dual cell performance evaluation

8/23/2019 Dual Cell Performance Evaluation

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Performance Evaluation on

Dual-Cell HSDPA Operation

Danielle Morais de Andrade, Axel Klein, Harri HolmaResearch, Technology and Platforms Department

Nokia Siemens Networks

Munich, Germany and Espoo, Finlanddanielle.andrade, axel.klein, [email protected]

Ingo Viering, Gnther LieblNomor Research GmbH

Munich, Germany

viering, [email protected]

Abstract This paper presents a quantitative performance

analysis of the Dual-Cell High-Speed Downlink Packet Access

(DC-HSDPA) operation focused on the gain achieved by pooling

the radio resources of two carriers in the same base station and

enabling a collaborative operation (joint-scheduling) on the lower

radio layers.

Keywords - Dual-Cell; HSDPA; joint-scheduler; multi-userdiversity; frequency selectivity

I. INTRODUCTION

One main target for the evolution of 3G mobilecommunication is to provide the possibility of significantlyhigher end-user data rates compared to what is achieved withthe first releases of the 3G standards. This also refers to higherdata rates over the entire cell area including users at the celledge. 3GPP standards body has significantly enhanced the peakuser throughput as part of Release-7 with features as MIMOand Higher Order Modulation (HOM) [1] and this has helpedto improve the average user throughput to some extent.

However, the rapid increase in mobile data usage calls foradditional enablers to provide enhanced user experiencethroughout the cell, especially in the outer area of the cellcoverage.

One approach to increase the typical user experienceconsists in pooling the radio resources of two or more carriersin the same base station and enabling a collaborative operationon the lower radio layers (i.e. L2 layer) for a better resourceutilization efficiency by dynamic radio resource managementover multiple carriers. With corresponding enhancements ofthe terminal capabilities this would also allow increased datarates for users in all coverage conditions by receivingtransmissions on multiple carriers simultaneously.

Within 3GPP such operation has been investigated underthe work item Dual-Cell HSDPA operation on adjacentcarriers (hereafter DC-HSDPA) [2]. As the name suggests, thework item restricts the pooling of radio resources to twocarriers and only for the downlink direction remaining the ULwith the possibility of only one carrier utilization. The goal is afeasibility study for the new feature, including thequantification of enhancements to user throughput throughoutthe cell and the system impacts of introducing such feature tothe existing UTRA system.

2 x 5 MHz1 x 5 MHz

2 x 5 MHz1 x 5 MHz

UE1

UE2

U plink Dow nlink

2 x 5 MHz1 x 5 MHz

2 x 5 MHz1 x 5 MHz

UE1

UE2

U plink Dow nlink

Fig. 1: 3GPP Work Item DC-HSPDA operation principle

With its potential to increase peak data rates, the featureDC-HSDPA is regarded as an alternative to MIMO without thecost and complexity of multi-antennas deployment (providedthat the spectrum is available), and is claimed to achieve better

performance gains particularly in unfavorable channelconditions, e.g. at the cell edge.

This paper presents a quantitative performance analysis ofthe DC-HSDPA operation (based on the above described 3GPPassumptions), demonstrating the gains of implementing acollaborative scheduling mechanism (joint scheduler) for thetwo carriers. In section II the basic concepts and expected

benefits of the feature are described and discussed. Section IIIintroduces the simulation model used in the investigations,with its major assumptions, parameter settings and in

particular, the implemented joint scheduling scheme. SectionIV presents and reviews various selected performance resultshighlighting the advantages of DC-HSDPA in differentconditions, including a comparison with the MIMO feature.Finally, section V summarizes the findings and concludes with

an outlook on remaining open issues.

II. DC-HSDPACONCEPT

DC-HSDPA operation has the purpose of enhancing theuser experience throughout the whole cell range, in particularin outer area of the cell coverage (at the cell edge where MIMOcan not be operated with dual stream transmission), by poolingthe radio resources of two carriers in the same base station andenabling a collaborative operation (joint-scheduler) on thelower radio layers. It aims to achieve double peak rates andmore than doubled sustained data rates (compared to a single

978-1-4244-2515-0/09/$25.00 2009 IEEE


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carrier deployment) without the cost of dual antennadeployment.

In terms of system performance, DC-HSDPA operationenables efficient and flexible spectrum asset utilization offeringefficient inherent load balancing across the carriers.Furthermore, the feature is a natural and smooth evolution ofHSPA [3] in terms of radio equipment and spectrum. Thecarrier aggregation is backward compatible with legacy devicesand it requires simple network upgrade.

If a second carrier is available to the operator, it is highlyprobable that it would first be utilized for capacityenhancement by static load distribution (two independentcarriers or two times single carrier, hereafter 2xSC) beforeintroducing enhancement feature like collaborative dual carrieroperation that requires new terminal capabilities. Therefore, thesimulations carried out in this paper are regarded as a fair

performance comparison of dual carrier (DC) over 2xSC cellconfiguration.

The main sources for performance gains from thecollaborative dual carrier over the 2xSC approach are:

Frequency selectivity which depends on carrierallocation. It is most pronounced for carriers indifferent bands, giving the possibility to select the

better of the two carriers at every transmissionopportunity.

Double peak rate by assigning all resources on bothcarriers to the same user. Note that increased peak ratesrequire carrier aggregation and therefore are mutuallyexclusive with frequency selectivity

Multi-user diversity gain [4], through more users toselect from in time scheduling.

Statistical multiplexing (or trunking gain), meaningbetter resource utilization efficiency of fast dynamicover semi-static load balancing (not treated in this

presented study).

These are directly related to the resource allocation andcoordination of the two carriers making the scheduling themost important part of the DC-HSDPA feature implementation,which determines the gain that can be achieved bycollaborative over independent (2xSC) dual carrierconfigurations (joint and disjoint scheduler, respectively).

The joint scheduler can be regarded as similar to dualstream scheduling in MIMO operation, yet is simpler (due tothe orthogonal channels) and less constrained: the carriers can

be allocated to the same or different users, which wouldcorrespond to multi-user (MU) MIMO scheduling [5].

The selection of specific scheduling schemes is up to thevendors, and its precise implementation is still for furtherstudy. However, the following requirements are reasonable:

The joint scheduler shall be backward compatible tothe already implemented scheduler for single carrieroperation while fulfilling the requirements of jointscheduling for DC-HSDPA operation terminals.

For dual carrier-capable terminals, it shall utilize theavailable resources of both carriers in everyTransmission Time Interval (TTI), prefer the carrierwith the higher Channel Quality Information (CQI) incase of single carrier allocation, and allow for dualcarrier allocation whenever this brings a benefit.

For legacy terminals (non-dual carrier capable), thereshall be an operation mode with independent (i.e. non-cooperative) scheduling on the two carriers, applyingthe already available single carrier scheduler schemeson statically allocated subsets of users for each carrier.

Mixed configurations of legacy and dual carrierterminals shall be handled in an integrated way.

III. SIMULATION ASSUMPTIONS

A. System-Level Simulation ModelAMoRE (Advanced Mobile Radio Real-time Experience)

[6] is a flexible and accurate simulation environment that canbe used for testing and demonstrating the performance of IP-

based applications over emulated radio networks (likeWCDMA) providing data services. Being mainly targeted forthe demonstration and observation of radio behavior at runtimethrough a powerful and flexible graphical user interface, thesemi-static system-level simulator in the core of the tool also

presents an efficient means for the systematic generation ofperformance statistics.

The system-level model simulates a hexagonal 3-sectorizedcell layout with multiple users in one target cell andsynthetically generated interference from multiple rings ofsurrounding cells (which in the HSDPA model are assumed totransmit continuously with full power). Data channeltransmissions are simulated in full detail with fast link-adaptive

scheduling and resource allocation, error model based on link-level lookup tables and Hybrid Automatic Repeat Request(HARQ) retransmission protocol. The control channel model issimplified with fixed power allocation and error-freetransmission, yet realistic constraints in terms of signalingaccuracy and delays.

Statistical performance evaluations are taken without usermobility over a multitude of snapshots where users arerandomly dropped into the target cell and the measured

performance values are averaged over the duration of eachdrop. Channel fading and intracell interference ismodeled according to [7]; the MMSE and MIMO extension isdescribed in [8]. Throughput and delay is measured on PDCP

layer (i.e. without L2 protocol overheads and after HARQretransmissions and RLC reassembly).

B. Simulation SetupThe simulations presented in this paper were performed

under the following assumptions: The inter-site distance in thecellular topology was fixed at 1500 m, the total transmission

power per cell was 20W, of which 16W were available forHSDPA transmissions. Pedestrian channel models of typePedA and PedB were used, both for terminal velocities of3km/h. The carrier bandwidth is 5MHz with both carriers


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located in the 2GHz band. The terminals are modeled withadvanced receivers of type 3 (i.e. with 2Rx antennas andequalizing receiver). Terminals are assumed to have either64QAM or MIMO capability (i.e HSDPA category 14 or 16).Dual Carrier capable terminals do not support MIMO, but64QAM. The base stations always transmit with one antenna,except for single carrier transmissions to MIMO terminals.

The fading correlation between the two carriers in thefrequency domain was not modeled in detail insteadindependent fading processes were applied providing an upper

bound for the frequency selectivity gain. It should be notedthat, at least for the more dispersive PedB channel, independentfading is a realistic assumption.

The evaluation section typically compares Dual Carrierconfigurations (where all terminals are DC-capable and jointlyscheduled) with Single Carrier configurations of twoindependently operated carriers (2xSC) where half of the totalnumber of terminals is statically assigned on each of thecarriers, corresponding to a perfect load balance. The defaulttraffic model for all terminals is full buffer, i.e. all users can atany time be assigned any data rate subject only to schedulerdecision. For the delay statistics a streaming-like traffic modelwas used with a constant bit rate (cbr) of 256kbps.

Statistical multiplexing gain was not treated in this study.

C. Joint-Scheduling SchemeThe joint scheduling model for DC-capable terminals

assumes common Tx buffers and common scheduler andHARQ entities for both carriers in the transmitting base station.That means each packet provided from higher layers into theTx buffer can be transmitted on any carrier, and also HARQretransmissions can be allocated on the same or a differentcarrier as the original transmission.

The common scheduler entity gets, for each user, periodicchannel quality information (from the so-called CQI reports)on both carriers, computes a metric function independently foreach carrier according to the selected single carrier schedulingscheme and assigns the resources on each carrier to the userwith the highest metric value. This can be the same or differentusers on the two carriers.

In the simulations for this paper only the Proportional Fair(PF) metric was applied, but our generic joint schedulerscheme also works with any other single carrier metric such asRound Robin, Maximum C/I or even QoS-aware metrics taking

buffer status and waiting time into account [9].

The joint PF scheduler used in the investigations applies ametric function, in which the instantaneous throughput in theenumerator depends on the carrier-specific CQI whereas theaverage past scheduled throughput term in the denominator iscommon for both carriers.

The modeled scheme is a straight-forward extension ofalready existing single carrier schedulers, which leads to aflexible utilization of the available resources on both carriers,exploits frequency selectivity (as far as CQI-based metrics areapplied) and allows for the allocation of both carriers to thesame user (carrier aggregation) whenever this brings a benefit.

IV. PERFORMANCE EVALUATION

A. Capacity and Throughput IncreaseSimply doubling the bandwidth, i.e. going from single

carrier to 2xSC configuration, will also double the average totalcell throughput. Taking advantage of the joint scheduling,however, the cell capacity will additionally increase oversystems where the carriers are used independently. This can be

observed in Fig. 2 where the DC and 2xSC configurations arecompared for different channel models.

0 5 10 15 20 250

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DL cell throughput (Mbps)

cdf

Capacity Gain from Joint-Scheduler (8 users)

PedA, DC; mean = 12.71

PedA, 2xSC; mean = 10.42

PedB, DC; mean = 9.48

PedB, 2xSC; mean = 8.09

Fig. 2: Cell Throughput: Capacity Gain from Joint-Scheduler (10MHz)

The benefit of joint scheduling comes from pooling allusers on both carriers, leading to increased multi-user diversity,and from giving each user scheduling opportunities on either oftwo carriers, thus exploiting frequency diversity. In case of

burst traffic with the load varying over time (not consideredhere), the pooling of users will also provide a statisticalmultiplexing gain by balancing the load between the twocarriers at any time. In contrast to the diversity gains, this effectdoes not depend on channel properties.

2 4 6 8 10 12 14 16 18 200

2

4

6

8

10

12

number of users

meanDLcellthroughput(Mbps)

Frequency Selectivity and Multi-User Diversity Gain for Full Buffer Traffic

PedA, DC

PedA, 2xSC

PedB, DC

PedB, 2xSC

PedA, DC identical fading

PedB, DC identical fading

Fig. 3: Frequency selectivity and Multi-user diversity Gain


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Fig. 3 shows the improvement of the mean cell throughput,over different number of users, due to frequency selectivity andmulti-user diversity. In order to separate the two effects, areference curve for the DC case has been added that wasgenerated with identical fading processes on both carriers, thuseliminating the frequency diversity effect. The observed multi-user diversity gain is more pronounced at low loads itvanishes with increasing number of users, while the gain from

frequency selectivity remains and presents the majority of theoverall DC gain in this scenario.

With 2 users per sector in a PedA channel, the gain isaround 24%, for 20 users per sector, it is around 19%. ForPedB channel the gain is about 20% and 16% for 2 and 20users per sector, respectively. It must be noted that for the lessdispersive PedA channel our assumption of independent fading

processes may be too optimistic (for adjacent carriers) and thussomewhat exaggerates the frequency diversity gain.

The benefits of HOM (64QAM modulation) and MIMO aremainly seen in high geometry (good coverage) and high SNR.In contrast, DC-HSDPA transmissions can achievesignificantly higher data rates for most users, including thosenear the cell edge experiencing only low or moderate SNR.This increases the number of users having access to improveddata rates, as can be viewed in the table on Fig. 4.

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

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1

DL user throughput (Mbps)

cdf

Throughput Gain over entire Cell Range (8 users)





183,6723,11490th

281,2190,95050th

280,4800,37410th

DC Gain

(%)

PedA, DC

(Mbps)

PedA, 2xSC

(Mbps)Percentile

183,6723,11490th

281,2190,95050th

280,4800,37410th

DC Gain

(%)

PedA, DC

(Mbps)

PedA, 2xSC

(Mbps)Percentile

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

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DL user throughput (Mbps)

cdf

Throughput Gain over entire Cell Range (8 users)





183,6723,11490th

281,2190,95050th

280,4800,37410th

DC Gain

(%)

PedA, DC

(Mbps)

PedA, 2xSC

(Mbps)Percentile

183,6723,11490th

281,2190,95050th

280,4800,37410th

DC Gain

(%)

PedA, DC

(Mbps)

PedA, 2xSC

(Mbps)Percentile

Fig. 4: DL User Throughput: Throughput Gain over entire Cell Range

Compared to 2xSC, DC has a throughput gain of 28%, alsoat cell edge (represented by the 10th percentile). At extremelygood coverage, i.e. 90th percentile, the gain is somewhat lower

only at 18%. This is because the throughput is here limited bythe modulation and coding scheme and the DC configuration ismeeting its hard upper bound.

B. Delay ImpactsAs delay measurements are not meaningful with full buffer

traffic, this investigation has been performed with constant bitrate (cbr) traffic of 256kbps, which can be regarded as anexample for a video streaming service. In this scenario thesystem load increases with the number of users, and at some

point the cell edge users start suffering from increasing delays,

as the decreasing amount of assigned resources (by theresource-fair PF scheduler) is no more sufficient to maintainthe fixed nominal bit rate.

2 4 6 8 10 12 14 16 18 200

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1

1.5

2

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3

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number of users

95thpercentileofDLpacketdelay

(s)

Outage Capacity for Streaming Traffic (cbr) at 256 kbps

PedA, DC

PedA, 2xSC

PedB, DC

PedB, 2xSC

Fig. 5: DL Packet Delay: Outage Capacity for Streaming Traffic at 256 kbps

Fig. 5 shows this effect on the 95th percentile of themeasured packet delays. Assuming a tolerable delay of 1s forthe streaming service, the intersection of the delay curves withthe 1s threshold line marks the outage limit where 5% of thesimulated cases exceed that threshold, thus defining the delay-

based outage capacity. In the example of the PedB channel, thisoutage capacity increases from slightly over 11 to 14 userscorresponding to a gain of about 25%.

C. DC vs. MIMO ComparisonMIMO technique can be introduced in a HSPA network to

increase the DL peak data rate up to 28Mbps; combined withHOM it can reach up to 42 Mbps [10]. Implementing DC-HSDPA (64-QAM capable), through carrier aggregation thesame 42Mbps can be reached with twice the bandwidth, yetwithout the extra cost of 2 Tx chains in the NodeB.

In practice the achieved net data rates are much lower,considering the protocol overheads, HARQ retransmissionsand the fading variations that often prevent the selection of thehighest Modulation and Coding Scheme (MCS) necessary forthe peak rate. Fig. 6 shows a snapshot view from the AMoREsimulation, where 4 users with different capabilities and indifferent locations are successively scheduled (from full

buffers). The red and blue users close to the base station

achieve sustained maximum rates of about 25 and 15 Mbps forthe DC and MIMO users, respectively. The observed highergain (compared with the theoretical 50% peak rateimprovement for DC with 64QAM over MIMO without64QAM) is due to the better separation between carriers than

between spatial MIMO streams. About the same relative DCgain is also achieved for users near the cell edge, but fordifferent reasons: Here, neither dual stream transmission nor64QAM modulation can be applied. Although the carrieraggregation for the DC user can not always be applied due tooccasional deep fading dips, better cell edge performance fromDC over MIMO is observed.


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Fig. 6: AMoRE snapshot of comparative DC vs. MIMO Performance

Fig. 7 compares the cdf of the total cell throughput for aMIMO scenario with 8 users on two single carriers with non-MIMO scenarios in 2xSC or DC configuration. It can be seenthat the DC gain (from joint scheduling) is slightly better thanthe MIMO gain (from Tx Diversity and occasional dual streamtransmission) in all situations. Even though the assumption ofindependent fading may be too optimistic for adjacent carriersand the PedA channel, it can be concluded that the DC featureimproves the cell capacity in the same order as the MIMOfeature, and additionally allows much higher throughput forsingle users in all channel conditions.

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DL cell throughput (Mbps)

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Comparative DC vs. MIMO Performance (PedA, 8 users)

DC; mean = 12.71

2xSC; mean = 10.42

2xSC MIMO; mean = 12.27

Fig. 7: DL Cell Throughput: Comparative DC vs. MIMO Performance

This benefit comes at the expense of double bandwidth, sothe DC gain in spectral efficiency is in fact smaller than withMIMO. As, however, a second carrier and the capability for2*SC operation is already present in most deployed 3Gnetworks, this makes upgrading to DC much less costly than aMIMO deployment.

V. CONCLUSION AND OUTLOOK

In this paper a quantitative performance analysis of DC-HSDPA operation was presented, giving an overview of thefeature operation with its benefits and expected performanceimpacts in dependence of channel, load and traffic conditions.

The results identified and distinguished DC-HSDPA gainsfrom different sources: carrier aggregation, pooling gains

(multi-user diversity) and frequency selectivity, which apply inand depend on different operating conditions (such as loadlevel, traffic type and channel conditions).

Carrier aggregation allows obtaining twice the peak rate fora single user than on a single carrier. In contrast to dual streamMIMO, a doubling of the user rate can be achieved in allchannel conditions (i.e. even at the cell edge) and without theexpenses of dual Tx antennas and power amplifiers.

Joint scheduling over two carriers provides a pooling gain(over independently scheduled carriers) through multi-userdiversity when link-adaptive scheduling is applied. Even moresignificant (particularly in cases of higher system load) are thefrequency selectivity gains obtained from DC operation, whenthe channel fading on the two carriers is sufficientlydecorrelated (as is the case in dispersive channels or for largercarrier distance.

The reported investigations did not cover another importantbenefit from joint DC scheduling: the trunking gain fromstatistical multiplexing that applies for limited buffer orrandom burst traffic by improving the resource utilizationefficiency through fast dynamic instead of (semi)-static load

balancing. This will be an issue for further investigations.

REFERENCES

[1] H. Holma, A. Toskala, K. Ranta-aho, J. Pirskanen, High-Speed Packet

Access Evolution in 3GPP Release 7, in IEEE CommunicationsMagazine, vol. 45, Dez. 2007, pp. 2935.

[2] 3GPP, Feasibility study on Dual-Cell HSDPA operation - Work itemdescription, 3GPP, RAN Plenary RP-080228, Mar. 2008.

[3] H. Holma, A. Toskala, WCDMA for UMTS. England: Wiley, 2004,

pp. 307345.

[4] H. Holma, A. Toskala, HSDPA/HSUPA for UMTS. England: Wiley,

2006, pp. 137140.

[5] P. Ting, J. Chen, C. Wen, J. Chen, Efficient multiuser MIMO

scheduling strategies, in Proc. 60th IEEE Vehicular Technology

Conference, Los Angeles, 2004, pp. 11391142.

[6] I. Viering, C. Buchner, E. Seidel, A. Klein, Real-time network

simulation of 3GPP Long Term Evolution, in Proc. IEEE Symposium

on a World of Wireless, Mobile and Multimedia Networks 2007,

Helsinki, Finland , 2007, pp. 13

[7] A. Seeger, M. Sikora, A. Klein, Variable orthogonality factor: a simpleinterface between link and system level simulation for High Speed

Downlink Packet Access, IEEE Vehicular Technology Conference2003 (VTC-Fall'03), Orlando, USA, 2003.

[8] M. Wrulich, S. Eder, I. Viering, M. Rupp, "System level modeling of

D-TxAA MIMO HSDPA, IEEE Globecom 2008 WirelessCommunications Symposium, New Orleans, LA, USA, November,

2008.

[9] E. Dahlman, S. Parkvall, J. Skold, 3G Evolution: HSPA and LTE for

Mobile Broadband, UK: Elsevier, 2007, pp. 109-120.

[10] J. Bergman, M. Ericson, D. Gerstenberger, B. Gransson, J. Peisa, S.

Wager. (2008). HSPA Evolution - Boosting the performance of mobile

broadband access. Ericsson Review. No. 1, pp. 32-37.

dual cell performance evaluation

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