Dynamic Optimization of Generalized Least Squares Handover Algorithms

Efficient handover algorithms are essential for highly performing mobile wireless communications. 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. First, a new modeling of the handover process by a hybrid system that takes as input the handover parameters is established. Then, this hybrid system is used to pose some dynamical optimization approaches 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. Based on these approximations, a new approach to the solution of the handover optimizations is proposed. A distributed optimization algorithm is then developed to maximize handover performance. From an extensive set of results obtained by numerical computations and simulations, it is shown that the proposed algorithm improves performance of the handover considerably when compared to more traditional approaches.