Dynamic optimization of generalized least squares handover algorithms

Efficient handover algorithms are essential for highly performing cellular networks. These algorithms depend on numerous parameters, whose settings must be appropriately optimized to offer a seamless connectivity. Nevertheless, such an optimization is difficult in a time varying context, unless adaptive strategies are used. In this paper, a new approach for the handover optimization is proposed. Three dynamical optimization approaches are presented, where the probability of outage and the probability of handover are considered. Since it is shown that these probabilities are difficult to compute, simple approximations of adequate accuracy are developed. A distributed optimization algorithm is then developed to maximize handover performance. Numerical results show that the proposed algorithm improves the performance of the handover considerably when compared to more traditional approaches.