cong control hspa

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Performance Enhancement due to the TNL

Congestion Control on the Simultaneous

Deployment of both HSDPA and HSUPA

Yasir Zaki1, Thushara Weerawardane

1, Andreas Timm-Giel

1, Carmelita Görg

1and Gennaro Ciro Malafronte

2

1University of Bremen, TZI ComNets, Otto-Hahn-Allee NW1, 28359 Bremen, Germany

{yzaki, tlw, atg, cg}@comnets.uni-bremen.de2Nokia Siemens Networks S.P.A., Via Monfalcone 1, 20092 Cinisello Balsamo, Italy

{gennaro.malafronte}@nsn.com

Abstract — the main focus of the work presented in this

paper is to analyze the effect of the Transport Network

Layer (TNL) congestion control on the High Speed Packet

Access (HSPA) performance. The TNL and in particular the

Iub link needs to be carefully dimensioned. Firstly because

it has significant impact on the end-to-end and network

performance and secondly due to the high number of

required links in the network, the Iub is a major cost factor

for the network operators. The congestion control function

works together with the air interface scheduler and Hybrid

Automatic Repeat Request (HARQ) in order to control the

offered load to the TNL network. In this manner, the data

flow over the TNL is adequately adapted to the user’s air

interface data rate and to the available TNL capacity

avoiding congestion in the transport network. In addition,the paper focuses as well on the effects of the simultaneous

deployment of both High Speed Downlink and Uplink

Packet Access (HSDPA & HSUPA). This is done by

comparing the results from deploying HSDPA or HSUPA

separately in the system against the simultaneous

deployment of both (To the best of our knowledge, there are

only few publications in which this has been investigated,

especially in combination with the Congestion Control). The

reason for such a comparison is to highlight the effects that

appear when both are deployed together, since most of the

previous studies were focusing only on either HSDPA or

HSUPA, whereas the final goal is to use both together in one

system. The simulation results presented in this paper

confirm that the congestion in the transport network can becontrolled in such a way that the available TNL capacity

can be effectively utilized and hence the performance of

HSPA network can be significantly improved in all aspects.

In the ComNets TZI working group at the university of

Bremen, a number of projects focusing on the TNL

dimensioning and TNL features development for the HSPA

network are being worked on [14, 15, 16, 17, 18, 19 and 20].

Index Terms — HSDPA, HSUPA, HSPA, Congestion

Detection, Congestion Control

I. INTRODUCTION

HSPA is an evolution of the existing 3GPP WCDMARelease 99 (R99) standard. It aims to enhance the data

packet traffic transmission on both downlink and uplink.

It significantly improves the system throughput, increasesthe system capacity, reduces the delay of the system

compared to R99 system and also can support higher per

user data rates (theoretically up to 14.4 Mbps in the

downlink and 5.76 Mbps in the uplink).

Both HSDPA and HSUPA introduce similar new

features: HARQ is used to recover erroneous air interfacetransmissions; a faster scheduling is located at the Node

B which is much closer to the air interface. Moving the

scheduler from the RNC (in R99) allows a better

adaptation to the predicted radio channel and thus a

shorter Transmission Time Interval (TTI) of 2ms is used

for HSDPA and optionally for HSUPA. Additionallythere are still some unique features that each extension

uses separately, for example the Soft Handover (SHO) is

only supported in HSUPA since the other Node B can

receive the UE transmission if in vicinity. In HSDPA the

Adaptive Modulation and Coding (AMC) is used to adapt

the modulation rank and coding rate to the current radio

channel condition of each user, which is not supported in

HSUPA due to uplink power constraints. The HSPA

UTRAN (UMTS Terrestrial Radio Access Network) has

the same network structure as the R99 UTRAN (see

Figure 1).

Figure 1. UMTS R99 network

In order for UMTS R99 to be able to support the HSPA

enhancements, several modifications are required in the

WCDMA R99 physical (PHY) and medium access

JOURNAL OF NETWORKS, VOL. 5, NO. 7, JULY 2010 773

© 2010 ACADEMY PUBLISHER doi:10.4304/jnw.5.7.773-781



control (MAC) layer. Figure 2 shows the HSPA (HSDPA

R5 [1] and HSUPA R6 [2]) protocol architecture.

PHY

MAC-es

MAC-e

MAC-d

RLC

P H Y

M A C

R L C

PHY

MAC-e

P H Y

M A C

TNL

EDCH

FP L 1 - h s L 2

H S -

D S C H

F P

L 1TNL

L 1

L 2

H S -

D S C H

F P

L 2

M A C

- c / s h H S

-

D S C H

F P

TNL

EDCH

FP

MAC-es

MAC-d

RLC

L 1

L 2

D S C H

H S -

F P

M A C - d

R L C

TNL

UE Node B DRNC SRNC

U u I u

b I u

r

HSUPA

HSDPA

Figure 2. HSPA protocol architecture

II. HSPA TNL CONGESTION CONTROL OVERVIEW

The basic approach of the HSPA Iub congestion

control is to control the Frame Protocol (FP) data rate in

case of congestion. In fact this algorithm provides a

possibility to the upper layers such as RLC and TCP torecover from congestion by minimizing the number of

transport network packet losses. Further, the algorithm

provides also a mechanism to adaptively reduce the

offered traffic to the transport network according to the

available transport bandwidth under congestion

situations. The rate reduction does not mean degrading

the per-user throughputs but just adapting the MAC data

flows over the Iub to the available TNL bandwidth. All

these activities guarantee the achievable throughput by

reducing the packet losses and thus minimizing the higherlayers retransmissions. Further the congestion control

approach assures that the MAC data flows with the same

statistical congestion detection probability are treated in afair way. “Fair” means that the MAC-d of UE’s with

similar radio conditions and throughput has also similar

rate reduction in case of Iub congestion.

The HSPA Iub congestion control consists of two basic

functionalities: congestion detection and congestion

control. The congestion detection is realized in the Node

B for HSDPA and in RNC for HSUPA. This algorithm

can detect any loss of frames or corrupted frames and

such event is considered as the server upcomingcongestion situation. Furthermore, this algorithm also

considers the high delay variation of data flow as

foreseen congestion situation and reacts to avoid such

situation happening in future. In all these situations, thecongestion detection module sends congestion indication

messages to the congestion control module in the Node Bthat takes appropriate actions to control the incoming

traffic.

III. CONGESTION DETECTION

The congestion detection can be either reactive or

preventive as discussed in [3]. The preventive congestiondetection scheme tries to identify a possible congestion

before it occurs, whereas the reactive congestion

detection scheme detects the congestion only at its

beginning. In real HSPA system deployments it ispossible to have both reactive and preventive Iub

congestion control schemes working in parallel. Thispaper investigates the performance of a fully fledged

HSPA Iub congestion control algorithm in which both

approaches are combined.The reactive Iub congestion detection mechanism

detects the congestion upon detection of packet losses at

the transport network. The loss can be identified either

due to corrupted frames or due to loss of one or severalcomplete frames. The later is mostly common due to the

bursty nature of losses. The corrupted frames can be

identified during the payload CRC check. The most

common frame errors in TNL network can be categorized

as follows:

A. Missing a last segment or tail of the FP frame

When the last segment or the tail of the FP PDU is lost,the receiver waits until it receives the last segment of the

next frame to be reassembled. This results in creating a

large frame with an invalid CRC during the reassembly

process. Both original frames are lost.

B. Missing any segment except the tail of a frame

The receiver can reassemble a FP frame having aninvalid CRC due to a missing segment or due to an

insertion of a foreign segment. Since the tail of the frame

is preserved, the next frame can be detected again.

C. Loss of complete frames

When a burst of cell losses occurs at the transport

network, one FP frame or several FP frames can be lost.

These bursty losses are very common in HSPA networks,

when congestion persists. These losses can be detected by

monitoring the Frame Sequence Number (FSN).

Error type A and B can be easily identified by the FP

payload CRC checksum. Error Type C (Loss of completeframes) can be identified by using a frame sequence

number (FSN) at the frame header. In both situations in

which the losses can be experienced, the congestion is

considered to be severe and an indication is sent to the

congestion control (CC) module to control the input

traffic. Up to now, the reactive congestion detection isconsidered. Next the preventive approach is discussed in

detail.

The preventive congestion detection is in charge of

detecting potential Iub packet losses before they occur.

The preventive based delay build-up algorithm monitors

the FP PDU delay variation for the correctly received FPframes through the transport network for each MAC-d

flow. The figure below shows the delay variation for

several FP PDU transmissions with respect to the RNC

and Node B reference counters.

Figure 3. FP PDU delay build-up behaviors through TNL network

774 JOURNAL OF NETWORKS, VOL. 5, NO. 7, JULY 2010

© 2010 ACADEMY PUBLISHER



According to Figure 3, the delay build-up algorithm

monitors the TNL delay variations for each arrival of aFP frame at the Node B. For example, the delay variation

between frames, i and i-1, is given in the following

formula.

1i 1),-i(i,TNL)t( DELAYi (1)

Where )t( i is the delay variation between i and i-1.

The accumulated delay variation is given by R(ti):

1i 1),i(i,ΔTNL)t()R(t j

2i

DELAYi

j

2i

i

(2)

Once the accumulated delay variation exceeds a certain

threshold within a certain time window, congestion is

assumed and an indication is sent to the CC module.Since it is based on a probabilistic approach, the

indication is considered to be a non severe congestion.

IV. CONGESTION CONTROLThe Iub congestion control is done in the Node B. The

main difference between the HSUPA CC and HSDPA

CC [3] is that the E-DCH congestion control cannot relyon any rate control provided by the flow control, since E-

DCH has no flow control by its standard. The Congestion

control algorithm (E-DCH_CC) has to monitor the uplink

(UL) E-DCH Iub rate (per MAC-d Flow) in order to

apply Iub UL rate deduction properly. Moreover the E-

DCH_CC supervises the Serving-RLS status (i.e. if the

Node B is the serving or non-serving RLS for the

concerned UE) and it accordingly triggers the specific

congestion control action. The Node B can change from

serving to non-serving and vice-versa without changingthe FP instance and the associated transport bearer.

The congestion control mainly has two states:

congestion control state and the non-congested state

which is called FC state in HSDPA congestion control

and shown in Figure 4.

Figure 4. Flow state machine for CC

At the congestion control state, the CC mechanism

uses the AIMD (a, b) algorithm [4, 5, 6, 7, and 8]. The

CC monitors the available capacity of the TNL network

and controls the incoming traffic flows. In HSUPA, itdecides the allowed capacity over the radio interface for

each user flows that is signaled back to the E-DCH

scheduler in order to decide the uplink grants of the next

TTI for the S-RLS users. In HSDPA, the Node B sends a

CA message to RNC in order to control the offered traffic

to the TNL network. The detailed description of the CCalgorithm can be found in [8].

V. SIMULATION MODEL

The HSPA simulation model is developed using the

OPNET simulation environment [9]. The main purpose of

this model is to perform TNL feature analysis. In addition

the model is also designed to support individualperformance analysis on the protocols like RLC,

TCP/UDP and application layers on a per user level. The

simulation model consists of both HSDPA and HSUPA.

Figure 5 shows an overview of the simulation model. Thered part is the implemented HSUPA protocols whereas

the yellow one represents the HSDPA protocols.

Internet or External

User

ApplicationTCPIP

RLCMAC-dMAC-esMAC-e

MAC-d

MAC-e MAC-hs

EDCHFP

HS-DSCH

FP

AAL2/ATM

MAC-dMAC-es

MAC-d

EDCHFP

HS-DSCH

FP

AAL2/ATM

RLC

ApplicationTCPIP

R A B

c o n n e c t i o

n s

S e r v i n

g R L S

Node B

UE

RNC

Figure 5. HSPA simulation model overview

In addition, the HSDPA/E-DCH scheduler, SHO,

HARQ, NSRLS (Non Serving Radio Link Set) traffic,

HSDPA/HSUPA congestion control (CC), and HSDPA

flow control were implemented in the simulation model.

In the network configuration, there are three different

traffic types carried in the TNL network: UMTS R99,

HSDPA and HSUPA. In order to handle their different

QoS requirements a traffic separation solution is applied.

A 3 VPs (Virtual Paths) traffic separation solution is

shown in Figure 6.

Node B RNC

R’99 Data Streams

(symmetric)

HSDPA Data Streams(asymmetric)

HSUPA Data Streams(asymmetric)

HSUPA User Data (E-DCH)

HSUPA Inband Signalling

HSDPA Inband Signalling

HSDPA User Data (HS - DSCH)

VPCBR

VPUBR/UBR+

VPUBR/UBR+

high priority trafficATM Service CategoryUBR+

ATM Service Category CBR

ATM Network

Figure 6. The three VP traffic separation solution

The three VPs solution is implemented in the

simulation model where each separate VP is assigned to

transport a traffic type but with individual QoS setting. ACBR (Constant Bit Rate) VP is used for R99; whereas

UBR+ (Unspecified Bit Rate +) VPs are used for HSDPA

and HSUPA since their traffic is treated as best effort

traffic. As R99 traffic mainly consists of delay sensitive

real time traffic like voice, it is configured as a higher

priority over HSPA traffic in order to protect its strictdelay QoS. The impact of different ATM configurations

for traffic separation is analyzed in [12].

VI. TRAFFIC MODELS & SIMULATION SCENARIOS

The packet traffic model is configured at the

application layer of the end user entities. The TCP

protocol is configured with New Reno version. Thetraffic model applied in this investigation generates heavy

traffic to be able to monitor the effects best. The traffic

model uses FTP with parameters as shown in table I.





Table 1. FTP TRAFFIC MODEL FOR HSPA

FTP Traffic Model (Worst-FTP) Parameters

File size Constant Distribution

Mean file size = 3 Mbyte

Inter-arrival time ~ 0.0 seconds

which means immediately after the first file

downloading of the second file is started

In this FTP traffic model, all users are uploading very

large files continuously all the time. Users have always

data to be transmitted at any time and demanding the

network resources continuously. Therefore such a traffic

model is considered as a worst case traffic from thenetwork point of view.

The simulations scenarios are classified into three

categories depending on the deployment of the HSPA

traffic (either HSDPA alone, HSUPA alone, or both

combined together). Each category consists of two

scenarios: one is configured with TNL congestion control

called “with CC” and the other is configured without

TNL congestion control feature denoted as “without CC”.All simulation scenarios are shown in table II. The next

section presents the simulation results and analysis.

Simulation scenarios

Config. I Combined HSDPA/HSUPA With CC

Without CC

Config. II HSDPA alone With CC

Without CC

Config. III HSUPA alone With CC

Without CC

VII. CONFIGURATION (I) RESULTS & ANALYSIS

All simulation scenarios run for 1000 seconds. The TNL

network is configured with a last mile rate of 4Mbps.This in turn is divided into 3 different VPs: Two 2MbpsUBR+ VPs, one is allocated for the uplink HSUPA traffic

and one for the downlink HSDPA traffic; and one 2Mbps

CBR VP is allocated for R99 traffic.

From the 2Mbps HSDPA and HSUPA VP, 100 kbps

capacity is allocated for the HSUPA and HSDPA in-bandsignaling respectively. As for the R99 VP the 2 Mbps are

completely utilized by the R99 traffic for this analysis. In

this context, R99 is considered to be in a worst case

scenario utilizing the full allocated capacity. Following

the main parameter configurations for the simulations are

given:

TTI = 2 ms HSDPA, 10 ms HSUPA

Noise Rise = 6dB

Others-to-own interference factor = 0.6

Number OF HARQ processes per user flow: 4

RLC protocol: Operate in RLC AM mode

TCP protocol: TCP New Reno version

The simulation is performed by configuring six users

in the cell (6 HSDPA in downlink and 6 HSUPA in

uplink). Two scenarios are investigated in this

configuration one with CC and one without. Apart from

the use of the congestion control functionality bothscenarios use the same system and protocol parameter

configurations.

A. ATM link throughput

Figure 7 and Figure 8 show the downlink ATM link

throughput and its probability distribution (CDF)

respectively for the two simulation scenarios. A higher

burstiness of ATM link throughput can be noticed for the

“without CC” scenario as compared to the “with CC”simulation scenario.

Figure 7. HSDPA ATM link instantaneous throughput with/without CC

Figure 8. HSDPA ATM link throughput CDF curve with/without CC

Figure 9 and Figure 10 show the uplink ATM link

throughput and its probability distribution (CDF)

respectively for the two simulation scenarios. Similarly to

the previous results on the downlink, a much higher

burstiness of ATM link throughput is shown for the

“without CC” scenario as compared to the “with CC”

scenario.

Figure 9. HSUPA ATM link instantaneous throughput with/without CC





Figure 10. HSUPA ATM link throughput CDF curve with/without CC

B. HSUPA Uu Air interface throughput and Noise Rise

The cumulative probability distribution (CDF) of the

overall air interface throughput and the noise rise areshown in Figure 11 and Figure 12 respectively.

The cell throughput is measured at the Uu interface,

more specifically by taking the sum of the MACe

throughput of all HSUPA users. The system noise rise is

calculated according to:

N

j

j

NR

1

)1(1

1

(3)

Where α is the other to own interference ratio which isassumed to be a constant value of 0.6, N is the total

number of users in the cell and η j is user j uplink load

factor which is calculated according to:

W R

N Eb

j

0

11

1 (5)

Where Eb/N0 is the energy per bit to noise power

spectral density ratio, R is the UE data rate and W is the

chip rate of the HSUPA which is equal to 3.84 Mcps.

The figures depict a large variation of the cell

throughput and the system noise rise for the “without

CC” scenario compared to the “with CC” scenario. A

large average cell throughput is achieved by using the

congestion control compared to the other scenario.

Figure 11. HSUPA cell throughput CDF curve with/without CC

Figure 12. HSUPA Noise Rise NR CDF curve with/without CC

C. ATM Cell Discards

The total number of ATM cell discards for the

HSDPA/HSUPA traffic is shown in Figure 13 andFigure14 respectively. A huge number of ATM cell discards can

be observed for the “without CC” case. Such effect is

expected since the congestion control algorithm is not

used and the system is congested. This will lead to even

more congestion at the TNL network causing many cell

losses because many retransmissions are triggered by

RLC and TCP layers causing more and more traffic to the

TNL network. Most of these lost packets are recovered

by retransmissions either at the RLC or TCP level; thoseretransmissions cause additional traffic to the network.

Figure 13. HSDPA ATM Cells Discard

Figure 14. HSUPA ATM Cells Discard

A clear advantage of using the congestion control

algorithm can be seen from the above figures. The packet

losses at the TNL are significantly reduced which in turn

reduce the higher layer retransmissions and the resultantTCP end-to-end delays.

D. Application Throughput

The per-user application throughputs for all users aswell as the overall application throughput are shown in

Figure 15, Figure 16, Figure 17 and Figure 18 for both





HSDPA and HSUPA respectively. The per-user

throughput is calculated by considering the file size of 3MByte divided by its upload/download time. It can be

noticed that the per-user/overall application throughput

for the CC based simulation achieves a clear gain

compared to the other scenario for both the uplink anddownlink.

Figure 15. HSDPA per user application throughput with/without CC

Figure 16. HSDPA total application throughput with/without CC

Figure 17. HSUPA per user application throughput with/without CC

Figure 18. HSUPA total application throughput with/without CC

VIII. CONFIGURATION (II) RESULTS & ANALYSIS

The simulation is performed by configuring only sixHSDPA FTP users in the cell (No HSUPA is configured

for the Uplink). The simulation parameters for this

configuration are exactly the same configured for the

previous one. Except the congestion control functionality,

both simulation scenarios use the same system andprotocol parameter configurations.

It can be seen from Figure 19 that there is a clear

advantage of using the congestion control mechanism interms of having higher per user application throughput

compared to the case without CC.

Figure 19. HSDPA (separate) per user app. throughput with/without CC

Figure 20 and Figure 21 show the per user/total

application throughput of running HSDPA separate

compared against deploying it with HSUPA. From the

results it can be seen that deploying HSUPA affects theperformance of HSDPA especially in the cases where theCC algorithm is not used. The reason for that is mainly

because the HSDPA RLC and TCP ACK/NACK(s) that

are carried through the uplink (HSUPA) are getting

delayed and discarded due to the HSUPA load.

Furthermore a congested uplink leads, as explainedbefore, to delaying the acknowledgments which may

cause HSDPA RLC/TCP to do unnecessary

retransmissions.

What can also be noticed is that having the CC

algorithm activated helps to reduce these effects and to

keep the throughput relatively the same as in the separate

scenario (the green and blue bars in the figures).

Figure 20. HSDPA (separate) compared to HSDPA (combined with

HSUPA) per user app. throughput

Figure 21. HSDPA (separate) compared to HSDPA (combined withHSUPA) total app. throughput

IX. CONFIGURATION (III) RESULTS & ANALYSIS

The simulation is performed by configuring only six

HSUPA FTP users in the cell (No HSDPA is configuredfor the downlink). The simulation parameters for this





configuration are exactly the same configured for the

previous one. Except the congestion control functionality,both simulation scenarios use the same system and

protocol parameter configurations.

Figure 22 shows the per user application throughput of

deploying HSUPA separate with and without the CCalgorithm. The result shows a higher application

throughput for the with CC case.

Figure 22. HSUPA (separate) per user app. throughput with/without CC

Figure 23 Figure 24 show per user/total applicationthroughput of the separate deployment of HSUPA

compared with the simultaneous deployment with

HSDPA. The results show that deploying HSDPA does

affect the HSUPA performance especially in the without

CC scenario. The reason is similar to the one explainedbefore in configuration 2, because now the HSDPA flow

in congested which in turn leads to delaying and

discarding the HSUPA RLC/TCP acknowledgments.

Which means that having the CC algorithm in

congested scenarios leads to significant gain in the per

user/overall performance, which can be seen in the green

and blue bar in the figures.

Figure 23. HSUPA (separate) compared to HSUPA (combined with

HSDPA) per user app. throughput

Figure 24. HSUPA (separate) compared to HSUPA (combined with

HSDPA) total app. throughput

X. CONCLUSION

This paper shows the different aspects of the TNL

congestion control algorithm in the HSPA simulation

model. The effects of the TNL congestion control

algorithm for the simultaneous deployment of both

HSDPA and HSUPA performance are presented.The results showed that using the congestion control

algorithm leads to significant performance enhancements,

ranging from higher per user and total application

throughput, reducing the losses over the TNL network significantly, lower burstiness and better resource

utilizations by reducing the overall number of

retransmissions.

In addition, the results also showed the effect of

deploying both HSDPA and HSUPA together in one

system. The RLC/TCP acknowledgments that are being

carried by the opposite direction are getting delayed andin some case even discarded, leading to reducing the

performance slightly when the CC algorithm is in use,

whereas in the case the CC algorithm in inactive the

performance of both HSDPA and HSUPA are

significantly reduced due to TCP mainly because the TCP

acknowledgments that are being carried over the oppositedirection suffers from higher delays and even discards in

the high loaded situations (congested link).

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paper award, in Proc. OPNETWORK 2007, September,

2007, Washington DC, USA, 2007

[20] X.Li, Y.Zeng, B. Kracker, R.Schelb, C.Görg and A. Timm-

Giel, “Carrier Ethernet for Transport in UMTS Radio

Access Network: Ethernet Backhaul Evolution”, (acceptedfor publication) 2008 IEEE 67th Vehicular Technology

Conference VTC2008-Spring, May 2008, Singapore, 2008.

Yasir Zaki received his bachelor (B.Sc.) degree in

Electronics and Communication at the University of Baghdad,Iraq in 2004 and master degree (M.Sc.) in Communication and

Information Technology at University of Bremen, Germany in

2007.

After completing his bachelor degree he was awarded a

DAAD scholarship to finish his master studies in Germany.

Then after completing his master degree he joined the Center

for Computer Science and Information Technology (TZI) of the

University of Bremen in the Communication Networks group as

a scientist researcher and a PhD candidate in 2007. He worked

in the industrial research project funded by Nokia Siemens

Networks on performance optimization of UMTS/HSPA radio

networks and transport networks from 2007 to 2008. Starting

from 2008 he started working in the 4WARD European project

that is focusing on the Future Internet; where he is mainlyfocusing on the network virtualization. Currently he is

investigating how the LTE (Long Term Evolution) system can

be virtualized, the wireless resources in particular and how this

could be shared between multiple virtual operators.

Mr. Yasir Zaki has published a number of scientific papers in

the field of communication networks.

Thushara Lanka Weerawardane received bachelor (B.Sc.)

degree in Electrical Engineering at the University of Moratuwa,

Sri Lanka in 1998 and master degree in Communication and

Information Technology at University of Bremen, Germany in

2004.

He worked as an assistant network manager in the

department of electrical engineering and as a system engineer

for Lanka Educational and Research Network (LEARN) in Sri

Lanka from 1999 to 2002. After completing his master degree,

he joined Center for Computer Science and Information

Technology (TZI) of the University of Bremen in the

Communication Networks group as a scientist researcher in

2004. He led the industrial research project funded by Nokia

Siemens Networks on performance optimization of UMTS/HSPA radio networks and transport networks from 2004

to 2007. His main responsibilities are UMTS/HSPA based

protocol design and development, HSPA (HSDPA/HSUPA)

simulator design and development for performance analysis of

HSPA radio networks and transport networks, optimization of

the HSPA transport network (Iub/Iur) by deploying different

congestion control and flow control features. Currently, he is

leading an LTE simulation research project funded by Nokia

Siemens Networks. In this ongoing research project, LTE

system level simulator design and development for the

optimization of LTE transport networks are the main

consideration.

Mr. Thushara Weerawardane has published many scientific

papers in the field of communication networks and is a memberof IEEE.

Andreas Timm-Giel, Dipl.-Ing in Electrical

Engineering/Information Technology (EE/IT) at University of

Bremen, Germany, 1994, Dr.-Ing. (PhD) in EE/IT on radio

channel modeling, University of Bremen, 1999.

From 1994 – 1999 he led a group at the University of

Bremen, that participated in several European R&D projects on

mobile and satellite communications. Starting in January 2000

he joined Media Mobil Communication GmbH as Technical

Project Leader of the EU funded project SATISFY2000. He was

involved in the technical and commercial set up of the mobile

satellite network and service provider M2sat Ltd. as TechnicalProduct Manager and Manager Network Operations. In

December 2002 he joined the Communication Networks Group

at the University of Bremen as senior researcher and lecturer.

He is leading several industry, national and EC funded research

projects at the university. Since October 2006 he is additionally

directing the interdisciplinary concerted activity “AdaptiveCommunications” of the Center for Computer Science and

Information Technology (TZI) in Bremen. His research interests

are adaptive mobile and wireless communication and sensor

networks.

Dr Timm-Giel is author or coauthor of 10 book contributions

and more than 65 reviewed publications in journals and on

international conferences. Dr. Timm-Giel is frequent reviewer

and TPC member for international conferences and journals andis Member of IEEE and VDE/ITG.





Carmelita Görg received her diploma degree from the

Department of Computer Science, University of Karlsruhe and

the Dr. rer. nat. degree and the appointment as lecturer from the

Department of Electrical Engineering, Aachen University of

Technology.

From 1985 until 1989 she worked as a consultant in the field

of communication networks. Since 1989 she has been working

as a group leader and since 1997 as an Assistant Professor at the

Communication Networks Institute, Aachen University of

Technology. Since 1999 she is leading the Communication

Networks Group (ComNets) at the University of Bremen within

TZI (Center for Computer Science and Information

Technology) and MRC (Mobile Research Center). Her research

interests include: Performance Analysis of Communication

Networks, Stochastic Simulation, Rare Event Simulation, High

Speed Networks, Personal Communication, Wireless Networks,

Mobility Support, New Services and Applications in

Telecommunication Networks, Network Virtualization.

Prof. Görg has been active in European projects starting with

the RACE program. She has been an evaluator and auditor forthe European Commission. The research group in Bremen

consists of about 15 Ph.D. students / research assistants, which

are funded by the state of Bremen and third-party projects

(European projects, DFG projects, BMBF projects, bilateral

industry projects). Prof. Görg has published a large number of

scientific papers in the field of communication networks. She is

a member of the board of the ITG (Information Technology

Society, Germany) and speaker of the ITG working group 5.2.1

on "System Architecture and Traffic Engineering".

Gennaro Ciro Malafronte received master degree in

Electronic Engineering in 1999 and PhD in Electrical

Engineering on Electrical and Electronic Measurements in 2003

at the University of Naples “Federico II”.In 2001, he joined the Italian COM division of the Siemens

Corporation, then merged in the Nokia Siemens Networks in

2007. He started his activity at Siemens COM for concept

analysis of Smart Antennas and Software Radio Technology.

He then worked as Sales Support for some UMTS service

providers in Europe. He was involved in special projects in

collaboration with the European Space Agency (ESTEC) for

requirement specifications of satellite transmission paths in the

terrestrial Siemens UMTS systems. Since 2004 he joined the

Siemens System Engineering Transport Expert Group and he

focused his activity in the optimization of the transport features

of UMTS terrestrial interfaces (Iub,Iur, Iu). In that field he was

responsible for the definition of HSDPA/HSUPA Iub/Iur

congestion control algorithms and he contributed to the 3GPP

for the definition of standardized procedures for Iub/Iur

congestion control.Dr. Gennaro Ciro Malafronte holds a number of patents in

the field of Iub/Iur HSDPA/HSUPA congestion control as

“Method for congestion control with macro diversity” (EP 1

816 879 A1), “Controlling congestion over a non -serving

branch” (EP 1 901 493 A1), “Method for decoupling congestioncontrol in a cascade of network elements of an UMTS radio

access network” (WO 2008/064983 A2) “Controlling

congestion detection in HSDPA systems” (WO 2008/037357A1), He is co-author of a number of papers in the field of

Iub/Iur HSDPA/HSUPA congestion control. His current field of

interest is Transport Optimization for LTE systems.



cong control hspa

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