1
Performance of HSDPA and HSUPA at 900/2000
MHz bands
João Pedro Roque1, Sérgio Pires
2 and António Rodrigues
1
1Instituto de Telecomunicações / Instituto Superior Técnico
Technical University of Lisbon, Lisbon, Portugal 2Celfinet, Portugal
Abstract— The main purpose of this paper is to study the High
Speed Downlink Packet Access (HSDPA) and High Speed Uplink
Packet Access (HSUPA) performance at 900/2000 MHz bands,
considering a multiple users and services scenario. The intention
is to evaluate the traffic management between the two carriers,
the coverage and capacity aspects. A simulator was developed to
study the multiple users’ scenario, enabling the analysis of
network performance by varying several parameters. In order to
better evaluate the system HSDPA and HSUPA 900/2000 MHz,
two different strategies were applied in the network, the “Carrier
2000 Loading” and the “Priority Service” strategy.
Keywords - UMTS, HSDPA 900/2000 MHz, HSUPA 900/2000
MHz, Traffic Management Strategies, Capacity, Coverage.
I. INTRODUCTION
UMTS carriers are currently used by data services based on the HSDPA and HSUPA technologies, which can now deliver peak data rates of up to 7.2 Mbps and 1.45 Mbps, respectively. The coverage of these services is unfortunately limited in the standard UMTS 2000 MHz band. This, results in a significant reduction of the practical data rates that can be delivered, especially inside large buildings, as well as in rural areas. One cost-effective way to address this issue is to deploy the mobile broadband services in the Global System for Mobile Communications (GSM) 900 MHz band, where the propagation characteristics are much more favourable when compared to the regular 2000 MHz band. This solution is referred to UMTS 900.
Furthermore, the UMTS deployed at 2000 MHz frequencies, where the signal attenuation is higher than at 900 MHz, requires fairly high site density making a challenge to match existing GSM 900 coverage with the same sites. Thus, UMTS can take benefit of the better signal propagation at 900 MHz, improving the indoor coverage and the cell sizes.
Hence, the main purpose of this paper is to study HSDPA and HSUPA performance at 900/2000 MHz bands, considering a multiple users and services scenario. The intention is to evaluate the traffic management between the two carriers, the coverage and capacity aspects, such as average network throughput and satisfaction rate, among others. A comparison of HSDPA performance for 5, 10 and 15 HS-PDSCH codes is addressed, as well as the different capacity impacts of the increase of the number of codes. The objectives were accomplished through the development and implementation of
a simulator that enables the analysis of HSDPA and HSUPA multiple users’ model at 900/2000 MHz, being capable to produce results according to several parameters.
The remainder of this paper is outline as follow. Some basic concepts necessary to understand the UMTS, HSDPA, HSUPA and UMTS 900 technologies are explained in section II. In section III, it is presented the multiple users’ model. In section IV, the results analysis is described. Finally, in section V, the conclusions are draw and the future research purposed.
II. BASIC CONCEPTS
A. UMTS
Since the beginning, UMTS network has been designed to
support any type of services, where each service does not
require particular network optimisation, whereas the 2nd
generation systems were designed for efficient delivery of
voice services. The UMTS network must be able to deliver
high and reasonably constant bit rate, to avoid high delay
connections. These bit rate and delay requirements may be
achieved in a cost efficient way by utilising the Quality of
Service (QoS) differentiation features that are available in
UMTS. Thus, when the system load is getting higher, it
becomes more important to prioritise the different services
according to their requirements, through the QoS.
B. HSDPA
The HSDPA concept was designed with the purpose to
improve the downlink (DL) packet data throughput, being
deployed on the top of WCDMA network and launched in
March 2002. HSDPA is also capable to improve capacity and
spectral efficiency, sharing all network elements with Release
99.
The HSDPA performance depends significantly on the
network algorithms, deployment scenarios traffic, QoS and
mobile terminal (MT) receiver performance and capability.
There are 12 MT categories in HSDPA, being the achievable
maximum data rates ranging from 0.9 to 14.4 Mbps.
C. HSUPA
HSUPA specification work started with focus on evaluating
potential enhancements for the uplink (UL) dedicated
2
transport channels, after the successful finalization of the first
version of HSDPA. Hence the first version was launched in
December 2004 by the 3rd Generation Partnership Project
(3GPP), being known as HSUPA Release 6.
HSUPA emerged to improve capacity and data rates in the UL
direction, being possible to achieve 1 to 2 Mbps data rates
compared to Release 99’s 384 kbps.
This technology uses most of the basic features of Release 99
in order to work, such as power control loop and Soft
Handover (SHO) which are essential for HSUPA operation.
The only change is a new way of delivering user data from the
user equipment (UE) to the Node B.
Similar to HSDPA, performance in HSUPA depends on
parameters such as network algorithms, deployment scenario,
MT transmitter capability, Node B receiver performance and
capability and type of traffic. Thus, there are 6 MT categories
for HSUPA, being the achievable maximum data rates ranging
from 69 kbps to 4.059 Mbps
D. UMTS 900
The main feature of UMTS 900 is to provide a better indoor
coverage in existing UMTS deployment areas and enabling
larger cell sizes in new UMTS areas, being possible to use the
same services and the same peak data rates as used by UMTS
2000.
Hence, deploying UMTS 900 with HSPA (High Speed Packet
Access) by reusing the existing GSM sites allows mobile
operators to offer UMTS services, such as high data rate
multimedia services, to the benefits of the consumers.
When there is a hot spot, e.g. tourist places, train stations, etc,
where more capacity is needed, higher frequency bands, such
as 2000 MHz band, can be used to offer additional capacity, as
shown in Figure 1.
Figure 1. UMTS coverage at the 900MHz and 2000 MHz,
extracted from [4].
Actually, the cell area with UMTS 2000 is from 2.5 to 3.0
km2, while in UMTS 900 the cell area can be 2.5 times larger,
7 to 8 km2. On the other hand, UMTS 900 can reduce the
required number of base station sites by 60 %, while
maintaining the same coverage [1], as illustrated in Figure 2.
The UMTS 900 voice and data have higher coverage, when
compared with UMTS deployed at 2000 MHz frequencies.
Hence, the deployment of less base station sites directly
implies lower cost for the network.
Figure 2. Suburban cell size with 95 % indoor coverage,
extracted from [2].
Concerning the carrier separation, when deploying macro
cellular UMTS 900 in urban area and rural area in co-
existence with another UMTS 900 network, the carrier
separation between two UMTS networks should be 5 MHz or
more, similar to the UMTS deployment in 2000 MHz band.
Concerning the traffic management between UMTS 900 and
UMTS 2000, it is believed that all, or at least, most of UMTS
900 handsets will have UMTS 900/2000 dual-band capability.
Taking into account that UMTS 900 cell range is larger than
UMTS 2000, in a dual-band UMTS 900/2000 network UMTS
traffic should be sent to UMTS 2000 layer (a). When possible,
leaving UMTS 900 layer to handle traffic in the area where
there is no UMTS 2000 coverage (b), as shown in Figure 3.
Figure 3. Traffic management between UMTS 900 and UMTS
2000, extracted from [4].
As a conclusion, the most significant benefit of deploying
UMTS in 900 MHz frequency band comes from the fact that,
compared to 2000 MHz band, radio wave propagation pathloss
at 900 MHz is much smaller. So, offering the same service
(data rates) and same coverage, the required number of sites in
900 MHz band is reduced by 60% compared to that in 2000
MHz band, [4]. This will bring economic benefit on UMTS
operator’s investments and makes it possible to propagate
benefits to the end-users in terms of wider coverage and
possibly lower level of usage costs. UMTS 900 will be
deployed by reusing the GSM sites within the existing service
area. Deploying UMTS 900 with HSPA in rural area by
reusing the existing GSM sites is a cost-effective solution for
mobile operators to offer UMTS services, such as high data
rate multimedia services, whereas deploying the UMTS at 900
MHz band in urban areas can improve indoor coverage.
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III. MODELS AND SIMULATOR DESCRIPTION
1) HSDPA and HSUPA models
In this section, a description of the HSDPA and HSUPA 900/2000 MHz model for the analysis of traffic management between Node Bs of 900 MHz and 2000MHz is presented. The objective of this model is to know the network capacity, average satisfaction rate and the instantaneous throughput available, according to the topology introduced in the user interface, which allow to modify several parameters, such as, Node B transmission power, number of HS-PDSCH codes for HSDPA simulator, Node Bs and MT antenna gains, type of environment, among others.
Regarding this analysis, two different strategies were developed considering the same network deployment, being necessary to calculate the maximum cell radius for both cells, 900 MHz and 2000 MHz. The maximum cell radius is calculated for the maximum distance that allows the user to be served with the desired throughput, so it was calculated for the service with higher throughput.
The pathloss is calculated using the COST-231 Walfisch-Ikegami propagation model:
[ ] [ ] [ ] [ ] [ ] [ ] [ ] [ ]dBdBirdBmrdBmdBtmdBttdBdBp MGPEIRPLLLL −+−=++= 0 (1)
where, L0 is the free space loss; Ltt, the rooftop-to-street diffraction loss; Ltm, the approximation for the multi-screen diffraction loss; EIRP, the Equivalent Isotropic Radiated Power; the Pr, available receiving power at the antenna; Gr, the receiving antenna gain; M, the total margin.
Thus, through the manipulation of (1) and the Ltt and L0
expressions from the propagation model, the maximum cell
radius can be calculated by the expression:
[ ]
[ ] [ ] [ ] [ ] [ ] [ ] [ ]
d
dBdBtmdBttdBdbiRdbMRdBm
K
LLLMGPEIRP
KmR+
−−−−+−
=20
'0
'
10
(2)
where, [ ])log('
Kmdtttt dKLL −= ; dK is the dependence of the
multiscreen diffraction loss versus distance; d is the distance
between the user and the Node B; [ ])log(200
'
0 KmdLL −= and R
is the maximum cell radius.
Regarding frequency, one can conclude that for 900 MHz, the
cell radius for the maximum service throughput considered in
HSDPA, 2.048 Mbps, is approximately 0.6 km, whereas the
cell radius for 2000 MHz is 0.3 km. This is due to fact that
with the increase of the frequency, the path loss increases,
leading to a cell radius decreases.
Regarding the traffic management optimization between the
two types of cells, it is considered one of the two strategies
available in the simulator, “Carrier 2000 Loading” or “Priority
Service” strategy. Furthermore, the operators can use several
strategies depending of the usersP importance, services’
priority, or different strategies can simply be applied for day
and for night. Following this approach, it was considered the
“Carrier 2000 Loading” to represent the most common
strategy, independent of if it is a dense area, if it is day or
night. This strategy takes into account the services’
penetration percentages and the priority list. The “Priority
Service” strategy also takes into account these same features,
but uses it in a different way, emphasizing the most priority
service. This second strategy is most useful when the network
is overflow and the operators opt to guarantee that the most
priority users are served.
In the “Carrier 2000 Loading” algorithm all users are
connected to the 2000 MHz carrier at the beginning. After, the
system capacity is analysed at each Node B, by summing the
throughput of all users connected to it. If the sum is higher
than the throughput threshold, the users are moved to the 900
MHz Node Bs, one by one, according to their distance and the
QoS priority list, since the furthest and less priority users are
the first to be analysed. Then, the capacity analysis is once
again made and if the system is over limit, the reduction
strategy at the 900 MHz Node Bs level is applied.
In the “Priority Service” strategy algorithm, initially, the users which belong to the most priority service are connected to the 900 carrier, whereas the others users are connected to the 2000 MHz Node Bs. Then, the system capacity is analysed at the Node Bs, by summing the throughput of all users connected to them, being the 2000 MHz cells the first to be analysed. Thus, if the total throughput is higher than the limit of each Node B, the users are moved to the 900 MHz cell, one by one, considering the distance and the QoS priority list. Finally, it is applied the reduction strategy, if the 900 MHz Node Bs are over their limit.
2) Network Deployment
The simulator has the capacity to load different scenarios,
according to the previously set parameters (e.g. physical
conditions, antenna configurations and type of topology),
giving the application a wide range of deployments and
outputs, due to the combination of the these parameters in
several ways.
Thus, it is possible to analyze the influence of a specific
parameter in the network, in order to evaluate the HSDPA and
HSUPA 900/2000 MHz performance. The application places
the 900 MHz Node Bs co-sited with the 2000 MHz, being the
number and the localisation of each one read from the “txt”
file set in the user interface, which takes into account the
maximum cells radius. The co-sited Node Bs are alternate
with the 2000 MHz Node Bs, along the network dimensions,
since the 900 MHz cells are bigger than the 2000.
3) User’s Generation
The main objective of the user’s generation module is to
generate and distribute a number of users, set at the user
interface, according to the services percentages defined in
Table 1. The services considered in this simulator do not
4
include voice; they are only data services, since the HSDPA
and HSUPA are mainly used for this type of services.
Table 1. Profile One Characterisation.
Penetration
Percentage [%] Services
Profile 1
Quality of Service (QoS)
priority
Web 46.4 1
Streaming 6.2 2
E-mail 1.0 3
FTP 1.0 4
Chat 3.1 5
P2P 42.3 6
Firstly, the number of users that belong to one of the services
considered in Table 1, are obtained using the Matlab random
function, being generated a number between 0 and 1.
This random number lays in one of the intervals that takes into
account the services’ penetration percentages, and according
to this interval the MS is set to a specific service. It is also
taken into account the users’ priority, according the QoS
priority list presented. These values can also be consulted in
Table 1.
Furthermore, this module has the capacity to distribute the
users’ generated, using a uniform distribution, for the network.
The distribution takes to account the network dimensions,
since the generated numbers are distributed by the network
width and height dimensions, for the horizontal and vertical
positions, respectively.
4) HSDPA and HSUPA 900/2000 MHz Implementation
The HSDPA and HSUPA are two different modules, which
were implemented to enable the analysis of the impact of the
900 MHz band in the network. However, this two applications
run under the same Network Deployment and make use of the
same Users’ Generation.
The HSDPA and HSUPA were built to analyze the network
capacity and coverage, through a snapshot approach,
calculating instantaneous network results as number of user
per Node B and traffic. Since they have a similar function,
these modules will be analysed together.
Concerning the main objectives of the simulator, the need to
calculate the signal to noise ratio (SNR) is inherent and
mandatory for the both applications. Using the throughput in
function of SINR graphic, the requested throughput is mapped
into SINR and Ec/N0 for HSDPA and HSUPA, respectively.
Hence, it is possible to calculate the minimum received power
that allows the user to be served with the requested
throughput, calculation.
min[dBm] [dBm] [dB] [dB]Rx P
P N G SNR= − + (3)
where, N is the Total Noise Power; Gp, the processing gain;
SNR, the Signal to Noise Ratio.
Firstly, the pathloss is calculated using the expression shown
in (1). Besides the considered path loss, the total pathloss
depends on some additional margins, which are set in the
menu interface with the objective to simulate different channel
conditions. These margins are related to the slow and fast
fading margins, being described by a Gaussian and Rayleigh
distribution, respectively, to the indoor penetration losses and
to the soft handover gain for HSUPA, being the impact on the
overall results quite significant.
After the total pathloss, several parameters related to the
Equivalent Isotropic Radiated Power (EIRP) are requested,
being set by the user. The EIRP requested parameters are: BS
and MT transmission power; BS and MT antenna gain; User
losses; Cable losses; Diversity gain, only for HSUPA; System
signalling and control power.
Another, important physical aspect is the noise power, which
is calculated taking into account the following parameters also
obtained from the menu interface: Noise Factor and the
Interference Margin. The interference margin is calculated
based on the total number of users of the Node B coverage
area. In this paper it is considered the higher number of users
connected to the Node Bs, thus the interference margin taking
into account for HSDPA and HSUPA is the maximum value,
i.e., 6 dB.
The number of HS-PDSCH codes is an important parameter
for the evaluation of the network HSDPA performance, since
it is responsible for the throughput increase of the end of user.
Finally, the application calculates the receiver sensitivity with
the objective to obtain SNR values of each user in the
network.
[ ] [ ] [ ] [ ]
[ ] [ ] [ ] [ ] [ ] [ ]dBdBdB
dBdBm
pdBmcudBirpdBm
pdBmRxdB
GNLGLEIRP
GNPSNR
+−−+−=
=+−=
/
(4)
After calculating the SNR values, the throughput is associated
with each user, according to the user distance between all
Node Bs to all users, i.e, the maximum throughput that each
Node B can offer to each user, using the expressions of
interpolation curves from [3]. Then, the user is connected to
the closest Node B, which has the minimum pathloss, and is
associated with the throughput of that connection.
Furthermore, concerning the throughput that can be offered to
the user, it is necessary to take into account 3 different
situations:
i) When the throughput associated to the distance is higher
than the service’s throughput, the user is served with the
requested throughput;
ii) On the other hand, if the throughput distance is higher than
the minimum service and lower than the maximum service
throughput, the user is served with the throughput distance;
iii) The other situation is when the throughput distance is
lower than the minimum service throughput, being the user
without coverage and is counted “outage”.
5
Additionally, the analysis of the system’s capacity is carried
out at the Node Bs, by summing the throughput of all users
connected to the Node B. So, if the sum is lower than the
maximum allowed throughput for Node B, all users are served
without reduction, whereas if the sum is higher than the
throughput threshold in Table 2, the “Quality of Service
Reduction” reduction strategy is applied. In this reduction
strategy all the users’ throughput of the same service is
reduced by 10%, according to a list containing the services’
priorities.
Table 2. HSDPA and HSUPA maximum application
throughput.
System Maximum Throughput
[Mbps]
HSDPA 5 HS-PDSCH codes
3.0
HSDPA 10 HS-PDSCH
codes 6.0
HSDPA 15 HS-PDSCH
codes 8.46
HSUPA 1.22
The approach used for HSDPA is also used for HSUPA, being
the SHO the only difference, because each user can be
connected to the two closest’ Node Bs. In this case, the user
throughput is the minimum throughput allowed by one of the
two available throughputs from each Node Bs. It is also
considered a limit for a user to be in SHO, 0.384 Mbps, since
a user in SHO allocated more resources than when the user is
connected to only one Node B.
The services considered in this simulator do not include voice;
they are only data services, since the HSDPA and HSUPA are
mainly used for this type of services. The Profile One
characterisation is shown in Table 3.
Table 3. Profile One Characterisation.
Penetration Percentage [%] Services
Profile 1
Quality of Service (QoS) priority
Web 46.4 1
Streaming 6.2 2
E-mail 1.0 3
FTP 1.0 4
Chat 3.1 5
P2P 42.3 6
IV. RESULTS ANALYSIS
As the main objective of this paper is to study HSDPA and
HSUPA performance at 900/2000 MHz bands, a set of
simulation scenarios was conceived in order to evaluate this
impact, regarding several parameters variation. Hence, it was
adopted a default scenario to simplify the results analysis, over
which was performed the parameters variation, comparisons
and further conclusions. The default scenario has the goal to
study the multiple users’ scenario, which considers the users
uniformly distributed along the network, performing different
services with different throughputs.
The main objective of the following analysis is to show how
much the use of the 900 MHz carrier could have improved the
previous releases, and to pick the systems with better
performance for DL and UL, which are the ones from the later
releases. For these systems, simulations were performed, for
DL and UL, varying the available configurations, with the
objective to evaluate the relative impact, in terms of coverage,
capacity and throughput.
The parameters considered for the default scenario are the 15
HS-PDSCH codes for HSDPA, 1000 users and the Profile
One. Then, it is analysed some parameters variation, such as
the 5 and 10 HS-PDSCH codes for HSDPA, 3000 users and
two others profiles characterization, as it is shown in Table 4.
Table 4. Alternative profiles characterisation.
Penetration
Percentage [%]
Penetration
Percentage [%] Services
Profile Two Profile Three
Quality of
Service (QoS) priority
Streaming 10 10 1
Web 40 40 2
Chat 10 20 3
FTP 10 10 4
P2P 10 5 5
E-mail 20 15 6
A. HSDPA 900/2000 MHz evaluation
All the results presented in this subsection were obtained using
the simulator and the HSDPA model introduced in Section III.
Hence, several simulations were effectuated for the two traffic
management strategies.
1) Default Scenario
Considering all the users served in all simulations performed
and their distance to the Node B they are connected to, it was
evaluated the instantaneous user throughput for the two
carriers. From Figure 4 one can notice that for a distance
further than 0.5 km, the user throughput starts to have an
irregular behaviour for both carriers. This occurrence can be
explained by the decreasing number of users that are served
when the user’s distance increases, since according to the
“QoS Reduction” strategy, the users are also evaluated from
their distance, i.e, the throughput reduction strategy starts to
be applied from the furthest user to the closest one. Hence, the
number of delayed and outage users are higher for distance
above 0.5 km.
Furthermore, the main differences of the user throughput for
the 900 MHz carrier and 2000 MHz carrier are due to the
traffic management strategy adopted in this case. For the 2000
MHz carrier, it is possible to notice three lines, where the
users are mainly concentrated. This fact happens, because the
users are firstly set to the 2000 MHz BSs, being moved to the
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900 BSs only after the system capacity analysis. Thus, there
are few users reduced and the higher number are localised
around their requested throughput, which are 1.536, 1,024 and
0.384 Mbps. Concerning the 900 MHz carrier, Figure 4 left
side, it is illustrated the “QoS Reduction Strategy”
performance, since the users are mainly spread between the
0.1 km and 0.5 km and are served with a large variety of
throughputs, according to the number of reductions suffered
by them.
0 0.2 0.4 0.6 0.80
0.5
1
1.5
2
Distance [Km]
Instantaneous User Throughput [M
bps]
900 MHz Carrier
0 0.2 0.4 0.6 0.80
0.5
1
1.5
2
Distance [Km]
Instantaneous User Throughput [M
bps]
2000 MHz Carrier
Figure 4. HSDPA instantaneous user throughput for all users
depending with distance, according to users’ distribution one.
The instantaneous user throughput for all network was got
from the overlap of both carriers, Figure 5. It can also be
noticed the same behaviour of each carrier separately, which is
also justified by the fact that the average user distance is
around 0.3 km.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90
0.5
1
1.5
2
Distance [Km]
Instantaneous User Throughput [M
bps] HSDPA Instantaneous Throughput for all users
Figure 5. HSDPA instantaneous users’ throughput of all
network depending with distance.
Regarding the offered and served traffic, there is a small
reduction of Web users which is compensated by a small
increase of 3.54% on the percentage of P2P users. The offered
and served percentages are similar for the other services
analysed. Due to the QoS differentiation introduced in the
reduction strategy used, the service with the higher priority,
Web, has the highest average instantaneous throughput per
user and the second highest satisfaction rate, almost 80%.
The average network throughput is 6.64 Mbps, while the
average instantaneous user throughput is around 0.81 Mbps
with a satisfaction rate of around 64.69%. Relatively to the
average instantaneous throughput per user, it is possible to
conclude that it decreases with distance, since the signal to
interference noise ratio (SINR) is the limiting factor, due to
the introduction of the interference margin in the multiple
users’ scenario. Thus, the SINR value for a user further away
from the Node B becomes lower, leading to a reduction of the
throughput given to each user. Further, there are differences
between the 900 MHz carrier and 2000 MHz carrier, due to
the traffic management strategy adopted in the default
scenario. This difference is in the user throughput, where in
the 2000 MHz carrier it is possible to notice that the users
spread over their requested throughput, since they are only
reduced in 900 MHz carrier.
2) Number of HS-PDSCH Codes
The influence of the number of HS-PDSCH codes was also
analysed, and can be observed that an increase from 10 to 15
codes improves the average network throughput around 2.14
Mbps, i.e. 32%, as well as the maximum throughput allowed
for a single Node B, since there are more codes available for
data transmission. When the variation is from 5 to 15 codes,
the increasing in average network throughput, satisfaction rate
and total served users is obviously higher, i.e. around 68%,
40% and 39% respectively. As conclusion, more codes
available lead to an increase of the total network throughput,
satisfaction rate and number of served users.
3) Number of Users
Relatively to the number of users’ impact in the network, it
can be seen that when introducing more users, from 1000 to
3000 users, the average network throughput presents an
increase of 13 %, as there are more users in the network to be
served. This increase is mostly due to the higher number of
web users served, which are the most priority and have a
higher requested throughput. Hence, the majority Node Bs are
full with the web users with their maximum throughput due to
the “Carrier 2000 Loading” strategy. On the other hand, as
there are more users in the network, and the resources are the
same, there is a reduction in the average satisfaction rate of
approximately 21 %. With more users in the network, the
average satisfaction rate and average ratio of served users
decrease, because the resources are the same to serve more
users. The average ratio of served users is lower, but the
number of effective served user when considering 3000 users
is higher. As expected, this difference is due to the fact that
the users suffer a higher reduction in the 900 MHz carrier,
when considered 3000 users, whereas the number of users in
2000 MHz carrier is approximately the same.
4) Alternative Profiles
When comparing the Profile One with Profile Two and Three,
Table 3, the alternative ones present a significant reduction on
the percentage of users performing P2P, which is one of the
most demanding services in terms of throughput. On the other
hand, there is an increase in the percentage of users
performing Chat, Email and FTP. In an overall perspective, it
can be said that both alternative profiles are more demanding,
in terms of users’ throughput, than the Profile One.
Evaluating these variations, it is possible to notice that there
are not variations on the average network throughput for the
alternative profiles, when comparing with the Profile One. For
the average satisfaction rate, there is a decrease when
changing from the Profile One to the alternative profiles. The
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profile number one has a significant number of users
performing Web, which was move from first to second in the
priority list, being, reduced more users of this service than in
the Profile One, leading to a lower average satisfaction rate.
The percentage of users performing Chat, whose maximum
throughput considered, is 0.384 Mbps, increases. These users
can be more easily served by the network, since are applied
less reductions. This implies an overall increase of the average
satisfaction rate from the Profile Two to the Profile Three.
5) Strategies Comparison
Analysing the two different strategies, which were applied in
the network, the “Carrier 2000 Loading” and the “Priority
Service” strategy, it is possible to notice that the “Carrier 2000
Loading” strategy is the best one, as it allows a higher
throughput and satisfaction rate per service in general, except
for web service, which presents better results when it is used
the “Priority Service” strategy.
The “Carrier 2000 Loading” strategy improves 0.33 Mbps the
average network throughput, representing an increase of 5.2
%, and it allows an increasing of 2.68% in the satisfaction
rate, when compared with the “Priority Service” strategy.
On the other hand, the “Priority Service” strategy is the best
one when the operators want to give extremely importance to
one specific group of users. As illustrated in this paper, it is
possible to improve the Web average throughput and
satisfaction rate, in 2.4% and 2.3% respectively, by using the
“Priority Service” instead of using the “Carrier 2000 Loading”
strategy.
B. HSUPA 900/2000 MHz evaluation
All the results presented in this subsection were obtained using
the simulator and HSUPA model introduced in Section III.
Hence, it was evaluated the instantaneous user throughput of
all network and for the both carriers separately.
1) Default Scenario
From Figure 6, is possible to notice the expected differences,
which are due to the “Carrier 2000 Loading” strategy. The
user can only be served by the 2000 carrier for distances until
0.38 km, as is shown in Figure 6 left side, since the HSUPA
system has less available resources than the HSDPA. Thus, the
users requesting HSUPA services for distances furthest than
0.38 km are moved to the 900 MHz Node Bs due the “Carrier
2000 Loading” strategy. On the other hand, it is possible to
observe the same three lines present in HSDPA user
throughput, being here where the users are mainly concentrate,
since they are localised around their requested throughput
which are 0.512, 0.384 and 0.064 Mbps.
0 0.2 0.4 0.6 0.80
0.1
0.2
0.3
0.4
0.5
Distance [Km]
Instantaneous User Throughput [M
bps] 900 MHz Carrier
0 0.2 0.4 0.6 0.80
0.1
0.2
0.3
0.4
0.5
Distance [Km]
Instantaneous User Throughput [M
bps] 2000 MHz Carrier
Figure 6. HSUPA instantaneous user throughput for all users
depending with distance, according to users’ distribution one.
As it is shown in Figure 7, the average instantaneous user
throughput is approximately constant for distances until 0.5
km. After this distance the network behaviour tends to be
irregular, which is due to the fact that few users are served
with the requested throughput when they are placed beyond
0.5 km, since according to the “QoS Reduction” strategy, the
users are evaluated from their distance, i.e, the throughput
reduction strategy start to be applied from the furthest user to
the closest one. The use of SHO also helps to justify the
constant throughput results, as when the distance increases and
one would expect a reduction of the user throughput, the
probability of the user being in SHO increases, as the user is
more likely to be near the cell edge. For the default scenario,
the average network radius is 0.23 km.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90
0.1
0.2
0.3
0.4
0.5
Distance [Km]
Instantaneous User Throughput [M
bps] HSDPA Instantaneous Throughput for all users
Figure 7. HSUPA instantaneous users’ throughput of all
network depending with distance.
Regarding the offered and served traffic, it is possible to
conclude that the reduction of 2.12% in the served users
performing Streaming, is mainly due to fact that these users
requested throughput is equal to its minimum throughput,
meaning that, when reductions are performed more than one
time, Streaming users are always delayed.
2) Number of Users
Relatively to the number of users’ impact in the network for HSUPA 900/2000 MHz, it can be seen that when introducing more users, from 1000 to 3000 users, the average network throughput presents an increase of 18.4%. With more users in the network, the average satisfaction rate and average ratio of served users decrease, because the resources are the same to serve more users. The average ratio of served users is lower, but the number of effective served user when considering 3000 users is higher.
8
3) Alternative Profiles
When introducing more demanding profiles, such as Profile
Two and Profile Three, the network is still capable of serving
the same users as the ones for the Profile One. This fact
explains the approximate same value for the percentage of
total served users, around 37%, i.e. 370 users. As for the
average satisfaction rate, there is a smooth increase when
changing from the Profile One to the alternative profiles. This
is due to the fact that the first one has a significant number of
users performing P2P, which is the first service to be reduced,
leading to a lower average satisfaction rate. The alternative
profiles present a low percentage of P2P, which it is now the
second service to be reduced. There is also an increase in
terms of percentage of Chat, whose maximum throughput is
0.384 Mbps, which can be more easily served by the network,
therefore, less reductions have to be performed. Concluding
implies an overall increase of the average satisfaction rate for
the alternative profiles.
For HSUPA, there are an increase of 0.5% and 0.6%, from
Profile One to Profile Two and Three, respectively.
4) Strategies Comparison
As observed in HSDPA, the “Carrier 2000 Loading” strategy
has a better performance in HSUPA, since allows uniform
results for all services. In the service by service analysis,
Streaming has an average satisfaction rate of 100%, even
though Web is the service with the highest QoS priority. This
is due to the fact that, for HSUPA, the maximum and
minimum Streaming throughputs are equal, meaning that,
when the Streaming users are served it is with the requested
throughput. On the other hand, the “Priority Service” strategy
shows the best results for web service, which it was given
more importance, being illustrated the strategies adopted by
the operators when want to give a better service for a specific
group. Hence, it is possible to improve the average network
throughput in 14.3% and the average satisfaction rate in 7.2%,
for users performing Web service when it is used the “Priority
Service” strategy. Hence, this strategy allows better
performances for one specific service, according to operator’s
requirements.
Regarding the average network throughput, it is possible to
notice that this one is also higher when it is applied the
“Carrier 2000 Loading” strategy, but the main difference is in
the satisfaction rate, which presents an increase of 23%
relatively to the “Priority Service” strategy.
V. CONCLUSIONS AND FUTURE WORK
The aim of this work was to analyse the HSDPA and HSUPA
performance in the 900/2000 MHz frequencies, in terms of
traffic management between the two carriers, capacity,
average network throughput and satisfaction rate. This model
was implemented in a simulator written in Matlab, with the
purpose to calculate the statistical parameters in a multiple
users’ scenario with a certain requested throughput, varying
several parameters of each system.
Concluding, the “Priority Service” strategy should only
applied, when the operators intend high requirements for one
specific users’ group, because the better performance of these
users is achieved by reducing one average the throughput and
satisfaction rate of the other services available.
For future work, it would also be interesting to study the
HSDPA and HSUPA 900/2000 MHz with GSM system, in the
same network. Hence, the strategies present in this paper could
be developed with the intention of allowing a traffic
management between the HSDPA and HSUPA 900/2000
MHz cells and 900 MHz GSM cells.
REFERENCES
[1] Holma, H. and Toskala A., WCDMA for UMTS – HSDPA Evolution and
LTE, John Wiley & Sons, Chichester, UK, 2007.
[2] Holma, H. and Toskala A., UMTS 900 Co-Existence with GSM 900, Holma, H., Ahopaa T and Prieur E.
[3] Lopes,J., Performance of UMTS/HSDPA/HSUPA at the Cellular Level, M.Sc. Thesis, IST-UTL, Lisbon, Portugal, 2008.
[4] UMTS Forum White Paper, Deployment of UMTS in 900 MHz band, Oct. 2006.
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