing detector is the most commonly used iteration detector at present, the maximum iteration number is set to be 50, and the update step length is set to beAnd 0.5, and the convergence judgment threshold is 0.01. The ratio of the time domain received data signal power to the noise power is denoted as SNR (signal-to-noise ratio) and the ratio of the pilot energy to the noise power is denoted as SNRp (signal-to-noise ratio of pilot). Under the condition of integer Doppler (the fractional part of normalized Doppler frequency shift is 0), considering the influence of SNRp and a threshold value on an EPA-MG channel estimation method; under fractional Doppler conditions, the influence of the spacing factor and SNRp on the EPA-MG channel estimation method is considered. Both conditions are compared when ideal Channel State Information (CSI) is used to verify the performance of the EPA-DR method. The following table sets the system parameters:
Figure BDA0004044666890000182
Figure BDA0004044666890000191
as shown in fig. 6, the relationship between the bit error rate and the signal-to-noise ratio SNR for channel estimation using the EPA-DR method under integer doppler, SNRp of 20dB, 25dB, and 30dB, respectively, is shown, while the relationship between the bit error rate and the signal-to-noise ratio under ideal channel state information is also shown as a comparison. It can be clearly seen that the greater the pilot energy to noise power ratio SNRp, the lower the bit error rate (better performance) at the same signal-to-noise ratio. Because the third step of the EPA-DR algorithm receiving end expands the noise to the whole, the larger the pilot frequency energy is, the smaller the noise normalized for the pilot frequency is, which indicates that the channel estimation is more accurate; secondly, it can be observed that the bit error rate of channel estimation using the EPA-DR method when SNRp reaches 30dB is almost indistinguishable from the bit error rate in the case of using ideal channel state information. Thus, the EPA-DR method can provide accurate channel estimation using a sufficiently large SNRp.
As shown in fig. 7, the relationship of bit error rate to threshold (multiple of noise variance) for channel estimation using EPA-DR method at integer doppler, SNRp of 20dB, 25dB and 30dB respectively is shown. It can be clearly seen that there is an optimal threshold for different SNRp. If the threshold is set higher than the optimal value, the paths with small energy channel gain are ignored; if the threshold is set below this optimum value, the interference of strong noise is amplified. Both of these cases result in decreased EPA-DR channel estimation performance and thus lower detection complexity. Furthermore, as the SNRp increases, the bit error rate is less sensitive to the threshold, and a larger threshold should be used to achieve optimal detection.
As shown in fig. 8, the relationship between the bit error rate and the signal to noise ratio when the EPA-DR method is used for channel estimation under the conditions of fractional doppler, srnp=45 dB, and separation factors of 1, 4, and 8, respectively, is shown, and the relationship between the bit error rate and the signal to noise ratio under the conditions of using ideal channel state information is also shown as a comparison. It can be clearly seen that the bit error performance improves as the spacing factor increases. The protection interval between two continuous delay blocks in the equivalent channel matrix is increased, so that the diagonal reconstruction result of the channel matrix is more accurate, and the delay interference is reduced. Meanwhile, according to the symbol arrangement scheme, the interval between pilot and data symbols also becomes large, meaning that both interference between pilots and interference between pilot data become small. However, an increase in the spacing factor results in an increase in the number of guard symbols, meaning that the data symbols transmitted by each transmit antenna are reduced. At the same time, the fractional doppler case requires the use of more energetic pilot symbols than the integer doppler case.
As shown in fig. 9, the time interval factor k at fractional doppler is shown v The relationship between bit error rate and SNRp when channel estimation is performed using EPA-DR method for snr=14 dB for 1 and 8. It can be observed that as SNRp increases, bit error performance increases and then decreases. Since noise is the dominant factor in interfering with channel estimation when SNRp is less than 40dB, increasing the energy of the pilot can mitigate the interference of the noise. However, increasing SNRp increases interference between pilot and data symbols, making symbol detection more difficult. Thus, for a MIMO-AFDM system, there is a tradeoff between pilot-aided channel estimation accuracy and pilot data orthogonality。
In the embodiment of the application, based on the problem of how to implement low-complexity and accurate channel estimation in a multi-input multi-output radio frequency division multiplexing wireless communication system, a pilot auxiliary diagonal reconstruction channel estimation method is designed, which realizes that pilot symbols are set at preset positions of transmission signals sent by any transmitting end antenna, and a first coordinate corresponding to the pilot symbols at the preset positions is determined; in the received signal of any receiving end antenna, determining a second coordinate of a pilot symbol in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna according to the first coordinate; performing threshold-based energy detection according to the absolute amplitude of the second coordinate to obtain a non-zero value with a large value in a column to which the first coordinate belongs in the equivalent channel matrix; diagonal reconstruction is carried out on the non-zero values with large values in the columns to which the first coordinates belong, the non-zero values with large values in the rest columns in the equivalent channel matrix are recursively deduced, and the technical scheme of the equivalent channel matrix of all transmitting end antennas and receiving end antennas in the discrete affine Fourier transform domain is obtained according to the non-zero values with large values in all columns; compared with the traditional pilot frequency auxiliary channel estimation method, the method occupies fewer communication resources, has lower calculation complexity and greatly improves the efficiency of channel estimation.
Although the steps in the flowcharts described above are shown in order as indicated by arrows, these steps are not necessarily executed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders.
In another embodiment, as shown in fig. 10, a second aspect of the present invention provides a pilot-aided diagonal reconstruction channel estimation system, which is applied to a mimo-rf-emulated-multiplex wireless communication system, the system comprising:
the pilot setting module 10 is configured to set a pilot symbol at a preset position of a transmission signal sent by any transmitting end antenna, and determine a first coordinate corresponding to the pilot symbol at the preset position;
a second coordinate determining module 20, configured to determine, in a received signal of any receiving end antenna, a second coordinate of the pilot symbol in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna according to the first coordinate;
the energy detection module 30 is configured to perform threshold-based energy detection according to the absolute amplitude of the second coordinate, so as to obtain a non-zero value with a large value in a column to which the first coordinate belongs in the equivalent channel matrix;
The channel estimation module 40 is configured to perform diagonal reconstruction on the non-zero values with large values in the columns to which the first coordinates belong, deliver the non-zero values with large values in the remaining columns of the equivalent channel matrix, and obtain the equivalent channel matrix of all the transmitting end antennas and the receiving end antennas in the discrete affine fourier transform domain according to the non-zero values with large values in all the columns.
It should be noted that, each module in the above-mentioned channel estimation system based on the embedded pilot auxiliary diagonal reconstruction may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules. For a specific limitation of a pilot-assisted diagonal reconstruction channel estimation system, see the limitation of a pilot-assisted diagonal reconstruction channel estimation method above, the two have the same function and function, and are not described herein.
A third aspect of the present invention provides an electronic device comprising:
a processor, a memory, and a bus;
The bus is used for connecting the processor and the memory;
the memory is used for storing operation instructions;
the processor is configured to, by invoking the operation instruction, cause the processor to perform an operation corresponding to a pilot-assisted diagonal reconstruction channel estimation method as shown in the first aspect of the present application.
In an alternative embodiment, an electronic device is provided, as shown in fig. 11, and the electronic device 5000 shown in fig. 11 includes: a processor 5001 and a memory 5003. The processor 5001 is coupled to the memory 5003, e.g., via bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. Note that, in practical applications, the transceiver 5004 is not limited to one, and the structure of the electronic device 5000 is not limited to the embodiment of the present application.
The processor 5001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. The processor 5001 may also be a combination of computing functions, e.g., including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.
Bus 5002 may include a path to transfer information between the aforementioned components. Bus 5002 may be a PCI bus or an EISA bus, among others. The bus 5002 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 11, but not only one bus or one type of bus.
The memory 5003 may be, but is not limited to, ROM or other type of static storage device, RAM or other type of dynamic storage device, which can store static information and instructions, EEPROM, CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disc, etc.), magnetic disk storage or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and capable of being accessed by a computer.
The memory 5003 is used for storing application program codes for executing the aspects of the present application and is controlled by the processor 5001 for execution. The processor 5001 is operative to execute application code stored in the memory 5003 to implement what has been shown in any of the method embodiments described previously.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like.
A fourth aspect of the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a pilot-aided diagonal reconstruction channel estimation method as shown in the first aspect of the present application.
Yet another embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding content of the foregoing method embodiment
In summary, the invention relates to the technical field of wireless communication, and discloses a pilot frequency auxiliary diagonal reconstruction channel estimation method, a system, equipment and a medium, which are applied to a multi-input multi-output radio frequency division multiplexing (MIMO) wireless communication system. The method is realized in a discrete affine Fourier transform domain, the positions of pilot symbols in a transmission signal are reasonably arranged on any transmitting end antenna according to the cycle characteristic of an equivalent channel matrix, the pilot symbols received by any receiving end antenna are non-zero bands of a certain column in the equivalent channel matrix between the transmitting end antenna and the receiving end antenna, then the diagonal reconstruction is carried out on the received pilot symbols according to the diagonal reconstruction characteristic of the equivalent channel matrix in an AFDM domain, the non-zero bands of other columns in the equivalent channel matrix are deduced, and then the equivalent channel matrix between each pair of transmitting end antennas and the receiving end antenna is estimated, so that the channel estimation is realized. The method has low bit error rate and high accuracy when estimating the channel, occupies fewer communication resources compared with the traditional pilot frequency auxiliary channel estimation method, has lower calculation complexity, greatly improves the efficiency of channel estimation, and has very wide prospect in engineering.
In this specification, each embodiment is described in a progressive manner, and all the embodiments are directly the same or similar parts referring to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments. It should be noted that, any combination of the technical features of the foregoing embodiments may be used, and for brevity, all of the possible combinations of the technical features of the foregoing embodiments are not described, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples represent only a few preferred embodiments of the present application, which are described in more detail and are not thereby to be construed as limiting the scope of the invention. It should be noted that modifications and substitutions can be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and substitutions should also be considered to be within the scope of the present application. Therefore, the protection scope of the patent application is subject to the protection scope of the claims.

Claims (10)

1. A pilot-assisted diagonal reconstruction channel estimation method, wherein the method is applied to a multiple-input multiple-output radio frequency division multiplexing-like wireless communication system, and the method comprises the following steps:
setting pilot symbols at preset positions of transmission signals sent by any transmitting end antenna, and determining first coordinates corresponding to the pilot symbols at the preset positions;
in the received signal of any receiving end antenna, determining a second coordinate of the pilot symbol in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna according to the first coordinate;
performing threshold-based energy detection according to the absolute amplitude of the second coordinate to obtain a non-zero value with a large value in a column to which the first coordinate belongs in the equivalent channel matrix;
and carrying out diagonal reconstruction on the non-zero values with large values in the columns to which the first coordinates belong, delivering out the non-zero values with large values in the rest columns in the equivalent channel matrix, and obtaining the equivalent channel matrix of all the transmitting end antennas and the receiving end antennas in the discrete affine Fourier transform domain according to the non-zero values with large values in all the columns.
2. The method for pilot-assisted diagonal reconstruction channel estimation according to claim 1, wherein the preset positions are in one-to-one correspondence with the first coordinates, and the first coordinates are determined by the following formula:
Figure FDA0004044666880000011
Wherein t=1, 2, … …, N t X is the transmitting end antenna t [m]For the transmission signal transmitted by the t-th transmitting-end antenna, m1 is a first coordinate,
Figure FDA0004044666880000012
is a first numerical value, l max For maximum time delay, alpha max Is the maximum integer Doppler shift, k v Is a non-negative integer for the spacing factor.
3. The method of pilot-assisted diagonal reconstruction channel estimation according to claim 1 wherein a matrix expression between a transmit signal transmitted by any transmit antenna and a receive signal received by any receive antenna is as follows:
y＝H r,t x+w
wherein y is a received signal vector of a receiving end antenna in a DAFT domain, x is a transmitted signal vector of a transmitting end antenna in the DAFT domain, w is a noise vector, and H r,t Is an equivalent channel matrix between any transmitting antenna and any receiving antenna.
4. The method of pilot-assisted diagonal reconstruction channel estimation according to claim 2 wherein said second coordinates are of the formula:
Figure FDA0004044666880000021
wherein m2 is a second coordinate.
5. The method of pilot-aided diagonal reconstruction channel estimation of claim 2 wherein threshold-based energy detection is performed by the following equation:
Figure FDA0004044666880000022
in the method, in the process of the invention,
Figure FDA0004044666880000023
the method is characterized in that the method is a non-zero value with large numerical value in a column to which a first coordinate belongs in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna; r=1, 2, … …, N r Is a receiving end antenna; y is r [m2]The pilot frequency symbol corresponding to the second coordinate position in the received signal of the r receiving end antenna; />
Figure FDA0004044666880000024
The first coordinate of the t-th transmitting-end antenna.
6. The method for pilot-assisted diagonal reconstruction of channel estimation according to claim 1, wherein said diagonal reconstruction of the large non-zero values in the columns to which the first coordinates belong, delivering out the large non-zero values in the remaining columns of the equivalent channel matrix, comprises:
setting a conversion factor, multiplying the conversion factor by a non-zero value with a large value in a column to which the first coordinate belongs according to the cycle characteristic of the equivalent channel matrix to obtain the non-zero value with the large value in an unknown column to which the right lower diagonal of the column to which the first coordinate belongs in the equivalent channel matrix, and pushing out the non-zero values with the large value in the rest columns in the equivalent channel matrix.
7. The method of pilot-aided diagonal reconstruction channel estimation of claim 6 wherein the conversion factor is of the formula:
Figure FDA0004044666880000031
in the method, in the process of the invention,
Figure FDA0004044666880000032
as a conversion factor, N is the number of subcarriers, subcarrier numbers m, m' =0, 1, … …, N-1, c 2 Is any irrational number or a rational number far smaller than 1/(2N), l' is a specific time delay () N Representing modulo N operation.
8. A pilot-aided diagonal reconstruction channel estimation system, the system being applied to a multiple-input multiple-output radio frequency-emulated-division-multiplexing wireless communication system, the system comprising:
the pilot frequency setting module is used for setting pilot frequency symbols at preset positions of transmission signals sent by any transmitting end antenna and determining first coordinates corresponding to the pilot frequency symbols at the preset positions;
the second coordinate acquisition module is used for determining a second coordinate of the pilot symbol in an equivalent channel matrix between any transmitting end antenna and any receiving end antenna according to the first coordinate in a received signal of any receiving end antenna;
the energy detection module is used for carrying out threshold-based energy detection according to the absolute amplitude value of the second coordinate to obtain a non-zero value with a large value in a column to which the first coordinate belongs in the equivalent channel matrix;
and the channel estimation module is used for carrying out diagonal reconstruction on the non-zero values with large values in the columns to which the first coordinates belong, delivering out the non-zero values with large values in the rest columns in the equivalent channel matrix, and obtaining the equivalent channel matrix of all the transmitting end antennas and the receiving end antennas in the discrete affine Fourier transform domain according to the non-zero values with large values in all the columns.
9. An electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the pilot-aided diagonal reconstruction channel estimation method of any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the pilot-aided diagonal reconstruction channel estimation method according to any one of claims 1 to 7.
CN202310025439.9A 2023-01-09 2023-01-09 Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium Pending CN116132225A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310025439.9A CN116132225A (en) 2023-01-09 2023-01-09 Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310025439.9A CN116132225A (en) 2023-01-09 2023-01-09 Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium

Publications (1)

Publication Number Publication Date
CN116132225A true CN116132225A (en) 2023-05-16

Family

ID=86307603

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310025439.9A Pending CN116132225A (en) 2023-01-09 2023-01-09 Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium

Country Status (1)

Country Link
CN (1) CN116132225A (en)

Similar Documents

Publication Publication Date Title
RU2321949C1 (en) Device and method for transmitting data using selected own vector in mimo-system of closed contour mobile communications
Chang et al. Model-based channel estimation for OFDM signals in Rayleigh fading
Gholam et al. Beamforming design for simplified analog antenna combining architectures
KR100918717B1 (en) Sequence estimating method and device in mimo ofdm communication system
CN101427485A (en) Reduced complexity beam-steered MIMO OFDM system
US8675720B2 (en) Noise estimation filter
Xu et al. Effect of pilot contamination on channel estimation in massive MIMO systems
CN103685096A (en) Optimal pilot frequency based MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) system channel estimation method
Dhanasekaran et al. Channel estimation using spatial partitioning with coalitional game theory (SPCGT) in wireless communication
CN102546483B (en) Method for broadband common-frequency interference noise estimation and interference suppression and corresponding system
CN101330357B (en) Method for feedback of channel condition information and net element equipment
WO2013168792A1 (en) Wireless reception device, wireless transmission device, wireless communication system, program, and integrated circuit
Bogale et al. Pilot contamination mitigation for wideband massive MMO: Number of cells vs multipath
CN102035787B (en) Band sequencing Turbo enhancement method for multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) wireless communication receiver
CN102006250B (en) Turbo enhancement method for MIMO-SCFDE wireless communication receiver
RU2470460C2 (en) Methods and systems for hybrid mimo schemes in ofdm/a systems
CN108365875B (en) Method for reducing PAPR (peak to average power ratio) of multiple antennas based on precoding and MIMO (multiple input multiple output) system
Singh et al. NOMA Based Generalized Precoding Aided Spatial Modulation with Multiuser MIMO in Downlink
CN116132225A (en) Pilot auxiliary diagonal reconstruction channel estimation method, system, equipment and medium
CN113315551B (en) Signal detection method and device of layered space-time code system and computer equipment
CN101719816A (en) Method for realizing low feedback velocity of self-adaptive MIMO-SCFDE system
CN101969417A (en) Low-return self-adaptive multimode transmission method of MIMO-SCFDE (Multiple Input Multiple Output Single Carrier Frequency Domain Equilibrium) system
JP2013162331A (en) Radio transmitter, radio receiver, radio communication system, and precoding method
Lu et al. TDD-based massive MIMO system with multi-antenna user equipments
Shin et al. User Group Selection Method in Multiuser MIMO-OFDM Transmission with Adaptive PAPR Reduction Using Null Space in MIMO Channel

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination