Henrik Nyberg

Empirical Testing of the Infinite Source Poisson Data Traffic Model

The infinite source Poisson model is a fluid queue approximation of network data transmission that assumes that sources begin constant rate transmissions of data at Poisson time points for random lengths of time. This model has been a popular one as analysts attempt to provide explanations for observed features in telecommunications data such as self-similarity, long range dependence and heavy tails. We survey some features of this model in cases where transmission length distributions have (a) tails so heavy that means are infinite, (b) heavy tails with finite mean and infinite variance and (c) finite variance. We survey the self-similarity properties of various descriptor processes in this model and then present analyses of four data sets which show that certain features of the model are consistent with the data while others are contradicted. The data sets are 1) the Boston University 1995 study of web sessions, 2) the UC Berkeley home IP HTTP data collected in November 1996, 3) traces collected in end of 1997 at a Customer Service Switch in Munich, and 4) detailed data from a corporate Ericsson WWW server from October 1998. #Research supported by the Gothenburg Stochastic Centre, by the EU TMR network ERB-FMRX-CT96-0095 on “Computational and statistical methods for the analysis of spatial data” and by the Knut and Aline Wallenburg Foundation. Sidney Resnicks research was also partially supported by NSF grant DMS-97-04982 and NSA Grant MDA904-98-1-0041 at Cornell University.

A streaming video traffic model for the mobile access network

A model of streaming video traffic from a streaming server to an end user is proposed. It mimics the codec output (video frames) segmentation into RTP (real time protocol) packets, transmission from the streaming server and reception of packets by the end user. The intention is to use the model in the performance analysis of radio networks. The level of detail is chosen to support the performance analysis of the transport of RTP packets from server to user. The model is based on measurements of H.263 encoded video at various bitrates. The bitrates and the codec settings are chosen to be suitable for mobile access.

A novel approach to WCDMA radio network dimensioning

A novel dimensioning approach for WCDMA radio networks is suggested. It is derived to handle real-time services on dedicated channels, but can easily be augmented to include best-effort traffic on the high-speed downlink shared channel. The method facilitates calculation of transmit power distributions based on detailed link gain statistics, enabling fast, yet accurate, estimation of, e.g., network design and cost. It is shown that good agreement with detailed dynamic simulations can be achieved.

Streaming services in GSM/EDGE-radio resource management concepts and system performance

Managing multiple services with controlled quality of service (QoS) is crucial to 3/sup rd/ generation cellular system. The real time services, i.e. the traffic classes streaming and conversational, will be the most costly services and therefore most crucial to manage in a spectral efficient manner. This paper proposes and evaluates possible ways to accomplish this for the GSM/EDGE Radio Access Network (GERAN). The evaluation is made with different mixes of voice, WWW browsing and video streaming services, where the latter is based on a novel traffic model for a streaming service using an H.263 codec with suitable settings. The results from the dynamic multiple-cell system simulations show that it is possible to efficiently manage streaming services in GERAN, in single as well as mixed service scenarios, by using service based radio resource management algorithms, e.g., power setting.

Resource efficient streaming bearer concept for GERAN

We present a complete concept for providing a resource efficient bearer service for streaming applications in the GSM/EDGE Radio Access Network, GERAN. The concept comprises rules for admission control, service quality monitoring functions and appropriate means to ensure that the service quality stays within the envisaged bounds. Results indicate that the achievable capacity is close to what could be expected from streaming over a best effort bearer, while at the same time QoS guarantees can be fulfilled, ensuring high end-user quality.

An Extension of Clarke's Model With Stochastic Amplitude Flip Processes

Stochastic modeling is an essential tool for studying statistical properties of wireless channels. In multipath fading channel (MFC) models, the signal reception is modeled by a sum of wave path contributions, and Clarkes model is an important example of such which has been widely accepted in many wireless applications. However, since Clarkes model is temporally deterministic, Feng and Field noted that it does not model real wireless channels with time-varying randomness well. Here, we extend Clarkes model to a novel time-varying stochastic MFC model with scatterers randomly flipping on and off. Statistical properties of the MFC model are analyzed and shown to fit well with real signal measurements, and a limit Gaussian process is derived from the model when the number of active wave paths tends to infinity. A second focus of this work is a comparison study of the error and computational cost of generating signal realizations from the MFC model and from its limit Gaussian process. By rigorous analysis and numerical studies, we show that in many settings, signal realizations are generated more efficiently by Gaussian process algorithms than by the MFC models algorithm. Numerical examples that strengthen these observations are also presented.