Flow-level performance and capacity of wireless networks with user mobility

  • Authors:
  • Thomas Bonald;Sem Borst;Nidhi Hegde;Matthieu Jonckheere;Alexandre Proutiere

  • Affiliations:
  • Orange Labs, Paris, France;Bell Labs, Alcatel-Lucent, Murray Hill, USA 07974 and Department of Mathematics & Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands 5600;Orange Labs, Paris, France;Department of Mathematics & Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands 5600;Microsoft Research, Cambridge, England

  • Venue:
  • Queueing Systems: Theory and Applications
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

The performance evaluation of wireless networks is severely complicated by the specific features of radio communication, such as highly variable channel conditions, interference issues, and possible hand-offs among base stations. The latter elements have no natural counterparts in wireline scenarios, and create a need for novel performance models that account for the impact of these characteristics on the service rates of users.Motivated by the above issues, we review several models for characterizing the capacity and evaluating the flow-level performance of wireless networks carrying elastic data transfers. We first examine the flow-level performance and stability of a wide family of so-called 驴-fair channel-aware scheduling strategies. We establish that these disciplines provide maximum stability, and describe how the special case of the Proportional Fair policy gives rise to a Processor-Sharing model with a state-dependent service rate. Next we turn attention to a network of several base stations with inter-cell interference. We derive both necessary and sufficient stability conditions and construct lower and upper bounds for the flow-level performance measures. Lastly we investigate the impact of user mobility that occurs on a slow timescale and causes possible hand-offs of active sessions. We show that the mobility tends to increase the capacity region, both in the case of globally optimal scheduling and local 驴-fair scheduling. It is additionally demonstrated that the capacity and user throughput improve with lower values of the fairness index 驴.