CN104717000A - Data processing method and device - Google Patents
Data processing method and device Download PDFInfo
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- CN104717000A CN104717000A CN201510083791.3A CN201510083791A CN104717000A CN 104717000 A CN104717000 A CN 104717000A CN 201510083791 A CN201510083791 A CN 201510083791A CN 104717000 A CN104717000 A CN 104717000A
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- 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
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- 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
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
- H04B7/0848—Joint weighting
- H04B7/0854—Joint weighting using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
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Abstract
The embodiment of the invention discloses a data processing method which is used for solving the problem that in a multilayer system, the good throughout capacity can not be realized through a traditional minimum mean square error (MMSE) algorithm and used for improving the demodulation quality. The data processing method is applied to a multi-antenna system which comprises a data receiving architecture, wherein the data receiving architecture comprises multiple-input and multiple-output (MIMO) demodulation. The method comprises the steps that firstly, user equipment (UE) acquires a first equivalent channel matrix and first data; secondly, the UE decomposes the first equivalent channel matrix to acquire a second equivalent channel matrix; thirdly, the UE demodulates the second equivalent channel matrix through a matrix decomposition maximum likelihood QRM algorithm, and second data are acquired according to the first data; fourthly, the UE demodulates the second equivalent channel matrix through the MMSE algorithm, and third data are acquired according to the first data; fifthly, the UE acquires fourth data according to the second data and the third data.
Description
Technical field
The present invention relates to communication technical field, be specifically related to a kind of data processing method and device.
Background technology
Future communication technologies system requirements holds user as much as possible in certain frequency band, and the transmission rate of data will reach 10 ~ 100Mb/s, multiple-input and multiple-output (English full name: Multiple-InputMultiple-Output, abbreviation: MIMO) technology is that the third generation and future communication systems realize high data rate, improve the important channel of transmission quality, abundant development space resource, multiaerial system is utilized to realize MIMO, significantly improve the capacity of communication system without increase in bandwidth, and channel reliability greatly strengthens.
At present, in multi-antenna systems, if transmitting terminal has T bar transmitting antenna, receiving terminal has R bar reception antenna.System model is as shown in Figure 1: the model of Received signal strength represents with formula below:
y＝Hx+n
Wherein, y represents the reception vector that reception antenna receives, and x is the transmission vector that transmitting antenna sends, and H is equivalent channel matrix, and n is noise.Send vector x=[x
1, x
2... x
t]
t, wherein, T is the antenna number that transmitting antenna sends, and receives vectorial y=[y
1, y
2... y
r]
t, n=[n
1, n
2... n
r]
tconcrete expression zero-mean, variance on reception antenna are σ
2white Gauss noise, H is specially R × T and ties up channel matrix, the object of MIMO receiver is from receiving the log-likelihood ratio obtaining each transmission bit vectorial y, but, in 4G multilayer system, adopt single conventional Least Mean Square error (English full name: (Minimum MeanSquare Error, abbreviation: MMSE) algorithm, cannot reach good throughput.
Summary of the invention
Embodiments provide a kind of data processing method and device, for solving in multilayer system, adopting conventional Least Mean Square error MMSE algorithm cannot reach the problem of good throughput, improving demodulation quality.
First aspect present invention provides a kind of data processing method, is applied to multiaerial system, and described multiaerial system comprises data receiver framework, and described data receiver framework comprises multiple-input and multiple-output MIMO demodulation, and described method comprises:
User equipment (UE) obtains the first equivalent channel matrix and the first data, and described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T;
Described first equivalent channel is decomposed to obtain the second equivalent channel matrix by described UE;
Described UE utilizes the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and according to described first data acquisition second data;
Described UE utilizes the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and according to described first data acquisition the 3rd data;
Described UE is according to described second data and described 3rd data acquisition the 4th data.
In conjunction with first aspect, in the first mode in the cards, described first equivalent channel is decomposed and is comprised to obtain the second equivalent channel matrix by described UE:
Described UE sorts to the SNR of each layer in described first equivalent channel matrix, and according to the result sorted to described each layer SNR to obtain at least the second two equivalent channel matrix.
In conjunction with the first possible implementation of first aspect, in the implementation that the second is possible, described UE utilizes the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and comprises according to described first data acquisition second data:
Described UE carries out Matrix QR Decomposition to obtain unitary matrice Q and upper triangular matrix R respectively to described at least two the second equivalent channel matrix, and wherein, H equals QR, and H is the second equivalent channel matrix;
Described UE obtains demodulation vector according to the described Q matrix and the vectorial y of described reception that decompose acquisition
wherein, by
Obtain
wherein, s is the transmission vector that base station sends, and n is noise,
for demodulated noise;
Described UE is according to described demodulation vector
survival route number M at different levels at least two the second equivalent channel matrix described in obtaining respectively
icorresponding metric;
Described UE is according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data.
In conjunction with the first possible implementation of first aspect, in the implementation that the third is possible, the SNR sequence of described UE to each layer in described first equivalent channel matrix comprises:
Described UE sorts to the SNR of described each layer according to putting in order and exchanging row order.
In conjunction with the implementation that the second of first aspect is possible, in the 4th kind of possible implementation, described UE is according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data and comprises:
The survival route number M that described UE is at different levels from described at least two the second equivalent channel matrix
iminimum degree value is chosen in corresponding metric;
Described UE according to described minimum degree value obtain bit be 0 and bit be the metric of 1;
Described UE by described bit be 0 and bit be 1 metric subtract each other obtain described second data.
In conjunction with first aspect, in the 5th kind of possible implementation, described UE utilizes the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and described first data acquisition the 3rd data comprise:
Described UE is according to formula (H
hh+ σ
2i)
-1h
hh obtains MMSE demodulation factor, and wherein, I is unit battle array, and H is the second equivalent channel matrix, σ
2represent noise power;
Described UE is according to formula (H
hh+ σ
2i)
-1h
hy obtains MMSE demodulation symbol;
Described UE obtains described 3rd data according to described MMSE demodulation factor and described demodulation symbol.
In conjunction with first aspect, in the 6th kind of possible implementation, described UE comprises according to described second data and described 3rd data acquisition the 4th data:
Described UE is by multiplied by weight corresponding with described second data for described second data;
Described UE is by multiplied by weight corresponding with described 3rd data for described 3rd data;
Described UE by the described results added be multiplied to obtain described 4th data.
Second aspect present invention provides a kind of data processing equipment, comprising:
Acquisition module, the first equivalent channel matrix and the first data, described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T;
Described acquisition module, also for decomposing described first equivalent channel to obtain the second equivalent channel matrix;
Described acquisition module, also for utilizing the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and according to described first data acquisition second data;
Described acquisition module, also for utilizing the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and according to described first data acquisition the 3rd data;
Described acquisition module, also for according to described second data and described 3rd data acquisition the 4th data.
In conjunction with second aspect, in the first mode in the cards, described acquisition module comprises:
Sequencing unit, for sorting to the SNR of each layer in described first equivalent channel matrix;
Acquiring unit, for according to the result sorted to described each layer SNR to obtain at least two the second equivalent channel matrix.
In conjunction with the first possible implementation of second aspect, in the implementation that the second is possible,
Described acquiring unit, also decompose for carrying out QR respectively to described at least two the second equivalent channel matrix to obtain unitary matrice Q and upper triangular matrix R, wherein, H equals QR, and H is the second equivalent channel matrix;
Described acquiring unit, also for obtaining demodulation vector according to the described Q matrix and the vectorial y of described reception that decompose acquisition
wherein, by
Obtain
wherein, s is the transmission vector that base station sends, and n is noise,
for demodulated noise;
Described acquiring unit, also for vectorial according to described demodulation
survival route number M at different levels at least two the second equivalent channel matrix described in obtaining respectively
icorresponding metric;
Described acquiring unit, also for according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data.
In conjunction with the first possible implementation of second aspect, in the implementation that the third is possible,
Described sequencing unit, specifically for sorting to the SNR of described each layer according to putting in order and exchanging row order.
In conjunction with the implementation that the second of second aspect is possible, in the 4th kind of possible implementation, described acquiring unit comprises:
Choose subelement, for survival route number M at different levels from described at least two the second equivalent channel matrix
iminimum degree value is chosen in corresponding metric;
Obtain subelement, for choose described in basis described minimum degree value that subelement chooses obtain bit be 0 and bit be the metric of 1;
Described acquisition subelement, also for by described bit be 0 and bit be 1 metric subtract each other obtain described second data.
In conjunction with second aspect, in the 5th kind of possible implementation,
Described acquiring unit, also for according to formula (H
hh+ σ
2i)
-1h
hh obtains MMSE demodulation factor, and wherein, I is unit battle array, and H is the second equivalent channel matrix, σ
2represent noise power;
Described acquiring unit, also for according to formula (H
hh+ σ
2i)
-1h
hy obtains MMSE demodulation symbol;
Described acquiring unit, also for obtaining described 3rd data according to described MMSE demodulation factor and described demodulation symbol.
In conjunction with second aspect, in the 6th kind of possible implementation,
Described acquiring unit, also for by multiplied by weight corresponding with described second data for described second data, the multiplied by weight corresponding with described 3rd data by described 3rd data, by the described results added be multiplied to obtain described 4th data.
Apply above technical scheme, UE obtains the second data according to the demodulation of QRM algorithm, obtains the 3rd data according to least mean-square error MMSE demodulation, and according to described second data and described 3rd data acquisition the 4th data.Visible, obtaining on the basis of the 3rd data according to MMSE algorithm, the second data are obtained further according to the demodulation of QRM algorithm, and the second data obtained and the 3rd data are carried out merging acquisition the 4th data, solve in multilayer system, adopt MMSE algorithm cannot reach the problem of good throughput, effectively improve demodulation quality.
Term " first ", " second ", " the 3rd " " 4th " etc. (if existence) in specification of the present invention and claims and above-mentioned accompanying drawing are for distinguishing similar object, and need not be used for describing specific order or precedence.The embodiments described herein should be appreciated that the data used like this can be exchanged in the appropriate case, so that can be implemented with the order except the content except here diagram or description.In addition, term " comprises " and " having " and their any distortion, intention is to cover not exclusive comprising, such as, contain those steps or unit that the process of series of steps or unit, method, system, product or equipment is not necessarily limited to clearly list, but can comprise clearly do not list or for intrinsic other step of these processes, method, product or equipment or unit.
The communication system of embodiment of the present invention application can be based on the improvement done by Long Term Evolution (Long TermEvaluation, LTE) system or other communication systems, does not limit herein to this.
What first illustrate is, subscriber equipment (the User Equipment that the embodiment of the present invention is mentioned, UE) may be that people is to people (H2H, Human to Human) subscriber equipment may be maybe machine to machine (M2M, Machine to Machine) subscriber equipment, or the UE of other type.Wherein, M2M subscriber equipment can claim machine type communication device (MTC Device, Machine Type Communications Device).
Refer to Fig. 2, in the embodiment of the present invention, an embodiment of data processing method comprises:
201, user equipment (UE) obtains the first equivalent channel matrix and the first data;
In embodiments of the present invention, described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T.
202, the first equivalent channel is decomposed to obtain the second equivalent channel matrix by UE;
In embodiments of the present invention, need the first equivalent channel matrix to decompose acquisition second equivalent channel matrix, to reach good throughput.
203, UE utilizes matrix decomposition maximum likelihood QRM algorithm demodulation second equivalent channel matrix, and according to the first data acquisition second data;
In embodiments of the present invention, matrix decomposition maximum likelihood (English full name: QR-MaximumLikelihood Detection, abbreviation: QRM) algorithm is the optimization carried out in the structure of prior art MIMO demodulation, unlike the prior art, in prior art, MIMO demodulation only relates to MMSE demodulation, and in multilayer system, adopts single MMSE algorithm demodulation cannot reach good throughput, therefore by the further optimization of QRM demodulation, defect of the prior art is solved.
204, UE utilizes least mean-square error MMSE algorithm demodulation second equivalent channel matrix, and according to the first data acquisition the 3rd data;
In embodiments of the present invention, more than employing QRM demodulation, also continues to adopt MMSE demodulation, by the merging of two kinds of demodulation, makes, in the face of complicated multilayer system, effectively to improve demodulation quality.
It should be noted that, step 203 and step 204 be order in no particular order, may also be and first carry out step 203, then carry out step 204, can also be carry out simultaneously, be not specifically limited herein.
205, UE is according to described second data and described 3rd data acquisition the 4th data.
In embodiments of the present invention, the 3rd data that the second data obtain QRM algorithm and MMSE algorithm obtain merge, and obtain the 4th data.
In the embodiment of the present invention, UE obtains the second data according to QRM algorithm, obtains the 3rd data according to least mean-square error MMSE algorithm, and according to described second data and described 3rd data acquisition the 4th data.Visible, obtaining on the basis of the 3rd data according to MMSE algorithm, the second data are obtained further according to QRM algorithm, and the second data obtained and the 3rd data are carried out merging acquisition the 4th data, solve in multilayer system, adopt MMSE algorithm cannot reach the problem of good throughput, effectively improve demodulation quality.
Embodiment illustrated in fig. 2 technical, UE obtains the second data according to QRM demodulation multiple implementation, and citing is below described in detail, and refer to Fig. 3, in the embodiment of the present invention, a kind of implementation of QRM demodulation comprises:
301, UE carries out QR decomposition to obtain unitary matrice Q and upper triangular matrix R respectively at least two the second equivalent channel matrix;
In embodiments of the present invention, H equals QR, and in practice, owing to being the second equivalent channel matrix H obtained by different sequences, therefore each second equivalent channel matrix is not identical, is not specifically limited herein.
Be understandable that, UE sorts to the SNR of layer each in the first equivalent channel matrix, and according to the result sorted to each layer SNR to obtain at least two the second equivalent channel matrix;
Optionally, UE sorts to the SNR of described each layer according to putting in order and exchanging row order.
It should be noted that, UE has a variety of according to putting in order and exchanging row order to the mode that the SNR of described each layer sorts, and according to SNR, can sort, be not specifically limited herein according to energy and other modes.
Be understandable that, at least second equivalent channel matrix is obtained according to putting in order, at least second equivalent channel matrix is obtained according to exchange row order, certainly, UE has a variety of according to putting in order and exchanging row order to the mode that the SNR of described each layer sorts, therefore, can be more than one according to putting in order the second equivalent channel matrix obtained, can be more than one according to the second equivalent channel matrix exchanging the acquisition of row order, wherein, the second equivalent channel matrix is the equivalent channel matrix obtained after the first equivalent channel matrix is carried out QR decomposition.
302, UE obtains demodulation vector according to decomposing the Q matrix obtained with the vectorial y of reception
In embodiments of the present invention, by
Obtain
wherein, s is the transmission vector that base station sends, and n is noise,
for demodulated noise.
303, UE is according to demodulation vector
obtain survival route number M at different levels in these at least two second equivalent channel matrix respectively
icorresponding metric;
In embodiments of the present invention, the demodulation vector launched in step 302 is utilized
by firmly sentencing node calculate survival route number M at different levels
icorresponding metric, until calculate the metric of afterbody.
Illustrate: for last one deck (i.e. the first order):
first firmly sentence and obtain
for a point in constellation point, then exist
near look for several constellation point, as M
tthe father node of individual survival route
under each father node, utilize formula
Calculate the metric ErrL of the first order
t,i;
Same, firmly can sentence in layer second from the bottom (second level) and a father node
utilize formula
Calculate the metric ErrL of the second level
t-1, i;
The like, finally find the father node of ground floor (T level)
utilize formula
calculate the metric ErrL of T level
1, i;
Finally, formula ErrL is utilized
i=ErrL
1, i+ ...+ErrL
t-1, i+ ErrL
t,icalculate father node
under metric.
304, UE is according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data.
Optionally, UE is according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data and comprises:
The survival route number M that UE is at different levels from described at least two the second equivalent channel matrix
iminimum degree value is chosen in corresponding metric;
UE according to described minimum degree value obtain bit be 0 and bit be the metric of 1;
UE by described bit be 0 and bit be 1 metric subtract each other obtain described second data.
In embodiments of the present invention, first choose a minimum degree value, and find out father node corresponding to this minimum degree value, constellation point is found by this father node, and find further bit be 0 and bit be the metric of 1, finally, by bit be 0 and bit be 1 metric subtract each other obtain described second data.
Embodiment illustrated in fig. 2 technical, UE obtains the second data according to least mean-square error MMSE demodulation multiple implementation, and citing is below described in detail, and refer to Fig. 4, in the embodiment of the present invention, a kind of implementation of MMSE demodulation comprises:
401, UE is according to formula (H
hh+ σ
2i)
-1h
hh obtains MMSE demodulation factor;
In embodiments of the present invention, σ
2represent noise power, I is unit battle array, and H is the second equivalent channel matrix, by the second equivalent channel matrix H of acquisition and noise power σ
2substitute into formula (H
hh+ σ
2i)
-1h
hh obtains MMSE demodulation factor.
402, UE is according to formula (H
hh+ σ
2i)
-1h
hy obtains MMSE demodulation symbol;
In embodiments of the present invention, by the second equivalent channel matrix H obtained, noise power σ
2and receive vectorial y substitution formula (H
hh+ σ
2i)
-1h
hy obtains MMSE demodulation symbol.
403, UE obtains the 3rd data according to MMSE demodulation factor and demodulation symbol.
In embodiments of the present invention, described 3rd data are obtained according to MMSE demodulation factor and described demodulation symbol further.
Optionally, according to MMSE demodulation factor and demodulation symbol, recycling log-likelihood ratio formula obtains described 3rd data.
On basis embodiment illustrated in fig. 2, refer to Fig. 5, in the embodiment of the present invention, another embodiment of data processing method comprises:
501, user equipment (UE) obtains the first equivalent channel matrix and the first data;
In embodiments of the present invention, described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T.
502, the first equivalent channel is decomposed to obtain the second equivalent channel matrix by UE;
Optionally, described first equivalent channel decomposition comprises to obtain the second equivalent channel matrix by UE:
Described UE sorts to the SNR of each layer in described first equivalent channel matrix, and according to the result sorted to described each layer SNR to obtain at least the second two equivalent channel matrix.
503, UE utilizes the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and according to described first data acquisition second data;
In embodiments of the present invention, UE obtains the first data according to QRM demodulation and specifically consults step 301 ~ 304 in Fig. 3, repeats no more herein.
504, UE utilizes the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and according to described first data acquisition the 3rd data;
In embodiments of the present invention, UE obtains the second data according to least mean-square error MMSE demodulation and specifically consults step 401 ~ 403 in Fig. 4, repeats no more herein.
505, UE is by multiplied by weight corresponding with the second data for the second data;
506, UE is by multiplied by weight corresponding with the 3rd data for the 3rd data;
In embodiments of the present invention, in order to make demodulation performance balance, need the first data multiplied by weight corresponding with the first data, the multiplied by weight that the second data are corresponding with the second data.
It should be noted that, the order of step 505 and step 506 can be exchanged, and is not specifically limited herein.
507, UE by the results added be multiplied to obtain the 4th data.
In embodiments of the present invention, by by the results added be multiplied to obtain the 4th data, when implementation complexity is limited, greatly improve power system capacity, improve demodulation performance.
In the embodiment of the present invention, UE obtains the second data according to QRM algorithm, the 3rd data are obtained according to least mean-square error MMSE algorithm, and the multiplied by weight corresponding with the second data according to described second data, the result of the multiplied by weight that described 3rd data are corresponding with the 3rd data is added to obtain the 4th data again.Visible, obtaining on the basis of the 3rd data according to MMSE algorithm, the second data are obtained further according to QRM algorithm, and the second data obtained and the 3rd data are carried out merging acquisition the 4th data, solve in multilayer system, adopt most MMSE algorithm cannot reach the problem of good throughput, effectively improve demodulation quality.
For ease of better implementing the above-mentioned correlation technique of the embodiment of the present invention, be also provided for the relevant apparatus coordinating said method below.
Refer to Fig. 6, in the embodiment of the present invention, an embodiment of data processing equipment 600 comprises: acquisition module 601.
Acquisition module 601, the first equivalent channel matrix and the first data, described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T;
Described acquisition module 601, also for decomposing described first equivalent channel to obtain the second equivalent channel matrix;
Described acquisition module 601, also for utilizing the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and according to described first data acquisition second data;
Described acquisition module 601, also for utilizing the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and according to described first data acquisition the 3rd data;
Described acquisition module 601, also for according to described second data and described 3rd data acquisition the 4th data.
In the embodiment of the present invention, acquisition module obtains the second data according to QRM demodulation, obtains the 3rd data further according to least mean-square error MMSE demodulation, and according to described second data and described 3rd data acquisition the 4th data.Solve in multilayer system, adopt most MMSE algorithm cannot reach the problem of good throughput, effectively improve demodulation quality.
On basis embodiment illustrated in fig. 6, refer to Fig. 7, described acquisition module 601 further illustrated:
Described acquisition module 601 comprises: sequencing unit 6011 and acquiring unit 6012.
Sequencing unit 6011, for sorting to the SNR of each layer in described first equivalent channel matrix;
Optionally, described sequencing unit, specifically for sorting to the SNR of described each layer according to putting in order and exchanging row order.
Acquiring unit 6012, for according to the result sorted to described each layer SNR to obtain at least two the second equivalent channel matrix.
Described acquiring unit 6012, also decompose for carrying out QR respectively to described at least two the second equivalent channel matrix to obtain unitary matrice Q and upper triangular matrix R, wherein, H equals QR, and H is the second equivalent channel matrix;
Described acquiring unit 6012, also for obtaining demodulation vector according to the described Q matrix and the vectorial y of described reception that decompose acquisition
wherein, by
Obtain
wherein, s is the transmission vector that base station sends, and n is noise,
for demodulated noise;
Described acquiring unit 6012, also for vectorial according to described demodulation
survival route number M at different levels at least two the second equivalent channel matrix described in obtaining respectively
icorresponding metric;
Described acquiring unit 6012, also for according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data.
Optionally, described acquiring unit 6012 comprises:
Choose subelement 60121, for survival route number M at different levels from described at least two the second equivalent channel matrix
iminimum degree value is chosen in corresponding metric;
Obtain subelement 60122, for choose described in basis described minimum degree value that subelement chooses obtain bit be 0 and bit be the metric of 1;
Described acquisition subelement 60122, also for by described bit be 0 and bit be 1 metric subtract each other obtain described second data.
On basis embodiment illustrated in fig. 6, refer to Fig. 7, described acquisition module 601 further illustrated:
Described acquisition module 601 comprises: acquiring unit 6011.
Described acquiring unit 6011, also for according to formula (H
hh+ σ
2i)
-1h
hh obtains MMSE demodulation factor, and wherein, I is unit battle array, and H is the second equivalent channel matrix, σ
2represent noise power;
Described acquiring unit 6011, also for according to formula (H
hh+ σ
2i)
-1h
hy obtains MMSE demodulation symbol;
Described acquiring unit 6011, also for obtaining described 3rd data according to described MMSE demodulation factor and described demodulation symbol.
Refer to Fig. 7, data processing equipment 600 of the present invention is further illustrated, comprising: acquisition module 601.
Acquisition module 601, the first equivalent channel matrix and the first data, described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T;
Described acquisition module 601, also for decomposing described first equivalent channel to obtain the second equivalent channel matrix;
Described acquisition module 601, also for utilizing the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and according to described first data acquisition second data;
Described acquisition module 601, also for utilizing the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and according to described first data acquisition the 3rd data;
Described acquisition module 601, also for according to described second data and described 3rd data acquisition the 4th data.
Optionally, acquisition module 601 comprises acquiring unit 6011:
Described acquiring unit 6011, also for by multiplied by weight corresponding with described second data for described second data, the multiplied by weight corresponding with described 3rd data by described 3rd data, by the described results added be multiplied to obtain described 4th data.
In the embodiment of the present invention, acquisition module obtains the second data according to the demodulation of QRM algorithm, the 3rd data are obtained further according to least mean-square error MMSE demodulation, the multiplied by weight that acquiring unit is corresponding with the second data according to described second data, the result of the multiplied by weight that described 3rd data are corresponding with the 3rd data is added to obtain the 4th data again.Solve in multilayer system, adopt most MMSE algorithm cannot reach the problem of good throughput, effectively improve demodulation quality.
Those skilled in the art can be well understood to, and for convenience and simplicity of description, the system of foregoing description, the specific works process of device and unit, with reference to the corresponding process in preceding method embodiment, can not repeat them here.
In several embodiments that the application provides, should be understood that, disclosed system, apparatus and method, can realize by another way.Such as, device embodiment described above is only schematic, such as, the division of described unit, be only a kind of logic function to divide, actual can have other dividing mode when realizing, such as multiple unit or assembly can in conjunction with or another system can be integrated into, or some features can be ignored, or do not perform.Another point, shown or discussed coupling each other or direct-coupling or communication connection can be by some interfaces, and the indirect coupling of device or unit or communication connection can be electrical, machinery or other form.
The described unit illustrated as separating component or can may not be and physically separates, and the parts as unit display can be or may not be physical location, namely can be positioned at a place, or also can be distributed in multiple network element.Some or all of unit wherein can be selected according to the actual needs to realize the object of the present embodiment scheme.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, also can be that the independent physics of unit exists, also can two or more unit in a unit integrated.Above-mentioned integrated unit both can adopt the form of hardware to realize, and the form of SFU software functional unit also can be adopted to realize.
If described integrated unit using the form of SFU software functional unit realize and as independently production marketing or use time, can be stored in a computer read/write memory medium.Based on such understanding, the part that technical scheme of the present invention contributes to prior art in essence in other words or all or part of of this technical scheme can embody with the form of software product, this computer software product is stored in a storage medium, comprising some instructions in order to make a computer equipment (can be personal computer, server, or the network equipment etc.) perform all or part of step of method described in each embodiment of the present invention.And aforesaid storage medium comprises: USB flash disk, portable hard drive, read-only memory (ROM, Read-OnlyMemory), random access memory (RAM, Random Access Memory), magnetic disc or CD etc. various can be program code stored medium.
The above, above embodiment only in order to technical scheme of the present invention to be described, is not intended to limit; Although with reference to previous embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein portion of techniques feature; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Accompanying drawing explanation
Fig. 1 is a structure chart of multiaerial system in the embodiment of the present invention;
Fig. 2 is an embodiment schematic diagram of data processing method in the embodiment of the present invention;
Fig. 3 is a schematic flow sheet of QRM demodulation method in the embodiment of the present invention;
Fig. 4 is a schematic flow sheet of MMSE demodulation method in the embodiment of the present invention;
Fig. 5 is another embodiment schematic diagram of data processing method in the embodiment of the present invention;
Fig. 6 is a structural representation of data processing equipment in the embodiment of the present invention;
Fig. 7 is another structural representation of data processing equipment in the embodiment of the present invention.
Embodiment
Embodiments provide a kind of data processing method and device, for solving in multilayer system, conventional Least Mean Square error MMSE algorithm cannot reach the problem of good throughput, improves demodulation quality.
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those skilled in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Claims (14)
1. a data processing method, is applied to multiaerial system, and described multiaerial system comprises data receiver framework, and described data receiver framework comprises multiple-input and multiple-output MIMO demodulation, it is characterized in that, described method comprises:
User equipment (UE) obtains the first equivalent channel matrix and the first data, and described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T;
Described first equivalent channel is decomposed to obtain the second equivalent channel matrix by described UE;
Described UE utilizes the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and according to described first data acquisition second data;
Described UE utilizes the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and according to described first data acquisition the 3rd data;
Described UE is according to described second data and described 3rd data acquisition the 4th data.
2. data processing method according to claim 1, is characterized in that, described first equivalent channel is decomposed and comprised to obtain the second equivalent channel matrix by described UE:
Described UE sorts to the SNR of each layer in described first equivalent channel matrix, and according to the result sorted to described each layer SNR to obtain at least the second two equivalent channel matrix.
3. data processing method according to claim 2, is characterized in that, described UE utilizes the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and comprises according to described first data acquisition second data:
Described UE carries out Matrix QR Decomposition to obtain unitary matrice Q and upper triangular matrix R respectively to described at least two the second equivalent channel matrix, and wherein, H equals QR, and H is the second equivalent channel matrix;
Described UE obtains demodulation vector according to the described Q matrix and the vectorial y of described reception that decompose acquisition
wherein, by
Obtain
wherein, s is the transmission vector that base station sends, and n is noise,
for demodulated noise;
Described UE is according to described demodulation vector
survival route number M at different levels at least two the second equivalent channel matrix described in obtaining respectively
icorresponding metric;
Described UE is according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data.
4. data processing method according to claim 2, is characterized in that, the SNR sequence of described UE to each layer in described first equivalent channel matrix comprises:
Described UE sorts to the SNR of described each layer according to putting in order and exchanging row order.
5. data processing method according to claim 3, is characterized in that, described UE is according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data and comprises:
The survival route number M that described UE is at different levels from described at least two the second equivalent channel matrix
iminimum degree value is chosen in corresponding metric;
Described UE according to described minimum degree value obtain bit be 0 and bit be the metric of 1;
Described UE by described bit be 0 and bit be 1 metric subtract each other obtain described second data.
6. data processing method according to claim 1, is characterized in that, described UE utilizes the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and described first data acquisition the 3rd data comprise:
Described UE is according to formula (H
hh+ σ
2i)
-1h
hh obtains MMSE demodulation factor, and wherein, I is unit battle array, and H is the second equivalent channel matrix, σ
2represent noise power;
Described UE is according to formula (H
hh+ σ
2i)
-1h
hy obtains MMSE demodulation symbol;
Described UE obtains described 3rd data according to described MMSE demodulation factor and described demodulation symbol.
7. data processing method according to claim 1, is characterized in that, described UE comprises according to described second data and described 3rd data acquisition the 4th data:
Described UE is by multiplied by weight corresponding with described second data for described second data;
Described UE is by multiplied by weight corresponding with described 3rd data for described 3rd data;
Described UE by the described results added be multiplied to obtain described 4th data.
8. a data processing equipment, is characterized in that, comprising:
Acquisition module, the first equivalent channel matrix and the first data, described first data comprise the signal to noise ratio snr of each layer in described first equivalent channel matrix and survival route number M at different levels
i, the number of transmit antennas T that base station sends, receive vectorial y, wherein, i is positive integer, and 1 is less than or equal to i, and i is less than or equal to T;
Described acquisition module, also for decomposing described first equivalent channel to obtain the second equivalent channel matrix;
Described acquisition module, also for utilizing the second equivalent channel matrix described in the demodulation of matrix decomposition maximum likelihood QRM algorithm, and according to described first data acquisition second data;
Described acquisition module, also for utilizing the second equivalent channel matrix described in the demodulation of least mean-square error MMSE algorithm, and according to described first data acquisition the 3rd data;
Described acquisition module, also for according to described second data and described 3rd data acquisition the 4th data.
9. data processing equipment according to claim 8, is characterized in that, described acquisition module comprises:
Sequencing unit, for sorting to the SNR of each layer in described first equivalent channel matrix;
Acquiring unit, for according to the result sorted to described each layer SNR to obtain at least two the second equivalent channel matrix.
10. data processing equipment according to claim 9, is characterized in that,
Described acquiring unit, also decompose for carrying out QR respectively to described at least two the second equivalent channel matrix to obtain unitary matrice Q and upper triangular matrix R, wherein, H equals QR, and H is the second equivalent channel matrix;
Described acquiring unit, also for obtaining demodulation vector according to the described Q matrix and the vectorial y of described reception that decompose acquisition
wherein, by
Obtain
wherein, s is the transmission vector that base station sends, and n is noise,
for demodulated noise;
Described acquiring unit, also for survival route number M at different levels at least two the second equivalent channel matrix described in obtaining respectively according to described demodulation vector y
icorresponding metric;
Described acquiring unit, also for according to survival route number M at different levels in described at least two the second equivalent channel matrix
icorresponding metric obtains described second data.
11. data processing equipments according to claim 9, is characterized in that,
Described sequencing unit, specifically for sorting to the SNR of described each layer according to putting in order and exchanging row order.
12. data processing equipments according to claim 10, is characterized in that, described acquiring unit comprises:
Choose subelement, for survival route number M at different levels from described at least two the second equivalent channel matrix
iminimum degree value is chosen in corresponding metric;
Obtain subelement, for choose described in basis described minimum degree value that subelement chooses obtain bit be 0 and bit be the metric of 1;
Described acquisition subelement, also for by described bit be 0 and bit be 1 metric subtract each other obtain described second data.
13. data processing equipments according to claim 8, is characterized in that,
Described acquiring unit, also for according to formula (H
hh+ σ
2i)
-1h
hh obtains MMSE demodulation factor, and wherein, I is unit battle array, and H is the second equivalent channel matrix, σ
2represent noise power;
Described acquiring unit, also for according to formula (H
hh+ σ
2i)
-1h
hy obtains MMSE demodulation symbol;
Described acquiring unit, also for obtaining described 3rd data according to described MMSE demodulation factor and described demodulation symbol.
14. data processing equipments according to claim 8, is characterized in that,
Described acquiring unit, also for by multiplied by weight corresponding with described second data for described second data, the multiplied by weight corresponding with described 3rd data by described 3rd data, by the described results added be multiplied to obtain described 4th data.
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