CN103368621B - The processing method and equipment of signal - Google Patents
The processing method and equipment of signal Download PDFInfo
- Publication number
- CN103368621B CN103368621B CN201210082789.0A CN201210082789A CN103368621B CN 103368621 B CN103368621 B CN 103368621B CN 201210082789 A CN201210082789 A CN 201210082789A CN 103368621 B CN103368621 B CN 103368621B
- Authority
- CN
- China
- Prior art keywords
- vector
- matrix
- covariance matrix
- channel
- weighing
- 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.)
- Active
Links
Abstract
The present invention provides a kind of processing method and equipment of signal, and this method includes：Obtain channel estimation value, and according to the channel estimation value, obtain the first up channel covariance matrix C, wherein, the first up channel covariance matrix C is the second up channel covariance matrix R k powers, and the second up channel covariance matrix R is the covariance matrix generated by the channel estimation value；According to the first up channel covariance matrix C, the initial vector V of input0(n) and configuration iterations m/k, obtain weighing vector U；According to weighing vector U, processing is weighted to downstream signal；Wherein, n represents initial vector V0(n) number of the element in, m, k and m/k are positive integer, and m is primary iteration number.The processing method and equipment of the signal of the present invention accelerate the convergence of characteristic vector, improve the speed for calculating characteristic vector, so as to accelerate the processing speed of whole piece link, and are realized beneficial to flowing water.
Description
Technical field
The present invention relates to the processing method and equipment of the communication technology, more particularly to a kind of signal.
Background technology
Wave beam forming is a kind of aerial array multiple antenna transmission technique applied to small spacing, and its cardinal principle is to utilize sky
Between channel strong correlation and ripple principle of interference produce highly directive antenna pattern, make the main lobe of antenna pattern adaptive
Answer ground to point to arrival bearing user, so as to improve signal to noise ratio, and improve power system capacity or coverage.The algorithm of wave beam forming
Have a variety of, the forming algorithm of wherein feature based value is fairly simple and is widely used, and concrete principle is the superposition on signal is sent
One weight coefficient so that the receiving power of receiving terminal is maximum.
Weight coefficient is obtained according to up channel covariance matrix, at present, is asked according to up channel covariance matrix
A kind of mode for solving weight coefficient is to use power method, i.e., carries out computing using formula (1) iteration to try to achieve final weight coefficient：
U=Rm*V(n) (1)
Wherein, R represents up channel covariance matrix, and V (n) represents that arbitrary n ties up non-zero vector, and m represents primary iteration time
Number.But when initial iterations m numerical value is larger, processing equipment asks for weighing vector often due to the limitation of disposal ability
The iterative process of (or being called characteristic vector) will spend more time, and calculating speed is also relatively slow, so as to cause the meter of whole piece link
Calculation bottleneck concentrates on the processing equipment iteration and asks for weighing vector part, and then is unfavorable for flowing water realization.
The content of the invention
On the one hand the embodiment of the present invention provides a kind of processing method of signal, including：
Channel estimation value is obtained, and according to the channel estimation value, obtains the first up channel covariance matrix C；Wherein,
The first up channel covariance matrix C be the second up channel covariance matrix R k powers, second up channel
Covariance matrix R is the covariance matrix generated by the channel estimation value；
According to the first up channel covariance matrix C, the initial vector V of input0(n) and configuration iterations
M/k, obtain weighing vector U；
According to the weighing vector U generate weight coefficient, processing is weighted to downstream signal, and send weighting handle after
Downstream signal；
Wherein, n represents the initial vector V0(n) number of the element in, m, k and m/k are positive integer, and m is first
Beginning iterations.
The another aspect of the embodiment of the present invention provides a kind of processing equipment of signal, including：
Matrix calculation unit, for obtaining channel estimation value, and according to the channel estimation value, obtain the first up channel
Covariance matrix C；Wherein, the first up channel covariance matrix C is the second up channel covariance matrix R k powers,
The second up channel covariance matrix is the covariance matrix generated by the channel estimation value；
Weighing vector processing unit, for according to the first up channel covariance matrix C, the initial vector V of input0
(n) and configuration iterations m/k, obtain weighing vector U；
Weighting processing unit, for generating weight coefficient according to the weighing vector U, place is weighted to downstream signal
Reason, and send the downstream signal after weighting processing；
Wherein, n represents the initial vector V0(n) number of the element in, m, k and m/k are positive integer, and m is first
Beginning iterations.
The solution have the advantages that：Because the first up channel covariance matrix C is the second up channel covariance square
Battle array R k powers, the iterations that processing equipment configures during handling the first up channel covariance matrix become
The 1/k of primary iteration number, alleviates the processing load of the processor, accelerates the convergence of characteristic vector, improve calculating
The speed of characteristic vector, so as to accelerate the processing speed of whole piece link, and realized beneficial to flowing water.
Brief description of the drawings
Fig. 1 is the flow chart of one embodiment of the processing method of signal of the present invention；
Fig. 2 is the flow chart of another embodiment of the processing method of signal of the present invention；
Fig. 3 is the flow chart of another embodiment of the processing method of signal of the present invention；
Fig. 4 is the flow chart of a still further embodiment of the processing method of signal of the present invention；
Fig. 5 is the structural representation of one embodiment of the processing equipment of signal of the present invention；
Fig. 6 is the structural representation of another embodiment of the processing equipment of feature of present invention vector；
Fig. 7 is the structural representation of another embodiment of the processing equipment of signal of the present invention；
Fig. 8 is buf_ctrl concrete structure schematic diagram.
Embodiment
Fig. 1 is the flow chart of one embodiment of the processing method of signal of the present invention, as shown in figure 1, the side of the present embodiment
Method includes：
Step 101, uplink demodulation reference signal (the Demodulation Reference Signal according to reception；Letter
Claim：DMRS) and (sounding) signal acquisition channel estimation value is measured, and according to the channel estimation value, obtains the first up letter
Road covariance matrix C；Wherein, the first up channel covariance matrix C is k time of the second up channel covariance matrix R
Side, the second up channel covariance matrix R are the covariance matrix generated by the channel estimation value.Specifically, it is described
When channel estimation value represents for the form of row vector, the second up channel covariance matrix R is by channel estimation value conjugate transposition
The square formation formed after being multiplied with the channel estimation value；When the channel estimation value represents for the form of column vector, the second up channel
Covariance matrix R is the square formation formed after being multiplied by channel estimation value with the channel estimation value conjugate transposition.
Alternatively, channel estimation value can be believed by channel status such as channel conditions, multidiameter delay, Doppler shifts
Breath obtains.
Step 102, according to first up channel covariance matrix C, the initial vector V of input0(n) and what is configured changes
Generation number m/k, obtain weighing vector (or being called characteristic vector) U.
Step 103, according to weighing vector U, generate weight coefficient, processing be weighted to downstream signal, and send and add
Downstream signal after power processing.Weight coefficient can be weighing vector U in the embodiment of the present invention.
In the present embodiment, n represents initial vector V0(n) number of the element in, m, k and m/k are positive integer, and
M is primary iteration number.
In the present embodiment, for example, work as m=4, and during k=4, according to the channel estimation value, obtain the first up letter
Road covariance matrix C time is 1s, and the time for obtaining weighing vector U is 1s (m/k=1), compared to obtaining in the prior art
For weighing vector U time is 4s (m=4), the present invention is effectively improved the speed for calculating characteristic vector.
In the present embodiment, because the first up channel covariance matrix C is the second up channel covariance matrix R k
Power, the iterations that processing equipment configures during handling the first up channel covariance matrix become initial
The 1/k of iterations, alleviate the processing load of the processor, accelerate the convergence of characteristic vector, improve calculate feature to
The speed of amount, so as to accelerate the processing speed of whole piece link, and realized beneficial to flowing water.
Fig. 2 is the flow chart of another embodiment of the processing method of signal of the present invention, as shown in Fig. 2 the present embodiment
Method includes：
Step 201, the up DMRS and sounding signal acquisitions channel estimation value according to reception, and estimated according to the channel
Evaluation, obtain the first up channel covariance matrix C；Wherein, the first up channel covariance matrix C is the second up letter
Road covariance matrix R k powers, the second up channel covariance matrix R are the association side generated by the channel estimation value
Poor matrix.Specifically, when the channel estimation value represents for the form of row vector, the second up channel covariance matrix R serves as reasons
The square formation that channel estimation value conjugate transposition is formed after being multiplied with the channel estimation value；The channel estimation value is the form table of column vector
When showing, the second up channel covariance matrix R is formed after being multiplied by channel estimation value with the channel estimation value conjugate transposition
Square formation.
Step 202, using formula (2)：
Vi+1(n)=Cm/k*Vi(n) (2)
By the first up channel covariance matrix C m/k powers and primary vector Vi(n) matrix multiple processing is carried out,
Obtain secondary vector Vi+1(n)。
In the present embodiment, the initial vector V of input is obtained0(n) and primary iteration number m, and to the primary iteration
Number m carries out configuration processing, obtains the iterations m/k of configuration.In addition, in initialization, i=0, and primary vector Vi(n)
=V0(n)。
Step 203, using formula (3)：
Vi+1(n)=Vi+1(n)/|Vi+1(n)| (3)
To secondary vector Vi+1(n) it is normalized.Step 203 can reduce signal handling equipment due to reality
The influence that signal handling capacity (such as handling bit wide) in use is limited and causes resource to be overflowed；If not considering, signal transacting is set
Standby signal handling capacity, can skip step 203.
Step 204, judge whether i is equal to m/k-1；If being equal to, step 206 is performed；If being not equal to, step is performed
205。
Step 205, i is added to 1, and perform step 202.
Step 206, by secondary vector Vi+1(n) it is used as weighing vector U.
In the present embodiment, because the first up channel covariance matrix C is the second up channel covariance matrix R k
Power, the iterations that processing equipment configures during handling the first up channel covariance matrix become initial
The 1/k of iterations, alleviate the processing load of the processor, accelerate the convergence of characteristic vector, improve calculate feature to
The speed of amount, so as to accelerate the processing speed of whole piece link, and realized beneficial to flowing water.
Fig. 3 is the flow chart of another embodiment of the processing method of signal of the present invention, as shown in figure 3, the present embodiment
Method includes：
Step 301, the up DMRS and sounding signal acquisitions channel estimation value according to reception, and estimated according to the channel
Evaluation, obtain the first up channel covariance matrix C；Wherein, specifically, the channel estimation value represents for the form of row vector
When, the second up channel covariance matrix R is the side formed after being multiplied by channel estimation value conjugate transposition with the channel estimation value
Battle array；When the channel estimation value represents for the form of column vector, the second up channel covariance matrix R is with being somebody's turn to do by channel estimation value
The square formation that channel estimation value conjugate transposition is formed after being multiplied.
Step 302, using formula (2)：
Vi+1(n)=Cm/k*Vi(n) (2)
By the first up channel covariance matrix C m/k powers and with primary vector Vi(n) carry out at matrix multiple
Reason, obtain secondary vector Vi+1(n)。
In the present embodiment, the initial vector V of input is obtained0(n) and primary iteration number m, and to the primary iteration
Number m carries out configuration processing, obtains the iterations m/k of configuration.In addition, in initialization, i=0, and primary vector Vi(n)
=V0(n)。
Step 303, judge whether i is equal to m/k-1；If being equal to, step 305 is performed；If being not equal to, step is performed
304。
Step 304, i is added to 1, and perform step 302.
Step 305, by secondary vector Vi+1(n) weighing vector U is used as, and using formula (4)：
U=U/ | U | (4)
Weighing vector U is normalized.Step 305 can reduce because signal handling equipment is due to actually making
The influence that signal handling capacity (such as handling bit wide) in is limited and causes resource to be overflowed；If do not consider signal handling equipment
Signal handling capacity, can skip step 305.
In the present embodiment, because the first up channel covariance matrix C is the second up channel covariance matrix R k
Power, the iterations that processing equipment configures during handling the first up channel covariance matrix become initial
The 1/k of iterations, alleviate the processing load of the processor, accelerate the convergence of characteristic vector, improve calculate feature to
The speed of amount, so as to accelerate the processing speed of whole piece link, and realized beneficial to flowing water.
Further, Fig. 4 is the flow chart of a still further embodiment of the processing method of signal of the present invention, as shown in figure 4,
On the basis of above-mentioned Fig. 2 or embodiment illustrated in fig. 3, it can also include after step 206 or step 305：
Step 401, according to weighing vector (or being called characteristic vector) U, using formula (5)：
λ=(R*U)H*U (5)
Obtain eigenvalue λ.
Step 402, according to weighing vector U and this feature value λ, using formula (6)：
R '=R- λ * (U*UH) (6)
Obtain the 3rd up channel covariance matrix R '；
Step 403, according to the 3rd up channel covariance matrix R ', the initial vector V0(n) and it is described repeatedly
Generation number m/k, obtain time weighing vector U '；
Step 404, by the arranged in matrix of the weighing vector U and secondary weighing vector U ' compositions it is the weight coefficient.
For under single stream case, calculate weighing vector U can as be finally superimposed upon send signal on weight coefficient, from
And cause receiving terminal receiving power to meet the index of systemic presupposition (ideal indicator is that receiving power reaches maximum here).For double
, can be according to embodiment one to three any one institutes of implementation when base station judges that present channel environment is adapted to stream transmission in the case of stream
State method and step calculate the second up channel covariance matrix R corresponding to characteristic vector (such as weighing vector U), then should
Characteristic vector substitutes into formula (5) and (6) and calculates the 3rd up channel covariance matrix R '.The 3rd up channel is assisted again
R in variance matrix R ' alternative embodiments one to method and step of the embodiment three described in any one, it is corresponding so as to calculate R '
Weighing vector (i.e. time weighing vector), the corresponding weighing vectors of R ' can be one of the second up channel covariance matrix R
Sub-eigenvector.Thus, it can be that weighing vector is corresponding with R ' as corresponding to R to be finally superimposed upon the weight coefficient sent on signal
Weighing vector form matrix.It will be understood by those skilled in the art that in the case of being generalized to multithread, final weight coefficient
It can be the matrix of multiple characteristic vector compositions corresponding to the second up channel covariance matrix R.
Initial vector in the embodiment of the present invention when obtaining characteristic vector is initial vector V0(n), iterations is equal
For m/k, it furthermore achieved that the unification of characteristic vector calculation, i.e., using identical initial vector and iterations, so that
Improve hard-wired convenience.
Fig. 5 is the structural representation of one embodiment of the processing equipment of signal of the present invention, as shown in figure 5, the present embodiment
The processing equipment of signal include：Matrix calculation unit 11, weighing vector processing unit 12 and weighting processing unit 13, wherein,
Matrix calculation unit 11 is used for the up DMRS and sounding signal acquisitions channel estimation value according to reception, and according to the channel
Estimate, obtain the first up channel covariance matrix C；Wherein, the first up channel covariance matrix C is second up
Channel covariance matrices R k powers, the second up channel covariance matrix are the association side generated by the channel estimation value
Poor matrix；Weighing vector processing unit 12 is used for according to first up channel covariance matrix C, the initial vector V of input0
(n) and configuration iterations m/k, obtain weighing vector U；Weighting processing unit 13 is used to be generated according to weighing vector U
Weight coefficient is weighted processing to downstream signal, and sends the downstream signal after weighting processing；Wherein, n represents described initial
Vectorial V0(n) number of the element in, m, k and m/k are positive integer, and m is primary iteration number.
The processing equipment of the signal of the present embodiment can perform the technical scheme of embodiment of the method shown in Fig. 1, and to hold
The technical scheme of row embodiment of the method as shown in Figure 1, the present embodiment is also with including some nonrestrictive electronic circuits and knot
Structure etc..
In the present embodiment, because the first up channel covariance matrix C is the second up channel covariance matrix R k
Power, the iterations that processing equipment configures during handling the first up channel covariance matrix become initial
The 1/k of iterations, alleviate the processing load of the processor, accelerate the convergence of characteristic vector, improve calculate feature to
The speed of amount, so as to accelerate the processing speed of whole piece link, and realized beneficial to flowing water.
Fig. 6 is the structural representation of another embodiment of the processing equipment of signal of the present invention, in implementation shown in above-mentioned Fig. 5
On the basis of example, as shown in fig. 6, the weighing vector processing unit 12 includes：At matrix-vector multiplication subelement 121, normalization
Manage subelement 122 and judgment sub-unit 123.
Preferably, matrix-vector multiplication subelement 121 is used to use formula Vi+1(n)=Cm/k*Vi(n) it is this is first up
Channel covariance matrices C and primary vector Vi(n) matrix-vector multiplication processing is carried out, obtains secondary vector Vi+1(n)；Normalization
Processing subelement 122 is used to use formula Vi+1(n)=Vi+1(n)/|Vi+1(n) | to secondary vector Vi+1(n) it is normalized
Processing；Judgment sub-unit 123 is used to judge whether i is equal to m/k-1；If the judgment sub-unit 123 is judged as being not equal to, by i plus
1, and handled accordingly using the matrix-vector multiplication subelement 121 and the normalized subelement 122；If the judgement
Subelement 123 is judged as being equal to, by secondary vector Vi+1(n) it is used as weighing vector U；Wherein, i is positive integer, and during initialization
I=0, primary vector Vi(n)=V0(n)。
Further, the processing equipment of the signal can also include：Characteristic value processing unit 14 and depression of order processing unit 15,
Wherein, characteristic value processing unit 14 is used for according to weighing vector U, using formula λ=(R*U)H* U, eigenvalue λ is obtained；Depression of order
Processing unit 15 is used for according to weighing vector U and this feature value λ, using formula R '=R- λ * (U*UH), obtain on the 3rd
Row channel covariance matrices R ', then weighing vector processing unit 12 be additionally operable to according to the 3rd up channel covariance matrix R ', just
Begin vectorial V0(n) time weighing vector U ' and iterations m/k, is obtained；Weighting processing unit 13 be additionally operable to weighing vector U and
The arranged in matrix of secondary weighing vector U ' compositions is weight coefficient.
The processing equipment of the signal of the present embodiment can perform the technical scheme of any shown embodiments of the method for Fig. 2 to Fig. 4,
And to perform the technical scheme of embodiment of the method as shown in Figures 2 to 4, the present embodiment is also with including some nonrestrictive electricity
Sub-circuit and structure etc..
In the present embodiment, because the first up channel covariance matrix C is the second up channel covariance matrix R k
Power, the iterations that processing equipment configures during handling the first up channel covariance matrix become initial
The 1/k of iterations, alleviate the processing load of the processor, accelerate the convergence of characteristic vector, improve calculate feature to
The speed of amount, so as to accelerate the processing speed of whole piece link, and realized beneficial to flowing water.Obtained in the embodiment of the present invention special each time
Initial vector when levying vectorial is initial vector V0(n), iterations is m/k, and the embodiment of the present invention furthermore achieved that
The unification of characteristic vector calculation, i.e., using identical initial vector and iterations, so as to improve it is hard-wired just
Victory.
Further, in another embodiment of invention, matrix-vector multiplication subelement 121 is used to use formula Vi+1
(n)=Cm/k*Vi(n), by the first up channel covariance matrix C and primary vector Vi(n) matrix-vector multiplication processing is carried out,
Obtain secondary vector Vi+1(n)；Judgment sub-unit 123 is used to judge whether i is equal to m/k-1；If the judgment sub-unit 123 judges
Go out to be not equal to, handled accordingly by i plus 1 and using the matrix-vector multiplication subelement 121；If the judgment sub-unit 123
Judge to be equal to, by secondary vector Vi+1(n) it is used as the weighing vector U；Normalized subelement 122 is used for using public
Formula U=U/ | U |, weighing vector U is normalized；I=0, primary vector V when wherein i is positive integer and initializationi
(n)=V0(n)。
The processing equipment of characteristic vector provided by the present invention can realize that one of which is preferable by multiple hardwares
Embodiment is described as follows：
Fig. 7 is the structural representation of another embodiment of the processing equipment of signal of the present invention, in the present embodiment, with this
The processing equipment of signal is based on field programmable gate array (Field-Programmable Gate Array；Referred to as：FPGA)
Hardware is realized, and exemplified by k=8, the technical scheme of the present embodiment is discussed in detail, as shown in fig. 7, the characteristic vector of the present embodiment
Processing equipment include：Matrix computations device 21 (equivalent to the matrix calculation unit 11 shown in Fig. 5 or Fig. 6), characteristic vector meter
Calculate device 22 (equivalent to the weighing vector processing unit 12 shown in Fig. 5 or Fig. 6), matrix reduction and feature value calculation apparatus 23
(including characteristic value processing unit 14 and depression of order processing unit 15 shown in above-mentioned Fig. 6) and output buffer storage 24.
It should be noted that the processing equipment of the signal of the present invention is not limited to realize based on FPGA hardware, may be used also
To be realized based on the hardware such as central processing unit or application specific integrated circuit, the central processing of parallel processing especially can be based on
The hardware such as device or application specific integrated circuit is realized.
In the present embodiment, the matrix computations device 21 can include three matrix square computing modules, and respectively first
Matrix square computing module U0, the second matrix square computing module U1 and the 3rd matrix square computing module U2.Specifically, first
Matrix square computing module U1 is mainly made up of 3 functional units：Cache prime input data soldier pang buffer (Ping-Pong
Buffering；Referred to as：PPBUF) group 0, buf_ctrl units and algorithm process unit U0_SQU.The caching prime inputs number
Include RAM0, RAM1 and RAM2 according to PPBUF groups 0.Algorithm process unit U0_SQU includes：Matrix square computing subelement, thoroughly
Pass and bypass handles subelement.Second matrix square computing module U1 is also mainly made up of 3 functional units：It is defeated to cache prime
Enter data PPBUF groups 1, buf_ctrl units and algorithm process unit U1_SQU.Caching prime input data PPBUF groups 1
Including RAM3, RAM4 and RAM5.Algorithm process unit U1_SQU includes：Matrix square computing subelement, transparent transmission and bypass
Handle subelement.3rd matrix square computing module U2 is also mainly made up of 3 functional units：Cache prime input data
PPBUF groups 2, buf_ctrl units and algorithm process unit U2_SQU.Caching prime input data PPBUF groups 2 include
RAM6, RAM7 and RAM8.Algorithm process unit U2_SQU includes：Matrix square computing subelement, transparent transmission and bypass processing
Subelement.
Characteristic vector computing device 22 includes：Prime input data PPBUF groups 3 are cached, at buf_ctrl modules and algorithm
Manage module GET_VECTOR.Wherein, caching prime input data PPBUF groups 3 includes RAM9 and RAM10.Algorithm processing module
GET_VECTOR includes acquiring unit, calculates feature vector units and transparent transmission unit.Wherein, acquiring unit is with calculating characteristic vector
Unit is connected, and with the matrix square computing subelement in each algorithm process unit U0_SQU to U2_SQU, transparent transmission and
Bypass processing subelement and algorithm processing module GTE_R are respectively connected with and (not drawn in figure).It should also be noted that, this is saturating
Pass and bypass handles in subelement and is additionally provided with NOT gate, one end of the NOT gate is connected with the acquiring unit.
Matrix reduction and feature value calculation apparatus 23 include：Ping-pong register, caching prime input data PPBUF groups 4,
Buf_ctrl modules and algorithm processing module GTE_RUSB.Wherein, caching prime input data PPBUF groups 4 includes RAM11.Calculate
Method processing module GTE_RUSB includes calculating characteristic value and R ' units and transparent transmission unit.
Exporting buffer storage 24 includes caching prime input data PPBUF groups 5 and buf_ctrl modules.Wherein, before caching
Level input data PPBUF groups 5 include RAM12.
It should be noted that RAM0 to RAM12 can be the dual port RAM that a reading one is write and be PPBUF.
In the present embodiment, the operation principle of the processing equipment of characteristic vector is mainly：Cache prime input data PPBUF
RAM0, RAM1 and RAM2 in group 0 store covariance matrix R (equivalent to the second up channel shown in above-described embodiment
Covariance matrix), algorithm process unit U0_SQU replicates the second up channel covariance matrix R in RAM0, and passes through transparent transmission
And bypass processing subelement writes covariance matrix R in RAM3.Meanwhile the matrix in algorithm process unit U0_SQU is put down
Square computing subelement reads the covariance matrix R in RAM1 and RAM2, row matrix of going forward side by side square operation.Further, since matrix is put down
Square computing subelement receives the non-by-passing signal bypass0 of acquiring unit transmission, and transparent transmission and bypass processing subelement receive
The non-by-passing signal bypass0 sent to the acquiring unit, and the NOT gate in transparent transmission and bypass processing subelement is not other to this
Road signal bypass0 carries out conversion process so that non-by-passing signal bypass0 is converted into by-passing signal, so that matrix is put down
Square computing subelement does not bypass, transparent transmission and bypass processing subelement bypass, therefore so that matrix square computing subelement will be counted
Calculate result, i.e. covariance matrix R2Output is into RAM4 and RAM5.
Algorithm process unit U1_SQU replicates the covariance matrix R in RAM3, and single by transparent transmission and bypass processing
Member writes covariance matrix R in RAM6.Meanwhile matrix square computing subelement is read in algorithm process unit U1_SQU
Covariance matrix R in RAM4 and RAM52, row matrix of going forward side by side square operation.Further, since matrix square computing subelement receives
The non-by-passing signal bypass1 of acquiring unit input, transparent transmission and bypass processing subelement receive acquiring unit transmission
Non- by-passing signal bypass1, and the NOT gate in transparent transmission and bypass processing subelement turns to the non-by-passing signal bypass1
Change processing so that non-by-passing signal bypass1 is converted into by-passing signal, then matrix square computing subelement is not bypassed, thoroughly
Pass and bypass processing subelement bypass, therefore, matrix square computing subelement is by result of calculation, i.e. covariance matrix R4Output
Into RAM7 and RAM8.
Algorithm process unit U2_SQU replicates the second up channel covariance matrix R in RAM6, and by transparent transmission and
Bypass processing subelement writes covariance matrix R in RAM9.Meanwhile matrix square computing in algorithm process unit U1_SQU
Subelement reads the covariance matrix R in RAM7 and RAM84, row matrix of going forward side by side square operation.Further, since matrix square computing
Subelement receives the non-by-passing signal bypass2 of acquiring unit input, and transparent transmission and bypass processing subelement receive the acquisition
The non-by-passing signal bypass2 that unit is sent, and the NOT gate in transparent transmission and bypass processing subelement is to the non-by-passing signal
Bypass2 carries out conversion process so that non-by-passing signal bypass2 is converted into by-passing signal, then causes matrix square operator
Unit does not bypass, and transparent transmission and bypass processing subelement bypass, therefore, matrix square computing subelement assists result of calculation
Variance matrix R8Output is into RAM10.
Algorithm processing module GET_VECTOR replicates the second up channel covariance matrix R in RAM9, and by the association side
Poor matrix R is write in RAM11 by transparent transmission unit.Meanwhile calculate feature vector units and receive not bypassing for acquiring unit input
Signal bypass3, then make it that calculating feature vector units does not bypass, reads the covariance matrix R in RAM108(equivalent to above-mentioned
The first up channel covariance matrix shown in embodiment), and initial vector V is obtained from acquiring unit0(n) and configuration
Iterations m/k, using formula U=Cm/k*V0(n) iteration carries out calculation process, obtains characteristic vector U (equivalent to above-mentioned implementation
Weighing vector shown in example), and this feature vector U is exported to the table tennis of matrix reduction and feature value calculation apparatus 23 and deposited
Device.
Algorithm processing module GTE_R ' reads the characteristic vector U in ping-pong register, calculating matrix depression of order, i.e. covariance square
Battle array R ' (equivalent to the 3rd up channel covariance matrix shown in above-described embodiment), and calculate eigenvalue λ.Further, since
The non-by-passing signal bypass4 of acquiring unit input is received, therefore, by covariance matrix R ', characteristic vector U and eigenvalue λ
It is written in RAM12.
Further, only need to be in caching prime input data PPBUF when needing to obtain sub-eigenvector and sub-eigenvalue
Covariance matrix R ' is stored in RAM0, RAM1 and RAM2 in group 0 and is repeated the above, you can to obtain sub-eigenvector
And sub-eigenvalue.
It is worth noting that, above-mentioned buf_ctrl units and the major function of buf_ctrl modules are distribution buffer
The right to use so that the side of writing in unit or subelement in PPBUF groups and reading side are when different to each in the PPBUF groups
Individual unit or subelement are operated respectively.Further, since the buffer controlled is PPBUF, therefore buf_ctrl units are simultaneously
PPBUF table tennis BUF and pang BUF are managed.
Fig. 8 is buf_ctrl concrete structure schematic diagram, is led as shown in figure 8, PPBUF control is distributed and switched
To pass through Flag [1:0] and wr_rsl [1:0]、rd_rls[1:0] three signals are completed, wherein Flag [1] and wr_rsl
[1], the control of rd_rls [1] signal pang BUF, Flag [0] and wr_rsl [0], rd_rls [0] signal control table tennis BUF.With control
Exemplified by table tennis BUF, it is as follows that it distributes the mechanism of BUF controls：
During reset, Flag [0] is 0, and now table tennis BUF control is in the side of writing, and now only in the side of writing, completion is write to table tennis BUF
Enter data, release is write after control (i.e. wr_rsl [0] is 1, and this signal is pulse signal), and Flag [0] becomes 1, now table tennis BUF
Control give reading side, only reading side complete to table tennis BUF read data, release read control (i.e. rd_rsl [0] be 1, this
Signal is pulse signal) after, Flag [0] becomes 0, and table tennis BUF control gives the side of writing, and so far completes the circulation of a read-write.
In this equipment, multiple PPBUF are all contained in PPBUF groups 0, PPBUF groups 1, PPBUF groups 2 and PPBUF groups 3, but
These PPBUF can unify to be controlled by 1 buf_ctrl unit or buf_ctrl modules, carry out PPBUF controls together
The switching of power.
, it is necessary to first write covariance matrix R when external unit calls this equipment to calculate the characteristic vector of covariance matrix
To RAM0, RAM1 and RAM2, then by register configuration initial vector and iterations to feature vector units are calculated, finally
This equipment is notified by the wr_rls signals of buf_ctrl units or buf_ctrl modules；This equipment will read covariance square
Battle array R, complete to calculate, and export the result R ' of this calculating and eigenvalue λ and characteristic vector U are exported to buffer storage 24, and
Release output output buffer storage 24 writes control；Buffer storage 24 is exported after data are finished receiving, buf_ctrl modules
Flag signals can become 1, so as to notify external unit to obtain final result of calculation.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above-mentioned each method embodiment can lead to
The related hardware of programmed instruction is crossed to complete.Foregoing program can be stored in a computer read/write memory medium.The journey
Sequence upon execution, execution the step of including above-mentioned each method embodiment；And foregoing storage medium includes：ROM, RAM, magnetic disc or
Person's CD etc. is various can be with the medium of store program codes.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations；To the greatest extent
The present invention is described in detail with reference to foregoing embodiments for pipe, it will be understood by those within the art that：Its according to
The technical scheme described in foregoing embodiments can so be modified, either which part or all technical characteristic are entered
Row equivalent substitution；And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology
The scope of scheme.
Claims (8)
- A kind of 1. processing method of signal, it is characterised in that including：Channel estimation value is obtained, and according to the channel estimation value, obtains the first up channel covariance matrix C；Wherein, it is described First up channel covariance matrix C be the second up channel covariance matrix R k powers, the second up channel association side Poor matrix R is the covariance matrix generated by the channel estimation value, wherein, the up solution that the channel estimation value passes through reception Reference signal and measurement signal is adjusted to obtain；According to the first up channel covariance matrix C, the initial vector V of input0(n) and configuration iterations m/k, Obtain weighing vector U；According to the weighing vector U generate weight coefficient, processing is weighted to downstream signal, and send weighting handle after under Row signal；Wherein, it is described that weight coefficient is generated according to the weighing vector U, specifically include：According to formulaλ=(R*U)H*UObtain eigenvalue λ；According to formulaR'=R- λ * (U*UH)Obtain the 3rd up channel covariance matrix R'；According to the 3rd up channel covariance matrix R', the initial vector V0(n) and the iterations m/k is obtained Secondary weighing vector U'；Arranged in matrix by the weighing vector U and time weighing vector U' compositions is the weight coefficient；Wherein, n represents the initial vector V0(n) number of the element in, m, k and m/k are positive integer, and m is primary iteration Number.
- 2. the processing method of signal according to claim 1, it is characterised in that described to be assisted according to first up channel Variance matrix C, the initial vector V of input0(n) and configuration iterations m/k, obtain weighing vector U, including：Using formula Vi+1(n)=Cm/k*Vi(n) by the first up channel covariance matrix C and primary vector Vi(n) carry out Matrix multiple processing, obtains secondary vector Vi+1(n)；Using formula Vi+1(n)=Vi+1(n)/|Vi+1(n) | to the secondary vector Vi+1(n) it is normalized；Judge whether i is equal to m/k-1；If being not equal to, by i plus 1, using formula Vi+1(n)=Cm/k*Vi(n) by the first up channel covariance matrix C and One vectorial Vi(n) matrix multiple processing is carried out, obtains secondary vector Vi+1(n)；And using formula Vi+1(n)=Vi+1(n)/|Vi+1 (n) | to the secondary vector Vi+1(n) it is normalized；If i is equal to m/k-1, by the secondary vector Vi+1(n) it is used as weighing vector U；Wherein, i is positive integer, and i=0, primary vector V during initializationi(n)=V0(n)。
- 3. the processing method of signal according to claim 1, it is characterised in that described to be assisted according to first up channel Variance matrix C, the initial vector V of input0(n) and configuration iterations m/k, obtain weighing vector U, including：Using formula Vi+1(n)=Cm/k*Vi(n) by the first up channel covariance matrix C and primary vector Vi(n) carry out Matrix-vector multiplication is handled, and obtains secondary vector Vi+1(n)；Judge whether i is equal to m/k-1；If being not equal to, by i plus 1, using formula Vi+1(n)=Cm/k*Vi(n) by the first up channel covariance matrix C and One vectorial Vi(n) matrix-vector multiplication processing is carried out, obtains secondary vector Vi+1(n)；If i is equal to m/k-1, by the secondary vector Vi+1(n) it is used as weighing vector U；Using formula U=U/ | U |, the weighing vector U is normalized；Wherein, i is positive integer, and i=0, primary vector V during initializationi(n)=V0(n)。
- 4. the processing method of signal according to claim 1, it is characterised in that the weighing vector U generates the weighting Coefficient, including：According to the weighing vector U, using formula λ=(R*U)H* U obtains eigenvalue λ；According to the weighing vector U and the eigenvalue λ, using formula R'=R- λ * (U*UH) obtain the 3rd up channel association Variance matrix R'；According to the 3rd up channel covariance matrix R', the initial vector V0(n) and the iterations m/k, obtain Secondary weighing vector U'；Arranged in matrix by the weighing vector U and time weighing vector U' compositions is the weight coefficient.
- A kind of 5. processing equipment of signal, it is characterised in that including：Matrix calculation unit, for obtaining channel estimation value, and according to the channel estimation value, obtain the first up channel association side Poor Matrix C；Wherein, the first up channel covariance matrix C is the second up channel covariance matrix R k powers, described Second up channel covariance matrix is the covariance matrix generated by the channel estimation value, wherein, the channel estimation value Obtained by the uplink demodulation reference signal and measurement signal of reception；Weighing vector processing unit, for according to the first up channel covariance matrix C, the initial vector V of input0(n) with And the iterations m/k of configuration, obtain weighing vector U；Weighting processing unit, for generating weight coefficient according to the weighing vector U, processing is weighted to downstream signal, and Send the downstream signal after weighting processing；Wherein, the weighting processing unit is specifically used for：According to formulaλ=(R*U)H*UObtain eigenvalue λ；According to formulaR'=R- λ * (U*UH)Obtain the 3rd up channel covariance matrix R'；According to the 3rd up channel covariance matrix R', the initial vector V0(n) and the iterations m/k is obtained Secondary weighing vector U'；Arranged in matrix by the weighing vector U and time weighing vector U' compositions is the weight coefficient；Wherein, n represents the initial vector V0(n) number of the element in, m, k and m/k are positive integer, and m is primary iteration Number.
- 6. the processing equipment of signal according to claim 5, it is characterised in that the weighing vector processing unit includes：Matrix-vector multiplication subelement, for using formula Vi+1(n)=Cm/k*Vi(n) by the first up channel covariance square Battle array C and primary vector Vi(n) matrix-vector multiplication processing is carried out, obtains secondary vector Vi+1(n)；Normalized subelement, for using formula Vi+1(n)=Vi+1(n)/|Vi+1(n) | to the secondary vector Vi+1(n) It is normalized；Judgment sub-unit, for judging whether i is equal to m/k-1；If the judgment sub-unit is judged as being not equal to, by i plus 1, and using the matrix-vector multiplication subelement and described return One changes processing subelement is handled accordingly；If the judgment sub-unit is judged as being equal to, by the secondary vector Vi+1(n) it is used as weighing vector U；Wherein, i is positive integer, and i=0, primary vector V during initializationi(n)=V0(n)。
- 7. the processing equipment of signal according to claim 5, it is characterised in that the weighing vector processing unit includes：Matrix-vector multiplication subelement, for using formula Vi+1(n)=Cm/k*Vi(n), by the first up channel covariance Matrix C and primary vector Vi(n) matrix-vector multiplication processing is carried out, obtains secondary vector Vi+1(n)；Judgment sub-unit, for judging whether i is equal to m/k-1；If the judgment sub-unit is judged to be not equal to, carried out accordingly by i plus 1, and using the matrix-vector multiplication subelement Processing；If the judgment sub-unit is judged to be equal to, by the secondary vector Vi+1(n) it is used as the weighing vector U；Normalized subelement, for using formula U=U/ | U |, the weighing vector U is normalized；Wherein, i is positive integer, and i=0, primary vector V during initializationi(n)=V0(n)。
- 8. the processing equipment of signal according to claim 5, it is characterised in that also include：Characteristic value processing unit, for according to the weighing vector U, using formula λ=(R*U)H* U, eigenvalue λ is obtained；Depression of order processing unit, for according to the weighing vector U and the eigenvalue λ, using formula R'=R- λ * (U*UH), The 3rd up channel covariance matrix R' is obtained, to obtain time weighing vector U'；Then the weighing vector processing unit is additionally operable to according to the 3rd up channel covariance matrix R', the initial vector V0(n) time weighing vector U' and the iterations m/k, is obtained；The weighting processing unit is additionally operable to add the weighing vector U and time arranged in matrix of weighing vector U' compositions to be described Weight coefficient.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210082789.0A CN103368621B (en) | 2012-03-26 | 2012-03-26 | The processing method and equipment of signal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210082789.0A CN103368621B (en) | 2012-03-26 | 2012-03-26 | The processing method and equipment of signal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103368621A CN103368621A (en) | 2013-10-23 |
| CN103368621B true CN103368621B (en) | 2017-12-15 |
Family
ID=49369256
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210082789.0A Active CN103368621B (en) | 2012-03-26 | 2012-03-26 | The processing method and equipment of signal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103368621B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1925362A (en) * | 2005-08-29 | 2007-03-07 | 中兴通讯股份有限公司 | Method for realizing intelligent antenna based on even linear array |
| CN101192868A (en) * | 2006-11-24 | 2008-06-04 | 中兴通讯股份有限公司 | Multi-service wave bundle shaping device for wireless communication system |
| CN101488792A (en) * | 2008-01-15 | 2009-07-22 | 大唐移动通信设备有限公司 | Wave beam shaping method and apparatus |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8306001B2 (en) * | 2010-01-14 | 2012-11-06 | Cisco Technology, Inc. | Dynamic downlink beamforming weight estimation for beamforming-space time code transmissions |
-
2012
- 2012-03-26 CN CN201210082789.0A patent/CN103368621B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1925362A (en) * | 2005-08-29 | 2007-03-07 | 中兴通讯股份有限公司 | Method for realizing intelligent antenna based on even linear array |
| CN101192868A (en) * | 2006-11-24 | 2008-06-04 | 中兴通讯股份有限公司 | Multi-service wave bundle shaping device for wireless communication system |
| CN101488792A (en) * | 2008-01-15 | 2009-07-22 | 大唐移动通信设备有限公司 | Wave beam shaping method and apparatus |
Non-Patent Citations (1)
| Title |
|---|
| "智能天线中的自适应波束形成算法研究与设计";肖航;《中国优秀硕士学位论文全文数据库》;20090415(第4期);第55-57、68页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103368621A (en) | 2013-10-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104849698B (en) | A kind of radar signal method for parallel processing and system based on heterogeneous multi-core system | |
| CN107544052A (en) | A kind of second-order statistic reconstruct DOA estimation method based on matrix completion | |
| CN103516643B (en) | MIMO detecting preprocessing device and method | |
| CN110326003A (en) | The hardware node with location-dependent query memory for Processing with Neural Network | |
| CN109003132A (en) | Advertisement recommended method and Related product | |
| CN105403874B (en) | Nonuniform noise owes standing wave arrival direction estimating method | |
| CN106951395A (en) | Towards the parallel convolution operations method and device of compression convolutional neural networks | |
| CN108462521A (en) | The anti-interference realization method of adaptive array antenna | |
| CN107666361A (en) | The adaptive cancellation method and device of multicarrier passive intermodulation interference | |
| CN106295122A (en) | A kind of sane zero falls into broadening Adaptive beamformer method | |
| CN106330276A (en) | Large-scale MIMO linear detection method and device based on SOR algorithm | |
| CN103871021A (en) | CPU (central processing unit)-GPU (graphic processing unit) cooperative work target track initializing method | |
| Chen et al. | Hardware and energy-efficient stochastic LU decomposition scheme for MIMO receivers | |
| Yinger et al. | Customizable FPGA OpenCL matrix multiply design template for deep neural networks | |
| CN107943756A (en) | A kind of computational methods and Related product | |
| CN106680779B (en) | Beam-forming method and device under impulsive noise | |
| CN103368621B (en) | The processing method and equipment of signal | |
| CN108108189A (en) | A kind of computational methods and Related product | |
| CN110635833A (en) | Power distribution method and device based on deep learning | |
| Chen et al. | Hardware efficient massive MIMO detector based on the Monte Carlo tree search method | |
| CN105869189B (en) | Radar target blind source separation method based on FFDIAG algorithm | |
| CN108512619A (en) | A kind of analogy method of the more bandwidth channels of shortwave multichannel | |
| CN102006105B (en) | Deep space receiving antenna array correlated weighting method and system | |
| CN107135026A (en) | Robust ada- ptive beamformer method based on matrix reconstruction in the presence of unknown mutual coupling | |
| US7925213B2 (en) | Method and system for audio signal processing for Bluetooth wireless headsets using a hardware accelerator |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |