WCDMA DOWNLJNK CAPACITY

IMPROVEMENT BY USING SMART ANTENNA

Tiong Sieb Kiong', Mahamod Ismail2, Azmi Hassan3

'College of Engineering, Universiti Tenaga Malaysia (UNITEN)km 7, Kajang-Puchong Road, 43009 Kajang, Selangor Darul Ehsan, Malaysia, siehkiong(uniten.edu.my

2 Faculty of Engineering, Universiti Kebangsaan Malaysia (UKM)43600 UKM Bangi, Selangor Darul Ehsan, Malaysia, mahamod(eng.ukm.my

3Faculty of Engineering, Universiti Kebangsaan Malaysia (UKM)43600 UKM Bangi, Selangor Darul Ehsan, Malaysia, azmi(2vlsi.eng.ukm..my

Abstract - Heterogeneous type of users in modern mobilecommunication expect network service provider providinghigh-speed data, multimedia and voice services. However,capacity has always been an issue to any generation of mobilecommunication technologies as it is always inverselyproportionate to QoS (quality of service) in nature. Hence, inorder to increase the system capacity without jeopardizing theQoS, smart antenna was proposed to increase the spectraleffi'ciency of the wireless channel. Many research works haveshown that the system capacity of modern mobilecommunication can be improved by employing smart antenna111121. A dynamic radio network simulator was developed inVisual C++< to study and estimate the downlink capacity of aWCDMA system with smart antenna. Capacity system byusing different smart antenna strategies was studied in thisresearch. Simulation was done based on single micro cellenvironment with considering interference from the first tier.User mobility is taken into account to provide a combinedevaluation of Radio Resource Management (RRM). Capacitysystem expressed in downlink outage under various simulationscenarios was represented in this paper.

Keywords - WCDMA, Capacity, downlink outage, SmartAntenna

1. INTRODUCTION

Third Generation (3G) Mobile Communication System wasdesigned to cater for the needs of modem heterogeneoustypes of users. In general, 3G systems are able to supporthigher data rates as compared to typical voice orientatedservices in 2G. In WCDMA systems, the main limitingfactor for capacity expansion is the interference [1].

In order to improve the capacity offered by WCDMAsystems, great attention has been drawn in the exploitationof spatial domain using smart antennas [2],[3]. Many studieshave shown that smart antennas are capable to provideenhanced coverage through Multiple Access Interference(MAI) cancellation, range extension, increase system

capacity and improve link quality [1],[4]. However, most ofthe studies were done on the uplink. This is due to most ofthe researchers believe that WCDMA system is reverse linklimited [5],[6]. Nevertheless, recent researches have shownthat the forward link can be the limiting link under certaincircumstances [7],[81. Thus, downlink capacityimprovement is targeted in this research.

The capacity of a system can be defined in several ways.Typically, maximal number of simultaneous users in thesystem is used and this method is widely used for designinga call-admission control for the given set of capacity lines.Another method is to determine the peak load that can besupported by the system while maintaining desired servicequality. The latter matter can be used to find the Erlangcapacity that is used in cell planning and in evaluatingcapacity expense [9]. In this paper, downlink outage in theaspect of blocking and dropping probability is used toevaluate the Eriang capacity as in [7].

11. SIMULATOR MODELLING

In order to simulate the downlink capacity of a WCDMAsystem, a dynamic system level simulation tool named asWSAGASlM (WCDMA Smart Antenna Genetic AlgorithmSimulator) was developed. The simulator consists of fivemajor parts: initialization, call admission control,beamforming and power control, mobile stations processesand simulation output.

(a) InitializationInitialization phase is the first part of the simulator, wheretopography of the simulation such as cell sites, Node B isgenerated. Besides, the UE traffic parameters such as meanarrival time and mean call duration are generated based onPoisson distribution model. Meanwhile, UE mobilityparameters are generated based on ITU-Vehicle A model.

The authors acknowledge that this research is a part of project fundedby government of Malaysia with IRPA 04-02-02-0062-EA289

1-4244-0000-7/05/$20.00 ©2005 IEEE. 828

(b) Call Admission ControlCall admission algorithm measures the received Energy per

bit per noise density, ( b ) from the UE whoNo+ It

requesting admission into the wireless system. Dependingon the position and location of the UTE, the algorithm decideswhich beam is best selected to serve the mobile station anddetermine whether the UE can be admitted to the systemwithout jeopardizing the performance of other UEs currently

Ebin the system. The downlink b threshold obtainedN +It

from the link level simulations as shown in Equation Ibelow and assuming that the downlink ortogonality factor isunity.

Eb Pt,nGtGr,n-) = (fNo + t A,nLp,nLtLrbrt (No + It,n)

where ptn is the traffic channel power of UE #n, Gt is NodeB antenna gain, Gr,n is UE #n antenna gain, A,, is lognormalshadowing experienced by LTE #n, 4LD is propagation lossfrom Node B to UE #n, 1, and 4 is cable loss at Node Btransmitter and UE receiver respectively, b,, is bit rate ofdownlink traffic channel, No is thermal noise density at 290K and I,, is the total interference density experienced by UE#n.

Total interference density experienced by UTE #n, I., isobtained by considering both interference within the homecell and also interference from first tier cells.

I (PT-Ptfn)GtGr,n x I (2)AInLPJn4L4Bw f;

where B, is bandwidth in Hz, f, is frequency reuse factorwhich representing interference caused by first tierneighbour cells and PT is the total ERP power from Node B.

Path loss is calculated based on channel characteristics andin this simulation, macrocell propagation model (Equation3), which is applicable for both urban and suburban areas,with assumption of nearly uniform height of buildings isused [10].

1p = 40(14x1J 3h)jOgJO(r)-l 81Jogo(h)+211Jogo(f)+8OdB (3)

Where lp is the path loss in dB, r is the distance betweenbase station and mobile station in kilometers, fis the carrierfrequency in MiHz and h is the base station antenna height,in meters, measure from the average rooftop level.

(c) lE MobilityIn this dynamic simulator, mobile stations are moving atdifferent speeds. UE speeds with 3km/hr, 20km/hrs and120knm/hr were used in the simulation. Thus, the mobilestations conditions need to be updated from time to time atcertain time steps. New locations of mobile stations areobtained by predefined mobility model during initializationphase. As mobile stations moving around, mobile stationsmay move from one antenna beam coverage to another andthus, intra-handover occurs between antenna beams.Consequently, beam ownership of every mobile station needto be updated from time to time. Besides, new states ofmobile stations will be checked in every time step todetermine each mobile station in progress, whether in activeor idle mode.

(d) Beamforming and power controlThree types of antennas were studied in this paper. They are600 sectorized antenna, 9-element switch beamn smartantenna, 9-element adaptive beam smart antenna. Forantenna elements, it is assumed that identical antennaelements arranged with equal spacing in circular are used. 9elements antenna array was used to simulate for snmatantenna system (fixed 400 degree beamwidth for switchbeam and variable 6°~=1200 for adaptive beam). Two types ofadaptive beam forming techniques were used in simulation.They are MAOAS (Maximum Angle of Arrival Separation)and GA (Genetic Algorithm) assisted beam forming. Powertransmitted by any particular antenna array at Node B isdepended on UE location and interference faced by UE.Closed loop power control is used to continuously monitor

Eb of every active UE in the system and ensure theNo+Itvalue is always more than required threshold level. In the

situation where b of a particular UE drop belowNo + It

threshold level, traffic channel power of that particular LTEEbat Node B will be increased to bring up the . To

is N.+Ireduce the complexity of simulator, a fixed conversation rateat 9.6Kbps were assumed in the simulation.

(e) Simulation OutputsOutput of the simulator is system outage that expressed inblocking and dropping probabilities. Blocking of a new UE

will occur if the Eb of the UE is below the minimumNo + It

threshold level as required during call connection requestand Nod B is unable to increase the traffic channel powerfor the new lUE due to maximum power limitation in theNod B. Dropping of a lIE will occur if an active UE movingout from current beam coverage and wants to enter anotherbeam but fail due to various kinds of reasons such as powerlimitation at antenna system in the Node B. By fixing the

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BER at constant rate,, these two parameters are indeed

representing the maximum capacity of the system. Blockingprobability, P(block), dropping probability, P(drop) andoutage probability, P(out) are expressed as below.

P(block) -

P(drop)=

Total_ Blocked_ CallsTotaI_ Mobile_ Stations_ Simulated

Total Dropped CallsTotal_ Mobile Stations_ Simulated

P(out) = P(block) + P(drop)

III. SIMULATION RESULT

blocking probability in adaptive antenna system. It is due topower usage at Node B that utilizing sectorized antenna andswitch beam antenna are not intelligently optimized. As aresult, power consumption in the system is higher and thus,higher possibility of a new UE to be blocked due to

insuff-icient power to improve the new UE's b , OnNo+It

the other hand, due to the dynamic beam forming inadaptive system, a UE may always been transferred fromone beam to another beam. This increases the chance ofdropping in the system. In all traffic load condition, GAassisted adaptive antenna gives the lowest outage probabilityand followed by MAOAS adaptive antenna.

The main simulation-parameters as shown in Table I and thesimulation results of downlink capacity are shown in FigureI to5.

Table 1: Simulation Parameters

Figure I to 4 shows the outage probability in the systemimplementing different types of antenna. Simulation wascarried out with different traffic load condition to obtain thecapacity perfonrnance under various traffic load condition.The composition of blocking probability and droppingprobability are shown in the figure.

Fig. 1. Outage Probability with Sectorized Antenna

P(out) Switch Beam Antenna

0.20----

90 180 270 360 450 540 630 720 810 900Traffic Load (Edrang)

o P(block) * P(drop)

Fig. 2. Outage Probability with Switch Beam Antenna

Meanwhile Figure 5 shows the comparison of systemcapacity by utilizing different antenna system underdifferent traffic load condition and Figure 6 shows theaverage number of users allowed in the system underdifferent outage probability.

From Figure 1 to 4, it is shown that adaptive antenna givesbetter capacity to the system as outage probability is lowerwith adaptive antenna. Relatively, blocking probability ishigher as compared to dropping probability in bothsectorized antenna and switch beam antenna system.However, dropping probability is relatively higher than

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Simulation Parameters ValueBandwidth, X 5 MHlzData rate, R 9600 bpsTraffic channel ERP, Tx 38.45dBmCommon channel ERP, Tcch 34.77dBmTotal ERP power, P, 40dBmCell size (radius), S2 1kmThreshold E1J/ 5 dBNode B antenna gain, G 17dBFrequency reuse factor, t 0.65Nod B cable loss, L, 2.5dBLog Normal shadowing, Al 6.2dBVocoder rate, v 0.6

Antenna radiation pattem, ga 2

P(out) MAOAS Adaptive Antenna1 0 I

0.60'-- __- __- __--_ _-_ _-_ _-_ _-_ _-_ _-_ _--_ _ -_ _ -_ _ -_

0.40-- -_- _ _ _ __- __- __- __- __- __- __- _ ___- __- __- _

0.20 --

90 180 270 360 450 540 630 720 810 900Traffic Load (Erlang)

B P(block) * P(drop)

Fig. 3. Outage Probability with MAOAS Adaptive Antenna

P(Out) GA Assisted Adaptive Antenna1.00-.

0.80-- -______-

0.40-.-------- --------- --- ____---

0.20

0.oc0 _90 180 270 360 450 540 630 720 810 900

Traffic Load (Ertang)

F P(block) a P(drop)Fig. 4. Outage Probability with GA Assisted Adaptive

Antenna

From Figure 5, it can be seen that the outage probability byusing sectorized antenna is higher than any smart antennas.As the system capacity is inversely proportional to outageprobability, thus the system capacity with sectorized antennais lower compared to any smart antennas. In other words,both switch beam smart antenna and adaptive beam smartantenna have improved the system capacity and the greatestcapacity improvement is obtained by using GA assistedadaptive antenna.

P(out)1.00

0.90 --

0.800.70 . .. - _ __-_-0.60 _ ____ _____,-- -

0.500.40 -

030 -- - ---- ---

0.20 - _- - -

0.0090 180 270 360 450 540 630 720 810 900

Tratfc Load (Erdang)---Sectonzed Antenna --Switch Beam Arnenna,6 MAOAS Adaptive Arnenna -+-GA Assisted Adaptive Antenna

Fig. 5. Comparison of outage Probability with DifferentTypes ofAntenna Systems

Figure 6 shows the average quantity of active UTE underdifferent outage probability. It can be seen that at the sameoutage probability, different antenna system will supportdifferent number of instantaneous active UE. Again, it canbe observed that adaptive antennas can support moreinstantaneous active UEs as compared to other antennasystem. GA assisted adaptive antenna gives the bestperformance in improving the system capacity as comparedto three other antenna systems.

P(out)090cr-r r-rr-rTrT-r T T 1-rTrnu--rn-t- ri rT-m- rrr-t---r-l -,-

0.80 L _ I I I tt t

0.70 L L LL L I IJ1 1i 11 JJ-JJJJ_J J tLt_1 L

0.50 r T r T T T TT tI l t tt1t11 t1--I t v-I

0.40 -L1 t ltL t til -tlii -tit tilt

0.30 L L L L ILl I I I -L .1.J...ZI btt.I I I I 1I tI It II t I itt i I }tIltIII I11 Ii t it tIII11 ii IIIJ

0.20 I- t- fi + -I+ + -t +i t1 ti ti -1 -i -1 -1-1-I-t

0 I(-F r r r T TT T T 7 7I I I-III1

tIII -

O.10orrrrrrr TTTTlllIll

0.00 -_0 50 100 150 200 250 300 350

Capacity (Awerage UE)-o-Sectorized Antenna.- MAOAS Adaptive Antenna

-.-Switch Beam Antennao GA Assisted Adaptne Arfnenna

Fig. 6. Average Number ofUE Under Different OutageProbability with Different Types ofAntenna Systems

Figure 7 shows the outage probability for different antennasystems at different cell radius. Simulation results show thatthe outage probability increases when cell radius increases.As expected, outage probability by using smart antennas islower as compared to sectorized antenna. At the cell radiuswith lkm, the outage probability is 0.03 for sectorizedantenna and 0.00 for any of the smart antenna systems. Atthe cell radius with 2km, the outage probability of sectorizedantenna increases to 0.51. Meanwhile, the outage probabilityof switch beam antenna, MAOAS adaptive antenna and GAassisted adaptive antenna at 2km cell radius are 0.37, 0.36and 0.31 respectively. GA assisted adaptive antennaprovides the highest capacity to the system at any cell sizewith radius between I to 2km.

P(out)1..-

0.50 ------------------------1

0.40-_---

0.30--

0.20 - -_-___--- ----

0.o0 - _

1.0 1.2 1.4 1.6 1.8 2.0Cell Radius (km)

--Sectorzed Antenna a_Switch Beam AntennaMAOAS Adaptie Antenna --GA Assisted Adaptie Ardenna

Fig. 7. Outage Probability By Using Different Types ofAntenna Systems At Different Cell Size

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IV. CONCLUSION

Simulation results validate the prediction of smart antennasin improving the capacity of WCDMA system. Thesimulation results have showed that all three types ofsimulated smart antenna systems were capable to providedownlink capacity improvement to WCDMA system.Simulation results also show that adaptive antenna assistedby Genetic Algorithm gives the greatest capacityimprovement in WCDMA system, followed by MAOASadaptive antenna and subsequently by switch beam antenna.

REFERENCES

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[21 S.H. Marikar, Resource Management In 3G SystemsEnploying Smart Antennas, Blacksburg, VA, 2002.

[3] R. Martinez, D. Trosa, L. D. Haro, M. Calvo, "SmartAntenna Performance Evaluation and Capacity issuefor WCDMA UMTS". IEEE Transactions onVehicular Technology 47(1): 147-151, 2001.

[4] J.C. Liberti, T.S. Rappaport, Smart Antenna forWireless Comnunications: IS95 and Third GenerationCDM Applications. Prentice Hall, 1999.

[5] H. Holma, D. Soldani and K. Sipila, "Simulated andMeasured WCDMA Uplink Performance", IEEE VIS54th Vehicular Technology Conference VYC 2001Fall, pp. 1148-1152.

[6] Hernandez, M.A., Janssen, J.M. & Prasad, R. "Uplinkperformance enhancement for WCDMA systemsthrough adaptive antenna and multiuser detection".Vehicular Technology Conference Proceedings VTC2000-Spring(1): 571-575, 2000.

[7] Wan C., Byung S.K., Jun C.L. and Kuen T.L.,"Forward link Erlang Capacity of 3G CDMA system",IEE 3G Mobile Communication Technologies,Conference Publication. No. 471. 213-217. 2000

[8] A. Eisenblatter, H.F. Geerdes, A. Munna and R.Verdone. "Comparison of Models for WCDMADownlink Capacity Assessment Based on a MORANSReference Scenario". Zuse Institute Verlin (ZIB),Genmany.

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[1O] 3G TR 25.942.2.1.3(2000-03)

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