Evaluating the GPRS Radio Interface

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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.