simplified training pattern for mimo-ofdm ch estimation technology

8/7/2019 simplified training pattern for MIMO-OFDM Ch estimation technology

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Inernaional Coerence on Compuer Applicaion and Syem Modeling ICCA

A mpld Tr Pttr for MIMO-OFDM Cl Estmto Tcoloy

Wang Zhe/Bai anInstitution ofElectronic and Information Engineering

Lanzhou iaotong UniversityLanzhou, China

e-mail: [email protected]

bstact k f f OOF fz However, f k f p p

f pp pp p pv pf f p p v ' p p pf f p k p pp v f OFDM p f k

Keywods channel estimation ;taining sequence

NTRODUCTIONFuture mobile wireless communication systems will

require high-bit-rate technologies. Orhogonal equencydivision multiplexing (OFDM) is a novel technique thatdivides entire channel into many narrow parallel subchannels, so that it improves data rate and avoids intersymbol interference (ISI) caused by multi-path propagation.Multi-input multi-output(MIMO) system uses multipleantennas at both sides to increase capacity of wirelesschannel without the need of extra bandwidth. These twotechniques can be used together to both improve capacityand quality of wireless communication systems.

In MIMO-OFDM systems, channel state information(CSI ) is required for Space-Time decoding. Various channelestimation methods for OFDM systems have been reportedin [ ]-[3]. In [ ], least squares (S) estimator and minimummean squared error (MMSE) channel estimator only basedon time-domain channel statistics have been described. Thecomplexity ofMMSE estimator is higher than the Sestimator, but the performance of that is better as the use ofchannel statistics. In [2], linear minimum mean squared error(LMMSE) channel estimator which only based on frequencycorrelation of channel has been proposed, which use Sestimation as the rough estimation. And the optimal low-rankestimator based on singular-value decomposition (SVD ) wasalso derived in [2] to reduce the complexity of LMMSEestimator. The robust channel estimation for OFDM systemsbased on both time-domain and equency-domaincorrelation of channel is proposed in [3]. However, in themulti-antenna systems the signal on the receiver is the

Jiang ZhanjunNational Mobil Communications Research Lab

South ast UniversityNanjing, China

e-mail: [email protected]

overlap of the signals om each transmitting antenna,channel estimators based on OFDM system can not be usedin the MIMO-OFDM system directly. Then many channelestimation methods for MIMO-OFDM systems weredeveloped in [4]-[10. In [4], the LS estimator for OFDMsystem with transmitting diversi based on the robustestimation presented in [3] was proposed. Because a largematrix inversion is needed in this method, the simpliedmethod for that estimator was presented in [5] by avoidinglarge matrix inversion. And many researches on blind andsemi-blind channel estimator was proposed in [6], [7].However, the complexity of the blind and semi-blindestimators is substantially high. In recent years, there aresome researches on improving estimator performance byimproving the training patte. Some design methods ofoptimal training sequences proposed in [4], 5], [8]. And thetransmitting patte of training sequence can also be changedto improve the performance of channel estimator. In [9], amethod to transmit all the training symbols cyclically at each

antenna can avoid the limitation caused by transmitting sametraining sequence at same antenna. In [10], the lowcomplexity channel estimation for MIMO-OFDM systembased on STBC training sequences was proposed. Althoughthe low complexity channel estimator presented in [10] isreduced the complexi for the system with two transmittingantennas, when the method used in some systems with moretransmitting antennas, more OFDM periods will be neededfor transmitting training blocks. In this paper, we propose asimplied ansmitting patte of training blocks for systemwith four transmitting antennas, which can save four OFDMperiods and ensure the estimator performance.

II. YSTEM ODEL

Consider the fading multi-path channel model, which isostitud b pth d th t-din rese of thchannel is

(1 )

where 7, is the delay of the th path, a, (t) is thecorresponding complex amplitude, and due to motion of thevehicle, it is modeled to be wide-sense stationarynarrowband complex Gaussian processes, and it isindependent for different paths. For alls, a, (t) has the samenormalized time correlation nction and dierent average

powers .

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Inernaional Coerence on Compuer Applicaion and Syem Modeling ICCASM

Consider the MIMO-OFM system shown in Fig. ,where a data block is encoded by ST encoder and transmittedinto two parallel OFDM blocks of baseband QKconstellation symbols. A cyclic prex is used for eachOFM branch to preserve orthogonality of the sub-carriersand eliminate the inter-symbol interference betweenconsecutive OFDM symbols. The number of sub-carriers is The length of the cyclic prex must be larger than thedelay spread of channel.

At data transmitting time n, data blockb[n, k]:k= 0, ,"', N is encoded into two signalss i[n, k]:k= O,"", N- for=, 2. The to signals are

transmitted by two dierent antennas simultaneously aermodulating of OFDM, and the OFDM demodulation ofreceived signal at each receiving antenna is the superpositionof the two distorted transmitted signals. The equencyresponse of channel for OFDM system can be expressed as

L-lH[n, k]=h[l]F:; (2)=0

where h[l]= h(r= DJ, t =1 N , and is the spacingof the sub-carrier. D is the delay spread of the th pathsampled by the rate of / t , and L is the number of paths.And F = exp( 2J / N) .

Hence, the received signal at the th receiver can beexpressed as

2r)n, k]=H,nk]s,[nk]+)nk] (3)i=l

where Hij [nk] is the channel equency response beteentheth transmitting antenna and the th receiving antenna forthe h sub-carrier at time n. Assuming that signalstransmitted through dierent antennas and received bydierent antennas undergo independent fades. )nk] is theadditive complex Gaussian noise on the th receiving antenna

with the zero-mean and the variance is . For dierent s,s ands )nk] is uncorrelated.

The index denotes dierent receiving antennas will beomitted om rj [nk] H [n k] and )n, k] in the followingfor brie The matrix form of received signal is as

r[n]=S[n] +[n] (4)

Figure I MIMO-OFDM system with two transmitting antennas

where [ ]=([n0].r[ n,N_] )T ; S[n]=(l [n], s [n] ) ,where si[n]= diag{s i[n, O], ., s i[n, N; = [Hl'H2f

where Hi=

(Hi[0]. Hi[N _

])

Tl[n]=([n,O]",[n,N_1])7.

III. IMPLIFIED RANSMITTING ATTERN ASED ONSTBC RAINING LOC

A Traditional LS and LMMSE Estimator for OFDMsystemFor OFDM system, the LS estimator can be expressed as

HS=X[nrlY[n] (5)where X{x[n,],x[n,I]" ,x[n,N-I denotes thetransmitted trag block,

Y=( y[n, O],y[n, I],. ",y[n,N_I] )Tdenotes the receivedsignal.

The LMMSE estimator for OFDM system can beexpressed as

where

= { HH}

= E{H }

(6)

where HLS is the LS estimate of channel equency response,and X{x[n,],x[n,I], . ,x[n,N-I is the trainingblock. is the variance of the additive complex Gaussiannoise. is the auto-covariance matrix of channel

equency response

Simpled Transmitting Pattern of training blockforsystem with four transmitting antennasWhen the STBC training patte applied in systems with

four transmitting antennas, the training block is given by

T 7 T-T -T7-7 T-T T

=-T-7 T

(7)T T T* T* 2 3

-T' * -T4* *3-7' T* * -T-T' 7* T* *

Hence, eight OFM periods will be needed to transmittraining sequences, and assume that the channel is quasixed over eight OFDM periods. More resources are wasted

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for transmitting training sequences, and the assumption is notreasonable. We can transmit training blocks according to thefollowing patte shown in g. 2.

At training time n transmiting antennas tl and t3transmit the rst group of training sequence and , thetransmitting antennas t2 and t4 do not transmit any data. Atthe time n +1 , tz and t4 transmit the rst group of trainingsequence Tz and T4 tl and t3do not ansmit any dataThen at time n +2 , tl and t3transmit the second group oftraining sequence T3 and ' , tz and t4 do not ansmitany data. At the last training time n +3 , t2 and t4 ansmitthe second group of training sequence T4*and T tl andt3do not transmit any data. The received signal can beexpressed as

where

( [n] ) HI ( [n] )[n+] 13H3+ [n+]( [n+1])=Z4( H2)+([n + ])[n+] H4 [n+]

(8)

(9)

Then we can see that the transmission of training blocksis completed only in four OFM periods, and the estimationmethod used in systems with two transmitting antennas canbe applied as following

C1 1 ( [n] ) HI 1 ( [n] ) (10) = 3n+ = +3n+(Cz)=.TZ4 ( r[n +1])=( Hz)+.TZ4 ( l[n+1]) (11)C4 2 [n+] H4 2 [n+]

where Ci=(cJO]ci[].cJN ] for i=I,2,3,4. It isobviously thatC1 Cz C3and C4 is the LS estimation of

HI Hz H3and H4 respectively.

Figure 2. simplified transmiting patte of training blocks

From (6) we acquired the LMMS estimation ofHi fori=1,2,3,4as following

(12 )

IV. IMULATION ESULTS

In the simulation we consider a system with fourtransmitting antennas and four receiving antennas. Thechannels between dierent transmitting antennas andreceiving antennas are independent, but have the samestatistic characteristic. The simulation results are acquiredunder typical urban (TU) and hilly terrain (HT ) delayproles respectively. The bandwidth for OFM system is500 kHz, divided into 64 sub-carriers and the total symbolperiod is 138Js , where 10 Js is the cyclic prex. Four-stateST trellis code is used to encode the data block.

Figs. 3 and Fig. 4show the MS of channel estimatorwith the old patte and the simplied training patteproposed here under TU and HT delay proles respectively.

From the simulation results we can see that the MS ofestimator with simplied transmitting patter of trainingblocks is almost equal to that of estimator with old patteunder low SNR. With the rise of SN the performance ofestimator with simplied patte gets better than the old one.And note that the estimator with simplied patte can savefour OFM periods for transmitting training blocks, and thecomplexity of estimator can also be reduced The efciencyof the estimator with simplied patte is higher than the oldone.

V. ONCLUSIONSIn this paper OFM system with multi-antennas is

studied. The estimator for channel parameter based on STBCtraining block is discussed. Through theoretical analysis, theSTBC estimator plays a good performance in systems withtwo transmitting antennas. However when it is used insystems with four transmitting antennas, the aining blockstake up more bandwidth resources, the efcient of system isdecreased. We propose a simplied transmitting patte oftraining blocks for the system with four transmittingantennas. The simplied patte saves four OFM periods totransmitting training blocks, and improves the eciency ofthe system. Finally, computer simulation results prove thatthe system with the simplied patte has almost equal

performance with the old one under low SNR, and has betterprformnce unde high SNR

CNOWLEDGNT

This work is suppored by the open research nd ofnational mobile communications research laboratory ofSoutheast University.

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-smCMMsE - -------,- NEWSTBC-MMSE() I - - - -l-

_____ ___________ _____ ____

I I I----- ----- ------ ----- -----

104 5L1O1L5-2O25-"WNR DBFigure 3. MSE of channel estimators under TU delay profile

= = = : STBCMMSE(H- - - - -

T- I -" NEW STBC-MMSE(H

! J T r '

L j 1 "

04 51O152O25WSNR in DBFigure 4. MSE of channel estimators under HT delay profile

[]

[2]

EFERENCES

1.-. Van de Beek, O. Edfors, M. Sandel, S. . Wilson and P. O.Borjesson, "On channel estimation in OFDM systems, Proc. IEEE,vol. 2, July 1995, pp. 815819.

O. Edfors, M. Sandell, I.-J. Van de Beek, S. . Wilson and P. O.Borjesson, "OFDM channel estimtion by singular valuedecomposition, IEEE Trans. Commun., vol. 46, July 1996, pp. 923927.

[3] Y. Li, L. J. Cimini Jr and N. R. Sollenberger, "Robust channelestimation for OFDM systems with rapid dispersive fading channels,IEEE Trans. Commun., vol. 46, July 1998, pp. 902915.

[4] Y. Li and N. Seshadri, "Channel estimation for OFDM systems withtransmitter diversity in mobile wireless channels, IEEE J. Select.Areas Commun., vol. 17, Mar. 1999, pp. 461471.

[5] Y. Li, "Simplified channel estimation for OFDM systems with

multiple transmit antennas, IEEE Trans. Wireless Commun., vol. ,Jan. 2002, pp. 67-75.

[6] Z Liu, G. B. Giannakis, S. Barbarossa and A. Scaglione, "Transmitantennae spacetime block coding for generalized OFDM in thepresence of unknown multipath, IEEE J. Select. Areas Commun.,vol. 19, July 2001, pp. 13521364.

[7] Gaoping Hu and Dong Li, "A low complexity algorithm for channelestimation of MIMO OFDM system, Inteational conference onelectronic computer technology, IEEE Press, 2009, pp. 113-116,doi:.09ICECT.2009.8.

[8] Eugene Golovins and Neco Ventura, "Optimal training for the SMMIMO-OFDM systems with MMSE channel estimation,Communication Networks and Services Research Conference, IEEEPress, 2008, pp. 470477, doi:10.1109/CNSR.2008.57.

[9] Wu Jianhua, Li Zhihong and He Lihong, "Channel estimationalgorithms for broadband MIMO-OFDM systems, Inteational

Conference on Computer Science and Information Technology, IEEEPress, 2008, pp. 139-142, doi:10.1109/ICCSIT.2008.115.

[10] Gong Y and LetaieB, "Low complexity channel estimation forspace-time coded wideband OFDM systems, IEEE Transactions onWireless Communications, Sept. 2003, vol. 2, pp. 876-882,doi:10.1109TWC.2003.816797.

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simplified training pattern for mimo-ofdm ch estimation technology

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