Self-organization in wireless networks: A flow-level perspective

Abstract

This paper introduces self-optimization for wireless networks taking into account flow-level dynamics. Users arrive and leave the network according to a traffic model. Elastic traffic is considered here. The developed solutions self-optimize the network stability region using user feedback (measurements). The use case considered is cell size optimization. An algorithm is given, and its convergence is proven using stochastic approximation techniques. Convergence points are characterized, allowing performance gains to be evaluated rigorously. Performance gains are evaluated numerically, showing an important increase of the network capacity.