CN106878219A - A kind of method and device of data processing - Google Patents
A kind of method and device of data processing Download PDFInfo
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- CN106878219A CN106878219A CN201510919849.3A CN201510919849A CN106878219A CN 106878219 A CN106878219 A CN 106878219A CN 201510919849 A CN201510919849 A CN 201510919849A CN 106878219 A CN106878219 A CN 106878219A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2647—Arrangements specific to the receiver only
- H04L27/2649—Demodulators
- H04L27/265—Fourier transform demodulators, e.g. fast Fourier transform [FFT] or discrete Fourier transform [DFT] demodulators
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Abstract
The present invention provides a kind of method and device of data processing, and the method includes：After receiving data-signal, linear process is carried out to the data-signal by designated treatment algorithm；Fast Fourier Transform (FFT) operation is carried out to the data-signal after treatment.The operational transformation that can make a big matrix by the present invention is operated into the matrix of multiple small dimensions, reduces the calculation process complexity of receiving terminal.
Description
Technical field
The present invention relates to communication field, more particularly to a kind of method and device of receiving terminal data processing.
Background technology
Long Term Evolution (Long Term Evolution, abbreviation LTE) is 4G (4th Generation
Mobile Communication System, forth generation GSM) radio honeycomb communication technology.
LTE uses OFDM (Orthogonal Frequency Division Multiplexing, OFDM)
The running time-frequency resource that technology, subcarrier and OFDM symbol are constituted constitutes the radio physical time-frequency of LTE system
Resource.Current OFDM technology has applied wider in wireless communications.Before circulation
Sew (Cyclic Prefix, abbreviation CP), CP-OFDM systems can solve multidiameter delay problem,
And frequency-selective channel be divide into a set of parallel flat channel, this simplifies channel and estimates well
Meter method, and have precision of channel estimation higher.However, CP-OFDM systematic functions are to adjacent sub-bands
Between frequency deviation and when it is partially more sensitive, this mainly due to the system spectrum leakage than larger, therefore hold
It is easily caused intersubband interference.And, CP also occupies time resource, reduces spectrum efficiency.
Present each major company is in the radio communication 5G that begins one's study (Fifth Generation Mobile
Communication System, the 5th Generation Mobile Communication System) technology, wherein GFDM (Generalized
Frequency Division Multiplexing, broad sense frequency multiplexing technique) it is possible to be used in 5G.
GFDM systems with a subframe (or data block) be unit, transmitting terminal carry out coded modulation treatment and
Decoding demodulation process is carried out in receiving terminal.A general subframe includes multiple subcarriers and multiple symbols,
Assuming that sub-carrier number is K, symbolic number is L, then a data for subframe are N=K × L.Due to GFDM
Between system subcarrier and intersymbol be non-orthogonal, therefore, be phase interaction between each data of sub- frame in
With with interfere.In receiving terminal, the data-signal of the subframe for receiving is this N number of data phase
Data-signal after interaction, these data-signals need to carry out just to isolate this after interference treatment N number of
Data are come.It is there is still a need for the problem for solving that how receiving terminal carries out more preferable interference treatment.
Nearest some documents propose some processing methods of GFDM system receiving terminals, one of which method
It is：The equivalent Base-Band Processing matrix of transmitting terminal is calculated, then using ZF (Zero Forcing, ZF)
Algorithm or MMSE (Minimum Mean Squared Error, Minimum Mean Squared Error estimation) algorithm pair
Matrix inversion, so as to isolate this N number of data, because the dimensional comparison of matrix is high, and with one
The increase of sub-frame data and increase, therefore receiving terminal operand, than larger, complexity is higher.It is another
Method is：This N number of data, the complexity of this method are isolated using the method for serial interference elimination
It is just higher.Therefore the receiving terminal in GFDM systems proposes that a kind of complexity is low and performance is also relatively good
Processing method be current techniques need solve a major issue.
In other new multicarrier systems, it is also desirable to the place that a kind of complexity is low and performance is also relatively good
Reason method.Therefore it is desirable that a kind of good processing method can be proposed in receiving terminal, be adapted to as far as possible with
It is general in multiple systems based on time-frequency physical resource.
The content of the invention
The technical problem to be solved in the present invention is to provide a kind of method and device of data processing, many to overcome
Transportation load present in receiving terminal available data treatment technology in carrier system is big, complexity defect high.
In order to solve the above-mentioned technical problem, the invention provides a kind of method of data processing, apply to many
Carrier system, including：
After receiving data-signal, linear process is carried out to the data-signal by designated treatment algorithm；
Fast Fourier Transform (FFT) operation is carried out to the data-signal after treatment.
Further, the above method also has following feature：It is described receive data-signal after, also include：
The data-signal is carried out into digital-to-analogue conversion into discrete data signal, then by designated treatment algorithm pair
The discrete data signal carries out linear process.
Further, the above method also has following feature：It is described by designated treatment algorithm to it is described from
Scattered data-signal carries out linear process, including：
The discrete data signal is grouped；
Go out multiple matrixes using the designated treatment algorithm construction, respectively to the discrete data that each is organized
Signal carries out linear operation.
Further, the above method also has following feature：It is described that the discrete data signal is divided
Group includes：
Packet is sampled to the discrete data signal.
Further, the above method also has following feature：It is described by designated treatment algorithm to the number
It is believed that after number carrying out linear process, also including：
Enter row interpolation and displacement overlap-add operation, the time domain data of the multiple symbols of output to every group of data-signal.
Further, the above method also has following feature：Data-signal after described pair for the treatment of is carried out soon
Fast Fourier transform operation, including：
Time domain data to each symbol carries out Fast Fourier Transform (FFT) operation respectively, the multiple symbols of output
Frequency domain data.
Further, the above method also has following feature：Data-signal after described pair for the treatment of is carried out soon
After fast Fourier transform operation, also include：
The frequency domain data after Fast Fourier Transform (FFT) operation is detected by specifying detection algorithm；
The frequency domain data is demodulated.
Further, the above method also has following feature：The specified detection algorithm includes：It is minimum equal
Square error estimation algorithm or zero forcing algorithm.
Further, the above method also has following feature：
The discrete data signal is discrete time-domain data-signal, includes the data-signal of multiple symbols.
Further, the above method also has following feature：
The designated treatment algorithm includes：Minimum Mean Squared Error estimation algorithm or zero forcing algorithm.
In order to solve the above problems, present invention also offers a kind of device of data processing, wherein, including：
First processing module, after receiving data-signal, by designated treatment algorithm to the data
Signal carries out linear process；
Second processing module, for carrying out Fast Fourier Transform (FFT) operation to the data-signal after treatment.
Further, said apparatus also have following feature：
The first processing module, is additionally operable to after receiving data-signal：The data-signal is entered into line number
Mould is converted into discrete data signal, then the discrete data signal is carried out linearly by designated treatment algorithm
Treatment.
Further, said apparatus also have following feature：
The first processing module, is linearly located by designated treatment algorithm to the discrete data signal
Reason includes：The discrete data signal is grouped；Go out multiple using the designated treatment algorithm construction
Matrix, carries out linear operation to the discrete data signal that each is organized respectively.
Further, said apparatus also have following feature：
The first processing module, carrying out packet to the discrete data signal includes：To the dispersion number
It is believed that number being sampled packet, the discrete data signal is discrete time-domain data-signal, includes multiple
The data-signal of symbol.
Further, said apparatus also have following feature：
The first processing module, after designated treatment algorithm carries out linear process to the data-signal,
It is additionally operable to：Enter row interpolation and displacement overlap-add operation, the time domain of the multiple symbols of output to every group of data-signal
Data.
Further, said apparatus also have following feature：
The Second processing module, Fast Fourier Transform (FFT) operation is carried out to the data-signal after treatment to be included：
Time domain data signal to each symbol carries out Fast Fourier Transform (FFT) operation respectively, the multiple symbols of output
Frequency domain data.
Further, said apparatus also have following feature：
The Second processing module, after carrying out Fast Fourier Transform (FFT) operation to the data-signal after treatment
It is additionally operable to：The frequency domain data after Fast Fourier Transform (FFT) operation is detected by specifying detection algorithm；
The frequency domain data is demodulated, the specified detection algorithm includes：Minimum Mean Squared Error estimation algorithm
Or zero forcing algorithm.
To sum up, the present invention provides a kind of method and device of data processing, can make a behaviour for big matrix
The matrix for being transformed into multiple small dimensions is operated, and reduces the calculation process complexity of receiving terminal；And
And the inventive method makes the treatment of receiving terminal can be with compatible other more launch scenarios.
Brief description of the drawings
Accompanying drawing is used for providing a further understanding of the present invention, and constitutes a part for specification, with this
The specific embodiment of invention is used to explain the present invention together, is not construed as limiting the invention.Attached
In figure：
Fig. 1 is the flow chart of the method for the data processing of the embodiment of the present invention；
Fig. 2 is the signal that carries out linear operation of the receiving terminal of the embodiment of the present invention to discrete data signal
Figure；
Fig. 3 carries out the signal of matrix linear operation for the receiving terminal of the embodiment of the present invention to discrete data signal
Figure；
Fig. 4 is a kind of schematic diagram of the device of data processing of the embodiment of the present invention.
Specific embodiment
As background technology is mentioned, the receiving terminal of GFDM systems carries out square to whole subframe or data block
Linear operation, then obtains the frequency domain data of whole subframe.After obtaining the frequency domain data of whole subframe,
Receiving terminal reuses the detection operation of MMSE or ZF algorithms, is then exported after demodulated module
The data of transmitting terminal.The dimension of this matrix for operating with is very big, therefore operand is very big, multiple
Miscellaneous degree is high.
To make the object, technical solutions and advantages of the present invention become more apparent, below in conjunction with accompanying drawing
Embodiments of the invention are described in detail.It should be noted that in the case where not conflicting, this Shen
Please in embodiment and the feature in embodiment can mutually be combined.
Fig. 1 is the flow chart of the method for the data processing of the embodiment of the present invention, as shown in figure 1, this implementation
The method of example includes：
S11, receive data-signal after, the data-signal is carried out linearly by designated treatment algorithm
Treatment；
S12, Fast Fourier Transform (FFT) operation is carried out to the data-signal after treatment.
Wherein, the designated treatment algorithm can include MMSE (Minimum Mean Squared Error,
Minimum Mean Squared Error estimation) algorithm or ZF (Zero Forcing, ZF) algorithm.
On carrying out matrix linear operation to whole subframe or data block, the embodiment of the present invention proposes to use divides
The method of step, is divided into the operation of 2 class different qualities, the i.e. line of MMSE algorithms (or ZF algorithms)
Property operation and FFT (Fast Fourier Transform, Fast Fourier Transform (FFT)) operation.Receiving terminal is received
To after data-signal, the linear operation of MMSE algorithms or ZF algorithms is first carried out, then carry out FFT
Operation.
Being divided into the benefit of the operation of 2 class different qualities is：
(1) it is grouped by sampling, it is possible to use the matrix of multiple small dimensions is operated, reduces computing and answer
Miscellaneous degree；
(2) it is divided into after the different operation of 2 classes, other types can be further added by between this 2 generic operation
Operation, be conducive to the transmitting terminal in GFDM systems to carry out transmitting data (such as, using new scheme
Each symbol of GFDM system data signals cannot add CP, using the scheme of the present embodiment after,
Each symbol of the data-signal of transmitting terminal can just increase CP, to improve anti-multipath channel capacity, connect
Receiving end, it is possible to increase the operation for removing CP between 2 generic operations that the present embodiment is proposed).Namely
Say, be divided into after the different operation of 2 classes, make the treatment of receiving terminal can be with compatible other more launch parties
Case.
(3) operated using the matrix of multiple small dimensions, the biography of mushing error between data can also be reduced
Pass, so as to improve the data demodulation performance of receiving terminal.
The MMSE algorithms are lms algorithm, and MMSE is also referred to as LMMSE (Linear
Minimum Mean Square Error, Linear Minimum Mean-Square Error Estimation), institute in the embodiment of the present invention
The MMSE algorithms of finger include MMSE, MMSE-IRC, EMMSE-IRC algorithm.Wherein,
MMSE-IRC(Linear Minimum Mean Square Error-Interference Rejection
Combining) refer to AF panel merge MMSE algorithms, be exactly when between data exist interference when,
The related information of interference is obtained by certain methods, these have been used in the linear operation of MMSE algorithms
Interference-related information, can play a part of to suppress interference.EMMSE-IRC(Enhanced Linear
Minimum Mean Square Error-Interference Rejection Combining) refer to enhanced dry
The MMSE algorithms for suppressing to merge are disturbed, is exactly more accurate by the interference-related information of better method acquisition
Really, so can preferably play a part of to suppress interference.
The data-signal in step S11 is carried out after digital-to-analogue conversion for receiving terminal to the signal for receiving
Discrete data signal.
The linear operation of the MMSE algorithms or ZF algorithms is to enter line using matrix to data-signal
Property operation, specially：First discrete data signal is grouped, is then carried out respectively using multiple matrixes
Linear operation.
Wherein, the multiple matrix be by MMSE algorithms or ZF algorithm constructions out.
In a preferred embodiment, it is described that discrete data signal is grouped, specially：To dispersion number
It is believed that number being sampled packet.
In a preferred embodiment, the discrete data signal is discrete time-domain data-signal, includes many
The data of individual symbol.
In a preferred embodiment, the data-signal is by the MMSE algorithms or ZF algorithms
After linear operation, the time domain data of the multiple symbols of output.
In a preferred embodiment, the data-signal is by the MMSE algorithms or ZF algorithms
After linear operation, every group of data are entered with row interpolation and displacement overlap-add operation again, the multiple symbols of output
Time domain data.
In a preferred embodiment, the FFT operations are that the time domain data of each symbol is carried out respectively
FFT is operated, the frequency domain data of the multiple symbols of output.
In a preferred embodiment, the frequency domain data after the FFT operations, then by specifying detection to calculate
The detection of method (such as MMSE algorithms or ZF algorithms) is operated, then demodulated output transmitting terminal
Data.
Illustrated with instantiation below.
Embodiment one
Assuming that a subframe (or a data block) of GFDM systems is individual comprising K subcarrier and L
Symbol, the DS that transmitting terminal is launched in a subframe be d, d be N rows 1 row matrix or
Referred to as vector (including the vector of N number of element), and there is K to be multiplied by L equal to N, i.e. K × L=N.
After Base-Band Processing of the DS by GFDM systems, it is changed into A*d, " * " is transported for matrix multiplication
Calculate, A is the equivalent matrix of the GFDM systems basebands treatment of M rows N row, M and N is positive integer
If (had during Base-Band Processing through over-sampling, then M>N；If not through over-sampling, then M=N.
In this example, it is assumed that not through over-sampling, therefore M=N=K × L can be made).Assuming that wireless channel is
AWGN (Additive White Gaussian Noise, additive white Gaussian noise) channel.The number of transmitting
According to by after awgn channel, the DS r that receiving terminal is received is：
R=A*d+n
Wherein, r is the matrix of the row of M rows 1, is the data-signal that receiving terminal is received, the data letter
Number discrete data signal for being carried out to the signal for receiving after digital-to-analogue conversion for receiving terminal.N is M rows 1
The matrix of row, is noise vector.
Packet is first sampled to DS r (i), sampling multiple is S=M/L, using progressively displacement
The method being sampled respectively, as shown in Figure 2.In Fig. 2, S times first is used to DS r (i)
It is sampled, obtains the 1st group of DS E1 (j), after then moving one to DS r (i),
Reuse S times to be sampled, obtain the 2nd group of DS E2 (j), then to having moved the number of
After being moved a bit further according to serial r (i), reuse S times and be sampled, obtain the 3rd group of DS E3
J (), by that analogy, can obtain common S groups DS：E1(j)、E2(j)、…、ES(j).
Decomposited from the equivalent matrix A of GFDM systems basebands treatment S small dimensions matrix a1,
A2 ..., aS, the dimension of this S matrix is L, the S matrix obtained using MMSE algorithm constructions
Respectively：
MMSE-a1=a1H*(a1*a1H+(1/SNR)*I)-1,
MMSE-a2=a2H*(a2*a2H+(1/SNR)*I)-1,
…
MMSE-aS=aSH*(aS*aSH+(1/SNR)*I)-1。
Wherein, MMSE-a1 represents the linear operation matrix obtained using MMSE algorithms using a1, together
Reason, MMSE-a2 and MMSE-aS represents what is obtained using MMSE algorithms using a2 and aS respectively
Linear operation matrix.Subscript H is represented carries out conjugate transposition computing to matrix.SNR represents that receiving terminal is received
The signal to noise ratio of data-signal.I represents unit matrix.Subscript -1 is represented to matrix inversion.
Then to obtain S groups DS F1 (j), F2 (j) ..., FS (j) is respectively using S
Times speed carries out interpolation, then shifter-adder, last output data series O (i) again.
DS O (i) length is M, is to include the L time domain data of symbol successively, is then made
The time domain data section of each symbol is operated successively with fft algorithm, the frequency of each symbol is finally obtained
Numeric field data.
Frequency domain data after FFT operation, then by frequency domain equalization, then by MMSE (or
ZF) the detection of algorithm is operated, then the data of demodulated output transmitting terminal.Usual frequency domain equalization with
The detection operation of MMSE (or ZF) algorithm is combined and is operated.
Embodiment two
Assuming that a subframe (or a data block) of GFDM systems is individual comprising K subcarrier and L
Symbol, the DS that transmitting terminal is launched in a subframe be d, d be N rows 1 row matrix or
Referred to as vector (including the vector of N number of element), and there is K to be multiplied by L equal to N, i.e. K × L=N.
After Base-Band Processing of the DS by GFDM systems, it is changed into A*d, " * " is transported for matrix multiplication
Calculate, A is the equivalent matrix of the GFDM systems basebands treatment of M rows N row, M and N is positive integer
If (had during Base-Band Processing through over-sampling, then M>N；If not through over-sampling, then M=N.
In this example, it is assumed that not through over-sampling, therefore M=N=K × L can be made).Assuming that wireless channel is
Awgn channel.By after awgn channel, the DS r that receiving terminal is received is the data of transmitting：
R=A*d+n
Wherein, r is the matrix of the row of M rows 1, is the data-signal that receiving terminal is received, the data letter
Number discrete data signal for being carried out to the signal for receiving after digital-to-analogue conversion for receiving terminal.N is M rows 1
The matrix of row, is noise vector.
Packet is first sampled to DS r (i), sampling multiple is S=M/L, using progressively displacement
The method being sampled respectively, as shown in Figure 2.In Fig. 2, S times first is used to DS r (i)
It is sampled, obtains the 1st group of DS E1 (j), after then moving one to DS r (i),
Reuse S times to be sampled, obtain the 2nd group of DS E2 (j), then to having moved the number of
After being moved a bit further according to serial r (i), reuse S times and be sampled, obtain the 3rd group of DS E3
J (), by that analogy, can obtain common S groups DS：E1(j)、E2(j)、…、ES(j).
Decomposited from the equivalent matrix A of GFDM systems basebands treatment S small dimensions matrix a1,
A2 ..., aS, the dimension of this S matrix is L, and the S matrix obtained using ZF algorithm constructions is divided
It is not：
ZF-a1=a1-1,
ZF-a2=a2-1,
…
ZF-aS=aS-1,
Or
ZF-a1=(a1H*a1)-1*a1H,
ZF-a2=(a2H*a2)-1*a2H,
…
ZF-aS=(aSH*aS)-1*aSH,
Then, S groups DS：E1 (j), E2 (j) ..., ES (j) respectively use matrix
MMSE-a1, MMSE-a2 ..., MMSE-aS carry out linear operation, obtain S group DSs F1
(j), F2 (j) ..., FS (j), i.e.,：
F1 (j)=MMSE-a1*E1 (j),
F2 (j)=MMSE-a2*E2 (j),
…
FS (j)=MMSE-aS*ES (j).
Then to obtain S groups DS F1 (j), F2 (j) ..., FS (j) is respectively using S
Times speed carries out interpolation, then shifter-adder, last output data series O (i) again.
DS O (i) length is M, is to include the L time domain data of symbol successively, is then made
The time domain data section of each symbol is operated successively with fft algorithm, the frequency of each symbol is finally obtained
Numeric field data.
Frequency domain data after FFT operation, then by frequency domain equalization, then by MMSE (or
ZF) the detection of algorithm is operated, then the data of demodulated output transmitting terminal.
Embodiment three
The present embodiment is with the difference of embodiment one, displacement, sampling packet, interpolation in such as Fig. 2,
The operation of shifter-adder, comes equivalent, as shown in Figure 3 when implementing using the certain operations of matrix.
For DS r (i), the individual data composition matrix columns of K (K=M/L) are intercepted successively, this
Sample has been constructed for the matrix R (K, L) of K rows L row.This operation is similar to the reshape in Matlab
The operation of function.Every data line of this matrix R (K, L) is equivalent to each after being sampled in Fig. 2
Group DS, such as the 1st row is exactly DS E1 (i).The line number K of matrix is equal to group number S
(S=K=M/L).Then to every a line of matrix R (K, L) successively using MMSE-a1,
MMSE-a2 ..., MMSE-aS matrixes carry out linear operation, obtain new every a line of matrix, because
This just obtains new matrix R ' (K, L), then again by each column data of matrix R ' (K, L) according to
Secondary to connect into DS O (i), this operation is also similar to that the behaviour of the reshape functions in Matlab
Make.Each column data of matrix R ' (K, L) is in turn connected into DS O (i), just quite
Interpolation and shifter-adder operation in Fig. 2.Other are identical with implementing one.
The receiving terminal processing scheme of the present embodiment in GFDM systems except that be able to can also use at it
In his multicarrier system.
Receiving terminal processing method of the invention can make an operational transformation for big matrix into multiple small dimensions
Matrix is operated, and reduces the calculation process complexity of receiving terminal；And the inventive method makes receiving terminal
Treatment can be with compatible other more launch scenarios.
Fig. 4 is a kind of schematic diagram of the device of data processing of the embodiment of the present invention, as shown in figure 4, this
The device of embodiment, including：
First processing module, after receiving data-signal, by designated treatment algorithm to the data
Signal carries out linear process；
Second processing module, for carrying out Fast Fourier Transform (FFT) operation to the data-signal after treatment.
In a preferred embodiment, the first processing module, is additionally operable to after receiving data-signal：Will
The data-signal carries out digital-to-analogue conversion into discrete data signal, then by designated treatment algorithm to it is described from
Scattered data-signal carries out linear process.
In a preferred embodiment, the first processing module, by designated treatment algorithm to described discrete
Data-signal carries out linear process to be included：The discrete data signal is grouped；Specified using described
Processing Algorithm constructs multiple matrixes, carries out linear operation to the discrete data signal that each is organized respectively.
In a preferred embodiment, the first processing module, is grouped to the discrete data signal
Including：Packet is sampled to the discrete data signal, the discrete data signal is discrete time-domain number
It is believed that number, include the data-signal of multiple symbols.
In a preferred embodiment, the first processing module, by designated treatment algorithm to the data
After signal carries out linear process, it is additionally operable to：Enter row interpolation and displacement overlap-add operation to every group of data-signal,
The time domain data of the multiple symbols of output.
In a preferred embodiment, the Second processing module, is carried out quickly to the data-signal after treatment
Fourier transform operation includes：Time domain data signal to each symbol carries out Fast Fourier Transform (FFT) respectively
Operation, the frequency domain data of the multiple symbols of output.
In a preferred embodiment, the Second processing module, is carried out quickly to the data-signal after treatment
It is additionally operable to after Fourier transform operation：After specifying detection algorithm to Fast Fourier Transform (FFT) operation
Frequency domain data is detected；The frequency domain data is demodulated, the specified detection algorithm includes：Most
Small mean square error algorithm for estimating or zero forcing algorithm.
One of ordinary skill in the art will appreciate that all or part of step in the above method can be by program
To instruct related hardware to complete, described program can be stored in computer-readable recording medium, such as read-only
Memory, disk or CD etc..Alternatively, all or part of step of above-described embodiment can also be used
One or more integrated circuits are realized.Correspondingly, each module/unit in above-described embodiment can be used
The form of hardware is realized, it would however also be possible to employ the form of software function module is realized.The present invention is not restricted to appoint
The combination of the hardware and software of what particular form.
The preferred embodiments of the present invention are these are only, certainly, the present invention can also there are other various embodiments,
In the case of without departing substantially from spirit of the invention and its essence, those of ordinary skill in the art work as can be according to this
Various corresponding changes and deformation are made in invention, but these corresponding changes and deformation should all belong to the present invention
Appended scope of the claims.
Claims (17)
1. a kind of method of data processing, applies to multicarrier system, including：
After receiving data-signal, linear process is carried out to the data-signal by designated treatment algorithm；
Fast Fourier Transform (FFT) operation is carried out to the data-signal after treatment.
2. the method for claim 1, it is characterised in that：It is described receive data-signal after, also
Including：
The data-signal is carried out into digital-to-analogue conversion into discrete data signal, then by designated treatment algorithm pair
The discrete data signal carries out linear process.
3. method as claimed in claim 2, it is characterised in that：It is described by designated treatment algorithm to institute
Stating discrete data signal carries out linear process, including：
The discrete data signal is grouped；
Go out multiple matrixes using the designated treatment algorithm construction, respectively to the discrete data that each is organized
Signal carries out linear operation.
4. method as claimed in claim 3, it is characterised in that：It is described that the discrete data signal is entered
Row packet includes：
Packet is sampled to the discrete data signal.
5. the method as described in claim 3 or 4, it is characterised in that：It is described by designated treatment algorithm
After carrying out linear process to the data-signal, also include：
Enter row interpolation and displacement overlap-add operation, the time domain data of the multiple symbols of output to every group of data-signal.
6. method as claimed in claim 5, it is characterised in that：Data-signal after described pair for the treatment of enters
Row Fast Fourier Transform (FFT) is operated, including：
Time domain data to each symbol carries out Fast Fourier Transform (FFT) operation respectively, the multiple symbols of output
Frequency domain data.
7. method as claimed in claim 6, it is characterised in that：Data-signal after described pair for the treatment of enters
After row Fast Fourier Transform (FFT) operation, also include：
The frequency domain data after Fast Fourier Transform (FFT) operation is detected by specifying detection algorithm；
The frequency domain data is demodulated.
8. method as claimed in claim 7, it is characterised in that：
The specified detection algorithm includes：Minimum Mean Squared Error estimation algorithm or zero forcing algorithm.
9. method as claimed in claim 2, it is characterised in that：
The discrete data signal is discrete time-domain data-signal, includes the data-signal of multiple symbols.
10. the method as any one of claim 1-4,6-9, it is characterised in that：
The designated treatment algorithm includes：Minimum Mean Squared Error estimation algorithm or zero forcing algorithm.
A kind of 11. devices of data processing, it is characterised in that including：
First processing module, after receiving data-signal, by designated treatment algorithm to the data
Signal carries out linear process；
Second processing module, for carrying out Fast Fourier Transform (FFT) operation to the data-signal after treatment.
12. devices as claimed in claim 11, it is characterised in that：
The first processing module, is additionally operable to after receiving data-signal：The data-signal is entered into line number
Mould is converted into discrete data signal, then the discrete data signal is carried out linearly by designated treatment algorithm
Treatment.
13. devices as claimed in claim 12, it is characterised in that：
The first processing module, is linearly located by designated treatment algorithm to the discrete data signal
Reason includes：The discrete data signal is grouped；Go out multiple using the designated treatment algorithm construction
Matrix, carries out linear operation to the discrete data signal that each is organized respectively.
14. devices as claimed in claim 13, it is characterised in that：
The first processing module, carrying out packet to the discrete data signal includes：To the dispersion number
It is believed that number being sampled packet, the discrete data signal is discrete time-domain data-signal, includes multiple
The data-signal of symbol.
15. device as described in claim 13 or 14, it is characterised in that：
The first processing module, after designated treatment algorithm carries out linear process to the data-signal,
It is additionally operable to：Enter row interpolation and displacement overlap-add operation, the time domain of the multiple symbols of output to every group of data-signal
Data.
16. devices as claimed in claim 15, it is characterised in that：
The Second processing module, Fast Fourier Transform (FFT) operation is carried out to the data-signal after treatment to be included：
Time domain data signal to each symbol carries out Fast Fourier Transform (FFT) operation respectively, the multiple symbols of output
Frequency domain data.
17. devices as claimed in claim 16, it is characterised in that：
The Second processing module, after carrying out Fast Fourier Transform (FFT) operation to the data-signal after treatment
It is additionally operable to：The frequency domain data after Fast Fourier Transform (FFT) operation is detected by specifying detection algorithm；
The frequency domain data is demodulated, the specified detection algorithm includes：Minimum Mean Squared Error estimation algorithm
Or zero forcing algorithm.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107426122A (en) * | 2017-09-07 | 2017-12-01 | 西安电子科技大学 | Low complex degree minimum mean-squared error algorithm method for GFDM systems |
| CN107682296A (en) * | 2017-08-17 | 2018-02-09 | 天津大学 | GFDM system high efficiency MMSE method of reseptances and device suitable for FSC |
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| CN101083644A (en) * | 2006-06-01 | 2007-12-05 | 大唐移动通信设备有限公司 | Channel estimation method of OFDM system |
| CN101098323B (en) * | 2006-06-29 | 2010-04-07 | 中国科学院上海微系统与信息技术研究所 | Transmitting device and corresponding frequency domain equalization method based on GMC system |
| CN101184069B (en) * | 2007-12-14 | 2010-06-16 | 东南大学 | Selective Feedback Detection Method Based on Single Carrier Frequency Domain Equalization |
| CN101299733B (en) * | 2008-03-05 | 2012-05-16 | 中国科学院嘉兴无线传感网工程中心 | Minimum mean-square error channel estimation apparatus for wireless sensing network |
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| CN107682296A (en) * | 2017-08-17 | 2018-02-09 | 天津大学 | GFDM system high efficiency MMSE method of reseptances and device suitable for FSC |
| CN107682296B (en) * | 2017-08-17 | 2020-06-30 | 天津大学 | MMSE (minimum mean square error) receiving method and device suitable for GFDM (ground fault frequency division multiplexing) system of FSC (frequency selective modulation) |
| CN107426122A (en) * | 2017-09-07 | 2017-12-01 | 西安电子科技大学 | Low complex degree minimum mean-squared error algorithm method for GFDM systems |
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