Evaluating the GPRS Radio Interface for Different Quality of Service Profiles

Abstract. This paper presents a discrete-event simulator for the General
Packet Radio Service (GPRS) on the IP level. GPRS is a standard on packet data
in GSM systems that will become commercially available by the end of this year.
The simulator focuses on the communication over the radio interface, because it
is one of the central aspects of GPRS. We study the correlation of GSM andGPRS
users by a static and dynamic channel allocation scheme. In contrast to
previous work, our approach represents the mobility of users through arrival
rates of new GSM and GPRS users as well as handover rates of GSM and GPRS users
from neighboring cells. Furthermore, we consider users with different QoS
profiles modeled by a weighted fair queueing scheme. The  simulator considers a
cell cluster comprising seven hexagonal cells. We provide curves for average
carried traffic and packet loss probabilities for differentchannel allocation
schemes and packet priorities as well as curves for average throughput per GPRS
user. A detailed comparison between static and dynamic channel allocation
schemes is provided.

1 Introduction

The General
Packet Radio Service (GPRS) is a standard from the European Telecommunications
Standards Institute (ETSI) on packet data in GSM systems [6], [14]. By
adding GPRS functionality to the existing GSM network, operators can givetheir
subscribers resource-efficient wireless access to external Internet
protocol-bases networks, such as the Internet and corporate intranets. The
basic idea of GPRS is to provide a packet-switched bearer service in a GSM
network. As impressively demonstrated by the Internet, packet-switched networks
make more efficient use of the resources for bursty data applications and
provide more flexibility in general. In previous work, several analytical
models have been developed to study data services in a GSM network. Ajmone
Marsan et al. studied multimedia services in a GSM network by providing more
than one channel for data services [1]. Boucherie and Litjens developed an
analytical model based on Markov chain analysis to study the performance of
GPRS under a given GSM call characteristic [4]. For analytical tractability,
they assumed exponentially distributed arrival times for packets and
exponential packet transfer times, respectively. On the other hand,
discrete-event simulation based studies of GPRS were conducted. Meyer et al.
focused on the performance of TCP over GPRS under several carrier to interference
conditions and coding schemes of data [10]. Furthermore, they provided a
detailed implementation of the GPRS protocol stack [11]. Malomsoky et al.
developed a simulation based GPRS  network dimensioning tool [9]. Stuckmann et
al. studied the correlation of GSM and GPRS users with the simulator GPRSim
[13]. This paper describes a discrete-event simulator for GPRS on the IP level.
The simulator is developed using the simulation package CSIM [12] and considers
a cellcluster comprising of seven hexagonal cells. The presented performance
studies were conducted for the innermost cell of the seven cell cluster. The
simulator focuses on the communication over the radio interface, because this
is one of the central aspects of GPRS. In fact, the air interface mainly
determines the performance of GPRS. We studied the correlation of GSM and GPRS
users by a static and dynamic channel allocation scheme. A first approach of
modeling dynamic channel allocation was introduced by Bianchi et al. and is
known as Dynamic Channel Stealing (DCS) [3].

The basic DCS
concept is to temporarily assign the traffic channels dedicated to 
circuit-switched connections but unused because statistical traffic
fluctuations. This can be done at no expense in terms of radio resource, and
with no impact on circuitswitched services performance if the channel
allocation to packet-switched services is

permitted only
for idle traffic channels, and the stolen channels are immediately released
when requested by the circuit-switched service. In contrast to the models
developed in [4], [9], [10], and [11], our approach additionally represents the
mobility of users through arrival rates of new GSM and GPRS users as well as
handover rates of GSM and GPRS users from neighboring cells. Furthermore, we
consider users with different QoS profiles modeled by a weighted fair queueing
scheme according to [5]. The remainder of the paper is organized as follows.
Section 2 describes the basic GPRS network architecture, the radio interface,
and different QoS profiles, which will be considered in the simulator. In
Section 3 we describe the software architecture of the GPRS simulator, details
about the mobility of GSM and GPRS users, the way we modeled quality of service
profiles, and the workload model we used. Results of the simulation studies are
presented in Section 4. We provide curves for average carried traffic and
packet loss probabilities for different channel allocation schemes and packet
priorities as well as curves for average throughput per GPRS user.

3 The Simulation
Model

We consider a
cluster comprising of sever hexadiagonal cells in an integrated GSM/GPRS
network, serving circuit-switched voice and packet-switched data calls. The
performance studies presented in Section 4 were conducted for the innermost cell
of the seven cell cluster. We assume that GSM and GPRS calls arrive in each
cell according to two mutually independent Poisson processes, with arrival
rates ëGSM
and ëGPRS,
respectively. GSM calls are handled circuit-switched, so that one physical
channel is exclusively dedicated to the corresponding mobile station. After the
arrival of a GPRS call, a GPRS session begins. During this time a GPRS
user allocates no physical channel exclusively. Instead the radio interface is
scheduled among different GPRS users by the Base Station Controller (BSC).
Every GPRS user receives packets according to a specified workload model. The
amount of time that a mobile station with an ongoing call remains within the
area covered by the same BSC is called dwell time. If the call is still
active after the dwell time, a handover toward an adjacent cell takes place.
The call duration is defined as the amount of time that the call will be
active, assuming it completes without being forced to terminate due to handover

failure. We
assume the dwell time to be an exponentially distributed random variable with
mean 1/µh,GSM
for GSM calls and 1/µh,GPRS for GPRS calls. The call durations are

also
exponentially distributed with mean values 1/µGSM and 1/µGPRS for GSM and

GPRS calls,
respectively. To exactly model the user behavior in the seven cell cluster, we
have to consider the handover flow of GSM and GPRS users from adjacent cells.
At the boundary cells of the seven cell cluster, the intensity of the incoming
handover flow cannot be

specified in
advance. This is due to the handover rate out of a cell depends on the

number of
active customers within the cell. On the other hand, the handover rate into

the cell
depends on the number of customers in the neighboring cells. Thus, the

iterative
procedure introduced in [2] is used to balance the incoming and outgoing

handover rates,
assuming that the incoming handover rate ëh GSM

in i ,

 ( ) ( ) −1 computed
at step i-1.

Since in the
end-to-end path, the wireless link is typically the bottleneck, and given

the anticipated
traffic asymmetry, the simulator focuses on resource contention in the

downlink (i.e.,
the path BSC → BTS → MS) of the radio interface. Because of the
anticipated traffic asymmetry the amount of uplink traffic, e.g. induced by

acknowledgments,
is assumed to be negligible. In the study we focus on the radio

interface. The
functionality of the GPRS core network is not included. The arrival

stream of
packets is modeled at the IP layer. Let N be the number of physical channels
available in the cell. We evaluate the performance of two types of radio
resource sharing schemes, which specify how the cell capacity is shared by GSM
and GPRS users:

•
the static scheme; that is the cell capacity of
N physical channels is split into

NGPRS channels
reserved for GPRS data transfer and NGSM = N - NGPRS channels

reserved for
GSM circuit-switched connections.

•
the dynamic scheme; that is the N physical channels
are shared by GSM and

GPRS services,
with priority for GSM calls; given n voice calls, the remaining

N-n channels
are fairly shared by all packets in transfer.

In both
schemes, the PDCHs are fairly shared by all packets in transfer up to a

maximum of 8
PDCHs per IP packet ("multislot mode") and a maximum of 8 packets

per PDCH [6].

The software
architecture of the simulator follows the network architecture of the

GPRS Network
[14]. To accurately model the communication over the radio

interface, we
include the functionality of a BSC and a BTS. IP packets that arrive at

the BSC are
logically organized in two distinct queues. The transfer queue can hold

up to Q n = ⋅ 8 packets that are served
according to a processor sharing service

discipline,
with n the number of physical channels that are potentially available for

data transfer,
i.e. n = NGPRS under the static scheme and n = N under the dynamic

scheme. The
processor sharing service discipline fairly shares the available channel

capacity over
the packets in the transfer queue. An arriving IP packet that cannot enter

the transfer
queue immediately is held in a first-come first-served (in case of one

priority)
access queue that can store up to K packets. The access queue models the

BSC buffer in
the GPRS network. Upon termination of a packet transfer, the IP

packet at the
head of the access queue is polled into the transfer queue, where it

immediately
shares in the assignment of available PDCHs. For this study, we fix the

modulation and
coding scheme to CS-2 [14]. It allows a data transfer rate of 13,4

kbit/sec on one
PDCH. Figure 1 depicts the software architecture of the simulator.

Figure 1.
Software Architecture of GSM/GPRS Simulator

To model the
different quality of service profiles GPRS provides, the simulator

implemented a Weighted
Fair Queueing (WFQ) strategy. The WFQ scheduling

algorithm can
easily be adopted to provide multiple data service classes by assigning

each traffic
source a weight determined by its class. The weight controls the amount

of traffic a
source may deliver relative to other active sources during some period of

time. From the
scheduling algorithm's point of view, a source is considered to be

active if it
has data queued at the BSC. For an active packet transfer with weight wi

the portion of
the bandwidth Âi(t) allocated at time t to this transfer should be

 ( ) ( ) = ⋅ ∑

where the sum
over all active packet transfers at time t. The overall bandwidth at time

t is denoted by
B(t) which is independent of t in the static channel allocation scheme.

The workload
model used in the GPRS simulator is a Markov-modulated Poisson

Process
(MMPP) [7]. It is used to generate the IP traffic
for each individual user in

the system. The
MMPP has been extensively used for modeling arrival processes,

because it
qualitatively models the time-varying arrival rate and captures some of the

important
correlations between the interarrival times. It is shown to be an accurate

model for
Internet traffic which usually shows self-similarity among different time

scales. For our
purpose the MMPP is parameterized by the two-state continuous-time

Markov chain
with infinitesimal generator matrix Q and rate matrix Ë:

0

The two states
represent bursty mode and non-bursty mode of the arrival process.

The process
resides in bursty mode for a mean time of 1/á and in non-bursty mode for

a mean time of
1/â respectively.
Such an MMPP is characterized by the average

arrival rate
of packets, ëavg and the degree of burstiness, B. The former is given by:

1 2

The degree
of burstiness is computed by the ratio between the bursty arrival rate and

the average
arrival rate, i.e., B = ë1/ëavg.

4 Simulation
Results

Table 1
summarizes the parameter settings underlying the performance experiments.

We group the
parameters into three classes: network model, mobility model, and

traffic model.
The overall number of physical channels in a cell is set to N = 20

among which at
least one channel is reserved for GPRS. The overall number of GPRS

users that can
be managed by a cell is set to M = 20. As base value, we assume that

5% of the
arriving calls correspond to GPRS users and the remaining 95% are GSM

calls. GSM call
duration is set to 120 seconds and call dwell time to 60 seconds, so

that users make
1-2 handovers on average. For GPRS sessions the average session

duration is set
to 5 minutes and the dwell time is 120 seconds. Thus, we assume

longer “online
times” and slower movement of GPRS users than for GSM users. The

average arrival
rate of data is set to 6 Kbit/sec per GPRS user corresponding to 0.73

IP packets per
second of size 1 Kbyte.

Parameter

Figure 2
presents curves for carried data traffic and packet loss probabilities due to

buffer overflow
in the BSC for the static channel allocation scheme and one packet

priority. For
GPRS 1, 2, and 4 PDCHs are reserved, respectively. The remaining

channels can be
used by GSM calls. With 4 PDCHs the system overloads at an arrival

rate of 0.8
GSM/GPRS users per second. This corresponds to an average of 12 GPRS

users in the
cell (see Figure 7). In Figure 3 we present corresponding curves for the

dynamic channel
allocation scheme. For GPRS 1, 2, and 4 PDCHs are reserved,

respectively
but more PDCHs can be reserved "on demand". That means that

additional
PDCHs can be reserved if they are not used for GSM voice service. From

Figure 3 we
observe that for low traffic in the considered cell GPRS makes

effectively use
of the on demand PDCHs. For example if 1 PDCH is reserved GPRS

utilizes up to
2 PDCHs at an arrival rate of 0.4 GSM/GPRS users per second. But

with increasing
load the overall performance of GPRS decreases because of

concurrency
among GPRS users, and more important, priority of GSM users over the

radio
interface. In comparison with the static channel allocation scheme we conclude

that the
combination of reserved PDCHs and on demand PDCH leads to a better

utilization of
the scarce radio frequencies. The only advantage of the static channel

allocation
scheme is that it can be realized more easily.

Figure 4
presents a comparison of overall channel utilization and average

throughput per
GPRS user for the static and dynamic channel allocation scheme. For

the static
scheme we reserved 2 and 4 PDCHs respectively and for the dynamic

scheme only 1
PDCH. We observe a higher overall utilization of physical channels by

the dynamic
scheme. Comparing the dynamic with the static scheme for 2 PDCHs we

detect a
slightly higher throughput for low traffic load for dynamic channel allocation.

This results
from the high radio channel capacity available to GPRS users in this case.

They can
utilize up to 8 PDCHs for their transfer (in contrast to 2 PDCHs in the static

scheme). When
load increases, GSM calls allocate most of the physical channels.

Thus,
throughput for GPRS users decreases very fast. In the static scheme (4 PDCHs)

the decrease in
throughput is not so fast, because GSM calls do not effect the PDCHs.

In an
additional experiment, we study the performance loss in the GSM voice

service due to
the introduction of GPRS. Figure 5 plots the carried voice traffic and

voice blocking
probability for different numbers of reserved PDCHs. The results are

valid for both
channel allocation schemes because of the priority of GSM voice

service over
GPRS. The presented curves indicate that the decrease in channel

capacity and,
thus, the increase of the blocking probability of the GSM voice service

is negligible
compared to the benefit of reserving additional PDCHs for GPRS users.

Figure 6 shows
carried data traffic and packet loss probabilities for the dynamic

channel
allocation scheme and different packet priorities. For GPRS 1 PDCH is

reserved.
Weights for packets with priority 1 (high), 2 (medium), and 3 (low) and

percentages of
GPRS users utilizing these priorities are given in Table 1. We observe

that for low
traffic in the considered cell most channels are covered by packets of low

priority. This
is due to the high portion of low priority packets (60%) among all

packets sharing
the radio interface. With increasing load medium priority packets and

at last high
priority packets suppress packets of lower priority and therefore the

utilization of
PDCHs for low and medium priority packets decreases. For a call arrival

rate of up to 2
calls per second the loss probability of high priority packets is still less

than 10-5 and
therefore the corresponding curve is omitted in Figure 6.

Figure 7
presents curves for average number of GPRS users in the cell and

blocking
probabilities of GPRS session requests due to reaching the limit of M active

GPRS sessions.
We observe that for 2% GPRS users the maximum number of 20

active GPRS
sessions is not reached. Therefore, the blocking probability remains very

low. For 10%
GPRS users and increasing call arrival rate, the average number of

sessions
approaches its maximum. Thus, some GPRS users will be rejected. It is

important to
note that the curves of Figure 7 can be utilized for determining the

average number
of GPRS users in the cell for a given call arrival rate. In fact, together

with the curves
of Figure 2 and 3, we can provide estimates for the maximum number

of GPRS users
that can be managed by the cell without degradation of quality of

service. For
example, for 5% GPRS users and 1 PDCHs reserved, in the static

allocation
scheme a packet loss probability of 10-3 can be guarantied until the call

arrival rate
exceeds 0.4 calls per second, i.e., until there are on the average 6 active

GPRS users in
the cell. For the dynamic allocation scheme a packet loss probability of

10-3 can be
guarantied until the call arrival rate exceeds 0.6 calls per second

corresponding
to 9 active GPRS users in the cell on average. Figure 8 investigates the impact
of the maximum number of GPRS user per cell to the performance of GPRS for the
dynamic channel allocation scheme with 1 PDCH reserved. Of course, the expected
number of GPRS users should be less than the maximum number in order to avoid
the rejection of new GPRS sessions. On the other hand, the maximum number of
active GPRS sessions must be limited for guaranteeing quality of service for
every active GPRS session even under high traffic. The tradeoff between
increasing performance for allowing more active GPRS sessions and the

increasing
blocking probability for GPRS users is illustrated by the curves of Figure 8.

Conclusions

This paper
presented a discrete-event simulator on the IP level for the General Packet
Radio Service (GPRS). With the simulator, we provided a comprehensive
performance study of the radio resource sharing by circuit switched GSM
connections and packet switched GPRS sessions under a static and a dynamic
channel allocation

scheme. In the
dynamic scheme we assumed a reserved number of physical channels permanently
allocated to GPRS and the remaining channels to be on-demand channels that can
be used by GSM voice service and GPRS packets. In the static scheme no ondemand
channels exist. We investigated the impact of the number of packet data

channels
reserved for GPRS users on the performance of the cellular network.
Furthermore, three different QoS profiles modeled by a weighted fair queueing
scheme were considered. Comparing both channel allocation schemes, we concluded
that the dynamic scheme is preferable at all. The only advantage of the static
scheme lies in its easy implementation. Next, we studied the impact of
introducing GPRS on GSM voice service and observed that the decrease in channel
capacity for GSM is negligible compared to the benefit of reserving additional
packet data channels for GPRS. With the curves presented we provide estimates
for the maximum number of GPRS users that can be managed by the cell without
degradation of quality of service. Such results give valuable hints for network
designers on how many packet data channels should be allocated for GPRS and how
many GPRS session should be allowed for a given amount of traffic in order to guarantee
appropriate quality of service.