CN106330280B - A kind of extensive MIMO method for precoding - Google Patents

A kind of extensive MIMO method for precoding Download PDF

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CN106330280B
CN106330280B CN201610674353.9A CN201610674353A CN106330280B CN 106330280 B CN106330280 B CN 106330280B CN 201610674353 A CN201610674353 A CN 201610674353A CN 106330280 B CN106330280 B CN 106330280B
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matrix
precoding
channel
estimated
extensive mimo
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CN106330280A (en
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李正权
满勇强
燕锋
夏玮玮
沈连丰
王兵
胡静
宋铁成
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Southeast University
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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
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels

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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Power Engineering (AREA)
  • Radio Transmission System (AREA)

Abstract

The invention discloses a kind of extensive MIMO method for precoding, this method comprises: modeling to extensive MIMO, obtain channel matrix；RZF pre-coding matrix is obtained according to channel matrix；The inverse matrix in pre-coding matrix is estimated using Kapteyn series is truncated, obtains precoding estimated matrix；Precoding is carried out to signal is sent using obtained precoding estimated matrix.In the case where truncating the identical situation of order, compared with based on the method for deploying for truncating Taylor series, the present invention can obtain higher average user arrival rate.

Description

A kind of extensive MIMO method for precoding
Technical field
The present invention relates to wireless communication technology field more particularly to a kind of extensive MIMO method for precoding.
Background technique
Multiple-input and multiple-output (multiple-input multiple-output, MIMO) technology is next generation mobile communication Core technology, core concept are that more antennas are respectively adopted in sending and receiving end to carry out sending and receiving for signal, are keeping high frequency Signal transmission quality is increased substantially while spectrum efficiency.With the high speed development of wireless communication technique, to data rate, service Quality and the demand of number of users are multiplied, and the small-scale mimo system of tradition is no longer satisfied requirement, driving wireless communication Develop towards the extensive direction MIMO.The a large amount of antenna of base station equipment (antenna amount is greater than 100) is in extensive mimo system More mobile subscriber's services, to obtain higher spectrum efficiency, message transmission rate, handling capacity and better communication quality.
In the downlink, when base station is aware of channel state information (CSI, channel state information), In order to effectively inhibit the mutual interference of intra-cell users, need to carry out precoding to mobile subscriber's desired signal.It prelists Code is broadly divided into two kinds of linear and nonlinear.It is foremost in nonlinear precoding to have dirty paper code and permanent envelope precoding.It is dirty Paper code and permanent envelope precoding are to exchange the elimination of interference for sacrifice complexity as cost, suitable for small-scale MIMO system System.And in linear predictive coding algorithm it is foremost be force zero (ZF, zero-forcing) and least mean-square error (MMSE, minimum mean square error).Research shows that when the ratio between antenna for base station number and mobile subscriber's antenna number are less than 10, It can achieve the 98% of stolen goods paper code scheme total bitrate using the total bitrate that ZF and MMSE linear predictive coding obtains.In ZF and MMSE On the basis of algorithm, scholar proposes canonical force zero (RZF, regularized zero-forcing) linear predictive coding algorithm.It grinds Study carefully and show when antenna for base station number and all many number of mobile users, RZF linear predictive coding is optimal linear predictive coding scheme.But These linear predictive coding algorithms need to carry out inversion operation to matrix, and when antenna number is larger, inversion operation complexity is still very It is high.
For avoid RZF linearly prelist coding in matrix inversion operation, matrix inversion is opened up using Taylor series It opens and truncates, carry out precoding using obtained result.But the algorithm does not account for the shadow of the corresponding order factor in expansion series It rings, effectively inverse matrix cannot be estimated.
Summary of the invention
Goal of the invention: in view of the problems of the existing technology the present invention, provides a kind of extensive mimo channel of low complex degree Estimation method.
Technical solution: extensive MIMO method for precoding of the present invention includes:
Extensive MIMO is modeled, channel matrix is obtained；
RZF pre-coding matrix is obtained according to channel matrix；
The inverse matrix in pre-coding matrix is estimated using Kapteyn series is truncated, obtains precoding estimated matrix；
Precoding is carried out to signal is sent using obtained precoding estimated matrix.
Further, described that extensive MIMO is modeled, channel matrix is obtained, is specifically included:
It is M that extensive MIMO base station antenna amount, which is arranged, and single-antenna subscriber number is K in cell, and channel is slow fading channel, Channel vector are as follows:
hk~CN (0M×1, Φ), k=1 ..., K
In formula, hkIndicate k-th of channel vector, hk~CN (0M×1, Φ) and indicate hkObeying mean value is 0M×1Variance is Φ's Distribution, 0M×1Indicate 0 matrix that M row 1 arranges, Φ is the coherence matrix of channel, the spectral norm with bounded；A relevant period Interior, channel vector has fixed value, i.e. channel model is Rayleigh rapid fading model；
Obtaining channel matrix H according to channel vector is H=[h1,...,hK]T。
Further, described that RZF pre-coding matrix is obtained according to channel matrix, it specifically includes:
RZF pre-coding matrix is calculated according to channel matrix H are as follows:In formula,Table Show the estimated value of H, β is to ensure that GRZFMeetThe power constraint factor, wherein P is actual transmission power；ξ is The optimized coefficients of formula, IMIt is the unit matrix of a M × M.
Further, the precoding estimated matrixAre as follows:
In formula, N is to truncate order,θ indicates a constant, and value isIt indicates so that meet convergent coefficient after series expansion,
Further, described to carry out precoding to signal is sent using obtained precoding estimated matrix, it specifically includes:
Utilize obtained precoding estimated matrixPrecoding is carried out to signal is sent, the signal after being encoded isIn formula, S indicates to send signal matrix.
The utility model has the advantages that compared with prior art, the present invention its remarkable advantage is: the present invention is truncating the identical situation of order Under, compared with based on the method for deploying for truncating Taylor series, truncation Kapteyn series expansion method can obtain higher average Arrival rate of customers.
Detailed description of the invention
Fig. 1 is the flow diagram of extensive MIMO method for precoding of the invention；
Fig. 2 is the present invention and the method for deploying based on truncation Taylor series, is 0.1 in channel estimation errors, sends day Line number 128, under conditions of receiving antenna 32, for different truncation coefficients, the corresponding average user arrival rate comparison diagram of signal-to-noise ratio；
Fig. 3 is the present invention and the method for deploying based on truncation Taylor series, is 0.1 in channel estimation errors, sends day Line number 64, under conditions of receiving antenna 16, for different truncation coefficients, the corresponding average user arrival rate comparison diagram of signal-to-noise ratio；
Fig. 4 is the present invention and the method for deploying based on truncation Taylor series, is 0.7 in channel estimation errors, sends day Line number 128, under conditions of receiving antenna 32, for different truncation coefficients, the corresponding average user arrival rate comparison diagram of signal-to-noise ratio.
Specific embodiment
As shown in Figure 1, the extensive MIMO method for precoding of the present embodiment the following steps are included:
S1, extensive MIMO is modeled, obtains channel matrix.
Specifically, it is M, single-antenna subscriber in cell that the step, which includes: S11, the extensive MIMO base station antenna amount of setting, Number is K, and channel is slow fading channel, channel vector are as follows: hk~CN (0M×1, Φ), k=1 ..., K, in formula, hkIt indicates k-th Channel vector, hk~CN (0M×1, Φ) and indicate hkObeying mean value is 0M×1Variance be Φ distribution, 0M×1Indicate 0 square that M row 1 arranges Battle array, Φ is the coherence matrix of channel, the spectral norm with bounded；S12, within a relevant period, channel vector have fix Value, i.e., channel model be Rayleigh rapid fading model；Obtaining channel matrix H according to channel vector is H=[h1,...,hK]T。
S2, RZF pre-coding matrix is obtained according to channel matrix.
Wherein, RZF pre-coding matrix is calculated according to channel matrix H are as follows:Formula In,Indicate the estimated value of H, β is to ensure that GRZFMeetThe power constraint factor, wherein P is practical transmission function Rate；ξ is the optimized coefficients of formula, IMIt is the unit matrix of a M × M.
S3, the inverse matrix in pre-coding matrix is estimated using truncation Kapteyn series, obtains precoding estimation square Battle array.
The specific steps estimated using Kapteyn series is truncated are as follows:
For matrix X, if maximum eigenvalue λ meets inequalityThen there is following expansion:
Θ in formula0(I)=I；Using formula (1) to RZF precoding square Inverse matrix in battle array is unfolded to obtain:
In formula α be so that meet convergent coefficient after series expansion, willSubstitution formula (2)
Formula (3) is truncated, truncation order value is N, and the series statement for finally obtaining RZF pre-coding matrix is
It enablesThen above formula is equal to
Two summation symbols of formula (5) are unfolded to obtain
Formula (4) are substituted into formula (5) to obtain
In formulaθ indicates a constant, and value is
By formula (7) as can be seen that being estimated using series RZF pre-coding matrix, finally by matrix inversion operation It is converted to matrix product and summation operation.And corresponding pre-coding matrix can be rapidly found out using iterative algorithm
S4, precoding is carried out to signal is sent using obtained precoding estimated matrix.
Wherein, the signal after coding isIn formula, S indicates to send signal matrix.
In order to verify performance of the invention, by the present invention and Taylor algorithm based on Kapteyn series polynomial expansion It comparing respectively, analysis truncates the influence of multinomial and its order factor pair complexity, and comparing result is as shown in Figure 2, Figure 3, Figure 4, The experimental results showed that compared with based on the method for deploying for truncating Taylor series, being truncated in the case where truncating the identical situation of order Kapteyn series expansion method can obtain higher average user arrival rate.
Above disclosed is only a preferred embodiment of the present invention, and the right model of the present invention cannot be limited with this It encloses, therefore equivalent changes made in accordance with the claims of the present invention, is still within the scope of the present invention.

Claims (5)

1. a kind of extensive MIMO method for precoding, it is characterised in that this method comprises:
Extensive MIMO is modeled, channel matrix is obtained；
RZF pre-coding matrix is obtained according to channel matrix；
The inverse matrix in pre-coding matrix is estimated using Kapteyn series is truncated, obtains precoding estimated matrix；
Precoding is carried out to signal is sent using obtained precoding estimated matrix.
2. extensive MIMO method for precoding according to claim 1, it is characterised in that: described to be carried out to extensive MIMO Modeling obtains channel matrix, specifically includes:
It is M that extensive MIMO base station antenna amount, which is arranged, and single-antenna subscriber number is K in cell, and channel is slow fading channel, channel Vector are as follows:
hk~CN (0M×1, Φ), k=1 ..., K
In formula, hkIndicate k-th of channel vector, hk~CN (0M×1, Φ) and indicate hkObeying mean value is 0M×1Variance is the distribution of Φ, 0M×1Indicate 0 matrix that M row 1 arranges, Φ is the coherence matrix of channel, the spectral norm with bounded；Within a relevant period, letter Road vector has fixed value, i.e. channel model is Rayleigh rapid fading model；
Obtaining channel matrix H according to channel vector is H=[h1,...,hK]T。
3. extensive MIMO method for precoding according to claim 2, it is characterised in that: described to be obtained according to channel matrix RZF pre-coding matrix, specifically includes:
RZF pre-coding matrix is calculated according to channel matrix H are as follows:In formula,Indicate H's Estimated value, β are to ensure that GRZFMeetThe power constraint factor, the wherein mark of tr () representing matrix, P is real Border sends power；ξ is the optimized coefficients of formula, IMIt is the unit matrix of a M × M.
4. extensive MIMO method for precoding according to claim 3, it is characterised in that: the precoding estimated matrixAre as follows:
In formula, N is to truncate order,θ indicates a constant, and value isα indicates so that meet convergent coefficient after series expansion, Θ0(I) unit matrix that=I, I are.
5. extensive MIMO method for precoding according to claim 4, it is characterised in that: the precoding that the utilization obtains Estimated matrix carries out precoding to signal is sent, and specifically includes:
Utilize obtained precoding estimated matrixPrecoding is carried out to signal is sent, the signal after being encoded isIn formula, S indicates to send signal matrix.
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CN106817155B (en) * 2017-01-23 2020-12-15 东南大学 Large-scale MIMO low-complexity channel estimation method based on weighted Kapetyn series expansion
CN107359920A (en) * 2017-07-27 2017-11-17 东南大学 A kind of extensive MIMO method for precoding based on tchebycheff's iteration method
CN108234368B (en) * 2018-01-15 2020-07-24 哈尔滨工业大学 High-spectrum-efficiency safe truncated orthogonal frequency division multiplexing transmission method

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101388703A (en) * 2008-10-08 2009-03-18 北京创毅视讯科技有限公司 Multi-user MIMO pre-encoding method and system
CN104579443A (en) * 2014-07-29 2015-04-29 北京邮电大学 Linear pre-coding method based on multi-cell coordination Massive MIMO system
CN105071843A (en) * 2015-07-29 2015-11-18 东南大学 Large-scale MIMO system low-complexity polynomial expansion matrix inversion method and application thereof
WO2016115546A1 (en) * 2015-01-16 2016-07-21 Ping Liang Beamforming in a mu-mimo wireless communication system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101388703A (en) * 2008-10-08 2009-03-18 北京创毅视讯科技有限公司 Multi-user MIMO pre-encoding method and system
CN104579443A (en) * 2014-07-29 2015-04-29 北京邮电大学 Linear pre-coding method based on multi-cell coordination Massive MIMO system
WO2016115546A1 (en) * 2015-01-16 2016-07-21 Ping Liang Beamforming in a mu-mimo wireless communication system
CN105071843A (en) * 2015-07-29 2015-11-18 东南大学 Large-scale MIMO system low-complexity polynomial expansion matrix inversion method and application thereof

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