Model-based movement patterns play a crucial role in evaluating the performance of mobility-dependent Personal Communication Service (PCS) strategies. This study proposes a new normal walk model to represent more closely the daily movement patterns of a mobile station (MS) in PCS networks than a conventional random walk model. A drift angle θ in this model is applied to determine the relative direction in which an MS handoffs in the next one step, based on the concepts that most real trips follow the shortest path and the directions of daily motion are mostly symmetric. Hence, θ is assumed to approach the normal distribution with the parameters: µ is set to 0and σ is in the range of 5to 90. Varying σ thus redistributes the probabilities associated with θ to make the normal mobility patterns more realistic than the random ones. Experimental results verify that the proposed normal walk is correct and valid for modeling an n-layer mesh cluster of PCS networks. Moreover, when σ = 79.5, a normal walk can almost represent, and even replace, a random walk.

Future personal communication service (PCS) networks consider smaller cells to accommodate continuously growing population of subscribers. That results in frequent location update and consequently higher signaling cost. Among various schemes proposed for improving the efficiency of location management, the distance-based and the direction-based location update methods work well for just certain mobility patterns. In this paper, we propose a hybrid location update (HLU) scheme, which takes into account both the moving distance and the moving direction when deciding on updating the location. We analyze the performance of the HLU under different mobility patterns and call-to-mobility ratios based on a 2D Markov walk model. The numerical results demonstrate that the HLU scheme can achieve better performance than the distance-based or the direction-based methods applied individually.

In this paper, we consider a location management scheme using Limited Pointer forwarding from Commonly visited sites (LPC) strategy for Personal Communication Services (PCS) networks. The Commonly Visited Site (CVS) is defined as a site in which a mobile user is found with high probability. A feature of the strategy is that it skips updating location information of the mobile user, provided that the mobile user moves within its CVSs. Such a strategy is expected to significantly reduce the location update cost. We evaluate the location management cost of the LPC scheme by employing a Continuous-Time Markov Chain (CTMC) model. We show that the LPC scheme can reduce the location management cost of a highly mobile user who is found in its CVS with high probability.

In this paper, we present several traffic handling schemes for improving the QoSs (quality-of-services) in a micro-cell based PCS (personal communication services) network. Traffic handling schemes are devised for the efficient use of the limited radio resources with the increasing number of users and multimedia traffic. Both mathematical analysis and computer simulations are carried out for the performance evaluation in terms of the blocking probability of new call, the forced termination probability of handoff voice and data and the average delay of data. Analytical models by bivariate Markov processes are provided. It reveals that a finite queueing scheme for handoff delay sensitive data guarantees QoS metrics, such as the blocking probability of new voice and data and forced termination probability of handoff voice and data, as well as the efficient use of radio resources. The optimal number of reserved channels for handoff delay sensitive data and the optimal number of reserved channels for handoff traffic (in reserved channel scheme) are investigated and obtained. Dynamically controlled reserved channel schemes turn out to provide no significant performance improvement.