CN108768480A - Extensive mimo system uplink data method of estimation with phase noise - Google Patents

Extensive mimo system uplink data method of estimation with phase noise Download PDF

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CN108768480A
CN108768480A CN201810748661.0A CN201810748661A CN108768480A CN 108768480 A CN108768480 A CN 108768480A CN 201810748661 A CN201810748661 A CN 201810748661A CN 108768480 A CN108768480 A CN 108768480A
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phase noise
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CN108768480B (en
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成先涛
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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
    • H04B7/0452—Multi-user MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/0848—Joint weighting
    • H04B7/0851—Joint weighting using training sequences or error signal
    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/36—Modulator circuits; Transmitter circuits
    • H04L27/362—Modulation using more than one carrier, e.g. with quadrature carriers, separately amplitude modulated
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/38—Demodulator circuits; Receiver circuits
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/0001—Arrangements for dividing the transmission path
    • H04L5/0014—Three-dimensional division
    • H04L5/0023—Time-frequency-space
    • H04L5/0025—Spatial division following the spatial signature of the channel
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/003—Arrangements for allocating sub-channels of the transmission path
    • H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver

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

Abstract

The invention belongs to wireless communication technology fields, are related to a kind of extensive mimo system uplink data method of estimation with phase noise.Present invention employs variational Bayesian algorithm, variational Bayesian algorithm is a kind of algorithm for the Posterior distrbutionp solving unknown stochastic variable, passes through constantly iteration, the mean value and variance of the hidden variable under the conditions of obtaining known to sample.Beneficial effects of the present invention are to realize under the conditions of can be existing for phase noise to estimate the data symbol of extensive mimo system uplink, significantly improve the performance of BER of system.

Description

Extensive mimo system uplink data method of estimation with phase noise
Technical field
The invention belongs to wireless communication technology field, it is related in the presence of phase noise, using based on change decibel Ye Si infers that algorithm carries out data estimation and demodulation to extensive mimo system uplink.
Background technology
In modern wireless communication systems, extensive mimo system due to its higher spectrum efficiency and energy efficiency and by It is broadly recognized as the core technology of next generation mobile communication, it is generally the case that base station possesses hundreds of antennas, can be same at the same time It is dozens of user service under conditions of frequency, to significantly improve spectrum efficiency.With the increase of antenna for base station number, on a large scale The antenna gain of MIMO can be such that the power of the transmission signal of each user significantly reduces, to improve energy efficiency.
However, extensive mimo system is still faced with many problems and needs to solve, one of them is phase noise.Greatly The signal of scale MIMO communication system is also non-by radio-frequency devices other than the decline of experience channel in transmission process The influence of linear factor, the two factors make the reduced performance in receiving terminal system.Radio-frequency front-end is non-ideal in communication system Part includes mainly phase noise, and IQ amplitude-phases are uneven, non-linearity of power amplifier distortion etc., phase noise, actually It is a kind of characterization to frequency source frequency stability.Under normal conditions, frequency stability is divided into long-term frequency stability and short-term Frequency stability.So-called short-term frequency stability refers to the phase fluctuation caused by random noise or frequency fluctuation.As for because Frequency slow drift caused by temperature, aging etc., then referred to as long-term frequency stability.Usually primary concern is that short-term stability Problem, it is believed that phase noise is exactly short-term frequency stability, only the different expression sides of the two of a physical phenomenon kind Formula.For oscillator, frequency stability is a kind of measurement of its generation identical frequency in entire defined time range.If There are instantaneous variations for signal frequency, cannot remain unchanged, then signal source there is unstability, cause is exactly that phase is made an uproar Sound.In extensive MIMO communication system, transmitting terminal is required for generating corresponding carrier wave to complete corresponding radio frequency with receiving terminal Frequency spectrum conversion between base band.However the crystal oscillator and having a certain difference property of phaselocked loop of carrier wave are generated, cause load There is random difference in short-term with target frequency in wave frequency rate, in turn result in generated sine wave signal and random phase jump occurs Become, shows as phase noise.For the modulation system of orthogonal frequency, phase noise will produce common phase error and intercarrier is dry It disturbs, this is by the performance for the system that seriously affects.
Invention content
It is a kind of for extensive MIMO-OFDM systems it is an object of the invention in the presence of phase noise, provide The data estimation for uplink of uniting and demodulation method, improve the performance of BER of the system under severe hardware condition.
Present invention employs variational Bayesian algorithm, variational Bayesian algorithm is a kind of unknown random change of solution The algorithm of the Posterior distrbutionp of amount passes through constantly iteration, the mean value and variance of the hidden variable under the conditions of obtaining known to sample.
Understanding for the ease of those skilled in that art to technical solution of the present invention, the system that the present invention is used first Model illustrates.
Consider that the model of the MIMO ofdm system uplinks with phase noise, transmitting terminal have K user, Mei Geyong Family has 1 antenna, receiving terminal base station to have M root antennas, the time domain letter between k-th of user of transmitting terminal and receiving terminal m root antennas Road vector is denoted asWherein L is the length of channel vector.For each OFDM symbol, receiving terminal The time-domain signal expression formula of m root antennas is
Wherein,It is the time-domain received signal on m root antennas, N is the number of OFDM subcarriers,It is the phase noise matrix of receiving terminal m root antennas,It is k-th To the Toeplitz channel matrixes between receiving terminal m root antennas, its 1st is classified as userWherein 01×(N-L)Indicate that element is all the row vector that 0, length is N-L.F∈CN×NIt is to return The one FFT matrixes changed, its j-th of element of the i-th row aredk=[dk,1,dk,2,…,dk,N]T It is the data or pilot frequency sequence that k-th of user sends.It is the white complex gaussian noise sequence of time domain,
Form below can be decomposed into：
Wherein Hm,k=diag { [Hm,k,1,Hm,k,2,…,Hm,k,N]T,
And(2) are substituted into (1) to obtain
θm=[θm,1,θm,2,…,θm,N]TFor the vector of phase noise of real Gaussian Profile, i.e. θm=N (0, Φ).Due to θm's Covariance matrix Φ is real symmetric matrix, and characteristic value is real number, and can carry out similarity diagonalization with orthogonal matrix：
Φ=U Λ UT (4)
Wherein Λ=diag { [λ1,λ2,…,λN]TIt is diagonal matrix, the characteristic value that the descending that diagonal element is Φ arranges, U is orthogonal matrix, its each row are the feature vectors of the characteristic value of Λ respective columns.By calculating pair it can be found that in Λ Angle member only has preceding several values larger, and other elements compare very little with preceding several items, therefore can only take first I to come closely Seemingly, i.e.,
Φ≈VΓVT (5)
Γ=diag { [λ1,λ2,…,λI]TIt is the V ∈ C using preceding I characteristic value in Λ as the diagonal matrix of diagonal elementN×I The matrix formed is arranged by the preceding I of preceding U.To vector of phase noise θmMake linear transformation
θm=Ux'm≈Vxm (6)
By the property of Gaussian Profile it is found that xm=N (0, Γ), since Γ is diagonal matrix, so xmEach component between be It is mutually independent.
Receiving terminal antenna is now divided into G groups, then has M/G=S root antennas, every group of S root antennas to use same oscillation for every group Device, then the value for organizing the phase noise on interior each antenna is identical, i.e., for the antenna in g (g=1,2 ..., G) group, hasG=1,2 ..., G.Priori probability density function be
The expression formula of frequency-domain received signal is
Wherein Tm=FPmFHIt is a Toeplitz matrix, its 1st is classified as Tm(:, 1) and=[Tm,1,Tm,2,…,Tm,N]T,
WhereinOnly consider TmIn diagonal line on element, i.e. TmIt is assumed to diagonal Matrix, Tm=Tm,1I, (8) can be approximated to be
If pilot tone number is R, and the pilot tone all same in different user data sequence, frequency pilot sign in an OFDM symbol RespectivelyThe frequency domain that pilot tone is equably inserted into each user sends symbol sebolic addressing dkIn, i.e.,R=1,2 ..., R.Consider further that the value to all phase noises on g (g=1,2 ..., G) group antennas It is all identical, thenThen for some specific frequency pilot signIt can utilize corresponding Group in all antennas reception symbolIt is right"ball-park" estimate is carried out, i.e.,
R is averaged, can be obtainedEstimated valueThen to organizing interior all antennas,It is rightAfter normalizing, to frequency-domain received symbols rmIt is mended ZF merging is carried out again after repaying
Further, the judgement of data symbol is carried out using (11), the data symbol ruled out is as algorithm iteration Initial value.
On the other hand, (3) are rewritten as
It is now assumed that symbol sebolic addressing dkObey following priori multiple Gauss distribution, and the data statistics meaning between different user On be independent from each other
p(dk)=CN (0, I)=π-Nexp{-||dk||2, k=1,2 ..., K (8)
Priori probability density function provided by (7), then under the conditions of phase noise and data symbol are all known, the Reception signal on m root antennasObey following multiple Gauss distribution
The present invention is achieved by the steps of：
S1, in the starting stage, calculate the common phase error of phase noise, after compensation on each antenna reception believe Number carry out ZF merging, obtain the initial value of data symbol
S2, the iteration that variation bayesian algorithm is realized by following step：
S21, the Posterior distrbutionp of vector is unfolded in phase noise mean value and variance are calculated
S22, calculate data symbol vectors Posterior distrbutionp mean value and variance：
S23, circulation step S21-S22, under conditions of known reception signal, data symbol vectors will converge on one Stable value.
Beneficial effects of the present invention are to realize to extensive mimo system uplink under the conditions of can be existing for phase noise The data symbol of link is estimated, the performance of BER of system is significantly improved.
Description of the drawings
Fig. 1 is the extensive mimo system uplink schematic diagram under the effect of phase noise that the present invention uses；
Fig. 2 is the flow chart that the present invention realizes data estimation algorithm；
Fig. 3 is the BER performance charts of the algorithm using the present invention under different antennae grouping；
Fig. 4 is the BER performance curve curve graphs of the algorithm using the present invention under out of phase noise level；
Specific implementation mode
The present invention is described in detail below in conjunction with the accompanying drawings：
S1, in the starting stage, calculate the common phase error of phase noise, after compensation on each antenna reception believe Number carry out ZF merging, obtain the initial value of data symbol
S2, the iteration that variation bayesian algorithm is realized by following step：
S21, the Posterior distrbutionp of vector is unfolded in phase noise mean value and variance are calculated
S22, calculate data symbol vectors Posterior distrbutionp mean value and variance：
S23, circulation step S21-S22, under conditions of known reception signal, data symbol vectors will converge on one Stable value.
Fig. 3 is performance of BER curve under conditions of different antenna groupings, and in simulations, modulation system is 64QAM, channel length 64, antenna for base station number are 64, and number of users 5, OFDM subcarrier numbers are 512, phase noise level - 85dBc/Hz@1MHz, antenna packet count is taken to take 1,8,64 respectively, the characteristic value number of the covariance matrix of phase noise is selected as 3, algorithm iteration number is 1.From simulation curve as can be seen that when antenna packet count is 64, i.e. every antenna regards 1 group of feelings as Under condition, system performance is best, and with the reduction of packet count, performance is gradually deteriorated, when all antennas as 1 group, Satisfied performance is cannot achieve, selects the characteristic value of the covariance matrix of phase noise as 5 at this time, algorithm iteration number is selected as 2, Preferable performance still may be implemented.
Fig. 4 is performance of BER curve under conditions of different antenna groupings, and antenna packet count is fixed as 8, phase Position noise level takes -90dBc/Hz@1MHz, -85dBc/Hz@1MHz, -80dBc/Hz@1MHz, other simulation parameters and figure respectively 3 is identical.From simulation result as can be seen that with phase noise raising, system performance is gradually deteriorated, but the algorithm of the present invention Preferable phase noise reduction may be implemented, obtain satisfied BER performances, when phase noise level is -80dBc/Hz@1MHz When, it is similar to the case where Fig. 3 phantom antenna packet counts are 1, selects the characteristic value of the covariance matrix of phase noise as 5, algorithm Iterations are selected as 2, and preferable performance still may be implemented.

Claims (1)

1. the extensive mimo system uplink data method of estimation with phase noise, MIMO of the setting with phase noise In ofdm system uplink, transmitting terminal has K user, each user to have 1 antenna, receiving terminal base station to have M root antennas, transmitting The time domain channel vector between k-th of user and receiving terminal m root antennas is held to be denoted asWherein L For the length of channel vector, for each OFDM symbol, the time-domain signal expression formula of receiving terminal m root antennas is
Wherein,It is the time-domain received signal on m root antennas, N is the number of OFDM subcarriers,It is the phase noise matrix of receiving terminal m root antennas,It is kth To the Toeplitz channel matrixes between receiving terminal m root antennas, its 1st is classified as a userWherein 01×(N-L)Indicate that element is all the row vector that 0, length is N-L；F∈CN×NIt is to return The one FFT matrixes changed, its j-th of element of the i-th row aredk=[dk,1,dk,2,…,dk,N]TIt is The data or pilot frequency sequence that k-th of user sends；It is the white complex gaussian noise sequence of time domain,
It is decomposed into form below：
Wherein Hm,k=diag { [Hm,k,1,Hm,k,2,…,Hm,k,N]T, and(2) are substituted into (1)
θm=[θm,1,θm,2,…,θm,N]TFor the vector of phase noise of real Gaussian Profile, i.e. θm=N (0, Φ)；Set θmAssociation side Poor matrix Φ is real symmetric matrix, and characteristic value is real number, and similarity diagonalization is carried out with orthogonal matrix：
Φ=U Λ UT (4)
Wherein Λ=diag { [λ1,λ2,…,λN]TIt is diagonal matrix, the characteristic value that the descending that diagonal element is Φ arranges, U is just Matrix is handed over, its each row are the feature vectors of the characteristic value of Λ respective columns；Several are set before the diagonal element in Λ only has Be worth larger, other elements compare very little with preceding several items, before only taking I it is approximate, i.e.,
Φ≈VΓVT (5)
Γ=diag { [λ1,λ2,…,λI]TIt is the V ∈ C using preceding I characteristic value in Λ as the diagonal matrix of diagonal elementN×IBe by The matrix of the preceding I row compositions of preceding U；To vector of phase noise θmMake linear transformation
θm=Ux'm≈Vxm (6)
By the property of Gaussian Profile it is found that xm=N (0, Γ), since Γ is diagonal matrix, so xmEach component between be mutual It is independent；
Receiving terminal antenna is divided into G groups, then has M/G=S root antennas, every group of S root antennas to use same oscillator for every group, then group The value of phase noise on interior each antenna is identical, i.e., for the antenna in g (g=1,2 ..., G) group, has Priori probability density function be
The expression formula of frequency-domain received signal is
Wherein Tm=FPmFHIt is a Toeplitz matrix, its 1st is classified as Tm(:, 1) and=[Tm,1,Tm,2,…,Tm,N]T,
WhereinOnly consider TmIn diagonal line on element, i.e. TmIt is assumed to angular moment Battle array, Tm=Tm,1I, (8) can be approximated to be
If pilot tone number is R in an OFDM symbol, and the pilot tone all same in different user data sequence, frequency pilot sign are distinguished ForThe frequency domain that pilot tone is equably inserted into each user sends symbol sebolic addressing dkIn, i.e.,Consider further that all phase noises on g (g=1,2 ..., G) group antennas value all It is identical, thenThen for some specific frequency pilot signIt can utilize corresponding The reception symbol of all antennas in groupIt is right"ball-park" estimate is carried out, i.e.,
R is averaged, can be obtainedEstimated valueThen to organizing interior all antennas, It is rightAfter normalizing, to frequency-domain received symbols rmZF merging is carried out again after compensating
The judgement of data symbol, initial value of the data symbol ruled out as algorithm iteration are carried out using (11)；
(3) are rewritten as
Set symbol sebolic addressing dkFollowing priori multiple Gauss distribution is obeyed, and is phase in the data statistics meaning between different user It is mutually independent
p(dk)=CN (0, I)=π-Nexp{-||dk||2, k=1,2 ..., K (8)
Priori probability density function provided by (7), then under the conditions of phase noise and data symbol are all known, m roots Reception signal on antennaObey following multiple Gauss distribution
It is characterized in that, the data evaluating method includes the following steps：
S1, in the starting stage, calculate the common phase error of phase noise, after compensation to the reception signal on each antenna into Row ZF merges, and obtains the initial value of data symbol
S2, the iteration that variation bayesian algorithm is realized by following step：
S21, the Posterior distrbutionp of vector is unfolded in phase noise mean value and variance are calculated
S22, calculate data symbol vectors Posterior distrbutionp mean value and variance：
S23, circulation step S21-S22, under conditions of known reception signal, data symbol vectors will converge on a stabilization Value.
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