A Hybrid Model of the UMTS Downlink Capacity with WWW Traffic on Dedicated Channels
One of the main advances of 3G networks like UMTS is the ability to support a large variety of different services. These services are subdivided in two domains, circuit-switched services and packet-switched services. The main application expected for packet-switched services is the browsing of the World Wide Web. The web traffic is usually described by quite sophisticated source traffic models and the packet arrivals on IP layer are determined by TCP. On the other hand, the planning process for UMTS networks relies on analytic methods or Monte Carlo simulations that assume the number of users to be Poisson distributed. The intention of this work is to examine if it is possible to apply the existing planning methods to web traffic. We are able to show that the Poisson assumption holds for the number of web users that simultaneously transmit over the air interface and that the resulting NodeB transmit power distribution is valid. We use the Monte Carlo simulation technique to evaluate the web capacity of an example UMTS network.
KeywordsOutage Probability Universal Mobile Telecommunication System Download Time Universal Mobile Telecommunication System Network Fast Power Control
Unable to display preview. Download preview PDF.
- 1.3GPP: Quality of service (QoS) concept and architecture. Technical Report TS 23.107 (2004)Google Scholar
- 2.3GPP: Radio frequency (RF) system scenarios. Technical Report TR 25.942 (2004)Google Scholar
- 3.3GPP: Physical layer procedures (FDD). Technical Report TR 25.214 (2004)Google Scholar
- 5.Choi, H., Limb, J.: A behavioral model of web traffic. In: Protocol 1999 (ICNP 1999), International Conference of Networking (1999)Google Scholar
- 7.Leibnitz, K.: Analytical Modeling of Power Control and its Impact on WCDMA Capacity and Planning. PhD thesis, University of Würzburg (2003)Google Scholar
- 8.Mäder, A., Staehle, D.: Uplink blocking probabilities in heterogeneous WCDMA networks considering other-cell interference. In: Southern African Telecommunication Networks & Applications Conference, South Western Cape, South Africa (2004)Google Scholar
- 9.Schröder, B., Weller, A.: Prediction of the connection stability of UMTS-services in the downlink - an analytical approach. In: Proc. of IEEE VTC Fall, Vancouver, CA (2002)Google Scholar
- 10.Staehle, D., Leibnitz, K., Heck, K.: Fast prediction of the coverage area in UMTS networks. In: Proc. of IEEE Globecom, Taipei, Taiwan (2002)Google Scholar
- 11.Staehle, D., Mäder, A.: An analytic model for deriving the Node-B transmit power in heterogeneous UMTS networks. In: IEEE VTC Spring, Milano, Italy (2004)Google Scholar
- 12.Staehle, D., Leibnitz, K., Tran-Gia, P.: Source traffic modeling of wireless applications. Technical report, University of Würzburg (2000)Google Scholar
- 15.Tran-Gia, P., Staehle, D., Leibnitz, K.: Source traffic modeling of wireless applications. International Journal of Electronics and Communications (AEÜ) 55 (2001)Google Scholar