Cell-related location area planning for 4G PCS networks with variable-order Markov model

Abstract

Location management is a critical issue in personal communication service (PCS) networks, tracking the location of user equipment (UE) with the goal of minimizing total signaling cost. Previous work can be classified into two categories: static and dynamic. Static schemes partition networks into fixed size LAs. However, these schemes are inefficient because they do not take UEs’ mobility and the call arrival rate into account. On the other hand, focusing on individual UEs, dynamic schemes have minimized the location management cost. However, they are difficult to implement because recording the individual information of numerous UEs and planning each of their LAs consume uncontrollable cost. Because of these reasons, we propose a cell-based scheme between static and dynamic schemes. Considering people usually stay in specific zones for long periods and the movement of UEs usually presents a strong moving direction in areas, this study presents a distributed algorithm by employing variable-order Markov models to find the mobility characteristic shared by UEs to plan better LAs with lower location management cost. When the order of Markov model is set to 1, our method is equal to a pure cell-centric LAP scheme; while the order of Markov model is high, it is more like a profile-based dynamic scheme. So, the setting of the order actually is a trade-off problem between the overall location management cost and the computing complexity. We present to retrieve a balance by using the expected location management cost and the number of total states of Markov models. In simulations, the origin–destination matrix (O–D matrix) from the Taipei Rapid Transit Corporation is used for representing the association between two cells. Simulation results demonstrate that the proposed scheme achieves good performance.