CN105978615B - The extensive MIMO interference elimination method of multiple cell based on day line options and interference alignment - Google Patents

The extensive MIMO interference elimination method of multiple cell based on day line options and interference alignment Download PDF

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CN105978615B
CN105978615B CN201610325499.2A CN201610325499A CN105978615B CN 105978615 B CN105978615 B CN 105978615B CN 201610325499 A CN201610325499 A CN 201610325499A CN 105978615 B CN105978615 B CN 105978615B
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interference
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channel matrix
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CN105978615A (en
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杨全校
杨海芬
林水生
周亮
袁强
尹腾飞
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University of Electronic Science and Technology of China
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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
    • H04B7/0426—Power distribution
    • 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
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • 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
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0602—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using antenna switching
    • H04B7/0608—Antenna selection according to transmission parameters

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

Abstract

The invention discloses a kind of extensive MIMO interference elimination methods of multiple cell being aligned based on day line options and interference, belong to mobile radio telecommunications technical field.The present invention includes: that base station end obtains channel matrix and calculates separately the norm of column vector corresponding to each transmitting antenna, selects the maximum preceding Ns root antenna of norm as active antenna, and close other antennas；Based on column vector corresponding to active antenna as new channel matrix and calculate each base station interference be aligned precoding vector, compel null vector according to the reception that interference alignment precoding vector and new channel matrix calculate receiving end and distributes the transmission power of each data flow accordingly, then it is updated again based on transmission power to force zero vector is received, finally, current base station is interfered based on it, alignment precoding vector, current reception compel null vector, the transmission power of each data flow generates the corresponding transmission Data Concurrent in receiving end and send.Implementation of the invention can reduce computation complexity, improve transmission rate and reduce bit error rate.

Description

The extensive MIMO interference elimination method of multiple cell based on day line options and interference alignment
Technical field
The invention belongs to mobile radio telecommunications technical field, in particular to it is a kind of based on day line options and interference alignment it is more The extensive MIMO interference elimination method of cell
Background technique
Extensive MIMO technology, by base station end configure a large amount of antenna can significantly improve system spectrum efficiency and Efficiency efficiency, the channel matrix when antenna for base station number tends to be infinite between different user tend to be orthogonal, so as to eliminate Thus inter-user interference and inter-cell interference receive extensive research and concern.However, the number of antennas in actual conditions is not May be infinite more, the channel matrix between different user is not ideal quadrature, i.e., inter-user interference still exists, especially Cell Edge User.
Alignment techniques are interfered, are in transmitting terminal using the channel state information design pre-coding matrix having learned that, so that Interference signal is aligned in receiving end, to obtain glitch-free desired signal, while having compressed the sky of son shared by interference signal Between, the dimension of desired signal is increased, the transmission rate of system is improved.Interference alignment algorithm is generally divided into linear disturbance at present Alignment and iteration interference alignment, and the former has certain advantage in practical application since computation complexity is lower.
Antenna Selection Technology is to select a portion antenna to carry out from all service antennas according to certain criterion Signal transmitting.Antenna selection criterion can be maximum channel capacity criterion, and maximum signal noise ratio principle and minimum bit-error rate are then quasi- Etc..In systems in practice, it is contemplated that actual physics limitation, the factors such as implementation complexity and cost, the antenna of substantial amounts can It can become the bottleneck of Project Realization.By Antenna Selection Technology can be effectively reduced system signal processing complexity and at This, and large-scale antenna array bring overwhelming majority excellent performance is remained to a certain extent, it may be implemented advising greatly Effective compromise of mould mimo system performance and complexity.
Power distribution is one of content of resource allocation, and carrying out power distribution according to actual channel conditions can be improved communication The performance of system, such as water-filling algorithm can make the channel capacity of mimo system maximize.If not considering power distribution, i.e., Constant power distribution, it will so that the efficient channel gain serious unbalance for each data flow transmitted, is difficult to make the performance of system It is optimal.Document " Interference Alignment Based On Antenna Selection For Massive MIMO System”(Zhiyuan Shi,Xiaopeng Zhu,Yifeng Zhao,Lianfen Huang,Computer Science&Education(ICCSE),2015 10th International Conference on,22-24July 2015, pp.606-610) joint uses day line options in extensive mimo system and interference alignment techniques are interfered to eliminate, But not considering the problems of power distribution, and the complexity of Antenna Selection Algorithem is higher, system performance still has biggish Room for promotion.
Summary of the invention
Goal of the invention of the invention is: in view of the above problems, proposing a kind of based on day line options, interference pair The extensive MIMO interference elimination method of neat and dynamic power distribution is greatly improved user's using interference alignment techniques Transmission rate and performance of BER, while channel matrix dimension is reduced by Antenna Selection Technology, to reduce operation Complexity is conducive to Project Realization.
The extensive MIMO interference elimination method of multiple cell based on day line options and interference alignment of the invention, including it is following Step:
Step 1: base station end obtains the channel state information CSI of all users by ascending pilot frequency, i.e. acquisition channel matrix Hij∈CN×M(CN×MIndicate N × Metzler matrix), wherein HijIndicate that the channel matrix of user j to base station i, M indicate the antenna of base station end Number, N are the number of antennas of user terminal.
Step 2: in each base station, according to the channel square for the user that channel capacity maximization criterion and base station are respectively serviced Battle array carries out day line options.The criterion of the antenna selection gist are as follows:Wherein φ is indicated The selected antenna subset of base station end, hiIndicate column vector corresponding to transmitting antenna i.Calculate separately channel matrix HiiInstitute There is the norm of column vector, selects the maximum preceding Ns root antenna of norm as active antenna, Ns is required selection number of antennas, and is closed Close remaining M-NsRoot antenna.
Step 3: base station end redefines the channel matrix actually used according to the result of step 2 day line options, for every One channel matrix Hij, select Ns column column vector therein as new channel matrix H _ asij, i.e. H_asij=[hijk]k∈φ, Wherein, [hijk] indicate channel matrix HijKth column.
Step 4: base station end is according to channel matrix H _ as after day line optionsijCalculate interference alignment precoding vector.
Interference alignment schemes of the present invention are described in step 401-403:
401: to confederate matrixEigenvalues Decomposition is carried out, selected characteristic value is maximum Interference alignment precoding vector v of D (D be send number of data streams) the column feature vector as base station 11Row vector of going forward side by side is returned One change processing；That is v1(:, r)=v1(:,r)/||v1(:, r) | |, r=1 ..., D, symbol (:, r) it indicates to take r column operations
402: according to formulaThe interference of calculation base station 2 is aligned precoding vector v2Row vector of going forward side by side is returned One change processing；
403: according to formulaThe interference of calculation base station 3 is aligned precoding vector v.3It goes forward side by side row vector Normalized.
Step 5: null vector is compeled in the reception for calculating receiving end.
The urgent null matrix that the force zero processing uses is obtained according to following equation:
wj=U_Hj((j-1)*D+1:j*D,:)
Wherein, wjFor D × N user j reception compel null matrix (D be user j send number of data streams, N be user j Number of antennas), i.e. wjIt is made of wherein corresponding d every trade vector,Channel matrix, U_H are sent for equivalent jointjIt is equivalent The pseudo inverse matrix of confederate matrix, ()HThe conjugate transposition of representing matrix, similarly hereinafter.
Step 6: calculate separately the reception force zero matrix column vector field homoemorphism value of each user, and according to the size of modulus value into Mobile state power distribution:
First calculate the force zero vector field homoemorphism value vector of user jWherein symbol diag (A) Expression takes the diagonal element of matrix A.
The transmission power distribution of data flow is carried out further according to modulus value:Wherein, P indicates all The total emission power of base station, pjrIndicate power of the current base station to user j transmitting r flow data, djrIndicate r-th of user j Force zero vector field homoemorphism value, i.e. matrix djThe corresponding modulus value of jth column,
Step 7: it is updated according to current power distribution condition and compels null matrix:Wherein pj=diag (pj1,pj2,...,pjD).Step 8: generating transmission in conjunction with the calculated result of above-mentioned day line options, interference alignment and power distribution Data: xj=vi*pj*sj, wherein xjIndicate that current base station sends data vector, p to the N × 1 of user jjFor current base station about The power distribution diagonal matrix of user j, diagonal element are the power p of each data flow distributionjr, sjFor the original for being sent to user j It originates and send data.
In conclusion by adopting the above-described technical solution, the beneficial effects of the present invention are: compared with prior art, this Invention reduces channel matrix dimension by antenna selecting method, so that big rule can be realized with relatively low complexity The interference of mould mimo system is eliminated, and the transmission rate of user is improved, while the mistake ratio of system is reduced by dynamic power distribution Special rate performance improves the reliability of system transmission.
Detailed description of the invention
Fig. 1 is the embodiment of the present invention schematic diagram of a scenario.
Fig. 2 is the implementation structural block diagram of the embodiment of the present invention.
Fig. 3 for the present invention taken Antenna Selection Algorithem and the optimal algorithm that fades of performance reachable rate correlation curve.
Fig. 4 is the performance of BER correlation curve under 4 antenna case of case study on implementation of the present invention.
Fig. 5 is the performance of BER correlation curve under 8 antenna case of case study on implementation of the present invention.
Fig. 6 is the reachable rate correlation curve under 4 antenna case of case study on implementation of the present invention.
Fig. 7 is the reachable rate correlation curve under 8 antenna case of case study on implementation of the present invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below with reference to embodiment and attached drawing, to this hair It is bright to be described in further detail.
Embodiment
Referring to Fig. 1, the system scenarios of this example are the extensive MIMO multi-cell system based on C-RAN framework, and system is adopted With TDD standard.Under C-RAN framework can the easily no-delay channel information for sharing all cells, substantially increase connection Close the exploitativeness of processing.3 cells, one base station of each cell are considered in present case, each base station services a cell Edge customer, the number of antennas of base station end are 128, and the number of antennas of user terminal is N, take 4 and 8 to emulate N in this example Analysis.Channel state information in the present embodiment is zero-mean, the multiple Gauss variable that variance is 1.The transmitting total work of all base stations Rate is P.
For above-described embodiment, it is provided by the invention based on day line options and interference alignment and power distribution it is extensive The specific implementation step of MIMO interference elimination method are as follows:
Step S1: base station end obtains the channel state information CSI of all users by ascending pilot frequency, i.e. acquisition channel matrix Hij∈CN×128, i, j=1,2,3, wherein HijIndicate the channel matrix of user j to base station i.
Step S2: in each base station, according to the channel square for the user that signal-to-noise ratio maximization criterion and base station are respectively serviced Battle array Hii, i=1,2,3 progress day line options.
I.e. according to formulaM=128 calculates separately channel matrix H11,H22And H33 All column vectors modulus value, select wherein the maximum N root antenna of modulus value close residue 128-N root antenna as active antenna.
Step S3: base station end redefines the channel matrix actually used according to the result of S2 days line options of step, for Each channel matrix selects N column column vector therein as new channel matrix H _ asij。
H_asij=[hijk]k∈φWherein, [hijk] indicate channel matrix HijKth column.
Step S4: base station end is according to channel matrix H _ as after day line optionsijCalculate interference alignment precoding vector vi.It is first First to confederate matrixEigenvalues Decomposition is carried out, selected characteristic is worth maximum N/2 (this reality Apply in example, the number of data streams D of transmission is N/2) interference alignment precoding vector v of the column feature vector as base station 11, and root According to formula v1(:, r)=v1(:,r)/||v1(:, r) | |, r=1 ..., N/2 carries out vector normalized；Then according to formulaThe interference of calculation base station 2 is aligned precoding vector v2Row vector of going forward side by side normalized；Finally according to public affairs FormulaThe interference of calculation base station 3 is aligned precoding vector v3Row vector of going forward side by side normalized.
Step S5: null vector is compeled in the reception for calculating receiving end.
Basis first Calculate U_Hj, further according to wj=U_Hj((j-1) * D+1:j*D :), null matrix w is compeled in the reception that j=1,2,3 obtains user jj, i.e. wj By U_HjIn corresponding N/2 every trade vector composition.
Step S6: the reception force zero matrix column vector field homoemorphism value of each user is calculated separately, and is counted according to modulus value According to the transmission power distribution of stream, i.e.,Wherein djrFor the force zero vector field homoemorphism value vector d of user jj R column modulus value, T is the sum of all user's force zero vector field homoemorphism values.
Step S7: it is updated according to power allocation case and compels null matrix.EvenWherein
Step S8: current base station end combines the calculated result of above-mentioned day line options, interference alignment and power distribution to generate About originally transmitted data sjTransmission data xj: xj=vi*pj*sj。
Step S9: receiving end is to reception signal yjCorresponding transmission data, i.e. y can be got by carrying out force zero processingj= wj*rj, wherein rjFor the received vector of N × 1.
In order to assess performance of the invention, channel capacity and bit error rate are imitated using Monte Carlo simulation method Very.
Fig. 3 is the reachable rate correlation curve of the algorithm that fades of Antenna Selection Algorithem and best performance that the present invention uses, Middle QPSK indicates that orthogonal frequency shift keying, AS indicate day line options, and IA indicates interference alignment, and ZF indicates force zero precoding, and MF is indicated Matched filtering precoding.It can be seen that being zero-mean, the multiple Gauss variable that variance is 1 in the channel coefficients that this example is assumed Under scene, channel capacity of the simple Antenna Selection Algorithem adopted by the present invention relative to the algorithm that fades, in low signal-to-noise ratio Performance is almost consistent, and only has the performance loss of about 1-2bps/Hz under high s/n ratio in 4 antenna, only has about 2- in 8 antenna The performance loss of 3bps/Hz.And Antenna Selection Algorithem complexity adopted by the present invention then wants much lower, is conducive to engineering reality It is existing.Antenna Selection Algorithem adopted by the present invention only needs the modulus value for calculating transmission vector corresponding to every transmitting antenna and takes it The middle maximum Ns root of modulus value, and channel capacity maximizes the algorithm that fades and needs to carry out N-Ns iteration, each iteration needs to calculate Channel capacity performance loss caused by every antenna is removed, complexity is substantially higher to be calculated in day line options adopted by the present invention Method.
Fig. 4 and Fig. 5 be algorithms of different performance of BER compare, it can be seen that the present invention invent propose based on interference The interference elimination method of alignment and dynamic power distribution, in terms of the performance of BER nearly close to ecotopia under QPSK Modulating system, the precoding of multipoint cooperative force zero and the interference alignment performance for not carrying out power distribution (constant power distribution) are close, Method proposed by the invention will be significantly better than the precoding of multipoint cooperative force zero when high s/n ratio, have under identical bit error rate The performance boost of 3-4dB.
Fig. 6 and Fig. 7 is the reachable rate correlation curve of algorithms of different, and comparison other is proposed by the invention based on day line selection It selects, the interference elimination method of interference alignment and dynamic power distribution, and is based on day line options, interfere the interference elimination side of alignment Method, the multipoint cooperative force zero precoding algorithms based on day line options, and the non-cooperating force zero precoding without day line options Algorithm.Simulation result shows, the non-cooperating force zero pre-coding system without day line options be it is interference-limited, be based on day line selection The cooperation force zero precoding selected be it is optimal, based on constant power distribution interference alignment schemes it is close.Method of the invention Opposite non-cooperating force zero method for precoding has obviously advantage, and up in rate performance after dynamic allocation algorithm is added There is certain loss, but loss is smaller, performance loss is about in 4 antenna relative to multipoint cooperative force zero method for precoding 3bits/sec/Hz, in 8 antenna, performance loss is about 5bits/sec/Hz, this still falls within tolerance interval.Because of the invention The complexity versus Multi-Point cooperation method for precoding of mentioned method is much lower, part the most complicated in the mentioned method of the present invention For matrix size be N × N Eigenvalues Decomposition and matrix inversion operation, complexity be O (N3), and multipoint cooperative force zero prelists Code needs to carry out the inversion operation of global channel matrix, and computation complexity is O ((KN)3), wherein K is total number of users.
The above description is merely a specific embodiment, any feature disclosed in this specification, except non-specifically Narration, can be replaced by other alternative features that are equivalent or have similar purpose；Disclosed all features or all sides Method or in the process the step of, other than mutually exclusive feature and/or step, can be combined in any way.

Claims (1)

1. the extensive MIMO interference elimination method of multiple cell based on day line options and interference alignment, which is characterized in that including under Column step:
Step 1: base station end obtains channel matrix Hij, wherein user identifier j=1,2,3, base station identifier i=1,2,3, and Hij For N × Metzler matrix, wherein N is the number of antennas of user terminal, and M is the number of antennas of base station end；
Step 2: in each base station, criterion is maximized according to channel capacity and the channel matrix of user that base station is respectively serviced into Row day line options: channel matrix H is calculated separatelykkAll column vectors norm, select the maximum preceding Ns root antenna of norm as Active antenna, and close remaining M-NsRoot antenna；Wherein k=1,2,3；
Step 3: base station end redefines the channel matrix actually used according to the result of the day line options of step 2, for each A channel matrix Hij, select column vector corresponding to Ns root active antenna therein as new channel matrix H _ asij, i.e. H_ asij=[hijk]k∈φ, wherein [hijk] indicate channel matrix HijKth column, φ indicate the selected antenna subset of base station end；
Step 4: base station end is according to channel matrix H _ asijCalculate the interference alignment precoding vector v of each base stationi:
401: to confederate matrixEigenvalues Decomposition is carried out, selected characteristic is worth maximum D Column feature vector is aligned precoding vector v as the interference of base station 11Row vector of going forward side by side normalized, wherein D is the number sent According to flow amount；That is v1(:, r)=v1(:,r)/||v1(:, r) | |, r=1 ..., D, symbol (:, r) it indicates to take r column operations；
402: according to formulaThe interference of calculation base station 2 is aligned precoding vector v2Row vector of going forward side by side normalization Processing；
403: according to formulaThe interference of calculation base station 3 is aligned precoding vector v.3Row vector of going forward side by side normalizing Change processing；
Step 5: base station end is according to formula wj=U_HjNull vector w is compeled in the reception that ((j-1) * D+1:j*D :) calculates user jj, i.e., It receives and compels null vector wjBy matrix U _ HjIn (j-1) * D+1 arrange to jth * D D every trade vector composition；
Wherein, matrixAnd Symbol ()HThe conjugate transposition of representing matrix；
Step 6: base station end, which is based on receiving, compels null vector wjDistribute the transmission power p of each data flowjr, i.e.,WhereinP indicates that the transmitting of all base stations is total Power, djrRepresenting matrix djR column nonzero element value, symbol diag () expression seek diagonal line；
Step 7: the transmission power p distributed according to step 6jrIt updates to receive and compels null vector, evenIts Middle pj=diag (pj1,pi2,...,pjD)；So that receiving end is based on updated receive and compels null vector wjCompel to signal is received Zero processing；
Step 8: i generation in current base station end is sent to user j and sends data xjAnd it sends, wherein xj=vi*pj*sj, the sjTable Show the originally transmitted data for being sent to user j.
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CN107566018B (en) * 2017-09-02 2020-04-14 西安电子科技大学 Delay CSIT interference alignment method of multi-cell MIMO-IMAC
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