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13th International Conference on Wireless Communications (Wireless 2001), July 2001.Calgary, Alberta, Canada

235

PERFORMANCE GAIN OF SMART ANTENNAS WITH DIVERSITYCOMBINING AT HANDSETS FOR THE 3GPP WCDMA SYSTEM

Suk Won Kim1, Dong Sam Ha1, and Jeong Ho Kim2

1VTVT (Virginia Tech VLSI for Telecommunications) LaboratoryDepartment of Electrical and Computer Engineering, Virginia Tech, Blacksburg, Virginia 24061 USA

2Next Generation Wireless Communication Research LaboratoryLG Electronics, Inc, Hogye-dong 533, Dongan-gu, Anyang-shi, Kyongki-do, Korea

Phone: +1-540-231-4942 Fax: +1-540-231-3362E-mail: [email protected], [email protected], and [email protected]

ABSTRACTIn this paper, we propose a dual smart antenna

system incorporated into handsets for the 3GPPWCDMA system, in which a diversity combinercombines the two rake receiver outputs using adiversity combining scheme. We considered threediversity combining schemes, selection diversity,square law combining, and equal gain combining(EGC), and two types of the channel model for thedual antenna signals, loosely correlated fadingchannel model (LCFCM) and spatially correlatedfading channel model (SCFCM). To obtain thechannel profile, we adopted a geometrically basedchannel model known as GBSB (geometricallybased single bounce) elliptical model in thesimulation. The simulation results indicate that i)the EGC scheme performs the best among the threediversity combining schemes and ii) as expected,the higher performance gain is achieved under theLCFCM than the SCFCM. The simulation resultsunder the two channel models are likely to be thelower and the upper bounds for the performancegain of the dual smart antenna system. Oursimulation results indicate that a dual smart antennasystem with diversity combining at handsets isbeneficial for the 3GPP WCDMA system.

I. INTRODUCTIONSmart antenna not only combats multipath

fading, but also suppresses interference signals.When spatial signal processing achieved throughsmart antenna is combined with temporal signalprocessing, the space-time processing can repairsignal impairments to result in a higher networkcapacity, coverage, and quality [1]. Whencompared with the conventional single antennasystem, a smart antenna system requires additionalantennas and circuitry to process multiple antennasignals. The additional antennas and circuitry resultin higher cost and more power consumption.

Smart antenna techniques have been consideredmostly for base stations so far [2],[3] because ofhigh system complexity and high powerconsumption. In addition, two (or multiple)antennas at a handset are in proximity, which mayreduce the effectiveness of the antenna system. Oneof the third generation wireless personalcommunication systems, 3GPP (third generationpartnership project) WCDMA (wideband codedivision multiple access) system [4], requiresantenna diversity at base stations and optionally atmobile stations [5]. The feasibility of implementingdual antennas at a mobile handset was investigatedin [6]. Due to the compact size and stringent cost ofhandsets and the limited battery capacity, smartantennas at handsets should have low circuitcomplexity and low power dissipation. To justifyemploying smart antenna techniques at handsets,the performance gain should be large enough tooffset the additional cost and power consumption.

Recently, the smart antenna technique has beenapplied to mobile stations [7]-[9]. For example, theHDR (high data rate) system of Qualcommemployed dual antennas at a mobile station [7].Each antenna signal is applied to its own rakereceiver followed by the maximal ratio diversitycombining, which combines the two rake receiversignals. A dual antenna system for handsets wasalso investigated for the digital European cordlesstelephone (DECT) system for the indoor radiochannel [8]. The dual antenna handset receiverselects one of two signals of the receivers based onthe signal-to-interference plus noise ratio (SINR).Each receiver processes a signal that is an equalgain combining of the signal from one antenna andthe phase-shifted signal from the other antenna.Wong and Cox proposed a dual antenna systemwhich could be applied to handheld devices as wellas base stations [9]. Summing the signals from twoantennas with proper weights in complex numberscancels the dominant interference and henceincreases the signal-to-interference ratio (SIR). To


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compute the antenna weights, a technique tooptimize the SIR was proposed. Unlike the abovetwo methods, the signal weighting and summingwas implemented at the radio frequency (RF) levelinstead of at the baseband signal level. Thus, itreduces the complexity of the receiver since itrequires only one baseband processor.

Smart antennas may employ two differentcombining schemes, diversity combining andadaptive combining. The diversity combiningscheme exploits the spatial diversity amongmultiple antenna signals. Thus, the diversitycombining achieves higher performance whenmultiple antenna signals are less correlated. Forinstance, if each antenna signal undergoesindependent fading, the diversity combing schemewould perform well. The adaptive combiningscheme adjusts the antenna weights dynamically toenhance the desired signal while suppressinginterference signals. Since the adaptive combiningscheme aims to add multiple antenna signalsconstructively, the scheme performs better forcorrelated antenna signals. Thus, if multipleantenna signals are exactly the same except thephase difference due to a nonzero angle of arrival,the adaptive combining achieves the highestperformance.

In [10], we showed that smart antennas with adiversity combining scheme at handsets for thecdma2000 system improve the performance(through reduction of the frame error rate) by from1.7 dB to as high as 12.7 dB depending on thecorrelation of the dual antenna signals. We alsoshowed that smart antennas with an adaptivecombining scheme at handsets for the cdma2000system improve the performance (through reductionof the frame error rate) by from 0.8 dB to 2.2 dBdepending on the mobile velocity [11].

In this paper, we propose a dual smart antennasystem incorporated into handsets for the 3GPPWCDMA system and present simulation results onthe performance gain for a diversity combining. Adiversity combiner combines the two rake receiveroutputs using a diversity combining scheme. Weconsider three diversity combining schemes, i)selection diversity (SD), ii) square law combining(SLC), and iii) equal gain combining (EGC). TheSD scheme selects the signal with higher power.The SLC scheme weights each signal by its signallevel and adds them according to the formula,

2222

||||

ba

bb

ba

aa

++

+, where a and b are

the two rake receiver outputs. The EGC schemesimply adds two signals with an equal weight of0.5. We consider two types of the channel model

for the dual antenna signals, i) loosely correlatedfading channel model (LCFCM) and ii) spatiallycorrelated fading channel model (SCFCM). In theLCFCM, each antenna signal is assumed to haveindependent Rayleigh fading. However, eachantenna signal in the SCFCM is subject to the sameRayleigh fading, and the two signals are differentonly in phase due to a nonzero angle of arrival. Achannel model with less correlated dual antennasignals, which is the LCFCM in our models, isexpected to yield higher diversity gain [12]. Webelieve that the actual channel of dual antennasignals lies in between these two channel models.To obtain the channel profile (such as delay,average power, and angle of arrival of eachmultipath signal), we adopted a geometrically basedchannel model known as GBSB (geometricallybased single bounce) elliptical model in oursimulation [13][14]. The GBSB elliptical model isapplicable for microcell environments found inurban areas.

The paper is organized as follows. The channelmodels employed for our simulation are presentedin Section 2. The 3GPP WCDMA system is brieflydescribed in Section 3. The system setup forsimulation and the simulation results are presentedin Section 4. Finally, Section 5 concludes the paper.

II. CHANNEL MODELBecause the channel model influences the

design of receivers and their performance, channelmodeling is important when evaluating a smartantenna system. In the uplink of the 3GPPWCDMA system, each user signal is transmittedasynchronously and traverses different paths from amobile station to the base station. Thus, the mainsource of interference is coming from other users’signals within the same cell (intra-cell interference).However, in the downlink of the 3GPP WCDMAsystem, the signal transmitted from the base stationis the superposition of all active users’ signals andcommon control signals. The desired user signaland multiple access interferences traverse the samepaths, but they are inherently orthogonal to eachother. So it dose not pose a serious problem athandsets. A multipath signal is effectively aninterference signal to another multipath signal.However, a rake receiver can manage multipathsignals to its advantage to improve theperformance. Another source of interference in thedownlink is coming from adjacent cells (inter-cellinterference), which can have a substantial impacton the performance. Note that the latter casebecomes manifest when the soft handover isoccurred. Since the number of adjacent base


237

stations and hence the number of interferencesignals from those base stations is small, a dualantenna system is a good candidate to combat suchinterference. It should be noted that a receiver withM antennas can suppress M-1 interferences [15].As to be described in Section 4, we consider theinterference from adjacent cells as additive whiteGaussian noises (AWGNs). Thus, only the diversity(rather than adaptive) combining technique wasconsidered to obtain the diversity gain at handsetsin our simulation.

We assume that the dual antennas at a handsetare identical, omnidirectional, and separated with aquarter wavelength of the carrier. For a wirelesschannel model, three components are consideredfor a typical variation in the received signal level[16]. The three components are mean path loss,lognormal fading (or slow fading), and Rayleighfading (or fast fading). Since the change of signallevel due to the lognormal fading is insignificantfor each simulation period, it is not included in ourchannel model. A channel model also shouldconsider spreads, i) delay spread due to multipathpropagation, ii) Doppler spread due to mobilemotion, and iii) angle spread due to scatterdistribution. In addition, we consider two types ofthe channel model specific to the dual antennasignals, i) loosely correlated fading channel model(LCFCM) and ii) spatially correlated fadingchannel model (SCFCM). The characteristics ofeach channel model are summarized in Table 1.

Table 1. Two Types of the Channel Model for aDual Antenna System

Channelmodel

Rayleighfading

Phasedifference

LCFCM Independent IndependentSCFCM Same Independent

Each antenna signal is assumed to haveindependent Rayleigh fading in the LCFCM. In theSCFCM, each antenna signal is subject to the sameRayleigh fading, but different in the phase due to anon-zero angle of arrival. A channel model withless correlated dual antenna signals, which is theLCFCM in our model, is expected to yield higherdiversity gain [12]. We believe that the actualchannel of dual antenna signals (for both thediversity combining and the adaptive combining)lies in between these two channel models.

It is assumed that a multipath signal has thesame arrival time for the two antennas in thechannel model. The two types of the channel modelare illustrated in Figure 1. The signal s(t) representsthe transmitted signal from the base station in the

figure, and signals r1(t) and r2(t) represent the tworeceived antenna signals at the mobile station.

(a) Loosely Correlated Fading Channel Model(LCFCM)

(b) Spatially Correlated Fading Channel Model(SCFCM)

Figure 1. Two Types of the Channel Model

To obtain the channel profile (such as delay,average power, and angle of arrival of eachmultipath signal), we adopted a geometrically basedchannel model known as GBSB (geometricallybased single bounce) elliptical model in oursimulation [13][14]. The GBSB elliptical model isapplicable for microcell environments found inurban areas. It is assumed in the GBSB ellipticalmodel that multipath signals are created by singlereflections of scatters which are uniformlydistributed in a predefined elliptical geometry.Delays, average power levels, and angles of arrival(AOAs) of each multipath signal are determinedfrom the locations of scatters.

In the GBSB elliptical model, a base station anda mobile station are assumed to locate at the foci of

Z-τ0

Rayleighfading

Rayleighfading

Z-τ1

Rayleighfading

Rayleighfading

Z-τ2

Rayleighfading

Rayleighfading

s(t)

r1(t)

r2(t)

Z-τ0

s(t)

Rayleighfading

Z-τ1Rayleigh

fading

Z-τ2Rayleigh

fading

r1(t)

r2(t)

e-jφ0

e-jφ1

e-jφ2


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an ellipse as shown in Figure 2. The two majorparameters of the model are D and τm. D is thedistance between a base station and a mobilestation, and τm is the maximum time of arrival(TOA), i.e. maximum delay. The maximum TOAτm is used to define the boundary (or a major axisand a minor axis) of the ellipse such that the majoraxis am = cτm/2, where c is the speed of light.Related equations with detailed derivationsincluding the joint TOA-AOA probability densityfunction at the mobile station are available in [14].Due to the symmetry of the geometry with respectto the base station and the mobile station, the jointTOA-AOA probability density function of themobile station is the same as that of the basestation.

Figure 2. Geometry of the GBSB Elliptical Model

The following procedure is used to obtain achannel profile in our simulation. A scatter isplaced randomly within a predefined ellipse. Thedistance rb between the base station and the scatterand the distance rs between the scatter and themobile station are obtained from the location of thescatter. The propagation delay τ is calculated as (rb

+ rs)/c. Then a new scatter is placed randomly andthe propagation delay calculated in the samemanner. If the difference between the newpropagation delay and any existing propagationdelay is greater than one chip delay (which is about260 ns for the 3GPP WCDMA system), then thescatter is selected. Otherwise, the scatter is deleted,as the multipath signal will not be processed by arake finger. The process repeats until a predefinednumber of multipaths (or scatters) is achieved. Theunit average power P0 is assigned to the multipathsignal with the smallest propagation delay τ0. Theaverage power of a multipath signal Pi, i ≠ 0 iscalculated using the mean pass loss model [16]such that Pi = P0 * (τi/τ0)

–n, where τi is thepropagation delay of the multipath and n is the pathloss exponent. We set n to 3.5 in our simulation.The AOA of each multipath signal is obtained fromthe location of the scatter and the mobile station.

Figure 3 illustrates a channel profile of fourmultipath signals obtained through the procedure

described above. The distance D was set to 800 mand the maximum delay τm to 32 chips(equivalently 8.3 µs) in the process. It is observedfrom the figure that the relative power level of othermultipath signals to the first multipath signal ismuch weaker.

(a) Power vs. Multipath Delay

(b) AOA vs. Multipath DelayFigure 3. Channel Profiles for the GBSB Elliptical

Model

III. 3GPP WCDMA SYSTEMThe code division multiple access (CDMA)

technology proliferates as the next generationwireless personal communication systems. Thereare two proposed wideband CDMA systems as thethird generation standard, which meet the ITU(International Telecommunication Union) IMT-2000 (International Mobile Telecommunications)requirements. The first one is the WCDMA(wideband CDMA) system often called ThirdGeneration Partnership Project (3GPP) [4]. Thesecond one is the cdma2000 system. There are twomodes for the radio access technologies for the3GPP WCDMA system, a TDD (time divisionduplex) mode and a FDD (frequency divisionduplex) mode. We consider the 3GPP WCDMA

D

rb

θb θs

base station mobile bm

am

scatterrs


239

system with the FDD mode in this paper. Hereafter,we call the 3GPP WCDMA system with the FDDmode as the 3GPP WCDMA system for brevity.

The block diagram of a downlink transmitterconsidered in our simulation is shown in Figure 4.Each bit of physical channels (PCH) is QPSK(quadriphase-shift keying) modulated. Themodulated I (in-phase) and Q (quadrature-phase)bits are channelized by multiplying OVSF(orthogonal variable spreading factor) codes at thechipping rate of 3.84 Mcps. All channelized signalsare combined first and then scrambled by acomplex long code, which is generated from theGold code set. The scrambled signal and theunscrambled signal of the synchronization channel(SCH) are combined together. The combined signalis pulse-shaped by a root-raised cosine FIR filterwith a roll-off factor of α = 0.22. The shaped signalis transmitted through the wireless channel.

Figure 4. Block Diagram of a DownlinkTransmitter

A receiver receives not only the signaltransmitted from the desired base station but alsothe signals from adjacent base stations. Thereceived signal is shaped back with the same root-raised cosine FIR filter. A rake receiver despreadsreceived multipath signals and coherently combinesthem. The coherent combining of multipath signalsnecessitates each multipath signal be multiplied bythe channel coefficient estimated from the despreadcommon pilot signal. To reduce the simulationtime, while considering various operatingconditions, we did not include the channel codingand decoding for the 3GPP WCDMA system in ourmodel.

IV. SIMULATION SETUP ANDRESULTS

A signal from a base station propagates throughthe channel. The two types of the channel modeldescribed in Section 2 are employed in thesimulation. The GBSB elliptical model is adoptedto generate the channel profile of multipath signals.The signals received at the dual antennas of a

handset are applied to their own rake receivers afterpulse shaped by an FIR filter as shown Figure 5. Adiversity combiner combines the two rake receiveroutputs. Three diversity combining schemes,selection diversity (SD) scheme, square-lawcombining (SLC) scheme, and equal gaincombining (EGC) scheme, were considered in oursimulation. In our simulation, the output of adiversity combiner is hard decided to either 1 or 0,and compared with the original data bits to evaluatethe system performance in terms of bit error rate(BER). For simplicity, we modeled the interferencefrom adjacent cells as additive white Gaussiannoises (AWGNs).

Figure 5. Dual Smart Antenna Receiver withDiversity Combiner

The environment considered in our simulation isas follows. The following model parameters calledbaseline parameters in this paper were assumed.The distance from the desired base station to themobile station is 800 m, and the maximummultipath delay is 32 chips in the GBSB ellipticalmodel. We also assumed that the mobile velocity is60 km/hr, which results in 119 Hz of Dopplerfrequency under 2.14 GHz of the carrier frequency,and the distance between two antennas is λ/4 (= 3.5cm). Eight users’ signals of the spreading factor 32and the common pilot (CPICH) signal arechannelized, combined, scrambled, pulse-shaped,and transmitted through the channel. 20% of thetotal transmitted power is allocated to the CPICH,and the remaining 80% of the power is dividedequally and allocated to each user signal. Fourmultipath signals with the channel profile obtainedfrom the GBSB elliptical model arrive at handsetantennas. A rake receiver with three rake fingers isconsidered at handsets.

The simulation results with three diversitycombining schemes and two types of the channelmodel are presented in Figure 6. Figure 6 (a) and(b) are the performance of the single and of the dualantenna systems under the SCFCM and theLCFCM, respectively. The y-axis of a plot is theBER, and the x-axis is the ratio of the symbol

FIR

filter

FIR

filter

Rakerx

Rakerx

SD/

SLC/

EGC

Data

AWGNs

FromTx

Σ FIR

filter

PCH1

PCHk

. . .

SCHS/P

S/P

OVSF1

OVSFk

Scramblecode

real or scalarcomplex orvector


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energy of the first multipath signal to the AWGN.The top graph in each plot is the BER of a singleantenna system. The second, the third, and thebottom graphs are the BERs of the dual antennasystem with SD, SLC, and EGC diversitycombining schemes, respectively. As can be seenfrom the two figures, the dual smart antenna systemalways performs better than a single antenna systemfor both channel models. For the dual smartantennas, the EGC performs the best among thethree diversity combining schemes. Theperformance of the dual smart antenna system withthe EGC diversity combining scheme under the twochannel models and that of a single antenna systemis shown in Figure 6 (c). The performance gain ofthe dual antenna system with the EGC diversitycombining over a single antenna system is 3.1 dBfor the SCFCM at BER=10-1 and 4.1 dB for theLCFCM. The performance gain increases furtherwith a lower BER. For example, the gain is 4.4 dBfor the SCFCM at BER=3x10-2 and 6.4 dB for theLCFCM. As expected, the higher performance gainis achieved under the LCFCM than the SCFCM.

It is worth noting that the BER is saturatedbeyond a certain level of Eb/No for both single anddual antenna systems, i.e., the increase of thetransmitter power beyond a certain level fails tofurther decrease the BER. This is explained as theincreased transmitter power increases the signallevel of all multipath signals, i.e., the power level ofthe interference signals.

To investigate the impact of individualparameters, we also simulated variation of severalindividual parameters and present the results below.Hereafter, we consider only the EGC diversitycombining scheme for the dual smart antennasystem. Firstly, we investigated the impact of thenumber of users. The simulation results with thenumber of users of 8, 12, and 16 under the LCFCMare presented in Figure 7. Note that all the otherparameters are the same as the baseline parametersin the simulation. The top cluster of the threegraphs represents the BERs of a single antennasystem where the number of users is 16, 12, and 8from top to bottom. The bottom cluster of the threegraphs represents the BERs of the dual antennasystem where the number of users is 16, 12, and 8from top to bottom. As the number of usersincreases, the signal power of the desired userdecreases, which results in increase of the powerlevel of the interference. Hence, the performance inBER decreases. Note that the deterioration of theperformance is substantial for large Eb/No. Forexample, the BER of the dual antenna system for 8users is 0.17 % at Eb/No = 21 dB, while the BERbecomes 1.27 % for 16 users.

(a) BERs under the SCFCM

(b) BERs under the LCFCM

(c) BER Bound with the EGCFigure 6. BERs with Three Diversity Combining

Schemes and Two Channel Models

Secondly, we investigated the impact of themobile velocity. We varied the mobile velocity to30, 60, and 90 km/hr, which results in 59, 119, and178 Hz of Doppler frequency, respectively, underthe LCFCM, while all the other parameters are thesame as the baseline parameters. The simulationresults are given in Figure 8. The top cluster of thethree graphs represents the BERs of a single


241

antenna system with the three mobile velocities.The bottom cluster of the three graphs representsthe BERs of the dual antenna system. Thesimulation results reveal that the dual smart antennasystem performs better than a single antenna systemfor all the three mobile velocities. It is notable thatthe impact of the mobile velocity is negligible forthe three mobile velocities for both single and dualantenna systems.

Figure 7. BERs with Various Numbers of Users

Figure 8. BERs with Various Mobile Velocities

Finally, we investigated the impact of thenumber of multipaths. We considered 4, 5, and 6multipaths under the LCFCM, and the simulationresults are presented in Figure 9. The top cluster ofthe three graphs represents the BERs of a singleantenna system for the three different numbers ofmultipaths, and the bottom cluster represents theBERs of the dual antenna system. It should benoted that the number of rake fingers is fixed tothree for all cases. As can be seen from the figure,the dual smart antenna system performs better thana single antenna system for all the three cases. IfEb/No is small, the figure indicates that the numberof multipaths has little impact on the performance.This is due to the fact that AWGN is dominant for

small Eb/No. Therefore, the interference due to theother multipaths is relatively insignificant.Obviously, the trend is reverse for large Eb/No asshown in the figure.

Figure 9. BERs with Various Numbers ofMultipaths

We investigated the impact of three individualparameters. The simulation results indicate that adual smart antenna system with diversitycombining always performs better than a singleantenna system.

V. CONCLUSIONIn this paper, we propose a dual smart antenna

system incorporated into handsets for the 3GPPWCDMA system, in which a diversity combinercombines the two rake receiver outputs using adiversity combining scheme. We considered threediversity combining schemes, selection diversity,square law combining, and equal gain combining(EGC). We also considered two types of thechannel model for the dual antenna signals, looselycorrelated fading channel model (LCFCM) andspatially correlated fading channel model(SCFCM). To obtain the channel profile (such asdelay, average power, and angle of arrival of eachmultipath signal), we adopted a geometrically basedchannel model known as GBSB (geometricallybased single bounce) elliptical model in thesimulation. The simulation results indicate that

i) the EGC scheme performs the best among thethree diversity combining schemes. This isbeneficial as the EGC scheme is simple inimplementation.

ii) As expected, the higher performance gain isachieved under the LCFCM than the SCFCM.It is believed that the actual performance of adual smart antenna lies in between theperformances obtained for the LCFCM andthe SCFCM models.


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In conclusion, a dual smart antenna system withdiversity combining at handsets is beneficial for the3GPP WCDMA system.

REFERENCES[1] Special Issue, Smart Antenna, IEEE Personal

Communications, Vol. 5, No. 1, February1998.

[2] J. S. Thompson, P. M. Grant, and B.Mulgrew, “Smart Antenna Arrays for CDMASystems,” IEEE Personal Communications,pp. 16-25, October 1996.

[3] S. Affes and P. Mermelstein, “A NewReceiver Structure for Asynchronous CDMA:STAR – The Spatio-Temporal Array-Receiver,” IEEE Journal on Selected Areas inCommunications, Vol. 16, No. 8, pp. 1411-1422, October 1998.

[4] http://www.3gpp.org/.[5] http://www.3gpp.org/ftp/Specs/2000-

12/R1999/25_series/25101-350.zip, “3GPPTS 25.101 UE Radio Transmission andReception (FDD),” 3GPP, December 2000.

[6] J. S. Colburn, Y. Rahmat-Samii, M. A.Jensen, and G. J. Pottie, “Evaluation ofPersonal Communications Dual-AntennaHandset Diversity Performance,” IEEETransactions on Vehicular Technology, Vol.47, No. 3, pp. 737-746, August 1998.

[7] http://www.qualcomm.com/hdr/pdfs/HDR_Tech_Airlink.pdf, “1x High Data Rate (1xHDR)Airlink Overview,” April 2000.

[8] G. Dolmans and L. Leyten, “PerformanceStudy of an Adaptive Dual Antenna Handsetfor Indoor Communications,” IEEProceedings of Microwaves, Antennas andPropagation, Vol. 146, No. 2, pp. 138-1444,April 1999.

[9] P. B. Wong and D. C. Cox, “Low-Complexity

Cochannel Interference Cancellation and

Macroscopic Diversity for High-Capacity,”

IEEE Transactions on Vehicular Technology,

Vol. 47, No. 1, pp. 124-132, February 1998.[10] S. W. Kim, D. S. Ha, and J. H. Kim,

“Performance Gain of Smart Dual Antennasat Handsets in 3G CDMA System,” CDMAInternational Conference, Vol. 2, pp. 223-227,November 2000.

[11] S. W. Kim, D. S. Ha, and J. H. Kim,“Performance of Smart Antennas withAdaptive Combining at Handsets for thecdma2000 System,” Accepted at InternationalConference on Third Generation Wireless andBeyond, May/June 2001.

[12] W. C. Jakes, Microwave MobileCommunications, John Wiley, New York,1974.

[13] R. B. Ertel, P. Cardieri, K. W. Sowerby, T. S.Rappaport, and J. H. Reed, “Overview ofSpatial Channel Models for Antenna ArrayCommunication Systems,” IEEE PersonalCommunications, pp. 10-22, February 1998.

[14] R. B. Ertel, “Antenna Array Systems:Propagation and Performance,” Ph. D.Dissertation, Virginia Polytechnic Instituteand State University, July 1999.

[15] J. Salz and J. H. Winters, “Effect of FadingCorrelation of Adaptive Arrays in DigitalMobile Radio,” IEEE Transactions onVehicular Technology, pp. 1049-1057,November 1994.

[16] T. S. Rappaport, Wireless Communications:Principles and Practice, Prentice Hall, NewJersey, 1996.

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