Joint mobility tracking and hard handoff in cellular networks via sequential Monte Carlo filtering

We consider the application of the sequential Monte Carlo (SMC) methodology to the problem of joint mobility tracking and hard handoff detection in cellular wireless communication networks based on the pilot signal strength measurements. The dynamics of the system under consideration are described by a nonlinear state-space model. Mobility tracking involves an on-line estimation of the location and velocity of the mobile, whereas handoff detection involves an on-line prediction of the pilot signal strength at some future time instants. The optimal solution to both problems is prohibitively complex due to the nonlinear nature of the system. The sequential Monte Carlo (SMC) methods are therefore employed to track the probabilistic dynamics of the system and to make the corresponding estimates and predictions. Hard handoff initiation is considered and two novel locally optimal handoff schemes are developed based on different criteria. It is seen that under the SMC framework, optimal mobility tracking and handoff detection can be implemented naturally in a joint fashion, and significant improvement is achieved over existing methods, in terms of both the tracking accuracy and the trade-off between service quality and resource utilization during hard handoff.