aluating the network-relevant QoS. And for each of these categories, different traffic classes (i.e. belong to elastic traffic or circuit-switched traffic) and traffic mixes are considered separately. Analytical Models User-Relevant QoS Network-Relevant QoS Traffic Circuit-switched Circuit- Elastic Traffic Mixed Traffic Elastic Traffic Mixed Traffic Scenario traffic switched traffic blocking QoS application delay both QoS need packet delay, packet loss ratio Measure or throughput to be met over the lub interface Processor Erlang Loss Processor Queuing Models with non- Non-preemptive Analytical Model Sharing Model Models Sharing Model Markovian Arrival Process priority queuing + Erlang Model model Modeling Call or Flow Level Modeling Packet Level Figure 4.7: Overview of analytical dimensioning models To obtain the user-relevant QoS, the applied analytical models should reflect the flow level behavior and predict per-flow performance. In this thesis, for the circuit-switched traffic a blocking model is used to estimate the blocking QoS (i.e. connection reject ratio). For the elastic traffic the dimensioning model is based on process sharing models on flow level, 4 Framework of UMTS Network Dimensioning which is used to calculate the end-to-end application delay or throughput. In case of the mixed traffic scenarios, two cases can be considered: (1) bandwidth partitioning; (2) bandwidth sharing. In the first case, it is assumed that technologies are employed in the network, which allow service-specific partitioning of link capacity. Thus a link can be divided up into bandwidth portions, which are assigned to the individual traffic classes. Traffic policing units (e.g. token buckets) at the network edges assure that individual traffic flows within the portion of each traffic type do not negatively interfere with each other. This assumption allows us dimension the necessary transport capacity for elastic traffic and circuit-switched traffic separately with their individual dimensioning models. To obtain the total capac