Use of Adaptive Sectorisation for Capacity Enhancement in CDMA Cellular Systems with Non-Uniform Traffic

Wireless Personal Communications 28: 107–120, 2004.© 2004 Kluwer Academic Publishers. Printed in the Netherlands.

Use of Adaptive Sectorisation for Capacity Enhancementin CDMA Cellular Systems with Non-Uniform Traffic �

TRUNG V. NGUYEN, PREM DASSANAYAKE and MIKE FAULKNERCentre for Telecommunications and Micro-Electronics, Faculty of Engineering and Science, Victoria University,P.O. Box 14428, Melbourne City, MC, VIC 8001, AustraliaE-mail: [email protected]

Abstract. This paper discusses the application of adaptive sectorisation in the capacity enhancement of a CDMAcellular system dealing with non-uniform traffic. It considers the particular case where the traffic distributionconsists of isolated areas of congested traffic called Hot Spots (HS). It is envisaged that the traffic density insidea HS is many more times that outside the HS. A more even traffic distribution among sectors is attempted byre-adjustment of sector boundaries using finite antenna beam switching. System capacity is estimated on thebasis of tolerable interference in a sector taking into account of both intrasector and intersector interference ina multicell environment. Interference is evaluated under the assumption of perfect power control in the uplink.Normal propagation environment is assumed in the cell that allows path losses and shadowing losses in the mobileradio signal. Variation in the antenna gain is also accommodated by taking appropriate radiation pattern intoaccount. It is shown that successive sector adjustment with increasing HS traffic intensity can deter call blockingin the HS sector. It is also shown that a significant improvement in system capacity could be obtained with adaptivesectorisation particularly when the HS user density is several orders of magnitude higher than that outside the HS.

Keywords: adaptive sectorisation, Hot Spots, cellular CDMA capacity.

1. Introduction

CDMA has received widespread acceptance as the radio interface for future generation cellu-lar mobile communication systems. The capacity of a CDMA cellular system is determinedby the amount of interference it can tolerate [1]. This interference is twofold. The interferencearising from other traffic in the same cell and the interference arriving from traffic in neigh-bouring cells. If the traffic could be redistributed among cells so as to minimize the overallinterference in a given cell more traffic can be accepted in that cell. In a sectorised cell theredistribution of traffic could be achieved by adaptive sectorisation.

This paper investigates the capacity of a CDMA system where the user distribution consistsof high density pockets called Hot Spots (HS). A HS is formed by the congregation of manyusers in a small area. In the present study, the user densities (within and outside the HS) areassumed to be uniform although the user density inside the HS is much higher than the userdensity outside the HS. The user density ratio in these two regions is taken as a parameter thatreflects the traffic environment.

Use of adaptive sectorisation to minimize the total received and transmitted power byall users has been studied in [2]. Adaptive sector control using Butler matrix fed circulararray is given in [3] and the impact of sectorisation on WCDMA network is discussed in[4]. These works have assumed ideal antenna characteristics and thus the non-interference

� This project is supported by Australian Telecommunications Cooperative Research Centre (ATcrc).

108 Trung V. Nguyen et al.

between sectors. Giuliano et al. [5] have considered the use of adaptive sectorisation in 3GCDMA systems to enhance capacity in a HS environment. Their study is based on the rotationof sectors to share the hot spots among the adjacent sectors.

The approach used in this investigation to improve cell capacity is to employ adaptivesectorisation. The sector coverage in a cell can be controlled by the use of antenna structuresthat allow finite beam switching. Finite width beams are combined to cover an area of a cellthat is divided into three sectors. Sectors could be adjusted in such a way that a given sectorcovers a HS either fully or partially. In contrast to smart antennas, which require the tracking ofa MS within a cell, the finite antenna beam switching provides a simple and robust techniquefor sector boundary adjustment.

The paper is organized as follows. In Section 2 the system model including the propagationmodel is presented. Section 3 considers the capacity evaluation in the presence of non-uniformtraffic distribution. Section 4 describes the procedure adopted for system simulation and theresults of simulation. In Section 5 conclusions are drawn.

2. System Model

In this investigation, the system model considers only the first tier of interfering cells, whichmeans that there are six interfering (neighbouring) cells. Therefore, the geometry of the in-terference model can be represented as shown in Figure 1. The interference from second andthird tiers to the home cell is extremely small [1], and thus is ignored. In Figure 1 home cell Aconsists of sector A1, A2, and A3 of which A1 is the home sector where the HS is located. A2

and A3 are adjacent sectors, and B1, B2, B3, C1, C2, and C3 are neighbour sectors from whichthe home sector may receive interference.

It is assumed that the users in each sector, including those in home sector, are uniformlydistributed. However, the traffic density in the HS region (Figure 1) is several times higherthan that outside the HS. In this investigation the mobility characteristics of users are ignored.Cells are assumed to be hexagonal in shape and identical in size.

2.1. PROPAGATION MODEL

The signal propagation in the mobile channel (when fast fading is ignored) is generally mod-eled as a product of three components, one inversely proportional to a power of the distancerepresenting the path loss, the second a random variable with lognormal distribution repre-senting the shadowing losses, and the third representing the directional antenna gain [1, 3, 6,7]. The shadowing represents slow variations in signal strength even for mobile users. On theother hand, fast fading, which is largely due to multipath propagation, can be assumed to haveno effect in the average signal power level [6]. Hence, for a user at a distance r from a BaseStation (BS) at an angle θ as per Figure 1, the total propagation path loss is a function of r, ζ ,and A(θ), given by

PL(r, ζ, θ) = r−n · 10ζ/10 · A(θ), (1)

where A(θ) is the antenna gain in the direction of mobile station (MS), and n is the propagationpath loss exponent which typically has a value of 4. ζ is a random variable with normaldistribution, (10ζ/10 representing the log-normal shadowing process). Due to shadowing thelocal mean of signal power fluctuates around the area mean with log-normal distribution, andthe standard deviation σ of this distribution generally varies between 6 dB and 12 dB and has

Use of Adaptive Sectorisation for Capacity Enhancement in CDMA Cellular Systems 109

Figure 1. Geometry of the system model for interference evaluation.

a typical value of 8 dB. In order for a BS to be the most favorable to a MS the PL(r, ζ, θ) withrespect to that BS must be smaller than the PL(r, ζ, θ) with respect to all other BSs [8].

2.2. ADAPTIVE ANTENNA ARRAY FACTOR

In applications such as cellular mobile systems, where adaptive sectorisation is required, thereis a need for the down link beam to scan in different directions in the azimuth and two ofthe most common scanning techniques used are the mechanical scanning and the electronicscanning. In case of mechanical scanning, the array can be rotated mechanically through 360◦to give all-round coverage and can be adopted when the rotating structure is not too large. Inother cases electronic scanning is preferred. The main beam of an antenna array consisting ofseveral equally spaced elements points in a direction θs to the array normal when the phasedifference between adjacent elements is given by [9]

β = k · d · sin θs , (2)

where k = 2π/λ (λ is the free space wave length) and d is the spacing between adjacentelements. Thus, by varying the phase difference β the beam can be steered through variousdirections. However, it is to be noted that for an element spacing of about half wavelength,beam steering is restricted to about ±60◦ to avoid grating lobes [9].

Since the Array Factor of a linear array of N elements is given by

AF(θ) =N−1∑n=0

exp [j · n(k · d · sin θ + β)], (3)


Figure 2. (a) Antenna element radiation pattern [10]. (b) Array factor (superimposed for θs = 45◦, 15◦, –15◦ and–45◦). (c) Resultant pattern (superimposed for θs = 45◦, 15◦, –15◦, and –45◦).

when element spacing is λ/2, substituting (2) into (3), we have,

AF(θ) =N−1∑n=0

exp [j · n · π · (sin θ + sin θs)], (4)

where 0◦ ≤ θ ≤ 360◦ and θs = [45◦, 15◦, −15◦, −45◦]. If A(θ) represents the radiationpattern of a single element of the array, the resultant Antenna Pattern AP(θ) is found by patternmultiplication (i.e., as the product of A(θ) and AF(θ))

AP(θ) = A(θ) · AF(θ) . (5)

By varying the element spacing d and/or the phase difference β between elementexcitations, the array factor and the resultant array pattern can be varied.

Figure 2(a) shows the radiation pattern of a single element of the antenna array [10].Figure 2(b) shows the antenna array patterns corresponding to main beam directions 45◦, 15◦,−15◦ and −45◦. Figure 2(c) gives the resultant antenna pattern obtained by pattern multipli-cation. Each element of the antenna array is a λ/2 dipole and the array spacing and the phaseof feed current are controlled to obtain the desired radiation pattern. It can be seen that themain beam can be steered to cover a desired part of a sector.

2.3. ADAPTIVE SECTOR CONTROL

We consider a BS antenna structure that consists of twelve fixed 30◦ beams per cell. Thenarrow beams are combined to obtain 3 composite beams, which would substitute for thebeams provided by the normal 120◦ directional antenna. Next, keeping the number of sectorsfixed at 3 per cell, we may adaptively change the sector size by combining an appropriatenumber of narrow beams (Figure 1). Obviously, each sector acts like a cell with it is ownpilot signal and the softer handover is responsible for switching the users from one sector toanother.

The adaptive sectorisation allows sector beamwidths to be approximately 30, 60, 90, 120,150, 180, or 210 degrees. Switched beams can adjust the sector size to include either fully orpartially an area of high user density, i.e., Hot Spot (HS). By using adaptive beam switchingthe traffic can be shifted from heavily loaded HS sectors to sectors that are underutilized.


3. System Capacity Evaluation

3.1. SECTORISED CELL CAPACITY

In this analysis we assume that perfect power control is in place in the uplink. This mean thatthe signal strength S received by a sector BS due to the presence of a MS in the sector isthe same for every MS in the sector, and is true for all sectors. Then the received Signal-to-Interference Ratio (SIR) at a sector BS can be expressed as,(

S

I

)=

(S

Iintra + Iinter + η

), (6)

where Iintra is the interference occurring within the sector, Iinter is the interference arrivingfrom neighbouring sectors, and η is the background thermal noise. If Ni is the number ofusers in the sector,

Iintra = (Ni − 1) · S. (7)

To evaluate Iinter consider a MS situated in the neighbour sector B1 (Figure 1). If P is itstransmit power, the received power at the BS of sector B1 is

S = PAB1k(θ)10ζB1k/10

r4B1k

, (8)

where AB1k(θ) is the BS antenna gain of sector B1 (in the direction of MS) and ζB1k is theGaussian random variable representing the shadowing process in sector B1.

The interference received at the BS of sector A1 due to the MS in sector B1 is

Ik = PAA1k(θ)10ζA1k/10

r4A1k

, (9)

where AA1k(θ) is the BS antenna gain of sector A1 (in the direction of MS) and ζA1k is theGaussian random variable representing the shadowing process in sector A1. Substituting (8)into (9) we have

Ik = S ·(

rB1k

rA1k

)4

·(

AA1k(θ)

AB1k(θ)

)· 10

ζA1k−ζB1k

10 . (10)

Iinter is found by summing (10) for all users in the adjacent and neighbour sectors, i.e.,

Iinter =∑

j=B:G

∑k∈{1··Nj }

S ·(

rjk

rAk

)4

·(

AAk

Ajk

)· 10(ζAk−ζjk )/10 . (11)

Substituting (7) and (11) into (6), and assuming that the contribution from thermal noise isnegligible, we have the SIR given by(

S

I

)A1

= S

χ

S · (NA1 − 1) +

∑j=B:G

∑k∈{1··Nj }

S ·(

rjk

rAk

)4

·(

AAk

Ajk

)· 10(ζAk−ζjk)/10

, (12)


Table 1. Parameters of simulation.

Cell radius, R unity

Required, Eb/N0 7.4 dB

Chip rate 1.2288 Mcps

Bite rate, Rb 9.6 kbps

Reverse link SIRth –13.6 dB

Number of sectors per cell 3

Standard deviation of shadow fading, σ 8 dB

Voice activity factor, χ 37.5%

where χ is the voice activity factor. Since ζA1k, ζjk are independent random variables of zeromean and standard deviation σ , the difference (ζA1k − ζjk) is also a random variable with zeromean and variance 2σ 2.

3.2. SYSTEM ACCESS

When an MS chooses to access a certain sector’s BS, the sector’s BS will check whether theprevailing SIR is greater than the minimum (threshold) value required. If the SIR is less thanthe threshold the MS is blocked. This threshold value, SIRth, is a function of Eb/N0 and thesystem Processing Gain (PG) and is given by SIRth[dB] = Eb/N0[dB] − PG[dB] [1]. TheEb/N0 required in a CDMA system is about 7.4 dB if the bit-error rate is not to exceed 10−3

[1].The SIRth based algorithm for call admission is a distributed mechanism [1]. It can be used

by each sector’s BS to determine whether or not a sector admits a call. If SIR > SIRth thecall request is accepted. Otherwise, the call request is rejected. Therefore, the call blockingprobability is given by,

Pb = Pr{SIR ≤ SIRth} . (13)

4. System Simulation

In this investigation of CDMA system capacity, the number of users the system can supportis evaluated using a computer simulation according to (13). The simulation is based on thesystem parameters shown in Table 1.

The HS is in the home sector A1 (Figure 1) (which therefore is also called the Hot SpotSector (HSS)) and the HSS can vary from 30◦ to 120◦ in steps of 30◦. In this investigationwe consider two cases, (1) Hot Spot Area (HSA) is completely inside the HSS and (2) HSAextends beyond the HSS. In both cases it is assumed that the HSA is confined to a strip ofdimension L × W where W is the arc width of the HS and L is its radial length.

The cell radii in all scenarios are normalized to unity and the conventional hexagonal cellpattern is assumed. Perfect power control is also assumed so that the received power at thesector’s BS from all mobiles within the sector is the same. A uniformly distributed mobilepopulation is generated with random locations within the home and the six neighbour sectors.This is done by generating two sets of random numbers that assign an angular position and a


radial distance to each mobile. The radial position is the distance of the MS from the homeBS. The individual path losses (coupled with the shadowing effect) are calculated for eachMS in order to evaluate the SIR at the sector BS.

The system capacity is evaluated in terms of possible number of users in each sector whenat most 1% new call blocking is experienced in any of the sectors. The cell capacity is the sumof three sector capacities.

The simulation starts with empty system (no users any where) and proceeds by addingusers progressively, one user at a time, positioning each user at a randomly selected locationin each sector and in HS region. Every time a user is added (any where in the system) theSIR at the BSs of all sectors are evaluated to see that with the added user the system blockingprobability does not exceed the stipulated value. When the blocking probability exceeds thestipulated value the simulation terminates and the number of users in each sector and the sectorcausing the simulation termination are noted.

4.1. CASE OF PERFECT ANTENNA

The case of a perfect antenna serves as a reference to examine the system under ideal condi-tions and to compare it with the practical case. The sector coverage in this case (with perfectantenna) is assumed to be uniform over the entire sector and there is no spillover of main lobeor occurrence of sidelobes in the radiation pattern.

4.1.1. Case 1, W = 20◦Figure 3 shows the results for the case of perfect antenna for a blocking probability of 1%,in the overall system. As mentioned earlier, in Figure 1, A1 is the HSS, A2 and A3 are theadjacent sectors, and B1, B2, B3, C1, C2, C3 are the neighbour sectors. In the absence ofHSs there is uniform traffic in every cell (HS to non-HS user density ratio is 1) and the systemoffers a traffic capacity of 34 users/sector. This is taken as the reference. The results (Figure 3)indicate that when all sectors are of the same size (i.e., A1 = 120◦), the possible number ofusers in hot spot sector A1 increases with increasing user density in HS while the possiblenumber of users in adjacent (A2 or A3) and neighbour (B1, C1, . . .) sectors decreases withincreasing user density in HS. Simulation shows that in this situation blocking always occursfirst in A1. This is in contrast to the situation when A1 is 60◦ or 30◦. In these cases blockingfirst occurs in the adjacent sectors (A2 or A3) and then moves to A1 as the HS to non-HSuser density ratio reaches 5 and 10, respectively. Figure 4 shows the change over of blockingsector as the HS to non-HS user density ratio increases from 1, in the three cases of sector size120◦, 60◦, and 30◦. The system capacity (per cell) can be obtained at a give HS to non-HSuser density ratio by summing up the number of users in each sector. Figure 5 illustrates thissituation and shows the cell capacity as a function of HS to non-HS user density ratio. It canbe seen that there is an overall capacity improvement which starts at a user density ratio ofabout 5, and reaches a maximum value of about 37% of the nominal capacity (i.e., referencecase) at a user density ratio of about 15.

4.1.2. Case 2, W = 600

Figure 6 shows the results for the case of perfect antenna for an overall blocking probabilityof 1%. In this case the blocking first occurs in the adjacent sectors and then moves to HSSwhen the HS to non-HS user density ratio reaches about 2 and 4, when HSS size is 60◦ and30◦, respectively. Figure 7 presents the blocking sector for this case. The results of Figure 8


Figure 3. Sector capacity versus hot-spot to non-hot spot user density ratio (Case 1, W = 20◦) (case of perfectantenna).

Figure 4. The change over of blocking sector between HSS (A1) and adjacent sectors (A2 and A3) (Case 1,W = 20◦) (case of perfect antenna).


Figure 5. Cell capacity versus hot spot to non-hot spot user density ratio. Comparison between different HSS sizes(120◦, 60◦, and 30◦) with W = 20◦. (case of perfect antenna).

show that the overall capacity improvement in this case starts to occur at a user density ratioof about 2 and it reaches about 60% of the nominal capacity at a user density ratio of about 12.

4.2. CASE OF PRACTICAL ANTENNA

In this case the overall gain factor of the antenna array is taken into account in the direction ofthe MS location. Due account is also made of the fact that some sidelobes are present in theradiation pattern.

4.2.1. Case 1, W = 200

The blocking sector change over behaviour in this case is similar to the case of perfect antenna(Figure 4). The blocking always starts to occur in A1 when HSS size is 120◦. When HSS sizeis 60◦ and 30◦ the blocking first occurs in A2, A3 and then moves to A1 when the user densityratio reaches about 5 and 7, respectively. Figure 9 shows the cell capacity for the case ofpractical antenna, for a blocking probability of 1% in the system. It can be seen that there is anoverall improvement in system capacity with adaptive sectorisation although the improvementis not as much as in the case of perfect antenna.

When there is uniform traffic in every cell (user density ratio is 1) the system offers atraffic capacity of 32 users/sector, which is taken as the reference. The results indicate that,similar to the case of perfect antenna, the possible number of users in HSS increases withincreasing user density in HS while the possible number of users in adjacent and neighboursectors decreases with increasing user density in HS. Figure 9 illustrates this situation andshows that the capacity improvement starts at a user density ratio of about 5, and reaches avalue of about 43% of the reference value at a user density ratio of about 15.


Figure 6. Sector capacity versus hot spot to non-HS user density ratio (Case 2, W = 60◦). (Case of perfectantenna).

4.2.2. Case 2, W = 600

The blocking sector behaviour in this case also is similar to the case of perfect antenna (Fig-ure 7). The blocking first occurs in A2, A3 and then moves to A1 as the user density ratioreaches about 2 and 4 when HSS size is 60◦ and 30◦, respectively. Figure 10 shows the cellcapacity for an overall blocking probability of 1%. The results of Figure 10 show that the

Figure 7. The change over of blocking sector between HSS (A1), and adjacent sectors (A2, A3) (Case 2,W = 60◦) (case of perfect antenna).


Figure 8. Cell capacity versus hot spot to non-HS user density ratio. Comparison between different HSS sizeswith W = 60◦ (case of perfect antenna).

Figure 9. Cell capacity versus hot spot to non-HS user density ratio. Comparison between different HSS sizeswith W = 20◦ (case of practical antenna).


Figure 10. Cell capacity versus hot spot to non-HS user density ratio. Comparison between different HSS sizeswith W = 60◦ (case of practical antenna).

system capacity improvement with adaptive sectorisation starts to occur at a user density ratioof about 2 and 3 for HSS size 60◦ and 30◦, respectively. This improvement reaches about 38%of the reference value at a user density ratio of 4 (HSS size = 60◦), and about 44% of thereference value at a user density ratio of 11 (HSS size = 30◦), respectively.

5. Conclusion

Adaptive sectorisation can be used to improve the capacity of a CDMA cellular system when acell or a sector contains an area of congested traffic. A simple and robust technique to achieveadaptive sectorisation is to employ finite beam switching with a suitable array antenna at thesector BS. The available capacity improvement is a function of the ratio of the user densitiesin the congested and non-congested areas of the sector and it appears that the improvement isparticularly significant when the user density in the congested area is an order of magnitudehigher than that of the rest. A simple beam forming dipole array antenna structure, such as theone considered here, can be used for the implementation of adaptive sectorisation.

References

1. J.-S. Wu, J.-K. Chung and C.-C. Wen, “Hot-Spot Traffic Relief with a Tilted Antenna in CDMA CellularNetworks”, IEEE Trans. Veh. Tech., Vol. 47, pp. 1–9, 1998.

2. C.U. Saraydar and A. Yener, “Capacity Enhancement for CDMA Systems through Adaptive Cell Sectoriza-tion”, IEEE 1999 Wireless Conf. and Networking Conf., Vol. 3, pp. 1139–1143.

3. M. Mahmoudi, E.S. Sousa and H. Alavi, “Adaptive Sector Size Control in a CDMA System Using ButlerMatrix”, IEEE 49th VTC’99, Vol. 2, pp. 1355–1359, 1999.

4. A. Wacker, J. Laiho-Steffens, K. Sipila and K. Heiska, “The Impact of the Base Station Sectorisation onWCDMA Radio Network Performance”, IEEE 50th VTC’99 – Fall, Vol. 5, pp. 2611–2615, 1999.


5. R. Giuliano, F. Mazzenga and F. Vatalaro, “Adaptive Cell Sectorization for UMTS Third Generation CDMASystems”, IEEE VTC’01 Spring, May 6–9, 2001.

6. A.J. Viterbi, A.M. Viterbi, K.S. Gilhousen and E. Zehavi, “Soft Handoff Extends CDMA Cell Coverage andIncreases Reverse Link Capacity”, IEEE Journal on Sel. Areas in Comm., Vol. 12, pp. 1281–1288, Vol. 1,pp. 219–223, 1994.

7. K.S. Gilhousen, I.M. Jacobs, R. Padovani, A.J. Viterbi, L.A. Weaver Jr. and C.E. Wheatley III, “On theCapacity of a Cellular CDMA System”, IEEE Trans. Veh. Tech., Vol. 40, pp. 303–312, 1991.

8. A. Chatovich and B. Jabbari, “Effect of Non-uniform Traffic Load on Erlang Capacity of CDMA”, IEEE49th VTC’99, Vol. 1, pp. 816–820, 1999.

9. F.R. Connor, Antennas, 2nd edn, Chapter 4, pp. 54–55, Edward Arnold: London, 1989.10. http://www.celwave.com/index.php?sid=c0e46ad491f02233c2bdcae4bb70f10e&p=340&l=1 (please down-

load PCS patterns, ALE1903H.199).11. M.R. Garcia, J.E.B. Lati, J.M.R. Jerez and A.D. Estrella, “Capacity Analysis of an Integrated Wide-

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Trung Nguyen is a Ph.D research student of Victoria University, Australia, working in the areaof 3G cellular mobile communications systems. He was graduated from RMIT University,Melbourne, Australia, in 1997, with the Bachelor degree in electrical engineering. In 1999, heobtained Master degree from Victoria University specialising in the area of telecommunicationengineering, winning the award for the best student in that year. He then joined the AustralianTelecommunications Cooperated Research Centre (ATcrc) and worked for a project that in-volved the design of antenna structures for adaptive sectorisation of cellular mobile systems.At present, he is working on his research project which involves the Capacity Improvement in3G Cellular Systems.


Prem Dassanayake is a Senior Lecturer at Victoria University, Footscray, Australia, and hasbeen there since 1985. Prior to that he was in the staff of University of Bahrain, State ofBahrain, and the University of Moratuwa, Sri Lanka. He has been a researcher at the Bareanof Medical Devices, Health and Welfare Canada, Ottawa, Canada, and at the Telstra Researchlaboratories, Clayton, Australia. He has obtained his B.Sc. Eng. degree from the Universityof Peradeniya, Sri Lanka, and M.Sc. and Ph.D. degrees from the University of Wales, Cardiff,United Kingdom.

Michael Faulkner (M’84) received the B.Sc.(Eng) from Queen Mary College, London Uni-versity, U.K., in 1970, the M.E. degree from the University of New South Wales, Australiain 1978, and the Ph.D. from University of Technology Sydney in 1993. From 1972 to 1975he was with STC (now Alcatel) Australia. From 1975 to 1977 he was with the Universityof New South Wales, and since then as a Lecturer and now Professor at Victoria Universityof Technology, Melbourne, Australia where he is Director of the Telecommunications andMicro-electronics research centre. Between 1988 and 2000 he spent four periods at LundUniversity, Sweden. He was Co-recipient of the IEE’s 1997 IERE prize for a paper on ampli-fier linearisation. His current interests are, signal processing, radio technology, radio systemsand MIMO/OFDM.

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Use of Adaptive Sectorisation for Capacity Enhancement in CDMA Cellular Systems with Non-Uniform Traffic