CN102130879A - Phase noise elimination method in orthogonal frequency division multiplexing system - Google Patents

Phase noise elimination method in orthogonal frequency division multiplexing system Download PDF

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CN102130879A
CN102130879A CN2011100582494A CN201110058249A CN102130879A CN 102130879 A CN102130879 A CN 102130879A CN 2011100582494 A CN2011100582494 A CN 2011100582494A CN 201110058249 A CN201110058249 A CN 201110058249A CN 102130879 A CN102130879 A CN 102130879A
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杜文
何晨
占敖
蒋铃鸽
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Shanghai Jiaotong University
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Abstract

The invention discloses a phase noise elimination method in an orthogonal frequency division multiplexing system in the technical field of wireless communication. The method comprises the following steps of: obtaining a channel transfer function (CTF) matrix through a pretreatment matrix and a channel estimation shock response vector so as to reduce the number of channel estimation parameters from the number of sub-carriers to the number of channel time domain lengths; reducing the number of phase noise estimation parameters through a down sampling matrix; estimating CTF matrix and a phase noise matrix in a pilot frequency time slot through an iterative method to obtain an optimal estimated value of the CTF matrix, namely continuously tracking and estimating to obtain the phase noise estimated value by utilizing the optimal estimated value under the condition that the channel is invariable in adjacent pilot frequency time slots; and compensating a received signal by utilizing the phase noise estimated value so as to eliminate the noise.

Description

Phase noise removing method in the ofdm system
Technical field
What the present invention relates to is a kind of method of wireless communication technology field, specifically is phase noise removing method in a kind of ofdm system.
Background technology
OFDM (Orthogonal Frequency Division Multiplexing, OFDM) technology has spectral efficient, anti-narrow band interference, utilize existing FFT (Fast Fourier Transform, fast Fourier transform) easy characteristic such as realization, become one of wideband wireless mobile communication system key technology, be widely used in broadband wireless MAN (IEEE802.16), DAB (Digital Audio Broadcasting, digital audio broadcast system), DVB-T wireless communication systems such as (Digital Video Broadcasting-terrestrial, digital video broadcast-terrestrial systems).The OFDM technology is also as one of following 4G core technology, in order to satisfy growing radio multimedium business demand.
Current increasing communication system is crowded in low-frequency range, causes this frequency range frequency spectrum resource deficient day by day.System modulation is obtained bigger bandwidth to higher frequency band, and adopt the higher OFDM technology of spectrum efficiency, can effectively solve low-frequency range communication spectrum congested problem.Promote working frequency range and cause that RF module performance worsens, PHN (the PHase Noise of increase system, phase noise) power, and OFDM adopts quadrature carrier to promote spectrum efficiency, responsive more to channel errors, phase noise etc., cause more serious CPE (Common Phase Error, common phase error) and ICI (Inter-Carrier Interference, disturb between adjacent sub-carrier), reduced the ofdm system communication performance.
Existing literature search is found, in the prior art:
1, document (Analysis of Phase Noise Effects in OFDM Modems (phase noise analysis in the orthogonal frequency division multiplexing modem), IEEE Transactions on Communications, vol.50, no.10, pp.1696-1705,2002) analyzing in detail ofdm system from the Different Effects of transmitting-receiving two-end local oscillator PHN to systematic function, but do not provide concrete cancellation scheme.
2, document (Estimation of Channel Transfer Function and Carrier Frequency Offset for OFDMSystems with Phase Noise (be subjected in the ofdm system that phase noise disturbs channel transfer functions and carrier shift estimate), IEEE Transactions on Vehicular Technology, vol.58, no.8, pp.4380-4387,2009.) provided the associating algorithm for estimating of ofdm system carrier deviation, phase noise and channel, do not consider the problem that the phase noise increase brings.
3, document (Phase Noise Estimation and Mitigation for OFDM Systems (estimation of phase noise and elimination in the ofdm system), IEEE Transactions on Wireless Communications, vol.5, no.12, pp.3616-3625,2006.) provided (Linear Minimum Mean Square Error based on LMMSE, linear minimum mean-squared error), ML (Maximum Likelihood, maximum likelihood) the phase noise elimination algorithm of criterion, but algorithm complex is higher and do not consider channel estimating, restricts its range of application.
Summary of the invention
The present invention is directed to the prior art above shortcomings, phase noise removing method in a kind of ofdm system is provided, by the low complexity algorithm of combined with CT F (Channel Transfer Function, channel transfer functions) and phase noise estimation.By analyzing ofdm system CTF and phase noise characteristic, on the OFDM pilot time slot, unite and estimate CTF and phase noise; Constant at pilot sub-carrier supposition channel, estimate the ICI interference that phase noise causes to suppress phase noise continuously.This paper performance evaluation and simulation result show: under big phase noise, and existing relatively OFDM channel estimation method, this algorithm has reduced pilot-frequency expense, effectively eliminates phase noise simultaneously, has improved the CTF estimated accuracy.
The present invention is achieved by the following technical solutions, the present invention includes following steps:
The first step:, obtain channel CTF matrix H, thereby the channel estimating number of parameters is reduced to the number of channel time domain length from the number of subcarrier by preconditioning matrix and the vectorial h of estimation CIR (Impulse response of channel channel impulse response).
Described channel CTF matrix H=T hH, wherein: H is an estimated value CTF matrix, H=[H 0H 1H N-1] T, go diagonalization to handle by H and obtain h=[h 0h 1H L-1] T, T hBe the channel preconditioning matrix:
Figure BDA0000049710450000021
Wherein:
Figure BDA0000049710450000022
L is a channel time domain length, and N is a sub-carrier number.
Second step: reduce phase noise estimated parameter number by subtracting sampling matrix, be specially:
2.1) get phase noise matrix P first row P C1=[P 0P 1P N-1] T, P C1And the pass between the phase noise vector p is: p=[e J φ [0], e J φ [1]..., e J φ [N-1]], Wherein: e J φ [m]The expression phase noise, W DFTBe the DFT transformation matrix, Wherein: T pFor subtracting sampling matrix, N p〉=M and preferred N p=M, then p ≈ T pP ', wherein:
2.2) obtain subtracting sampling matrix in that phase noise statistical property known conditions is next Wherein: T p=R Pp '(R P ' p ') -1, wherein: R Pp '=pp ' *, R P ' p '=p ' p ' *, p and p ' are respectively the sampling average of phase noise and subtract the sampling average, by subtracting sampling matrix T pIndirect Estimation p reduces to M with phase noise estimated parameter number from N, and wherein N is a sub-carrier number, and M is the pilot sub-carrier frequency domain interval.
The 3rd step: estimate CTF matrix H and phase noise matrix by iterative method at pilot time slot, obtain the optimum valuation H of CTF matrix, concrete steps comprise:
3.1) by p ≈ T pP ' can get
Figure BDA0000049710450000031
(P) i, under the LS criterion, find the solution
Figure BDA0000049710450000032
Can get CIR vector optimal value is:
Figure BDA0000049710450000033
3.2) by H=T hH can get (H) i=T h(h) i, under the LS criterion, find the solution Can get phase noise vector optimal value is:
Figure BDA0000049710450000035
Add up then i=i+1 and return step 3.1);
Wherein: p ' iterative initial value is
Figure BDA0000049710450000036
P 0Be CPE, can be by following formula in the hope of P 0Valuation: () iRepresent the i time iteration result of this variable, S PThe expression set of pilot symbols:
When adjacent twice iteration as a result difference less than set point (le for example -4) time stop iteration, promptly obtain the optimum valuation of CTF matrix
The 4th step: utilize optimum valuation under the situation that channel is constant in the adjacent pilot frequencies time slot
Figure BDA0000049710450000039
Continuous Tracking is estimated to obtain the phase noise valuation, and concrete steps are: reappraise phase noise matrix P,
Figure BDA00000497104500000310
Wherein (p ') NiBe the valuation of phase noise on i symbol.
The 5th step: utilize the phase noise valuation to compensate to received signal, realize noise removing: obtaining phase noise after the valuation on each symbol, receiving terminal utilizes the phase noise valuation that receiving symbol is done compensation:
Figure BDA00000497104500000312
Wherein:
Figure BDA00000497104500000313
Be phase noise valuation compensation vector, Y is a receiving symbol,
Figure BDA00000497104500000314
It is receiving symbol through compensation.
The invention has the advantages that by preconditioning matrix and estimated channel impulse response vector, thereby reduce the estimated parameter number, and estimate to obtain the phase noise valuation, compensate to received signal, realize noise removing with optimum valuation Continuous Tracking.
Description of drawings
Fig. 1 is the ofdm system block diagram.
Fig. 2 is an ofdm system pilot tone pattern.
Fig. 3 is that different parameters is provided with down algorithm to the effective SNR lifting of system.
Embodiment
Below embodiments of the invention are elaborated, present embodiment is being to implement under the prerequisite with the technical solution of the present invention, provided detailed execution mode and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
The ofdm system model that following examples realize is as follows:
Figure BDA0000049710450000041
Figure BDA0000049710450000042
For 0≤t＜T, wherein: r (t) represents received signal, s (t) expression OFDM baseband signal, X kSource symbol after expression is changed through constellation mapping, S/P, N represents the ofdm system sub-carrier number, T represents the OFDM symbol period, being added with property of n (t) expression white Gaussian noise (Additive White Gaussian Noise, AWGN), h (t) expression channel impulse response (Channel Impulse Response, CIR), φ TX(t) and φ RX(t) represent the transmitting-receiving two-end phase noise respectively.Since this algorithm do not relate to Cyclic Prefix (Cycle Prefix, CP), so will not discuss.
Make φ (t)=φ TX(t)+φ RX(t), sampling has following expression to received signal:
Figure BDA0000049710450000043
Wherein: suppose channel length be L (L＜N) and to h (m) (L＜m≤N) does the zero padding operation.
Order
Figure BDA0000049710450000044
Rewrite following formula and can get the sytem matrix expression formula:
Figure BDA0000049710450000046
Wherein: X=[X 0X 1X N-1] T: Y=[Y 0Y 1Y N-1] TW=[W 0W 1W N-1] TH=diag[H 0H 1H N-1];
Figure BDA0000049710450000047
Reasonably the pilot tone pattern can be obtained littler channel estimating MSE under identical pilot density.Under channel estimating MSE and spectral efficient constraint: the channel frequency domain correlation is strong, then inserts frequency pilot sign continuously on the plurality of sub carrier wave; The channel time domain correlation is strong, then inserts frequency pilot sign in given some time slots.Scatter the pilot tone algorithm based on bulk, pectination channel estimation method, two dimension in addition and all only estimate channel, do not consider the influence of phase noise.Two adjacent pilot time slots are spaced apart K OFDM symbol among Fig. 2, and the pilot sub-carrier frequency domain interval is a M subcarrier.
The ofdm communication system system parameter setting is as follows under the present embodiment:
Table 1 system emulation parameter is provided with
The first step: can find the solution for guaranteeing optimization problem, by preconditioning matrix to reduce the channel estimating number of parameters.In this example, channel preconditioning matrix T hAs follows:
Figure BDA0000049710450000052
By channel preconditioning matrix T hThe channel estimating number of parameters is reduced to L from N.
Second step: by preconditioning matrix to reduce phase noise estimated parameter number.In this example, M=32,
Figure BDA0000049710450000053
And get phase noise matrix P first row P C1=[P 0P 1P N-1] T, it is as follows to get phase noise statistic p ':
p′＝[0.9829+0.0460i 1.0434+0.0263i 1.0334+0.0227i 1.0453+0.0271i?0.9618-0.0365i?1.0400+0.0433i?0.9992+0.0034i?0.9821+0.0466i?1.0510+0.0317i?0.9612-0.0355i?1.0409+0.0428i?1.0510+0.0317i?1.0498+0.0288i?0.9963+0.0340i1.0153+0.0240i?0.9743+0.0128i?1.0322+0.0475i?0.9928+0.0232i?1.0498+0.0288i0.9788+0.0489i?1.0512+0.0293i?1.0366+0.0454i?0.9927+0.0236i?0.9803+0.0481i?0.9929-0.0398i?0.9614-0.0359i?0.9817+0.0439i?0.9686+0.0065i?0.9585-0.0276i?0.9920+0.0252i?0.9958-0.0369i?0.9957+0.0154i]
Pass through R Pp '=pp ' *, R P ' p '=p ' p ' *Can try to achieve phase noise and subtract sampling matrix T p=R Pp '(R P ' p ') -1Behind the phase noise preconditioning matrix, the estimated parameter number of phase noise is reduced to M from N.Satisfying under the situation of M+L＜N, just can carry out next step and find the solution.T pMatrix is bigger, does not provide its actual value in this example here, obtains but can derive by this example.
The 3rd step: at first find the solution P 0Valuation is as the initial value of iterative computation.P in this example 0Valuation is as follows:
Figure BDA0000049710450000061
Obtaining
Figure BDA0000049710450000062
After, at pilot time slot iterative CTF matrix H and phase noise matrix P, concrete steps are as follows:
1. by p ≈ T pP ' can get And then obtain (P) i, under the LS criterion, find the solution
Figure BDA0000049710450000064
It is as follows to get the channel optimal value:
(h) 1=[0.4202-0.6839i 0.3174-0.4238i 0.1257-0.3103i 0.0463-0.0934i 0.0210-0.0525i] brings the result that the above-mentioned first time, iteration obtained into the 2nd step.
2. pass through H=T hH can get (H) i=T h(h) i, under the LS criterion, find the solution
Figure BDA0000049710450000065
It is as follows to get phase noise vector optimal value:
(p) 1＝[0.9664+0.0460i 1.0756+0.0263i 1.0253+0.0227i 1.0695+0.0271i 1.0308-0.0365i?1.0831+0.0433i?0.9840+0.0034i 0.9876+0.0466i 1.1319+0.0317i 0.9182-0.0355i?0.9856+0.0428i?1.0912+0.0317i 1.0961+0.0288i 1.0138+0.0340i 1.0284+0.0240i?0.9335+0.0128i 1.0195+0.0475i 1.0205+0.0232i 1.0828+0.0288i1.0338+0.0489i 1.0300+0.0293i 1.1011+0.0454i 0.9423+0.0236i 0.9812+0.0481i0.9803-0.0398i?0.8741-0.0359i 0.9590+0.0439i 0.9352+0.0065i 0.9626-0.0276i0.9538+0.0252i?0.8828-0.0369i 0.9369+0.0154i]
Obtaining (p) 1After, returned for the 1st step, and with i=i+1.
When twice iteration in front and back as a result difference stop iteration when setting thresholding, obtain instantly
Figure BDA0000049710450000066
Be CTF matrix and phase noise matrix local optimum.Setting the thresholding position in this example is le -4, iterations is generally between 5 to 7 times.Obtain channel in this example and the phase noise local optimum is respectively:
(h) 7＝[0.3502-0.6739i?0.2774-0.5338i?0.1082-0.2081i?0.0344-0.0663i?0.0126-0.0243i](p) 7＝[0.9829+0.0460i 1.0434+0.0263i 1.0334+0.0227i 1.0453+0.0271i 0.9618-0.0365i 1.0400+0.0433i?0.9992+0.0034i?0.9821+0.0466i 1.0510+0.0317i?0.9612-0.0355i 1.0409+0.0428i 1.0510+0.0317i 1.0498+0.0288i?0.9963+0.0340i 1.0153+0.0240i?0.9743+0.0128i 1.0322+0.0475i 0.9928+0.0232i 1.0498+0.0288i0.9788+0.0489i?1.0512+0.0293i 1.0366+0.0454i?0.9927+0.0236i 0.9803+0.0481i0.9929-0.0398i?0.9614-0.0359i?0.9817+0.0439i?0.9686+0.0065i?0.9585-0.0276i0.9920+0.0252i?0.9958-0.0369i?0.9957+0.0154i]
By (P C1) i=T p(p) 7Can get the phase noise matrix First row can get whole phase noise matrix by displacement afterwards
Figure BDA0000049710450000072
By (H) i=T h(h) 7Can get channel matrix.
The 4th step: utilize optimal value Continuous Tracking is estimated phase noise.Supposing that channel remains unchanged in K=20 OFDM symbol time slot, also is channel matrix (h) 7Remain unchanged, estimate phase noise continuously.With reference to the pilot time slot algorithm for estimating, reappraise the phase noise matrix P in each symbol period.With second symbol period is example, obtains following phase noise valuation:
[p] 2＝[0.9829+0.0460i 1.0434+0.0263i 1.0334+0.0227i 1.0453+0.0271i?0.9618-0.0365i 1.0400+0.0433i?0.9992+0.0034i?0.9821+0.0466i 1.0510+0.0317i?0.9612-0.0355i 1.0409+0.0428i 1.0510+0.0317i 1.0498+0.0288i?0.9963+0.0340i1.0153+0.0240i?0.9743+0.0128i 1.0322+0.0475i?0.9928+0.0232i 1.0498+0.0288i0.9788+0.0489i 1.0512+0.0293i 1.0366+0.0454i?0.9927+0.0236i?0.9803+0.0481i0.9929-0.0398i?0.9614-0.0359i?0.9817+0.0439i?0.9686+0.0065i?0.9585-0.0276i0.9920+0.0252i?0.9958-0.0369i?0.9957+0.0154i]
The 5th step: utilize the phase noise valuation to compensate to received signal.The phase noise that the step obtains in each symbol period in the utilization is estimated, gets its conjugation, obtains the phase noise compensation matrix, eliminates the influence that phase noise brings with this.
Fig. 3 is this routine analogous diagram: (SNR under the high s/n ratio situation 1〉=20dB), compare situation about only needing except that CPE, can promote the effective SNR of 4dB system at least, and along with ofdm system SNR 1Raising, algorithm promotes effect also to be increased thereupon.Ideal situation refers among the figure
Figure BDA0000049710450000074
Change, as a reference with this.
Pilot sub-carrier counts M and pilot time slot interval K can influence the lifting of algorithm to the effective SNR of system.By two curves in [M, K]=[64,10] in the comparison diagram 3 and [M, K]=[32,10], can determine to increase effective SNR of the further elevator system of pilot sub-carrier number meeting.At high SNR 1Can be similar to and think SNR down, 3∝ M.Two curves in [M, K]=[32,20] and [M, K]=[32,10] in the comparison diagram reduce pilot interval K and can increase algorithm to system's effective SNR lifting effect.Can further eliminate phase noise although increase M and reduce K, can reduce spectrum efficiency and increase amount of calculation.

Claims (6)

1. phase noise removing method in the ofdm system is characterized in that, may further comprise the steps:
The first step: by preconditioning matrix and estimated channel impulse response vector, obtain channel CTF matrix, thereby the channel estimating number of parameters is reduced to the number of channel time domain length from the number of subcarrier;
Second step: reduce phase noise estimated parameter number by subtracting sampling matrix;
The 3rd step: estimate CTF matrix and phase noise matrix by iterative method at pilot time slot, obtain the optimum valuation of CTF matrix:
The 4th step: utilize optimum valuation Continuous Tracking to estimate to obtain the phase noise valuation under the situation that channel is constant in the adjacent pilot frequencies time slot;
The 5th step: utilize the phase noise valuation to compensate to received signal, realize noise removing.
2. phase noise removing method in the ofdm system according to claim 1 is characterized in that, described channel CTF matrix H=T hH, wherein: H is an estimated value CTF matrix, H=[H 0H 1... H N-1] T, go diagonalization to handle by H and obtain h=[h 0h 1... h L-1] T, T hBe the channel preconditioning matrix:
Figure FDA0000049710440000011
Wherein:
Figure FDA0000049710440000012
L is a channel time domain length, and N is a sub-carrier number.
3. phase noise removing method in the ofdm system according to claim 1 is characterized in that, described second step specifically is meant:
2.1) get phase noise matrix P first row P C1=[P 0P 1... P N-1] T, P C1And the pass between the phase noise vector p ' is: p=[e J φ [0], e J φ [1]..., e J φ [N-1]],
Figure FDA0000049710440000013
Wherein: e J φ [m]The expression phase noise, W DFTBe the DFT transformation matrix,
Figure FDA0000049710440000014
Wherein:
Figure FDA0000049710440000015
T pFor subtracting sampling matrix, N p〉=M and preferred N p=M, then p ≈ T pP ', wherein:
2.2) obtain subtracting sampling matrix in that phase noise statistical property known conditions is next
Figure FDA0000049710440000017
Wherein: T p=R Pp '(R P ' p ') -1, wherein: R Pp '=pp ' *, R P ' p '=p ' p ' *, p and p ' are respectively the sampling average of phase noise and subtract the sampling average, by subtracting sampling matrix T pIndirect Estimation p reduces to M with phase noise estimated parameter number from N, and wherein N is a sub-carrier number, and M is the pilot tone subcarrier spacing.
4. phase noise removing method in the ofdm system according to claim 1 is characterized in that, described the 3rd step specifically is meant:
3.1) by p ≈ T pP ' can get
Figure FDA0000049710440000021
(P) i, under the LS criterion, find the solution
Figure FDA0000049710440000022
Can get CIR vector optimal value is:
Figure FDA0000049710440000023
3.2) by H=T hH can get (H) i=T h(h) i, under the LS criterion, find the solution
Figure FDA0000049710440000024
Can get phase noise vector optimal value is: Add up then i=i+1 and return step 3.1);
Wherein: p ' iterative initial value is
Figure FDA0000049710440000026
P 0Be CPE, can be by following formula in the hope of P 0Valuation:
Figure FDA0000049710440000027
() iRepresent the i time iteration result of this variable, S PThe expression set of pilot symbols;
When adjacent twice iteration as a result difference less than set point (le for example -1) time stop iteration, promptly obtain the optimum valuation of CTF matrix
Figure FDA0000049710440000028
5. phase noise removing method in the ofdm system according to claim 1 is characterized in that, described the 4th step is meant: concrete steps are: reappraise phase noise matrix P,
Figure FDA0000049710440000029
Wherein: (p ') NiBe the valuation of phase noise on i symbol.
6. phase noise removing method in the ofdm system according to claim 1 is characterized in that, described the 5th step is meant: obtaining phase noise after the valuation on each symbol, receiving terminal utilizes the phase noise valuation that receiving symbol is done compensation:
Figure FDA00000497104400000211
Wherein:
Figure FDA00000497104400000212
Be phase noise valuation compensation vector, Y is a receiving symbol,
Figure FDA0000049710440000031
It is receiving symbol through compensation.
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CN103139128A (en) * 2011-12-05 2013-06-05 中国科学院微电子研究所 Method of orthogonal frequency division multiplexing (OFDM) system phase compensation
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