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"Performance Evaluation of Smart Antenna for BroadbandWireless Communication System"

Nidhi Jaina, R.P.Yadavb'Research Scholar, "Professor & HOD, MNIT

Department of Electronics & Communication EngineeringNIMS University; Jaipur (Rajasthan)

Email: nidhi651985jain@gmail.com.rpyadav@yahoo.com

. Abstract

Smart . Antenna greatly influences theperformance of broadband wirelesscommunicationSystems.Spatial Multiplexingtechnique in smart antenna increases theperformance of broadband wireless systems.Smart antenna technology provides rangeextension, increased data rate, highernetwork capacity and better service quality.In this paper, we present a Broadband smartantenna whichpoints its main beam towardsdesired directionof the array and suppressesinterference and noise coming from otherthan look direction of the array. The DOAestimation algorithmscan use the signal spacederived by spectral spatial smoothing toestimate the DOAof the received signals andthe DOA based beamformiIig algorithmsgenerate the weightingvector to mitigate themultipath fading, increase the diversity gain,and suppress the co-channel interference ofdifferent devices. Finally simulation resultsshowthe suppressioncapabilities of the smartantenna. The future research and applicationon broadband smart antenna systems arebriefly indicated.

1. Introduction

In today's mobile communication systems radiofrequency spectrum is a limited resource. One of themajor probl~ of future mobile communicationsystem is the rapid increase in the demand fordifferent broadband services and applications. Toovercome this limitation considerable research isgoing on to use the given frequency bands as efficientas possible. The deployment of smart antennas is oneway to increase spectrum efficiency in mobile

communication systems. Two or more users can be ,served at the same frequency, time and code which.directly lead to an increase in capacity.

Despite the advantages of wireless access, thereremain a number of critical issues to be resolvedbefore Broadband wireless system can successfullypenetrate the market. The chief concerns arespectrum efficiency, network scalability, self-installable directional anteIU1as,and reliable non-lineof sight operation. Smart antennas (SA) offer apowerful tool to address these problems.

An Antenna is smart only when it can recognize andtrack the signal of a particular mobile telephonewhile suppressing interfering signals [2-4]. A smartantenna is a digital wireless communications antennasystem that takes advantage of diversity effect at thesource (transmitter), the destination (receiver), orboth [I]. Diversity effect involves the transmissionand/or reception of multiple radio .frequency (RF)waves to increase data speed and reduce the errorrate.

Due to the actual need for increasing channelcapacity, the required bandwidth is becoming widerand wider. which brings significant deteriorates ofthe narrowband smart antenna systems because theinter-element phase shift becomes a function offre.quency while the adaption weights are keptindependent of frequency [5]. The narrowband smartantenna system is therefore not able to follow thefrequency variation of the incident signals. In otherwords. the narrowband weighting scheme isimpossible to handle broadband signals. To improvethe performance, the adaptation should take intoaccount the frequency dependence of inter-elementphase sbift. The processing behind each element mustbe able to provide a weight that varies withfrequency.

In the following sections we will discussconfiguration of smart antenna system in section II.Then direction of arrival and Broadband

beamfonning algorithm is explained in scetion Ill.The performance of these techniques is given bysimulation in section IV. In the end, conclusion andfuture \vork are given in section V.

2. Configuration of Broadband SmartAntenna System:

A Smart antenna consists or an antenna array or ~i

clements, a Radio ullit, a bemnforming network (lnd asignal processing unit. The radio unit consists of Ndown converters corresponding to N array clementsand an analog to digital conversion (A DC). The downeonvertcrs take the RF signal received at thecorresponding antcnna clements and convert thesignals to baseband, then send them to the ADC todigitize it before sending them further to the signalprocessing unit and beam forming network.

Broadband signals usc ,1 combination of spatialfiltering with temporal filtering on each branch of the<lrray. [6]. The desired angle and f-l"CCluencycharacteristic of lhe array are the key de'iignparameters of the bcamformer. The undcsircdf-i.cquellcy characteristic of the l1ntcnna elements canbe compensated by the bealllforlllcr. Theconfiguration of it is given in Fig.l.

With regard to spati31 filtering, the signals receivedby the individual antcnna clements ,1rc multiplied byweights. For timc processing. (l tapped-delay-line(TDL) is used 011 each elcment of the array. The TDLallows each element to have a pha~c response thatvaries with frequency, compensating for the fact thatlower frequency signal components have less phaseshift for a given propagation distance, whereas higherfrequency components have greater phase sl1iH asthey travel the same length 1)-81.

Fig. I Space~tilllc signal processor

the impinging waves arc used to synthesi;r.e heamsstcered at the \vanted signill with nulls dirccted toother co-channel users. The DOA estimation is a keyclement in our smart antenna processing scheme. Theresults of DOA estimalion arc thcn uscd by the arrayto design the adaptive bC<lmformcr, which is used tomaximize the pO\ver radiatcJ tmvards users 15J. As aresult. we can infer tll"t a successful design of anad<lplive array depends hi.~-~.hlyon the performance ofthe DO,:\ algorithm.

The core of the Slll,lrt antellll(\ is the selection of thesmart algorithms. Using cach algorithm we can adjustthe weights of the J.l1tenna arrays to form certainamount of adaptive beams to track cOITespondingusers automatically. An adaptive bcamrol"mer,consists of multiple antennas; complex weights. thefunction of which is to amplify (or attclluate) anddelay the signals from each antenna element: and asummer to add all of the processed sign"i1s. ill orelerto tunc out the signals not of interest. 'whileenhancing the signal of interest. Hence, be<lmforming,is sometimes referred to [~..> spatial filtering. sinccsome incoming signals frem certain spatial dircctionsarc 'filtered ouL while others arc amplificd. Theoutput response of the uniform linctlr array is givenby:

where w is the complex weights vector and x is thereceived signal vector givcn in [9]. The complex\veights vector W is obtained using a tapped delaylinc processing for an J.,j'vlS array algorithm. Thealgorithm updates the weights at each iteration byestimating the gradient of the quadratic surface andthen moving the weights ill t.he ncgative direction ofthe gradient hy a small 8.mOUl1t. The COllst"nt thatdetermines this amount is called step si:ze. \Vhcn thisstcp size is small, process leads these estimatedweights to the optimal weights.

Consider a four clemcnt adaptivc array using theLi'vlS algorithm to provide the adaptive weightadjustments. If \\1 is the colul1ln vector of arrayweights, R~~is lhe corrclation matrix of input signalsto each adaptive weight ilnd rxd is the cross-correlation vector betwcen the rcceived signal vt'ctorx(t) and the rcferenc.e signal d(t).

3. DirectiolJ of arrival andbeamforming Algorithm:

Spatial reference beam forming mayembedded training sequences. Instead.

Bl'Oadband

not usc ofthe f)OA of

Thc~ oplimum ilrl"aY we:zbt vector tl1<\tI::{(~-(t)}.where

fXt) =, d(t) ... array OUlput

millillli;t.c

line employing realis just a time delayed

Consider the tapped delay\",eights and each signal xlt)version OfXl(t), it follows that

X,(t) ~ x,(1 - 1\)X](t) ~ x,(t - 21\)

XL(I) ~ x,lt - (1,-1 )l,]The implication of these constraints is that the arraypnttern has a unity response in the look direction.

from N=8 to n, l2, the performance of the systemImproves. This takcs thc form of sharper peaks andlowcr noise floor in the :lllgular spectrulll. FigAshows that the performance of thc snwrt antennasystem improves also when the spacing betwecll the

elcments in the sensor array :hanges from d Cc OJU 10

0.5 ), where A is the wave,ength of the carrier signal.

5. Simulation and performance evaluation:

In this section, we present the results of thesimulation. The simulation is bnsed on MATLAB.Fig.2 shows the spectrum for 2 users with no. ofclements in the sensor array is 1).. Here peaks showthe true direction ofnrrival signnl.

For the smart antenna structure three consccutiveantennas arc plact:d at a distance ;:, /2. It is alsoassumcd that cach antenna clement cOlltnins' ;r.crothermal noise and thcy arc un correlated with eachother Fig.::; shmvs the radiation p::Ittcrn of I.MSbeamforl1lcr algorithm. Ilcre main beam ste(:rcd to ,lOdegree and null steered to -30 degree/50 degree.

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To analyze the performance of the DOA algorithmwe compared in two cases. Fig 3 shows that when thcnumber of elemcnts in the sensor array is increased

The null is shown to provide an attcnU,llion ill exceedof 20 dB. Fig 6 shows the radiation response of Ihesmart antenna for various SNR levels. As the: SNR

- '.

increases increase in the llull depths arc also noted.Shallow nulling is seen for lower level ofSNR. Fig 7shows that using a large value for the adaptive stepsize i~....,0.00 I yields better results when compared to

a smaller step size ,14 - 0.000 1.

-25 oi---ll_._-'---_-'-_-' __ "- __L_-L_-'

20 ~o 5U 80 100 I:!O 140 160 100The Phase Angle III D~Gre8s

However, we have to point out that anumber of challenging problems remain unsolved.For example, lillIe attention has been paid to thelllutual coupling effect between the hro<ldb8nd smartantennas; it ll<1s a greatly negative effect on thebroadband beamforming. Be<.lmforming algorithmsrequire a lal'ge number of computations which 1118kcsit difficult for them to keep up with the high datarates of today's \virclcss systems. Furthermoresuccessful broadband wireless system need 10 bescalable, should have high spectrulll efficiency,should otTer high data rates and should be easy todeploy at the infrastructure and subscriber end. Smartantenna teclmology offers significant leverages toenable such features. The challenges arc 10 developand deliver a well designed broadband wirelesssystem that captures the capabilities of SAtechnology without s8crificing robustness, simplicityand cost.

7. Rcfcrcnces

6. Conclusions and Future work

Fig 6 Rndiation paltcrn for various SNR at 2A C;]lz

Fig '7AmI)' Beam paHel"il for different v,l!lIes ofad,lptivcstep size

II] S Al<l1110lltl, "A simple transmitter diversity wchnlljuc forwir(.less cOllllllunic,ltIOIlS" nEE .Jownaf 011 Selected Areos illCOl!/llIlIlIICallOl1S ( Spccial Issuc on Sirm11 Processing I()r WifC'leSSCOlllll1l1llic8tlOl1st Oct, 1()9S, vol. 16, ilO, 0. PI' 1451 ..;';121 R.T.Compton, Ad,lpll\'e Antcnll,ls: Concepts ,1I1d perforlllancc.En['Jewood clins, N.l: Prcl1\1s ..l.lall, )C)SS[3] Xin llllang, "Smart AlltenllllS t{)r il1lclll['.l'nt Trililsporl<ltillilSyslcms". ITS Tciccommlinicati(\lls Proccedings, 7.()OG 6':'Interna110nal ContcrCIlCC 011, pp. 47.6-47.9, .rulle :'.lJ0614J LOl.ano ,1\, Goldsmith i\. V£llel1zLlcla I{. A, Lil~Wll1S 1\1. t\,Gcsbert D "Advances in Slmlli Antennas" \VlfckssComlllunication, IEEE, vol.)]. rp. ().7, Aug7.006l5] L,1I C Godarn. Applie:ltiol1 or <lntcnn<l arrays to mohileeommllniclltions, Par! 11, J3eam-formillg ,lIld Dircclion oj" ,Irriv(liCOllsidcmtiolls," proe. OClhl' IEEE, 1'01 :-;5. no R. augusl jl)'r!161 i\1 GIWVllllli, "\Vlclcball(' Smart Anto:nml ThL'()I"y usingRectangular ArI',lY StI'LlCIUrL's", If-=:EI;Trans, On Sit: .. I'roc., \"ol)()pr, ? I,n ..~ I;; I Serl. 7.00:?["71 .i\rtlgY~lS\\'.lll1l .I. Paulraj. "Sprlce-time processing for \\'irckssC()IllIllUllicnliolls" IEFE Signal Proccs ....ing Mllr,a:.-.illc. I'()j )4, pp'19...'0. Nov 1')9-;In S SJCOIl, V.Wang. Y.()i:\l1, alld T.ltolL 'A NI1\L.1 SllI,lr(Antl'lll1U SYSI,'1ll IIllpiclllL'll1<ltiOll 11.,1' r1rnad.I-1~lI1d \l,,'il.d..: .....sCOll1ll1ullie,ltions." IEEI::: Tr,lIlS 011 Allt. And Prop _ \'nl ::ill No,S.M:J~'2007..!9.1 Lal C Godur,L "Iimiwtion ,1I1d capahtlitics of dirCclitlll of

~lITi\"llle ....tim,ltinn techniques using ,111,UT<lYor AntcIlIWS. /\ mobileCOI1l\ll\lllicatlLln pcrsp..:etl\"1.'

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The performance of an smart antenna forbroadband applications W,YS invcstigmcd. Thebcamfonning properties and the behavior ofthe meansquare error we're investigated. The bC31lllormingalgorithm was then performed on the incomingsignals \vith vnriolls SNR levels. Deep llulling of theinterfcrcnce had been observed for differentfrequency in the band (L6 2.56] GHz for all SNRlevels. It was also noted that as the SNR increased,the deeper the nulling would be. The mean squareerror of both the smart antenna was not the same forboth cases. As expected the MSE decreased v.lithincrease the SNR of the channel.

"Performance Evaluation of Smart Antenna for BroadbandWireless Communication System"

. Nidhi Jain", R.P.Yadavb

'Research Scholar, "professor & HOD, MNITDepal1ment of Electronics & Communication Engineering

NIMS University;Jaipur (Rajasthan)Email: nidhi65l985jain@gmaiLcom.rpyadav@yahoo.com

Abstract

Smart Antenna greatly influences theperformance of broadband wirelesscommunication Systems. Spatial Multiplexingtechnique in smart antenna increases theperformance of broadband wireless systems.~mart antenna technology provides rangeextension, increased data rate, highernetwork capacity and better service quality.In this paper, we present a Broadband smartantenna which points its main beam towardsdesired direction of the array and suppressesinterference and noise coming from otherthan look direction of the array. The DOAestimation algorithms can use the .signal spacederived by spectral spatial smoothing toestimate the DOA of the received signals andthe DOA based beamforming algorithms.generate the weighting vector to mitigate themultipath fading, increase the diversity gain,and suppress the co-channel interference ofdifferent devices. Finally simulation resultsshow the suppression capabilities of the smartantenna. The future research and applicationon broadband smart antenna systems arebriefly indicated.

1. Introduction

In loday's mobile communication systems radiofrequency spectrum is a limited resource. One of themajor problems of future mobile communicationsystem is the rapid increase in the demand. fordifferent broadband services and applications. Toovercome this limitation considerable research isgoing on to use the given frequency bands as efficientas possible. The deployment of smart antennas is oneway to increase spectrum efficiency in mobile

communication systems. Two or more users can be'served at the same frequency, time and code whichdirectly lead to an increase in capacily.

Despite the advantages of wireless access, there!remain a number of critical issues to be resolved:before Broadband wireless system can successfully'penetrate the market. The chief concerns are i

spectrum efficiency, network scalability, self-installable directional antennas, and reliable non-lineof sight operation. Smart antennas (SA) offer apowerful tool to address these problems. I

An Antenna is smart only when it can recognize andtrack the signal of a particular mobile telephonewhile suppressing interfering signals [2-4]. A smartantenna is a digital wireless communications antenna;system that takes advantage of diversity effect at the'source (transmitter), the destination (receiver), or;both [I]. Diversity effect involves the transmission;and/or reception of multiple radio frequency (RF)I'waves to increase data speed and reduce the errorrate.

Due to the actual need for increasing channelcapacity, the required bandwidth is becoming widerand wider, which brings significant deteriorates ofthe narrowband smart antenna systems because theinter-element phase shift becomes a function offrequency while the. adaption weights are keptindependent of frequency [5]. The narrowband smartantenna system is therefore not able to follow thefrequency variation of the incident signals. In othe1words, the narrowband weighting scheme isimpossible to handle broadband signals. To improve!the performance, the adaptation should take into'account the frequency dependeoce of ioter-elementphase shift. The processiog behiod each element mustbe able to provide a weight that varies withfrequency.

In the following sections we will discussconfiguration of smart antenna system in section II.Then direction of arrival and Broadband

•

bC<llllforming algorithm is explained in section 1IJ.The pcrfonmHlcc of these techniques is given bysimulation in section IV. ]11 the enu, conclusion ,11ld

future work arc given in section V.

2. Configuration of Broadbaud SmartAntenna System:

;\ Smart antenna consists of an antenna array of Nclelllents, a Radio unit, a beal11forrning network and asignal processing unit. The radio unit consists of Ndown conveners corresponding to N array clementsand all analog to digital conversion (ADC). The dO\vnconverters takc the RF signal received m thecorresponding antenna clcmepts and convert theSigll.11s to baseband, then send them La the ADC todigitize it before sending them fUl1hcr to the signalprocessing unit and bcamforrning network.

Broadband signals usc a combin<ltioll of spali<llfiltering with temporal filtering on each branch of thearray. [6]. The desired angle and tl"cquencycharacteristic of the array arc the key dcsignparametcrs of thc beamformer. The undesiredfrequcncy characteristic of thc antcnna clemcnts canbc compcnsated by the bcalllformcr. Theconfiguration orit is given in Fig.l.

the impinging W<lves <lrc L1sed to synthcsi7.c beamssteered at the wanted signal with nulls directed toother co-ch<'lnllel users. The DOA estimation is a keyclement in our smarl antellna processing scheme. Theresults of DO/\ estimation are then used by the :1rr<1Yto design the <ldaptive beam former. \vhich is used tomaximize the powa r<ldiated towards users 1"5]. :\s aresult, we can infer that <I successful design of <llladaptive array depends highly on the perfonll,lllce ofthe 00/\ algorithm.

The core of the smart antenna is the selection of thesmart al2,orithms. Using each algorithm we can mULIstthe weights of the antellna arrays to form certain<llllOUllt or adaptive bC;lI11S to tracK correspondingusers aUl\)lllatically. An adaptive bcamfot"lner,consists of multiplc antenn<lS; complex weights, thefunction of which is to mnplify (or <lttenuatc) anddelay' thc signals fl'ol11 each antenna elemcnt; and aSUlllmcr (0 add all of the processed signals, in orderto tunc out the signals not of interest. whileenh<lIlCing the signal of interest. Hence, bealllformingis sometimes referred to as spatial filtering, sincesome incoming signals from certain spatial directionsarc f-iltcred out, while others arc amplified. Theoutput response of the uniform linear array is givenby:

Fig.l Spacc-timc signnl proccssor

With rcgnrd to spatial filtering, the signals receivedby the individual antenna e1emcnts arc multiplied byweights. For time proc'cssing, a tappcd~delay~line(TDL) is used on each element of the array. The TDLallows cach clement to have a phase response thatvaries with frequcncy, compensating for the fact thatlower frcquency signal componcnts have less phascshift for a given propagation distance, whereas higherhequcncy componcnts havc grcatcr phasc shift asthcy tr<lve! the samc Icngth ["7~S].

,'en) ~ \V"x(n)

Considcr a four clcment adaptive array using theLMS algorithm to provide the adaptive weight<1djusllncnls. If W is the column vector of <11"1',IYweights. H~" is the correlation matrix of input signalsto c:lch (ld<lptivc weight and r:<d is the cr055-correlation vec,tor betwct'n the received signal vcClorxC!) alld the '.cfcrellcc signal del).

where w is the complex weights vector and x is therecei vcd signal vector given in [0]. The complexweights vector W is obtained llsing a tapped delaylinc processing for an L-MS array <llgorithm. Thealgorithm upd<l1e~ the weights at eReil iteration byestimating the gradient of the quadratic surface <lndthen moving the weights in the ncgCltivc direction ofthe gr,H.licnt by a Slll<ll! amount. The constant thntdctermines this amount is called step size. When thisstep si;.-:c is small, process leads thcse estimatedlVl:ights t(,tllc optimal wcigllts.

3. Direction of arrival "ndhcamforming Algorithm:

Spatial refercncc beam forming lllaycmbedded training scqucnces. Instead,

Broadband

not lISC ofthe DOA of

The optimum <lITay weight vector thatEf(~(t)}, whcre

('(t) '0 d(l) _.array outpu!

11lInllllPT

•

•

Consider the tapped delay line employing r(:a\weights and each signal x/t) is just a time del8ycdversion ofAI(t). it follows that

X,(t) ~ Xl(t - _I)X.;(t) ~ Xl(t - 26)

XL(t) ~ xilt (L-I )6]The impJicmion of these constraints is that the arraypattern has a unity response in the look direction.

s. Simulation and performance evaluation:

In this section. we present the results of thesimulation. The simulation is nascd on MATLAB.fig.2 shows the spectrum for 2 users with 110. ofclements in the sensor array is 1\. Here peaks showthe true direction of(\rrival signal.

from N=8 10 1\1=12, the pcrJormance of the systemImproves. This takes the form of sharper pe8ks andlower noise noar in the <lnguI8l" spectrum. Fig.4shows that the performance of the sllwrl antennasystem improves also whell the spacing betwcen the

clements in the sensor array changes from d ;. OA)' 10

0.5 ;l where ,,\ is the wavelength of thc carrier sign<ll.

For the smart antenna structure three consccutiveantcllnas arc placed at a C::stancc ".l /2. It is alsoassumed that each nntcL,13 clement contains 7.erothermal noise and they are ullcorrel<lted with eaehother Fig.:) shows the radiation paltl..'CIl of i}v1SbC<lmlormcr algorithm. I Jere main beam steered to 40degree and null steered to -30 degree/50 de-gree.

-50

20 .10 60 00 10G 120 1.10 1GCl 180The Ph~se An91e In DegreeS

Fig.2. Spectrum for 2 users with IlUlllbcr ofclcl1lcnts is 4

1:'lg.3. Spcctnllll for dilTcrClll vnlllcs nfnumber of01elllcills

To analyze the performance of the 00;\ nlgorithmwe compared in two C(lses. Fig J shows that when thenumber of clements in the sensor array is inerc,lscd

Fig 4 sp(;ctrum lor different val lies of inter-element sp,lcing

.1;0 -_. ~-\O-- -iii w no i"O 140 1W 1::0T!"Ph"cf'C\:jc "D.-or''''

Fig 5 !{adiutioll pattern for lx:ami'ofmer <llgoritl\111

The llull is shown to provide an attenuation in exceedof 20 dB. rig 6 shows the adiation response of thesmart <lntcnna for variow- SNR kvels. ;\5 the SNR

•increases increase in the null depths arc also noted.SlwllO\v nulling is seen for lower level ofSNR. Fig 7shows that using a large value for the adaptive stepsize ,u 0.001 yields better results when compared toa smaller step size u .-0.000 1.

~ -5

..

0,;:.10

IT,

~ 1'.

z(: -2[1

However, we have to point out thai anumber of challenging problems remain unsolved.For example, little attention has heen paid to themutual coupling effect between the broadband smartantennas: it has'a greatly negative effect on thcbroadband beamforming. Beamforming algorithmsrequire a large llumber of computations which makcsit difficult for thcm to keep up with the high dataratcs of today's wireless sy~.;tCl1ls. Furthermoresuccessful broadband wireless system need to hescalable, should have high spectrum cflicicllcy .should offer high data rates and should be casy todeploy at the infi-astruclurc and subscriber end. Smartantcnna technology offers significant Icverages 10enable such fcZltures. The challenges an: to developand deliver CI \Veil designed brorldbrlnd wirelesssvstCl11 that captures the eapabi] ities of SAtechnology without sacrificing robustness, simplicityand cost.

.~5o 20 40 60 00 100 120 140 150 18[1The r-hase .A~91e In DBgr~es 7. References

Fig 6 Rndiation paltel"l1 I'or various SNR ,II 7..4 GI [7.

Fig 7 Array J3cam palkrn fl.)!"different values ol'aclaptivestep size

6. Conclusions and Future work

The performance of an smart antellna forbroadband applications was il1vcstigmcd. 'rhebcamfonning properties cl11d the behavior of the meansquare error were investigated. The bcalllfortllingalgorithm 'vva~.;then performed on the incomingsignals with various SNR levels. Deep nulling of theinterfercnce had been observed for di f!crcntfrequency in the band 1.1.6 2.561 GHz for all SNRlevels. It was also noted that as the SNR increased.the deeper the nulling would be. The mC<ltl squareerror of both the smart antenna was not the saine fl1rboth cases. As expectcd the MSE decreased withincrease the SNR of the channel.

[I] S. 1\Lll1louti. "A simple transmillcr JI\'crsily techniquc forwirckss cOIllIllLlnlc,lllons", Ib"LI.::: ./rJ1lI"1I0! (J1l S'cfecled Areas ill

COJllm1lnications ( SPCCi,11 Issue 011 'SIgnal Proecs~il1U t{)r \VlrckssCOllllllunicalions).Ocl. 19%, yol. I (J. no, 8, pp. 1'151-8.[2] RT Compton, 1\dapli\'c Antennas: Concepts and rcrforll1"-l1ce1~ll!:tlewood eliiTs. N.I, I'rl'nlis--!"bll, 19K8[3] Xin llmng, "Sllwrl Antennas i(lr intellif.',clll TnlllspOrhlliollSystems"_ ITS TeleCOll1l11UniCillioils l'rl)eeedl[tgs 20(1C, 6'hIntcrn~lll(lnal Con1Cn.'11Cl' OIL pp. 426-429 . .Iune 2006[41 L07.,lIh) ./\" C;oldsmith 1\. ValcnZllcl<l R, A. 1,<-lgU~lliSI'vl i\.Gcsbcrt [) "i\dv,lIlces 111 Smart Antel1l1as" \:VirekssC()llll11Unication. II~l::E, vo1.13, pp. 6 .."1, Aug ;:006[5] Lui C Go{i<lr,l. Applicatloll of anlcnn~1 Ilrmys In 11l0blkCOllllllllllleatiolls. !',In II: Bcam,forming and Direction of "-I-rivetl(;(Insidn,lli{'IlS." prIll' Orlh", IEI:::E. vol 85. no B. <tlluuSI 19'-n[61 M. Gh,IVClI11I. "\\'idcband Snwrt Antl'11I1et Thcory L1sinuRect<lngLll:lr Array Structures". IEEE Trans. On SiS l'roc., vol.SO.pp. 2143.-2151. Scpt. 7,002.[7] Ar()gyaS\\~lmi .I, PClulra.l "Spacc-time processing I'm \\,ireksscommllllicniinns" IEEI~ Signal Processing Magazinc. vol I d. i'P49 ..B3, Nov 1IN"I.[XI 5.S .len:l, Y,V/ung. Y.C)i<ll1. alld '1'.11011. "A l\'ovei SllwrtAntel1na Svskrn lmpll'mcntanon i(lr 13romJ.I3aml \Vlrl'k~sCommunicalton:.," IEEE Tran~, 011 Ant And Prop._ \'nl. ::i0. No,).M:1Y::OO).[9] l.al C Godant, "limitalion and capahililics of dirc('tlOll or

arri\al eSlill1,,-tlonlechlllqucs using an IlrTay ()r Anlel1llils' /\ llIobikCOl11lTIUl1lCallOIlperspCctivl'