Dynamic Optimization of Generalized Least Squares Handover Algorithms

TL;DR

This paper introduces a novel adaptive optimization approach for handover algorithms in wireless communications, modeling the process with a hybrid system and using a trellis-based distributed algorithm to enhance performance.

Contribution

It presents a new hybrid system model for handover optimization and a trellis-based distributed algorithm, improving performance over traditional methods.

Findings

Significant performance improvement over traditional approaches

Effective approximation methods for outage and handover probabilities

Successful validation through numerical simulations

Abstract

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 by the use of a trellis diagram. 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 allows to improve performance of the handover considerably when compared to more traditional approaches.