The lookahead strategy for distance-based location tracking in wireless cellular networks

Abstract

Based on a multi-scale, straight-oriented mobility model, this paper presents a lookahead strategy for distance-based location tracking so the rate of location update can be reduced without incurring extra terminal paging costs. For linear mobility graphs, the optimal registered cell is found by an iterative algorithm so the average cycle length is maximized. For planar mobility graphs, the authors employ the results from linear cases to determine the eligible registered cell. Performance gain is evaluated by using Monte Carlo simulation for mobiles with different degrees and scales of mobility. Analysis shows that the tracking cost for mobile users with large mobility scales in microcellular networks, costs which are usually underestimated by the traditional random walk model, can be effectively reduced.