CN107425898A - A kind of multiple cell MIMO Limited Feedback interference alignment schemes based on optimization bit distribution - Google Patents
A kind of multiple cell MIMO Limited Feedback interference alignment schemes based on optimization bit distribution Download PDFInfo
- Publication number
- CN107425898A CN107425898A CN201710305729.3A CN201710305729A CN107425898A CN 107425898 A CN107425898 A CN 107425898A CN 201710305729 A CN201710305729 A CN 201710305729A CN 107425898 A CN107425898 A CN 107425898A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msubsup
- msup
- rsqb
- lsqb
- 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.)
- Granted
Links
Classifications
-
- 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
- H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
-
- 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
- H04B7/0426—Power distribution
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03891—Spatial equalizers
- H04L25/03898—Spatial equalizers codebook-based design
- H04L25/0391—Spatial equalizers codebook-based design construction details of matrices
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Power Engineering (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
A kind of multiple cell MIMO Limited Feedback interference alignment schemes based on optimization bit distribution are claimed in the present invention, are related to wireless communication system.First, to overcome low SNR time-frequency spectrums loss of efficiency, precoding is asked for by the signal power for maximizing user and the interference for leaking into other cells and the ratio of noise power sum, AF panel matrix is designed by maximizing the Signal to Interference plus Noise Ratio of each data flow.Secondly, because traditional bit distribution algorithm is to reveal average based on interference, the actual total number of bits used of system can be made to be less than the total bit number mesh that system provides, and and it is non-optimal, therefore there is shown herein a kind of novel bit allocation scheme to improve systematic bits utilization rate, with the influence of lower quantization error.Finally, emulation experiment shows, can effectively reduce influence of the quantization error to systematic function using scheme proposed by the invention and significantly improve the bit-rate utilisation of system, performance during Limited Feedback CSI is lifted.
Description
Technical field
The invention belongs to interference management in wireless communication field, more particularly to multi-cell wireless communication.
Background technology
At present, most of interference alignment (Interference Alignment, IA) are all based on preferable channel status
Scheme under information (Channel State Information, CSI) hypothesis.But in channel radio actual such as FDD etc.
In letter system, the CSI of transmitting terminal is as obtained by receiving terminal Limited Feedback, thus the CSI of gained is usually inevitably present
Error, and then cause interference with the hydraulic performance decline of alignment algorithm.In recent years, increasing scholar starts to Limited Feedback CSI bars
The research that IA technologies under part expand.
In terms of quantized channel matrix, document [Zhang Yuxian, Cheng R S.On the design of
interference alignment scheme for multi-user MIMO with limited feedback[C]//
2013IEEE International Conference on Communications(ICC).Budapest:IEEE Press,
2013:5646-5650.] solution of independent vector quantization matrix is given, the problem of quantization matrix, is converted into and quantifies M+
The problem of 1 independent vector so that better performance can be obtained under less antenna number.Although the program gives preferably
Solution, but because the space space that ratio precoding takes eventually that channel matrix takes is big, thus caused by
Quantization error is larger, and performance is unsatisfactory.In terms of pre-coding matrix is quantified, document [Gao Hui, Lv T, Wei Long, et
al.Limited feedback-based interference alignment for interfering multi-access
channels[J].IEEE Communications Letters,2014,18(4):540-543.] change precoding quantization
Strategy simultaneously provides a kind of united quantization scheme, and the independent code book to extend one's service simultaneously selects minimum from the compound code book of expansion
Change the quantization code word of inter-cell interference, but do not account for the transmission quality of signal.
Whether quantized channel matrix or pre-coding matrix is quantified, conventional bit allocative decision is revealed based on interference
For average come what is carried out, this can make the feedback bits sum of actual use be less than the total bit number mesh that system provides, and the user having
Speed is relatively low, and this is simultaneously non-optimal.In addition, the condition of traditional linear disturbance alignment requirements interference close alignment is harsh, it is impossible to full
The needs of sufficient practical communication system.Therefore, in the case of Limited Feedback CSI, invent suitable under MIMO-MAC systems
A kind of multiple cell MIMO Limited Feedbacks based on optimization bit distribution disturb alignment scheme.
The content of the invention
Present invention seek to address that above problem of the prior art.A kind of quantization error that effectively reduces is proposed to systematic function
Influence and significantly improve the bit-rate utilisation of system, enable that performance during Limited Feedback CSI lifts based on optimization bit
The multiple cell MIMO Limited Feedback interference alignment schemes of distribution.Technical scheme is as follows：
A kind of multiple cell MIMO Limited Feedback interference alignment schemes based on optimization bit distribution, it comprises the following steps：
101st, in multiple cell MIMO-MAC systems, by maximizing the signal power of this community user itself with being leaked to
The ratio of the interference plus noise power sum of other cells asks for pre-coding matrix, and the letter by maximizing each data flow is dry makes an uproar
Than designing AF panel matrix；
102nd, in the case where the total number of feedback bits of system is fixed, optimal number of feedback bits is distributed for each user；
103rd, after the bit number that step 102 user is distributed, using minimum chordal distance criterion to being obtained in step 101
Pre-coding matrix quantified, obtain quantify precoding；
104th, according to precoding is quantified in step 103, the AF panel matrix in step 101 is recalculated, asked for steady
Strong interference arranges matrix.
Further, the step 101 is small with being leaked to other by the signal power for maximizing this community user itself
The ratio of the interference plus noise power sum in area asks for pre-coding matrix, specifically includes following steps：Precoding V[k,i]For：
Characteristic vector corresponding to the preceding d eigenvalue of maximum of matrix A is asked in expression,Represent base station i kth
The signal of individual user [k, i] travels to the signal power during j of base station,Represent the channel square between user [k, i] and base station j
Battle array, U[n,j]The AF panel matrix of user [n, j] is represented,Represent noise variance, INtRepresent Nt×NtThe unit matrix of dimension, U[k,i]The AF panel matrix of user [k, i] is represented,Represent the channel matrix between user [k, i] and base station i.
Further, the step 101 designs AF panel matrix by maximizing the Signal to Interference plus Noise Ratio of each data flow,
Including step：AF panel matrix is：
Represent the AF panel matrix of user [k, i] than the m-th data stream, T[k,i]Expression receiving terminal receives all dry
The covariance matrix with noise is disturbed,Represent the channel matrix between user [k, i] and base station i.
Further, the step 102 is that the optimal number of feedback bits of each user distribution specifically includes：
Feedback CSI bit number is distributed for each user, if the number of bits of feedback of user [k, i] is B[k,i], when system is total
Number of bits of feedbackWhen fixed, the optimization problem is：
Code book is quantified using random vector and searches for optimal codes step by step, system is calculated in the region of the bits such as each layer distribution
The significant bit sum for uniting actual：
If Beffective＜ BT, continue to search for toward outer layer；If Beffective=BT, it is assumed that the layer is br, then this layer of institute
The bit number of acquirement is optimum bit number now；If Beffective＞ BT, it is assumed that the layer is br, then the last layer of this layer
br-1Acquired bit number is optimum bit number now, it is assumed that by contrasting Beffective and BTThe search layer of determination
For bf, the bit number B of computing redundancy againT-Beffective, then the redundant bit number of each user be
So now should beOptimal quantization code word is asked on layer.
Further, the step 103 is carried out using minimum chordal distance criterion to the pre-coding matrix obtained in step 101
Quantify, obtain quantifying precoding, specifically include：
Wherein,Each ciAll it is a secondary unitary matrix.
Advantages of the present invention and have the beneficial effect that：
The interference that the present invention tries to achieve near-optimization using alternative manner arranges matrix, overcomes linear IA schemes during multi-user
The problem of being difficult to try to achieve closed solutions.
Do not require that interference is perfectly aligned and (slightly deviation be present) when the 1st, designing precoding so that have in Limited Feedback
Bigger interference space, improve the SINR of reception signal.
2nd, bit distribution is carried out based on the actually active bit number of system, overcomes conventional bit allocative decision (based on interference
Leakage average) can not maximally utilize system offer feedback bits the problem of.
Brief description of the drawings
Fig. 1 is that the present invention provides the cell of preferred embodiment two per cell K user's Limited Feedback MIMO-MAC cellular system moulds
Type；
Fig. 2 is that system configuration is [2,1, (3 × 2)]2When channel capacity；
Fig. 3 is that system configuration is [2,2, (6 × 4)]2When channel capacity；
Fig. 4 is that system configuration is [2,1, (3 × 2)]2, BTThe channel capacity of algorithm when=24；
Fig. 5 is that system configuration is [2,2, (6 × 4)]2, BTThe channel capacity of algorithm when=32；
Fig. 6 is that system configuration is [2,1, (3 × 2)]2, BTThe spectrum efficiency of algorithm when=32；
Fig. 7 is that system configuration is [2,2, (6 × 4)]2, BTThe spectrum efficiency of algorithm when=32；
Fig. 8 is system configuration [2,1, (3 × 2)]2, the averaged lower bound of system user speed during Limited Feedback Bit=6；
Fig. 9 is system configuration [2,2, (6 × 4)]2, the averaged lower bound of system user speed during Limited Feedback Bit=8；
Figure 10 is bit distribution diagram；
Figure 11 is that the multiple cell MIMO Limited Feedbacks based on optimization bit distribution of the preferred embodiment of the present invention disturb alignment
Method flow diagram.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, detailed
Carefully describe.Described embodiment is only the part of the embodiment of the present invention.
The present invention solve above-mentioned technical problem technical scheme be：
The present invention proposes a kind of multiple cell MIMO Limited Feedback interference alignment schemes based on optimization bit distribution, and it is more
In cell mimo-MAC systems, optimal pre-coding matrix and AF panel matrix is asked for by iteration to realize sane interference pair
Together, and combine the bit distribution design of optimization and improve the bit-rate utilisation of system.
The technical solution of the present invention comprises the following steps：
Step 1：The system of the program is the situation of the up-link (MIMO-MAC) of multiple cell MIMO cellular networks, such as
Fig. 1 show the interference channel model of each K user of cell of 2 cells.The antenna number of each user and each base station point
Wei not NtAnd Nr；The free degree that each user can obtain is dl(l=1,2 ..., K), and make d1=d2=... dl=d, that is, it is
Each user can obtain the identical free degree in system, and thus total free degree of system can reach maximum Kmin (Nr, Nt)/2.
Step 2: assume that the channel that each transmission in synchronization same frequency is received between is flat fading
, and channel coefficients independent same distribution.On a specific running time-frequency resource, the signal that base station i is received is represented by：
Wherein, [k, i] represents k-th of user of the i-th cell, d0Reference distance is represented, γ represents path loss index,WithRepresent that user [l, i] and [m, j] arrives base station i propagation distance, dimension N respectivelyr×Nt'sWithTable respectively
Show that user [l, i] and user [m, j] arrive base station i channel matrix, it is 0 that its element, which obeys average, and the Cyclic Symmetry that variance is 1 is answered
Gaussian Profile.Dimension is Nt×diV[l,i]It is N with dimensiont×djV[m,j]It is that user [l, i] and [m, j] correspond to base respectively
Stand i and j pre-coding matrix, and meet Dimension is d[l,i]× 1 s[l,i]
It is d with dimension[m,j]× 1 s[m,j]It is user [l, i] and [m, j] upstream data vector signal, and meets power constraintP[l,i]And P[m,j]The transmitting work(of user [l, i] and [m, j] is represented respectively
Rate.Dimension is Nr× 1 ni, it is 0 that its element, which obeys average, variance δ2Additive white Gaussian noise, i.e.,
Step 3: in the case where limit bit feeds back CSI, by the signal power and the leakage that maximize this cell itself
Ratio to the interference plus noise power of other cells designs precoding, is asked for by maximizing the SINR of each data flow
AF panel matrix.
Step 4: using the powerful signal handling capacity in base station, the bit number for feeding back CSI is distributed for each user.If with
The number of bits of feedback at family [k, i] is B[k,i], when the total number of bits of feedback of systemWhen fixed, the optimization
Problem is：
This programme quantifies code book using random vector and searches for optimal codes step by step, in the region of the bits such as each layer distribution
The actual significant bit sum of computing system：
If Beffective＜ BT, continue to search for toward outer layer；If Beffective=BT, it is assumed that the layer is br, then this layer of institute
The bit number of acquirement is optimum bit number now；If Beffective＞ BT, it is assumed that the layer is br, then the last layer of this layer
br-1Acquired bit number is optimum bit number now.It is assumed that by contrasting Beffective and BTThe search layer of determination
For bf, for more accurately distributing bit, the bit number B of computing redundancy again hereinT-Beffective, then each user
Redundant bit number isSo now should beOptimal quantization code is asked on layer
Word.
Step 5: quantization code word is asked for using minimum chordal distance criterion.
Wherein,Each ciAll it is a secondary unitary matrix.
1. asking for optimal interference arranges matrix：
User [k, i] send signal be in the decoded signal of base station end：
The Signal to Interference plus Noise Ratio of the than the m-th data stream of user [k, i]It can be expressed as follows：
Wherein, T[k,i]To disturb the covariance matrix of (all interference signals that receiving terminal receives) plus noise：
It can be obtained by matrix theory, maximize the Signal to Interference plus Noise Ratio of the than the m-th data stream of user [k, i]Unit to
AmountFor：
For the AF panel matrix of determination, we are by maximizing the signal power of this community user itself with leaking into
The ratio of the interference plus noise of other cells designs precoding, and the optimization problem can be expressed as following form：
By matrix theory it is recognised that the mark of matrix has following property：
tr(Aw×rBr×w)=tr (Br×wAw×r) (10)
Tr (C+D)=tr (C)+tr (D) (11)
Therefore, formula (9) can be further expressed as
In above-mentioned expression formula, due to matrixWithIt is Hermite matrixes, therefore maximization formula (12) is known that by matrix theory
Precoding V[k,i]For：
Wherein,Characteristic vector corresponding to the preceding d eigenvalue of maximum of matrix A is asked in expression.
2. bit distributes
Interference leakage is due to caused by the quantization error of precoding, therefore, utilizes minimum chordal distance criterion, optimization problem
It can be described as follows：
In the Limited Feedback scheme of bit number is allocated in advance, because code book is random (code word and ideal in code book
The chordal distance size of precoding is random, unordered), it is assumed that distribute b to user1Bit, but quantify the code word of precoding
Index only needs to use b2Bit (wherein b2≤b1And in most cases b2＜ b1), therefore can have b1-b2Redundancy bits.Enter
One step, carry out distributing bit there is also the situation of redundancy bits according to the system velocity loss under statistical significance, so that feedback ratio
The effective rate of utilization of special number reduces.Therefore, patent of the present invention provides a kind of novel bit allocation scheme, specific implementation is such as
Under：
(1) code book is preset
Pre- feedback bit number, optimal codes index, effective Feedback bit number and chordal distance during Limited Feedback are present
Such as the relation of following table：
Each magnitude relation of table Limited Feedback
(2) optimal codes are searched for
Referring to bit distribution diagram
A. setThen bit is being waited to distribute b0Region in, ask for actual significant bit sum：
B. if Beffective＜ BT, b is set1=b0+ 1, then waiting bit to distribute b1In region, ask for actual effective
Total number of bits：
C. if Beffective＜ BT, continue to set b2=b1+ 1, then waiting bit to distribute b2In region, ask for actual
Significant bit sum：
D. if Beffective＜ BT, continue executing with the process similar with step (2) and step (3)；
If Beffective=BT, it is assumed that the layer is br, then the bit number acquired by this layer is optimum bit number now
Mesh；
If Beffective＞ BT, it is assumed that the layer is br, then the last layer b of this layerr-1Acquired bit number is now
Optimum bit number.
E. assume that the bit-level that step (4) is tried to achieve is bf, for more accurately distributing bit, calculate again herein superfluous
Remaining bit number BT-Beffective, then the redundant bit number of each user beSo now should beOptimal quantization code word is asked on layer.
3. rate loss is analyzed
In preferable CSI, the speed of user [k, i] can be expressed as：
In formula,
AndFor matrix U[k,i]Q row,For matrix V[k,i]Q row,WithSignal power when respectively user [k, i] and [m, j] signal travel to base station i.
In Limited Feedback, the speed of user [k, i] can be expressed as：
In formula,
AndFor matrix U[k,i]Q row,For matrix V[k,i]Q row,WithSignal power when traveling to base station i for the signal of user [k, i] and user [m, j].
The difference of speed during speed and Limited Feedback CSI when user rate loss is defined as preferable CSI, i.e.,：
It is because log that first inequality, which is set up,2() be incremented by andSecond inequality into
Vertical is because AF panel matrixWith It is uniformly distributed in space, and pre-coding matrixWith It is uniformly distributed in space, so havingWithIt is equal, and
4. the impact analysis of quantization error
In preferable CSI, current many IA algorithms by design precoding and AF panel matrix can well by
Interference is alignd and eliminated so that IA technologies have great advantage on user's free degree and system spectral efficiency is improved.But
During Limited Feedback CSI, due to the influence of quantization error so that precoding deviate from the direction of preferable precoding, make user by
Interference can not be aligned, the leakage interfered, and disturb the linear increasing function that leakage is user emission power can make
It is limited into degree of freedom in system, so power system capacity has the limit in Limited Feedback CSI.
In the MIMO-MAC systems of 2 cells K user of each cell, the premise bar of the interference alignment algorithm of linear ZF
Part is interference close alignment, but in Limited Feedback CSI, due to that perfectly aligned can not disturb, causes algorithm to quantization error
Sensitivity is very high, and algorithm performance drastically declines.In addition, the Limited Feedback IA schemes based on quantized channel matrix, due to channel square
The dimension of battle array is more much larger than precoding, it will largely increases quantization error.And patent of the present invention then using
MAX-SINR criterions, just do not require that close alignment disturbs in preferable CSI, the space for disturbing storage is relatively large, and is having
During limit feedback CSI, interference not close alignment also largely allow for, it is allowed to certain deviation be present, therefore reduce
Influence of the quantization error to systematic function.Further, effective utilization of feedback bits is improved by improving bit distribution algorithm
Rate so that performance is further lifted in Limited Feedback.
5. significant bit Utilization Ratio Analysis
From the derivation in above formula (22), the average of user rate loss meets：
Wherein, NG=2d (Nt- d), c is Grassmann manifold spheroid coefficient, and second inequality is by Jensen inequality
Obtain.
Below, we analyze the bit-rate utilisation of this chapter algorithms.For simplicity, it is assumed that the rate loss of user is
One constant, this is requiredWithLinearly.Therefore have
Wherein λ (λ ＞ 0) is a scale factor.Formula (24) both sides are taken the logarithm：
In identical system total bit number now, it is assumed that in common IA algorithmsScale factor be
λ0(λ0＞ 0)；In this paper algorithmsScale factor be λnew(λnew＞ 0).By analysis above
It is recognised that the interference leakage of this paper algorithms is smaller, so there is λnew≤λ0, convolution (25), significant bit number meets as follows
Relation：
From formula (26) as can be seen that under identical systematic bits number, this paper algorithms reduce interference leakage, and improve
The bit-rate utilisation of system.
The interference alignment scheme proposed to patent of the present invention is carried out to the emulation of spectrum efficiency and significant bit distribution below,
Two documents in comparative analysis technical background carry algorithm (quantized channel and quantify pre-coding scheme 3), document [Lee N,
Shin W,Heath R W,et al.Interference alignment with limited feedback for two-
cell interfering MIMO-MAC[C]//2012International Symposium on Wireless
Communication Systems(ISWCS).Paris:IEEE Press,2012:566-570.] quantization pre-coding scheme 1
With document [Kim M J, Lee H H, Ko Y C.Limited feedback design for interference
alignment on two-cell interfering MIMO-MAC[J].IEEE Transactions on Vehicular
Technology,2015,64(9):4019-4030.] quantization pre-coding scheme 2.Simulation parameter is arranged to [K, d, (Nr×
Nt)]2, i.e. the free degree of each K user of cell of 2 cells and each user are d.If the channel between all dual-mode antennas is equal
It is flat fading, and it is 0 that channel element, which obeys average, the AWGN that variance is 1 is distributed.In addition, interchannel noise is zero-mean list
The additive white Gaussian noise of position variance, emulation all this chapter all take 5000 secondary channels to realize.
Fig. 2 and Fig. 3 shows that in systematic parameter be [2,1, (3 × 2)]2[2,2, (6 × 4)]2When corresponding system spectrum
Efficiency.It can be seen that in [2,1, (3 × 2)]2Configuration under, other algorithms are perfectly aligned and eliminate the algorithm of interference
It is not optimal, and patent of the present invention is interfered with by the gradual rotary compression of iteration and is advantageous to make performance on the direction that signal receives
Great lifting is obtained.In [2,2, (6 × 4)]2Configuration under because the algorithm of scheme 2 is fully examined when designing precoding
The correlation between data flow is considered, so performance will be good than scheme 1 and 3, and patent of the present invention is disturbed by Iterative Design
The gradual rotary compression of matrix is arranged to disturb, its performance scheme 2 is good.Further, since the ratio precoding of the dimension of quantized channel is big,
Quantization error can be bigger so as to caused by, so the scheme of the ratio precoding of its performance of the scheme of quantized channel will be poor.Enter
One step is observed it can be found that the data flow of user's transmission is more, and the lifting effect of patent of the present invention is more obvious, and the low letter in
Make an uproar than even in middle high s/n ratio, there is larger performance advantage.
Fig. 4 and Fig. 5 shows that system parameter setting is [2,1, (3 × 2)]2[2,2, (6 × 4)]2When corresponding average frequency
Spectrum efficiency, power loss when signal reaches base station is not still considered herein.It can be seen that under two kinds of system configurations
Patent of the present invention is optimal.Because the optimal pre-coding matrix of this paper algorithms design does not require strict interference pair
Together so that interference can be remaining a part of in signal space, and then obtains larger Signal to Interference plus Noise Ratio.And due to quantized channel square
There is the scheme of battle array larger quantization error to cause its performance will be poor compared with the scheme of each quantization precoding.In addition, scheme 3
The strategy quantified as a result of joint, thus performance it is all better than scheme 1 and 2 but not as good as patent of the present invention.In addition, from figure
It is also seen that：1. this patent, in multiple degrees of freedom, performance is lifted all the more obvious relative to other schemes；2. using the present invention specially
The availability of frequency spectrum of algorithm when the bit allocation scheme of profit improves Limited Feedback really；3. due to the influence of quantization error, make
Into interference leakage it is increasing so that the limit be present in system spectral efficiency.
Average spectral efficiency (ase) when Fig. 6 and Fig. 7 shows fading channel under bit distribution algorithm.Fed back for limit bit
CSI and signal are transferred to the situation up to power attenuation during base station, and each simulation parameter is arranged to：Base station radius is R=500m, reference
Distance is d0=200m, path loss index is γ=3 and all users all fall within distance objective base station DsIn=700m region, it is
Total number of bits of feedback of uniting is BT=32.As seen from the figure, this patent is distributed by bit, is [2,1, (3 × 2)] in system configuration2
[2,2, (6 × 4)]2When greatly improve the performance of algorithm really, and it can further be seen that the free degree is more big calculates herein
The advantage of method is further obvious.
Fig. 8 and Fig. 9 shows the significant bit distribution situation of Limited Feedback CSI under same equal loss, does not also consider to believe herein
Number it is transferred to power attenuation during base station.It can be seen that under two kinds of system configurations, when user allocate in advance it is equal
During bit, the bit utilization power of other schemes is essentially identical, and uses the bit allocation scheme of patent of the present invention effectively to carry
The high bit availability of system.Such as in fig. 8, when the total number of bits of feedback of system is 24bit, scheme 1,2 and 3 is
The total number of feedback bits actually used of uniting largely is distributed between 17-24bit, and the bit distribution algorithm of patent of the present invention
21-24Bit is then had focused largely on, is greatly improved the bit availability of system.Further looking to find, when multiple data
When flowing simultaneous transmission, the lifting effect of systematic bits utilization rate is more obvious.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limited the scope of the invention.
After the content for having read the record of the present invention, technical staff can make various changes or modifications to the present invention, these equivalent changes
Change and modification equally falls into the scope of the claims in the present invention.
Claims (5)
1. it is a kind of based on optimization bit distribution multiple cell MIMO Limited Feedback interference alignment schemes, it is characterised in that including with
Lower step：
101st, in multiple cell MIMO-MAC systems, by maximizing the signal power of this community user itself and being leaked to other
The ratio of the interference plus noise power sum of cell asks for pre-coding matrix, by maximize the Signal to Interference plus Noise Ratio of each data flow come
Design AF panel matrix；
102nd, in the case where the total number of feedback bits of system is fixed, optimal number of feedback bits is distributed for each user；
103rd, it is pre- to what is obtained in step 101 using minimum chordal distance criterion after the bit number that step 102 user is distributed
Encoder matrix is quantified, and obtains quantifying precoding；
104th, according to precoding is quantified in step 103, the AF panel matrix in step 101 is recalculated, it is sane to ask for
Interference arranges matrix.
2. the multiple cell MIMO Limited Feedback interference alignment schemes according to claim 1 based on optimization bit distribution, its
It is characterised by, the step 101 is by maximizing the signal power of this community user itself and being leaked to the interference of other cells
The ratio of plus noise power sum asks for pre-coding matrix, specifically includes following steps：Precoding V[k,i]For：
<mrow>
<msup>
<mi>V</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msup>
<mo>=</mo>
<msubsup>
<mi>v</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
<mi>d</mi>
</msubsup>
<mrow>
<mo>(</mo>
<msup>
<mrow>
<mo>&lsqb;</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mi>j</mi>
<mo>&NotEqual;</mo>
<mi>i</mi>
</mrow>
<mi>K</mi>
</munderover>
<msubsup>
<mi>P</mi>
<mi>j</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>H</mi>
<mi>j</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>U</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>n</mi>
<mo>,</mo>
<mi>j</mi>
<mo>&rsqb;</mo>
</mrow>
</msup>
<msup>
<mrow>
<mo>(</mo>
<msup>
<mi>U</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>n</mi>
<mo>,</mo>
<mi>j</mi>
<mo>&rsqb;</mo>
</mrow>
</msup>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msubsup>
<mi>H</mi>
<mi>j</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>K&delta;</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
<msub>
<mi>I</mi>
<msub>
<mi>N</mi>
<mi>t</mi>
</msub>
</msub>
<mo>&rsqb;</mo>
</mrow>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>&lsqb;</mo>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>H</mi>
<mi>i</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msup>
<mi>U</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msup>
<msup>
<mrow>
<mo>(</mo>
<msup>
<mi>U</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msup>
<mo>)</mo>
</mrow>
<mi>H</mi>
</msup>
<msubsup>
<mi>H</mi>
<mi>i</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<mo>&rsqb;</mo>
<mo>)</mo>
</mrow>
</mrow>
Characteristic vector corresponding to the preceding d eigenvalue of maximum of matrix A is asked in expression,Represent base station i k-th of use
The signal at family [k, i] travels to the signal power during j of base station,Represent the channel matrix between user [k, i] and base station j, U[n,j]The AF panel matrix of user [n, j] is represented,Represent noise variance,Represent Nt×NtThe unit matrix of dimension, U[k,i]
The AF panel matrix of user [k, i] is represented,Represent the channel matrix between user [k, i] and base station i.
3. the multiple cell MIMO Limited Feedback interference alignment schemes according to claim 2 based on optimization bit distribution, its
It is characterised by, the step 101 designs AF panel matrix, including step by maximizing the Signal to Interference plus Noise Ratio of each data flow
Suddenly：AF panel matrix is：
<mrow>
<msubsup>
<mi>U</mi>
<mi>m</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<mo>=</mo>
<mfrac>
<mrow>
<mi>i</mi>
<mi>n</mi>
<mi>v</mi>
<mrow>
<mo>(</mo>
<msup>
<mi>T</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msup>
<mo>)</mo>
</mrow>
<msubsup>
<mi>H</mi>
<mi>i</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<msubsup>
<mi>V</mi>
<mi>m</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
</mrow>
<mrow>
<mo>|</mo>
<mo>|</mo>
<mi>i</mi>
<mi>n</mi>
<mi>v</mi>
<mrow>
<mo>(</mo>
<msup>
<mi>T</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msup>
<mo>)</mo>
</mrow>
<msubsup>
<mi>H</mi>
<mi>i</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<msubsup>
<mi>V</mi>
<mi>m</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<mo>|</mo>
<mo>|</mo>
</mrow>
</mfrac>
</mrow>
Represent the AF panel matrix of user [k, i] than the m-th data stream, T[k,i]Represent all interference for receiving of receiving terminal with
The covariance matrix of noise,Represent the channel matrix between user [k, i] and base station i.
4. the multiple cell MIMO Limited Feedback interference alignment schemes according to claim 2 based on optimization bit distribution, its
It is characterised by, the step 102 is that the optimal number of feedback bits of each user distribution specifically includes：
Feedback CSI bit number is distributed for each user, if the number of bits of feedback of user [k, i] is B[k,i], when total anti-of system
Present bit numberWhen fixed, the optimization problem is：
<mrow>
<mtable>
<mtr>
<mtd>
<mi>min</mi>
</mtd>
<mtd>
<mrow>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mn>2</mn>
</msubsup>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>K</mi>
</msubsup>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>q</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>d</mi>
</munderover>
<msubsup>
<mi>I</mi>
<mrow>
<mi>q</mi>
<mo>,</mo>
<mi>L</mi>
<mi>F</mi>
<mi>B</mi>
</mrow>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>s</mi>
<mo>.</mo>
<mi>t</mi>
<mo>.</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mn>2</mn>
</msubsup>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>K</mi>
</msubsup>
<msup>
<mi>B</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msup>
<mo>&le;</mo>
<msub>
<mi>B</mi>
<mi>T</mi>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
Code book is quantified using random vector and searches for optimal codes step by step, it is real in the region computing system of the bits such as each layer distribution
The significant bit sum on border：
<mrow>
<msub>
<mi>B</mi>
<mrow>
<mi>e</mi>
<mi>f</mi>
<mi>f</mi>
<mi>e</mi>
<mi>c</mi>
<mi>t</mi>
<mi>i</mi>
<mi>v</mi>
<mi>e</mi>
</mrow>
</msub>
<mo>=</mo>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mn>2</mn>
</msubsup>
<msubsup>
<mi>&Sigma;</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>K</mi>
</msubsup>
<msubsup>
<mi>B</mi>
<mrow>
<mi>e</mi>
<mi>f</mi>
<mi>f</mi>
<mi>e</mi>
<mi>c</mi>
<mi>t</mi>
<mi>i</mi>
<mi>v</mi>
<mi>e</mi>
</mrow>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msubsup>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
If Beffective＜ BT, continue to search for toward outer layer；If Beffective=BT, it is assumed that the layer is br, then acquired by the layer
Bit number be optimum bit number now；If Beffective＞ BT, it is assumed that the layer is br, then the last layer b of this layerr-1
Acquired bit number is optimum bit number now, it is assumed that by contrasting Beffective and BTThe search layer of determination is bf,
The bit number B of computing redundancy againT-Beffective, then the redundant bit number of each user beSo this
When should beOptimal quantization code word is asked on layer.
5. the multiple cell MIMO Limited Feedback interference alignment schemes according to claim 4 based on optimization bit distribution, its
It is characterised by, the step 103 is quantified using minimum chordal distance criterion to the pre-coding matrix obtained in step 101, is obtained
To precoding is quantified, specifically include：
<mrow>
<msup>
<mi>V</mi>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
<mo>&rsqb;</mo>
</mrow>
</msup>
<mo>=</mo>
<munder>
<mi>arg</mi>
<mrow>
<msub>
<mi>c</mi>
<mi>x</mi>
</msub>
<mo>&Element;</mo>
<mi>C</mi>
</mrow>
</munder>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<msqrt>
<mn>2</mn>
</msqrt>
</mfrac>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>c</mi>
<mi>x</mi>
</msub>
<msubsup>
<mi>c</mi>
<mi>x</mi>
<mi>H</mi>
</msubsup>
<mo>-</mo>
<msup>
<mi>V</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
</mrow>
</msup>
<msup>
<mi>V</mi>
<mrow>
<mo>&lsqb;</mo>
<mi>k</mi>
<mo>,</mo>
<mi>i</mi>
<mo>&rsqb;</mo>
<mi>H</mi>
</mrow>
</msup>
<mo>|</mo>
<msub>
<mo>|</mo>
<mi>F</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein,Each ciAll it is a secondary unitary matrix.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710305729.3A CN107425898B (en) | 2017-05-03 | 2017-05-03 | Multi-cell MIMO (multiple input multiple output) limited feedback interference alignment method based on optimized bit allocation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710305729.3A CN107425898B (en) | 2017-05-03 | 2017-05-03 | Multi-cell MIMO (multiple input multiple output) limited feedback interference alignment method based on optimized bit allocation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107425898A true CN107425898A (en) | 2017-12-01 |
| CN107425898B CN107425898B (en) | 2020-08-04 |
Family
ID=60424875
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710305729.3A Active CN107425898B (en) | 2017-05-03 | 2017-05-03 | Multi-cell MIMO (multiple input multiple output) limited feedback interference alignment method based on optimized bit allocation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107425898B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109560885A (en) * | 2018-12-24 | 2019-04-02 | 广东理致技术有限公司 | A kind of wireless sensor network quality data communication means and device |
| CN110177065A (en) * | 2019-06-06 | 2019-08-27 | 中国石油大学(华东) | A kind of interference alignment scheme for distributing channel feedback bit according to user demand |
| CN111314933A (en) * | 2020-02-08 | 2020-06-19 | 南京邮电大学 | Energy efficiency improving method of MU-MIMO wireless data and power transmission system based on limited feedback |
| CN112534787A (en) * | 2018-08-08 | 2021-03-19 | 中兴通讯股份有限公司 | Multiple access scheme with interference suppression |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103747515A (en) * | 2014-01-10 | 2014-04-23 | 东南大学 | Interference aligning method suitable for combined power distribution of wireless local area network |
| CN104506226A (en) * | 2014-12-16 | 2015-04-08 | 西安交通大学 | Cooperative femtocell-based interference suppressing precoding method in double-layer heterogeneous network |
| CN104539392A (en) * | 2014-12-31 | 2015-04-22 | 中国电子科技集团公司第五十四研究所 | Multi-cell space interference aligning implementing method based on limited rate pre-coding feedback |
| US20160308590A1 (en) * | 2013-12-13 | 2016-10-20 | Zte Corporation | Pre-coding System and Method based on Interference Alignment |
| CN106130697A (en) * | 2016-07-05 | 2016-11-16 | 重庆邮电大学 | Estimate based on Bayes and between data stream, combining of power distribution disturbs phase alignment method |
-
2017
- 2017-05-03 CN CN201710305729.3A patent/CN107425898B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160308590A1 (en) * | 2013-12-13 | 2016-10-20 | Zte Corporation | Pre-coding System and Method based on Interference Alignment |
| CN103747515A (en) * | 2014-01-10 | 2014-04-23 | 东南大学 | Interference aligning method suitable for combined power distribution of wireless local area network |
| CN104506226A (en) * | 2014-12-16 | 2015-04-08 | 西安交通大学 | Cooperative femtocell-based interference suppressing precoding method in double-layer heterogeneous network |
| CN104539392A (en) * | 2014-12-31 | 2015-04-22 | 中国电子科技集团公司第五十四研究所 | Multi-cell space interference aligning implementing method based on limited rate pre-coding feedback |
| CN106130697A (en) * | 2016-07-05 | 2016-11-16 | 重庆邮电大学 | Estimate based on Bayes and between data stream, combining of power distribution disturbs phase alignment method |
Non-Patent Citations (2)
| Title |
|---|
| RAJESH T. KRISHNAMACHARI ET AL: "Interference Alignment Under Limited Feedback for MIMO Interference Channels", 《ISIT 2010》 * |
| 谢显中等: "一种最大化系统用户速率下限的MIMO．MAC有限反馈干扰对齐算法", 《电子学报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112534787A (en) * | 2018-08-08 | 2021-03-19 | 中兴通讯股份有限公司 | Multiple access scheme with interference suppression |
| CN112534787B (en) * | 2018-08-08 | 2022-05-27 | 中兴通讯股份有限公司 | Wireless communication method, wireless communication device and computer readable medium |
| CN109560885A (en) * | 2018-12-24 | 2019-04-02 | 广东理致技术有限公司 | A kind of wireless sensor network quality data communication means and device |
| CN110177065A (en) * | 2019-06-06 | 2019-08-27 | 中国石油大学(华东) | A kind of interference alignment scheme for distributing channel feedback bit according to user demand |
| CN111314933A (en) * | 2020-02-08 | 2020-06-19 | 南京邮电大学 | Energy efficiency improving method of MU-MIMO wireless data and power transmission system based on limited feedback |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107425898B (en) | 2020-08-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP2809025B1 (en) | Coordinated multipoint transmission and reception (CoMP) | |
| CN107425898A (en) | A kind of multiple cell MIMO Limited Feedback interference alignment schemes based on optimization bit distribution | |
| CN102055563B (en) | Adaptive joint linear precoding method applicable to multi-base station coordination | |
| CN106549697B (en) | Transmission method for combining beam forming and antenna selection in cooperative communication system | |
| CN104601209B (en) | A kind of cooperative multi-point transmission method suitable for 3D mimo systems | |
| US8811316B2 (en) | Methods and apparatuses for multi-cell collaborative communication in a multiple input multiple output system | |
| CN103117787B (en) | Self-adaptive bit allocation method and device in a kind of collaboration multiaerial system | |
| CN101867462A (en) | Multi-base station cooperation linear precoding method based on minimum total bit error rate | |
| CN106060950A (en) | Opportunity interference alignment-based method for data transmission in cellular downlink channel | |
| CN106452525A (en) | Energy efficiency, spectral efficiency and QoS integrated optimization method in large-scale MIMO | |
| CN101483874A (en) | Uplink resource allocation method for distributed antenna MIMO-OFDM/SDMA system | |
| CN105703812A (en) | A downlink precoding and base station power control method in a pilot frequency time shifting large-scale MIMO system | |
| CN109714085B (en) | Downlink NOMA transmission method based on dual-polarization MIMO | |
| CN106793108A (en) | Federated user selection and power distribution optimization method in mimo system downlink | |
| CN101783776B (en) | Precoding feedback method, system, user equipment and base station | |
| Chen et al. | Coexistence of URLLC and eMBB Services in MIMO-NOMA Systems | |
| CN102647728A (en) | Method for beam forming of down link, transmitting terminal and multi-cell cooperative system | |
| CN102055547A (en) | Method and equipment for acquiring channel state information | |
| CN108900449B (en) | Interference alignment method of multi-cell MIMO-IMAC | |
| Qian et al. | Enabling Fully-Decoupled Radio Access with Elastic Resource Allocation | |
| CN103178939B (en) | The method that feedback quantity improves system throughput is reduced based on Limited Feedback technology | |
| CN102752071B (en) | For downlink precoding method and the central processing node of multipoint cooperative system | |
| CN102088779A (en) | Efficient feedback method aiming at beamforming of closed loop coordinated multipoint transmission | |
| Skjevling et al. | Low-complexity distributed multibase transmission and scheduling | |
| Joshi et al. | Distributed SINR balancing for MISO downlink systems via the alternating direction method of multipliers |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |