A new normal walk model for mesh PCS networks

Movement patterns play a crucial role in evaluating the performance of mobility-dependent Personal Communication Service (PCS) strategies, such as location updating and paging schemes. This study proposes a novel normal walk model to represent more closely the daily mobility patterns of a mobile station (MS) in mesh PCS networks than a conventional random walk model. The proposed model applies an equivalent drift angle ?? to determine the direction in which an MS leaves a mesh cell in the next one step. The angle ?? is assumed to approach a normal distribution with parameters: μ = 0° and ?? is on the interval [5°, 90°], based on the concept that most trips follow the shortest path. This assumption implies that varying ?? can redistribute the probabilities associated with ?? to make the normal movement patterns more realistic than the random ones. Moreover, for ?? = 79.5°, a normal walk can behave almost like a conventional random walk.