In mobile communication systems, mobility tracking operations are executed to maintain known the whereabouts of each mobile terminal (MT). In this article, we propose and analyse two new versions of the original time-based registration method, namely the Stop and Wait (S W) and the Reset and Wait (R W) time-based strategies. We also propose and study the modified S&W and R&W schemes as a result of combining the S&W and R&W policies with the enhanced time-based method in [3]. When the MT uses one of the four schemes proposed, it sends less location update (LU) messages. As a result of fewer LUs, which results in less contacts with the network, the uncertainty of the MT position increases in the proposed time-based schemes. Although the MT paging (PG) cost is lightly increased, a significant reduction in the LU cost is achieved. As it is shown, the net effect is a saving in the total location management cost per call arrival. In order to analyse the four strategies and compare them with the original and enhanced time-based schemes, a performance evaluation method based on Markovian standard tools is proposed here. The location management cost for all these time-based policies are evaluated analytically here by using this evaluation method.

An efficient location management for mobile stations plays an important role in personal communication systems. The key elements of location management are location registration and paging. In this paper, we propose the improved movement-based registration method with a selective paging scheme which enables to minimize the signaling traffic such as a paging load and a registration load. For reducing the paging load, we newly establish a paging area and analyze its performance by modeling as one dimensional random walk model with a barrier state. Further, for decreasing the registration load, we also propose a new movement-based registration scheme by using a counter and a buffer which can store the number of cell boundary crossings and the cell identification, respectively. Through numerical results, we show that our proposed movement-based registration provides a better performance than the conventional movement-based registration.