A Simulation Environment for Enhanced UMTS Performance Evaluation J. Antoniou, V. Vassiliou †, A. Pitsillides, G. Hadjipollas and N. Jacovides Department of Computer Science University of Cyprus Nicosia, Cyprus
[email protected]
Abstract – The paper proposes a new simulator that supports UMTS and Enhanced-UMTS performance evaluation. Existing UMTS simulators integrate linklevel and system-level simulators, implemented using time-based simulation techniques. The proposed simulator integrates time-based link level simulations into an event-based system level simulator by extending ns-2. The simulator can evaluate parameters associated with UMTS or EnhancedUMTS performance (delay, loss, jitter, throughput), to assess the impact of new services, protocols and architectures. Performance evaluation does not only capture the performance over the air interface but also investigates the influence of the all-IP network in the overall system behaviour. A scenario modelling a demanding traffic-mix in a business city centre environment is evaluated and results are presented. I. INTRODUCTION The Universal Mobile Telecommunications System (UMTS), standard belongs to the 3rd Generation (3G) of mobile networks. The main idea behind 3G is to prepare a universal infrastructure able to carry both existing and future services. 3G is standardized by the worldwide 3G Partnership Projects (3GPP in Europe and 3GPP2 in USA) [1], [2]. The UMTS and All-IP UMTS network infrastructure will have to provide network service to a variety of applications that can seamlessly integrate voice and data through various wireless access technologies (GSM, Wideband Code Division Multiple Access (WCDMA), and Code Division Multiple Access (CDMA2000)). An Enhanced UMTS network is an All-IP based network that will support additions and modifications to the UMTS network [3]. Such modifications aim to satisfy the need for a capacity increase in the access network, flexibility in the core network and support supplementary integrated services that the standardized UMTS network is not expected to provide. Therefore, Enhanced UMTS is a UMTS evolution step, which makes possible an effective end-to-end packet-based transmission.
This work has been performed in the framework of the IST-2001-34900 SEACORN project
†
Department of Computer Science INTERCOLLEGE Nicosia, Cyprus
[email protected]
Enhanced-UMTS system-level simulations aim to model a network based on an existing or planned topology design, an estimated traffic distribution and a mix of services with multiple Quality of Service (QoS) requirements. This is opposed to second-generation networks where the main application to be considered was voice, and QoS was easy to predict even for full load. The system-level simulations parameters target coverage, capacity and QoS in the real network. These answer the question of whether the designed network can support the envisaged traffic mix. Consequently, parameters affecting QoS support for applications can be examined. This allows one to investigate how applications function in varying radio environments, under different network topologies (Radio Access Network [RAN] and Core Network), architectures and protocols. This paper proposes a simulation environment that enables the performance evaluation of All-IP UMTS [4] and Enhanced-UMTS networks. The need for such a simulator arises from the multi-type user aspects of UMTS and Enhanced-UMTS, as well as the need to consider user mobility, handover, Radio Resource Management (RRM) mechanisms, in an All-IP RAN and Core network, within such a framework. This framework also allows the development of flexible models, algorithms, new network protocols and RRM mechanisms for the deployment of the future UMTS networks. Contrary to existing time-based system level simulator approaches [12], [13], which are based on integrating time-base link level simulations with a time based system level simulator, our proposed system level simulator integrates time-based link level simulations into an eventbased system level UMTS simulator. It extends ns-2, a popular public domain network simulator [5]. The paper is structured as follows. Section II addresses the basic design and structure of the simulator. Section III provides a proof-of-concept demonstration of results for a traffic mix scenario in a business city centre environment and Section IV presents the conclusions and ideas for future work. II. SYSTEM LEVEL SIMULATOR The proposed UMTS system-level simulator was developed by extensions to ns-2 (Network Simulator – version 2), a publicly available network simulation
environment [5]. UMTS extensions were implemented within the IST SEACORN project [3]. The simulator was implemented according to the system architecture of Enhanced-UMTS for packet-switched operations, illustrated in Figure 1. The very demanding requirement of preparing a universal infrastructure to support current and future UMTS services is achieved by the separation of the access, the transport and the service (connection control) technologies. Therefore, the entire architecture can be broken down into subsystems based on different parameters such as the nature of traffic, protocol structures or physical elements. Radio Interface
UTRAN
Environment and Performance Evaluation. The system level simulator structure is presented in Figure 2. This modular approach allows the implementation and investigation of current and new networking protocols, which aim to address QoS provision issues (e.g. Diff-Serv architecture [9], RMD [10], IDCC [11]).
Core Network
IP
RNC Node B
SGSN
GGSN
Packet-Switched Domain
UE
1 2 3 4 5 6 7 8 9 * 8 #
Node B
Figure 1: UMTS Architecture for Packet Switched Operations
The architecture includes the Radio Access Network (RAN) and the Core Network (CN). The RAN consists of the User Equipment (UE) and the UMTS Terrestrial Radio Access Network (UTRAN). The nodes comprising the UTRAN are: the base station (Node-B), the IP routers, and the Radio Network Controller (RNC) [6]. The Core network includes the Serving GPRS Support Node (SGSN) and the Gateway GPRS Support Node (GGSN). SGSN is responsible for the delivery of data packets from and to the UEs within its service area. GGSN allows interconnection with external packet switched networks (e.g. other IP networks) [7]. UEs communicate with Node-Bs in a wireless mode via the radio interface. Each Node-B manages the network's air interface for the UEs that are in the same cell as the Node-B. The RNC manages the resources of the air interface of all the UEs connected to Node-Bs served by that RNC. It coordinates the admission control process, manages the handovers of UEs between Node-Bs due to UE mobility, buffers packets destined for UEs, and communicates with the SGSN allowing the SGSN to send and receive data to and from the UEs. An RNC will be connected to multiple Node-Bs to communicate with the UEs of the network and to manage multiple calls. The interconnection of the RAN with the Node-Bs is done using IP-based routers [8]. The ns-2 extensions include all the UMTS-aware nodes (UE, Node B, RNC) and models representing the radio propagation, the mobility, the RRM mechanisms and the traffic mix for different operating environments. For the external networks (core network) the simulator uses default ns-2 nodes. The simulator is built in a modular manner. The modules may be categorized according to their functionality into three main categories: Control Mechanisms, Mobile
Figure 2: System level simulator modules
In IP-based networks QoS cannot be guaranteed. Hence, the bottleneck can be anywhere in the network (i.e. it is not limited to the air interface). The proposed system level simulator allows capturing not only the air interface behaviour as the only probable bottleneck (a common assumption in most literature that deals with system level simulations of mobile environments [12], [13]), but also the dynamic end-to-end behaviour of the overall network. III. EVALUATING A SCENARIO The proposed simulations framework allows the evaluation of scenarios that reflect the projected traffic behaviour in a UMTS and Enhanced UMTS network, for different topologies, under given network architectures and protocols. These scenarios should represent realistic conditions, including but not limited to, a sensible transmission range, representative data traffic models, mobility models, as well as accurate radio propagation models. In parallel, a concerted effort is provided to cut down simulation times, without significantly reducing accuracy. For example, a limited number of focused sub-problems can be specified and for each sub-problem the simulation requirements can be determined. Furthermore, the level of required detail regarding traffic, mobility models, RRM mechanisms and propagation environments can be investigated. The simulator is able to perform systemlevel simulations in order to evaluate the performance of the network itself by monitoring several QoS indices (e.g. delay, loss, jitter, and throughput). A. Mobile Environments A usual separation of the operating environments is in outdoor environments and indoor environments. By outdoor environments we mean physical locations that are outdoors such as: roads and railway tracks, rural areas,
urban areas and downtown areas. On the other hand, indoor environments include: home, office, airports, train stations, commercial zones, theatres, stadiums and parking zones. When simulating mobile networks, there is one further classification of environments that needs to be made. The environments need to be separated according to their cell size (defined by the maximum transmit power of each Node B). There are usually three categories: pico-cellular environments, micro-cellular environments and macrocellular environments. Pico-cellular environments are characterised by small cells and low transmit powers, and both the users and the base stations are located indoors. Some examples of physical environments that correspond to the pico-cellular category are: home, office, airport and train stations, malls, theatres, covered stadiums and covered parking zones. Micro-cellular environments are characterised by small cells and low transmit powers as well. Usually, however, only outdoor users are considered. Examples of microcellular environments are: open stadiums, open parking lots, open commercial zones, downtown areas (business city centres). The macro-cellular environments have large cells and transmit high powers as opposed to the previous two types of environments. The cell radius reaches 2000m for services less than 144kbps and 500m for higher rates. Distances between base stations vary from 1km to 6km. Examples of such environments are: urban areas, rural areas, roads and railway tracks. B. Environment Specifications The environment modelled in the illustrative example is a business city centre environment. High buildings and high user density characterize this environment. The model used follows the Manhattan grid model [15]. For a single cell, four buildings separated by a crossroad are modelled. Each building has dimensions 200m x 200m and the width of the roads is 30m. The nodes in the simulations are UMTS-enabled nodes developed for the IST Project SEACORN. One RNC, one Node B, 300 UEs, one SGSN, one GGSN, and two external IP-enabled nodes are used in this scenario. The simulation topology consists of a single cell with the Node B connected to the RNC. Two nodes represent the SGSN and GGSN and more nodes represent external IP networks, to model a single communication path between a number of mobiles and a fixed communicating node. The topology is shown in Figure 3. The communicating hosts are an external (non-UMTS host) node at one end and a number of UEs (UMTS host) at the other end. Traffic flows from the external node to another such node (representing the external IP network), to the GGSN, the SGSN, the RNC, and the Node B and over the wireless interface to the UEs (in the cell). Traffic can flow in both directions along this path.
Figure 3: The single cell topology simulated
The propagation models used for simulating the path loss in a UMTS network are the COST 231 models [16]. The project COST Action 231 models are based on theoretical and empirical approaches and extensive measurementcampaigns in European cities. Each of these models may be used for a separate scenario. The Propagation model used in the simulation of the business city centre scenario is called “Walfisch-IkegamiLoS” model and assumes an air interface that includes outdoor base stations, buildings, outdoor users, low speeds and low transmit powers at a Line-of-Sight path. C. Traffic Mix Four categories of services are taken into consideration: sound, high interactive multimedia, narrowband and wideband services. A corresponding application for each type of service contributes to the traffic mix according to its usage percentage. The four applications considered are Voice over IP (VoIP), Video-Telephony, FTP, and High Definition Video-Telephony. Voice Over IP (VoIP) is the transmission of voice over IP networks instead of the traditional public switched telephone network (PSTN) [14]. Video-Telephony is a full-duplex, real-time audiovisual communication between end-users. As high speed Internet access becomes widely available, video telephony at high resolution (High-Definition Video Telephony) is expected to be widely used. Finally, FTP is a file transfer application. Table 1: Services with corresponding applications and anticipated usage for a UMTS business city centre environment.
Service
Application
Sound High Interactive Multi-Media Narrowband Wideband
Voice Over IP Video-Telephony FTP High Definition Video-Telephony
Percentage Usage 27% 16%
26% 31%
To model the above service mix it is necessary to define certain characterisation parameters for each service. These parameters may easily become quite numerous, in some cases more than can be effectively handled by a single simulation. Hence, we try to identify a number of
necessary parameters that will abstract the model at an appropriate level. The first parameter necessary is the percentage usage, which is given, in Table 1. The percentage usage of each service reflects the projected traffic behaviour of Enhanced UMTS in a business city centre environment. Besides the usage, necessary modelling parameters include the data rate for each service, the duration distribution, and the active and inactive times. Table 2 and Table 3 present these parameters for each service.
narrowband FTP traffic and high bit rate Video Telephony exceed 120000 packets over the simulation run of 300 seconds. From the plots it is evident, that for this topology, the traffic and number of users used do not have a major effect on the end-to-end delay per packet (system capacity is not overloaded). For all traffic types the delay is relatively constant for the duration of the simulation. The average delay for all types and all users is below 100ms (between 90ms – 98ms), which is lower than the acceptable value for all the examined traffic types.
Table 2: Duration and data rate specifications for each application
Application
Duration (Distribution/Avg)
Data Rate (kb/s)
Voice Over IP Video Telephony FTP High Definition Video Telephony
EXP. / 3min EXP. / 5min EXP. / 1-5 s EXP. / 30min
12 128 384 1920
Table 3: Active and Inactive time specificatins for each application
Application Voice Over IP Video Telephony FTP High Definition Video Telephony
Active Time (Distribution/ Avg) EXP. / 1.4s
EXP. / 10s EXP. / 1-5 s EXP. / 180 s
Inactive Time (Distribution/ Avg)
Figure 4: End-to-end delay for sound traffic
EXP. / 1.7 s
EXP. /10s EXP. / 10s
This is a demanding scenario because of the user density and the support of services close to 2Mb/s such as highdefinition video telephony. The higher usage of this application in our traffic mix model is both to reflect future use of this application and to demonstrate the increase of computational demands on the simulation environment. Once each service is modelled and included in the traffic mix, the performance is monitored according to certain end-user expectations. These reflect the QoS experienced by the user. Statistics regarding delay, packet loss as well as jitter and throughput are collected.
Figure 5: End-to-end delay for multimedia traffic
D. Results The scenario was run for increasing cell load (number of users) generating traffic according to the model described above. The simulation results were obtained by tracing all packets through all links from source to destination. Raw data was collected in a trace file, which in turn was manipulated using additional analysis scripts, in order to extract information about several performance metrics. Figures 4-7 show the average delay experienced by each transmitted packet of the same data type as the load increases from 100 to 200 users. Observe that the low bit rate voice connections transmit less than 1000 packets, the multimedia traffic about 6500 packets, whereas the
Figure 6: End-to-end delay for narrowband FTP traffic
The simulation environment is currently being extended to handle multi-cellular topologies and more demanding traffic through more detailed simulation scenarios. These extensions will provide better understanding of next generation mobile networks. V. REFERENCES 3rd Generation Partnership Project. http://www.3gpp.org [2] 3rd Generation Partnership Project 2. http://www.3gpp2.org [3] Simulation of Enhanced UMTS Access and Core Networks (SEACORN). http://seacorn.ptinovacao.pt rd [4] 3 Generation Partnership Project: Technical Specification Group Radio Access Networks; RF System Scenarios (Release 5). [5] The ns Manual. UC Berkeley, LBL, USC/ISI and Xerox PARC. April 2002. rd [6] 3 Generation Partnership Project: Technical Specification Group Radio Access Network. 3G TR 25.832 version 3.0.0. [7] Kaaranen et al. “UMTS Networks: Architecture, Mobility and Services,” Finland. Wiley, 2001. [8] Muratore F. Ed. “UMTS: Mobile Communications for the Future,” Wiley, 2001. [9] Blake et al. “An architecture for differentiated services,” Internet RFC 2475, December 1998. [10] Westberg et. al., “Resource Management in Diffserv (RMD): A functionality and Performance Behavior Overview,” Seventh IFIP/IEEE Workshop on Protocols for High-Speed Networks (PfHSN'2002), 2002. [11] Pitsillides et al. “Congestion Control for Differentiated-Services using Non-Linear Control Theory,” IEEE Symposium on Computers & Communications, ISCC 2001. [12] Hoppe et al. “Dynamic simulator for studying WCDMA radio network performance,” 53rd Vehicular Technology Conference (VTC) 2001. [13] Kurjeniemmi et al. “System Simulator for UTRA TDD,” 5th CDMA International Conference & Exhibition. [14] Varshney U., Snow A., McGivern M., Howard C. “Voice Over IP,“ Communications of the ACM, January 2002, Vol.45 No. 1. [15] Camp T., Boleng J., Davies V. „A Survey of Mobility Models for AdHoc Network Research,“. Wireless Communication & Mobile Computing (WCMC). Special issue on Mobile Ad Hoc Networking: Research, Trends and Applications, vol.2, no. 5, pp.483-502, 2002. [16] “Digital mobile radio towards future generation systems,” COST Action 231, Brussels, Belgium, 1999. [17] 3GPP Technical Standards TS 22.105. Services and Service Capabilities. 2001. [1]
Figure 7: End-to-end delay for wideband High Definition Video Telephony traffic
For the sound traffic, shown in Figure 4, an expanded time delay scale is used to highlight the delay variation over the simulation run. Figure 8 shows the average jitter for the sound traffic. The maximum jitter recorded is well below the 1ms range generally accepted for all UMTS data types [17]. The jitter recorded for the other three traffic types was even lower.
Figure 8: Average Jitter for sound traffic
As indicated in section III-B, the simulation topology included only one Node B and mobile users were restricted to the range of this micro-cell. These resulted in no instances of call blocking or call dropping and no handovers. The packet losses were negligible and only for the wireless last hop. IV. CONCLUSION AND FUTURE WORK This paper presented a new simulation environment for the performance evaluation of Enhanced UMTS. The simulator is based on the publicly available ns-2 simulator. The simulator was extended using event-based techniques. Major extensions were developed to implement all the UMTS-aware nodes, the expected traffic types, topology and mobility scenarios. The paper illustrates a representative scenario for the simulation of a business city centre. The scenario specifies the micro-cellular environment, including propagation models, traffic mix and user mobility. The simulator functionality was highlighted through this scenario, demonstrating its capability as a performance evaluation tool for E-UMTS environment.
