In this paper, we analyze phenomena related to user clumps and hot spots occuring in mobile networks at the occasion of large urban mass gatherings. Our analysis is based on observations made on mobility traces of GSM users in several large cities. Classical mobility models, such as the random waypoint, do not allow one to represent the observed dynamics of clumps in a proper manner. This motivates the introduction and the mathematical analysis of a new interaction-based mobility model, which is the main contribution of the present paper. This model is shown to allow one to describe the dynamics of clumps and in particular to predict key phenomena such as the building of hot spots and the scattering between hot spots, which play a key role in the engineering of wireless networks. We show how to obtain the main parameters of this model from simple communication activity measurements and we illustrate this calibration process on real cases.

Due to the introduction of new services, the volume of data transferred in mobile networks is rapidly growing and operators periodically face the necessity to upgrade their network. Such upgrades allow them to increase the capacity and provide adequate Quality of Service (QoS). In this paper we propose a general framework for deriving the optimal date for a network upgrade. We show that this date is the result of a compromise between the decrease of upgrade investment cost with time and the loss of profit generated by insufficient capacity. The upgrade should hence be performed when the loss of profit, derived using analytical capacity expressions, exceeds the expected discount. The model presented herein accounts for the randomness of the demand and upgrading cost functions, and results are given for a HSDPA network.

In this work, we study cooperation between UMTS and GSM systems. The aim is to find the best Joint Radio Resource Management (JRRM) strategies that achieve lowest blocking rates. We first present analytical models for capacity in GERAN and UTRAN. We then consider different strategies of Joint Radio Resource Management (JRRM) with or without inter-system (vertical) handovers and show how to calculate the steady-state probabilities and the performance measures (blocking probabilities, loads). Our numerical results compare the different JRRM strategies and point out the advantages and drawbacks for each of them. We show that the best performance is obtained when authorising vertical handovers. However, a simple strategy without vertical handover may, in some cases, achieve comparable performance with less signaling overhead.