 different ATM VC or VPs. For example, the HSDPA and HSUPA traffic can use either two individual UBR VCs (one for HSUPA and the other is for HSDPA) or a single UBR VC, while the Rel99 traffic is using a separate CBR VC. By defining different ATM QoS categories, and giving different configurations and priorities on the individual VCs for different traffic paths, differentiated QoS support can be attained and the utilization of the transport resources can be optimized. This will be discussed in Appendix A.16. 5.8 Traffic Models Knowing the traffic demand that a UMTS network has to satisfy is an essential point when coming to the dimensioning of its resources. For this purpose, traffic models are needed in order to predict the user load in the network. Traffic models are used to characterize various service types with certain parameters characterizations. This section gives a survey of various traffic models for voice, web browsing and ftp applications, and emphasizes the traffic models which are used in this thesis. 5.8.1 Voice Traffic Model Voice traffic is characterized by its symmetric nature, where the inherent QoS allows a very small delay [ETSI98]. For voice traffic, the traffic model can be described as an ON- OFF model with active and silent periods, illustrated in Figure 5.8. Bandwidth (kbps) Call Arrives Active Period Silent Period Figure 5.8: Voice traffic model In this thesis, the voice traffic model defined in the MOMENTUM project [TWP*02] is used for simulations and performance analysis. In this voice traffic model, both active (ON) 5.8 Traffic Models and silent periods (OFF) are exponentially distributed. Mean value for active and silence periods are equal to 3 seconds and independent on the up and downlink. In addition, the call duration is also exponentially distributed. The exponential probability density function is calculated as below: 1(1)=1e7,120 (5.1) Where T is the average voice call duration, and =1/t, is the service rate. In this voice traffic model, an average call duration of 120 seconds