An Admission Control-based Benefit Optimization Model for Mobile Communications: the Effect of a Decision Time Budget

In mobile communication systems, a soft handoff (SHO) technique is used to optimize the quality and capacity of communications. However, because the handoff process incurs a high overhead there must be a tradeoff between the system capacity and the handoff overhead. In this paper, we propose a benefit optimization model for mobile communications. The model tries to maximize the overall system capacity by considering SHO process overhead and quality of service requirements jointly. We first construct a framework of admission policies and devise an appropriate admission control policy, which is then used to analyze the system benefit. The service rate is defined by three measures: the call blocking ratio, system load, and admit-to-existence ratio; while the solution quality is defined by the gap between the upper bound and lower bound of the objective function value. By applying iteration-based Lagrangian relaxation as a solution approach, a time budget is allocated to each iteration so that admission control can be implemented. To fulfill the continuous admission process requirements in the long-term, users’ demands are randomly distributed via a simulation process. The goal of this paper is to investigate the effect of the admission control policy on the system benefit, service rate and solution quality. Experiment results are presented to demonstrate the efficacy of both the proposed model and the solution approach